ArticleImmunity & ageing : I & A2025
Ageing and dysregulated lung immune responses in fatal COVID-19.
Article in Immunity & ageing : I & A, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Clinical predictors of impaired pulmonary diffusing capacity in patients recovering from COVID-19: A secondary analysis of multicentre datasets.Canadian journal of respiratory therapy : CJRT = Revue canadienne de la therapie respiratoire : RCTR · 2026Article
- Aging and vaccines: impact of immunosenescence and inflammaging in vaccine response.Frontiers in aging · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Elderly individuals were disproportionally affected during the COVID-19 pandemic, and more than 80% of the global COVID-19-related deaths between 2020 and 2021 occurred among people aged 60 years or older. Several cellular modifications in aged cells may lead to systemic inflammation and fibrotic responses. Age or exogenous insults induce cellular senescence, further increasing the release of pro-inflammatory mediators, leading to the condition known as inflammaging, that can contribute to disease severity. Older individuals presented signs of systemic hyperinflammation in severe COVID-19, but few studies analyzed the influence of age on lung tissue responses in cases of severe COVID-19. We hypothesized that age related alterations regarding innate/acquired immunity and cellular senescence in lung tissue of individuals without lung diseases could predispose to viral infection. We also aimed to identify how the aged lung responded to severe COVID-19 infection. We studied lung tissues from 19 individuals that died from non-pulmonary causes and 28 adult individuals who died from COVID-19 between March and May of 2020, divided according to their age (> or < 60 years). Tissue sections were stained, via immunohistochemistry, and 19 markers among immune cells, COVID-19 receptors, cytokines and senescence were analyzed in the lung parenchyma of both groups. In the COVID-19 group, the Luminex multiplex assay technique was used to detect a panel of 25 cytokines/chemokines. In control lungs, aged individuals had a lower TLR7 expression, without differences in other markers. Older patients had a shorter time between onset of symptoms and death, with a significant negative correlation with age. Unlike the adult younger group, older COVID - 19 patients presented significant differences in relation to their age matched controls in the expression of CD8 + T cells, IFN-α2, TLR7, pSTAT-3, p21 and p53. They also presented higher protein expression that IFN-α2 and TGF-beta than the adult COVID-19 group, with a trend to decreased CD20 + cell density in the lungs. Taken together, our data show age adversely affects the lung expression of key proteins related to COVID-19 susceptibility and severity, by perpetuating inflammation and increasing pro-fibrotic responses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.