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 con...
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Autor*in:	Deng, Xiaoyue [verfasserIn] Liu, Xiaomin Zhang, Yan Ke, Dan Yan, Rui Wang, Qian Tian, Xinping Li, Mengtao Zeng, Xiaofeng Hu, Chaojun

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	RA ILD Immunoglobulin G Lectin microarray Glycosylation

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Clinical proteomics - Totowa, NJ : Humana Press, 2004, 20(2023), 1 vom: 21. Feb.
Übergeordnetes Werk:	volume:20 ; year:2023 ; number:1 ; day:21 ; month:02

Links:	Volltext

DOI / URN:	10.1186/s12014-023-09395-z

Katalog-ID:	SPR051483963

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520			\|a 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.
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allfields	10.1186/s12014-023-09395-z doi (DE-627)SPR051483963 (SPR)s12014-023-09395-z-e DE-627 ger DE-627 rakwb eng Deng, Xiaoyue verfasserin aut Changes of serum IgG glycosylation patterns in rheumatoid arthritis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. RA (dpeaa)DE-He213 ILD (dpeaa)DE-He213 Immunoglobulin G (dpeaa)DE-He213 Lectin microarray (dpeaa)DE-He213 Glycosylation (dpeaa)DE-He213 Liu, Xiaomin aut Zhang, Yan aut Ke, Dan aut Yan, Rui aut Wang, Qian aut Tian, Xinping aut Li, Mengtao aut Zeng, Xiaofeng aut Hu, Chaojun aut Enthalten in Clinical proteomics Totowa, NJ : Humana Press, 2004 20(2023), 1 vom: 21. Feb. (DE-627)397618883 (DE-600)2163624-2 1559-0275 nnns volume:20 year:2023 number:1 day:21 month:02 https://dx.doi.org/10.1186/s12014-023-09395-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2023 1 21 02
spelling	10.1186/s12014-023-09395-z doi (DE-627)SPR051483963 (SPR)s12014-023-09395-z-e DE-627 ger DE-627 rakwb eng Deng, Xiaoyue verfasserin aut Changes of serum IgG glycosylation patterns in rheumatoid arthritis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. RA (dpeaa)DE-He213 ILD (dpeaa)DE-He213 Immunoglobulin G (dpeaa)DE-He213 Lectin microarray (dpeaa)DE-He213 Glycosylation (dpeaa)DE-He213 Liu, Xiaomin aut Zhang, Yan aut Ke, Dan aut Yan, Rui aut Wang, Qian aut Tian, Xinping aut Li, Mengtao aut Zeng, Xiaofeng aut Hu, Chaojun aut Enthalten in Clinical proteomics Totowa, NJ : Humana Press, 2004 20(2023), 1 vom: 21. Feb. (DE-627)397618883 (DE-600)2163624-2 1559-0275 nnns volume:20 year:2023 number:1 day:21 month:02 https://dx.doi.org/10.1186/s12014-023-09395-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2023 1 21 02
allfields_unstemmed	10.1186/s12014-023-09395-z doi (DE-627)SPR051483963 (SPR)s12014-023-09395-z-e DE-627 ger DE-627 rakwb eng Deng, Xiaoyue verfasserin aut Changes of serum IgG glycosylation patterns in rheumatoid arthritis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. RA (dpeaa)DE-He213 ILD (dpeaa)DE-He213 Immunoglobulin G (dpeaa)DE-He213 Lectin microarray (dpeaa)DE-He213 Glycosylation (dpeaa)DE-He213 Liu, Xiaomin aut Zhang, Yan aut Ke, Dan aut Yan, Rui aut Wang, Qian aut Tian, Xinping aut Li, Mengtao aut Zeng, Xiaofeng aut Hu, Chaojun aut Enthalten in Clinical proteomics Totowa, NJ : Humana Press, 2004 20(2023), 1 vom: 21. Feb. (DE-627)397618883 (DE-600)2163624-2 1559-0275 nnns volume:20 year:2023 number:1 day:21 month:02 https://dx.doi.org/10.1186/s12014-023-09395-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2023 1 21 02
allfieldsGer	10.1186/s12014-023-09395-z doi (DE-627)SPR051483963 (SPR)s12014-023-09395-z-e DE-627 ger DE-627 rakwb eng Deng, Xiaoyue verfasserin aut Changes of serum IgG glycosylation patterns in rheumatoid arthritis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. RA (dpeaa)DE-He213 ILD (dpeaa)DE-He213 Immunoglobulin G (dpeaa)DE-He213 Lectin microarray (dpeaa)DE-He213 Glycosylation (dpeaa)DE-He213 Liu, Xiaomin aut Zhang, Yan aut Ke, Dan aut Yan, Rui aut Wang, Qian aut Tian, Xinping aut Li, Mengtao aut Zeng, Xiaofeng aut Hu, Chaojun aut Enthalten in Clinical proteomics Totowa, NJ : Humana Press, 2004 20(2023), 1 vom: 21. Feb. (DE-627)397618883 (DE-600)2163624-2 1559-0275 nnns volume:20 year:2023 number:1 day:21 month:02 https://dx.doi.org/10.1186/s12014-023-09395-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2023 1 21 02
