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Genet Med. 2017 Dec;19(12):1300-1308. doi: 10.1038/gim.2017.50. Epub 2017 May 4.

Assessment of the ExAC data set for the presence of individuals with pathogenic genotypes implicated in severe Mendelian pediatric disorders.

Author information

1
Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia, Canada.
2
Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.
3
BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.
4
Institute of Physiology and Biochemistry, Faculty of Biology, The University of Belgrade, Belgrade, Serbia.
5
Genome Science and Technology Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada.
6
Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.
7
Department of Pediatrics, Emma Children's Hospital, Academic Medical Centre, Amsterdam, The Netherlands.

Abstract

PurposeWe analyzed the Exome Aggregation Consortium (ExAC) data set for the presence of individuals with pathogenic genotypes implicated in Mendelian pediatric disorders.MethodsClinVar likely/pathogenic variants supported by at least one peer-reviewed publication were assessed within the ExAC database to identify individuals expected to exhibit a childhood disorder based on concordance with disease inheritance modes: heterozygous (for dominant), homozygous (for recessive) or hemizygous (for X-linked recessive conditions). Variants from 924 genes reported to cause Mendelian childhood disorders were considered.ResultsWe identified ExAC individuals with candidate pathogenic genotypes for 190 previously published likely/pathogenic variants in 128 genes. After curation, we determined that 113 of the variants have sufficient support for pathogenicity and identified 1,717 ExAC individuals (~2.8% of the ExAC population) with corresponding possible/disease-associated genotypes implicated in rare Mendelian disorders, ranging from mild (e.g., due to SCN2A deficiency) to severe pediatric conditions (e.g., due to FGFR1 deficiency).ConclusionLarge-scale sequencing projects and data aggregation consortia provide unprecedented opportunities to determine the prevalence of pathogenic genotypes in unselected populations. This knowledge is crucial for understanding the penetrance of disease-associated variants, phenotypic variability, somatic mosaicism, as well as published literature curation for variant classification procedures and predicted clinical outcomes.

PMID:
28471432
PMCID:
PMC5729344
DOI:
10.1038/gim.2017.50
[Indexed for MEDLINE]
Free PMC Article

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