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Adeoye T, Shah SI, Ullah G. Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585267. [PMID: 38559218 PMCID: PMC10980062 DOI: 10.1101/2024.03.15.585267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.
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Affiliation(s)
- Temitope Adeoye
- Department of Physics, University of South Florida, Tampa, FL 33620
| | - Syed I Shah
- Department of Physics, University of South Florida, Tampa, FL 33620
| | - Ghanim Ullah
- Department of Physics, University of South Florida, Tampa, FL 33620
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Chi H, Sun Y, Lin P, Zhou J, Zhang J, Yang Y, Qiao Y, Liu D. Glucose Fluctuation Inhibits Nrf2 Signaling Pathway in Hippocampal Tissues and Exacerbates Cognitive Impairment in Streptozotocin-Induced Diabetic Rats. J Diabetes Res 2024; 2024:5584761. [PMID: 38282656 PMCID: PMC10817812 DOI: 10.1155/2024/5584761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 12/25/2023] [Accepted: 01/09/2024] [Indexed: 01/30/2024] Open
Abstract
Background This research investigated whether glucose fluctuation (GF) can exacerbate cognitive impairment in streptozotocin-induced diabetic rats and explored the related mechanism. Methods After 4 weeks of feeding with diets containing high fats plus sugar, the rat model of diabetes mellitus (DM) was established by intraperitoneal injection of streptozotocin (STZ). Then, GF was triggered by means of alternating satiety and starvation for 24 h. The weight, blood glucose level, and water intake of the rats were recorded. The Morris water maze (MWM) test was carried out to appraise the cognitive function at the end of week 12. Moreover, the morphological structure of hippocampal neurons was viewed through HE and Nissl staining, and transmission electron microscopy (TEM) was performed for ultrastructure observation. The protein expression levels of Nrf2, HO-1, NQO-1, Bax, Bcl-2, and Caspase-3 in the hippocampal tissues of rats were measured via Western blotting, and the mRNA expressions of Nrf2, HO-1, and NQO-1 were examined using qRT-PCR. Finally, Western blotting and immunohistochemistry were conducted to detect BDNF levels. Results It was manifested that GF not only aggravated the impairment of spatial memory in rats with STZ-induced type 2 DM but also stimulated the loss, shrinkage, and apoptosis of hippocampal neurons. Regarding the expressions in murine hippocampal tissues, GF depressed Nrf2, HO-1, NQO-1, Bcl-2, and BDNF but boosted Caspase-3 and Bax. Conclusions GF aggravates cognitive impairment by inhibiting the Nrf2 signaling pathway and inducing oxidative stress and apoptosis in the hippocampal tissues.
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Affiliation(s)
- Haiyan Chi
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Department of Endocrinology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, Shandong, China
| | - Yujing Sun
- Department of Traditional Chinese Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Peng Lin
- Department of Traditional Chinese Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Junyu Zhou
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Jinbiao Zhang
- Department of Neurology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, Shandong, China
| | - Yachao Yang
- Department of Endocrinology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, Shandong, China
| | - Yun Qiao
- Department of Traditional Chinese Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Deshan Liu
- Department of Traditional Chinese Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
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van Sleen Y, Shetty SA, van der Heiden M, Venema MCA, Gutiérrez-Melo N, Toonen EJM, van Beek J, Buisman AM, van Baarle D, Sauce D. Frailty is related to serum inflammageing markers: results from the VITAL study. Immun Ageing 2023; 20:68. [PMID: 38012652 PMCID: PMC10680197 DOI: 10.1186/s12979-023-00391-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 11/08/2023] [Indexed: 11/29/2023]
Abstract
Frailty describes an age-associated state in individuals with an increased vulnerability and less resilience against adverse outcomes. To score frailty, studies have employed the questionnaires, such as the SF-36 and EQ-5D-3L, or the Frailty Index, a composite score based on deficit accumulation. Furthermore, ageing of the immune system is often accompanied by a state of low-grade inflammation (inflammageing). Here, we aimed to associate 29 circulating markers of inflammageing with frailty measures in a prospective cohort study to understand the mechanisms underlying ageing.Frailty measures and inflammageing markers were assessed in 317 participants aged 25-90. We determined four different measures of frailty: the Frailty Index based on 31 deficits, the EQ-5D-3L and two physical domains of the SF-36. Serum/plasma levels of inflammageing markers and CMV/EBV seropositivity were measured using different techniques: Quanterix, Luminex or ELISA.All four measures of frailty strongly correlated with age and BMI. Nineteen biomarkers correlated with age, some in a linear fashion (IL-6, YKL-40), some only in the oldest age brackets (CRP), and some increased at younger ages and then plateaued (CCL2, sIL-6R). After correcting for age, biomarkers, such as IL-6, CRP, IL-1RA, YKL-40 and elastase, were associated with frailty. When corrected for BMI, the number of associations reduced further.In conclusion, inflammageing markers, particularly markers reflecting innate immune activation, are related to frailty. These findings indicate that health decline and the accumulation of deficits with age is accompanied with a low-grade inflammation which can be detected by specific inflammatory markers.
