Associations of plasma soluble CD22 levels with brain amyloid burden and cognitive decline in Alzheimer’s disease

Bu, Xian‐Le; Sun, Pu‐Yang; Fan, Dong-Yu; Wang, Jun; Sun, Hao‐Lun; Cheng, Yuan; Zeng, Guihua; Chen, Dong-Wan; Li, Huiyun; Xu, Yifeng; Shen, Yujie; Miles, Luke A.; Maruff, Paul; Gu, Ben; Fowler, Christopher; Masters, Colin L.; Wang, Yan‐Jiang

doi:10.1126/sciadv.abm5667

Cited by 8 publications

(5 citation statements)

References 30 publications

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“…Inhibition of CD22 promotes microglial phagocytosis of Ab oligomers and lessens cognitive impairment in aged mice. The plasma levels of soluble CD22 are elevated in patients with Alzheimer’s disease, and its level was correlated with brain Ab burden, cerebrospinal fluid (CSF) p-tau levels, and baseline cognitive impairment ( 50 ). Therefore, increased levels of soluble CD22 are promising biomarkers of various disorders, including cancer, infections, and neurogenerative disorders.…”

Section: Discussionmentioning

confidence: 99%

B-cell immune dysregulation with low soluble CD22 levels in refractory seronegative myasthenia gravis

Okuzono,

Miyakawa,

Itou

et al. 2024

Front. Immunol.

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Myasthenia gravis (MG), primarily caused by acetylcholine receptor (AChR) autoantibodies, is a chronic autoimmune disorder causing severe muscle weakness and fatigability. In particular, seronegative MG constitutes 10%–15% of MG cases and presents diagnostic challenges especially in early-onset female patients who often show severe disease and resistance to immunosuppressive therapy. Furthermore, the immunopathology of seronegative MG remains unclear. Thus, in this study, we aimed to elucidate the pathogenic mechanism of seronegative MG using scRNA-seq analysis and plasma proteome analysis; in particular, we investigated the relationship between immune dysregulation status and disease severity in refractory seronegative MG. Employing single-cell RNA-sequencing and plasma proteome analyses, we analyzed peripheral blood samples from 30 women divided into three groups: 10 healthy controls, 10 early-onset AChR-positive MG, and 10 refractory early-onset seronegative MG patients, both before and after intravenous immunoglobulin treatment. The disease severity was evaluated using the MG-Activities of Daily Living (ADL), MG composite (MGC), and revised 15-item MG-Quality of Life (QOL) scales. We observed numerical abnormalities in multiple immune cells, particularly B cells, in patients with refractory seronegative MG, correlating with disease activity. Notably, severe MG cases had fewer regulatory T cells without functional abnormalities. Memory B cells were found to be enriched in peripheral blood cells compared with naïve B cells. Moreover, plasma proteome analysis indicated significantly lower plasma protein levels of soluble CD22, expressed in the lineage of B-cell maturation (including mature B cells and memory B cells), in refractory seronegative MG patients than in healthy donors or patients with AChR-positive MG. Soluble CD22 levels were correlated with disease severity, B-cell frequency, and RNA expression levels of CD22. In summary, this study elucidates the immunopathology of refractory seronegative MG, highlighting immune disorders centered on B cells and diminished soluble CD22 levels. These insights pave the way for novel MG treatment strategies focused on B-cell biology.

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Section: Discussionmentioning

confidence: 99%

B-cell immune dysregulation with low soluble CD22 levels in refractory seronegative myasthenia gravis

Okuzono,

Miyakawa,

Itou

et al. 2024

Front. Immunol.

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“…Previous studies have proven that the FGF8 [520], SERPINA1 [521], LRRK2 [522], CHRNA4 [523], TF (transferrin) [524], TRDN (triadin) [525], NR0B1 [526], RELN (reelin) [527], HTR2C [528], RIT2 [529], REN (renin) [530], TLR2 [531], MOBP (myelin associated oligodendrocyte basic protein) [532], TNR (tenascin R) [533], ADGRB1 [534], GPR37 [535], SHH (sonic hedgehog signaling molecule) [536], XDH (xanthine dehydrogenase) [537], SIRT2 [538], BMP2 [539], HAS2 [540], CSMD1 [541], NTF3 [542], SNCB (synuclein beta) [543], MMP3 [544], HLA-DRB5 [545], HLA-DRB1 [546], HLA-DRA [547], VWF (von Willebrand factor) [548], AKR1C3 [549], CASP1 [550], CHRNA5 [551], TET1 [552], LRRN3 [553], EGFR (epidermal growth factor receptor) [554], PLXNA4 [555], FOXG1 [556], MAP1B [557], ANK1 [558], ATP10B [559], RND3 [560], COMT (catechol-O-methyltransferase) [561], LIFR (LIF receptor subunit alpha) [562] and TRAF5 [212] are involved in Parkinson’s disease. Recent studies have shown that SERPINA1 [563], LRRK2 [522], CHRNA4 [564], CD22 [565], TF (transferrin) ssociated tyrosine kinase) [579], FGF14 [580], INSC (INSC spindle orientation adaptor protein) [581], BARHL1 [582], PRKCH (protein kinase C eta) [583], SLC24A4 [584], TMEM176B [585], MBP (myelin basic protein) [586], ACAN (aggrecan) [587], SHH (sonic hedgehog signaling molecule) [588], SIRT2 [589], RBP4 [590], ISM1 [591], HOXB6 [592], CDH13 [593], NTF3 [594], TRPC6 [595], MMP3 [596], HLA-DRB5 [597], HLA-DRB1 [546], CD74 [598],...…”

