Schuol Sebastian, Schickhardt Christoph, Wiemann Stefan, Bartram Claus R, Tanner Klaus, Eils Roland, Meder Benjamin, Richter Daniela, Glimm Hanno, von Kalle Christof, Winkler Eva C
EURAT Project, Department of Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, 69120 Heidelberg, Germany.
Department of Medical Oncology, Program for Ethics and Patient Oriented Care, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, 69120 Heidelberg, Germany.
Genome Med. 2015 Jul 30;7(1):83. doi: 10.1186/s13073-015-0198-3. eCollection 2015.
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.
在医学基因组研究中，偶然发现是激烈伦理辩论的主题。每个人类基因组都包含一些潜在的致病变异，这些变异可能在对特定病症进行全面基因分析的过程中被检测到。然而现有证据表明，研究中偶然发现的频率远低于预期。在本观点文章中，我们认为偶然发现水平较低的原因是在基因组数据的常规处理过程中所应用的过滤技术和方法去除了这些变异。由于偶然发现被系统性地过滤掉了，现在是时候评估伦理辩论是否聚焦于正确的问题了。我们的结论是，关键问题在于是否要刻意针对并搜索最初导致基因分析的指征之外的致病变异，例如通过使用阳性列表和算法。
