Biomarker signatures of aging
Open accessAbstract
Because people age differently, age is not a sufficient marker of susceptibility to disabilities, morbidities, and mortality. We measured nineteen blood biomarkers that include constituents of standard hematological measures, lipid biomarkers, and markers of inflammation and frailty in 4704 participants of the Long Life Family Study (LLFS), age range 30-110 years, and used an agglomerative algorithm to group LLFS participants into clusters thus yielding 26 different biomarker signatures. To test whether these signatures were associated with differences in biological aging, we correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type 2 diabetes, and mortality using longitudinal data collected in the LLFS. Signature 2 was associated with significantly lower mortality, morbidity, and better physical function relative to the most common biomarker signature in LLFS, while nine other signatures were associated with less successful aging, characterized by higher risks for frailty, morbidity, and mortality. The predictive values of seven signatures were replicated in an independent data set from the Framingham Heart Study with comparable significant effects, and an additional three signatures showed consistent effects. This analysis shows that various biomarker signatures exist, and their significant associations with physical function, morbidity, and mortality suggest that these patterns represent differences in biological aging. The signatures show that dysregulation of a single biomarker can change with patterns of other biomarkers, and age-related changes of individual biomarkers alone do not necessarily indicate disease or functional decline.
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A multitude of biomarkers linked to disease are strongly correlated with age; e.g., triglycerides, HbA1c, waist circumference, IL-6 increase with age, while albumin, IGF and creatinine clearance decrease [84,85].
“For instance, triglycerides, glycated hemoglobin (HbA1c), waist circumference, IL-6 increase with age, but other parameters like albumin, IGF and creatinine clearance go in an opposite direction [84, 85].”
From Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare (2018) · cites this paper as [84]
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- Authors
- Sebastiani, P., Thyagarajan, B., Sun, F., Schupf, N., Newman, A. B., Montano, M., & Perls, T. T.
- Affiliations
- Department of Biostatistics; Boston University School of Public Health; 801 Massachusetts Avenue Boston MA 02118 USA
- University of Minnesota (US)
- Boston University (US)
- Columbia University (US)
- University of Pittsburgh (US)
- Brigham and Women's Hospital (US)
- Venue
- Aging Cell
- Publisher
- Wiley
- Published
- 2017-01-06
- Volume
- 16
- Issue
- 2
- Pages
- 329-338
- ISSN
- 1474-9718 (ISSN-L)
- PMC
- PMC5334528
- OpenAlex
- W2568684118
- Cited by
- 222
- References
- 36
- Citations by year
- 2026: 8 · 2025: 18 · 2024: 25 · 2023: 23 · 2022: 31 · 2021: 33 · 2020: 19 · 2019: 34 · 2018: 17 · 2017: 13 · 2015: 1
- FWCI
- 13.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Aging Cell (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institute on Aging (U01-AG023712, U01-AG23744, U01-AG023746, U01-AG023749, U01-AG023755, U19 AG023122)
- National Institute of Allergy and Infectious Diseases
- National Heart, Lung, and Blood Institute (R21HL128871)
- NHLBI/NIH (N 01HC25195)
- Boston University School of Medicine
- Marty and Paulette Samowitz Foundation
- Topics
- Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
- 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
- Keywords
- biomarker signatures, biological aging, Long Life Family Study, blood biomarkers, lipid biomarkers, inflammation, frailty, physical function, mortality, morbidity, cancer risk, cardiovascular disease, type 2 diabetes, agglomerative clustering, successful aging, Framingham Heart Study
- MeSH terms
- Adult, Aged, Aged, 80 and over, Aging, Calibration, Family, Female, Humans, Longevity, Male, Middle Aged, Mortality, Reproducibility of Results, Biomarkers, Age Distribution
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