Showing papers by "Daniel I. Chasman published in 2010"

Biological, clinical and population relevance of 95 loci for blood lipids

Abstract: Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Abstract: 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 similar to 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 x 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.

Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Abstract: 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 approximately 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 x 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.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Genome-wide meta-analyses identify multiple loci associated with smoking behavior

Abstract: Consistent but indirect evidence has implicated genetic factors in smoking behavior1,2. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], b = 1.03, standard error (s.e.) = 0.053, beta = 2.8 x 10(-73)). Two 10q25 SNPs (rs1329650[G], b = 0.367, s. e. = 0.059, beta = 5.7 x 10(-10); and rs1028936[A], b = 0.446, s. e. = 0.074, beta = 1.3 x 10(-9)) and one 9q13 SNP in EGLN2 (rs3733829[G], b = 0.333, s. e. = 0.058, P = 1.0 x 10(-8)) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04-1.08, P = 1.8 x 10(-8)). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08-1.18, P = 3.6 x 10(-8)) was significantly associated with smoking cessation.

Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution

Abstract: Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.

New loci associated with kidney function and chronic kidney disease

Abstract: 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.

Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies

Abstract: 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.

Association between a literature-based genetic risk score and cardiovascular events in women.

Abstract: Context While multiple genetic markers associated with cardiovascular disease have been identified by genome-wide association studies, their aggregate effect on risk beyond traditional factors is uncertain, particularly among women. Objective To test the predictive ability of a literature-based genetic risk score for cardiovascular disease. Design, Setting, and Participants Prospective cohort of 19 313 initially healthy white women in the Women's Genome Health Study followed up over a median of 12.3 years (interquartile range, 11.6-12.8 years). Genetic risk scores were constructed from the National Human Genome Research Institute's catalog of genome-wide association study results published between 2005 and June 2009. Main Outcome Measure Incident myocardial infarction, stroke, arterial revascularization, and cardiovascular death. Results A total of 101 single nucleotide polymorphisms reported to be associated with cardiovascular disease or at least 1 intermediate cardiovascular disease phenotype at a published P value of less than 10 −7 were identified and risk alleles were added to create a genetic risk score. During follow-up, 777 cardiovascular disease events occurred (199 myocardial infarctions, 203 strokes, 63 cardiovascular deaths, 312 revascularizations). After adjustment for age, the genetic risk score had a hazard ratio (HR) for cardiovascular disease of 1.02 per risk allele (95% confidence interval [CI], 1.00-1.03/risk allele; P = .006). This corresponds to an absolute cardiovascular disease risk of 3% over 10 years in the lowest tertile of genetic risk (73-99 risk alleles) and 3.7% in the highest tertile (106-125 risk alleles). However, after adjustment for traditional factors, the genetic risk score did not improve discrimination or reclassification (change in c index from Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults [ATP III] risk score, 0; net reclassification improvement, 0.5%; [P = .24]). The genetic risk score was not associated with cardiovascular disease risk (ATP III–adjusted HR/allele, 1.00; 95% CI, 0.99-1.01). In contrast, self-reported family history remained significantly associated with cardiovascular disease in multivariable models. Conclusion After adjustment for traditional cardiovascular risk factors, a genetic risk score comprising 101 single nucleotide polymorphisms was not significantly associated with the incidence of total cardiovascular disease.

Multiple genetic loci influence serum urate levels and their relationship with gout and cardiovascular disease risk factors

Abstract: Background—Elevated serum urate levels can lead to gout and are associated with cardiovascular risk factors. We performed a genome-wide association study to search for genetic susceptibility loci f...

Genome-Wide Association of Lipid-Lowering Response to Statins in Combined Study Populations

Abstract: Background: Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy. Methods and Principal Findings: Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/ Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks). Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P=1.8610 28 ). This SNP was less significantly associated with change in LDL-cholesterol (posterior probability=0.16, P=4.0610 26 ). Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol. Conclusions and Significance: Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we have identified SNPs that may be associated with variation in the magnitude of statin-mediated reduction in total and LDL-cholesterol, including one in the CLMN gene for which statistical evidence for association exceeds conventional levels of genome-wide significance. Trial Registration: PRINCE and TNT are not registered. CAP is registered at Clinicaltrials.gov NCT00451828

Genetic variants at 2q24 are associated with susceptibility to type 2 diabetes.

