Genetic Determinants of Major Blood Lipids in Pakistanis Compared With Europeanscircgenetics.ahajournals.org/content/circcvg/3/4/348... · Genetic Determinants of Major Blood Lipids

Genetic Determinants of Major Blood Lipids in PakistanisCompared With Europeans

Danish Saleheen, MBBS, MPhil; Nicole Soranzo, BSc, PhD; Asif Rasheed, MBBS;Hubert Scharnagl, PhD; Rhian Gwilliam, PhD; Myriam Alexander, MSc, MPhil; Michael Inouye, PhD;Moazzam Zaidi, MBBS; Simon Potter, PhD; Philip Haycock, MSc, MPhil; Suzanna Bumpstead, BSc;

Stephen Kaptoge, PhD; Emanuele Di Angelantonio, MD, MSc, PhD;Nadeem Sarwar, MRPharmS, PhD; Sarah E. Hunt, PhD; Nasir Sheikh, MSc; Nabi Shah, B-Pharmacy;

Maria Samuel, BSc, MSc; Shajjia Razi Haider, MSc; Muhammed Murtaza, MBBS;Alexander Thompson, PhD; Reeta Gobin, MBBS, MPhil; Adam Butterworth, PhD, MSc;

Usman Ahmad, MBBS; Abdul Hakeem, MBBS; Khan Shah Zaman, MBBS, MRCP, FRCP, MRCS;Assadullah Kundi, MBBS, FCPS; Zia Yaqoob, MBBS, FACC; Liaquat Ali Cheema, MBBS, PhD;

Nadeem Qamar, MBBS, FACC; Azhar Faruqui, FACC, FRCP, FCPS, FAHA;Nadeem Hayat Mallick, MBBS, MRCP; Muhammad Azhar, MBBS, MRCP; Abdus Samad, MD, FACC;

Muhammad Ishaq, MBBS, MRCP, FRCP, FACC; Syed Zahed Rasheed, MD, FESC, FRCP;Rashid Jooma, MBBS; Jawaid Hassan Niazi, MBBS, FCPS; Ali Raza Gardezi, MBBS, MRCP;

Nazir Ahmed Memon, MBBS, FRCP, FACC, FACVS; Abdul Ghaffar, MBBS, FCPS;Fazal-ur Rehman, MBBS; Michael Marcus Hoffmann, PhD; Wilfried Renner, PhD; Marcus E. Kleber, PhD;

Tanja B. Grammer, MD; Jonathon Stephens, BSc; Anthony Attwood; Kerstin Koch, PhD;Mustafa Hussain, MBBS; Kishore Kumar, MBBS; Asim Saleem, MBBS; Kishwar Kumar, MBBS;

Muhammad Salman Daood, MBBS; Aftab Alam Gul, MBBS; Shahid Abbas, MBBS; Junaid Zafar, MBBS;Faisal Shahid, MBBS; Shahzad Majeed Bhatti, MBBS; Syed Saadat Ali, MBBS;

Muhammad Fahim, MBBS; Gurdeep Sagoo, BSc, MSc, PhD; Sarah Bray, MA, PhD;Ralph McGinnis, PhD; Frank Dudbridge, PhD; Bernhard R. Winkelmann, PhD; Bernhard Boehm, MD, PhD;

Simon Thompson, DSc; Willem Ouwehand, MD, PhD, FRCPath; Winfried Marz, MD;Philippe Frossard, PhD, DSc; John Danesh, DPhil, FRCP, FFPH; Panos Deloukas, PhD

Background—Evidence is sparse about the genetic determinants of major lipids in Pakistanis.Methods and Results—Variants (n�45 000) across 2000 genes were assessed in 3200 Pakistanis and compared with 2450

Germans using the same gene array and similar lipid assays. We also did a meta-analysis of selected lipid-relatedvariants in Europeans. Pakistani genetic architecture was distinct from that of several ethnic groups represented ininternational reference samples. Forty-one variants at 14 loci were significantly associated with levels of HDL-C,

Received September 3, 2009; accepted May 5, 2010.From the Center for Non-Communicable Diseases (D.S., A.F., M.Z., N.Shah, M.S., S.R.H., M.M., U.A., K.Kumar, A.H., M.H., A.S., Kishore Kumar,

Kishwar Kumar, M.S.D., A.A.G., S.S., J.Z., F.S., S.M.B., S.S.A., S.M.B., S.S.Ali, M.F., P.F.) Karachi, Pakistan; Department of Public Health and PrimaryCare (D.S., M.A., P.H., S.K., E.D.A., N.Sarwar, N.Sheikh, A.T., R.G., A.B., J.D.), University of Cambridge, United Kingdom; Wellcome Trust SangerInstitute (N.S., R.G., M.I., S.P., S.B., P.D., S.E.H., R.G.), Hinxton, Cambridge, United Kingdom; Department of Twin Research and GeneticEpidemiology (N.S., W.O.), King’s College London, St Thomas’ Hospital Campus, London, United Kingdom; Clinical Institute of Medical and ChemicalLaboratory Diagnostics (H.S., W.R.), Medical University Graz, Graz, Austria; National Institute of Cardiovascular Diseases (K.S.Z., A.K., Z.Y., L.A.C.,N.Q., A.F.), Karachi, Pakistan; Punjab Institute of Cardiology (N.H., M.A.), Lahore, Pakistan; Karachi Institute of Heart Diseases (A.S., M.I., S.Z.R.),Karachi, Pakistan; Jinnah Postgraduate Medical Centre (R.J., J.H.N.), Karachi, Pakistan; Multan Institute of Cardiology (A.R.G.), Multan, Pakistan; CivilHospital (N.A.M., A.G.), Hyderabad, Pakistan; Red Crescent Institute of Cardiology (F.u.R.), Hyderabad, Pakistan; Division of Clinical Chemistry(M.M.H.), Department of Medicine, Albert Ludwig University, Freiburg Germany; LURIC Nonprofit LLC (M.E.K.), Freiburg, Germany; Synlab Centerof Laboratory Diagnostics Heidelberg (T.B.G., W.M.), Heidelberg, Germany; Department of Haematology (J.S., A.A., W.O., K.Koch), University ofCambridge and NHS Blood and Transplant, Cambridge, United Kingdom; PHG Foundation (G.S.), Strangeways Research Laboratories, United Kingdom;MRC Biostatistics Unit (S.B., F.D., S.T.), Cambridge, United Kingdom; Division of Endocrinology and Diabetes and Institute of Public Health (B.R.W.,W.M.), Social Medicine and Epidemiology, Medical Faculty Mannheim, University of Heidelberg, Germany, Graduate School Molecular Endocrinologyand Diabetes, University of Ulm, Ulm Germany; and Cardiology Group Frankfurt (B.B.), Frankfurt, Germany.

Drs Saleheen, Soranzo, Danesh, and Deloukas contributed equally to this work.The online-only Data Supplement is available at http://circgenetics.ahajournals.org/cgi/content/full/CIRCGENETICS.109.906180/DC1.Correspondence to Danish Saleheen, MBBS, Center for Non-Communicable Diseases (CNCD), Karachi, Pakistan, and Department of Public Health

and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge CB1 8RN, UK. E-mail [email protected]© 2010 American Heart Association, Inc.

Circ Cardiovasc Genet is available at http://circgenetics.ahajournals.org DOI: 10.1161/CIRCGENETICS.109.906180

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triglyceride, or LDL-C. The most significant lipid-related variants identified among Pakistanis corresponded to genespreviously shown to be relevant to Europeans, such as CETP associated with HDL-C levels (rs711752; P�10�13),APOA5/ZNF259 (rs651821; P�10�13) and GCKR (rs1260326; P�10�13) with triglyceride levels; and CELSR2 variantswith LDL-C levels (rs646776; P�10�9). For Pakistanis, these 41 variants explained 6.2%, 7.1%, and 0.9% of thevariation in HDL-C, triglyceride, and LDL-C, respectively. Compared with Europeans, the allele frequency of rs662799in APOA5 among Pakistanis was higher and its impact on triglyceride concentration was greater (P-value for difference�10�4).

Conclusions—Several lipid-related genetic variants are common to Pakistanis and Europeans, though they explain only amodest proportion of population variation in lipid concentration. Allelic frequencies and effect sizes of lipid-relatedvariants can differ between Pakistanis and Europeans. (Circ Cardiovasc Genet. 2010;3:348-357.)

Key Words: lipids � HDL-C � LDL-C � triglyceride � Pakistan � gene � population structure � GWAS� IBC-array � meta-analysis

Levels of major blood lipids—that is, concentrations oflow- and high-density lipoprotein cholesterol (LDL-C and

HDL-C) and triglyceride—are each strongly, log-linearly, andpositively (or, in the case of HDL-C, inversely) associated withthe risk of coronary heart disease (CHD).1,2 Linkage and twinbased studies suggest that more than 50% of the variation inthese circulating lipids is determined by genetic factors.3–5

Several genetic variants have been established in the regula-tion of lipid metabolism in people of European continentalancestry, including 40 genomic loci (represented by 152SNPs) identified in genome-wide association studies.5–16 Incontrast with considerable evidence available on people ofEuropean ancestry, data on genetic regulation of major bloodlipids in Pakistanis are limited. For example, the previouslargest relevant study reported on 5 genetic markers inrelation to a few hundred participants.17

Clinical Perspective on p 357We report the first large-scale study of the genetic deter-

minants of LDL-C, HDL-C and triglyceride concentrations inpeople living in Pakistan, a country of �180 million peoplewith a high burden of cardiovascular disease. We haveassayed over 45 000 single nucleotide polymorphisms (SNPs)across 2000 candidate genes using the ITMAT-Broad-CARe(IBC) array18 in 3200 participants from the Pakistan Risk ofMyocardial Infarction Study (PROMIS).19 We comparedassociation signals observed in PROMIS with those in 2450participants of German ancestry from the Ludwigshafen Riskand Cardiovascular Health (LURIC) prospective study, whichused the same gene array.20 To place the German findings inthe context of data from other populations of Europeanancestry, we did a meta-analysis of published studies.

Materials and MethodsParticipantsThis report follows the reporting recommendations of STREGA.21

PROMIS is a case-control study of acute myocardial infarction (MI)in 6 centers in urban Pakistan.20 MI cases had symptoms within 24hours of hospital presentation, typical ECG changes, and a positivetroponin-I test. Control subjects were individuals without a history ofcardiovascular disease. They were frequency-matched to cases bysex and age (in 5-year bands) and concurrently identified in the samehospitals as index cases because they were either (1) visitors ofpatients attending the outpatient department, (2) patients attendingthe outpatient department for routine noncardiac complaints, or (3)

non–blood-related visitors of index MI cases. People with recentillnesses or infections were not eligible. Information was recorded onpersonal and parental ethnicity, spoken language, dietary intake,lifestyle factors, and other characteristics. Nonfasting blood samples(with the time since last meal recorded) were drawn from eachparticipant and centrifuged within 45 minutes of venepuncture.Serum samples were stored at �80°C. Total cholesterol, HDL-C,and triglyceride concentrations were measured using enzymaticmethods (Roche Diagnostics, USA) at the Center for Non-Communicable Diseases, Pakistan. LDL-C concentration was calcu-lated using the Friedewald formula.22

LURIC is a prospective study of cardiovascular death in individ-uals of German ancestry resident in southwest Germany whounderwent elective coronary angiography and left ventriculographybetween June 1997 and January 2000.21 CHD in the current analyseswas defined by troponin-confirmed MI (ie, acute ST- or non–ST elevation MI or based on past medical records) or presence ofvisible luminal narrowing of �50% in at least 1 coronary vessel.Individuals with �20% but �50% stenosis were excluded from theanalyses. Individuals with stenosis �20% were regarded as controlsubjects. Fasting blood samples collected before angiography werekept frozen at �80°C between the day of blood draw and the day ofanalysis for total cholesterol, HDL-C and triglycerides (alldetermined enzymatically).

The studies were approved by relevant ethics committees, andparticipants gave informed consent.

GenotypingAll genotyping was performed at the Wellcome Trust SangerInstitute using the “IBC” array of about 2000 candidate genes.18

Variants on the array were selected on the basis of (1) genes withknown associations for various cardiovascular, pulmonary, and sleeprelated disorders, (2) information from pathway-based tools for theidentification of biologically plausible candidate genes, (3) unpub-lished functional experiments in mice, (4) findings from variousgenome-wide scans, and (5) priority SNPs identified by IBC con-sortium investigators.18 SNPs (n�45 237) in version 1 of this arraywere genotyped in the PROMIS participants and were called usingthe Illuminus algorithm.23 Markers were excluded from analysis ifthe call rate was �95% (372 SNPs); there was evidence of departurefrom Hardy-Weinberg Equilibrium at a probability value of �10�3

(1750 SNPs); or the minor allele frequency (MAF) was �1%(11 931 SNPs, with most such omissions due to genetic markersrelevant in Africans being uninformative in Pakistanis and Europe-ans). LURIC participants were typed with version 2 of the IBC arrayand underwent the same calling and quality control procedures.Because version 2 has 4050 additional SNPs, these SNPs wereexcluded from the current analysis. After quality control, 31 883SNPs in 3197 Pakistanis and 35 533 SNPs in 2452 Germans wereavailable for analyses.

Statistical MethodsTo compare the genetic structure of Pakistanis with that of severalmajor ethnic groups, we received permission from HapMap3 inves-

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tigators to conduct principal components analyses on 1124 partici-pants in HapMap3. We selected 19 931 SNPs in common with thePROMIS sample, and excluded 11 952 A/T and C/G SNPs to avoidpossible strand alignment bias because it is difficult to infer theminor allele for A/T or C/G SNPs for non-HapMap populations.8 Toinvestigate genetic substructure, we classified Pakistani participantsinto 8 self-identified ethnic and linguistic groups and calculatedprincipal components on the matrix of identity-by-state sharing of allpairs of individuals. Quantile-quantile plots were produced byplotting the observed �log10 probability value for each lipid againstthe expected �log10 probability value. The association between eachlipid measure and genetic variants was tested using linear regression.

Additive models calculated the change in lipid level per copy of theminor allele. �-coefficients have been reported using the commonallele as the reference allele in PROMIS. All analyses were doneusing models adjusting for age and sex, the first 2 principalcomponents and case-control status. Effect estimates in LURIC werereported for the same allele taken as reference in PROMIS.

The Bonferroni correction for the 32 000 SNPs for 3 traits is 10�7,assuming 96 000 independent tests with no prior information. Wechose a cutoff 10�6 owing to the likely higher prior odds ofassociation because the array involves candidate genes and becausethere is a high degree of correlation between the tested SNPs. Toreduce potential biases, lipid analyses were stratified by case-controlstatus and excluded participants on lipid-lowering medication at thetime of baseline examination. Analyses used PLINK 1.06, R version2.9.1, and STATA 10.0.

Meta-AnalysisWe sought genetic association studies of lipid-related variants inpeople of European ancestry published between January 1970 andJanuary 2009. We focused on SNPs (ie, rs1800775, rs708272,rs646776, and rs662799) identified as top signals in the Pakistanstudy to enable comparison of their impact in Europeans (with theexception of rs780093, for which there was minimal previous data,owing to its completely recent discovery). Electronic searchesinvolved MEDLINE, EMBASE, BIOSIS, and Science Citation indexand combined search terms related to genes (eg, cholesteryl estertransfer protein [CETP]) and lipids (eg, HDL-C) without languagerestriction. These searches were supplemented by scanning referencelists, hand-searching relevant journals, and correspondence withauthors. Two investigators independently extracted the followinginformation: mean and SD of lipid levels by genotype; proportion ofmales; fasting status; and assay methods. Analyses involved onlywithin-study comparisons. Mean levels of lipids (and differences inmean levels in comparison with the common homozygotes) werecalculated using both fixed and random-effects models (as the latter

Figure 1. A, Scatterplot of the first 2 principal components identified by principal component analysis of the identity-by-state matrix.The colors of points refer to the self-reported ethnicities in PROMIS control participants and HAPMAP (these ethnicities were not usedin the PCA). B, Scatterplot of the first 2 principal components and self-reported ethnicities in PROMIS control participants. A and B,PAK indicates Pakistani from the PROMIS control subjects; YRI, Yoruba in Ibadan, Nigeria; LWK, Luhya in Webuye, Kenya; ASW, Afri-can ancestry in Southwest United States; MKK, Maasai in Kinyawa, Kenya; GIH, Gujrati Indians in Houston, Tex; CEU, Utah residentswith Northern and Western European ancestry from the CEPH collection; TSI, Toscani in Italy; MEX, Mexican ancestry in Los Angeles,Calif; JPT, Japanese in Tokyo, Japan; CHD, Chinese in Metropolitan Denver, Colo; CHB Han Chinese in Beijing, China; C1, first princi-pal component; C2, second principal component; and PCA, principal components analysis.

