VA Palo Alto Healthcare System, Palo Alto, CA, USA.
Division of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, USA.
Nat Rev Cardiol. 2022 May;19(5):291-301. doi: 10.1038/s41569-021-00638-w. Epub 2021 Nov 22.
Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.
在过去的十年中，在发现导致冠心病风险的等位基因方面取得了重大进展。除了为疾病提供因果关系的见解外，这些努力还产生并改进了多基因风险评分。这些评分可用于预测多个队列中的冠心病事件，并在临床试验的事后分析中表明对某些预防疗法的临床反应。这些观察结果以及从直接面向消费者和医疗保健相关生物库计算多基因风险评分的广泛能力，引发了有关负责任的临床应用的许多问题。在这篇综述中，我们描述了多基因风险评分的推导和验证的技术和下游注意事项，以及它们的有效性和安全性的现有证据。我们讨论了这些评分在临床医学中的应用，包括冠心病风险预测和筛查算法、优先考虑可能从治疗中受益的患者亚组，以及高效的前瞻性临床试验设计。
