Machine learning-assisted immune profiling stratifies peri-implantitis patients with unique microbial colonization and clinical outcomes

The endemic of peri-implantitis affects over 25% of dental implants. Current treatment depends on empirical patient and site-based stratifications and lacks a consistent risk grading system. We investigated a unique cohort of peri-implantitis patients undergoing regenerative therapy with comprehensi...

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Bibliographic Details
Published in:Theranostics 2021-01, Vol.11 (14), p.6703-6716
Main Authors: Wang, Chin-Wei, Hao, Yuning, Di Gianfilippo, Riccardo, Sugai, James, Li, Jiaqian, Gong, Wang, Kornman, Kenneth S, Wang, Hom-Lay, Kamada, Nobuhiko, Xie, Yuying, Giannobile, William V, Lei, Yu Leo
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
B-Lymphocytes - immunology
Clinical outcomes
Cohort Studies
Cytokines - metabolism
Dental implants
Fusobacterium nucleatum - isolation & purification
Gene expression
Humans
Immunophenotyping
Machine Learning
Macrophages - immunology
Microbiota - genetics
Pathogens
Patients
Peri-Implantitis - classification
Peri-Implantitis - immunology
Peri-Implantitis - microbiology
Prevotella intermedia - isolation & purification
Research Paper
Risk Factors
Th1 Cells - metabolism
Th17 Cells - metabolism
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Summary:The endemic of peri-implantitis affects over 25% of dental implants. Current treatment depends on empirical patient and site-based stratifications and lacks a consistent risk grading system. We investigated a unique cohort of peri-implantitis patients undergoing regenerative therapy with comprehensive clinical, immune, and microbial profiling. We utilized a robust outlier-resistant machine learning algorithm for immune deconvolution. Unsupervised clustering identified risk groups with distinct immune profiles, microbial colonization dynamics, and regenerative outcomes. Low-risk patients exhibited elevated M1/M2-like macrophage ratios and lower B-cell infiltration. The low-risk immune profile was characterized by enhanced complement signaling and higher levels of Th1 and Th17 cytokines. and were significantly enriched in high-risk individuals. Although surgery reduced microbial burden at the peri-implant interface in all groups, only low-risk individuals exhibited suppression of keystone pathogen re-colonization. Peri-implant immune microenvironment shapes microbial composition and the course of regeneration. Immune signatures show untapped potential in improving the risk-grading for peri-implantitis.
ISSN:1838-7640
1838-7640
DOI:10.7150/thno.57775