Table. Characteristics of the Participants From PROMIS andLURIC Studies

CharacteristicsPROMIS

(n�3195)LURIC

(n�2452)

Age, y 53.2 (10) 62 (10)

Women, % 17.5 29.5

Self-reported history of diabetesmellitus, %

17.2 32.4

Family history of MI, % 15.4% 10%

Body mass index, kg/m2 25.2 (4.3) 27.4 (4.0)

Total cholesterol, mmol/L 4.6 (1.3) 5.0 (1.0)

Low density lipoprotein cholesterol,mmol/L

2.70 (1.20) 2.96 (0.85)

High density lipoprotein cholesterol,mmol/L

0.82 (0.24) 0.99 (0.27)

Triglycerides, mmol/L 0.56 (0.22–0.95) 0.49 (0.21–0.81)

Data are mean (SD), median (IQR), or %.

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makes allowances for between-study heterogeneity). Probabilityvalues for difference between the effect estimates obtained inPROMIS and European participants were calculated through a �2 testof heterogeneity.

ResultsThe main characteristics of the Pakistani and German partic-ipants in this study are summarized in the Table. Comparisonwith HapMap3 population panels shows that the Pakistanipopulation clustered distinctly from 11 other major ethnicgroups, indicated by the separate clustering on the scatterplotof principal components (Figure 1). Pakistanis appear genet-ically closest to, but still clearly distinct from, GujaratiIndians living in the United States, a group that is known todiffer genetically from Indians living in India.24 Analysis ofthe 8 ethnic and linguistic groups in the Pakistani studysuggested the possibility of relatively minor population sub-structure; the different ethnicities could not be demarcateddiscretely on the scatter plots involving different principalcomponents (Figure 1 and the online-only Data SupplementFigure 1). Compared with Germans, the Pakistani participantswere about a decade younger and had broadly similar LDL-Cand triglyceride values but lower HDL-C (Table).

Variants With Highly Significant AssociationsUnder an additive model, linear regression analysis for each lipidmeasure identified several SNPs deviating from the expected �2

values as shown by the quantile-quantile plots in Figure 2. Atotal of 25 variants in 4 genomic regions were associated withlipid levels in Pakistanis (P�10�6), including 16 variants forHDL-C, 8 variants for triglycerides, and 1 variant for LDL-C.All 16 HDL-C–related variants were on the cholesteryl estertransfer protein (CETP) gene (10�14�P�10�6; Figure 3A andonline-only Data Supplement Table 1). Each copy of the minorallele of rs711752, the lead SNP, was associated with0.048 mmol/L (95% CI, 0.04 to 0.06; P�10�14) higher HDL-Clevels. MAFs and effect sizes of the CETP variants in Pakistaniswere broadly similar to those observed in this German popula-tion (Figure 3A), with overlapping genetic association signalsand a similar pattern of linkage disequilibrium (LD) in thisregion (Figure 4). Subsidiary analyses in PROMIS cases andcontrol participants for these variants revealed qualitativelysimilar results (online-only Data Supplement Figures 2a to 2c).To further explore LD patterns in Europeans, subsidiary analy-ses were conducted in CEU HapMap2 data, which revealed asimilar pattern of LD in the CEU HapMap2 population andLURIC participants (data available on request). As shown in

Figure 2. Q-Q plots for PROMIS and LURIC in association with major lipids. Lambda: Genomic inflation factor.




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Figure 5, meta-analyses of the 2 most extensively studied CETPvariants in Europeans yielded overall increases in HDL-Cconcentration of 0.063 mmol/L (0.055 to 0.071; I2�67%, 55%to 77%) per copy of the A allele of the Taq1B variant (rs708272;46 studies, 65 640 participants) and 0.071 mmol/L (0.066 to

0.075; I2�10%, 0% to 43%) per copy of the A allele of theC-629A variant (rs1800775; 26 studies, 80 184 participants).Associations of the Taq1B variant appeared of similar size in the2 studies; the Taq1B variant was in strong LD with rs711752(r2�0.99), the lead variant in the Pakistani population. By

Figure 3. Association with A, HDL-C and B,log-triglyceride in PROMIS and LURIC par-ticipants of SNPs signficantly associated inPROMIS (P�10�6). Estimates represent theper-minor allele increase in lipid levels,adjusted for age, sex, the first 2 principalcomponents, and case-control status. Theprobability value for difference betweenstudies corresponds to a test of nullity ofinteraction term between study and theSNP of interest. Size of boxes are propor-tional to the inverse of the variance of studyestimates. Chr indicates chromosome; SNP,single nucleotide polymorphism; and MAF,minor allele frequency.




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contrast, the association of the C-629A variant with HDL-Cappeared somewhat stronger in Europeans than in Pakistanis (�2

test for difference, P�2�10�4; Figure 5 and online-only DataSupplement Figure 3a-1b).

Eight variants in 2 genomic regions were highly significantlyassociated with log triglyceride concentration in the Pakistaniparticipants. The most significant SNP (rs662799; P�1.25�10�14) localized to the APOA5 gene (Figure 3B and online-onlyData Supplement Table 1). Each copy of the rs662799-C alleleat this locus was associated with a 0.14 mmol/L higher logtriglyceride concentration (Figures 3B and 4), with MAF about2 times higher in the Pakistani than German participants (0.17versus 0.07). This variant was in strong LD with several othervariants in APOA5 and nearby ZNF259 that were also signifi-cantly associated with triglyceride concentration but apparentlynot in LD with any of the variants in APOA1, APOC3 orAPOA4. Overall, APOA5 variants appeared to have stronger LDand associations with triglyceride concentration in Pakistani thanin German participants (Figure 4). Meta-analysis of rs662799 inavailable European studies yielded 0.20 mmol/L (0.14 to 0.26)higher triglyceride per each copy of the minor allele (18 studies,20 963 participants: Figure 5 and online-only Data SupplementFigure 3D), an effect size that was lower than that observed inthe Pakistani participants (�2 for difference, P�7�10�4; Figure5). Three variants in the glucokinase regulatory protein (GCKR)gene highly significantly associated with triglyceride in Paki-stanis (P�10�6) had broadly similar-sized effects in Germans(Figure 3B).

Only rs646776 in the cadherin, EGF LAG 7-pass G-typereceptor 2 (CELSR2) gene was highly significantly associatedwith LDL-C concentration in the Pakistani participants(P�1.25�10�10) and was associated with a 0.16 mmol/L(�0.23 to �0.08) lower LDL-C concentration per copy of theminor allele. This variant was not significantly associated

with LDL-C concentration in the German participants(n�1175), perhaps owing to limited statistical power. Anal-yses conducted earlier in a larger LURIC study population(n�3189) for the same locus yielded a similar associationwith LDL-C levels to that observed in Pakistanis.25 Thecurrent meta-analysis of rs646776, however, established thisvariant’s relevance more reliably in Europeans, yielding anoverall 0.15 mmol/L (�0.17 to �0.14) lower LDL-C pereach copy of the minor allele (14 studies, 48 445 participants;Figure 5), an effect size comparable to that observed inPakistanis (�2 test for difference, P�0.84; Figure 5 andonline-only Data Supplement Figure 3c).

No significant interactions were observed on an additivescale of the 25 top variants with lipid measures by ghee ortobacco consumption or by sex (online-only Data SupplementFigure 4). Qualitatively similar results were observed inanalyses adjusted for time since onset of MI symptoms in 875cases in PROMIS with relevant information (available onrequest).

Variants With Nominally Significant AssociationsOf the 152 lipid-related SNPs discovered through previousgenome-wide association studies in European populations, 49were covered by the gene array used in the current study (23for HDL-C, 17 for LDL-C, and 17 for triglycerides with a fewSNPs associated with 2 or all 3 traits). At a prespecifiednominal value of P�0.01, 12 of the 23 established HDL-C–related variants were associated with HDL-C concentration(including 7 variants described earlier in CETP and 5 othervariants in LIPG, LIPC, and DPEP2); 10 of the established17 triglyceride-related variants were associated with triglyc-eride concentration (including 3 variants described earlier inAPOA5 and GCKR and 7 other variants in DOCK7, TBL2,LPL, BAZ1b, and APOB); and 5 of the 17 establishedLDL-C-related variants were associated with LDL-C concen-

Figure 4. Genomic location of all thegenotyped variants in CETP and APOA5and a comparison of linkage disequilib-rium in PROMIS and LURIC participants.A, PROMIS (blue) and LURIC (red); B,LD plot (D�) LURIC; C, LD plot (D�) PRO-MIS. LD plots have been drawn using1595 PROMIS control and 1175 LURICcontrol participants. Similar analyses forCELSR2 gene in PROMIS and LURICwere not possible because the currentgene array used contains only few SNPsin this gene.




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tration (including 1 variant in CELSR2 described above and 4other variants in FADS1, FADS2 and CELSR2: online-onlyData Supplement Figure 5). Hence, we identified a total of 41different variants significantly related to major lipid levels inPakistanis (ie, 25 variants at P�10�6 and a further 16variants at P�10�2). Analyses of these genes in PROMISand LURIC participants revealed a similar pattern of LD,with somewhat stronger LD blocks in APOB and LPL genesin Pakistanis than in Europeans (online-only Data Supple-ment Figure 6). Collectively, in the Pakistani participants,these variants explained 6.2%, 7.1%, and 0.9% of the varia-tion in HDL-C, triglyceride, and LDL-C, respectively,whereas corresponding analyses in the German participantsexplained 5.9%, 7.2%, and 0.71% of the variation in theselipids, respectively.

Subsidiary analyses yielded odds ratio for MI in Paki-stanis with each of the 41 principal SNPs that werecompatible with the direction of associations of each of

these variants with lipid concentration, although the cur-rent study was underpowered for reliable gene-MI analyses(online-only Data Supplement Figure 7).

DiscussionThe current study has identified a total of 41 variants at 14 locithat were significantly associated with levels of HDL-C, triglyc-eride or LDL-C in Pakistanis. The most highly significantlipid-related variants identified among Pakistanis correspondedto genes previously shown to be relevant to lipid metabolism inEuropeans, such as CETP, APOA5, and CELSR2. Even collec-tively, however, the top variants explained only 6.2%, 7.1%, and0.9% of the population variation in HDL-C, triglyceride, andLDL-C levels in Pakistanis, respectively (a similar proportion oflipid variation was explained by the top signals in our parallelanalysis of Germans). The current study has also suggested somedifferences in allelic frequencies and magnitude of associationwith lipids for variants in APOA5 in Pakistanis compared with

Figure 5. Comparison of associations with lipid traits observed in PROMIS with previously published studies in participants of Euro-pean descent. Estimates represent the per-minor allele increase in lipid levels. PROMIS estimates are derived fitting a regression,adjusting for age, sex, case-control status, and the first 2 components of PCA. Estimates in whites are derived from a random-effectsmeta-analysis of additive estimates. Individual plots for each meta-analysis are presented in online Figures 2a through 2d. The proba-bility value of heterogeneity derives from a heterogeneity test between the overall estimates in whites and the estimate in PROMIS. Sizeof boxes are proportional to the inverse of the variance of study estimates. The mean difference is in mmol/L. Scales differ betweenlipids.




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Europeans. As discussed below, however, further studies areneeded to confirm whether such differences are mainly related toethnicity rather than other characteristics.

Most of the highly significant lipid-related loci identifiedin Pakistani participants were related to HDL-C and triglyc-eride rather than LDL-C concentration, a finding that isconsistent with a lower yield of genetic loci associated withLDL-C in previous GWA studies in Europeans.5–16 ForHDL-C, our most highly significant findings related to theCETP gene.26 HDL is believed to exert atheroprotectiveeffects through several mechanisms, including transfer ofcholesterol from peripheral tissues to liver.26,27 CETP facili-tates this process by exchanging cholesterol esters from HDLwith triglyceride in apolipoprotein B–containing particles.26

Deficiency of this protein leads to higher HDL-C levels andother lipoprotein abnormalities.25,26 Our meta-analysis fo-cused on the Taq1B and C-629A variants in CETP, whichalter CETP mass and activity and, consequently, increaseHDL-C concentration.27

For triglyceride, our most highly significant findings related tovariants in APOA5, which is part of the APOA1/C3/A4/A5 genecluster localized to chromosome 11q23.28,29 It has been proposedthat APOAV regulates lipoprotein lipase-mediated hydrolysis oftriglycerides contained in VLDL particles.28 Further triglycer-ide-related variants were found in GCKR,30 which regulatesactivity of glucokinase, a key enzyme responsible for the firstrate-limiting step in the glycolysis pathway, deficiency of whichalters glucose and lipoprotein metabolism.31 For LDL-C, thesole highly significant finding related to a variant in CELSR2,32

a gene that expresses itself along with PSRC1 and SORT1 withina transcriptional network proposed to regulate metabolic profileand atherosclerosis,32,33 although precise mechanisms remainunknown.

Compared with the German participants we studied, thefrequency of the rs662799-C allele in the APOA5 locus washigher in Pakistanis and appeared to have a greater impact ontriglyceride concentration. However, as at least part of thesedifferences could have been due to nonethnic factors (eg,differences in sample size and/or population sampling frame-works used), further study is needed. Evidence of ethnic-relateddifferences is emerging from other contexts, such as suggestionsthat total cholesterol is a stronger risk factor among South Asiansthan Europeans34 and that the LTA4H haplotype has higher oddsratios for myocardial infarction in Africans than Europeans.35

The value of large ethnic-specific studies has also been illus-trated by the discovery of the strongest common susceptibilitylocus (KCNQ1) yet for T2D,36–38 identified in East Asians butnot initially in Europeans because the allele frequency in EastAsians is much higher (40% versus 5%) despite similar oddsratios in both populations.36–38

For reasons of feasibility, we used existing genetic tools basedon catalogues of genetic variation mostly discovered in Europe-ans, East Asians, and West Africans, even though we wereaware that these tools may not adequately capture geneticvariation in Pakistanis (or other South Asians).39,40 For example,the recent discovery of a 7-fold relative risk for heart failure withthe 25-bp deletion allele in the MYBPC3 gene would haveremained undetected using conventional platforms because thisvariant is present only in South Asians.41 Further study in

Pakistanis is therefore needed involving better population-specific tools for genetic mapping. Larger replication studiesshould also help to quantify and control any overestimation inhypothesis-generating estimates. Such studies should aim toinvolve fine-mapping of relevant loci (eg, APOA5) and func-tional studies.42 Future studies may also yield stronger (or novel)genetic signals by direct assay of LDL-C rather than, as in thecurrent study, calculation of LDL-C using the Friedewaldformula. However, as a large prospective study has shown thatassociations of major lipids with CHD risk are at least asextreme in nonfasted participants as in fasted participants,41 useof nonfasting samples in the current study seems unlikely tohave influenced materially the findings here.

Sources of FundingEpidemiological field work in PROMIS was supported by unre-stricted grants to investigators at the University of Cambridge and inPakistan. Genotyping for this study was funded by the WellcomeTrust and the EU Framework 6–funded Bloodomics IntegratedProject (LSHM-CT-2004-503485). The British Heart Foundation hassupported some biochemical assays. The Yousef Jameel Foundationsupports Dr Saleheen. The cardiovascular disease epidemiologygroup of Dr Danesh is underpinned by programme grants from theBritish Heart Foundation and the UK Medical Research Council.

DisclosuresDr Saleheen received research funding from the Fogarty Interna-tional Center, National Heart, Lung and Blood Institute, NationalInstitute of Neurological Disorders and Stroke, and the WellcomeTrust. Dr Danesh reports having received research funding from theBritish Heart Foundation, BUPA Foundation, diaDexus, EuropeanUnion, Evelyn Trust, Fogarty International Center, GlaxoSmithKline,Medical Research Council, Merck, National Heart, Lung and BloodInstitute, National Institute of Neurological Disorders and Stroke,Novartis, Pfizer, Roche, UK Biobank, and the Wellcome Trust.