allfieldsSound	10.1186/s12014-023-09395-z doi (DE-627)SPR051483963 (SPR)s12014-023-09395-z-e DE-627 ger DE-627 rakwb eng Deng, Xiaoyue verfasserin aut Changes of serum IgG glycosylation patterns in rheumatoid arthritis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. RA (dpeaa)DE-He213 ILD (dpeaa)DE-He213 Immunoglobulin G (dpeaa)DE-He213 Lectin microarray (dpeaa)DE-He213 Glycosylation (dpeaa)DE-He213 Liu, Xiaomin aut Zhang, Yan aut Ke, Dan aut Yan, Rui aut Wang, Qian aut Tian, Xinping aut Li, Mengtao aut Zeng, Xiaofeng aut Hu, Chaojun aut Enthalten in Clinical proteomics Totowa, NJ : Humana Press, 2004 20(2023), 1 vom: 21. Feb. (DE-627)397618883 (DE-600)2163624-2 1559-0275 nnns volume:20 year:2023 number:1 day:21 month:02 https://dx.doi.org/10.1186/s12014-023-09395-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2023 1 21 02
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source	Enthalten in Clinical proteomics 20(2023), 1 vom: 21. Feb. volume:20 year:2023 number:1 day:21 month:02
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author	Deng, Xiaoyue
spellingShingle	Deng, Xiaoyue misc RA misc ILD misc Immunoglobulin G misc Lectin microarray misc Glycosylation Changes of serum IgG glycosylation patterns in rheumatoid arthritis
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topic_title	Changes of serum IgG glycosylation patterns in rheumatoid arthritis RA (dpeaa)DE-He213 ILD (dpeaa)DE-He213 Immunoglobulin G (dpeaa)DE-He213 Lectin microarray (dpeaa)DE-He213 Glycosylation (dpeaa)DE-He213
topic	misc RA misc ILD misc Immunoglobulin G misc Lectin microarray misc Glycosylation
topic_unstemmed	misc RA misc ILD misc Immunoglobulin G misc Lectin microarray misc Glycosylation
topic_browse	misc RA misc ILD misc Immunoglobulin G misc Lectin microarray misc Glycosylation
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title	Changes of serum IgG glycosylation patterns in rheumatoid arthritis
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title_full	Changes of serum IgG glycosylation patterns in rheumatoid arthritis
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author_browse	Deng, Xiaoyue Liu, Xiaomin Zhang, Yan Ke, Dan Yan, Rui Wang, Qian Tian, Xinping Li, Mengtao Zeng, Xiaofeng Hu, Chaojun
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title_sort	changes of serum igg glycosylation patterns in rheumatoid arthritis
title_auth	Changes of serum IgG glycosylation patterns in rheumatoid arthritis
abstract	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. © The Author(s) 2023
abstractGer	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. © The Author(s) 2023
abstract_unstemmed	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. © The Author(s) 2023
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title_short	Changes of serum IgG glycosylation patterns in rheumatoid arthritis
url	https://dx.doi.org/10.1186/s12014-023-09395-z
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author2	Liu, Xiaomin Zhang, Yan Ke, Dan Yan, Rui Wang, Qian Tian, Xinping Li, Mengtao Zeng, Xiaofeng Hu, Chaojun
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up_date	2024-07-03T22:04:52.875Z
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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. 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Changes of serum IgG glycosylation patterns in rheumatoid arthritis

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