Genotype–environment correlation by intervention effects underlying middle childhood peer rejection and associations with adolescent marijuana use

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Abstract

Aggressive behavior in middle childhood can contribute to peer rejection, subsequently increasing risk for substance use in adolescence. However, the quality of peer relationships a child experiences can be associated with his or her genetic predisposition, a genotype–environment correlation ( rGE). In addition, recent evidence indicates that psychosocial preventive interventions can buffer genetic predispositions for negative behavior. The current study examined associations between polygenic risk for aggression, aggressive behavior, and peer rejection from 8.5 to 10.5 years, and the subsequent influence of peer rejection on marijuana use in adolescence ( n = 515; 256 control, 259 intervention). Associations were examined separately in control and intervention groups for children of families who participated in a randomized controlled trial of the family-based preventive intervention, the Family Check-Up . Using time-varying effect modeling (TVEM), polygenic risk for aggression was associated with peer rejection from approximately age 8.50 to 9.50 in the control group but no associations were present in the intervention group. Subsequent analyses showed peer rejection mediated the association between polygenic risk for aggression and adolescent marijuana use in the control group. The role of rGEs in middle childhood peer processes and implications for preventive intervention programs for adolescent substance use are discussed.

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Principal components analysis corrects for stratification in genome-wide association studies.

Alkes L. Price, Nick Patterson, Robert Plenge … (2006)

Population stratification--allele frequency differences between cases and controls due to systematic ancestry differences-can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers.

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Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

Roseann E. Peterson, Karoline Kuchenbaecker, Raymond K Walters … (2019)

Genome-wide association studies (GWAS) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.