Multi-Omics
Phenome-wide and molecular consequences of inbreeding
| Submitted by | Manichaikul, Ani
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| Authors | Maria Murach, Center for Public Health Genomics, University of Virginia, USA
Zhennan Zhu, , Center for Public Health Genomics, University of Virginia, USA Mark O. Goodarzi, Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA Gina M. Peloso, Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA Leslie A. Lange, Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, Colorado, USA Jingzhong Ding, Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA Francois Aguet, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA Kristin G. Ardlie, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA Robert E. Gerszten, Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA The MESATOPMed Multi-omics Team Jerome I Rotter, The Institute for Translational Genomics and Population Sciences, The Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA Stephen S. Rich, Center for Public Health Genomics, University of Virginia, USA Ani Manichaikul, Center for Public Health Genomics, University of Virginia, USA Wei-Min Chen, Center for Public Health Genomics, University of Virginia, USA |
| Name and Date of Professional Meeting | American Society of Human Genetics (Oct 27-31, 2020)
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| Associated paper proposal(s) | |
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| Abstract Text |
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. |
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