Metabolic profiling deciphering the potential targets of Yi-Gan San against vascular dementia in rat.

Vascular dementia (VaD) is widely recognized as the second most common type of dementia, yet effective treatments are still lacking. Traditional Chinese medicine Yi-Gan San (YGS) has potent efficacy on treating VaD in clinical practice. However, the underlying mechanism is still unclear. In the present study, a UPLC-QTOFMS-based metabolomic method was established to explore the therapeutic mechanisms of YGS on VaD. Experimental VaD model was induced by bilateral occlusion of the common carotid arteries (two-vessel occlusion [2-VO]) in rats. Cognitive function, pathological changes and oxidative stress condition in the brains of VaD rats were assessed using Morris water maze tests, hematoxylin-eosin staining and antioxidant assays (MDA, SOD, GSH and GSH-Px), respectively. UPLC-QTOFMS combined with computational systems analysis were conducted to study the changes of metabolic networks in serum of rats. The results indicated that VaD model was established successfully and 2-VO caused a decline in spatial learning and memory and hippocampal histopathological abnormalities of rats. YGS significantly improved the cognitive impairment induced by 2VO and attenuated hippocampal histopathological abnormalities. The inducement of 2-VO significantly elevated the level of MDA, and reduced SOD and GSH-Px activities, and YGS can significantly regulate the levels. We have identified 34 significantly changed metabolites related to 2-VO-induced VaD, and YGS can significantly regulate the abnormalities of 24 metabolites. Metabolic pathway enrichment analysis revealed that the mechanisms of YGS against 2-VO-induced VaD may be attributed to modulating the metabolic disorders of arachidonic acid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and sphingolipid metabolism. The present study provides new experimental information on the pathogenesis of VaD, unravels the potential targeted metabolic pathways of YGS against VaD on the whole metabolic network and highlights the importance of metabolomics as a potential tool for deciphering drug-targeted metabolic pathways.