Title |
Periodic reanalysis of whole-genome sequencing data enhances the diagnostic advantage over standard clinical genetic testing
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Published in |
European Journal of Human Genetics, February 2018
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DOI | 10.1038/s41431-018-0114-6 |
Pubmed ID | |
Authors |
Gregory Costain, Rebekah Jobling, Susan Walker, Miriam S. Reuter, Meaghan Snell, Sarah Bowdin, Ronald D. Cohn, Lucie Dupuis, Stacy Hewson, Saadet Mercimek-Andrews, Cheryl Shuman, Neal Sondheimer, Rosanna Weksberg, Grace Yoon, M. Stephen Meyn, Dimitri J. Stavropoulos, Stephen W. Scherer, Roberto Mendoza-Londono, Christian R. Marshall |
Abstract |
Whole-genome sequencing (WGS) as a first-tier diagnostic test could transform medical genetic assessments, but there are limited data regarding its clinical use. We previously showed that WGS could feasibly be deployed as a single molecular test capable of a higher diagnostic rate than current practices, in a prospectively recruited cohort of 100 children meeting criteria for chromosomal microarray analysis. In this study, we report on the added diagnostic yield with re-annotation and reanalysis of these WGS data ~2 years later. Explanatory variants have been discovered in seven (10.9%) of 64 previously undiagnosed cases, in emerging disease genes like HMGA2. No new genetic diagnoses were made by any other method in the interval period as part of ongoing clinical care. The results increase the cumulative diagnostic yield of WGS in the study cohort to 41%. This represents a greater than 5-fold increase over the chromosomal microarrays, and a greater than 3-fold increase over all the clinical genetic testing ordered in practice. These findings highlight periodic reanalysis as yet another advantage of genomic sequencing in heterogeneous disorders. We recommend reanalysis of an individual's genome-wide sequencing data every 1-2 years until diagnosis, or sooner if their phenotype evolves. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 7 | 18% |
United Kingdom | 5 | 13% |
Spain | 3 | 8% |
Netherlands | 2 | 5% |
Japan | 1 | 3% |
Belgium | 1 | 3% |
Brazil | 1 | 3% |
Ireland | 1 | 3% |
New Zealand | 1 | 3% |
Other | 1 | 3% |
Unknown | 15 | 39% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 18 | 47% |
Members of the public | 17 | 45% |
Practitioners (doctors, other healthcare professionals) | 2 | 5% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 137 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 18% |
Student > Master | 18 | 13% |
Student > Ph. D. Student | 16 | 12% |
Other | 15 | 11% |
Student > Bachelor | 11 | 8% |
Other | 20 | 15% |
Unknown | 33 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 43 | 31% |
Medicine and Dentistry | 26 | 19% |
Agricultural and Biological Sciences | 17 | 12% |
Computer Science | 4 | 3% |
Neuroscience | 3 | 2% |
Other | 6 | 4% |
Unknown | 38 | 28% |