Molecular crosstalk between COVID-19 and Alzheimer’s disease using microarray and RNA-seq datasets: A system biology approach

Premkumar, T.; Lulu, Sajitha

doi:10.3389/fmed.2023.1151046

Cited by 10 publications

(7 citation statements)

References 92 publications

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“…Multiple neurodegenerative studies have been utilizing both microarray and RNA-seq analyses simultaneously, and they have isolated DEGs common to both methods of expression quantification [ 117 , 118 , 119 ]. For example, a systemic biological approach has also been adopted to integrate RNA-seq datasets for COVID-19 and microarray datasets for AD.…”

Section: Rna Based Microarray Gene Expression Analysismentioning

confidence: 99%

“…For example, a systemic biological approach has also been adopted to integrate RNA-seq datasets for COVID-19 and microarray datasets for AD. This was conducted in order to examine and identify the common transcriptional alterations between COVID-19 and AD patients [ 119 ]. This study identified 26 hub genes that could be potential biomarkers and therapeutic targets for COVID-19 patients with AD comorbidities.…”

Section: Rna Based Microarray Gene Expression Analysismentioning

confidence: 99%

“…Ad tionally, through network analysis, they found that genes IL1B, P2RX7, IFNB1, TNF, CASP1 enhanced the network connectivity between the combined gene sets of MS COVID-19, which is associated with NOD-like receptor signaling [116]. Multiple neurodegenerative studies have been utilizing both microarray and RN seq analyses simultaneously, and they have isolated DEGs common to both method expression quantification [117][118][119]. For example, a systemic biological approach has been adopted to integrate RNA-seq datasets for COVID-19 and microarray datasets AD.…”

Section: Admentioning

confidence: 99%

“…Together, these findings iden molecular signatures in PD patients' brain and blood for potential pathophysiologic prognostic importance, and these findings may potentially be applicable to other disea including AD and MS. Multiple neurodegenerative studies have been utilizing both microarray and RN seq analyses simultaneously, and they have isolated DEGs common to both method expression quantification [117][118][119]. For example, a systemic biological approach has been adopted to integrate RNA-seq datasets for COVID-19 and microarray datasets AD.…”

Section: Microarray Analysis Of Non-coding Rna (Mirna Circrna and Lnc...mentioning

confidence: 99%

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Data Mining of Microarray Datasets in Translational Neuroscience

O’Connor,

Zeng

et al. 2023

Brain Sciences

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Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

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Section: Rna Based Microarray Gene Expression Analysismentioning

confidence: 99%

Section: Rna Based Microarray Gene Expression Analysismentioning

confidence: 99%

Section: Admentioning

confidence: 99%

Section: Microarray Analysis Of Non-coding Rna (Mirna Circrna and Lnc...mentioning

confidence: 99%

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Data Mining of Microarray Datasets in Translational Neuroscience

O’Connor,

Zeng

et al. 2023

Brain Sciences

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“…Cav-1 might contribute to neuroinflammation in COVID-19. Strikingly, Cav-1 is upregulated in forebrains of COVID-19 decedents (Green et al, 2022; Premkumar and Sajitha Lulu, 2023). Transcellular BBB permeability is described in models of COVID-19 (Krasemann et al, 2022; Rhea et al, 2021; Zhang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Caveolin-1 mediates neuroinflammation and cognitive impairment in SARS-CoV-2 infection

Trevino,

Fogel,

Minshall

et al. 2023

Preprint

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Leukocyte infiltration of the CNS can contribute to neuroinflammation and cognitive impairment. Brain endothelial cells regulate adhesion, activation, and diapedesis of T cells across the blood-brain barrier (BBB) in inflammatory diseases. The integral membrane protein Caveolin-1 (Cav-1) critically regulates BBB permeability, but its influence on T cell CNS infiltration in respiratory viral infections is unknown. In this study, we sought to determine the role of Cav-1 at the BBB in neuroinflammation in a COVID-19 mouse model. We used mice genetically deficient in Cav-1 to test the role of this protein in T cell infiltration and cognitive impairment. We found that SARS-CoV-2 infection upregulated brain endothelial Cav-1. Moreover, SARS-CoV-2 infection increased brain endothelial cell vascular cell adhesion molecule-1 (VCAM-1) and CD3+ T cell infiltration of the hippocampus, a region important for short term learning and memory. Concordantly, we observed learning and memory deficits. Importantly, genetic deficiency in Cav-1 attenuated brain endothelial VCAM-1 expression and T cell infiltration in the hippocampus of mice with SARS-CoV-2 infection. Moreover, Cav-1 KO mice were protected from the learning and memory deficits caused by SARS-CoV-2 infection. These results indicate the importance of BBB permeability in COVID-19 neuroinflammation and suggest potential therapeutic value of targeting Cav-1 to improve disease outcomes.

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Parallel electrophysiological abnormalities due to COVID‐19 infection and to Alzheimer's disease and related dementia

Jiang,

Neal,

Sompol

et al. 2024

Alzheimer's & Dementia

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Many coronavirus disease 2019 (COVID‐19) positive individuals exhibit abnormal electroencephalographic (EEG) activity reflecting “brain fog” and mild cognitive impairments even months after the acute phase of infection. Resting‐state EEG abnormalities include EEG slowing (reduced alpha rhythm; increased slow waves) and epileptiform activity. An expert panel conducted a systematic review to present compelling evidence that cognitive deficits due to COVID‐19 and to Alzheimer's disease and related dementia (ADRD) are driven by overlapping pathologies and neurophysiological abnormalities. EEG abnormalities seen in COVID‐19 patients resemble those observed in early stages of neurodegenerative diseases, particularly ADRD. It is proposed that similar EEG abnormalities in Long COVID and ADRD are due to parallel neuroinflammation, astrocyte reactivity, hypoxia, and neurovascular injury. These neurophysiological abnormalities underpinning cognitive decline in COVID‐19 can be detected by routine EEG exams. Future research will explore the value of EEG monitoring of COVID‐19 patients for predicting long‐term outcomes and monitoring efficacy of therapeutic interventions.Highlights Abnormal intrinsic electrophysiological brain activity, such as slowing of EEG, reduced alpha wave, and epileptiform are characteristic findings in COVID‐19 patients. EEG abnormalities have the potential as neural biomarkers to identify neurological complications at the early stage of the disease, to assist clinical assessment, and to assess cognitive decline risk in Long COVID patients. Similar slowing of intrinsic brain activity to that of COVID‐19 patients is typically seen in patients with mild cognitive impairments, ADRD. Evidence presented supports the idea that cognitive deficits in Long COVID and ADRD are driven by overlapping neurophysiological abnormalities resulting, at least in part, from neuroinflammatory mechanisms and astrocyte reactivity. Identifying common biological mechanisms in Long COVID‐19 and ADRD can highlight critical pathologies underlying brain disorders and cognitive decline. It elucidates research questions regarding cognitive EEG and mild cognitive impairment in Long COVID that have not yet been adequately investigated.

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Molecular crosstalk between COVID-19 and Alzheimer’s disease using microarray and RNA-seq datasets: A system biology approach

Cited by 10 publications

References 92 publications

Data Mining of Microarray Datasets in Translational Neuroscience

Data Mining of Microarray Datasets in Translational Neuroscience

Caveolin-1 mediates neuroinflammation and cognitive impairment in SARS-CoV-2 infection

Parallel electrophysiological abnormalities due to COVID‐19 infection and to Alzheimer's disease and related dementia

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