Biology subjects

Onisiforou, A.

Publications and source records attributed to Onisiforou, A..

10 recordsLinked to original sources

bioRxiv2026

Endothelial gain of PIEZO/TRPV mechanosensors drives cavernous malformations

Vascular disease often begins as a failure to read mechanical force. Cerebral cavernous malformations (CCMs) are leaky, brain-invading capillary clusters that cause stroke and seizures and arise from endothelial loss of the CCM complex. They form exclusively in low-flow vessels but existing models cannot explain this selectivity. We previously established that CCM-mutant endothelium inverts its adhesive balance, weakening cell-cell junctions while building matrix-degrading adhesions. The mechanosensors imposing this switch are unknown. Here we show that the mechanosensitive Ca2+ channels PIEZO1, TRPV2 and TRPV4 are overexpressed in the endothelium of CCM lesions in a 42-patient cohort, and that lesion volume scales with their expression level. Mechanistically, PIEZO1 partners with TRPV4 to destabilise cell-cell junctions and with TRPV2 to reinforce cell-matrix adhesions; silencing TRPV4 restores junctional integrity and abolishes KLF4 induction, whereas silencing TRPV2 or inhibition with tranilast abolishes matrix degradation and invasion. In vivo, trpv4 knockdown or inhibition with GSK2798745 restores atrioventricular canal morphogenesis in ccm2-mutant zebrafish. Gain of mechanosensory channel function is thus a causal step in CCM pathogenesis, upstream of the KLF program. Combined therapeutic targeting of TRPV2 and TRPV4 with inhibitors validated in humans offers a route to therapy.

cell biology↗

bioRxiv2026

Ethanol withdrawal induces temporally distinct alterations in oxytocinergic, opioidergic, glutamatergic and neuroimmune systems associated with recognition memory deficits

Alcohol use disorder is associated with persistent neuroadaptations and cognitive impairments, particularly during withdrawal, yet the temporal dynamics and interactions between these processes remain poorly understood. In the present study, we investigated time-dependent alterations in the oxytocin receptor (OTR), -opioid receptor (MOPr), metabotropic glutamate receptor 5 (mGlu5R), and translocator protein (TSPO) following chronic ethanol exposure and withdrawal, and their relationship to behavioral impairments. Male C57BL/6J mice were exposed to a 10-day escalating-dose ethanol liquid diet paradigm followed by 1, 4, or 7 days of withdrawal. Motor coordination and recognition memory were assessed using rotarod and novel object recognition tests, and receptor binding was quantified using autoradiography across multiple brain regions. Chronic ethanol exposure induced motor deficits that persisted during early withdrawal, whereas recognition memory impairments emerged after 7 days of withdrawal. Ethanol exposure and withdrawal produced region- and time-dependent alterations across all systems examined, with increased OTR binding in septal regions and transient reductions in basomedial amygdala OTR binding during intermediate withdrawal that normalized following prolonged withdrawal, transient increases in MOPr binding in striatal regions at 4 days of withdrawal, increased mGlu5R binding in the nucleus accumbens core, basolateral amygdala, and hippocampus, and early transient increases in TSPO binding indicative of neuroimmune activation. Notably, mGlu5R binding in the caudate-putamen and amygdala was associated with recognition memory deficits in a withdrawal stage-dependent manner. Bioinformatic analysis of human postmortem hippocampal transcriptomic datasets from individuals with alcohol use disorder revealed no consistent changes in GRM5 expression, suggesting that mGlu5R dysregulation may be driven by post-transcriptional mechanisms. These findings demonstrate that ethanol withdrawal is characterized by temporally distinct neuroadaptations across multiple systems and identify mGlu5R as a key correlate of withdrawal-associated memory impairment, highlighting its potential as a translational therapeutic target.

pharmacology and toxicology↗

bioRxiv2025

VirTarget: Virus-Informed Pharmacogenomics Framework Identifies Immunotherapies That Mitigate Epstein-Barr Virus-Driven Dysregulation in Multiple Sclerosis