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CLINICAL PERSPECTIVELevels of the major blood lipids, LDL-C, HDL-C, and triglyceride are each strongly associated with the risk of coronaryheart disease (CHD). Several genetic variants have been established in the regulation of lipid metabolism in people ofEuropean continental ancestry; however there are few data available on the genetic determinants of these lipid traits inSouth Asians a population with a high burden of cardiometabolic conditions. We investigated 45 000 variants across 2000genes in 3200 Pakistanis, and 2450 Germans using the same gene array. A total of 41 variants at 14 loci, were found tobe significantly associated with major lipid traits in Pakistanis, explaining 6.2%, 7.1%, and 0.9% of the variation in HDL-C,triglyceride, and LDL-C, respectively. The most significant lipid-related variants identified among Pakistanis correspondedto genes previously shown to be relevant to Europeans, such as CETP associated with HDL-C levels; APOA5/ZNF259 andGCKR with triglyceride levels; and CELSR2 variants with LDL-C levels. However, differing allelic frequencies and lipideffects for variants in APOA5 were observed in Pakistanis compared with Europeans. This study suggests that severallipid-related genetic variants are common to Pakistanis and Europeans, though they explain only a modest portion ofpopulation variation in lipid concentration. Allelic frequencies and the effect sizes of lipid-related variants can differbetween Pakistanis and Europeans.




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Frossard, John Danesh and Panos DeloukasPhilippeWinkelmann, Bernhard Böehm, Simon Thompson, Willem Ouwehand, Winfried März,

Muhammad, Gurdeep Sagoo, Sarah Bray, Ralph McGinnis, Frank Dudbridge, Bernhard R.Shahid Abbas, Junaid Zafar, Faisal Shahid, Shahzad Majeed Bhatti, Syed Saadat Ali, Fahim

Kishore Kumar, Asim Saleem, Kishwar Kumar, Muhammad Salman Daood, Aftab Alam Gul,Tanja B. Grammer, Jonathon Stephens, Anthony Attwood, Kerstin Koch, Mustafa Hussain, Ghaffar, Fazal-ur Rehman, Michael Marcus Hoffmann, Wilfried Renner, Marcus E. Kleber,

Rasheed, Rashid Jooma, Jawaid Hassan Niazi, Ali Raza Gardezi, Nazir Ahmed Memon, Abdul Nadeem Hayat Mallick, Muhammad Azhar, Abdus Samad, Muhammad Ishaq, Syed Zahed

Zaman, Assadullah Kundi, Zia Yaqoob, Liaquat Ali Cheema, Nadeem Qamar, Azhar Faruqui, Thompson, Reeta Gobin, Adam Butterworth, Usman Ahmad, Abdul Hakeem, Khan Shah

Nasir Sheikh, Nabi Shah, Maria Samuel, Shajjia Razi Haider, Muhammed Murtaza, Alexander Bumpstead, Stephen Kaptoge, Emanuele Di Angelantonio, Nadeem Sarwar, Sarah E. Hunt,

Alexander, Michael Inouye, Moazzam Zaidi, Simon Potter, Philip Haycock, Suzanna Danish Saleheen, Nicole Soranzo, Asif Rasheed, Hubert Scharnagl, Rhian Gwilliam, MyriamGenetic Determinants of Major Blood Lipids in Pakistanis Compared With Europeans

Print ISSN: 1942-325X. Online ISSN: 1942-3268 Copyright © 2010 American Heart Association, Inc. All rights reserved.

Dallas, TX 75231is published by the American Heart Association, 7272 Greenville Avenue,Circulation: Cardiovascular Genetics

doi: 10.1161/CIRCGENETICS.109.9061802010;3:348-357; originally published online June 22, 2010;Circ Cardiovasc Genet.

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1

"SUPPLEMENTAL MATERIAL."

2

Supplemental Figure 1: Scatter plot of additional principal components and self reported ethnicities in PROMIS control participants

3

PROMIS LURIC P‐value for difference between studies

Chr snp bp gene a1 N maf beta se p N maf beta se p

Association with HDL‐C levels (mmol/l)

16 rs711752 55553712 CETP T 3023 0.47 0.048 0.006 4.67E‐14 2451 0.42 0.058 0.007 5.05E‐15 0.45

16 rs708272 55553789 CETP A 3023 0.47 0.048 0.006 4.77E‐14 2450 0.42 0.058 0.007 4.77E‐15 0.76

16 rs17231506 55552029 CETP A 3023 0.33 0.049 0.007 5.54E‐13 2451 0.32 0.059 0.008 7.50E‐14 1

16 rs3764261 55550825 CETP A 3023 0.33 0.049 0.007 1.17E‐12 2451 0.32 0.058 0.008 1.08E‐13 0.63

16 rs11508026 55556829 CETP A 3021 0.46 0.046 0.006 1.47E‐12 2452 0.42 0.058 0.007 3.40E‐15 0.55

16 rs1532625 55562802 CETP T 2996 0.48 0.045 0.006 2.27E‐12 2428 0.43 0.058 0.007 8.28E‐15 0.63

16 rs1800775 55552737 CETP G 3024 0.40 ‐0.045 0.006 3.00E‐12 2451 0.53 ‐0.062 0.007 3.69E‐17 0.11

16 rs1532624 55562980 CETP T 3023 0.48 0.044 0.006 4.06E‐12 2448 0.43 0.057 0.007 8.69E‐15 0.25

16 rs1864163 55554734 CETP A 3024 0.22 ‐0.043 0.008 1.56E‐08 2443 0.27 ‐0.063 0.009 2.40E‐13 0.16

16 rs7499892 55564091 CETP A 3023 0.22 ‐0.042 0.008 3.82E‐08 2452 0.18 ‐0.063 0.010 8.52E‐11 0.11

16 rs11076175 55563879 CETP G 3022 0.19 ‐0.044 0.008 5.04E‐08 2451 0.18 ‐0.063 0.010 1.27E‐10 0.36

16 rs5880 55572592 CETP G 3024 0.08 ‐0.064 0.012 7.86E‐08 2451 0.05 ‐0.068 0.017 5.25E‐05 0.69

16 rs12720922 55558386 CETP T 3024 0.20 ‐0.042 0.008 1.29E‐07 2451 0.18 ‐0.060 0.010 1.02E‐09 0.48

16 rs9939224 55560233 CETP A 3021 0.22 ‐0.039 0.008 2.74E‐07 2452 0.21 ‐0.062 0.009 1.49E‐11 0.25

16 rs12708967 55550712 CETP G 3021 0.22 ‐0.039 0.008 3.85E‐07 2452 0.20 ‐0.036 0.009 1.16E‐04 0.26

16 rs11076176 55564947 CETP C 3021 0.21 ‐0.038 0.008 6.71E‐07 2450 0.18 ‐0.063 0.010 9.67E‐11 0.04

Association with LDL‐C levels (mmol/l)

1 rs646776++ 109620053 CELSR2 G 5576 0.25 ‐0.158 0.025 7.19E‐10 1175 0.239 ‐0.014 0.040 0.7224 0.05

Association with log‐triglyceride levels (mmol/l)

11 rs662799 116168917 APOA5 C 3195 0.17 0.142 0.018 1.25E‐14 2452 0.07 0.080 0.026 2.22E‐03 0.07

11 rs651821 116167789 APOA5 C 3195 0.17 0.142 0.018 1.47E‐14 2452 0.07 0.083 0.026 1.49E‐03 0.15

11 rs2072560 116167036 APOA5 A 3195 0.16 0.142 0.019 2.13E‐14 2450 0.07 0.077 0.026 3.34E‐03 0.11

11 rs2266788 116165896 APOA5 G 3195 0.20 0.129 0.017 6.94E‐14 2452 0.07 0.073 0.025 3.83E‐03 0.17

11 rs2075290 116158506 ZNF259/APOA5 G 3189 0.19 0.132 0.018 8.77E‐14 2452 0.07 0.077 0.025 2.15E‐03 0.19

2 rs1260326++ 27584444 GCKR T 5500 0.26 0.078 0.012 1.09E‐10 2451 0.44 0.078 0.014 7.19E‐09 0.86

2 rs780093 27596107 GCKR T 3194 0.26 0.075 0.016 2.35E‐06 2445 0.44 0.080 0.014 3.41E‐09 0.64

2 rs780094 27594741 GCKR T 3185 0.26 0.074 0.016 2.63E‐06 2449 0.44 0.080 0.014 3.86E‐09 0.69

Supplemental Table 1: Association of major lipid traits in PROMIS and comparison with the LURIC participants of SNPs significantly associated in PROMIS (P < 10-6)

++Genotyping was done in further 2555 PROMIS individuals for variants associated with lipid traits at a P < 10-5

Chr: chromosome, a1: minor allele, N: number of individuals, maf: minor allele frequency, beta: per-minor allele increase in lipid levels, adjusted for age, sex, the first two principal components and case-control status. For LDL, the LURIC dataset was restricted to participants not on lipid lowering drugs. The P-value for difference between studies corresponds to a test of nullity of interaction term between study and the SNP of interest.

4

rs1107617516

rs1107617616

rs1150802616

rs1270896716

rs1272092216

rs153262416

rs153262516

rs1723150616

rs180077516

rs186416316

rs376426116

rs588016

rs70827216

rs71175216

rs749989216

rs993922416

SNP_id/Chr.

Status

-0.05 (-0.07, -0.02)-0.08 (-0.11, -0.05)

-0.04 (-0.06, -0.01)-0.06 (-0.08, -0.03)

0.05 (0.03, 0.07)0.06 (0.04, 0.09)

-0.06 (-0.08, -0.03)-0.06 (-0.09, -0.03)

-0.05 (-0.07, -0.02)-0.08 (-0.11, -0.05)

0.05 (0.03, 0.07)0.06 (0.04, 0.09)

0.05 (0.03, 0.08)0.07 (0.04, 0.09)

0.06 (0.04, 0.09)0.07 (0.05, 0.10)

-0.04 (-0.06, -0.02)-0.07 (-0.10, -0.05)

-0.05 (-0.07, -0.02)-0.07 (-0.10, -0.04)

0.06 (0.04, 0.09)0.07 (0.05, 0.10)

-0.08 (-0.12, -0.04)-0.07 (-0.11, -0.02)

0.05 (0.03, 0.08)0.07 (0.05, 0.09)

0.06 (0.03, 0.08)0.07 (0.05, 0.09)

-0.05 (-0.07, -0.02)-0.07 (-0.10, -0.04)

-0.04 (-0.07, -0.02)-0.07 (-0.10, -0.05)

Mean difference (95% CI)

.128

.288

.554

.869

.118

.491

.502

.609

.049

.196

.57

.609

.327

.362

.327

.119

P-value het.

-0.05 (-0.07, -0.02)-0.08 (-0.11, -0.05)

-0.04 (-0.06, -0.01)-0.06 (-0.08, -0.03)

0.05 (0.03, 0.07)0.06 (0.04, 0.09)

-0.06 (-0.08, -0.03)-0.06 (-0.09, -0.03)

-0.05 (-0.07, -0.02)-0.08 (-0.11, -0.05)

0.05 (0.03, 0.07)0.06 (0.04, 0.09)

0.05 (0.03, 0.08)0.07 (0.04, 0.09)

0.06 (0.04, 0.09)0.07 (0.05, 0.10)

-0.04 (-0.06, -0.02)-0.07 (-0.10, -0.05)

-0.05 (-0.07, -0.02)-0.07 (-0.10, -0.04)

0.06 (0.04, 0.09)0.07 (0.05, 0.10)

-0.08 (-0.12, -0.04)-0.07 (-0.11, -0.02)

0.05 (0.03, 0.08)0.07 (0.05, 0.09)

0.06 (0.03, 0.08)0.07 (0.05, 0.09)

-0.05 (-0.07, -0.02)-0.07 (-0.10, -0.04)

-0.04 (-0.07, -0.02)-0.07 (-0.10, -0.05)

.128

.288

.554

.869

.118

.491

.502

.609

.049

.196

.570

.609

.327

.362

.327

.119

0-.1 -.05 0 .05 .1

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

mmol/l

Supplemental Figure 2(a): Association with HDL-C in PROMIS cases and controls for SNPs significantly associated with HDL-C levels in all PROMIS participants (P < 10-6)

5

Supplemental Figure 2(b): Association with log-triglyceride in PROMIS cases and controls for SNPs significantly associated with triglyceride levels in all PROMIS participants (P < 10-6)

rs12603262

rs207256011

rs207529011

rs226678811

rs65182111

rs66279911

rs7800932

rs7800942

SNP_id/chr

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

Status

0.08 (0.04, 0.12)0.08 (0.03, 0.12)

0.15 (0.10, 0.20)0.13 (0.08, 0.18)

0.14 (0.09, 0.19)0.12 (0.07, 0.17)

0.13 (0.08, 0.18)0.13 (0.08, 0.18)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

Mean Difference(95% CI)

.908

.608

.561

.972

.732

.734

.909

.838

P-value het.

0.08 (0.04, 0.12)0.08 (0.03, 0.12)

0.15 (0.10, 0.20)0.13 (0.08, 0.18)

0.14 (0.09, 0.19)0.12 (0.07, 0.17)

0.13 (0.08, 0.18)0.13 (0.08, 0.18)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

.908

.608

.561

.972

.732

.734

.909

.838

0 .050 .05 .1 .15 .2

log mmol/l

rs12603262

rs207256011

rs207529011

rs226678811

rs65182111

rs66279911

rs7800932

rs7800942

SNP_id/chr

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

casecontrol

Status

0.08 (0.04, 0.12)0.08 (0.03, 0.12)

0.15 (0.10, 0.20)0.13 (0.08, 0.18)

0.14 (0.09, 0.19)0.12 (0.07, 0.17)

0.13 (0.08, 0.18)0.13 (0.08, 0.18)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)


.908

.608

.561

.972

.732

.734

.909

.838

P-value het.

0.08 (0.04, 0.12)0.08 (0.03, 0.12)

0.15 (0.10, 0.20)0.13 (0.08, 0.18)

0.14 (0.09, 0.19)0.12 (0.07, 0.17)

0.13 (0.08, 0.18)0.13 (0.08, 0.18)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.15 (0.10, 0.20)0.13 (0.08, 0.19)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

0.07 (0.03, 0.11)0.08 (0.03, 0.12)

.908

.608

.561

.972

.732

.734

.909

.838

0 .050 .05 .1 .15 .2

log mmol/l

6

Supplemental Figure 2(c): Association with LDL-C in PROMIS cases and controls for SNPs significantly associated with LDL-C levels in all PROMIS participants

Supplemental Figures 2 (a-c): Estimates represent the per-minor allele increase in lipid levels, adjusted for age, sex, the first two principal components. P_value het. Is the P-value for heterogeneity for effect estimates obtained in cases and controls. Chr: chromosome.

rs6467761

chr

case

control

Status

-0.05 (-0.09, -0.02)

-0.07 (-0.11, -0.03)


.584

P_value het.

-0.05 (-0.09, -0.02)

-0.07 (-0.11, -0.03)

.584

0-.1 -.05 0 .05

SNP_id/

rs6467761

chr

case

control

Status

-0.05 (-0.09, -0.02)

-0.07 (-0.11, -0.03)


.584

P_value het.

