From the Universitätsklinikum RWTH Aachen, Institute for Molecular Cardiovascular Research, Germany (P.R.G., V.J., H.N., E.L., F.K., E.B., J.J.); Experimental Vascular Pathology, Cardiovascular Research Institute Maastricht, University of Maastricht, The Netherlands (P.R.G., E.B., J.J.); Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria (G.H.); Departments of Medicine and Surgery (G.B.) and Statistics and Quantitative Methods (D.S.), University of Milano-Bicocca, Italy; Department of Cardiovascular, Neural, and Metabolic Sciences, Istituto Auxologico Italiano, Milan, Italy (G.B.); Istituto Auxologico Italiano, IRCCS, Milan, Italy (A.Z., D.S.); Università degli Studi di Milano, Italy (A.Z.); Department of Internal Medicine IV, Medical University Innsbruck, Austria (P.P.); Charité-Universitätsmedizin Berlin (CBF), Germany (A.S., W.Z.); Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK (C.D.); Department of Hypertension and Diabetology, Medical University of Gdansk, Poland (K.N.); First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Krakow, Poland (K.K.-J.); and Internal Medicine II, Universitätsklinikum RWTH Aachen, Germany (J.F.).
Hypertension. 2017 Aug;70(2):412-419. doi: 10.1161/HYPERTENSIONAHA.116.08906. Epub 2017 Jun 26.
Despite advancements in lowering blood pressure, the best approach to lower it remains controversial because of the lack of information on the molecular basis of hypertension. We, therefore, performed plasma proteomics of plasma from patients with hypertension to identify molecular determinants detectable in these subjects but not in controls and vice versa. Plasma samples from hypertensive subjects (cases; n=118) and controls (n=85) from the InGenious HyperCare cohort were used for this study and performed mass spectrometric analysis. Using biostatistical methods, plasma peptides specific for hypertension were identified, and a model was developed using least absolute shrinkage and selection operator logistic regression. The underlying peptides were identified and sequenced off-line using matrix-assisted laser desorption ionization orbitrap mass spectrometry. By comparison of the molecular composition of the plasma samples, 27 molecular determinants were identified differently expressed in cases from controls. Seventy percent of the molecular determinants selected were found to occur less likely in hypertensive patients. In cross-validation, the overall was 0.434, and the area under the curve was 0.891 with 95% confidence interval 0.8482 to 0.9349, <0.0001. The mean values of the cross-validated proteomic score of normotensive and hypertensive patients were found to be -2.007±0.3568 and 3.383±0.2643, respectively, <0.0001. The molecular determinants were successfully identified, and the proteomic model developed shows an excellent discriminatory ability between hypertensives and normotensives. The identified molecular determinants may be the starting point for further studies to clarify the molecular causes of hypertension.
尽管在降低血压方面取得了进展，但由于缺乏高血压分子基础的信息，降低血压的最佳方法仍然存在争议。因此，我们对高血压患者的血浆进行了血浆蛋白质组学分析，以鉴定在这些患者中可检测到而在对照组中不可检测的分子决定因素。本研究使用了来自 InGenious HyperCare 队列的高血压患者（病例；n=118）和对照者（n=85）的血浆样本，并进行了质谱分析。使用生物统计学方法鉴定了与高血压特异性的血浆肽，并使用最小绝对收缩和选择算子逻辑回归建立了模型。使用基质辅助激光解吸电离轨道阱质谱离线鉴定潜在肽并测序。通过比较血浆样本的分子组成，鉴定出 27 个在病例与对照之间表达不同的分子决定因素。所选择的分子决定因素有 70%被发现不太可能出现在高血压患者中。在交叉验证中，总体的为 0.434，曲线下面积为 0.891，95%置信区间为 0.8482 至 0.9349，<0.0001。在经过交叉验证的正常血压和高血压患者的蛋白质组得分的平均值分别为-2.007±0.3568 和 3.383±0.2643，<0.0001。成功鉴定了分子决定因素，开发的蛋白质组模型在高血压患者和正常血压患者之间具有出色的区分能力。鉴定出的分子决定因素可能是进一步研究阐明高血压分子原因的起点。
