Dalton Conley

This study shows that within-family GWAS does not improve prediction accuracy in admixed populations, suggesting genetic architecture differences, not confounding factors, drive the decline in polygenic index performance.

This study examines whether adjusting for population structure via principal components (PCs) in GWAS and polygenic index analyses reduces detectable direct genetic effects, finding minimal impact on polygenic effects.

The paper introduces variance polygenic scores (vPGS) to better study gene-environment interplay by capturing genetic contributions to outcome plasticity, and applies them to analyze the effects of an education reform on health and education.

The paper shows that polygenic scores have varying prediction accuracy within a single ancestry group based on factors like age, sex, and GWAS study design.

The paper examines genetic similarities between friends and schoolmates using longitudinal health data, finding that social forces contribute to genetic correlation rather than individual selection.

The paper introduces a family-based method to identify variance-controlling loci (vQTLs) that influence phenotypic variation, showing improved performance over existing methods in the presence of confounding.

The paper identifies genetic variants associated with subjective well-being, depressive symptoms, and neuroticism using genome-wide association studies and proxy-phenotype analyses.