Longitudinal changes in blood-borne geroscience biomarkers: results from a population-based study

Multi-marker approaches are well suited for untangling the intrinsic complexity of aging and related conditions. Herein, we quantified (1) baseline concentrations of a panel of geroscience biomarkers pertaining to four biological domains (i.e., metabolism, inflammation, vascular/organ dysfunction and cellular senescence, and neurodegeneration) in individuals aged ≥60 years; (2) investigated linear and non-linear changes in biomarker levels over a 6-year period according to age and sex; and (3) described the relationships among geroscience biomarkers at baseline and follow-up. We found that repeated measures of age-dependent changes of 47 blood-borne biomarkers over 6 years had differential associations depending on the biological domains. The most relevant biomolecules in the associations between age and repeated assessments were (1) adiponectin, C-peptide, renin (metabolism), (2) CXCL10, IL-1α, IL-1β, IL-6, IL-10, IL-12p70, MPO (inflammation), (3) cystatin C, MMP7, MMP12, VCAM-1 (vascular/organ dysfunction and cellular senescence), and (4) S100B and Tau protein (neurodegeneration). Among these molecules, a negative association with increasing age was found for IL-1α, IL-1β, IL-12p70, S100B, and Tau protein. Non-linear relationships were also identified with age for IGFBP-1, leptin, β2M, TNFRSF1B, fibrinogen, GDF-15, N-cadherin, and BDNF. Our results indicate that inflammatory and metabolic biomolecules are strongly associated with aging over 6 years of follow-up. Whether the biological pathways reflected by these biomarkers contribute to the aging process or are associated with negative health-related events needs to be explored through comprehensive multi-omics longitudinal analysis in larger cohorts.

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Publication Details

Journal
GeroScience
Published
2025-04-23
DOI
https://doi.org/10.1007/s11357-025-01666-x
Citations
2
Primary Topic
Adipokines, Inflammation, and Metabolic Diseases
Type
article
Field-Weighted Citation Impact
2.71

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article

Longitudinal changes in blood-borne geroscience biomarkers: results from a population-based study

Riccardo Calvani, Amaia Calderón‐Larrañaga, Ngoc Viet Nguyen, Claudia Fredolini et al.
2 citations
GeroScience
Adipokines, Inflammation, and Metabolic Diseases
2.71
article

Longitudinal changes in blood-borne geroscience biomarkers: results from a population-based study

Riccardo Calvani, Amaia Calderón‐Larrañaga, Ngoc Viet Nguyen, Claudia Fredolini, Emanuele Marzetti, Anna Picca, Matilda Dale, Davide Liborio Vetrano
article en
2 citations

Abstract

Multi-marker approaches are well suited for untangling the intrinsic complexity of aging and related conditions. Herein, we quantified (1) baseline concentrations of a panel of geroscience biomarkers pertaining to four biological domains (i.e., metabolism, inflammation, vascular/organ dysfunction and cellular senescence, and neurodegeneration) in individuals aged ≥60 years; (2) investigated linear and non-linear changes in biomarker levels over a 6-year period according to age and sex; and (3) described the relationships among geroscience biomarkers at baseline and follow-up. We found that repeated measures of age-dependent changes of 47 blood-borne biomarkers over 6 years had differential associations depending on the biological domains. The most relevant biomolecules in the associations between age and repeated assessments were (1) adiponectin, C-peptide, renin (metabolism), (2) CXCL10, IL-1α, IL-1β, IL-6, IL-10, IL-12p70, MPO (inflammation), (3) cystatin C, MMP7, MMP12, VCAM-1 (vascular/organ dysfunction and cellular senescence), and (4) S100B and Tau protein (neurodegeneration). Among these molecules, a negative association with increasing age was found for IL-1α, IL-1β, IL-12p70, S100B, and Tau protein. Non-linear relationships were also identified with age for IGFBP-1, leptin, β2M, TNFRSF1B, fibrinogen, GDF-15, N-cadherin, and BDNF. Our results indicate that inflammatory and metabolic biomolecules are strongly associated with aging over 6 years of follow-up. Whether the biological pathways reflected by these biomarkers contribute to the aging process or are associated with negative health-related events needs to be explored through comprehensive multi-omics longitudinal analysis in larger cohorts.

GeroScienceVol. 47(5)
Università Cattolica del Sacro Cuore (IT), Libera Università Maria SS. Assunta (IT), Stockholm University (SE), Science for Life Laboratory (SE), Agostino Gemelli University Polyclinic (IT), Karolinska Institutet (SE), Stockholm Gerontology Research Center Foundation (SE), KTH Royal Institute of Technology (SE)
European Commission, Ministero della Salute, Karolinska Institutet, Vetenskapsrådet, Università Cattolica del Sacro Cuore
Good health and well-being
Openalex Percentile: Top 11%
Adipokines, Inflammation, and Metabolic Diseases
2.71
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