Robert Edgardo Gerszten

The paper introduces the Proteomic Sex Index (PSI), a continuous measure of plasma proteome alignment with chromosomal sex, showing its association with health and disease traits.

ScreenDMT identifies metabolites consistently linked to sleep disorders across three human cohorts, revealing replicable associations with insomnia, sleep duration, and daytime sleepiness.

The paper presents initial findings from the MoTrPAC consortium, showing that acute and chronic exercise induce distinct physiological and molecular responses, with chronic training improving key health metrics.

The paper analyzes multi-omic, multi-tissue molecular responses to acute exercise in sedentary adults, identifying key pathways and exerkines involved in exercise effects.

The paper identifies shared and distinct biochemical responses to different exercise modes through plasma proteomics, metabolomics, and transcriptomics in sedentary humans.

TorchGWAS2 improves genome-wide association testing in related samples by using a deterministic variance-correction algorithm, achieving faster and more powerful results across large-scale omics data.

The paper identifies genetic drivers of protein change over time using longitudinal proteomics data from MESA, UK Biobank, and CARDIA, finding that baseline adjustment improves replication but may introduce biases.

This study integrates CAD GWAS with transcriptomic data to identify genes and networks associated with CAD and subclinical atherosclerosis.

This study improves proteome-wide association study results by using multi-ancestry data, finding more protein-phenotype associations and better prediction models.

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

This study identifies rapid remodeling of human subcutaneous white adipose tissue within one month after bariatric surgery using snRNA-seq, revealing changes in adipocyte populations and transcriptional dynamics.

The paper identifies tissue-specific transcriptional regulatory programs in rats undergoing endurance exercise training by integrating chromatin accessibility, DNA methylation, and gene expression data.

This study identifies a PTER inhibitor that reduces food intake and body weight in mice, linking PTER function to obesity treatment.

The paper identifies plasma proteins associated with diffusion tensor imaging biomarkers of white matter injury and suggests potential causal relationships using Mendelian randomization.

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

This study examines how different exercise intensities affect the human plasma secretome and interorgan communication through multi-cohort interventions and multi-organ gene expression analysis.

The paper analyzes circulating metabolites using genome-wide association data from the TOPMed program, identifying 1,778 loci and highlighting sex-specific genetic contributions.

This study identifies FNDC1 as a key regulator of vascular calcification through the FNDC1-NAMPT-NAD axis, showing its role in both microvascular and macrovascular diseases and its potential as a therapeutic target.

This study identifies a proteomic signature in humans following acute cold exposure that correlates with cardioprotective and anti-aging effects.

The paper identifies genetic drivers and clinical consequences of mosaic chromosomal alterations in 1 million individuals, linking specific aut-mCAs to disease risk and therapeutic targets.

This paper introduces GENN, a method for multi-omic interactome analysis that improves prediction of biomedical outcomes by learning salient associations in a low-dimensional space.

The paper conducts proteome-wide and transcriptome-wide association studies for blood lipids, finding high-level consistency between proteome and transcriptome-lipid associations across tissues.

The paper introduces a parametric bootstrap method to compute confidence intervals for genetic correlations, applied to protein-protein networks from proteomics data.

This paper evaluates the effects of ninerafaxstat on cardiac energetics and function in patients with cardio-metabolic syndromes using hyperpolarized MR and metabolomics.

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

This paper introduces MCFA, an unsupervised integration method for multi-omic data, and applies it to five omics types across 614 samples to infer shared and private factors.

The paper develops genetic scores for 17,227 molecular traits using multi-omic data from INTERVAL and validates them across ancestries, demonstrating their utility in pathway analysis and disease association discovery.

This paper improves multi-omics integration by enhancing orthogonality in canonical vectors and demonstrates transferability across cohorts for proteomics and methylomics data.

This study profiles multi-omic changes in multiple tissues of rats during endurance exercise training, identifying molecular adaptations and sex-specific responses across time.

This study shows that proteomic data can be linked to specific genomes using pQTL knowledge, highlighting privacy risks and the need for protections similar to genomic data.