Sanjiv Jayendra Shah

Machine Learning Identifies Distinct Treg-Mediated Remodeling in HFpEF Hearts Treated with Neonatal Mesenchymal Stem Cells and Their Secretome

This study uses machine learning to identify Treg-mediated mechanisms by which nMSCs and their secretome improve diastolic function in HFpEF.

Multiomics Integration Reveals a Metabolic Myopathy in Cardiometabolic HFpEF

This study identifies a metabolic myopathy in HFpEF through multiomics analysis of skeletal muscle, revealing mitochondrial dysfunction and altered amino acid metabolism.

Low Dose GLP-1 Therapy Attenuates Pathological Cardiac and Hepatic Remodelling in HFpEF Independent of Weight Loss

This study shows low-dose GLP-1RA therapy improves cardiac and hepatic function in HFpEF without weight loss, through mechanisms like reduced fibrosis and lipid accumulation.

Dysregulation of Nitrosylation Dynamics Promotes Nitrosative Stress and Contributes to Cardiometabolic Heart Failure with Preserved Ejection Fraction

This study identifies dysregulated nitrosylation dynamics in HFpEF patients and ZSF1 obese rats, showing elevated nitrosative stress markers and impaired trans- and de-nitrosylase activity.

Hydrogen Sulfide Deficiency and Therapeutic Targeting in Cardiometabolic HFpEF: Evidence for Synergistic Benefit with GLP-1/Glucagon Agonism

This study shows H2S deficiency in HFpEF patients and models, and that H2S supplementation or combination with GLP-1/glucagon agonists improves HFpEF outcomes.

Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood

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

Differences in Cardiac Mechanics among Genetically At-Risk First-Degree Relatives: The DCM Precision Medicine Study

The paper examines cardiac mechanics in genetically at-risk first-degree relatives of DCM patients, finding that older relatives with variants of uncertain significance or pathogenic variants have reduced global longitudinal strain.

Machine Learning of the Cardiac Phenome and Skin Transcriptome to Categorize Heart Disease in Systemic Sclerosis

This paper uses machine learning to classify heart disease subgroups in systemic sclerosis using echocardiographic and skin transcriptome data, identifying distinct phenotypes and associated molecular pathways.

Parent of Origin Effects on Quantitative Phenotypes in a Founder Population

The paper identifies parent of origin effects on 11 quantitative phenotypes in a Hutterite population, showing that these effects are common, clinically relevant, and often missed by traditional GWAS.