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.

中文翻译：

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通过新的多标记方法识别身体虚弱和肌肉减少症的生物标记：BIOSPHERE 研究的结果。


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质量低。本研究的目的是使用新颖的多变量分析策略为 PF&S 提供生物标志物的初步选择。 200 名社区居民，其中 100 名 PF&S 患者和 100 名 70 岁及以上的非身体虚弱、非肌肉减少症 (nonPF&S) 对照者被纳入老年人肌肉减少症和身体虚弱相关生物标志物 (BIOSPHERE) 研究的一部分。对涉及炎症、肌肉生长和重塑、神经肌肉接头损伤和氨基酸代谢的 74 种血清分析物进行了分析。生物标志物选择是通过序贯和正交协方差选择（SO-CovSel）分析完成的。为整个研究人群和两种性别构建了单独的 SO-CovSel 模型。使用七个生物分子构建了用最少变量获得的最佳预测能力的模型。该模型允许对 80.6 ± 5.3% 的 PF&S 参与者和 79.9 ± 5.1% 的非 PF&S 对照进行正确分类。 PF&S 生物标志物谱的特征是天冬酰胺、天冬氨酸和瓜氨酸的血清水平较高。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，决定了非 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，在男性和女性中具有独特的特征。SO-CovSel 分析允许识别一组 PF&S 的潜在生物标志物。 采用这种创新的多变量方法可以帮助解决 PF&S 复杂的病理生理学问题，将生物标志物的发现从实验室转化为临床，并揭示新的干预目标。