Large Numbers of Genetic Variants Considered to be Pathogenic are Common in Asymptomatic Individuals

Massachusetts Institute of Technology, Cambridge, MA
Human Mutation (Impact Factor: 5.14). 09/2013; 34(9). DOI: 10.1002/humu.22375
Source: PubMed


It is now affordable to order clinically interpreted whole genome sequence reports from clinical laboratories. One major component of these reports is derived from the knowledge base of previously identified pathogenic variants, including research articles, locus specific and other databases. While over 150,000 such pathogenic variants have been identified, many of these were originally discovered in small cohort studies of affected individuals, so their applicability to asymptomatic populations is unclear. We analyzed the prevalence of a large set of pathogenic variants from the medical and scientific literature in a large set of asymptomatic individuals (N = 1,092) and found 8.5% of these pathogenic variants in at least one individual. In the average individual in the 1000 Genomes Project, previously identified pathogenic variants occur on average 294 times (σ = 25.5) in homozygous form and 942 times (σ = 68.2) in heterozygous form. We also find that many of these pathogenic variants are frequently occurring: there are 3,744 variants with MAF > = 0.01 (4.6%) and 2,837 variants with MAF > = 0.05 (3.5%). This indicates that many of these variants may be erroneous findings or have lower penetrance than previously expected. This article is protected by copyright. All rights reserved.

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Available from: Christopher A Cassa, Sep 29, 2015
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    • "Another major source of analytic error is misinterpretation. Recent analyses indicate that disease-causing variants reported in the medical literature and in large-scale databases such as the Human Gene Mutation Database are frequently incorrect, with reported error frequencies of 4%–23% [Bell et al., 2011; Tong et al., 2011; Cassa et al., 2013]. In addition, current in silico tools for predicting variant pathogenicity, such as SIFT and PolyPhen, have less than 80% accuracy [Gray et al., 2012; Sim et al., 2012]. "
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    ABSTRACT: Our increasing knowledge of how genomic variants affect human health and the falling costs of whole genome sequencing are driving the development of individualized genetic medicine. This new clinical paradigm uses knowledge of an individual's genomic variants to guide health care decisions throughout life, in order to anticipate, diagnose and manage disease. While individualized genetic medicine offers the promise of transformative change in health care, it forces us to reconsider existing ethical, scientific and clinical paradigms. The potential benefits of presymptomatic identification of at risk individuals, improved diagnostics, individualized therapy, accurate prognosis, and avoidance of adverse drug reactions co-exist with the potential risks of uninterpretable results, psychological harm, outmoded counselling models and increased health care costs. Here we review the challenges of integrating genomic analysis into clinical practice and describe a prototype for implementing genetic medicine. Our multidisciplinary team of bioinformaticians, health economists, ethicists, geneticists, genetic counsellors, and clinicians has designed a “Genome Clinic” research project that addresses multiple challenges in genomic medicine – ranging from development of bioinformatics tools for the clinical assessment of genomic variants and the discovery of disease genes to health policy inquiries, assessment of clinical care models, patient preference and the ethics of consent. This article is protected by copyright. All rights reserved
    Human Mutation 05/2014; 35(5). DOI:10.1002/humu.22536 · 5.14 Impact Factor
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    Nature Genetics 06/2014; DOI:10.1038/ng.3021 · 29.35 Impact Factor
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