Cited by 414Aging and Gerontology ResearchHealth disparities and outcomesFrailty in Older Adults

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An Immune Risk Phenotype, Cognitive Impairment, and Survival in Very Late Life: Impact of Allostatic Load in Swedish Octogenarian and Nonagenarian Humans

Wikby, Anders, Ferguson, Frederick, Forsey, Rosalyn, Thompson, Julie, Strindhall, Jan, Löfgren, Sture, Nilsson, Bengt-Olof, Ernerudh, Jan, Pawelec, Graham, Johansson, Boo·2005·The Journals of Gerontology Series A: Biological Sciences and Medical Sciences

DOI 10.1093/gerona/60.5.556

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Abstract

In the previous OCTO longitudinal study, we identified an immune risk phenotype (IRP) of high CD8 and low CD4 numbers and poor proliferative response. We also demonstrated that cognitive impairment constitutes a major predictor of nonsurvival. In the present NONA longitudinal study, we simultaneously examine in a model of allostatic load IRP and compromised cognition in 4-year survival in a population-based sample (n = 138, 86–94 years). Immune system measurements consisted of determinations of T-cell subsets, plasma interleukin 6 and cytomegalovirus and Epstein–Barr virus serology. Interleukin 2 responsiveness to concanavalin A, using data from the previous OCTO (octogenarians) immune study, hereafter OCTO immune, was also examined. Cognitive status was rated using a battery of neuropsychological tests. Logistic regression indicated that the IRP and cognitive impairment together predicted 58% of observed deaths. IRP was associated with late differentiated CD8+CD28−CD27− cells (p <.001), decreased interleukin 2 responsiveness (p <.05) and persistent viral infection (p <.01). Cognitive impairment was associated with increased plasma interleukin 6 (p <.001). IRP individuals with cognitive impairment were all deceased at the follow-up, indicating an allostatic overload.

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Additional file 6 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186333
Additional file 7 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186339
Additional file 3 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186315
Additional file 4 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186321
Additional file 5 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186327
Additional file 2 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186309
Additional file 1 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection
Romero‐Rodríguez, D. P., Ramírez, C., Imaz-Rosshandler, I., Ormsby, C. E., Peralta-Prado, A., Olvera-García, G., Cervantes, F., Würsch-Molina, D., Romero-Rodríguez, J., Jiang, W., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12186306
Pretreatment CD8+PD-1+ to CD4+PD-1+ ratio is associated with the prognosis of advanced melanoma patients treated with PD-1 inhibitors
Gao, Y., Wang, Y., Luo, Y., Zhang, Y., Wang, S., Tang, X., Qin, P., Xu, B., Gao, Q., & Li, T. (2024) · Melanoma Research · doi:10.1097/cmr.0000000000000972
Factors associated with the formation of neutralizing antibodies post-vaccination: a lesson from COVID-19 vaccination
Ratnawati, H., Tih, F., Puspasari, G., Pelapelapon, A. A., & Felim, S. (2025) · Exploration of Immunology · doi:10.37349/ei.2025.1003180
Investigating Chronic Post-Infection and Post-Injury Symptom Syndromes: Clinical Outcomes, Biological Pathways, and Potential Links to Neurodegenerative Disease
Grossberg, A. N. (2024) · Digital Commons - DU (University of Denver) · doi:10.56902/etdcrp.2024.14

Authors: Wikby, A., Ferguson, F., Forsey, R., Thompson, J., Strindhall, J., Löfgren, S., Nilsson, B.-O., Ernerudh, J., Pawelec, G., & Johansson, B.
Affiliations: Jönköping University (SE)
Corresponding author: Wikby, Anders
ORCID: Ernerudh, Jan
Pawelec, Graham
Johansson, Boo
Venue: The Journals of Gerontology Series A: Biological Sciences and Medical Sciences
Publisher: Oxford University Press (OUP)
Published: 2005-05-01
Volume: 60
Issue: 5
Pages: 556-565
ISSN: 1079-5006 (ISSN-L)
1758-535X
DOI: 10.1093/gerona/60.5.556
OpenAlex: W2153840275
Cited by: 407
References: 57
Citations by year: 2026: 11 · 2025: 8 · 2024: 12 · 2023: 7 · 2022: 14 · 2021: 22 · 2020: 20 · 2019: 30 · 2018: 22 · 2017: 30 · 2016: 29 · 2015: 18 · 2014: 27 · 2013: 18 · 2012: 21
FWCI: 23.42
Type: journal article
Language: en
Open access: closed
Locations: The Journals of Gerontology Series A (publishedVersion)
PubMed (publishedVersion)
Funders: European Commission
Topics: Social Sciences › Psychology › Developmental and Educational Psychology › Aging and Gerontology Research
Social Sciences › Health › Health disparities and outcomes
Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
Keywords: allostatic load, cognitive impairment, survival, octogenarians, nonagenarians, interleukin-2 responsiveness, interleukin-6, cytomegalovirus serology, Epstein-Barr virus serology, viral persistence, T cell subsets, mortality prediction, oldest old
MeSH terms: Aged, Aged, 80 and over, Aging, Analysis of Variance, Cognition Disorders, Female, Health Status Indicators, Humans, Interleukin-2, Life Expectancy, Longevity, Longitudinal Studies, Male, Phenotype, Probability, Sweden, Cohort Studies, Geriatric Assessment, Antigens, CD, Interleukin-6, Survival Rate, CD4-CD8 Ratio, Immunocompromised Host, Risk Assessment, Statistics, Nonparametric

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An Immune Risk Phenotype, Cognitive Impairment, and Survival in Very Late Life: Impact of Allostatic Load in Swedish Octogenarian and Nonagenarian Humans

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