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Summary: Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWASs) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWASs) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWASs and TWASs can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p values across all the genes, which suggests high-level consistency between proteome-lipid associations and transcriptome-lipid associations. more...

Abstract Insulin resistance causes multiple epidemic metabolic diseases, including type 2 diabetes, cardiovascular disease, and fatty liver, but is not routinely measured in epidemiological studies. To discover novel insulin resistance genes in the general population, we conducted genome-wide association studies in 382,129 individuals for triglyceride to HDL-cholesterol ratio (TG/HDL), a surrogate marker of insulin resistance calculable from commonly measured serum lipid profiles. We identified 251 independent loci, of which 62 were more strongly associated with TG/HDL compared to TG or HDL alone, suggesting them as insulin resistance loci. Candidate causal genes at these loci were prioritized by fine mapping with directions-of-effect and tissue specificity annotated through analysis of protein coding and expression quantitative trait variation. Directions-of-effect were corroborated in an independent cohort of individuals with directly measured insulin resistance. We highlight two phospholipase encoding genes, PLA2G12A and PLA2G6, which liberate arachidonic acid and improve insulin sensitivity, and VGLL3, a transcriptional co-factor that increases insulin resistance partially through enhanced adiposity. Finally, we implicate the anti-apoptotic gene TNFAIP8 as a sex-dimorphic insulin resistance factor, which acts by increasing visceral adiposity, specifically in females. In summary, our study identifies several candidate modulators of insulin resistance that have the potential to serve as biomarkers and pharmacological targets. more...

Abstract Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22–3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76–0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = − 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment. more...

Abstract Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p more...

Abstract We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure. more...

ABSTRACTPsoriasis, an immune-mediated inflammatory disease, affects nearly 125 million people globally. The interleukin (IL)-17A homodimer is a key driver of psoriasis and other autoimmune diseases, including psoriatic arthritis, axial spondyloarthritis, hidradenitis suppurativa, and uveitis. Treatment with monoclonal antibodies (mAbs) against IL−17A provides an improvement in the Psoriasis Area and Severity Index compared to conventional systemic agents. In this study, the AffibodyⓇ technology was used to identify and optimize a novel, small, biological molecule comprising three triple helical affinity domains, izokibep (previously ABY-035), for the inhibition of IL-17A signaling. Preclinical studies show that izokibep, a small 18.6 kDa IL-17 ligand trap comprising two IL-17A-specific Affibody domains and one albumin-binding domain, selectively inhibits human IL-17A in vitro and in vivo with superior potency and efficacy relative to anti-IL-17A mAbs. A Phase 1 first-in-human study was conducted to establish the safety, pharmacokinetics, and preliminary efficacy of izokibep, when administered intravenously and subcutaneously as single doses to healthy subjects, and as single intravenous and multiple subcutaneous doses to patients with psoriasis (NCT02690142; EudraCT No: 2015–004531–13). Izokibep was well tolerated with no meaningful safety concerns identified in healthy volunteers and patients with psoriasis. Rapid efficacy was seen in all psoriasis patients after one dose which further improved in patients receiving multiple doses. A therapeutic decrease in joint pain was also observed in a single patient with concurrent psoriatic arthritis. The study suggests that izokibep has the potential to safely treat IL17A-associated diseases such as psoriasis, psoriatic arthritis, axial spondyloarthritis, hidradenitis suppurativa, and uveitis. more...

Summary: While lipid traits are known essential mediators of cardiovascular disease, few approaches have taken advantage of their shared genetic effects. We apply a Bayesian multivariate size estimator, mash, to GWAS of four lipid traits in the Million Veterans Program (MVP) and provide posterior mean and local false sign rates for all effects. These estimates borrow information across traits to improve effect size accuracy. We show that controlling local false sign rates accurately and powerfully identifies replicable genetic associations and that multivariate control furthers the ability to explain complex diseases. Our application yields high concordance between independent datasets, more accurately prioritizes causal genes, and significantly improves polygenic prediction beyond state-of-the-art methods by up to 59% for lipid traits. The use of Bayesian multivariate genetic shrinkage has yet to be applied to human quantitative trait GWAS results, and we present a staged approach to prediction on a polygenic scale. more...

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk. more...

Abstract To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis-eQTL variant-gene transcript (eGene) pairs at p more...

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data. more...

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk. more...

Abstract Background Publications suggest immunomodulation co-therapy improves responder rates in uncontrolled/refractory gout patients undergoing pegloticase treatment. The MIRROR open-label trial showed a 6-month pegloticase + methotrexate co-therapy responder rate of 79%, compared to an established 42% pegloticase monotherapy responder rate. Longer-term efficacy/safety data are presented here. Methods Uncontrolled gout patients (serum urate [SU] ≥ 6 mg/dL and SU ≥ 6 mg/dL despite urate-lowering therapy [ULT], ULT intolerance, or functionally-limiting tophi) were included. Patients with immunocompromised status, G6PD deficiency, severe kidney disease, or methotrexate contraindication were excluded. Oral methotrexate (15 mg/week) and folic acid (1 mg/day) were administered 4 weeks before and during pegloticase therapy. Twelve-month responder rate (SU more...

