The aging lung: Physiology, disease, and immunity
Open accessAbstract
The population is aging at a rate never seen before in human history. As the number of elderly adults grows, it is imperative we expand our understanding of the underpinnings of aging biology. Human lungs are composed of a unique panoply of cell types that face ongoing chemical, mechanical, biological, immunological, and xenobiotic stress over a lifetime. Yet, we do not fully appreciate the mechanistic drivers of lung aging and why age increases the risk of parenchymal lung disease, fatal respiratory infection, and primary lung cancer. Here, we review the molecular and cellular aspects of lung aging, local stress response pathways, and how the aging process predisposes to the pathogenesis of pulmonary disease. We place these insights into context of the COVID-19 pandemic and discuss how innate and adaptive immunity within the lung is altered with age.
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Several lung diseases have been associated with ageing and causally linked to telomere dysfunction and senescent cell accumulation.
“Several lung diseases have been associated with ageing50 and causally linked to telomere dysfunction and senescent cell accumulation.”
From Telomere dysfunction in ageing and age-related diseases (2022) · cites this paper as [50]
The TGFβ pathway representation in non-senescent epithelial cells from old lungs is consistent with enhanced paracrine signaling from increased numbers of senescent neighbors and with established features of epithelial aging.
“consistent with enhanced paracrine signaling from increased numbers of senescent neighbors and with established features of epithelial aging.23,25,32–35”
From SenCat: Cataloging human cell senescence through multi-omic profiling of multiple senescent primary cell types (2026) · cites this paper as [35]
Reliably detecting senescent cells within tissues and organs has been a central difficulty for the field.
“A major challenge in the field has been to reliably identify senescent cells in tissues and organs.23,25,32–35”
From SenCat: Cataloging human cell senescence through multi-omic profiling of multiple senescent primary cell types (2026) · cites this paper as [35]
The ‘Cellular senescence in the aging lung’ section describes senescent-cell characteristics and markers in lung tissue, but does not say that reliably identifying senescent cells in tissues or organs has been a major challenge. Searches for difficulty detecting senescent cells in vivo and for specific biomarkers did not find a passage making that point. (LLM, conf=0.72)
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Effects of aging on B cell function
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Innate immune responses in the ageing lung.
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Aging impairs both primary and secondary RIG-I signaling for interferon induction in human monocytes
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IMPAIRED PULMONARY FUNCTION AS A RISK FACTOR FOR MORTALITY
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SIRT3 diminishes inflammation and mitigates endotoxin-induced acute lung injury
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A randomised, placebo-controlled study of omipalisib (PI3K/mTOR) in idiopathic pulmonary fibrosis
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Proteomic Analysis of Altered Extracellular Matrix Turnover in Bleomycin-induced Pulmonary Fibrosis
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Long-term clearance from small airways decreases with age
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Influenza Virus Vaccination Elicits Poorly Adapted B Cell Responses in Elderly Individuals
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Genome-wide association analysis identifies six new loci associated with forced vital capacity
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Expression of CD39 on activated T cells impairs their survival in older individuals
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Improving Vaccine-Induced Immunity: Can Baseline Predict Outcome?
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Flagged first, then by citations
Cited by
Sorted by citations
Inflammation and aging: signaling pathways and intervention therapies
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“3).(173) The increased susceptibility of elderly individuals to lung diseases can be ascribed to age-related changes in immunity and anti-infection responses.”
BackgroundTelomere dysfunction in ageing and age-related diseases
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COVID-19 and cellular senescence
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The YAP-TEAD complex promotes senescent cell survival by lowering endoplasmic reticulum stress
Anerillas, C., Mazan-Mamczarz, K., Herman, A. B., Munk, R., Lam, K.-W. G., Calvo-Rubio, M., Garrido, A., Tsitsipatis, D., Martindale, J. L., Altés, G., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00480-4 · Cited by 76 · see citing works
Nuclear envelope disruption triggers hallmarks of aging in lung alveolar macrophages
De Silva, N. S., Siewiera, J., Alkhoury, C., Nader, G. P. F., Nadalin, F., de Azevedo, K., Couty, M., Izquierdo, H. M., Bhargava, A., Conrad, C., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00488-w · Cited by 34 · see citing works
Xiaofei, Y., Tingting, L., Xuan, W., & Zhiyi, H. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.1043474 · Cited by 31 · see citing works
Anerillas, C., Altés, G., Gresova, K., Tsitsipatis, D., Mazan-Mamczarz, K., Banarjee, R., Cunningham, A. S. G., Salamini-Montemurri, M., Yang, J.-H., Munk, R., et al. (2026) · Molecular Cell · doi:10.1016/j.molcel.2026.05.017 · Cited by 11 · see citing works
- Authors
- Schneider, J. L., Rowe, J. H., Garcia-de-Alba, C., Kim, C. F., Sharpe, A. H., & Haigis, M. C.
- Affiliations
- Harvard University (US)
- Boston Children's Hospital (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Kim, Carla F.
- Sharpe, Arlene H.
- Haigis, Marcia C.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 184
- Issue
- 8
- Pages
- 1990-2019
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC8052295
- OpenAlex
- W3152420549
- Semantic Scholar
- 3afc4b5d48374929acb02309d4c451bb7e35b498
- Cited by
- 500
- References
- 293
- Citations by year
- 2026: 90 · 2025: 137 · 2024: 112 · 2023: 87 · 2022: 55 · 2021: 19
- FWCI
- 5.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 379 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Roche
- Bristol-Myers Squibb
- Ludwig Center at Harvard
- AstraZeneca
- Mayo Clinic (GV20)
- National Heart, Lung, and Blood Institute
- School of Public Health, University of California Berkeley
- AbbVie
- Boehringer Ingelheim
- Merck KGaA
- National Cancer Institute (U54CA224088, R35HL150876, P01 AI056299, T32CA071345, R01CA213062)
- Glenn Foundation for Medical Research (R01CA213062)
- National Institutes of Health
- Novartis
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Keywords
- lung aging, respiratory infections, lung cancer, stress response pathways, lung immunity, innate immunity, adaptive immunity, COVID-19 pandemic, older adults
- MeSH terms
- COVID-19, Aged, Aging, Humans, Lung, Lung Diseases, Cellular Senescence, Oxidative Stress, Adaptive Immunity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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