TSC1-mTORC1 signaling in Alzheimer’s disease: an integrated bioinformatic analysis linking gene expression to neuropathology

Background and objective Alzheimer’s disease (AD) is characterized by the accumulation of amyloid-β (Aβ) plaques and tau pathology, with mTORC1 hyperactivation implicated in disease pathogenesis via suppression of autophagy. However, systematic evidence regarding its key upstream repressor, TSC1, in human AD brains remains limited. Methods Using an integrated, multi-level bioinformatic approach combining RNA-seq, neuropathological, and clinical data from the ROSMAP cohort, we comprehensively investigated the TSC1-mTORC1 axis in AD. Gene co-expression network analysis and gene set enrichment analysis were applied to contextualize TSC1 within disease-associated molecular networks. Results Our analysis revealed significant TSC1 downregulation and concomitant mTOR and RPTOR upregulation in AD brains. Critically, lower TSC1 expression was strongly correlated with higher Aβ plaque density, greater tau tangle burden, worse global cognitive performance, and an exacerbated neuroinflammatory microenvironment characterized by increased microglial and astrocytic activation. Gene co-expression network analysis positioned TSC1 within a disease-associated module showing the strongest association with AD pathology. Gene set enrichment analyses further demonstrated that the TSC1 low-expression phenotype was associated not only with suppression of autophagy-related pathways but also with significant enrichment of broad pro-inflammatory and immune response pathways. Conclusion and discussion These integrated human data provide compelling evidence that TSC1 deficiency is a hallmark of AD and is associated with mTORC1 hyperactivation, aggravated amyloid-tau pathologies, cognitive impairment, and neuroinflammation. These findings are consistent with a model in which TSC1 deficiency and mTORC1 hyperactivation may contribute to AD pathophysiology, thereby nominating the TSC1-mTORC1 axis and its associated inflammatory networks as promising multi-faceted therapeutic targets. Future replication in independent cohorts is warranted to assess the generalizability of these findings.