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Wu Z, Dong L, Tian Z, Yu C, Shu Q, Chen W, Li H. Integrative Analysis of the Age-Related Dysregulated Genes Reveals an Inflammation and Immunity-Associated Regulatory Network in Alzheimer's Disease. Mol Neurobiol 2024; 61:5353-5368. [PMID: 38190023 DOI: 10.1007/s12035-023-03900-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease with a long incubation period. While extensive research has led to the construction of long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) regulatory networks, which primarily derived from differential analyses between clinical AD patients and control individuals or mice, there remains a critical knowledge gap pertaining to the dynamic alterations in transcript expression profiles that occur with age, spanning from the pre-symptomatic stage to the onset of AD. In the present study, we examined the transcriptomic changes in AD model mice at three distinct stages: the unaffected (un-) stage, the pre-onset stage, and the late-onset stage, and identified 14, 57, and 99 differentially expressed mRNAs (DEmRs) in AD model mice at 3, 6, and 12 months, respectively. Among these, we pinpointed 16 mRNAs closely associated with inflammation and immunity and excavated their lncRNA-mRNA regulatory network based on a comprehensive analysis. Notably, our preliminary analysis suggested that four lncRNAs (NONMMUT102943, ENSMUST00000160309, NONMMUT083044, and NONMMUT126468), eight miRNAs (miR-34a-5p, miR-22-5p, miR-302a/b-3p, miR-340-5p, miR-376a/b-5p, and miR-487b-5p), and four mRNAs (C1qa, Cd68, Ctss, and Slc11a1) may play pivotal roles in orchestrating immune and inflammatory responses during the early stages of AD. Our study has unveiled age-related AD risk genes, and provided an analytical framework for constructing lncRNA-mRNA networks using time series data and correlation analysis. Most notably, we have successfully constructed a comprehensive regulatory ceRNA network comprising genes intricately linked to inflammatory and immune functions in AD.
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Affiliation(s)
- Zhuoze Wu
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Lei Dong
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Zhixiao Tian
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Chenhui Yu
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Qingrong Shu
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Wei Chen
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Hao Li
- Department of Pathophysiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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2
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Sokouti B. The identification of biomarkers for Alzheimer's disease using a systems biology approach based on lncRNA-circRNA-miRNA-mRNA ceRNA networks. Comput Biol Med 2024; 179:108860. [PMID: 38996555 DOI: 10.1016/j.compbiomed.2024.108860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 06/16/2024] [Accepted: 07/06/2024] [Indexed: 07/14/2024]
Abstract
In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer's disease.
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Affiliation(s)
- Babak Sokouti
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
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3
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Gao Y, Xu SM, Cheng Y, Takenaka K, Lindner G, Janitz M. Investigation of the Circular Transcriptome in Alzheimer's Disease Brain. J Mol Neurosci 2024; 74:64. [PMID: 38981928 PMCID: PMC11233389 DOI: 10.1007/s12031-024-02236-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 06/10/2024] [Indexed: 07/11/2024]
Abstract
Circular RNAs (circRNAs) are a subclass of non-coding RNAs which have demonstrated potential as biomarkers for Alzheimer's disease (AD). In this study, we conducted a comprehensive exploration of the circRNA transcriptome within AD brain tissues. Specifically, we assessed circRNA expression patterns in the dorsolateral prefrontal cortex collected from nine AD-afflicted individuals and eight healthy controls. Utilising two circRNA detection tools, CIRI2 and CIRCexplorer2, we detected thousands of circRNAs and performed a differential expression analysis. CircRNAs which exhibited statistically significantly differential expression were identified as AD-specific differentially expressed circRNAs. Notably, our investigation revealed 120 circRNAs with significant upregulation and 1325 circRNAs displaying significant downregulation in AD brains when compared to healthy brain tissue. Additionally, we explored the expression profiles of the linear RNA counterparts corresponding to differentially expressed circRNAs in AD-afflicted brains and discovered that the linear RNA counterparts exhibited no significant changes in the levels of expression. We used CRAFT tool to predict that circUBE4B had potential to target miRNA named as hsa-miR-325-5p, ultimately regulated CD44 gene. This study provides a comprehensive overview of differentially expressed circRNAs in the context of AD brains, underscoring their potential as molecular biomarkers for AD. These findings significantly enhance our comprehension of AD's underlying pathophysiological mechanisms, offering promising avenues for future diagnostic and therapeutic developments.
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Affiliation(s)
- Yulan Gao
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Si-Mei Xu
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Yuning Cheng
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Konii Takenaka
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Grace Lindner
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Michael Janitz
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia.
