McKnight Tracy R, Yoshihara Hikari A I, Sitole Lungile J, Martin Jeffery N, Steffens Francois, Meyer Debra
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Mol Biosyst. 2014 Nov;10(11):2889-97. doi: 10.1039/c4mb00347k.
Individuals infected with the human immunodeficiency virus (HIV) often suffer from concomitant metabolic complications. Treatment with antiretroviral therapy has also been shown to alter the metabolism of patients. Although chemometric analysis of nuclear magnetic resonance (NMR) spectra of human sera can distinguish normal sera (HIVneg) from HIV-infected sera (HIVpos) and sera from HIV-infected patients on antiretroviral therapy (ART), quantitative analysis of the discriminating metabolites and their relationship to disease status has yet to be determined. The objectives of the study were to analyze NMR spectra of HIVneg, HIVpos, and ART serum samples with a combination of chemometric and quantitative methods and to compare the NMR data with disease status as measured by viral load and CD4 count. High-resolution magic angle spinning (HRMAS) NMR spectroscopy was performed on HIVneg (N = 10), HIVpos (N = 10), and ART (N = 10) serum samples. Chemometric linear discriminant analysis classified the three groups of spectra with 100% accuracy. Concentrations of 12 metabolites were determined with a semi-parametric metabolite quantification method named high-resolution quantum estimation (HR-QUEST). CD4 count was directly associated with alanine (p = 0.008), and inversely correlated with both glutamine (p = 0.017) and glucose (p = 0.022) concentrations. A multivariate linear model using alanine, glutamine and glucose as covariates demonstrated an association with CD4 count (p = 0.038). The combined chemometric and quantitative analysis of the data disclosed previously unknown associations between specific metabolites and disease status. The observed associations with CD4 count are consistent with metabolic disorders that are commonly seen in HIV-infected patients.
感染人类免疫缺陷病毒(HIV)的个体常常伴有代谢并发症。抗逆转录病毒疗法也已被证明会改变患者的新陈代谢。尽管对人血清核磁共振(NMR)谱进行化学计量分析能够区分正常血清(HIV阴性)与HIV感染血清(HIV阳性)以及接受抗逆转录病毒疗法(ART)的HIV感染患者的血清,但对具有鉴别作用的代谢物进行定量分析及其与疾病状态的关系尚未确定。本研究的目的是结合化学计量学和定量方法分析HIV阴性、HIV阳性和接受ART治疗的血清样本的NMR谱,并将NMR数据与通过病毒载量和CD4细胞计数衡量的疾病状态进行比较。对HIV阴性(N = 10)、HIV阳性(N = 10)和接受ART治疗(N = 10)的血清样本进行了高分辨率魔角旋转(HRMAS)NMR光谱分析。化学计量学线性判别分析以100%的准确率对三组光谱进行了分类。使用一种名为高分辨率量子估计(HR-QUEST)的半参数代谢物定量方法测定了12种代谢物的浓度。CD4细胞计数与丙氨酸直接相关(p = 0.008),与谷氨酰胺(p = 0.017)和葡萄糖(p = 0.022)浓度呈负相关。使用丙氨酸、谷氨酰胺和葡萄糖作为协变量的多元线性模型显示与CD4细胞计数相关(p = 0.038)。对数据进行的化学计量学和定量分析相结合,揭示了特定代谢物与疾病状态之间此前未知的关联。观察到的与CD4细胞计数的关联与HIV感染患者中常见代谢紊乱一致。