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Components of the transforming growth factor-β (TGF-β) signal pathway function as classic tumor suppressors, but the role of the TGF-βs themselves is less clear. Here we show that mice heterozygous for deletion of the TGF-β1 gene express only 10–30% of wild-type TGF-β1 protein levels. Although grossly normal, these mice have a subtly altered proliferative phenotype, with increased cell turnover in the liver and lung. Treatment of these mice with chemical carcinogens resulted in enhanced tumorigenesis when compared with wild-type littermates. However, tumors in the heterozygous mice did not lose the remaining wild-type TGF-β1 allele, indicating that the TGF-β1 ligand is a new form of tumor suppressor that shows true haploid insufficiency in its ability to protect against tumorigenesis.

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.

The authors present a multiomics study of type 2 diabetes and quantitative blood lipid and lipoprotein traits in Hispanic/Latino populations. They demonstrate how integrating GWAS with omics characterization can advance precision medicine.

Exome-sequencing analyses of a large cohort of patients with type 2 diabetes and control individuals without diabetes from five ancestries are used to identify gene-level associations of rare variants that are associated with type 2 diabetes.

Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.

A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

Meta-analyses in up to 1.3 million individuals identify 87 rare-variant associations with blood pressure traits. On average, rare variants exhibit effects ~8 times larger than the mean effects of common variants and implicate candidate causal genes at associated regions.

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 multi-ancestry genome-wide gene–smoking interaction study identifies 13 new loci associated with serum lipids.

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.

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.

Trans-ancestry meta-analysis of estimated glomerular filtration rate (eGFR) from 1,046,070 individuals identifies 264 associated loci, providing a resource of molecular targets for translational research of chronic kidney disease.

Association analyses in over 1 million individuals identify 535 new loci influencing blood pressure traits. The results provide new insights into blood pressure regulation and highlight shared genetic architecture between blood pressure and lifestyle exposures.

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.

On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.

Wang et al. identify a promoter variant in xanthine oxidoreductase associated with diabetic kidney disease through increased podocyte depletion and glomerular injury.

Trans-ethnic analyses of exome array data identify new risk loci for type 2 diabetes. Fine-mapping analyses using genome-wide association data show that the index coding variants represent the likely causal variants at only a subset of these loci.

A transancestral exome-wide association study for body-fat distribution identifies protein-coding variants that are significantly associated with waist-to-hip ratio adjusted for body mass index.

A trans-ancestry genome-wide association study of serum urate levels identifies 183 loci influencing this trait. Enrichment analyses, fine-mapping and colocalization with gene expression in 47 tissues implicate the kidney and liver as key target organs and prioritize potential causal genes.

Data from over 700,000 individuals reveal the identity of 83 sequence variants that affect human height, implicating new candidate genes and pathways as being involved in growth.

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 studies (GWAS) have become a key tool to discover genetic markers for complex traits; however, environmental factors that interact with genes are rarely considered. Here, the authors conduct a GWAS of obesity traits, and find that smoking may alter genetic susceptibilities.

Both rare and common variants contribute to the aetiology of complex traits such as type 2 diabetes (T2D). Here, the authors examine the effect of coding variation on glycaemic traits and T2D, and identify low-frequency variation in GLP1Rsignificantly associated with these traits.

Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

Exome-wide analysis identifies rare and low-frequency coding variants associated with body mass index. Gene-based meta-analysis and functional studies implicate 13 genes, eight of which are novel, and neuronal pathways as factors in human obesity.

Bicuspid aortic valve (BAV) is the most common human congenital cardiovascular malformation. Here, the authors perform a genome-wide association study for BAV and identify risk variants in the gene region of cardiac-specific transcription factor GATA4 and implicate GATA4 in heart valve development.

Kyle Gaulton, Mark McCarthy, Andrew Morris and colleagues report fine mapping and genomic annotation of 39 established type 2 diabetes susceptibility loci. They find that the set of potential causal variants is enriched for overlap with FOXA2 binding sites in human islet and liver cells, and they show that a likely causal variant near MTNR1B increases FOXA2-bound enhancer activity, providing a molecular mechanism to explain the effect of this locus on disease risk.

Sequencing data from two large-scale studies show that most of the genetic variation influencing the risk of type 2 diabetes involves common alleles and is found in regions previously identified by genome-wide association studies, clarifying the genetic architecture of this disease.

Louise Wain, Ian Hall, Martin Tobin and colleagues report genome-wide association analyses of lung function, identifying 43 new signals associated with one or more lung function traits. A genetic risk score derived from these results was significantly associated with risk for chronic obstructive pulmonary disease in independent populations.

Danish Saleheen, Benjamin Voight and colleagues perform genome-wide analysis of multi-ancestry cohorts to identify genetic associations with type 2 diabetes (T2D) and coronary heart disease (CHD). They find novel loci and show that 24% of T2D loci are also associated with CHD and that greater genetic risk of T2D increases risk of CHD.

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.

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.

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.

A dataset of coding variation, derived from exome sequencing of nearly one million individuals from a range of ancestries, provides insight into rare variants and could accelerate the discovery of disease-associated genes and advance precision medicine efforts.

Estimated glomerular filtration rate (eGFR) is a measure of kidney function used to define chronic kidney disease. Here, Morris et al. perform trans-ethnic genome-wide meta-analyses for eGFR in 312,468 individuals and identify novel loci and downstream putative causal genes.

A new study shows that reduced fat metabolism in renal tubule cells contributes to kidney fibrosis.

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.

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.

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.

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.

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.

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.

Genetic analyses of ancestrally diverse populations show evidence of heterogeneity across ancestries and provide insights into clinical implications, highlighting the importance of including ancestrally diverse populations to maximize genetic discovery and reduce health disparities.