Polygenic scores and social determinants of health: Their correlations and potential biases

The use of polygenic scores (PGS) for personalized medicine has gained momentum, along with caution to avoid accentuating health disparities. Greater ancestral diversity in genetic studies is needed, as well as close attention to the social determinants of health (SDoH).We measured the correlations between 3,030 PGS from the PGS Catalog and SDoH among participants in the Personalized Environment and Genes Study (PEGS). Correlations mainly ranged from −0.05 to 0.05, yet there was a heterogeneity of correlations across SDoH themes, with the largest amount of heterogeneity for PGS predicting body measures and smoking, as well as some common diseases. We also quantify the expected bias of PGS effect size on disease risk when strong predictors, such as SDoH, are omitted from models, emphasizing the importance of including SDoH with PGS to avoid biased estimates of PGS risk and to achieve equitable precision medicine.Analysis of 3,030 polygenic scores (PGS) in PEGS participants showed a range of correlations with social determinants of health (SDoH), with accentuated correlation heterogeneity for traits like body measures and smoking. Omitting strong predictors can bias the effects of included variables, emphasizing inclusion of SDoH to ensure equity in precision medicine.

多基因评分（PGS）在个性化医疗中的应用势头渐增，同时人们也谨慎行事以避免加剧健康差异。基因研究需要更大的祖先多样性，并且要密切关注健康的社会决定因素（SDoH）。我们测量了PGS目录中的3030个多基因评分与个性化环境和基因研究（PEGS）参与者的健康社会决定因素之间的相关性。相关性主要在 -0.05到0.05之间，但在不同的健康社会决定因素主题中存在相关性的异质性，在预测身体指标、吸烟以及一些常见疾病的多基因评分中异质性最大。我们还量化了当诸如健康社会决定因素等强预测因子从模型中被省略时，多基因评分对疾病风险影响大小的预期偏差，强调将健康社会决定因素与多基因评分一起考虑的重要性，以避免对多基因评分风险的估计偏差，并实现公平的精准医疗。对PEGS参与者的3030个多基因评分的分析显示，其与健康的社会决定因素存在一系列相关性，在身体指标和吸烟等特征上相关性异质性更为明显。省略强预测因子会使纳入变量的效应产生偏差，强调纳入健康社会决定因素以确保精准医疗的公平性。