MINI-REVIEW CD 271 (P75 NEUROTROPHIN RECEPTOR) M … · (neurotensin receptor 3), a recently described co-receptor with CD271 for pro-neurotrophins, induces cell death by the activation

JOURNAL OF BIOLOGICAL REGULATORS & HOMEOSTATIC AGENTS

0393-974X (2008)Copyright © by BIOLIFE, s.a.s.

This publication and/or article is for individual use only and may not be furtherreproduced without written permission from the copyright holder.

Unauthorized reproduction may result in financial and other penalties1

CD 271 (P75 NEUROTROPHIN RECEPTOR)

M-L. ROGERS, A. BEARE1, H. ZOLA1 and R.A. RUSH

Department of Human Physiology, Centre for Neuroscience, Flinders University, South Australia; 1Child Health Research Institute, Women’s and Children’s Health Research Institute,

North Adelaide, South Australia.

Received April 4, 2006 - Accepted March 28, 2007

After cleavage of its 28-amino acid signal peptide, CD271 is a 399-amino acid transmembrane protein that has a single asparagine-linked carbohydrate at position 33 and several O-linked carbohydrates in the juxtamembrane stalk domain (Fig. 1) (1). Like all members of the TNFR superfamily, CD271 contains cysteine-rich domains (CRD) in the extracellular domain (2). There are four CRDs (CRD1–CRD4 from amino-terminus) in CD271. Experimental and structural modeling studies have mapped the neurotrophin binding sites to CRD2 and CRD3 (3-7). Cysteine 279 of the intracellular domain of p75NTR is palmitoylated and multiple serine and threonine residues are phosphorylated in the mature protein (8). The functions of these post-translational modifications are not known but could include roles in protein–protein interaction, proper intracellular folding of the receptor, or in directing the cellular localization of CD271. Both alternative splicing and

post-synthetic proteolysis result in production of various truncated isoforms of CD271, including the neurotrophin receptor homologue 2 (NRH2) which has been found to associate with the other major receptor for NGF, the Tyrosine Kinase A receptor (TrkA) and bind NGF (9).

CD271 is an unusual member of the TNFR family due to its propensity to bind dimeric rather than trimeric ligands, and because the neurotrophins are structurally unrelated to the ligands which typically bind TNFR family members (10-11). However, in keeping with its membership in the TNFR family, the intracellular domain of CD271 contains an 80-amino acid ‘death domain’ module with six α helices, similar to TNFR1 (12). However, unlike TNFR1, CD271 contains TRAF-interacting motifs which classify it as a Type II death domain, and activation of these leads to multiple signal transduction pathways (2).

Mailing address: Dr Mary-Louise Rogers, Centre for Neuroscience, Department of Human Physiology,School of Medicine, Room 6E136, Flinders Medical Centre, Bedford Park, 5042,South Australia, Australia Tel: ++61 8 8204 5238 Fax: ++61 8 8204 5768e-mail: [email protected]

Key words: TFN receptor, NGF, BDNF, neuron, P75 monoclonal antibody

MINI-REVIEW

Vol. 22, no. 1, 1-6 (2008)

CD271, (or p75NTR) is the sixteenth member of the Tumor Necrosis Factor receptor (TNFR) super family of transmembrane proteins. Members of the TNFR family including CD271, share homology in their extracellular domain, and have a cytoplasmic death domain, although CD271 has unique intracellular structure and downstream signalling partners. CD271 is also differentiated from other members of the TNFR receptor family in that it binds pro and mature neurotrophins and affects the growth, differentiation and death of the nervous system. The ligands for CD271 are neurotrophins, which are Nerve Growth Factor (NGF), Brain-Derived Growth factor (BDNF), Neurotrophin 3 (NT3) and Neurotrophin 4/5 (NT4/5). Recent studies have provided evidence that CD271 also serves as a receptor for the pro-forms of these neurotrophins.

2

Multiple receptor partners and functionsCD271 has contradictory actions; it functions to

promote cell survival or induce cell death. These opposing effects are mediated by the association of CD271 with a number of different receptor partners (Fig. 2). Firstly, in the absence of Trk neurotrophin receptor expression CD271 can induce apoptosis and cell death. The signaling pathways from the CD271-dependent apoptotic response are incompletely understood but are thought to involve activation of JNK and further downstream events such as release of cytochrome c and activation of caspases 9, 6 and 3 (3). A number of intracellular proteins have been shown to activate JNK and promote apoptosis. These include neurotrophin-receptor-interacting MAGE (melanoma-associated antigen) homologue (NRAGE), neurotrophin-associated cell death executor (NADE), TNF (tumour necrosis factor)-receptor-associated factors 2 and 6 (TRAF2

and TRAF6), and neurotrophin-receptor-interacting factor (NRIF) (13-18).

In contrast to CD271-dependent apoptosis, while in complex with TrkA, CD271 promotes cell growth by enhancing the TrkA downstream signaling induced upon NGF binding (4,19). Conversely, sortilin (neurotensin receptor 3), a recently described co-receptor with CD271 for pro-neurotrophins, induces cell death by the activation of an as yet unidentified pathway. For example, proNGF simultaneously engages sortilin and CD271 to signal cell death (20). Another co-receptor for CD271 is the glycolipid-anchored Nogo receptor (Nogo-R (21)) which binds myelin based growth inhibitors, including NogoA, myelin-associated glycoprotein (MAG) and oligodendrocyte myelin glycoprotein (OMGP) and restricts axonal regeneration by promoting growth cone collapse of injured neurons (22). This effect is known to necessitate co-expression with CD271 and

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36. Rogers M-L, Atmosukarto I, Abebe D, Matusica D, Macardle P, Rush RA. Functional

Monoclonal Antibodies to p75 Neurotrophin Receptor Raised in Knockout Mice. J

Neurosci Methods. 2006; 158:109-20.

37. Bentley KL, Bradshaw MS, Ruddle FH. Human HOXB cluster and the nerve growth

factor receptor gene: comparison with an orthologous chromosomal domain in mouse.

Genomics 1995; 30:18-24.

Fig. 1. Schematic representation of the structure of the CD271 protein. CD271 is a Type I transmembrane receptor with an extracellular domain that contains four cysteine-rich domains (CRDs), and one N- and several O-linked glycosylation sites. The intracellular domain contains a palmitoylation site at cysteine 279, two potential TRAF-binding sites, a Type II death domain, a potential G protein activating domain, and a PDZ domain binding motif (adapted from 1).

M-L. ROGERS ET AL.

3Journal of Biological Regulators & Homeostatic Agents

the transmembrane protein LINGO-1 because both are required for a response to myelin (21). Upon ligand binding, CD271 binds to the Rho guanine dissociation inhibitor (Rho-GDI), relieving RhoA from its inhibition, an activation cascade distinct from that in proapoptotic stimulation (23). In summary, the outcome of CD271 activation depends on the type of ligand and the ability to crosslink and co-ordinate co-receptors, thereby facilitating the activation of specific signaling pathways.

TISSUE DISTRIBUTION

Neural TissueCD271 is widely expressed in developing

neural tissue (24, 1). However, in the adult, CNS expression is limited to a few restricted cell populations including olfactory glia, and cerebellar Purkinje neurons (25). Subpopulations of peripheral sympathetic and sensory neurons express varying levels of the receptor (24).

Non-Neural TissueOutside the nervous system, p75NTR is expressed

in myoblasts and developing tissues of mesenchymal origin, including hair follicles, limb bud fibroblasts, kidney, lung and testes (26). In mature cells, non-neural expression is found in endothelial cells, perivascular fibroblasts, dental pulp cells, prostate epithelial cells and immune B cells (27).

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Fig. 1. Schematic representation of the structure of the CD271 protein. CD271 is a Type I

transmembrane receptor with an extracellular domain that contains four cysteine-rich

domains (CRDs), and one N- and several O-linked glycosylation sites. The intracellular

domain contains a palmitoylation site at cysteine 279, two potential TRAF-binding sites, a

Type II death domain, a potential G protein activating domain, and a PDZ domain binding

motif (adapted from 1).

Fig. 2. Although it lacks a kinase domain, p75NTR (CD271) co-operates with many different

protein partners and forms multimeric receptor complexes to produce a number of cellular

responses, including apoptosis, neurite outgrowth and myelination. So far, sortilin

(neurotensin receptor 3), LINGO-1, Nogo-66 (NogoR) and Trk receptors have been identified

as co-receptors (19-21). In addition, the intracellular domain of CD271 interacts with many

different adaptor and signaling proteins. These include neurotrophin-receptor-interacting

MAGE (melanoma-associated antigen) homologue (NRAGE), neurotrophin-associated cell

Fig. 2. Although it lacks a kinase domain, p75NTR (CD271) co-operates with many different protein partners and forms multimeric receptor complexes to produce a number of cellular responses, including apoptosis, neurite outgrowth and myelination. So far, sortilin (neurotensin receptor 3), LINGO-1, Nogo-66 (NogoR) and Trk receptors have been identified as co-receptors (19-21). In addition, the intracellular domain of CD271 interacts with many different adaptor and signaling proteins. These include neurotrophin-receptor-interacting MAGE (melanoma-associated antigen) homologue (NRAGE), neurotrophin-associated cell death executor (NADE), TNF (tumour necrosis factor)-receptor-associated factors 2 and 6 (TRAF2 and TRAF6), and neurotrophin-receptor-interacting factor (NRIF) (13-18). GDI, guanine-nucleotide dissociation inhibitor; MAG, myelin-associated glycoprotein; OMGP, oligodendrocyte myelin glycoprotein; RhoA, small G protein (3).

4

CD271 in DiseaseImportantly, although CD271 is abundantly expressed

during development, it is down regulated in many cells of the adult organism and only re-expressed in conditions involving neuronal injury, such as neurodegenerative disease states. Numerous neurological diseases, deficits and syndromes have been correlated with CD271 expression. These include Alzheimer’s disease, amyotrophic lateral sclerosis, neural crest tumors, stroke, ischemia and excitoxicity, cerebellar Purkinje cell degeneration, schizophrenia, bronchial asthma and some autoimmune disorders (28, 24). The expression patterns of CD271 in various types of cancer have also been studied extensively. The largest study involved 1150 tumours and fetal and normal tissue. Although CD271 expression was not correlated with a cancerous phenotype it was found to be a useful marker in specific non neural mesenchymal tumours such as dermatofibrosarcoma and rhadomyosarcoma (29). In addition, in some cancers such as prostate and bladder carcinoma, CD271 acts as a tumour suppressor and progression from benign to metastatic tumours is associated with a decrease in CD271 expression (30-32).

Available Antibodies and Species ReactivityNGFR5 (33, 27) Human, Baboon, Cat, Ferret,

Monkey and Rabbit, does not react with Mouse or Rat.ME20.4, 8211 (34) Human, primate,

rabbit, raccoon, dog, cat, pig and sheep, doesnot react with Mouse or Rat.

MLR1, 2 and 3 (35) Human, Rat and Mouse, no other species tested.

Sequence InformationGENENGFR, Entrez gene accession no. ID 4804http://www.gene.ucl.ac.uk/nomenclature/data/get_data.php?hgnc_id=7809NGFR gene has been localised to 17q12-q22, a site that appears to be closely distal to the breakpoint (at 17q21) in acute promyelocytic leukemia (36). It is also closely linked to the HOX2 gene cluster and is separated by a maximum of 500 kb from the HOX2 region (37).

PROTEINSwiss prot: accession P08138; http://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?

val=4505393&itemID=6&view=gpwithparts427AA (Underlined: Signal peptide present in precursor; Bold: cysteine rich domains; Italic: transmembrane domain; Bold and Underlined: death domain)

MGAGATGRAM DGPRLLLLLL LGVSLGGAKE ACPTGLYTHS GECCKACNLG EGVAQPCGAN QTVCEPCLDS VTFSDVVSAT EPCKPCTECV GLQSMSAPCV EADDAVCRCA YGYYQDETTG RCEACRVCEA GSGLVFSCQD KQNTVCEECP DGTYSDEANH VDPCLPCTVC EDTERQLREC TRWADAECEE IPGRWITRST PPEGSDSTAP STQEPEAPPE QDLIASTVAG VVTTVMGSSQ PVVTRGTTDN LIPVYCSILA AVVVGLVAYI AFKRWNSCKQ NKQGANSRPV NQTPPPEGEK LHSDSGISVD SQSLHDQQPH TQTASGQALK GDGGLYSSLP PAKREEVEKL LNGSAGDTWR HLAGELGYQP EHIDSFTHEA CPVRALLASW ATQDSATLDA LLAALRRIQR ADLVESLCSE STATSPV

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2. Dempsey PW, Doyle SE, He JQ, Cheng G. The signaling adaptors and pathways activated by TNF superfamily. Cytokine Growth Factor Rev 2003; 14:193-209.

3. Lu B, Pang PT, Woo NH. The yin and yang of neurotrophin action. Nat Rev Neurosci 2005; 6:603-614.

4. Nykjaer A, Willnow TE, Petersen CM. p75NTR--live or let die. Curr Opin Neurobiol 2005; 15:49-57.

5. Welcher AA, Bitler CM, Radeke MJ, Shooter EM. Nerve growth factor binding domain of the nerve growth factor receptor. Proc Natl Acad Sci USA 1991; 88:159-163.

6. Yan H, Chao MV. Disruption of cysteine-rich repeats of the p75 nerve growth factor receptor leads to loss of ligand binding. J Biol Chem 1991; 266:12099-12104.

7. He XL, Garcia KC. Structure of nerve growth factor complexed with the shared neurotrophin receptor p75. Science 2004; 304(5672):870-875.

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8. Barker PA, Barbee G, Misko TP, Shooter EM. The low affinity neurotrophin receptor, p75LNTR, is palmitoylated by thioester formation through cysteine 279. J Biol Chem 1994; 269:30645-30650.

9. Murray SS, Perez P, Lee R, Hempstead BL, Chao MV. A novel p75 neurotrophin receptor-related protein, NRH2, regulates nerve growth factor binding to the TrkA receptor. J Neurosci 2004; 24:2742-2749.

10. McDonald NQ, Lapatto R, Murray-Rust J, Gunning J, Wlodawer A, Blundell TL. New protein fold revealed by a 2.3-A resolution crystal structure of nerve growth factor. Nature 1991; 354(6352):411-414.

11. Park YC, Burkitt V, Villa AR, Tong L, Wu H. Structural basis for self-association and receptor recognition of human TRAF2. Nature 1999; 398(6727):533-538.

12. Liepinsh E, Ilag LL, Otting G, Ibanez CF. NMR structure of the death domain of the p75 neurotrophin receptor. Embo J 1997; 16:4999-5005.

13. Salehi AH, Roux PP, Kubu CJ et al. NRAGE, a novel MAGE protein, interacts with the p75 neurotrophin receptor and facilitates nerve growth factor-dependent apoptosis. Neuron 2000; 27:279-288.

14. Mukai J, Hachiya T, Shoji-Hoshino S et al. NADE, a p75NTR-associated cell death executor, is involved in signal transduction mediated by the common neurotrophin receptor p75NTR. J Biol Chem 2000; 275:17566-17570.

15. Ye X, Mehlen P, Rabizadeh S et al. TRAF family proteins interact with the common neurotrophin receptor and modulate apoptosis induction. J Biol Chem 1999; 274:30202-30208.

16. Khursigara G, Orlinick JR, Chao MV. Association of the p75 neurotrophin receptor with TRAF6. J Biol Chem 1999; 274:2597-2600.

17. Casademunt E, Carter BD, Benzel I, Frade JM, Dechant G, Barde YA. The zinc finger protein NRIF interacts with the neurotrophin receptor p75(NTR) and participates in programmed cell death. Embo J 1999; 18(21):6050-6061.

18. Linggi MS, Burke TL, Williams BB et al. Neurotrophin receptor interacting factor (NRIF) is an essential mediator of apoptotic signaling by the p75 neurotrophin receptor. J Biol Chem 2005; 280:13801-13808.

19. Hempstead BL, Martin-Zanca D, Kaplan DR, Parada LF, Chao MV. High-affinity NGF binding requires coexpression of the trk proto-oncogene and the low-affinity NGF receptor. Nature 1991; 350(6320):678-683.

20. Nykjaer A, Lee R, Teng KK et al. Sortilin is essential for proNGF-induced neuronal cell death. Nature 2004;427(6977):843-848.

21. Mi S, Lee X, Shao Z et al. LINGO-1 is a component of the Nogo-66 receptor/p75 signaling complex. Nat Neurosci 2004; 7(3):221-228.

22. Wang KC, Kim JA, Sivasankaran R, Segal R, He Z. P75 interacts with the Nogo receptor as a co-receptor for Nogo, MAG and OMgp. Nature 2002; 420:74-78.

23. Yamashita T, Tohyama M. The p75 receptor acts as a displacement factor that releases Rho from Rho-GDI. Nat Neurosci 2003; 6:461-467.

24. Schor NF. The p75 neurotrophin receptor in human development and disease. Prog Neurobiol 2005; 77:201-214.

25. Richardson PM, Issa VM, Riopelle RJ. Distribution of neuronal receptors for nerve growth factor in the rat. J Neurosci 1986; 6:2312-2321.

26. Wheeler EF, Bothwell M. Spatiotemporal patterns of expression of NGF and the low-affinity NGF receptor in rat embryos suggest functional roles in tissue morphogenesis and myogenesis. J Neurosci 1992; 12:930-945.

27. Thompson SJ, Schatteman GC, Gown AM, Bothwell M. A monoclonal antibody against nerve growth factor receptor. Immunohistochemical analysis of normal and neoplastic human tissue. Am J Clin Pathol 1989; 92:415-423.

28. Dawbarn D, Allen SJ. Neurotrophins and neurodegeneration. Neuropathol Appl Neurobiol 2003; 29:211-230.

29. Fanburg-Smith JC, Miettinen M. Low-affinity nerve growth factor receptor (p75) in dermatofibrosarcoma protuberans and other nonneural tumors: a study of 1,150 tumors and fetal and adult normal tissues. Hum Pathol 2001; 32:976-983.

30. Khwaja F, Djakiew D. Inhibition of cell-cycle effectors of proliferation in bladder tumor epithelial cells by the p75NTR tumor suppressor. Mol Carcinog 2003; 36:153-160.

31. Khwaja F, Allen J, Lynch J, Andrews P, Djakiew D.

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Ibuprofen inhibits survival of bladder cancer cells by induced expression of the p75NTR tumor suppressor protein. Cancer Res 2004; 64:6207-6213.

32. Krygier S, Djakiew D. The neurotrophin receptor p75NTR is a tumor suppressor in human prostate cancer. Anticancer Res 2001; 21(6A):3749-3755.

33. Marano N, Dietzschold B, Earley JJ Jr. et al. Purification and amino terminal sequencing of human melanoma nerve growth factor receptor. J Neurochem 1987; 48:225-232.

34. Ross AH, Grob P, Bothwell M et al. Characterization of nerve growth factor receptor in neural crest tumors using monoclonal antibodies. Proc Natl Acad Sci USA 1984; 81:6681-6685.

35 Huebner K, Isobe M, Chao M et al. The nerve growth factor receptor gene is at human chromosome region 17q12-17q22, distal to the chromosome 17 breakpoint in acute leukemias. Proc Natl Acad Sci USA 1986; 83:1403-1407.

36. Rogers M-L, Atmosukarto I, Abebe D, Matusica D, Macardle P, Rush RA. Functional Monoclonal Antibodies to p75 Neurotrophin Receptor Raised in Knockout Mice. J Neurosci Methods. 2006; 158:109-20.

37. Bentley KL, Bradshaw MS, Ruddle FH. Human HOXB cluster and the nerve growth factor receptor gene: comparison with an orthologous chromosomal domain in mouse. Genomics 1995; 30:18-24.

M-L. ROGERS ET AL.





FROM SINGLE GENE TO INTEGRATIVE MOLECULAR CONCEPT MAPS: PITFALLS AND POTENTIALS OF MICROARRAY TECHNOLOGY

G. CHIORINO, M. MELLO GRAND, M. SCATOLINI and P. OSTANO

Laboratory of Cancer Pharmacogenomics, Fondo Edo Tempia, Biella, Italy

Received March 14, 2007 – Accepted May 3, 2007

Mailing address: Dr G. Chiorino,Laboratory of Cancer Pharmacogenomics, Fondo Edo Tempia,Via Malta 3,13900 Biella, ItalyTel: ++39 015351830 Fax: ++39 01521116e-mail: [email protected]

Microarray experiments have a large variety of applications and several important achievements have been obtained by means of this technology, especially within the field of whole genome expression profiling, which undoubtedly is the most diffused world-wide. Nevertheless, care must be taken in unconditionally applying such high-throughput techniques and in extracting/interpreting their results. Both the validity and the reproducibility of microarray-based clinical research have recently been challenged. Pitfalls and potentials of the microarray technology for gene expression profiling are critically reviewed in this paper.

The simultaneous measurement of the expression levels of thousands of genes has found widespread application in many and various fields and is generally referred to as “the microarray technology”, even if this name includes other whole genome microarray applications, such as comparative genomic hybridization (array CGH), large scale methylation analysis and chromatine immunoprecipitation on chips (ChIP on Chip). These latter are generating novel and important results (1-10), but are not as diffused as the gene expression profiling technique. The analysis of large-scale gene expression data has become a fundamental approach to functional genomics and the identification of potential clinical biomarkers or drug targets. Many research groups have applied it to genome-wide screenings in a large variety of situations, such as the comparison between control and treatment or disease and normal groups (11-15), the identification of novel disease subtypes (16-19), the investigation of time series (developmental stages, transgene induction, cell cycle), the prediction of response to

therapy (20-26), and the identification of patterns associated with prolonged patient survival time (27-29). However, the results derived from such studies cannot be trusted unless they are adequately designed and reported. Many published studies dealing with cancer-related clinical outcomes have recently been criticized as they contain basic flaws such as lack of control for multiple testing, misuse of class discovery algorithms and biased estimation of prediction accuracy (30-31). This means that the prognostic value of many published microarray results in cancer studies should be considered with caution. Several critical points can be highlighted within the multi-step process that generates gene expression results. Here we deal with some of these, without considering the issue of comparing results between different microarray platforms and/or laboratories, since it has already been widely covered by our and many other groups (32-35).

Pitfalls of global scale analysisAlong the microarray experiment workflow,

Keywords: gene profiling, high-throughput technology, feature selection, enrichment analysis

EDITORIAL

Vol. 22, no. 1, 7-16 (2008)

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there are many sources of variability, most of which are overcome via a good design of the experiment and an initial set-up phase to optimize every step. However, since technology is still under continuous development, a “standard” way to process samples and data does not yet exist.

Different protocols could give different results

To assure the reproducibility of a microarray experiment, it is important to adopt robust laboratory protocols, either commercial or in-house. One of the limits of high density microarray technology, is the difficulty of profiling gene expression from archive tissue, the best source of information on the patients’ clinical history side, but the poorest on the RNA quality side. However, new interesting protocols (36-38) have recently been developed that allow expression profiling of a limited number of selected genes (up to 1500) starting from partially degraded RNA extracted from fixed tissue. In this case, the expression signal observed for any particular gene is always relative to the other genes present in the pool, and therefore sensitivity and fold-change measures are only valid within a given pool and are not easily comparable to results from the usual high density gene profiling assays. For these latter, sample integrity and purity are essential, and the combination of two instruments (namely, the Bioanalyzer and the Nanodrop) can overcome their own limitations and allow the correct identification of integer and pure RNA. After RNA extraction, the subsequent critical experimental steps involve amplification and labeling. Several protocols have been developed, either commercial or in-house, and comparison studies (39-41) show that these procedures may contribute to the variability of gene expression profiling with DNA microarrays. For example, as reported by Laurell and co-workers, different amplification strategies yield results in agreement with those obtained from non-amplified RNA, but different in terms of reproducibility. In general, intra-method reproducibility is higher than that between different methods, and this is probably due to the diverse reaction yields, lengths of sequences obtained and sequence-dependent biases introduced by sample labeling. Variability usually affects low intensity data and therefore care must be taken in considering differentially expressed

sequences with close to background signals.

Different oligonucleotide probes for the same gene could give different results

The design of one probe for a particular gene x follows specific rules, starting from the collection of all available data of all transcripts from various databases, the creation of consensus sequences from those transcripts, the computational design of several probes per consensus region and the comparison of results from different consensus regions by means of real life experiments. The goal is to identify an oligonucleotide sequence or a probeset which reflects the transcriptional behaviour of as many as possible transcripts from that gene. It may happen that the consensus region 1 of gene x shows a different expression behavior in respect to the consensus region 2, therefore the best performing probe for each consensus region that has a specific expression pattern is usually selected. In the case of known splice variants (different transcripts from the same gene that share exons), alternative reading frames (different transcripts for the same gene that share parts of exons and are characterized by a reading frame-shift) or use of alternative poly(A) signals, discordant results are expected. However, it sometimes happens that probes or probesets associated to the same transcript give highly variable signals (43). This could depend on hybridization constants between probe and target, and in this case single color supports are more affected than double color ones, where the relative abundance between sample and reference is calculated. But sometimes, as was reported by Stalteri and colleagues, it could also depend on incorrect annotation. Therefore, care must be taken when assessing whether groups of probes all measure the same transcript.

Furthermore, even when alternative splice forms are present on the array, information about their tissue-specific regulation is often poor or unavailable. This makes data interpretation non trivial, with specific patterns of expression that may change within tissue and time. On the other hand, traditional microarrays for genome-wide expression analysis are designed to measure the total level of expression of a gene, without attempting to distinguish between different splice forms. Being biased towards the 3’ end of the gene, they might contain only one oligo probe or probeset for some genes with known splice variants or alternative reading frames. For these particular cases, only

G. CHIORINO ET AL.


suitable post-hoc primer design may allow detection of differential expression, although specific high density supports are also available on the market, such as overall predicted exon microarrays (44), genomic tiled microarrays (45), or splicing-specific (exon junction) microarrays (38, 46).

In conclusion, interpreting results from different probes for the same “gene” involves shifting to the view that the genome largely encodes a series of functional RNAs and polypeptides that are expressed in characteristic spatial, temporal, and quantitative patterns. The classical concept of the “gene” ultimately forms a barrier to trying to understand phenotypes in terms of encoded functional products.

Different algorithms could give different resultsTypical experimental designs of microarray studies

may be two-class (e.g. control versus treatment, normal versus disease) or many-class comparisons (e.g. time courses), with the first ones mostly used by the vast majority of scientific communities. The aim of a two class comparison performed with the microarray technique is to extract the genes that are differentially expressed between the two conditions. The main problems in getting statistically significant and meaningful information lie in the intrinsic nature of microarray experiments: the huge number of genes analyzed, the often limited number of cases considered and the noise inherent in that kind of data. Depending on the number of samples analyzed and the amount of noise present in the dataset, one can choose the most appropriate feature selection method. A research paper recently published (47) evaluates and compares several statistical methods for generating differentially expressed gene lists from microarray data. Ten feature selection methods were applied to nine two-class datasets publicly available. Different sample sizes were considered, but no more than 21% of genes were in common across all the feature selection methods applied. They then split the datasets so as to have the same number of samples per class in a training and in a test subset. The efficiency of the feature selection methods analyzed (in this case applied on the training sets) was obtained by evaluating how they performed in class prediction of the related test sets. Classification success was strongly influenced by the amount of noise in the dataset, the choice of feature selection method, the number of the samples analyzed in the study and of

the features contained in the gene list.Overall, methods which do not model the variance

when ranking genes, such as fold change, rank products or between group analysis (47), perform well when datasets have a low number of samples or a high noise level. On the contrary, when the number of samples is bigger than 30 and the variance is not too high, ROC methods (48-49) are more suitable. Methods that model the variance, such as classical t-test, ANOVA and moderate t-statistics (SAM or empirical bayes methods), lie in between, with empirical bayes t-statistic (50) being the most robust method across a wide range of sample sizes. A critical issue not considered by Jeffery and co-workers, but that strongly influences the comparability of results, concerns how to assess the statistical significance of findings when using the aforementioned tests. As already stated, microarray experiments measure expression levels for thousands of genes at the same time. As a consequence of this, thousands of hypothesis are tested simultaneously, generating large multiplicity problems. Even studies with a limited number of candidate genes involve several hypotheses (51). To assess the statistical significance of findings, adjustment for multiple testing is needed. The choice between adjustment methods (typically that of Bonferroni, also called family wise error rate FWER, and that of Benjamini-Hochberg, also called false discovery rate FDR) depends on what kind of results a researcher would like to obtain. Usually, it is preferable to choose control of the FWER if high confidence in all selected genes is desired. In this case, the main problem is linked to the loss of the power due to large numbers of tests: many differentially expressed genes may not appear significant. On the contrary, if a certain proportion of false positives is tolerable, procedures based on FDR are more flexible.