BackgroundEpstein-Barr virus (EBV) is increasingly recognized as a central driver of multiple sclerosis (MS), yet current immunotherapies are selected without regard to their effects on EBV or EBV-MS genetic interactions. To address this gap, we developed VirTarget, the first virus-informed pharmacogenomics network framework that systematically evaluates approved MS immunotherapies with respect to EBV-driven pathogenesis and host genetic susceptibility risk. MethodsVirTarget integrates three complementary layers: (1) EBV-host interactomics, mapping viral-host protein- protein interactions within MS-relevant pathways; (2) host genetic susceptibility, linking MS-associated variants to EBV-targeted, therapy-modulated networks; and (3) transcriptomics directionality analysis, contrasting drug signatures with the convergent MS-EBV transcriptomic signature to classify therapies as reinforcers or reversers. ResultsNetwork analysis revealed substantial heterogeneity among therapies. Dimethyl fumarate showed the strongest and broadest engagement with the MS-EBV network, followed by natalizumab and interferons, while anti-CD20 antibodies and S1P modulators exerted the weakest effects. Genetic mapping highlighted convergence on key risk genes (HLA-DRB1, IL7R, IL2RA, CD40, TYR) directly targeted by EBV proteins within therapy-modulated pathways. Transcriptomic profiling stratified therapies into reinforcers (e.g., dimethyl fumarate, fingolimod, dexamethasone, interferon-{beta}1b) and reversers (e.g., prednisolone, cladribine, interferon-{beta}1a, rituximab), reflecting opposing influences on the MS{cap}EBV signature. Notably, multiple therapies reversed EBV-driven dysregulation of cytokine and innate immune pathways, suggesting their benefits extend in counteracting viral-mediated modulation of immune processes. ConclusionVirTarget provides the first systems-level, virus-informed comparative map of how MS immunotherapies engage with the MS-EBV network, intersect with MS genetic susceptibility risk, and modulate both MS- and EBV-related transcriptomic signatures. By revealing drug-specific patterns of viral pathway engagement and genetic convergence, this framework establishes a foundation for precision treatment strategies in MS, where therapeutic selection is informed by viral serostatus, host genetics, and system-level transcriptomic responses.

bioinformatics↗

bioRxiv2025

VirTrack: A Framework for Inferring Viral Influence on Disease-Associated Transcriptomes -- Clinical Type-Specific Epstein-Barr Virus Pathogenesis in Multiple Sclerosis

BackgroundEpstein-Barr virus (EBV) is strongly implicated in Multiple Sclerosis (MS), but how its influence varies across MS clinical types remains unclear. MethodsWe developed VirTrack, a computational framework that integrates experimentally validated EBV-host protein-protein interactions (PPIs) with clinical type-specific peripheral blood transcriptomes from Clinically Isolated Syndrome (CIS), Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), and Primary Progressive MS (PPMS) (GSE136411). VirTrack (i) anchors viral interactions in differentially expressed genes (DEGs), (ii) ranks EBV targeting of DEGs and host hubs, and (iii) applies machine learning- based clustering to identify clinical type-specific functional pathways influenced by EBV. ResultsEBV engagement was clinical type-dependent. In early MS (CIS and RRMS), EBV targeted approximately 13-18% of dysregulated genes, enriching for B-cell-related processes, Toll-like receptor signaling, and infection-like inflammatory pathways, while suppressing antiviral and NF-{kappa}B responses. Progressive clinical types exhibited fewer viral connections but distinct mechanistic shifts: SPMS was characterized by suppression of vascular and cardiac repair-associated pathways, whereas PPMS was dominated by upregulation of vacuolar and lysosomal remodeling processes. Hub analyses revealed a stable core of influential EBV proteins, EBNA-LP (consistently top-ranked), BZLF1, BVLF1, LMP2, and BDLF4, while BNLF2A showed broad but less hub-focused targeting and LMP1 ranked low across types. ConclusionEBV shapes MS through dynamic, clinical type-specific perturbations, driving strong immunomodulation in early disease and selective cellular remodeling during progressive types. VirTrack identifies key viral proteins and host pathways for stage-tailored therapeutic targeting, supporting early EBV-directed interventions and revealing potential links to vascular comorbidity in progressive MS types. More broadly, VirTrack offers a generalizable, systems-level framework for elucidating viral contributions across complex human diseases.

