Background: Chronic obstructive pulmonary disease (COPD), a leading cause of morbidity and mortality, is significantly influenced by genetic factors. Despite more than 200 loci discovered by large-scale genome-wide association studies, identified loci explain only a small portion of the heritability of pulmonary function and COPD.
Methods: After sample and variant quality control, we performed whole genome sequence (WGS) analysis of pulmonary function (FEV1, FVC and FEV1/FVC) and COPD disease status of 39,644 multi-ethnic samples in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We performed single variant analysis using the Scalable and Accurate Implementation of GEneralized mixed model (SAIGE) implemented on the ENCORE platform.
Results: Using a genome-wide significance level of 5×10-9, we identified 18 genome-wide significant regions (within 2Mb) including 1,520 variants in the multi-ethnic data. In the ancestry-stratified analysis, we identified 11 genetic regions in the European- and 1 in the African-ancestry samples, respectively. In total, we identified 20 distinct regions with 1,532 variants; 10 of these regions were previously identified in the Freeze5b data in the TOPMed program including fewer samples. These newer regions were near EPHA6, GRK7, LAMA5, MGC57346-CRHR1, RHOBTB3, SCRT2 and SLC52A3. Some of these regions have been previously associated with a range of traits including blood protein measurements, body height, and others. Our analyses complement the large-scale GWAS studies with a focus on low-frequency variants, and indicates that new genetic regions could be discovered with larger sample size of whole genome sequencing data.

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.