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目的应用质谱核磁共振(1H-nuclear magnetic resonance,1H-NMR)代谢组技术研究维吾尔族原发性高血压(高血压)患者和健康正常人血清中代谢物,筛选维吾尔族高血压患者特征代谢物,并从代谢途径探讨高血压发病机制。方法 256例维吾尔族观察对象进入研究范围(高血压组为157,正常组为99例),均来自新疆医科大学高血压研究组2009~2012年在新疆和田策勒县的维吾尔族人群流行病学调查,其中维吾尔族要求三代血亲为本民族血统。高血压组和正常对照组血清标本采用Inova600型核磁共振波谱仪分别进行1H-NMR实验,采集NMR谱图后进行数据预处理。鉴定高血压患者和健康者血清中差异性代谢成分,根据差异性代谢物信息构建与高血压相关的代谢途径网络。结果两组年龄、体质量、身高和血清三酰甘油、低密度脂蛋白胆固醇浓度比较,差异无统计意义(P>0.05);两组空腹血糖、收缩压、舒张压和血清高密度脂蛋白胆固醇、总胆固醇浓度比较,差异有统计学意义(P<0.05)。正交偏最小二乘判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)结果显示主成分积分值集中分布于椭圆形散点图(95%置信区间内)的4个区域,从得分图和3D空间分布图中可以明确两组的分布区域完全分开,高血压组与正常组血清在代谢成分上有明显差异,鉴定出12种差异性代谢物。高血压组与正常组比较,血清中多种氨基酸浓度显著降低,包括缬氨酸、丙氨酸、丙酮酸、肌醇、酪氨酸、甲基组氨酸等,差异有统计学意义(P<0.05)。高血压组者血清中血清极低密度脂蛋白胆固醇、低密度脂蛋白胆固醇、乳酸、丙酮较正常组增加,差异有统计学意义(P<0.05)。结论 1H-NMR代谢组技术结合OPLS-DA模式识别方法是高通量筛选高血压患者血清中代谢物差异表达的有效研究手段。使用OPLSDA对NMR谱数据进行模式识别分析,可以区分高血压患者和健康正常人代谢物的差异。维吾尔族高血压患者体内的代谢表型发生了显著变异,12种特征代谢物有可能是高血压的血清潜在生物标记物。
OBJECTIVE: To study the metabolites of essential hypertension (Hypertension) and healthy controls in the Uigur population by 1H-nuclear magnetic resonance (1H-NMR) , And explore the pathogenesis of hypertension from metabolic pathways. Methods A total of 256 Uygur subjects were enrolled into the study (157 in the hypertension group and 99 in the normal group), all from the Uyghur population epidemiology in Xinjiang Hypertension Group from 2009 to 2012 in Cele, Xinjiang Survey, in which the Uyghurs require three generations of blood-based ethnic origin. The blood samples of hypertension group and normal control group were respectively analyzed by 1H-NMR with Inova600 nuclear magnetic resonance spectrometer. The NMR spectra were collected before data pretreatment. Identify differential metabolites in the serum of hypertensive patients and healthy individuals, and construct metabolic networks related to hypertension according to differential metabolite information. Results There was no significant difference in age, body weight, height, serum triglyceride, and LDL cholesterol between the two groups (P> 0.05). The fasting blood glucose, systolic pressure, diastolic blood pressure and serum high density lipoprotein cholesterol , Total cholesterol concentration, the difference was statistically significant (P <0.05). The results of orthogonal partial least squares discriminant analysis (OPLS-DA) showed that the principal component integral values were concentrated in 4 regions of elliptic scattergram (95% confidence interval) In the 3D spatial distribution map, the distribution of the two groups can be clearly separated, and there are significant differences in the metabolic components of the serum between the hypertension group and the normal group, and 12 kinds of differential metabolites are identified. Compared with the normal group, the concentrations of amino acids in the serum were significantly decreased in the hypertension group, including valine, alanine, pyruvate, inositol, tyrosine and methyl histidine (P <0.05). Serum levels of serum very low density lipoprotein cholesterol, low density lipoprotein cholesterol, lactate and acetone in hypertension group were significantly higher than those in normal group (P <0.05). Conclusion The 1H-NMR metabolomics combined with OPLS-DA pattern recognition is an effective method for high-throughput screening of differential expression of metabolites in the serum of hypertensive patients. Using OPLSDA for pattern recognition analysis of NMR spectral data, the differences between metabolites in hypertensive patients and healthy individuals can be distinguished. The metabolic phenotype of Uighur hypertensive patients showed significant variation, and 12 kinds of characteristic metabolites may be potential serum biomarkers of hypertension.