Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Max Planck Institute for Demographic Research, Rostock, Germany.
J Gerontol A Biol Sci Med Sci. 2021 Aug 13;76(9):1643-1652. doi: 10.1093/gerona/glab137.
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.
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.
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.
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.
衰弱与生活质量下降、不良健康结局和死亡有关。过去的研究已经调查了特定生物标志物与衰弱的关系，但了解生物标志物之间的相互关系以及与衰弱相关的风险对于临床应用至关重要。
使用瑞典 AMORIS（载脂蛋白 M 死亡率风险）队列中基线年龄≥59 岁的样本（n=19341），并在基线时测量了 18 种生物标志物，我们使用潜在类别分析进行了分析，并使用 Cox 模型来确定类别与衰弱和全因死亡率之间的关系。
确定了四个类别。与最大的类别相比，参考类别（81.7%），所有其他类别都与衰弱和死亡率的风险增加有关。贫血类别（5.8%）的特点是相对较低的铁标志物和较高的炎症标志物，其危险比（HR）为 1.54，95%置信区间（CI）为 1.38-1.73，用于衰弱，HR 为 1.76，95%CI 为 1.65-1.87，用于死亡率。糖尿病类别（6.5%）的特点是葡萄糖和果糖胺较高，其 HR 为 1.59，95%CI 为 1.43-1.77，用于衰弱，HR 为 1.74，95%CI 为 1.64-1.85，用于死亡率。最后，肝脏类别（6.0%）的特点是肝脏酶水平较高，其 HR 为 1.15，95%CI 为 1.01-1.30，用于衰弱，HR 为 1.40，95%CI 为 1.31-1.50，用于死亡率。按性别分层的分析没有显示男性和女性之间有任何实质性差异。
不同的常见生物标志物集合与衰弱的发生有关，在患者中监测这些生物标志物可能可以更早地发现衰弱，并有可能预防衰弱，从而提高生活质量。
