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Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios

2015; Elsevier BV; Volume: 17; Issue: 10 Linguagem: Inglês

10.1038/gim.2014.191

1530-0366

Xiaolin Zhu, Slavé Petrovski, Pingxing Xie, Elizabeth K. Ruzzo, Yifan Lu, K. Melodi McSweeney, Bruria Ben‐Zeev, Andreea Nissenkorn, Yair Anikster, Danit Oz-Levi, Ryan S. Dhindsa, Yuki Hitomi, Kelly Schoch, Rebecca C. Spillmann, Gali Heimer, Dina Marek‐Yagel, Michal Tzadok, Yujun Han, Gordon Worley, Jennifer Goldstein, Yong‐hui Jiang, Doron Lancet, Elon Pras, Vandana Shashi, Duncan McHale, Anna C. Need, David B. Goldstein,

Genetic factors in colorectal cancer

PurposeDespite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene–disease associations.MethodsWe analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients.ResultsWe obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10−8). This enrichment is only partially explained by mutations found in known disease-causing genes.ConclusionThis work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications.