Daniel Jacob Benjamin

The paper introduces GRMA, a method that improves genetic association analyses by reducing bias and expanding population coverage compared to GWAS.

This study evaluates the portability of polygenic indexes for behavioral traits across genetic ancestries, finding reduced accuracy in non-European populations and factors contributing to this loss.

The paper updates a polygenic index repository with more phenotypes, datasets, and improved causal inference methods, enhancing predictive performance and interpretability.

The paper evaluates the impact of non-random mating and environmental transmission on genetic methods and introduces a simulation tool to improve robustness.

Family-based GWAS meta-analysis of 34 phenotypes shows standard GWAS effects carry sizeable confounding uncorrelated with direct genetic effects, while assortative mating likely inflates SNP heritability and genetic correlations.

This study identifies genetic variants associated with income and shows they correlate with health outcomes and educational attainment.

This paper introduces a method to adjust genetic studies for assortative mating using polygenic indexes, finding that assortative mating inflates genetic correlation estimates between health traits and education by 14% on average.

The paper introduces novel estimators for family-based GWAS that increase power and robustness to population structure by improving imputation of missing parent genotypes and using a linear-mixed model.

The paper develops a method to impute parental genotypes from sibling data to estimate direct and indirect genetic effects, finding that standard GWAS underestimates direct effects for several traits.

The paper constructs polygenic indexes for 47 phenotypes across 11 datasets and provides a tool to correct errors-in-variables bias when using PGIs as proxies for the additive SNP factor.

This paper introduces MAMA, a method for multi-ancestry GWAS meta-analysis, which identifies novel genetic associations and improves power across populations.

In 159,701 siblings from 17 cohorts, population GWAS overstate direct effects on height, education, smoking, cognition, depressive symptoms and age at first birth; clinical traits mostly agree across models.

This study identifies genetic loci associated with macronutrient intake and links them to health outcomes using GWAS in over 235,000 individuals.

GWAS in over one million individuals identify 611 loci across risk tolerance and risky behaviors, revealing shared genetic architecture and implicating glutamatergic and GABAergic neurotransmission.

The paper quantifies assortative mating on complex traits by analyzing SNP data from 400,000 individuals, finding significant evidence for height and educational attainment.

MTAG improves GWAS results by combining summary statistics across traits, increasing significant loci and enhancing polygenic score variance.

This study investigates the association between CpG methylation and educational attainment, finding limited significant associations that may be influenced by confounding factors.