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Multi-ancestry genome-wide and transcriptome-wide association studies of aortic stenosis identify more than 200 independent risk loci and provide insights into its genetic architecture.

Inbreeding depression has been observed in many different species, but in humans a systematic analysis has been difficult so far. Here, analysing more than 1.3 million individuals, the authors show that a genomic inbreeding coefficient (FROH) is associated with disadvantageous outcomes in 32 out of 100 traits tested.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

Timothy Frayling, Joel Hirschhorn, Peter Visscher and colleagues report a meta-analysis of genome-wide association studies for adult height in 253,288 individuals. They identify 697 variants in 423 loci significantly associated with adult height and find that these variants cluster in pathways involved in growth and together explain one-fifth of the heritability for this trait.

A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

The genetics and clinical consequences of resting heart rate (RHR) remain incompletely understood. Here, the authors discover new genetic variants associated with RHR and find that higher genetically predicted RHR decreases risk of atrial fibrillation and ischemic stroke.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient ‘biotypes’ characterized by partially distinct disease mechanisms.

Here the authors provide an explanation for 95% of examined predicted loss of function variants found in disease-associated haploinsufficient genes in the Genome Aggregation Database (gnomAD), underscoring the power of the presented analysis to minimize false assignments of disease risk.

Patricia Munroe, Christopher Newton-Cheh, Andrew Morris and colleagues perform association studies in over 340,000 individuals of European ancestry and identify 66 loci, of which 17 are novel, involved in blood pressure regulation. The risk SNPs are enriched for cis-regulatory elements, particularly in vascular endothelial cells.

Heribert Schunkert and colleagues report a meta-analysis of 14 genome-wide association studies of coronary disease (CAD) followed by replication in additional cohorts. They confirm 10 previously associated loci and identify 13 loci newly associated with CAD.

Erik Ingelsson and colleagues report a large-scale genome-wide meta-analysis for associations to the extremes of anthropometric traits, including body mass index, height, waist-to-hip ratio and clinical obesity. They identify four loci newly associated with height and seven loci newly associated with clinical obesity and find overlap in the genetic structure and distribution of variants identified for these extremes of the trait distributions and for the general population.

This large, multi-ethnic genome-wide association study identifies 97 loci significantly associated with atrial fibrillation. These loci are enriched for genes involved in cardiac development, electrophysiology, structure and contractile function.

Genome-wide association analyses, functionally informed fine-mapping and complementary gene prioritization approaches identify new risk loci and candidate effector genes for CAD.

Panos Deloukas, Nilesh Samani and colleagues report a large-scale association analysis using the Metabochip array in 63,746 coronary artery disease cases and 130,681 controls. They identify 15 susceptibility loci, refine previous associations and use network analysis to highlight biological pathways.

A meta-analysis of genome-wide association studies in more than 66,000 individuals identifies 68 new genomic loci that reliably associate with platelet count and volume, and reveals new gene functions.

Mokry et al. performed bulk RNA sequencing of 654 advanced human carotid plaques from the Athero-Express biobank and 162 coronary samples, and they show that unsupervised clustering defines plaque types corresponding to different cell compositions and clinical presentations. Circulating biomarkers can be potentially used to mark the different transcriptomic-defined plaque phenotypes.

Ruth Loos and colleagues report results of a large genome-wide association study for body mass index. They identify 18 new loci associated with this trait, some of which map near key hypothalamic regulators of energy balance.

Koplev et al. apply interactive system analyses to infer and characterize gene-regulatory networks (GRNs) active within and across tissues that cause cardiometabolic disease and coronary artery disease (CAD). By including GWAS in the integrative analysis, the provided multiorgan framework of GRNs is suggested to explain significantly more heritability of CAD than what has been achieved by analyzing GWAS alone.

Nicole Soranzo and colleagues report a meta-analysis of genome-wide association datasets identifying 22 associations to 8 clinically relevant hematological traits. They also identify a long-range haplotype at 12q24 that includes variants associated with platelet counts as well as coronary artery disease and shows evidence of a selective sweep in Europeans.

Hugh Watkins, Sekar Kathiresan, Ruth McPherson, Martin Farrall and colleagues report the results of a large genome-wide association meta-analysis of coronary artery disease based on 1000 Genomes imputation. They identify ten new risk loci and show that susceptibility to this disease is largely determined by common SNPs with small effect sizes.

Lipid concentration in the serum is one of the most important risk factors for coronary artery disease and can be targeted for therapeutic intervention. A genome-wide association study in >100,000 individuals of European ancestry now finds 95 significantly associated loci that also affect lipid traits in non-European populations. Among associated loci are those involved in cholesterol metabolism, known targets of cholesterol-lowering drugs and those that contribute to normal variation in lipid traits and to extreme lipid phenotypes.

