Burt Callie H
Georgia State University.
Sociol Methodol. 2024 Aug;54(2):300-350. doi: 10.1177/00811750241236482. Epub 2024 Mar 21.
Polygenic indices (PGI)-the new recommended label for polygenic scores (PGS) in social science-are genetic summary scales often used to represent an individual's liability for a disease, trait, or behavior based on the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science datasets have facilitated increased uptake of PGIs in social science research-a trend that will likely continue. Yet, most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, we provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. We summarize our recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. We conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.
多基因指数（PGI）——社会科学中多基因分数（PGS）的新推荐术语——是一种遗传汇总量表，常用于根据测量到的基因变异的累加效应来表示个体患某种疾病、具有某种特质或表现出某种行为的倾向。将基因数据与社会结果联系起来的热情以及社会科学数据集中预建的PGI的纳入，促进了PGI在社会科学研究中的更多应用——这一趋势可能会持续下去。然而，大多数社会科学家缺乏在社会科学研究中解释和评估PGI的专业知识。在此，我们为社会科学家提供一份关于PGI的入门指南，重点介绍关键概念、独特的统计遗传学考量以及计算、估计、报告和解释方面的最佳实践。我们将推荐的最佳实践总结为一份清单，以帮助社会科学家评估和解释使用PGI的研究。我们通过讨论PGI与标准社会科学量表之间的相似性以及独特的解释性考量来结束本文。
