Frailty is characterized by loss of physical function and is preferably diagnosed at an early stage (e.g., during pre-frailty). Unfortunately, sensitive tools that can aid early detection are lacking. Blood-based biomarkers, reflecting pathophysiological adaptations before physical symptoms become apparent, could be such tools. We identified candidate biomarkers using a mechanism-based computational approach which integrates a priori defined database-derived clinical biomarkers and skeletal muscle transcriptome data. Identified candidate biomarkers were used as input for a sex-specific correlation analysis, using individual gene expression data from female (n = 24) and male (n = 28) older adults (all 75 + years, ranging from fit to pre-frail) and three frailty-related physical parameters. Male and female groups were matched based on age, BMI, and Fried frailty index. The best correlating candidate biomarkers were evaluated, and selected biomarkers were measured in serum. In females, myostatin and galectin-1 and, in males, cathepsin B and thrombospondin-4 serum levels were significantly different between the physically weakest and fittest participants (all p < 0.05). Logistic regression confirmed the added value of these biomarkers in conjunction with age and BMI to predict whether the subjects belonged to the weaker or fittest group (AUC = 0.80 in females and AUC = 0.83 in males). In conclusion, both in silico and in vivo analyses revealed the sex-specificity of candidate biomarkers, and we identified a selection of potential biomarkers which could be used in a biomarker panel for early detection of frailty. Further investigation is needed to confirm these leads for early detection of frailty.

衰弱的特征是身体功能丧失，最好在早期诊断（例如，在衰弱前期）。不幸的是，缺乏有助于早期检测的敏感工具。基于血液的生物标志物反映了身体症状变得明显之前的病理生理适应，可能就是这样的工具。我们使用基于机制的计算方法确定了候选生物标志物，该方法整合了先验定义的数据库衍生的临床生物标志物和骨骼肌转录组数据。使用来自女性 （n = 24） 和男性 （n = 28） 老年人 （均为 75 + 岁，从健康到衰弱前期） 的个体基因表达数据和三个与衰弱相关的物理参数，将确定的候选生物标志物用作性别特异性相关性分析的输入。根据年龄、 BMI 和 Fried 衰弱指数对男性和女性组进行匹配。评估最相关的候选生物标志物，并在血清中测量选定的生物标志物。在女性中，肌肉生长抑制素和半乳糖凝集素-1 以及男性中，组织蛋白酶 B 和血小板反应蛋白-4 血清水平在身体最弱和最健康的参与者之间有显著差异 （均 p < 0.05）。Logistic 回归证实了这些生物标志物与年龄和 BMI 相结合的附加值，以预测受试者是否属于较弱或最健康的组（女性 AUC = 0.80，男性 AUC = 0.83）。总之，计算机和体内分析都揭示了候选生物标志物的性别特异性，我们确定了一系列潜在的生物标志物，这些生物标志物可用于生物标志物组，用于早期检测衰弱。需要进一步的调查来确认这些线索，以便早期发现虚弱。