Clinical Whole-Exome Sequencing for the Diagnosis of Mendelian Disorders

By Yaping Yang, D. Muzny, Jeffrey G. Reid, M. Bainbridge, A. Willis, P. Ward, Alicia A. Braxton, J. Beuten, F. Xia, Zhiyv Niu and 14 more. New England Journal of Medicine, 2013

1,887 citations recorded by the source corpus.

BACKGROUND Whole-exome sequencing is a diagnostic approach for the identification of molecular defects in patients with suspected genetic disorders. METHODS We developed technical, bioinformatic, interpretive, and validation pipelines for whole-exome sequencing in a certified clinical laboratory to identify sequence variants underlying disease phenotypes in patients. RESULTS We present data on the first 250 probands for whom referring physicians ordered whole-exome sequencing. Patients presented with a range of phenotypes suggesting potential genetic causes. Approximately 80% were children with neurologic pheno-types. Insurance coverage was similar to that for established genetic tests. We identified 86 mutated alleles that were highly likely to be causative in 62 of the 250 patients, achieving a 25% molecular diagnostic rate (95% confidence interval, 20 to 31). Among the 62 patients, 33 had autosomal dominant disease, 16 had auto-somal recessive disease, and 9 had X-linked disease. A total of 4 probands received two nonoverlapping molecular diagnoses, which potentially challenged the clinical diagnosis that had been made on the basis of history and physical examination. A total of 83% of the autosomal dominant mutant alleles and 40% of the X-linked mutant alleles occurred de novo. Recurrent clinical phenotypes occurred in patients with mutations that were highly likely to be causative in the same genes and in different genes responsible for genetically heterogeneous disorders. CONCLUSIONS Whole-exome sequencing identified the underlying genetic defect in 25% of consecutive patients referred for evaluation of a possible genetic condition. (Funded by the National Human Genome Research Institute.)

View Paper: https://www.semanticscholar.org/paper/73921a10d537f4f1013f1627227301a056facc73

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Zhiyv Niu
2. A. Stray-Pedersen
3. Ankita Patel
4. M. Bainbridge
5. M. Holtgrewe
6. Min Wang
7. Jeffrey G. Reid
8. R. Person

Citations in the corpus

• Molecular Findings Among Patients Referred for Clinical Whole-Exome Sequencing (2014, methodology): “1 In brief, the tier 1 (focused) report included the following 6 variant reporting categories: (1) deleterious mutations (also known as pathogenic variants) related to the disease phenotype; (2) variants of unknown clinical significance related to the disease phenotype; (3) medically actionable muta”
• Next-generation diagnostics and disease-gene discovery with the Exomiser (2015, background): “WES has been enormously successful in the identification of novel Mendelian disease–associated genes 1,2 , and it has recently begun to be used for clinical diagnostics 3–6 .”
• Clinical Exome Sequencing for Genetic Identification of Rare Mendelian Disorders (2014, unknown): “DD + hypotonia 28/111 25 (18-34) 2/27 7 (1-24) 26/80 33 (23-43) 0/4 0 (0-55)”
• M-CAP eliminates a majority of variants of uncertain significance in clinical exomes at high sensitivity (2016, unknown): “Whole-exome sequencing for the diagnosis of Mendelian diseases is now a routine part of medical genetics clinical practice 1–3 , but variant interpretation remains a serious challenge 4,5 .”
• Evaluation of CADD Scores in Curated Mismatch Repair Gene Variants Yields a Model for Clinical Validation and Prioritization (2015, unknown): “…diagnostics, which is identifying large numbers of candidate disease-causative variants, ranging from about 250 [Lohmann and Klein, 2014], to 400–700 [Yang et al., 2013], up to a mean of 1,083 [Saunders et al., 2012] variants per exome, depending on which filter steps and stringency are applied.”
• An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge (2014, unknown): “For example, many studies have utilized WES datasets essentially as large gene panels, int rrogating data for only a small set of candidate genes determined based on clinical presenta tions [13] while others have developed a concept of identifying and qualifying mutations anyw here in the genome [9]”