-0.05 (-0.09, -0.02)

-0.07 (-0.11, -0.03)

.584

0-.1 -.05 0 .05

SNP_id/

mmol/l

7

Supplemental Figure 3(a): Meta-analysis of previously published studies in Europeans for the association of rs1800775 (C-629A) variant, located in the CETP gene, with HDL-C levels Suppl1-20

% Weight

NOTE: Weights are from random effects analysis

Overall random effect I-squared = 10% (95% CI 0% - 43%), p = 0.318)

Blankenberg S (AtheroGene)

Thompson JF

Ridker (WGHS)

Eiriksdottir Reykjavik)

Thompson JF

Overall fixed effect

Dullaart (PREVEND)

Schouw (PROSPECT/EPIC)

Bernstein MS

Sabatti (NFBC1966)

Kathiresan (NORDIL)

Girelli (Verona Heart Project)

Kathiresan (FIINRISK97)

Kathiresan (MDC-CC)

Kakko (OPERA)

Tobin MD

Aulchenko (ENGAGE consortium)

Bauerfeind

Freeman DJ (WOSCOPS)

Kathiresan (DGI)

Horne (IHCS)

Dachet C (ECTIM)

Author (Name of Study)

Heidema (CDRFMP)

Chasman (WGHS)

Barzilai N (Longevity)

McCaskie (CUDAS/BPHS/CUPID)

Rotterdam study

2004

2007

2009

2001

2003

2007

2003

2009

2008

2008

2008

2001

2004

2009

2002

2003

2008

2007

1999

Year

2007

2008

2003

2007

2007

574

2087

18000

745

93

8141

1519

1720

4531

5095

1187

7940

5519

481

182

5840

185

1107

2758

1309

668

Number ofparticipants

1071

6195

743

1059

1435

0.07 (0.07, 0.08)

0.08 (0.03, 0.13)

0.05 (0.03, 0.07)

0.08 (0.07, 0.09)

0.08 (0.05, 0.11)

0.08 (-0.00, 0.15)

0.07 (0.07, 0.08)

0.06 (0.05, 0.08)

0.08 (0.05, 0.11)

0.05 (0.02, 0.09)

0.07 (0.05, 0.09)

0.08 (0.05, 0.10)

0.07 (0.04, 0.10)

0.06 (0.05, 0.08)

0.08 (0.07, 0.09)

0.05 (0.01, 0.09)

0.06 (-0.01, 0.13)

0.06 (0.05, 0.08)

0.07 (-0.01, 0.15)

0.06 (0.04, 0.08)

0.07 (0.05, 0.09)

0.05 (-0.00, 0.11)

0.08 (0.04, 0.12)

ES (95% CI)

0.07 (0.04, 0.10)

0.09 (0.08, 0.10)

0.07 (0.03, 0.11)

0.07 (0.04, 0.11)

0.08 (0.06, 0.11)

100.00

0.84

5.44

14.06

2.38

0.32

9.87

2.32

1.50

3.79

3.88

2.24

7.79

7.79

1.17

0.38

9.33

0.32

4.20

4.43

0.59

1.11

(D+L)

2.14

8.28

1.17

1.73

2.94

0.07 (0.07, 0.08)

0.08 (0.03, 0.13)

0.05 (0.03, 0.07)

0.08 (0.07, 0.09)

0.08 (0.05, 0.11)

0.08 (-0.00, 0.15)

0.07 (0.07, 0.08)

0.06 (0.05, 0.08)

0.08 (0.05, 0.11)

0.05 (0.02, 0.09)

0.07 (0.05, 0.09)

0.08 (0.05, 0.10)

0.07 (0.04, 0.10)

0.06 (0.05, 0.08)

0.08 (0.07, 0.09)

0.05 (0.01, 0.09)

0.06 (-0.01, 0.13)

0.06 (0.05, 0.08)

0.07 (-0.01, 0.15)

0.06 (0.04, 0.08)

0.07 (0.05, 0.09)

0.05 (-0.00, 0.11)

0.08 (0.04, 0.12)

ES (95% CI)

0.07 (0.04, 0.10)

0.09 (0.08, 0.10)

0.07 (0.03, 0.11)

0.07 (0.04, 0.11)

0.08 (0.06, 0.11)

100.00

0.84

5.44

14.06

2.38

0.32

9.87

2.32

1.50

3.79

3.88

2.24

7.79

7.79

1.17

0.38

9.33

0.32

4.20

4.43

0.59

1.11

(D+L)

2.14

8.28

1.17

1.73

2.94

0-.153 0 .153

Effect Size

8

Supplemental Figure 3(b): Meta-analysis of previously published studies in Europeans for the association of rs708272 (Taq1B) variant, located in the CETP gene, with HDL-C levels Suppl3, 5, 8, 21-59

% Weight


Overall Random Effect I-squared = 67.0% (95% CI 55% - 76%), p = <0.001)

Mitchell

Pai J (NHS)

Gudson (EARS)

Corella D

Eiriksdottir (Reykjavik)

Klos K (CARDIA)


Noone EOrdovas (Framingham)

Schouw (PROSPECT-EPIC)Sorli

Hall

Cuchel (NORM & CATH)

Horne (IHCS)

Miltiadous

Ridker (WGHS)

I-V Overall

Plat

Vohl MC


Dullaart (PREVEND)

Liu (PHS)Kuivenhoven JA (The Monitoring Project)

Riemens

Talmud (NPHS)

Deguchi (SVTR)

Freeman DJ

Kondon I

Tenkanen H

Heidema (CDRFMP)

Juvonen T

Thompson JF

Blankenberg S (Atherogene)

Thompson JF

Hannuksela


Kauma H

Pai J (HPFS)

Nettleton (ARIC)

Keavney

Carr


Fumeron F (ECTIM)

Bauerfeind


Sandhofer (Salzburg Atherosclerosis Prevention)

Arca

Weitgasser (SAPHIR)

1994

2004

1998

2000

2001

2007

20002007

2006

2006

2002

2007

2004

2009

2002

1999

2003

2007

20021997

1999

2002

2004

1994

1989

1991

2007

1995

2007

2004

2003

1994

2003

1996

2004

2006

2004

2002

2007

1995

2002

Year

2008

2001

2004

112

480

767

514

745

1586

296

632916

1399549

116

224

1298

95

18245

112

182

373

8289

384238

32

1727

49

220

146

109

1075

91

2105

571

93

82

1105

524

513

8764

4665

120

1058

724

184

Number ofParticipants

1503

180

1017

0.06 (0.05, 0.07)

0.12 (0.02, 0.21)

0.11 (0.06, 0.17)

0.07 (0.05, 0.09)

0.11 (0.07, 0.14)

0.07 (0.03, 0.10)

0.06 (0.04, 0.08)

0.02 (-0.03, 0.07)

0.02 (-0.12, 0.15)0.06 (0.04, 0.08)

0.06 (0.03, 0.09)0.05 (0.01, 0.09)

0.08 (-0.02, 0.18)

0.06 (-0.02, 0.13)

0.05 (-0.01, 0.11)

0.03 (-0.05, 0.11)

0.07 (0.07, 0.08)

0.07 (0.07, 0.07)

0.06 (-0.03, 0.15)

0.06 (0.02, 0.09)

0.12 (0.05, 0.18)

0.06 (0.05, 0.08)

0.05 (0.01, 0.09)0.12 (0.05, 0.18)

-0.00 (-0.11, 0.11)

0.05 (0.04, 0.07)

0.02 (-0.10, 0.15)

0.10 (0.03, 0.17)

0.11 (0.02, 0.20)

0.04 (-0.07, 0.16)

0.07 (0.04, 0.10)

0.20 (0.03, 0.37)

0.05 (0.03, 0.07)

0.08 (0.03, 0.13)

0.07 (-0.02, 0.17)

0.10 (-0.00, 0.20)

0.05 (0.02, 0.07)

0.06 (0.02, 0.10)

-0.11 (-0.15, -0.07)

0.07 (0.06, 0.09)

0.06 (0.04, 0.07)

0.10 (0.01, 0.19)

0.07 (0.03, 0.10)

0.08 (0.04, 0.12)

0.06 (-0.02, 0.14)

0.06 (0.03, 0.09)

0.10 (0.01, 0.18)

0.09 (0.05, 0.12)

100.00

0.66

1.39

3.98

3.04

2.85

3.96

1.67

0.334.34

3.052.53

0.55

0.98

1.38

0.84

5.58

0.66

2.68

1.21

5.00

2.141.26

0.47

4.51

0.40

1.03

0.65

0.46

3.11

0.20

4.41

1.82

0.59

0.54

3.98

2.22

2.29

4.96

4.93

0.69

2.75

2.35

0.86

(D+L)

3.24

0.76

2.72

0.06 (0.05, 0.07)

0.12 (0.02, 0.21)

0.11 (0.06, 0.17)

0.07 (0.05, 0.09)

0.11 (0.07, 0.14)

0.07 (0.03, 0.10)

0.06 (0.04, 0.08)

0.02 (-0.03, 0.07)

0.02 (-0.12, 0.15)0.06 (0.04, 0.08)

0.06 (0.03, 0.09)0.05 (0.01, 0.09)

0.08 (-0.02, 0.18)

0.06 (-0.02, 0.13)

0.05 (-0.01, 0.11)

0.03 (-0.05, 0.11)

0.07 (0.07, 0.08)

0.07 (0.07, 0.07)

0.06 (-0.03, 0.15)

0.06 (0.02, 0.09)

0.12 (0.05, 0.18)

0.06 (0.05, 0.08)

0.05 (0.01, 0.09)0.12 (0.05, 0.18)

-0.00 (-0.11, 0.11)

0.05 (0.04, 0.07)

0.02 (-0.10, 0.15)

0.10 (0.03, 0.17)

0.11 (0.02, 0.20)

0.04 (-0.07, 0.16)

0.07 (0.04, 0.10)

0.20 (0.03, 0.37)

0.05 (0.03, 0.07)

0.08 (0.03, 0.13)

0.07 (-0.02, 0.17)

0.10 (-0.00, 0.20)

0.05 (0.02, 0.07)

0.06 (0.02, 0.10)

-0.11 (-0.15, -0.07)

0.07 (0.06, 0.09)

0.06 (0.04, 0.07)

0.10 (0.01, 0.19)

0.07 (0.03, 0.10)

0.08 (0.04, 0.12)

0.06 (-0.02, 0.14)

ES (95% CI)

0.06 (0.03, 0.09)

0.10 (0.01, 0.18)

0.09 (0.05, 0.12)

100.00

0.66

1.39

3.98

3.04

2.85

3.96

1.67

0.334.34

3.052.53

0.55

0.98

1.38

0.84

5.58

0.66

2.68

1.21

5.00

2.141.26

0.47

4.51

0.40

1.03

0.65

0.46

3.11

0.20

4.41

1.82

0.59

0.54

3.98

2.22

2.29

4.96

4.93

0.69

2.75

2.35

0.86

(D+L)

3.24

0.76

2.72

0-.374 0 .374

% Weight


Overall Random Effect I-squared = 67.0% (95% CI 55% - 76%), p = <0.001)

Mitchell

Pai J (NHS)

Gudson (EARS)

Corella D

Eiriksdottir (Reykjavik)

Klos K (CARDIA)


Noone EOrdovas (Framingham)

Schouw (PROSPECT-EPIC)Sorli

Hall

Cuchel (NORM & CATH)

Horne (IHCS)

Miltiadous

Ridker (WGHS)

I-V Overall

Plat

Vohl MC


Dullaart (PREVEND)

Liu (PHS)Kuivenhoven JA (The Monitoring Project)

Riemens

Talmud (NPHS)

Deguchi (SVTR)

Freeman DJ

Kondon I

Tenkanen H

Heidema (CDRFMP)

Juvonen T

Thompson JF

Blankenberg S (Atherogene)

Thompson JF

Hannuksela


Kauma H

Pai J (HPFS)

Nettleton (ARIC)

Keavney

Carr


Fumeron F (ECTIM)

Bauerfeind


Sandhofer (Salzburg Atherosclerosis Prevention)

Arca

Weitgasser (SAPHIR)

1994

2004

1998

2000

2001

2007

20002007

2006

2006

2002

2007

2004

2009

2002

1999

2003

2007

20021997

1999

2002

2004

1994

1989

1991

2007

1995

2007

2004

2003

1994

2003

1996

2004

2006

2004

2002

2007

1995

2002

Year

2008

2001

2004

112

480

767

514

745

1586

296

632916

1399549

116

224

1298

95

18245

112

182

373

8289

384238

32

1727

49

220

146

109

1075

91

2105

571

93

82

1105

524

513

8764

4665

120

1058

724

184

Number ofParticipants

1503

180

1017

0.06 (0.05, 0.07)

0.12 (0.02, 0.21)

0.11 (0.06, 0.17)

0.07 (0.05, 0.09)

0.11 (0.07, 0.14)

0.07 (0.03, 0.10)

0.06 (0.04, 0.08)

0.02 (-0.03, 0.07)

0.02 (-0.12, 0.15)0.06 (0.04, 0.08)

0.06 (0.03, 0.09)0.05 (0.01, 0.09)

0.08 (-0.02, 0.18)

0.06 (-0.02, 0.13)

0.05 (-0.01, 0.11)

0.03 (-0.05, 0.11)

0.07 (0.07, 0.08)

0.07 (0.07, 0.07)

0.06 (-0.03, 0.15)

0.06 (0.02, 0.09)

0.12 (0.05, 0.18)

0.06 (0.05, 0.08)

0.05 (0.01, 0.09)0.12 (0.05, 0.18)

-0.00 (-0.11, 0.11)

0.05 (0.04, 0.07)

0.02 (-0.10, 0.15)

0.10 (0.03, 0.17)

0.11 (0.02, 0.20)

0.04 (-0.07, 0.16)

0.07 (0.04, 0.10)

0.20 (0.03, 0.37)

0.05 (0.03, 0.07)

0.08 (0.03, 0.13)

0.07 (-0.02, 0.17)

0.10 (-0.00, 0.20)

0.05 (0.02, 0.07)

0.06 (0.02, 0.10)

-0.11 (-0.15, -0.07)

0.07 (0.06, 0.09)

0.06 (0.04, 0.07)

0.10 (0.01, 0.19)

0.07 (0.03, 0.10)

0.08 (0.04, 0.12)

0.06 (-0.02, 0.14)

0.06 (0.03, 0.09)

0.10 (0.01, 0.18)

0.09 (0.05, 0.12)

100.00

0.66

1.39

3.98

3.04

2.85

3.96

1.67

0.334.34

3.052.53

0.55

0.98

1.38

0.84

5.58

0.66

2.68

1.21

5.00

2.141.26

0.47

4.51

0.40

1.03

0.65

0.46

3.11

0.20

4.41

1.82

0.59

0.54

3.98

2.22

2.29

4.96

4.93

0.69

2.75

2.35

0.86

(D+L)

3.24

0.76

2.72

0.06 (0.05, 0.07)

0.12 (0.02, 0.21)

0.11 (0.06, 0.17)

0.07 (0.05, 0.09)

0.11 (0.07, 0.14)

0.07 (0.03, 0.10)

0.06 (0.04, 0.08)

0.02 (-0.03, 0.07)

0.02 (-0.12, 0.15)0.06 (0.04, 0.08)

0.06 (0.03, 0.09)0.05 (0.01, 0.09)

0.08 (-0.02, 0.18)

0.06 (-0.02, 0.13)

0.05 (-0.01, 0.11)

0.03 (-0.05, 0.11)

0.07 (0.07, 0.08)

0.07 (0.07, 0.07)

0.06 (-0.03, 0.15)

0.06 (0.02, 0.09)

0.12 (0.05, 0.18)

0.06 (0.05, 0.08)

0.05 (0.01, 0.09)0.12 (0.05, 0.18)

-0.00 (-0.11, 0.11)

0.05 (0.04, 0.07)

0.02 (-0.10, 0.15)

0.10 (0.03, 0.17)

0.11 (0.02, 0.20)

0.04 (-0.07, 0.16)

0.07 (0.04, 0.10)

0.20 (0.03, 0.37)

0.05 (0.03, 0.07)

0.08 (0.03, 0.13)

0.07 (-0.02, 0.17)

0.10 (-0.00, 0.20)

0.05 (0.02, 0.07)

0.06 (0.02, 0.10)

-0.11 (-0.15, -0.07)

0.07 (0.06, 0.09)

0.06 (0.04, 0.07)

0.10 (0.01, 0.19)

0.07 (0.03, 0.10)

0.08 (0.04, 0.12)

0.06 (-0.02, 0.14)

ES (95% CI)

0.06 (0.03, 0.09)

0.10 (0.01, 0.18)

0.09 (0.05, 0.12)

100.00

0.66

1.39

3.98

3.04

2.85

3.96

1.67

0.334.34

3.052.53

0.55

0.98

1.38

0.84

5.58

0.66

2.68

1.21

5.00

2.141.26

0.47

4.51

0.40

1.03

0.65

0.46

3.11

0.20

4.41

1.82

0.59

0.54

3.98

2.22

2.29

4.96

4.93

0.69

2.75

2.35

0.86

(D+L)

