From Viral Infections to Alzheimer's Disease: Unveiling the Mechanistic Links Through Systems Bioinformatics.

BACKGROUND: Emerging evidence suggests that viral infections may contribute to Alzheimer's disease (AD) onset and/or progression. However, the extent of their involvement and the mechanisms through which specific viruses increase AD susceptibility risk remain elusive. METHODS: We used an integrative systems bioinformatics approach to identify viral-mediated pathogenic mechanisms, by which Herpes Simplex Virus 1 (HSV-1), Human Cytomegalovirus (HCMV), Epstein-Barr virus (EBV), Kaposi Sarcoma-associated Herpesvirus (KSHV), Hepatitis B Virus (HBV), Hepatitis C Virus (HCV), Influenza A Virus (IAV) and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) could facilitate AD pathogenesis via virus-host protein-protein interactions (PPIs). We also explored potential synergistic pathogenic effects resulting from herpesvirus reactivation (HSV-1, HCMV, and EBV) during acute SARS-CoV-2 infection, potentially increasing AD susceptibility. RESULTS: Herpesviridae members (HSV-1, EBV, KSHV, HCMV) impact AD-related processes like amyloid-ß (Aß) formation, neuronal death, and autophagy. Hepatitis viruses (HBV, HCV) influence processes crucial for cellular homeostasis and dysfunction, they also affect microglia activation via virus-host PPIs. Reactivation of HCMV during SARS-CoV-2 infection could potentially foster a lethal interplay of neurodegeneration, via synergistic pathogenic effects on AD-related processes like response to unfolded protein, regulation of autophagy, response to oxidative stress, and Aß formation. CONCLUSIONS: These findings underscore the complex link between viral infections and AD development. Viruses impact AD-related processes through shared and distinct mechanisms, potentially influencing variations in AD susceptibility.

Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches.

During the course of a viral infection, virus-host protein-protein interactions (PPIs) play a critical role in allowing viruses to replicate and survive within the host. These interspecies molecular interactions can lead to viral-mediated perturbations of the human interactome causing the generation of various complex diseases. Evidences suggest that viral-mediated perturbations are a possible pathogenic etiology in several neurodegenerative diseases (NDs). These diseases are characterized by chronic progressive degeneration of neurons, and current therapeutic approaches provide only mild symptomatic relief; therefore, there is unmet need for the discovery of novel therapeutic interventions. In this paper, we initially review databases and tools that can be utilized to investigate viral-mediated perturbations in complex NDs using network-based analysis by examining the interaction between the ND-related PPI disease networks and the virus-host PPI network. Afterwards, we present our theoretical-driven integrative network-based bioinformatics approach that accounts for pathogen-genes-disease-related PPIs with the aim to identify viral-mediated pathogenic mechanisms focusing in multiple sclerosis (MS) disease. We identified seven high centrality nodes that can act as disease communicator nodes and exert systemic effects in the MS-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways network. In addition, we identified 12 KEGG pathways, 5 Reactome pathways and 52 Gene Ontology Immune System Processes by which 80 viral proteins from eight viral species might exert viral-mediated pathogenic mechanisms in MS. Finally, our analysis highlighted the Th17 differentiation pathway, a disease communicator node and part of the 12 underlined KEGG pathways, as a key viral-mediated pathogenic mechanism and a possible therapeutic target for MS disease.

Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for coronavirus disease 2019 (COVID-19). Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs. Our approach resulted in a highly informed integrated drug shortlist by combining structural diversity filtering along with experts' curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src tyrosine kinase (bosutinib, dasatinib, cytarabine and saracatinib), which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflammatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action. Overall, this multiplex drug repurposing approach, developed and utilized herein specifically for SARS-CoV-2, can offer a rapid mapping and drug prioritization against any pathogen-related disease.

One path, two solutions: Network-based analysis identifies targetable pathways for the treatment of comorbid type II diabetes and neuropsychiatric disorders.