Considering the issues already discussed, one should evaluate a priori the statistical method to apply for microarray data analysis. Nevertheless, the apparent equivalence between two or more statistical criteria giving partially overlapping results, seems to vanish when error weighting methods are adopted. Applying for example Student t-test and ANOVA statistics on the same subset of experimental data without error weighting, usually gives a comparable number of significant genes (same p-value cut-off), with always a lower number of genes extracted by the t-statistic. A large proportion of the genes

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extracted by the Student t-test represents a subgroup of the total number of genes extracted by ANOVA, as long as the difference between classes is high and the intraclass variance is low. By contrast, when an error weighting model is applied (Bonferroni, FDR, Holm, Q-value), the differences between results are substantial. For example, applying a FDR correction to the t-test results, the number of significant genes dramatically decreases. This occurs also when other models are adopted (Bonferroni, Holm, Q-value). On the contrary, applying p-value adjustment to the ANOVA results, does not lead to drastic data reductions, as observed with Student t-test.

In conclusion, depending on the number of samples and on the noise level of our dataset, suitable algorithms and adjustment methods should be applied to detect differentially expressed genes, with the desired level of confidence.

Different annotation levels could give different resultsApart from all kinds of data treatment and statistical

issues, the annotation level to which the analysis is set may strongly influence results. The first level is looking at single oligo probes on the array. Whole genome supports contain verified sequences with a corresponding RefSeq ID, as well as sequences that only have GenBank accession numbers or that code for unknown products. Therefore, a second level of analysis consists in looking at RefSeq (52) or GenBank (53) clusters and combining results from the probes available on the array for each cluster to obtain a single estimate of the abundance of that cluster. At this level, results from probes corresponding to the same Refseq ID are more consistent, while it may often happen that sequences found significant at the single probe level will not correspond to significant GenBank clusters when results are averaged. Another issue to be considered, is that annotation needs continuous updating to avoid misinterpretation of results, since the three organizations collaborating for the GenBank database exchange data on a daily basis and a new release is made every two months.

Growing analysis level, one could choose to look at UniGene clusters (54-55). As far as the UniGene database, it should be noted that the procedures for automated sequence clustering are still under development and the results may change from time to time as improvements are made. Moreover, since

5’ and 3’ reads from the same cDNA clone do not always overlap and clusters may contain splicing variants, no attempt is made to produce contigs or consensus sequences. Therefore, as was discussed before, significant changes associated to putative novel splice variants might fail to be found when setting the analysis to this level.

As a matter of fact, the challenge no longer lies in obtaining gene expression profiles, but rather in interpreting the results to gain insights into biological mechanisms. When link to the protein level is needed, for example to put expression results in relation to functional pathways, individual reporters have to be annotated with the name of the corresponding protein. This typically means that we need protein ID’s (such as Swissprot, trEMBL or Genbank protein ID’s). However, the reporters on the array are usually annotated with the ID of the Unigene or the GenBank cluster to which the reporting sequence belongs, obtained through sequence alignment with the Unigene or GenBank database. Several tools have been developed for improving functional annotation of microarray reporters (56), taking into account the protein level too. Unfortunately, pathway enrichment of gene lists obtained from microarray experiments gives only partial results, since a (sometimes high) percentage of the sequences extracted as differentially expressed still does not have a protein correspondence, due to the yet unknown function of the transcript. Furthermore, signals could even correspond to regulatory non-coding transcripts such as microRNAs.

Potentials of global scale analysisAlthough, as was reported above, the microarray

technology for gene expression profiling still has plenty of uncontrollable parameters, its big potential resides in the global scale analysis level. This refers not only to the possibility of investigating the whole human (or other species) genome, but also in setting the analysis to a multi-gene level. This means that results should be investigated by looking at gene sets rather than individual genes, and at this level most of the variability of the technology is overcome and results are comparable even if analyses are performed in different laboratories using different protocols, platforms, algorithms, etc. Moreover, single-gene analysis may miss important

G. CHIORINO ET AL.


effects on pathways. Cellular processes often affect sets of genes acting in concert. An increase of 20% in all genes encoding members of a metabolic pathway may dramatically alter the flux through the pathway and may be more important than a 20-fold increase in a single gene. When a long list of statistically significant genes without any unifying biological theme is given as output of the analysis, interpretation can be daunting and ad hoc, being dependent on a biologist’s area of expertise. The so called “Gene Set Enrichment Analysis” (GSEA) method was proposed by Subramanian et al (59) for assessing the significance of pre-defined gene sets, rather than individual genes. The gene sets can be derived from different sources, for example the sets of genes representing biological pathways in the cell, or sets of genes whose DNA sequences are close. The idea is that these gene sets are strongly related and hence will have similar expression patterns. In addition, as already stated, in comparing study results from different labs, one might get more reproducibility from gene sets than from individual genes, because of biological and technical variability. GSEA is a computational method useful in the interpretation of gene expression data that determines whether an a priori defined set of genes is enriched in elements from a particular Gene Ontology category.

Recently, several analysis tools (http://www.geneontology.org/GO.tools.microarray.shtml) have become available to identify statistically significant enrichment of functionally related genes in such lists. These tools differ in the visualization capabilities, statistical model used, correction for multiple comparisons and other installation and annotation issues. The main problem of this kind of analysis concerns the correction for multiple experiments. In fact, statistical procedures assume the variables are independent, which is known to be false in this type of analysis. The very hierarchy of the Gene Ontology on which this type of analysis relies, shows that many biological categories are very closely related, sometimes as children of the same node on the next level up. The FDR method is more appropriate when it is known that dependencies exist (60). Another integrative method is that of “Molecular Concept Maps” (MCM), as defined by Tomlins et al (61), which is an “analytical framework for exploring the network of relationships among a growing collection of ‘molecular concepts’,

or biologically related gene sets”. Within this framework, it is possible to compute pair-wise associations among all gene sets in the database, allowing for the identification and visualization of ‘enrichment networks’ of linked concepts. Molecular concepts include lists of differentially expressed genes extracted from microarray datasets available in the Oncomine public database (62), and these lists also contain sequences with unknown function. This enhances the gene set enrichment power, since the queried lists always include such sequences which cannot be linked to any annotated information. Enrichment networks are easily interpretable, with node sizes proportional to the number of genes contained and the thickness of edges proportional to the statistical significance of the association tested between the connected nodes. Each molecular concept type is assigned to a particular color, and this makes visualization easier.

Finally, the molecular systems biology approach is devoted to the inference of gene networks from expression profiles (63) and is based on reverse-engineering algorithms able to identify functional modules (e.g. subsets of genes that regulate each other with multiple and various interactions), to predict the behavior of one system after external perturbations or to identify real physical interactions (such as transcription factors bound to specific sites), via integration of gene profiling results and information from sequences or other experimental techniques.

FOCUS ON RNA PROCESSING

RNA quality control: A total RNA profile output from the Bioanalyzer should give a 28S/18S peak ratio near 2, a linear baseline (otherwise there is some degradation) and no DNA peak at high molecular weight (after the 28S peak). The Bioanalyzer also estimates the RNA integrity number (RIN), giving a score that ranges from 0 to 10 (i.e. a very good sample). The calculation of RNA concentration may not be accurate, because it derives from the comparison between the areas of the sample and of the ladder, which is manually put into the chip. To estimate nucleic acid concentration, it is better to use the Nanodrop, a spectrophotometer that offers some special features: only 1 µl of sample is necessary, without any dilution, and it can be recovered. It is very fast and no consumable is required. To be sure that RNA

12

is free of residual solvents (that can inhibit subsequent enzymatic reactions) or proteins, it is important to verify that 260/230 and 260/280 ratios are greater than 1.8. As a common spectrophotometer, the Nanodrop does not allow distinction between DNA and RNA, because they have the same absorption at 260 nm. Therefore, DNA contaminations determine RNA overestimation.

Sample amplification is essential to increase sample quantity and, if oligo dT primers are used, to select only mRNA between all the RNA populations, avoiding the use of specific mRNA isolation kits, more expensive and less versatile. On the other hand, if mRNA is not directly isolated, one must assume that if totRNA quality is good, also the quality of mRNA (approximately 1-3 % of the total) will be. There are several amplification methods, but some criteria are to be considered: first of all, amplification must not distort the original proportion between different transcripts. Moreover, DNA polymerase and RT- transcriptase have to be highly processable and stable. The reaction yield must also be taken into account: one or two amplification cycles could be performed, but for the latter the average transcript length gets shorter. After amplification, aRNA quality can be evaluated by means of Bioanalyzer electropherograms. The expected result is a normal curve, whose peak corresponds to the average transcript length (for one amplification cycle); for two cycles of amplification, the curve will be shifted on the left.

Labeling techniques, could be subdivided into two main groups: direct and indirect methods. Fluorescent incorporation timing is the principal difference between them. Direct labeling methods are quicker, because fluorescently labeled nucleotides are incorporated during amplification: therefore amplification and labeling occur together, whereas when indirect procedures are used, they are consecutive. Generally, each procedure maintains the correct biological information but the former is more affected by different dye incorporation rate (two color assays). Traditional indirect labeling methods incorporate modified nucleotides during amplification, but this reduces the amplification yield. New protocols combine the indirect method advantage with the use of unmodified and amplified RNA (42). aRNA is more stable for storage, gives longer fragments than modified aRNA and moreover it is suitable, not only for microarray analysis, but also for other applications (e.g. qPCR).

FOCUS ON MULTIPLE HYPOTHESIS TESTING

A hypothesis testing has the following assumptions: the null hypothesis, usually the hypothesis that variation is only due to chance, and the alternative hypothesis (e.g. differential expression). The alternative hypothesis usually represents what we would like to demonstrate. In general, in any testing situation, two types of errors can be committed: Type I error (or false positive), committed by declaring that a gene is differentially expressed when it is not, and Type II error (or false negative), committed when the test fails to identify a truly differentially expressed gene. The power of a statistical test represents the probability of rejecting the null hypothesis when it is in fact false and should be rejected. Type I and II errors may be reduced (and power increased) simultaneously by increasing the sample size n. Moreover, the concept of p-value is strictly associated with the hypothesis testing: it gives the probability of observing a value as extreme or more extreme than the one just observed if the null hypothesis were true. In other words, it is a measure of support of the null hypothesis. Looking at raw p-values could lead to serious misunderstandings and errors in the interpretation on microarray data. In fact, when many hypotheses are tested and each test has a specified Type I error probability, the chance of committing some Type I errors increases, often sharply, with the number of hypotheses. For example, if we suppose having 10,000 genes on a chip and not a single one is differentially expressed, one would expect 10,000*0.01 = 100 of them to have a p-value < 0.01. In this case, individual p–values of e.g. 0.01 no longer correspond to significant findings.

FOCUS ON ANNOTATION DATABASES

GenBankGenBank® is the NIH genetic sequence database,

an annotated collection of all publicly available DNA sequences (56). It is part of the International Nucleotide Sequence Database Collaboration, which comprises the DNA DataBank of Japan (DDBJ), the European Molecular Biology Laboratory (EMBL), and GenBank at NCBI. These three organizations exchange data on a daily basis. There are more than 60,000,000 sequence records in the traditional GenBank division and a new

G. CHIORINO ET AL.


release is made every two months.

UnigeneUniGene (54-55), a gene indexing database, is at

present the most substantial repository of transcript information from human, rat, mouse and zebrafish. Expressed sequence tags (ESTs) and annotated mRNA sequences from GenBank are automatically partitioned into a non-redundant set of clusters, each of which represents unique genes. Sequences are clustered together when they share a statistically significant overlap, or when they originate from different sequencing reads of the same cDNA clone. Because 5’ and 3’ reads from the same cDNA clone do not always overlap and clusters may contain splicing variants (different transcripts from the same gene that share exons), no attempt is made to produce contigs or consensus sequences for UniGene clusters. Expressed pseudogenes are also present in the database. Each UniGene entry is a set of transcript sequences together with information on protein similarities, gene expression, cDNA clone reagents, and genomic location. It should be noted that the procedures for automated sequence clustering are still under development and the results may change from time to time as improvements are made.

RefSeqRefSeq (52) is a public database of nucleotide

and protein sequences with corresponding feature and bibliographic annotation. The RefSeq database is built and distributed by the NCBI, that makes RefSeq publicly available, at no cost, over the internet via FTP, Entrez query, BLAST programs, and incorporation in a wide range of NCBI resources. In contrast to GenBank, RefSeq represents a nearly non-redundant collection that is a synthesis and summary of available information, and represents the ‘current’ view of the sequence information, names and other annotations. RefSeq records can be distinguished from GenBank records by the format of the accession series. RefSeq accession numbers are formatted as two alphabetic characters, followed by an underscore (‘_’), optionally followed by four alphabetic characters (specific to the NZ_prefix), followed by six, eight or nine numerals. GenBank accessions never include an underscore. Different alphabetic prefixes have implied meaning in terms of both the

process of generation and the type of molecule represented.

Swiss-ProtUniProtKB/Swiss-Prot (57-58) is a manually

annotated protein knowledgebase established in 1986 and maintained since 2003 by the UniProt Consortium, a collaboration between the Swiss Institute of Bioinformatics (SIB) and the Department of Bioinformatics and Structural Biology of the Geneva University, the European Bioinformatics Institute (EBI) and the Georgetown University Medical Center’s Protein Information Resource (PIR). The UniProtKB/Swiss-Prot database gives access to all the publicly available protein sequences and distinguishes itself from other protein sequence databases by three distinct criteria: annotation, minimal redundancy and integration with other databases.

CONCLUSION

We conclude by visualizing all the issues discussed in this review via an “enrichment network” of linked concepts (Fig. 1), without which we think no microarray project should be even started.

Fig. 1. “Enrichment network” of the concepts discusses in the paper and related to the identification of a set of differentially expressed genes (grey circle in the middle of the network). Concepts are subdivided into classes as shown in the legend. Node sizes are proportional to the level of importance of the concept and the thickness of the edges is proportional to the level of interdependence between connected concepts.

Annotationlevel

N. ofsamples

Intraclassvariability

Samplehomogeneity N. of

replicates

Protocol

Platform

Feature selectionmethod

Dataprocessing

Interclassvariability

Differentially expressed genes

Sample characteristics

Data processing

Experimental design

Annotationlevel

N. ofsamples

Intraclassvariability

Samplehomogeneity N. of

replicates

Protocol

Platform

Feature selectionmethod

Dataprocessing

Interclassvariability

Differentially expressed genes

Sample characteristics

Data processing

Experimental design

14

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TOLL-LIKE RECEPTORS

P. DASARI1,2, I.C. NICHOLSON1, 2, 3 and H. ZOLA1, 2, 3

1Child Health Research Institute, Women’s and Children’s Hospital, Adelaide; 2Department of Paediatrics, Flinders University of South Australia, Adelaide; 3Cooperative Research Centre for

Diagnostics, Australia

Received January 30, 2006 – Accepted March 2, 2007

Mailing address:Pallave Dasari,72 King William Road,North Adelaide, S.A.,Australia 5006Tel: ++61 8 8161 7443 Fax: ++61 8 8239 0267e-mail: [email protected]

Key words: CD281 - TLR1, CD282 - TLR2, CD283 - TLR3, CD284 - TLR4, CD289 - TLR9, CD290 - TLR10

Toll-like receptors are a family of transmembrane receptors responsible for recognition and initiation of a response to invading microbes by the immune system. As part of the innate immune system, toll-like receptors recognise pathogen-associated molecular patterns, highly conserved components that are essential to microbial function. Some of ten toll-like receptors identified in humans are able to recognise several pathogen-associated molecular patterns.

Toll-like receptors (TLR) are a family of transmembrane receptors responsible for recognition and the initiation of a response to invading microbes by the immune system (1). As part of the innate immune system, TLR recognise pathogen-associated molecular patterns (PAMP), highly conserved components that are essential to microbial function (2, 3). Ten TLR have been identified in humans with some TLR able to recognise several PAMPs (4-7).

StructureTLR are Type I integral membrane glycoproteins

with molecular weights ranging 90-115kDa (8). The protein chains range from 780-1,000 amino acids (5, 9) and they share a conserved cytoplasmic domain, known as Toll/IL-1R (TIR) domain, with the interleukin-1 receptor family (IL-1R) (3). The extracellular domains of TLR and IL-1R differ in that TLR have several leucine-rich repeat (LRR) motifs, while IL-1R have three immunoglobulin domains (3). TLR can be located either on cell surfaces or on endosomal surfaces (8) (See Fig. 1 and Table I).

The ectodomain of TLR contain 19-25 copies

of LRR capped with a 31-amino acid long N-flanking region and a cysteine-rich domain on the C-terminal end (3, 8). An individual LRR is made of approximately 24 residues and forms a loop, with the first 10 residues forming a β-hairpin (8). The LRR motifs all form a coil with a large β-sheet on the concave surface formed by β-strands of each motif (8). Other, similar, receptors bind to their ligands on the concave β-sheet of the LRR motifs with new binding sites created by inserting or deleting residues in the LRR motifs, suggesting that similar binding sites for ligands may occur in TLR (8).

The TIR domain has a sequence conservation of approximately 20-30% with most of the conserved residues located in the hydrophobic core of the structure, the core approximately 130-165 residues in length (10). The TIR domain has five β-strands, parallel, surrounded by five α-helices, with secondary structures all connected by loops (10). Three regions in the conserved sequence identified as boxes 1, 2 and 3 appear to have a role in signalling as deletions in each box eliminated signalling (11). Mutations in boxes 1 and 2 affected signalling and mutations

EDITORIAL

Vol. 22, no. 1, 17-26 (2008)

18

induce cytokine production (21).Late-phase activation of NF-κB to induce

expression of co-stimulatory molecules and IFN-associated products is triggered by MyD88-independent signalling pathway (19). This pathway induces DC maturation via TLR4 (22) and also triggers activation of interferon-regulatory factor (IRF3) to directly induce expression of type 1 IFN genes (19). The MyD88-independent pathway has not yet been elucidated, but TLR 3 and 4 require TRIF for signalling through the MyD88-independent pathway (22-23).

LPS-activated TLR4 utilises both MyD88-dependent and MyD88-independent pathways for inflammatory cytokine production and TRAM is required by TLR4 for the MyD88-independent pathway (24). TLR initiate several signalling

in box 3 reduced cell surface expression (11). The three regions in the TIR domain all play essential roles in receptor localisation and signalling (11).

Cell and tissue distributionTLR are expressed by a wide range of cells and

tissues, including endothelia and epithelia (1), as well as being present on immune cells (see Table II). TLR can be expressed either on the cell surface, such as TLR 1, 2, 4, 6, 9 and 10 (12-14), or in the case of TLR3, on cell endosomes (15). Both the functions of the cells and the TLR type affect location of TLR expression, for instance, TLR with viral ligands are more likely to be expressed in dendritic cell (DC) endosomes. Cells also vary TLR expression according to whether they are resting or activated. As observed by Komai-Koma, activated T cells upregulate surface expression of TLR2 and TLR4 (16). Activation of cells which alters TLR expression can occur by several mechanisms including direct activation (16), microbial infections (17-18) and cytokines (18). TLR expression can be differentially regulated from resting cells to activated cells through inflammation or disease.

SignallingTLR engagement initiates signalling cascades

eventuating in activation of nuclear factor-κB (NF-κB) to express target genes encoding inflammatory cytokines, costimulatory molecules and interferon (IFN)-inducible products (19). A family of adaptor proteins, each containing a TIR domain, directs TLR signals to different signalling cascades resulting in distinct outcomes. The adaptor proteins, myeloid differentiation primary-response protein 88 (MyD88), TIR-domain-containing adaptor protein (TIRAP), TIR-domain-containing adaptor protein inducing IFN-β (TRIF) and TRIF-related adaptor molecule (TRAM), interact with TLR to trigger signalling pathways (19).

Engaged TLR 1, 2, 4, 5, 6, 7 or 9 can activate NF-κB via MyD88-dependent pathway by dimerising TIR domains with MyD88 in the cytoplasm to initiate a signalling cascade as described by Akira (19). This cascade culminates in early-phase activation of NF-κB which transcribes expression of inflammatory cytokines (19-20). TIRAP acts upstream of MyD88 in the pathway and is essential for TLR 2 and 4 to

22

Fig. 1. Schematic structure of Toll-like Receptor 1. Other TLR have similar structure, except for differences in numbers of LRR motifs.

Fig. 1. Schematic structure of Toll-like Receptor 1. Other TLR have similar structure, except for differences in numbers of LRR motifs.

P. DASARI ET AL.


cascades for NF-κB and IRF3 activation, but further work is required to elucidate the steps in these cascades completely.

FunctionTLR have a profound impact on both innate

and adaptive immune responses by either directly activating immune cells or indirectly influencing them through cytokine signals from TLR-engaged cells. TLR can interact with ligands individually or increase their range of ligands through dimerisation with other TLR or cell receptors (see Table III). This section gives a brief overview of the impact each TLR has on immune cells.

TLR1. Heterodimers of TLR1 and TLR2 recognise lipopeptides or lipopolysaccharide (LPS) and activate cells to secrete proinflammatory cytokines (25-26). The importance of TLR1 as an accessory molecule is observed in TLR2-activated macrophages with enhanced responses in the presence of TLR1 against mycobacterial components (26).

TLR2. Heterodimers of TLR2 with either TLR1 or TLR6, can recognise a wide repertoire of ligands from bacterial and viral products to endogenous ligands (16, 25, 27).

TLR2-activated neutrophils display several anti-microbial functions including phagocytosis and recruitment of immune cells through increased proinflammatory cytokine and chemokine expression (12). TLR2 ligands also activate B lymphocytes to proliferate and secrete IgG or IgM antibodies (28) and T lymphocytes to proliferate and secrete cytokines which augment the adaptive response (16).

TLR3. Engagement of TLR3 activates macrophages to secrete IFN (29) and stimulates mast cells to activate lymphocytes through chemokines and co-stimulatory molecule signals (30, 31). TLR3 can activate T lymphocytes directly (32) or activate and influence CD8+ T cell function indirectly through TLR3-stimulated mast cells and DCs (15, 30).

TLR4. As discussed above, LPS-activated TLR4, with co-receptor CD14 (27), initiates several signalling cascades, thereby amplifying the signals leading to cellular responses (24).

The stimulation of neutrophils, the primary innate immune leucocytes, by LPS via TLR4 increases antimicrobial activities through increased phagocytosis and superoxide production, decreased

chemotaxis and increased chemokine and cytokine expression (12, 33). TLR4 engagement can activate T lymphocytes directly (32) or indirectly through cytokine secretions of TLR4-stimulated DCs (34). TLR4 stimulation of B lymphocytes causes maturation and proliferation in the adaptive response (35).

TLR5. TLR5-activated neutrophils display increased phagocytosis, superoxide production and immune cell recruitment through increased expression of proinflammatory cytokines and chemokines (12).

TLR6. TLR6 can form heterodimers with TLR1 or TLR2 to increase specificity of ligand recognition and enhance cellular activation with subsequent cytokine induction (13).

TLR7. As has been noted with the other TLR, TLR7 engagement is effective for activating antimicrobial functions in neutrophils (12). TLR7-

15

Table I. TLR differ in structure through variable numbers of LRR motifs.

TLR Numbers of LRR

1 19

2 19

3 23

4 21

5 20

6 19

7 25

8 25

9 25

10 19

Table I. TLR differ in structure through variable numbers of LRR motifs.

20

engaged eosinophils have prolonged survival and induce superoxide production (36). TLR7 ligands activates T lymphocytes directly (32) and induce IFN-α and IFN-regulated cytokines in PBMCs (34).

TLR8. TLR8 ligands are effective for inducing proinflammatory cytokine expression from peripheral blood mononuclear cells (PBMCs) and differential cytokine signals from plasmacytoid DCs and myeloid DCs (34). A recent study has revealed

16

Table II. expression of TLR on human immune cells (references in brackets).

Cell Type Polymerase

Chain

Reaction

Flow

Cytometry

Fluorescent

Microscopy

Peripheral Blood

�� Neutrophils 1, 2, 3, 4, 5, 6,

7, 8, 9, 10

(12, 36)

1, 2, 4, 6, 9

(12, 13, 18, 33)

NR*

�� Monocytes 1, 2, 4, 5, 6, 7,

8, 9

(42, 56, 57)

1, 2, 4, 6, 9

(18, 33, 56),

(13, 17, 57)

9

(17)

�� Eosinophils 1, 4, 6, 7, 9, 10

(33, 36)

NR NR

�� Basophils 2, 4

(33)

2, 4

(33)

NR

�� T cells 1, 2, 3, 4, 5, 6,

8, 9

(16, 42, 58)

2, 4

(16)

2, 4

(16)

�� B cells 1, 2, 4, 6, 7, 9,

10

(14, 42)

1, 9

(17, 59)

NR

�� Natural

Killer cells

1, 2, 3, 4, 5, 6,

8, 9

NR NR

17

(42, 58)

Tonsillar B

lymphocytes

1, 6, 7, 8, 9, 10

(41)

9

(60)

2

(18)

Macrophages NR 4

(57, 61)

2, 4

(18, 61)

Dendritic Cells

�� Immature

DCs

1, 2, 3, 4, 6

(56)

1

(56)

NR

�� Mature DCs 1, 6

(56)

9

(60)

NR

�� Plasmacytoid

DCs

1, 6, 7, 9, 10

(14, 42)

9

(60)

NR

*NR � Not reported

Table II. Expression of TLR on human immune cells (references in brackets).

*NR – Not reported

19

Human HSP60 and HSP70 (27, 62)

Human fibronectin (27)

Human hyaluronic acid, etc (27)

5 Bacterial flagellin (52)

6 Lipopeptide/lipoprotein (Mycoplasma) (13)

Peptidoglycan (13)

Zymosan (12)

7 ssRNA (27)

8 ssRNA (27)

9 Unmethylated CpG DNA motifs (9)

10 Not known

18

Table III. Ligands of TLR.

TLR Ligands

1 Lipoprotein (Mycobacterium sp.) (26)

LPS (25)

Soluble factors (Neisseria meningitidis) (25)

2 Lipopeptides/lipoproteins (including Mycoplasma and Mycobacterium

tuberculosis) (13, 16, 51)

Glycolipids (13, 16)

LPS (18, 25)

Soluble factors (Neisseria meningitidis) (25)

Zymosan (16)

Peptidoglycan (13, 16)

Porin (27)

Bacterial fimbrae (27)

Haemagglutinin protein (27)

Cytomegalovirus virions (27)

Human Heat shock protein (HSP) 60 and HSP70 (27, 62)

3 dsRNA (31)

4 LPS (6, 12)

Respiratory syncytial virus (53)

Chlamydial HSP60 (27)

Mycobacterial HSP65 (27)

Fibrinogen (27, 53)

Table III. Ligands of TLR.

P. DASARI ET AL.


a direct, DC-independent, role for TLR8 ligand suppressing T regulatory cells and reversing their effects (37).