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4
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Li X, Tang P, Pang X, Song X, Xiong J, Yu L, Liu H, Pang C. The features analysis of hemoglobin expression on visual information transmission pathway in early stage of Alzheimer's disease. Sci Rep 2024; 14:15636. [PMID: 38972885 PMCID: PMC11228039 DOI: 10.1038/s41598-024-64099-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder characterized primarily by cognitive impairment. The motivation of this paper is to explore the impact of the visual information transmission pathway (V-H pathway) on AD, and the following feature were observed: Hemoglobin expression on the V-H pathway becomes dysregulated as AD occurs so as to the pathway becomes dysfunctional. According to the feature, the following conclusion was proposed: As AD occurs, abnormal tau proteins penetrate bloodstream and arrive at the brain regions of the pathway. Then the tau proteins or other toxic substances attack hemoglobin molecules. Under the attack, hemoglobin expression becomes more dysregulated. The dysfunction of V-H pathway has an impact on early symptoms of AD, such as spatial recognition disorder and face recognition disorder.
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Affiliation(s)
- Xuehui Li
- College of Computer Science, Sichuan Normal University, Chengdu, 610101, China
| | - Pan Tang
- School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Xinping Pang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Xianghu Song
- College of Computer Science, Sichuan Normal University, Chengdu, 610101, China
| | - Jing Xiong
- College of Computer Science, Sichuan Normal University, Chengdu, 610101, China
| | - Lei Yu
- College of Computer Science, Sichuan Normal University, Chengdu, 610101, China
| | - Hui Liu
- School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China.
| | - Chaoyang Pang
- College of Computer Science, Sichuan Normal University, Chengdu, 610101, China.
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Kim JM, Kim WR, Park EG, Lee DH, Lee YJ, Shin HJ, Jeong HS, Roh HY, Kim HS. Exploring the Regulatory Landscape of Dementia: Insights from Non-Coding RNAs. Int J Mol Sci 2024; 25:6190. [PMID: 38892378 PMCID: PMC11172830 DOI: 10.3390/ijms25116190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 05/24/2024] [Accepted: 06/03/2024] [Indexed: 06/21/2024] Open
Abstract
Dementia, a multifaceted neurological syndrome characterized by cognitive decline, poses significant challenges to daily functioning. The main causes of dementia, including Alzheimer's disease (AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), and vascular dementia (VD), have different symptoms and etiologies. Genetic regulators, specifically non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are known to play important roles in dementia pathogenesis. MiRNAs, small non-coding RNAs, regulate gene expression by binding to the 3' untranslated regions of target messenger RNAs (mRNAs), while lncRNAs and circRNAs act as molecular sponges for miRNAs, thereby regulating gene expression. The emerging concept of competing endogenous RNA (ceRNA) interactions, involving lncRNAs and circRNAs as competitors for miRNA binding, has gained attention as potential biomarkers and therapeutic targets in dementia-related disorders. This review explores the regulatory roles of ncRNAs, particularly miRNAs, and the intricate dynamics of ceRNA interactions, providing insights into dementia pathogenesis and potential therapeutic avenues.
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Affiliation(s)
- Jung-min Kim
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Woo Ryung Kim
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Eun Gyung Park
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Du Hyeong Lee
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Yun Ju Lee
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Hae Jin Shin
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Hyeon-su Jeong
- Department of Integrated Biological Sciences, Pusan National University, Busan 46241, Republic of Korea; (J.-m.K.); (W.R.K.); (E.G.P.); (D.H.L.); (Y.J.L.); (H.J.S.); (H.-s.J.)
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
| | - Hyun-Young Roh
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
- Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 46241, Republic of Korea
| | - Heui-Soo Kim
- Institute of Systems Biology, Pusan National University, Busan 46241, Republic of Korea;
- Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 46241, Republic of Korea
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Yu L, Pang X, Yang L, Jin K, Guo W, Wei Y, Pang C. Sensitivity of substrate translocation in chaperone-mediated autophagy to Alzheimer's disease progression. Aging (Albany NY) 2024; 16:9072-9105. [PMID: 38787367 PMCID: PMC11164475 DOI: 10.18632/aging.205856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 04/15/2024] [Indexed: 05/25/2024]
Abstract
Alzheimer's disease (AD) is a progressive brain disorder marked by abnormal protein accumulation and resulting proteotoxicity. This study examines Chaperone-Mediated Autophagy (CMA), particularly substrate translocation into lysosomes, in AD. The study observes: (1) Increased substrate translocation activity into lysosomes, vital for CMA, aligns with AD progression, highlighted by gene upregulation and more efficient substrate delivery. (2) This CMA phase strongly correlates with AD's clinical symptoms; more proteotoxicity links to worse dementia, underscoring the need for active degradation. (3) Proteins like GFAP and LAMP2A, when upregulated, almost certainly indicate AD risk, marking this process as a significant AD biomarker. Based on these observations, this study proposes the following hypothesis: As AD progresses, the aggregation of pathogenic proteins increases, the process of substrate entry into lysosomes via CMA becomes active. The genes associated with this process exhibit heightened sensitivity to AD. This conclusion stems from an analysis of over 10,000 genes and 363 patients using two AI methodologies. These methodologies were instrumental in identifying genes highly sensitive to AD and in mapping the molecular networks that respond to the disease, thereby highlighting the significance of this critical phase of CMA.
