Journal Article

DZNE-2026-00582

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Large-scale analysis of temporal gene expression variation in peripheral blood.

Mishra, N. ; Kimmig, F. ; Vandeputte, D. ; Talevi, V.DZNE* ; De Commer, L. ; Verspecht, C. ; Vich Vila, A. ; El-Sayed Moustafa, J. S. ; Kreft, L. ; Botzki, A. ; El Darzi, Y. ; Proost, S. ; Devolder, L. ; Wang, D. ; Bernardes, J. P. ; Aziz, N. A.DZNE* ; consortium, S. (Collaboration Author) ; Franke, A. ; Schreiber, S. ; Dermitzakis, E. T. ; Vieira-Silva, S. ; Falony, G. ; Small, K. S. ; Breteler, M. M. B.DZNE* ; Schultze, J. L.DZNE* ; Raes, J. ; Rosenstiel, P. ; Aden, K. (Contributor) ; Andersen, V. (Contributor) ; Banos, A. (Contributor) ; Bertsias, G. (Contributor) ; Beyer, M. (Contributor)Extern* ; Blase, J. I. (Contributor) ; Boumpas, D. (Contributor) ; Christofidou, P. (Contributor) ; Finckh, A. (Contributor) ; Gasparoni, G. (Contributor) ; Georges, M. (Contributor) ; Gu, W. (Contributor) ; Häsler, R. (Contributor) ; Huthmacher, S. (Contributor) ; Jawhara, M. (Contributor) ; Kenyon, A. (Contributor) ; Kratsch, C. (Contributor) ; Krause, R. (Contributor) ; Lauc, G. (Contributor) ; Lyons, P. A. (Contributor) ; Mangino, M. (Contributor) ; McKinney, E. F. (Contributor) ; Natoli, G. (Contributor) ; Nordström, K. (Contributor) ; Ostaszewski, M. (Contributor) ; Overgaard, S. H. (Contributor) ; Pezer, M. (Contributor) ; Rahmouni, S. (Contributor) ; Reiz, B. (Contributor) ; Rosati, E. (Contributor) ; Sanoudou, D. (Contributor) ; Satagopam, V. (Contributor) ; Schneider, R. (Contributor) ; Schulte-Schrepping, J. (Contributor)Extern* ; Sidiropoulos, P. (Contributor) ; Smith, K. G. C. (Contributor) ; Sørensen, S. B. (Contributor) ; Spector, T. (Contributor) ; Vojta, A. (Contributor) ; Walter, J. (Contributor) ; Warnat-Herresthal, S. (Contributor)Extern* ; Zoldoš, V. (Contributor)

2026
Springer Nature [London]

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Please use a persistent id in citations: doi:10.1038/s41467-026-73218-6

Abstract: Transcriptomic profiling of peripheral blood offers a promising, non-invasive approach for disease diagnosis and monitoring. However, its clinical translation is hindered by limited knowledge of the natural temporal variation. Here, we present a comprehensive reference map of longitudinal transcriptomic variability, based on RNA-sequencing of 333 healthy individuals sampled at three time points over six months. We find that 85% of genes and 99% of transcripts exhibit greater intra-individual than inter-individual variation, primarily driven by dynamic regulation of housekeeping pathways. In contrast, immune-related transcripts -particularly those linked to T and B cell activity- are strikingly stable over time. Gene expression levels drive inter-individual differences, while splicing variation contributes more to intra-individual fluctuation. In an independent twin cohort (148 monozygotic, 166 dizygotic), genes with high inter-individual variability show greater heritability, suggesting genetic control of steady-state expression. By integrating extensive clinical and environmental data, we trace temporal expression changes to genetic, compositional, and external factors, and identify robust seasonal and sex-specific signatures. These findings were validated in a third, cross-sectional cohort of 3,480 individuals. The observed temporal variation patterns have important implications for cohort-based transcriptomic analyses, as they may limit discovery and reproducibility of expression quantitative trait loci and increase the risk of spurious associations in cross-sectional studies. This resource provides a critical baseline for distinguishing disease-associated transcriptomic changes from normal physiological variation, advancing the reliability of blood-based biomarkers in clinical practice.

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Contributing Institute(s):

1. Population & Clinical Neuroepidemiology (AG Aziz)
2. Population Health Sciences (AG Breteler)
3. Clinical Single Cell Omics (CSCO) / Systems Medicine (AG Schultze)
4. Platform for Single Cell Genomics and Epigenomics (PRECISE)

Research Program(s):

1. 354 - Disease Prevention and Healthy Aging (POF4-354) (POF4-354)
2. 352 - Disease Mechanisms (POF4-352) (POF4-352)

Experiment(s):

1. Rhineland Study / Bonn
2. Platform for Single Cell Genomics and Epigenomics at DZNE University of Bonn

Appears in the scientific report 2026

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