bioinformatics↗

bioRxiv2025

Selective transcriptomic recovery by (2R,6R)-hydroxynorketamine in opioid-abstinent mice: Machine learning identifies predictive biomarkers

BackgroundOpioid abstinence induces persistent emotional disturbances and widespread neuroplastic changes, in areas of the brain including the hippocampus. Although ketamine and its metabolite (2R,6R)-hydroxynorketamine (HNK) show potential in reversing opioid abstinence-related deficits in rodents, the molecular mechanisms underlying their efficacy remain poorly understood. MethodsMale C57BL/6J mice underwent a 3-week opioid abstinence paradigm, followed by a single (2R,6R)-HNK (10 mg/kg, i.p.) or saline injection on day 28. Sucrose and social preference tests were used to assess behavioral deficits. We conducted RNA sequencing of ventral hippocampal tissue from these mice, followed by differential gene expression and functional enrichment analyses. Additionally, Random Forest machine was applied to identify predictive differentially expressed genes (DEGs) associated with (2R,6R)-HNK treatment response. ResultsTranscriptomic analysis identified 206 DEGs in morphine-abstinent mice without treatment compared to opioid-naive controls (MOR-SAL vs. SAL-SAL), implicating altered immune signaling, synaptic function, and structural plasticity. Comparison of opioid-abstinent mice treated with (2R,6R)-HNK to opioid-naive controls (MOR-HNK vs. SAL-SAL) revealed 186 residual DEGs, enriched for Th17-mediated immune and fear regulation pathways, suggesting a persistent intermediate molecular phenotype despite normalized behavioural scores. DEGs overlap analysis between MOR-HNK vs. MOR-SAL and MOR-SAL vs. SAL-SAL indicated that (2R,6R)-HNK treatment reversed 55 DEGs in opioid-abstinent mice, including Transthyretin (Ttr) and T-cell surface glycoprotein (Cd5) expression levels. Machine learning identified interleukin 1 receptor accessory protein-like 1 (Il1rapl1) and cytotoxic T lymphocyte-associated protein 2 beta (Ctla2b) as top predictors of (2R,6R)-HNKs treatment response. Notably, while (2R,6R)-HNK induces transcriptional changes in opioid-naive mice (SAL-HNK), it does not affect behavior compared to untreated controls (SAL-SAL). In contrast, its therapeutic effects are evident in morphine-abstinent mice (MOR-HNK), highlighting its context-dependent efficacy. Conclusion(2R,6R)-HNK promotes both transcriptional and behavioral recovery in opioid-abstinent mice, reversing key gene expression changes. However, persistent dysregulation of neuroimmune and emotion-related pathways suggests an intermediate molecular state, reflecting ongoing recovery.

neuroscience↗

bioRxiv2025

Metformin Shows Greater Potential Than Semaglutide in Reducing Alzheimer's Risk in Diabetes Type II via Dual Actions: Tackling Disease Pathways and Environmental Herpesvirus Triggers

Alzheimers disease (AD) and Diabetes Mellitus Type II (DM2) share overlapping pathological mechanisms, with DM2 increasing AD risk. Disease-modifying therapies (DMTs) for DM2, including Metformin and Semaglutide, have been explored for neuroprotection, yet their efficacy in AD remains unclear. Here, we introduce a novel integrative framework combining comparative network pharmacology, Mendelian Randomization (MR), and transcriptomic validation to systematically assess the therapeutic impact of 39 DM2 DMTs in preventing AD in DM2. Metformin emerged as the top-ranked therapy, whereas Semaglutide ranked among the least effective based on comparative analysis within the DM2-AD pathway-pathway comorbidity network. Notably, a two-sample MR analysis finds no evidence supporting a genetic liability to either drug being associated with AD risk, suggesting that their benefits may arise through non-direct mechanisms or that their relationship could be confounded by third factors. Metformins neuroprotective impact is mediated through AMPK, insulin, and adipocytokine signaling, which regulate key AD-related processes. Additionally, Metformin may indirectly affect herpesviruses, emerging environmental contributors to AD, potentially enhancing its neuroprotective effects. In contrast, Semaglutide, despite its growing clinical prominence as a weight loss therapy, exhibits minimal engagement with core neurodegenerative pathways within the DM2-AD comorbidity network, highlighting variability in neuroprotective potential across DM2 DMTs. Furthermore, specific dual-action therapies (e.g., Insulin Glargine and Lixisenatide, Insulin Degludec and Liraglutide) exhibit efficacy comparable to Metformin, reinforcing the need for a precision medicine approach. These findings challenge the assumption that all DM2 DMTs confer equal neuroprotection, revealing significant differences in their impact on AD-related pathways. While some show strong potential for AD prevention, others appear far less effective. Metformins effects depend on genotype, disease state, and environmental factors, underscoring the need to re-evaluate DM2 DMTs for AD prevention in population-specific clinical trials. Metformin stands out as a strong candidate for targeted investigations in DM2 patients at high risk of AD.

bioinformatics↗

bioRxiv2024

Network-Based Analysis Identifies Targetable Pathways in Comorbid Type II Diabetes and Neuropsychiatric Disorders

Comorbid diseases complicate patient outcomes and escalate healthcare costs, necessitating 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 underpinnings of this comorbidity remain poorly understood. To address this, we developed a novel pathway-based network computational framework that identifies critical common disease mechanisms between DM2 and the five prevalent NPDs. Our approach involves reconstructing an integrated DM2 {cap} NPDs KEGG pathway network and applying two complementary analytical methods, including the "minimum path to comorbidity" method to identify the shortest pathways 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. The dysregulation of these pathways likely contributes to the development of DM2-NPDs comorbidity. 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. This framework can be adapted to study other complex comorbid conditions, offering broad implications for improving patient care.

bioinformatics↗

bioRxiv2023

(2R,6R)-hydroxynorketamine facilitates extinction and prevents emotional impairment and stress-induced reinstatement in morphine abstinent mice

Opioid addiction is a pressing public health concern marked by frequent relapse during periods of abstinence, perpetuated by negative affective states and anhedonia-driven behaviors. In addition to the current epidemic that was declared in the U.S.A., opioid-related deaths are increasing in other countries around the world. Classical antidepressants, or the currently prescribed opioid substitution pharmacotherapies have limited efficacy to reverse maladaptive behavioral responses, negative affect or prevent relapse in opioid abstinent individuals. Here, by establishing and using novel mouse models for the study of opioid addiction, we demonstrate, for the first time, the therapeutic potential of ketamines metabolite, (2R,6R)-hydroxynorketamine (HNK). In particular, our studies showcase (2R,6R)-HNKs ability to reverse conditioning to sub-effective doses of morphine in stress-susceptible mice, prevent conditioned-place aversion and mitigate acute somatic withdrawal symptoms in opioid-dependent animals. In addition, we show that this metabolite reverses anhedonia, anxiety-like behaviors, cognitive impairment, and general stress susceptibility associated with protracted opioid withdrawal, thereby presenting a promising therapeutic avenue for opioid relapse prevention. Our results strongly suggest that (2R,6R)-HNK, potentially by augmenting downstream brain-derived neurotrophic factor (BDNF) and GluN2A N-methyl-D-aspartate receptor signaling, effectively reverses maladaptive behavioral responses typical of protracted opioid abstinence. Furthermore, it facilitates the extinction of opioid conditioning and prevents stress-induced reinstatement of opioid-seeking behaviors. Our findings highlight how (2R,6R)-HNK, through an enhancement of synaptic plasticity in mood-regulating brain areas, has the potential to be an effective, next-generation pharmacotherapy for opioid use disorders by addressing emotional disturbances associated with protracted abstinence. SIGNIFICANCE STATEMENTOur studies represent a comprehensive exploration into the critical facets of opioid addiction and abstinence, offering critical insights into the significant potential of (2R,6R)-HNK as a treatment for this disorder. By unraveling the complex dynamics of opioid withdrawal and addressing the profound emotional disturbances underlying relapse vulnerability, our findings illuminate a promising innovative avenue for therapeutic intervention. The demonstrated ability of (2R,6R)-HNK to reverse maladaptive behaviors emerging during protracted opioid abstinence, facilitate extinction of opioid conditioning, prevent stress-induced reinstatement, represents a paradigm shift in addiction research. These revelations not only deepen our comprehension of the neurobehavioral complexities associated with opioid abstinence but also underscore the profound implications of (2R,6R)-HNK as a prospective pharmacotherapy in mitigating the devastating impact of opioid use disorder, potentially transforming addiction treatment strategies.

neuroscience↗

bioRxiv2023

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

BackgroundEmerging evidence suggests that certain microorganisms, including viral infections, may contribute to the onset and/or progression of Alzheimers Disease (AD), a neurodegenerative condition characterized by memory impairment and cognitive decline. However, the precise extent of their involvement and the underlying mechanisms through which specific viruses increase AD susceptibility risk remain elusive. MethodsWe used an integrative systems bioinformatics approach to identity viral-mediated pathogenic mechanisms by which specific viral species, namely 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 the pathogenesis of AD via virus-host protein-protein interactions (PPIs). We also sought to uncover potential synergistic pathogenic effects resulting from the reactivation of specific herpesviruses (HSV-1, HCMV and EBV) during acute SARS-CoV-2 infection, potentially increasing AD susceptibility. ResultsOur findings show that Herpesviridae Family members (HSV-1, EBV, KSHV, HCMV) impact AD-related processes like amyloid-beta formation, neuronal death, and autophagy. Hepatitis viruses (HBV, HCV) influence processes crucial for cellular homeostasis and dysfunction. Importantly, hepatitis viruses 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 amyloid-beta formation. ConclusionsCollectively, these findings underscore the complex link between viral infections and AD development. Perturbations in AD-related processes by viruses can arise from both shared and distinct mechanisms among viral species in different categories, potentially influencing variations in AD susceptibility.

bioinformatics↗

bioRxiv2020

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 evade host immune responses, replicate and hence 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, from cancer to neurodegenerative diseases (NDs). There are evidences suggesting that viral-mediated perturbations are a possible pathogenic aetiology in several NDs such as Amyloid Later Sclerosis, Parkinsons disease, Alzheimers disease and Multiple Sclerosis (MS), as they can cause degeneration of neurons via both direct and/or indirect actions. These diseases share several common pathological mechanisms, as well as unique disease mechanisms that reflect disease phenotype. NDs are chronic degenerative diseases of the central nervous system and current therapeutic approaches provide only mild symptomatic relief rather than treating the disease at heart, therefore there is unmet need for the discovery of novel therapeutic targets and pharmacotherapies. 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 integrative network-based bioinformatics approach that accounts for pathogen-genes-disease related PPIs with the aim to identify viral-mediated pathogenic mechanisms focusing in MS disease. We identified 7 high centrality nodes that can act as disease communicator nodes and exert systemic effects in the MS enriched KEGG pathways network. In addition, we identified 12 KEGG pathways targeted by 67 viral proteins from 8 viral species that might exert viral-mediated pathogenic mechanisms in MS by interacting with the disease communicator nodes. Finally, our analysis highlighted the Th17 differentiation pathway, a hub-bottleneck 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.

bioinformatics↗