Open Access
Blood-Based Biomarkers and Long-term Risk of Frailty—Experience From the Swedish AMORIS Cohort
Author(s) -
Alexandra Wennberg,
Mozhu Ding,
Marcus Ebeling,
Niklas Hammar,
Karin Modig
Publication year - 2021
Publication title -
the journals of gerontology. series a, biological sciences and medical sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.134
H-Index - 189
eISSN - 1758-535X
pISSN - 1079-5006
DOI - 10.1093/gerona/glab137
Subject(s) - medicine , hazard ratio , confidence interval , cohort , proportional hazards model , cohort study , anemia
Background Frailty is associated with reduced quality of life, poor health outcomes, and death. Past studies have investigated how specific biomarkers are associated with frailty but understanding biomarkers in concert with each other and the associated risk of frailty is critical for clinical application. Methods Using a sample aged ≥59 years at baseline from the Swedish AMORIS (Apolipoprotein MOrtality RISk) cohort (n = 19 341), with biomarkers measured at baseline (1985–1996), we conducted latent class analysis with 18 biomarkers and used Cox models to determine the association between class and frailty and all-cause mortality. Results Four classes were identified. Compared to the largest class, the Reference class (81.7%), all other classes were associated with increased risk of both frailty and mortality. The Anemia class (5.8%), characterized by comparatively lower iron markers and higher inflammatory markers, had hazard ratio (HR) = 1.54, 95% confidence interval (CI) 1.38, 1.73 for frailty and HR = 1.76, 95% CI 1.65, 1.87 for mortality. The Diabetes class (6.5%) was characterized by higher glucose and fructosamine, and had HR = 1.59, 95% CI 1.43, 1.77 for frailty and HR = 1.74, 95% CI 1.64, 1.85 for mortality. Finally, the Liver class (6.0%), characterized by higher liver enzyme levels, had HR = 1.15, 95% CI 1.01, 1.30 for frailty and HR = 1.40, 95% CI 1.31, 1.50 for mortality. Sex-stratified analyses did not show any substantial differences between men and women. Conclusions Distinct sets of commonly available biomarkers were associated with development of frailty and monitoring these biomarkers in patients may allow for earlier detection and possible prevention of frailty, with the potential for improved quality of life.