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Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration

BACKGROUND: Current research on autophagy is mainly focused on intervertebral disc tissues and cells, while there is few on human peripheral blood sample. therefore, this study constructed a diagnostic model to identify autophagy-related markers of intervertebral disc degeneration (IVDD). METHODS: G...

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Autores principales: Wang, Yifeng, Wang, Zhiwei, Tang, Yifan, Chen, Yong, Fang, Chuanyuan, Li, Zhihui, Jiao, Genlong, Chen, Xiongsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10691083/
https://www.ncbi.nlm.nih.gov/pubmed/38041088
http://dx.doi.org/10.1186/s12891-023-06886-w
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author Wang, Yifeng
Wang, Zhiwei
Tang, Yifan
Chen, Yong
Fang, Chuanyuan
Li, Zhihui
Jiao, Genlong
Chen, Xiongsheng
author_facet Wang, Yifeng
Wang, Zhiwei
Tang, Yifan
Chen, Yong
Fang, Chuanyuan
Li, Zhihui
Jiao, Genlong
Chen, Xiongsheng
author_sort Wang, Yifeng
collection PubMed
description BACKGROUND: Current research on autophagy is mainly focused on intervertebral disc tissues and cells, while there is few on human peripheral blood sample. therefore, this study constructed a diagnostic model to identify autophagy-related markers of intervertebral disc degeneration (IVDD). METHODS: GSE150408 and GSE124272 datasets were acquired from the Gene Expression Omnibus database, and differential expression analysis was performed. The IVDD-autophagy genes were obtained using Weighted Gene Coexpression Network Analysis, and a diagnostic model was constructed and validated, followed by Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). Meanwhile, miRNA–gene and transcription factor–gene interaction networks were constructed. In addition, drug-gene interactions and target genes of methylprednisolone and glucosamine were analyzed. RESULTS: A total of 1,776 differentially expressed genes were identified between IVDD and control samples, and the composition of the four immune cell types was significantly different between the IVDD and control samples. The Meturquoise and Mebrown modules were significantly related to immune cells, with significant differences between the control and IVDD samples. A diagnostic model was constructed using five key IVDD-autophagy genes. The area under the curve values of the model in the training and validation datasets were 0.907 and 0.984, respectively. The enrichment scores of the two pathways were significantly different between the IVDD and healthy groups. Eight pathways in the IVDD and healthy groups had significant differences. A total of 16 miRNAs and 3 transcription factors were predicted to be of great value. In total, 84 significantly related drugs were screened for five key IVDD-autophagy genes in the diagnostic model, and three common autophagy-related target genes of methylprednisolone and glucosamine were predicted. CONCLUSION: This study constructs a reliable autophagy-related diagnostic model that is strongly related to the immune microenvironment of IVD. Autophagy-related genes, including PHF23, RAB24, STAT3, TOMM5, and DNAJB9, may participate in IVDD pathogenesis. In addition, methylprednisolone and glucosamine may exert therapeutic effects on IVDD by targeting CTSD, VEGFA, and BAX genes through apoptosis, as well as the sphingolipid and AGE-RAGE signaling pathways in diabetic complications.
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spelling pubmed-106910832023-12-02 Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration Wang, Yifeng Wang, Zhiwei Tang, Yifan Chen, Yong Fang, Chuanyuan Li, Zhihui Jiao, Genlong Chen, Xiongsheng BMC Musculoskelet Disord Research BACKGROUND: Current research on autophagy is mainly focused on intervertebral disc tissues and cells, while there is few on human peripheral blood sample. therefore, this study constructed a diagnostic model to identify autophagy-related markers of intervertebral disc degeneration (IVDD). METHODS: GSE150408 and GSE124272 datasets were acquired from the Gene Expression Omnibus database, and differential expression analysis was performed. The IVDD-autophagy genes were obtained using Weighted Gene Coexpression Network Analysis, and a diagnostic model was constructed and validated, followed by Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). Meanwhile, miRNA–gene and transcription factor–gene interaction networks were constructed. In addition, drug-gene interactions and target genes of methylprednisolone and glucosamine were analyzed. RESULTS: A total of 1,776 differentially expressed genes were identified between IVDD and control samples, and the composition of the four immune cell types was significantly different between the IVDD and control samples. The Meturquoise and Mebrown modules were significantly related to immune cells, with significant differences between the control and IVDD samples. A diagnostic model was constructed using five key IVDD-autophagy genes. The area under the curve values of the model in the training and validation datasets were 0.907 and 0.984, respectively. The enrichment scores of the two pathways were significantly different between the IVDD and healthy groups. Eight pathways in the IVDD and healthy groups had significant differences. A total of 16 miRNAs and 3 transcription factors were predicted to be of great value. In total, 84 significantly related drugs were screened for five key IVDD-autophagy genes in the diagnostic model, and three common autophagy-related target genes of methylprednisolone and glucosamine were predicted. CONCLUSION: This study constructs a reliable autophagy-related diagnostic model that is strongly related to the immune microenvironment of IVD. Autophagy-related genes, including PHF23, RAB24, STAT3, TOMM5, and DNAJB9, may participate in IVDD pathogenesis. In addition, methylprednisolone and glucosamine may exert therapeutic effects on IVDD by targeting CTSD, VEGFA, and BAX genes through apoptosis, as well as the sphingolipid and AGE-RAGE signaling pathways in diabetic complications. BioMed Central 2023-12-01 /pmc/articles/PMC10691083/ /pubmed/38041088 http://dx.doi.org/10.1186/s12891-023-06886-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wang, Yifeng
Wang, Zhiwei
Tang, Yifan
Chen, Yong
Fang, Chuanyuan
Li, Zhihui
Jiao, Genlong
Chen, Xiongsheng
Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
title Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
title_full Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
title_fullStr Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
title_full_unstemmed Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
title_short Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
title_sort diagnostic model based on key autophagy-related genes in intervertebral disc degeneration
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10691083/
https://www.ncbi.nlm.nih.gov/pubmed/38041088
http://dx.doi.org/10.1186/s12891-023-06886-w
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