ArticleClinical proteomics2023
Changes of serum IgG glycosylation patterns in rheumatoid arthritis.
Article in Clinical proteomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Quantitative Modeling of IgG N-Glycosylation Profiles from Population Data.International journal of molecular sciences · 2025Article
- Lectin Microarray-based Glycomics and Machine Learning Identify Shared Osteoarthritis Biomarkers in Humans, Dogs, and Horses.bioRxiv : the preprint server for biology · 2025Article
- Multivariate analysis of glycogenes reveals coordinated regulation of immunoglobulin glycosylation in an immortalized human B cell system.bioRxiv : the preprint server for biology · 2025Article
- Glycosylation Regulation by TMEM230 in Aging and Autoimmunity.International journal of molecular sciences · 2025Article
- Recent Advances in Biomimetic Drug Delivery for Rheumatoid Arthritis Treatment.International journal of nanomedicine · 2025Review
- Immunoglobulin G glycosylation and its alterations in aging-related diseases.Acta biochimica et biophysica Sinica · 2024Review
- Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights.Acta biochimica et biophysica Sinica · 2024Review
- Recent advances in N-glycan biomarker discovery among human diseases.Acta biochimica et biophysica Sinica · 2024Review
- Cell Membrane Sialome: Sialic Acids as Therapeutic Targets and Regulators of Drug Resistance in Human Cancer Management.Cancers · 2023Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundRA 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.
methodLectin 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.
resultsAs 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.
conclusionLectin 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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