ISSN: 1524-4636 Copyright © 2008 American Heart Association. All rights reserved. Print ISSN: 1079-5642. Online
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DOI: 10.1161/ATVBAHA.108.176917 published online Oct 30, 2008; Arterioscler Thromb Vasc Biol
behalf of the EARSII Consortium and the HIFMECH Consortium Nicholas J. Wareham, Kay-Tee Khaw, Meena Kumari, Steve E. Humphries and onNicaud, Fotios Drenos, Jutta Palmen, Michael G. Marmot, S. Matthijs Boekholdt, Philippa J. Talmud, Melissa Smart, Edward Presswood, Jackie A. Cooper, Viviane
Postprandial Responses, and CHD Risk E40K and T266M. Effects on Plasma Triglyceride and HDL Levels,ANGPTL4
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ANGPTL4 E40K and T266MEffects on Plasma Triglyceride and HDL Levels, Postprandial Responses,
and CHD Risk
Philippa J. Talmud, Melissa Smart, Edward Presswood, Jackie A. Cooper, Viviane Nicaud,Fotios Drenos, Jutta Palmen, Michael G. Marmot, S. Matthijs Boekholdt, Nicholas J. Wareham,
Kay-Tee Khaw, Meena Kumari, Steve E. Humphries,on behalf of the EARSII Consortium and the HIFMECH Consortium
Background—Angiopoietin-like 4 is a dual-function protein: an inhibitor of LPL, influencing plasma triglycerides (TGs),with angiogenic properties. We examined the association of common ANGPTL4 variants with CHD traits and risk in5 studies (13 527 individuals).
Methods and Results—The effects on plasma lipids of 6 tagging SNPs and the recently identified E40K were examinedin a study of 2772 men. Only T266M (rs1044250, MAF�30%) and E40K (MAF�2%) were significantly associatedwith TG-lowering (�10.4%, P�0.004 and �20.4%, P�0.0001), respectively. T266M no longer showed significantassociations when K40 carriers (K40�) were excluded (P�0.2). Combining data from 5 studies confirmed theTG-lowering effect of K40� (weighted mean difference: �0.12 [95% CI �0.18, �0.05] mmol/L TG P�0.0001).Surprisingly, in the 3 prospective studies, the combined OR for CHD was 1.48 (1.11 to 1.96, P�0.007), independentof TG. In individuals with a paternal history of MI (n�332) T266M, but not E40K, showed effects on postprandial AUCTG and glucose (P�0.009 and P�0.017, respectively) compared to controls (n�370).
Conclusion—Although associated with an atheroprotective lipid profile, E40K was associated with increased CHD risk,suggesting Angptl4 influences parameters beyond lipid levels. T266M showed effects only under conditions ofpostprandial stress. The functionality of these potential “loss-of-function” variants needs validation. (ArteriosclerThromb Vasc Biol. 2008;28:2321-2327.)
Key Words: ANGPTL4 � LPL � inhibition � angiogenesis � E40K � T266M � postprandial responses
The angiopoietin-like proteins (Angptl) are a family ofsecreted proteins involved in energy metabolism which
share tertiary structural domains with angiopoietins, with anN-terminal coiled-coil domain and a fibrinogen-like C-Ter.1
Angptl4 is also known as hepatic fibrinogen angiogenic-related protein, fasting induced adipose factor, and PPARangiogenic related protein, and these names collectively giveinsight into the expression and function of the protein.Angptl4 expression under conditions of fasting increases inthe liver,2 in adipose tissue in certain mouse strains,3 and isespecially prominent in heart and skeletal muscle.4 Angptl4 isthus involved in the switch from fatty acids storage to�-oxidation and energy consumption.5 Angptl4 is cleavedproteolytically in plasma and circulates as N-Ter and C-Terfragments as well as the full length protein, with the N-Terand full length protein undergoing oligomerization.6 The
involvement in lipid metabolism was demonstrated by intra-venous injection of recombinant Angptl4 into mice, resultingin an increase in plasma TG levels attributable to lipoproteinlipase (LPL) inhibition.7 In vitro studies showed that theN-Ter domain is responsible for this, by acting as anunfolding molecular-chaperone, destabilizing the LPL activedimer to inactive monomer.8 The fibrinogen-like domain inangiopoietins bind Tie2 receptors, essential for angiogenicfunction, however Angptls do not bind Tie1 or Tie2 receptorsand as such are orphan ligands.9 Angptl4 has been suggestedto regulate angiogenesis,10 but depending on the experimentalsystem both a proangiogenic role, for example during ische-mia,11 and an antiangiogenic role, as in vascular permeability,12
have been reported. Yang et al recently showed that Angptl4C-Ter inhibits angiogenesis by inhibiting the basic FGF signal-ing cascade, thus suppressing the MAP kinase pathway.13
Original received July 8, 2008; final version accepted September 23, 2008.From the Division of Cardiovascular Genetics, Department of Medicine (P.J.T., M.S., E.P., J.A.C., F.D., J.P., S.E.H.), University College London
Medical School, UK; INSERM, UMR S 525 (V.N.), Paris, France; Universite Pierre et Marie Curie-Paris6 (V.N.), UMR S 525, Paris, France; theDepartment of Epidemiology and Public Health (M.G.M., M.K.), University College London, UK; the Department of Cardiology (S.M.B.), AcademicMedical Center, Amsterdam, The Netherlands; MRC Epidemiology Unit (M.N.W.), Institute of Metabolic Science, Cambridge, UK; and the Departmentof Public Health and Primary Care (K.-T.K.), University of Cambridge, UK.
Correspondence to Philippa J. Talmud, Division of Cardiovascular Genetics, Department of Medicine, University College London Medical School, 5University St, London WC1E 6JF, United Kingdom. E-mail [email protected]
© 2008 American Heart Association, Inc.
