Title |
So rare we need to hunt for them: reframing the ethical debate on incidental findings
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Published in |
Genome Medicine, July 2015
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DOI | 10.1186/s13073-015-0198-3 |
Pubmed ID | |
Authors |
Sebastian Schuol, Christoph Schickhardt, Stefan Wiemann, Claus R. Bartram, Klaus Tanner, Roland Eils, Benjamin Meder, Daniela Richter, Hanno Glimm, Christof von Kalle, Eva C. Winkler |
Abstract |
Incidental findings are the subject of intense ethical debate in medical genomic research. Every human genome contains a number of potentially disease-causing alterations that may be detected during comprehensive genetic analyses to investigate a specific condition. Yet available evidence shows that the frequency of incidental findings in research is much lower than expected. In this Opinion, we argue that the reason for the low level of incidental findings is that the filtering techniques and methods that are applied during the routine handling of genomic data remove these alterations. As incidental findings are systematically filtered out, it is now time to evaluate whether the ethical debate is focused on the right issues. We conclude that the key question is whether to deliberately target and search for disease-causing variations outside the indication that has originally led to the genetic analysis, for instance by using positive lists and algorithms. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 12% |
United Kingdom | 2 | 12% |
Canada | 1 | 6% |
Bosnia and Herzegovina | 1 | 6% |
New Zealand | 1 | 6% |
Saudi Arabia | 1 | 6% |
France | 1 | 6% |
Netherlands | 1 | 6% |
Germany | 1 | 6% |
Other | 1 | 6% |
Unknown | 5 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 7 | 41% |
Members of the public | 6 | 35% |
Practitioners (doctors, other healthcare professionals) | 2 | 12% |
Science communicators (journalists, bloggers, editors) | 2 | 12% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
Unknown | 51 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 27% |
Student > Ph. D. Student | 9 | 17% |
Professor | 4 | 8% |
Student > Bachelor | 3 | 6% |
Other | 3 | 6% |
Other | 8 | 15% |
Unknown | 11 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 13 | 25% |
Medicine and Dentistry | 11 | 21% |
Biochemistry, Genetics and Molecular Biology | 6 | 12% |
Immunology and Microbiology | 2 | 4% |
Computer Science | 2 | 4% |
Other | 7 | 13% |
Unknown | 11 | 21% |