Abstract: To identify type 2 diabetes (T2D) susceptibility loci, we conducted genome-wide association (GWA) scans in nested case-control samples from two prospective cohort studies, including 2591 patients and 3052 controls of European ancestry. Validation was performed in 11 independent GWA studies of 10 870 cases and 73 735 controls. We identified significantly associated variants near RBMS1 and ITGB6 genes at 2q24, best-represented by SNP rs7593730 (combined OR = 0.90, 95% CI = 0.86-0.93; P = 3.7 × 10). The frequency of the risk-lowering allele T is 0.23. Variants in this region were nominally related to lower fasting glucose and HOMA-IR in the MAGIC consortium (P < 0.05). These data suggest that the 2q24 locus may influence the T2D risk by affecting glucose metabolism and insulin resistance.

On the use of variance per genotype as a tool to identify quantitative trait interaction effects: a report from the Women's Genome Health Study.

Abstract: Testing for genetic effects on mean values of a quantitative trait has been a very successful strategy. However, most studies to date have not explored genetic effects on the variance of quantitative traits as a relevant consequence of genetic variation. In this report, we demonstrate that, under plausible scenarios of genetic interaction, the variance of a quantitative trait is expected to differ among the three possible genotypes of a biallelic SNP. Leveraging this observation with Levene's test of equality of variance, we propose a novel method to prioritize SNPs for subsequent gene–gene and gene–environment testing. This method has the advantageous characteristic that the interacting covariate need not be known or measured for a SNP to be prioritized. Using simulations, we show that this method has increased power over exhaustive search under certain conditions. We further investigate the utility of variance per genotype by examining data from the Women's Genome Health Study. Using this dataset, we identify new interactions between the LEPR SNP rs12753193 and body mass index in the prediction of C-reactive protein levels, between the ICAM1 SNP rs1799969 and smoking in the prediction of soluble ICAM-1 levels, and between the PNPLA3 SNP rs738409 and body mass index in the prediction of soluble ICAM-1 levels. These results demonstrate the utility of our approach and provide novel genetic insight into the relationship among obesity, smoking, and inflammation.

Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Abstract: 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 similar to 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 x 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.

A large-scale candidate gene association study of age at menarche and age at natural menopause

Abstract: Recent genome-wide association (GWA) studies have identified several novel genetic loci associated with age at menarche and age at natural menopause. However, the stringent significance threshold used in GWA studies potentially led to false negatives and true associations may have been overlooked. Incorporating biologically relevant information, we examined whether common genetic polymorphisms in candidate genes of nine groups of biologically plausible pathways and related phenotypes are associated with age at menarche and age at natural menopause. A total of 18,862 genotyped and imputed single nucleotide polymorphisms (SNPs) in 278 genes were assessed for their associations with these two traits among a total of 24,341 women from the Nurses’ Health Study (NHS, N = 2,287) and the Women’s Genome Health Study (WGHS, N = 22,054). Linear regression was used to assess the marginal association of each SNP with each phenotype. We adjusted for multiple testing within each gene to identify statistically significant SNP associations at the gene level. To evaluate the overall evidence for an excess of statistically significant gene associations over the proportion expected by chance, we applied a one-sample test of proportion to each group of candidate genes. The steroid-hormone metabolism and biosynthesis pathway was found significantly associated with both age at menarche and age at natural menopause (P = 0.040 and 0.011, respectively). In addition, the group of genes associated with precocious or delayed puberty was found significantly associated with age at menarche (P = 0.013), and the group of genes involved in premature ovarian failure with age at menopause (P = 0.025).

Genome-Wide Association Study Identifies Variants at the IL18 -BCO2 Locus Associated With Interleukin-18 Levels

Abstract: Objective— Interleukin-18 (IL-18) is a proinflammatory cytokine involved in the processes of innate and acquired immunities and associated with cardiovascular disease and type 2 diabetes. We sought to identify the common genetic variants associated with IL-18 levels. Methods and Results— We performed a 2-stage genome-wide association study among women of European ancestry from the Nurses’ Health Study (NHS) and Women’s Genome Health Study (WGHS). IL-18 levels were measured by ELISA. In the discovery stage (NHS, n=1523), 7 single-nucleotide polymorphisms (SNPs) at the IL18-BCO2 locus were associated with IL-18 concentrations at the 1×10−5 significance level. The strongest association was found for SNP rs2115763 in the BCO2 gene (P=6.31×10−8). In silico replication in WGHS (435 women) confirmed these findings. The combined analysis of the 2 studies indicated that SNPs rs2115763, rs1834481, and rs7106524 reached a genome-wide significance level (P<5×10−8). Forward selection analysis indicated that SNPs rs211...

