@article{Karp:2026:10.1016/j.jaci.2026.10.003,
author = {Karp, T and Faiz, A and Kerstjens, HAM and Nawijn, MC and Gillett, TE and Sun, Y and Kersten, ETG and Vonk, JM and Wen, H and Kraft, M and Beghé, B and Rabe, KF and Piraino, A and Papi, A and Brightling, CE and Singh, D and Kocks, JWH and Siddiqui, S and Koppelman, GH and van, den Berge M and Guryev, V and of, ATLANTIS investigators},
doi = {10.1016/j.jaci.2026.10.003},
journal = {J Allergy Clin Immunol},
title = {Accounting for seasonal variation of nasal gene expression improves transcriptome analysis of asthma.},
url = {http://dx.doi.org/10.1016/j.jaci.2026.10.003},
year = {2026}
}

Download

TY  - JOUR
AB  - INTRODUCTION: Environmental seasonal changes, including allergen exposure, pollutants, and viral prevalence, impact gene expression across human tissues. Therefore, season of sample collection is critical to consider when analyzing disease-associated transcriptional programs. In this study we aimed to investigate the effect of season on identification of asthma-associated genes. METHODS: We analyzed RNA-seq data from nasal brushes of asthma patients (n=361) and healthy controls (n=57) included in the ATLANTIS study. Samples were compared across two time periods defined by a data-driven approach: winter-spring (Nov 15 -May 14) and summer-autumn (May 15 - Nov 14), correcting for age, sex, smoking, and asthma status. Gene Set Variation Analysis (GSVA) scores of the obtained seasonal gene signatures were compared using Mann-Whitney U test in the independent PIAMA cohort (n=325) for replication. RESULTS: We identified 1,731 genes differentially expressed between the two time periods (813 higher and 918 lower in winter-spring compared with summer-autumn; FDR < 0.05). This signature was replicated in the PIAMA cohort nasal gene expression data and was independent of asthma or allergy status. Samples collected in winter-spring showed a significantly lower predicted proportion of ciliated cells (p = 0.005) and a higher proportion of basal cells (p = 0.04) compared to those from summer-autumn. Crucially, including season as a covariate in models for asthma-associated gene expression nearly doubled the number of differentially expressed genes, from 126 to 271 (FDR < 0.05). We conclude that season of sampling strongly affects the nasal transcriptome, and we demonstrate that season-adjusted analyses significantly enhance sensitivity for detecting disease-associated changes.
AU  - Karp,T
AU  - Faiz,A
AU  - Kerstjens,HAM
AU  - Nawijn,MC
AU  - Gillett,TE
AU  - Sun,Y
AU  - Kersten,ETG
AU  - Vonk,JM
AU  - Wen,H
AU  - Kraft,M
AU  - Beghé,B
AU  - Rabe,KF
AU  - Piraino,A
AU  - Papi,A
AU  - Brightling,CE
AU  - Singh,D
AU  - Kocks,JWH
AU  - Siddiqui,S
AU  - Koppelman,GH
AU  - van,den Berge M
AU  - Guryev,V
AU  - of,ATLANTIS investigators
DO  - 10.1016/j.jaci.2026.10.003
PY  - 2026///
TI  - Accounting for seasonal variation of nasal gene expression improves transcriptome analysis of asthma.
T2  - J Allergy Clin Immunol
UR  - http://dx.doi.org/10.1016/j.jaci.2026.10.003
UR  - https://www.ncbi.nlm.nih.gov/pubmed/42892519
ER  - 

Download