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Genet Med ; 20(1): 31-41, 2018 01.
Article in English | MEDLINE | ID: mdl-28726809

ABSTRACT

PurposeWe integrated whole-exome sequencing (WES) and chromosomal microarray analysis (CMA) into a clinical workflow to serve an endogamous, uninsured, agrarian community.MethodsSeventy-nine probands (newborn to 49.8 years) who presented between 1998 and 2015 remained undiagnosed after biochemical and molecular investigations. We generated WES data for probands and family members and vetted variants through rephenotyping, segregation analyses, and population studies.ResultsThe most common presentation was neurological disease (64%). Seven (9%) probands were diagnosed by CMA. Family WES data were informative for 37 (51%) of the 72 remaining individuals, yielding a specific genetic diagnosis (n = 32) or revealing a novel molecular etiology (n = 5). For five (7%) additional subjects, negative WES decreased the likelihood of genetic disease. Compared to trio analysis, "family" WES (average seven exomes per proband) reduced filtered candidate variants from 22 ± 6 to 5 ± 3 per proband. Nineteen (51%) alleles were de novo and 17 (46%) inherited; the latter added to a population-based diagnostic panel. We found actionable secondary variants in 21 (4.2%) of 502 subjects, all of whom opted to be informed.ConclusionCMA and family-based WES streamline and economize diagnosis of rare genetic disorders, accelerate novel gene discovery, and create new opportunities for community-based screening and prevention in underserved populations.


Subject(s)
Genetic Testing/statistics & numerical data , Genetics, Medical/methods , Genetics, Medical/statistics & numerical data , Genomics/statistics & numerical data , Healthcare Disparities/statistics & numerical data , Vulnerable Populations , Adolescent , Adult , Algorithms , Child , Child, Preschool , Female , Genetic Association Studies , Genetic Predisposition to Disease , Genetic Testing/methods , Genomics/methods , Humans , Incidental Findings , Infant , Infant, Newborn , Male , Middle Aged , Pedigree , Population Surveillance , Workflow , Young Adult
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