3.24

0.76

2.72

0-.374 0 .374Effect Size

9

Supplemental Figure 3(c): Meta-analysis of previously published studies in Europeans for the association of rs646776 variant, located in the CELSR2 gene, with LDL-C levels Suppl 60-64


12685

1461

3293

781

4507

587

1686

993

2891

2014

5519

1330

2758

7940

-0.15 (-0.17, -0.14)

-0.14 (-0.17, -0.11)

-0.08 (-0.16, -0.00)

-0.18 (-0.24, -0.12)

-0.29 (-0.49, -0.09)

-0.16 (-0.20, -0.11)

-0.19 (-0.31, -0.07)

-0.15 (-0.21, -0.09)

-0.18 (-0.28, -0.08)

-0.20 (-0.30, -0.10)

-0.17 (-0.23, -0.11)

-0.15 (-0.19, -0.11)

-0.13 (-0.21, -0.05)

-0.19 (-0.25, -0.13)

-0.14 (-0.18, -0.10)

100.00

24.53

3.45

6.13

0.55

8.83

1.53

6.13

2.21

2.21

6.13

13.80

3.45

5.74

15.29

-0.15 (-0.17, -0.14)

-0.14 (-0.17, -0.11)

-0.08 (-0.16, -0.00)

-0.18 (-0.24, -0.12)

-0.29 (-0.49, -0.09)

-0.16 (-0.20, -0.11)

-0.19 (-0.31, -0.07)

-0.15 (-0.21, -0.09)

-0.18 (-0.28, -0.08)

-0.20 (-0.30, -0.10)

-0.17 (-0.23, -0.11)

-0.15 (-0.19, -0.11)

-0.13 (-0.21, -0.05)

-0.19 (-0.25, -0.13)

-0.14 (-0.18, -0.10)

100.00

24.53

3.45

6.13

0.55

8.83

1.53

6.13

2.21

2.21

6.13

13.80

3.45

5.74

15.29

0-.3 -.2 -.1 0

Overall random effect

2008

2009

2008

2008

2008

2008

2008

2008

2008

2008

2008

2009

2008

Kathiresan (FINRISK 97)

Sabatti (NFBC1966)

Wallace (Twins UK)

Sandhu (EPIC-Norfolk Obese)

Sandhu (EPIC-Norfolk Replication)

Sandhu (Ely study)

Kathiresan (MDC-CC)

Kathiresan (NHS98 Malaysia)

Sandhu (1958 British Birth Cohort )

Kathiresan (NHS98 India)

Sandhu (EPIC-Norfolk subcohort)

Aulchenko (Meta-analysis 15 studies)

Kathiresan (DGI)

2008Kathiresan (NHS98 China)

ES (95% CI)%WeightES (95% CI)%WeightNo. of participantsYearAuthor (name of study)

-0.15 (-0.17, -0.14)Overall fixed effect

I2 = 0 (95% CI 0%-55%), p = 0.695

Effect Size

10

Supplemental Figure 3(d): Meta-analysis of previously published studies in Europeans for the association of variant rs662799 (T1131C), located in the ApoA5 gene, with triglyceride levels Suppl 65-80


Overall random effect

Hubacek (Male)

Hubacek (Female)

Helgadottir (PennCATH)

Lee (Japanese American Family)

Talmud (NPHSII)

Grallert (KORA & SAPHIR)

Szalai

Martinelli (Verona Heart Project)

Lee

Vaessen (EPIC-Norfolk)

Aouizerat

Farall (PROCARDIS)

Lai (Framingham Offspring)

Klos (CARDIA)

Evans

Vaverkova

1191

1368

476

154

2537

3264

310

913

438

1800

198

2956

1725

3415

1094

267

0.20 (0.14, 0.26)

0.27 (0.05, 0.49)

0.14 (0.03, 0.25)

0.06 (0.00, 0.12)

0.30 (0.04, 0.57)

0.18 (0.06, 0.31)

0.11 (0.01, 0.21)

0.18 (0.01, 0.35)

0.19 (0.04, 0.34)

0.48 (0.04, 0.93)

0.27 (0.15, 0.39)

0.25 (0.05, 0.44)

0.23 (0.12, 0.34)

0.42 (0.25, 0.58)

0.08 (0.03, 0.14)

0.94 (0.39, 1.50)

0.33 (-0.22, 0.88)

100.00

4.55

8.40

10.64

3.62

7.98

9.05

6.25

6.88

1.56

8.18

5.33

8.40

6.23

10.80

1.06

1.07

0.20 (0.14, 0.26)

0.27 (0.05, 0.49)

0.14 (0.03, 0.25)

0.06 (0.00, 0.12)

0.30 (0.04, 0.57)

0.18 (0.06, 0.31)

0.11 (0.01, 0.21)

0.18 (0.01, 0.35)

0.19 (0.04, 0.34)

0.48 (0.04, 0.93)

0.27 (0.15, 0.39)

0.25 (0.05, 0.44)

0.23 (0.12, 0.34)

0.42 (0.25, 0.58)

0.08 (0.03, 0.14)

0.94 (0.39, 1.50)

0.33 (-0.22, 0.88)

100.00

4.55

8.40

10.64

3.62

7.98

9.05

6.25

6.88

1.56

8.18

5.33

8.40

6.23

10.80

1.06

1.07

00 .2 .4 .6 .8 1

ES (95% CI)%WeightES (95% CI)%WeightNo. of participantsYearAuthor (name of study)

2004

2004

2007

2004

2002

2007

2004

2007

2004

2006

2003

2006

2004

2005

2003

2004

0.14 (0.11, 0.17)Overall fixed effect

I2 = 66 (95% CI 43%-80%), p <0.001

Effect Size

11

References for Supplemental figures 3a-3d

Supplementary references for the SNP rs1800775 (C-629A) and SNP rs708272 (Taq1B)

1. Aulchenko YS, Ripatti S, Lindqvist I, Boomsma D, Heid IM, Pramstaller PP, Penninx BW, Janssens AC, Wilson JF, Spector T, Martin NG, Pedersen NL, Kyvik KO, Kaprio J, Hofman A, Freimer NB, Jarvelin MR, Gyllensten U, Campbell H, Rudan I, Johansson A, Marroni F, Hayward C, Vitart V, Jonasson I, Pattaro C, Wright A, Hastie N, Pichler I, Hicks AA, Falchi M, Willemsen G, Hottenga JJ, De Geus EJ, Montgomery GW, Whitfield J, Magnusson P, Saharinen J, Perola M, Silander K, Isaacs A, Sijbrands EJ, Uitterlinden AG, Witteman JC, Oostra BA, Elliott P, Ruokonen A, Sabatti C, Gieger C, Meitinger T, Kronenberg F, Doring A, Wichmann HE, Smit JH, McCarthy MI, van Duijn CM, Peltonen L. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet 2009;41:47-55.

2. Barzilai N, Atzmon G, Schechter C, Schaefer EJ, Cupples AL, Lipton R, Cheng S, Shuldiner AR. Unique lipoprotein phenotype and genotype associated with exceptional longevity. JAMA 2003;290:2030-40.

3. Bauerfeind A, Knoblauch H, Schuster H, Luft FC, Reich JG. Single nucleotide polymorphism haplotypes in the cholesteryl-ester transfer protein (CETP) gene and lipid phenotypes. Hum Hered 2002;54:166-73.

4. Bernstein MS, Costanza MC, James RW, Morris MA, Cambien F, Raoux S, Morabia A. No physical activity x CETP 1b.-629 interaction effects on lipid profile. Med Sci Sports Exerc 2003;35:1124-9.

5. Blankenberg S, Tiret L, Bickel C, Schlitt A, Jungmair W, Genth-Zotz S, Lubos E, Espinola-Klein C, Rupprecht HJ. [Genetic variation of the cholesterol ester transfer protein gene and the prevalence of coronary artery disease. The AtheroGene case control study]. Z Kardiol 2004;93 Suppl 4:IV16-IV23.

6. Chasman DI, Pare G, Zee RYL, Parker AN, Cook NR, Buring JE, Kwiatkowski DJ, Rose LM, Smith JD, Williams PT, Rieder MJ, Rotter JI, Nickerson DA, Krauss RM, Miletich JP, Ridker PM. Genetic Loci Associated With Plasma Concentration of Low-Density Lipoprotein Cholesterol, High-Density Lipoprotein Cholesterol, Triglycerides, Apolipoprotein A1, and Apolipoprotein B Among 6382 White Women in Genome-Wide Analysis With Replication. Circ Cardiovasc Genet 2008;1:21-30.

7. Dachet C, Poirier O, Cambien F, Chapman J, Rouis M. New functional promoter polymorphism, CETP/-629, in cholesteryl ester transfer protein (CETP) gene related to CETP mass and high density lipoprotein cholesterol levels: role of Sp1/Sp3 in transcriptional regulation. Arterioscler Thromb Vasc Biol 2000;20:507-15.

8. Dullaart RP, Borggreve SE, Hillege HL, Dallinga-Thie GM. The association of HDL cholesterol concentration with the -629C>A CETP promoter polymorphism is not fully explained by its relationship with plasma cholesteryl ester transfer. Scand. J Clin.Lab Invest 67: 2007.

9. Eiriksdottir G, Bolla MK, Thorsson B, Sigurdsson G, Humphries SE, Gudnason V. The -629C>A polymorphism in the CETP gene does not explain the association of TaqIB polymorphism with risk and age of myocardial infarction in Icelandic men. Atherosclerosis 2001;159:187-92.

10. Freeman DJ, Griffin BA, Holmes AP, Lindsay GM, Gaffney D, Packard CJ, Shepherd J. Regulation of plasma HDL cholesterol and subfraction distribution by genetic and environmental factors. Associations between the TaqI B RFLP in the CETP gene and smoking and obesity. Arterioscler Thromb 1994;14:336-44.

11. Heidema AG, Feskens EJ, Doevendans PA, Ruven HJ, van Houwelingen HC, Mariman EC, Boer JM. Analysis of multiple SNPs in genetic association studies: comparison of three multi-locus methods to prioritize and select SNPs. Genet Epidemiol 2007.

12

12. Horne BD, Camp NJ, Anderson JL, Mower CP, Clarke JL, Kolek MJ, Carlquist JF. Multiple less common genetic variants explain the association of the cholesteryl ester transfer protein gene with coronary artery disease. J Am Coll Cardiol 2007;49:2053-60.

13. Kakko S, Tamminen M, Paivansalo M, Kauma H, Rantala AO, Lilja M, Reunanen A, Kesaniemi YA, Savolainen MJ. Variation at the cholesteryl ester transfer protein gene in relation to plasma high density lipoproteins cholesterol levels and carotid intima-media thickness. Eur J Clin Invest 2001;31:593-602.

14. Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, Cooper GM, Roos C, Voight BF, Havulinna AS, Wahlstrand B, Hedner T, Corella D, Tai ES, Ordovas JM, Berglund G, Vartiainen E, Jousilahti P, Hedblad B, Taskinen MR, Newton-Cheh C, Salomaa V, Peltonen L, Groop L, Altshuler DM, Orho-Melander M. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet 2008.

15. McCaskie PA, Beilby JP, Chapman CM, Hung J, McQuillan BM, Thompson PL, Palmer LJ. Cholesteryl ester transfer protein gene haplotypes, plasma high-density lipoprotein levels and the risk of coronary heart disease. Hum Genet 2007;121:401-11.

16. Ridker PM, Pare G, Parker AN, Zee RYL, Miletich JP, Chasman DI. Polymorphism in the CETP Gene Region, HDL Cholesterol, and Risk of Future Myocardial Infarction: Genomewide Analysis Among 18 245 Initially Healthy Women From the Women's Genome Health Study. Circ Cardiovasc Genet 2009;2:26-33.

17. Sabatti C, Service SK, Hartikainen AL, Pouta A, Ripatti S, Brodsky J, Jones CG, Zaitlen NA, Varilo T, Kaakinen M, Sovio U, Ruokonen A, Laitinen J, Jakkula E, Coin L, Hoggart C, Collins A, Turunen H, Gabriel S, Elliot P, McCarthy MI, Daly MJ, Jarvelin MR, Freimer NB, Peltonen L. Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet 2009;41:35-46.

18. Thompson JF, Lira ME, Durham LK, Clark RW, Bamberger MJ, Milos PM. Polymorphisms in the CETP gene and association with CETP mass and HDL levels. Atherosclerosis 2003;167:195-204.

19. Thompson JF, Wood LS, Pickering EH, Dechairo B, Hyde CL. High-density genotyping and functional SNP localization in the CETP gene. J Lipid Res 2007;48:434-43.

20. Tobin MD, Braund PS, Burton PR, Thompson JR, Steeds R, Channer K, Cheng S, Lindpaintner K, Samani NJ. Genotypes and haplotypes predisposing to myocardial infarction: a multilocus case-control study. Eur Heart J 2004;25:459-67.

21. Arca M, Montali A, Ombres D, Battiloro E, Campagna F, Ricci G, Verna R. Lack of association of the common TaqIB polymorphism in the cholesteryl ester transfer protein gene with angiographically assessed coronary atherosclerosis. Clin Genet 2001;60:374-80.

22. Barzilai N, Atzmon G, Schechter C, Schaefer EJ, Cupples AL, Lipton R, Cheng S, Shuldiner AR. Unique lipoprotein phenotype and genotype associated with exceptional longevity. JAMA 2003;290:2030-40.

23. Carr MC, Ayyobi AF, Murdoch SJ, Deeb SS, Brunzell JD. Contribution of hepatic lipase, lipoprotein lipase, and cholesteryl ester transfer protein to LDL and HDL heterogeneity in healthy women. Arterioscler Thromb Vasc Biol 2002;22:667-73.

24. Corella D, Saiz C, Guillen M, Portoles O, Mulet F, Gonzalez JI, Ordovas JM. Association of TaqIB polymorphism in the cholesteryl ester transfer protein gene with plasma lipid levels in a healthy Spanish population. Atherosclerosis 2000;152:367-76.

13

25. Cuchel M, Wolfe ML, deLemos AS, Rader DJ. The frequency of the cholesteryl ester transfer protein-TaqI B2 allele is lower in African Americans than in Caucasians. Atherosclerosis 2002;163:169-74.

26. Deguchi H, Pecheniuk NM, Elias DJ, Averell PM, Griffin JH. High-density lipoprotein deficiency and dyslipoproteinemia associated with venous thrombosis in men. Circulation 2005;112:893-9.

27. Eiriksdottir G, Bolla MK, Thorsson B, Sigurdsson G, Humphries SE, Gudnason V. The -629C>A polymorphism in the CETP gene does not explain the association of TaqIB polymorphism with risk and age of myocardial infarction in Icelandic men. Atherosclerosis 2001;159:187-92.

28. Freeman DJ, Griffin BA, Holmes AP, Lindsay GM, Gaffney D, Packard CJ, Shepherd J. Regulation of plasma HDL cholesterol and subfraction distribution by genetic and environmental factors. Associations between the TaqI B RFLP in the CETP gene and smoking and obesity. Arterioscler Thromb 1994;14:336-44.

29. Freeman DJ, Samani NJ, Wilson V, McMahon AD, Braund PS, Cheng S, Caslake MJ, Packard CJ, Gaffney D. A polymorphism of the cholesteryl ester transfer protein gene predicts cardiovascular events in non-smokers in the West of Scotland Coronary Prevention Study. Eur Heart J 2003 ;24:1833-42.

30. Fumeron F, Betoulle D, Luc G, Behague I, Ricard S, Poirier O, Jemaa R, Evans A, Arveiler D, Marques-Vidal P, . Alcohol intake modulates the effect of a polymorphism of the cholesteryl ester transfer protein gene on plasma high density lipoprotein and the risk of myocardial infarction. J Clin Invest 1995;96:1664-71.

31. Gudnason V, Kakko S, Nicaud V, Savolainen MJ, Kesaniemi YA, Tahvanainen E, Humphries S. Cholesteryl ester transfer protein gene effect on CETP activity and plasma high-density lipoprotein in European populations. The EARS Group. Eur J Clin Invest 1999;29:116-28.

