C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We sought to identify genetic variants that are associated with CRP leve Show more
C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We sought to identify genetic variants that are associated with CRP levels. We performed a genome-wide association analysis of CRP in 66 185 participants from 15 population-based studies. We sought replication for the genome-wide significant and suggestive loci in a replication panel comprising 16 540 individuals from 10 independent studies. We found 18 genome-wide significant loci, and we provided evidence of replication for 8 of them. Our results confirm 7 previously known loci and introduce 11 novel loci that are implicated in pathways related to the metabolic syndrome (APOC1, HNF1A, LEPR, GCKR, HNF4A, and PTPN2) or the immune system (CRP, IL6R, NLRP3, IL1F10, and IRF1) or that reside in regions previously not known to play a role in chronic inflammation (PPP1R3B, SALL1, PABPC4, ASCL1, RORA, and BCL7B). We found a significant interaction of body mass index with LEPR (P<2.9×10(-6)). A weighted genetic risk score that was developed to summarize the effect of risk alleles was strongly associated with CRP levels and explained ≈5% of the trait variance; however, there was no evidence for these genetic variants explaining the association of CRP with coronary heart disease. We identified 18 loci that were associated with CRP levels. Our study highlights immune response and metabolic regulatory pathways involved in the regulation of chronic inflammation. Show less
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between bod Show more
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studi Show more
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)). Show less
The National Heart, Lung, and Blood Institute's Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-re Show more
The National Heart, Lung, and Blood Institute's Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-related traits, comprises >40,000 participants representing 4 ethnic groups in 9 community-based cohorts. The goals of CARe include the discovery of new variants associated with traits using a candidate gene approach and the discovery of new variants using the genome-wide association mapping approach specifically in African Americans. CARe has assembled DNA samples for >40,000 individuals self-identified as European American, African American, Hispanic, or Chinese American, with accompanying data on hundreds of phenotypes that have been standardized and deposited in the CARe Phenotype Database. All participants were genotyped for 7 single-nucleotide polymorphisms (SNPs) selected based on prior association evidence. We performed association analyses relating each of these SNPs to lipid traits, stratified by sex and ethnicity, and adjusted for age and age squared. In at least 2 of the ethnic groups, SNPs near CETP, LIPC, and LPL strongly replicated for association with high-density lipoprotein cholesterol concentrations, PCSK9 with low-density lipoprotein cholesterol levels, and LPL and APOA5 with serum triglycerides. Notably, some SNPs showed varying effect sizes and significance of association in different ethnic groups. The CARe Pilot Study validates the operational framework for phenotype collection, SNP genotyping, and analytic pipeline of the CARe project and validates the planned candidate gene study of approximately 2000 biological candidate loci in all participants and genome-wide association study in approximately 8000 African American participants. CARe will serve as a valuable resource for the scientific community. Show less
Chronic kidney disease (CKD) is a significant public health problem, and recent genetic studies have identified common CKD susceptibility variants. The CKDGen consortium performed a meta-analysis of g Show more
Chronic kidney disease (CKD) is a significant public health problem, and recent genetic studies have identified common CKD susceptibility variants. The CKDGen consortium performed a meta-analysis of genome-wide association data in 67,093 individuals of European ancestry from 20 predominantly population-based studies in order to identify new susceptibility loci for reduced renal function as estimated by serum creatinine (eGFRcrea), serum cystatin c (eGFRcys) and CKD (eGFRcrea < 60 ml/min/1.73 m(2); n = 5,807 individuals with CKD (cases)). Follow-up of the 23 new genome-wide-significant loci (P < 5 x 10(-8)) in 22,982 replication samples identified 13 new loci affecting renal function and CKD (in or near LASS2, GCKR, ALMS1, TFDP2, DAB2, SLC34A1, VEGFA, PRKAG2, PIP5K1B, ATXN2, DACH1, UBE2Q2 and SLC7A9) and 7 loci suspected to affect creatinine production and secretion (CPS1, SLC22A2, TMEM60, WDR37, SLC6A13, WDR72 and BCAS3). These results further our understanding of the biologic mechanisms of kidney function by identifying loci that potentially influence nephrogenesis, podocyte function, angiogenesis, solute transport and metabolic functions of the kidney. Show less
