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Exp Gerontol. 2018 Jul 1;107:11-17. doi: 10.1016/j.exger.2017.07.011. Epub 2017 Jul 16.

The risks of biomarker-based epidemiology: Associations of circulating calcium levels with age, mortality, and frailty vary substantially across populations.

Author information

1
Groupe de recherche PRIMUS, Department of Family Medicine, University of Sherbrooke, 3001 12e Ave N, Sherbrooke, QC, J1H 5N4, Canada. Electronic address: Alan.Cohen@USherbrooke.ca.
2
Groupe de recherche PRIMUS, Department of Family Medicine, University of Sherbrooke, 3001 12e Ave N, Sherbrooke, QC, J1H 5N4, Canada. Electronic address: Veronique.Legault@USherbrooke.ca.
3
Institute for Biostatistics and Informatics in Medicine and Ageing Research, IBIMA Rostock University Medical Center, Ernst-Heydemann, Str. 8, 8057 Rostock, Germany. Electronic address: fuellen@uni-rostock.de.
4
Research Center on Aging, Department of Medicine, University of Sherbrooke, CSSS-IUGS, 1036 rue Belvédère Sud, Sherbrooke, QC, J1H 4C4, Canada. Electronic address: Tamas.Fulop@USherbrooke.ca.
5
Mailman School of Public Health, Columbia University, 722 W. 168th Street, R1408, New York, NY, 10032, United States. Electronic address: lpfried@columbia.edu.
6
Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, 3001 S. Hanover Street, Baltimore, MD, 21225, United States. Electronic address: ferruccilu@mail.nih.gov.

Abstract

Recent studies have shown contradictory associations between calcium levels and health outcomes. We suspected these conflicting results were the consequence of more general issues with how biomarkers are analyzed in epidemiological studies, particularly in the context of aging. To demonstrate the risks of typical analyses, we used three longitudinal aging cohort studies and their demographic subsets to analyze how calcium levels change with age and predict risk of mortality and frailty. We show that calcium levels either increase or decrease with age depending on the population, and positively or negatively predict frailty depending on the population and analysis; both age and frailty results showed substantial heterogeneity. Mortality analyses revealed few significant associations but were likely underpowered. Variation in population composition (demographics, diseases, diet, etc.) leads to contradictory findings in the literature for calcium and likely for other biomarkers. Epidemiological studies of biomarkers are particularly sensitive to population composition both because biomarkers generally have non-linear and often non-monotonic relationships with other key variables, notably age and health outcomes, and because there is strong interdependence among biomarkers, which are integrated into complex regulatory networks. Consequently, most biomarkers have multiple physiological roles and are implicated in multiple pathologies. We argue that epidemiological studies of aging using biomarkers must account for these factors, and suggest methods to do this.

KEYWORDS:

Aging biomarkers; Calcium; Frailty; Physiological complexity; Population composition

PMID:
28723411
PMCID:
PMC5995116
DOI:
10.1016/j.exger.2017.07.011
[Indexed for MEDLINE]
Free PMC Article

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