Comparing Within- and Between-Family Polygenic Score Prediction.

TitleComparing Within- and Between-Family Polygenic Score Prediction.
Publication TypeJournal Article
Year of Publication2019
AuthorsSelzam, S, Ritchie, SJ, Pingault, J-B, Reynolds, CA, O'Reilly, PF, Plomin, R
JournalAm J Hum Genet
Date Published2019 Aug 01
ISSN Number1537-6605
KeywordsAdolescent, Adult, Child, Cognition, Cognition Disorders, Diseases in Twins, Educational Status, Family, Female, genes, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Multifactorial Inheritance, Neurodevelopmental Disorders, Phenotype, Polymorphism, Single Nucleotide, Schizophrenia, Young Adult

Polygenic scores are a popular tool for prediction of complex traits. However, prediction estimates in samples of unrelated participants can include effects of population stratification, assortative mating, and environmentally mediated parental genetic effects, a form of genotype-environment correlation (rGE). Comparing genome-wide polygenic score (GPS) predictions in unrelated individuals with predictions between siblings in a within-family design is a powerful approach to identify these different sources of prediction. Here, we compared within- to between-family GPS predictions of eight outcomes (anthropometric, cognitive, personality, and health) for eight corresponding GPSs. The outcomes were assessed in up to 2,366 dizygotic (DZ) twin pairs from the Twins Early Development Study from age 12 to age 21. To account for family clustering, we used mixed-effects modeling, simultaneously estimating within- and between-family effects for target- and cross-trait GPS prediction of the outcomes. There were three main findings: (1) DZ twin GPS differences predicted DZ differences in height, BMI, intelligence, educational achievement, and ADHD symptoms; (2) target and cross-trait analyses indicated that GPS prediction estimates for cognitive traits (intelligence and educational achievement) were on average 60% greater between families than within families, but this was not the case for non-cognitive traits; and (3) much of this within- and between-family difference for cognitive traits disappeared after controlling for family socio-economic status (SES), suggesting that SES is a major source of between-family prediction through rGE mechanisms. These results provide insights into the patterns by which rGE contributes to GPS prediction, while ruling out confounding due to population stratification and assortative mating.

Citation Key13195
PubMed ID31303263
PubMed Central IDPMC6698881
Grant List295366 / ERC_ / European Research Council / International
MR/N015746/1 / MRC_ / Medical Research Council / United Kingdom
G0901245 / MRC_ / Medical Research Council / United Kingdom
R01 AG046938 / AG / NIA NIH HHS / United States
G19/2 / MRC_ / Medical Research Council / United Kingdom
MR/M021475/1 / MRC_ / Medical Research Council / United Kingdom