Population Genetics

Phenome-wide and molecular consequences of inbreeding

Submitted by	Manichaikul, Ani
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)
Associated paper proposal(s)	Phenome-wide and molecular consequences of inbreeding
Working Group(s)	Anthropometry - Adiposity (includes Physical Activity) Diabetes Lipids Multi-Omics PFT Lung Population Cohorts Population Genetics
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.

Evidence of natural selection in Samoans is associated with BMI and the immune system

Submitted by	Russell, Emily
Authors	Emily M. Russell, Daniel N. Harris, Jenna C. Carlson, Jerry Z. Zhang, Nicola L. Hawley, Hong Cheng, Take Naseri, Muagututi‘a Sefuiva Reupena, Ida Y Chen, DC Rao, Agnes C. Hsiung, Lee-Ming Chuang, Wayne Sheu, Dawood Darbar, Ranjan Deka, Timothy D. O’Connor, Stephen T. McGarvey, Daniel E. Weeks, and Ryan L. Minster with the TOPMed Population Genetics Working Group
Name and Date of Professional Meeting	ASHG Conference (October 18, 2019)
Associated paper proposal(s)	Identifying genetic signatures of adaptation in the Samoan population.
Working Group(s)	Population Genetics
Abstract Text	Samoa is part of the Polynesian Islands which were settled 3,000 years ago. Challenges faced by the settlers of Samoa may have led to positive adaptive selection when food was limited, especially for energy efficient alleles. Selection may also have occurred as a result of exposure to infectious diseases during migration or contact with outside populations. Genetic signatures of adaptation have been identified in other population isolates so, given Samoa’s genetic isolation, they are likely to be identified in Samoa as well. We performed a SNP-based population branch statistic analysis (PBS) to simultaneously compare the genetic population differentiation between Samoa and a closely-related in-group and a distantly-related out-group. 419 unrelated Samoans were compared to 1,432 unrelated Taiwan Chinese and 1,083 unrelated Europeans. All individuals were sequenced as part of the TOPMed Program. We also tested for evidence of selective sweeps in 419 unrelated Samoans using nSL, a single-population haplotype-based analysis. Since nSL values are dependent on allele frequency, nSL was calculated once with MAF>0.01 and once with MAF>0.05. The top 25 variants from the PBS, nSL(0.01), and nSL(0.05) analyses were explored further. We performed gene ontology (GO) enrichment analysis on the PBS results. The top 25 variants from the PBS, nSL(0.01), and nSL(0.05) analyses included 29 variants in/near genes (ADH5P2, ARHGEF28, CLN3, GRIN2A, KIAA1217, LOC101929563, LRFN5, OFCC1, PDZD8, RNU5F-1, SCN3A, SEMAB, and TIGAR) that have been associated with BMI and 17 variants in/near genes (ARL17B, B4GALNT4, C22orf34, LOC101929563, MIR4289, MROH1, PFKFB3, PLXNC1, and PPP2R2D) that have been associated with the immune system or respiratory disease. Genes (ABC11, ARL17B, MCU, and TMEM132C) which have been identified in other genome-wide scans of selection were also identified. Of the 10 gene sets that were significantly enriched in the GO enrichment analysis, 4 were associated with immune system-related biological processes. This suggests that variants associated with an energy efficient metabolism and the immune system may have been selected for in Samoans. Selection for BMI related alleles may have occurred during times of food scarcity. Selection for immune related alleles may have occurred in response to exposure to an infectious disease at some point in Samoan population history.