Journal
GEROSCIENCE
Volume 43, Issue 3, Pages 1317-1329Publisher
SPRINGER
DOI: 10.1007/s11357-021-00334-0
Keywords
Frailty; Biomarkers; Omics; Clinical phenotype; Disability
Categories
Funding
- European Union [305483]
- Fondation pour la Recherche Medicale
- Caisse Nationale Maladie des Travailleurs Salaries
- Direction Generale de la Sante
- Conseil Regionaux of Aquitaine
- Fondation de France
- Ministry of Research-INSERM Program Cohortes et collections de donnees biologiques
- Fondation Plan Alzheimer (FCS 2009-2012)
- Caisse Nationale pour la Solidarite et l'Autonomie
- Italian Ministry of Health [ICS110.1/RF97.71]
- U.S. National Institute on Aging [263 MD 9164, 263 MD 821336]
- Intramural Research Program of the National Institute on Aging, National Institutes of Health, Baltimore, Maryland
- Conseil Regionaux of Bourgogne
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The study identified various biomarkers associated with frailty, including protective markers like vitamin D3 and lutein zeaxanthin, as well as the risk marker cardiac troponin T. The relationship patterns of these biomarkers differ depending on the presence or absence of disability.
Phenotype-specific omic expression patterns in people with frailty could provide invaluable insight into the underlying multi-systemic pathological processes and targets for intervention. Classical approaches to frailty have not considered the potential for different frailty phenotypes. We characterized associations between frailty (with/without disability) and sets of omic factors (genomic, proteomic, and metabolomic) plus markers measured in routine geriatric care. This study was a prevalent case control using stored biospecimens (urine, whole blood, cells, plasma, and serum) from 1522 individuals (identified as robust (R), pre-frail (P), or frail (F)] from the Toledo Study of Healthy Aging (R=178/P=184/F=109), 3 City Bordeaux (111/269/100), Aging Multidisciplinary Investigation (157/79/54) and InCHIANTI (106/98/77) cohorts. The analysis included over 35,000 omic and routine laboratory variables from robust and frail or pre-frail (with/without disability) individuals using a machine learning framework. We identified three protective biomarkers, vitamin D3 (OR: 0.81 [95% CI: 0.68-0.98]), lutein zeaxanthin (OR: 0.82 [95% CI: 0.70-0.97]), and miRNA125b-5p (OR: 0.73, [95% CI: 0.56-0.97]) and one risk biomarker, cardiac troponin T (OR: 1.25 [95% CI: 1.23-1.27]). Excluding individuals with a disability, one protective biomarker was identified, miR125b-5p (OR: 0.85, [95% CI: 0.81-0.88]). Three risks of frailty biomarkers were detected: pro-BNP (OR: 1.47 [95% CI: 1.27-1.7]), cardiac troponin T (OR: 1.29 [95% CI: 1.21-1.38]), and sRAGE (OR: 1.26 [95% CI: 1.01-1.57]). Three key frailty biomarkers demonstrated a statistical association with frailty (oxidative stress, vitamin D, and cardiovascular system) with relationship patterns differing depending on the presence or absence of a disability.
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