Immune senescence and biomarkers profile of Bambuí aged population-based cohort
Abstract
During immunosenescence many proinflammatory markers such as cytokines and chemokines are increased. This process called by Franceschi and colleagues as inflammaging is associated with chronic inflammation and the ethiology and pathophysiolgy of many ageing diseases as Alzheimer's and atherosclerosis. The knowledge of immune profile during ageing may provide some interventions that would improve the immune function in elderly and quality of life for old people. However, the identification of a group of potential biomarkers to monitor the ageing process is very difficult. In addition, most of the evidence evaluating immune biomarkers profile is based on data from older Caucasian adults. To our knowledge, no previous Latin American old population-based cohort has evaluated immunological parameters along the ageing process. The present work evaluated CXCL8, CXCL9, CXCL10, CCL2, CCL5, IL-1, IL-6, IL-12, TNF and IL-10 serum levels in 1494 older adults aged 60 to 95 from a population based ageing cohort in Brazil. Our data suggest that there is an increased positive predicted probability of participants to be a high producer of IL-6, CXCL8 and CXCL9. Moreover, results did not differ between men and women, except for CXCL10 that increased only in men. Results were not different in the adjusted model by many potential confounders, including African genomic ancestry. Together, these findings add novel insights about the immunologic aspects of ageing supported by a large population-based cohort study that provides evidences that corroborate with the inflammaging proposal and subsidize the establishment of biomarkers for monitoring the health status of aged population.
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CXCL9 increases with age in humans.
“Some studies in humans have found CXCL9 to increase with age93–98”
From An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging (2021) · cites this paper as [95]
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Self-citation
- Authors
- Torres, K. C. L., Rezende, V. B. D., Lima-Silva, M. L., Santos, L. J. D. S., Costa, C. G., Mambrini, J. V. D. M., Peixoto, S. V., Tarazona-Santos, E., Martins Filho, O. A., Lima-Costa, M. F., & Teixeira-Carvalho, A.
- Affiliations
- Fiocruz Minas (BR)
- Universidade Federal de Minas Gerais (BR)
- Corresponding author
- Torres, Karen Cecília Lima
- ORCID
- Venue
- Experimental Gerontology
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 103
- Pages
- 47-56
- ISSN
- 0531-5565 (ISSN-L)
- OpenAlex
- W2773862001
- Cited by
- 30
- References
- 39
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 3 · 2023: 4 · 2022: 5 · 2021: 1 · 2020: 4 · 2019: 3 · 2018: 2
- FWCI
- 1.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Experimental Gerontology (publishedVersion)
- PubMed (publishedVersion)
- Arca - Repositório Institucional da Fiocruz (submittedVersion)
- Funders
- Ministry of Health
- Ministry of Science and Technology
- Ministry of Science and Technology, Brazil
- Ministry of Education, Brazil
- Minas Gerais State Research Foundation (PP-SUS CDS - APQ-03590-13)
- PDS
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Keywords
- immunosenescence, inflammaging, aging, older adults, immunological markers, cytokines, chemokines, interleukin-6, interleukin-8, CXCL9, CXCL10, MCP-1, RANTES, TNF-α, IL-10, IL-12, sex differences
- MeSH terms
- Immunosenescence, Aged, Aged, 80 and over, Aging, Brazil, Female, Humans, Male, Middle Aged, Sex Factors, Cohort Studies, Biomarkers, Interleukin-6, Logistic Models, Interleukin-8, Chemokine CXCL10, Chemokine CXCL9
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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