Arterioscler Thromb Vasc Biol is available at http://atvb.ahajournals.org DOI: 10.1161/ATVBAHA.108.176917
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To explore the effect of ANGPTL4 variation on lipidmetabolism we identified 6 tagging SNPs (tSNPs) thatcapture �92% of the variation at that locus and examinedtheir effects individually and as haplotypes on plasma lipidsin the prospective Northwick Park Heart Study II (NPHSII).14
A single cSNP, T266M (rs1044250), showed association withTG levels. Concurrently Romeo et al identified a singlecSNP, E40K, associated with lower TG levels, with effectsreplicated in 2 further studies.15 We have examined theassociation of T266M and E40K in a total of 13 527 individ-uals, participating in 3 prospective studies, an MI case-control study and an MI offspring study, to determine effectson plasma lipids, postprandial responses, and risk of CHD.
MethodsStudy PopulationsThe recruitment protocols and baseline characteristics of the 5studies have been extensively published before.16–20 Brief details aregiven in the supplemental Methods section (available online athttp://atvb.ahajournal.org). Tagging SNP Identification and genotyp-ing are presented in supplemental Methods. Details of tagging SNPPrimers and probes for TaqMan assays are presented in supplementalTable I.
Statistical AnalysesHardy-Weinberg equilibrium was assessed using chi-squared tests.Linkage disequilibrium (LD) as measured by D� was assessed usingHaploview (http://www.broad.mit.edu/mpg/haploview/). All analy-ses were performed on normally-distributed data after appropriatetransformation (log or square root). Results are presented as meanand standard deviation (SD) (or standard error of the mean [SEM] inTable 1). t tests and analysis of variance were used, where appro-priate, to compare the changes of the continuous variables across theSNPs categories. Haplotypes were inferred using THESIAS21 ex-cluding individuals with missing values, and differences in triglyc-eride by haplotype assessed assuming an additive model. The effectof genotype on risk in NPHSII was assessed by Cox proportionalhazards models. Age and classical CHD risk factors were included ascovariates and models were stratified by general practice. In HIFMECHconditional logistic regression models were used to take account of thematching for age and center. For EARSII because of the repeatmeasures the data were also analyzed by a repeated measuresanalysis of variance. Two-way analysis of variance for repeatedmeasures (SAS PROC GLM/repeated time) were run to test for theoverall significance of postprandial measurements over time andacross genotypes. Results were combined over studies and forestplots constructed using the “metan” command in Stata. The level of
statistical significance was taken as P�0.01. No adjustments weremade for multiple testing as this has been suggested to lead to errorsin interpretation.22
ResultsThe baseline characteristics of the 5 studies are presented inTable 1. Detailed tSNP and haplotype analysis were initiallycarried out in NPHSII alone. The baseline characteristics forNPHSII men, stratified by CHD status, are published else-where.23 Men who developed CHD during follow-up(n�273) were older, had higher plasma total cholesterollevels, triglycerides, blood pressure, and lower HDL-choles-terol levels and the prevalence of smoking was higher than inthose who remained CHD free (n�2499).
tSNP Frequencies and Association With LipidTraits and BMI in NPHSIISix tSNPs, which explained �92% of the genetic variationin ANGPTL4, were identified: rs4076317 (�207C�G),rs7255436 (3991A�C), rs1044250 (6959C�T, T266M),rs11672433 (9511A�G), rs7252574 (12574C�T), andrs1808536 (12651G�A) and genotyped in the study, togetherwith E40K.15 The genotype distributions of all SNPs did notdeviate from Hardy-Weinberg equilibrium (supplemental Ta-ble II). A map of ANGPTL4 is shown in supplemental Figure1, demonstrating strong LD across the gene.
Of the 7 SNPs examined, only T266M (rs1044250) andE40K showed significant associations with lipid traits (Table2). Results for the other tSNPs are presented in supplementalTables IIIa through IIIe. M266 showed a recessive associa-tion with plasma TG levels with MM homozygotes having10.4% lower TG levels (P�0.01) compared to men homozy-gous for the common allele. The effect of E40K was larger,showing a codominant effect with heterozygote men having20.4% lower TG levels (P�0.0001) and 10% higher HDL-Clevels (P�0.007), compared to EE homozygotes. NeitherSNP was associated with effects on body mass index (datanot shown). Seven haplotypes occurred at frequencies over2%, but only haplotype H6, with rare alleles of both T266Mand E40K (frequency 0.022), was associated with 34% lowerTG-levels (P�0.0004) and borderline significantly higherHDL-C levels (by 16% P�0.02) compared to the commonhaplotype H1 (frequency�0.30; supplemental Table IV). TG
Table 1. Baseline Characteristics (mean�SEM) of Participants in Northwick Park Heart Study II, WhitehallStudy II, Epic–Norfolk Case:Control Cohort, HIFMECH, and EARSII
NPHSII WHII EPIC HIFMECH EARSII
Study Type Prospective Prospective Cohort Case/Control Offspring
n 2772 5637 3289 1091 822
BMI, kg/m2 26.2 (3.4) 26.4 (4.1) 26.4 (3.5) 26.6 (3.3) 23.3 (0.1)
% male 100% 72.9% 63.8% 100% 100%
Age, y 56.1 (3.4) 60.9 (6.0) 64.8 (7.8) 51.6 (5.4) 22.9 (0.1)
Curr smoking 28.1% 12.4% 10.7% 23.7 (259) 26%
HDL, mmol/L 0.80 (0.24) 1.52 (0.42) 1.28 (0.36) � � � 1.19 (0.01)
LDL, mmol/L 3.99 (0.96) 3.53 (0.94) 4.07 (1.02) � � � 2.79 (0.03)
TG, mmol/L 1.79 (0.95) 1.21 (0.62) 1.75 (0.88) 1.63 (0.71) 0.97 (0.01)
Cholesterol, mmol/L 5.74 (1.01) 5.75 (1.02) 6.24 (1.15) 5.46 (1.08) 4.41 (0.03)
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levels associated with haplotype H2, which carries M266independent of K40 (frequency 0.28), did not differ signifi-cantly from the common haplotype. To examine furtherwhether T266M contributed to TG-lowering independent ofE40K, whole genotypes defined by T266M and E40K were
examined. Compared to the TG levels in EE/TT men(1.83�0.98 mmol/L), EK/TM and EK/MM men had 18.6%(1.49�0.83 mmol/L; P�0.0001) and 25% (1.38�0.66 mmol/L;P�0.0001) lower TGs. When E40K men were excluded fromthe reanalysis, there was no longer a significant associationbetween T266M and TG levels (P�0.29; Table 2). BecauseANGPTL4 expression is regulated by PPARs we examinedwhether these ANGPTL4 SNPs showed interaction withPPAR variants. Neither SNP showed significant evidence ofinteraction with PPARA SNPs L162V (rs1800206) and intron7G�C (rs4253778) or PPARG P12A (rs1801282), nor LPLS447X (rs328) on lipid levels. Nor was there evidence ofinteraction with smoking on TG levels (data not shown).E40K explained 0.8% of the variance and T266M 0.3% of thevariance in TG, and together explained 0.9% of the variancein plasma TG levels.
