Gene expression profiling in ethnic Malays with type 2 diabetes mellitus, with and without diabetic nephropathy

778 © 2011 Società Italiana di Nefrologia - ISSN 1121-8428

JN (2011; :06) 778-78924EPHROL

DOI:10.5301/JN.2011.6382

IntroductIon

End-stage renal disease (ESRD) among the elderly and in patients with diabetes is a major financial burden on the health care system in many developed countries (1). In Malaysia, diabetic nephropathy (DN) is the most common cause of ESRD among patients undergoing dialysis (2), and with the latest diabetes prevalence of 14.9% (3), will further increase the health care costs of treating DN.

AbstrAct

Background: Diabetic nephropathy (DN) is the most common cause of end-stage renal disease (ESRD) among type 2 diabetes mellitus patients (DM) in Malay-sia. This study used microarray analysis to determine the gene expression profiling in ethnic Malay patients with type 2 DM. Methods: A total of 312 patients were recruited; 25 were on dialysis due to ESRD, 128 were classified as normoalbuminuric, 93 as microalbuminuric and 66 as macroalbuminuric, based on urine albumin to crea-tinine ratio of <3.5, between 3.5 and 35 and ≥35 mg/mmol, respectively.Results: Microalbuminuria was associated with up- and down-regulation of 2,694 and 2,538 genes, re-spectively, while macroalbuminuria was associated with up-regulation of 2,520 genes and down-regula-tion of 2,920 genes. There was significant up-regula-tion of 1,135 genes and down-regulation of 908 genes in the ESRD samples. Thirty-seven significantly up-regulated genes and 40 down-regulated genes were commonly expressed in all 3 groups of patients with worsening of renal functions. Up-regulated genes included major histocompatibility complex (HLA-C), complement component 3a receptor 1 (C3AR1), solute carrier family 16, member 3 (SLC16A3) and solute car-

Gene expression profiling in ethnic Malays with type 2 diabetes mellitus, with and without diabetic nephropathy

ORIGINAL ARTICLE

1 Cardiovascular, Diabetes and Nutrition Research Centre, Institute for Medical Research, Kuala Lumpur - Malaysia

2 School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu - Malaysia

3 Department of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur - Malaysia

4 Penang Medical College, Malaysia, Penang - Malaysia5 Putrajaya Hospital, Putrajaya - Malaysia

Faradianna E. Lokman 1, Norhashimah A. Seman 1, Aziz al-Safi Ismail 2, Nor Azwany Yaacob 2, Norlaila Mustafa 3, Amir S.M. Khir 4, Zanariah Hussein 5, Wan Nazaimoon Wan Mohamud 1

rier family 9 (sodium/hydrogen exchanger) (SLC9A8). Consistently down-regulated genes included were bone morphogenetic phosphatase kinase (BMP2K), solute carrier family 12, member 1 (SLC12A1), solute carrier family 7 (SLC7A2), paternally expressed 10 (PEG10) and protein phosphatase 1 regulatory (inhibi-tor unit) (PPP1R1C). Conclusion: This study has identified several genes of interest, such as HLA-C, SLC16A3, SLC9A8, SLC12A1 and SLC7A2, that require verification of their roles as susceptibility genes for diabetic nephropathy in ethnic Malays with type 2 DM.

Key words: Diabetic nephropathy, Gene expression, Malay, Type 2 diabetes mellitus

779© 2011 Società Italiana di Nefrologia - ISSN 1121-8428

JN (2011; :06) 778-78924EPHROL

Individuals who had diabetes and developed progressive DN and/or ESRD were thought to have done so as a result of long-term chronic exposure to hyperglycemia (4). How-ever, there has been cumulative epidemiological evidence to suggest a role of genetic factors in the development and progression of DN (5, 6). Gene expression profiling on a genomic scale by microarray technology has become an important tool in uncovering the molecular basis of many biological processes (7). The method has been widely used in identifying genes that are up-regulated or down-regulated in DN patients, resulting in the identification of several new candidate disease susceptibility genes (8, 9). However, most of the studies carried out on the candidate genes associated with DN were completed largely in white (10), Korean (11) and Japanese (12) populations, as well as in animal models (13, 14). The objective of this current study was therefore to deter-mine the gene expression profiling in the Malay popula-tion with type 2 diabetes mellitus (DM), with or without renal impairment, using the microarray technology. The Malays belong to an ethnic group of Austronesians living predominantly in the Malay Peninsula and parts of Su-matra and Borneo Island, and in Malaysia, they make up about half of the total population.

