Valsartan repurposing to mitigate autoimmune encephalomyelitis via ACE2/Ang1-7/MasR axis pathway cognitive and...

Multiple sclerosis (MS) is a debilitating neuroinflammatory disease frequently associated with cognitive impairment. Recent research suggests that targeting the renin-angiotensin system (RAS) may offer a promising therapeutic strategy for alleviating cognitive deficits in neurodegenerative disorders. This study aimed to explore the interactions between valsartan (VAL), an angiotensin II receptor antagonist, ACE2/Ang 1-7/MasR signaling, and PI3K/Akt/CREB/BDNF pathway in preserving cognitive function using an experimental autoimmune encephalomyelitis (EAE) mouse model. EAE was induced in mice through spinal cord homogenate, leading to motor and cognitive impairments that mimic those observed in MS patients. In addition, comprehensive bioinformatics and chemo-bioinformatics analyses were conducted. Oral administration of VAL (40 mg/kg/day) significantly ameliorated EAE-induced cognitive deficit in spatial and learning memory as evidenced by improved performance in the novel object recognition (NOR) and Morris water maze (MWM), along with a reduction in EAE clinical scoring. Histological analysis further revealed that VAL treatment mitigated EAE-induced demyelination in the corpus callosum. Mechanistically, VAL activated ACE2/Ang 1-7/MasR signaling pathway, stimulating the p-PI3K/p-Akt/p-CREB axis, and consequently elevating BDNF, its receptor TrkB and synapsin I, thereby establishing a cycle of neuroprotection. Furthermore, VAL mitigated EAE-induced neuroinflammation by reducing p-NFκB p65, TNF-α and IL-6 contents, while restoring redox balance by enhancing SOD and GPx activities, elevating GSH content and reducing MDA content. Collectively, these findings highlight the potential of VAL in preserving cognitive function in EAE by modulating key neuroprotective and anti-inflammatory pathways, offering valuable insights into novel therapeutic strategies for MS and related neuroinflammatory disorders. These conclusions are further supported by complementary bioinformatics analyses.