Frequency Distribution of E40K and T266MAcross Europe (HIFMECH and EARSII)Genotypes were in Hardy-Weinberg equilibrium by region,but with a significantly higher MAF frequency of both cSNPsin the Northern recruitment centers compared to the South inboth studies (supplemental Figure IIa and IIb).
Effects of E40K and T266M on Lipid Traits inall StudiesThe effect of both E40K and T266M on TG and HDL levelswas assessed in all studies. The association of E40K, repre-sented as a Forest plot examining the weighted mean differ-ence in TG and HDL levels in K40carriers (K40�) versusE40 homozygotes, showed a consistent effect for TG levelswith K40� having a lower weighted mean of �0.12 (95% CI�0.18,�0.05) mmol/L, P�0.0001 (Figure 1a). The effect onHDL was also consistent, with K40� having significantlyhigher weighted mean HDL levels 0.09 (95% CI 0.06 to 0.12)P�0.0001 (Figure 1b). To determine the effect of T266Mindependent of E40K, K40� were excluded from the analy-sis. In confirmation of results from NPHSII, T266M (-K40�)did not show a significant effect on TG or HDL levels overall(data not shown).
Association Between of T266M and E40K andRisk of Future CHDAs shown in Figure 2, E40K was consistently associated withCHD risk with a pooled OR of 1.48 (1.11 to 1.96) P�0.007
Weighted Mean diff.-.52 .52
Study Weighted Mean diff.(95% CI) EK vs EE
-0.10 (-0.19,-0.01)Whitehall-0.17 (-0.33,-0.01)EPIC-0.37 (-0.52,-0.22)NPHSII-0.17 (-0.43,0.09)HIFMECH N-0.03 (-0.40,0.34)HIFMECH S-0.13 (-0.27,0.01)EARSII
-0.16 (-0.22,-0.10) mmol/lOverall (95% CI)
Weighted Mean diff.-.16
Study Weighted Mean diff.(95% CI) EK vs EE
0.03 (-0.00,0.07)Whitehall
0.07 (0.00,0.13)EPIC
0.10 (0.03,0.16)NPHSII
0.09 (0.03,0.15)EARSII
0.06 (0.03,0.08) mmol/lOverall (95% CI)
.16
a
b
Figure 1. a, Forest plot of weighted mean TG level differencebetween EK carriers and EE homozygotes. Data are adjusted forage, BMI, and where appropriate center, case-control status,and gender. b, Forest plot of weighted mean HDL level differ-ence between EK carriers and EE homozygotes. Data areadjusted for age, BMI, and where appropriate center, case-control status, and gender.
Table 2. Association of T266M (rs1044250) and E40K With Lipid Levels in NPHSII Men
T266M E40K
TTn�1355
TMn�1108
MMn�262 P Value (ANOVA)
EEn�2505
EKn�107 P Value (t Test)
Cholesterol, mmol/L 5.77 (1.02) 5.72 (1.03) 5.69 (0.96) 0.31 5.75 (1.02) 5.56 (1.01) 0.06
Triglyceride,* mmol/L 1.83 (0.97) 1.81 (0.95) 1.64 (0.85) 0.01 1.81 (0.96) 1.44 (0.77) �0.0001
HDL,* mmol/L 0.80 (0.25) 0.80 (0.23) 0.82 (0.27) 0.60 0.80 (0.24) 0.88 (0.25) 0.007
LDL, mmol/L 4.04 (0.96) 3.94 (0.95) 4.00 (0.97) 0.12 4.00 (0.96) 3.91 (0.97) 0.45
After exclusion of K40 carriers TT n�1273 TM n�1273 MM n�211
Triglycerides* 1.83 (0.98) 1.82 (0.95) 1.72 (0.89) 0.29
*Geometric mean (approximate SD).
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for K40 carriers compared to E40 homozygotes, after adjust-ment for baseline TG levels, age, BMI, SBP, smoking, HDL,LDL and where appropriate gender. The effect of E40K onCHD risk is therefore independent of these classical riskfactors. After exclusion of K40 carriers, the pooled OR forT266M showed no significant association with CHD riskwith little consistency of effect (supplemental Figure III).
Association of T226M and E40K With BaselineLipids and Postprandial Responses in EARSIIThe association of the cSNPs with postprandial levels after anoral fat tolerance test (OFTT) and an oral glucose tolerancetest (OGTT) was examined in EARSII, where young men
were defined as “cases” on the basis of their father’s prematureMI and “controls” when their father had no premature MI. In therepeated measures analysis of variance, the interaction betweentime and T266M was P�0.10 for triglyceride after the OFTTand P�0.0003 for glucose after the OGTT. However there wasan interaction time*T266M*case-control status (P�0.023)with respect to triglyceride (Figure 3a). Further analyses wererun on AUC and peak of triglyceride and glucose in cases andcontrols separately. As shown in Figure 3a, there was asignificant genotype effect in cases, with M266 homozygousshowing the lowest AUC and peak TG measures (P�0.009and P�0.004, respectively). However, after further adjust-ment on fasting level, the significances were P�0.063 andP�0.033 respectively. After the glucose challenge, MMcases showed the lowest AUC glucose and peak glucosecompared to other genotypes (P�0.017 and P�0.001, re-spectively; Figure 3b). The significances were unchangedafter adjustment on fasting glucose value.
