目标:儿童肥胖,一个紧迫的全球健康问题,显著增加代谢并发症的风险,包括与脂肪变性肝病(MASLD)相关的代谢功能障碍。对脂肪变性的早期检测和筛查进行准确的非侵入性测试至关重要。在这项研究中,我们探索了血清蛋白质组,鉴定蛋白质作为非侵入性脂肪变性诊断试验的潜在生物标志物。
方法:59名肥胖青少年接受超声检查以评估脂肪变性。收集血清样品并用邻近延伸测定技术通过靶向蛋白质组学进行分析。评估临床和生化参数,以及它们之间的相关性,个性化的标记,并进行脂肪变性。受试者工作特征(ROC)曲线用于确定确定的候选人的脂肪变性诊断性能,脂肪肝指数(FLI),以及它们在逻辑回归模型中的组合。
结果:在有和没有脂肪变性的受试者之间观察到各种临床和生化参数的显着差异。还注意到血清蛋白质组的性别相关差异。五种循环蛋白,包括组织蛋白酶O(CTSO),钙黏着蛋白2(CDH2),和脯氨酸内肽酶(FAP),被鉴定为脂肪变性的生物标志物。CDH2,CTSO,白细胞免疫球蛋白样受体A5(LILRA5),BMI,腰围,HOMA-IR,和FLI,其中,与脂肪变性程度显著相关。CDH2、FAP、和LDL结合在logit模型中实现了AUC为0.91的诊断性能(95%CI0.75-0.97,100%灵敏度,84%的特异性)。
结论:CDH2和FAP结合其他临床参数,代表准确诊断脂肪肝的有用工具,强调将新标记物整合到MASLD诊断算法中的重要性。
OBJECTIVE: Childhood obesity, a pressing global health issue, significantly increases the risk of metabolic complications, including metabolic dysfunction associated with steatotic liver disease (MASLD). Accurate non-invasive tests for early detection and screening of steatosis are crucial. In this study, we explored the serum proteome, identifying proteins as potential biomarkers for inclusion in non-invasive steatosis diagnosis tests.
METHODS: Fifty-nine obese adolescents underwent ultrasonography to assess steatosis. Serum samples were collected and analyzed by targeted proteomics with the Proximity Extension Assay technology. Clinical and biochemical parameters were evaluated, and correlations among them, the individuated markers, and steatosis were performed. Receiver operating characteristic (ROC) curves were used to determine the steatosis diagnostic performance of the identified candidates, the fatty liver index (FLI), and their combination in a logistic regression model.
RESULTS: Significant differences were observed between subjects with and without steatosis in various clinical and biochemical parameters. Gender-related differences in the serum proteome were also noted. Five circulating proteins, including Cathepsin O (CTSO), Cadherin 2 (CDH2), and Prolyl endopeptidase (FAP), were identified as biomarkers for steatosis. CDH2, CTSO, Leukocyte Immunoglobulin Like Receptor A5 (LILRA5), BMI, waist circumference, HOMA-IR, and FLI, among others, significantly correlated with the steatosis degree. CDH2, FAP, and LDL combined in a logit model achieved a diagnostic performance with an AUC of 0.91 (95% CI 0.75-0.97, 100% sensitivity, 84% specificity).
CONCLUSIONS: CDH2 and FAP combined with other clinical parameters, represent useful tools for accurate diagnosis of fatty liver, emphasizing the importance of integrating novel markers into diagnostic algorithms for MASLD.