Integrative bioinformatics analysis of potential therapeutic targets and immune infiltration characteristics in dilated cardiomyopathy

Yang, Yujiao; Liu, Ping; Teng, Ruo-Ling; Liu, Fenfen; Zhang, Cuiping; Lu, Xiang; Ding, Yi

doi:10.21037/atm-22-732

Cited by 11 publications

(16 citation statements)

References 62 publications

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“…Different from previous studies 19 , 20 , our enrichment analysis, in this study, for DEGs revealed that multiple enrichment items were significantly involved in immune response. Regulation of memory T cell differentiation, including regulation of T cell mediated cytotoxicity and immunological memory formation, has been mainly enriched in biological process.…”

Section: Discussioncontrasting

confidence: 99%

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis

et al. 2023

Sci Rep

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Dilated cardiomyopathy (DCM) is characterized by the left ventricular dilatation and impaired myocardial systolic dysfunction with high mortality and morbidity. However, the underlying mechanisms remain elusive. We first identified the differentially expressed genes (DEGs) between the DCM and control group using two expression profiles from GSE3585 and GSE84796. Enrichment analysis was conducted to explore the potential mechanisms underlying DCM. A total of four algorithms, including key module of MCODE, degree, maximum neighborhood component (MNC), and maximal clique centrality (MCC), were used to identify the hub genes within Cytoscape. The correlation between hub genes and infiltrated immune cells was evaluated to determine potential immune-related genes. The expression analysis and diagnosis value analysis of potential immune-related genes were performed. Finally, the expression analysis with GSE57338 and relationship analysis with the comparative toxicogenomics database (CTD) were performed to identify the key immune-related genes in DCM. A total of 80 DEGs were screened for DCM. Enrichment analysis revealed that DEGs were involved in the immune-related pathological process. Immune infiltration analysis indicated a potentially abnormal immune response in DCM. Four up-regulated genes (COL1A2, COL3A1, CD53, and POSTN) were identified as potential immune-related genes. Finally, three genes (COL1A2, COL3A1, and POSTN) were determined as the key immune-related genes in DCM via expression analysis with a validation set (GSE57338) and relationship analysis with CTD. Our study suggested that the upregulated COL1A2, COL3A1, and POSTN might be the key immune-related genes for DCM. Further studies are needed to validate the underlying mechanisms.

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Section: Discussioncontrasting

confidence: 99%

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis

et al. 2023

Sci Rep

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“…In this study, similar to previous studies [19,20] , our enrichment analysis for DEGs revealed that multiple enrichment items were signi cantly involved in immune response. Regulation of memory T cell differentiation, including regulation of T cell mediated cytotoxicity, immunological memory formation, and so forth, has been mainly enriched in biological process.…”

Section: Discussionsupporting

confidence: 88%

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis

et al. 2022

Preprint

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Background:Dilated cardiomyopathy (DCM) is characterized by the left ventricular dilatation and impaired myocardial systolic dysfunction with high mortality and morbidity. However, the underlying mechanisms remain elusive.Methods:Differentially expressed genes (DEGs) analysis was performed using two expression profiles from GSE3585 and GSE8479. Enrichment analysis to explore the potential mechanisms underlying DCM was conducted. A total of four algorithms were used within Cytoscape to identify the hub genes. Correlation analysis between hub genes and infiltrated immune cells to identify potential immune-related genes. The expression analysis and diagnosis value analysis of potential immune-related genes were performed. Finally, the expression analysis with GSE57338 and relationship analysis with the comparative toxicogenomics database (CTD) were performed for identification of the key immune-related genes in DCM. Results:A total of 80 DEGs were screened for DCM. Enrichment analysis revealed that DEGs were involved in immune-related pathological process. Immune infiltration analysis indicated a potential immune response abnormal in DCM. Four up-regulated genes, including COL1A2, COL3A1, CD53, and POSTN, were identified as potential immune-related genes. Finally, three genes (COL1A2, COL3A1, and POSTN) were determined as the key immune-related genes in DCM via expression analysis with a validation set (GSE57338) and relationship analysis with CTD.Conclusions:Our study suggested that the upregulated COL1A2, COL3A1, and POSTN might be the key immune-related genes for DCM. Further studies are needed to validate the underlying mechanisms.

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“…Compared with previous studies, SERPIAN3 presented the diagnosis value (38) in HF, and this work expanded its scale into DCM with the same point as Asakura and Kitakaze (39). Furthermore, Yang et al (40) emphasizes the therapeutic value of FRZB, and our study expands its treatment potential to diagnosis value. Regarding FCN3, though studies pay attention to the diagnosis value for HF (41), no study reports the diagnosis value for DCM to our knowledge.…”

Section: Discussionmentioning

confidence: 59%

Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy

Zhang

Lin²,

Wang³

et al. 2023

Front. Cardiovasc. Med.

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IntroductionMachine learning (ML) has gained intensive popularity in various fields, such as disease diagnosis in healthcare. However, it has limitation for single algorithm to explore the diagnosing value of dilated cardiomyopathy (DCM). We aim to develop a novel overall normalized sum weight of multiple-model MLs to assess the diagnosing value in DCM.MethodsGene expression data were selected from previously published databases (six sets of eligible microarrays, 386 samples) with eligible criteria. Two sets of microarrays were used as training; the others were studied in the testing sets (ratio 5:1). Totally, we identified 20 differently expressed genes (DEGs) between DCM and control individuals (7 upregulated and 13 down-regulated).ResultsWe developed six classification ML methods to identify potential candidate genes based on their overall weights. Three genes, serine proteinase inhibitor A3 (SERPINA3), frizzled-related proteins (FRPs) 3 (FRZB), and ficolin 3 (FCN3) were finally identified as the receiver operating characteristic (ROC). Interestingly, we found all three genes correlated considerably with plasma cells. Importantly, not only in training sets but also testing sets, the areas under the curve (AUCs) for SERPINA3, FRZB, and FCN3 were greater than 0.88. The ROC of SERPINA3 was significantly high (0.940 in training and 0.918 in testing sets), indicating it is a potentially functional gene in DCM. Especially, the plasma levels in DCM patients of SERPINA3, FCN, and FRZB were significant compared with healthy control.DiscussionSERPINA3, FRZB, and FCN3 might be potential diagnosis targets for DCM, Further verification work could be implemented.

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Integrative bioinformatics analysis of potential therapeutic targets and immune infiltration characteristics in dilated cardiomyopathy

Cited by 11 publications

References 62 publications

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis

Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy

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