Association of IGHM polymorphisms with susceptibility to type 1 diabetes

Zouidi, Ferjeni; Fakhfakh, R.; Abida, Olfa; Penha‐Gonçalves, Carlos; Masmoudi, Hatem

doi:10.1007/s12026-021-09252-x

Cited by 5 publications

(2 citation statements)

References 32 publications

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“…IgM plays a vital role in identifying and removing foreign substances, such as viruses and bacteria, from the body. 67 However, IGHM is also involved in the development of autoimmune diseases like RA. 68 In the case of RA, IGHM is involved in the production of autoantibodies that target self-antigens, activating B cells to produce them.…”

Section: Discussionmentioning

confidence: 99%

The m6A/m1A/m5C-Related Methylation Modification Patterns and Immune Landscapes in Rheumatoid Arthritis and Osteoarthritis Revealed by Microarray and Single-Cell Transcriptome

Zheng,

Aihaiti,

Cai

et al. 2023

JIR

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The goal of this study was to explore the expression characteristics of RNA modification-related genes, reveal immune landscapes and identify novel potential diagnostic biomarkers in osteoarthritis (OA) and rheumatoid arthritis (RA) patients. Patients and Methods: RNA microarray and single-cell sequencing (scRNA-seq) data were downloaded from gene expression omnibus (GEO) database. Differentially expressed RNA modification-related genes were identified and then functionally annotated. Univariate logistic regression and lasso regression analysis were used to identify primary disease genes for OA and RA. Validation was done using scRNA-seq analysis and immunohistochemistry (IHC) in human knee synovial tissues and a murine destabilization of the medial meniscus (DMM) model. Through WGCNA analysis, genes associated with cell pyroptosis or autophagy in OA and RA were identified, which were then combined with differentially expressed RNA modification-related genes to construct a PPI interaction network. Furthermore, hub genes were selected for ceRNA interaction network analysis, correlation analysis with OA and RA molecular subtypes, as well as correlation analysis with 22 immune cells. Results: Six RNA modification-related genes (ADAMDEC1, IGHM, OGN, TNFRSF11B, SCARA3 and PTN) were identified as potential OA and RA pathogenesis biomarkers. Their expression was validated in human knee synovial tissues and a murine DMM model. Functional enrichment of differentially expressed RNA modification-related genes between RA and OA was analyzed using GO, KEGG, GSEA, and GSVA. Based on WGCNA and PPI analysis, the six hub genes related to pyroptosis and RNA modification (CXCL10, CXCL9, CCR7, CCL5, CXCL1, and CCR2) were identified as central nodes for ceRNA interaction, correlation with OA and RA molecular subtypes, and association with 22 immune cells. Conclusion: Our research revealed the significance of RNA modification-related genes in the development of OA and RA pathogenesis, thereby providing a novel research direction for understanding the mechanisms, diagnosis, and treatment of OA and RA.

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Section: Discussionmentioning

confidence: 99%

The m6A/m1A/m5C-Related Methylation Modification Patterns and Immune Landscapes in Rheumatoid Arthritis and Osteoarthritis Revealed by Microarray and Single-Cell Transcriptome

Zheng,

Aihaiti,

Cai

et al. 2023

JIR

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“…Nevertheless, reduced total plasma IgM has recently been reported in school aged children with type 1 diabetes 28 . Certain variants of the IGHM gene locus have been associated with an increased risk to type 1 diabetes 29 , 30 . Interestingly, in a plasma proteomic study of twins, both IGHM and its binding partner CD5L were reported among the top proteins, that were mostly affected by heritability 20 .…”

Section: Discussionmentioning

confidence: 99%

Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes

Hirvonen,

Lietzén,

Moulder

et al. 2023

Sci Rep

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Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.

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Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Gokuladhas

Zaied

Schierding

et al. 2022

Nuclear, Chromosomal, and Genomic Architecture in Biology and Medicine

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Association of IGHM polymorphisms with susceptibility to type 1 diabetes

Cited by 5 publications

References 32 publications

The m6A/m1A/m5C-Related Methylation Modification Patterns and Immune Landscapes in Rheumatoid Arthritis and Osteoarthritis Revealed by Microarray and Single-Cell Transcriptome

The m6A/m1A/m5C-Related Methylation Modification Patterns and Immune Landscapes in Rheumatoid Arthritis and Osteoarthritis Revealed by Microarray and Single-Cell Transcriptome

Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

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