{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T09:47:10Z","timestamp":1790934430209,"version":"4.1.0"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T00:00:00Z","timestamp":1759795200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Aims<\/jats:title><jats:p>We hypothesize that specific macrophage differentiation trajectories in heart failure (HF) are coupled with subtype-specific and context-dependent engagement of programmed cell death (PCD) pathways, particularly ferroptosis and anoikis, which in turn influence disease progression and remodeling. HF is a progressive and heterogeneous clinical syndrome characterized by adverse immune remodeling, yet the precise contributions of macrophage heterogeneity, lineage dynamics, and PCD programs to its pathogenesis remain unclear. This study aimed to delineate, at single-cell resolution, the cellular and molecular landscape of cardiac macrophage subpopulations and their engagement with immunogenic cell death programs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We profiled human cardiac tissues from HF and non-failing donors using scRNA-seq from the SCP1303 dataset, initially comprising ~600,000 cells and reduced to ~120,000 high-quality cells from 18 samples after stringent quality control to retain biologically valid but metabolically distinct populations. Standardized cell-type annotation and pseudotime trajectory reconstruction were applied. Pathway activity was quantified using AUCell (primary) and GSVA (complementary) for cell death\u2013related signatures. Integrated differential expression analysis, protein\u2013protein interaction network mapping, and multi-algorithm feature selection (LASSO, SVM-RFE, Random Forest) were performed, and candidate biomarkers were validated using an independent bulk RNA-seq dataset (GSE57345).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Thirteen major cardiac cell types were identified, with macrophages showing the highest transcriptional heterogeneity. We resolved four macrophage subtypes and mapped bifurcating disease-associated differentiation trajectories, revealing distinct activation patterns of ferroptosis- and anoikis-related pathways. Ferroptosis-associated genes and anoikis-associated genes displayed subtype-specific enrichment and significant differential activation in HF. Pseudotime analysis demonstrated that suppression of ferroptosis and anoikis was linked to late-stage, HF-enriched macrophage states. Key biomarkers\u2014including CD163, FPR1, and VSIG4\u2014achieved robust diagnostic performance (AUC &amp;gt; 0.80) in discriminating HF phenotypes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>This is the first study to integrate scRNA-seq, differentiation trajectory inference, and PCD pathway scoring to define the context-dependent engagement of ferroptosis and anoikis in macrophage subtypes in HF. The identification of subtype-specific biomarkers and functional states provides novel mechanistic insight and potential diagnostic and therapeutic targets, underscoring the value of high-resolution immune profiling for precision immunology in cardiovascular disease.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2025.1604226","type":"journal-article","created":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T04:13:49Z","timestamp":1759810429000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Deciphering macrophage differentiation and cell death dynamics in heart failure: a single-cell sequencing 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