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Zhang MM, Liang MJ, Zhang DM, Cai JN, Yang QJ, Zhao Y, Zhang JP, Li YL. The function and mechanism of LAPTM5 in diseases. Biomed Pharmacother 2024; 178:117237. [PMID: 39096616 DOI: 10.1016/j.biopha.2024.117237] [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: 06/05/2024] [Revised: 07/25/2024] [Accepted: 07/30/2024] [Indexed: 08/05/2024] Open
Abstract
The Lysosomal Protein Transmembrane 5 (LAPTM5) is a lysosomal transmembrane protein preferentially expressed in hematopoietic cells. The human LAPTM5 gene is located at position 1p34 and extends approximately 25 kb. Its protein includes five transmembrane domains, three PY motifs, and one UIM. The PY and UIM motifs can interact with various substrates, mediating sorting of proteins from Golgi to lysosome and subsequently participating in intracellular substrate transport and lysosomal stability regulation. Overexpression of LAPTM5 can induce lysosomal cell death (LCD), although the integrity of LAPTM5 protein is necessary for maintaining lysosome stability. Furthermore, LAPTM5 plays a role in autophagy activation during disease processes and has been confirmed to be closely associated with the regulation of immunity and inflammation. Therefore, LAPTM5 regulates a wide range of physiological processes and is involved in various diseases. This article summarizes the characteristics of the LAPTM5 gene and protein structure and provides a comprehensive review of the mechanisms involved in cell death, autophagy, immunity, and inflammation regulation. It emphasizes the significance of LAPTM5 in the clinical prevention and treatment of cardiovascular diseases, immune system disorders, viral infections, cancer, and other diseases, which could provide new therapeutic ideas and targets for human diseases.
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Affiliation(s)
- Man-Man Zhang
- Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Ming-Jun Liang
- Department of Critical Care Medicine, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Dong-Mei Zhang
- Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Jun-Nan Cai
- Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Quan-Jun Yang
- Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yun Zhao
- Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Jian-Ping Zhang
- Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Yang-Ling Li
- Department of Clinical Pharmacology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou 310006, China.
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Liang H, Liu Y, Zhang C, Qin Y. Potential Shared Mitochondrial-Related Gene Signatures and Molecular Mechanisms Between Polycystic Ovary Syndrome (PCOS) and Major Depressive Disorder (MDD): Evidence from Transcriptome Data and Machine Learning. Mol Biotechnol 2024:10.1007/s12033-024-01225-3. [PMID: 39048886 DOI: 10.1007/s12033-024-01225-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/24/2024] [Indexed: 07/27/2024]
Abstract
Polycystic ovary syndrome (PCOS) is strongly associated with major depressive disorder (MDD), but the shared pathophysiological mechanisms between them are ambiguous, and the aim of this study was to explore the shared genetic features and associated pathways between these two disorders. MDD-related genes and mitochondrial function genes were downloaded from the GeneCards database. Weighted gene co-expression network analysis of Merge Cohort (GSE80432 and GSE34526) was performed to identify PCOS-related genes. Overlaps between PCOS-related genes, MDD-related genes, and mitochondrial function genes were defined as mitochondrial function-related shared genes. Functional enrichment analysis and protein-protein interaction (PPI) network analysis were performed on the shared genes. Functional genes were then identified using Last Absolute Shrinkage and Selection Operator Regression (LASSO), and a support vector machine (SVM-RFE) was constructed to measure the accuracy of the calculations. Finally, the results were tested using the whole blood datasets GSE54250 (for PCOS) and GSE98793 (for MDD) as external validation sets. A total of 498 PCOS-related genes, 5909 MDD-related genes, and 7232 mitochondrial function genes were acquired, and totally, 40 shared genes were obtained from the overlap of the above three. The shared mitochondrial function genes were enriched for biological processes mainly involving cholesterol biosynthetic process, lipid metabolic process, triglyceride biosynthetic process, response to drug phosphatidic acid biosynthetic process, and endoplasmic reticulum membrane. Based on LASSO regression and SVM-RFE model, NPAS2 and NTS were identified as characteristic genes shared by two disorders. According to two external validation sets for PCOS and MDD, NPAS2 was finally identified as a key shared gene. Our analysis identified a mitochondrial functional gene-NPAS2-as the most critical candidate for linking PCOS and MDD. The present findings may provide new insights into the diagnosis and treatment of PCOS and MDD comorbidities.
