Practical assessment of incidental finding recommendations for use in clinical exome testing. M. C. Dulik1, E. T. DeChene1, L. K. Conlin1, S. Mulchandani1, A. Santani1, J. L. Abrudan1, M. J. Italia2, M. Sarmady2, J. C. Perin2, B. Bernhardt3, C. A. Stolle1, R. E. Pyeritz3, A. Wilkens4, S. E. Noon4, P. S. White2,4, I. D. Krantz4, N. B. Spinner1 1) Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA; 2) Center for Biomedical Informatics, The Childrens Hospital of Philadelphia, Philadelphia, PA; 3) Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; 4) Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
The utilization of next generation sequencing (NGS) for diagnostics is leading to increased identification of incidental findings (IFs). IFs are clinically relevant results not related to the reason for the clinical test. Identification of IFs may significantly impact patient care if the findings lead to early diagnosis and improved treatment or management. As part of the NHGRI-funded Clinical Sequencing Exploratory Research Program, the Pediatric Genetic Sequencing (PediSeq) Project at The Childrens Hospital of Philadelphia and the University of Pennsylvania is identifying best practices for introducing exome and genome sequencing into pediatric clinical diagnostics. In addition to ascertaining the molecular cause of the patients primary findings, we are exploring various methods to effectively and efficiently identify IFs, which we have categorized into immediately medically actionable (IMA), childhood or adult onset medically actionable and carrier status. With the recent release of the American College of Medical Genetics and Genomics (ACMG) recommendations for reporting IFs in clinical exome and genome sequencing, we compared the results obtained using the 57 ACMG recommended genes with results obtained from our PediSeq IF analysis of 1953 disease genes with available clinical sequencing tests. Samples were processed for exome capture and sequencing, followed by alignment and variant calling using standard methods. Filtering strategies were applied to the variant calling files using both the PediSeq and ACMG IF gene lists. Most variants were present in control databases and not considered pathogenic (~93% of variants identified in the ACMG genes and ~77% of variants identified with the PediSeq IF framework). Minor allele frequency cut offs were established by identifying well-known, common pathogenic mutations. We identified an average of three potentially pathogenic variants per individual (range: 1-6) for follow up interpretation using the ACMG recommendations, and an average of 77 variants (range: 69-84) with the PediSeq gene list. Although the smaller number of variants identified using the ACMG gene list lessens the overall burden of interpreting IFs, we suggest that only returning IFs from these genes would limit the amount of potentially useful information available to families to a restricted, though important, set of conditions.
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