DiscussionThe principal findings of this study are a confirmation of astrong association of the E40K variant with lower TG levelsin over 13 000 individuals. There were equally robust andconsistent associations with higher HDL levels. However,despite these beneficial lipid associations we observed aborderline association of the K40 allele with increased CHDrisk, independent of effects on TG and HDL levels and ofother classical CHD risk factors. The association with mea-sures of lipid and glucose levels of T266M, independent of
Odds Ratio.5 1 2 3 4 5 6
Combined
NPHSII
EPIC
Whitehall
1.38 (1.05-1.80) p=0.02
Figure 2. Forest plot of the OR for CHD in the 3 prospectivestudies for E40K after adjustment for age, BMI, SBP, smoking,HDL, LDL, TG, and where appropriate gender and center.
0
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0 2 3 4 6Time (hours)
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TTTMMM
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AUC TG p=0.009AUC TG p=0.91
’sesaC‘’slortnoC‘
’sesaC‘’slortnoC‘
AUC Glu p=0.017AUC Glu p= 0.16
a
b
Figure 3. a, Area under the curve for triglycerides (SE) after the oral fat tolerance test in EARSII cases and controls by T266M geno-type. *P�0.05, **P�0.01, ***P�0.001. b, Area under curve for glucose (SE) after the oral fat tolerance test in EARSII cases and controlsby T266M genotype. *P�0.05, **P�0.01, ***P�0.001.
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the K40 allele, was only seen under conditions of postpran-dial stress.
Effect of ANPTL4 E40K on Baseline Lipid LevelsE40K is a rare variant and was reported to occur in only 1.3to 3.0% of whites. Heterozygotes had 12% to 27% lower TGlevels and homozygotes up to 56% lower TG levels comparedto common allele homozygotes, and there was a significantbut modest association with HDL levels.15 In the UK-basedstudies, NPHSII, WHII, and EPIC-Norfolk, E40K occurred ata similar frequency (1.6 to 2.0%) with up to 30% lower TGlevels and 31% higher HDL levels in the K40 homozygotes.E40K, however, had no effect on mean fasting glucose inWHII where fasting glucose was measured at three recalls(P�0.89, data not shown).
This cSNP showed a significant frequency gradient acrossEurope (HIFMECH), occurring at a frequency of 4.2% in theNorth and 1.5% in the South, a difference confirmed inEARSII.
A number of other genetic variants show similar frequencygradients across Europe, for example the APOE �4 allele,recently reviewed by Lao et al.24 The higher frequency of theK40 allele in the North compared to the South of Europe, andits association with increased CHD risk suggests that thisvariant might be contributing to the CHD gradient acrossEurope.
In EARSII, in the fasting state, E40K heterozygotes hadsignificantly higher HDL levels (8.5%, P�0.01) but TGswere similar, although the size of the effect in the heterozy-gous state was of a similar magnitude as reported (12%lowering) but showed only borderline statistical significance(P�0.09).
T266M, tSNPs, and Effects on Baseline Lipids andPostprandial ResponsesOf the initial 6 ANGPTL4 tSNPs identified, only T266M(rs1044250) showed a significant effect on TG levels, with a10% TG-lowering effect in NPHSII. However, the impact ofthis variant on plasma TG levels was small (R2�0.8%). Thisis comparable to that of the APOA5 S19W and �1131T�CSNPs, which together explain only 0.9% of the TG variancein NPHSII, whereas LPL S447X explains only 0.3% (Talmudand Cooper, unpublished data). This highlights the polygenicdetermination of TG levels, whereas diet is likely to play a fargreater role. Despite the fact that the tSNPs captured morethan 92% of the genetic variation in ANGPTL4, none of themshowed association with lipid levels and haplotype analysisprovided no additional TG-lowering effects other than thoseseen with the haplotype defined by both K40 and M266.However, whole genotype analysis of the 2 cSNPs showedonly a 5% difference in TG lowering in EK/TM mencompared to EK/TT men, when K40 carriers were removedfrom the analysis T266M no longer showed a significantassociation with lower TG levels. This suggests that the effectof this SNP on baseline TG levels was minimal and reflectedthe LD with E40K (D��1.0 and an R2�0.5). Thus E40K isacting as a marker or is itself the functional variant; this latterproposal is supported by the resequencing study,15 but func-tional studies are needed to verify this.
In EARSII, under the conditions of an oral fat load and anoral glucose load, those homozygous for the M266 showedbetter clearance of both TGs and glucose in the young menclassified as “cases,” on the basis of a family history ofpremature paternal MI. No significant genotype effect wasseen in the age and region matched “controls.” A similarcase:control heterogeneity of effect in EARSII was reportedfor the USF1 variants on glucose clearance,25 and togetherthese data highlight that even in these healthy young men, thegenotypes effect are influenced and magnified in those with afamily history of early MI. For E40K although a similar trendwas seen, this did not approach statistical significance.
These results, except for the postprandial responses, con-firm the findings of Staiger et al who examined 4 ANGPTL4SNPs (3 of them studied here, including T266M) and reportedthat none of them were associated with anthropometricmeasures, fasting or postprandial lipids, or a family history ofT2D.26
Although Angptl4 is induced in the fasting state it ispossible that the 2 cSNPs behave differently under fastingand fed conditions. These potential “loss-of-function” vari-ants are analogous to the angptl4 knock-out mice modelwhich delineated the role of angplt4 to TG clearance ratherthan production, in both fed and fasted state.27 The effect onglucose metabolism is less clear. Adenoviral overexpressionof Angptl4 improved glucose tolerance but led to lowerglucose levels while inducing hepatosteatosis.28 However,Mandard et al reported no effect on fasting glucose intransgenic mice, but impaired glucose tolerance after chronicfat feeding,29 which supports the results seen in EARSII withM266 showing better clearance after the OGTT than wild-type T266. Romeo et al, reported borderline effects of E40Kon fasting insulin levels but not glucose levels suggesting thatto see the predicted modest effects on fasting levels, verylarge studies will be needed.15
Effects of E40K and T266M on CHD RiskE40K, but not T266M, was associated with an unexpectedincrease in CHD risk, independent of lipid levels, with K40�showing a pooled OR for CHD of 1.38 (1.05-.80) P�0.02even after adjustment for TG levels, suggesting that theseeffects go beyond the association with TG, implicating theangiogenic properties of Angptl4.
