Shared and specific blood biomarkers for multimorbidity

Aging is accompanied by the progressive accumulation of biological deficits, which increases susceptibility to developing multiple chronic diseases (that is, multimorbidity). The biological underpinnings of multimorbidity remain poorly understood. Here we analyzed 54 blood biomarkers reflecting inflammatory, vascular, metabolic and neurodegenerative processes in 2,247 individuals aged 60 and over from the Swedish National Study on Aging and Care in Kungsholmen. Multimorbidity was assessed using three measures: baseline total disease count, baseline multimorbidity patterns identified through latent class analysis and 15-year rate of disease accumulation. Associations between baseline biomarkers and multimorbidity measures were examined using least absolute shrinkage and selection operator regression. Growth differentiation factor 15, hemoglobin A1c, cystatin C, leptin and insulin were consistently and positively associated with all multimorbidity measures. Additional biomarkers demonstrated specific associations with distinct multimorbidity patterns. Moreover, faster disease accumulation was directly associated with gamma-glutamyl transferase and inversely with albumin. Longitudinal results were externally validated in 522 participants from the Baltimore Longitudinal Study of Aging, with comparable predictive accuracy. Our findings suggest that multiple biological processes contribute to multimorbidity through shared and distinct mechanisms. Metabolic disturbances emerged as a key driver of multimorbidity. If confirmed, these processes could represent targets for interventions to mitigate disease accumulation.

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Publication Details

Journal
Nature Medicine
Published
2026-01-02
DOI
https://doi.org/10.1038/s41591-025-04038-2
Primary Topic
Chronic Disease Management Strategies
Type
article
Field-Weighted Citation Impact
0.00

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article

Shared and specific blood biomarkers for multimorbidity

Laura Fratiglioni, Federico Triolo, Claudia Fredolini, Giuseppe Bellelli et al.
Nature Medicine
Chronic Disease Management Strategies
article

Shared and specific blood biomarkers for multimorbidity

Laura Fratiglioni, Federico Triolo, Claudia Fredolini, Giuseppe Bellelli, Alice Margherita Ornago, Alessandra Marengoni, Ann Zenobia Moore, Giorgi Beridze, Matilda Dale, Davide Liborio Vetrano, Giulia Grande, Amaia Calderón-Larrañaga, Caterina Gregorio, Luigi Ferrucci
article en

Abstract

Aging is accompanied by the progressive accumulation of biological deficits, which increases susceptibility to developing multiple chronic diseases (that is, multimorbidity). The biological underpinnings of multimorbidity remain poorly understood. Here we analyzed 54 blood biomarkers reflecting inflammatory, vascular, metabolic and neurodegenerative processes in 2,247 individuals aged 60 and over from the Swedish National Study on Aging and Care in Kungsholmen. Multimorbidity was assessed using three measures: baseline total disease count, baseline multimorbidity patterns identified through latent class analysis and 15-year rate of disease accumulation. Associations between baseline biomarkers and multimorbidity measures were examined using least absolute shrinkage and selection operator regression. Growth differentiation factor 15, hemoglobin A1c, cystatin C, leptin and insulin were consistently and positively associated with all multimorbidity measures. Additional biomarkers demonstrated specific associations with distinct multimorbidity patterns. Moreover, faster disease accumulation was directly associated with gamma-glutamyl transferase and inversely with albumin. Longitudinal results were externally validated in 522 participants from the Baltimore Longitudinal Study of Aging, with comparable predictive accuracy. Our findings suggest that multiple biological processes contribute to multimorbidity through shared and distinct mechanisms. Metabolic disturbances emerged as a key driver of multimorbidity. If confirmed, these processes could represent targets for interventions to mitigate disease accumulation.

Nature MedicineVol. 32(2)
Stockholm University (SE), Karolinska Institutet (SE), Azienda Ospedaliera San Gerardo (IT), National Institute on Aging (US), Stockholm Gerontology Research Center Foundation (SE), Istituti di Ricovero e Cura a Carattere Scientifico (IT), University of Milano-Bicocca (IT), University of Brescia (IT), KTH Royal Institute of Technology (SE)
U.S. Department of Health and Human Services, Karolinska Institutet, Vetenskapsrådet, Socialdepartementet, Science for Life Laboratory, National Institutes of Health
Good health and well-being
Openalex Percentile: Top 99%
Chronic Disease Management Strategies
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