دورية أكاديمية
The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease.
| العنوان: | The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. |
|---|---|
| المؤلفون: | Moutsianas L; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom., Agarwala V; Program in Biophysics, Harvard University, Cambridge, Massachusetts, United States of America; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America., Fuchsberger C; Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America., Flannick J; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America; Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America., Rivas MA; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom., Gaulton KJ; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom., Albers PK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom., McVean G; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom., Boehnke M; Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America., Altshuler D; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America; Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America; Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America., McCarthy MI; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom. |
| مؤلفون مشاركون: | GoT2D Consortium |
| المصدر: | PLoS genetics [PLoS Genet] 2015 Apr 23; Vol. 11 (4), pp. e1005165. Date of Electronic Publication: 2015 Apr 23 (Print Publication: 2015). |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101239074 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7404 (Electronic) Linking ISSN: 15537390 NLM ISO Abbreviation: PLoS Genet Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: San Francisco, CA : Public Library of Science, c2005- |
| مواضيع طبية MeSH: | Genetic Diseases, Inborn* , Genetic Variation* , Genome-Wide Association Study* , Models, Theoretical*, Alleles ; Computer Simulation ; Diabetes Mellitus, Type 2/genetics ; Exome/genetics ; Genetic Predisposition to Disease ; Humans ; Linkage Disequilibrium ; Phenotype |
| مستخلص: | Genome and exome sequencing in large cohorts enables characterization of the role of rare variation in complex diseases. Success in this endeavor, however, requires investigators to test a diverse array of genetic hypotheses which differ in the number, frequency and effect sizes of underlying causal variants. In this study, we evaluated the power of gene-based association methods to interrogate such hypotheses, and examined the implications for study design. We developed a flexible simulation approach, using 1000 Genomes data, to (a) generate sequence variation at human genes in up to 10K case-control samples, and (b) quantify the statistical power of a panel of widely used gene-based association tests under a variety of allelic architectures, locus effect sizes, and significance thresholds. For loci explaining ~1% of phenotypic variance underlying a common dichotomous trait, we find that all methods have low absolute power to achieve exome-wide significance (~5-20% power at α = 2.5 × 10(-6)) in 3K individuals; even in 10K samples, power is modest (~60%). The combined application of multiple methods increases sensitivity, but does so at the expense of a higher false positive rate. MiST, SKAT-O, and KBAC have the highest individual mean power across simulated datasets, but we observe wide architecture-dependent variability in the individual loci detected by each test, suggesting that inferences about disease architecture from analysis of sequencing studies can differ depending on which methods are used. Our results imply that tens of thousands of individuals, extensive functional annotation, or highly targeted hypothesis testing will be required to confidently detect or exclude rare variant signals at complex disease loci. |
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| معلومات مُعتمدة: | 098381 United Kingdom WT_ Wellcome Trust; 1RC2DK088389 United States DK NIDDK NIH HHS; RC2-HG005688 United States HG NHGRI NIH HHS; U01 DK085545 United States DK NIDDK NIH HHS; R01 DK098032 United States DK NIDDK NIH HHS; R01 HG000376 United States HG NHGRI NIH HHS; T32 GM007753 United States GM NIGMS NIH HHS; R56 HG000376 United States HG NHGRI NIH HHS; R01 DK062370 United States DK NIDDK NIH HHS; DK062370 United States DK NIDDK NIH HHS; HG000376 United States HG NHGRI NIH HHS; U01-DK085545 United States DK NIDDK NIH HHS; R56 DK062370 United States DK NIDDK NIH HHS; 090367 United Kingdom WT_ Wellcome Trust; R01-DK098032 United States DK NIDDK NIH HHS; RC2 DK088389 United States DK NIDDK NIH HHS; T32GM008313 United States GM NIGMS NIH HHS; U01 DK062370 United States DK NIDDK NIH HHS; 090532 United Kingdom WT_ Wellcome Trust; T32 GM008313 United States GM NIGMS NIH HHS; P30 DK020572 United States DK NIDDK NIH HHS; T32GM007753 United States GM NIGMS NIH HHS; United Kingdom WT_ Wellcome Trust |
| تواريخ الأحداث: | Date Created: 20150424 Date Completed: 20160412 Latest Revision: 20210109 |
| رمز التحديث: | 20221213 |
| مُعرف محوري في PubMed: | PMC4407972 |
| DOI: | 10.1371/journal.pgen.1005165 |
| PMID: | 25906071 |
| قاعدة البيانات: | MEDLINE |
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