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Changes of serum IgG glycosylation patterns in rheumatoid arthritis

BACKGROUND: RA is a common chronic and systemic autoimmune disease, and the diagnosis is based significantly on autoantibody detection. This study aims to investigate the glycosylation profile of serum IgG in RA patients using high-throughput lectin microarray technology. METHOD: Lectin microarray c...

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Autores principales: Deng, Xiaoyue, Liu, Xiaomin, Zhang, Yan, Ke, Dan, Yan, Rui, Wang, Qian, Tian, Xinping, Li, Mengtao, Zeng, Xiaofeng, Hu, Chaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942403/
https://www.ncbi.nlm.nih.gov/pubmed/36810000
http://dx.doi.org/10.1186/s12014-023-09395-z
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author Deng, Xiaoyue
Liu, Xiaomin
Zhang, Yan
Ke, Dan
Yan, Rui
Wang, Qian
Tian, Xinping
Li, Mengtao
Zeng, Xiaofeng
Hu, Chaojun
author_facet Deng, Xiaoyue
Liu, Xiaomin
Zhang, Yan
Ke, Dan
Yan, Rui
Wang, Qian
Tian, Xinping
Li, Mengtao
Zeng, Xiaofeng
Hu, Chaojun
author_sort Deng, Xiaoyue
collection PubMed
description BACKGROUND: RA is a common chronic and systemic autoimmune disease, and the diagnosis is based significantly on autoantibody detection. This study aims to investigate the glycosylation profile of serum IgG in RA patients using high-throughput lectin microarray technology. METHOD: Lectin microarray containing 56 lectins was applied to detect and analyze the expression profile of serum IgG glycosylation in 214 RA patients, 150 disease controls (DC), and 100 healthy controls (HC). Significant differential glycan profiles between the groups of RA and DC/HC as well as RA subgroups were explored and verified by lectin blot technique. The prediction models were created to evaluate the feasibility of those candidate biomarkers. RESULTS: As a comprehensive analysis of lectin microarray and lectin blot, results showed that compare with HC or DC groups, serum IgG from RA patients had a higher affinity to the SBA lectin (recognizing glycan GalNAc). For RA subgroups, RA-seropositive group had higher affinities to the lectins of MNA-M (recognizing glycan mannose) and AAL (recognizing glycan fucose), and RA-ILD group had higher affinities to the lectins of ConA (recognizing glycan mannose) and MNA-M while a lower affinity to the PHA-E (recognizing glycan Galβ4GlcNAc) lectin. The predicted models indicated corresponding feasibility of those biomarkers. CONCLUSION: Lectin microarray is an effective and reliable technique for analyzing multiple lectin–glycan interactions. RA, RA-seropositive, and RA-ILD patients exhibit distinct glycan profiles, respectively. Altered levels of glycosylation may be related to the pathogenesis of the disease, which could provide a direction for new biomarkers identification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12014-023-09395-z.
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spelling pubmed-99424032023-02-22 Changes of serum IgG glycosylation patterns in rheumatoid arthritis Deng, Xiaoyue Liu, Xiaomin Zhang, Yan Ke, Dan Yan, Rui Wang, Qian Tian, Xinping Li, Mengtao Zeng, Xiaofeng Hu, Chaojun Clin Proteomics Research BACKGROUND: RA is a common chronic and systemic autoimmune disease, and the diagnosis is based significantly on autoantibody detection. This study aims to investigate the glycosylation profile of serum IgG in RA patients using high-throughput lectin microarray technology. METHOD: Lectin microarray containing 56 lectins was applied to detect and analyze the expression profile of serum IgG glycosylation in 214 RA patients, 150 disease controls (DC), and 100 healthy controls (HC). Significant differential glycan profiles between the groups of RA and DC/HC as well as RA subgroups were explored and verified by lectin blot technique. The prediction models were created to evaluate the feasibility of those candidate biomarkers. RESULTS: As a comprehensive analysis of lectin microarray and lectin blot, results showed that compare with HC or DC groups, serum IgG from RA patients had a higher affinity to the SBA lectin (recognizing glycan GalNAc). For RA subgroups, RA-seropositive group had higher affinities to the lectins of MNA-M (recognizing glycan mannose) and AAL (recognizing glycan fucose), and RA-ILD group had higher affinities to the lectins of ConA (recognizing glycan mannose) and MNA-M while a lower affinity to the PHA-E (recognizing glycan Galβ4GlcNAc) lectin. The predicted models indicated corresponding feasibility of those biomarkers. CONCLUSION: Lectin microarray is an effective and reliable technique for analyzing multiple lectin–glycan interactions. RA, RA-seropositive, and RA-ILD patients exhibit distinct glycan profiles, respectively. Altered levels of glycosylation may be related to the pathogenesis of the disease, which could provide a direction for new biomarkers identification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12014-023-09395-z. BioMed Central 2023-02-21 /pmc/articles/PMC9942403/ /pubmed/36810000 http://dx.doi.org/10.1186/s12014-023-09395-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Deng, Xiaoyue
Liu, Xiaomin
Zhang, Yan
Ke, Dan
Yan, Rui
Wang, Qian
Tian, Xinping
Li, Mengtao
Zeng, Xiaofeng
Hu, Chaojun
Changes of serum IgG glycosylation patterns in rheumatoid arthritis
title Changes of serum IgG glycosylation patterns in rheumatoid arthritis
title_full Changes of serum IgG glycosylation patterns in rheumatoid arthritis
title_fullStr Changes of serum IgG glycosylation patterns in rheumatoid arthritis
title_full_unstemmed Changes of serum IgG glycosylation patterns in rheumatoid arthritis
title_short Changes of serum IgG glycosylation patterns in rheumatoid arthritis
title_sort changes of serum igg glycosylation patterns in rheumatoid arthritis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942403/
https://www.ncbi.nlm.nih.gov/pubmed/36810000
http://dx.doi.org/10.1186/s12014-023-09395-z
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