Next generation sequencing for clinical diagnostics: Five year experience of an academic laboratory

Paige Hartman(University of Minnesota, Duluth), Kenneth B. Beckman(University of Minnesota), Kevin A.T. Silverstein(University of Minnesota), Sophia Yohe(University of Minnesota), Matthew Schomaker(University of Minnesota), Christine Henzler(University of Minnesota), Getiria Onsongo(Macalester College), Ham Ching Lam(University of Minnesota), Sarah Munro(University of Minnesota), Jerry Daniel(University of Minnesota), Bradley Billstein(University of Minnesota), Archana Deshpande(University of Minnesota), Adam Hauge(Illumina (United States)), Paweł Mróz(University of Minnesota), Whiwon Lee(University of Minnesota), Jennifer Holle(Invitae (United States)), Katie M. Wiens(University of Minnesota), Kylene Karnuth(University of Minnesota), Teresa Kemmer(University of Minnesota), Michaela M. Leary(University of Minnesota), Stephen Michel(University of Minnesota), Laurie Pohlman(University of Minnesota), Venugopal Thayanithy(University of Minnesota), Andrew C. Nelson(University of Minnesota), Matthew Bower(University of Minnesota), Bharat Thyagarajan(University of Minnesota)
Molecular Genetics and Metabolism Reports
March 1, 2019
Cited by 62Open Access
Full Text

Abstract

Clinical laboratories have adopted next generation sequencing (NGS) as a gold standard for the diagnosis of hereditary disorders because of its analytic accuracy, high throughput, and potential for cost-effectiveness. We describe the implementation of a single broad-based NGS sequencing assay to meet the genetic testing needs at the University of Minnesota. A single hybrid capture library preparation was used for each test ordered, data was informatically blinded to clinically-ordered genes, and identified variants were reviewed and classified by genetic counselors and molecular pathologists. We performed 2509 sequencing tests from August 2012 till December 2017. The diagnostic yield has remained steady at 25%, but the number of variants of uncertain significance (VUS) included in a patient report decreased over time with 50% of the patient reports including at least one VUS in 2012 and only 22% of the patient reports reporting a VUS in 2017 (p = .002). Among the various clinical specialties, the diagnostic yield was highest in dermatology (60% diagnostic yield) and ophthalmology (42% diagnostic yield) while the diagnostic yield was lowest in gastrointestinal diseases and pulmonary diseases (10% detection yield in both specialties). Deletion/duplication analysis was also implemented in a subset of panels ordered, with 9% of samples having a diagnostic finding using the deletion/duplication analysis. We have demonstrated the feasibility of this broad-based NGS platform to meet the needs of our academic institution by aggregating a sufficient sample volume from many individually rare tests and providing a flexible ordering for custom, patient-specific panels.


Related Papers

No related papers found

Powered by citation graph analysis