Evaluation of the diagnostic accuracy of exome sequencing and its impact on diagnostic thinking for patients with rare disease in a publicly funded health care system: A prospective cohort study.

PURPOSE: To evaluate the diagnostic utility of publicly funded clinical exome sequencing (ES) for patients with suspected rare genetic diseases. METHODS: We prospectively enrolled 297 probands who met eligibility criteria and received ES across 5 sites in Ontario, Canada, and extracted data from medical records and clinician surveys. Using the Fryback and Thornbury Efficacy Framework, we assessed diagnostic accuracy by examining laboratory interpretation of results and assessed diagnostic thinking by examining the clinical interpretation of results and whether clinical-molecular diagnoses would have been achieved via alternative hypothetical molecular tests. RESULTS: Laboratories reported 105 molecular diagnoses and 165 uncertain results in known and novel genes. Of these, clinicians interpreted 102 of 105 (97%) molecular diagnoses and 6 of 165 (4%) uncertain results as clinical-molecular diagnoses. The 108 clinical-molecular diagnoses were in 104 families (35% diagnostic yield). Each eligibility criteria resulted in diagnostic yields of 30% to 40%, and higher yields were achieved when >2 eligibility criteria were met (up to 45%). Hypothetical tests would have identified 61% of clinical-molecular diagnoses. CONCLUSION: We demonstrate robustness in eligibility criteria and high clinical validity of laboratory results from ES testing. The importance of ES was highlighted by the potential 40% of patients that would have gone undiagnosed without this test.

Bridging clinical care and research in Ontario, Canada: Maximizing diagnoses from reanalysis of clinical exome sequencing data.

We examined the utility of clinical and research processes in the reanalysis of publicly-funded clinical exome sequencing data in Ontario, Canada. In partnership with eight sites, we recruited 287 families with suspected rare genetic diseases tested between 2014 and 2020. Data from seven laboratories was reanalyzed with the referring clinicians. Reanalysis of clinically relevant genes identified diagnoses in 4% (13/287); four were missed by clinical testing. Translational research methods, including analysis of novel candidate genes, identified candidates in 21% (61/287). Of these, 24 families have additional evidence through data sharing to support likely diagnoses (8% of cohort). This study indicates few diagnoses are missed by clinical laboratories, the incremental gain from reanalysis of clinically-relevant genes is modest, and the highest yield comes from validation of novel disease-gene associations. Future implementation of translational research methods, including continued reporting of compelling genes of uncertain significance by clinical laboratories, should be considered to maximize diagnoses.