Authors
Haotian Li, Sai Liu, Zheng Zhou, Qiulun Lu, Guangji Wang, Zheying Zhu, Xinuo Li
Published in
Briefings in bioinformatics. Volume 27. Issue 5. Sep 01, 2026.
Abstract
Aging shapes disease susceptibility and recovery, yet it remains unclear whether disease-induced molecular perturbations can be quantitatively mapped onto healthy aging trajectories. Here, we integrated 10 753 whole-blood transcriptomic profiles from 23 cohorts and developed a blood aging predictor (BAP) using 5808 healthy individuals to define a reference trajectory of blood molecular aging. Applying BAP to COVID-19 revealed marked transcriptomic age acceleration (AgeAccel), with patients showing an average AgeAccel of 9.34 years after cohort-specific baseline correction. This aging-referenced deviation occurred across age groups and was associated with interferon signaling, immune-inflammatory activation, cytokine and neutrophil-related programs, DNA damage responses, proteostasis stress, and impaired cellular quality-control pathways. Longitudinal analysis showed that AgeAccel increased during acute infection but declined during recovery, indicating a potentially reversible aging-like molecular state at the cohort level rather than irreversible aging. Extension to sepsis, influenza, and major depressive disorder further demonstrated that elevated AgeAccel captures disease-associated molecular burden across distinct pathological contexts. Together, our study redefines transcriptomic AgeAccel as an interpretable measure of disease-induced deviation from healthy molecular homeostasis and provides a quantitative framework for assessing systemic disease burden and recovery dynamics from peripheral blood transcriptomes.
PMID:
42960996
Bibliographic data and abstract were imported from PubMed on 30 Oct 2026.
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