32. Hall WL, Vafeiadou K, Hallund J, Bugel S, Reimann M, Koebnick C, Zunft HJ, Ferrari M, Branca F, Dadd T, Talbot D, Powell J, Minihane AM, Cassidy A, Nilsson M, hlman-Wright K, Gustafsson JA, Williams CM. Soy-isoflavone-enriched foods and markers of lipid and glucose metabolism in postmenopausal women: interactions with genotype and equol production. Am J Clin Nutr 2006;83:592-600.

33. Hannuksela ML, Liinamaa MJ, Kesaniemi YA, Savolainen MJ. Relation of polymorphisms in the cholesteryl ester transfer protein gene to transfer protein activity and plasma lipoprotein levels in alcohol drinkers. Atherosclerosis 1994;110:35-44.

34. Heidema AG, Feskens EJ, Doevendans PA, Ruven HJ, van Houwelingen HC, Mariman EC, Boer JM. Analysis of multiple SNPs in genetic association studies: comparison of three multi-locus methods to prioritize and select SNPs. Genet Epidemiol 2007

35. Horne BD, Camp NJ, Anderson JL, Mower CP, Clarke JL, Kolek MJ, Carlquist JF. Multiple less common genetic variants explain the association of the cholesteryl ester transfer protein gene with coronary artery disease. J Am Coll Cardiol 2007;49:2053-60.

36. Juvonen T, Savolainen MJ, Kairaluoma MI, Lajunen LH, Humphries SE, Kesaniemi YA. Polymorphisms at the apoB, apoA-I, and cholesteryl ester transfer protein gene loci in patients with gallbladder disease. J Lipid Res 1995;36:804-12.

37. Kauma H, Savolainen MJ, Heikkila R, Rantala AO, Lilja M, Reunanen A, Kesaniemi YA. Sex difference in the regulation of plasma high density lipoprotein cholesterol by genetic and environmental factors. Hum Genet 1996;97:156-62.

38. Keavney B, Palmer A, Parish S, Clark S, Youngman L, Danesh J, McKenzie C, Delepine M, Lathrop M, Peto R, Collins R. Lipid-related genes and myocardial infarction in 4685 cases and

14

3460 controls: discrepancies between genotype, blood lipid concentrations, and coronary disease risk. Int J Epidemiol 2004;33:1002-13.

39. Klos KL, Sing CF, Boerwinkle E, Hamon SC, Rea TJ, Clark A, Fornage M, Hixson JE. Consistent effects of genes involved in reverse cholesterol transport on plasma lipid and apolipoprotein levels in CARDIA participants. Arterioscler Thromb Vasc Biol 2006;26:1828-36.

40. Kondo I, Berg K, Drayna D, Lawn R. DNA polymorphism at the locus for human cholesteryl ester transfer protein (CETP) is associated with high density lipoprotein cholesterol and apolipoprotein levels. Clin Genet 1989;35:49-56.

41. Kuivenhoven JA, De KP, Boer JM, Smalheer HA, Botma GJ, Seidell JC, Kastelein JJ, Pritchard PH. Heterogeneity at the CETP gene locus. Influence on plasma CETP concentrations and HDL cholesterol levels. Arterioscler Thromb Vasc Biol 1997;17:560-8.

42. Liu S, Schmitz C, Stampfer MJ, Sacks F, Hennekens CH, Lindpaintner K, Ridker PM. A prospective study of TaqIB polymorphism in the gene coding for cholesteryl ester transfer protein and risk of myocardial infarction in middle-aged men. Atherosclerosis 2002;161:469-74.

43. McCaskie PA, Beilby JP, Chapman CM, Hung J, McQuillan BM, Thompson PL, Palmer LJ. Cholesteryl ester transfer protein gene haplotypes, plasma high-density lipoprotein levels and the risk of coronary heart disease. Hum Genet 2007;121:401-11.

44. Miltiadous G, Hatzivassiliou M, Liberopoulos E, Bairaktari E, Tselepis A, Cariolou M, Elisaf M. Gene polymorphisms affecting HDL-cholesterol levels in the normolipidemic population. Nutr Metab Cardiovasc Dis 2005;15:219-24.

45. Mitchell RJ, Earl L, Williams J, Bisucci T, Gasiamis H. Polymorphisms of the gene coding for the cholesteryl ester transfer protein and plasma lipid levels in Italian and Greek migrants to Australia. Hum Biol 1994;66:13-25.

46. Nettleton JA, Steffen LM, Ballantyne CM, Boerwinkle E, Folsom AR. Associations between HDL-cholesterol and polymorphisms in hepatic lipase and lipoprotein lipase genes are modified by dietary fat intake in African American and White adults. Atherosclerosis 2006.

47. Noone E, Roche HM, Black I, Tully AM, Gibney MJ. Effect of postprandial lipaemia and Taq 1B polymorphism of the cholesteryl ester transfer protein (CETP) gene on CETP mass, activity, associated lipoproteins and plasma lipids. Br J Nutr 2000;84:203-9.

48. Pai JK, Pischon T, Ma J, Manson JE, Hankinson SE, Joshipura K, Curhan GC, Rifai N, Cannuscio CC, Stampfer MJ, Rimm EB. Inflammatory markers and the risk of coronary heart disease in men and women. N Engl J Med 2004;351:2599-610.

49. Plat J, Mensink RP. Relationship of genetic variation in genes encoding apolipoprotein A-IV, scavenger receptor BI, HMG-CoA reductase, CETP and apolipoprotein E with cholesterol metabolism and the response to plant stanol ester consumption. Eur J Clin Invest 2002;32:242-50.

50. Ridker PM, Pare G, Parker AN, Zee RYL, Miletich JP, Chasman DI. Polymorphism in the CETP Gene Region, HDL Cholesterol, and Risk of Future Myocardial Infarction: Genomewide Analysis Among 18 245 Initially Healthy Women From the Women's Genome Health Study. Circ Cardiovasc Genet 2009;2:26-33.

51. Riemens SC, van TA, Stulp BK, Dullaart RP. Influence of insulin sensitivity and the TaqIB cholesteryl ester transfer protein gene polymorphism on plasma lecithin:cholesterol acyltransferase and lipid transfer protein activities and their response to hyperinsulinemia in non-diabetic men. J Lipid Res 1999;40:1467-74.

15

52. Sandhofer A, Tatarczyk T, Laimer M, Ritsch A, Kaser S, Paulweber B, Ebenbichler CF, Patsch JR. The Taq1B-variant in the Cholesteryl Ester-Transfer Protein Gene and the Risk of Metabolic Syndrome. Obesity (Silver Spring) 2008.

53. Sorli JV, Corella D, Frances F, Ramirez JB, Gonzalez JI, Guillen M, Portoles O. The effect of the APOE polymorphism on HDL-C concentrations depends on the cholesterol ester transfer protein gene variation in a Southern European population. Clin Chim Acta 2006;366:196-203.

54. Talmud PJ, Hawe E, Robertson K, Miller GJ, Miller NE, Humphries SE. Genetic and environmental determinants of plasma high density lipoprotein cholesterol and apolipoprotein AI concentrations in healthy middle-aged men. Ann Hum Genet 2002;66:111-24.

55. Tenkanen H, Koshinen P, Kontula K, alto-Setala K, Manttari M, Manninen V, Runeberg SL, Taskinen MR, Ehnholm C. Polymorphisms of the gene encoding cholesterol ester transfer protein and serum lipoprotein levels in subjects with and without coronary heart disease. Hum Genet 1991;87:574-8.

56. Thompson JF, Lira ME, Durham LK, Clark RW, Bamberger MJ, Milos PM. Polymorphisms in the CETP gene and association with CETP mass and HDL levels. Atherosclerosis 2003;167:195-204.

57. Thompson JF, Wood LS, Pickering EH, Dechairo B, Hyde CL. High-density genotyping and functional SNP localization in the CETP gene. J Lipid Res 2007;48:434-43.

58. Vohl MC, Lamarche B, Pascot A, Leroux G, Prud'homme D, Bouchard C, Nadeau A, Despres JP. Contribution of the cholesteryl ester transfer protein gene TaqIB polymorphism to the reduced plasma HDL-cholesterol levels found in abdominal obese men with the features of the insulin resistance syndrome. Int J Obes Relat Metab Disord 1999;23:918-25.

59. Weitgasser R, Galvan G, Malaimare L, Derflinger I, Hedegger M, Lang J, Iglseder B, Ladurner G, Paulweber B. Cholesteryl ester transfer protein TaqIB polymorphism and its relation to parameters of the insulin resistance syndrome in an Austrian cohort. Biomed Pharmacother 2004;58:619-27.

Supplementary references for the SNP rs646776 located in the CELSR2 gene

60. Aulchenko YS, Ripatti S, Lindqvist I, Boomsma D, Heid IM, Pramstaller PP, Penninx BW, Janssens AC, Wilson JF, Spector T, Martin NG, Pedersen NL, Kyvik KO, Kaprio J, Hofman A, Freimer NB, Jarvelin MR, Gyllensten U, Campbell H, Rudan I, Johansson A, Marroni F, Hayward C, Vitart V, Jonasson I, Pattaro C, Wright A, Hastie N, Pichler I, Hicks AA, Falchi M, Willemsen G, Hottenga JJ, de Geus EJ, Montgomery GW, Whitfield J, Magnusson P, Saharinen J, Perola M, Silander K, Isaacs A, Sijbrands EJ, Uitterlinden AG, Witteman JC, Oostra BA, Elliott P, Ruokonen A, Sabatti C, Gieger C, Meitinger T, Kronenberg F, Döring A, Wichmann HE, Smit JH, McCarthy MI, van Duijn CM, Peltonen L; ENGAGE Consortium. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet. 2009;41:47-55

61. Sabatti C, Service SK, Hartikainen AL, Pouta A, Ripatti S, Brodsky J, Jones CG, Zaitlen NA, Varilo

T, Kaakinen M, Sovio U, Ruokonen A, Laitinen J, Jakkula E, Coin L, Hoggart C, Collins A, Turunen H, Gabriel S, Elliot P, McCarthy MI, Daly MJ, Järvelin MR, Freimer NB, Peltonen L. Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet. 2009;41:35-46.

62. Sandhu MS, Waterworth DM, Debenham SL, Wheeler E, Papadakis K, Zhao JH, Song K, Yuan X,

Johnson T, Ashford S, Inouye M, Luben R, Sims M, Hadley D, McArdle W, Barter P, Kesäniemi YA, Mahley RW, McPherson R, Grundy SM; Wellcome Trust Case Control Consortium, Bingham SA, Khaw KT, Loos RJ, Waeber G, Barroso I, Strachan DP, Deloukas P, Vollenweider P, Wareham NJ, Mooser V. LDL-cholesterol concentrations: a genome-wide association study. Lancet. 2008 9;371:483-91.

16

63. Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, Cooper GM, Roos C, Voight BF, Havulinna AS, Wahlstrand B, Hedner T, Corella D, Tai ES, Ordovas JM, Berglund G, Vartiainen E, Jousilahti P, Hedblad B, Taskinen MR, Newton-Cheh C, Salomaa V, Peltonen L, Groop L, Altshuler DM, Orho-Melander M. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet. 2008;40:189-97. Epub 2008 Jan 13. Erratum in: Nat Genet. 2008;40(11):1384.

64. Wallace C, Newhouse SJ, Braund P, Zhang F, Tobin M, Falchi M, Ahmadi K, Dobson RJ, Marçano

AC, Hajat C, Burton P, Deloukas P, Brown M, Connell JM, Dominiczak A, Lathrop GM, Webster J, Farrall M, Spector T, Samani NJ, Caulfield MJ, Munroe PB. Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia. Am J Hum Genet. 2008;82:139-49.

Supplementary reference for SNP rs662799 (T1131C) located in the ApoA5 gene

65. Klos KL, Hamon S, Clark AG, Boerwinkle E, Liu K, Sing CF. APOA5 polymorphismsinfluence

plasma triglycerides in young, healthy African Americans and whites of the CARDIA Study. J Lipid Res. 2005;46:564-71

66. Grallert H, Sedlmeier EM, Huth C, Kolz M, Heid IM, Meisinger C, Herder C, Strassburger K,

Gehringer A, Haak M, Giani G, Kronenberg F, Wichmann HE, Adamski J, Paulweber B, Illig T, Rathmann W. APOA5 variants and metabolic syndrome in Caucasians. J Lipid Res. 2007;48:2614-21

67. Talmud PJ, Hawe E, Martin S, Olivier M, Miller GJ, Rubin EM, Pennacchio LA, Humphries SE.

Relative contribution of variation within the APOC3/A4/A5 gene cluster in determining plasma triglycerides. Hum Mol Genet. 2002;11:3039-46

68. Vaessen SF, Schaap FG, Kuivenhoven JA, Groen AK, Hutten BA, Boekholdt SM, Hattori H,

Sandhu MS, Bingham SA, Luben R, Palmen JA, Wareham NJ, Humphries SE, Kastelein JJ, Talmud PJ, Khaw KT. Apolipoprotein A-V, triglycerides and risk of coronary artery disease: the prospective Epic-Norfolk Population Study. J Lipid Res. 2006;47:2064-70

69. Vaessen SF, Schaap FG, Kuivenhoven JA, Groen AK, Hutten BA, Boekholdt SM, Hattori H,

Sandhu MS, Bingham SA, Luben R, Palmen JA, Wareham NJ, Humphries SE, Kastelein JJ, Talmud PJ, Khaw KT. Apolipoprotein A-V, triglycerides and risk of coronary artery disease: the prospective Epic-Norfolk Population Study. J Lipid Res.2006 ;47:2064-70

70. Lai CQ, Demissie S, Cupples LA, Zhu Y, Adiconis X, Parnell LD, Corella D, Ordovas JM. Influence

of the APOA5 locus on plasma triglyceride, lipoprotein subclasses, and CVD risk in the Framingham Heart Study. J Lipid Res. 2004;45:2096-105

71. Hubacek JA, Skodova Z, Adamkova V, Lanska V, Poledne R. The influence of APOAV

polymorphisms (T-1131>C and S19>W) on plasma triglyceride levels and risk of myocardial infarction. Clin Genet. 2004;65:126-30

72. Evans D, Buchwald A, Beil FU. The single nucleotide polymorphism -1131T>C in the

apolipoprotein A5 (APOA5) gene is associated with elevated triglycerides in patients with hyperlipidemia. J Mol Med. 2003;81:645-54

73. Martinelli N, Trabetti E, Bassi A, Girelli D, Friso S, Pizzolo F, Sandri M, Malerba G, Pignatti PF,

Corrocher R, Olivieri O. The -1131 T>C and S19W APOA5 gene polymorphisms are associated with high levels of triglycerides and apolipoprotein CIII, but not with coronary artery disease: an angiographic study. Atherosclerosis. 2007;191:409-17

74. Lee KW, Ayyobi AF, Frohlich JJ, Hill JS. APOA5 gene polymorphism modulates levels of

triglyceride, HDL cholesterol and FERHDL but is not a risk factor for coronary artery disease. Atherosclerosis. 2004 Sep;176(1):165-72Lee KW, Ayyobi AF, Frohlich JJ, Hill JS. APOA5 gene

17

polymorphism modulates levels of triglyceride, HDL cholesterol and FERHDL but is not a risk factor for coronary artery disease. Atherosclerosis. 2004;176:165-72

75. Szalai C, Keszei M, Duba J, Prohaszka Z, Kozma GT, Csaszar A, Balogh S, Almassy Z, Fust G,

Czinner A. Polymorphism in the promoter region of the apolipoprotein A5 gene is associated with an increased susceptibility for coronary artery disease. Atherosclerosis. 2004;173:109-14

76. Vaverkova H, Novotn D, Kar sek D, Bud kov. Slav L, Hutyra, Halenka M. Polymorphism T-1131C

(SNP3) of apoAV gene increases triglycerides levels independently of the presence of insulin resistance. Abstract, 74th EAS Congress, 2004.