TLR9. CpG DNA is a strong immune adjuvant (38) which stimulates B lymphocytes directly through TLR9, inducing polyclonal activation and proliferation, low affinity antibody production, co-stimulatory molecular expression and cytokine secretion (39-41). Independently of T lymphocytes, TLR9-engaged memory B cells can secrete antibodies allowing innate immunity to induce an adaptive response (39). Macrophages and DCs activated by TLR9 ligands elevate co-stimulatory molecule expression and secrete cytokines for

differential immune responses (9, 34). TLR9 engagement can activate T lymphocytes directly (32) or indirectly through cytokine signals from TLR9-engaged DCs (32). TLR9 ligands activate natural killer (NK) lymphocytes to secrete cytokines and clear pathogens (39, 42) and neutrophils to induce antimicrobial functions (12).

TLR10. TLR10 forms heterodimers with TLR1 or TLR2 (14), but its ligand and function are still unknown.

General Functions DC maturation by TLR engagement results

in up-regulation of co-stimulatory molecules,

20

Table IV. Mouse and rat anti-human TLR monoclonal antibodies.

TLR Format Source

1 P, B, PE eBiosciences, BD Biosciences, Imgenex,

RnD Systems

2 P, B, F, PE, Pe-Cy7, APC,

AF405, AF488, AF647

eBiosciences, BD Biosciences, Imgenex,

RnD Systems

3 P, B, F, PE eBiosciences, BD Biosciences, Imgenex

4 P, B, F, PE, Pe-Cy5, Pe-Cy7,

APC, AF405, AF488, AF647

eBiosciences, BD Biosciences, Imgenex

5 P, F, PE Imgenex

6 P*, B*, F eBiosciences, Imgenex

7 -

8 P, B, F, PE Imgenex

9 P*, B, F, PE* eBiosciences, Imgenex

10 P Imgenex

P � Purified; B � Biotinylated; F � Fluorescein; PE � Phycoerythrin; Pe-Cy5; Pe-Cy7; APC � Allophycocyanin; AF � Alexa Fluor *Available as rat antibodies from eBiosciences

Table IV. Mouse and rat anti-human TLR monoclonal antibodies.

P – Purified; B – Biotinylated; F – Fluorescein; PE – Phycoerythrin; Pe-Cy5; Pe-Cy7; APC – Allophycocyanin; AF – Alexa Fluor *Available as rat antibodies from eBiosciences

22

21

Table V. Genebank accession numbers. NCBI Reference Sequence

TLR Species Protein mRNA

1 Mouse NP_109607 NM_030683

Human NP_003254 NM_003263

2 Mouse NP_036035 NM_011905

Human NP_003255 NM_003264

3 Mouse NP_569054 NM_126166

Human NP_003256 NM_003265

4 Mouse NP_067272 NM_021297

Human NP_612564 NM_138554

5 Mouse XP_622092 XM_622092

Human NP_003259 NM_003268

6 Mouse NP_035734 NM_011604

Human NP_006059 NM_006068

7 Mouse NP_573474 NM_133211

Human NP_057646 NM_016562

8 Mouse NP_573475 NM_133212

Human NP_057694 NM_016610

9 Mouse NP_112455 NM_031178

Human NP_059138 NM_017442

10 Rat XP_223422 XM_223422

Human NP_112218 NM_030956

Table V. Genebank accession numbers.

P. DASARI ET AL.


altered expression of chemokines and secretion of proinflammatory cytokines allowing them to increase their antigen presenting ability and migrate to lymph nodes (1, 39). Different TLR, when engaged, trigger different pathways with different cellular outcomes. Differential cytokine release and co-stimulatory molecule expression by subsets of DCs shapes T cell differentiation, therefore influencing adaptive response (1, 39). DCs can also be stimulated by agonists for TLR3 and TLR4 acting synergistically with each other or with TLR8, with synergy enhanced further by IFN-γ or CD40L. The cytokine signals expressed in this instance activate T cells to secrete IFN-γ (43). A recent study has found TLR-activated DCs secrete IL-6 to suppress regulatory T cells from interfering with activated CD4+ T cells (44).

DiseaseAutoimmunity. The influence which TLR exert

over the adaptive response and their ability to recognise endogenous ligands has implications for development of systemic autoimmune diseases. TLR9 and B cell receptor on autoreactive B cells engaged with murine chromatin from apoptotic cells, triggering activation and proliferation (45). TLR9 is also implicated in breaking T cell self tolerance via TLR9-engaged antigen-presenting cells and inducing murine experimental autoimmune encephalomyelitis, the animal model of multiple sclerosis (46). Inflammatory bowel disease, a localised autoimmune condition, has been linked to Asp299Gly TLR4 polymorphism which has an impaired signalling pathway for LPS (47, 48). In summary, TLR dysregulation or impaired signalling pathways can lead to systemic or localised autoimmune conditions.

Infectious Diseases. Since TLR launch an immune response against invading pathogens, TLR dysfunction may be related to pathology of infectious diseases. With focus on polymorphisms, the Asp299Gly TLR4 polymorphism, known to have lowered response to LPS (47), has been associated with patient cohorts suffering Gram-negative septic shock (49) and systemic inflammatory response syndrome (50) indicating predisposition of this population carrying this polymorphism to these illnesses. Other polymorphisms in TLR2 and TLR5 may be associated with increased susceptibility to

tuberculosis (51) and Legionnaire’s Disease (52). TLR activity can aggravate effects of microbes further as seen in infants with the Asp299Gly TLR4 polymorphism suffering severe respiratory syncytial viral infections (53). The effects of excessive presence of inflammatory cytokines from TLR activation can be damaging as is demonstrated by patients developing septic shock (54) or in murine models where TLR2 activity induced streptococcal arthritis in joints (55). New therapies may need to target TLR or their signalling pathways to reduce pathology of certain diseases.

CONCLUSIONS

In conclusion, interest in TLR has increased considerably in recent years as their significance in the innate and adaptive immune systems has been revealed. The discovery of TLR has renewed interest in the innate immune system by showing, through cell activation and inflammatory responses, the importance of the early innate immune response against invading pathogens. The influence the innate system has on adaptive immunity is illustrated by how TLR tailor the adaptive response through cytokine signals, directly activating lymphocytes and indirectly influencing T cell differentiation. These known functions have linked the two branches of immunity, innate and adaptive, previously considered to have separate, isolated roles from each other. TLR have extensive effects in immunity and the full extent of TLR activities on the immune system requires further research.

Available Reagents: See Table IVGenebank Accession Numbers: See Table V

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REPRODUCIBILITY OF ATOPY PATCH TESTS WITH FOOD AND INHALANT ALLERGENS

R. RONCHETTI1, M. JESENAK1,2, S. BARBERI1, F. RONCHETTI3,Z. RENNEROVA1,4, D. TRUBACOVA1,4 and M.P. VILLA1

1Department of Paediatrics, Second School of Medicine, University “Sapienza”, Rome; 2Department of Paediatrics, Jessenius School of Medicine, Comenius University in Bratislava,

Martin, Slovak Republic; 3Department of Otorhinolaryngology, Second School of Medicine, University “ Sapienza”, Rome, Italy; 4Srobar’s Institute for Respiratory Diseases and Tuberculosis

for Children, Dolný Smokovec, Vysoké Tatry, Slovak Republic

Received April 19, 2007 – Accepted January 15, 2008

hen’s egg and cereals) (4-9). Despite the need for standardization, especially for food APT (10-11), this test has an acknowledged clinical role, especially in the diagnosis of atopic dermatitis and food allergy (5, 12). Among several variables that can strongly influence the results of APT are allergen concentration, skin site and devices used for

Although atopy patch tests (APT) seem a valuable additional tool in the diagnostic work-up for food allergy in children with atopic eczema/dermatitis syndrome, the immunopathology and some technical aspects of testing remain controversial. Few published data are available on the reproducibility of APT with inhalants and only two studies include fresh food allergens. In this study we therefore investigated the reproducibility of duplicate APT (left versus right side of the back) with native and commercially available food (cow’s milk, hen’s egg, tomato, wheat flour) and with inhalant allergens (Dermatophagoides pteronyssinus and mixed grasses) in a large unselected population of children. We tested a population of 277 Italian schoolchildren with three APT allergens: fresh food (cow’s milk, hen’s egg, tomato and wheat flour), standardised food allergens in petrolatum (the same four foods) and standardised inhalant allergens routinely used for skin prick testing. For the four food allergens (applied in the natural form or as the standardised commercial preparation) from one- to three quarters of the APT gave positive results on one side and negative reactions on the opposite side (Cohen’s κ coefficient between 0.38, fresh tomato and 0.81, fresh cow’s milk). Conversely, APT with inhalant allergens were invariably reproducible (Cohen’s κ = 1.00). The possible technical and immunologic reasons explaining why reproducibility of APT differed for the two types of allergens await an answer from extensive controlled studies.

Mailing address: Prof. Roberto Ronchetti, MD., PhD.Clinica Pediatrica, Ospedale Sant’Andrea,Via Grottarossa 1035/1039, 00189 Rome, ItalyTel: ++39-06-3377 5856Fax: ++39-06-3377 5941e-mail: [email protected]

Key words: atopy patch test, children, food allergens, inhalant allergens, reproducibility, unselected population

The atopy patch test (APT), an epicutaneous application of intact protein allergens followed by the evaluation of skin reactions after 48-72 hours, is widely used as a diagnostic tool in patients with symptoms elicited by aeroallergens (particularly Dermatophagoides pteronyssinus) (1-3) and food allergens (especially cow’s milk,

Vol. 22, no. 1, 27-33 (2008)

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same children (131 children, 58% males, age 9.40 ± 2.24 years, 88 belonging to the younger and 43 to the older group) also underwent atopy patch testing with two solutions of inhalant allergen. All the tests were applied simultaneously on each side of the back.

The study was approved by the Ethical Committee of the Paediatric Clinic of Rome University ‘Sapienza’.

Atopy patch tests (APT) All APTs were carried out in duplicate applying

plastic quadratic chambers 10 mm in diameter (Finn Chambers, Haye’s, the Netherlands) on each side of the back. One drop of each allergen (50 μL) was placed into the chambers which were attached to an area of unaffected skin on the children’s backs. As a negative control, physiological solution was used. In the younger group we applied four fresh food allergens: cow’s milk (containing 3.5% fat), whisked hen’s egg (egg white and yolk), tomato and wheat flour (dissolved in saline, 1g/10 mL). In the older group we carried out APT with standardised food allergens (cow’s milk 10%, hen’s egg 10%, tomato 20%, wheat flour 10%) dissolved in petrolatum (Lofarma S.p.a., Milano, Italy). In a subgroup of children (taken from the older and younger groups) we also performed APT with two standardised inhalant allergen solutions for skin-prick testing (Dermatophagoides pteronyssinus and mixed grasses: Avena sativa, Hordeum vulgare, Secale cereale, Triticum sativum; ALK-ABELLO, Hørsholm, Denmark). The occlusion time was 48 hours. The results were read 20 min after the chambers were removed and at 72 hours for the final test evaluation. The reading criteria were those recommended by the revised European Task Force on atopic dermatitis for APT reading (11). Reactions were classified as positive if they caused either erythema with infiltration or papules. Erythema without palpable infiltration was considered as questionable. In the final judgment questionable results were considered as negative.

Statistical methodsData were analysed with the software package SPSS

version 9.0 (SPSS Inc. Chicago, IL, USA). Chi square (χ2) test or Fisher’s exact test were used for statistical comparison. P values less than or equal to 0.05 were considered to indicate statistical significance. The reproducibility of the APT was evaluated by assessing the percentage of agreement and by the κ statistic (Cohen’s test).

RESULTS

Each of the three types of allergens tested on the two sides of the back elicited identical mean

allergen application, and reading time or criteria for defining positive reactions. These variables seem to be specific for each allergen (7, 13-17).

Before any diagnostic test is applied in routine clinical practice its results must meet the criteria for reproducibility. The studies on APT reproducibility leave important unsolved issues because of peculiar study design (including retesting at variable intervals only of subjects with positive tests), small numbers of studied subjects, variable quality and concentrations of allergens, and non-homogenous criteria for reading and reporting positive tests. APT positive reactions and scores often differ in patients (especially those with atopic dermatitis) and healthy controls (1, 13, 14, 18, 19), a finding which should be considered in the many studies involving selected patients (18, 20-23). For these and many other reasons, APT performed in parallel with the same allergen in the same individual has been found reproducible for chemical substances (24-27) but the results varied from absolute agreement (20, 23, 28-29) to very poor reproducibility (18-19, 21, 30) for APT with inhalant allergens. No satisfactory data exist on the reproducibility of APT with food allergens (18, 22). Results from studies comparing two APT performed at different times in the same individual are less reproducible than tests performed at the same time in two different skin sites (18-19, 21, 31-34).

In this study, we investigated the reproducibility of duplicate APT (left versus right side of the back) with food (cow’s milk, hen’s egg, tomato, wheat flour) in its native form and as supplied by a commercial company, and with inhalant allergens (Dermatophagoides pteronyssinus and mixed grasses) in a large unselected population of school children.

MATERIALS AND METHODS

Study populationsWe enrolled an unselected population of 277 children

attending two primary schools in the north of Rome (Italy) from October 2005 to March 2006. We studied the children in 2 age groups: the younger group (184 children, 52.7% males, age 8.71 ± 1.41 years) underwent APT with fresh food allergens and the older group (93 children, 50.5% males, age 12.92 ± 0.81 years) with standardised food allergens in petrolatum vehicle. A subgroup of the

R. RONCHETTI ET AL.


APT positive reactions – we observed the same frequencies of positive APT results on both sides of the back for each allergen in the studied population (p non significant; χ2 test or Fisher’s exact, Table I). The prevalence of positive APT for cow’s milk tended to be lower in older children (standardised food allergens). The mean number of positive reactions on the two sides remained unchanged regardless of the criteria used to define positivity (Table I).

The four food allergens applied as standardised commercial preparations yielded reproducible results in 50-57% of the tests (Cohen’s κ between 0.65 and 0.71). Among fresh food allergens, tomato

(Cohen’s κ = 0.375) and wheat flour (Cohen’s κ = 0.490) gave reproducible results in 25-32% of the tests, whereas fresh cow’s milk yielded reproducible results in 70% of positive reactions and achieved the highest Cohen’s κ (0.81) (Table II).

Conversely, inhalant allergens invariably gave optimally reproducible results. All the positive APT reactions were positive on the opposite side of the back and negative reactions were negative also on the other side (Cohen’s κ = 1.00 for both allergens) (Table II).

All the reported reproducibility rates were the same in males and females (p non significant; χ2 test

Table I. Prevalence of atopy patch tests with food allergens (fresh and standardised) or inhalant allergens.

Atopy patch test performedwith fresh

food allergens (n = 184)

with standardisedfood allergens

(n = 93)

with inhalant allergens

(n = 131) Left right left right left right Cow�s milk Dermatophagoides pteronyssinusneg. 153 (83.2%) 154 (83.7%) 80 (86%) 85 (91.4%) 91 (69.5%) 91 (69.5%) � ? 10 (5.4%) 10 (5.4%) 8 (8.6%) 2 (2.2%) 1 (0.8%) 1 (0.8%) � + 7 (3.8%) 8 (4.3%) 5 (5.4%) 6 (6.5%) 0 0 � ++ 11 (6.0%) 10 (5.4%) 0 0 5 (3.8%) 4 (3.1%) � +++ 3 (1.6%) 2 (1.1%) 0 0 34 (26%) 35 (26.7%) pos. (�+�+�) 21 (11.4%) 20 (10.9%) 5 (5.4%) 6 (6.5%) 39 (29.8%) 39 (29.8%) Hen�s egg Mixed grasses neg. 155 (84.2%) 161 (87.5%) 86 (92.5%) 88 (94.6%) 126 (96.2%) 126 (96.2%) � ? 14 (7.6%) 12 (6.5%) 4 (4.3%) 2 (2.2%) 0 0 � + 6 (3.3%) 5 (2.7%) 3 (3.2%) 3 (3.2%) 0 0 � ++ 6 (3.3%) 5 (2.7%) 0 0 2 (1.5%) 3 (2.3%) � +++ 3 (1.6%) 1 (0.5%) 0 0 3 (2.3%) 2 (1.5%) pos. (�+�+�) 15 (8.2%) 11 (6.0%) 3 (3.2%) 3 (3.2%) 5 (3.8%) 5 (3.8%) Tomatoneg. 171 (92.9%) 170 (92.4%) 51 (96.2%) 51 (96.2%) � ? 5 (2.7%) 7 (3.8%) 1 (1.9%) 0 � + 3 (1.6%) 1 (0.5%) 1 (1.9%) 1 (1.9%) � ++ 3 (1.6%) 4 (2.2%) 0 0 � +++ 2 (1.1%) 2 (1.1%) 0 1 (1.9%) pos. (�+�+�) 8 (4.3%) 7 (3.8%) 1 (1.1%) 2 (3.8%) Wheat flourneg. 165 (89.7%) 163 (88.6%) 83 (89.2%) 85 (91.4%) � ? 8 (4.3%) 9 (4.9%) 5 (5.4%) 4 (4.3%) � + 2 (1.1%) 2 (1.1%) 3 (3.2%) 3 (3.2%) � ++ 7 (3.8%) 8 (4.3%) 1 (1.1%) 1 (1.1%) � +++ 2 (1.1%) 2 (1.1%) 1 (1.1%) 0 pos. (�+�+�) 11 (6.0%) 12 (6.5%) 5 (5.4%) 4 (4.3%) neg. - negative reaction; � ? � erythema without infiltration; � + - erythema with palpable infiltration; � ++ - erythema and less than 3 papules; � +++ - erythema and 4 or more or spreading papules; pos. � positive reaction.

Table I. Prevalence of atopy patch tests with food allergens (fresh and standardised) or inhalant allergens.

neg. - negative reaction; � ? – erythema without infiltration; � + - erythema with palpable infiltration; � ++ - erythema and less than 3 papules; � +++ - erythema and 4 or more or spreading papules; pos. – positive reaction.

30

or Fisher’s exact test).

DISCUSSION

In this study, carrying out APT on both sides of the back with food allergens (fresh or standardised) in two unselected groups of schoolchildren aged 9 or 13, we achieved poor reproducibility between the two sides of the back: 25-75% of positive APT resulted negative when repeated on the opposite side. Conversely, APT with standardised inhalant allergens (Dermatophagoides pteronyssinus and mixed grasses) yielded optimal overall reproducibility with 100% of the tests giving identical results in the two sides.

The much better APT reproducibility obtained with inhalant allergens than with food allergens cannot be added to current knowledge because of insufficient information concerning food allergens (18, 22). Although reproducibility might have differed owing to technical aspects of the procedure (allergen origin, diameter and form of the chamber, duration

of application and time of reading, and criteria for defining positive reactions) (7, 13-17, 20), we think this unlikely considering our standardised technique produced perfectly reproducible results for the two inhalant allergens. With fresh foods we achieved rather better reproducibility, especially with fresh cow’s milk (the highest Cohen’s kappa) than with standardised food allergens. Canani et al observed the differences in the diagnostic accuracy of APT with the same food allergen in two different forms (native foods and freeze-dried purified food extracts in petrolatum). The better results were achieved with fresh food allergens. These differences could be due to various factors, including protein purification procedure, antigen concentration or capability of penetrating the skin (9). Hence, on the basis of our findings and of the convincing literature data showing that patch tests with chemical substances yield good reproducibility rates (discordance less than 10%) (24-27) we conclude that APT results strongly depend on the tested allergens, with food allergens being at the bottom of reproducibility

Table II. Atopy patch test reproducibility (comparison of the two sides of the back tested).

Atopy patch tests with fresh food allergens

(n = 184)

Atopy patch tests with standardised food allergens

(n = 93) Left +/ Right +

Left -/ Right-

Left +/Right- Left-/Right+

Cohen�skappa

Left +/ Right +

Left -/ Right-


Cohen�skappa

Cow�smilk

17(9.2%)

160(87%)

7(3.8%)

0.808 4 (4.3%)

86(92.5%)

3(3.2%)

0.710

Hen�s egg 9(4.9%)

167(90.8%)

8(4.3%)

0.670 2 (2.2%)

89(95.7%)

2(2.2%)

0.656

Tomato 3(1.6%)

172(93.5%)

9(4.9%)

0.375 1 (1.9%)

51(96.2%)

1(1.9%)

0.658

Wheatflour

6(3.3%)

167(90.8%)

11(6%)

0.490 3 (3.2%)

87(93.5%)

3(3.3%)

0.650

Atopy patch tests with inhalant allergens

(n = 131) Left +/ Right +

Left -/ Right-


Cohen�skappa

Dermatophagoides pteronyssinus 39(29.8%)

92(70.2%)

0 1.000

Mixed grasses (Avena sativa, Hordeum vulgare, Secale cereale, Triticum sativum)

5(3.8%)

126(96.2%)

0 1.000

Table II. Atopy patch test reproducibility (comparison of the two sides of the back tested).

R. RONCHETTI ET AL.


scale. No doubt, also for inhalant allergens a certain variability of results has been reported in literature: using inhalant allergens, Weissenbacher et al (23) found a concordance of only 69% by comparing the two arms of the same individual at the same time. In their study, Heinemann et al (21), taking into consideration inhalant allergens obtained from two different commercial sources, two sites of application and results obtained at an interval of 4-12 weeks, observed a reproducibility of only 56%. Using inhalant allergens from two different commercial sources, two sites of application (back and arms) and results in eczematous and healthy subjects re-tested after 2 to several weeks, Bygum et al (18) and Ingordo et al (19) report an APT reproducibility of less than 70% corresponding to a Cohen’s kappa of 0.60- 0.85). Although Cohen’s kappa statistic optimally takes into account all the outcomes of a repeated diagnostic test (concordant and discordant positive and negative results), it is influenced by the prevalence of positive as well as of negative results: if the prevalence of positive test lies between 1 and 11%, a “satisfactory” (19) kappa value (>0.60) corresponds to a reproducibility of positive APT reactions in only about 50% of cases and a “highly satisfactory” (19) Cohen’s kappa (>0.81) corresponds to the reproducibility of only about 66% of positive tests. The fact that certain allergens elicit dissimilar positive reactions in two different skin sites and that the variability of the results increases significantly when the test is repeated after a certain time, even for patch tests performed with chemical allergens (31-34), demonstrated that certain individual characteristics relevant for the APT result can differ in different parts of the body or can change over time.

We conjecture that local skin conditions such as permeability, perfusion, humidity or transpiration can be naturally heterogeneous or subtly modulated by environmental factors including micro-trauma, quality of clothing, environmental temperature, duration and timing of physical activity, and emotional and psychological factors. These and other appropriate factors could be sufficient to modify locally the status of the skin and significantly influence the degree of allergen contact with the skin and its penetrance. Presumably these factors would be relevant for food allergens but far less relevant for

chemical or inhalant allergens. In conclusion, our study shows that APT

performed simultaneously in two back sites in unselected children with the recommended standardised technique yield absolutely reproducible results with inhalant allergens but reproducible results in only about 33% (tomato and wheat flour) to 71% (cow’s milk) of tests with food allergens. We need further extensive studies investigating and developing the optimal testing material (optimal allergen source and form, sufficient concentration of main allergens, procedure of its preparation) for APT which could lead to better reproducibility of the results. In particular, APT should be standardised not only for the amount of antigen deposited in the Finn Chamber but also for the amount of antigen able to reach the reactive cells in the skin (9). Reaching good reproducibility of APT re-testing at the same time, the clinical validity of APT with food allergens will become more stable and evident. Our study supplies sound data suitable for opening the discussion on children regarding the clinical mean of these tests widely used in practice.

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2. Ingordo V, D’Andria GD, D’Andria CD, Tortora A. Results of atopy patch tests with house dust mites in adults with “intrinsic” and “extrinsic” atopic dermatitis. J Eur Acad Dermatol Venereol 2002; 16:450-461.

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6. Giusti F, Seidenari S. Patch testing with egg represents a useful integration to diagnosis of egg allergy in children with atopic dermatitis. Pediatr Dermatol 2005; 22:109-117.

7. Heine RG, Verstege A, Mehl A, Staden U, Rolinck-Werninghaus C, Niggemann B. Proposal for a standardized interpretation of the atopy patch test in children with atopic dermatitis and suspected food allergy. Pediatr Allergy Immunol 2006; 17:213.

8. Mehl A, Rolinck-Werninghaus C, Staden U, Verstege A, Wahn U, Beyer K, Niggemann B. The atopy patch test in the diagnostic workup of suspected food-related symptoms in children. J Allergy Clin Immunol 2006; 118:923-930.

9. Canani Berni R, Ruotolo S, Auricchio L, Caldore M, Porcaro F, Manguso F, Terrin G, Troncone R. Diagnostic accuracy of the atopy patch test in children with food allergy-related gastrointestinal symptoms. Allergy 2007; 62:738-743.

10. Kerchenlohr K, Darsow U, Burgdorf WHC, Ring J, Wollenberg A. Lessons from atopy patch testing in atopic dermatitis. Curr Allergy Asthma Rep 2004; 4:285-292.

11. Turjanmaa K, Darsow U, Niggemann B, Rancé F, Vanto T, Werfel T. EAACI/GA2LEN Position paper: Present status of atopy patch test. Allergy 2006; 61:1377-84.

12. De Bruin-Weller MS, Knol EF, Bruijnzeel-Koomen CAFM. Atopy patch testing – a diagnostic tool? Allergy 1999; 54:784-789.

13. Darsow U, Vieluf D, Ring J. Atopy patch test with different vehicles and allergen concentrations: An approach to standardization. J. Allergy Clin Immunol 1995; 95:677-682.

14. Langeveld-Wildschut EG, Bruijnzeel PLB, Mudde GC, Versluis C, Van Ieperen-Van Dijk AG, Bihari IC, Knoll EF, Thepen T, Bruijnzeel-Koomen CA, van Reijsen FC. Clinical and immunological variables in skin of patients with atopic eczema and either positive or negative atopy patch test reactions. J Allergy Clin Immunol 2000; 105:1008-14.

15. Niggemann B, Ziegert M, Reibel S. Importance of chamber size for the outcome of atopy patch testing in children with atopic dermatitis and food allergy. J Allergy Clin Immunol 2002; 110:515-521.

16. Rancé F. What is the optimal occlusion time for the

atopy patch test in the diagnosis of food allergies in children with atopic dermatitis? Pediatr Allergy Immunol 2004; 15:93-98.

17. Oldhoff JM, Bihari IC, Knol EF, Bruijnzeel-Koomen CAFM, de Bruin-Weller MS. Atopy patch test in patients with atopic eczema/dermatitis syndrome: comparison of petrolatum and aqueous solution as a vehicle. Allergy 2004; 59:451-458.

18. Bygum A, Mortz CG, Andersen KE. Atopy patch tests in young adult patients with atopic dermatitis and controls: dose-response relationship, objective reading, reproducibility and clinical interpretation. Acta Derm Venereol 2003; 83:18-26.

19. Ingordo V, Nogare RD, Colecchia B, D’Andria C. Is the atopy patch test with house dust mites specific for atopic dermatitis? Dermatol. 2004; 209:276-280.

20. Langeveld-Wildschut EG, van Marion AMW, Thepen T, Muddle GC, Bruijnzeel PLB, Bruijnzeel-Koomen CAFM. Evaluation of variables influencing the outcome of atopy patch test. J Allergy Clin Immunol 1995; 96:66-70.

21. Heinemann C, Schliemann-Willers S, Kelterer D, Metzner U, Kluge K, Wigger-Alberti W, Elsner P. The atopy patch test – reproducibility and comparison of different evaluation methods. Allergy 2002; 57:641-646.

