The DOI matches its Crossref record; 258 of the 258 references it cites were found in a registry or an index.
Immunosenescence and inflammaging in the aging process: age-related diseases or longevity?
Open accessAbstract
During aging the immune system (IS) undergoes remarkable changes that collectively are known as immunosenescence. It is a multifactorial and dynamic phenomenon that affects both natural and acquired immunity and plays a critical role in most chronic diseases in older people. For a long time, immunosenescence has been considered detrimental because it may lead to a low-grade, sterile chronic inflammation we proposed to call "inflammaging" and a progressive reduction in the ability to trigger effective antibody and cellular responses against infections and vaccinations. Recently, many scientists revised this negative meaning because it can be considered an essential adaptation/remodeling resulting from the lifelong immunological biography of single individuals from an evolutionary perspective. Inflammaging can be considered an adaptive process because it can trigger an anti-inflammatory response to counteract the age-related pro-inflammatory environment. Centenarians represent a valuable model to study the beneficial changes occurring in the IS with age. These extraordinary individuals reached the extreme limits of human life by slowing down the aging process and, in most cases, delaying, avoiding or surviving the major age-associated diseases. They indeed show a complex and heterogeneous phenotype determined by an improved ability to adapt and remodel in response to harmful stimuli. This review aims to point out the intimate relationship between immunosenescence and inflammaging and how these processes impact unsuccessful aging rather than longevity. We also describe the gut microbiota age-related changes as one of the significant triggers of inflammaging and the sex/gender differences in the immune system of the elderly, contributing to the sex/gender disparity in terms of epidemiology, pathophysiology, symptoms and severity of age-related diseases. Finally, we discuss how these phenomena could influence the susceptibility to COVID-19 infection.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“During aging, the imbalance between the increased production and decreased disposal via autophagy, mitophagy, and proteasome, stimulus the innate immune system and thereby triggers the body from a pre-inflammatory state towards a pro-inflammatory state.234”
From Inflammation and aging: signaling pathways and intervention therapies (2023) · cites this paper as [234]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Immunobiology of Dendritic Cells
Banchereau, J., Brière, F., Caux, C., Davoust, J. M., Lebecque, S., Liu, Y., Pulendran, B., & Palucka, K. (2000) · Annual Review of Immunology · doi:10.1146/annurev.immunol.18.1.767 · Cited by 6,755
Sex differences in immune responses
Klein, S. L., & Flanagan, K. L. (2016) · Nature Reviews Immunology · doi:10.1038/nri.2016.90 · Cited by 6,370
Inflamm‐aging: An Evolutionary Perspective on Immunosenescence
FRANCESCHI, C., BONAFÈ, M., VALENSIN, S., OLIVIERI, F., DE LUCA, M., OTTAVIANI, E., & DE BENEDICTIS, G. (2000) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2000.tb06651.x · Cited by 5,358
Chronic inflammation in the etiology of disease across the life span
Furman, D., Campisi, J., Verdin, E., Carrera-Bastos, P., Targ, S., Franceschi, C., Ferrucci, L., Gilroy, D. W., Fasano, A., Miller, G. W., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0675-0 · Cited by 4,915
Cellular senescence: when bad things happen to good cells
Campisi, J., & d'Adda di Fagagna, F. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2233 · Cited by 4,441
Chronic Inflammation (Inflammaging) and Its Potential Contribution to Age-Associated Diseases
Franceschi, C., & Campisi, J. (2014) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/glu057 · Cited by 3,891
Research works printed but not linked: 1
- 2004, Vol. 4
Cited by
Sorted by citations
Inflammation and aging: signaling pathways and intervention therapies
Li, X., Li, C., Zhang, W., Wang, Y., Qian, P., & Huang, H. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01502-8 · Cited by 1,443
“During aging, the imbalance between the increased production and decreased disposal via autophagy, mitophagy, and proteasome, stimulus the innate immune system and thereby triggers the body from a preinflammatory state towards a pro-inflammatory state.(234)”
BackgroundSalminen, A., Kaarniranta, K., & Kauppinen, A. (2022) · Inflammation Research · doi:10.1007/s00011-022-01598-8 · Cited by 432
The Impact of Immune System Aging on Infectious Diseases
Quiros-Roldan, E., Sottini, A., Natali, P. G., & Imberti, L. (2024) · Microorganisms · doi:10.3390/microorganisms12040775 · Cited by 133
Metadata
- Authors
- Santoro, A., Bientinesi, E., & Monti, D.
- Affiliations
- University of Bologna (IT)
- University of Florence (IT)
- Corresponding author
- Monti, Daniela
- Venue
- Ageing Research Reviews
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 71
- Pages
- 101422
- ISSN
- 1568-1637 (ISSN-L)
- OpenAlex
- W3194316549
- Cited by
- 603
- References
- 258
- Citations by year
- 2026: 133 · 2025: 147 · 2024: 154 · 2023: 101 · 2022: 60 · 2021: 8
- FWCI
- 6.67
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Ageing Research Reviews (publishedVersion)
- PubMed (publishedVersion)
- Florence Research (University of Florence) (submittedVersion, other-oa)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion, cc-by-nc-nd)
- Funders
- Fondazione Cassa di Risparmio di Firenze (24,213-(2018.1015)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
- Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
- Keywords
- immunosenescence, inflammaging, aging, age-related diseases, centenarians, gut microbiota, sex differences in immunity, COVID-19 susceptibility, chronic inflammation, adaptive immunity, vaccine response
- MeSH terms
- Immunosenescence, COVID-19, SARS-CoV-2, Aged, Aged, 80 and over, Humans
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 ›
Are you an author, or do you see a problem with this page? Request a review