Higher resting heart rate is associated with increased cardiovascular disease and mortality risk. Though heritable factors play a substantial role in population variation, little is known about specif Show more
Higher resting heart rate is associated with increased cardiovascular disease and mortality risk. Though heritable factors play a substantial role in population variation, little is known about specific genetic determinants. This knowledge can impact clinical care by identifying novel factors that influence pathologic heart rate states, modulate heart rate through cardiac structure and function or by improving our understanding of the physiology of heart rate regulation. To identify common genetic variants associated with heart rate, we performed a meta-analysis of 15 genome-wide association studies (GWAS), including 38,991 subjects of European ancestry, estimating the association between age-, sex- and body mass-adjusted RR interval (inverse heart rate) and approximately 2.5 million markers. Results with P < 5 × 10(-8) were considered genome-wide significant. We constructed regression models with multiple markers to assess whether results at less stringent thresholds were likely to be truly associated with RR interval. We identified six novel associations with resting heart rate at six loci: 6q22 near GJA1; 14q12 near MYH7; 12p12 near SOX5, c12orf67, BCAT1, LRMP and CASC1; 6q22 near SLC35F1, PLN and c6orf204; 7q22 near SLC12A9 and UfSp1; and 11q12 near FADS1. Associations at 6q22 400 kb away from GJA1, at 14q12 MYH6 and at 1q32 near CD34 identified in previously published GWAS were confirmed. In aggregate, these variants explain approximately 0.7% of RR interval variance. A multivariant regression model including 20 variants with P < 10(-5) increased the explained variance to 1.6%, suggesting that some loci falling short of genome-wide significance are likely truly associated. Future research is warranted to elucidate underlying mechanisms that may impact clinical care. Show less
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, Show more
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less
To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the Show more
To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing. Show less
Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association a Show more
Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity. Show less
Polymorphisms in the APOC3 and APOA5 genes, from the APOA1/APOC3/APOA4/APOA5 gene cluster on chromosome 11q23, have been associated with interindividual variation in plasma triglycerides. APOA5 polymo Show more
Polymorphisms in the APOC3 and APOA5 genes, from the APOA1/APOC3/APOA4/APOA5 gene cluster on chromosome 11q23, have been associated with interindividual variation in plasma triglycerides. APOA5 polymorphisms implicated include 2 in the promoter region (-1131 T/C and -3 A/G) and 1 in exon 2 (+56 C/G). APOC3 polymorphisms implicated include 1 (SstI) in the 3' untranslated region and 1 (-2854 G/T) in the APOC3-APOA4 intergenic region. We analyzed the associations of haplotypes and multilocus genotypes of these polymorphisms on longitudinal serum triglyceride profiles in 360 African American and 823 white subjects from the Bogalusa Heart Study. Subjects were examined from 2 to 8 times (mean +/- SD, 5.4 +/- 1.3) between 1973 and 1996, at ages ranging from 4 to 38 years, with 1978 observations in African Americans and 4465 in whites. Serum triglycerides were significantly higher among whites across all ages. Allele frequencies differed significantly between African Americans and whites at all but the APOA5 +56 C/G locus. Linkage disequilibrium among the loci was higher in whites and haplotype diversity lower: 6 haplotypes had estimated frequencies of more than 1% in African Americans, 5 in whites. Individually, all polymorphisms except APOC3 -2854 G/T showed significant associations with triglyceride levels in the full sample. However, genotype models including all 5 loci showed significant triglyceride associations for only 3 (APOC3 SstI, APOA5 -1131 T/C, and APOA5 +56 C/G); significant interactions among them indicated their effects were not independent. Neither APOC3 -2854 G/T nor APOA5 -3 A/G had significant effects when the other 3 loci were in the models. The EM algorithm was used to estimate haplotype frequencies and assign haplotype probabilities to individuals, which is conditional on their genotypes; individuals' haplotype probability vectors were then used as predictors in multilevel mixed models of longitudinal triglyceride profiles. Of haplotypes comprising, in order, APOC3 SstI and -2854 G/T and APOA5 -1131 T/C, -3 A/G, and +56 C/G, 3 were significantly associated with higher triglycerides, even after adjusting for multiple tests: GGTAG (P = .002), GTTAG (P < .0001), and CGCGC (P = .0002). Each GGTAG haplotype carried would be expected to raise triglyceride levels (relative to those of GTTAC homozygotes) by approximately 19 mg/dL, each GTTAG haplotype by approximately 15 mg/dL, and each CGCGC haplotype by approximately 7 mg/dL. Haplotypes comprising the 3 loci implicated by genotype analyses (SstI, -1131 T/C, and +56 C/G) were also tested: haplotypes C_C_C and G_T_G significantly raised triglycerides, even after adjustment for multiple comparisons (P < .002 for both), with each copy of C_C_C expected to raise triglycerides by approximately 7 mg/dL and each copy of G_T_G by approximately 15 mg/dL. Overall, our findings support those of others in associating specific polymorphisms and haplotypes in the APOA1/C3/A4/A5 gene cluster with higher serum triglyceride levels. However, the degree to which polymorphisms in the APOC3 and APOA5 genes may be independently associated with triglyceride levels remains to be determined. Show less