Comorbid diseases complicate patient outcomes and escalate healthcare costs, necessitating the need for a deeper mechanistic understanding. Neuropsychiatric disorders (NPDs) such as Neurotic Disorder, Major Depression, Bipolar Disorder, Anxiety Disorder, and Schizophrenia significantly exacerbate Type 2 Diabetes Mellitus (DM2), often leading to suboptimal treatment outcomes. The neurobiological mechanisms underlying this comorbidity remain poorly understood. To address this gap, we developed a novel pathway-based network computational framework to identify critical shared disease mechanisms between DM2 and these five prevalent comorbid NPDs. Our approach involves reconstructing an integrated DM2 âˆ© NPDs KEGG pathway-pathway network and employs two complementary analytical methods, including the "minimum path to comorbidity" method to identify the shortest path fostering comorbid development. This analysis uncovered shared pathways like the PI3K-Akt signaling pathway and highlighted key nodes such as calcium signaling, MAPK, estrogen signaling, and apoptosis pathways. Dysregulation of these pathways likely contributes to the development of DM2-NPDs comorbidity. These findings have significant clinical implications, as they identify promising therapeutic targets that could lead to more effective treatments addressing both DM2 and NPDs simultaneously. Our model not only elucidates the intricate molecular interactions driving this comorbidity but also identifies promising therapeutic targets, paving the way for innovative treatment strategies. Additionally, the framework developed in this study can be adapted to study other complex comorbid conditions, advancing personalized medicine for comorbidities and improving patient care.

Molecular signatures of premature aging in Major Depression and Substance Use Disorders.

Major depressive disorder (MDD) and substance-use disorders (SUDs) often lead to premature aging, increasing vulnerability to cognitive decline and other forms of dementia. This study utilized advanced systems bioinformatics to identify aging "signatures" in MDD and SUDs and evaluated the potential for known lifespan-extending drugs to target and reverse these signatures. The results suggest that inhibiting the transcriptional activation of FOS gene family members holds promise in mitigating premature aging in MDD and SUDs. Conversely, antidepressant drugs activating the PI3K/Akt/mTOR pathway, a common mechanism in rapid-acting antidepressants, may accelerate aging in MDD patients, making them unsuitable for those with comorbid aging-related conditions like dementia and Alzheimer's disease. Additionally, this innovative approach identifies potential anti-aging interventions for MDD patients, such as Deferoxamine, Resveratrol, Estradiol valerate, and natural compounds like zinc acetate, genistein, and ascorbic acid, regardless of comorbid anxiety disorders. These findings illuminate the premature aging effects of MDD and SUDs and offer insights into treatment strategies for patients with comorbid aging-related conditions, including dementia and Alzheimer's disease.

The impact of estradiol on serotonin, glutamate, and dopamine systems.

Estradiol, the most potent and prevalent member of the estrogen class of steroid hormones and is expressed in both sexes. Functioning as a neuroactive steroid, it plays a crucial role in modulating neurotransmitter systems affecting neuronal circuits and brain functions including learning and memory, reward and sexual behaviors. These neurotransmitter systems encompass the serotonergic, dopaminergic, and glutamatergic signaling pathways. Consequently, this review examines the pivotal role of estradiol and its receptors in the regulation of these neurotransmitter systems in the brain. Through a comprehensive analysis of current literature, we investigate the multifaceted effects of estradiol on key neurotransmitter signaling systems, namely serotonin, dopamine, and glutamate. Findings from rodent models illuminate the impact of hormone manipulations, such as gonadectomy, on the regulation of neuronal brain circuits, providing valuable insights into the connection between hormonal fluctuations and neurotransmitter regulation. Estradiol exerts its effects by binding to three estrogen receptors: estrogen receptor alpha (ERα), estrogen receptor beta (ERß), and G protein-coupled receptor (GPER). Thus, this review explores the promising outcomes observed with estradiol and estrogen receptor agonists administration in both gonadectomized and/or genetically knockout rodents, suggesting potential therapeutic avenues. Despite limited human studies on this topic, the findings underscore the significance of translational research in bridging the gap between preclinical findings and clinical applications. This approach offers valuable insights into the complex relationship between estradiol and neurotransmitter systems. The integration of evidence from neurotransmitter systems and receptor-specific effects not only enhances our understanding of the neurobiological basis of physiological brain functioning but also provides a comprehensive framework for the understanding of possible pathophysiological mechanisms resulting to disease states. By unraveling the complexities of estradiol's impact on neurotransmitter regulation, this review contributes to advancing the field and lays the groundwork for future research aimed at refining understanding of the relationship between estradiol and neuronal circuits as well as their involvement in brain disorders.

Transcriptomic analysis reveals sex-specific patterns in the hippocampus in Alzheimer's disease.