22. Hansen TK, Høst A, Bidslev-Jensen C. An evaluation of the diagnostic value of different skin tests with egg in clinically egg-allergic children having atopic dermatitis. Pediatr Allergy Immunol 2004; 15:428-434.

23. Weissenbacher S, Bacon T, Targett D, Behrendt H, Ring J, Darsow U. Atopy patch test – Reproducibility and elicitation of itch in different application sites. Acta Derm Venereol 2005; 85:147-153.

24. Lindelöf B. A left versus right side comparative study of Finn ChamberTM patch tests in 220 consecutive patients. Contact Dermatitis 1990; 22:288-293.

25. Bousema MT, Geursen AM, van Joost TH. High reproducibility of patch tests [letter]. J Am Acad Dermatol 1991; 24:322-328.

26. Memon AA, Friedmann PS. Studies on the reproducibility of allergic contact dermatitis. Br J Dermatol 1996; 134:208-212.

27. Schiessl C, Wolber C, Strohal R. Reproducibility of patch tests: comparison of identical test allergens from different commercial sources. Contact

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tests with Dermatophagoides: a study on 85 patients with atopic dermatitis. Contact Dermatitis 2004; 50:18-24.

30. Ingordo V, D’Andria G, Cannata AT. Reproducibility of the atopy patch test with whole house dust mite bodies in atopic dermatitis. Contact Dermatitis 2000; 42:174-180.

31. Mitchell JC. The angry back syndrome: eczema

creates eczema. Contact Dermatitis 1975; 1:193-97. 32. Maibach H, Fregert S, Magnusson B, Pirilä V, Hjorth

N, Wilkinson D, Malten K, Lachapelle JM, Calnan C, Cronin E. Quantification of the excited skin syndromes (the “angry back”). Retesting one patch at a time. Contact Dermatitis 1982; 8:78-83.

33. Bruynzeel DP, van Ketel WG, von Blomberg der Flier M, Scheper RJ. Angry back or excited skin syndrome. A prospective study. J Am Acad Dermatol 1983; 8:392-97.

34. Gollhausen R, Przybilla B, Ring J. Reproducibility of patch tests. J Am Acad Dermatol 1989; 21:1196-1201.





VITAMIN K AND D ASSOCIATION STIMULATES IN VITRO OSTEOBLAST DIFFERENTIATION OF FRACTURE SITE DERIVED HUMAN

MESENCHYMAL STEM CELLS

A. GIGANTE1,2, M. TORCIANTI1, E. BOLDRINI3, S. MANZOTTI2, G. FALCONE3, F. GRECO1,2

and M. MATTIOLI-BELMONTE2

1Clinica Ortopedica, Università Politecnica delle Marche, Ancona; 2Dipartimento di Patologia Molecolare e Terapie Innovative, Facoltà di Medicina e Chirurgia, Università Politecnica delle

Marche, Ancona; 3OPOCRIN S.p.A., Corlo di Formigine, Italy


There is growing interest in osteoinductive agents for fracture healing especially in patients with non-union or delayed-union fractures. The aim of the present study is the assessment of the association of Vitamins D3 and K1 on proliferation and differentiation of human mesenchymal stem cells (hMSCs) derived from fracture sites in view of a possible clinical use. The synergic effect of Vitamin D3 and Vitamin K2 in preventing osteoporosis has been documented in clinical practice, however no reports investigating this association for fracture healing are present. Our data show a different outcome on cell proliferation linked to the different timing of drug administration as well as a synergic effect of the two vitamins on cell differentiation. The high level of osteocalcin and carboxylated osteocalcin detected in hMSCs treated with the association of the two vitamins in comparison with controls and with single vitamin administration underline the differentiation of these cells into osteoblastic phenotype. Our results indicate for the first time that vitamin D3 and K1 association is able to modulate in vitro the differentiation towards osteoblastic phenotype of hMSCs derived from fracture sites, thus offering clinicians a promising and low-cost strategy for reparative osteogenesis.

Mailing address: Dr. Antonio Gigante, Dipartimento di Patologia Molecolare e Terapie Innovative,Università Politecnica delle Marche, Via Tronto 10/A 60020 Ancona, ItaliaTel./Fax: ++39 0715963628e-mail: [email protected]

Key words: vitamin K, vitamin D, human mesenchymal stem cells (hmscs), osteoblasts, Gla-proteins

There is growing interest in osteoinductive agents for bone tissue regeneration improvement, especially for patients with pseudo-arthrosis or in unstable fractures. Among the mechanical and humoral factors involved in bone metabolism and in osteogenesis, growth factors, inflammatory cells as well as multilineage mesenchymal progenitor cells have been shown to play an important role in bone healing (1-2). Moreover, adequate dietary intake of vitamin D (3) and, as recently shown, of vitamin K (4) is essential to building and maintaining healthy

bone. A considerable body of data indicates that 1α,25-

dihydroxyvitamin D3 (1,25D), the biologically active metabolite of vitamin D, is essential for the maintenance of a healthy skeleton. Vitamin D3 has a biphasic effect on osteoblasts: it abrogates or stimulates the normal developmental pathway or gene expression profiles, depending upon whether it is given, respectively, during the proliferation or differentiation stage (5).

Vitamin K is a group name for several

Vol. 22, no. 1, 35-44 (2008)

36

molecular forms that have a common 2-methyl-1,4 naphthoquinone ring, but which differ in the structures of the aliphatic side chains attached at the 3-position. Vitamin K in mammals serves as a cofactor for the endoplasmic enzyme gamma-glutamyl carboxylase, promoting the post-translational conversion of selective protein-bound glutamate residues into gamma-carboxy glutamate (Gla) (6-7).

Two Gla-proteins are associated with bone formation: osteocalcin and matrix Gla-protein (MGP) (8). Osteocalcin appears to be a regulator of bone formation (8), whereas MGP is a strong inhibitor of tissue calcification (9). Whereas osteocalcin is exclusively synthesized in osteoblasts, MGP mRNA has been found in various cells, including chondrocytes (10), vascular smooth muscle cells (11) and epithelium. Elevated levels of under-carboxylated osteocalcin, marker for the vitamin K status of bone, have been reported as a risk factor for low bone mass, postmenopausal osteoporosis, and hip fracture (12-13). Moreover, markedly depressed circulating levels of vitamin K1 were found in patients with fractures, and the time taken for this level to return to normal appeared to be influenced by the severity of the fracture (14).

Some experimental studies have suggested that vitamin K administration might promote mesenchymal stem cells (MSCs) differentiating into osteoblast progenitors and inhibiting osteoclast formation (15). Furthermore, several recent data have reported a synergy between Vitamin K and Vitamin D3 in increasing vertebral bone mass in postmenopausal women (16-18).

The aim of the present work is the in vitro assessment of the association of Vitamins D3 and K1 on hMSCs derived from haematoma occurring at the fracture sites (19).


Human Mesenchymal Stem Cell (hMSCs) Isolation Following exposure of the fracture site, haematoma

containing organised fibrin clots was removed manually and placed in sterile polypropylene containers. Specimens were then washed with phosphate buffered saline (PBS) to remove blood, and divided with a scalpel into small pieces with the addition of MesenCult™ Basal Medium supplemented with Mesenchymal Stem Cell Stimulatory

Supplements (StemCell Technologies, Inc. Vancouver, BC, and Canada) and 1% penicillin-streptomycin (Gibco Invitrogen, Scotland, UK) on a 100 mm diameter culture dish (Falcon® Becton Dickinson Labware, NJ, USA). The cultures were incubated at 37°C with 5% humidified CO2. Five to seven days after initial incubation the culture medium was changed. After one week of culture, the flask was washed with PBS to remove non-viable cells and debris. Cells were then plated in 25 cm2 culture flasks (Falcon® Becton Dickinson Labware, NJ, USA) in MesenCult™ Basal Medium supplemented with Mesenchymal Stem Cell Stimulatory Supplements and 1% penicillin-streptomycin. Near-confluence cultures were then further processed by trypsinisation (Trypsin-EDTA 1X -Gibco Invitrogen, Scotland, UK) and expansion (split ratio 1:3) through sequential passages and used at the 4th passages.

hMSCs immuno-phenotyping In agreement with the International Society for

Cellular Therapy (20), cells were characterized by FACSCalibur flow cytometry system (Becton Dickinson, CA, USA), using the following monoclonal antibodies: anti HLA-DR-PE, anti-class III CD34-PE, anti-CD105-FITC, anti-CD14-FITC, anti-CD19-FITC and anti-CD45-PE (Diaclone, Besancon, France), anti-CD73-PE (Becton Dickinson, CA, USA) and anti-CD90-FITC (StemCell Technologies, Inc. Vancouver, BC, and Canada). hMSCs characterisation is shown in Fig. 1. Differentiation towards osteoblast, adipocyte and chondroblast was also performed (data not shown).

Vitamin administration Cells were seeded (in triplicate) in 12-and 6–well

polystyrene tissue culture plates (Falcon, Becton Dickinson, CA, USA) at a density of 2000 cells/well. The cells were grown in controlled atmosphere (5% CO2; T = 37°C) in Dulbecco Modified Essential Medium (DMEM) supplemented with 10% Foetal Bovine Serum (FBS), 1% Penicillin/streptomycin (all from Gibco Invitrogen, Scotland, UK) and with 5 mM β-glicero-phosphate (Sigma Aldrich, MO, USA) and 50 µg/mL ascorbic acid (Carlo Erba Reagenti, Milano, Italy).

The Vitamin D3 concentration (10 nM) was chosen on the basis of previous studies (15, 21). Firstly, the assessment of the better vitamin K1 (Konakion, Roche) concentration to be used in association with 10 nM vitamin D3 (1α,25-Dihydroxyvitamin D3, Sigma Aldrich, MO, USA) was performed. In this first set of experiments, 24 hours after cell seeding culture medium was substituted with a treatment medium containing Vitamin K1 (1 µM, 3 µM or 10 µM). Cells were then cultured for 10 and 20 days changing the medium twice a week. Otherwise cells

A. GIGANTE ET AL.


were cultured for 10 and 20 days by adding the treatment medium containing Vitamin K1 (1 µM, 3 µM or 10 µM) once a week. Controls were cell monolayers cultured in DMEM for 10 and 20 days.

In a second set of experiments the association of Vitamins D3 and was K1 tested. Also for this experimentation a different timing for drug administration was experienced. Part of the cultures received treatment medium containing drugs only 24 hours after cell seeding;

the cells were then cultured for 10 and 20 days. In the remnant cultures, the cells were cultivated for 10 and 20 days, adding the treatment medium containing vitamins once a week.

Controls were cell monolayers cultured in DMEM for 10 and 20 days and cells treated with single or repeated doses of Vitamin D3 (10 nM) for 10 and 20 days. Comparison with the administration of vitamin K alone was also performed.

Fig. 1. Flow cytometric characterisation of hMSCs derived from fracture site showing a negative reaction for CD34, CD45, HLA-DR, CD14 and CD19 and cell positivity for CD90, CD73 and CD105.Fig. 1.

Fig. 2. Fig. 2. Histogram displaying cell viability (MTT test) in the presence of the three different Vitamin K1 concentrations (1 µM, 3 µM or 10 µM) at 20 days. Values are expressed as percentage over the control culture. Mean values of three different experiments are reported.

38

MTT (3-dimethylthiazol-2,5-diphenyltetrazolium bromide) After incubation (10 and 20 days), the medium from

cultures was removed; 200 µl of MTT (SIGMA M56655) solution (5 mg/ml in DMEM without phenol red) and 1.8ml of DMEM without Phenol red were added to the cell monolayers; the multi-well plates were incubated at 37°C for a further 4 h. After discarding the supernatants, the dark blue formazan crystals were dissolved by adding 2 ml of solvent (0.1N HCl in absolute isopropanol), and quantified spectrophotometrically (UV/Vis Lambda 3 Perkin Elmer, MA, USA) at 570 nm. The results are reported as a percentage of control cultures. The experiment was performed in triplicate

Analysis of cell differentiationCell differentiation was assessed after 10 and 20 days

of cultures by FACSCalibur flow cytometry system (Becton Dickinson, CA, USA). Cells were trypsinised, washed in Dulbecco’s Buffered Saline (D-PBS), fixed for 15 min in 4% para-formaldehyde and permeabilised for 15 min with D-PBS containing 0.1% Triton X (Fluka), 1% Bovine

Serum albumine (BSA) and 2% Normal Goat serum (NGS) (Sigma Aldrich, MO, USA). The following primary antibodies were used: 5 µg/ml anti-osteocalcin (clone OC1, Biodesign International, ME, USA), 1:500 anti-carboxylated osteocalcin (clone OC4-30, TaKaRa Bio Inc., Japan), 8 µg/ml anti-osteonectina (clone N50, Biodesign International, ME, USA ) and 5 µg/ml anti-collagen I (clone I-8H5, Immunological Sciences, Roma, Italy). After 1 h incubation at RT cells were washed in D-PBS and then dark incubated for 45 min at 4°C with a Goat Anti-Mouse IgG (Fab Specific)-FITC 1:100 (Sigma Aldrich, MO, USA). Negative control was represented by cells incubated only with the Goat Anti-Mouse IgG –FITC. After incubation cells were washed, re-suspended in FACS-Flow (Becton Dickinson, CA, USA) and analysed with FACSCalibur (Becton Dickinson, CA, USA).

Carboxylated osteocalcin assessment The amount of Carboxylated osteocalcin after 20 days

of culture was assessed in culture media with Gla-type Osteocalcin EIA kit (TaKaRa Bio Inc., Japan) according

A. GIGANTE ET AL.

Table I. Carboxylated ostecalcin concentration in culture media of cells treated with Vitamin K1.

Table I. Carboxylated ostecalcin concentration in culture media of cells treated with Vitamin K1.

Single dose Repeated doses

ng/ml ng/ml

Controls 21.67 ± 0.59 /

1�m K1 23.63 ± 0.30 20.62 ±0.13

3�m K 25.37 ± 0.51 20.64 ±0.30

10�m K1 23.68 ± 0.27 21.96 ±0.59 Table II. Carboxylated ostecalcin concentration in culture media of cells treated with Vitamin K1 and D3 association.

Single dose Repeated doses

ng/ml ng/ml

Controls 21.66 ± 0.20 /

1µM K1+ 10nM D3 25.61 ± 0.50 23.24 ± 0.27

3µM K1+ 10nM D3 23.47 ± 0.34 21.84 ±0.12

10nM D3 20.70 ± 2.72 23.71±1.75

Table II. Carboxylated ostecalcin concentration in culture media of cells treated with Vitamin K1 and D3 association.


Fig. 3. Fig. 3. Flow cytometric detection of carboxylated osteocalcin in cell treated with single (a) and repeated (b) doses of vitamin K1 (1 µM, 3 µM or 10 µM).

0%

20%

40%

60%

80%

100%

120%

D 10nM D+K1um D+K3 um

MTT viability test

Single Dose Repeated doses

Fig. 4. Fig. 4. Histogram displaying cell viability (MTT test) in the presence of Vitamin D3 alone and of the two different associations of Vitamin D3 and Vitamin K1 tested (1 µM K1+ 10 nM D3 and 3 µM K1+ 10 nM D3) at 20 days. Values are expressed as percentage over the control culture. Mean values of three different experiments are reported.

40

to the manufacturer’s instructions. Detection was performed at 450 nm with Victor2™ fluorimeter (Perkin Elmer, MA, USA).

Statistical analysis The mean and the standard deviation were obtained

from the sums of three different experiments. The data were analyzed by one-way ANOVA, Bonferroni’s test and Student’s t test. Statistical significance was tested at p<0.05

RESULTS

Assessment of vitamin K1 concentrationMTT test performed in cells treated with the

different Vitamin K1 concentration showed a

decrease, albeit not significant, in cell viability in the presence of the higher concentration (10 µM) either with a single vitamin administration (73 ± 4%) or with repeated drug administration (71 ± 5%). The other vitamin K1 concentration displayed a good cell viability with no significant differences between the two types of drug administration (Fig. 2).

Flow cytometric analysis showed a slight increase in cell carboxylated osteocalcin (Fig. 3).

ELISA detection of carboxylated ostecalcin in the culture media after 20 days of culture (Table I) displayed a significant (p<0.05) increase of values for all vitamin K single dose administration in comparison with control culture. On the contrary, no

Fig. 5. Fig. 5. Flow cytometric detection of osteocalcin in cells treated with single (a) and repeated (b) doses of vitamin D3 (10 nM) and vitamin association (1 µM K1+ 10 nM D3 and 3 µM K1+ 10 nM D3).

A. GIGANTE ET AL.


changes were detected with repeated doses of drug administration.

Evaluation of vitamin associationSince 1 µM and 3 µM vitamin K1 concentrations

displayed the better cell viability, both were used in association with 10 nM vitamin D3 for testing cell performances in the presence of vitamin association.

At 10 days no significant differences in MTT values were observed between treated cells and controls and no significant variations were present between the two types of drug administration performed.

At 20 days an evident increase in cell viability, albeit not significant, was observed in cells cultured in the presence of a single dose of vitamin association

(1 µM K1+ 10 nM D3) in comparison with cells treated with repeated drug administrations. The same behaviour was observed in cells treated with vitamin D3 alone (Fig. 4).

As far as cell differentiation markers are concerned, an increased in ostecalcin and carboxylated-osteocalcin expression was observed after 20 days of culture either with a single vitamin dose or after repeated drug administrations for both tested associations (Figs. 5 and 6). Collagen I and osteonectin expressions displayed a reduction if drug administration was repeated (data not shown).

Data concerning ELISA detection of carboxylated osteocalcin in the culture media after 20 days of culture are summarised in Table II. A significant (p< 0.05) increase in carboxylated osteocalcin in

Fig. 6.

Fig. 6. Flow cytometric detection of carboxylated osteocalcin in cells treated with single (a) and repeated (b) doses of vitamin D3 (10 nM) and vitamin association (1 µM K1+ 10 nM D3 and 3 µM K1+ 10 nM D3).

42

comparison with controls and cells receiving only Vitamin D was detected for the association 1 µM K1+ 10 nM D3, with no significant differences between the two types of drug administration. On the contrary, the association 3 µM K1+ 10 nM D3 showed significant (p<0.05) higher values of carboxylated osteocalcin only with single dose drug administration.

Conflicting results with only vitamin K1 administration in comparison with its association were present.

DISCUSSION

Functional bone tissue with a normal structure can be obtained in vitro mimicking the conditions of normal in vivo tissue development, offering clinicians a promising alternative strategy for the treatment of osseous defects, fractures and anomalies (22).

The potential of mesenchymal cells to differentiate to osteoblasts and contribute to bone formation, which prompted the idea of their use in bone engineering, has been largely demonstrated (23-24). Several papers have also reported that fracture haematoma occurring at a fracture site, which is known to play an important role in bone healing (2), contains mesenchymal cells (19). Though MSCs are abundant in the skeletal tissues, damaged bone may fail to heal spontaneously. Therefore, an efficient MSCs transplantation system including an inductive microenvironment may be an ideal tool to support the natural propensity to regenerate bone tissue.

The aim of the present study is the in vitro assessment of the association of Vitamins D3 and K1, either in single dose or with repeated administrations, on proliferation and differentiation of hMSCs derived from facture sites in view of a possible clinical use in fracture healing. In clinical practice the synergic effect of Vitamin D3 and Vitamin K2 in preventing osteoporosis and in increasing vertebral bone mass in postmenopausal women has already been suggested (16-18). However, the literature shows no report investigating this association for fracture healing.

Vitamin D has a well-known stimulatory effect on osteoblast alkaline phosphatase activity (25), and the active metabolite of Vitamin D [1,25-(OH)2D3] stimulates bone formation through the up-regulation

of osteoblast differentiation and extracellular matrix mineralization (3, 5, 26). hMSCs can be differentiated in vitro into osteoblasts by vitamin D and ascorbic acid administration (27), and vitamin K stimulates in vitro osteoblastogenesis, also by regulating osteoclastogenesis, in bone marrow cells (15).

Our data show a different effect on cell proliferation related to the different timing of drug administration (single dose vs repeated doses). As far as differentiation is concerned, flow cytometric analysis highlighted a synergic effect of the two vitamins which was more marked with repeated doses in comparison with single dose drug administration. The anti-proliferative and pro-differentiative well-documented in vitro effect of Vitamin D3 on osteoblasts (5) may be less evident on hMSCs as they are a more heterogeneous population. The association of the vitamins may therefore stimulate proliferating cells toward differentiation.

The high level of carboxylated osteocalcin detected in the media of hMSCs treated either with vitamin K1 alone or with the association of the two vitamins in comparison with controls further underline the differentiation of these cells into osteoblastic phenotype.

Osteocalcin (OC) is a vitamin K-dependent Ca2+-binding protein that carries three carboxylated glutamic acid residues (Gla) which are known to mediate strong binding of OC to hydroxyapatite. OC constitutes about 15% of the non-collagenous bone matrix proteins and is produced exclusively in osteoblasts and its dental counterpart, the odontoblast (28). Because of this tissue specific expression, the level of OC could be considered as an indicator of the overall activity of cells operating in bone formation. Therefore, when there is increased bone formation, the OC concentration will also be increased (28).

Our data are in agreement with Koshihara et al (15) and confirm the ability of vitamin K to enhance the accumulation of γ-carboxyglutamic acid-containing osteocalcin as well as osteocalcin synthesis in Vitamin D3-osteoblast-induced hMSCs (26).

For the first time the ability of vitamin K1 alone or in association with vitamin D3 has been demonstrated as modulating in vitro differentiation towards osteoblastic phenotype of hMSCs derived from fracture sites. The origin of these latter cells may be haematoma (19) or they can derive from

A. GIGANTE ET AL.


circulating mesenchymal stem cells that enter the fracture site from the circulation via the damaged vasculature (29). Fracture healing, in fact, can be divided into five distinct stages: an initial stage in which a haematoma is formed at the fracture site associated with an inflammatory response, a subsequent stage in which angiogenesis develops and cartilage begins to form, three successive stages of cartilage calcification, cartilage removal and bone formation and, ultimately, a more extended stage of bone remodelling. The intramembranous bone is formed by committed osteoprogenitor cells that reside in the periosteum (1-2, 19) The presence of growth factors within the haematoma is a prerequisite for the regulation of the processes that occur during fracture healing (2, 19).

Based on our results, one possible improvement for fracture healing may be achieved by the use of Vitamin K1 alone or in association with Vitamin D3. These molecules may act on hMSCs at different stages of healing, favouring their differentiation into osteoblasts, as well as on the periosteal osteoprogenitor cells and on circulating osteoblastic cells. Given the potential overlap between osteoblastic and endothelial cells (30), it is also possible that precursor cells in the vasculature (i.e. within the capillary wall penetrating the fracture) give rise to osteoblastic progenitors (30). Moreover, the use of vitamin K could also affect remodelling processes acting on RANK/ODF expression (15).

In conclusion, the in vitro ability of vitamin K1 alone or in association with vitamin D3 in modulating differentiation towards osteoblastic phenotype of fracture-derived hMSCs has been demonstrated, thus offering clinicians a promising and low-cost strategy for reparative osteogenesis. Further in vitro studies and in vivo experiments are needed to better examine the capability of K vitamins (K1 and K2) in affecting fracture healing and bone remodelling as well as the interrelated mechanism of Vitamin K and D association.

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Joint Surg Br 1990; 72-B: 822–9.3. Weaver CM, Fleet JC. Vitamin D requirements: current

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Oliveira Latorre M, Wood RJ. Dietary phylloquinone depletion and repletion in postmenopausal women: effects on bone and mineral metabolism Osteoporos Int 2006; 17:929-35.

5. Gurlek A, Pittelkow MR, Kumar R. Modulation of growth factor/cytokine synthesis and signaling by 1alpha,25-dihydroxyvitamin D(3): implications in cell growth and differentiation. Endocr Rev 2002; 23(6):763-86.

6. Suttie JW. Synthesis of vitamin K-dependent proteins. FASEB J 1993; 7:445–52.

7. Bouchard BA, Furie BC. Vitamin K-dependent biosynthesis of γ-carboxyglutamic acid. Blood 1999; 93:1798–808.

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10. Yagami K, Suh J-Y, Enomoto-Iwamoto M, Koyama E, Abrams WR, Shapiro IM, Pacifici M, Iwamoto M. Matrix GLA-protein is a developmental regulator of chondrocyte mineralization and, when constitutively expressed, blocks endochondral and intramembranous ossification in the limb. J Cell Biol 1999; 147:1097–108.

11. Shanahan CM, Weissberg PL. Smooth muscle cell heterogeneity: patterns of gene expression in vascular smooth muscle cells in vitro and in vivo. Arterioscler Thromb Vasc Biol 1998; 18:333–8.

12. Szulc P, Chapuy M-C, Meunier PJ, Delmas PD Serum undercarboxylated osteocalcin is a marker of the risk of hip fracture: a three year follow-up study. Bone 1996; 18:487–88.

13. Luukinen H, Käkönen S-M, Pettersson K et al. Strong prediction of fractures among older adults by the ratio of carboxylated to total serum osteocalcin. J Bone Miner Res 2000; 15:2473-8.

14. Bitensky L, Hart JP, Catterall A, Hodges SJ, Pilkington MJ, Chayen J. Circulating vitamin K levels in patients with fractures. J Biol Chem 1988;

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H, Yamamoto S. Vitamin K stimulates osteoblastogenesis and inhibits osteoclastogenesis in human bone marrow cell culture. J Endocrinol. 2003; 176: 339-48.

16. Schaafsma A, Muskiet FA, Storm H, Hofstede GJ, Pakan I, Van der Veer E. Vitamin D(3) and vitamin K(1) supplementation of Dutch postmenopausal women with normal and low bone mineral densities: effects on serum 25-hydroxyvitamin D and carboxylated osteocalcin. Eur J Clin Nutr 2000; 54:626-31.

17. Takahisa U, Atushi I, Minoru U. Effect of continuous combined therapy with vitamin K2 and vitamin D3 on bone mineral density and coagulofibrinolysis function in postmenopausal women. Maturitas 2002; 41:211–21.

18. Bolton-Smith C, McMurdo ME, Paterson CR et al. Two-year randomized controlled trial of vitamin K1 (phylloquinone) and vitamin D3 plus calcium on the bone health of older women. J Bone Miner Res 2007; 22:509-19.

19. Oe K, Miwa M, Sakai Y, Lee SY, Kuroda R, Kurosaka M. An in vitro study demonstrating that haematomas found at the site of human fractures contain progenitor cells with multilineage capacity. J Bone Joint Surg Br 2007; 89:133-8.

20. Dominici M, Le Blank K, Muller I et al. Minimal Criteria for deifying multipotent mesenchymal stem cells. The International Society for Cellular Therapy position statement. Cytotherapy 2006; 8:315-17.

21. Koshihara Y, Hoshi K, Ishibashi H, Shiraki M. Vitamin K2 promotes 1alpha,25(OH)2 vitamin

D3-induced mineralization in human periosteal osteoblasts. Calcif Tissue Int. 1996; 59:466-73.

22. Mistry AS, Mikos AG. Tissue engineering strategies for bone regeneration. Adv Biochem Eng Biotechnol 2005; 94:1–22.

23. Dominici M, Hofmann TJ, Horwitz EM. Bone marrow mesenchymal cells: biological properties and clinical applications. J Biol Regul Homeost Agents 2001; 15:28-37.

24. Vats A, Tolley NS, Buttery LDK, Polak JM. The stem cell in orthopaedic surgery. J Bone Joint Surg 2004; 86:159–64.

25. Gonnerman, KN, Brown LS, Chu TM. Effects of growth factors on cell migration and alkaline phosphatase release. Biomed Sci Instrum 2006; 42:60–66.

26. Van Leeuwen JP, Van Driel M, Van den Bemd GJ, Pols HA. Vitamin D control of osteoblast function and bone extracellular matrix mineralization. Crit Rev Eukaryot Gene Expr 2001; 11:199–226.

