A genome-wide linkage and association scan reveals novel loci for autism

Member of the Autism Genome Project Consortium: Astrid M. VicenteAlthough autism is a highly heritable neurodevelopmental disorder, attempts to identify specific susceptibility genes have thus far met with limited success. Genome-wide association studies using half a million or more markers, particularly those with very large sample sizes achieved through meta-analysis, have shown great success in mapping genes for other complex genetic traits. Consequently, we initiated a linkage and association mapping study using half a million genome-wide single nucleotide polymorphisms (SNPs) in a common set of 1,031 multiplex autism families (1,553 affected offspring). We identified regions of suggestive and significant linkage on chromosomes 6q27 and 20p13, respectively. Initial analysis did not yield genome-wide significant associations; however, genotyping of top hits in additional families revealed an SNP on chromosome 5p15 (between SEMA5A and TAS2R1) that was significantly associated with autism (P = 2 x 10(-7)). We also demonstrated that expression of SEMA5A is reduced in brains from autistic patients, further implicating SEMA5A as an autism susceptibility gene. The linkage regions reported here provide targets for rare variation screening whereas the discovery of a single novel association demonstrates the action of common variants

Mitochondrial DNA Copy Number and Incident Heart Failure: The Atherosclerosis Risk in Communities (ARIC) Study

Heart failure (HF) is a leading clinical and public health concern because of its high prevalence and poor prognosis. It is thus critical to identify novel risk factors for developing HF. Mitochondrial DNA copy number (mtDNA-CN), an indirect biomarker of mitochondrial dysfunction, is associated with atherosclerotic cardiovascular disease endpoints, cardiovascular risk factors, all-cause mortality, and sudden cardiac death. The association between mtDNA-CN and the risk of incident HF, however, is unknown. We examined this association in the Atherosclerosis Risk in Communities (ARIC) cohort

Novel gene variants predict serum levels of the cytokines IL-18 and IL-1ra in older adults

Activation of inflammatory pathways measured by serum inflammatory markers such as interleukin-18 (IL-18) and interleukin-1 receptor antagonist (IL-1ra) is strongly associated with the progression of chronic disease states in older adults. Given that these serum cytokine levels are in part a heritable trait, genetic variation may predict increased serum levels. Using the Cardiovascular Health Study and InCHIANTI cohorts, a genome-wide association study was performed to identify genetic variants that influence IL18 and IL-1ra serum levels among older adults. Multiple linear regression models characterized the association between each SNP and log-transformed cytokine values. Tests for multiple independent signals within statistically significant loci were performed using haplotype analysis and regression models conditional on lead SNP in each region. Multiple SNPs were associated with these cytokines with genome-wide significance, including SNPs in the IL18-BCO gene region of chromosome 2 for IL-18 (top SNP rs2250417, P = 1.9×10−32) and in the IL1 gene family region of chromosome 2 for IL-1ra (rs6743376, P = 2.3×10−26). Haplotype tests and conditional linear regression models showed evidence of multiple independent signals in these regions. Serum IL-18 levels were also associated with a region on chromosome 2 containing the NLRC4 gene (rs12989936, P = 2.7×10−19). These data characterize multiple robust genetic signals that influence IL-18 and IL-1ra cytokine production. In particular, the signal for serum IL-18 located on chromosome two is novel and potentially important in inflammasome triggered chronic activation of inflammation in older adults. Replication in independent cohorts is an important next step, as well as molecular studies to better understand the role of NLRC4

Independent susceptibility markers for atrial fibrillation on chromosome 4q25

Background-: Genetic variants on chromosome 4q25 are associated with atrial fibrillation (AF). We sought to determine whether there is more than 1 susceptibility signal at this locus. Methods and results-: Thirty-four haplotype-tagging single-nucleotide polymorphisms (SNPs) at the 4q25 locus were genotyped in 790 case and 1177 control subjects from Massachusetts General Hospital and tested for association with AF. We replicated SNPs associated with AF after adjustment for the most significantly associated SNP in 5066 case and 30 661 referent subjects from the German Competence Network for Atrial Fibrillation, Atherosclerosis Risk In Communities Study, Cleveland Clinic Lone AF Study, Cardiovascular Health Study, and Rotterdam Study. All subjects were of European ancestry. A multimarker risk score composed of SNPs that tagged distinct AF susceptibility signals was constructed and tested for association with AF, and all results were subjected to meta-analysis. The previously reported SNP, rs2200733, was most significantly associated with AF (minor allele odds ratio 1.80, 95% confidence interval 1.50 to 2.15, P=1.2×10) in the discovery sample. Adjustment for rs2200733 genotype revealed 2 additional susceptibility signals marked by rs17570669 and rs3853445. A graded risk of AF was observed with an increasing number of AF risk alleles at SNPs that tagged these 3 susceptibility signals. Conclusions-: We identified 2 novel AF susceptibility signals on chromosome 4q25. Consideration of multiple susceptibility signals at chromosome 4q25 identifies individuals with an increased risk of AF and may localize regulatory elements at the locus with biological relevance in the pathogenesis of AF

