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Smoking-associated DNA methylation features link to HIV outcomes

ABSTRACT: Smoking-associated DNA methylation features link to HIV outcomes

PROVIDER: PRJNA483450 | ENA |

REPOSITORIES: ENA

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Smoking-associated DNA methylation features link to HIV outcomes [Infinium MethylationEPIC]

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.

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Project description:Smoking-associated DNA methylation features link to HIV outcomes [HumanMethylation450 BeadChip]

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Smoking-associated DNA methylation features link to HIV outcomes [Infinium MethylationEPIC]

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Smoking-associated DNA methylation features link to HIV outcomes

Project description:This SuperSeries is composed of the SubSeries listed below.

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Distinguishing smoking related lung disease phenotypes via imaging and molecular features

Project description:Distinguishing smoking related lung disease phenotypes via imaging and molecular features

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Cannabis smoking is associated with advanced epigenetic age

Project description:Cannabis use has been controversial, largely having been designated a controlled substance over the last century. The link between cannabis smoking and disease pathogenesis may best be explored through DNA methylation, an epigentic mechanism. We investigated the relationship between epigenetic age and cannabis smoking in participants within the Canadian Cohort of Obstructive Lung Disease (CanCOLD) cohort (n=93) (ClinicalTrials.gov identifier NCT00920348). Blood samples were profiled for DNA methylation using the Illumina MethylationEPIC BeadChipv1 at two separate laboratories and the blood epigenetic age of each sample was calculated using the Clock Foundation tool (https://dnamage.clockfoundation.org). An ANOVA was used to identify differences in the age acceleration residuals associated with cannabis smoking status (never, former, and current), adjusted for chronological age, sex, body mass index (BMI), batch, cigarette smoking status, and the first two principal components of blood cell proportions. Our observations indicated that current cannabis smoking and higher joint-years exposure are associated with epigenetic age acceleration; cessation, however, may help to normalize in part this age acceleration.

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