Automated Clinical Exome Reanalysis Reveals Novel Diagnoses.

J Mol Diagn 2019 01;21(1):38-48

Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address:

Clinical exome sequencing (CES) has a reported diagnostic yield of 20% to 30% for most clinical indications. The ongoing discovery of novel gene-disease and variant-disease associations are expected to increase the diagnostic yield of CES. Performing systematic reanalysis of previously nondiagnostic CES samples represents a significant challenge for clinical laboratories. Here, we present the results of a novel automated reanalysis methodology applied to 300 CES samples initially analyzed between June 2014 and September 2016. Application of our reanalysis methodology reduced reanalysis variant analysis burden by >93% and correctly captured 70 of 70 previously identified diagnostic variants among 60 samples with previously identified diagnoses. Notably, reanalysis of 240 initially nondiagnostic samples using information available on July 1, 2017, revealed 38 novel diagnoses, representing a 15.8% increase in diagnostic yield. Modeling monthly iterative reanalysis of 240 nondiagnostic samples revealed a diagnostic rate of 0.57% of samples per month. Modeling the workload required for monthly iterative reanalysis of nondiagnostic samples revealed a variant analysis burden of approximately 5 variants/month for proband-only and approximately 0.5 variants/month for trio samples. Approximately 45% of samples required evaluation during each monthly interval, and 61.3% of samples were reevaluated across three consecutive reanalyses. In sum, automated reanalysis methods can facilitate efficient reevaluation of nondiagnostic samples using up-to-date literature and can provide significant value to clinical laboratories.

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Source
https://linkinghub.elsevier.com/retrieve/pii/S15251578183006
Publisher Site
http://dx.doi.org/10.1016/j.jmoldx.2018.07.008DOI Listing
January 2019
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