Macrophage programming in systemic sclerosis: Niches, networks, and translational horizons.

Authors

Huichen Luo, Danhui Hu

Published in

Seminars in immunopathology. Volume 48. Issue 1. Aug 27, 2026. Epub Aug 27, 2026.

Abstract

Systemic sclerosis (SSc) is a multisystem autoimmune disease characterized by immune dysregulation, microvascular injury, and progressive fibrosis. Among the immune populations implicated in SSc, macrophages are increasingly recognized as context-dependent participants in endothelial stress, inflammatory amplification, tissue remodeling, and fibroblast activation. Rather than relying on a static M1/M2 framework, recent studies support the view that macrophage-associated states are shaped by inducing cues, tissue niche, dominant effector function, and disease phase. In this review, we synthesize current evidence on macrophage-associated programs across vascular, dermal, and pulmonary compartments in SSc and discuss how these programs may help organize current understanding of the coupling between autoimmunity, vasculopathy, and fibrosis. We also highlight that recurrent signaling hubs-including JAK/STAT, TGF-β/SMAD, PDGF/PI3K/AKT/mTOR, Notch/Wnt, Hippo/YAP/TAZ, and metabolic regulators-reappear across macrophage-stromal crosstalk in SSc and related fibrotic settings. Importantly, we distinguish findings supported directly in human SSc from those derived from experimental systems or extrapolated from related fibrotic and autoimmune diseases, and we discuss biomarkers and therapeutic strategies according to their translational maturity. We propose that a macrophage-centered framework may be useful as an organizing and hypothesis-refining tool in SSc, but not as a validated disease-specific taxonomy or treatment algorithm. At present, many macrophage-centered biomarkers and therapeutic concepts remain insufficiently validated for routine clinical use, underscoring the need for stronger human tissue validation, clearer evidence calibration, and stage-aware translational studies.

PMID:
42658262
Bibliographic data and abstract were imported from PubMed on 28 Aug 2026.

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