Person:

Ellinor, Patrick

Background: Vascular disease is a feature of aging, and coronary vascular events are a major source of morbidity and mortality in rare premature aging syndromes. One such syndrome is caused by mutations in the lamin A/C (LMNA) gene, which also has been implicated in familial insulin resistance. A second gene related to premature aging in man and in murine models is the KLOTHO gene, a hypomorphic variant of which (KL-VS) is significantly more common in the first-degree relatives of patients with premature coronary artery disease (CAD). We evaluated whether common variants at the LMNA or KLOTHO genes are associated with rigorously defined premature CAD. Methods: We identified 295 patients presenting with premature acute coronary syndromes confirmed by angiography. A control group of 145 patients with no evidence of CAD was recruited from outpatient referral clinics. Comprehensive haplotyping of the entire LMNA gene, including the promoter and untranslated regions, was performed using a combination of TaqMan® probes and direct sequencing of 14 haplotype-tagging single nucleotide polymorphisms (SNPs). The KL-VS variant of the KLOTHO gene was typed using restriction digest of a PCR amplicon. Results: Two SNPs that were not in Hardy Weinberg equilibrium were excluded from analysis. We observed no significant differences in allele, genotype or haplotype frequencies at the LMNA or KLOTHO loci between the two groups. In addition, there was no evidence of excess homozygosity at the LMNA locus. Conclusion: Our data do not support the hypothesis that premature CAD is associated with common variants in the progeroid syndrome genes LMNA and KLOTHO.

Fibromuscular dysplasia (FMD) is a nonatherosclerotic vascular disease leading to stenosis, dissection and aneurysm affecting mainly the renal and cerebrovascular arteries. FMD is often an underdiagnosed cause of hypertension and stroke, has higher prevalence in females (~80%) but its pathophysiology is unclear. We analyzed ~26K common variants (MAF>0.05) generated by exome-chip arrays in 249 FMD patients and 689 controls. We replicated 13 loci (P<10−4) in 402 cases and 2,537 controls and confirmed an association between FMD and a variant in the phosphatase and actin regulator 1 gene (PHACTR1). Three additional case control cohorts including 512 cases and 669 replicated this result and overall reached the genomic level of significance (OR = 1.39, P = 7.4×10−10, 1,154 cases and 3,895 controls). The top variant, rs9349379, is intronic to PHACTR1, a risk locus for coronary artery disease, migraine, and cervical artery dissection. The analyses of geometrical parameters of carotids from ~2,500 healthy volunteers indicate higher intima media thickness (P = 1.97×10−4) and wall to lumen ratio (P = 0.002) in rs9349379-A carriers, suggesting indices of carotid hypertrophy previously described in carotids of FMD patients. Immunohistochemistry detected PHACTR1 in endothelium and smooth muscle cells of FMD and normal human carotids. The expression of PHACTR1 by genotypes in primary human fibroblasts showed higher expression in rs9349379-A carriers (N = 86, P = 0.003). Phactr1 knockdown in zebrafish resulted in dilated vessels indicating subtle impaired vascular development. We report the first susceptibility locus for FMD and provide evidence for a complex genetic pattern of inheritance and indices of shared pathophysiology between FMD and other cardiovascular and neurovascular diseases.

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 an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27–1.65, P = 4.3 × 10–8). Eight additional gene-gene interactions were also marginally significant (P < 5 × 10–7). However, none of the top interactions were replicated. In summary, we did not find significant interactions that were associated with AF susceptibility. Future increases in sample size and denser genotyping might facilitate the identification of gene-gene interactions associated with AF.

Background: Atrial fibrillation (AF) results in significant morbidity and mortality. Genome‐wide association studies (GWAS) have identified genetic variants associated with AF. Whether genetic variants associated with AF are also associated with atrial structure, an intermediate phenotype for AF, has had limited investigation. We sought to investigate associations between single nucleotide polymorphisms (SNPs) and atrial structure obtained by cardiovascular imaging in the Framingham Heart Study. Methods and Results: We selected 11 SNPs that have been associated with AF in GWAS. We examined the SNPs' relations to cross‐sectional left atrial (LA) dimensions (determined by transthoracic echocardiography) and LA volume (determined by cardiovascular magnetic resonance [CMR]) employing linear regression. The total sample included 1555 participants with CMR LA volume (age 60±9 years, 53% women) and 6861 participants with echocardiographic LA diameter (age 48±13 years, 52% women) measured. We employed a significance threshold of P<0.0023 to account for multiple testing of the 11 SNPs and 2 LA measures. In a primary analysis, no SNPs were significantly related to the LA measures. Likewise, in secondary analyses excluding individuals with prevalent AF (n=77, CMR sample; n=105, echocardiography sample) no SNPs were related to LA volume or diameter. Conclusion: In a community‐based cohort, we did not identify a statistically significant association between selected SNPs associated with AF and measures of LA anatomy. Further investigations with larger longitudinally assessed samples and a broader array of SNPs may be necessary to determine the relation between genetic loci associated with AF and atrial structure.

