Editors' ChoiceGenetics

Pitfalls in Identifying Causal Mutations for Disease

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Science Translational Medicine  30 Oct 2013:
Vol. 5, Issue 209, pp. 209ec180
DOI: 10.1126/scitranslmed.3007776

What can you learn from sequencing seven genes? Flannick et al. have done just this in genes that carry mutations causing maturity-onset diabetes of the young (MODY) in a well-phenotyped, population-based sample of 4003 individuals. This set of genes is instructive for understanding the implications of personalized genetics: Each has well-established dominant Mendelian risk variants that cause disease; the illness occurs early, typically before age 25; many of these affected individuals either go undiagnosed or are misdiagnosed; and knowing carrier status can help because lifestyle changes can substantively reduce risk.

The overall study design contrasts the sequences of these genes from randomly sampled members of the population to those sampled from the extremes of the phenotypic distribution. The authors applied two primary bioinformatics approaches to select variants for evaluation: those that were previously reported in the literature to potentially cause pathogenic effects, and those predicted by computational methods such as SIFT and PolyPhen2 to have functional consequences.

The individuals selected from the phenotypic extremes of the population showed that low-frequency nonsynonymous variants confer risk, and that these individuals carry an excess of both previously reported causal mutations and possibly pathogenic mutations. However, in the random samples from the population, ~5% of individuals carried a low-frequency nonsynonymous variant, ~1.5% of individuals carried a previously reported variant from the Human Gene Mutation Database (HGMD), and ~0.5% of individuals carried a variant reported to be possibly pathogenic in HGMD. Overall, the carriers in the random sample did not show a MODY phenotype or an apparent increase in the risk of type 2 diabetes or impaired fasting glucose.

What we learn from sequencing these seven genes is that the current best practices for screening rare mutations in genes already known to harbor disease-causing Mendelian mutations do not unequivocally identify true pathogenic mutations. A pressing challenge is to develop the ability to accurately annotate which mutations are relevant to disease. Furthermore, the current estimates about the penetrance of mutations in Mendelian genes may be somewhat inflated as a result of the study designs that focus on extreme phenotypes.

J. Flannick et al., Assessing the phenotypic effects in the general population of rare variants in genes for a dominant Mendelian form of diabetes. Nat. Genet., published online 6 October 2013 (10.1038/ng.2794). [Abstract]

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