| Autor: |
Lassen FH; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom., Venkatesh SS; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom., Baya N; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom., Zhou W; Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Analytical and Translational Genetics Unit, Department of Medicine Massachusetts General Hospital, Boston, MA, USA., Bloemendal A; Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Novo Nordisk Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Data Sciences Platform Broad Institute of MIT and Harvard, Cambridge, MA, USA., Neale BM; Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Analytical and Translational Genetics Unit, Department of Medicine Massachusetts General Hospital, Boston, MA, USA., Kessler BM; Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom., Whiffin N; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom.; Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA, USA., Lindgren CM; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom.; Nuffield Department of Population Health Health, Medical Sciences Division University of Oxford, Oxford, United Kingdom., Palmer DS; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom. |
| Abstrakt: |
Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.001%) in exome sequencing data from 175,587 UK Biobank (UKBB) participants, which we then systematically annotate to identify putatively deleterious CH coding variation. We show that 6.5% of individuals carry such damaging variants in the CH state, with 90% of variants occurring at MAF < 0.34%. Using a logistic mixed model framework, systematically accounting for relatedness, polygenic risk, nearby common variants, and rare variant burden, we investigate recessive effects in common complex diseases. We find six exome-wide significant ( P < 1.68 × 10 - 7 ) and 17 nominally significant ( P < 5.25 × 10 - 5 ) gene-trait associations. Among these, only four would have been identified without accounting for CH variation in the gene. We further incorporate age-at-diagnosis information from primary care electronic health records, to show that genetic phase influences lifetime risk of disease across 20 gene-trait combinations (FDR < 5%). Using a permutation approach, we find evidence for genetic phase contributing to disease susceptibility for a collection of gene-trait pairs, including FLG -asthma ( P = 0.00205 ) and USH2A -visual impairment ( P = 0.0084 ). Taken together, we demonstrate the utility of phasing large-scale genetic sequencing cohorts for robust identification of the phenome-wide consequences of compound heterozygosity. |
