BACKGROUND: Runs of homozygosity (ROH) are long stretches of homozygous genotypes in a person’s genome that result from the individual inheriting identical haplotypes from each of their two parents, often reflecting some degree of inbreeding. Long ROHs can be accurately inferred from genome-wide SNP data and can be used to indicate the level of inbreeding. We perform phenome-wide and comprehensive analysis of multi-omics data to identify the correlates of inbreeding.
METHODS: We used our tool KING to estimate inbreeding coefficients (F_ROH) in UK Biobank and MESA, using long ROHs (>3Mb) which may be indicative of identical by descent (IBD) rather than identical by state (IBS) sharing. We used data from the UK Biobank to perform association studies between the inbreeding coefficient and various cardiometabolic, pulmonary, body size, cognition, and socioeconomic traits using linear and logistic regression (1) across all participants (433,768) and (2) stratified by sex. Regression models were adjusted for sex, age, study site and principal components of ancestry. Data from the Multi-Ethnic Study of Atherosclerosis (MESA), which includes samples from people of diverse ancestries, was used to investigate the proteomic and transcriptomic consequences of inbreeding. Genes/proteins correlated with a higher inbreeding coefficient were found using a linear regression model and then they were used to identify significant pathways that may help to understand the effects of ROH and underlying mechanisms in the human genome.
RESULTS: In the UK Biobank, considering a Bonferroni P value cutoff 0.00025, inbreeding showed significant associations in 23 out of 200 traits (11.5%), including pulmonary traits (e.g., forced vital capacity FVC), body size traits (e.g., height), socioeconomic traits (e.g., Townsend deprivation index), and cognitive traits (e.g., fluid intelligence score). We identified sex differences of the inbreeding effect on the health outcomes, with generally larger effects on women than men. For example, the effect of inbreeding on the risk of diabetes was much stronger in women (OR1st-degree=6.0, P = 0.0002) than in men (P=0.54). In MESA, both the proteomics and transcriptomic analyses identified genes enriched for immune-related pathways, for example, stimulatory C-type lectin receptor signaling pathway (P < 0.05), which may suggest that inbreeding has an impact on human immunology.
CONCLUSION: Inbreeding affects significantly a large proportion of health outcome and molecular traits, and the effects may differ by sex. Future work could perform homozygosity mapping to detect genomic regions responsible for those outcomes in human phenotypes.

Genome-wide association studies (GWAS) have identified >250 genetic loci associated with type 2 diabetes (T2D), but, currently, few associations have been translated to causal genes. To directly implicate genes in T2D pathogenesis, we analyzed coding variants from the largest whole exome sequencing (WES) study to date, consisting of 36,652 cases and 91,024 controls from the Accelerating Medicines Partnership-T2D-GENES, Cohorts for Heart and Aging Research in Genomic Epidemiology, Myocardial Infarction Genetics, and NHLBI Trans-Omics for Precision Medicine consortia. Through single-variant and gene-level meta-analysis, we identify three evidence tiers of T2D-susceptibility genes. First, 11 genes harbor exome-wide significant missense associations (p≤4.3x10-7) and four genes have significant gene-level associations (p≤2.5x10-6). Two of these associations are novel: a missense mutation in MET (p=2.33x10-7), a gene with no previous genetic link to T2D, and, while presence of misdiagnosed MODY cases cannot be excluded, a series of alleles in GCK providing the first exome-wide significant association with common T2D. Second, we apply a gene-level Bayesian statistical approach to identify 29 genes with posterior probabilities (PPA) of ≥50% of explaining signals at GWAS loci. Twenty-one of these genes lie within loci where no causal gene is known, including SGP7 (PPA=0.85), a zinc metalloprotease that contains a previously reported independent common missense variant associated with T2D. Finally, we extend this Bayesian approach to another 1,069 genes previously studied in mice. This analysis identifies 17 genes with gene-level association PPA ≥50%, including 11 genes with no prior human genetic link to T2D including ONECUT1 (PPA=0.54), which is exclusively expressed in liver and pancreas. Our results further illustrate the value of WES in identifying genes that may be future T2D drug targets. All results presented will be available through the AMP-T2D Knowledge Portal.