subjects And methods

Subjects

Subjects were recruited from the university hospitals of Uni-versity Kebangsaan Malaysia and University Sains Malaysia, Putrajaya Hospital and Penang Medical College, Malaysia. Inclusion criteria for patient selection were ethnic Malay for at least 2 generations and having been diagnosed with type 2 DM for more than 6 years. After giving signed informed consent, participants underwent clinical and physical ex-aminations, and answered a set of health-related question-naires. The study was approved by the Medical Research Ethics Committee, Ministry of Health Malaysia and the re-spective ethics committees of each hospital.

Blood and urine collection

A total sample of 10 mL venous blood was drawn and trans-ferred into 2 ethylenediaminetetraacetic acid (EDTA) tubes. Blood samples were immediately transported at 4°C to the Institute for Medical Research or were processed on-site. Urine samples of about 10 to 20 mL were also collected from all patients except those with ESRD. The urine collect-

ed was aliquoted and kept frozen at −20°C until analyzed. The kidney status of subjects for both sexes was catego-rized based on urine albumin to creatinine ratio (ACR) as suggested by the American Diabetes Association (ADA) (15): normoalbuminuria (ACR <3.5 mg/mmol), microalbuminuria (ACR 3.5 to 35 mg/mmol) and macroalbuminuria (≥35 mg/mmol). No urine sample was collected from subjects who were on dialysis due to DN (ESRD).

RNA extraction and microarray analysis

The RNA was extracted from fresh blood using an RNA Extraction Kit (Qiagen, USA) according to the manufac-turer’s protocol, and quantified spectrophotometrically (Biophotometer Plus, Eppendorf, Germany). The 2-Cycle Eukaryotic Target Labeling Assay protocol was used for microarrays. Briefly, 100 ng of total RNA was required as the starting material to synthesize the complimenta-ry DNA (cDNA). T7-Oligo (dt) Promoter Primer was used in the second-strand cDNA synthesis to generate the double-stranded cDNA template containing T7 promoter sequences. After amplification and labeling using a bioti-nylated nucleotide analog/ribonucleotide mix in the sec-ond in vitro transcription (IVT) reaction, the labeled cRNA was cleaned, fragmented and hybridized to an Affymetrix GeneChip 1.0 ST array containing 28,869 transcripts. Mi-croarray hybridization was performed at 45°C with rota-tion for 16 hours (overnight) on an Affymetrix GeneChip Hybridization Oven (Affymetrix Inc., Santa Clara, CA, USA). The GeneChips were washed and stained on an Af-fymetrix Fluidics Station 450 (Affymetrix Inc., Santa Clara, CA, USA) then scanned on a GeneChip Scanner 3000 (Af-fymetrix Inc., Santa Clara, CA, USA).

Confirmation of array results by quantitative real-time polymerase chain reaction

HLA-C and BMP2K genes identified from the microarray analysis were selected for confirmation by quantitative real-time polymerase chain reaction (RT-PCR; Applied Biosystem 7300 Real-time PCR). The housekeeping gene used was human 18s rRNA. The sequences of oligonu-cleotide primer pairs and probes of selected genes were obtained from TaqMan (Applied Biosystem Inc., Foster City, CA, USA) (Tab. I). RNA was converted to cDNA by using an Advantaged RT-for-PCR kit (Clonetech, Moun-tain View, CA, USA). Amplification conditions used for RT-PCR were initiated at 50°C for 2 minutes and 95°C for 10 minutes, followed by 40 cycles at 95°C for 15 sec-onds and 60°C for 1 minutes.


