Search

Here, the authors leverage whole-genome sequencing from >88,000 diverse individuals to uncover 18 BMI-related genetic signals, including novel variants in participants of African genetic ancestry, highlighting the value of diversity in genetic discovery.

MultiSTAAR provides a general and flexible statistical framework for functionally informed multi-trait rare variant analysis of biobank-scale sequencing studies by jointly analyzing multiple traits and incorporating annotation information.

Using data from a single time point, passenger-approximated clonal expansion rate (PACER) estimates the fitness of common driver mutations that lead to clonal haematopoiesis and identifies TCL1A activation as a mediator of clonal expansion.

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.

Allele-preferential transcription factor binding can influence pancreatic ductal adenocarcinoma risk loci function. Here, the authors show allele-specific JunB and JunD binding at chr1p36.33 and propose a role for KLHL17 in protein homeostasis by mitigating inflammation.

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.

Here, the authors perform large trans-ancestry fine-mapping analyses identifying large numbers of association signals and putative target genes for colorectal cancer risk, advancing our understanding of the genetic and biological basis of this cancer.

Analyses of genome and exome sequencing data identify rare coding and structural variants associated with atrial fibrillation and highlight genetic links between atrial fibrillation and cardiomyopathies.

It is unclear how often genetic mosaicism of chromosome X arises. Here, the authors examine women with cancer and cancer-free controls and show that X chromosome mosaicism occurs more frequently than on autosomes, especially on the inactive X chromosome, but is not linked to non-haematologic cancer risk

A meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

Whole genome sequences enable discovery of rare variants which may help to explain the heritability of common diseases. Here the authors find that ultra-rare variants explain ~50% of coronary artery disease (CAD) heritability and highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components. STAAR accounts for population structure and relatedness and is scalable for analyzing large whole-genome sequencing studies.

Analysis of whole-genome sequences of 25,465 individuals of European ancestry shows that rare variants contribute substantially to the heritability of height and body mass index.

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

Multiancestry genome-wide association analyses identify new risk loci for stroke and stroke subtypes. Fine mapping and bioinformatics analyses of these risk loci point to mechanisms not previously implicated in stroke pathophysiology.

Polygenic risk scores have potential to predict an individual’s risk of disease based on genetic markers. Here, the authors develop a polygenic risk score for hypertension and test it in a multi-ethnic cohort, finding that the score is associated with higher likelihood of hypertension development 4-6 years later.

Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.

The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Hundreds of genetic loci associated with age at menopause, combined with experimental evidence in mice, highlight mechanisms of reproductive ageing across the lifespan.

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.

Here, the authors perform a rare-variant analysis of whole-genome sequence data that takes advantage of three global biobanks. They identify 29 novel rare variants associated with human height, and demonstrate an approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data.

GWAS have identified more than 500 genetic loci associated with blood lipid levels. Here, the authors report a genome-wide analysis of interactions between genetic markers and physical activity, and find that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol.

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data.

STAARpipeline is a comprehensive framework for flexible and scalable rare-variant association analysis using whole-genome sequencing data and annotation information.

This analysis of individuals of admixed genetic ancestries suggests that complex trait causal variant effect sizes are, by and large, similar across ancestries, and discusses the implications for the study of these and other diverse populations.

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.

Genome-wide analysis of venous thromboembolism identifies 22 new risk loci and facilitates construction of a polygenic risk score. Comparison to arterial vascular disease highlights shared pathophysiology and potential therapeutic strategies.

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

A cross-ancestry meta-analysis of genome-wide association studies identifies association signals for stroke and its subtypes at 89 (61 new) independent loci, reveals putative causal genes, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as potential drug targets, and provides cross-ancestry integrative risk prediction.

A multi-ancestry transcriptome-wide association study using an optimal linear combination of association statistics provides insights into tobacco use biology and suggests opportunities for drug repurposing.

Genetic variants associated with susceptibility to pancreatic cancer have been identified using genome wide association studies (GWAS). Here, the authors combine data from over 9000 patients and perform a meta-analysis to identify five novel loci linked to pancreatic cancer.

A multi-ancestry genome-wide association study meta-analysis, combined with transcriptome- and methylome-wide association analyses, identifies risk loci associated with colorectal cancer. Credible effector genes and their target tissues are also highlighted, showing that over a third probably act outside the colonic mucosa.

Here the authors conduct a multi-ancestry meta-analysis of telomere length, used diverse approaches to identify genes underlying association signals, and experimentally validated POP5 and KBTBD6 as regulators of telomere length in human cells.

Schuermans et al. identify a causal relationship between the circulating proteins spondin-1 and atrial fibrillation and SPINT1 and coronary artery disease and show that adding proteomic data improves clinical risk factor-based cardiovascular risk prediction.

A multi-ancestry meta-regression study analyses diverse genome-wide association studies and genome loci associated with tobacco and alcohol use.

Accurate classification of genetic variants is critical for research and patient care. Here, the authors report that population-based associations between rare variants and quantitative endophenotypes for monogenic diseases can provide support for variant pathogenicity.

Repetto et al. provide an analysis of the genetic basis of variation of neuro-related protein levels in plasma and link this to human behaviour and disorders.

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.

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.

Here, the authors assess performance and limitations to polygenic risk scores in different race/ethnic groups. They find that polygenic risk score performance improves with diverse training data, and a better understanding of varying genetic backgrounds, social and environmental factors, and gene-environment interactions, is needed to enhance PRS performance for all groups.

Evan Eichler and colleagues analyze copy number variation in 15,767 children with intellectual disability, developmental delay, congenital birth defects and/or other related phenotypes. They identify 59 likely pathogenic CNV regions, including 14 new candidate regions, and estimate that ~14% of disorders in this sample collection are caused by large CNVs.

Sleep duration is associated with an adverse lipid profile. Here, the authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time.

Genome-wide association analyses based on whole-genome sequencing and imputation identify 40 new risk variants for colorectal cancer, including a strongly protective low-frequency variant at CHD1 and loci implicating signaling and immune function in disease etiology.

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.

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.

Luis Pérez-Jurado, Stephen Chanock and colleagues detect clonal chromosomal abnormalities in peripheral blood or buccal samples from individuals in the general population. They show that the frequency of such events increases with age and is associated with elevated risk of developing subsequent hematological cancers.

Rachael Stolzenberg-Solomon, Laufey Amundadottir and colleagues report a genome-wide association study of pancreatic cancer. They identify four new susceptibility loci.

To overcome limitations of previous genome-wide association studies of coronary artery disease, this study incorporates a cohort of individuals containing large fractions of Black and Hispanic individuals to provide a wider view of the genetic landscape of this disease.