27. De Kok IJ, Hicok KC, Padilla RJ, Young RG, Cooper LF. Effect of vitamin D pretreatment of human mesenchymal stem cells on ectopic bone formation. J Oral Implantol. 2006; 32:103-9.

28. Deftos LJ, Parthemore JG, Price PA. Changes in plasma bone GLA protein during treatment of bone disease. Calcif Tissue Int 1982; 34:121-4.

29. Eghbali-Fatourechi GZ, Lamsam J, Fraser D et al. Circulating osteoblast-lineage cells in humans. N Engl J Med 2005; 352:1959-66.

30. Eghbali-Fatourechi GZ, Mödder UIL, Charatcharoenwitthaya N et al. Characterization of circulating osteoblast lineage cells in humans. Bone 2007; 40:1370–1377.

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A FOREST BATHING TRIP INCREASES HUMAN NATURAL KILLER ACTIVITY AND EXPRESSION OF ANTI-CANCER PROTEINS IN FEMALE SUBJECTS

Q. LI, K. MORIMOTO1, M. KOBAYASHI, H. INAGAKI, M. KATSUMATA,Y. HIRATA, K. HIRATA, T. SHIMIZU, Y.J. LI, Y. WAKAYAMA, T. KAWADA,

T. OHIRA2, N. TAKAYAMA2, T. KAGAWA2 and Y. MIYAZAKI3

Department of Hygiene and Public Health, Nippon Medical School, Tokyo; 1Department of Social and Environmental Medicine, Osaka University Graduate School of Medicine, Osaka; 2Forestry

and Forest Products Research Institute, Tsukuba; 3Chiba University, Chiba, Japan

Received December 27, 2007 – Accepted January 13, 2008

We previously reported that forest bathing trips enhanced human NK activity, number of NK cells, and intracellular anti-cancer proteins in lymphocytes, and that the increased NK activity lasted for more than 7 days after the trip in male subjects. In the present study, we investigated the effect of forest bathing trip on human NK activity in female subjects. Thirteen healthy nurses, age 25-43 years, professional career 4-18 years, were selected with informed consent. The subjects experienced a three-day/two-night trip to forest fields. On day 1, the subjects walked for two hours in the afternoon in a forest field; on day 2, they walked for two hours each in the morning and afternoon in two different forest fields; and on day 3, the subjects finished the trip and returned to Tokyo after drawing blood and completing a questionnaire. Blood and urine were sampled on the second and third days during the trip, and on days 7 and 30 after the trip. NK activity, numbers of NK and T cells, and granulysin, perforin, and granzymes A/B-expressing lymphocytes in the blood samples, the concentrations of estradiol and progesterone in serum, and the concentrations of adrenaline and noradrenaline in urine were measured. Similar control measurements were made before the trip on a normal working day. The concentrations of phytoncides in the forests were measured. The forest bathing trip significantly increased NK activity and the numbers of NK, perforin, granulysin, and granzymes A/B-expressing cells and significantly decreased the percentage of T cells, and the concentrations of adrenaline and noradrenaline in urine. The increased NK activity lasted for more than 7 days after the trip. Phytoncides, such as alpha-pinene and beta-pinene were detected in forest air. These findings indicate that a forest bathing trip also increased NK activity, number of NK cells, and levels of intracellular anti-cancer proteins in female subjects, and that this effect lasted at least 7 days after the trip. Phytoncides released from trees and decreased stress hormone levels may partially contribute to the increased NK activity.

Mailing address: Qing Li, MD, Ph.DDepartment of Hygiene and Public Health, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, Tokyo 113-8602, JapanTel: ++81-3-3822-2131 Fax: ++81-3-5685-3065e-mail: [email protected]

Key words: anti-cancer proteins, female subjects, forest bathing, granulysin, granzyme, NK activity, perforin

A forest bathing trip, which is similar to natural aromatherapy, involves a visit to a forest field for the purpose of relaxation and recreation by breathing in

volatile substances, called phytoncides, consisting of antimicrobial volatile organic compounds derived from trees, such as alpha-pinene and limonene

Vol. 22, no. 1, 45-55 (2008)

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(1-3). Forest bathing trips are possible in similar environments throughout the world. We found previously that forest bathing trips increased human natural killer (NK) activity, NK cell numbers, and intracellular levels of perforin, granulysin (GRN), and granzymes A/B (GrA/B) in peripheral blood lymphocytes in male subjects (2-3) and that tree-derived phytoncides, such as alpha-pinene and limonene, enhance NK activity and intracellular levels of perforin, GRN, and granzyme A in NK cells in vitro (1). Komori et al (4) also reported that citrus fragrance found in forest affects the human endocrine and immune systems in depressed male inpatients as analyzed by the measurement of urinary cortisol and dopamine levels, NK activity, and CD4/8 ratios. Nevertheless, the question remained to be resolved whether forest bathing trips also increase NK activity in female subjects. In the present study, we addressed this question.


Subjects Thirteen healthy and non-pregnant female nurses,

aged 25-43 years (mean 28.8±4.6), professional career 4-18 years (mean 6.7±3.8), were selected from Nippon Medical School hospital in Tokyo, Japan for the present study. Information gathered from a self-administered questionnaire, including age and lifestyle habits that asked about cigarette smoking, alcohol consumption, eating breakfast, sleeping hours, working hours, physical exercise, nutritional balance, and mental stress, have been reported previously (2-3, 5). Since the menstrual cycle influences NK activity (6), information on the menstrual cycle from all subjects was also gathered. Written informed consent was obtained from all subjects after a full explanation of the study procedures. None of the subjects had any signs or symptoms of infectious disease, used drugs that might affect immunological analysis, or were taking any medications at the time of the study. The Ethics Committee of the Nippon Medical School approved this study (approval No. 16-1).

Forest bathing tripThe subjects experienced a three-day/two-night

trip to three different forest fields at Shinano town in Nagano prefecture located in northwestern Japan in early September, 2007. On the first day, the subjects walked for two hours in the afternoon in a forest field, and then stayed at a nearby hotel within the forest. On the second day, the subjects walked for 2 hours each in the morning

and afternoon in two different forest fields, and then stayed at the same hotel. On day 3, the subjects finished the trip and returned to Tokyo after drawing blood and completing a questionnaire. Each walking course was 2.5 km, which closely resembled the normal physical activity for the subjects on an average working day. Daily physical activity of the subjects was monitored with a pedometer (2-3), and the level of background walking steps of the subjects on normal working days were monitored for a week, and the averaged walking distance of all the subjects was about 5.0 km/day. Then, we set the walking distances in the trip based on the result. The duration of sleep was measured with a piezo-electric accelerometer, Actiwatch (R) (Mini Mitter Co. Inc., Sunriver), worn on the wrist of the non-dominant arm (2-3, 7). Blood was sampled on the second and third days during the trip, and on days 7 and 30 after the trip, and three days prior to the trips as a control. Since it has been reported that human NK cell activity shows circadian rhythms (8-9), all samples were obtained at 8:00 am. All blood samples were placed in an ice/water box at 4°C and assays were performed within four hours from the blood being drawn. White blood cell (WBC) counts, NK activity, proportions of NK and T cells, and GRN, perforin, and granzymes A/B-expressing cells in peripheral blood lymphocytes (PBLs) were measured. Adrenaline and noradrenaline concentrations in urine were also determined. Since estradiol and progesterone affect human NK activity (10-13), estradiol and progesterone concentrations in serum were also determined.

NK activityPBLs were separated from peripheral blood with a BD

Vacutainer CPT (Becton Dickinson, Franklin Lakes, NJ, USA), and then adjusted to 4x106 cells/ml for the assay of NK activity. NK activity was assayed according to a standard method (2-3, 14). Briefly, K-562 target cells were labeled with a sodium 51Cr-chromate solution (Perkin Elmer, Boston, MA, USA) for 60 min at 37°C in 5% CO2 and washed 4 times in RPMI-1640 containing 10% fetal bovine serum (FBS) (JRH Biosciences, Lenexa, KS, USA). The target cells were plated into round-bottomed 96-well microplates, then the effector cells (PBLs) at 4x106, 2x106, and 1x106 cells/ml in 100 µl were added to the wells in triplicate at E:T ratios of 40:1, 20:1, and 10:1. Following a 4-h incubation at 37°C in 5% CO2, the microplates were centrifuged and 100 µl of supernatant from each well was collected and measured in a gamma counter. Then, the NK activity was calculated as described previously (2-3, 14). For laboratory controls of the NK activity assay, we used the same K-562 cells as the target in all experiments and always kept the K-562 cells in the same conditions before the experiments, e.g.

Q. LI ET AL.


we always used the K-562 cells 96-hr after thawing out the cells (3).

Cell staining and flow cytometric analysis The surface markers of PBLs were stained with

fluorescein isothiocynate (FITC)/phycoerythrin (PE) -CD16 and PerCP-Cy5.5-CD3 monoclonal antibodies (BD PharMingen, San Diego, CA, USA) for NK and T cells, and FITC/PE/PerCP-Cy5.5-mouse IgG1 as negative controls, for 30 min in the dark. Then, the cells were fixed/permeablized with Cytofix/cytoperm solution (BD PharMingen) for 20 min at 4°C, and then intracellular perforin and GrA/B were stained with FITC- anti-human perforin and FITC-GrA/B antibodies, respectively, with FITC-IgG2b for perforin and FITC-IgG1 for GrA/B as negative controls (BD PharMingen) for 30 min at 4°C according to the manufacturer’s instructions. Intracellular GRN was stained with a rabbit anti-human GRN polyclonal antibody and rabbit serum as the negative control (1-3, 5) after fixation/permeablization with Cytofix/cytoperm solution, and then stained with FITC-goat anti-rabbit IgG (Vector Laboratories Inc., Burlingame, CA, USA) for 30 minutes at 4°C in the dark. After staining, the cells were washed twice with fixative solution and once with PBS containing 1% FBS. Flow cytometric analysis was performed with a FACScan flow cytometer as described previously (2-3, 5, 15). Lymphocytes were identified by their characteristic appearance on a dot plot of FSC versus SSC and electronically gated to exclude dead cells and granulocytes. The fluorescence gates were set using negative controls. For laboratory controls in the cell staining and flow cytometric analysis, we used antibodies from the same lot and we always added the same volume of antibodies to the cells with the same volume of buffer in all experiments, e.g. we added 10 µl FITC-anti-granzyme A into the cell suspension in 30 µl PBS in all experiments (3).

Urinary adrenaline and noradrenaline measurementsThe levels of adrenaline and noradrenaline in urine

were measured by an HPLC method using an HLC-725CAII analyzer. The instrument features a column-switching system composed of two pretreatment columns, one separation column, and a high-sensitivity detection unit based on a post-column reaction using a fluorogenic reagent, 1,2-diphenylethyleneamine. The detection limits of adrenaline and noradrenaline in urine were 8 and 14 fmol/ml, respectively (3, 16).

Measurements of estradiol and progesterone in serumThe levels of estradiol and progesterone in serum

were measured by a chemiluminescent microparticle immunoassay (Architect estradiol and Architect progesterone, respectively, Abbott Japan, Tokyo, Japan). The detection limits of estradiol and progesterone in

serum were 17.9 pg/ml and 0.1 ng/ml, respectively (17).

WBC count.WBC, RBC, and platelet counts, the percentages

of granulocytes, lymphocytes, and macrophages in peripheral blood, and the concentration of Hb, Hct, MCV, MCH, and HCHC were determined by an automatic cell counter (LC-550, Horiba Co., LTD. Kyoto, Japan) as described previously (2-3).

POMS test The Profile of Mood States (POMS) test was used to

examine mood changes of each subject before and after forest bathing using the POMS test in Japanese (2).

Measurements of phytoncides and environmental temperature/ humidity in the forest fields during the investigation

The concentration of volatile organic compounds (phytoncides), temperature, and humidity in the forests were measured as reported previously (2-3).

Statistical analysisWe analyzed the data using two-way ANOVA with

no-repeated measures (one-way ANOVA with repeated measures), with the variability among individuals and the different days as two factors. Comparisons between different days were made with the paired t-test if the analysis of variance was significant. The analyses were performed with the Microsoft Excel software package for Windows. The significance level for p values was set at < 0.05.

RESULTS

Effect of a forest bathing trip on NK activityThe forest bathing trip significantly increased

human NK activity, and this increase lasted for more than 7 days (Fig. 1).

Effect of a forest bathing trip on CD16+ NK cellsThe forest bathing trip significantly increased

the percentage of CD16+ NK cells, and this increase lasted for more than 7 days after the trip (Fig. 2). The forest bathing trip did not affect lymphocyte or WBC counts.

Effect of a forest bathing trip on the percentage of cells expressing cytolytic molecules

The forest bathing trip significantly increased the percentages of GRN, perforin, and GrA/B-expressing cells in PBLs, and this increase lasted for

48

more than 7 days after the trip (Fig 3).

Effect of a forest bathing trip on T (CD3+) cells.The forest bathing trip significantly decreased the

percentage of T cells in almost all subjects after the trip compared with the control measurement. There were significant differences between before and after the trip on days 1, 2, and 7 in the percentage of T cells (Fig. 4).

Effect of a forest bathing trip on adrenaline and noradrenaline concentrations in urine

The forest bathing trip significantly decreased the concentrations of adrenaline and noradrenaline in urine (Fig. 5).

Changes of estradiol and progesterone concentrations in serum before, during, and after the trip

There was no significant change in the concentration of estradiol in serum before, during, or after the trip. The concentration of progesterone in serum 30 days after the trip was significantly higher than that before the trip. On the other hand, although the concentration of progesterone in serum on days 1 and 2 was higher than that before the trip, the difference was not significant (Fig. 6).

Effect of forest bathing trip on the score of POMS test

The forest bathing trip significantly increased the score for vigour and decreased the scores for anxiety, depression, anger, fatigue, and confusion in the POMS test (Fig. 7).

There were no significant differences in daily physical activity before and during the trip (data not shown). The hours of sleep increased during trip compared with control days (data not shown).

Lastly, phytoncides, such as alpha-pinene, beta-pinene, tricyclene, camphene, and isoprene, were detected in the forest fields during the investigation (Table I), but were not detected in the urban area of Tokyo. Weather during the forest bathing trip was excellent with average temperatures and humidity of 19.13 ± 0.23°C, 99.9 ± 0.00% on day 1 in the afternoon, 20.97 ± 0.12°C, 73.80 ± 2.74% on day 2 in the morning, and 18.97 ± 0.05°C, 90.87 ± 0.9% on day 2 in the afternoon in the forest fields during the walks. The average temperature and humidity in the

urban area of Tokyo on the control day was 28.63°C and 59%, respectively.

DISCUSSION

We found previously that a forest bathing trip, but not a city visit significantly increased human NK activity, number of NK cells, and intracellular levels of perforin, GRN, and granzymes A/B in PBLs in male subjects (2-3), and that the increased NK activity lasted for more than 7 days after the trip (3). However, it was not clear whether a forest bathing trip can also increase NK activity in female subjects. The present study found that a forest bathing trip also enhances the immune response in the female subjects as measured by human NK activity and the percentage of NK cells, indicating that forest bathing does indeed enhance human NK activity. Moreover, we also confirmed that the increased NK activity and percentage of NK cells induced by a forest bathing trip lasted for more than 7 days, even 30 days, after the trip (3). This suggests that if people visit a forest once a month, they may be able to maintain increased NK activity. This may be important in health promotion and preventive medicine (3).

NK cells kill tumor or virus-infected cells by the release of perforin, granzymes (15, 18-21), and GRN (22-23) via the granule exocytosis pathway.

In order to explore the mechanism of enhancement of NK activity by forest bathing in female subjects, we investigated the effect of forest bathing on the intracellular levels of perforin, GRN, and GrA/B in PBLs. We found that the forest bathing trip significantly increased the proportion of PBLs expressing these effector molecules, confirming our previous reports (2-3). Moreover, we found that increased perforin, GRN, and GrA/B-expressing cells induced by a forest bathing trip lasted for more than 7 days after the trip, confirming our previous report (3). These cytolytic molecules contribute to NK and anti-tumor activity (23-24).

Adrenaline is released from the adrenal medulla, and the adrenaline level increases under circumstances of novelty, anticipation, unpredictability, and general emotional arousal, whereas noradrenaline is the predominant neurotransmitter released by the sympathetic system, and some of this enters the blood; the level

Q. LI ET AL.


of noradrenaline increases during increased physical activity (25). Measurement of free adrenaline and noradrenaline in urine provides a reliable measure of the circulating concentration of adrenaline and noradrenaline in the bloodstream and thus a measure

of sympathoadrenal medulla activity (26). The concentrations of adrenaline and noradrenaline in urine have been used to evaluate work related stress in nurses (27), lorry drivers (28), long distance coach drivers (29), and psychosocial stress (30). We found

27

Table I. Concentration of volatile substances (phytoncides) in the air of forest fields calculated as alpha-pinene (ng/m3)Measuringpoints

Field 1 Day 1 pm

Field 2 Day 2 am

Field 3 Day 2 pm

Kind of Trees Cryptomeria

japonica D.DonCryptomeria

japonica D.Don

Quercus mongolica var. grosseserrata,

Fagus crenata Blume,Cercidiphyllum japonicum

isoprene 3.8 8.0 12.8tricyclene 1.6 3.0 2.1�-pinene 103.7 35.7 13.2camphene 14.1 2.7 1.3�-pinene 4.6 26.7 5.8�-3-carene 1.6 0.0 0.0p-cymene 1.6 0.0 0.0limonene 1.6 0.0 0.0

Table I. Concentration of volatile substances (phytoncides) in the air of forest fields calculated as alpha-pinene (ng/m3).

Fig. 1. Effect of the forest bathing trip on NK activity. Data are presented as the mean+SE (n=13). Two-way ANOVA with no-repeated measures indicated that the forest bathing trip and the variability between individuals significantly affected NK activity (all p<0.01). *: p<0.05, **: p<0.01, significantly different from before the trip by paired t-test. The activity values for an E/T ratio of 20/1 are shown, and similar results were also obtained with E/T ratios of 40/1 and 10/1.

Before Day 1 Day 2 Day 7 Day 300

5

10

15

20

25

30

35

NK

act

ivity

(%

)

��

��


5

10

15

20

25

30

NK

cel

ls (

%)

��

��

��

Fig. 2. Effect of the forest bathing trip on the percentage of NK cells. Data are presented as the mean+SE (n=13). Two-way ANOVA with no-repeated measures indicated that the forest bathing trip and the variability between individuals significantly affected the percentage of NK cells (all p<0.01). *: p<0.05, **: p<0.01 significantly different from before the trip by paired t-test.

50

that a forest bathing trip significantly decreased the concentrations of adrenaline and noradrenaline in urine, confirming our previous report (3), and suggesting that the subjects were under conditions of lower stress during the forest bathing trip. It has been reported that adrenaline inhibits human NK activity (31). Addition of noradrenaline to intrathecal morphine augments the postoperative suppression of natural killer cell activity (32), suggesting that noradrenaline also inhibits human NK activity. We found previously that physical and/or psychological stress decreased NK activity, NK receptor levels, and mRNA transcription of granzymes and perforin in mice (33). The increase in NK activity during a forest bathing trip may be related to an attenuated stress hormone response (adrenaline, noradrenaline) associated with the forest bathing trip, whereas increased sympathetic activity may


10

20

30

40

50

Perf

orin

exp

ress

ing

cells

(%

)


10

20

30

40

Gra

nuly

sin-

expr

essi

ng c

ells

(%

)


10

20

30

40

50

GrA

-exp

ress

ing

cells

(%

)


10

20

30

40

50

GrB

-exp

ress

ing

cells

(%

)

��

��

��

��

��

��

��

Fig. 3. Effect of the forest bathing trip on GRN, perforin, and GrA/B-expressing cells in PBLs. Data are presented as the mean+SE (n=13). Two-way ANOVA with no-repeated measures indicated that the forest bathing trip and the variability between individuals significantly affected the GRN, perforin, GrA/B-expressing cells in PBLs (all p<0.01). *: p<0.05, **: p<0.01, significantly different from before the trip by paired t-test.


10

20

30

40

50

60

70

T c

ells

(%

)

��

��

Fig. 4. Effect of the forest bathing trip on the percentage of T cells. Data are presented as the mean+SE (n=13). Two-way ANOVA with no-repeated measures indicated that the forest bathing trip and the variability between individuals significantly affected the percentage of T cells (all p<0.05). *: p<0.05, **: p<0.01 significantly different from before the trip by paired t-test.

Q. LI ET AL.


decreased T cells in the female subjects. It has been reported that mental stress increased T cell in PBLs (38-40). We also have found that people with a poor lifestyle showed a higher percentage of T cells than people with a good lifestyle (5); therefore, we speculate that the proportion of T cells in PBLs may reflect stress status.

Many factors, including circadian variation (8-9), physical exercise (5, 41), alcohol consumption (5, 42), and menstruation (6) can affect human NK

have an immunosuppressive effect through release of adrenaline (34). Previous studies have reported that a forest bathing trip reduces the concentration of cortisol in saliva, reduces prefrontal cerebral activity, reduces blood pressure, and stabilizes autonomic nervous activity in humans (35-37). The result of the POMS scores in the present study also suggests that the subjects were physiologically relaxed during the forest bathing trip.

We found that the forest bathing trip significantly

Fig. 5. Effect of the forest bathing trip on adrenaline and noradrenaline concentrations in urine. Data are presented as the mean+SE (n=13). Two-way ANOVA with no-repeated measures indicated that the forest bathing trip significantly affected the adrenaline concentration in urine (p<0.01). *: p<0.05, **: p<0.01, significantly different from before the trip by paired t-test.


2

4

6

8

10

ug/g

cre

atin

ine


20

40

60

80

ug/g

cre

atin

ine

Adrenaline in urine Noradrenaline in urine

��

��

��

��


20

40

60

80

100

120

140

pg/m

l


2

4

6

8

10

12

ng/m

l

�

Estradiol Progesterone

��

Fig. 6. Changes in estradiol and progesterone concentrations in serum before, during, and after the trip. Data are presented as the mean+SE (n=13). Two-way ANOVA with no-repeated measures indicated that there was no difference in the estradiol and progesterone concentrations in serum between the days before, during, and after the trip. *: p<0.05, significantly different from before the trip by paired t-test.

52

activity in female subjects. In order to control the effect of circadian rhythm on NK activity, we sampled blood at 8 am on all days. To control for the effect of physical exercise on NK activity, we limited the walking steps during the trip to the averaged normal workday distances as monitored by a pedometer. To control the effect of alcohol on NK activity, the subjects did not consume alcohol during the study period. The sleeping hours during the trips were a little longer than on average working days (data not shown). We found previously that slightly longer sleeping hours during the trip than those on average working days did not affect either NK activity, cell numbers, or the levels of perforin, GRN, or GrA/B-expressing cells in PBLs (2-3), and that there was no difference in the numbers of NK cells, nor the levels of perforin, GRN, or GrA/B-expressing cells in PBLs among the subjects who slept for 5, 6, or 7 hours (5). Kusaka et al. (43) also reported that sleeping hours did not affect NK activity, or NK cell numbers under physiological conditions.

It has been reported that NK activity was significantly higher in the follicular than in the luteal phase of the menstrual cycle, and that postmenopausal women showed NK activity similar to women in the follicular phase but significantly higher than women

in the luteal phase of the menstrual cycle (6). On the other hand, Yovel et al. (44) reported that the menstrual cycle had no significant effect on activity levels of NK cells. Roszkowski et al. (10) found that patients with low (<50 pg/ml) and high (>200 pg/ml) estradiol levels showed an increase and a decrease of NK cell activity, respectively. Progesterone at 100-400 nM (31.45-125.8 ng/ml) inhibits NK activity in healthy pregnant women, whereas 100 times higher concentrations are required for reducing NK activity in non-pregnant women (11). On the other hand, estradiol at 10-6 M (272.39 pg/ml) or progesterone at 10-6 M (314.47 pg/ml) did not affect NK activity with 20 h in vitro incubation (12); no significant correlation between the increase in NK activity and the decrease in estradiol concentration was found (13). The above mentioned studies suggest that the menstrual cycle and the levels of estradiol and progesterone in serum may affect human NK activity. To control for the influence of menstrual cycle on NK activity, we took a questionnaire to obtain information on the menstrual cycle of the subjects. The ratios of subjects who were in the follicular phase during the experiment were 5/13, 6/13, 6/13, 7/13, and 6/13 on the day before the trip, days 1 and 2 during the trip, and days 7 and 30 after

B

BB

B BB

Before After Before After Before After30

40

50

60

Scor

es

B Anxiety

Depression

Anger

Vigour

Fatigue

Confusion

Day 1 PM Day 2 AM Day 2 PM

***

** **** ** **

��

Fig. 7. Effect of the forest bathing trip on POMS scores. Data are presented as the means (n=13). *: p<0.05, **: p<0.01, significantly different from before the trip on Day 1pm by paired t-test (anxiety, depression, anger, fatigue, and confusion).

Q. LI ET AL.


the trip, respectively, indicating that there was no significant difference in the menstrual cycle of the subjects between the different days. This suggests that the menstrual cycle had a similar influence on NK activity on the different days. In addition, we also measured the concentrations of estradiol and progesterone in serum of the subjects to confirm the influence of estradiol and progesterone on NK activity. In the present study, there was no significant difference in the concentration of estradiol in serum between days before, during, and after the forest bathing trip, indicating that estradiol had a similar effect on NK activity between different days in the subjects in this case. Although there was no significant difference in the concentration of progesterone in serum between days 1 or 2 and before the trip, the levels of progesterone on days 1 and 2 were higher than that before, suggesting that progesterone may show an inhibitory effect on NK activity on days 1 and 2. However, although there was a possible inhibitory effect of progesterone, the NK activity on days 1 and 2 was still significantly higher than that before, indicating that the effect of the forest bathing trip on NK activity has exceeded the effect of progesterone. The level of progesterone on day 30 was significantly higher than that before the trip, suggesting that progesterone may show an inhibitory effect on NK activity on day 30. In fact, we found previously that increased human NK activity lasted for more than 30 days in male subjects (3); however, in the present study, although the NK activity on day 30 was higher than that before the trip, the difference was not significant, suggesting that this may be due to the higher level of progesterone in serum in the subjects on day 30.

As detailed in Table I, we detected several phytoncides, such as alpha-pinene, beta-pinene, tricyclene, camphene, and limonene in the forest fields during the trip, but not in the urban area of Tokyo. We found previously that such phytoncides significantly enhanced human NK activity and increased the expression of intracellular cytolytic molecules, perforin, GrA, and GRN in vitro (1). Komori et al. (4) also reported that citrus fragrance found in forest affects the human endocrine and immune systems as analyzed by the measurement of urinary cortisol and dopamine levels, NK activity, and CD4/8 ratios. These findings suggest that

phytoncides may contribute to the enhanced NK activity during the forest bathing trip (3).

In summary, a forest bathing trip can increase NK activity, the number of NK cells, and the expression of intracellular perforin, GrA/B, and GRN in female subjects. Forest bathing may contribute to decreased stress and improved immunity, and phytoncides from trees may contribute to this effect.

ACKNOWLEDGEMENTS

This work was supported in part by research projects from Japanese Society of Forest Therapy and Shinano Town, Nagano prefecture, Japan (2007).

