Exploring the patterns in traditional Chinese medicine for bipolar disorder: a data-driven network approach.

AIM OF THE STUDY

Traditional Chinese Medicine offers a holistic approach that could provide complementary benefits for bipolar disorder treatment. However, the clinical cases in Traditional Chinese Medicine are highly dispersed, creating challenges for translational research. This study employs a novel data-mining-derived approach to identify treatment patterns and active metabolite interactions within these clinical cases.

METHODS AND MATERIALS

Bipolar disorder-related targets were determined using DisGeNET and GeneCards databases. Active botanical drugs were extracted from the BATMAN-TCM 2.0 database. All terms for botanical drugs and diseases were confirmed via the Pharmacopoeia of the People's Republic of China 2020 Edition and Medical Subject Headings. Networks were constructed using Cytoscape, with data analysis performed using Python. MTT cell viability and qRT-PCR analysis were used to perform experiments on SH-SY5Y neuroblastoma cells.

RESULTS

Five key botanical drugs-, , , , and -were identified as core drugs in BD treatment formulas. The botanical drug-metabolite-target network was constructed. experiments using SH-SY5Y neuroblastoma cells demonstrated dose-dependent effects of palmitic acid (PA) and stearic acid (SA) on cell viability and gene expression. qRT-PCR analysis revealed bidirectional regulation of GABRA1 and ESR1 by these metabolites.

CONCLUSION

Five botanical drugs: , , , , and , were identified as the core botanical drugs in bipolar disorder treatment. The main mechanism of these botanical drugs is their effects on the gamma-aminobutyric acid type A receptor and ESR1.