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Górska AM, Santos-García I, Eiriz I, Brüning T, Nyman T, Pahnke J. Evaluation of cerebrospinal fluid (CSF) and interstitial fluid (ISF) mouse proteomes for the validation and description of Alzheimer's disease biomarkers. J Neurosci Methods 2024:110239. [PMID: 39102902 DOI: 10.1016/j.jneumeth.2024.110239] [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: 03/26/2024] [Revised: 07/22/2024] [Accepted: 07/26/2024] [Indexed: 08/07/2024]
Abstract
BACKGROUND Mass spectrometry (MS)-based cerebrospinal fluid (CSF) proteomics is an important method for discovering biomarkers of neurodegenerative diseases. CSF serves as a reservoir for interstitial fluid (ISF), and extensive communication between the two fluid compartments helps to remove waste products from the brain. NEW METHOD We performed proteomic analyses of both CSF and ISF fluid compartments using intracerebral microdialysis to validate and detect novel biomarkers of Alzheimer's disease (AD) in APPtg and C57Bl/6J control mice. RESULTS We identified up to 625 proteins in ISF and 4,483 proteins in CSF samples. By comparing the biofluid profiles of APPtg and C57Bl/6J mice, we detected 37 and 108 significantly up- and downregulated candidates, respectively. In ISF, 7 highly regulated proteins, such as Gfap, Aldh1l1, Gstm1, and Txn, have already been implicated in AD progression, whereas in CSF, 9 out of 14 highly regulated proteins, such as Apba2, Syt12, Pgs1 and Vsnl1, have also been validated to be involved in AD pathogenesis. In addition, we also detected new interesting regulated proteins related to the control of synapses and neurotransmission (Kcna2, Cacng3, and Clcn6) whose roles as AD biomarkers should be further investigated. COMPARISON WITH EXISTING METHODS This newly established combined protocol provides better insight into the mutual communication between ISF and CSF as an analysis of tissue or CSF compartments alone. CONCLUSIONS The use of multiple fluid compartments, ISF and CSF, for the detection of their biological communication enables better detection of new promising AD biomarkers.
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Affiliation(s)
- Anna Maria Górska
- Translational Neurodegeneration Research and Neuropathology Lab, Department of Clinical Medicine (KlinMed), Medical Faculty, University of Oslo (UiO) and Section of Neuropathology Research, Department of Pathology, Clinics for Laboratory Medicine (KLM), Oslo University Hospital (OUS) Sognsvannsveien 20, NO-0372 Oslo, Norway; School of Neurobiology, Biochemistry and Biophysics, The Georg S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, IL-6997801, Israel.
| | - Irene Santos-García
- Translational Neurodegeneration Research and Neuropathology Lab, Department of Clinical Medicine (KlinMed), Medical Faculty, University of Oslo (UiO) and Section of Neuropathology Research, Department of Pathology, Clinics for Laboratory Medicine (KLM), Oslo University Hospital (OUS) Sognsvannsveien 20, NO-0372 Oslo, Norway; School of Neurobiology, Biochemistry and Biophysics, The Georg S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, IL-6997801, Israel.
| | - Ivan Eiriz
- Translational Neurodegeneration Research and Neuropathology Lab, Department of Clinical Medicine (KlinMed), Medical Faculty, University of Oslo (UiO) and Section of Neuropathology Research, Department of Pathology, Clinics for Laboratory Medicine (KLM), Oslo University Hospital (OUS) Sognsvannsveien 20, NO-0372 Oslo, Norway; School of Neurobiology, Biochemistry and Biophysics, The Georg S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, IL-6997801, Israel.
| | - Thomas Brüning
- Translational Neurodegeneration Research and Neuropathology Lab, Department of Clinical Medicine (KlinMed), Medical Faculty, University of Oslo (UiO) and Section of Neuropathology Research, Department of Pathology, Clinics for Laboratory Medicine (KLM), Oslo University Hospital (OUS) Sognsvannsveien 20, NO-0372 Oslo, Norway; School of Neurobiology, Biochemistry and Biophysics, The Georg S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, IL-6997801, Israel.
| | - Tuula Nyman
- Proteomics Core Facility, Department of Immunology, Oslo University Hospital (OUS) and University of Oslo (UiO), Faculty of Medicine, Sognsvannsveien 20, NO-0372 Oslo, Norway; School of Neurobiology, Biochemistry and Biophysics, The Georg S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, IL-6997801, Israel.
| | - Jens Pahnke
- Translational Neurodegeneration Research and Neuropathology Lab, Department of Clinical Medicine (KlinMed), Medical Faculty, University of Oslo (UiO) and Section of Neuropathology Research, Department of Pathology, Clinics for Laboratory Medicine (KLM), Oslo University Hospital (OUS) Sognsvannsveien 20, NO-0372 Oslo, Norway; Proteomics Core Facility, Department of Immunology, Oslo University Hospital (OUS) and University of Oslo (UiO), Faculty of Medicine, Sognsvannsveien 20, NO-0372 Oslo, Norway; Institute of Nutritional Medicine (INUM) and Lübeck Institute of Dermatology (LIED), University of Lübeck (UzL) and University Medical Center Schleswig-Holstein (UKSH), Ratzeburger Allee 160, D-23538 Lübeck, Germany; Department of Pharmacology, Faculty of Medicine and Life Sciences, University of Latvia, Jelgavas iela 3, LV-1004 Rīga, Latvia; School of Neurobiology, Biochemistry and Biophysics, The Georg S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, IL-6997801, Israel.