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ANTI-CYCLIC CITRULLINATED PEPTIDE ANTIBODIES IN PATIENTS AFFECTED BY HCV-RELATED ARTHRITIS

A. RICCIO, L. POSTIGLIONE1, P. LA DOGANA1, A. SPANÒ, C. MARZOCCHELLA and G. TARANTINO

Department of Clinical and Experimental Medicine and 1Department of Biology and Cellular Pathology “L. Califano”, Federico II University Medical School of Naples, Italy

Received August 3, 2007 - Accepted February 11, 2008

Hepatitis C Virus (HCV) infection can induce immunological disorders with different clinical expressions such as arthritis, Sjögren Syndrome and various forms of vasculitis. Retrospectively, the prevalence of anti-Cyclic Citrullinated peptide antibodies (anti-CCP) in a group of patients affected by HCV-related arthritis with positivity for Rheumatoid Factor (RF) and the eventual correlations with RF and/or Anti-Nuclear Antibodies (ANA) and articular involvement were studied. Thirty patients with arthritis were selected from a population of 380 subjects affected by HCV infection. Each patient was evaluated by clinical examination (23 denoted poliarticular and 7 mono-oligoarticular involvement), by X-graphic aspects of joint involvement (8 patients presented joint erosions), by ANA, RF and anti-CCP positivity. Ten of the HCV-related arthritis patients (33.3%) presented positivity for anti-CCP, without significant correlation between such parameter and ANA, RF and articular involvement. Anti-CCP resulted positive in 4 out of the 8 patients with joint erosions, and only in 6 out of the 22 patients without joint erosions. Such frequencies analyzed by chi square resulted with no significant differences. Our patients presented an interesting prevalence of the positivity for anti-CCP. These data are cause to consider the specificity recently attributed to this parameter in the diagnosis of rheumatoid arthritis.

Mailing address: Prof. Giovanni Tarantino, Dept of Clin. & Expermt. Medicine, Via Sergio Pansini, 5Federico II University Medical School, 80131 Naples, ItalyTel: ++39 081 7462024 Fax: ++39 081 5466152e-mail: [email protected]

Key-words: HCV-related arthritis, anti-CCP antibodies

The onset of a rheumatoid-like arthritis in the course of an HCV infection has been reported by several authors in the past (1-4), as well as other extrahepatic manifestations such as Sjögren Syndrome and various forms of vasculitis (5-6). These conditions have been considered as clinical expression of an immunologic imbalance induced by HCV, confirmed by the frequent presence of autoimmunity markers such as cryoglobulins (7-8), Rheumatoid Factor (RF) and Anti-Nuclear Antibodies (ANA) (4, 9-11) in the serum of patients affected by HCV infection. It is not easy

to distinguish rheumatoid arthritis in the course of HCV infection from HCV-related arthritis, even if asymmetrical and non-erosive articular involvement is more frequent, but not typical in the last condition (4, 8). In this regard one of the most used criteria to distinguish rheumatoid arthritis from HCV related arthritis is the presence in the serum of anti-Keratin (AKA) and anti-Cyclic Citrullinated Peptide antibodies (anti-CCP), that have been usually accepted as a specific marker of rheumatoid arthritis (11-12). False positivities of this parameter are very rare in other conditions,

Vol. 22, no. 1, 57-61 (2008)

58

such as viral infections, connective tissue diseases and Lyme disease (13).

In this retrospective study the authors present data on the prevalence of anti-CCP antibodies in a group of patients affected by HCV related arthritis with RF positivity. These data appear important to be reported because they suggest the opportunity to review this specificity.


PatientsThree hundred and eighty patients with HCV-

related chronic hepatitis, (196 M, mean age 47.2±2 SD), were observed in the Hepatological Unit of the Department of Clinical and Experimental Medicine, Federico II University Medical School of Naples, between January 2002 and October 2004. Arthritis was detected on the basis of clinical (presence of arthralgias and joint swelling) and imaging features (reduction of joint space, inconstant joint erosions) in thirty-eight cases (10 %): three of them, presenting psoriasis, were labelled as psoriatic arthritis, in another five HCV infection was subsequent to the onset of arthritis, the remaining thirty patients were defined as HCV-related arthritis. In this last group, twenty three subjects denoted polyarticular involvement, whilst the other seven individuals mono-oligoarticular involvement; only eight patients presented joint erosions, x-ray detected. All of them were suffering from arthritis at least a year after HCV infection. Laboratory methods

Diagnosis of chronic HCV infection was defined by histology, Ishak median fibrosis score 1 (range 1-3), positivity for anti HCV, either an enzyme immunoassay (EIA; Ortho HCV 3.0) or a recombinant Immunoblot assay (RIBA 2; Ortho HCV RIBA II, Orthoclinical Diagnostic) and appropriate quantitative and qualitative HCV-RNA detected by reverse transcription polymerase chain reaction (PCR).

The following parameters were examined: ANA, RF, cryoglobulins and anti-CCP. ANA were determined by a semi-quantitative, solid phase enzyme linked immunosorbent assay, with reference value <1 IU/ml (Quanta Lite ANA ELISA). Anti-CCP, with reference values < 20 units, were studied by Quanta Lite CCP Ig ELISA. RF was determined by ELISA method, (LIOFILCHEM IMMUNOLOGY) with reference value less than 15 U/mL.

Spearman’s rho was used to verify associations. Frequencies were evaluated by chi square test. As statistical package, MedCalc version 9.3.0 was used.

RESULTS

In the sample of thirty tested patients, ten (33.3 %) presented positivity for anti-CCP, with a median value of anti-CCP of 35 units (range 20-60 units), as shown in Table I. No significant correlation was found between such parameter and ANA, RF and cryoglobulins (Spearman’s rho = - 0.022, P = 0.9, -0.12, P = 0.5, and 0.019, P = 0.9 respectively). In the polyarticular involvement group of twenty-three patients, eight (35%) showed anti-CCP positivity, while in the group with mono-oligoarticular damage (seven patients) only one (14 %) denoted such positivity. Furthermore, anti-CCP resulted positive in four out of the eight patients with articular erosions (50 %), but only in six out of twenty-two patients with non-erosive arthritis (27%, Table II). Such frequencies, analyzed by chi square, resulted in no significant differences (Table III).

DISCUSSION

Anti-CCP react with an antigen derived from citrullination of fillagrin, a protein synthesized in the granular layer of the skin (14). Studies with monoclonal antibodies demonstrated the presence of citrullinated proteins in the cells of rheumatoid arthritis synovium, but not in normal synovium and the high concentrations of these antibodies in

A. RICCIO ET AL.

Table I. Anti-CCP levels (Units) in the serum of anti CCP positive patients.

Reference values = < 20 Units, median value of anti-CCP : 35 units (range 20-60 units).

Table I. Anti-CCP levels (Units) in the serum of anti CCP positive patients.

Patients Values of Anti-CCP (UI/mL)

1 60 2 40 3 30 4 20 5 40 6 25 7 30 8 40 9 30 10 40

Reference values = < 20 Units, median value of anti-CCP : 35 units (range 20-60 units).


Table II. Distribution of anti-CCP toward the joint involvement and presence of erosions.

Table III. Statistical difference of anti-CCP positivity.

Joint involvement Anti-CCP mono-oligo articular :

23 patients

poly articular : 7 patients

� = 0.32 p = 0.6

Articular erosions Anti-CCP

present:8 patients

absent:22 patients

� = 0.5 p = 0.5

Table III. Statistical difference of anti-CCP positivity.

Legend: χ = chi square; p = NS

Table II. Distribution of anti-CCP toward the joint involvement and presence of erosions.

Erosion presence Articular involvement

Erosivearthritis

8 patients

Anti-CCP

Positive:

4 patients

(50 %)

Not erosive arthritis

22 patients

Anti-CCP

Positive:

6 patients

(27 %)

Poly articular involvement

23 patients

Anti-CCP

Positive:

9 patients

(39 %)

Mono-oligo articularinvolvement

7 patients

Anti-CCP

Positive:

1 patient

(14 %)

rheumatoid pannus suggested that they are produced in this tissue (15). Therefore, the presence of these autoantibodies in the serum of arthritic patients has been considered as an index of erosive activity, according to the usual findings in such cases of severe x-graphic lesions (16).

In our HCV-related arthritis patients we found more than 30% of positivity for anti-CCP, associated,

but not related to the presence in the serum of RF, ANA and/or cryoglobulins. Moreover, this positivity appeared unrelated to the number of involved joints and to the presence of joint erosions. As our study is retrospective, we had no control group comprehending HCV-infected patients without arthritis.

As reported in the introduction, anti-CCP are considered specific for rheumatoid arthritis (96%), with positivity in about 75% of patients with long-term arthritis and in 50-60% of patients with early arthritis (17). However, our data seem sufficient to induce a revision of the specificity of anti-CCP and their usefulness in the differential diagnosis of the two forms. These results can be seen from different points of view. Firstly, a casual association between HCV infection and rheumatoid arthritis in our patients can not be excluded, since there are no certain criteria to differentiate HCV-related arthritis and rheumatoid arthritis. Secondly, anti-CCP are not so specific as those usually considered for rheumatoid arthritis, even if this is in contrast with recent literature data. In this regard, the absence of correlation with the presence of cryoglobulins excludes that anti-CCP positivity could be related to non-specific binding to plastic in such patients, as recently suggested (18). Moreover, hypothesizing a link of anti-CCP with the erosive process, it appears difficult to exclude that their presence can be found also in arthritic forms

60

other than classic rheumatoid arthritis. Thirdly, in some cases, HCV could play a pathogenic role in the induction of the autoimmune process leading to the onset of rheumatoid arthritis and, in this regard, HCV-related arthritis and rheumatoid arthritis cannot be differentiated in all cases. This last speculation could be explained considering the lymphotropism of the virus, therefore, in this regard HCV could be a trigger cause at least in various cases of rheumatoid arthritis. Indeed, these results could be in accordance with recent data (19) reporting high levels of anti-CCP in course of autoimmune hepatitis, that, at least concerning the type-2 (AIH-2), is considered a nosological entity sometimes overlapping with the HCV form (20). Therefore, anti-CCP could be due to causes other than erosive process.

Our population sample is not elevated, but it appears sufficiently indicative because of the low prevalence of HCV-related arthritis (4). Further prospective studies are needed to define the true meaning of Anti-CCP in course of HCV-related arthritis. Particularly, it would be interesting to clarify whether the presence of such antibodies could be linked to an exaggerated immune response induced by HCV.

REFERENCES

1. Sawada T, Hirohata S, Inoue T, Ito K. Development arthritis after hepatitis C virus infection. Arthritis Rheum 1991; 34:1620-1.

2. Ueno Y, Kinoshita R, Kishimoto I, Okamoto S. Polyarthritis associated with Hepatitis C virus infection. Br J Rheumatol 1994; 33:289-1.

3. Lovy M, Starkebaum G, Uberoi S. Hepatitis C infection and rheumatic manifestations: a mimic of rheumatoid arthritis. J Rheumatol 1996; 23:979-83.

4. Buskila D. Hepatitis C-associated arthritis. Curr Opin Rheumatol. 2000; 12:295-9.

5. Loustaud-Ratti V, Lunel F. Extrahepatic manifestations of hepatitis C virus infection. Rev Prat 2000; 15:1089-93.

6. Pyrsopoulos NT, Reddy KR. Extrahepatic manifestations of chronic viral hepatitis. Curr Gastroenterol Rep 2001; 3:71-8.

7. Rivera J, García-Monforte A, Pineda A, Millán Núñez-Cortés J. Arthritis in patients with chronic hepatitis C virus infection. J Rheumatol 1999; 26:

420-4.8. Zuckerman E, Yeshurun D, Rosner I. Management

of hepatitis C virus-related arthritis. Biodrugs 2001; 15:573-84.

9. Meyer zum Buschenfelde KH, Lohse AW, Gerken G. The role of autoimmunity in hepatitis C infection. J Hepatology 1995; 22:93-6.

10. Bogdanos DP, Mieli-Vergani G, Vergani D. Virus, liver and autoimmunity. Dig Liver Dis 2000; 32:440-6.

11. Baeten D, Peene I, Union A et al. Specific presence of intracellular citrullinated proteins in rheumatoid arthritis synovium: relevance to fillagrin antibodies. Arthritis Rheum 2001; 44:2255-62.

12. Suzuki K, Sawada T, Murakami A et al. High diagnostic performance of Elisa detection of antibodies to citrullinated antigens in rheumatoid arthritis. Scand J Rheumatol 2003; 32:197-204.

13. Bizzaro N, Mazzanti G, Tonutti E, Villalta D, Tozzoli R. Diagnostic accuracy of the anti-citrulline antibody assay for rheumatoid arthritis. Clin Chem 2001;47:1089-93. Erratum in: Clin Chem 2001; 47:1748.

14. Putte LB, van Venrooij WJ. Citrulline is an essential constituent of antigenic determinants recognized by rheumatoid arthritis-specific autoantibodies. J Clin Invest 1998; 101:273–81.

15. Masson-Bessiere C, Sebbag M, Durieux JJ et al. In the rheumatoid pannus, antifillagrin autoantibodies are produced by local plasma cells and constitute a higher proportion of IgG than in synovial fluid and serum. Clin Exp Immunol 2000; 119:544-52.

16. van Boekel MA, Vossenaar ER, van den Hoogen FH, van Venrooij WJ. Autoantibody systems in rheumatoid arthritis: specificity, sensitivity and diagnostic value. Arthritis Res 2002; 4:87-93.

17. Schellekens GA, Visser H. The diagnostic properties of rheumatoid arthritis antibodies recognizing a cyclic citrullinated peptide. Arthritis Rheum 2000; 43:155-63.

18. Sene D, Ghillani-Dalbin P, Limal N et al. Anti-cyclic citrullinated peptide antibodies in hepatitis C virus associated rheumatological manifestations and Sjogren’s syndrome. Ann Rheum Dis 2006; 65:394-7.

19. Vannini A, Cheung K, Fusconi M et al. Anti-cyclic citrullinated peptide positivity in non-rheumatoid arthritis disease samples: citrulline-dependent or not? Ann Rheum Dis 2007; 66:511-6.

A. RICCIO ET AL.


20. Bogdanos DP, Lenzi M, Okamoto M et al. Multiple viral/self immunological cross-reactivity in liver kidney microsomal antibody positive hepatitis C virus

infected patients is associated with the possession of HLA B51. Int J Immunopathol Pharmacol 2004; 17:83-92.





EFFECT OF A SUBGINGIVAL CHLORHEXIDINE CHIP ON THE CLINICAL PARAMETERS AND THE LEVELS OF ALKALINE PHOSPHATASE ACTIVITY IN

GINGIVAL CREVICULAR FLUID DURING THE NON-SURGICAL TREATMENT OF PERIODONTITIS

M. PAOLANTONIO, M. DOLCI, G. PERFETTI, G. SAMMARTINO1, D. D’ARCHIVIO, G. SPOTO, C. CIAMPOLI, D. DE AMICIS2 and S. TETÈ

Department of Stomatology and Oral Sciences, University of Chieti; 1Department of Stomatology and Maxilofacial Surgery, University of Naples; 2Department of Orthopaedics, University of Chieti,

Italy

Received November 30, 2007 – Accepted March 6, 2008

The main therapeutic approaches for inflammatory periodontal diseases include the mechanical treatment of root surfaces. Multi-center clinical trials have demonstrated that the adjunctive use of a chlorhexidine (CHX) chip is effective in improving clinical results compared to scaling and root planing (SRP) alone. However, some recent studies failed to confirm these clinical results, nor have any data been reported regarding the capability of the CHX chip in affecting the activity of alkaline phosphatase (ALP) in the gingival crevicular fluid (GCF). This enzyme has been related to a condition of destructive activity of periodontitis. The aim of this study is to provide further data on the clinical and biochemical effects of CHX chips when used as an adjunct to SRP. Eighty-two systemically healthy patients, aged 31-63, with moderate and advanced periodontitis were recruited from the departments of Periodontology of the University of Chieti. In each patient 2 experimental sites, located in two symmetric quadrants, were chosen with a probing depth of ≥5 mm and bleeding on probing. The 2 sites were selected randomly at the split-mouth level; control sites received SRP alone, and test sites SRP plus 1 CHX chip. Clinical indices, including probing depth (PPD), clinical attachment level (CAL), bleeding on probing (BOP), and the ALP activity in GCF were evaluated at baseline and after 6 months. Alkaline phosphatase activity was assayed spectrophotometrically. The PPD and CAL were significantly lower at 6 months as compared to the baseline scores in both treatments (p<0.01). The PPD reduction was 2.7 mm in the CHX+SRP group and 1.9 mm in the SRP alone group. The CHX+SRP group showed a significantly greater gain of clinical attachment (mean: 1.4 mm) in comparison with the SRP group (mean: 0.9; p<0.05). No differences were observed in the decrease of the % of BOP-positive sites between the experimental groups. Conversely, the CHX+SRP group underwent a significantly greater decrease (p<0.01) of the GCF-ALP activity 6 months after treatment in comparison with the SRP alone group. The adjunctive use of the CHX chip resulted in a significant improvement of pocket reduction and clinical attachment gain as compared with SRP alone. These results were concomitant with a significantly greater reduction of the GCF-ALP activity levels.

Mailing address: Dr M. Paolantonio,Department of Stomatology And Oral Sciences,University G. d’Annunzio,Chieti, ItalyTel/Fax: ++39 08713554121e-mail: [email protected]

Key words: subgingival chlorhexidine chip, periodontitis, alkaline phosphatase, non-surgical periodontal therapy

Vol. 22, no. 1, 63-72 (2008)

64

Periodontitis is an inflammatory disease caused by a local bacterial infection from a pathogenic micro flora colonizing the gingival crevice and the periodontal pockets of susceptible subjects (1). The treatment of chronic periodontitis is directed towards arresting the destruction of the periodontal support of the teeth by eliminating the pathogenic bacteria present in the inflamed pocket. This is performed by mechanical scaling and root planing (SRP), in which subgingival calculus is removed together with most of the bacteria (2). However, some limitations affect this clinical procedure: in particular, as probing depth increases, the effectiveness of SRP decreases, leaving subgingival plaque and calculus on the root surfaces (3-4). This has led to the adjunctive use of antibacterial agents to overcome the limited efficacy of the conventional treatment. The use of systemic antibiotics is limited by the fact that the doses necessary to achieve sufficient local concentrations of antimicrobials in the periodontal environment might be associated with undesirable side effects. Local administration of antiseptics or antibiotics therefore, may be considered an alternative to overcome these problems (5-7). As an antiseptic, Chlorhexidine (CHX) has been used effectively for over 30 years in the treatment of gingival inflammation (8-10). A controlled local delivery system containing 2.5 mg of chlorhexidine gluconate incorporated into a biodegradable chip of hydrolyzed gelatine was introduced for subgingival antimicrobial treatment (11). Multi-center clinical trials have demonstrated that the adjunctive use of a CHX chip is effective in reducing probing depth and maintaining attachment level over a 6 to 9-month period, compared to SRP alone (12-13). Furthermore, recently published studies have confirmed the clinical effectiveness of chlorhexidine chips, reporting also a positive effect of the drug on the gingival crevicular fluid (GCF) levels of Matrix Metalloproteinase-8 (14) and PGE2 (15).

Alkaline phosphatase (ALP) is an enzyme that allows bone mineralization by releasing an organic phosphate that contributes to the deposition of calcium-phosphate complexes into the osteoid matrix (16-19). ALP might also promote mineralization by hydrolyzing inorganic pyrophosphate, a potent inhibitor of hydroxyapatite crystal formation and dissolution, within the extracellular calcifying

matrix vesicles. ALP is a membrane-bound glycoprotein produced by many cells, such as polymorphonuclear leukocytes, osteoblasts, macrophages, and fibroblasts, within the area of the periodontium and gingival crevice (20). ALPs have often been measured in gingival crevicular fluid (GCF) to examine the relationship between periodontal conditions and disease activity (20–22). Plagnat et al (23) studied ALP in GCF from implants with and without peri-implantitis and suggested that ALP could be a promising marker of bone loss around dental implants. Gibert et al (24) studied ALP activity in serum from patients with chronic periodontitis and showed a relationship between loss of attachment in periodontal disease and ALP activity in serum. Binder et al (22) performed a longitudinal study of eight patients and demonstrated a positive correlation between GCF-ALP concentration and periodontal disease activity.

Nakashima et al (1996) reported that levels of ALP in GCF were found significantly raised at periodontal sites undergoing active destruction as compared with those where periodontitis was not in an active condition. Chapple et al (22) reported that GCF-ALP levels were significantly higher in periodontal sites showing progressive disease in comparison with sites not showing attachment loss progression during a 3-month observation period. Currently, GCF-ALP level from periodontitis affected sites is considered to be a good predictor of future or current disease activity (22).

To our knowledge, there is no published data determining the effects of the chlorhexidine chip on crevicular ALP levels and on the clinical parameters of periodontitis in the same study. Therefore, the purpose of the present study is to examine the possible effect of the chlorhexidine chip on clinical periodontal status, and to assess changes in GCF-ALP levels when used as an adjunct to SRP in patients with chronic periodontitis.


Study DesignThis was a randomized, single-blind, controlled, split-

mouth study. The experimental protocol was approved by the Institutional ethical committee of the “G. d’Annunzio” University of Chieti, and voluntary informed patient consent was obtained after receiving detailed information

M. PAOLANTONIO ET AL.


on the purpose, benefits and possible hazards associated with the trial.

Patient selectionEighty-two systemically healthy patients (49 women

and 33 men), aged 31-63 years, with moderate and advanced periodontitis participated in the study. At a preliminary visit, general oral health was assessed and full mouth periodontal examinations were carried out. The patients were enrolled in the study if they had at least a minimum of 10 natural teeth and periodontal disease characterized by the presence of 2 or more teeth with pocket probing depth (PPD) of ≥5 mm, and bleeding on probing (BOP). Exclusion criteria were: smoking; pregnancy; allergy to chlorhexidine; systemic anti-microbial and anti-inflammatory drug therapy within 3 months prior to study; periodontal treatment undertaken <6 months prior to the baseline visit.

Experimental site selectionA screening visit took place 2 weeks before the

baseline appointment. In this appointment, full mouth supragingival scaling and oral hygiene instructions were carried out prior to the baseline visit. At the screening visit the periodontal examination was carried out with a manual 15 mm PCP unc 157 probe (Hu-Friedy Manufacturing Company, Inc., Chicago, Illinois, USA). The measurements were carried out at four sites around each tooth (mesio-buccal, mid-buccal, disto-buccal, and mid-lingual/palatal).

Based on this charting, the target sites were identified. Two experimental sites were chosen in each patient as follows: they had to be interproximal sites with a probing depth of ≥5 mm and bleeding on probing; furthermore, the experimental sites had to be located in two symmetric quadrants and they had to show a difference in PPD ≤ 2 mm. The 2 sites were chosen randomly at the split-mouth level.

Clinical RecordingsClinical measurements were performed by a single

examiner who was unaware of the attribution of the sites to the test or control group.

The following clinical parameters were recorded at baseline and 6 months after treatment in each experimental site:• Pocket probing depth (PPD; measured to the nearest

millimeter from the free gingival margin to the base of the pocket);

• Clinical Attachment level (CAL; corresponding to the distance from the cementum-enamel junction to the base of the pocket);

• Bleeding on probing (BOP).

BOP was recorded as absent or present. BOP was given a positive rating if bleeding occurred within 20 s after pocket probing. For each experimental group the percentage of BOP-positive sites was calculated.

GCF collection and measurementEach crevicular site included in the study was isolated

with cotton tampons. Before the GCF collection, any supragingival plaque, if present, was removed by cotton pellets, and a gentle air stream was directed towards the tooth surface for 5 seconds to dry the area. GCF was collected by use of #30 standardised sterile paper strips (Inline, Turin, Italy), inserted 1 mm into the gingival crevice and left in situ for 30 seconds. Care was taken to avoid mechanical injury. Immediately after collection, the paper points were transferred to plastic vials. GCF total volume was determined for each sample as previously described (26).

Alkaline phosphatase assay Alkaline phosphatase activity was assayed

spectrophotometrically (23) using a spectrophotometer at 405 nm (model 8453, Hewlett Packard, Waldgrohn, Germany). The cone sample was incubated at 30°C, with less than 0.05°C fluctuation, for 20 min in a substrate containing p-nitrophenyl phosphate (10 mM), carbonate buffer (pH 10.2 ± 0.1 at 30 °C), mannitol (200 mM) and MgCl2 (3 mM), to a total volume of 1.0 mL. ALP hydrolyses p-nitrophenyl phosphate to p-nitrophenol and inorganic phosphate. The rate of increase in absorbance at 405 nm was monitored as the p-nitrophenol formed. Using 18.45 as the p-nitrophenol millimolar absorptivity, the absorbance was converted into enzyme activity units (1 U = 1 μmol of p-nitrophenol released per min at 30°C). The final results were expressed as total ALP activity (mU/sample).

Study TreatmentsAt the baseline appointment, after GCF collection

and recording of clinical data, SRP was performed under local anesthesia in the whole dentition in 2 successive appointments within 24 hours, each appointment being 2 hours long. SRP was performed by Gracey curettes. Specifically, in the experimental sites SRP was performed in 5 minutes per each site. Control sites received SRP alone (SRP sites) and test sites SRP plus 1 CHX chip (CHX+SRP sites).

Patients were asked not to use dental floss for 10 days to avoid displacement of the chlorhexidine chip; normal oral hygiene procedures were permitted except for the use of chemotherapeutic mouthwashes and oral irrigation devices. At the 6-month visit, a full mouth supragingival prophylaxis was undertaken according to clinical needs,

66

and oral hygiene instructions were reinforced.

Data AnalysisParametric methods were used when appropriate

after having tested the normality of the data, by means of a Shapiro–Wilk test and by Q–Q normality plots. The changes in clinical and laboratory parameters between baseline and 6 months were analyzed within the treatment groups using Student’s t-test for paired samples. The same analysis was employed to determine significant differences between the test and control groups at the baseline and 6-month examination, respectively. A p value less than 0.05 was used for rejection of the null hypothesis, and appropriate Bonferroni corrections were applied to adjust the p values in the pairwise comparisons.

RESULTS

All patients who were enrolled in the study completed the 6-month examination. The results obtained in this study are summarized in Table I and Fig. 1-3. Mean values of baseline and 6-month examinations relative to PPD and CAL measurements, percentages of BOP-positive sites and GCF-ALP levels are presented in Table I. At baseline, test and control sites did not differ significantly in any of the clinical and biochemical parameters investigated.

The PPD and CAL measurements, the percentage of BOP-positive sites and the total GCF-ALP activity were significantly lower at the 6-month examination as compared to the baseline scores in both treatment groups (p<0.01). At the 6-month examination, the between-groups comparison showed significantly lower PPD, CAL and GCF-ALP values in the test sites as compared with the control sites (PPD/CAL: p<0.05; GCF-ALP: p<0.01). On the contrary, the percentage of BOP-positive sites did not significantly differ between the experimental groups.

Fig. 1 shows the changes of PPD and CAL scores during the study period. The PPD reduction was 2.7 mm in the CHX+SRP group and 1.9 mm in the SRP alone group at 6 months. The CHX+SRP group underwent a significantly greater reduction of PPD at 6 months in comparison with the SRP-alone group (p<0.05). The CHX+SRP group showed a significantly greater gain of clinical attachment (mean: 1.4 mm) in comparison with the SRP group (mean: 0.9; p<0.05). Fig. 2 illustrates the mean decrease in the percentage of BOP-positive sites

throughout the study period. Both groups underwent a dramatic decrease in the number of periodontal sites that bled after periodontal probing; however, this decrease was similar in both groups (p>0.1). The SRP alone and SRP plus chlorhexidine chip groups resulted in a mean reduction in GCF-ALP levels over the entire experimental period. However, the test group had a significantly greater reduction in GCF-ALP level at 6 months (p<0.01; Fig. 3).

DISCUSSION

Recently, a systematic review on the effects of the SRP + CHX chip in the treatment of chronic periodontitis (28) emphasized the need for more randomized, controlled clinical trials providing data to further elucidate the effectiveness of the CHX chip as an adjunct to SRP. This conclusion derives from the consideration that, while multicenter trials have proven the effectiveness of CHX+SRP treatment as compared to SRP alone (12-13). On the other hand, some recent studies (29) failed to confirm these results. Furthermore, a scarcity of studies investigating the effects of a CHX+SRP treatment on the composition of GCF can be highlighted.

