Kari E. North

This study identifies 86 T2D GWAS associations in 125,000 admixed Mexican adults, including 21 novel signals, and highlights the role of common regulatory variation in the endocrine pancreas.

HAUDI improves polygenic score construction for admixed populations by efficiently extending the GAUDI method to multi-way admixture with faster computation and better performance.

This study investigates the association between mosaic loss of Y chromosome (mLOY) and lung function, emphysema, and epigenetic aging in men across multiple cohorts.

The paper identifies ancestry-specific eQTL effects in Hispanic/Latino and African American populations, showing how local ancestry influences gene expression and disease risk.

This study integrates metabolomic and genetic data from the CARDIA study to identify novel variants associated with metabolite levels across diverse populations.

cellSTAAR integrates single-cell ATAC-seq with whole-genome sequencing to enhance power and interpretation of rare variant association tests in non-coding regions.

The paper identifies genes associated with obesity risk loci by integrating genetic and transcriptomic data from blood and brain tissues.

This study identifies genetic subtypes of obesity that uncouple adiposity from cardiometabolic risks, revealing distinct biological pathways and protein associations.

This study identifies novel genetic signals associated with severe obesity through GWAS and shows strong genetic overlap with BMI, highlighting shared comorbidities and lifestyle interactions.

The paper integrates proteomics and transcriptomics with genetic analyses to identify molecular mechanisms and targets of coronary artery disease.

The paper introduces MultiSTAAR, a statistical framework for multi-trait rare variant analysis in WGS studies, identifying new lipid trait associations in diverse populations.

This study conducts an epigenome-wide association study (EWAS) meta-analysis of BMI in African American adults, identifying 208 significant CpGs and 54 DMRs associated with BMI, including novel and replicated findings.

The paper identifies genetic and phenotypic correlates of mosaic loss of chromosome Y in blood using whole genome sequencing data from the TOPMed program.

This study conducts a GWAS on fatty acids and oxylipins in HCHS/SOL participants, identifying 19 genetic loci and shared/distinct genetic architecture.

This study identifies gene-environment interactions between excessive daytime sleepiness and genetic variants linked to obstructive sleep apnea severity, revealing novel therapeutic targets.

The paper introduces ClOneHORT, a method to generate synthetic genomes with high fidelity using deep generative models, achieving accurate results in downstream analyses.

The paper estimates mCA fitness in the NHLBI TOPMed cohort and identifies genetic variants associated with clonal expansion rates.

MUSSEL improves polygenic risk prediction across populations by integrating GWAS summary statistics and using Bayesian hierarchical modeling with ensemble learning.

This paper introduces HAMSTA, a method to estimate heritability from admixture mapping summary statistics while adjusting for ancestral stratification bias, and applies it to African American datasets.

The paper analyzes inflammation biomarkers using whole-genome sequencing from the TOPMed consortium, identifying both single-variant and rare variant associations with inflammatory traits.

The paper validates novel telomere length regulation genes POP5 and KBTBD6 identified through trans-ancestry GWAS using functional experiments in blood cells.

The paper identifies a gene-diet interaction modifying the association between macronutrient intake and glycemic traits, highlighting challenges in detecting such interactions due to measurement error and sample size.

This study uses whole-genome sequencing to analyze mosaic chromosomal alterations across diverse ancestries, finding higher rates in certain populations and associations with germline variants.

The paper performs whole genome sequence analysis of plasma lipid levels in 66,329 individuals, identifying new lipid-associated alleles, including rare non-coding variants.

The paper quantifies similarity in causal effects across local ancestries in admixed individuals and finds high genetic correlation (radmix=0.95) within individuals.

This paper improves genetic scores for adiposity traits in East Asian populations by using trans-ancestry meta-analysis, increasing variance explained compared to European-derived scores.

The paper uses bidirectional Mendelian randomization to show LTL lengthening increases CHIP risk, while CHIP accelerates LTL shortening, with modest mediation between CHIP and CAD via LTL.

The paper identifies 1,000 gene-level associations and conserved pathway associations for 25 traits across seven ancestries using enrichment analyses on large-scale GWA data.