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Affiliation(s)
| | | | | | | | - Nicolas Gutiérrez-Melo
- Sorbonne Université, INSERM, Centre d'Immunologie Et Des Maladies Infectieuses, Cimi-Paris, 75013, Paris, France
| | | | - Josine van Beek
- Center of Infectious Diseases Control, National Institute of Public Health and the Environment, Bilthoven, Netherlands
| | - Anne-Marie Buisman
- Center of Infectious Diseases Control, National Institute of Public Health and the Environment, Bilthoven, Netherlands
| | | | - Delphine Sauce
- Sorbonne Université, INSERM, Centre d'Immunologie Et Des Maladies Infectieuses, Cimi-Paris, 75013, Paris, France
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van der Ende EL, In ‘t Veld SGJG, Hanskamp I, van der Lee S, Dijkstra JIR, Hok-A-Hin YS, Blujdea ER, van Swieten JC, Irwin DJ, Chen-Plotkin A, Hu WT, Lemstra AW, Pijnenburg YAL, van der Flier WM, del Campo M, Teunissen CE, Vermunt L. CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease. Brain 2023; 146:4495-4507. [PMID: 37348871 PMCID: PMC10629764 DOI: 10.1093/brain/awad213] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/24/2023] Open
Abstract
Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.
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Affiliation(s)
- Emma L van der Ende
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Sjors G J G In ‘t Veld
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Iris Hanskamp
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Sven van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Janna I R Dijkstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Yanaika S Hok-A-Hin
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Elena R Blujdea
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - John C van Swieten
- Alzheimer Center and Department of Neurology, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William T Hu
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30307, USA
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Marta del Campo
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, 28003 Madrid, Spain
- Barcelonabeta Brain Research Center (BBRC), Pasqual Maragall Foundation, 08005 Barcelona, Spain
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Lisa Vermunt
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
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Russo C, Valle MS, Casabona A, Malaguarnera L. Chitinase Signature in the Plasticity of Neurodegenerative Diseases. Int J Mol Sci 2023; 24:ijms24076301. [PMID: 37047273 PMCID: PMC10094409 DOI: 10.3390/ijms24076301] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 03/30/2023] Open
Abstract
Several reports have pointed out that Chitinases are expressed and secreted by various cell types of central nervous system (CNS), including activated microglia and astrocytes. These cells play a key role in neuroinflammation and in the pathogenesis of many neurodegenerative disorders. Increased levels of Chitinases, in particular Chitotriosidase (CHIT-1) and chitinase-3-like protein 1 (CHI3L1), have been found increased in several neurodegenerative disorders. Although having important biological roles in inflammation, to date, the molecular mechanisms of Chitinase involvement in the pathogenesis of neurodegenerative disorders is not well-elucidated. Several studies showed that some Chitinases could be assumed as markers for diagnosis, prognosis, activity, and severity of a disease and therefore can be helpful in the choice of treatment. However, some studies showed controversial results. This review will discuss the potential of Chitinases in the pathogenesis of some neurodegenerative disorders, such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and multiple sclerosis, to understand their role as distinctive biomarkers of neuronal cell activity during neuroinflammatory processes. Knowledge of the role of Chitinases in neuronal cell activation could allow for the development of new methodologies for downregulating neuroinflammation and consequently for diminishing negative neurological disease outcomes.
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Affiliation(s)
- Cristina Russo
- Section of Pathology, Department of Biomedical and Biotechnological Sciences, School of Medicine, University of Catania, 95123 Catania, Italy
| | - Maria Stella Valle
- Laboratory of Neuro-Biomechanics, Section of Physiology, Department of Biomedical and Biotechnological Sciences, School of Medicine, University of Catania, 95123 Catania, Italy
- Correspondence:
| | - Antonino Casabona
- Laboratory of Neuro-Biomechanics, Section of Physiology, Department of Biomedical and Biotechnological Sciences, School of Medicine, University of Catania, 95123 Catania, Italy
| | - Lucia Malaguarnera
- Section of Pathology, Department of Biomedical and Biotechnological Sciences, School of Medicine, University of Catania, 95123 Catania, Italy
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