Common Variants in Cardiac Ion Channel Genes Are Associated With Sudden Cardiac Death

Abstract: Background— Rare variants in cardiac ion channel genes are associated with sudden cardiac death in rare primary arrhythmic syndromes; however, it is unknown whether common variation in these same genes may contribute to sudden cardiac death risk at the population level. Methods and Results— We examined the association between 147 single nucleotide polymorphisms (SNPs) (137 tag, 5 noncoding SNPs associated with QT interval duration, and 5 nonsynonymous SNPs) in 5 cardiac ion channel genes, KCNQ1 , KCNH2 , SCN5A , KCNE1 , and KCNE2 , and sudden and/or arrhythmic death in a combined nested case-control analysis among 516 cases and 1522 matched control subjects of European ancestry enrolled in 6 prospective cohort studies. After accounting for multiple testing, 2 SNPs (rs2283222 located in intron 11 in KCNQ1 and rs11720524 located in intron 1 in SCN5A ) remained significantly associated with sudden/arrhythmic death (false discovery rate=0.01 and 0.03, respectively). Each increasing copy of the major T-allele of rs2283222 or the major C-allele of rs1172052 was associated with an odds ratio of 1.36 (95% confidence interval, 1.16 to 1.60; P =0.0002) and 1.30 (95% confidence interval, 1.12 to 1.51; P =0.0005), respectively. Control for cardiovascular risk factors and/or limiting the analysis to definite sudden cardiac death did not significantly alter these relationships. Conclusion— In this combined analysis of 6 prospective cohort studies, 2 common intronic variants in KCNQ1 and SCN5A were associated with sudden cardiac death in individuals of European ancestry. Further study in other populations and investigation into the functional abnormalities associated with noncoding variation in these genes may lead to important insights into predisposition to lethal arrhythmias.

Interpreting metabolomic profiles using unbiased pathway models.

Abstract: Human disease is heterogeneous, with similar disease phenotypes resulting from distinct combinations of genetic and environmental factors. Small-molecule profiling can address disease heterogeneity by evaluating the underlying biologic state of individuals through non-invasive interrogation of plasma metabolite levels. We analyzed metabolite profiles from an oral glucose tolerance test (OGTT) in 50 individuals, 25 with normal (NGT) and 25 with impaired glucose tolerance (IGT). Our focus was to elucidate underlying biologic processes. Although we initially found little overlap between changed metabolites and preconceived definitions of metabolic pathways, the use of unbiased network approaches identified significant concerted changes. Specifically, we derived a metabolic network with edges drawn between reactant and product nodes in individual reactions and between all substrates of individual enzymes and transporters. We searched for “active modules”—regions of the metabolic network enriched for changes in metabolite levels. Active modules identified relationships among changed metabolites and highlighted the importance of specific solute carriers in metabolite profiles. Furthermore, hierarchical clustering and principal component analysis demonstrated that changed metabolites in OGTT naturally grouped according to the activities of the System A and L amino acid transporters, the osmolyte carrier SLC6A12, and the mitochondrial aspartate-glutamate transporter SLC25A13. Comparison between NGT and IGT groups supported blunted glucose- and/or insulin-stimulated activities in the IGT group. Using unbiased pathway models, we offer evidence supporting the important role of solute carriers in the physiologic response to glucose challenge and conclude that carrier activities are reflected in individual metabolite profiles of perturbation experiments. Given the involvement of transporters in human disease, metabolite profiling may contribute to improved disease classification via the interrogation of specific transporter activities.

Prospective study of common variants in the retinoic acid receptor-related orphan receptor α gene and risk of neovascular age-related macular degeneration.

