During aging, alterations in astrocyte phenotype occur in areas associated with age-related cognitive decline, including hippocampus. Previous work reported subregion-specific changes in surface, volume, and soma size of hippocampal astrocytes during physiological aging. Herein we extensively analyzed, by morphometric analysis, fine morphological features of GFAP+ astrocytes in young (6-month-old) and middle-aged (14-month-old) male mice. We observed remarkable heterogeneity in the astrocytic response to aging in distinct subfields and along the dorsoventral axis of hippocampus and in entorhinal cortex. In middle-aged mice dorsal granule cell and molecular layers, but not hilus, astrocytes underwent remarkable increase in their morphological complexity. These changes were absent in ventral Dentate Gyrus (DG). In addition, in entorhinal cortex, the major input to dorsal DG, astrocytes underwent remarkable atrophic changes in middle-aged mice. Since dorsal DG, and not ventral DG, is involved in cognitive functions, these findings appear worth of further evaluation. Our findings also suggest an additional level of complexity in the structural changes associated with brain aging.

Astrocytes perform important housekeeping functions in the nervous system including maintenance of adequate neuronal excitability, although the regulatory mechanisms are currently poorly understood. The astrocytic Ca²⁺/calmodulin‐activated phosphatase calcineurin (CaN) is implicated in the development of reactive gliosis and neuroinflammation, but its roles, including the control of neuronal excitability, in healthy brain is unknown. We have generated a mouse line with conditional knockout (KO) of CaN B1 (CaNB1) in glial fibrillary acidic protein‐expressing astrocytes (astroglial calcineurin KO [ACN‐KO]). Here, we report that postnatal and astrocyte‐specific ablation of CaNB1 did not alter normal growth and development as well as adult neurogenesis. Yet, we found that specific deletion of astrocytic CaN selectively impairs intrinsic neuronal excitability in hippocampal CA1 pyramidal neurons and cerebellar granule cells (CGCs). This impairment was associated with a decrease in after hyperpolarization in CGC, while passive properties were unchanged, suggesting impairment of K⁺ homeostasis. Indeed, blockade of Na⁺/K⁺‐ATPase (NKA) with ouabain phenocopied the electrophysiological alterations observed in ACN‐KO CGCs. In addition, NKA activity was significantly lower in cerebellar and hippocampal lysates and in pure astrocytic cultures from ACN‐KO mice. While no changes were found in protein levels, NKA activity was inhibited by the specific CaN inhibitor FK506 in both cerebellar lysates and primary astroglia from control mice, suggesting that CaN directly modulates NKA activity and in this manner controls neuronal excitability. In summary, our data provide formal evidence for the notion that astroglia is fundamental for controlling basic neuronal functions and place CaN center‐stage as an astrocytic Ca²⁺‐sensitive switch.

Autism spectrum disorder (ASD) is a complex multifactorial neurodevelopmental disorder. Despite extensive research involving genome-wide association studies, copy number variant (CNV) testing, and genome sequencing, the comprehensive genetic landscape remains incomplete. In this context, we developed a systems biology approach to prioritize genes associated with ASD and uncover potential new candidates. A Protein–Protein Interaction (PPI) network was generated from genes associated to ASD in a public database. Leveraging gene topological properties, particularly betweenness centrality, we prioritized genes and unveiled potential novel candidates (e.g., CDC5L, RYBP, and MEOX2). To test this approach, a list of genes within CNVs of unknown significance, identified through array comparative genomic hybridization analysis in 135 ASD patients, was mapped onto the PPI network. A prioritized gene list was obtained through ranking by betweenness centrality score. Intriguingly, by over-representation analysis, significant enrichments emerged in pathways not strictly linked to ASD, including ubiquitin-mediated proteolysis and cannabinoid receptor signaling, suggesting their potential perturbation in ASD. Our systems biology approach provides a promising strategy for identifying ASD risk genes, especially in large and noisy datasets, and contributes to a deeper understanding of the disorder’s complex genetic basis.

Proteomics represents a fundamental layer for understanding the molecular complexity of solid tumors by quantifying protein abundance and capturing proteoforms and post-translational modifications undetected in genomics or transcriptomics analyses. As mass spectrometry-based technologies and public proteomics repositories have expanded, opportunities for large-scale data reuse have grown accordingly. Nevertheless, data availability has not been translated into straightforward reuse: differences in experimental design, acquisition strategies, quantification workflows and metadata quality still limit the reproducibility and cross-study comparability. In this review, proteomics data reuse is defined as the systematic reanalysis and integration of publicly available datasets to support precision oncology applications such as biomarker assessment and antibody–drug conjugate target prioritization. We discuss reuse as an end-to-end analytical process, focusing on data analysis workflows, harmonization strategies, and the impact of heterogeneous experimental and analytical choices on interoperability. The increased application of artificial intelligence in proteomics data integration and reuse is also addressed, highlighting its analytical potential while underscoring the risks of overinterpretation when biological context and data structure are not adequately considered. Using colorectal and prostate cancer as representative examples, we illustrate how proteomics data reuse can support biological discovery and translational research, while critically examining the factors that limit robustness and clinical relevance.

TANGO2 deficiency disorder is a rare autosomal recessive disease (~100 cases reported worldwide). Despite being caused by loss-of-function variants in the TANGO2 gene, patients exhibit marked phenotypic variability, including intrafamilial differences among individuals carrying identical variants. To uncover potential modifier mechanisms influencing disease severity, we developed an integrative Systems biology framework, combining exome sequencing, transcriptomics, variant effect prediction, and Human Phenotype Ontology mapping. This approach was applied to two siblings carrying identical compound heterozygous TANGO2 variants but opposite clinical outcomes: one severely affected and one asymptomatic. Personalized protein–protein interaction networks and combined univariate and multivariate analyses were employed to maximize specificity in this single-family comparison. In the affected sibling, a cumulative burden of common APOB variants, together with altered VLDLR, NTN1, and LDHA expression, implicated disrupted lipid metabolism and neurodevelopmental pathways. The asymptomatic sibling harbored a potentially protective 3′-UTR variant in EP300 and no APOB variant burden, supporting enhanced post-transcriptional regulation within developmental biology networks. These findings highlight lipid metabolism as a key pathway in TANGO2 deficiency pathophysiology and suggest autophagy and mitophagy as additional modifier mechanisms influencing phenotypic variability. Our integrative multi-omics framework provides a valuable strategy for elucidating genotype-phenotype relationships in rare diseases and supports personalized therapeutic approaches.