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Affiliation(s)
- Huan Liang
- Department of Obstetrics and Gynecology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefectrue, Enshi, Hubei, China.
| | - Yi Liu
- Department of Obstetrics and Gynecology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefectrue, Enshi, Hubei, China.
| | - Chunhua Zhang
- Department of Obstetrics and Gynecology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefectrue, Enshi, Hubei, China
| | - Yaoqin Qin
- Reproductive Medicine Centre, The Central Hospital of Enshi Tujia and Miao Autonomous Prefectrue, Enshi, Hubei, China
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Wu Y, Wang Z, Hu H, Wu T, Alabed AAA, Sun Z, Wang Y, Cui G, Cong W, Li C, Li P. Identification of Immune-Related Gene Signature in Schizophrenia. ACTAS ESPANOLAS DE PSIQUIATRIA 2024; 52:276-288. [PMID: 38863043 PMCID: PMC11190455 DOI: 10.62641/aep.v52i3.1648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
BACKGROUND Schizophrenia (SCZ) is a type of psychiatric disorder characterized by multiple symptoms. Our aim is to decipher the relevant mechanisms of immune-related gene signatures in SCZ. METHODS The SCZ dataset and its associated immunoregulatory genes were retrieved using Gene Expression Omnibus (GEO) and single-sample gene set enrichment analysis (ssGSEA). Co-expressed gene modules were determined through weighted gene correlation network analysis (WGCNA). To elucidate the functional characteristics of these clusters, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used. Additionally, gene set enrichment analysis (GSEA) and Gene Set Variation Analysis (GSVA) were conducted to identify enriched pathways for the immune subgroups. A protein-protein interaction (PPI) network analysis was performed to identify core genes relevant to SCZ. RESULTS A significantly higher immune score was observed in SCZ compared to control samples. Seven distinct gene modules were identified, with genes highlighted in green selected for further analysis. Using the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method, degrees of immune cell adhesion and accumulation related to 22 different immune cell types were calculated. Significantly enriched bioprocesses concerning the immunoregulatory genes with differential expressions included interferon-beta, IgG binding, and response to interferon-gamma, according to GO and KEGG analyses. Eleven hub genes related to immune infiltration emerged as key players among the three top-ranked GO terms. CONCLUSIONS This study underscores the involvement of immunoregulatory reactions in SCZ development. Eleven immune-related genes (IFITM1 (interferon induced transmembrane protein 1), GBP1 (guanylate binding protein 1), BST2 (bone marrow stromal cell antigen 2), IFITM3 (interferon induced transmembrane protein 3), GBP2 (guanylate binding protein 2), CD44 (CD44 molecule), FCER1G (Fc epsilon receptor Ig), HLA-DRA (major histocompatibility complex, class II, DR alpha), FCGR2A (Fc gamma receptor IIa), IFI16 (interferon gamma inducible protein 16), and FCGR3B (Fc gamma receptor IIIb)) were identified as hub genes, representing potential biomarkers and therapeutic targets associated with the immune response in SCZ patients.
