Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing

BackgroundAnti-citrullinated peptide antibodies (ACPA)-negative (ACPA−) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distinctive cellular and metabolic profiles for more targeted...

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Main Authors: Yafeng Jiang, Zhaolan Hu, Roujie Huang, Kaying Ho, Pengfei Wang, Jin Kang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Immunology
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Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2024.1512483/full
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author Yafeng Jiang
Zhaolan Hu
Roujie Huang
Kaying Ho
Pengfei Wang
Jin Kang
Jin Kang
author_facet Yafeng Jiang
Zhaolan Hu
Roujie Huang
Kaying Ho
Pengfei Wang
Jin Kang
Jin Kang
author_sort Yafeng Jiang
collection DOAJ
description BackgroundAnti-citrullinated peptide antibodies (ACPA)-negative (ACPA−) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distinctive cellular and metabolic profiles for more targeted interventions.MethodsSingle-cell RNA sequencing data from peripheral blood mononuclear cells (PBMCs) and synovial tissues of patients with ACPA− and ACPA+ RA, as well as healthy controls, were analyzed. Immune cell populations were classified based on clustering and marker gene expression, with pseudotime trajectory analysis, weighted gene co-expression network analysis (WGCNA), and transcription factor network inference providing further insights. Cell-cell communication was explored using CellChat and MEBOCOST, while scFEA enabled metabolic flux estimation. A neural network model incorporating key genes was constructed to differentiate patients with ACPA− RA from healthy controls.ResultsPatients with ACPA− RA demonstrated a pronounced increase in classical monocytes in PBMCs and C1QChigh macrophages (p < 0.001 and p < 0.05). Synovial macrophages exhibited increased heterogeneity and were enriched in distinct metabolic pathways, including complement cascades and glutathione metabolism. The neural network model achieved reliable differentiation between patients with ACPA− RA and healthy controls (AUC = 0.81). CellChat analysis identified CD45 and CCL5 as key pathways facilitating macrophage-monocyte interactions in ACPA− RA, prominently involving iron-mediated metabolite communication. Metabolic flux analysis indicated elevated beta-alanine and glutathione metabolism in ACPA− RA macrophages.ConclusionThese findings underscore that ACPA-negative rheumatoid arthritis is marked by elevated classical monocytes in circulation and metabolic reprogramming of synovial macrophages, particularly in complement cascade and glutathione metabolism pathways. By integrating single-cell RNA sequencing with machine learning, this study established a neural network model that robustly differentiates patients with ACPA− RA from healthy controls, highlighting promising diagnostic biomarkers and therapeutic targets centered on immune cell metabolism.
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spelling doaj-art-f79fdf53f9be4c59aa590ffb3c85afaa2025-01-03T06:47:17ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-01-011510.3389/fimmu.2024.15124831512483Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencingYafeng Jiang0Zhaolan Hu1Roujie Huang2Kaying Ho3Pengfei Wang4Jin Kang5Jin Kang6Department of Hematology, the Second Xiangya Hospital of Central South University, Changsha, ChinaDepartment of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, ChinaDepartment of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Rheumatology and Immunology, the Second Xiangya Hospital of Central South University, Changsha, ChinaDepartment of Rheumatology and Immunology, Clinical Medical Research Center for Systemic Autoimmune Diseases in Hunan Province, Changsha, ChinaBackgroundAnti-citrullinated peptide antibodies (ACPA)-negative (ACPA−) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distinctive cellular and metabolic profiles for more targeted interventions.MethodsSingle-cell RNA sequencing data from peripheral blood mononuclear cells (PBMCs) and synovial tissues of patients with ACPA− and ACPA+ RA, as well as healthy controls, were analyzed. Immune cell populations were classified based on clustering and marker gene expression, with pseudotime trajectory analysis, weighted gene co-expression network analysis (WGCNA), and transcription factor network inference providing further insights. Cell-cell communication was explored using CellChat and MEBOCOST, while scFEA enabled metabolic flux estimation. A neural network model incorporating key genes was constructed to differentiate patients with ACPA− RA from healthy controls.ResultsPatients with ACPA− RA demonstrated a pronounced increase in classical monocytes in PBMCs and C1QChigh macrophages (p < 0.001 and p < 0.05). Synovial macrophages exhibited increased heterogeneity and were enriched in distinct metabolic pathways, including complement cascades and glutathione metabolism. The neural network model achieved reliable differentiation between patients with ACPA− RA and healthy controls (AUC = 0.81). CellChat analysis identified CD45 and CCL5 as key pathways facilitating macrophage-monocyte interactions in ACPA− RA, prominently involving iron-mediated metabolite communication. Metabolic flux analysis indicated elevated beta-alanine and glutathione metabolism in ACPA− RA macrophages.ConclusionThese findings underscore that ACPA-negative rheumatoid arthritis is marked by elevated classical monocytes in circulation and metabolic reprogramming of synovial macrophages, particularly in complement cascade and glutathione metabolism pathways. By integrating single-cell RNA sequencing with machine learning, this study established a neural network model that robustly differentiates patients with ACPA− RA from healthy controls, highlighting promising diagnostic biomarkers and therapeutic targets centered on immune cell metabolism.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1512483/fullrheumatoid arthritissingle-cell RNA sequencingACPAsynovial macrophagebeta-alanine and glutathione metabolism
spellingShingle Yafeng Jiang
Zhaolan Hu
Roujie Huang
Kaying Ho
Pengfei Wang
Jin Kang
Jin Kang
Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing
Frontiers in Immunology
rheumatoid arthritis
single-cell RNA sequencing
ACPA
synovial macrophage
beta-alanine and glutathione metabolism
title Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing
title_full Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing
title_fullStr Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing
title_full_unstemmed Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing
title_short Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing
title_sort metabolic reprogramming and macrophage expansion define acpa negative rheumatoid arthritis insights from single cell rna sequencing
topic rheumatoid arthritis
single-cell RNA sequencing
ACPA
synovial macrophage
beta-alanine and glutathione metabolism
url https://www.frontiersin.org/articles/10.3389/fimmu.2024.1512483/full
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