多平台泪液蛋白质组学分析揭示了糖尿病视网膜病变的新型非侵入性生物标志物。

Multiplatform tear proteomic profiling reveals novel non-invasive biomarkers for diabetic retinopathy.

机构信息

Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China.

International Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong, 518040, China.

出版信息

Eye (Lond). 2024 Jun;38(8):1509-1517. doi: 10.1038/s41433-024-02938-0. Epub 2024 Feb 9.

DOI:10.1038/s41433-024-02938-0

PMID:38336992

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11126564/

Abstract

OBJECTIVES

To investigate a comprehensive proteomic profile of the tear fluid in patients with diabetic retinopathy (DR) and further define non-invasive biomarkers.

METHODS

A cross-sectional, multicentre study that includes 46 patients with DR, 28 patients with diabetes mellitus (DM), and 30 healthy controls (HC). Tear samples were collected with Schirmer strips. As for the discovery set, data-independent acquisition mass spectrometry was used to characterize the tear proteomic profile. Differentially expressed proteins between groups were identified, with gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis further developed. Classifying performance of biomarkers for distinguishing DR from DM was compared by the combination of three machine-learning algorithms. The selected biomarker panel was tested in the validation cohort using parallel reaction monitoring mass spectrometry.

RESULTS

Among 3364 proteins quantified, 235 and 88 differentially expressed proteins were identified for DR when compared to HC and DM, respectively, which were fundamentally related to retina homeostasis, inflammation and immunity, oxidative stress, angiogenesis and coagulation, metabolism, and cellular adhesion processes. The biomarker panel consisting of NAD-dependent protein deacetylase sirtuin-2 (SIR2), amine oxidase [flavin-containing] B (AOFB), and U8 snoRNA-decapping enzyme (NUD16) exhibited the best diagnostic performance in discriminating DR from DM, with AUCs of 0.933 and 0.881 in the discovery and validation set, respectively.

CONCLUSIONS

Tear protein dysregulation is comprehensively revealed to be associated with DR onset. The combination of tear SIR2, AOFB, and NUD16 can be a novel potential approach for non-invasive detection or pre-screening of DR.

CLINICAL TRIAL REGISTRATION

Chinese Clinical Trial Registry Identifier: ChiCTR2100054263. https://www.chictr.org.cn/showproj.html?proj=143177 . Date of registration: 2021/12/12.

摘要

目的

探究糖尿病视网膜病变（DR）患者的泪液全蛋白质组谱，并进一步确定非侵入性生物标志物。

方法

本研究为一项横断面、多中心研究，纳入 46 例 DR 患者、28 例糖尿病患者和 30 例健康对照者。使用 Schirmer 条采集泪液样本。在发现组中，采用数据非依赖性采集质谱法来描述泪液蛋白质组图谱。通过基因本体富集分析和京都基因与基因组百科全书富集分析进一步研究组间差异表达蛋白。采用三种机器学习算法的组合比较区分 DR 和 DM 的生物标志物的分类性能。使用平行反应监测质谱法在验证队列中测试选定的生物标志物组合。

结果

在定量的 3364 种蛋白质中，与 HC 和 DM 相比，DR 分别有 235 种和 88 种差异表达蛋白，这些蛋白主要与视网膜内稳态、炎症和免疫、氧化应激、血管生成和凝血、代谢以及细胞黏附过程相关。由 NAD 依赖性蛋白去乙酰化酶 Sirtuin-2（SIR2）、胺氧化酶[黄素]B（AOFB）和 U8 snoRNA 脱帽酶（NUD16）组成的生物标志物组合在区分 DR 和 DM 方面表现出最佳的诊断性能，在发现组和验证组中的 AUC 分别为 0.933 和 0.881。