ArticleJournal of insurance medicine (New York, N.Y.)2018
A Droplet Digital PCR Assay for Smoking Predicts All-Cause Mortality.
Article in Journal of insurance medicine (New York, N.Y.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Opioid medication use and blood DNA methylation: epigenome-wide association meta-analysis.Epigenomics · 2022Pooled it
- Pulmonary Function and Blood DNA Methylation: A Multiancestry Epigenome-Wide Association Meta-analysis.American journal of respiratory and critical care medicine · 2022Pooled it
- Linking Prenatal Environmental Exposures to Lifetime Health with Epigenome-Wide Association Studies: State-of-the-Science Review and Future Recommendations.Environmental health perspectives · 2023Review
- The association between DNA methylation of 6p21.33 and AHRR in blood and coronary heart disease in Chinese population.BMC cardiovascular disorders · 2022Article
- Methylation, smoking, and reduced lung function.The European respiratory journal · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectives-Determine whether an epigenetic assay for smoking predicts all-cause mortality in adults participating in a longitudinal study of Iowa adoptees.
background-Improved biomarkers for smoking are needed given its large public health impact and significant limitations of both self-report and current biomarkers, such as cotinine in detecting smoking. In the past 5 years, multiple epigenome-wide association studies of smoking have identified loci suitable for translation as epigenetic biomarkers for smoking, in particular the CpG cg05575921. Digital polymerase chain reaction methods hold promise for the development of this and other epigenetic biomarkers.
methods-Participants in the Iowa Adoption Studies were interviewed regarding their smoking habits. DNA was prepared from whole blood and bisulfite-converted for methylation analysis and digital droplet polymerase chain reaction assay of methylation at cg05575921 was performed. National Death Index records were requested for 584 study participants, resulting in 24 complete matches, 210 partial matches and 350 non-matching records. Complete matches were coded as deceased while the remainder were coded as alive (ie, censored). In total, methylation data and vital status information were available for a total of N = 193 subjects, including 15 deceased and 178 non-deceased. Cox regression was used to examine the ability of cg05575921 methylation as a continuous value to predict the timing of mortality with and without the inclusion of age, sex, race, BMI, marital status, educational status, socioeconomic status, cardiovascular risk factors, and a history of cancer as covariates.
results-Methylation at cg05575921 predicted the hazard of mortality as the sole predictor and after accounting for major demographic and clinical risk factors. The fitted model showed the hazard ratio increased by 3.5% for every 1% decrease in methylation.
conclusions-Decreased methylation at cg05575921, an emerging epigenetic biomarker for smoking, was associated with early mortality in a longitudinal study of adults after accounting for the impact of major demographic and clinical risk factors for all-cause mortality. This approach may be useful in clinical research or actuarial assessments.
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