Potential Impact of E40K and T266M onAngptl4 FunctionAngptl4 undergoes oligomerization promoted by disulphidebonds in the coiled-coil N-Ter forming variable sized multi-mers,6 which undergo proteolytic cleavage releasing aC-terminal fibrinogen domain which circulates as a stablemonomer.30 Both cleaved and full-length Angptl4 are presentin the plasma.31 These data suggest that the N-Ter coiled-coilmultimer and the monomeric C-Ter fibrinogen-like domainmay have distinct functions. It is now clear that inhibition ofLPL is mediated through the Angptl4 coiled-coil domain,which converts the active dimer to inactive monomer, de-scribed as an “unfolding molecular chaperone.”8 Both E40and T266 are conserved across human, mouse, and rat,6
supporting a potential functional role. E40 lies in the
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N-terminal coil-coil domain and may therefore participate inLPL inactivation with “loss-of –functio” K40 showing lessLPL-inhibition resulting in more TG hydrolysis and lowerTG levels. T266 is positioned in the C-Ter fibrinogendomain. Under baseline conditions the association M266 withTG-lowering appears to reflect LD with E40K. However,under conditions of stress and in the fed state, we speculatethat as part of the full-length Angptl4, it may influence LPLinhibition and might reflect differentially induced expressionin the fed compared to the fasted state.
The function of the C-terminal fibrinogen domain remainsunclear. It is stable in plasma as a monomer, and it has beensuggested that it may have angiogenic properties. It has nowbeen confirmed that Angptl4 inhibits angiogenesis by sup-pressing the Raf/MEK/extracellular signal regulated kinase(ERK) signaling cascade thus blocking bFGF-induced acti-vation of MAP kinase.13 In its full length form it is possiblethat E40K influences the angiogenic properties of the C-Ter,and as a loss of function mutation would reduce the suppres-sion of the Raf/MEK/ERK signaling pathway,13 thus promot-ing angiogenesis. Although angiogenesis may be protective,because vascular endothelial growth factor (VEGF) therapyin ischemic heart disease enhances the arterioprotectivefunctions of the endothelium,32 its antiprotective effects aredemonstrated by the fact that neovascularization promotesgrowth of the atherosclerotic lesion leading to plaque desta-bilization and rupture.33 Thus if we extrapolate this to areduction in Angptl4 inhibition, this could promote neovas-cularization and thus plaque instability.
In conclusion, the replication of the association of ANGPTL4variants with lower lipid levels, yet increased CHD risk inthese studies, places Angptl4 in an interesting position,potentially influencing parameters beyond lipid levels. How-ever, this study is not without its limitations. Although weanalyzed 4 large studies, clarification of the associations withglucose levels is necessary. The tSNP approach captures thelarge majority of genetic variation, and we can rule outcomprehensively the possibility that there are other commonamino acid variants which might be functional, although theremight be upstream variants in LD which affect the level ofgene expression. Clearly, confirmation of these results isneeded, together with in vitro studies of these 2 variants tovalidate their functionality.
AcknowledgmentsThe authors thank the participants, general practitioners, and staff inNPHSII and EPIC-NORFOLK.
Sources of FundingNPHSII was supported by MRC UK, US NIH (grant NHLBI 33014),and Du Pont Pharma, Wilmington, USA. EPIC-Norfolk is supportedby MRC UK and Cancer Research UK, with additional support fromthe EU, Stroke Association, British Heart Foundation (GrantPG2000/015), Department of Health, Food Standards Agency, andWellcome Trust. The Whitehall Study II is supported by MRC UK,BHF, Department of Health, NHLBI (Hl36310); NIA (AG13196),and John D. and Catherine T McArthur Foundation. The HIFMECHstudy was supported by the European Commission (BMH4-CT96-0272), the full list of investigators is presented in supplementalinformation. EARSII was supported by the European Community(EU-Biomed 2 BMG4-98 to 3324), the full list of participants is
presented in supplemental information. P.J.T., J.A.C., J.P., F.D., andS.E.H. are supported by BHF (PG2005/014). M.S. is supported by aUnilever/BBSRC Case studentship. M.G.M. is supported by anMRC professorship.
DisclosuresNone.
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Talmud et al ANGPTL4 E40K and T266M: Effects on Lipids and CHD 2327
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Supplement Material HIFMECH co-investigators: Anders Hamsten, Steve E. Humphries, Irène Juhan-Vague, Maurizio Margaglione, Giovanni di Minno, John Yudkin, Elena Tremoli.
EARS II Project Leader :
D. St. J. O'Reilly, UK
EARS II Project Management Group :
F. Cambien, France
G. De Backer, Belgium
D. St. J. O'Reilly, UK
M. Rosseneu, Belgium
J. Shepherd, UK
L. Tiret, France
The EARS II Group Collaborating Centres and their Associated Investigators :
Austria : H. J. Menzel, Institute for Medical Biology and Genetics, University of
Innsbruck, laboratory.
Belgium : G. De Backer, S. De Henauw, Department of Public Health, University of
Ghent, recruitment centre.
Belgium : M. Rosseneu, Laboratorium voor Lipoproteïne Chemie/Vakgroep
Biochemie, University of Ghent, laboratory.
Denmark : O. Faergeman, C. Gerdes, Medical Department I, Aarhus Amtssygehus,
Aarhus, recruitment centre.
Estonia : M. Saava, K. Aasvee, Department of Nutrition and Metabolism, Estonian
Institute of Cardiology, Tallinn, recruitment centre.
