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A concurrent dual analysis of genomic data augments diagnoses: experiences of two clinical sites in the Undiagnosed Diseases Network. Genetics in medicine : official journal of the American College of Medical Genetics Spillmann, R. C., Tan, Q. K., Reuter, C., Schoch, K., Kohler, J., Bonner, D., Zastrow, D., Alkelai, A., Baugh, E., Cope, H., Marwaha, S., Wheeler, M. T., Bernstein, J. A., Shashi, V. 2022


Next generation sequencing (NGS) has revolutionized the diagnostic process for rare/ultra-rare conditions. However, diagnosis rates differ between analytical pipelines. In the NIH-Undiagnosed Diseases Network (UDN) study, each individual's NGS data are concurrently analyzed by the UDN sequencing core laboratory and the clinical sites. We examined the outcomes of this practice.A retrospective review was performed at two UDN clinical sites, to compare variants, and diagnoses/candidate genes identified with the dual analyses of the NGS data.Ninety-five individuals had 100 diagnoses/candidate genes. There was 59% concordance between the UDN sequencing core laboratories and the clinical sites in identifying diagnoses/candidate genes. The core laboratory provided more diagnoses, while the clinical sites prioritized more research variants/candidate genes (p <0.001). The clinical sites solely identified 15% of the diagnoses/candidate genes. The differences between the two pipelines were more often due to variant prioritization disparities, than variant detection.The unique dual analysis of NGS data in the UDN synergistically enhances outcomes. The core laboratory provides a clinical analysis with more diagnoses and the clinical sites prioritized more research variants/candidate genes. Implementing such concurrent dual analyses in other genomic research studies and clinical settings can improve both variant detection and prioritization.

View details for DOI 10.1016/j.gim.2022.12.001

View details for PubMedID 36481303