Dan L. Nicolae

This study identifies a genetic variant associated with reduced lung function in urban children and shows its mediation by DNA methylation linked to smoking exposure.

The paper analyzes longitudinal DNA methylation data to show that race-associated patterns are present at birth and primarily genetic, with strong genetic and weak non-genetic contributions.

The paper identifies context-specific genetic mechanisms at asthma risk loci by integrating multi-omics data with GWAS results in airway epithelial cells exposed to rhinovirus.

This study identifies shared and distinct genetic risk factors for childhood and adult onset asthma using GWAS and transcriptome-wide analysis, finding 61 loci with 23 childhood-specific, 1 adult-specific, and 37 shared.

The paper introduces MulTiXcan, a method that improves association detection by integrating eQTL data across tissues, showing it identifies more significant genes than single-tissue analyses.

The paper uses gene co-expression networks in whole blood to identify molecular pathways associated with obese asthma, finding four modules linked to obesity and enriched for inflammatory pathways.

The paper identifies two new imprinted genes in a founder population using allele-specific expression and phased genotype data.

The paper identifies rare non-coding variants in a founder population associated with plasma lipid traits using Bayesian methods and functional annotations.

The paper identifies parent of origin effects on 11 quantitative phenotypes in a Hutterite population, showing that these effects are common, clinically relevant, and often missed by traditional GWAS.

The paper designs a genotyping array (ADPC) for African-specific genetic variation using whole genome sequences from the CAAPA consortium, improving GWAS for African ancestry populations.

This study identifies novel asthma susceptibility loci in individuals of African ancestry through genome-wide association analysis and admixture mapping.

This study uses PrediXcan to identify and replicate two novel genome-wide significant genes associated with bipolar disorder risk using existing GWAS data.