Rajat M. Gupta

NERINE tests gene network hypotheses with rare variant associations, identifying a subnetwork linked to Parkinson's disease.

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

This paper links CAD GWAS variants to causal genes in SMCs using single-cell chromatin accessibility and Hi-C data, creating a scV2E2G map for disease mechanism discovery.

The paper introduces a method to prioritize causal genes for complex traits by integrating GWAS data with gene expression and biological data, achieving high precision in gene-trait pair identification.

HiDDEN refines case-control labels in single-cell transcriptomics to detect disease-relevant cell populations, improving detection of subtle perturbations in simulated and real datasets.

The paper maps coronary artery disease risk loci to endothelial cell gene programs, identifying convergence on the CCM pathway and a new CAD gene, TLNRD1.

This study uses deep learning to analyze aortic dimensions from MRI and identifies genetic loci associated with aortic diameter, highlighting SVIL as a key gene and developing a polygenic score for aneurysm risk.

A coronary artery disease GWAS of 181,522 cases among 1,165,690 participants yields 241 associations (54 new); an eight-predictor consensus nominates 185 candidate causal genes, 94 with ≥3 predictors.

This study creates a single-cell and spatial atlas of autopsy tissues from COVID-19 patients, revealing altered cellular responses and potential therapeutic targets.