Background: The hippocampus, vital for memory and learning, is among the first brain regions affected in Alzheimer's Disease (AD) and exhibits adult neurogenesis. Women face twice the risk of developing AD compare to men, making it crucial to understand sex differences in hippocampal function for comprehending AD susceptibility. Methods: We conducted a comprehensive analysis of bulk mRNA postmortem samples from the whole hippocampus (GSE48350, GSE5281) and its CA1 and CA3 subfields (GSE29378). Our aim was to perform a comparative molecular signatures analysis, investigating sex-specific differences and similarities in the hippocampus and its subfields in AD. This involved comparing the gene expression profiles among: (a) male controls (M-controls) vs. female controls (F-controls), (b) females with AD (F-AD) vs. F-controls, (c) males with AD (M-AD) vs. M-controls, and (d) M-AD vs. F-AD. Furthermore, we identified AD susceptibility genes interacting with key targets of menopause hormone replacement drugs, specifically the ESR1 and ESR2 genes, along with GPER1. Results: The hippocampal analysis revealed contrasting patterns between M-AD vs. M-controls and F-AD vs. F-controls, as well as M-controls vs. F-controls. Notably, BACE1, a key enzyme linked to amyloid-beta production in AD pathology, was found to be upregulated in M-controls compared to F-controls in both CA1 and CA3 hippocampal subfields. In M-AD vs. M-controls, the GABAergic synapse was downregulated, and the Estrogen signaling pathway was upregulated in both subfields, unlike in F-AD vs. F-controls. Analysis of the whole hippocampus also revealed upregulation of the GABAergic synapse in F-AD vs. F-controls. While direct comparison of M-AD vs. F-AD, revealed a small upregulation of the ESR1 gene in the CA1 subfield of males. Conversely, F-AD vs. F-controls exhibited downregulation of the Dopaminergic synapse in both subfields, while the Calcium signaling pathway showed mixed regulation, being upregulated in CA1 but downregulated in CA3, unlike in M-AD vs. M-controls. The upregulated Estrogen signaling pathway in M-AD, suggests a compensatory response to neurodegenerative specifically in males with AD. Our results also identified potential susceptibility genes interacting with ESR1 and ESR2, including MAPK1, IGF1, AKT1, TP53 and CD44. Conclusion: These findings underscore the importance of sex-specific disease mechanisms in AD pathogenesis. Region-specific analysis offers a more detailed examination of localized changes in the hippocampus, enabling to capture sex-specific molecular patterns in AD susceptibility and progression.

Role of group II metabotropic glutamate receptors in ketamine's antidepressant actions.

Major Depressive Disorder (MDD) is a serious neuropsychiatric disorder afflicting around 16-17 % of the global population and is accompanied by recurrent episodes of low mood, hopelessness and suicidal thoughts. Current pharmacological interventions take several weeks to even months for an improvement in depressive symptoms to emerge, with a significant percentage of individuals not responding to these medications at all, thus highlighting the need for rapid and effective next-generation treatments for MDD. Pre-clinical studies in animals have demonstrated that antagonists of the metabotropic glutamate receptor subtype 2/3 (mGlu2/3 receptor) exert rapid antidepressant-like effects, comparable to the actions of ketamine. Therefore, it is possible that mGlu2 or mGlu3 receptors to have a regulatory role on the unique antidepressant properties of ketamine, or that convergent intracellular mechanisms exist between mGlu2/3 receptor signaling and ketamine's effects. Here, we provide a comprehensive and critical evaluation of the literature on these convergent processes underlying the antidepressant action of mGlu2/3 receptor inhibitors and ketamine. Importantly, combining sub-threshold doses of mGlu2/3 receptor inhibitors with sub-antidepressant ketamine doses induce synergistic antidepressant-relevant behavioral effects. We review the evidence supporting these combinatorial effects since sub-effective dosages of mGlu2/3 receptor antagonists and ketamine could reduce the risk for the emergence of significant adverse events compared with taking normal dosages. Overall, deconvolution of ketamine's pharmacological targets will give critical insights to influence the development of next-generation antidepressant treatments with rapid actions.

Unraveling the transcriptomic signatures of Parkinson's disease and major depression using single-cell and bulk data.