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Affiliation(s)
- Yu Wu
- School of Nursing, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Zhichao Wang
- Department of Academic Research, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Houjia Hu
- School of Basic Medical Sciences, Nanchang University, 330006 Nanchang, Jiangxi, China
| | - Tong Wu
- Department of Psychology, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Alabed Ali A. Alabed
- Community Medicine Department, Faculty of Medicine, Lincoln University College, 47301 Petaling Jaya, Selangor, Malaysia
| | - Zhenghai Sun
- Department of Psychology, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Yuchen Wang
- Department of Psychology, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Guangcheng Cui
- Department of Psychology, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Weiliang Cong
- Department of Anaesthesiology, The Third Affiliated Hospital of Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Chengchong Li
- Department of Psychology, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
| | - Ping Li
- Department of Psychology, Qiqihar Medical University, 161000 Qiqihar, Heilongjiang, China
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Zhao S, Hulsurkar MM, Lahiri SK, Aguilar-Sanchez Y, Munivez E, Müller FU, Jain A, Malovannaya A, Yiu CHK, Reilly S, Wehrens XHT. Atrial proteomic profiling reveals a switch towards profibrotic gene expression program in CREM-IbΔC-X mice with persistent atrial fibrillation. J Mol Cell Cardiol 2024; 190:1-12. [PMID: 38514002 DOI: 10.1016/j.yjmcc.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 02/19/2024] [Accepted: 03/18/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Overexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF. PURPOSE To identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis. METHODS Atrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. RESULTS A total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and structural based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns reminiscent of those seen in humans with persistent AF. CONCLUSIONS This study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.
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Affiliation(s)
- Shuai Zhao
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mohit M Hulsurkar
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Satadru K Lahiri
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yuriana Aguilar-Sanchez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elda Munivez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Frank Ulrich Müller
- Institute of Pharmacology and Toxicology, University of Münster, Münster, Germany
| | - Antrix Jain
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA
| | - Anna Malovannaya
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA; Department of Biochemistry, Baylor College of Medicine, Houston, TX 77030, USA
| | - Chi Him Kendrick Yiu
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Svetlana Reilly
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Xander H T Wehrens
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Medicine (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA; Department of Pediatrics (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA; Center for Space Medicine, Baylor College of Medicine, Houston, USA.
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Wang H, Cheng W, Hu P, Ling T, Hu C, Chen Y, Zheng Y, Wang J, Zhao T, You Q. Integrative analysis identifies oxidative stress biomarkers in non-alcoholic fatty liver disease via machine learning and weighted gene co-expression network analysis. Front Immunol 2024; 15:1335112. [PMID: 38476236 PMCID: PMC10927810 DOI: 10.3389/fimmu.2024.1335112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 02/08/2024] [Indexed: 03/14/2024] Open
Abstract
Background Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease globally, with the potential to progress to non-alcoholic steatohepatitis (NASH), cirrhosis, and even hepatocellular carcinoma. Given the absence of effective treatments to halt its progression, novel molecular approaches to the NAFLD diagnosis and treatment are of paramount importance. Methods Firstly, we downloaded oxidative stress-related genes from the GeneCards database and retrieved NAFLD-related datasets from the GEO database. Using the Limma R package and WGCNA, we identified differentially expressed genes closely associated with NAFLD. In our study, we identified 31 intersection genes by analyzing the intersection among oxidative stress-related genes, NAFLD-related genes, and genes closely associated with NAFLD as identified through Weighted Gene Co-expression Network Analysis (WGCNA). In a study of 31 intersection genes between NAFLD and Oxidative Stress (OS), we identified three hub genes using three machine learning algorithms: Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine - Recursive Feature Elimination (SVM-RFE), and RandomForest. Subsequently, a nomogram was utilized to predict the incidence of NAFLD. The CIBERSORT algorithm was employed for immune infiltration analysis, single sample Gene Set Enrichment Analysis (ssGSEA) for functional enrichment analysis, and Protein-Protein Interaction (PPI) networks to explore the relationships between the three hub genes and other intersecting genes of NAFLD and OS. The distribution of these three hub genes across six cell clusters was determined using single-cell RNA sequencing. Finally, utilizing relevant data from the Attie Lab Diabetes Database, and liver tissues from NASH mouse model, Western Blot (WB) and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) assays were conducted, this further validated the significant roles of CDKN1B and TFAM in NAFLD. Results In the course of this research, we identified 31 genes with a strong association with oxidative stress in NAFLD. Subsequent machine learning analysis and external validation pinpointed two genes: CDKN1B and TFAM, as demonstrating the closest correlation to oxidative stress in NAFLD. Conclusion This investigation found two hub genes that hold potential as novel targets for the diagnosis and treatment of NAFLD, thereby offering innovative perspectives for its clinical management.
