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Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease

BACKGROUND: Protein glycosylation has been confirmed to be involved in the pathological mechanisms of Alzheimer’s disease (AD); however, there is still a lack of systematic analysis of the immune processes mediated by protein glycosylation-related genes (PGRGs) in AD. MATERIALS AND METHODS: Transcri...

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Autores principales: Ma, Zhaotian, Yang, Fan, Fan, Jiajia, Li, Xin, Liu, Yuanyuan, Chen, Wei, Sun, Honghao, Ma, Tengfei, Wang, Qiongying, Maihaiti, Yueriguli, Ren, Xiaoqiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667030/
https://www.ncbi.nlm.nih.gov/pubmed/36408104
http://dx.doi.org/10.3389/fnagi.2022.968190
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author Ma, Zhaotian
Yang, Fan
Fan, Jiajia
Li, Xin
Liu, Yuanyuan
Chen, Wei
Sun, Honghao
Ma, Tengfei
Wang, Qiongying
Maihaiti, Yueriguli
Ren, Xiaoqiao
author_facet Ma, Zhaotian
Yang, Fan
Fan, Jiajia
Li, Xin
Liu, Yuanyuan
Chen, Wei
Sun, Honghao
Ma, Tengfei
Wang, Qiongying
Maihaiti, Yueriguli
Ren, Xiaoqiao
author_sort Ma, Zhaotian
collection PubMed
description BACKGROUND: Protein glycosylation has been confirmed to be involved in the pathological mechanisms of Alzheimer’s disease (AD); however, there is still a lack of systematic analysis of the immune processes mediated by protein glycosylation-related genes (PGRGs) in AD. MATERIALS AND METHODS: Transcriptomic data of AD patients were obtained from the Gene Expression Omnibus database and divided into training and verification datasets. The core PGRGs of the training set were identified by weighted gene co-expression network analysis, and protein glycosylation-related subtypes in AD were identified based on k-means unsupervised clustering. Protein glycosylation scores and neuroinflammatory levels of different subtypes were compared, and functional enrichment analysis and drug prediction were performed based on the differentially expressed genes (DEGs) between the subtypes. A random forest model was used to select important DEGs as diagnostic markers between subtypes, and a line chart model was constructed and verified in other datasets. We evaluated the differences in immune cell infiltration between the subtypes through the single-sample gene set enrichment analysis, analyzed the correlation between core diagnostic markers and immune cells, and explored the expression regulation network of the core diagnostic markers. RESULTS: Eight core PGRGs were differentially expressed between the training set and control samples. AD was divided into two subtypes with significantly different biological processes, such as vesicle-mediated transport in synapses and neuroactive ligand-receptor interactions. The high protein glycosylation subtype had a higher level of neuroinflammation. Riluzole and sulfasalazine were found to have potential clinical value in this subtype. A reliable construction line chart model was constructed based on nine diagnostic markers, and SERPINA3 was identified as the core diagnostic marker. There were significant differences in immune cell infiltration between the two subtypes. SERPINA3 was found to be closely related to immune cells, and the expression of SERPINA3 in AD was found to be regulated by a competing endogenous RNA network that involves eight long non-coding RNAs and seven microRNAs. CONCLUSION: Protein glycosylation and its corresponding immune process play an important role in the occurrence and development of AD. Understanding the role of PGRGs in AD may provide a new potential therapeutic target for AD.
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spelling pubmed-96670302022-11-17 Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease Ma, Zhaotian Yang, Fan Fan, Jiajia Li, Xin Liu, Yuanyuan Chen, Wei Sun, Honghao Ma, Tengfei Wang, Qiongying Maihaiti, Yueriguli Ren, Xiaoqiao Front Aging Neurosci Neuroscience BACKGROUND: Protein glycosylation has been confirmed to be involved in the pathological mechanisms of Alzheimer’s disease (AD); however, there is still a lack of systematic analysis of the immune processes mediated by protein glycosylation-related genes (PGRGs) in AD. MATERIALS AND METHODS: Transcriptomic data of AD patients were obtained from the Gene Expression Omnibus database and divided into training and verification datasets. The core PGRGs of the training set were identified by weighted gene co-expression network analysis, and protein glycosylation-related subtypes in AD were identified based on k-means unsupervised clustering. Protein glycosylation scores and neuroinflammatory levels of different subtypes were compared, and functional enrichment analysis and drug prediction were performed based on the differentially expressed genes (DEGs) between the subtypes. A random forest model was used to select important DEGs as diagnostic markers between subtypes, and a line chart model was constructed and verified in other datasets. We evaluated the differences in immune cell infiltration between the subtypes through the single-sample gene set enrichment analysis, analyzed the correlation between core diagnostic markers and immune cells, and explored the expression regulation network of the core diagnostic markers. RESULTS: Eight core PGRGs were differentially expressed between the training set and control samples. AD was divided into two subtypes with significantly different biological processes, such as vesicle-mediated transport in synapses and neuroactive ligand-receptor interactions. The high protein glycosylation subtype had a higher level of neuroinflammation. Riluzole and sulfasalazine were found to have potential clinical value in this subtype. A reliable construction line chart model was constructed based on nine diagnostic markers, and SERPINA3 was identified as the core diagnostic marker. There were significant differences in immune cell infiltration between the two subtypes. SERPINA3 was found to be closely related to immune cells, and the expression of SERPINA3 in AD was found to be regulated by a competing endogenous RNA network that involves eight long non-coding RNAs and seven microRNAs. CONCLUSION: Protein glycosylation and its corresponding immune process play an important role in the occurrence and development of AD. Understanding the role of PGRGs in AD may provide a new potential therapeutic target for AD. Frontiers Media S.A. 2022-11-02 /pmc/articles/PMC9667030/ /pubmed/36408104 http://dx.doi.org/10.3389/fnagi.2022.968190 Text en Copyright © 2022 Ma, Yang, Fan, Li, Liu, Chen, Sun, Ma, Wang, Maihaiti and Ren. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Ma, Zhaotian
Yang, Fan
Fan, Jiajia
Li, Xin
Liu, Yuanyuan
Chen, Wei
Sun, Honghao
Ma, Tengfei
Wang, Qiongying
Maihaiti, Yueriguli
Ren, Xiaoqiao
Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease
title Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease
title_full Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease
title_fullStr Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease
title_full_unstemmed Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease
title_short Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer’s disease
title_sort identification and immune characteristics of molecular subtypes related to protein glycosylation in alzheimer’s disease
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667030/
https://www.ncbi.nlm.nih.gov/pubmed/36408104
http://dx.doi.org/10.3389/fnagi.2022.968190
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