ArticleClinical epigenetics2018
Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality.
Article in Clinical epigenetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 68 citations in OpenAlex.
- Artificial intelligence for HIV care: a global systematic review of current studies and emerging trends.Journal of the International AIDS Society · 2025Pooled it
- Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts.PLoS pathogens · 2024Pooled it
- A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes.Genome medicine · 2023Pooled it
- Guidelines on optimizing DNA methylation reference panels for cell-type deconvolution.Communications biology · 2026Article
- Variations in Innate Immune Cell Subtypes Correlate with Epigenetic Clocks, Inflammaging and Health Outcomes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- AI Methods Tailored to Influenza, RSV, HIV, and SARS-CoV-2: A Focused Review.Pathogens (Basel, Switzerland) · 2025Review
- Epigenetic clocks and inflammaging: pitfalls caused by ignoring cell-type heterogeneity.GeroScience · 2025Article
- Aberrant DNA methylation of genes regulating CD4+ T cell HIV-1 reservoir in women with HIV.Clinical and translational medicine · 2025Article
- AI applications in HIV research: advances and future directions.Frontiers in microbiology · 2025Review
- Identifying the HIV-Resistance-Related Factors and Regulatory Network via Multi-Omics Analyses.International journal of molecular sciences · 2024Article
- Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.Tissue engineering. Part A · 2024Review
- Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker.Nature aging · 2024Article
- High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study.BMC medical research methodology · 2024Article
- An improved epigenetic counter to track mitotic age in normal and precancerous tissues.Nature communications · 2024Article
- Cis-meQTL for cocaine use-associated DNA methylation in an HIV-positive cohort show pleiotropic effects on multiple traits.BMC genomics · 2023Article
- Impact of age, antiretroviral therapy, and cancer on epigenetic aging in people living with HIV.Cancer medicine · 2023Article
- Epigenetic Age Acceleration Markers Are Associated With Physiologic Frailty and All-Cause Mortality in People With Human Immunodeficiency Virus.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Review
- DNA Methylation Analysis Reveals Distinct Patterns in Satellite Cell-Derived Myogenic Progenitor Cells of Subjects with Spastic Cerebral Palsy.Journal of personalized medicine · 2022Article
- Epigenome-wide epidemiologic studies of human immunodeficiency virus infection, treatment, and disease progression.Clinical epigenetics · 2022Review
Corrections and comments
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Authors and funding
12 authors at 8 institutions in 1 country.
Funding
Abstract
backgroundThe 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.
resultsWe 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.
conclusionWe demonstrated that smoking-associated DNA methylation features in white blood cells predict HIV infection-related clinical outcomes in a population living with HIV.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.