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Project description: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.
2019-07-23 | GSE117860 | GEO
Project description: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.
2019-07-23 | GSE117859 | GEO
Project description:Smoking-associated DNA methylation features link to HIV outcomes
| PRJNA483450 | ENA
Project description:Smoking-associated DNA methylation features link to HIV outcomes [Infinium MethylationEPIC]
| PRJNA483457 | ENA
Project description:Smoking-associated DNA methylation features link to HIV outcomes [HumanMethylation450 BeadChip]
| PRJNA483456 | ENA
Project description:Genome wide DNA methylation profiling of smokers and non-smokers in PBMC samples. The Illumina Infinium 450k Human DNA methylation Beadchip v1.1 was used to obtain DNA methylation profiles across 485,577 CpGs in PBMC samples. Samples included 24 smokers and 28 non-smokers.
2017-02-13 | GSE59550 | GEO
Project description:Smoking is associated with poorer health outcomes for both African and European Americans. In order to better understand whether ethnic-specific genetic variation may underlie some of these differences, we compared the smoking-associated genome-wide methylation signatures of African Americans with those of European Americans, and followed up this analysis with a focused examination of the most ethnically divergent locus, cg19859270, at the GPR15 gene. We examined the association of methylation at this locus to the rs2230344 SNP and GPR15 gene and protein expression. Consistent with prior analyses, AHRR residue cg05575921 was the most differentially methylated residue in both African Americans and European Americans. However, the second most differentially methylated locus in African Americans, cg19859270, was only modestly differentially methylated in European Americans. Interrogation of the methylation status of this CpG residue found in GPR15, a chemokine receptor involved in HIV pathogenesis, showed a significant interaction of ethnicity with smoking as well as a marginal effect of genotype at rs2230344, a neighboring non-synonymous SNP, but only among African Americans. Gene and protein expression analyses showed that demethylation at cg19859270 was associated with an increase in both mRNA and protein levels. Since GPR15 is involved in the early stages of viral replication for some HIV-1 and HIV-2 isolates, and the prevalence of HIV is increased in African Americans and smokers, these data support a possible role for GPR15 in the ethnically dependent differential prevalence of HIV.
| S-EPMC4585036 | biostudies-literature
Project description:BACKGROUND:The effects of tobacco smoking on epigenome-wide methylation signatures in white blood cells (WBCs) collected from persons living with HIV may have important implications for their immune-related outcomes, including frailty and mortality. The application of a machine learning approach to the analysis of CpG methylation in the epigenome enables the selection of phenotypically relevant features from high-dimensional data. Using this approach, we now report that a set of smoking-associated DNA-methylated CpGs predicts HIV prognosis and mortality in an HIV-positive veteran population. RESULTS:We first identified 137 epigenome-wide significant CpGs for smoking in WBCs from 1137 HIV-positive individuals (p?<?1.70E-07). To examine whether smoking-associated CpGs were predictive of HIV frailty and mortality, we applied ensemble-based machine learning to build a model in a training sample employing 408,583 CpGs. A set of 698 CpGs was selected and predictive of high HIV frailty in a testing sample [(area under curve (AUC)?=?0.73, 95%CI 0.63~0.83)] and was replicated in an independent sample [(AUC?=?0.78, 95%CI 0.73~0.83)]. We further found an association of a DNA methylation index constructed from the 698 CpGs that were associated with a 5-year survival rate [HR?=?1.46; 95%CI 1.06~2.02, p?=?0.02]. Interestingly, the 698 CpGs located on 445 genes were enriched on the integrin signaling pathway (p?=?9.55E-05, false discovery rate = 0.036), which is responsible for the regulation of the cell cycle, differentiation, and adhesion. CONCLUSION:We demonstrated that smoking-associated DNA methylation features in white blood cells predict HIV infection-related clinical outcomes in a population living with HIV.
| S-EPMC6293604 | biostudies-literature
Project description:BackgroundDNA methylation has been hypothesized as a mechanism for explaining the association between smoking and adverse prostate cancer (PCa) outcomes. This study was aimed at assessing whether smoking is associated with prostate tumor DNA methylation and whether these alterations may explain in part the association of smoking with PCa recurrence and mortality.MethodsA total of 523 men had radical prostatectomy as their primary treatment, detailed smoking history data, long-term follow-up for PCa outcomes, and tumor tissue profiled for DNA methylation. Ninety percent of the men also had matched tumor gene expression data. A methylome-wide analysis was conducted to identify differentially methylated regions (DMRs) by smoking status. To select potential functionally relevant DMRs, their correlation with the messenger RNA (mRNA) expression of corresponding genes was evaluated. Finally, a smoking-related methylation score based on the top-ranked DMRs was created to assess its association with PCa outcomes.ResultsForty DMRs were associated with smoking status, and 10 of these were strongly correlated with mRNA expression (aldehyde oxidase 1 [AOX1], claudin 5 [CLDN5], early B-cell factor 1 [EBF1], homeobox A7 [HOXA7], lectin galactoside-binding soluble 3 [LGALS3], microtubule-associated protein τ [MAPT], protocadherin γ A [PCDHGA]/protocadherin γ B [PCDHGB], paraoxonase 3 [PON3], synaptonemal complex protein 2 like [SYCP2L], and zinc finger and SCAN domain containing 12 [ZSCAN12]). Men who were in the highest tertile for the smoking-methylation score derived from these DMRs had a higher risk of recurrence (odds ratio [OR], 2.29; 95% confidence interval [CI], 1.42-3.72) and lethal disease (OR, 4.21; 95% CI, 1.65-11.78) in comparison with men in the lower 2 tertiles.ConclusionsThis integrative molecular epidemiology study supports the hypothesis that smoking-associated tumor DNA methylation changes may explain at least part of the association between smoking and adverse PCa outcomes. Future studies are warranted to confirm these findings and understand the implications for improving patient outcomes. Cancer 2016;122:2168-77. © 2016 American Cancer Society.
| S-EPMC4930391 | biostudies-literature
Project description:Smoking is a well-documented risk factor in various cancers, especially lung cancer. In the current study, we tested the hypothesis that abnormal DNAm loci associated with smoking are enriched in genes and pathways that convey a risk of cancer by determining whether smoking-related methylated genes led to enrichment in cancer-related pathways. We analyzed two sets of smoking-related methylated genes from 28 studies originating from blood and buccal samples. By analyzing 320 methylated genes from 26 studies on blood samples (N = 17,675), we found 57 enriched pathways associated with different types of cancer (FDR < 0.05). Of these, 11 were also significantly overrepresented in the 661 methylated genes from two studies of buccal samples (N = 1,002). We further found the aryl hydrocarbon receptor signaling pathway plays an important role in the initiation of smoking-attributable cancer. Finally, we constructed a subnetwork of genes important for smoking-attributable cancer from the 48 non-redundant genes in the 11 oncogenic pathways. Of these, genes such as DUSP4 and AKT3 are well documented as being involved in smoking-related lung cancer. In summary, our findings provide robust and systematic evidence in support of smoking's impact on the epigenome, which may be an important contributor to cancer.
| S-EPMC5431893 | biostudies-literature