Background: Atrial fibrillation (AF) involves substantial electrophysiological, structural and contractile remodeling. We hypothesize that characterizing gene expression might uncover important pathways related to AF. Methods and Results: We performed genome-wide whole blood transcriptomic profiling (Affymetrix Human Exon 1.0 ST Array) of 2446 participants (mean age 66±9 years, 55% women) from the Offspring cohort of Framingham Heart Study. The study included 177 participants with prevalent AF, 143 with incident AF during up to 7 years follow up, and 2126 participants with no AF. We identified seven genes statistically significantly up-regulated with prevalent AF. The most significant gene, PBX1 (P = 2.8×10−7), plays an important role in cardiovascular development. We integrated differential gene expression with gene-gene interaction information to identify several signaling pathways possibly involved in AF-related transcriptional regulation. We did not detect any statistically significant transcriptomic associations with incident AF. Conclusion: We examined associations of gene expression with AF in a large community-based cohort. Our study revealed several genes and signaling pathways that are potentially involved in AF-related transcriptional regulation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, but little is known about the molecular mechanisms associated with AF arrhythmogenesis. DNA methylation is an important epigenetic mechanism that regulates gene expression and downstream biological processes. We hypothesize that DNA methylation might play an important role in the susceptibility to develop AF. A total of 2,639 participants from the Offspring Cohort of Framingham Heart Study were enrolled in the current study. These participants included 183 participants with prevalent AF and 220 with incident AF during up to 9 years follow up. Genome-wide methylation was profiled using the Illumina Infinium HumanMethylation450 BeadChip on blood-derived DNA collected during the eighth examination cycle (2005–2008). Two CpG sites were significantly associated with prevalent AF, and five CpGs were associated with incident AF after correction for multiple testing (FDR < 0.05). Fourteen previously reported genome-wide significant AF-related SNP were each associated with at least one CpG site; the most significant association was rs6490029 at the CUX2 locus and cg10833066 (P = 9.5 × 10−279). In summary, we performed genome-wide methylation profiling in a community-based cohort and identified seven methylation signatures associated with AF. Our study suggests that DNA methylation might play an important role in AF arrhythmogenesis.

Non-syndromic mitral valve prolapse (MVP) is a common degenerative cardiac valvulopathy of unknown aetiology that predisposes to mitral regurgitation, heart failure and sudden death1. Previous family and pathophysiological studies suggest a complex pattern of inheritance2–5. We performed a meta-analysis of two genome-wide association studies in 1,442 cases and 2,439 controls. We identified and replicated in 1,422 cases and 6,779 controls six loci and provide functional evidence for candidate genes. We highlight LMCD1 encoding a transcription factor6, for which morpholino knockdown in zebrafish results in atrioventricular (AV) valve regurgitation. A similar zebrafish phenotype was obtained for tensin1 (TNS1), a focal adhesion protein involved in cytoskeleton organization. We also show the expression of tensin1 during valve morphogenesis and describe enlarged posterior mitral leaflets in Tns1−/− mice. This study identifies the first risk loci for MVP and suggests new mechanisms involved in mitral valve regurgitation, the most common indication for mitral valve repair7.

Atrial fibrillation (AF) is a morbid and heritable arrhythmia. Over 35 genes have been reported to underlie AF, most of which were described in small candidate gene association studies. Replication remains lacking for most, and therefore the contribution of coding variation to AF susceptibility remains poorly understood. We examined whole exome sequencing data in a large community-based sample of 1,734 individuals with and 9,423 without AF from the Framingham Heart Study, Cardiovascular Health Study, Atherosclerosis Risk in Communities Study, and NHLBI-GO Exome Sequencing Project and meta-analyzed the results. We also examined whether genetic variation was enriched in suspected AF genes (N = 37) in AF cases versus controls. The mean age ranged from 59 to 73 years; 8,656 (78%) were of European ancestry. None of the 99,404 common variants evaluated was significantly associated after adjusting for multiple testing. Among the most significantly associated variants was a common (allele frequency = 86%) missense variant in SYNPO2L (rs3812629, p.Pro707Leu, [odds ratio 1.27, 95% confidence interval 1.13–1.43, P = 6.6x10-5]) which lies at a known AF susceptibility locus and is in linkage disequilibrium with a top marker from prior analyses at the locus. We did not observe significant associations between rare variants and AF in gene-based tests. Individuals with AF did not display any statistically significant enrichment for common or rare coding variation in previously implicated AF genes. In conclusion, we did not observe associations between coding genetic variants and AF, suggesting that large-effect coding variation is not the predominant mechanism underlying AF. A coding variant in SYNPO2L requires further evaluation to determine whether it is causally related to AF. Efforts to identify biologically meaningful coding variation underlying AF may require large sample sizes or populations enriched for large genetic effects.

Genome-wide association studies (GWAS) have identified thousands of loci associated wtih complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes involved in the Mendelian disorder long QT syndrome (LQTS). We integrated the LQTS network with GWAS loci from the corresponding common complex trait, QT interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LQTS protein network to filter weak GWAS signals by identifying single nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics.

Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration. We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse. Our work provides a general approach for improving the detection of novel loci associated with complex human traits. DOI: http://dx.doi.org/10.7554/eLife.10557.001