Introduction: The availability of large-scale multi-omic data has revolution-ized the study of cellular machinery, enabling a systematic understanding of biological processes. However, the integration of these datasets into Genome-Scale Models of Metabolism (GEMs) re-mains underexplored. Existing methods often link transcriptome and proteome data independently to reaction boundaries, providing models with estimated maximum reaction rates based on individual datasets. This independent approach, however, introduces uncertainties and inaccuracies.Methods: To address these challenges, we applied a principal component analysis (PCA)-based approach to integrate transcriptome and proteome data. This method facilitates the reconstruction of context-specific models grounded in multi-omics data, enhancing their biological relevance and predictive capacity.Results: Using this approach, we successfully reconstructed an astrocyte GEM with improved prediction capabilities compared to state-of-the-art models available in the literature.Discussion: These advancements underscore the potential of multi-omic inte-gration to refine metabolic modeling and its critical role in studying neurodegeneration and developing effective therapies.

Astrocytes play a pivotal role in maintaining brain homeostasis. Recent research has highlighted the significance of palmitic acid (PA) in triggering pro-inflammatory pathways contributing to neurotoxicity. Furthermore, Genomic-scale metabolic models and control theory have revealed that metabolic switches (MSs) are metabolic pathway regulators by potentially exacerbating neurotoxicity, thereby offering promising therapeutic targets. Herein, we characterized these enzymatic MSs in silico as potential therapeutic targets, employing protein–protein and drug–protein interaction networks alongside structural characterization techniques. Our findings indicate that five MSs (P00558, P04406, Q08426, P09110, and O76062) were functionally linked to nervous system drug targets and may be indirectly regulated by specific neurological drugs, some of which exhibit polypharmacological potential (e.g., Trifluperidol, Trifluoperazine, Disulfiram, and Haloperidol). Furthermore, four MSs (P00558, P04406, Q08426, and P09110) feature ligand-binding or allosteric cavities with druggable potential. Our results advocate for a focused exploration of P00558 (phosphoglycerate kinase 1), P04406 (glyceraldehyde-3-phosphate dehydrogenase), Q08426 (peroxisomal bifunctional enzyme, enoyl-CoA hydratase, and 3-hydroxyacyl CoA dehydrogenase), P09110 (peroxisomal 3-ketoacyl-CoA thiolase), and O76062 (Delta(14)-sterol reductase) as promising targets for the development or repurposing of pharmacological compounds, which could have the potential to modulate lipotoxic-altered metabolic pathways, offering new avenues for the treatment of related human diseases such as neurological diseases.

Extracellular vesicles (EVs) are small capsular bodies released by cells, mediating responses in intercellular communication. The role of EVs in Aβ pathology spreading in the Alzheimer’s disease (AD) brain has been evidenced, although whether this occurs due to the co-transportation of Aβ peptides or contribution of other factors, such as EV-associated transcripts, remains uncertain. In vitro studies of miRNA cargo in neuron-derived extracellular vesicles (NDEVs) show that Aβ hyperexpression alters the transcriptomic profile; however, it is not clear to what extent this causes changes at the organ level. By utilizing datasets from published studies, we generated competing endogenous RNA (ceRNA) networks for miRNAs co-expressed in NDEVs and the brain in different stages of pathology, using both an APP overexpressing neuronal model (in vitro) and brain cortices from 6- and 9-month-old APP/PSEN1 mice (in vivo). Networks integrating information from mRNAs, lncRNAs, and circRNAs showed two candidate lncRNAs (Kcnq1ot1 and Gm42969) and a circRNA (Pum1), while enrichment analyses detected that NDEVs miRNAs signal to other CNS cells and that this signal can be disrupted by Aβ pathology, contributing to the loss of long-term potentiation seen in early AD.