涉及人体样本高通量测序数据共享与数据库建设中的伦理挑战

Ethical Challenges Related to the Sharing of High-throughput Sequencing Data from Human Samples and the Construction of Databases

高通量测序数据是精准医学与个体化医疗的重要基础之一,涉及人体样本的高通量测序数据共享意义重大,但同时带来了新的伦理挑战。通过对学术期刊和常见数据库的共享模式对比分析,总结其中的伦理风险和应对策略。不同类型测序数据的伦理风险不同,原始测序数据中包含大量“未知”信息并缺乏统一标准,在知情同意、隐私保密、科学边界等方面存在伦理风险。数据库收录是当前学术期刊主流数据共享模式。统一预处理能够显著节约计算资源,规避伦理风险和促进数据挖掘。人体样本高通量测序数据是国家在生物医学领域的核心竞争力,建设大型本地数据库并提供预分析,能够在符合伦理学原则的范围内,推动高通量测序数据的共享和健康事业发展。

High-throughput sequencing data is one of the important foundations of precision medicine and personalized medicine.The sharing of high-throughput sequencing data involving human samples is of great significance,but it also brings new ethical challenges.This study made a comparative analysis of the data sharing models in academic journals and common database,summarized the ethical risks and countermeasures.Different types of high-throughput sequencing data had different ethical risks.The original sequencing data contained a lot of“unknown”information and lacked a unified standard.There were some ethical risks in terms of informed consent,privacy confidentiality,scientific boundaries and so on.Database collection was the current mainstream data sharing model of academic journals.Most of the data sharing did not require the original data,and the unified pre-processing of the database could significantly save computing resources,avoid ethical risks and promote data mining.High-throughput sequencing data of human samples is the core competence of the country in the biomedical field.Building a large-scale local database at the macro level and providing pre-analysis can greatly promote the sharing of high-throughput sequencing data and the development of health business within the scope of ethical principles.