A reproducible computational transcriptomic framework for cell-type-resolved fibroinflammatory-AKT remodeling in...

Area of Science:

• Cardiovascular Biology
• Computational Biology
• Genomics

Background:

• Human heart failure (HF) involves complex transcriptional changes across multiple cell types.
• Existing transcriptomic studies often lack cell-type specificity and direct links to potential interventions.
• Bridging this gap is crucial for a deeper understanding of HF pathogenesis.

Purpose of the Study:

• To develop a computational framework for integrating diverse transcriptomic data in human heart failure.
• To identify cell-type-specific transcriptional remodeling in HF.
• To prioritize potential therapeutic targets through perturbational analysis.

Main Methods:

• Integrated human left-ventricular bulk transcriptomes with single-cell/single-nucleus atlas data.
• Utilized external single-nucleus RNA sequencing (snRNA-seq) for validation.
• Applied module scoring, ligand-receptor analysis, and LINCS/L1000 perturbational matching.

Main Results:

• Identified 14,358 HF-associated genes, with 1633 consistently upregulated and 785 downregulated.
• Localized significant remodeling to cardiomyocytes, fibroblasts, and myeloid cells.
• Revealed a fibroinflammatory axis involving activated fibroblasts and inflammatory myeloid cells, linked to AKT signaling.

Conclusions:

• Established a computational framework connecting reproducible HF signatures with cell-type resolution.
• Provided a method for prioritizing perturbational genomic targets in HF research.
• Highlighted glimepiride and simvastatin as candidates for further experimental validation.