Efficacy and Key Materials of East Asian Herbal Medicine Combined with Conventional Medicine on Inflammatory Skin Lesion in Patients with Psoriasis Vulgaris: A Meta-Analysis, Integrated Data Mining, and Network Pharmacology

Abstract

Psoriasis is a chronic inflammatory disease that places a great burden on both individuals and society. The use of East Asian herbal medicine (EAHM) in combination with conventional medications is emerging as an effective strategy to control the complex immune-mediated inflammation of this disease from an integrative medicine (IM) perspective. The safety and efficacy of IM compared to conventional medicine (CM) were evaluated by collecting randomized controlled trial literature from ten multinational research databases. We then searched for important key materials based on integrated drug data mining. Network pharmacology analysis was performed to predict the mechanism of the anti-inflammatory effect. Data from 126 randomized clinical trials involving 11,139 patients were used. Compared with CM, IM using EAHM showed significant improvement in the Psoriasis Area Severity Index (PASI) 60 (RR: 1.4280; 95% CI: 1.3783–1.4794; p < 0.0001), PASI score (MD: −3.3544; 95% CI: −3.7608 to −2.9481; p < 0.0001), inflammatory skin lesion outcome, quality of life, serum inflammatory indicators, and safety index of psoriasis. Through integrated data mining of intervention data, we identified four herbs that were considered to be representative of the overall clinical effects of IM: Rehmannia glutinosa (Gaertn.) DC., Isatis tinctoria subsp. athoa (Boiss.) Papan., Paeonia × suffruticosa Andrews, and Scrophularia ningpoensis Hemsl. They were found to have mechanisms to inhibit pathological keratinocyte proliferation and immune-mediated inflammation, which are major pathologies of psoriasis, through multiple pharmacological actions on 19 gene targets and 8 pathways in network pharmacology analysis. However, the quality of the clinical trial design and pharmaceutical quality control data included in this study is still not optimal; therefore, more high-quality clinical and non-clinical studies are needed to firmly validate the information explored in this study. This study is informative in that it presents a focused hypothesis and methodology for the value and direction of such follow-up studies.

Network Pharmacology and Experimental Verifications to Discover Scutellaria baicalensis Georgi’s Effects on Joint Inflammation, Destruction, and Pain in Osteoarthritis

“…Therefore, this study investigated whether SB is a promising multicomponent material that can ameliorate the multi-pathology of OA through computational prediction and experimental validation. For pharmacological prediction, we used network pharmacology analysis, a technique that predicts the complex relationships between multiple components and multiple targets in natural products from a network science perspective [29][30][31][32][33][34][35]. This method allows more precise predictive information to be derived about the drug-targetdisease relationship, which provides the basis for designing optimized experiments to explore the mechanisms of action of multicomponent herbal medicines, including SB.…”

Network analysis, in vivo, and in vitro experiments identified the mechanisms by which Piper longum L. [Piperaceae] alleviates cartilage destruction, joint inflammation, and arthritic pain

“…Natural substances offer various pharmacologically active constituents, which have a long history of human use for the treatment of various diseases ( Jo et al, 2023c ; Lee et al, 2023 ). The unique properties of natural products, such as multitarget effects based on multiple compounds, are thought to be well adapted to the requirements of DMOADs in drug discovery ( Yang et al, 2017 ; Luo et al, 2020 ; Jo et al, 2021 ; 2023b ; Panossian, 2023 ; Ren et al, 2023 ).…”