Lokman et al: Diabetic nephropathy in Malays: gene profiles

Data analysis

Data analysis was carried out using the Partek Genomic Suite Software (St. Louis, MO, USA) and NettAfix (Affyme-trix Inc., Santa Clara, CA, USA). For the probe intensity values generated by the Affymetrix scanner, robust mul-tichip average (RMA) algorithm was used for normaliza-tion and statistical processing. Using the Partek Genomic software, 1-way analysis of variance (ANOVA) was per-formed to compare data between groups and to generate a list of differentially expressed genes. Only those genes

with p<0.05 and a false delivery rate (FDR) of less than 0.05 were considered.

results

A total of 312 Malay patients with type 2 DM agreed to par-ticipate in the study. Grouped according to their ACR status, there were 128 patients with normoalbuminuria, 93 patients with microalbuminuria and 66 patients with macroalbuminu-ria. Twenty-five patients were on dialysis due to DN (ESRD) (Tab. II). There was no age difference between the 4 groups,

TABLE I PRIMERS AND TAQMAN PROBE SEQUENCE

Gene Forward primer Reverse primer TaqMan probe Reporter

BMP2K5’-ACCTGAGGAGAGCC-TGTTGG-3’

5’-CTGATGTGGAGGG-TGCCATG-3’

5’-CCCTTCGGTGCCA-AGCCCTTCCAT-3’

FAM

HLA-C5’-CGGGAGACACAGA-AGTACAAGC-3’

5’GTCCTCGCTCTGGTTG-TAGTA-3’

5’-CGCAGGTTCCGCAG-GCTCACTCG-3’

FAM

Human 18s rRNA5’-GTTGATTAAGTCCC-TGCCCTTTG-3’

5’-AAGTTCGACCG-TCTTCTCAGC-3’

5’-ACACACCGCCCG-TCGCTACTACCG-3’

FAM

TABLE II BIOCHEMICAL PROFILES OF STUDY SUBJECTS

Normoalbuminuria Microalbuminuria Macroalbuminuria End-stage renal failure

Age, years 57 ± 9.7 57 ± 8.7 57 ± 10.5 57 ± 8.7

Number (male/female) 128 (52/76) 93 (60/33) 66 (39/27) 25 (11/14)

Disease duration, years 13 ± 6.4 16 ± 7.7 16 ± 7.1 16 ± 6.6

Systolic blood pressure, mm Hg 138 ± 21 144 ± 20 155 ± 31* 163 ± 34*

Diastolic blood pressure, mm Hg 76 ± 10 77 ± 11 79 ± 10 83 ± 14

HbA1c, % 6.8 ± 1.8 7.7 ± 2.0 8.6 ± 2.2 9.0 ± 2.3

Fasting glucose, mmol/L 7.4 ± 4.2 8.3 ± 6.3 9.4 ± 5.7 10.1 ± 3.2

*p<0.01, vs. normoalbuminuria.


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and although patients with renal impairment appeared to have a longer duration of diabetes, the mean was not signifi-cantly different from that of the normoalbuminuric patients.Using Partek Genomic Suite Software, a list of up- and down-regulated genes with >1.0-fold change was gener-ated. Results showed that microalbuminuria was associ-ated with the up- and down-regulation of 2,694 and 2,538 genes, respectively, while macroalbuminuria was associat-ed with up-regulation of 2,520 genes and down-regulation of 2,920 genes. A total of 1,135 genes were significantly up-regulated and 908 genes were significantly down-regu-lated in the ESRD samples.Compared with the gene expression data obtained from pa-tients with normoalbuminuria, a total of 37 significantly up-regulated genes (Tab. III) and 40 significantly down-regulat-ed genes (Tab. IV) were commonly expressed in all 3 groups of patients where some genes became either significantly more up- or down-regulated with worsening of renal func-tions. Among the significantly and consistently up-regulated genes were the major histocompatibility complex (HLA-C), complement component 3a receptor 1 (C3AR1), solute car-rier family 16, member 3 (SLC16A3) and solute carrier fam-ily 9 (sodium/hydrogen exchanger) (SLC9A8). Consistently down-regulated genes included bone morphogenetic phos-phatase kinase (BMP2K), solute carrier family 12, member 1

(SLC12A1), solute carrier family 7 (SLC7A2), paternally ex-pressed 10 (PEG10) and protein phosphatase 1 regulatory (inhibitor unit) (PPP1R1C). The validity and reliability of our microarray data was confirmed by RT-PCR where there was no difference in the gene expression patterns of HLA-C and BMP2K between the 2 methods (Fig. 1).

dIscussIon

Human leukocyte antigens (HLA) have been associated with increased risk of type 1 DM and microvascular dis-ease (16), including DN (4). Similarly in type 2 DM, there is now some evidence to support that ethnic variations in HLA, may contribute, in part, to the higher prevalence rates of diabetic renal disease seen in some populations (17, 18). While Pima Indians (19) and Nauruans (20) with type 2 DM were found to be associated with HLA-A2 and HLA-Bw22, respectively, Maori natives with type 2 DM and renal failure had increased HLA-B48 and HLA-B60 (21). In contrast, this present study found HLA-C to be significantly and consistently up-regulated in all patients with renal im-pairment. There is no doubt that more studies with larger sample sizes are needed to determine the importance and role of HLC-C as the susceptibility gene for DN in the Malay population.

