Evidence map›Paper›PMID 38245772›Full record

ArticleClinical epigenetics2024

Integrative analysis identifies gene signatures mediating the effect of DNA methylation on asthma severity and lung function.

Eskezeia Y Dessie, Lili Ding, Tesfaye B Mersha

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 16% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Proteomic Risk Score of Increased Respiratory Susceptibility: A Multicohort Study.American journal of respiratory and critical care medicine · 2025
    Article
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

3 authors at 1 institution in 1 country.

Eskezeia Y DessieDivision of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Lili DingDivision of Biostatistics and Epidemiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Tesfaye B MershaDivision of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA. tesfaye.mersha@cchmc.org.ORCID 0000-0002-9189-8447
Cincinnati Children's Hospital Medical Center · US

Funding

Epigenome-wide variations and socio-environmental exposures in African American asthmatic childrenR01HG011411 · NHGRI · CINCINNATI CHILDRENS HOSP MED CTR · PI MERSHA, TESFAYE B. · 2021 to 2025
$3.4M
NHGRI NIH HHS R01 HG011411
6 · The paper itself

Abstract

DNA methylation (DNAm) changes play a key role in regulating gene expression in asthma. To investigate the role of epigenetics and transcriptomics change in asthma, we used publicly available DNAm (asthmatics, n = 96 and controls, n = 46) and gene expression (asthmatics, n = 79 and controls, n = 39) data derived from bronchial epithelial cells (BECs). We performed differential methylation/expression and weighted co-methylation/co-expression network analyses to identify co-methylated and co-expressed modules associated with asthma severity and lung function. For subjects with both DNAm and gene expression data (asthmatics, n = 79 and controls, n = 39), machine-learning technique was used to prioritize CpGs and differentially expressed genes (DEGs) for asthma risk prediction, and mediation analysis was used to uncover DEGs that mediate the effect of DNAm on asthma severity and lung function in BECs. Finally, we validated CpGs and their associated DEGs and the asthma risk prediction model in airway epithelial cells (AECs) dataset. The asthma risk prediction model based on 18 CpGs and 28 DEGs showed high accuracy in both the discovery BEC dataset with area under the receiver operating characteristic curve (AUC) = 0.99 and the validation AEC dataset (AUC = 0.82). Genes in the three co-methylated and six co-expressed modules were enriched in multiple pathways including WNT/beta-catenin signaling and notch signaling. Moreover, we identified 35 CpGs correlated with DEGs in BECs, of which 17 CpGs including cg01975495 (SERPINE1), cg10528482 (SLC9A3), cg25477769 (HNF1A) and cg26639146 (CD9), cg17945560 (TINAGL1) and cg10290200 (FLNC) were replicated in AECs. These DEGs mediate the association between DNAm and asthma severity and lung function. Overall, our study investigated the role of DNAm and gene expression change in asthma and provided an insight into the mechanisms underlying the effects of DNA methylation on asthma, asthma severity and lung function.

Indexed as

AsthmaDNA MethylationEpigenesis, GeneticHumansLungTranscription FactorsTranscription FactorsAsthmaAsthma severityBiomarkersLung functionMediation analysisMulti-omics analysisWeighted correlation network analysis

Identifiers

PMID38245772
PMCPMC10800055
OpenAlexW4391057587

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.