Zhao Gaowa, Cheng Dong, Wang Yu, Cao Yalan, Xiang Shuting, Yu Qin
Department of Cardiology, Affiliated Zhongshan Hospital of Dalian University Jiefang Street 6, Zhongshan District Dalian 116001 China
Medical College, Dalian University Dalian 116622 China.
RSC Adv. 2020 May 22;10(33):19621-19628. doi: 10.1039/c9ra10684g. eCollection 2020 May 20.
: a dried blood spot (DBS) method integrated with direct infusion mass spectrometry (MS) focused on a metabolomic analysis was applied to detect and compare the difference of metabolites between the heart failure (HF) patients and non-HF patients in order to facilitate the early detection of heart failures, provide targeted intervention and offer prognostic insights. : the method we used was an untargeted metabolic approach. The dry blood spot mass spectrometry (DBS) was used to analyze 23 types of amino acids and 26 types of carnitine in blood samples. In the current study, 49 metabolites were selected to establish the PLS-DA model to compare the differences between the 117 HF patients and 118 non-HF patients, which inclined to detect the difference between the two groups. Multiple algorithms were run for selecting different metabolites as potential biomarkers. Ten-fold cross validation method was used to verify and evaluate the selected potential biomarkers. : through significant analysis of the microarrays (SAM) and analysis of 9 parameters, 8 metabolites showed significant discrepancies between the HF and non-HF groups. Among these metabolites, the levels of 5 metabolites were increased, and the other 3 metabolites were decreased in the HF group compared with the non-HF group. However, 7 metabolites including Asn, C0, C14, C4DC, C5-OH, C6 and Glu were selected to distinguish the HF group from the non-HF group with specificity and sensitivity of 0.8475 and 0.8974, respectively. : metabolomic study for chronic heart failure (CHF) patients based on the dried blood spot mass spectrometry approach would be beneficial to understand the metabolic pathway of HF, and probably work as biomarkers to predict the prognosis of HF and provide the basis for an individualized treatment.
一种结合直接进样质谱法（MS）的干血斑（DBS）方法用于代谢组学分析，以检测和比较心力衰竭（HF）患者与非HF患者之间代谢物的差异，从而促进心力衰竭的早期检测，提供针对性干预并提供预后见解。我们使用的方法是一种非靶向代谢方法。干血斑质谱法（DBS）用于分析血样中的23种氨基酸和26种肉碱。在本研究中，选择49种代谢物建立偏最小二乘判别分析（PLS-DA）模型，以比较117例HF患者和118例非HF患者之间的差异，倾向于检测两组之间的差异。运行多种算法以选择不同的代谢物作为潜在生物标志物。采用十倍交叉验证法对所选潜在生物标志物进行验证和评估。通过微阵列显著性分析（SAM）和9个参数的分析，8种代谢物在HF组和非HF组之间存在显著差异。在这些代谢物中，与非HF组相比，HF组中5种代谢物水平升高，另外3种代谢物水平降低。然而，选择包括天冬酰胺、C0、C14、C4DC、C5-OH、C6和谷氨酸在内的7种代谢物来区分HF组和非HF组，特异性和敏感性分别为0.8475和0.8974。基于干血斑质谱法对慢性心力衰竭（CHF）患者进行代谢组学研究将有助于了解HF的代谢途径，并可能作为预测HF预后的生物标志物，为个体化治疗提供依据。