Combining a standard polygenic risk score (PRS) as a feature in a machine learning model increases the percentage variance explained for those traits, helping to account for non-linearities or interaction effects in genetics-based prediction models. more...

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus. more...

SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations. more...

Background Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. Methods An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. Results The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. Conclusion A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality. more...

PurposeWe aimed to discover loci associated with triglyceride (TG) levels in the context of type 2 diabetes (T2D). We conducted a genome-wide association study (GWAS) in 424,120 genotyped participants of the UK Biobank (UKB) with T2D status and TG levels.MethodsWe stratified the cohort based on T2D status and conducted association analyses of TG levels for genetic variants with minor allele count (MAC) at least 20 in each stratum. Effect differences of genetic variants by T2D status were determined by Cochran's Q-test and we validated the significantly associated variants in the Mass General Brigham Biobank (MGBB).ResultsAmong 21,176 T2D and 402,944 non-T2D samples from UKB, stratified GWAS identified 19 and 315 genomic risk loci significantly associated with TG levels, respectively. Only chr6p21.32 exhibited genome-wide significant heterogeneity (I2 = 98.4%; pheterogeneity = 2.1x10-15), with log(TG) effect estimates of -0.066 (95%CI: -0.082, -0.050) and 0.002 (95%CI: -0.002, 0.006) for T2D and non-T2D, respectively. The lead variant rs9274619:A (allele frequency 0.095) is located 2Kb upstream of the HLA-DQB1 gene, between HLA-DQB1 and HLA-DQA2 genes. We replicated this finding among 25,137 participants (6,951 T2D cases) of MGBB (pheterogeneity = 9.5x10-3). Phenome-wide interaction association analyses showed that the lead variant was strongly associated with a concomitant diagnosis of type 1 diabetes (T1D) as well as diabetes-associated complications.ConclusionIn conclusion, we identified an intergenic variant near HLA-DQB1/DQA2 significantly associates with decreased triglycerides only among those with T2D and highlights an immune overlap with T1D. more...

Summary: Human genetics studies have uncovered genetic variants that can be used to guide biological research and prioritize molecular targets for therapeutic intervention for complex diseases. We have identified a missense variant (P746S) in EDEM3 associated with lower blood triglyceride (TG) levels in >300,000 individuals. Functional analyses in cell and mouse models show that EDEM3 deficiency strongly increased the uptake of very-low-density lipoprotein and thereby reduced the plasma TG level, as a result of up-regulated expression of LRP1 receptor. We demonstrate that EDEM3 deletion up-regulated the pathways for RNA and endoplasmic reticulum protein processing and transport, and consequently increased the cell surface mannose-containing glycoproteins, including LRP1. Metabolomics analyses reveal a cellular TG accumulation under EDEM3 deficiency, a profile consistent with individuals carrying EDEM3 P746S. Our study identifies EDEM3 as a regulator of blood TG, and targeted inhibition of EDEM3 may provide a complementary approach for lowering elevated blood TG concentrations. : Genetics; Diabetology; Specialized Functions of Cells; Metabolomics Subject Areas: Genetics, Diabetology, Specialized Functions of Cells, Metabolomics more...

Abstract Statistical power, which is the probability of correctly rejecting a false null hypothesis, is a limitation of genome-wide association studies (GWAS). Sample size is a major component of statistical power that can be easily affected by missingness in phenotypic data and restrain the ability to detect associated single-nucleotide polymorphisms (SNPs) with small effect sizes. Although some phenotypes are hard to collect because of cost and loss to follow-up, correlated phenotypes that are easily collected can be leveraged for association analysis. In this paper, we evaluate a phenotype imputation method that incorporates family structure and correlation between multiple phenotypes using GAW20 simulated data. The distribution of missing values is derived using information contained in the missing sample’s relatives and additional correlated phenotypes. We show that this imputation method can improve power in the association analysis compared with excluding observations with missing data, while achieving the correct Type I error rate. We also examine factors that may affect the imputation accuracy. more...

