Maternal asthma imprints fetal lung ILC2s via glucocorticoid signaling leading to worsened allergic airway inflammation in murine adult offspring

T Tomoaki Takao A Ako Matsui (Division of Allergy and Immunology, Medical Institute of Bioregulation, Kyushu University) C Chie Kikutake (Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University) K Keiko Kan-o A Azusa Inoue M Mikita Suyama (Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University) I Isamu Okamoto M Minako Ito

Abstract

Abstract The root of asthma can be linked to early life, with prenatal environments influencing risk. We investigate the effects of maternal asthma on the offspring’s lungs during fetal and adult life. Adult offspring of asthmatic mothers show an increase in lung group 2 innate lymphoid cell (ILC2) number and function with allergen-induced lung inflammation. Offspring of asthmatic mothers show phenotypic alteration of their lung ILC2s during fetal life, with increased expression of genes related to activation and glucocorticoid signaling. Furthermore, these offspring carry overlapping chromatin-accessible altered regions, including glucocorticoid receptor-binding regions in their lung ILC2s both at the fetal stage and adulthood, suggesting persistent prenatal epigenetic changes. Moreover, maternal exposure to glucocorticoids has similar effects on fetal lung ILC2s and contributes to allergen-induced lung inflammation during adulthood. Thus, asthma during pregnancy may have long-term effects on lung ILC2s in the offspring from the embryonic period, contributing to an increased risk of developing asthma.

Article Details

Volume / Issue Vol. 16, Issue 1
Published January 13, 2025
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (8)

T

Tomoaki Takao

A

Ako Matsui

Division of Allergy and Immunology, Medical Institute of Bioregulation, Kyushu University

C

Chie Kikutake

Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University

K

Keiko Kan-o

A

Azusa Inoue

M

Mikita Suyama

Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University

I

Isamu Okamoto

M

Minako Ito