77. Aouizerat BE, Kulkarni M, Heilbron D, Drown D, Raskin S, Pullinger CR, Malloy MJ, Kane JP.

Genetic analysis of a polymorphism in the human apoA-V gene: effect on plasma lipids. J Lipid Res. 2003;44:1167-73

78. Lee KW, Ayyobi AF, Frohlich JJ, Hill JS. APOA5 gene polymorphism modulates levels of

triglyceride, HDL cholesterol and FERHDL but is not a risk factor for coronary artery disease. Atherosclerosis. 2004;176:165-72

79. Farrall M, Green FR, Peden JF, Olsson PG, Clarke R, Hellenius ML, Rust S, Lagercrantz J,

Franzosi MG, Schulte H, Carey A, Olsson G, Assmann G, Tognoni G, Collins R, Hamsten A, Watkins H. Genome-wide mapping of susceptibility to coronary artery disease identifies a novel replicated locus on chromosome 17. PLoS Genet. 2006;2:e72

80. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, Jonasdottir

A, Sigurdsson A, Baker A, Palsson A, Masson G, Gudbjartsson DF, Magnusson KP, Andersen K, Levey AI, Backman VM, Matthiasdottir S, Jonsdottir T, Palsson S, Einarsdottir H, Gunnarsdottir S, Gylfason A, Vaccarino V, Hooper WC, Reilly MP, Granger CB, Austin H, Rader DJ, Shah SH, Quyyumi AA, Gulcher JR, Thorgeirsson G, Thorsteinsdottir U, Kong A, Stefansson K. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science. 2007;316:1491-3

18

Supplemental Figure 4: Effect modification of genetic effects by gender, ghee consumption and tobacco consumption in Pakistanis

Log triglyceridesrs1260326GCKR

Rs271LPL

rs651821APOA5/ZNF259

LDL-CRs646776CELSR2

HDL-Crs711752CETP

Lipid traitSNPGene

Gender

Oil type

Tobacco

Gender

Oil type

Tobacco

Gender

Oil type

Tobacco

Gender

Oil type

Tobacco

Gender

Oil type

Tobacco

malefemale

gheeoilcombination

EverCurrent

malefemale

gheeoilcombination

EverCurrent

malefemale

gheeoilcombination

EverCurrent

malefemale

gheeoilcombination

EverCurrent

malefemale

gheeoilcombination

EverCurrent

Subgroup

2,558 578

4491,925635

1,625 1,426

2,559 578

4501,925635

1,625 1,427

2,557578

4491,924 635

1,624 1,426

2,424 498

4381,769601

1,486 1,357

2,440 505

4411,785603

1,504 1,360

No. of participants

0.03 (-0.04, 0.10)0.09 (-0.05, 0.23)

0.09 (0.05, 0.13)0.05 (-0.08, 0.18)0.05 (-0.07, 0.17)

0.08 (0.04, 0.12)0.07 (-0.03, 0.18)

-0.09 (-0.18, -0.01)-0.08 (-0.26, 0.10)

-0.07 (-0.12, -0.02)-0.12 (-0.28, 0.03)-0.06 (-0.20, 0.08)

-0.10 (-0.15, -0.05)-0.05 (-0.18, 0.07)

0.13 (0.05, 0.21)0.15 (-0.03, 0.32)

0.12 (0.08, 0.17)0.06 (-0.09, 0.22)0.24 (0.10, 0.38)

0.11 (0.06, 0.16)0.16 (0.04, 0.29)

-0.09 (-0.26, 0.08)-0.16 (-0.52, 0.19)

-0.20 (-0.29, -0.11)-0.03 (-0.31, 0.25)-0.14 (-0.40, 0.11)

-0.18 (-0.28, -0.09)-0.13 (-0.36, 0.10)

0.06 (0.04, 0.09)0.05 (-0.01, 0.11)

0.05 (0.03, 0.06)0.06 (0.01, 0.11)0.06 (0.02, 0.11)

0.05 (0.03, 0.07)0.05 (0.01, 0.09)

0.13

0.50

0.78

0.82

0.60

0.27

0.78

0.01

0.16

0.44

0.24

0.46

0.32

0.49

0.71

Interaction p-value

0.03 (-0.04, 0.10)0.09 (-0.05, 0.23)

0.09 (0.05, 0.13)0.05 (-0.08, 0.18)0.05 (-0.07, 0.17)

0.08 (0.04, 0.12)0.07 (-0.03, 0.18)

-0.09 (-0.18, -0.01)-0.08 (-0.26, 0.10)

-0.07 (-0.12, -0.02)-0.12 (-0.28, 0.03)-0.06 (-0.20, 0.08)

-0.10 (-0.15, -0.05)-0.05 (-0.18, 0.07)

0.13 (0.05, 0.21)0.15 (-0.03, 0.32)

0.12 (0.08, 0.17)0.06 (-0.09, 0.22)0.24 (0.10, 0.38)

0.11 (0.06, 0.16)0.16 (0.04, 0.29)

-0.09 (-0.26, 0.08)-0.16 (-0.52, 0.19)

-0.20 (-0.29, -0.11)-0.03 (-0.31, 0.25)-0.14 (-0.40, 0.11)

-0.18 (-0.28, -0.09)-0.13 (-0.36, 0.10)

0.06 (0.04, 0.09)0.05 (-0.01, 0.11)

0.05 (0.03, 0.06)0.06 (0.01, 0.11)0.06 (0.02, 0.11)

0.05 (0.03, 0.07)0.05 (0.01, 0.09)

Change in lipid trait (mmol/L) per copy of the minor allele (95% CI)

0-.516 0 .516

Lipid level (mmol/L) and 95% confidence intervalsAnalyses are presented only for the lead SNPs at loci that showed highly signficant associations with lipid traits (P < 10-6)Size of data markers are proportional to the inverse of the variance of the minor allele effect. P-values were derived from F tests of the interaction terms fitted in linear regression models of each lipid trait, adjusted for age, gender, the first two principle components and case-control status.

19

9

20

1

16

16

16

16

16

19

2

15

16

16

16

8

9

12

16

16

1

15

8

18

CETP

CETP

rs1883025

LPL

rs1800961

rs2144300

rs5882

rs1800775

APOB

rs1800777CETP

rs5880

APOE

HNF4A

rs255052

GALNT2

rs157580

LIPC

rs693

CETP

CETP

LPL

ABCA1

rs1800588

rs7499892

CETP

rs3764261

rs2197089

CETP

LIPC

rs3890182

DPEP2

rs2338104

rs1864163

KCTD10

rs711752

rs4846914

rs261332

CETP

ABCA1

rs328

rs1532624

rs2156552(intergenic)

GALNT2

CETP

A

A

A

C

G

A

G

A

G

T

T

A

A

A

T

C

A

T

A

A

G

T

A

2451

2451

3023

2434

3021

3023

3024

3024

2451

30242452

3024

2449

2451

3024

2450

3015

2452

3024

2443

2452

2451

2451

3024

3023

2448

3023

3001

2452

2451

3024

2449

3023

3024

2451

3023

3022

3022

2451

2451

3024

3023

30202451

2452

2451

0.06 (0.04, 0.07)

-0.07 (-0.10, -0.04)

-0.01 (-0.03, -0.00)

0.02 (0.01, 0.04)

-0.01 (-0.05, 0.03)

0.00 (-0.01, 0.02)

0.02 (0.01, 0.04)

-0.05 (-0.06, -0.03)

-0.02 (-0.03, -0.00)

-0.06 (-0.10, -0.03)-0.07 (-0.11, -0.03)

-0.06 (-0.09, -0.04)

0.00 (-0.01, 0.02)

-0.07 (-0.12, -0.03)

0.03 (0.01, 0.04)

0.02 (0.00, 0.03)

0.01 (-0.00, 0.02)

0.04 (0.02, 0.05)

-0.01 (-0.02, 0.00)

-0.06 (-0.08, -0.05)

0.03 (0.02, 0.05)

0.05 (0.03, 0.07)

-0.03 (-0.05, -0.01)

0.02 (0.01, 0.03)

-0.04 (-0.06, -0.03)

0.06 (0.04, 0.07)

0.05 (0.04, 0.06)

0.00 (-0.01, 0.02)

-0.06 (-0.08, -0.04)

0.04 (0.02, 0.06)

-0.01 (-0.03, 0.01)

0.03 (0.01, 0.05)

0.01 (-0.00, 0.02)

-0.04 (-0.06, -0.03)

0.00 (-0.01, 0.02)

0.05 (0.04, 0.06)

0.00 (-0.01, 0.02)

0.02 (0.01, 0.04)

-0.06 (-0.08, -0.05)

-0.02 (-0.04, -0.01)

0.02 (-0.00, 0.04)

0.04 (0.03, 0.06)

-0.02 (-0.04, -0.00)-0.00 (-0.02, 0.02)

0.02 (0.00, 0.03)

0.06 (0.04, 0.07)

.32

.05

.35

.55

.03

.45

.43

.4

.46

.04

.04

.08

.36

.04

.19

.58

.47

.22

.27

.27

.32

.11

.12

.25

.22

.43

.34

.44

.18

.23

.08

.15

.44

.22

.57

.47

.45

.19

.53

.26

.10

.48

.14

.15

.58

.42

1.1e-13

5.2e-05

3.4e-02

5.4e-03

5.3e-01

5.1e-01

5.4e-04

3.0e-12

4.4e-02

1.8e-042.8e-04

7.9e-08

5.4e-01

8.8e-04

5.4e-04

2.1e-02

1.9e-01

8.7e-05

1.6e-01

2.4e-13

3.8e-05

2.6e-05

5.9e-03

7.3e-03

3.8e-08

8.7e-15

1.2e-12

6.0e-01

8.5e-11

1.2e-05

3.8e-01

6.0e-03

1.8e-01

1.6e-08

5.0e-01

4.7e-14

4.9e-01

5.5e-03

3.7e-17

4.2e-03

5.8e-02

4.1e-12

2.6e-026.9e-01

2.2e-02

5.0e-15

0.06 (0.04, 0.07)

-0.07 (-0.10, -0.04)

-0.01 (-0.03, -0.00)

0.02 (0.01, 0.04)

-0.01 (-0.05, 0.03)

0.00 (-0.01, 0.02)

0.02 (0.01, 0.04)

-0.05 (-0.06, -0.03)

-0.02 (-0.03, -0.00)

-0.06 (-0.10, -0.03)-0.07 (-0.11, -0.03)

-0.06 (-0.09, -0.04)

0.00 (-0.01, 0.02)

-0.07 (-0.12, -0.03)

0.03 (0.01, 0.04)

0.02 (0.00, 0.03)

0.01 (-0.00, 0.02)

0.04 (0.02, 0.05)

-0.01 (-0.02, 0.00)

-0.06 (-0.08, -0.05)

0.03 (0.02, 0.05)

0.05 (0.03, 0.07)

-0.03 (-0.05, -0.01)

0.02 (0.01, 0.03)

-0.04 (-0.06, -0.03)

0.06 (0.04, 0.07)

0.05 (0.04, 0.06)

0.00 (-0.01, 0.02)

-0.06 (-0.08, -0.04)

0.04 (0.02, 0.06)

-0.01 (-0.03, 0.01)

0.03 (0.01, 0.05)

0.01 (-0.00, 0.02)

-0.04 (-0.06, -0.03)

0.00 (-0.01, 0.02)

0.05 (0.04, 0.06)

0.00 (-0.01, 0.02)

0.02 (0.01, 0.04)

-0.06 (-0.08, -0.05)

-0.02 (-0.04, -0.01)

0.02 (-0.00, 0.04)

0.04 (0.03, 0.06)

-0.02 (-0.04, -0.00)-0.00 (-0.02, 0.02)

0.02 (0.00, 0.03)

0.06 (0.04, 0.07)

.32

.35

.55

.45

.43

.40

.46

.36

.19

.58

.47

.22

.27

.27

.32

.11

.12

.25

.22

.43

.34

.44

.18

.23

.15

.44

.22

.57

.47

.45

.19

.53

.26

.48

.14

.15

.58

.42

0-.1 -.05 0 .05 .1

Minor allele

Number of subjects P-value

for associationMean difference(95% CI)

MAFSNPGene

Chr

PROMISLURIC

0.15

0.10

0.74

0.92

0.02

0.10

0.87

0.19

0.10

0.67

0.52

0.28

0.63

0.30

0.13

0.16

0.08

0.09

0.69

0.09

0.08

0.30

0.35

P-value for difference

between studies

genome wide association studies in association with HDL-C levels

Supplemental Figure 5(a): Association with HDL-C (mmol/l) in PROMIS and LURIC participants of SNPs discovered in previous genome wide association studies in association with HDL-C levels

20

19

19

5

5

1

19

11

11

19

2

19

1

6

2

11

rs16996148

HMGCR

rs2228671

rs12654264

rs3846662

LDLR

FADS2

rs646776

APOE

rs6511720

rs102275

rs1535

HMGCR

rs2075650

rs7575840

rs157580

APOB

CELSR2

FADS1

APOE

LDLR

(intergenic)

rs599839

rs2254287

CILP2

FADS1

CELSR2

COL11A2

rs693

rs174570

T

A

A

T

G

T

C

G

C

A

G

G

C

T

T

3013

1175

3015

3014

3015

1177

1176

3014

1175

3015

3013

3009

1175

3014

3015

3006

1176

1175

1175

1177

1176

1176

3013

3014

1176

1175

1176

1174

3015

3013

-0.03 (-0.13, 0.07)

-0.01 (-0.07, 0.06)

-0.06 (-0.18, 0.06)

-0.03 (-0.09, 0.04)

-0.02 (-0.08, 0.04)

-0.07 (-0.17, 0.03)

-0.04 (-0.13, 0.06)

-0.15 (-0.23, -0.08)

0.01 (-0.06, 0.07)

-0.08 (-0.19, 0.04)

-0.11 (-0.19, -0.03)

-0.10 (-0.18, -0.02)

-0.00 (-0.07, 0.06)

0.06 (-0.03, 0.15)

0.01 (-0.08, 0.09)

0.06 (0.00, 0.12)

0.03 (-0.04, 0.09)

-0.01 (-0.09, 0.06)

-0.04 (-0.11, 0.03)

0.07 (-0.02, 0.17)

-0.11 (-0.20, -0.01)

0.06 (-0.01, 0.13)

-0.16 (-0.23, -0.08)

0.05 (-0.01, 0.11)

-0.07 (-0.18, 0.04)

-0.04 (-0.11, 0.03)

-0.02 (-0.09, 0.06)

-0.01 (-0.07, 0.06)

0.01 (-0.06, 0.07)

-0.16 (-0.27, -0.05)

.11

.63

.07

.42

.41

.13

.13

.25

.35

.08

.20

.18

.58

.11

.16

.47

.45

.24

.30

.14

.13

.25

.49

.10

.31

.24

.58

.27

.08

5.1e-01

8.5e-01

3.5e-01

4.0e-01

5.5e-01

1.6e-01

4.5e-01

3.4e-05

8.5e-01

1.9e-01

4.5e-03

1.4e-02

9.7e-01

2.0e-01

8.6e-01

4.6e-02

4.4e-01

7.2e-01

2.5e-01

1.2e-01

3.7e-02

8.8e-02

2.7e-05

1.3e-01

1.9e-01

2.6e-01

6.7e-01

8.0e-01

8.9e-01

3.5e-03

-0.03 (-0.13, 0.07)

-0.01 (-0.07, 0.06)

-0.06 (-0.18, 0.06)

-0.03 (-0.09, 0.04)

-0.02 (-0.08, 0.04)

-0.07 (-0.17, 0.03)

-0.04 (-0.13, 0.06)

-0.15 (-0.23, -0.08)

0.01 (-0.06, 0.07)

-0.08 (-0.19, 0.04)

-0.11 (-0.19, -0.03)

-0.10 (-0.18, -0.02)

-0.00 (-0.07, 0.06)

0.06 (-0.03, 0.15)

0.01 (-0.08, 0.09)

0.06 (0.00, 0.12)

0.03 (-0.04, 0.09)

-0.01 (-0.09, 0.06)

-0.04 (-0.11, 0.03)

0.07 (-0.02, 0.17)

-0.11 (-0.20, -0.01)

0.06 (-0.01, 0.13)

-0.16 (-0.23, -0.08)

0.05 (-0.01, 0.11)

-0.07 (-0.18, 0.04)

-0.04 (-0.11, 0.03)

-0.02 (-0.09, 0.06)

-0.01 (-0.07, 0.06)

0.01 (-0.06, 0.07)

-0.16 (-0.27, -0.05)

.11

.63

.42

.41

.13

.13

.25

.35

.08

.18

.58

.11

.16

.47

.45

.24

.14

.13

.30

.25

.49

.31

.24

.58

.27

Minor allele

Number of participants P-value

for associationMean difference(95% CI)

