Spectrum-effect relationships between fingerprints of caulophyllum robustum maxim and inhabited pro-inflammation cytokine effects

Abstract

Caulophyllum robustum Maxim (CRM) is a Chinese folk medicine with significant effect on treatment of rheumatoid arthritis (RA). This study was designed to explore the spectrum-effect relationships between high-performance liquid chromatography (HPLC) fingerprints and the anti-inflammatory effects of CRM. Seventeen common peaks were detected by fingerprint similarity evaluation software. Among them, 15 peaks were identified by Liquid Chromatography-Mass Spectrometry (LC-MS). Pharmacodynamics experiments were conducted in collagen-induced arthritis (CIA) mice to obtain the anti-inflammatory effects of different batches of CRM with four pro-inflammation cytokines (TNF-α, IL-β, IL-6, and IL-17) as indicators. These cytokines were suppressed at different levels according to the different batches of CRM treatment. The spectrum-effect relationships between chemical fingerprints and the pro-inflammation effects of CRM were established by multiple linear regression (MLR) and gray relational analysis (GRA). The spectrum-effect relationships revealed that the alkaloids (N-methylcytisine, magnoflorine), saponins (leiyemudanoside C, leiyemudanoside D, leiyemudanoside G, leiyemudanoside B, cauloside H, leonticin D, cauloside G, cauloside D, cauloside B, cauloside C, and cauloside A), sapogenins (oleanolic acid),-sitosterols, and unknown compounds (X3, X17) together showed anti-inflammatory efficacy. The results also showed that the correlation between saponins and inflammatory factors was significantly closer than that of alkaloids, and saponins linked with less sugar may have higher inhibition effect on pro-inflammatory cytokines in CIA mice. This work provided a general model of the combination of HPLC and anti-inflammatory effects to study the spectrum-effect relationships of CRM, which can be used to discover the active substance and to control the quality of this treatment.