Institute for Molecular Medicine Finland, FIMM, HiLIFE (E.W., N.J., S.R., I.S., N.M., P.R., J.J.P., J.A., T.T., A.P., J.K., S.R.), University of Helsinki, Helsinki, Finland.
Department of Internal Medicine, University of Michigan, Ann Arbor (I.D.).
Circ Genom Precis Med. 2022 Apr;15(2):e003459. doi: 10.1161/CIRCGEN.121.003459. Epub 2022 Feb 7.
Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear.
We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior.
When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, <0.001), with both high clinical (<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], =0.003) contributing independently.
Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.
将多基因风险评分与临床因素相结合的预测工具为改善动脉粥样硬化性心血管疾病的预测和预防提供了新的机会，但多基因风险评分的临床实用性仍不清楚。
我们收集了一个前瞻性队列的 7342 名个体（64%为女性，平均年龄 56 岁），并通过传统风险评分和综合评分来估计他们 10 年内发生动脉粥样硬化性心血管疾病的风险，综合评分将多基因风险评分和临床危险因素的影响结合起来。然后，我们测试了通过交互式网络工具返回个人风险信息如何影响参与者的健康行为。
在 1.5 年后通过临床访问和问卷调查再次评估时，20.8%的高风险 (>10%) 10 年动脉粥样硬化性心血管疾病风险个体已就诊，12.4%报告体重减轻，14.2%的吸烟者已戒烟，15.4%已在线注册健康教练。总的来说，42.6%的高风险个体与低/平均风险个体（33.5%）相比，至少做出了一项健康行为改变，因此更高的基线风险预示着更有利的改变（比值比[CI]，1.53 [1.37-1.72]，高风险个体与其余个体相比，<0.001），高临床风险（<0.001）和基因组风险（比值比[CI]，1.10 [1.03-1.17]，=0.003）均独立贡献。
向中年个体提供基于网络的个人动脉粥样硬化性心血管疾病风险数据（包括多基因风险）的沟通，可激励健康行为的积极改变和寻求医疗的意愿。它支持将基因组信息整合到临床风险计算器中，作为增强疾病预防的可行方法。
