Pradeep Natarajan

This study identifies genetic variants associated with healthcare costs across multiple systems, finding polygenic influences and large effects from specific loss-of-function variants.

This study evaluates polygenic risk scores for cardiovascular diseases in predicting carotid stenosis, finding that PAD and CAD PRSs show significant associations and improved discrimination over traditional risk factors.

The paper estimates penetrance of disease variants in genes prioritized for genomic newborn screening using adult biobank data, finding higher penetrance than ICD codes suggest.

This paper evaluates polygenic risk scores (PRSs) in diverse populations using absolute risk models, finding that PRSs can provide greater utility in risk stratification for certain diseases in non-European populations.

This study links a polygenic risk score for coronary artery disease to coronary atherosclerotic burden measured by clinical CT angiograms.

The paper identifies 800 exome-wide significant rare coding variants associated with blood lipids in over a million diverse individuals, including 130 driven by non-European-like populations.

The paper establishes a global consortium to discover rare genetic associations by integrating data from multiple biobanks, identifying 514 gene-trait associations, many detectable only through cross-ancestry meta-analysis.

The paper identifies genetic associations with liver radiomic features and their links to metabolic diseases using UK Biobank data.

This paper develops a machine learning framework to impute cross-platform proteomic data, improving replication of epidemiological findings and protein quality scoring.

The paper evaluates individual-level performance of polygenic risk scores (PRSs) using a benchmark cohort of early-onset coronary artery disease patients, showing variability in PRS accuracy and highlighting the need for individual-level validation.

This paper constructs phenome-derived polygenic scores and evaluates how they, along with social determinants of health, influence disease risk across different populations and diseases.

This study examines associations between leukocyte telomere length and genomic, phenomic, and geographic factors in diverse U.S. populations, identifying novel loci and genes.

This paper identifies genetic variants associated with amiodarone-induced thyroid dysfunction and shows they improve risk prediction beyond general thyroid disease PRS.

This study identifies a genetic association between thromboembolism risk and long COVID in individuals of European ancestry, suggesting thromboembolism as a potential contributor to long COVID pathogenesis.

The paper identifies plasma proteins associated with clonal hematopoiesis and links them to cardiovascular disease through proteomic and genetic analyses.

The paper investigates the association between clonal hematopoiesis gene variants and premature coronary artery disease in South Asian Indians, finding high prevalence and specific gene variant associations.

The paper investigates the mechanism of age-related mtDNA mutation accumulation in human blood using whole genome sequences, revealing a two-step process involving cryptic mutations and clonal expansion.

The paper identifies pleiotropic loci across 1,167 traits using GWAS meta-analysis and shows they are enriched for functional annotations and improve polygenic score predictions.

The paper evaluates the instability of polygenic risk scores (PRS) across different publications and introduces an integrative scoring framework to improve classification consistency.

This paper develops a polygenic score for peripheral artery disease (PAD) that improves risk prediction across diverse populations and identifies high-risk individuals for adverse limb events.

ALADYNOULLI integrates longitudinal health records and genetic data to model disease progression, identifying interpretable disease signatures with cross-population consistency and improving clinical prediction.

This study investigates genetic factors influencing weight loss from GLP1-RA and bariatric surgery in 10,960 individuals across 9 biobanks, finding no strong genetic associations with GLP1-RA effectiveness but a modest link between BMI polygenic scores and reduced bariatric surgery weight loss.

The paper develops a method to quantify somatic mutation burden in whole-genome sequencing data without paired-tissue samples and identifies genetic and phenotypic correlates of clonal hematopoiesis without known driver mutations.

This paper optimizes the SAIGE algorithm using GPUs to accelerate GWAS on large datasets, achieving 20x speedup on the Million Veteran Program data.

The paper describes the design and pilot results of a study returning genetic results for familial hypercholesterolemia to MVP participants, showing a reduction in LDL-C after genetic counseling.

This study identifies 240 novel genetic loci associated with mosaic loss of chromosome Y through a multi-ancestry GWAS of the Million Veteran Program and UK Biobank.

Cross-trait Elastic Net mixing of PGS Catalog scores (PRSmix+) lifted mean PRS accuracy 1.72-fold in Europeans and 1.42-fold in South Asians over the best single score.

The paper analyzes genetic, ancestral, and geospatial data from a biobank to explore their relationships with health outcomes in a historically diverse population.

The paper identifies 83 rare lncRNA variant sets associated with blood lipid levels using WGS data from the TOPMed program and validates some in UK Biobank data.

This study analyzes 4,187 participants over 21 years to identify factors influencing the development of clonal hematopoiesis, finding age, sex, and dyslipidemia as significant predictors.