Finland : C. Ehnholm*, R. Elovainio**, J. Peräsalo, *National Public Health Institute,
**The Finnish Student Health Service, Helsinki, recruitment centre.
Finland : Y.A. Kesäniemi*, M.J. Savolainen*, P. Palomaa**, *Department of
Internal Medicine and Biocenter, Oulu, **The Finnish Student Health Service,
University of Oulu, recruitment centre.
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France : L. Tiret, V. Nicaud, O. Poirier, INSERM U525, Paris, EARS data centre,
laboratory.
France : S. Visvikis, Centre de Médecine Préventive, Nancy, laboratory.
France : J. C. Fruchart, J. Dallongeville, Service de Recherche sur les Lipoprotéines
et l'Athérosclérose (SERLIA), INSERM U325, Institut Pasteur, Lille, laboratory.
Germany : U. Beisiegel, C. Dingler, Medizinische Klinik Universitäts-Krankenhaus
Eppendorf, Hamburg, recruitment centre and laboratory.
Greece : G. Tsitouris, N. Papageorgakis, G. Kolovou, Department of Cardiology,
Evangelismos Hospital, Athens, recruitment centre.
Italy : E. Farinaro, Dept. of Medical Preventive Sciences, University "Frederico II" of
Naples,
recruitment centre.
The Netherlands : L. M. Havekes, IVVO-TNO Health Research, Gaubius Institute,
Leiden, laboratory.
Portugal : M. J. Halpern, J. Canena, Instituto Superior de Ciencas da Saude, Lisbon,
recruitment centre.
Spain : L. Masana, J. Ribalta, A. Jammoul, A. LaVille, Unitat Recerca Lipids,
University Rovira i Virgili, Reus, recruitment centre and laboratory.
Switzerland : F. Gutzwiller, B. Martin, Institute of Social and Preventive Medicine,
University of Zurich, recruitment centre and laboratory.
United Kingdom : D. St J. O'Reilly, M. Murphy, Institute of Biochemistry, Royal
Infirmary, Glasgow, recruitment centre and laboratory.
United Kingdom : S.E. Humphries, P.J. Talmud, V. Gudnason, R.M. Fisher,
University College London School of Medicine, London, laboratory.
United Kingdom : D. Stansbie, A.P. Day, M. Edgar, Department of Chemical
Pathology, Royal Infirmary, Bristol, recruitment centre and laboratory.
United Kingdom : F. Kee*, A. Evans**, *Northern Health and Social Services Board,
**Department of Epidemiology and Public Health, the Queen's University of Belfast,
Belfast, recruitment centre.
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Supplementary methods Northwick Park Heart Study II (NPHSII) 1: 3052 healthy men aged 50 to 61 years,
registered with 9 general medical practices, were recruited for prospective surveillance.
The study had full ethical approval with subjects giving informed consent. Repeat plasma
lipid measures were available for the first 5 years of the study. All men were free of CHD
on entry and CHD events taken as end points were fatal (sudden or not) and non-fatal MI,
plus coronary artery surgery and silent MI on the follow-up ECG. DNA was available on
2772 Caucasian men.
Whitehall II is a longitudinal study of 10,308 male and female British civil servants aged
35-852. All participants completed a self-administered health questionnaire and attended a
health-screening clinic at the time of enrolment into the study and follow-up. At phase 7
(2002-2004), 6156 participants gave consent for genetic studies. Data are used from 5666
participants who described themselves as ‘white’. Ethical approval was granted for the
study, and all participants provided written consent.
EPIC-Norfolk 3: Briefly, 25 663 healthy men and women, aged between 45 and 79 years,
were recruited from age–sex registers of general practices in Norfolk. The participants
completed a baseline questionnaire survey between 1993 and 1997, attended a clinic visit,
and were followed-up for an average of 6 years. Case ascertainment has been described
previously. Cases were those having fatal or nonfatal CAD during follow-up. All
individuals who reported a history of heart attack or stroke at the baseline visit were
excluded. Controls were subjects who remained free of cardiovascular disease during
follow-up. 2 controls were matched to each case by sex, age (within 5 years), and time of
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enrollment (within 3 months) 4. All individuals have been flagged for death certification at
the UK Office of National Statistics, with vital status ascertained for the entire cohort. In
addition, participants admitted to hospital were identified using their National Health
Service number by data linkage with the East Norfolk Health Authority database, which
identifies all hospital contacts throughout England and Wales for Norfolk residents. The
study was approved by the Norwich Health Authority Ethics Committee, and all
participants provided written informed consent.
Hypercoagulability and Impaired Fibrinolytic function MECHanisms (HIFMECH) 5:
Male, Caucasian, post-MI patients aged under 60 years (n=533) and age and region-
matched controls (n=575) were recruited from four centres representing the North and
South of Europe. Ethical approval was obtained in each centre.
European Atherosclerosis Research Study II (EARSII) 6: Participants were 18 - 28 year
old men recruited from universities in 11 European countries divided into 4 regions Baltic,
UK, Middle and South. Ethical approval was obtained from each Centre. ‘Cases’ were
classified on the basis of their father having an early myocardial infarction (MI) (pre- 55
years; cases n=407) and age-matched controls (n=415). Each participant undertook a
standard 100mg oral glucose tolerance test (OGTT) and a standardised oral fat tolerance
test (OFTT; 1493Kcal).
Tagging SNP identification and genotyping
ANGPTL4 tagging SNPs (tSNPs) were identified using the CHIP-Bioinformatics utility
(http://snpper.chip.org) with the International HapMap project database
(www.hapmap.org). Six ANGPTL4 tSNPs were identified (rs4076317, rs7255436,
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rs1044250, rs11672433, rs7252574, rs1808536). Rs1808536 was determined by
polymerase chain reaction (PCR) with sense (5’- ACCCACCAGAAGGAAACG -3’) and
anti-sense (5’- GTGGCACTGTATCCGGAATTG-3’) oligonucleotides and digested with
NlaIII (New England Biolabs) generating fragment sizes of 102/57bp in common
homozygotes, and 159bp in rare homozygotes. Fragments were resolved using Microtitre
Array Diagonal Gel Electrophoresis (MADGE) 7. Two negative controls were included in
each PCR run. All other SNPs including E40K (which has not as yet been given an rs
number) were genotyped using TaqMan technology (Applied Biosciences, ABI,
Warrington UK). Oligonucleotides and MGB probes are detailed in Supplementary Table
I.
