IMPORTANCE Population-based assessment of disease risk associated with gene variants informs clinical decisions and risk stratification approaches. OBJECTIVE To evaluate the population-based disease risk of clinical variants in known disease predisposition genes. DESIGN, SETTING, AND PARTICIPANTS This cohort study included 72 434 individuals with 37 780 clinical variants who were enrolled in the BioMe Biobank from 2007 onwards with follow-up until December 2020 and the UK Biobank from 2006 to 2010 with follow-up until June 2020. Participants had linked exome and electronic health record data, were older than 20 years, and were of diverse ancestral backgrounds.EXPOSURES Variants previously reported as pathogenic or predicted to cause a loss of protein function by bioinformatic algorithms (pathogenic/loss-of-function variants). MAIN OUTCOMES AND MEASURESThe primary outcome was the disease risk associated with clinical variants. The risk difference (RD) between the prevalence of disease in individuals with a variant allele (penetrance) vs in individuals with a normal allele was measured. RESULTS Among 72 434 study participants, 43 395 were from the UK Biobank (mean [SD] age, 57 [8.0] years; 24 065 [55%] women; 2948 [7%] non-European) and 29 039 were from the BioMe Biobank (mean [SD] age, 56 [16] years; 17 355 [60%] women; 19 663 [68%]non-European). Of 5360 pathogenic/loss-of-function variants, 4795 (89%) were associated with an RD less than or equal to 0.05. Mean penetrance was 6.9% (95% CI, 6.0%-7.8%) for pathogenic variants and 0.85% (95% CI, 0.76%-0.95%) for benign variants reported in ClinVar (difference, 6.0 [95% CI,] percentage points), with a median of 0% for both groups due to large numbers of nonpenetrant variants. Penetrance of pathogenic/loss-offunction variants for late-onset diseases was modified by age: mean penetrance was 10.3% (95% CI, 9.0%-11.6%) in individuals 70 years or older and 8.5% (95% CI, 7.9%-9.1%) in individuals 20 years or older (difference, 1.8 [95% CI,] percentage points). Penetrance of pathogenic/loss-of-function variants was heterogeneous even in known disease predisposition genes, including BRCA1 (mean [range], 38% [0%-100%]), BRCA2 (mean [range], 38% [0%-100%]), and PALB2 (mean [range], 26% [0%-100%]). CONCLUSIONS AND RELEVANCEIn 2 large biobank cohorts, the estimated penetrance of pathogenic/loss-of-function variants was variable but generally low. Further research of population-based penetrance is needed to refine variant interpretation and clinical evaluation of individuals with these variant alleles.

Individuals with supranormal left ventricular ejection fraction (snLVEF; LVEF >70%) have increased mortality. However, the genetic and phenotypic profile of snLVEF remains unknown. This study aimed to determine the relationship of both snLVEF genetic risk and phenotype with survival and underdiagnosed heart failure (HF).

A major goal of genomic medicine is to quantify the disease risk of genetic variants. Here, we report the penetrance of 37,772 clinically relevant variants (including those reported in ClinVar1 and of loss-of-function consequence) for 197 diseases in an analysis of exome sequence data for 72,434 individuals over five ancestries and six decades of ages from two large-scale population-based biobanks (BioMe Biobank and UK Biobank). With a high-quality set of 5,359 clinically impactful variants, we evaluate disease prevalence in carriers and non-carriers to interrogate major determinants and implications of penetrance. First, we associate biomarker levels with penetrance of variants in known disease-predisposition genes and illustrate their clear biological link to disease. We then systematically uncover large numbers of ClinVar pathogenic variants that confer low risk of disease, even among those reviewed by experts, while delineating stark differences in variant penetrance by molecular consequence. Furthermore, we ascertain numerous variants present in non-European ancestries and reveal how increasing carrier age modifies penetrance estimates. Lastly, we examine substantial heterogeneity of penetrance among variants in known disease-predisposition genes for conditions such as familial hypercholesterolemia and breast cancer. These data indicate that existing categorical systems for variant classification do not adequately capture disease risk and warrant consideration of a more quantitative system based on population-based penetrance to evaluate clinical impact.

Phenome-wide association studies identified numerous loci associated with traits and diseases. To help interpret these associations, we constructed a phenome-wide network map of colocalized genes and phenotypes. We generated colocalized signals using the Genotype-Tissue Expression data and genome-wide association results in UK Biobank. We identified 9151 colocalized genes for 1411 phenotypes across 48 tissues. Then, we constructed bipartite networks using the colocalized signals in each tissue, and showed that the majority of links were observed in a single tissue. We applied the biLouvain clustering algorithm in each tissue-specific network to identify co-clusters of genes and phenotypes. We observed significant enrichments of these co-clusters with known biological and functional gene classes. Overall, the phenome-wide map provides links between genes, phenotypes and tissues, and can yield biological and clinical discoveries.

Biobanks with exomes linked to electronic health records (EHRs) enable the study of genetic pleiotropy between rare variants and seemingly disparate diseases. We performed robust clinical phenotyping of rare, putatively deleterious variants (lossof-function [LoF] and deleterious missense variants) in ERCC6, a gene implicated in inherited retinal disease. We analyzed 213,084 exomes, along with a targeted set of retinal, cardiac, and immune phenotypes from two large-scale EHR-linked biobanks.In the primary analysis, a burden of deleterious variants in ERCC6 was strongly associated with (1) retinal disorders; (2) cardiac and electrocardiogram perturbations; and (3) immunodeficiency and decreased immunoglobulin levels. Metaanalysis of results from the BioMe Biobank and UK Biobank showed a significant association of deleterious ERCC6 burden with retinal dystrophy (odds ratio [OR] =