The results from the present controlled randomized study confirm those from the former multi-center clinical studies (12-13) and offer new data on the effects of the CHX chip as an adjunct to SRP on the composition of GCF. Both CHX-SRP and SRP alone treatments significantly reduced PPD as compared to baseline scores; however, periodontal treatment based on the adjunct of the CHX chip to SRP yielded significantly lower PPD values at the 6-month evaluation in comparison with SRP alone (Table I).

Significantly greater improvement of PPD values was observed at the 6-month visits in the CHX+SRP treatment group as compared with the SRP group; a similar trend was observed for CAL gain; in the CHX+SRP group sites it was significantly greater at the 6-month visit (Fig. 1). These results confirm those from former multi-center trials. In comparison with the clinical results of Soskolne et al (10) and Jeffcoat et al (13), ours show greater PPD and CAL improvements in both test and control groups. In particular, our pocket reductions and clinical attachment gains from the control group are in



good agreement with those reported in the relevant literature (30-32).

The better results reported in the present research in comparison with the former multi-center studies (12-13) may be explained by the different SRP treatment used. Soskolne et al (12) and Jeffcoat et al (13) limited the therapy time to 1 hour with the

aim of reflecting the time that is likely to be given to such therapy in an average general dental practice. Conversely, in the present study full-mouth SRP was performed in two 2-hour clinical sessions; furthermore, the experimental teeth were scaled for 5 minutes.

Our better results may also be explained by the

Table 1. Baseline and 6-month examination scores of the clinical and biochemical parameters from CHX+SRP- and SRP-treated sites, and statistical significance of the between- and within-group differences at each experimental visit.

PPD CAL BOP ALP

Baseline 6-month

Withingroups

differenceBaseline 6-

month

Withingroups


month

Withingroups


month

Withingroups

difference

CHX+SRPsites

6.6�1.2 3.9�1.6t=4.88

p<0.01 S 8.7�1.4 7.3�0.54t=6

p<0.01 S100% 13.75% t=5.9

p<0.01 S 33.3�7.2 19�8.1t=3.84

p<0.01 S

SRP sites 6.7�2.2 4.8�1.5t=4.98

p<0.01 S 8.8�2.1 7.9�1.41t=4.14

p<0.01 S100% 15% t=6.2

p<0.01 S 35.4�8.3 28�7.4t=2.69

p<0.05 S

Between groups

difference

t=1.82NS

t=2.26p<0.05

S

t=1.23NS

t=2.22p<0.05

S

t=0 N.S

t=0.74N.S t=1.90

NSt=3.9

p<0.01S

PPD and CAL: millimetres BOP: % of sites BOP-positive ALP: enzyme activity in mU/sample

Table 1. Baseline and 6-month examination scores of the clinical and biochemical parameters from CHX+SRP- and SRP-treated sites, and statistical significance of the between- and within-group differences at each experimental visit.

PPD and CAL: millimetresBOP: % of sites BOP-positiveALP: enzyme activity in mU/sample

PPD reduction CAL gain

Fig. 1. PPD reduction and CAL gain (in mm) at the 6 month examination from the baseline scores. *** statistically significant difference at p<0.05 level

CHX + SRPSRP

Fig. 1. PPD reduction and CAL gain (in mm) at the 6 month examination from the baseline scores. *** statistically significant difference at p<0.05 level

68

fact that in this study SRP procedures were performed within a 24-hour period according to the principles of the “full-mouth disinfection” as proposed by Bollen et al (33). The Authors hypothesize that during a normal periodontal treatment strategy, with consecutive root planings per quadrant or sextant at 1 or 2 week intervals, a re-infection of a previously disinfected area might well occur before the completion of the treatment. A short term pilot study, by Quirynen et al (34), showed that a so-called “full-

mouth disinfection” within a period of 24 h resulted in a significantly better outcome, microbiologically as well as clinically.

Our results suggest that CHX chips are capable of improving the clinical results obtained by a very accurate SRP performed according to the principles of the “full-mouth disinfection”. Contrary to our study, Grisi et al (29) reported that there were no statistically significant differences between the SRP and SRP plus chlorhexidine groups for clinical

Fig. 2. % decrease of BOP-positive sites at the 6 month examination from the baseline scores.

0

10

20

30

40

50

60

70

80

90

100

% re

duct

ion

of B

OP-

posi

tive

site

s

Fig. 2. % decrease of BOP-positive sites at the 6 month examination from the baseline scores.

CHX + SRPSRP

0

2

4

6

8

10

12

14

16

18

20

ALP

act

ivity

mU

/sam

ple

Fig. 3. ALP activity decrease (mU/sample) at the 6 month examination from the baseline scores. *** statistically significant difference at p<0.05 level

CHX + SRPSRP

***

Fig. 3. ALP activity decrease (mU/sample) at the 6 month examination from the baseline scores.*** statistically significant difference at p<0.05 level



parameters after a 9-month period. This may be due to the lack of statistical power in that study: in fact the authors investigated only a limited number of patients (20 subjects), taking into account that the absolute dimension of the greater clinical gain offered by all different topical adjunctive antimicrobial substances in periodontology is relatively small, the lack of a study population of adequate dimension, may lead to a type II statistical error.

In our study, the percentage of BOP-positive sites showed a dramatic decrease from baseline to the 6-month visits in both CHX+SRP- and SRP-treated sites with no significant differences between the experimental groups. This finding does not agree with those from the former multi-center studies (12-13); both clinical trials reported a significant greater decrease of BOP-positive sites in the CHX+SRP groups in comparison with controls. The different modalities of SRP used in the present study, compared with those from Soskolne et al (12) and Jeffcoat et al (13), may explain this disagreement. More recently, other authors, in accordancre with our results, reported a lack of adjunctive effect of the CHX chip in reducing gingival bleeding (14, 35).

In the literature, few studies are focused on the clinical effectiveness of chlorhexidine chips on the gingival crevicular fluid components. Azmak et al (14) and Mizrak et al (15) reported a significant greater decrease of Matrix Metalloproteinase-8 and PGE2 in GCF after the combined CHX-SRP treatment of periodontal pockets. No data are currently available on the effects of CHX chips on the GCF levels of ALP

Alkaline phosphatase (orthophosphoric monoester phospho-hydrolase EC 3.1.3.1) is a membrane-bound glycoprotein found on most cell membranes in the body (36-40) which is produced by many cells within the periodontal environment, the principal sources being polymorphonuclear leukocytes (PMNL’s) (43), bacteria within the supra and sub-gingival plaque (42) and through osteoblasts and fibroblast activity (43-49). ALP within GCF is probably of mixed serum, host tissue, PMNL and bacterial origin. The predominant source is important to elucidate, since it indicates whether GCF levels of the enzyme are potential measures of inflammation, attachment loss, bacterial load or composition, or indeed a combination of these factors. Harrap et al

(50) investigated the inhibition of bacterial, PMNL, bone, serum and GCF ALP, using levamisole and enzyme precipitation by Concanavalin A. They concluded that bacterial ALP was an important contributor to overall GCF ALP activity. However, the studies of Binder et al (22), using repeat sampling of GCF, suggest that the activity is predominantly of host tissue origin.

Since periodontal disease is characterised by gingival inflammation and loss of alveolar bone, alkaline phosphatase (ALP) is a potentially powerful marker of periodontal disease activity. This was first recognised by Ishikawa and Cimasoni (51-54) who demonstrated levels of the enzyme in gingival crevicular fluid (GCF) 3 times those of serum and showed a significant correlation between ALP concentration in GCF and pocket depth. Chapple et al (55) reported that GCF ALP levels would detect changes in sub-clinical inflammatory status. In the same study the authors demonstrated that total levels of GCF ALP collected over a 30-second period were significantly higher at sites of gingivitis than healthy sites. Binder et al (18) performed a longitudinal study of 8 patients and demonstrated that GCF ALP concentration showed a positive relationship with periodontal attachment loss and achieved good sensitivity and specificity as a diagnostic tool for active disease. More recently Nakashima et al (17) confirmed significantly raised GCF ALP levels in inflamed gingivae and demonstrated a positive correlation with clinical disease status.

Our results show that a CHX-SRP treatment is significantly more effective in reducing the levels of GCF-ALP compared to SRP alone. As GCF-ALP level is currently considered a reliable indicator of periodontal inflammation and disease activity, the observation that the combined CHX-SRP non-surgical treatment is capable of reducing its level for a significantly greater extent than the conventional SRP treatment, may suggest the indication to use an adjunctive CHX chip during the non-surgical phase of periodontal treatment of those patients who are considered to be at higher risk for active periodontitis recurrence i.e. patients suffering from localized or generalized forms of Aggressive Periodontitis.

However, we were not able to compare our data with other studies because we could not find a previous study on the effect of chlorhexidine chip

70

application on crevicular ALP levels. In conclusion, clinical and biochemical data

in the present study indicate that application of the chlorhexidine chip adjunctive to SRP might be beneficial in improving clinical periodontal parameters and in reducing GCF ALP levels. Furthermore, taking into account that currently GCF-ALP level from periodontitis affected sites is considered to be a good predictor of future or current disease activity (20), our results suggest that the use of a subgingival chlorhexidine chip during the routine supportive periodontal treatment of the periodontal patient may help to reduce the risk of disease recurrence.

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QUALITY OF LIFE IN NON-ALLERGIC RHINITIS DEPENDS ON THE PREDOMINANT INFLAMMATORY CELL TYPE

M. GELARDI, A. MASELLI DEL GIUDICE, M.L. FIORELLA, P. SOLETI1, M. DI GIOACCHINO2, C.M. CONTI3, M. FULCHERI3, R. DOYLE4 and G. CIPRANDI5

Dipartimento di Oculistica e Otorinolaringoiatria, Università di Bari; 1Department of Statistic Sciences, Faculty of Economics,University of Bari, Bari; 2Allergy Related Diseases Unit, G.

d’Annunzio University, Chieti; 3Clinical Psychology Department, G. d’Annunzio University, Chieti, Italy; 4Psychiatry Department, Massachusetts General Hospital, Harvard Medical School, Boston MA, USA; 5Dipartimento di Medicina Interna, Azienda Ospedaliera Universitaria San Martino,

Genova, Italy


Three main types of inflammatory Non-Allergic Rhinitis (NAR) have been defined: NAR infiltrated by eosinophils (NARES), by mast cells (NARMA), and by neutrophils (NARNE). In the absence of studies that investigated the Quality of Life (QoL) in NAR, the present work is aimed at evaluating the Quality of Life of patients with NARES, NARMA, and NARNE. One hundred thirty one (131) NAR patients were prospectively and consecutively evaluated: 54 patients with NARES, 38 with NARMA, and 39 with NARNE. Their history, nasal infiltration and rhinomanometry were characterized, and Quality of Life (using 2 instruments) was evaluated, and associated to clinical and histological features. Quality of Life was significantly different in the 3 groups (p<0.001); NARES patients had the worst Quality of Life. Nasal resistances were significantly higher in the NARES group. Significant associations were shown in NARES patients between Quality of Life and nasal function. This study provides the first evidence that Quality of Life is impaired in NAR as well as in allergic rhinitis. Furthermore, Quality of Life impairment differs among the various forms of NAR, and there is a correlation with the cellular infiltrating type.

Mailing address: Prof. M. Di Gioacchino,Allergy Related Diseases UnitG. d’Annunzio University,Chieti, ItalyTel: ++39 0871 358578Fax: ++30 0871 551615e-mail: [email protected]

Key words: Quality of life, inflammatory cells, non-allergic rhinitis, polyps, nasal resistances, nasal cytology

Non-Allergic Rhinitis (NAR), is a heterogeneous disease, which is characterized by nasal hyperreactivity that results in symptoms which include nasal blockage, rhinorrhoea, and sneezing, similar to those of allergic rhinitis. Diagnosis of NAR is established on the basis of persistent symptoms throughout the year after exclusion of infection (as indicated by a clear and watery nasal discharge, as compared with a purulent discharge

produced in infectious rhinitis), any anatomical or medical disorder of the nose, and negative skin prick testing for IgE-mediated sensitivity to relevant aeroallergens (1-4).

NAR comprises several forms of rhinitis. The aetiology and/or pathophysiology is established only for some forms of the disease, such as drug-induced rhinitis and non-allergic rhinitis with eosinophilia syndrome (NARES). Other minor forms of rhinitis

Vol. 22, no. 1, 73-81 (2008)

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include occupational rhinitis, non-allergic hormonal rhinitis, food-induced rhinitis, emotion-induced rhinitis, physical/chemical irritant-induced rhinitis, and rhinitis of the elderly. In contrast, the aetiology is largely unknown for a majority of about 75–80% of the individuals in whom the disease is classified as being idiopathic or vasomotor rhinitis. This high percentage of idiopathic aetiology is, at least in part, due to the fact that nasal cytology is very rarely performed. Indeed, nasal cytology only recognizes and identifies the NAR types, characterized by an inflammatory cell infiltrate (5-8). In this regard, three main types of NAR characterized by typical inflammatory cell infiltrate has been defined: NAR infiltrated by eosinophils (i.e. NARES), by mast cells (i.e. NARMA), and by neutrophils (i.e. NARNE). These forms of non-allergic rhinitis are characterized by local inflammation that appears to be the main underlying pathological mechanism (9-11). NARES is clinically characterized by perennial nasal symptoms of sneezing paroxysms, profuse watery rhinorrhea, and itching of the nasopharyngeal mucosa in an “on-again-off-again” symptomatic pattern (12). Additionally, these patients had profound nasal eosinophilia (>20% of the granulocytic or mononuclear cells present excluding nasal epithelial cells), which was not associated with allergic disease, as indicated by negative skin-prick testing and no evidence for increased levels of either total or specific IgE in the nasal secretions. In addition, it has been suggested that this condition may be prevalent in up to one third of adults with non-allergic rhinitis, and although it usually occurs as an isolated disorder, in severe cases it may be associated with non-IgE-mediated asthma, aspirin intolerance and nasal polyps (13-16). Eosinophilia in NARES may contribute to nasal mucosal dysfunction, since major basic protein (MBP) and eosinophil cationic protein (ECP) released from the eosinophil granules are capable of damaging the nasal ciliated epithelium and prolonging mucociliary clearance. Prolonged or delayed mucociliary clearance itself may increase the propensity towards infection and predispose the individual to the development of nasal polyps. Nevertheless, the presence of eosinophilia in NARES may be an important predictor for response to treatment with topical anti-inflammatory therapy.

NARMA was initially described by Connell

and is characterized by a predominant infiltrate by mast cells (17-20). Mast cells are an important source of mediators, including histamine and leukotrienes, causing profound symptoms, and for pro-inflammatory cytokines, inducing inflammatory cascade.

NARNE is characterized by predominant neutrophilic infiltration without infection. Aetiology is multi-factorial, including cystic fibrosis, antro-choanal polyp, pollution, tobacco smoke (21-24). Infiltrating neutrophils release enzymes, mainly elastase, which produce free radicals that cause mucosal damage. On the other hand, the Quality of Life (QoL) has been widely evaluated in allergic rhinitis (3), but there is no study that deeply investigated QoL in NAR, therefore, the aim of this study is to evaluate QoL in patients with NARES, NARMA, and NARNE.


Study design This prospective study was conducted including

patients with NAR consecutively visited at the ENT Clinic of Bari (Italy). Subjects with acute upper respiratory infections, anatomic nasal defects (i.e. septum deviation), asthma and/or bronchial hyperreactivity who were using nasal or oral corticosteroids, nasal or oral decongestants, antileukotrienes, and antihistamines during the previous 4 weeks were excluded.

The diagnosis of NAR was made on the basis of a history of nasal symptoms (including sneezing, rhinorrhea, and nasal obstruction typically dependent on exposure to triggers such as odors, irritants, weather changes), presence of inflammatory cells on nasal smears, and negative skin prick test according to validated criteria (2-3).

Skin prick tests, nasal cytology and endoscopy, rhinomanometry, and QoL evaluation by questionnaire were carried out on all subjects. The study was approved by the Institutional Review Board of the University of Bari, and an informed consent was obtained from all patients.

Skin prick testAllergy was assessed by the presence of sensitization

to the most common classes of aeroallergens by carrying out a skin prick test as stated by the European Academy of Allergy and Clinical Immunology: sensitization was considered when the wheal diameter was equal or greater than 3 mm (25). The allergen panel consisted of the

M. GELARDI ET AL.


following: house dust mites (Dermatophagoides farinae and pteronyssinus), cat, dog, grasses mix, Compositae mix, Parietaria judaica, birch, hazel tree, olive tree, Alternaria tenuis, Cladosporium, and Aspergilli mix; the concentration of allergen extracts was 100 I.R./mL (Stallergenes, Milan, Italy).

Nasal cytologyCytological samples were obtained by scraping with

a Rhino-Probe™. The samples were collected from the medial portion of the inferior middle turbinate. After fixing with absolute alcohol for 3 minutes and drying, the samples were stained using the May-Grünwald-Giemsa (Carlo Erba, Milan, Italy) method, then mounted on covered slides and examined under microscopy (Nikon E600, Nikon Italy). Cell count was performed on 10 microscopic samples at high-power magnification (x1000) in immersion (15). Samples were examined blindly by two different readers.

NARES was diagnosed if nasal eosinophils were >20% of total cells recovered from nasal scraping, including

both inflammatory and epithelial cells; NARMA was diagnosed if nasal mast cells were >10% of total cells; and NARNE was diagnosed if nasal neutrophils were >50% of total cells (26).

RhinomanometryNasal airflow resistance was measured by active

anterior electronic rhinomanometry. Patients wore a tight-fitting face mask, and breathed through one nostril with their mouth closed. A sensor, placed in the controlateral nostril, recorded data on pre- and post-nasal pressures via airflow and pressure transducers. The instrument (Rhinomanometer Menfis, Amplifon Italy) was connected to a personal computer. The signals of transnasal airflow and pressure were amplified, digitalized, and saved for statistical analysis.

Nasal resistance is measured as Pa/mL/sec as the sum of the recorded airflow in milliliter per second through the right and left nostrils at a pressure difference of 150 Pa across the nasal passage.

Four or more airflow measurements were performed

Table I. QoL evaluation by using the HRQL-RS questionnaire.

NARES

(n=54)

NARMA

(n=38)

NARNE

(n=39)Dimension

Mean

Score

� Mean

Score

� Mean

Score

�

TEST

Kruskal-

Wallis P

value

Social Problems 2.75 0.53 1.62 0.50 1.59 0.33 <0.001

Sleep 2.40 0.84 1.55 0.63 1.60 0.44 <0.001

Non-nasal symptoms 2.30 0.67 1.30 0.41 1.65 0.40 <0.001

Nasal Symptoms 2.62 0.45 1.56 0.34 1.69 0.33 <0.001

QoL � VAS 3.54 1.578 5.37 1.076 6.64 0.723 <0.001

Mann-Whitney p-value NAR types

Social

Problems Sleep

Non Nasal

symptoms

Nasal

symptoms QoL � VAS

NARNE vs NARES <0.01 <0.01 <0.01 <0.01 <0.01

NARMA vs NARES <0.01 <0.01 <0.01 <0.01 <0.01

NARNE vs NARMA 0.3 0.25 <0.01 0.04 <0.01

A significant difference among groups (p<0.001) was evident. Patients with nonallergic rhinitis with eosinophilia syndrome (NARES) showed the worst score for all dimensions.

Table I. QoL evaluation by using the HRQL-RS questionnaire.

A significant difference among groups (p<0.001) was evident. Patients with non-allergic rhinitis with eosinophilia syndrome (NARES) showed the worst score for all dimensions.

76

for each patient and the mean value was recorded when reproducible values were achieved. Normal values are < 0.50 Pa/mL/sec ( 27).

Quality of LifeHealth-Related Quality of Life (HRQL) assessment

included two disease-specific instruments. The first was the Health-Related Quality of Life in Rhino Surgery (HRQL-RS), validated (28) and adapted for the use in the Italian population. This specific health profile HRQL-RS questionnaire consists of 25 items summarized in 6 dimensions: nasal and non-nasal symptoms, sleep, emotional symptoms, headache, and practical problems, these last three dimensions were summarized in a single dimension: social problems. Responses to the items are scored on a 4-point scale, the lower the score, the better the HRQL. Most items are the same used in the Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) provided by Juniper and colleagues (29).

Moreover, a visual analogue scale (from 0=worst QoL to 10=best QoL) was given to measure the patients’ general feeling related to their nasal disease.

The second questionnaire was the above-mentioned Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) consisting of 28 items distributed in seven dimensions: sleep problems (3 items), non-hay fever symptoms (7 items), practical problems (3 items), nasal problems (4 items), eye symptoms (4 items), activities (3 items), and emotions (4 items). Responses to the items are scored on a 7-point Likert scale, while dimensions and overall scores are scored on a 0-6 scale (29). In both cases, the lower the score, the better the HRQL.

Statistical analysisData were described as mean and standard deviation.

Continuous variables and categorical variables were compared by means of the Kruskall Wallis test (non-parametric analysis of variance) and the Mann Whitney

Table II. QoL evaluation by using the RQLQ questionnaire.

NARES

(n=54)

NARMA

(n=38)

NARNE

(n=39)

Dimension

Mean

Score

� Mean

Score

� Mean

Score

�

TEST

Kruskal-

Wallis P

value

Social Problems 2.75 0.53 1.62 0.50 1.59 0.33 <0.001

Sleep 2.40 0.84 1.55 0.63 1.60 0.44 <0.001

Non-nasal symptoms 2.30 0.67 1.30 0.41 1.65 0.40 <0.001

Nasal Symptoms 2.62 0.45 1.56 0.34 1.69 0.33 <0.001

QoL � VAS 3.54 1.578 5.37 1.076 6.64 0.723 <0.001

Mann-Whitney p-value NAR types

Social

Problems Sleep

Non Nasal

symptoms

Nasal

symptoms

QoL � VAS

NARNE vs NARES <0.01 <0.01 <0.01 <0.01 <0.01

NARMA vs NARES <0.01 <0.01 <0.01 <0.01 <0.01

NARNE vs NARMA 0.3 0.25 <0.01 0.04 <0.01

A significant difference among groups (p<0.001) was evident. Patients with nonallergic rhinitis with eosinophilia syndrome (NARES) showed the worst score for all dimensions. NARMA=nonallergic rhinitis with mast cells; NARNA= nonallergic rhinitis with neutrophils

Table II. QoL evaluation by using the RQLQ questionnaire.

A significant difference among groups (p<0.001) was evident. Patients with non-allergic rhinitis with eosinophilia syndrome (NARES) showed the worst score for all dimensions. NARMA=non-allergic rhinitis with mast cells; NARNA= non-allergic rhinitis with neutrophils

M. GELARDI ET AL.


U test for post-hoc comparisons. The Kolmogorov-Smirnov test was used to compare nasal resistance values. Correlations were evaluated by the Spearman test. Q2 and G2 tests were used to compare the frequency and onset age of polyps to NAR subsets. SPSS software was used for computation. A 2-sided p-value<0.05 was considered statistically significant.

RESULTS

Patients131 patients with NAR were prospectively and

consecutively evaluated: 75 males and 56 females, mean age 40.6 ± 4.4 years. All of them were negative to the skin prick test. They were grouped according to diagnosis, such as the type of infiltrating inflammatory cells: 54 patients with NARES, 38 with NARMA, and 39 with NARNE.

Quality of Lifei) HRQL-RS questionnaire: globally there was

a significant difference among groups (p<0.001).

In particular, NARES patients showed the worst score for all dimensions: social problems (p<0.01), sleep (p<0.01), non-nasal symptoms (p<0.01), nasal symptoms (p<0.01), and personal perception of QoL by VAS (p<0.01) in comparison with the other two groups. NARNE patients had worse QoL concerning nasal symptoms (p=0.04), non-nasal symptoms (p<0.01), and QoL perception by VAS (p<0.01) in comparison to NARMA patients (Table I). For sleep NARNE patients had worse snoring and nocturnal awakening, as reported in Fig. 1;

ii) RQLQ questionnaire: globally there was a significant difference among groups (p<0.001). In particular, NARES patients showed the worst score for all dimensions: practical problems (p<0.01), sleep problems (p<0.05), non-hay fever symptoms (p<0.01), nasal problems (p<0.01), and emotional problems (p<0.01) in comparison with the other two groups. NARNE patients had worse QoL concerning non-hay fever symptoms (p<0.01), and emotional problems (p<0.05) in comparison to NARMA

Fig. 1. Nasal resistances, expressed as Pa/mL/sec in patients with non-allergic rhinitis with eosinophilia syndrome (NARES), non-allergic rhinitis with mastcells (NARMA) and with Neutrophils (NARNA). There were significant differences between NARES and NARNE (*) (p<0.001), NARES and NARMA (**) (p=0.005), and NARNE and NARMA (***) (p=0.001).

78

patients (Table II).

RhinomanometryNasal resistances were increased in all groups

with difference among groups (p<0.001). There were significant differences between NARES and NARNE (p<0.001), NARES and NARMA (p=0.005), and NARNE and NARMA (p=0.001) as reported in Fig. 1.

Relationship between QoL and rhinomanometry A significant association was reported for the

relationship between nasal obstruction and dry throat (p<0.001), nasal obstruction and snoring (p<0.001) in all groups, nasal resistance and QoL perception by VAS in NARES patients (p=0.045) as reported in Fig. 2.

Association with nasal polyps57.5% of NARES patients had nasal polyps,

30.2% of NARMA patients, and 3.3% of NARNE (p<0.0001). In addition, nasal polyps are more frequent in subjects with age >35 years in NARES patients (p<0.001). However, given the number of subscales, patient subgroups, and statistical comparisons, a loss of statistical power inherent in performing multiple statistical comparisons has to be considered.

DISCUSSION

NAR diagnosis is based on two main issues in patients with nasal symptoms consequent to exposure to irritants: negative skin prick test and cytologic assessment. Nasal cytology is a crucial step to manage patients with NAR. Indeed, cytology alone allows to correctly diagnosis the different types of NAR. On the basis of prevalent inflammatory cell type, three main forms of NAR may be considered: NARES, NARNE, and NARMA.

Fig. 2. Relationships between (a) nasal symptoms, expressed as Pa/mL/sec, and sleep (p=0.001), (b) sleep (p=0.001), and (c) QoL perception by VAS (p=0.045) in patients with non-allergic rhinitis with eosinophilia syndrome (NARES).

M. GELARDI ET AL.


The condition “non-allergic rhinitis with eosinophilia syndrome” (NARES) was originally characterized on the basis of the presence of greater than 20% eosinophils in nasal smears of symptomatic patients with perennial sneezing attacks, a profuse watery rhinorrhea, nasal pruritis, nasal obstruction and occasional loss of smell (1, 13). In addition to these symptoms, a marked feature of the disease was the lack of evidence of allergy, as indicated by negative skin prick tests and/or absence of serum IgE antibodies to specific allergens. The prevalence of NARES has been shown to range between 13 and 33% in patients with non-allergic rhinitis (31-32). Although the specific etiology of NARES is not clear, in view of the features shared by this syndrome and the ASA triad (nasal polyposis, intrinsic asthma, and intolerance to aspirin) and because NARES patients frequently develop nasal polyps and asthma later on in life, it has been suggested that NARES may be an early expression of the triad (1). Indeed, in about 50% of NARES patients without a history of respiratory symptoms, bronchial responsiveness is associated with an increase in the number of sputum eosinophils, but not with an increase in the number of nasal eosinophils (33-36). Few studies have investigated NARMA; this rhinitis is characterized by a pathophysiologic mechanism and clinical pattern very similar to allergic rhinitis (17, 37-39). NARNE is a chronic inflammation of the nose due to different causative agents that induce damage of the respiratory epithelium.

