The osteoimmune cell atlas of peri-implantitis: A narrative scoping review.

Authors

Emilio A Cafferata, Anton Sculean, Frank Schwarz

Published in

Periodontology 2000. Oct 13, 2026. Epub Oct 13, 2026.

Abstract

Peri-implantitis represents a complex osteoimmune disorder characterized by dysregulated cellular ecosystems that drive chronic inflammation and accelerated peri-implant bone loss.
This article was designed as a narrative scoping review to map and integrate the available evidence from transcriptomics, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, flow cytometry, and immunohistochemistry to construct a comprehensive cellular atlas of peri-implantitis.
Current evidence suggests that peri-implantitis lesions contain expanded and activated neutrophil, macrophage, T-cell, and B-lineage compartments, together with stromal and vascular cell populations that may contribute to inflammatory amplification and osteoclastogenic signaling. Reported features include CXCR2⁺ neutrophil subsets with NETosis-associated activity, inflammatory macrophage states, altered Th17/Treg-related immune responses, and expanded B-cell/plasma-cell compartments forming organized adaptive immune niches. Proposed molecular mechanisms include NF-κB-related inflammatory activation, CXCL13-associated adaptive immune organization, NETosis-related pathways, and RANKL-mediated osteoclastogenic signaling. However, several of these pathways remain incompletely validated in human peri-implantitis tissue. Critical knowledge gaps include limited direct evidence for NLRP3 inflammasome activation, uncharacterized type I interferon signaling, unresolved hierarchies of cellular RANKL sources, and limited functional data for rare immune populations.
The peri-implantitis osteoimmune microenvironment constitutes a highly organized, self-reinforcing inflammatory ecosystem. Progress toward precision therapeutic strategies requires spatial multiomics at subcellular resolution, longitudinal human studies, and functional ex vivo validation models to interrogate the self-sustaining circuits identified here.

PMID:
42867320
Bibliographic data and abstract were imported from PubMed on 14 Oct 2026.

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