Polygenic indices (PGI)—the new recommended label for polygenic scores in social science applications—are genetic summary scales often used to represent an individual’s liability for a disease, trait, or behavior on the basis of the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science data sets 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, I 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. I summarize recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. I conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.

中文翻译：

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社会科学中的多基因指数（又名多基因分数）：解释和评估指南

多基因指数（PGI）——社会科学应用中多基因评分的新推荐标签——是遗传汇总量表，通常用于根据测量的遗传变异的累加效应来表示个体对疾病、性状或行为的责任。人们对将遗传数据与社会结果联系起来以及将预制 PGI 纳入社会科学数据集中的热情促进了 PGI 在社会科学研究中的应用，这一趋势可能会持续下去。然而，大多数社会科学家缺乏解释和评估社会科学研究中的 PGI 的专业知识。在这里，我为社会科学家提供了关于 PGI 的入门读物，重点关注关键概念、独特的统计遗传学考虑因素以及计算、估计、报告和解释方面的最佳实践。我将推荐的最佳实践总结为清单，以帮助社会科学家评估和解释 PGI 的研究。最后，我讨论了 PGI 和标准社会科学量表之间的相似之处以及独特的解释性考虑。