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Simple Biologically Informed Inflammatory Index of Two Serum Cytokines Predicts 10 Year All-Cause Mortality in Older Adults
Open accessAbstract
BACKGROUND: Individual measurements of inflammation have been utilized to assess adverse outcomes risk in older adults with varying degrees of success. This study was designed to identify biologically informed, aggregate measures of inflammation for optimal risk assessment and to inform further biological study of inflammatory pathways. METHODS: In total, 15 nuclear factor-kappa B-mediated pathway markers of inflammation were first measured in baseline serum samples of 1,155 older participants in the InCHIANTI population. Of these, C-reactive protein, interleukin-1-receptor antagonist, interleukin-6, interleukin-18, and soluble tumor necrosis factor-α receptor-1 were independent predictors of 5-year mortality. These five inflammatory markers were measured in baseline serum samples of 5,600 Cardiovascular Health Study participants. A weighted summary score, the first principal component summary score, and an inflammation index score were developed from these five log-transformed inflammatory markers, and their prediction of 10-year all-cause mortality was evaluated in Cardiovascular Health Study and then validated in InCHIANTI. RESULTS: The inflammation index score that included interleukin-6 and soluble tumor necrosis factor-α receptor-1 was the best predictor of 10-year all-cause mortality in Cardiovascular Health Study, after adjusting for age, sex, education, race, smoking, and body mass index (hazards ratio = 1.62; 95% CI: 1.54, 1.70) compared with all other single and combined measures. The inflammation index score was also the best predictor of mortality in the InCHIANTI validation study (hazards ratio 1.33; 95% CI: 1.17-1.52). Stratification by sex and CVD status further strengthened the association of inflammation index score with mortality. CONCLUSION: A simple additive index of serum interleukin-6 and soluble tumor necrosis factor-α receptor-1 best captures the effect of chronic inflammation on mortality in older adults among the 15 biomarkers measured.
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“In addition, a separate multistage population-based study reported that serum levels of IL-6 and soluble TNFα could be used as an inflammatory index to predict mortality in the elderly (Varadhan et al, 2014).”
From Microglia Priming with Aging and Stress (2017) · cites this paper as Varadhan et al, 2014
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Additional file 1 of Immune cell phenotypes and mortality in the Framingham Heart Study
Ragab, A. A. Y., Doyle, M. F., Chen, J., Fang, Y., Lunetta, K. L., & Murabito, J. M. (2024) · Figshare · doi:10.6084/m9.figshare.26732857
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059560
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059545
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059551
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059557
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Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059554
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059569
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Additional file 2 of Health impacts of a randomized biomass cookstove intervention in northern Ghana
Abdo, M., Kanyomse, E., Alirigia, R., Coffey, E. R., Piedrahita, R., Diaz-Sanchez, D., Hagar, Y., Naumenko, D. J., Wiedinmyer, C., Hannigan, M. P., et al. (2021) · Figshare · doi:10.6084/m9.figshare.17125925
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059548
Arvey, A. J., Rowe, M., Legutki, J. B., An, G., Gollapudi, A., Lei, A., Colston, B. W., Putterman, C., Smith, D., Stiles, J., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13059542
Additional file 1 of Health impacts of a randomized biomass cookstove intervention in northern Ghana
Abdo, M., Kanyomse, E., Alirigia, R., Coffey, E. R., Piedrahita, R., Diaz-Sanchez, D., Hagar, Y., Naumenko, D. J., Wiedinmyer, C., Hannigan, M. P., et al. (2021) · Figshare · doi:10.6084/m9.figshare.17125922
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Metadata
- Authors
- Varadhan, R., Yao, W., Matteini, A., Beamer, B. A., Xue, Q.-L., Yang, H., Manwani, B., Reiner, A., Jenny, N., Parekh, N., Fallin, M. D., Newman, A., Bandeen-Roche, K., Tracy, R., Ferrucci, L., & Walston, J.
- Affiliations
- Johns Hopkins University (US)
- Baltimore VA Medical Center (US)
- University of Washington (US)
- University of Vermont (US)
- University of Pittsburgh (US)
- National Institute on Aging (US)
- ORCID
- Venue
- The Journals of Gerontology Series A: Biological Sciences and Medical Sciences
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-05-20
- Volume
- 69A
- Issue
- 2
- Pages
- 165-173
- ISSN
- 1079-5006 (ISSN-L)
- 1758-535X
- PMC
- PMC4038244
- OpenAlex
- W2117554687
- Cited by
- 273
- References
- 39
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 27 · 2023: 20 · 2022: 33 · 2021: 23 · 2020: 40 · 2019: 19 · 2018: 22 · 2017: 15 · 2016: 16 · 2015: 23 · 2014: 7 · 2013: 2
- FWCI
- 8.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journals of Gerontology Series A (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Johns Hopkins University
- Ministero della Salute (N.1-AG-1-2111, 263 MD 821336, 263 MD 9164, N.1-AG-1-1)
- National Institutes of Health (263MD9164, N.1-AG-1-2111, N.1-AG-1-1, N01-HC-85239, UL1TR001079, 263 MD 821336, n01hc055222-001, N01HC85086, AG 20098, N01HC85079, AG-023629, N01-HC-75150, N01HC-35129, N01HC-15103, N01-HC-45133, HL080295)
- National Institute on Aging (N.1‐AG‐1‐2111, 263 MD 9164, N01HC85079, R01AG027236, N01‐HC‐85239, 821336, N01 HC‐15103, AG-023629, AG-15928, AG-20098, and AG-027058, AG 20098, N.1-AG-1-1, AG-15928, 263MD821336, 1-AG-1-2111, N01HC55222, N01‐HC‐35129, N01-HC-75150, AG023629, AG027058, HL080295, N01‐HC‐45133, N01‐HC‐85086, R01AG023629, R01AG015928, R01AG027058, P30AG024827, P30AG021334)
- National Heart, Lung, and Blood Institute (AG-023629, AG-027058, N0-1-HC-85239, N01HC15103, N01HC‐75150, N01 HC85086, AG-20098, N01 HC55222, N01‐HC‐45133, AG-15928, N01-HC-85079 through N01-HC-85086, HL080295, N01-HC85079, N01HC35129)
- National Institute of Neurological Disorders and Stroke (AG023629, AG‐15928, AG‐027058, N01-HC-85239, AG‐20098, N01-HC-75150, HL080295, N01-HC-35129, N01-HC-45133, N01-HC-85086, N01 HC-55222, N01HC85079, N01-HC-15103)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
- Keywords
- inflammation, all-cause mortality, older adults, interleukin-6, soluble tumor necrosis factor receptor 1, inflammation index, C-reactive protein, interleukin-1 receptor antagonist, IL-18, chronic inflammation, risk prediction, cardiovascular disease, sex differences, Cardiovascular Health Study
- MeSH terms
- Aged, Aged, 80 and over, C-Reactive Protein, Female, Humans, Inflammation, Longevity, Male, Risk Factors, Cohort Studies, Biomarkers, Interleukin-6, Interleukin-18, Receptors, Tumor Necrosis Factor, Type I, Interleukin 1 Receptor Antagonist Protein
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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