On the other hand, Health-Related Quality of Life (HRQL) measures the impact of a pathologic condition in the patient’s daily life. Besides the disease-related symptoms, it includes a wide spectrum of daily life activities such as physical and social activities, emotional problems, general feeling, and so on. HRQL of patients with nasal diseases is frequently used in clinical studies. A Health-Related Quality of Life in Rhinological Surgery questionnaire has been proposed in patients surgically treated (28). RQLQ is the most used instrument in studies concerning allergic rhinitis (28).

This study provides the first evidence that QoL is impaired in NAR and there is a significant difference between different forms. In particular, NARES is the more severe form of NAR as demonstrated by worst QoL, increased nasal resistance, and

frequent association with nasal polyps. It appears evident that eosinophilic infiltration induces severe inflammation that causes the most severe symptoms. Indeed, eosinophils are the best markers of allergic inflammation (40-42). Moreover, eosinophils are the main inflammatory cell infiltrating nasal polyps. Inflammatory edema associated with polyp neoformation contributes to the impairment of nasal airflow. In this regard, nasal obstruction is a crucial symptom that causes several complications (43).

This study demonstrates that there is a relationship between inflammation, nasal obstruction, impaired nasal airflow, and QoL. Moreover, NARES is frequently associated with nasal polyps, thus making this form of NAR the most severe. In addition, there is also a difference between NARNE and NARMA based on the different cellular pattern. In other words, the inflammatory cell type appears to be crucial in determining the severity of nasal symptoms that may be evaluated both by QoL questionnaires and rhinomanometry.

In conclusion, this study provides the first evidence that QoL is also impaired in NAR, as well as in allergic rhinitis, and the QoL impairment is dependent on the type of cellular infiltrate. Moreover, nasal cytology is a crucial diagnostic tool to diagnosis these disorders. Finally, further studies should be addressed to evaluate whether patients with NARES, NARNE, and NARMA may have differential treatment responses.

REFERENCES

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3. Bachert C, van Cauwenberge P. The WHO ARIA (allergic rhinitis and its impact on asthma) initiative. Chem Immunol Allergy 2003; 82:119-26.

4. Fokkens WJ. Thoughts on the pathophysiology of non-allergic rhinitis. Curr Allergy Asthma Reports 2002; 2:203-9.

5. Gelardi M, Cassano P, Cassano M et al. Nasal cytology: description of a hyperchromatic

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supranuclear stria as a possible marker for the anatomical and functional integrity of the ciliated cell. Am J Rhinol 2003; 17:263-8.

6. Hauswirth AW, Sonneck K, Florian St, Krauth MT, Böhm A, Sperr WR, Valenta R, Schernthaner G-H, Printz D, Fritsch G, Bühring H-J, Valent P. Interleukin-3 promotes the expression of E-NPP3/CD203C on human blood basophils in healthy subjects and in patients with birch pollen allergy. Int J Immunopathol Pharmacol 2007; 20:267-278.


8. Bernardini R, Mistrello G, Pucci N, Roncarolo D, Lombardi E, Zanoni D, Mori F, de Martino M, Novembre E, Massai C, Azzari C, Vierucci A. Diagnostic value of three different latex extracts. Int J Immunopathol Pharmacol 2007; 20:393-400.

9. Bachert C. Persistent rhinitis - allergic or non-allergic? Allergy 2004; 59:11-5.



12. Dykewicz MS. Clinical approach to diagnosis and treatment of non-allergic rhinitis. Clin Allergy Immunol 2007; 19:335-50.

13. Ellis AK, Keith PK. Non-allergic rhinitis with eosinophilia syndrome and related disorders. Clin Allergy Immunol 2007; 19:87-100.

14. Cadoni S, Ruffelli M, Fusari S, de Pità O. Oral allergic syndrome and recombinant allergens rBet v 1 and rBet v 2. Eur J Inflamm 2007; 5:21-25.

15. Ciprandi G, Cirillo I, Troisi RM, Marseglia GL. Allergic subjects have more numerous respiratory infections and severe gastrointestinal infections

than non-allergic subjects: preliminary results. Eur J Inflamm 2007; 5:27-29.

16. Deepak P, Kumar S, Acharya A. IL-13 neutralization modulates function of type II polarized macrophages in vivo in a murine T-cell lymphoma. Eur J Inflamm 2007; 5:37-45.

17. Connell JT. Allergic rhinitis. Human experimental model. NY State J Med 1970; 70:1751-60.

18. Ahangari G, Chavoshzadeh Z, Lari Z, Ramyar A, Farhoudi A. Novel mutation detection of an inflammatory molecule Elastase II gene encoding neutrophil Elastase in Kostmann syndrome. Eur J Inflamm 2007; 5:65-71

19. Stassi G, Cascio A, Iaria C, Gazzara D, Costa GB, Iannello D, Arena A. Modulation of GRO-α and TNF-α production by peripheral blood mononuclear cells treated with killed helicobacter pylori. Eur J Inflamm 2007; 5:83-87.

20. Ciardelli L, Garofoli F, Avanzini MA, De Silvestri A, Gasparoni A, Sabatino G, Stronati M Escherichia coli specific secretory IgA and cytokines in human milk from mothers of different ethnic groups resident in northern Italy. Int J Immunopathol Pharmacol 2007; 20:335-340.

21. Hellgren J, Toren K. Non-allergic occupational rhinitis. Clin Allergy Immunol 2007; 19:241-8.

22. Shusterman D. Environmental non-allergic rhinitis. Clin Allergy Immunol 2007; 19:249-66.

23. Baraniuk JN, Clauw D, Yuta A et al. Nasal secretion analysis in allergic rhinitis, cystic fibrosis, and non-allergic fibromyalgia/chronic fatigue syndrome subjects. Am J Rhinol 1998; 12:435-40.

24. Capodiferro S, Scully C, Ficarra G, de Frenza G, Grassi R, Maiorano E, Favia G, Mastrangelo F, Tetè S. Orofacial granulomatosis: report of two cases with gingival onset. Eur J Inflamm 2007; 5:51-56.

25. Dreborg S. EAACI Subcommittee on Skin Tests. Skin tests used in type I allergy testing. Position Paper. Allergy 1989; 44:1-51.

26. Gelardi M. Atlas of Nasal Cytology. Centro Scientifico Editore, 2006, Torino, Italy.

27. Cole P, Fenton RS. Contemporary rhinomanometry. J Otolaryngol 2006; 35:83-7.

28. Kramer MF, Rasp G, Kastenbauer E. Health-Related Quality of Life in rhino surgery. Am J Otolaryngol 2003; 24 :97-105.

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for an inflammatory pathophysiology in idiopathic rhinitis. Clin Exp Allergy 2001; 31:864-72.

38. Papoff P, Mancuso M, Barbàra CS, Moretti C. The role of terlipressin in pediatric septic shock: a review of the literature and personal experience. Int J Immunopathol Pharmacol 2007; 20:213-222.

39. D’Offizi G, Gioia C, Corpolongo A, Martini F, Paganelli R, Volpi I, Sacchi A, Tozzi V, Narciso P, Poccia F. An IL-15 dependent CD8 T cell response to selected HIV epitopes is related to viral control in early-treated HIV-infected subjects. Int J Immunopathol Pharmacol 2007; 20:473-485.

40. Ciprandi G, Vizzaccaro A, Cirillo I et al. Nasal eosinophils display the best correlation with symptoms, pulmonary function and inflammation in allergic rhinitis. Int Arch Allergy Immunol 2005; 136:266-72.

41. Ventura MT, Sanapo F, Calogiuri GF, Satriano F. Anaphylaxis induced by intramuscular betamethasone disodium phosphate: reflections on a clinical case. Int J Immunopathol Pharmacol 2007; 20:387-392.

42. Garbuglia AR, Grasso F, Donà MG, Mochi S, Conti P, De Lutiis MA, Giorgi C, Iezzi T. TTV infection: role of IFNs, IL-28 and IL-29 cytokines, antiviral proteins. Int J Immunopathol Pharmacol 2007; 20:249-258.

43. Ciprandi G, Cirillo I, Vizzaccaro A et al. Nasal obstruction in patients with seasonal allergic rhinitis: relationships between allergic inflammation and nasal airflow. Int Arch Allergy Immunol 2004; 134:34-40.

29. Juniper EF, Guyatt GH. Development and testing of a new measure of health status for clinical trials in rhinoconjunctivitis. Clin Exp Allergy 1991; 21:77-83.

30. Ellis AK, Keith PK. Non-allergic rhinitis with eosinophilia syndrome. Curr Allergy Asthma Rep 2006; 6:215-20.

31. Newhall KK, McGrath KG. Non-allergic rhinitis. Allergy Asthma Proc 2004; 25:S13-5.

32. Settipane RA. Rhinitis: a dose of epidemiological reality. Allergy Asthma Proc 2003; 24:147-54.

33. Leone C, Teodoro C, Pelucchi A et al. Bronchial responsiveness and airway inflammation in patients with non-allergic rhinitis with eosinophilia syndrome. J Allergy Clin Immunol 1997; 100:775–780.

34. Zhu W, Mantione KJ, Kream RM, Cadet P, Stefano GB. Cholinergic regulation of morphine release from human white blood cells: evidence for a novel nicotinic receptor via pharmacological and microarray analysis. Int J Immunopathol Pharmacol 2007; 30:229-238.


36. di Lorenzo L, Vacca A, Corfiati M, Lovreglio P, Soleo L. Evaluation of tumor necrosis factor-alpha and granulocyte colony-stimulating factor serum levels in lead-exposed smoker workers. Int J Immunopathol Pharmacol 2007; 20:239-247.

37. Powe DG, Huskisson RS, Carney AS et al. Evidence





SUBJECTIVE AND PSYCHOPATHOLOGICAL RESPONSE IN PATIENTS UNDER DIFFERENT ANTIPSYCHOTIC TREATMENTS: ARE THERE DIFFERENCES IN REAL

CLINICAL PRACTICE?

R. POLLICE, A. TOMASSINI, M. MALAVOLTA, E. DI GIOVAMBATTISTA, L. VERNI, R. RONCONE, C.M. CONTI1 and M. CASACCHIA

Psychiatric Clinic, S.M.I.L.E., Department of Experimental Medicine, University of L’Aquila; 1Psychology Division, University of Chieti-Pescara, Chieti, Italy

Received January 17, 2008 – Accepted January 19, 2008

The aim of this study is to investigate whether subjective well-being in patients under treatment with typical (ATPs) and atypical antipsychotic (ATPsA) compounds can be compared with the improvement of psychopathological state and to verify if both variables correlate to adherence to treatment. We assessed 106 consecutive patients receiving ATPs or ATPsA in the University Psychiatric Ward of L’Aquila, according to DSM-IV diagnosis of Schizophrenia and Bipolar Disorder. Psychopathological state was assessed by Brief Psychiatric Rating Scale-4.0 version (BPRS), adherence to treatment and subjective well-being was assessed by Drug Attitude Inventory (DAI-10) and Subjective Well-being under Neuroleptics (SWN), respectively. BPRS and DAI-10 were administered on admission (T0) and at the end of recovery (T1). The subjects enrolled in this study were divided into 2 groups according to ATP prescribed. We observed an improvement of BPRS and SWN total scores in each group, and increasing scores in DAI-10, from admission to discharge, both in total samples and in each group. There were statistical differences between the patients receiving ATPs and those receving ATPsA regardindg the SWN total score and its different dimensions. This study emphasizes that patients receiving ATPsA show better subjective response compared with patients undergoing ATP treatment, although the adherence to pharmacotherapy and clinical improvement do not differ between the groups.

Mailing address: Rocco Pollice,Dept. of Experimental Medicine, University of L’Aquila,Via Vetoio, Loc. Coppito,67100 L’AquilaTel: ++39 0862368314 Fax: ++39 0862312104e-mail: [email protected]

Key-words: atypical antipsychotic, typical antipsychotic, compliance, subjective well-being, psychopathological state

Over the years many studies have been directed towards the development of antipsychotic drugs with higher efficacy and effectiveness on both positive and negative symptoms in order to keep the individual’s global functioning and reduce the long-term consequences of the disorder.

For decades conventional antipsychotic (ATPs) drugs (neuroleptics or traditional antipsychotics) have been the base for treatment of acute and chronic psychotic disorders. However, ATPs were

breakthrough therapies for the positive symptoms but were less effective in treating the negative symptoms (1). In addition, these drugs could produce significant side effects [e.g. tardive dyskinesia, extrapyramidal symptoms (EPS)].

The atypical antipsychotic drugs (ATPsA), introduced in the mid-1990s, include clozapine, olanzapine, quetiapine, risperidone, aripiprazole and amisulpiride. The term “atypical” refers to a class of drugs with a broad spectrum of neurotrasmittorial

Vol. 22, no. 1, 83-91 (2008)

84

activity (2), which, although different between the various agents, can be involved in blocking the serotonin and dopamine receptors in the SNC. Both these effects mediate the ability of ATPsA to act on both positive and negative symptoms and also affective symptoms. For these reasons this class is considered in the international guidelines as the “first choice” in the pharmacotherapy of psychotic disorders (3), with the exception of Clozapine because of the risks associated with its use (4).

In several studies the ATPsA, compared with ATPs, have proven effective in improving psychotic symptoms (5-8). These studies have often evaluated the efficacy of treatment with ATPsA in patients poorly responsive or non-responsive to an initial ATPs therapy (9). There was also a response in the first psychotic episode (10-11). Long term trials have shown that ATPsA compared to ATPs lead to a reduction in the rates of relapse and hospitalization in chronic psychotic patients (12-13).

This class of drugs has proven effective in mood and schizoaffective disorders (14) and in reducing schizophrenia affective symptoms (such as depression) (15). Moreover, risperidone, quetiapine and olanzapine have been shown to be effective either as combination therapy or as monotherapy for the treatment of bipolar mania. These agents have shown efficacy in maintenance therapy because they exhibited both anti-manic and anti-depressant effects (16).

Non-compliance contributes to the severity of psychotic disorder and is present in 80% of patients (17). The side effects associated with antipsychotic drugs, in particular EPS, seem to be related to a high rate of non-compliance. For this and other reasons, it was shown that the compliance is higher in treatment with ATPsA than conventional drugs. Recently, Putzhammer et al (18) suggested that under ATPs treatment, subjective well-being depends particularly on major side effects, whereas in atypically treated patients, it is mainly influenced by psychopathological status.

The aim of this study is to investigate whether subjective well-being in patients undergoing treatment with typical (ATPs) and atypical antipsychotic (ATPsA) drugs can be compared with the improvement of the psychopathological state and to verify if both variables correlate in different drug

compliance.


One hundred and six consecutive in-patients in the University Psychiatric Ward of L’Aquila, who met the Diagnostic and Statistical Manual of Mental Disorders- IV edition (DSM-IV) criteria for schizophrenic and bipolar disorders and who were receiving antipsychotic therapy, were assessed. All subjects gave written informed consent to participate in this study, as approved by the University Human Studies Committee.

Psychopathological state was assessed by the Brief Psychiatric Rating Scale-4.0 version (BPRS), subjective reaction and subjective well-being was assessed by the Drug Attitude Inventory (DAI-10) and the Subjective Well-being under Neuroleptics (SWN), respectively. BPRS and DAI-10 were administered on admission (T0) and at the end of recovery (T1).

The Italian version of BPRS is a validated and widely used psychometric scale (19). Severity of a total of 24 symptoms, grouped in 6 different domains, was evaluated using a 7-point rating scale ranging from 1 (not present) to 7 (extremely severe) to obtain an overall total score. High levels of inter-rater reliability between experienced (i.e. psychiatrists and psychologists) and inexperienced (i.e. medical and psychosocial rehabilitation students) operators were shown in previous trials.

The DAI is a self-report scale developed to assess subjective responses and attitudes of schizophrenic patients towards the maintenance of antipsychotic treatment. The original version of the scale consists of 30 items covering seven categories: subjective positive, subjective negative, health and illness, physician control, prevention, and harm. A shorter version consisting of 10 key items was subsequently developed (the DAI-10). These items are presented as self-report statements with which the patient agrees or disagrees. Each response is scored as +1 if correct or -1 if incorrect. The final score is the grand total of the positive and negative points. A positive total score means a positive subjective response. A negative total score means a negative subjective response. The DAI-10 is concise, easy to administer, and its psychometric properties are well established. The scale has been shown to have test-retest reliability, high internal consistency, and discriminant, predictive, and concurrent validity (20).

The SWN is a 38 item and 6 point Likert-type self-rating scale developed by Naber in 1995 for assessing the psycho-physical well-being of patients treated with neuroleptics. It examines the feelings arising from the treatment and the patient’s attitude toward treatment.

R. POLLICE ET AL.


Table 1. Patients� medication.

Type of Antipsychotic Number of patients Dose ( Mean±SD) Haloperidol 51 10.74±8.99 Quetiapine 20 487.5±239.45 Risperidone 20 3.65±2.11 Olanzapine 5 10±3.54 Clozapine 2 450±212.13 Amisulpiride 3 600±200 Aripiprazolo 5 12±2.74

Table II. SWN evaluation in total sample.

Mean ±SD(N=106)

SWN-total score 75.96±17.09SWN-mental functioning 14.82±4.27SWN-self control 14.96±3.92SWN-emotional regulation 15.45±4.21SWN-physical functioning 15.11±4.36SWN-social integration 15.71±3.83

Table III. Socio-demographic and clinical features in the two group evaluated (Mean ±SD).

ATPs Group (N=51)

ATPsAGroup(N=55)

t p

Age (years) 45.96±17.10 41.18±11.39 -1.38 NS Duration of disorder (years) 10.84±8.44 10.64±9.55 -0.12 NS Day of hospitalisation 16.74±9.90 15.47±10.66 -0.63 NS M/F 23/32 23/28 0.02* NS *Chi-quadro

Table IV. BPRS and DAI-10 evaluation in two group evaluated at times T0 and T1 (Mean ± SD).

ATPs Group (N=51)

ATPsAGroup(N=55)

t p

BPRS T0 55.41±9.76 48.91±12.80 -2.92 <.05 BPRS T1 33.96±5.08 32.94±5.32 -0.99 NS DAI-10 T0 -0.08±3.92 1.45±4.70 1.81 NS DAI-10 T1 3±3.12 4.96±3.56 3.0 <.05

Table 1. Patients’ medication.Table 1. Patients� medication.



Mean ±SD(N=106)



ATPs Group (N=51)

ATPsAGroup(N=55)

t p



ATPs Group (N=51)

ATPsAGroup(N=55)

t p






Mean ±SD(N=106)



ATPs Group (N=51)

ATPsAGroup(N=55)

t p



ATPs Group (N=51)

ATPsAGroup(N=55)

t p



*Chi-square




Mean ±SD(N=106)



ATPs Group (N=51)

ATPsAGroup(N=55)

t p



ATPs Group (N=51)

ATPsAGroup(N=55)

t p


Table IV. BPRS and DAI-10 total scores in two group evaluated at times T0 and T1 (Mean ± SD).

86

The original scale includes 38 items, but in 2001 Naber developed and validated a short form to 20 items, strongly related to the original one. The scale comprises 5 subscales: emotional regulation, mental functions, self-control, social and physical states. The items are clear, easy to understand and even patients with cognitive disorders are able to complete the questionnaire in 10-15 minutes (21-22).

Statistical analyses were performed using SPSS software (23). To compare demographic variables between the two groups, an independent sample t-test was used. The categorical variable (i.e. gender) was compared using the Pearson chi-square test. To assess correlations between dimension scores, Pearson Product Moment (r)

co-efficients were computed. All analyses yielding a p value of less than 0.05 were considered significant.

RESULTS

One hundred and six (46 men and 60 women) hospitalized patients meeting DSM-IV criteria for Schizophrenia (n=50) and Bipolar Disorder (n=56) were assessed. The mean age was 43.04±14.46. The mean duration of disorder was 10.74±8.99 years and the mean of days of hospitalisation was 16.08±10.27. Fifty-one patients underwent typical antipsychotic and 55 atypical antipsychotic therapy (Table I).

Table V. SWN evaluation in two group evaluated at T0 (Mean ± SD).

ATPs Group (N=51)

ATPsAGroup(N=55)

t p

SWN-total score 71.39±13.34 80.20±19.11 2.73 <.05 SWN-mental functioning 13.55±2.91 16±4.97 3.06 <.05 SWN-self control 14.02±3.45 15.84±4.14 2.44 <.05 SWN-emotional regulation 14.61±3.52 16.24±4.65 2.02 <.05 SWN-physical functioning 14.10±3.49 16.05±4.88 2.36 <.05 SWN-social integration 15.12±3.57 16.25±4.01 1.53 NS

Table VI. Correlations between evaluated variables in total sample.

Age (years)

Durationof

disorder(years)

Days of hospitalisation

DAI-10T0

BPRS T1

BPRS T0 .27* -.21* .51** DAI-10 T1 .60** SWN-total score -.23* -.24* -.37** SWN-mentalfunctioning

-.20* -.32**

SWN-self control -.21* -.30** -.22* SWN-emotionalregulation

-.24* -.30** -.36**

SWN-physicalfunctioning

-.21* -.37**

SWN-socialintegration

-.21*

*p<.05**p<.001



ATPs Group (N=51)

ATPsAGroup(N=55)

t p

SWN-total score 71.39±13.34 80.20±19.11 2.73 <.05 SWN-mental functioning 13.55±2.91 16±4.97 3.06 <.05 SWN-self control 14.02±3.45 15.84±4.14 2.44 <.05 SWN-emotional regulation 14.61±3.52 16.24±4.65 2.02 <.05 SWN-physical functioning 14.10±3.49 16.05±4.88 2.36 <.05 SWN-social integration 15.12±3.57 16.25±4.01 1.53 NS


Age (years)

Durationof

disorder(years)

Days of hospitalisation

DAI-10T0

BPRS T1

BPRS T0 .27* -.21* .51** DAI-10 T1 .60** SWN-total score -.23* -.24* -.37** SWN-mentalfunctioning

-.20* -.32**

SWN-self control -.21* -.30** -.22* SWN-emotionalregulation

-.24* -.30** -.36**

SWN-physicalfunctioning

-.21* -.37**

SWN-socialintegration

-.21*

*p<.05**p<.001


*p<.05**p<.001

R. POLLICE ET AL.


The BPRS evaluation in the total samples at the two times of evaluation is shown in Fig. 1. There is a statistically significant BPRS total score improvement (p<.001, t=14.79) at the end of recovery (T1) in respect to admission (T0).

The adherence to antipsychotic treatment in the total sample revealed by DAI-10 is shown in Fig. 2. The DAI-10 mean scores at T0 significantly differ from those at T1.

The SWN total sample assessed at T1 time in the total sample is shown in Table II.

The subjects enrolled in this study were divided into 2 groups according to the type of antipsychotic therapy prescribed: an ATPs group and an ATPsA group that included the subjects who assumed typical

and atypical antipsychotic medication, respectively. There was no significant statistical differences in sociodemographic and clinical features in the two groups (Table III).

Psychopathological evaluation showed statistically significant difference in BPRS at T0 (Table IV) between the two groups. BPRS at T0 was higher in the ATPs group than in the ATPsA one. DAI-10 mean score at T1 was higher in the ATPsA than in the ATPs group. There were no statistically significant differences in BPRS at T1 and DAI-10 at T0 between the two groups. The BPRS and DAI-10 assessment in the two groups at the two times of evaluation showed a statistically significant improvement in both scales (Fig. 3 and 4).

*

0

10

20

30

40

50

60

T0 T1

Fig. 1. BPRS evaluation in total sample at two times of evaluation.p<.001

*

012345678910

T0 T1

Fig. 2. DAI-10 evaluation in total sample at two time of evaluation.p<.001


*

0

10

20

30

40

50

60

T0 T1


*

012345678910

T0 T1



88

The ATPsA group rather than ATPs group obtained higher mean scores on SWN total score and all SWN dimensions, excepting social integration dimension (Table V).

Table VI shows the correlations between sociodemographic and clinical variables in total samples. The analysis of the correlations showed negative correlations between SWN total score and all SWN dimensions and BPRS at the T1 time and also showed negative correlations between SWN total score and self-control, emotional regulation dimensions and age. Moreover, negative correlations were observed between SWN self-control dimension and duration of disorder. Days of hospitalization showed significant negative correlations with SWN total score and all SWN dimension, except self-control and social integration, and positive correlation with BPRS at time T0. On the other hand, BPRS at T0 showed a negative correlation with DAI-10 at T0 and a positive one with BPRS at T1. Positive correlation between DAI-10 at T0 and DAI-10 at T1 was observed.

DISCUSSION

In 1983 Hogan et al. (24) coined the term “subjective answer” in order to indicate the subjective feelings of the patients under antipsychotic drug treatment. Later, Awad (25) highlighted that such answer could represent the subjective interpretation of the patients to the consequent physiological changes to the pharmacological administration. Moreover, the same Authors observed that the subjective answer to the treatment with antipsychotic drugs was independent of the associate-demographic conditions of the subject (26-29).

In our study subjects receiving both types of therapy had a good psychopathological response and a good adherence to therapy. However, a statistically significant trend towards better subjective response was observed in the group of patients who took ATPsA drugs. This data could be explained by the observation that the subjective response seems to be related to anti-dopaminergic mesolimbic activity of new antipsychotic drugs (30). The results obtained are clinically important, regardless of the pharmachodynamic mechanism. The subjective response to antipsychotic treatment is a prognostic

factor because it appears to be associated to compliance, quality of life, substance abuse and to suicidality (33-38).

The studies on subjective well-being perceived by patients treated with antipsychotic drugs are few. Only 13% of the studies on the effectiveness of antipsychotic drugs have investigated the subjective experience of patients to treatment (39-41). The limited research in this field can be attributed to a lack of a definition of the term “subjective well-being” or the belief that psychotic patients are unable to assess the subjective experience of treatment.

However, several studies have shown that patients are more sensitive to the advantages and disadvantages of the various antipsychotic agents (42-46). Some of these studies also indicate that there are often differences between the patients’ subjective experience and the psychiatrist’s clinical psychopathological evaluation (47-51). Recently, a study carried out with the help of single photon emission computerized tomography (SPECT) demonstrated a relationship between subjective well-being and antipsychotic D2 receptor occupation (52). There are also several suggestions that the subjective experience to treatment with antipsychotics is relevant to compliance (53-56).

In our study the subjective well-being evaluation shows a perception of greater well-being in patients treated with ATPsA, especially in mental and physical functioning, self-control and emotional regulation.

The most significant study result is the statistically significant negative correlation between the days of hospitalization and the SWN self-control subscale. Several studies have emphasized that a longer hospitalization does not give greater benefit than a shorter one regarding symptoms, social functioning in the community and the rate of re-hospitalisation (57). Our data should add that patients with psychotic disorders are not helped by long hospitalization, also from the point of view of subjective well-being. Therefore, for “acute” psychotic patients, whose psychotic symptoms respond quickly to antipsychotic treatment, a brief hospitalization seems to be more effective, possibly followed by treatment at a day-hospital, compared to long-term hospitalisation.

The data observed in our study highlight

R. POLLICE ET AL.


how the subjective response and subjective well-being of patients taking ATPsA are consistent with the response achieved with the objective psychopathological and clinical assessment. There were no significant differences detected between antipsychotic agents as regards the adherence to treatment or symptomatology improvement.

This study has a number of limitations including small sample size, lack of functional outcomes, lack of neuropsychological evaluation and quality of life assessment.

Furthermore, the design of an open-label study does not include randomization techniques and blinding of investigators to patient status, which may introduce selection bias. Nevertheless, large randomized, double-blind, placebo-controlled studies are needed to explore the differences and the value of subjective response to ATPs and ATPsA treatment in severe psychotic disorders.

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