Most tests of association between DNA sequence variation and quantitative phenotypes in samples of randomly chosen individuals rely on specification of genotypic strata followed by comparison of pheno Show more
Most tests of association between DNA sequence variation and quantitative phenotypes in samples of randomly chosen individuals rely on specification of genotypic strata followed by comparison of phenotypes across these strata. This strategy often succeeds when phenotypic differences are caused by one or two single nucleotide polymorphisms (SNPs) among the surveyed markers. However, when multiple-SNP haplotypes account for observed phenotypic variation, identification of the best partitioning requires examination of an inordinate number of SNP combinations. An alternative approach is to rank individuals by their phenotypic measures and ask whether attributes of the genotypic variation show a non-random distribution along this phenotypic ranking. One simple version of this strategy selects the top and bottom tails of the distribution, and then tests whether genotypes from these two samples are drawn from a single population. This framework does not require the recovery of phased haplotypes and allows contrasts between large numbers of sites at once. We use a method based on this approach to identify associations between plasma triglyceride level, a risk factor for cardiovascular disease, and multi-site genotypes located in the APOA1/C3/A4/A5 cluster of apolipoprotein genes in unrelated individuals (1,071 African-American females, 780 African-American males, 1,036 European-American females, and 930 European-American males) sampled from four US cities as part of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Method performance is investigated using simulations that model genealogical variation and different genetic architectures. Results indicate that this multi-site test can identify genotype-phenotype associations with reasonable power, including those generated by some simple epistatic models. Show less
Evaluate the consistency of the contribution of interactions between single nucleotide polymorphism (SNP) genotype effects to variation in measures of lipid metabolism across ethnic strata within gend Show more
Evaluate the consistency of the contribution of interactions between single nucleotide polymorphism (SNP) genotype effects to variation in measures of lipid metabolism across ethnic strata within gender. We considered 80 SNPs within the apolipoprotein (APO) A1/C3/A4/A5 gene cluster using an over-parameterized general linear model to identify SNPs whose genotype effects combine non-additively to influence plasma levels of high density lipoprotein cholesterol (HDL-C), total cholesterol (TC) and triglycerides (TG) in a consistent manner across ethnic strata. We analyzed population-based samples of unrelated 18 to 30 year old African-Americans (n = 1,858) and European-Americans (n = 1,973) ascertained without regard to health at four field centers (Birmingham, Ala.; Chicago, Ill.; Minneapolis, Minn. and Oakland, Calif., USA) by the Coronary Artery Risk Development in Young Adults (CARDIA) study. To identify which SNP genotype effects combine non-additively we used a two-tier analysis strategy. We first required that pairs of SNPs show statistically significant non-additivity in both ethnic strata within a gender, where experiment-wise significance was evaluated using a permutation test to determine the probability of observing the number of tests significant in both ethnic strata by chance alone. Second, we required no significant evidence of heterogeneity of the relationship between the phenotype and the two SNP genotypes across ethnic strata and across field centers within each ethnic group. From this strategy we identified ten pairs of SNPs, involving thirteen SNPs, that displayed statistically significant non-additivity of SNP genotype effects on TC. Only one of these thirteen SNPs had statistically significant genotype effects that were consistent across samples. Our analyses suggest that ignoring the contribution of interactions between SNP genotype effects when modeling multi-SNP genotype-phenotype relationships may result in an underestimate of the contribution of genetic variation to variation in quantitative cardiovascular disease (CVD) risk factor traits. Show less
Apolipoproteins (apo) A-I and C-III are components of high-density lipoprotein-cholesterol (HDL-C), a quantitative trait negatively correlated with risk of cardiovascular disease (CVD). We analyzed th Show more