SNP identification In identifying tSNPs Staiger et al initially covered the complete ANGPTL4 gene and 5kb
5’ and 2.5kb 3’ (17.75kb in total). In contrast we aimed to cover the variation in the gene
and 5kb upstream and downstream, a total of 20.25kb. Moreover, Staiger et al8 after using
the “solid spine of LD” mode within the HaploView software reduced the area they
wanted to examine from 17.75kb to a single 9kb LD block and only chose to tag the
variation within this 9kb Block. We, however, did not use this method as we wanted to
tag the total 20.25 region. Our tagging SNPs were identified from release 21, July 2006,
HapMap. A pairwise approach was adopted, with a MAF of >4% and r2 >0.8.
5 tagging SNPs were identified.
rs4076317
rs1044250
rs11672433
rs1808536
rs2278236: tagged rs7255436 and rs725274
A suitable working assay for rs2278236 could not be designed so we chose to genotype
both rs7255436 and rs725274. This resulted in the use of 6 tagging SNPs.
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A suitable working assay for rs2278236 could not be designed so we chose to genotype
both rs7255436 and rs725274. This resulted in the use of 6 tagging SNPs.
References
1. Miller GJ, Bauer KA, Barzegar S, Foley AJ, Mitchell JP, Cooper JA, Rosenberg RD.
The effects of quality and timing of venepuncture on markers of blood coagulation
in healthy middle-aged men. Thromb Haemost 1995;73:82-86.
2. Marmot MG, Smith GD, Stansfeld S, Patel C, North F, Head J, White I, Brunner E,
Feeney A. Health inequalities among British civil servants: the Whitehall II study.
Lancet 1991;337:1387-1393.
3. Day N, Oakes S, Luben R, Khaw KT, Bingham S, Welch A, Wareham N. EPIC-
Norfolk: study design and characteristics of the cohort. European Prospective
Investigation of Cancer. Br J Cancer 1999;80 Suppl 1:95-103.
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Samnegard A, Hawe E, Yudkin J, Margaglione M, Di Minno G, Hamsten A,
Humphries SE. Plasma thrombin-activatable fibrinolysis inhibitor antigen
concentration and genotype in relation to myocardial infarction in the north and
south of Europe. Arterioscler Thromb Vasc Biol 2002;22:867-873.
6. Tiret L, de Knijff P, Menzel HJ, Ehnholm C, Nicaud V, Havekes LM. ApoE
polymorphism and predisposition to coronary heart disease in youths of different
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European populations. The EARS Study. European Atherosclerosis Research Study.
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array diagonal gel electrophoresis (MADGE). Biotechniques 1995;19:830-835.
8. Staiger H, Machicao F, Werner R, Guirguis A, Weisser M, Stefan N, Fritsche A,
Haring HU. Genetic variation within the ANGPTL4 gene is not associated with
metabolic traits in white subjects at an increased risk for type 2 diabetes mellitus.
Metab 2008;57:637-643.
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Supplementary Table I Tagging SNP Primers and MGB probes used in NPHSII
rs number and
chr
position
Forward Primer Reverse Primer Probe 1 (VIC) Probe 2 (FAM)
rs4076317
chr19:8334999
ACCCCGCCTCCAAGACT CGCCCGAGGACGGTTTT CCCACTCCGCACCCA CCACTCGGCACCCA
rs7255436
chr19:8339196
GCTGGATTACAGGCATGAACCA GCCCCAGCGCATAGCA CCCATTCATCAAGTCT CCATTCCTCAAGTCT
rs1044250
chr19:8342164
CTGGCTGGGTCTGGAGAAG GCCAGGCGGCTGTTG CCCCCGTGATGCTA TCCCCCATGATGCTA
rs11672433
chr19:8344716
GGCAGAAGCTTAAGAAGGGAATCT GCCATGGGCTGGATCAACAT CTACTACCCACTGCAGGC ACCCGCTGCAGGC
rs7252574
chr19:8347779
CTGAGCCAGTGAAACCATGAAC GCGGTAAGTGTTCCAGCTCTT AAGGAAGAAACGCTGAACA AGGAAGAAACGTTGAACA
E40K
Chr19:8335323
TCGCCGCGCTTTGC CCGTGCGCCAGGACAT CCTGGGACGAGATGA CCTGGGACAAGATGA
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Supplementary Table II. Genotype distribution and allele frequencies of ANGPTL4 tSNP in NPHSII
rs number
Chr 19 position
rs4076317
8334999
promoter
C>G
E40K[13]
8335323
Exon 1
G>A
rs7255436
8339196
intron 3
A>C
rs1044250
8342164
exon 6
C>T
rs11672433
8344716
exon 7
A>G
rs725274
8347779
3’UTR
C>T
rs1808536
8347857
3’UTR
G>A
AA change E40K T266M P389P
Genotype
distribution
MAF
(95%CI) :
CC 1326
CG 1089
GG 262
0.30
(0.29-0.31)
GG 2505
GA 107
AA 0
0.02
(0.02-0.02)
AA 711
AC 1322
CC 655
0.49
(0.48-0.50)
CC 1355
CT 1108
TT 262
0.30
(0.29-0.31)
GG 1980
GA 677
AA 56
0.15
(0.14-0.16)
CC 665
CT 1341
TT 691
0.50
(0.49-0.52)
GG 1544
GA 664
AA 87
0.18
(0.17-0.19)
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Supplementary Tables III a-e Univariate analysis of seven ANGPTL4 tSNPs with mean (+SD) lipid levels and BMI in NPHSII
a
b.