MAFSNPGene

Chr

PROMIS

LURIC

Effect size

0-.2 -.15 -.1 -.05 0 .05 .1 .15

0.04

0.75

0.64

0.03

0.02

0.19

0.89

0.05

0.06

0.91

0.46

0.78

0.51

0.38

0.05

P-value fordifference

between studies

Supplemental Figure 5(b): Association with LDL-C (mmol/l) in PROMIS and LURIC participants of SNPs discovered in previous genome wide association studies in association with LDL-C levels

21

8

2

11

7

19

8

2

1

2

19

2

7

1

8

11

19

1

(intergenic)

GALNT2

DOCK7

CILP2

rs328

APOE

APOE

(intergenic)

rs780094

rs12286037

LPL

rs17145738

rs16996148

APOB

GCKR

GCKR

rs17321515

rs673548

rs4846914

rs1260326

rs439401

APOBrs693

rs714052

ZNF259

BAZ1B

rs12130333

APOA5

rs2197089

rs662799

rs157580

TBL2

rs1748195

LPL

G

T

T

T

T

C

A

A

T

C

T

G

T

A

C

G

G

2451

2450

2440

2451

3197

2449

2426

2450

3185

3197

2451

3197

3195

2451

2451

2449

3197

3196

3194

3196

3183

24513197

3193

2452

2451

3197

2451

3172

3195

3188

2451

3195

2434

-0.02 (-0.05, 0.01)

-0.03 (-0.05, 0.00)

-0.02 (-0.05, 0.01)

-0.11 (-0.16, -0.06)

-0.08 (-0.13, -0.03)

-0.02 (-0.05, 0.01)

0.04 (0.02, 0.07)

-0.03 (-0.06, -0.00)

0.07 (0.04, 0.11)

0.12 (0.06, 0.19)

-0.12 (-0.17, -0.08)

-0.09 (-0.14, -0.05)

-0.05 (-0.09, -0.01)

-0.04 (-0.07, -0.01)

0.08 (0.05, 0.10)

0.08 (0.05, 0.11)

-0.01 (-0.04, 0.01)

-0.04 (-0.06, -0.01)

-0.02 (-0.04, 0.01)

0.08 (0.05, 0.11)

0.04 (0.01, 0.07)

0.02 (-0.00, 0.05)0.03 (-0.00, 0.06)

-0.08 (-0.12, -0.03)

0.08 (0.03, 0.13)

-0.02 (-0.06, 0.03)

-0.04 (-0.07, -0.00)

0.14 (0.09, 0.19)

-0.02 (-0.05, 0.01)

0.14 (0.11, 0.18)

-0.03 (-0.06, -0.01)

-0.02 (-0.06, 0.03)

-0.06 (-0.08, -0.03)

-0.04 (-0.07, -0.02)

.20

.58

.31

.36

.61

.48

.26

.04

.11

.11

.22

.44

.44

.37

.49

.45

.26

.45

.46

.27

.10

.068

.11

.17

.06

.44

.17

.47

.11

.45

.55

2.5e-01

6.8e-02

1.3e-01

6.5e-06

6.5e-04

1.9e-01

1.9e-03

3.5e-02

2.6e-06

2.8e-04

2.2e-08

7.3e-05

2.5e-02

6.8e-03

7.2e-09

3.9e-09

3.3e-01

5.7e-03

2.4e-01

9.0e-07

4.1e-03

9.1e-028.1e-02

1.0e-03

2.2e-03

4.9e-01

4.6e-02

1.3e-07

1.7e-01

1.2e-14

1.6e-02

4.5e-01

2.6e-05

1.8e-03

-0.02 (-0.05, 0.01)

-0.03 (-0.05, 0.00)

-0.02 (-0.05, 0.01)

-0.11 (-0.16, -0.06)

-0.08 (-0.13, -0.03)

-0.02 (-0.05, 0.01)

0.04 (0.02, 0.07)

-0.03 (-0.06, -0.00)

0.07 (0.04, 0.11)

0.12 (0.06, 0.19)

-0.12 (-0.17, -0.08)

-0.09 (-0.14, -0.05)

-0.05 (-0.09, -0.01)

-0.04 (-0.07, -0.01)

0.08 (0.05, 0.10)

0.08 (0.05, 0.11)

-0.01 (-0.04, 0.01)

-0.04 (-0.06, -0.01)

-0.02 (-0.04, 0.01)

0.08 (0.05, 0.11)

0.04 (0.01, 0.07)

0.02 (-0.00, 0.05)0.03 (-0.00, 0.06)

-0.08 (-0.12, -0.03)

0.08 (0.03, 0.13)

-0.02 (-0.06, 0.03)

-0.04 (-0.07, -0.00)

0.14 (0.09, 0.19)

-0.02 (-0.05, 0.01)

0.14 (0.11, 0.18)

-0.03 (-0.06, -0.01)

-0.02 (-0.06, 0.03)

-0.06 (-0.08, -0.03)

-0.04 (-0.07, -0.02)

.58

.31

.09

.10

.36

.61

.48

.26

.11

.10

.11

.22

.44

.44

.37

.49

.45

.26

.45

.46

.27

.068

.11

.17

.44

.17

.47

.11

.45

.55

0-.15 -.1 -.05 0 .05 .1 .15 .2

Minor allele

Number of participants

P-valuefor association

Mean difference(95% CI)

MAFSNPChr

PROMIS

LURIC

0.81

0.07

0.73

0.07

0.07

0.02

0.68

0.80

0.50

0.12

0.69

0.69

0.39

0.65

0.48

0.86

0.09

P-value for difference

between studies

Supplemental Figure 5(c): Association with log triglycerides (mmol/l) in PROMIS and LURIC participants of SNPs discovered in previous genome wide association studies in association with triglyceride levels

WebFigures 4 (a-b): Estimates represent the per-minor allele increase in lipid levels, adjusted for age, sex, the first two principal components and case-control status. The P-value for difference between studies corresponds to a test of nullity of interaction term between study and the SNP of interest. Boxes are proportional to the inverse of the variance of study estimates. Chr: chromosome, SNP: Single Nucleotide Polymorphism, MAF: minor allele frequency

22

Supplemental Figure 6(a): Comparison of linkage disequilibrium in PROMIS and LURIC participants for genes with nominally significant associations with HDL-C concentration

23

Supplemental Figure 6(b): Comparison of linkage disequilibrium in PROMIS and LURIC participants for genes with nominally significant associations with triglyceride concentration

24

Supplemental Figure 6(c): Comparison of linkage disequilibrium in PROMIS and LURIC participants for genes with nominally significant associations with LDL-C concentration

25

Supplemental Figure 7(a): Association with MI for SNPs associated with high density cholesterol in PROMIS

rs12708967

rs11508026

rs9939224

rs255052

rs17231506

rs1800777rs5882

rs2156552

rs1864163

rs261332

rs12720922

rs11076175

rs3764261

rs5880

rs711752

rs1883025

rs1532625

rs1800775

rs7499892rs11076176

rs1800588

rs708272

rs1532624

G

A

A

A

A

AC

A

A

A

T

G

A

G

T

A

T

G

AC

T

A

T

CETP

CETP

CETP

DPEP2

CETP

CETPCETP

(intergenic)

CETP

LIPC

CETP

CETP

CETP

CETP

CETP

ABCA1

CETP

CETP

CETPCETP

LIPC

CETP

CETP

0.98 (0.86, 1.09)

0.98 (0.88, 1.07)

0.97 (0.86, 1.08)

1.15 (1.03, 1.26)

0.97 (0.88, 1.07)

0.93 (0.69, 1.17)0.97 (0.88, 1.06)

0.94 (0.81, 1.07)

0.97 (0.86, 1.08)

0.84 (0.73, 0.96)

0.97 (0.86, 1.08)

1.00 (0.88, 1.12)

0.97 (0.88, 1.07)

1.00 (0.83, 1.17)

0.99 (0.90, 1.08)

0.92 (0.83, 1.02)

0.99 (0.90, 1.09)

0.97 (0.87, 1.06)

1.01 (0.90, 1.12)1.00 (0.89, 1.11)

0.89 (0.78, 0.99)

0.99 (0.90, 1.08)

0.98 (0.89, 1.07)

.22

.46

.22

.2

.33

.038

.43

.14

.22

.18

.2

.19

.33

.08

.47

.35

.48

.4

.22

.21

.24

.47

.48

.65

.62

.55

.017

.6

.56

.49

.37

.57

.0049

.57

.99

.6

.97

.82

.11

.87

.49

.81

.97

.026

.86

.7

0.98 (0.86, 1.09)

0.98 (0.88, 1.07)

0.97 (0.86, 1.08)

1.15 (1.03, 1.26)

0.97 (0.88, 1.07)

0.93 (0.69, 1.17)0.97 (0.88, 1.06)

0.94 (0.81, 1.07)

0.97 (0.86, 1.08)

0.84 (0.73, 0.96)

0.97 (0.86, 1.08)

1.00 (0.88, 1.12)

0.97 (0.88, 1.07)

1.00 (0.83, 1.17)

0.99 (0.90, 1.08)

0.92 (0.83, 1.02)

0.99 (0.90, 1.09)

0.97 (0.87, 1.06)

1.01 (0.90, 1.12)1.00 (0.89, 1.11)

0.89 (0.78, 0.99)

0.99 (0.90, 1.08)

0.98 (0.89, 1.07)

.22

.46

.22

.2

.33

.038

.43

.14

.22

.18

.2

.19

.33

.08

.47

.35

.48

.4

.22

.21

.24

.47

.48

.8 1 1.2

Chromosome 15

Chromosome 16

Chromosome 18

Chromosome 9

SNP Gene OR (95% CI) P-valueMAFRisk allele

odds ratio

26

Supplemental Figure 7(b): Association with MI for SNPs associated with low density cholesterol in PROMIS

Chromosome 11

rs1535

rs174570

rs102275

rs599839

Chromosome 19

rs646776

rs157580

Chromosome 1

G

T

C

G

G

G

FADS1

FADS2

FADS1

CELSR2

CELSR2

APOE

0.95 (0.83, 1.07)

1.03 (0.87, 1.19)

0.99 (0.88, 1.11)

0.87 (0.76, 0.98)

0.85 (0.75, 0.96)

0.99 (0.90, 1.09)

.17

.085

.2

.24

.24

.46

.42

.72

.93

.011

.0041

.91

0.95 (0.83, 1.07)

1.03 (0.87, 1.19)

0.99 (0.88, 1.11)

0.87 (0.76, 0.98)

0.85 (0.75, 0.96)

0.99 (0.90, 1.09)

.17

.085

.2

.24

.24

.46

.8 1 1.2 1.4


odds ratio

27

Supplemental Figure 7c: Association with MI for SNPs associated with triglycerides in PROMIS

rs12286037

rs1748195

rs10750097

rs157580

Chromosome 11

rs662799

Chromosome 19

rs1260326

rs16996148

Chromosome 7

rs2266788

rs271

rs780093

rs12130333

rs714052

Chromosome 8

Chromosome 2rs673548

rs2072560

Chromosome 1

rs780094

rs17145738

rs2075290

rs439401

rs651821

rs328

T

G

G

G

C

T

T

G

A

T

T

G

A

A

T

T

G

C

C

G

APOA5

DOCK7

APOA5

APOE

ZNF259

GCKR

CILP2

ZNF259

LPL

GCKR

(intergenic)

BAZ1B

APOB

ZNF259

GCKR

TBL2

APOA5

APOE

ZNF259

LPL

0.99 (0.77, 1.22)

1.03 (0.94, 1.12)

0.98 (0.88, 1.07)

0.99 (0.90, 1.09)

0.96 (0.84, 1.08)

1.01 (0.90, 1.11)

0.92 (0.77, 1.07)

0.94 (0.82, 1.05)

0.86 (0.74, 0.99)

1.03 (0.93, 1.14)

1.06 (0.95, 1.18)

0.96 (0.81, 1.12)

0.95 (0.86, 1.04)

0.97 (0.84, 1.09)

1.02 (0.92, 1.13)

0.97 (0.81, 1.13)

0.97 (0.85, 1.09)

0.97 (0.88, 1.06)

0.96 (0.84, 1.08)

0.84 (0.68, 0.99)

.043

.46

.44

.46

.17

.26

.11

.19

.16

.26

.18

.1

.49

.16

.26

.095

.18

.45

.17

.091

.94

.56

.61

.91

.52

.91

.27

.28

.021

.56

.31

.63

.24

.6

.68

.72

.61

.54

.53

.027

0.99 (0.77, 1.22)

1.03 (0.94, 1.12)

0.98 (0.88, 1.07)

0.99 (0.90, 1.09)

0.96 (0.84, 1.08)

1.01 (0.90, 1.11)

0.92 (0.77, 1.07)

0.94 (0.82, 1.05)

0.86 (0.74, 0.99)

1.03 (0.93, 1.14)

1.06 (0.95, 1.18)

0.96 (0.81, 1.12)

0.95 (0.86, 1.04)

0.97 (0.84, 1.09)

1.02 (0.92, 1.13)

0.97 (0.81, 1.13)

0.97 (0.85, 1.09)

0.97 (0.88, 1.06)

0.96 (0.84, 1.08)

0.84 (0.68, 0.99)

.043

.46

.44

.46

.17

.26

.11

.19

.16

.26

.18

.1

.49

.16

.26

.095

.18

.45

.17

.091

.8 1 1.2 1.4


odds ratio

28

Acknowledgements

We would like to acknowledge the contributions of the following individuals: Epidemiological fieldwork in Pakistan: Zeeshan Ozair, Fahad Shuja, Mustafa Qadir Hameed, Imad Hussain, Hamza Khalid, Ali Memon, Kamran Shahid, Ali Kazmi, Sana Nasim, Muhammad Ahsan Javed, Zahir Hussain, Kanwal Aamir, Mazhar Khan, Muhammad Zuhair Yusuf, Muhammad Zafar, Faisal Majeed, Madiha Ishaq, Turkey Hussain Marmoos, Faud Khurshid, Farhat Abdul Muntaqim, Sarosh Fatima, Rehan Ahmed, Muhammad Nabeel, Mansoor Ahmed Khokar, Syed Shazad Hussain, Madad Ali Ujjan, Parveen Sultan, Asghar Ali, Ayaz Ali, Mir Alam, Hassan Zaib, Abdul Ghafoor, Saeed Ahmed, Muhammad Riazuddin, Muhammad Irshad Javed, Jabir Furqan, Abdul Ghaffar, Muhammad Shahid, Tanveer Baig Mirza, Muhammad Naeem, Afzal Hussain, Abdul Hakeem, Zahid Hussain, Tanveer Abbas, Muhammad Khurram Shahzad, Khowaja Muhammad Shoaib, Muhammad Imran Nisar, Altaf Hussain, Waleed Kayani, Muhammad Shazad, Mehmood Jafree and Ayeesha Kamal. Laboratory assays: Asad Ali Shah, Sobia Naz, Farina Hanif, Shaheen Khanum, Aisha Nazir, Aisha Sultana, Mehwish Jabar, Zahid Hussain, Madiha Yameen, Nadir Khan, Inosh Hasan, Jonathan Stephens, Pamela Whittaker, Radhi Ravindrarajah, Owen T McCann and the personnel of the WTSI Genotyping Facility Jackie Bryant, Sarah L. Clark, Jen S. Conquer, Thomas Dibling, Stephen Gamble, Clifford Hind, Michelle Ricketts, Claire R. Stribling, Sam Taylor, Alicja Wilk, Julia C. Wyatt, Silvia Behaim, Ursula Discher, Isolde Friedrich, Brigitte Haas, Gaby Herr and Brigitte Kreisel. Data management: Sarfaraz Sher Ali, Touqeer Ahmed, Fariha Nadeem, Matthew Walker, Sarah Watson and Mohammed J.R. Ghori. Epidemiological/statistical support: Nilesh Samani and Kausik Ray. Administration: Kashif Saleheen and Hannah Sneath.

Documents

Genetic Determinants of Major Blood Lipids in Pakistanis Compared With Europeanscircgenetics.ahajournals.org/content/circcvg/3/4/348... · Genetic Determinants of Major Blood Lipids