A proposal on the first Japanese practical guidance for the return of individual genomic results in research settings

Journal of Human Genetics(2020)

引用 4|浏览15
暂无评分
摘要
Large-scale, low-cost genome analysis has become possible with next-generation sequencing technology, which is currently used in research and clinical practice. Many attempts of returning individual genomic results have commenced not only in clinical practice, but also in research settings of several countries. In Japan, the government guidelines include a section on the disclosure of genetic information regarding genome analysis in research. However, no practical guidance for the return of individual genomic results in research settings (ROGRR) currently exists. We propose practical guidance regarding ROGRR in Japan based on extensive research, including a literature review of related previous studies, an examination of the relevant legislation in Japan, and interviews with stakeholders. The guidance we developed consists of “Points to consider” and “Issues for further discussion and consideration.” The “Points to consider” were divided into five parts, from preliminary review before discussion of policy, to the actual return and follow-up process, in the order of the assumed ROGRR process. It is anticipated that a situation will arise where numerous research projects will consider ROGRR carefully and realistically in the future, and in the process of drafting such practical guidance, various issues requiring continuous discussion will emerge. The necessities of continuous discussion concerning ROGRR in Japan’s context is increasing, particularly in terms of the ethical, legal, and social implications. We believe such discussions and considerations may contribute to creating a new system that will increase availability of personalized medicine and prevention using genetic information, allowing them to become useful to the broader population.
更多
查看译文
关键词
Ethics,Medical ethics,Human Genetics,Molecular Medicine,Gene Function,Gene Expression,Gene Therapy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要