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Diagnostic yield of pediatric and prenatal exome sequencing in a diverse population.

Anne SlavotinekShannon RegoNuriye Sahin-HodoglugilMark KvaleBillie LianoglouTiffany YipHannah HobanSimon OutramBeatrice AnguianoFlavia ChenJeremy MichelsonRoberta M CilioCynthia CurryRenata C GallagherMarisa GardnerRachel KupermanBryce MendelsohnElliott SherrJoseph T C ShiehJonathan StroberAllison TamJessica TenneyWilliam WeissAmy WhittleGarrett ChinAmanda FaubelHannah PrasadYusuph MavuraJessica Van ZiffleW Patrick DevineUgur HodoglugilPierre-Marie MartinTeresa N SparksBarbara KoenigSara AckermanNeil RischPui-Yan KwokMary E Norton
Published in: NPJ genomic medicine (2023)
The diagnostic yield of exome sequencing (ES) has primarily been evaluated in individuals of European ancestry, with less focus on underrepresented minority (URM) and underserved (US) patients. We evaluated the diagnostic yield of ES in a cohort of predominantly US and URM pediatric and prenatal patients suspected to have a genetic disorder. Eligible pediatric patients had multiple congenital anomalies and/or neurocognitive disabilities and prenatal patients had one or more structural anomalies, disorders of fetal growth, or fetal effusions. URM and US patients were prioritized for enrollment and underwent ES at a single academic center. We identified definitive positive or probable positive results in 201/845 (23.8%) patients, with a significantly higher diagnostic rate in pediatric (26.7%) compared to prenatal patients (19.0%) (P = 0.01). For both pediatric and prenatal patients, the diagnostic yield and frequency of inconclusive findings did not differ significantly between URM and non-URM patients or between patients with US status and those without US status. Our results demonstrate a similar diagnostic yield of ES between prenatal and pediatric URM/US patients and non-URM/US patients for positive and inconclusive results. These data support the use of ES to identify clinically relevant variants in patients from diverse populations.
Keyphrases
  • end stage renal disease
  • ejection fraction
  • chronic kidney disease
  • newly diagnosed
  • pregnant women
  • peritoneal dialysis
  • prognostic factors
  • healthcare
  • radiation therapy
  • machine learning
  • deep learning
  • genome wide