Abstract: Objectives The retinoic acid receptor (RAR)–related orphan receptor α gene ( RORA ) is implicated as a candidate for age-related macular degeneration (AMD) through a previous microarray expression study, linkage data, biological plausibility, and 2 clinic-based cross-sectional studies. We aimed to determine if common variants in RORA predict future risk of neovascular AMD. Methods We measured genotypes for 18 variants in intron 1 of the RORA gene among 164 cases who developed neovascular AMD and 485 age- and sex-matched controls in a prospective, nested, case-control study within the Nurses' Health Study and the Health Professionals Follow-up Study. We determined the incidence rate ratios and 95% confidence intervals (CI) for neovascular AMD for each variant and examined interactions with other AMD-associated variants and modifiable risk factors. Results We identified one single-nucleotide polymorphism (rs12900948) that was significantly associated with increased incidence of neovascular AMD. Participants with 1 and 2 copies of the G allele were 1.73 (CI, 1.32-2.27) and 2.99 (CI, 1.74-5.14) times more likely to develop neovascular AMD. Individuals homozygous for both the G allele of rs12900948 and ARMS2 A69S had a 40.8-fold increased risk of neovascular AMD (CI, 10.1-164; P = .017). Cigarette smokers who carried 2 copies of the G allele had a 9.89-fold risk of neovascular AMD but the interaction was not significant ( P = .08). We identified a significant AMD-associated haplotype block containing the single-nucleotide polymorphisms rs730754, rs8034864, and rs12900948, with P values for ACA = 1.16 × 10 −9 , ACG = 5.85 × 10 −12 , and GAA = .0001 when compared with all other haplotypes. Conclusions Common variants and haplotypes within the RORA gene appear to act synergistically with the ARMS2 A69S polymorphism to increase risk of neovascular AMD. These data add further evidence of a high level of complexity linking genetic and modifiable risk factors to AMD development and should help efforts at risk prediction.

Association Between a Literature-Based Genetic Risk Score and Cardiovascular Events in Women

Abstract: Genetic markers associated with cardiovascular disease, which may be predictive, have been identified by of genome-wide association studies, but their predictive ability has not been tested. The evaluation of a literature-based genetic risk score for cardiovascular disease is now possible using the online catalog maintained by the National Human Genome Research Institute of all genetic markers identified in genome-wide association studies. This prospective cohort study investigated the predictive ability of literature-based genetic risk scores for cardiovascular disease, and tested their relationship to incident cardiovascular events and their potential to improve prediction. The participants—a cohort of 19,313 initially healthy females enrolled in the Women's Genome Health Study—were followed for a median of 12.3 years. Genetic risk scores were constructed using the online National Human Genome Research Institute catalog of studies published between 2005 and 2009. The scores were based on the selection of single nucleotide polymorphisms (SNPs) that were known markers associated with either cardiovascular disease (myocardial infarction, stroke, coronary disease, or cardiovascular death), or an intermediate phenotype (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, hypertension, and other phenotypes). A total of 101 SNPs were identified with a published risk allele and a P value of less than or equal to 10−7 for the association with cardiovascular disease or at least 1 intermediate phenotype; the addition of risk alleles created the genetic risk score. During the follow-up period, there were 777 incident cardiovascular events (199 myocardial infarctions, 203 strokes, 63 cardiovascular deaths, and 312 revascularizations). Adjustment for age showed that the 101 SNP genetic risk scores were associated with increased risk of cardiovascular disease: the age-adjusted hazard ratio for cardiovascular disease per allele for the101 SNP genetic risk scores was 1.02 per risk allele, with a 95% confidence interval of 1.00 to 1.03 per risk allele; P = 0.006). Over a 10-year study period, this represented an absolute cardiovascular disease risk of 3% in the lowest tertile of genetic risk (73–99 risk alleles) and 3.7% in the highest tertile (106–125 risk alleles). However, after adjusting for traditional risk factors, the ability of the risk score alone to discriminate between women at risk for cardiovascular events and those not at risk was minimal with a c index of 0.52 in the ATP III (Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults) risk score; the ATP III–adjusted hazard ratio per allele was 1.00, with a 95% CI of 0.99 to 1.01. In contrast, self-reported family history remained an independent risk factor in multivariate models for incident cardiovascular disease. These findings indicate that a genetic risk score comprised of 101 SNPs is not significantly associated with incident cardiovascular disease, after adjustment for traditional risk factors, and has no significant effect on discrimination or reclassification.

Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies

Abstract: 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.