Association of lipid-related genetic variants with the incidence of atrial fibrillation: The AFGen consortium

Background: Several studies have shown associations between blood lipid levels and the risk of atrial fibrillation (AF). To test the potential effect of blood lipids with AF risk, we assessed whether previously developed lipid gene scores, used as instrumental variables, are associated with the incidence of AF in 7 large cohorts. Methods: We analyzed 64,901 individuals of European ancestry without previous AF at baseline and with lipid gene scores. Lipid-specific gene scores, based on loci significantly associated with lipid levels, were calculated. Additionally, non-pleiotropic gene scores for high-density lipoprotein cholesterol (HDLc) and low-density lipoprotein cholesterol (LDLc) were calculated using SNPs that were only associated with the specific lipid fraction. Cox models were used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) of AF per 1-standard deviation (SD) increase of each lipid gene score. Results: During a mean follow-up of 12.0 years, 5434 (8.4%) incident AF cases were identified. After meta-analysis, the HDLc, LDLc, total cholesterol, and triglyceride gene scores were not associated with incidence of AF. Multivariable-adjusted HR (95% CI) were 1.01 (0.98-1.03); 0.98 (0.96-1.01); 0.98 (0.95-1.02); 0.99 (0.97-1.02), respectively. Similarly, non-pleiotropic HDLc and LDLc gene scores showed no association with incident AF: HR (95% CI) = 1.00 (0.97-1.03); 1.01 (0.99-1.04). Conclusions In this large cohort study of individuals of European ancestry, gene scores for lipid fractions were not associated with incident AF

Functionally oriented analysis of cardiometabolic traits in a trans-ethnic sample

Interpretation of genetic association results is difficult because signals often lack biological context. To generate hypotheses of the functional genetic etiology of complex cardiometabolic traits, we estimated the genetically determined component of gene expression from common variants using PrediXcan (1) and determined genes with differential predicted expression by trait. PrediXcan imputes tissue-specific expression levels from genetic variation using variant-level effect on gene expression in transcriptome data. To explore the value of imputed genetically regulated gene expression (GReX) models across different ancestral populations, we evaluated imputed expression levels for predictive accuracy genome-wide in RNA sequence data in samples drawn from European-Ancestry and African-Ancestry populations and identified substantial predictive power using European-derived models in a non-European target population.We then tested the association of GReX on 15 cardiometabolic traits including blood lipid levels, body mass index, height, blood pressure, fasting glucose and insulin, RR interval, fibrinogen level, factor VII level and white blood cell and platelet counts in 15 755 individuals across three ancestry groups, resulting in 20 novel gene-phenotype associations reaching experiment-wide significance across ancestries. In addition, we identified 18 significant novel gene-phenotype associations in our ancestry-specific analyses. Top associations were assessed for additional support via query of S-PrediXcan (2) results derived from publicly available genome-wide association studies summary data. Collectively, these findings illustrate the utility of transcriptome-based imputation models for discovery of cardiometabolic effect genes in a diverse dataset

Twenty-eight genetic loci associated with ST-T-wave amplitudes of the electrocardiogram

The ST-segment and adjacent T-wave (ST-T wave) amplitudes of the electrocardiogram are quantitative characteristics of cardiac repolarization. Repolarization abnormalities have been linked to ventricular arrhythmias and sudden cardiac death. We performed the first genome-wide association meta-analysis of ST-T-wave amplitudes in up to 37 977 individuals identifying 71 robust genotype-phenotype associations clustered within 28 independent loci. Fifty-four genes were prioritized as candidates underlying the phenotypes, including genes with established roles in the cardiac repolarization phase (SCN5A/SCN10A, KCND3, KCNB1, NOS1AP and HEY2) and others with as yet undefined cardiac function. These associations may provide insights in the spatiotemporal contribution of genetic variation influencing cardiac repolarization and provide novel leads for future functional follow-up

Common genetic variation near the connexin-43 gene is associated with resting heart rate in African Americans: A genome-wide association study of 13,372 participants

Genome-wide association studies have identified several genetic loci associated with variation in resting heart rate in European and Asian populations. No study has evaluated genetic variants associated with heart rate in African Americans

Gene-gene Interaction Analyses for Atrial Fibrillation

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in a

Multi-ethnic genome-wide association study of decomposed cardioelectric phenotypes illustrates strategies to identify and characterize evidence of shared genetic effects for complex traits

Background: We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci. Methods: We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test. Results: We identified 6 novels (CD36, PITX2, EMB, ZNF592, YPEL2, and BC043580) and 87 known loci (adaptive sum of powered score test P<5×10-9). Lead single-nucleotide polymorphism rs3211938 at CD36 was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci. Conclusions: Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies