Biology subjects

Hemedan, A. A.

Publications and source records attributed to Hemedan, A. A..

3 recordsLinked to original sources

bioRxiv2025

Sex-specific microRNA regulators of Parkinson disease: insights from cohort-stratified simulations of compensatory pathway dynamics

Parkinsons disease (PD) exhibits sex differences in prevalence, symptom severity, and progression, suggesting distinct underlying molecular mechanisms. However, the pathophysiological mechanisms remain largely obscure, particularly in the context of the post-transcriptional regulations, where microRNAs (miRNAs) suppress the expression of multiple genes. Bulk transcriptomic data often blur these effects, especially when regulatory patterns vary by sex or cell type. miRNAs have emerged as key regulators of PD-related processes, but their complexity demands computational methods that enable capturing the functional impact at the pathway level. In this study, we investigated how sex may affect miRNA-regulated PD pathways using Boolean modeling across two large PD cohorts, the Parkinsons Progression Markers Initiative (PPMI) and the Luxembourg Parkinsons Study (LuxPark). First, differential expression analysis identified significant variations in miRNA expression between the sexes across both cohorts. These miRNAs were analysed to identify molecular pathways that are over-represented among the predicted targets of the dysregulated microRNAs (i.e. enrichment analysis). The enriched pathways were used to build Boolean models to simulate the effects of sex-specific miRNA dysregulation. These simulations showed consistent male-specific impairment in mitochondrial biogenesis, and respiratory chain activity. Mitophagy and oxidative stress response pathways were also disrupted, alongside dysregulation of autophagy-related protein-folding mechanisms. Our findings suggest that sex-specific miRNA dysregulation contributes to differences in molecular patterns in PD by influencing compensatory related pathways and responses. These results highlight the need for sex-stratified approaches in modeling, translational research, and precision medicine strategies for disease-modifying treatments.

systems biology↗

bioRxiv2025

Association of ulcerative colitis with atopic dermatitis: identification of shared and unique mechanisms by construction and computational analysis of disease maps

Background and AimsUlcerative colitis (UC) and atopic dermatitis (AD) are immune-mediated inflammatory diseases with limited treatment options. They are known to be related which may explain higher risk of development of UC in patients with AD. The goal of this work is to review and analyse molecular mechanisms of UC in comparison to AD towards insights into UC complexity, potential comorbidities and novel therapies. MethodsWe developed graphical computational models of UC and AD molecular mechanisms (disease maps) by integrating information from over 800 manually curated articles. The maps are available online at https://imi-immuniverse.elixir-luxembourg.org. Disease-specific risk variants and gene expression profiles are visualised to identify signatures specific to UC, and shared with AD. Computational analysis shows key proteins, their interactions and pathways shared between UC and AD. ResultsUC and AD maps include more than 2000 molecular interactions. Systematic computational comparison shows that both disorders exhibit epithelial barrier dysfunction, immune dysregulation involving abnormal Th2, Th1 and ILC response, common inflammatory pathways and biomarkers such as IL-13, IL-4R, IFNG, and IL-18. Visualisation and analysis of omics data demonstrates UC map usability. ConclusionsWe developed the first computational graphic model of UC molecular mechanisms. Its content focuses on mechanisms of epithelial barrier disruption and downstream immune dysregulation through cytokines and other mediators. The comparison of UC to AD mechanisms demonstrates common signalling pathways and biomarkers, and supports potential drug repurposing and treatment options. The workflow can be reused and new findings can be dynamically integrated into the maps. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/650149v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@1c4c80eorg.highwire.dtl.DTLVardef@2a1e66org.highwire.dtl.DTLVardef@131ece3org.highwire.dtl.DTLVardef@b74971_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHICAL ABSTRACTC_FLOATNO C_FIG

bioinformatics↗

bioRxiv2024

Cohort-specific Boolean models highlight different regulatory modules during Parkinson's disease progression

1Parkinsons Disease (PD) is a multifaceted neurodegenerative disorder characterised by complex molecular dysregulations and diverse comorbidities. It is critical to decode the molecular pathophysiology of PD, which involves complex molecular interactions and their changes over time. Systems medicine approaches can help with this by a) encoding knowledge about the mechanisms into computational models b) simulating these models using patient-specific omics data. This study employs the PD map, a detailed repository of PD-related molecular interactions, as a comprehensive knowledge resource. We aim to dissect and understand the intricate molecular pathways implicated in PD by using logical modelling. This approach is essential for capturing the dynamic interplay of molecular components that contribute to the disease. We incorporate cohort-level and real-world patient data to ensure our models accurately reflect PDs subtype-specific pathway deregulations. This integration is crucial for addressing the heterogeneity observed in PD manifestations and responses to treatment. To combine logical modelling with empirical data, we rely on Probabilistic Boolean Networks (PBNs).These networks provide a robust framework, capturing the stochastic nature of molecular interactions and offering insights into the variable progression of the disease. By combining logical modelling with empirical data through PBNs, we achieve a more refined and realistic representation of PDs molecular landscape. The findings provide insights into the molecular mechanisms of PD. We identify key regulatory biomolecules and pathways that differ significantly across PD subtypes. These discoveries have substantial implications for the development of precise medical treatments. The study provides hypothesis for targeted therapeutic interventions by linking molecular dysregulation patterns to clinical phenotypes and advancing our understanding of PD progression and patient stratification.

systems biology↗