rs7252574 CC N=655
CT N=1341
TT N=691
P value (ANOVA)
P value TT vs
CT/CC
Interaction with smoking
Cholesterol 5.73 (0.98)
5.74 (1.02)
5.73 (1.01)
0.98 0.85 0.74
Triglyceride* 1.76 (0.92)
1.85 (0.98)
1.75 (0.91)
0.04 0.12 0.39
HDL* 0.81 (0.25)
0.79 (0.24)
0.81 (0.24)
0.13 0.14 0.35
LDL
4.03 (0.92)
3.97 (0.96)
3.98 (0.97)
0.58 0.87 0.87
BMI*
26.3 (3.3)
26.2 (3.5)
26.3 (3.2)
0.86 0.67 0.56
rs4076317
CC N=1326
CG N=1089
GG N=262
P value (ANOVA)
P value GG vs. CG/CC
Interaction with smoking
Cholesterol 5.75 (1.02)
5.70 (1.02)
5.81 (0.99)
0.23 0.24 0.69
Triglyceride* 1.79 (0.95)
1.79 (0.95)
1.82 (0.96)
0.89 0.63 0.39
HDL* 0.80 (0.24)
0.80 (0.25)
0.82 (0.23)
0.67 0.38 0.46
LDL
4.02 (0.98)
3.92 (0.94)
4.09 (0.89)
0.04 0.13 0.70
BMI*
26.3 (3.4)
26.1 (3.4)
26.5 (3.5)
0.28 0.28 0.97
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c
d
rs1808536
GG N=1544
GA N=664
AA N=87
P value (ANOVA)
P value AA vs. GA/GG
Interaction with smoking
Cholesterol 5.72 (1.02)
5.77 (1.01)
5.74 (1.01)
0.62 0.93 0.07
Triglyceride* 1.78 (0.92)
1.83 (0.99)
1.71 (0.86)
0.37 0.42 0.37
HDL* 0.81 (0.24)
0.81 (0.24)
0.82 (0.23)
0.93 0.71 0.74
LDL
3.98 (0.94)
4.00 (0.97)
4.07 (0.94)
0.79 0.52 0.44
BMI*
26.3 (3.3)
26.2 (3.5)
26.4 (2.8)
0.83 0.70 0.27
rs11672433
CC N=1980
CT N=677
TT N=56
P value (ANOVA)
P value TT vs
CC/CT
Interaction with smoking
Cholesterol 5.73 (1.00)
5.75 (1.05)
5.88 (1.15)
0.56 0.31 0.26
Triglyceride* 1.77 (0.94)
1.85 (0.97)
2.07 (1.04)
0.03 0.04 0.55
HDL* 0.80 (0.24)
0.80 (0.24)
0.79 (0.22)
0.94 0.75 0.48
LDL
4.00 (0.94)
3.99 (0.99)
4.07 (1.09)
0.88 0.63 0.95
BMI*
26.2 (3.4)
26.4 (3.4)
26.7 (3.0)
0.34 0.33 0.82
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e
rs7255436
AA N=711
AC N=1322
CC N=655
P value (ANOVA)
P value CC vs
AC/AA
Interaction with
smoking Cholesterol 5.74
(1.03) 5.74
(1.03) 5.74
(0.98) 0.999 0.96 0.76
Triglyceride* 1.77 (0.91)
1.84 (0.98)
1.77 (0.93)
0.14 0.27 0.38
HDL* 0.81 (0.24)
0.79 (0.24)
0.81 (0.25)
0.12 0.38 0.18
LDL
3.99 (0.98)
3.98 (0.96)
4.03 (0.92)
0.63 0.34 0.87
BMI*
26.3 (3.3)
26.2 (3.5)
26.3 (3.3)
0.86 0.93 0.53
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Supplementary Table IV. Association of ANGPTL4 haplotypes with plasma triglyceride and HDL levels in NPHSII as analysed using
THESIAS
Order of SNPs: rs4076317(-207C>G), E40K (118G>A), rs7255436 (3991A>C) rs1044250 (T266M; 6959C>T) , rs11672433(9511A>G),
rs725274(12,574C>T), rs1808536 (12,651 G>A)
*geometric means for triglyceride [95% CI] for two copies of the haplotype
Haplotype Frequency (
number)
Triglyceride* P value HDL-C* P value
GGCCACG
CGATATG
CGCCACA
CGACGTG
CGACATG
CAATATG
CGCCACG
0.30 (1201) 0.28 (1137) 0.16 (671) 0.14 (590) 0.05 (218) 0.022 (87) 0.021 (83)
1.86 [1.76 – 1.95]
1.75 [1.65 – 1.85]
1.76 [1.63 – 1.90]
1.97 [1.80 – 2.15]
1.75 [1.51 – 2.03]
1.23 [0.98 – 1.53]
1.89 [1.53 – 2.33]
-
0.14
0.26
0.31
0.47
0.0004
0.89
0.81 [0.78 – 0.84]
0.81 [0.78 – 0.84]
0.83 [0.78 – 0.87]
0.79 [0.75 – 0.85]
0.75 [0.68 – 0.83]
0.94 [0.79 – 1.11]
0.69 [0.59 – 0.78]
-
0.97
0.56
0.70
0.19
0.10
0.02
Global p value
P=0.01 0.10
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Supplementary Figure ISupplementary Figure IMap of ANGPTL4 showing the position of the SNPsstudies and the HaploView map showing the LD across the region.
E40K
rs40
7631
7
rs72
5543
6
rs10
4425
0
rs11
6724
33
rs72
5257
4
rs18
0853
6
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Supplementary Figure II: Minor allele frequency (95%CI) across regions in the EARSII study for E40K (a) and T266M (b).
E40K 0 0
a
0.0
0.03
0.04
0.05
MA
F
South vs rest p=0.08 p<0.0005
0
0.01
2
Baltic South
UK Middle SouthNorth
EARSII HIFMECH
T266Mb T266M
0 40.60.8
p<0.001Across regions p=0.006
F
00.20.4
Baltic UK MiddleSouth North South
MA
F
EARSII HIFMECH
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Supplementary Figure III: Forest plot of the OR for CHD in the three prospective studies for T266M (excluding E40K carriers)prospective studies for T266M (excluding E40K carriers)
EPIC
Whitehall
NPHSII
Combined 0.98 (0.69-1.40) p=0.92
Odds Ratio.5 1 2 3 4 5 6
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