Ahmed Abdel-Latif

Clinical Professorof Internal Medicine - Cardiology, Program Director of Internal Medicine, Michigan Medical School

Cardiac inflammation, multi-omics, and translational heart failure research.

Portrait of a man in a blazer with arms crossed, standing outdoors near a building.

My laboratory investigates the immune and metabolic mechanisms that drive heart failure and post-infarction cardiac remodeling, with a particular focus on myeloid cell biology, bioactive lipid signaling, and mitochondrial redox pathways. We study both heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), and our work spans from mechanistic discovery in animal models to translational validation in human tissue and clinical cohorts.

A central challenge in cardiovascular research is resolving the heterogeneity of immune and stromal cell populations that govern injury response, fibrosis, and repair. To address this, our group integrates multi-omics approaches, including bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics, with conventional physiological and histological phenotyping. We use computational pipelines built on Scanpy, Seurat, and scVI for dimensionality reduction, clustering, trajectory inference, and cross-condition integration of single-cell datasets. For bulk transcriptomic analyses, we employ DESeq2- and edgeR-based differential expression workflows coupled with gene set enrichment and weighted gene co-expression network analysis (WGCNA) to identify disease-relevant transcriptional programs.

A growing component of our work involves integrating transcriptomic data with metabolomic profiling of lipid mediators (eicosanoids, lysophospholipids, specialized pro-resolving mediators) to map signaling-to-phenotype relationships in cardiac inflammation. We are also developing comparative multi-omics frameworks using the spiny mouse (Acomys), a regeneration-competent mammal, to identify transcriptional and metabolic features that distinguish regenerative from fibrotic cardiac repair.

Our goal is to move from descriptive profiling toward mechanistic and predictive models that identify therapeutic targets in heart failure — connecting computational discovery to testable interventions in lipid signaling, myeloid reprogramming, and mitochondrial oxidative stress.