Adiposity significantly modifies genetic risk for dyslipidemia

Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (PInteraction = 2.87 × 10−4) and HDLc (PInteraction = 1.05 × 10−3). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRSLDL cholesterol × adiposity interaction was not significant. Sexual dimorphism was evident for the GRSHDL on HDLc in obese (PInteraction = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability. Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (PInteraction = 2.87 × 10−4) and HDLc (PInteraction = 1.05 × 10−3). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRSLDL cholesterol × adiposity interaction was not significant. Sexual dimorphism was evident for the GRSHDL on HDLc in obese (PInteraction = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability. Recent genome-wide association studies (GWASs) have identified multiple genetic variants robustly associated with plasma lipid traits. The Global Lipids Consortium reported 157 significant loci (P < 5 × 10−8) (1Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2787) Google Scholar, 2Willer C.J. Schmidt E.M. Sengupta S. Peloso G.M. Gustafsson S. Kanoni S. Ganna A. Chen J. Buchkovich M.L. Mora S. et al.Discovery and refinement of loci associated with lipid levels.Nat. Genet. 2013; 45: 1274-1283Crossref PubMed Scopus (1889) Google Scholar). Many are novel, and several encompass genes not previously implicated in plasma lipid metabolism. Furthermore, these loci were shown to contribute not only to general variation in plasma lipids, but also to extreme lipid phenotypes (3Johansen C.T. Wang J. Lanktree M.B. McIntyre A.D. Ban M.R. Martins R.A. Kennedy B.A. Hassell R.G. Visser M.E. Schwartz S.M. et al.An increased burden of common and rare lipid-associated risk alleles contributes to the phenotypic spectrum of hypertriglyceridemia.Arterioscler. Thromb. Vasc. Biol. 2011; 31: 1916-1926Crossref PubMed Scopus (74) Google Scholar). Notably, for TGs, individuals in the top quartile of the TG risk score were 44 times more likely to have hypertriglyceridemia as compared with individuals in the bottom quartile (P = 4 × 10−28). For HDL cholesterol (HDLc), individuals in the top quartile of the risk score were four times more likely to have high HDLc as compared with those in the bottom quartile (1Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2787) Google Scholar). Although family-based association studies indicate that 40% to 60% of variation in plasma TG and HDLc is genetically based (4Namboodiri K.K. Kaplan E.B. Heuch I. Elston R.C. Green P.P. Rao D.C. Laskarzewski P. Glueck C.J. Rifkind B.M. The Collaborative Lipid Research Clinics Family Study: biological and cultural determinants of familial resemblance for plasma lipids and lipoproteins.Genet. Epidemiol. 1985; 2: 227-254Crossref PubMed Scopus (95) Google Scholar, 5Yu Y. Wyszynski D.F. Waterworth D.M. Wilton S.D. Barter P.J. Kesaniemi Y.A. Mahley R.W. McPherson R. Waeber G. Bersot T.P. et al.Multiple QTLs influencing triglyceride and HDL and total cholesterol levels identified in families with atherogenic dyslipidemia.J. Lipid Res. 2005; 46: 2202-2213Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar), the identified loci explain <12% of variation in each of these lipid traits (1Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2787) Google Scholar). Environmental and clinical factors including BMI, physical activity, and alcohol intake are also important determinants of plasma TG and HDLc (6Howard B.V. Ruotolo G. Robbins D.C. Obesity and dyslipidemia.Endocrinol. Metab. Clin. North Am. 2003; 32: 855-867Abstract Full Text Full Text PDF PubMed Scopus (215) Google Scholar). Thus, interactions between genetic risk factors and clinical phenotypes may account for some of the unexplained heritability of plasma lipid traits. Here we have examined whether the effect of a weighted genetic risk score (GRS) on each of TG and HDLc is modified by adiposity, as assessed by BMI. This study provides biological insight into specific genetic associations and may aid in the identification of dyslipidemic subjects for whom weight loss is likely to be an important intervention. Subjects with a BMI ≥30 kg/m2 were defined as obese, those with a BMI ≤23 kg/m2 as lean, and intermediate subjects (30 kg/m2 ≥ BMI ≥ 23 kg/m2) as normal range. The BMI cutoff of ≤23 for the lean subgroup is below the 25th percentile for the majority of individuals studied. Two cohorts were studied. Obese, unrelated subjects of strictly European ancestry were recruited from the University of Ottawa Weight Management Clinic. Obese individuals displayed a BMI of >35 kg/m2 and a history of at least 10 years of adult obesity with no medical or psychiatric predisposing factors. Unrelated lean subjects were recruited from the Ottawa community. These healthy individuals had a lifelong BMI of less than the 25th percentile for sex and age, and no medical or psychiatric conditions affecting body weight (7Ahituv N. Kavaslar N. Schackwitz W. Ustaszewska A. Martin J. Hebert S. Doelle H. Ersoy B. Kryukov G. Schmidt S. et al.Medical sequencing at the extremes of human body mass.Am. J. Hum. Genet. 