Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism 1-5 , yet our knowledge of the causes and consequences of this is limited. Using a newly developed approach, we estimate that 20% of the UK Biobank male population (N=205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes involved in cell-cycle regulation, cancer susceptibility, somatic drivers of tumour growth and cancer therapy targets. We demonstrate that genetic susceptibility to LOY is associated with nonhaematological health outcomes in both men and women, supporting the hypothesis that clonal haematopoiesis is a biomarker of genome instability in other tissues. Single-cell RNA sequencing identifies dysregulated autosomal gene expression in leukocytes with LOY, providing insights into why clonal expansion of these cells may occur. Collectively, these data highlight the utility of studying clonal mosaicism to uncover fundamental mechanisms underlying cancer and other ageing-related diseases. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

Genome-wide association studies (GWAS) have identified many variants associated with complex traits, but identifying the causal gene(s) is a major challenge. Here we present an open resource that provides systematic fine-mapping and gene prioritization across 133,441 published human GWAS loci. We integrate genetics (GWAS Catalog and UK Biobank) with transcriptomic, proteomic and epigenomic data, including systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues. We identify 729 loci fine-mapped to a single coding causal variant and colocalized with a single gene. We trained a machine learning model using the fine-mapped genetics and functional genomics data using 445 gold-standard curated GWAS loci to distinguish causal genes from neighboring, outperforming a naive distance-based model. Our prioritized genes were enriched for known approved drug targets (OR = 8.1, 95% CI: (5.7, 11.5)). These results are publicly available through a web portal ( http://genetics.opentargets.org ), enabling users to easily prioritize genes at disease-associated loci and assess their potential as drug targets.

The Y-chromosome is frequently lost in hematopoietic cells, representing the most common somatic mutation in men. However, the mechanisms regulating mosaic loss of chromosome-Y (mLOY), and its clinical relevance, are unknown. Using genotype array intensity data and sequence reads in 85,542 men, we identify 19 genomic regions (P<5x10-8) associated with mLOY. Cumulatively, these loci also predicted X-chromosome loss in women (N=96,123, P=4x10-6). Additional epigenome-wide methylation analyses in whole blood highlighted 36 differentially methylated sites associated with mLOY. Identified genes converge on aspects of cell proliferation and cell-cycle regulation, including DNA synthesis (NPAT), DNA damage response (ATM), mitosis (PMF1-CENPN-MAD1L1) and apoptosis (TP53). We highlight shared genetic architecture between mLOY and cancer susceptibility, in addition to inferring a causal effect of smoking on mLOY. Collectively, our results demonstrate that genotype array intensity data enable a measure of cell-cycle efficiency at population scale, identifying genes implicated in aneuploidy, genome instability and cancer susceptibility.

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Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 × 10−8) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality.

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