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.

Keywords: East Asian herbal medicine; association rule mining; chronic inflammation; integrative medicine; network pharmacology; psoriasis; social network analysis; systematic review.

Figure 1

Study workflow of the multi-faceted analysis of IM for inflammatory skin lesion of psoriasis.

Figure 2

PRISMA 2020 flow diagram.

Figure 3

Risk of bias 2.0 summary: authors’ judgements for each risk of bias domain across all included trials.

Figure 4

(A) Orchard plot of the trials that compared IM with CM for the PASI 60; (B) Drapery plot of the trials that compared IM with CM for the PASI 60; (C) Orchard plot of the trials that compared IM with CM for the PASI score; (D) Drapery plot of the trials that compared IM with CM for the PASI score. The red line in the drapery plot is the P-value curve of the pooled estimates; the light blue region in the drapery plot is the prediction region.

Figure 5

Forest plot of the trials that compared IM with CM for (A) PASI 70; (B) Recurrence rate; (C) DLQI; (D) VAS.

Figure 5

Forest plot of the trials that compared IM with CM for (A) PASI 70; (B) Recurrence rate; (C) DLQI; (D) VAS.

Figure 6

Forest plot of the trials that compared IM with CM for (A) TNF-α; (B) IL-8; (C) IL-17; (D) IL-22; (E) IL-23; (F) IFN-γ.

Figure 6

Forest plot of the trials that compared IM with CM for (A) TNF-α; (B) IL-8; (C) IL-17; (D) IL-22; (E) IL-23; (F) IFN-γ.

Figure 7

Forest plot of the incidence rates of reported adverse events: (A) drug induced liver injury; (B) cutaneous symptoms; (C) alimentary symptoms; (D) metabolic disorder; (E) other symptoms.

Figure 8

Forest plot of the sensitivity analysis ordered by heterogeneity for (A) PASI 60 and (B) PASI score.

Figure 9

Bubble plot of the meta-regression analysis for (A) source of investigational medicine and (B) formulation type.

Figure 10

Contour-enhanced funnel plot of (A) PASI 60 and (B) PASI scores.

Figure 11

IM herbal materials network used in more than 5% of trials for inflammatory skin lesion of psoriasis.

Figure 12

Network graph of the core association rule in the IM component herbs prescribed for inflammatory skin lesion in psoriasis.

Figure 13

(A) Venn diagram of targets of the four core herbs against psoriasis; (B) PPI network construction sequence of four core herbs against psoriasis gene targets by MCC algorithm; MCC: Maximum Clique Centrality.

Figure 14

(A) Top 5 of GO enrichment analysis for biological process, cellular components, and molecular functions.; (B) Bubble plot of GO enrichment; (C) Sankey and dot plot of KEGG pathway enrichment analysis illustrating 8 enriched pathways; (D) Gene ontology chord diagram of KEGG pathway analysis; (E) Pathways in cancer were colored using the KEGG mapper. (F) AGE-RAGE signaling pathway in diabetic complications were colored using the KEGG mapper. Orange represents the therapeutic targets in this pathway where the four core herbs act to alleviate psoriasis.

Figure 15

Alluvial plot showing the compound–target-pathway network for the therapeutic mechanism of psoriasis from four core herbs.