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Zhong X, Chen X, Liu Y, Gui S, Pu J, Wang D, Tao W, Chen Y, Chen X, Chen W, Chen X, Qiao R, Tao X, Li Z, Xie P. Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex. Heliyon 2024; 10:e28960. [PMID: 38628773 PMCID: PMC11019182 DOI: 10.1016/j.heliyon.2024.e28960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/22/2024] [Accepted: 03/27/2024] [Indexed: 04/19/2024] Open
Abstract
Background Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. Methods We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. Results Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. Conclusions The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.
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Affiliation(s)
- Xiaogang Zhong
- College of Basic Medicine, Chongqing Medical University, Chongqing, 400016, China
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
| | - Xiangyu Chen
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yiyun Liu
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
| | - Siwen Gui
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
| | - Juncai Pu
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Dongfang Wang
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
| | - Wei Tao
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
| | - Yue Chen
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiang Chen
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Weiyi Chen
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaopeng Chen
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Renjie Qiao
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiangkun Tao
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zhuocan Li
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Peng Xie
- College of Basic Medicine, Chongqing Medical University, Chongqing, 400016, China
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
- The Jin Feng Laboratory, Chongqing, 401329, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
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Zhang Y, Liu C. Transcriptomic analysis of mRNAs in human whole blood identified age-specific changes in healthy individuals. Medicine (Baltimore) 2023; 102:e36486. [PMID: 38065846 PMCID: PMC10713173 DOI: 10.1097/md.0000000000036486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/14/2023] [Indexed: 12/18/2023] Open
Abstract
Older age is one of the most important shared risk factors for multiple chronic diseases, increasing the medical burden to contemporary societies. Current research focuses on identifying aging biomarkers to predict aging trajectories and developing interventions aimed at preventing and delaying the progression of multimorbidity with aging. Here, a transcriptomic changes analysis of whole blood genes with age was conducted. The age-related whole blood gene-expression profiling datasets were downloaded from the Gene Expression Omnibus (GEO) database. We screened the differentially expressed genes (DEGs) between healthy young and old individuals and performed functional enrichment analysis. Cytoscape with Cytohubba and MCODE was used to perform an interaction network of DEGs and identify hub genes. In addition, ROC curves and correlation analysis were used to evaluate the accuracy of hub genes. In total, we identified 29 DEGs between young and old samples that were enriched mainly in immunoglobulin binding and complex, humoral immune response, and immune response-activating signaling pathways. In combination with the PPI network and topological analysis, 4 hub genes (IGLL5, Jchain, POU2AF1, and Bach2) were identified. Pearson analysis showed that the expression changes of these hub genes were highly correlated with age. Among them, 3 hub genes (IGLL5, POU2AF1, and Bach2) were identified with good accuracy (AUC score > 0.7), indicating that these genes were the best indicators of age. Together, our results provided potential biomarkers IGLL5, POU2AF1, and Bach2 to identify individuals at high early risk of age-related disease to be targeted for early interventions and contribute to understanding the molecular mechanisms in the progression of aging.
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Affiliation(s)
- Yan Zhang
- Department of Ophthalmology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chonghui Liu
- College of Life Science, Northeast Forestry University, Harbin, China
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