Fig. 1 - Validation of microarray data by (RTPCR). RTPCR was used to validate expression ratios from the microarray hybrid-ization. Human 18srRNA was used as a housekeeping gene. Fold changes were obtained by calculating the ratio of the mean expression values from MI, MA and ESRD with N samples (p<0.01). BMP2K: Bone marrow phosphatase kinase 2; HLA: His-tocompatibility complex; ESRD = end-stage renal disease; HLA = histocompatibility complex; MA = macroalbuminuria; MI = microalbuminuria; N = normoalbuminuria.



TABLE III THIRTY-SEVEN MOST COMMONLY UP-REGULATED GENES IN PATIENTS WITH MICROALBUMINURIA (MI), MACROALBUMINURIA (MA) AND ESRD VERSUS NORMOALBUMINURIA (N)

Gene symbol Gene name

(MI vs. N) (MA vs. N) (ESRD vs. N)

Gene functionFold

changep Value

Fold change

p ValueFold

changep Value

C17orf37Chromosome 17 open reading frame 37

2.2 0.001 2.2 0.036 2.2 0.029 Selenium binding

C3AR1Complement component 3a receptor 1

3.3 0.024 3.3 0.005 3.4 0.010Rhodopsin-like receptor activity

CHMP4BChromatin-modi-fying protein 4B

1.1 0.01 1.2 0.014 1.2 0.007Maintenance of lens transparency

CKAP4Cytoskeleton-as-sociated protein 4

3.1 0.017 3.2 0.008 3.4 0.000

Epithelial cell receptor for antiproliferative factor

CLEC4EC-type lectin domain family 4, member E

1.3 0.015 1.4 0.009 1.6 0.003 Binding

CSF2RAColony-stimulating factor 2 receptor

1.3 0.003 1.2 0.033 1.3 0.047 Receptor activity

DMXL2 Dmx-like 2 2.2 0.038 2.4 0.006 2.4 0.043Translation initia-tion factor activity

DUSP23Dual specificity phosphatase 23

1.3 0.046 1.3 0.02 1.6 0.043Protein tyrosine phosphatase activity

FAM8A1Family with se-quence similarity 8, member A1

1.1 0.017 1.1 0.01 1.2 0.014 Unknown

FCGR1AFc fragment of IgG, high affinity Ia, receptor


FCGR3AFc fragment of IgG, low affinity IIIa, receptor


FLJ44635 TPT1-like protein 1.2 0.006 1.2 0.003 1.4 0.038 Unknown

to be continued


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GBP1 Guanylate binding protein 1 1.3 0.035 1.4 0.035 1.4 0.050 Nucleotide binding

GBP2Guanylate binding protein 2, interfe-ron-inducible

1.3 0.05 1.3 0.016 1.5 0.044 Nucleotide binding

GLIPR2GLI pathogenesis-related 2

1.3 0.009 1.3 0.013 1.3 0.050 Unknown

GPR125G protein-coupled receptor 125



1.3 0.004 1.3 0.003 1.3 0.030Rhodopsin-like receptor activity

HLA-CMajor histocom-patibility complex, class I, C

3.4 0.001 3.6 0.001 3.7 0.001MHC class I re-ceptor activity

HDCHistidine decarbo-xylase

2.1 0.04 2.1 0.013 2.2 0.018Histidine decarbo-xylase activity

IRAK3Interleukin-1 re-ceptor-associated kinase 3


KLHL22Kelch-like 22 (Dro-sophila)

2.1 0.029 2.1 0.01 2.1 0.013 Protein binding

LMO2LIM domain only 2 (rhombotin-like 1)

