Smoking-associated DNA methylation features link to HIV outcomes [HumanMethylation450 BeadChip]. Smoking-associated DNA methylation features link to HIV outcomes [HumanMethylation450 BeadChip]

Smoking is common in people who live with HIV infection and has significant adverse effects on HIV outcomes. The impacts of smoking on methylome has been well established in non-HIV populations. However, the smoking’s effects on host methylome in HIV-positive population has not been investigated and it is unknown if smoking-associated DNA methylation link to HIV outcomes. In this study, we applied machine learning methods selected smoking-associated DNA methylation features to predict HIV related frailty and mortality. Overall design: We have collected blood samples from the Veteran Aging Cohort Study (VACS). Smoking status was based on self -report. HIV frailty was measured by VACS index. All DNA samples were extracted from whole blood in HIV-positive men. Epigenome-wide DNA methylation of each sample was profiled using the Illumina Infinium HumanMethylation450 BeadChip array. Data were normalized and controlled for quality using standard techniques. Please note that the 'readme.txt' contains a brief description for each sample characteristics. The following data is included in each sample records (as characteristics) and in the 'PCA_analysis_results.txt' file: Cont_Pr_850k_PC1-PC30 PCA analysis results (PC1 to PC30) on positive control intensities resi_850k_PC1-PC5 PCA analysis results (PC1 to PC5) on residual values of the first regression model

吸烟在HIV感染者中十分普遍，且对HIV转归存在显著不良影响。吸烟对甲基化组（methylome）的影响在非HIV人群中已得到充分证实。然而，目前尚未有研究探讨吸烟对HIV阳性人群宿主甲基化组的影响，且吸烟相关DNA甲基化（DNA methylation）是否与HIV转归相关仍属未知。本研究采用机器学习方法筛选吸烟相关DNA甲基化特征，以预测HIV相关衰弱与死亡。
总体研究设计：我们从退伍军人衰老队列研究（Veteran Aging Cohort Study, VACS）中采集了血液样本。吸烟状态基于自我报告确定。HIV相关衰弱程度通过VACS指数进行评估。所有DNA样本均提取自HIV阳性男性的全血。采用Illumina Infinium HumanMethylation450 BeadChip芯片对每个样本进行全表观基因组DNA甲基化（Epigenome-wide DNA methylation）谱分析。数据通过标准技术完成标准化处理与质量控制。
请注意，"readme.txt"文件中包含了各样本特征的简要说明。以下数据既作为特征包含于各样本记录中，也存在于"PCA_analysis_results.txt"文件内：基于阳性对照信号强度的Cont_Pr_850k_PC1-PC30主成分分析（Principal Component Analysis, PCA）结果（PC1至PC30），以及基于首次回归模型残差的resi_850k_PC1-PC5主成分分析（Principal Component Analysis, PCA）结果（PC1至PC5）。