Year: 2021
Type: article
Abstract: Studies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.
Source: Nature Communications
Institutions: Vanderbilt University, Vanderbilt University Medical Center, Broad Institute, Massachusetts General Hospital, Stanley Center for Psychiatric Research, Brigham and Women's Hospital, University of Florida, University of Denver, University of Illinois Chicago, University of South Australia, University of Cambridge, MRC Epidemiology Unit
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,560
Funders: U.S. Department of Health and Human Services, Vanderbilt University, Vanderbilt University Medical Center, Georgia Clinical and Translational Science Alliance, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Neurological Disorders and Stroke, National Center for Research Resources, National Center for Advancing Translational Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1182793083, G1435936284, Pharmacogenomics of Arrhythmia Therapy, G1511474956, G1531600799, Integrating Common and Rare Variation to Discover Genes Associated with Tourette Syndrome, G1766209448, G1846282300, G1951620746, G2043477120, G2103760183, G2209161966, Understanding the genetic risk underlying racial disparities in uterine fibroids, G2265622010, G2308744219, G2615776415, G2683268942, G332351177, Improving Prediction of Drug Action, G3395468139, Mental health and chronic disease: A psycheMERGE investigation into the shared biology underlying psychiatric disorders and their physical comorbidities, G3619590958, G364208108, G3791753988, G3938985443, G4049315607, G4107354744, G4198746417, Automated Storage and Retrieval of Biological Systems, G4335719375, G4395870004, G4410787187, G4425699080, Overall: Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center at Vanderbilt, G5366963641, G560889077, G563474107, G5679716143, G5717004637, Haplotype-aware models of gene and isoform expression with application to genetic studies of disease in diverse populations, G5868276417, Functional Genomics: A Phenome-wide Survey, Genetic Epidemiology of Multiple Sclerosis, G6159295536, G6173849340, G6263508347, G6589054092, The Vanderbilt Institute for Clinical and Translational Research (VICTR) UL1, Large-Scale Collaborative Genetic and Epigenetic Studies of Tourette Syndrome, VESPA: Vanderbilt Electronic Systems for Pharmacogenomic Assessment, G7163342664, G7653134492, G7750255963, The Vanderbilt Institute for Clinical and Translational Research (VICTR), Vanderbilt Genome Electronic Records Project, Discovering Biology for Neuropsychiatric Diseases Through Omics Studies on Comorbidities, G8098630230, Epidemiologic Architecture for Genes Linked to Environment (EAGLE), G8332127685, G8680553600, G8843537459, G8844593329, Advancing Multi-Omics and Electronic Health Records Computational Methodologies, G8997515769, G9000033427, G9000300101, Vanderbilt Institute for Clinical and Translational Research (VICTR)
OpenAlex ID: W3183867452