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基于超高效液相色谱-四极杆-静电场轨道阱质谱技术的高血压前期肝火亢盛证非靶向代谢组学研究及生物标志物筛选

[Non-targeted metabolomics study and biomarker screening of prehypertensive liver-fire hyperactivity syndrome based on UPLC-Q-Exactive MS technology].

作者信息

Wang Yu, Li Shu-Min, Li Chao, Yang Wen-Qing, Li Yun-Lun

机构信息

Affiliated Hospital of Shandong University of Traditional Chinese Medicine Ji'nan 250011, China.

Shandong University of Traditional Chinese Medicine Ji'nan 250355, China.

出版信息

Zhongguo Zhong Yao Za Zhi. 2021 Jun;46(11):2881-2888. doi: 10.19540/j.cnki.cjcmm.20210323.201.

Abstract

In this study, patients with prehypertensive liver-fire hyperactivity syndrome(LFHS) were selected as the research objects. The plasma samples of healthy volunteers and patients with prehypertensive LFHS were analyzed by non-targeted metabolomics based on UPLC-Q-Exactive MS. The differential biomarkers and metabolic pathways were screened out by multivariate statistics and metabolic pathway analysis, which revealed the characteristics of metabolic patterns of the syndrome. Thirty-three potential biomarkers such as androsterone and lysophosphatidylcholine and 16 related metabolic pathways such as steroid hormone metabolism and lipid metabolism were identified, and a partial least squares-discriminant analysis(PLS-DA) model of traditional Chinese medicine(TCM) syndromes was preliminarily constructed: Y =-0.070X_(13)-0.006X_8+ 0.040X_5-0.152X_1+0.131X_(10)+0.036X_(11)+0.043X_(23)+0.076X_(16)+0.132X_(20)+0.081X_(19)-0.101X_(31)+0.082X_(15)-0.038X_9+0.079X_(24). The predictive value of the model was 88.1%, and the explanatory power was 88.4%. In this study, the characteristic metabolic pattern of the prehypertensive LFHS was distinguished and revealed by metabolomics. The constructed PLS-DA model is expected to provide an objective basis for the identification of TCM syndromes in prehypertension, and inspiration for exploring the biological basis of TCM syndromes at small-molecular and overall levels.

摘要

本研究选取高血压前期肝火亢盛证(LFHS)患者作为研究对象。采用基于超高效液相色谱-四极杆-静电场轨道阱质谱(UPLC-Q-Exactive MS)的非靶向代谢组学方法,对健康志愿者和高血压前期LFHS患者的血浆样本进行分析。通过多元统计和代谢通路分析筛选出差异生物标志物和代谢通路,揭示该证型的代谢模式特征。鉴定出33种潜在生物标志物,如雄酮和溶血磷脂酰胆碱,以及16条相关代谢通路,如类固醇激素代谢和脂质代谢,并初步构建了中医证型的偏最小二乘判别分析(PLS-DA)模型:Y = -0.070X₁₃ - 0.006X₈ + 0.040X₅ - 0.152X₁ + 0.131X₁₀ + 0.036X₁₁ + 0.043X₂₃ + 0.076X₁₆ + 0.132X₂₀ + 0.081X₁₉ - 0.101X₃₁ + 0.082X₁₅ - 0.038X₉ + 0.079X₂₄。该模型的预测值为88.1%,解释力为88.4%。本研究通过代谢组学区分并揭示了高血压前期LFHS的特征性代谢模式。构建的PLS-DA模型有望为高血压前期中医证型的识别提供客观依据,并为从小分子和整体水平探索中医证型的生物学基础提供启示。

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