Apolipoproteins (apo) A-I and C-III are components of high-density lipoprotein-cholesterol (HDL-C), a quantitative trait negatively correlated with risk of cardiovascular disease (CVD). We analyzed the contribution of individual and pairwise combinations of single nucleotide polymorphisms (SNPs) in the APOA1/APOC3 genes to HDL-C variability to evaluate (1) consistency of published single-SNP studies with our single-SNP analyses; (2) consistency of single-SNP and two-SNP phenotype-genotype relationships across race-, gender-, and geographical location-dependent contexts; and (3) the contribution of single SNPs and pairs of SNPs to variability beyond that explained by plasma apo A-I concentration. We analyzed 45 SNPs in 3,831 young African-American (N=1,858) and European-American (N=1,973) females and males ascertained by the Coronary Artery Risk Development in Young Adults (CARDIA) study. We found three SNPs that significantly impact HDL-C variability in both the literature and the CARDIA sample. Single-SNP analyses identified only one of five significant HDL-C SNP genotype relationships in the CARDIA study that was consistent across all race-, gender-, and geographical location-dependent contexts. The other four were consistent across geographical locations for a particular race-gender context. The portion of total phenotypic variance explained by single-SNP genotypes and genotypes defined by pairs of SNPs was less than 3%, an amount that is miniscule compared to the contribution explained by variability in plasma apo A-I concentration. Our findings illustrate the impact of context-dependence on SNP selection for prediction of CVD risk factor variability. Show less
Genetic variation in the apolipoprotein A-V gene (APOA5) has been associated with variation in plasma triglyceride (TG) levels in African American and white females and males older than 40 years and/o Show more
Genetic variation in the apolipoprotein A-V gene (APOA5) has been associated with variation in plasma triglyceride (TG) levels in African American and white females and males older than 40 years and/or at increased risk of coronary artery disease. We have examined whether plasma TG levels are associated with 16 APOA5 polymorphisms in young (18-30 years) African American (1,075 females and 783 males) and white (1,041 females and 932 males) individuals of the Coronary Artery Risk Development in Young Adults (CARDIA) Study selected without regard to health. Plasma TG was significantly (P < 0.01) associated with markers 27376 and 28837 (-3A/G) in both white females and males, with 27709 (-1131T/C) and 29085 in white males, with 29009 (S19W) in African American females and white males, and with 30966 in African American females. No statistically significant associations were observed in African American males. These six single-nucleotide polymorphisms individually accounted for 0-0.78% of lnTG variation among white females, 0-2.46% among white males, and 0-0.69% among African American females. The results of our study suggest a small but replicable context-dependent influence of the APOA5 gene region on plasma TG levels in young, healthy individuals. Show less
While there is considerable appeal to the idea of selecting a few SNPs to represent all, or much, of the DNA sequence variability in a local chromosomal region, it is also important to quantify what d Show more
While there is considerable appeal to the idea of selecting a few SNPs to represent all, or much, of the DNA sequence variability in a local chromosomal region, it is also important to quantify what detail is lost in adopting such an approach. To address this issue, we compared high- and low-resolution depictions of sequence diversity for the same genomic region, the APOA1/C3/A4/A5 gene cluster on chromosome 11. First, extensive re-sequencing identified all nucleotide and sequence haplotype variation of the linked apolipoprotein genes in 72 individuals from three populations: African-Americans from Jackson, Miss., Europeans from North Karelia, Finland, and European-Americans from Rochester, Minn. We identified 124 SNPs in 17.7 kb and significant differences in variation among genes. APOC3 gene diversity was particularly distinctive at high resolution, showing large allele frequency differences ( F(ST) values >0.250) between Jackson and the other two samples, and divergent population-specific haplotype lineages. Next, we selected haplotype-tagging SNPs (htSNPs) for each gene, at a density of approximately one SNP per kb, using an algorithm suggested by Stram et al. (2003). The 17 htSNPs identified were then used to reconstruct low-resolution haplotypes, from which inferences about the structure of variation were also drawn. This comparison showed that while the htSNPs successfully tagged common haplotype variation, they also left much underlying sequence diversity undetected and failed, in some cases, to co-classify groups of closely related haplotypes. The implications of these findings for other haplotype-based descriptions of human variation are discussed. Show less