2007; 80: 779-791Abstract Full Text Full Text PDF PubMed Scopus (178) Google Scholar, 8Davies R.W. Lau P. Naing T. Nikpay M. Doelle H. Harper M.E. Dent R. McPherson R. A 680 kb duplication at the FTO locus in a kindred with obesity and a distinct body fat distribution.Eur. J. Hum. Genet. 2013; 21: 1417-1422Crossref PubMed Scopus (8) Google Scholar). Body weight was measured using a Tanita electronic scale to the nearest 0.3 kg. BMI was defined as weight in kilograms divided by height in meters squared (kg/m2). Height was measured to the nearest 0.5 cm. Plasma lipid fractions were measured using standard procedures. For coronary artery disease controls (CAD-C) subjects on lipid modifying medication, written documentation of pretreatment plasma lipids was obtained from the primary care physician and used for these analyses. These data were not available for 6.4% of the CAD-C subjects, none of whom were treated with a fibrate or niacin. In the obese versus lean (OBLE) cohort, 2.6% of lean and 14.8% of obese subjects were on low- to moderate-dose statin therapy, not expected to have major effects on TG or HDLc. The study was approved by the Human Ethics Experimentation Committees of the University of Ottawa Heart Institute and the Ottawa Hospital and written informed consent was obtained from all subjects. Details of the CAD-C cohorts have been previously described (9Davies R.W. Wells G.A. Stewart A.F. Erdmann J. Shah S.H. Ferguson J.F. Hall A.S. Anand S.S. Burnett M.S. Epstein S.E. et al.A genome-wide association study for coronary artery disease identifies a novel susceptibility locus in the major histocompatibility complex.Circ. Cardiovasc. Genet. 2012; 5: 217-225Crossref PubMed Scopus (97) Google Scholar). Briefly, CAD-C included healthy controls recruited as part of the Ottawa Heart Genomics Study in collaboration with the Cleveland Clinic Gene Bank (OHGS_A and OHGS_CCGB_B). These subsets were combined together to form a single CAD-C sample. Subjects were collected under human research protocols approved by their respective committees. SNP genotyping of the OBLE and CAD-C cohorts was performed on Affymetrix 6.0 or 500K Arrays at the University of Ottawa Heart Institute using the standard protocol recommended by the manufacturer and processed as described (10Dandona S. Stewart A.F. Chen L. Williams K. So D. O'Brien E. Glover C. Lemay M. Assogba O. Vo L. et al.Gene dosage of the common variant 9p21 predicts severity of coronary artery disease.J. Am. Coll. Cardiol. 2010; 56: 479-486Crossref PubMed Scopus (126) Google Scholar, 11Schunkert H. Konig I.R. Kathiresan S. Reilly M.P. Assimes T.L. Holm H. Preuss M. Stewart A.F. Barbalic M. Gieger C. et al.Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.Nat. Genet. 2011; 43: 333-338Crossref PubMed Scopus (1395) Google Scholar). Imputation was performed using IMPUTE2 and the August 2009 1000 Genomes European reference panel (12Howie B.N. Donnelly P. Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies.PLoS Genet. 2009; 5: e1000529Crossref PubMed Scopus (2805) Google Scholar). After imputation, ∼5.5 M SNPs passed post-quality control (QC) measures (info >0.5, Hardy Weinberg Equilibrium >1e–6, missing <10%). To create weighted GRSs for TG (GRSTG) and HDLc (GRSHDLc), we applied the findings of the Global Lipids Consortium 2010 study, which performed a fixed-effects meta-analysis on 46 separate GWASs comprising >100,000 individuals of European descent at a total of ∼2.6 million imputed or directly genotyped (1Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2787) Google Scholar). Because the Global Lipids SNPs were identified in populations separate from those being considered here, we have avoided the bias inherent in performing discovery and effect size estimation in the same data set. SNPs were individually coded as 0, 1, or 2, according to the number of trait-increasing alleles at that To the SNPs were in the to the SNPs were To GRS for cholesterol SNPs were SNPs for each to in populations and were from a SNP in a was coded as missing in the total A weighted GRS was for each by a SNPs of the number of reference alleles 1, or at that SNP and by the effect score of that Thus, we as an of coded 1, or and as the effect size at that defined by the Global Lipids Consortium (1Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2787) Google Scholar, and of risk Genet. 2013; PubMed Scopus Google Scholar, S. B. K. L. D. J. P. et a for association and J. Hum. Genet. 2007; Full Text Full Text PDF PubMed Scopus Google Scholar). with we that a weighted GRS or a (9Davies R.W. Wells G.A. Stewart A.F. Erdmann J. Shah S.H. Ferguson J.F. Hall A.S. Anand S.S. Burnett M.S. Epstein S.E. et al.A genome-wide association study for coronary artery disease identifies a novel susceptibility locus in the major histocompatibility complex.Circ. Cardiovasc. Genet. 2012; 5: 217-225Crossref PubMed Scopus (97) Google Scholar, and of risk Genet. 