Section: Discussionmentioning

confidence: 99%

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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Huntington's disease (HD) is the primary cause of progressive motor deficits, psychiatric symptoms, and cognitive impairment. The exact molecular mechanisms of HD pathogenesis are largely unknown. This investigation aims to identify the hub genes, miRNA and TFs in HD and explore their potential molecular regulatory network. Next generation sequencing (NGS) dataset (GSE105041) was extracted from the Gene Expression Omnibus (GEO) database. An integrated bioinformatics pipeline including identification of differentially expressed genes (DEGs), Gene ontology and REACTOME pathway enrichment analysis, protein-protein interaction (PPI) network and module analysis, miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network analysis, and receiver operating characteristic curve (ROC) analysis were applied to identify hub genes, miRNA and TFs, and key drivers of HD pathogenesis. We identified 958 DEGs in the discovery phase, consisting of 479 up regulated genes and 479 down regulated genes. GO and REACTOME enrichment analyses of the 479 up regulated genes and 479 down regulated genes showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and MHC class II antigen presentation. Further analysis of the PPI network using Cytoscape and PEWCC plugins identified 10 hub genes, including LRRK2, MTUS2, HOXA1, IL7R, ERBB3, EGFR, TEX101, WDR76, NEDD4L and COMT. Possible target miRNAs and TFs, including hsa-mir-1292-5p, hsa-mir-4521, ESRRB and SREBF1, were predicted by constructing a miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network. This investigation used bioinformatics methods to explore the molecular pathogenesis of HD, and identified potential molecular markers. These molecular markers might provide novel ideas and methods for the early diagnosis, treatment, and monitoring of HD.

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“…According to a recent study, higher plasma soluble CD22 (sCD22) levels are associated with accelerated cognitive deterioration. Furthermore, plasma sCD22 levels predicted longitudinal cognitive deterioration during 7.5 years of follow-up [ 51 ]. This evidence suggests that CD22 may be an important marker to help us identify patients who are more likely to transform from MCI to AD.…”

Section: Discussionmentioning

confidence: 99%

Systems Genetic Identification of Mitochondrion-Associated Alzheimer’s Disease Genes and Implications for Disease Risk Prediction

Wang

Bennett

et al. 2022

Biomedicines

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Cumulative evidence has revealed the association between mitochondrial dysfunction and Alzheimer’s disease (AD). Because the number of mitochondrial genes is very limited, the mitochondrial pathogenesis of AD must involve certain nuclear genes. In this study, we employed systems genetic methods to identify mitochondrion-associated nuclear genes that may participate in the pathogenesis of AD. First, we performed a mitochondrial genome-wide association study (MiWAS, n = 809) to identify mitochondrial single-nucleotide polymorphisms (MT-SNPs) associated with AD. Then, epistasis analysis was performed to examine interacting SNPs between the mitochondrial and nuclear genomes. Weighted co-expression network analysis (WGCNA) was applied to transcriptomic data from the same sample (n = 743) to identify AD-related gene modules, which were further enriched by mitochondrion-associated genes. Using hub genes derived from these modules, random forest models were constructed to predict AD risk in four independent datasets (n = 743, n = 542, n = 161, and n = 540). In total, 9 potentially significant MT-SNPs and 14,340 nominally significant MT-nuclear interactive SNPs were identified for AD, which were validated by functional analysis. A total of 6 mitochondrion-related modules involved in AD pathogenesis were found by WGCNA, from which 91 hub genes were screened and used to build AD risk prediction models. For the four independent datasets, these models perform better than those derived from AD genes identified by genome-wide association studies (GWASs) or differential expression analysis (DeLong’s test, p < 0.05). Overall, through systems genetics analyses, mitochondrion-associated SNPs/genes with potential roles in AD pathogenesis were identified and preliminarily validated, illustrating the power of mitochondrial genetics in AD pathogenesis elucidation and risk prediction.

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Associations of plasma soluble CD22 levels with brain amyloid burden and cognitive decline in Alzheimer’s disease

Cited by 8 publications

References 30 publications

B-cell immune dysregulation with low soluble CD22 levels in refractory seronegative myasthenia gravis

B-cell immune dysregulation with low soluble CD22 levels in refractory seronegative myasthenia gravis

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Systems Genetic Identification of Mitochondrion-Associated Alzheimer’s Disease Genes and Implications for Disease Risk Prediction

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