Abstract Background DNA methylation, an epigenetic modification, can be affected by environmental factors and thus regulate gene expression levels that can lead to alterations of certain phenotypes. Network analysis has been used successfully to discover gene sets that are expressed differently across multiple disease states and suggest possible pathways of disease progression. We applied this framework to compare DNA methylation levels before and after lipid-lowering medication and to identify modules that differ topologically between the two time points, revealing the association between lipid medication and these triglyceride-related methylation sites. Methods We performed quality control using beta-mixture quantile normalization on 463,995 cytosine-phosphate-guanine (CpG) sites and deleted problematic sites, resulting in 423,004 probes. We identified 14,850 probes that were nominally associated with triglycerides prior to treatment and performed weighted gene correlation network analysis (WGCNA) to construct pre- and posttreatment methylation networks of these probes. We then applied both WGCNA module preservation and generalized Hamming distance (GHD) to identify modules with topological differences between the pre- and posttreatment. For modules with structural changes between 2 time points, we performed pathway-enrichment analysis to gain further insight into the biological function of the genes from these modules. Results Six triglyceride-associated modules were identified using pretreatment methylation probes. The same 3 modules were not preserved in posttreatment data using both the module-preservation and the GHD methods. Top-enriched pathways for the 3 differentially methylated modules are sphingolipid signaling pathway, proteoglycans in cancer, and metabolic pathways (p values more...

Common genetic variants associated with plasma lipids have been extensively studied for a better understanding of common diseases. Here, the authors use whole-genome sequencing of 16,324 individuals to analyze rare variant associations and to determine their monogenic and polygenic contribution to lipid traits. more...

Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels. more...

Abstract Introduction There is conflicting evidence whether high‐density lipoprotein cholesterol (HDL‐C) is a risk factor for Alzheimer's disease (AD) and dementia. Genetic variation in the cholesteryl ester transfer protein (CETP) locus is associated with altered HDL‐C. We aimed to assess AD risk by genetically predicted HDL‐C. Methods Ten single nucleotide polymorphisms within the CETP locus predicting HDL‐C were applied to the International Genomics of Alzheimer's Project (IGAP) exome chip stage 1 results in up 16,097 late onset AD cases and 18,077 cognitively normal elderly controls. We performed instrumental variables analysis using inverse variance weighting, weighted median, and MR‐Egger. Results Based on 10 single nucleotide polymorphisms distinctly predicting HDL‐C in the CETP locus, we found that HDL‐C was not associated with risk of AD (P > .7). Discussion Our study does not support the role of HDL‐C on risk of AD through HDL‐C altered by CETP. This study does not rule out other mechanisms by which HDL‐C affects risk of AD. more...

Background Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations. Two major sources of sugar in the US diet are sugar‐sweetened beverages (SSBs) and 100% fruit juices. Low‐calorie sweetened beverages are common replacements. Methods and Results Fasting plasma lipoprotein concentrations were measured in the FOS (Framingham Offspring Study) (1991–2014; N=3146) and Generation Three (2002–2001; N=3584) cohorts. Beverage intakes were estimated from food frequency questionnaires and grouped into 5 intake categories. Mixed‐effect linear regression models were used to examine 4‐year changes in lipoprotein measures, and Cox proportional hazard models were used to estimate hazard ratios for incident dyslipidemia, adjusting for potential confounding factors. We found that regular (>1 serving per day) versus low ( more...

The original version of this article contained an error in the name of the author Ramachandran S. Vasan, which was incorrectly given as Vasan S. Ramachandran. This has now been corrected in both the PDF and HTML versions of the article. more...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10(-22)) and also for PC2 (r = 0.80, P = 7x10(-29)). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10(-28)) and for PC2 (r = 0.45, P = 2x10(-39)). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account. more...

A low level of HDL-C is the most common plasma lipid abnormality observed in men with established coronary heart disease (CHD). To identify allelic variants associated with susceptibility to low HDL-C and CHD, we examined 60 candidate genes with key roles in HDL metabolism, insulin resistance, and inflammation using samples from the Veterans Affairs HDL Intervention Trial (VA-HIT; cases, n = 699) and the Framingham Offspring Study (FOS; controls, n = 705). VA-HIT was designed to examine the benefits of HDL-raising with gemfibrozil in men with low HDL-C (≤40 mg/dl) and established CHD. After adjustment for multiple testing within each gene, single-nucleotide polymorphisms (SNP) significantly associated with case status were identified in the genes encoding LIPC (rs4775065, P < 0.0001); CETP (rs5882, P = 0.0002); RXRA (rs11185660, P = 0.0021); ABCA1 (rs2249891, P = 0.0126); ABCC6 (rs150468, P = 0.0206; rs212077, P = 0.0443); CUBN (rs7893395, P = 0.0246); APOA2 (rs3813627, P = 0.0324); SELP (rs732314, P = 0.0376); and APOC4 (rs10413089, P = 0.0425). Included among the novel findings of this study are the identification of susceptibility alleles for low HDL-C/CHD risk in the genes encoding CUBN and RXRA, and the observation that genetic variation in SELP may influence CHD risk through its effects on HDL. more...