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Affiliation(s)
- Haining Wang
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Wei Cheng
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ping Hu
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Tao Ling
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Hu
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yongzhen Chen
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yanan Zheng
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Junqi Wang
- Department of Medical Oncology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Ting Zhao
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Qiang You
- Medical Center for Digestive Diseases, Department of Geriatrics, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Dai L, Yuan W, Jiang R, Zhan Z, Zhang L, Xu X, Qian Y, Yang W, Zhang Z. Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis. Lipids Health Dis 2024; 23:23. [PMID: 38263097 PMCID: PMC10804801 DOI: 10.1186/s12944-023-01988-9] [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: 09/20/2023] [Accepted: 12/11/2023] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Ferroptosis, is characterized by lipid peroxidation of fatty acids in the presence of iron ions, which leads to cell apoptosis. This leads to the disruption of metabolic pathways, ultimately resulting in liver dysfunction. Although ferroptosis is linked to nonalcoholic steatohepatitis (NASH), understanding the key ferroptosis-related genes (FRGs) involved in NASH remains incomplete. NASH may be targeted therapeutically by identifying the genes responsible for ferroptosis. METHODS To identify ferroptosis-related genes and develop a ferroptosis-related signature (FeRS), 113 machine-learning algorithm combinations were used. RESULTS The FeRS constructed using the Generalized Linear Model Boosting algorithm and Gradient Boosting Machine algorithms exhibited the best prediction performance for NASH. Eight FRGs, with ZFP36 identified by the algorithms as the most crucial, were incorporated into in FeRS. ZFP36 is significantly enriched in various immune cell types and exhibits significant positive correlations with most immune signatures. CONCLUSION ZFP36 is a key FRG involved in NASH pathogenesis.
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Affiliation(s)
- Longfei Dai
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Wenkang Yuan
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Renao Jiang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Zhicheng Zhan
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Liangliang Zhang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Xinjian Xu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Yuyang Qian
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Wenqi Yang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
| | - Zhen Zhang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China.
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Zhao S, Hulsurkar MM, Lahiri SK, Aguilar-Sanchez Y, Munivez E, Müller FU, Jain A, Malovannaya A, Yiu K, Reilly S, Wehrens XH. Atrial Proteomic Profiling Reveals a Switch Towards Profibrotic Gene Expression Program in CREM-IbΔC-X Mice with Persistent Atrial Fibrillation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.575097. [PMID: 38260363 PMCID: PMC10802622 DOI: 10.1101/2024.01.10.575097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Background Overexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF. Purpose To identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis. Methods Atrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. Results A total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and remodeling based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns that resembled those of humans with persistent AF. Conclusions This study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.
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Affiliation(s)
- Shuai Zhao
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mohit M. Hulsurkar
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Satadru K. Lahiri
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yuriana Aguilar-Sanchez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elda Munivez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Frank Ulrich Müller
- Institute of Pharmacology and Toxicology, University of Münster, Münster, Germany
| | - Antrix Jain
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA
| | - Anna Malovannaya
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA
- Department of Biochemistry, Baylor College of Medicine, Houston, TX 77030, USA
| | - Kendrick Yiu
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Svetlana Reilly
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Xander H.T. Wehrens
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Medicine (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pediatrics (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA
- Center for Space Medicine, Baylor College of Medicine, Houston, USA
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