Polygenic Scores for ADHD: A Meta-Analysis

Citation

Li, J. J. & He, Q. (2021). Polygenic Scores for ADHD: A Meta-Analysis. Research on Child and Adolescent Psychopathology. vol. 49 (3) pp. 297-310

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder that is known to have a polygenic (i.e., many genes of individually small effects) architecture. Polygenic scores (PGS), which characterize this polygenicity as a single score for a given individual, are considered the state-of-the-art in psychiatric genetics research. Despite the proliferation of ADHD studies adopting this approach and its clinical implications, remarkably little is known about the predictive utility of PGS in ADHD research to date, given that there have not yet been any systematic or meta-analytic reviews of this rapidly developing literature. We meta-analyzed 12 unique effect sizes from ADHD PGS studies, yielding an N = 40,088. These studies, which included a mixture of large population-based cohorts and case–control samples of predominantly European ancestry, yielded a pooled ADHD PGS effect size of rrandom = 0.201 (95% CI = [0.144, 0.288]) and an rfixed = 0.190 (95% CI = [0.180, 0.199]) in predicting ADHD. In other words, ADHD PGS reliably account for between 3.6% (in the fixed effects model) to 4.0% (in the random effects model) of the variance in broadly defined phenotypic ADHD. Findings provide important insights into the genetics of psychiatric outcomes and raise several key questions about the impact of PGS on psychiatric research moving forward. Our review concludes by providing recommendations for future research directions in the use of PGS, including new methods to account for comorbidities, integrating bioinformatics to elucidate biological pathways, and leveraging PGS to test mechanistic models of ADHD.

URL

https://doi.org/10.1007/s10802-021-00774-4

Keyword(s)

Polygenic scores

Reference Type

Journal Article

Journal Title

Research on Child and Adolescent Psychopathology

Author(s)

Li, J. J.
He, Q.

Year Published

2021

Volume Number

49

Issue Number

3

Pages

297-310

Edition

March 1, 2021

ISSN/ISBN

2730-7174

DOI

10.1007/s10802-021-00774-4

Reference ID

10228