2013; PubMed Scopus Google Scholar, R.W. S. Stewart A.F. Chen L. R. McPherson R. Wells G.A. of disease based on a panel of SNPs identified association Cardiovasc. Genet. 2010; PubMed Scopus Google Scholar). GRSs were in association analysis S. B. K. L. D. J. P. et a for association and J. Hum. Genet. 2007; Full Text Full Text PDF PubMed Scopus Google Scholar). SNPs and effect for each of TG and HDLc are in I. are for the primary genotyped SNPs were coded as 0, 1, or according to the number of effect alleles and a weighted GRS was for each according to the previously described for each of TG and HDLc. general were used to for the association between and HDLc and were for age, and data were into lean, obese and normal in to the effect of genetic risk the BMI SNP was for associations to from the GRS using and interaction were for SNP × obese/lean status and SNP × sex by including an interaction in the respective The same which were used to the were also for SNP × obese/lean status and SNP × sex interaction were by were in S. B. K. L. D. J. P. et a for association and J. Hum. Genet. 2007; Full Text Full Text PDF PubMed Scopus Google and The general of obese and lean subjects in each of the two cohorts are shown in the OBLE and CAD-C subjects were for and The OBLE was and extremes of BMI 0.3 kg/m2 as compared with the CAD-C BMI kg/m2 of the study by and by under for measured in standard BMI kg/m2 and less than 25th BMI kg/m2 for 23 kg/m2 BMI score to the of the effect size risk by the effect size of that risk divided by the total number of risk are as standard for in a new standard BMI kg/m2 and less than 25th BMI kg/m2 for 23 kg/m2 BMI score to the of the effect size risk by the effect size of that risk divided by the total number of risk are as standard for For the the in TG for subjects or below the percentile of the weighted was = = × For obese subjects, this was = < × and for lean subjects = < × The in HDLc for all subjects or below the percentile of the GRSHDL on was = < × This was for the obese = = × and for the lean = = × subjects. shown in 2, analysis by multiple a significant in the effect size of the GRS on each of TG and HDLc in the obese versus lean For on TG in the obese = = = × versus for the lean = = = × with a significant interaction (PInteraction = 2.87 × 10−4) For GRSHDL and HDLc in the obese = = = × versus = = = × in the lean, significant interactions for obese/lean status × GRSHDL (PInteraction = 1.05 × For in the obese = = = × to the lean population = = = × no significant interaction between and obese/lean status was (PInteraction = Subjects with a BMI in the normal kg/m2 < BMI < kg/m2) a between the lean and obese for TG, = = = × for = = = × but not for = = = × Subjects with a BMI in the normal kg/m2 < BMI < kg/m2) a between the lean and obese for TG, = = = × for = = = × but not for = = = × of GRS with lipid by of individuals with included in for measured in of individuals with included in for measured in in a new compared with GRS by lean versus obese with are displayed for obese and lean individuals a to a number of The effect in HDL is to SNPs tagging cholesteryl ester transfer protein (CETP), endothelial lipase (LIPG), GalNAc-transferase (GALNT2), and phospholipid transfer protein loci not previously noted to Because obesity status the clinical of these lipid we the of the and in obese versus lean subjects. For on TG, = for obese versus = for lean subjects, a was for on on = for lean versus = for In contrast, for the on was only in the obese = versus lean = We next examined the SNPs included in the and TG SNPs and and four HDLc SNPs were to have a significant obese/lean status × SNP effect interaction at a discovery of LPL and a for TG, and and a for HDLc. However, at a only LPL and were significant. for multiple was by each SNP from least to The interaction that was less than the the of the of the SNP divided by the number of SNPs of by the was to be the cutoff at which were as significant Y. Y. the discovery a and to multiple R. B. Scholar). SNP × obese/lean status are in To whether these SNPs were the major to the obese/lean status × GRS a new score was for each these the interaction was no significant = = loci that effects in obese versus lean of individuals with used in for measured in of and LPL and of individuals with used in for measured in of and LPL and in a new we whether GRS effects by sex not the effect of the GRS on in the population = = = However, for on was a significant interaction with sex in the obese (PInteraction = 0.016) but not the lean (PInteraction = A sex effect by obese/lean was not for the lipid traits. analysis of SNPs to significant interaction in the population for TG or HDLc. However, locus for HDLc was in each of the lean tagging and obese tagging with However, for multiple these loci were only significant = SNP × sex interaction data may be in SNPs with of loci are of individuals with used in for measured in of is significant at loci are of individuals with used in for measured in of is significant at in a new and clinical factors may genetic For the effect of a GRS on BMI was to be in versus individuals S. J. the genetic to