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Research Review: A guide to computing and implementing polygenic scores in developmental research
Author(s) -
Allegrini Andrea G.,
Baldwin Jessie R.,
Barkhuizen Wikus,
Pingault JeanBaptiste
Publication year - 2022
Publication title -
journal of child psychology and psychiatry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.652
H-Index - 211
eISSN - 1469-7610
pISSN - 0021-9630
DOI - 10.1111/jcpp.13611
Subject(s) - longitudinal data , psychology , focus (optics) , longitudinal study , population , developmental science , data science , child development , developmental psychology , computer science , data mining , medicine , physics , environmental health , pathology , optics
The increasing availability of genotype data in longitudinal population‐ and family‐based samples provides opportunities for using polygenic scores (PGS) to study developmental questions in child and adolescent psychology and psychiatry. Here, we aim to provide a comprehensive overview of how PGS can be generated and implemented in developmental psycho(patho)logy, with a focus on longitudinal designs. As such, the paper is organized into three parts: First, we provide a formal definition of polygenic scores and related concepts, focusing on assumptions and limitations. Second, we give a general overview of the methods used to compute polygenic scores, ranging from the classic approach to more advanced methods. We include recommendations and reference resources available to researchers aiming to conduct PGS analyses. Finally, we focus on the practical applications of PGS in the analysis of longitudinal data. We describe how PGS have been used to research developmental outcomes, and how they can be applied to longitudinal data to address developmental questions.