Guidelines for investigating causality of sequence variants in human disease

Daniel G. MacArthur(Massachusetts General Hospital), Teri A. Manolio(National Human Genome Research Institute), David Dimmock(Medical College of Wisconsin), Heidi L. Rehm(Harvard University), Jay Shendure(University of Washington), Gonçalo R. Abecasis(University of Michigan–Ann Arbor), David R. Adams(National Institutes of Health), Russ B. Altman(Stanford University), Stylianos E. Antonarakis(University of Geneva), Euan A. Ashley(Stanford University), Jeffrey C. Barrett(Wellcome Sanger Institute), Leslie G. Biesecker(National Human Genome Research Institute), Don F. Conrad(Washington University in St. Louis), Gregory M. Cooper(HudsonAlpha Institute for Biotechnology), Nancy J. Cox(University of Chicago), Mark J. Daly(Massachusetts General Hospital), Mark Gerstein(Yale University), David B. Goldstein(Duke University), Joel N. Hirschhorn(Boston Children's Hospital), Suzanne M. Leal(Baylor College of Medicine), L Pennacchio(Joint Genome Institute), J Stamatoyannopoulos(University of Washington), Shamil Sunyaev(Harvard University), David Valle(Johns Hopkins University), Benjamin F. Voight(University of Pennsylvania), Wendy Winckler(Broad Institute), Chris Gunter(HudsonAlpha Institute for Biotechnology)
Nature
April 1, 2014
Cited by 1,273Open Access
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Abstract

Acceleration in discovery of rare genetic variants possibly linked with disease may mean an increased risk of false-positive reports of causality; this Perspective proposes guidelines to distinguish disease-causing sequence variants from the many potentially functional variants in a human genome, and to assess confidence in their pathogenicity, and highlights priority areas for development. The wide-scale availability of high-throughput DNA sequencing technologies means that data on genetic variation in human diseases are accumulating rapidly. In this Perspective, Daniel MacArthur and colleagues sound a note of caution, pointing out that up to a quarter of reported disease-linked mutations have been found to either be common polymorphisms or have lacked sufficient evidence for pathogenicity. The authors discuss the key challenges associated with assessing sequence variants in human disease and propose guidelines for the robust differentiation between disease-causing genetic variants and other variants present in the human genome. They highlight several areas where research and resource development are urgently needed if genomic research findings are to be successfully translated into the clinical diagnostic setting. The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.


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