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建立人类唾液蛋白质组的年龄组特异性参考区间及其在癫痫诊断中的初步应用。

Establishing age-group specific reference intervals of human salivary proteome and its preliminary application for epilepsy diagnosis.

作者信息

Xue Nianci, Xia Xia, Wang Yini, Li Xianju, Zheng Nairen, Wang Yi, Gong Baoying, Zhang Bin, Chen Yanjia, Chen Yue, Li Yanjuan, Cao Hong, Liu Wofeng, Huang Hongqiang, Yang Shuo, Sui Lisen, Meng Lin, Guo Jianwen, Qin Jun

机构信息

State Key Laboratory of Traditional Chinese Medicine Syndrome, State Key Laboratory of Dampness Syndrome of Chinese Medicine Syndrome, Department of Neurology, The Secondary Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou, 510120, China.

State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.

出版信息

Sci China Life Sci. 2025 Mar;68(3):809-824. doi: 10.1007/s11427-024-2730-6. Epub 2024 Dec 25.

Abstract

Salivary proteins serve multifaceted roles in maintaining oral health and hold significant potential for diagnosing and monitoring diseases due to the non-invasive nature of saliva sampling. However, the clinical utility of current saliva biomarker studies is limited by the lack of reference intervals (RIs) to correctly interpret the testing result. Here, we developed a rapid and robust saliva proteome profiling workflow, obtaining coverage of >1,200 proteins from a 50-µL unstimulated salivary flow with 30 min gradients. With the workflow, we investigated protein variation in a cohort of 1,743 healthy individuals. The significant differences in non-linear saliva proteomes among age groups resulted in the establishment of age-related RIs covering 1,123 salivary protein variations. We then utilized a cohort of 30 epilepsy patients as a case study to illustrate the practical application of RIs in identifying disease-enriched outlier proteins, elucidating their cellular origins, determining disease diagnosis, and visualizing outlier proteins in each epilepsy patient. Our study showed the classification model based on the RI achieved PR-AUC of 0.815 (95%CI: 0.813-0.826). Additionally, we validated these results in an independent test set. Furthermore, the epilepsy cohort could be further stratified into 2 major subtypes, with one subtype characterized by disrupted metabolic proteins and containing mostly Focal Cortical Dysplasia (FCD) type III epilepsy patients. Overall, our study provided a proof-of-principle workflow for the use of salivary proteome for health monitoring, epilepsy diagnosis and subtyping.

摘要

唾液蛋白在维持口腔健康方面发挥着多方面作用,且由于唾液采样具有非侵入性,在疾病诊断和监测方面具有巨大潜力。然而,目前唾液生物标志物研究的临床应用受到缺乏参考区间(RI)的限制,无法正确解释检测结果。在此,我们开发了一种快速且稳健的唾液蛋白质组分析流程,通过30分钟的梯度分析,从50微升未刺激唾液流中获得了超过1200种蛋白质的覆盖范围。利用该流程,我们对1743名健康个体组成的队列中的蛋白质变异进行了研究。各年龄组非线性唾液蛋白质组的显著差异导致建立了涵盖1123种唾液蛋白质变异的年龄相关参考区间。然后,我们以30名癫痫患者组成的队列作为案例研究,来说明参考区间在识别疾病富集的异常蛋白质、阐明其细胞来源、确定疾病诊断以及可视化每位癫痫患者的异常蛋白质方面的实际应用。我们的研究表明,基于参考区间的分类模型的PR-AUC为0.815(95%CI:0.813 - 0.826)。此外,我们在一个独立测试集中验证了这些结果。此外,癫痫队列可进一步分为2个主要亚型,其中一个亚型的特征是代谢蛋白紊乱,主要包含III型局灶性皮质发育不良(FCD)癫痫患者。总体而言,我们的研究为利用唾液蛋白质组进行健康监测、癫痫诊断和亚型分类提供了一个原理验证流程。

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