Evidence map›Paper›PMID 35716602›Full record

ArticleRespiratory medicine

Predicting risk of lung function impairment and all-cause mortality using a DNA methylation-based classifier of tobacco smoke exposure.

Christina M Eckhardt, Haotian Wu, Diddier Prada, Pantel S Vokonas, David Sparrow, Lifang Hou, Joel Schwartz, Andrea A Baccarelli

Abstract read
In one paragraph

Article in Respiratory medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Christina M EckhardtColumbia University Irving Medical Center, Division of Pulmonary, Allergy and Critical, Care Medicine, Department of Medicine, New York, NY, USA. Electronic address: Cme2113@cumc.columbia.edu.
Haotian WuColumbia University Mailman School of Public Health, Environmental Health Sciences, Department, New York, NY, USA.
Diddier PradaColumbia University Mailman School of Public Health, Environmental Health Sciences, Department, New York, NY, USA; Instituto Nacional de Cancerología, México City, Mexico.
Pantel S VokonasBoston University School of Medicine, VA Normative Aging Study, VA, Boston, USA; Healthcare System and Department of Medicine, Boston, MA, USA.
David SparrowBoston University School of Medicine, VA Normative Aging Study, VA, Boston, USA; Healthcare System and Department of Medicine, Boston, MA, USA.
Lifang HouNorthwestern Feinberg School of Medicine, Department of Preventive Medicine, Chicago, IL, USA.
Joel SchwartzHarvard T.H. Chan School of Public Health, Department of Epidemiology, Cambridge, MA, USA.
Andrea A BaccarelliColumbia University Mailman School of Public Health, Environmental Health Sciences, Department, New York, NY, USA.

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
NRSA Training CoreTL1TR001875 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SPANN, MARISA N, TAYLOR, JACQUELYN Y · 2016 to 2025
$8.9M
Circulating microRNAs in Extracellular Vesicles, Air Particulate Pollution, and Lung Function in an Aging CohortR01ES025225 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BACCARELLI, ANDREA · 2016 to 2020
$2.9M
NCATS NIH HHS TL1 TR001875NCATS NIH HHS UL1 TR001873NIEHS NIH HHS P30 ES009089NIEHS NIH HHS R01 ES025225
6 · The paper itself

Abstract

backgroundThe Epigenetic Smoking Status Estimator (EpiSmokEr) predicts smoking phenotypes based on DNA methylation at 121 CpG sites.

objectiveEvaluate associations of EpiSmokEr-predicted versus self-reported smoking phenotypes with lung function and all-cause mortality in a cohort of older adults.

methodsThe prospective Normative Aging Study collected DNA methylation measurements from 1999 to 2012 with follow-up through 2016. The R package EpiSmokEr derived predicted smoking phenotypes based on DNA methylation levels assayed by the Illumina HumanMethylation450 Beadchip. Spirometry was collected every 3-5 years. Airflow limitation was defined as forced expiratory volume in 1 s/forced vital capacity <0.7. Vital status was monitored through periodic mailings.

resultsAmong 784 participants contributing 5414 person-years of follow-up, the EpiSmokEr-predicted smoking phenotypes matched the self-reported phenotypes for 228 (97%) never smokers and 22 (71%) current smokers. In contrast, EpiSmokEr classified 407 (79%) self-reported former smokers as never smokers. Nonetheless, the EpiSmokEr-predicted former smoking phenotype was more strongly associated with incident airflow limitation (hazard ratio [HR] = 3.15, 95% confidence interval [CI] = 1.50-6.59) and mortality (HR = 2.11, 95% CI = 1.56-2.85) compared to the self-reported former smoking phenotype (airflow limitation: HR = 2.21, 95% CI = 1.13-4.33; mortality: HR = 1.08, 95% CI = 0.86-1.36). Risk of airflow limitation and death did not differ among self-reported never smokers and former smokers who were classified as never smokers. The discriminative accuracy of EpiSmokEr-predicted phenotypes for incident airflow limitation and mortality was improved compared to self-reported phenotypes.

conclusionsThe DNA methylation-based EpiSmokEr classifier may be a useful surrogate of smoking-induced lung damage and may identify former smokers most at risk of adverse smoking-related health effects.

Indexed as

Tobacco Smoke PollutionDNA MethylationForced Expiratory VolumeHumansLungProspective StudiesRisk FactorsTobacco Smoke PollutionAll-cause mortalityDNA MethylationLung functionSmoking

Identifiers

PMID35716602
PMCPMC10560590

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.