Gao Kuo, Zhao Huihui, Gao Jian, Wen Binyu, Jia Caixia, Wang Zhiyong, Zhang Feilong, Wang Jinping, Xie Hua, Wang Juan, Wang Wei, Chen Jianxin
School of Preclinical Medicine, Beijing University of Chinese Medicine, Beijing, China.
Beijing University of Chinese Medicine, Dongfang Hospital, Beijing, China.
Front Pharmacol. 2017 Nov 22;8:864. doi: 10.3389/fphar.2017.00864. eCollection 2017.
Chronic heart failure (CHF) is a major public health problem in huge population worldwide. The detailed understanding of CHF mechanism is still limited. Zheng (syndrome) is the criterion of diagnosis and therapeutic in Traditional Chinese Medicine (TCM). Syndrome prediction may be a better approach for understanding of CHF mechanism basis and its treatment. The authors studied disturbed metabolic biomarkers to construct a predicting mode to assess the diagnostic value of different syndrome of CHF and explore the Chinese herbal medicine (CHM) efficacy on CHF patients. A cohort of 110 patients from 11 independent centers was studied and all patients were divided into 3 groups according to TCM syndrome differentiation: group of Qi deficiency syndrome, group of Qi deficiency and Blood stasis syndrome, and group of Qi deficiency and Blood stasis and Water retention syndrome. Plasma metabolomic profiles were determined by UPLC-TOF/MS and analyzed by multivariate statistics. About 6 representative metabolites were highly possible to be associated with CHF, 4, 7, and 5 metabolites with Qi deficiency syndrome, Qi deficiency and Blood stasis syndrome, and Qi deficiency and Blood stasis and Water retention syndrome (VIP > 1, < 0.05). The diagnostic model was further constructed based on the metabolites to diagnose other CHF patients with satisfying sensitivity and specificity (sensitivity and specificity are 97.1 and 80.6% for CHF group vs. NH group; 97.1 and 80.0% for QD group vs. NH group; 97.1 and 79.5% for QB group vs. NH group; 97.1 and 88.9% for QBW group vs. NH group), validating the robustness of plasma metabolic profiling to diagnostic strategy. By comparison of the metabolic profiles, 9 biomarkers, 2-arachidonoylglycerophosphocholine, LysoPE 16:0, PS 21:0, LysoPE 20:4, LysoPE 18:0, linoleic acid, LysoPE 18:2, 4-hydroxybenzenesulfonic acid, and LysoPE 22:6, may be especially for the effect of CHM granules. A predicting model was attempted to construct and predict patient based on the related symptoms of CHF and the potential biomarkers regulated by CHM were explored. This trial was registered with NCT01939236 (https://clinicaltrials.gov/).
慢性心力衰竭(CHF)是全球大量人群面临的主要公共卫生问题。对CHF机制的详细了解仍然有限。证是中医诊断和治疗的标准。证型预测可能是理解CHF机制基础及其治疗的更好方法。作者研究了代谢紊乱的生物标志物,以构建一种预测模型,评估CHF不同证型的诊断价值,并探索中药对CHF患者的疗效。对来自11个独立中心的110例患者进行了研究,所有患者根据中医辨证分为3组:气虚证组、气虚血瘀证组和气阴两虚水停证组。通过超高效液相色谱-飞行时间质谱(UPLC-TOF/MS)测定血浆代谢组学谱,并进行多元统计分析。约6种代表性代谢物极有可能与CHF相关,气虚证、气虚血瘀证和气阴两虚水停证分别有4、7和5种代谢物(VIP>1,<0.05)。基于这些代谢物进一步构建诊断模型,以诊断其他CHF患者,具有令人满意的敏感性和特异性(CHF组与非CHF组相比,敏感性和特异性分别为97.1%和80.6%;气虚证组与非CHF组相比,敏感性和特异性分别为97.1%和80.0%;气虚血瘀证组与非CHF组相比,敏感性和特异性分别为97.1%和79.5%;气阴两虚水停证组与非CHF组相比,敏感性和特异性分别为97.1%和88.9%),验证了血浆代谢谱对诊断策略的稳健性。通过比较代谢谱,9种生物标志物,即2-花生四烯酰甘油磷酸胆碱、溶血磷脂酰乙醇胺16:0、磷脂酰丝氨酸21:0、溶血磷脂酰乙醇胺20:4、溶血磷脂酰乙醇胺18:0、亚油酸、溶血磷脂酰乙醇胺18:2、4-羟基苯磺酸和溶血磷脂酰乙醇胺二十二碳六烯酸,可能特别与中药颗粒的疗效有关。尝试构建一个预测模型,并根据CHF的相关症状对患者进行预测,同时探索受中药调节的潜在生物标志物。该试验已在NCT01939236(https://clinicaltrials.gov/)注册。