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. 2025 May 10;17(1):79.
doi: 10.1186/s13148-025-01858-4.

Maternal asthma and newborn DNA methylation

Affiliations

Maternal asthma and newborn DNA methylation

Casper-Emil Tingskov Pedersen et al. Clin Epigenetics. .

Abstract

Background: Prenatal exposure to maternal asthma may influence DNA methylation patterns in offspring, potentially affecting their susceptibility to later diseases including asthma.

Objective: To investigate the relationship between parental asthma and newborn blood DNA methylation.

Methods: Epigenome-wide association analyses were conducted in 13 cohorts on 7433 newborns with blood methylation data from the Illumina450K or EPIC array. We used fixed effects meta-analyses to identify differentially methylated CpGs (DMCs) and comb-p to identify differentially methylated regions (DMRs) associated with maternal asthma during pregnancy and maternal asthma ever. Paternal asthma was analyzed for comparison. Models were adjusted for covariates and cell-type composition. We examined whether implicated sites related to gene expression analyses in publicly available data for childhood blood and adult lung.

Results: We identified 27 CpGs associated with maternal asthma during pregnancy at False Discovery Rate < 0.05 but none for maternal asthma ever. Two distinct CpGs were associated with paternal asthma. We observed 5 DMRs associated with maternal asthma during pregnancy 3 associated with maternal asthma ever and 13 DMRs associated with paternal asthma. Gene expression analysis using data in blood from 832 children and lung from 424 adults showed associations between identified DMCs using maternal asthma and expression of several genes, including HLA genes and HOXA5, previously implicated in asthma or lung function.

Conclusion: Parental asthma, especially maternal asthma during pregnancy, may be associated with alterations in newborn DNA methylation. These findings might shed light on underlying mechanisms for asthma susceptibility.

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Conflict of interest statement

Declarations. Competing interests: All authors declare no potential, perceived or real conflict of interest regarding the content of this manuscript. The funding agencies did not have any role in design and conduct of the study; collection, management and interpretation of the data; or preparation, review or approval of the manuscript. No pharmaceutical company was involved in the study.

Figures

Fig. 1
Fig. 1
Flowchart describing the number of samples, the primary quality control filters as well as the analyses included
Fig. 2
Fig. 2
Manhattan plot of epigenome-wide association of maternal asthma during pregnancy and offspring methylation. Models include the following covariates: child sex, maternal smoking during pregnancy, gestational age, mode of delivery, maternal age at childbirth, maternal socioeconomic status, estimated cell type, batch covariates and ancestry. Panel A) shows analysis restricted to 435,329 probes on the 450 K chip for 7 cohorts using 202 exposed and 2946 non-exposed individuals (lambda = 1.09), and panel B) shows 321,034 probes exclusive to the EPIC chip for 2 cohorts using 76 exposed and 675 non-exposed individuals (lambda = 1.18). The red line indicates 5% FDR significance
Fig. 3
Fig. 3
Spearman correlations of effects from meta-analyses of all included models for A) CpGs pertaining to the overlap between the 450 K and EPIC chip and B) the CpGs unique to the EPIC chip. MAP, maternal asthma during pregnancy; MAE, maternal asthma ever while; PAE, paternal asthma ever. Sex-stratified models are defined by suffixes. ‘Int’ represent interaction models testing for differences between the sexes

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