Combining evidence from human genetic and functional screens to identify pathways altering obesity and fat distribution.

Overall adiposity and body fat distribution are heritable traits associated with altered risk of cardiometabolic disease and mortality. Performing rare variant (minor allele frequency<1%) association testing using exome-sequencing data from 402,375 participants in the UK Biobank (UKB) for nine overall and tissue-specific fat distribution traits, we identified 19 genes where putatively damaging rare variation associated with at least one trait (Bonferroni-adjusted P<1.58×10-7) and 52 additional genes at FDR≤1% (P≤4.37×10-5). These 71 genes exhibited higher (P=3.58×10-18) common variant prioritisation scores than genes not significantly enriched for rare putatively damaging variation, with evidence of monotonic allelic series (dose-response relationships) among ultra-rare variants (minor allele count≤10) in 22 genes. Five of the 71 genes have cognate protein UKB Olink data available; all five associated (P<3.80×10-6) with three or more analysed traits. Combining rare and common variation evidence, allelic series and proteomics, we selected 17 genes for CRISPR knockout in human white adipose tissue cell lines. In three previously uncharacterised target genes, knockout increased (two-sided t-test P<0.05) lipid accumulation, a cellular phenotype relevant for fat mass traits, compared to Cas9-empty negative controls: COL5A3 (fold change [FC]=1.72, P=0.0028), EXOC7 (FC=1.35, P=0.0096), and TRIP10 (FC=1.39, P=0.0157); furthermore, knockout of SLTM resulted in reduced lipid accumulation (FC=0.51, P=1.91×10-4). Integrating across population-based genetic and in vitro functional evidence, we highlight therapeutic avenues for altering obesity and body fat distribution by modulating lipid accumulation.

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank.

The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.