obesity in and from population 2010; PubMed Scopus Google Scholar). To the effects of adiposity on genetic risk for we have a GRS from loci previously reported by the Global Lipids We that obesity status the effect of genetic variants associated with increased TGs as as those associated with levels of but not For TG, the effect size of a weighted in the obese population was that of the lean population = shown in 1, for plasma TG levels are for obese versus lean subjects. This is not effects of on TG in obese the effect of the effect of genetic variants at In both obese and lean with TGs, but the of the for versus TG for obese as compared with lean a significant interaction the in plasma TG by the was for the obese subjects, that for the lean population In to TGs, the effect of a of on HDLc was for the lean = than the obese = For is important to that we a GRSHDL of alleles genetic score for obese individuals have levels of lipoproteins, to TG of HDL and more HDL Thus, as shown in 2, is likely that the effect of hypertriglyceridemia to the effect of for genes and The GRSHDL for HDLc of HDLc variation in the lean versus in the obese subjects. Thus, the genetic risk for hypertriglyceridemia is by the obese the effect of genetic variants is These data that the × adiposity interaction contributes to part of the unexplained genetic in plasma lipids we an weighted risk score than the more common In the also as an been used to a of effect S. B. K. L. D. J. P. et a for association and J. Hum. Genet. 2007; Full Text Full Text PDF PubMed Scopus Google Scholar). However, a risk score been shown to (7Ahituv N. Kavaslar N. Schackwitz W. Ustaszewska A. Martin J. Hebert S. Doelle H. Ersoy B. Kryukov G. Schmidt S. et al.Medical sequencing at the extremes of human body mass.Am. J. Hum. Genet. 2007; 80: 779-791Abstract Full Text Full Text PDF PubMed Scopus (178) Google Scholar, S. Stewart A.F. Chen L. Williams K. So D. O'Brien E. Glover C. Lemay M. Assogba O. Vo L. et al.Gene dosage of the common variant 9p21 predicts severity of coronary artery disease.J. Am. Coll. Cardiol. 2010; 56: 479-486Crossref PubMed Scopus (126) Google Scholar). We not analysis hypertriglyceridemia and are defined by and Although we the to the effects of all we identified novel loci not previously reported to have SNPs tagging (PInteraction = × (PInteraction = × and LPL (PInteraction = × 10−4) interaction with obese/lean status for These encompass genes both TG and The the glucokinase glucokinase with to the and a major for C. M. The variant in associated with plasma and triglyceride levels effect increased glucokinase in Genet. 2009; PubMed Scopus Google Scholar). LPL and major determinants of of lipoproteins, LPL and the a of LPL I. N. Y. D. E.M. A.D. in hypertriglyceridemia to of and of their Thromb. Vasc. Biol. 2005; PubMed Scopus Google Scholar). The effect of the previously TG loci were the in this study = = and = and not were for the significant obese/lean status × GRS in a population the effect on plasma TG levels was to be modified by Y. A.F. J. D.C. Y. association with lipids in an effect on triglyceride Lipid Res. 2013; Full Text Full Text PDF PubMed Scopus Google Scholar), of For interactions were noted for SNPs tagging (PInteraction = × (PInteraction = × (PInteraction = × and (PInteraction = × The of and in HDL in the are GalNAc-transferase to a in of in lipid including M.B. T. W. O. H. of protein of in of of plasma Biol. 2010; Full Text Full Text PDF PubMed Scopus Google Scholar). In the HDLc levels (1Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2787) Google Scholar). Although these HDLc loci effect = = = and = as compared with the top TG were for the significant × obese/lean status interaction In contrast, no significant interaction was for × obese/lean In a we performed a The effect of weighted was to be for versus for the population as a dimorphism for genetic effects on HDLc was driven by the obese subjects (PInteraction = 0.016) and was not evident in the lean (PInteraction = or all (PInteraction = Obese an in HDLc in to as compared with in each for obese and for were to be However, for multiple these only significant in In we have weighted GRSs for each of TG and HDLc based on loci identified by the Global Lipids Consortium and effects in separate obese and lean are discovery an association with adiposity Here we Notably, lean subjects have an in the genetic for increased TGs and an to as compared with obese subjects. These effects are driven by SNPs tagging and LPL for TG, and for HDLc. We also dimorphism for genetic effects on HDLc that is to the obese of subjects. These findings that obese individuals are more to genetic risk for SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability. with coronary artery disease controls ester transfer protein with discovery GalNAc-transferase glucokinase glucokinase receptor genetic risk score genome-wide association study HDL cholesterol cholesterol endothelial lipase obese versus lean study phospholipid transfer protein control

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