1.1 0.015 1.1 0.027 1.1 0.010 Protein binding

LOC645018Hypothetical LOC645018

1.1 0.046 1.2 0.001 1.4 0.022Structural consti-tuent of ribosome

MYADMMyeloid-associa-ted differentiation marker

2.3 0.001 2.3 0.007 2.4 0.008Physiological role during myeloid differentiation

PGAM1Phosphoglycerate mutase 1 (brain)

2.2 0.007 2.2 0.024 2.3 0.022Bisphosphogly-cerate mutase activity

PGAM1Phosphoglycerate mutase 1 (brain)


TABLE III CONTINUED



Gene functionFold

changep Value

Fold change

p ValueFold

changep Value

to be continued



PGAM4Phosphoglycerate mutase family member 4


PTP4A3Protein tyrosine pho-sphatase type IVA, member 3

2.1 0.042 2.2 0.024 2.3 0.003Prenylated protein tyrosine phospha-tase activity

RBM15BRNA binding motif protein 15B


SDCBPSyndecan-binding protein (syntenin)

1.1 0.008 1.2 0.013 1.2 0.037Interleukin-5 receptor binding

SDCCAG1Serologically defined colon cancer antigen 1

1.2 0.03 1.3 0.03 1.5 0.039 Unknown

SLC16A3Solute carrier family 16, member 3

2.3 0.021 2.3 0.007 2.5 0.013Transporter activity

SLC9A8Solute carrier family 9 (sodium/hydrogen exchanger)

2.2 0.032 2.2 0.015 2.3 0.033 Antiporter activity

SORT1 Sortilin 1 1.2 0.021 1.3 0.008 1.3 0.033 Receptor activity

SPATA6Spermatogenesis-associated 6

1.2 0.013 1.2 0.001 1.3 0.043Rab GTPase binding

SPTLC2Serine palmitoyltran-sferase, long chain base subunit 2

1.2 0.026 1.3 0.01 1.5 0.031Serine C-palmi-toyltransferase activity

TDRD7Tudor domain containing 7

1.2 0.016 1.3 0 1.2 0.043Nucleic acid binding

TPI1Triosephosphate isomerase 1

2.2 0.005 2.2 0.012 2.2 0.031Triose-phosphate isomerase activity

ESRD = end-stage renal disease.

TABLE III CONTINUED



Gene functionFold

changep Value

Fold change

p ValueFold

changep Value


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TABLE IV FORTY MOST COMMONLY DOWN-REGULATED GENES IN PATIENTS WITH MICROALBUMINURIA (MI), MACROAL-BUMINURIA (MA) AND ESRD VERSUS NORMOALBUMINURIA (N)



Gene functionFold

changep Value

Fold change

p ValueFold

changep Value

ALDH1B1Aldehyde dehydrogena-se 1 family, member B1

-2.1 0.006 -2.1 0.009 -2.1 0.01Aldehyde dehydroge-nase (NAD) activity

BEX5 BEX family member 5 -1.1 0.009 -1.2 0.001 -1.1 0.043Receptor-mediated si-gnaling and apoptosis

BMP2KBone morphogenetic phosphatase kinase 2

-2.9 0.001 -2.9 0.001 -3.2 0.001Skeletal development and patterning

BNIP1BCL2/adenovirus E1B 19kDa interacting protein 1

-3.1 0.034 -3.1 0 -3.6 0.022 Protein binding


-1.1 0.002 -1.1 0.049 -1.1 0.046 Unknown


-2.1 0.022 -2.1 0.022 -2.1 0.048 Unknown


-1.1 0.003 -1.1 0.008 -1.2 0.019 Unknown

CCNYL3 Cyclin Y-like 3 -1.1 0.027 -1.1 0.038 -1.1 0.047Mediate phospho-rylation of cellular proteins

CDCA8Cell division cycle asso-ciated 8

-1.1 0.017 -1.1 0.021 -1.1 0.024 Protein binding

DEFB106A Defensin, beta 106A -1.1 0.036 -1.2 0.032 -1.3 0.018 Defense response

DPH2DPH2 homolog (S. cerevisiae)

