Hesam Dashti

The paper maps context-dependent genetic regulation of cardiometabolic loci in human adipocytes using a multi-donor cell village system and single-nucleus multiome sequencing under various metabolic stress conditions.

The paper uses Mendelian Randomization to predict adverse drug reactions by linking genetic variants to gene expression and protein abundance across large datasets.

This study identifies 282 genetic loci associated with insulin resistance through multi-trait GWAS, highlighting adipose-specific and systemic regulators and potential therapeutic targets.

This study uses large biobanks to identify gene-trait pairs with causal evidence, rediscover approved drug targets, and develop a predictive model for drug development.

This study identifies 12 enhancers in the 9p21.3 CAD risk locus that regulate MTAP, modulating vascular cell-state transitions and CAD risk through stress-responsive mechanisms.

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

The paper identifies rare missense variants in LAR that destabilize the extracellular domain, disrupt LAR:NGL-3 interactions, and impair synaptic adhesion and synaptogenesis.

This study shows that reducing RREB1 in mice and humans decreases adipogenesis and improves insulin sensitivity, linking RREB1 to type 2 diabetes risk.

This study identifies novel genetic risk variants and potential drug targets for heart failure using GWAS and Mendelian randomization proteomics.

The paper introduces LipocyteProfiler, a high-throughput microscopy assay to profile lipid-storing cells and identifies cellular programs linked to metabolic traits like insulin resistance and lipodystrophy.

The paper introduces a software pipeline called RUNER for reproducible molecular modeling of small molecules, demonstrating its use on over 4,100 compounds.