Background: Motor symptoms are well-characterized in Parkinson's disease (PD). However, non-motor symptoms, such as depression, are commonly observed and can appear up to 10 years before motor features, resulting in one-third of individuals being misdiagnosed with a neuropsychiatric disorder. Thus, identifying diagnostic biomarkers is crucial for accurate PD diagnosis during its prodromal or early stages. Methods: We employed an integrative approach, combining single nucleus RNA and bulk mRNA transcriptomics to perform comparative molecular signatures analysis between PD and major depressive disorder (MDD). We examined 39,834 nuclei from PD (GSE202210) and 32,707 nuclei from MDD (GSE144136) in the dorsolateral prefrontal cortex (dlPFC) of Brodmann area 9. Additionally, we analyzed bulk mRNA peripheral blood samples from PD compared to controls (GSE49126, GSE72267), as well as MDD compared to controls (GSE39653). Results: Our findings show a higher proportion of astrocytes, and oligodendrocyte cells in the dlPFC of individuals with PD vs. MDD. The excitatory to inhibitory neurons (E/I) ratio analysis indicates that MDD has a ratio close to normal 80/20, while PD has a ratio of 62/38, indicating increased inhibition in the dlPFC. Microglia displayed the most pronounced differences in gene expression profiles between the two conditions. In PD, microglia display a pro-inflammatory phenotype, while in MDD, they regulate synaptic transmission through oligodendrocyte-microglia crosstalk. Analysis of bulk mRNA blood samples revealed that the COL5A, MID1, ZNF148, and CD22 genes were highly expressed in PD, whereas the DENR and RNU1G2 genes were highly expressed in MDD. CD22 is involved in B-cell activation and the negative regulation of B-cell receptor signaling. Additionally, CD86, which provides co-stimulatory signals for T-cell activation and survival, was found to be a commonly differentially expressed gene in both conditions. Pathway analysis revealed several immune-related pathways common in both conditions, including the complement and coagulation cascade, and B-cell receptor signaling. Discussion: This study demonstrates that bulk peripheral immune cells play a role in both conditions, but neuroinflammation in the dlPFC specifically manifests in PD as evidenced by the analysis of single nucleus dlPFC datasets. Integrating these two omics levels offers a better understanding of the shared and distinct molecular pathophysiology of PD and MDD in both the periphery and the brain. These findings could lead to potential diagnostic biomarkers, improving accuracy and guiding pharmacological treatments.

Immunomodulatory effects of microbiota-derived metabolites at the crossroad of neurodegenerative diseases and viral infection: network-based bioinformatics insights.

Bidirectional cross-talk between commensal microbiota and the immune system is essential for the regulation of immune responses and the formation of immunological memory. Perturbations of microbiome-immune system interactions can lead to dysregulated immune responses against invading pathogens and/or to the loss of self-tolerance, leading to systemic inflammation and genesis of several immune-mediated pathologies, including neurodegeneration. In this paper, we first investigated the contribution of the immunomodulatory effects of microbiota (bacteria and fungi) in shaping immune responses and influencing the formation of immunological memory cells using a network-based bioinformatics approach. In addition, we investigated the possible role of microbiota-host-immune system interactions and of microbiota-virus interactions in a group of neurodegenerative diseases (NDs): Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Parkinson's disease (PD) and Alzheimer's disease (AD). Our analysis highlighted various aspects of the innate and adaptive immune response systems that can be modulated by microbiota, including the activation and maturation of microglia which are implicated in the development of NDs. It also led to the identification of specific microbiota components which might be able to influence immune system processes (ISPs) involved in the pathogenesis of NDs. In addition, it indicated that the impact of microbiota-derived metabolites in influencing disease-associated ISPs, is higher in MS disease, than in AD, PD and ALS suggesting a more important role of microbiota mediated-immune effects in MS.

Systems Bioinformatics Reveals Possible Relationship between COVID-19 and the Development of Neurological Diseases and Neuropsychiatric Disorders.

Coronavirus Disease 2019 (COVID-19) is associated with increased incidence of neurological diseases and neuropsychiatric disorders after infection, but how it contributes to their development remains under investigation. Here, we investigate the possible relationship between COVID-19 and the development of ten neurological disorders and three neuropsychiatric disorders by exploring two pathological mechanisms: (i) dysregulation of host biological processes via virus-host protein-protein interactions (PPIs), and (ii) autoreactivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epitopes with host "self" proteins via molecular mimicry. We also identify potential genetic risk factors which in combination with SARS-CoV-2 infection might lead to disease development. Our analysis indicated that neurodegenerative diseases (NDs) have a higher number of disease-associated biological processes that can be modulated by SARS-CoV-2 via virus-host PPIs than neuropsychiatric disorders. The sequence similarity analysis indicated the presence of several matching 5-mer and/or 6-mer linear motifs between SARS-CoV-2 epitopes with autoreactive epitopes found in Alzheimer's Disease (AD), Parkinson's Disease (PD), Myasthenia Gravis (MG) and Multiple Sclerosis (MS). The results include autoreactive epitopes that recognize amyloid-beta precursor protein (APP), microtubule-associated protein tau (MAPT), acetylcholine receptors, glial fibrillary acidic protein (GFAP), neurofilament light polypeptide (NfL) and major myelin proteins. Altogether, our results suggest that there might be an increased risk for the development of NDs after COVID-19 both via autoreactivity and virus-host PPIs.