-1.1 0.013 -1.1 0.001 -1.1 0.022Diphthamide biosyn-thesis

FAM135BFamily with sequence similarity 135, member B

-1.1 0.003 -1.1 0.031 -1.2 0.047 Unknown

FAM138AFamily with sequence similarity 138, member A

-1.1 0.033 -1.1 0.011 -1.1 0.024 Retina protein

FAM138FFamily with sequence similarity 138, member F

-1.1 0.04 -1.1 0.012 -1.1 0.047 Retina protein

FANCBFanconi anemia, com-plementation group B

-1.1 0.028 -1.2 0.048 -1.2 0.016Repair of DNA damage

FBXO16 F-box protein 16 -1.1 0.015 -1.2 0.015 -1.5 0.047 DNA binding

to be continued



FRMD7FERM domain contai-ning 7

-1.2 0.043 -1.3 0.013 -1.5 0.012 Binding


-3.0 0.043 -3.2 0.017 -3.2 0.015Rhodopsin-like receptor activity

IGKV2-24Immunoglobulin kappa variable 2-24

-1.2 0.004 -1.6 0.001 -1.8 0.037 Unknown

IL1A Interleukin-1, alpha -1.1 0.049 -1.2 0.039 -1.4 0.019Signal transducer activity

KCNK2Potassium channel, subfamily K, member 2

-1.2 0.002 -1.2 0.014 -1.3 0.038 Ion channel activity

LARGE Like-glycosyltransferase -1.2 0.025 -1.3 0.01 -1.4 0.007Acetylglucosaminyl-transferase activity

LOC440742Hypothetical gene sup-ported by AK124614

-1.1 0.001 -1.1 0.008 -1.1 0.022 Unknown

LOC441931Putative G-protein coupled receptor

-1.0 0.018 -1.2 0.039 -1.3 0.036 Receptor activity

MGC26356Similar to zinc finger protein 595

-1.1 0.005 -1.1 0.019 -1.1 0.015DNA, metal ion and zinc ion binding

OR1S2Olfactory receptor, family 1, subfamily S, member 2


OR2T5Olfactory receptor, family 2, subfamily T, member 5


OR7G1Olfactory receptor, family 7, subfamily G, member 1


OR9A4Olfactory receptor, family 9, subfamily A, member 4


OR9G1Olfactory receptor, family 9, subfamily G, member 1


TABLE IV CONTINUED



Gene functionFold

changep Value

Fold change

p ValueFold

changep Value

to be continued


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Another group of differentially expressed genes identified in this study belongs to the solute-carrier gene (SLC) superfam-ily which encodes membrane-bound transporters that include passive transporters, symporters and antiporters, located in all cellular and organelle membranes (22). Mutation of these genes has been shown to be the cause of many human dis-eases (23). Polymorphisms in solute carrier family 12 member 3 (SLC12A3) have been associated with DN in Korean (24) and Japanese patients (25) with type 2 DM. In this present study, progression from normoalbuminuria to microalbuminuria or overt proteinuria and ESRD were associated with significant

up-regulation of SLC16A3 and SLC9A8 and down-regulation of SLC12A1 and SLC7A2. Further in-depth studies however are required to determine whether these could be candidate genes for DN susceptibility in the Malay population.On the other hand, despite the various limitations of this study, including the small sample size and the possibility of false-positive results due to multiple comparisons, our results were comparable to the findings by Guttula et al who studied genes in the peripheral blow cells of type 2 DM Asian Indians with DM (26). We also found significant down-regulation of PEG10 and PPP1R1C in all subjects with microalbuminuria,

OVGP1 Oviductal glycoprotein 1 -2.4 0.003 -2.5 0.007 -2.6 0.033 Catalytic activity

PEG10 Paternally expressed 10 -3.1 0.006 -3.2 0.001 -3.1 0.02 DNA binding

PPP1R1CProtein phosphatase 1, regulatory (inhibitor) subunit

-3.1 0.001 -3.1 0.038 -3.1 0.023Protein phosphatase inhibitor activity

RNASE9Ribonuclease, RNase A family, 9

-1.1 0.004 -1.1 0.014 -1.1 0.033 Nucleic acid binding

SLC12A1 Solute carrier family 12 -2.1 0.034 -2.1 0.012 -2.3 0.016 Transporter activity

SLC7A2 Solute carrier family 7 -2.1 0.014 -2.1 0.004 -2.1 0.021Basic amino acid transmembrane transporter activity

TTC39ATetratricopeptide repeat domain 39A

-1.1 0.009 -1.1 0.009 -1.1 0.036 Binding

TNIP3TNFAIP3 interacting protein 3

-2.1 0.013 -2.1 0.002 -2.2 0.005Regulation of immuni-ty and tissue homeo-stasis

ZNF23 Zinc finger protein 23 -1.1 0.002 -1.1 0.009 -1.1 0.007 Nucleic acid binding

ZNF354B Zinc finger protein 354B -1.0 0.003 -1.1 0.033 -1.1 0.007 DNA binding

ESRD = end-stage renal disease.