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Zeng Y, Cao S, Li N, Tang J, Lin G. Identification of key lipid metabolism-related genes in Alzheimer's disease. Lipids Health Dis 2023; 22:155. [PMID: 37736681 PMCID: PMC10515010 DOI: 10.1186/s12944-023-01918-9] [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: 06/22/2023] [Accepted: 09/04/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) represents profound degenerative conditions of the brain that cause significant deterioration in memory and cognitive function. Despite extensive research on the significant contribution of lipid metabolism to AD progression, the precise mechanisms remain incompletely understood. Hence, this study aimed to identify key differentially expressed lipid metabolism-related genes (DELMRGs) in AD progression. METHODS Comprehensive analyses were performed to determine key DELMRGs in AD compared to controls in GSE122063 dataset from Gene Expression Omnibus. Additionally, the ssGSEA algorithm was utilized for estimating immune cell levels. Subsequently, correlations between key DELMRGs and each immune cell were calculated specifically in AD samples. The key DELMRGs expression levels were validated via two external datasets. Furthermore, gene set enrichment analysis (GSEA) was utilized for deriving associated pathways of key DELMRGs. Additionally, miRNA-TF regulatory networks of the key DELMRGs were constructed using the miRDB, NetworkAnalyst 3.0, and Cytoscape software. Finally, based on key DELMRGs, AD samples were further segmented into two subclusters via consensus clustering, and immune cell patterns and pathway differences between the two subclusters were examined. RESULTS Seventy up-regulated and 100 down-regulated DELMRGs were identified. Subsequently, three key DELMRGs (DLD, PLPP2, and PLAAT4) were determined utilizing three algorithms [(i) LASSO, (ii) SVM-RFE, and (iii) random forest]. Specifically, PLPP2 and PLAAT4 were up-regulated, while DLD exhibited downregulation in AD cerebral cortex tissue. This was validated in two separate external datasets (GSE132903 and GSE33000). The AD group exhibited significantly altered immune cell composition compared to controls. In addition, GSEA identified various pathways commonly associated with three key DELMRGs. Moreover, the regulatory network of miRNA-TF for key DELMRGs was established. Finally, significant differences in immune cell levels and several pathways were identified between the two subclusters. CONCLUSION This study identified DLD, PLPP2, and PLAAT4 as key DELMRGs in AD progression, providing novel insights for AD prevention/treatment.
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Affiliation(s)
- Youjie Zeng
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Si Cao
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Nannan Li
- Department of Nephrology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Juan Tang
- Department of Nephrology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
| | - Guoxin Lin
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
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Casey AE, Liu W, Hein LK, Sargeant TJ, Pederson SM, Mäkinen VP. Transcriptional targets of senataxin and E2 promoter binding factors are associated with neuro-degenerative pathways during increased autophagic flux. Sci Rep 2022; 12:17665. [PMID: 36271102 PMCID: PMC9587291 DOI: 10.1038/s41598-022-21617-2] [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: 06/07/2022] [Accepted: 09/29/2022] [Indexed: 01/18/2023] Open
Abstract
Autophagy is an intracellular recycling process that degrades harmful molecules and enables survival during starvation, with implications for diseases including dementia, cancer and atherosclerosis. Previous studies demonstrate how a limited number of transcription factors (TFs) can increase autophagy. However, this knowledge has not resulted in translation into therapy, thus, to gain understanding of more suitable targets, we utilized a systems biology approach. We induced autophagy by amino acid starvation and mTOR inhibition in HeLa, HEK 293 and SH-SY5Y cells and measured temporal gene expression using RNA-seq. We observed 456 differentially expressed genes due to starvation and 285 genes due to mTOR inhibition (PFDR < 0.05 in every cell line). Pathway analyses implicated Alzheimer's and Parkinson's diseases (PFDR ≤ 0.024 in SH-SY5Y and HeLa) and amyotrophic lateral sclerosis (ALS, PFDR < 0.05 in mTOR inhibition experiments). Differential expression of the Senataxin (SETX) target gene set was predicted to activate multiple neurodegenerative pathways (PFDR ≤ 0.04). In the SH-SY5Y cells of neuronal origin, the E2F transcription family was predicted to activate Alzheimer's disease pathway (PFDR ≤ 0.0065). These exploratory analyses suggest that SETX and E2F may mediate transcriptional regulation of autophagy and further investigations into their possible role in neuro-degeneration are warranted.
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Affiliation(s)
- Aaron E. Casey
- grid.430453.50000 0004 0565 2606Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000 Australia ,grid.1026.50000 0000 8994 5086Australian Centre for Precision Health, Cancer Research Institute, University of South Australia, Adelaide, Australia
| | - Wenjun Liu
- grid.1010.00000 0004 1936 7304Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia
| | - Leanne K. Hein
- grid.430453.50000 0004 0565 2606Lysosomal Health in Ageing, Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Timothy J. Sargeant
- grid.430453.50000 0004 0565 2606Lysosomal Health in Ageing, Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Stephen M. Pederson
- grid.1010.00000 0004 1936 7304Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia
| | - Ville-Petteri Mäkinen
- grid.430453.50000 0004 0565 2606Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000 Australia ,grid.1026.50000 0000 8994 5086Australian Centre for Precision Health, Cancer Research Institute, University of South Australia, Adelaide, Australia ,grid.10858.340000 0001 0941 4873Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland ,grid.10858.340000 0001 0941 4873Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
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