Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease
BackgroundAs the most common neurodegenerative disease, Alzheimer’s disease (AD) leads to progressive loss of cognition and memory. Presently, the underlying pathogenic genes of AD patients remain elusive, and effective disease-modifying therapy is not available. This study explored novel biomarkers...
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| Format: | Article |
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Frontiers Media S.A.
2021-07-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.658323/full |
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| author | Zhuohang Liu Zhuohang Liu Hang Li Shuyi Pan Shuyi Pan |
| author_facet | Zhuohang Liu Zhuohang Liu Hang Li Shuyi Pan Shuyi Pan |
| author_sort | Zhuohang Liu |
| collection | DOAJ |
| description | BackgroundAs the most common neurodegenerative disease, Alzheimer’s disease (AD) leads to progressive loss of cognition and memory. Presently, the underlying pathogenic genes of AD patients remain elusive, and effective disease-modifying therapy is not available. This study explored novel biomarkers that can affect diagnosis and treatment in AD based on immune infiltration.MethodsThe gene expression profiles of 139 AD cases and 134 normal controls were obtained from the NCBI GEO public database. We applied the computational method CIBERSORT to bulk gene expression profiles of AD to quantify 22 subsets of immune cells. Besides, based on the use of the Least Absolute Shrinkage Selection Operator (LASSO), this study also applied SVM-RFE analysis to screen key genes. GO-based semantic similarity and logistic regression model analyses were applied to explore hub genes further.ResultsThere was a remarkable significance in the infiltration of immune cells between the subgroups. The proportions for monocytes, M0 macrophages, and dendritic cells in the AD group were significantly higher than those in the normal group, while the proportion of some cells was lower than that of the normal group, such as NK cell resting, T-cell CD4 naive, T-cell CD4 memory activation, and eosinophils. Additionally, seven genes (ABCA2, CREBRF, CD72, CETN2, KCNG1, NDUFA2, and RPL36AL) were identified as hub genes. Then we performed the analysis of immune factor correlation, gene set enrichment analysis (GSEA), and GO based on seven hub genes. The AUC of ROC prediction model in test and validation sets were 0.845 and 0.839, respectively. Eventually, the mRNA expression analysis of ABCA2, NDUFA2, CREBRF, and CD72 revealed significant differences among the seven hub genes and then was confirmed by RT-PCR.ConclusionA model based on immune cell infiltration might be used to forecast AD patients’ diagnosis, and it provided a new perspective for AD treatment targets. |
| first_indexed | 2024-12-16T18:47:39Z |
| format | Article |
| id | doaj.art-0fa1160b8bcc46969b12c16bfce34567 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-16T18:47:39Z |
| publishDate | 2021-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-0fa1160b8bcc46969b12c16bfce345672022-12-21T22:20:47ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-07-011210.3389/fgene.2021.658323658323Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s DiseaseZhuohang Liu0Zhuohang Liu1Hang Li2Shuyi Pan3Shuyi Pan4The Fifth Clinical Medical College of Anhui Medical University, Beijing, ChinaDepartment of Hyperbaric Oxygen, Sixth Medical Center, Chinese PLA General Hospital, Beijing, ChinaDepartment of Hyperbaric Oxygen, Sixth Medical Center, Chinese PLA General Hospital, Beijing, ChinaThe Fifth Clinical Medical College of Anhui Medical University, Beijing, ChinaDepartment of Hyperbaric Oxygen, Sixth Medical Center, Chinese PLA General Hospital, Beijing, ChinaBackgroundAs the most common neurodegenerative disease, Alzheimer’s disease (AD) leads to progressive loss of cognition and memory. Presently, the underlying pathogenic genes of AD patients remain elusive, and effective disease-modifying therapy is not available. This study explored novel biomarkers that can affect diagnosis and treatment in AD based on immune infiltration.MethodsThe gene expression profiles of 139 AD cases and 134 normal controls were obtained from the NCBI GEO public database. We applied the computational method CIBERSORT to bulk gene expression profiles of AD to quantify 22 subsets of immune cells. Besides, based on the use of the Least Absolute Shrinkage Selection Operator (LASSO), this study also applied SVM-RFE analysis to screen key genes. GO-based semantic similarity and logistic regression model analyses were applied to explore hub genes further.ResultsThere was a remarkable significance in the infiltration of immune cells between the subgroups. The proportions for monocytes, M0 macrophages, and dendritic cells in the AD group were significantly higher than those in the normal group, while the proportion of some cells was lower than that of the normal group, such as NK cell resting, T-cell CD4 naive, T-cell CD4 memory activation, and eosinophils. Additionally, seven genes (ABCA2, CREBRF, CD72, CETN2, KCNG1, NDUFA2, and RPL36AL) were identified as hub genes. Then we performed the analysis of immune factor correlation, gene set enrichment analysis (GSEA), and GO based on seven hub genes. The AUC of ROC prediction model in test and validation sets were 0.845 and 0.839, respectively. Eventually, the mRNA expression analysis of ABCA2, NDUFA2, CREBRF, and CD72 revealed significant differences among the seven hub genes and then was confirmed by RT-PCR.ConclusionA model based on immune cell infiltration might be used to forecast AD patients’ diagnosis, and it provided a new perspective for AD treatment targets.https://www.frontiersin.org/articles/10.3389/fgene.2021.658323/fullgenetic correlationAlzheimer diseaseimmune infiltrationbioinformatics analysisGSEA |
| spellingShingle | Zhuohang Liu Zhuohang Liu Hang Li Shuyi Pan Shuyi Pan Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease Frontiers in Genetics genetic correlation Alzheimer disease immune infiltration bioinformatics analysis GSEA |
| title | Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease |
| title_full | Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease |
| title_fullStr | Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease |
| title_full_unstemmed | Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease |
| title_short | Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease |
| title_sort | discovery and validation of key biomarkers based on immune infiltrates in alzheimer s disease |
| topic | genetic correlation Alzheimer disease immune infiltration bioinformatics analysis GSEA |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.658323/full |
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