TABLE IV CONTINUED



Gene functionFold

changep Value

Fold change

p ValueFold

changep Value



macroalbuminuria or ESRD. The growth factor bone morpho-genetic protein 2 (BMP-2) was another gene that was found to be significantly down-regulated in our samples. BMP-2 has been shown to be down-regulated in the glomeruli from kidneys of patients with DN (8). Another significantly up-reg-ulated gene that may be worth further study was C3AR1. Ac-tivation of C3a anaphylatoxin through its G protein-coupled

receptor, C3aR, has been implicated as contributing to renal tubulointerstitial injury (27). Expression of C3AR1 was found to increase significantly in the kidneys of MRL/lpr lupus mice before the onset of renal disease, and it increased further as the disease progressed (13). There have been several genes proposed as good candi-dates for conferring susceptibility to DN. Among them were IGF-binding protein 1 (IGFBP1), carnosinase (CNDP1), apo-lipoprotein E (ApoE), angiotensin-converting enzyme (ACE) and superoxide dismutase 2 (SOD2) which were found to be significantly associated with DN in white (10, 28), Ko-rean (11) and Japanese populations (12). However, none of these genes were found to be significantly expressed in our cohort of Malay patients with type 2 DM. Type 2 DM is associated with insulin resistance, character-ized by reduced insulin-stimulated glucose transport activity in the skeletal muscle and adipose tissue (29). Several meta-bolic genes in various tissues have been proposed as con-tributing to the pathogenesis of insulin resistance, leading to development of type 2 DM and its complications including DN. As reported by Patti et al (30), there was a significant reduction in the expression of peroxisome proliferators-acti-vated receptor-γ coactivator 1-α and -β in the skeletal mus-cle of prediabetic and type 2 DM patients of Mexican-Amer-ican ethnicity. Further, by integrating the transcriptome data sets from studies of Mexican-American and white Swedish men (31), using human metabolic network reconstructions, insulin resistance and type 2 DM were shown to be associ-ated with several significantly differentially expressed me-tabolites from the tricarboxylic acid (TCA) cycle, oxidative

phosphorylation and lipid metabolism, as well as the highly connected reporter metabolites ATP/ADP and NAD+/NADH (32). These data would be particularly valuable in molecular and metabolic pathway studies, in particular, for identifica-tion of new therapeutic targets. One such good example has been the identification of peroxisome proliferator-activated receptors (PPARs) which are found expressed in various tis-sues such as adipose tissue, liver, heart as well as the kidney (33, 34). There is now increasing evidence to support the use of PPAR agonists not only as therapeutic agents for type 2 DM, obesity, hypertension, hyperlipidemia and atherosclero-sis, but also for DN (35). In conclusion, this study has identified several genes – in particular, HLA-C, SLC16A3, SLC9A8, SLC12A1 and SLC7A2 – with possible roles as susceptibility genes for DN in ethnic Malays with type 2 DM. There is no doubt that further research is needed to verify and confirm the clinical significance of these findings.

Acknowledgements

The authors wish to thank the Director General of Health Ma-laysia for his scientific comments during proposal writing and preparation of this manuscript as well as giving permission to publish these findings.

Financial support: This study, with code number 06-CAM-03, was

funded by the Ministry of Health, Malaysia.

Conflict of interest statement: None declared.

Address for correspondence: Wan Nazaimoon Wan Mohamud, PhDCardiovascular, Diabetes and Nutrition Research CentreInstitute for Medical ResearchJalan Pahang50588, Kuala Lumpur, [email protected]

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Accepted: December 27, 2010

Documents

Gene expression profiling in ethnic Malays with type 2 diabetes mellitus, with and without diabetic nephropathy