Jeanette Erdmann and colleagues identify a locus on chromosome 3q22.3 associated with coronary artery disease. The SNP with the strongest association is in MRAS, which encodes a membrane-anchored GTP-binding protein.

Using a haplotype-based approach, David-Alexandre Trégouët and colleagues report that the SLC22A3-LPAL2-LPA gene cluster is associated with risk of coronary artery disease.

A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis.

Genome-wide association meta-analyses identify more than 350 loci associated with atrial fibrillation. A polygenic score derived from these results improves atrial fibrillation risk prediction compared to published clinical and polygenic scores.

A strategy for inferring phase for rare variant pairs is applied to exome sequencing data for 125,748 individuals from the Genome Aggregation Database (gnomAD). This resource will aid interpretation of rare co-occurring variants in the context of recessive disease.

The inner surface of the heart has a meshwork of muscles called trabeculae. McGurk et al. report the genetic regulation of these complex structures across common and rare variants, revealing pathways implicated in heart development and cell fate.

The Myocardial Infarction Genetics Consortium reports results of a genome-wide association study of early-onset myocardial infarction. The study analyzed common SNPs, common CNVs and rare CNVs and identified SNP alleles at three new loci associated with disease risk.

Samuli Ripatti and colleagues report the results of a genome-wide association study for circulating lipid levels based on 1000 Genomes Project imputation. Their results implicate several new loci, refine the association signals at many established loci and highlight the impact of low-frequency variants on lipid traits.

Daniel Chasman, Daniel Levy, Christopher Newton-Cheh, Georg Ehret and colleagues perform an association meta-analysis for blood pressure in ∼330,000 individuals and identify 31 new risk loci, implicating biological pathways related to vascular function and cardiometabolic traits. Their findings highlight potential therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Reduced glomerular filtration rate (eGFR) is a hallmark of chronic kidney disease. Here, Pattaro et al. conduct a meta-analysis to discover several new loci associated with variation in eGFR and find that genes associated with eGFR loci often encode proteins potentially related to kidney development.

A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.

A large empirical assessment of sequence-resolved structural variants from 14,891 genomes across diverse global populations in the Genome Aggregation Database (gnomAD) provides a reference map for disease-association studies, population genetics, and diagnostic screening.

Examination of predicted loss-of-function (pLOF) genetic variants allows direct identification of genes with therapeutic potential. Here, Emdin et al. perform association analysis for 3759 pLOF variants with 24 traits and highlight protective variants against cardiometabolic and immune phenotypes.

A genomic constraint map for the human genome constructed using data from 76,156 human genomes from the Genome Aggregation Database shows that non-coding constrained regions are enriched for regulatory elements and variants associated with complex diseases and traits.

Upstream open reading frames (uORFs), located in 5’ untranslated regions, are regulators of downstream protein translation. Here, Whiffin et al. use the genomes of 15,708 individuals in the Genome Aggregation Database (gnomAD) to systematically assess the deleteriousness of variants creating or disrupting uORFs.

Multi-nucleotide variants (MNV) are genetic variants in close proximity of each other on the same haplotype whose functional impact is difficult to predict if they reside in the same codon. Here, Wang et al. use the gnomAD dataset to assemble a catalogue of MNVs and estimate their global mutation rate.

A novel variant annotation metric that quantifies the level of expression of genetic variants across tissues is validated in the Genome Aggregation Database (gnomAD) and is shown to improve rare variant interpretation.

Hugh Watkins and colleagues meta-analyze data from the UK Biobank along with recent genome-wide association studies for coronary artery disease. They identify 13 new loci that were genome-wide significant and 243 loci at a 5% false discovery rate.

Here, a combination of genetic studies of gene expression, cross-species network analysis and genome-wide association studies has been used to identify gene networks and the loci underlying their regulation in rats. The results show that an inflammatory network driven by interferon regulatory factor 7 contributes to susceptibility to type 1 diabetes, and implicate the innate viral-response pathway and macrophages in the aetiology of this disease.

This very large genome-wide association study identifies hundreds of new genetic variants influencing adult height in at least 180 loci enriched for genes involved in skeletal growth defects. The results show that the likely causal gene is often located near the most strongly associated variant, that many loci have multiple independently associated variants and that associated variants are enriched for likely functional effects on genes.

Nilesh Samani and colleagues report a meta-analysis of genome-wide association studies for mean leukocyte telomere length in 37,684 individuals, with replication of selected variants in an additional 10,739 individuals. They identify seven loci associated with mean telomere length, including two that have been associated with several cancers, and also find that alleles associated with shorter telomere length were associated with a higher risk of coronary artery disease.

Joanna Howson and colleagues perform a genome-wide association study and meta-analysis for coronary artery disease in large, trans-ancestry cohorts. They identify 15 new loci and correlate these regions with cell-type-specific gene expression and plasma protein levels to find novel pathways and potential mechanisms of disease.