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Affiliation(s)
- Lei Yu
- College of Computer Science, Sichuan Normal University, Chengdu 610101, China
| | - Xinping Pang
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu 610041, China
| | - Lin Yang
- College of Computer Science, Sichuan Normal University, Chengdu 610101, China
| | - Kunpei Jin
- College of Computer Science, Sichuan Normal University, Chengdu 610101, China
| | - Wenbo Guo
- College of Computer Science, Sichuan Normal University, Chengdu 610101, China
| | - Yanyu Wei
- National Key Laboratory of Science and Technology on Vacuum Electronics, School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Chaoyang Pang
- College of Computer Science, Sichuan Normal University, Chengdu 610101, China
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7
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Zhang Z, Liu X, Zhang S, Song Z, Lu K, Yang W. A review and analysis of key biomarkers in Alzheimer's disease. Front Neurosci 2024; 18:1358998. [PMID: 38445255 PMCID: PMC10912539 DOI: 10.3389/fnins.2024.1358998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/02/2024] [Indexed: 03/07/2024] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.
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Affiliation(s)
- Zhihao Zhang
- School of Computer Science and Technology, Xinjiang University, Ürümqi, China
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
| | - Xiangtao Liu
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
| | - Suixia Zhang
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- State Key Laboratory of Pathogenesis, Prevention, Treatment of Central Asian High Incidence Diseases, First Affiliated Hospital of Xinjiang Medical University, Ürümqi, China
| | - Zhixin Song
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
| | - Ke Lu
- School of Computer Science and Technology, Xinjiang University, Ürümqi, China
| | - Wenzhong Yang
- School of Computer Science and Technology, Xinjiang University, Ürümqi, China
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8
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Xiong J, Pang X, Song X, Yang L, Pang C. The coherence between PSMC6 and α-ring in the 26S proteasome is associated with Alzheimer's disease. Front Mol Neurosci 2024; 16:1330853. [PMID: 38357597 PMCID: PMC10864545 DOI: 10.3389/fnmol.2023.1330853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/22/2023] [Indexed: 02/16/2024] Open
Abstract
Alzheimer's disease (AD) is a heterogeneous age-dependent neurodegenerative disorder. Its hallmarks involve abnormal proteostasis, which triggers proteotoxicity and induces neuronal dysfunction. The 26S proteasome is an ATP-dependent proteolytic nanomachine of the ubiquitin-proteasome system (UPS) and contributes to eliminating these abnormal proteins. This study focused on the relationship between proteasome and AD, the hub genes of proteasome, PSMC6, and 7 genes of α-ring, are selected as targets to study. The following three characteristics were observed: 1. The total number of proteasomes decreased with AD progression because the proteotoxicity damaged the expression of proteasome proteins, as evidenced by the downregulation of hub genes. 2. The existing proteasomes exhibit increased activity and efficiency to counterbalance the decline in total proteasome numbers, as evidenced by enhanced global coordination and reduced systemic disorder of proteasomal subunits as AD advances. 3. The synergy of PSMC6 and α-ring subunits is associated with AD. Synergistic downregulation of PSMC6 and α-ring subunits reflects a high probability of AD risk. Regarding the above discovery, the following hypothesis is proposed: The aggregation of pathogenic proteins intensifies with AD progression, then proteasome becomes more active and facilitates the UPS selectively targets the degradation of abnormal proteins to maintain CNS proteostasis. In this paper, bioinformatics and support vector machine learning methods are applied and combined with multivariate statistical analysis of microarray data. Additionally, the concept of entropy was used to detect the disorder of proteasome system, it was discovered that entropy is down-regulated continually with AD progression against system chaos caused by AD. Another conception of the matrix determinant was used to detect the global coordination of proteasome, it was discovered that the coordination is enhanced to maintain the efficiency of degradation. The features of entropy and determinant suggest that active proteasomes resist the attack caused by AD like defenders, on the one hand, to protect themselves (entropy reduces), and on the other hand, to fight the enemy (determinant reduces). It is noted that these are results from biocomputing and need to be supported by further biological experiments.
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Affiliation(s)
- Jing Xiong
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Xinping Pang
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, China
| | - Xianghu Song
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Lin Yang
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Chaoyang Pang
- College of Computer Science, Sichuan Normal University, Chengdu, China
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Piergiorge RM, da Silva Francisco Junior R, de Vasconcelos ATR, Santos-Rebouças CB. Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network. Comput Biol Med 2023; 166:107494. [PMID: 37769462 DOI: 10.1016/j.compbiomed.2023.107494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 09/05/2023] [Accepted: 09/15/2023] [Indexed: 09/30/2023]
Abstract
Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.
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Affiliation(s)
- Rafael Mina Piergiorge
- Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | - Cíntia Barros Santos-Rebouças
- Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil.
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