Fondazione Policlinico Universitario ''Agostino Gemelli'' IRCCS, L.go F. Vito 1, 00168, Rome, Italy.
Università Cattolica del Sacro Cuore, L.go F. Vito 1, 00168, Rome, Italy.
Geroscience. 2021 Apr;43(2):727-740. doi: 10.1007/s11357-020-00197-x. Epub 2020 Jun 1.
Physical frailty and sarcopenia (PF&S) is a prototypical geriatric condition characterized by reduced physical function and low muscle mass. The aim of the present study was to provide an initial selection of biomarkers for PF&S using a novel multivariate analytic strategy. Two-hundred community-dwellers, 100 with PF&S and 100 non-physically frail, non-sarcopenic (nonPF&S) controls aged 70 and older were enrolled as part of the BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons (BIOSPHERE) study. A panel of 74 serum analytes involved in inflammation, muscle growth and remodeling, neuromuscular junction damage, and amino acid metabolism was assayed. Biomarker selection was accomplished through sequential and orthogonalized covariance selection (SO-CovSel) analysis. Separate SO-CovSel models were constructed for the whole study population and for the two genders. The model with the best prediction ability obtained with the smallest number of variables was built using seven biomolecules. This model allowed correct classification of 80.6 ± 5.3% PF&S participants and 79.9 ± 5.1% nonPF&S controls. The PF&S biomarker profile was characterized by higher serum levels of asparagine, aspartic acid, and citrulline. Higher serum concentrations of platelet-derived growth factor BB, heat shock protein 72 (Hsp72), myeloperoxidase, and α-aminobutyric acid defined the profile of nonPF&S participants. Gender-specific SO-CovSel models identified a "core" biomarker profile of PF&S, characterized by higher serum levels of aspartic acid and Hsp72 and lower concentrations of macrophage inflammatory protein 1β, with peculiar signatures in men and women.SO-CovSel analysis allowed identifying a set of potential biomarkers for PF&S. The adoption of such an innovative multivariate approach could help address the complex pathophysiology of PF&S, translate biomarker discovery from bench to bedside, and unveil novel targets for interventions.
身体虚弱和肌肉减少症(PF&S)是一种典型的老年病,其特征是身体功能下降和肌肉量低。本研究的目的是使用新的多变量分析策略为 PF&S 提供初步的生物标志物选择。作为 BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons(BIOSPHERE)研究的一部分,招募了 200 名居住在社区的 70 岁及以上的老年人,其中 100 名患有 PF&S,100 名非身体虚弱、非肌肉减少症(非 PF&S)。检测了一组涉及炎症、肌肉生长和重塑、神经肌肉接头损伤和氨基酸代谢的 74 种血清分析物。通过顺序和正交协方差选择(SO-CovSel)分析进行生物标志物选择。为整个研究人群和两个性别分别构建了 SO-CovSel 模型。使用七个生物分子构建了具有最佳预测能力和最小变量数的模型。该模型可正确分类 80.6±5.3%的 PF&S 参与者和 79.9±5.1%的非 PF&S 对照组。PF&S 生物标志物谱的特征是天冬酰胺、天冬氨酸和瓜氨酸血清水平较高。血小板衍生生长因子 BB、热休克蛋白 72(Hsp72)、髓过氧化物酶和α-氨基丁酸的血清浓度较高定义了非 PF&S 参与者的特征。性别特异性 SO-CovSel 模型确定了 PF&S 的“核心”生物标志物谱,其特征是天冬氨酸和 Hsp72 血清水平较高,巨噬细胞炎症蛋白 1β 浓度较低,男性和女性具有独特的特征。SO-CovSel 分析允许确定一组潜在的 PF&S 生物标志物。采用这种创新的多变量方法可以帮助解决 PF&S 的复杂病理生理学问题,将生物标志物的发现从实验室转化为临床,并揭示干预的新靶点。