Serum disease-specific IgG Fc glycosylation as potential biomarkers for nonproliferative diabetic retinopathy using mass spectrometry

糖尿病性视网膜病变 医学 接收机工作特性 生物标志物 质谱法 糖基化 曲线下面积 眼科 胃肠病学 内科学 生物标志物发现 色谱法 糖尿病 内分泌学 化学 蛋白质组学 生物化学 基因
作者
Yixin Zhang,Zhizhen Lai,Zhonghao Yuan,Bin Qu,Li Yan,Wenyu Yan,Bing Li,Weihong Yu,Shanjun Cai,Hua Zhang
出处
期刊:Experimental Eye Research [Elsevier BV]
卷期号:233: 109555-109555 被引量:2
标识
DOI:10.1016/j.exer.2023.109555
摘要

To explore the potential of serum disease-specific immunoglobulin G (DSIgG) glycosylation as a biomarker for the diagnosis of nonproliferative diabetic retinopathy (NPDR). A total of 387 consecutive diabetic patients presenting in an eye clinic without proliferative diabetic retinopathy (DR) were included and divided into those with nondiabetic retinopathy (NDR) (n = 181) and NPDR (n = 206) groups. Serum was collected from all patients for DSIgG separation. The enriched glycopeptides of the tryptic digests of DSIgG were detected using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Patients were randomly divided into discovery and validation sets (1:1). The differences in glycopeptide ratios between the groups were compared by using Student's t-test or the Mann–Whitney U test. The predictive ability of the model was assessed using the area under the receiver operating characteristic curve (AUC). DSIgG1 G1FN/G0FN, G2N/G2, G2FN/G2N and DSIgG2 G1F/G0F, G1FN/G0FN, G2N/G1N, G2S/G2 were significantly different between NDR and NPDR patients (p < 0.05) in both the discovery and validation sets. The prediction model that was built comprising the seven glycopeptide ratios showed good NPDR prediction performance with an AUC of 0.85 in the discovery set and 0.87 in the validation set. DSIgG Fc N-glycosylation ratios were associated with NPDR and can be used as potential biomarkers for the early diagnosis of DR.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
阔达的碧彤完成签到,获得积分10
1秒前
直率若烟完成签到 ,获得积分10
2秒前
飞矢不动完成签到,获得积分10
2秒前
2秒前
4秒前
科研通AI6.2的应助被Jeff采纳,获得10
6秒前
Lrcx完成签到 ,获得积分10
7秒前
9秒前
qi完成签到 ,获得积分10
9秒前
13344发布了新的文献求助10
9秒前
12秒前
cyskdsn完成签到 ,获得积分10
16秒前
13344完成签到,获得积分10
16秒前
充电宝的应助被bobo采纳,获得10
18秒前
23秒前
25秒前
Yuyu完成签到 ,获得积分10
27秒前
28秒前
清脆夜阑完成签到,获得积分10
30秒前
30秒前
30秒前
32秒前
33秒前
35秒前
37秒前
断了的弦完成签到,获得积分10
38秒前
39秒前
Jeff发布了新的文献求助10
40秒前
Jeff发布了新的文献求助50
40秒前
41秒前
现代的代丝完成签到,获得积分10
41秒前
42秒前
Jeff发布了新的文献求助50
44秒前
Jeff发布了新的文献求助10
44秒前
Jeff发布了新的文献求助10
44秒前
Jeff发布了新的文献求助50
44秒前
Jeff发布了新的文献求助10
44秒前
44秒前
Jeff发布了新的文献求助10
47秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
A Will for the Machine: Computerization, Automation, and the Arts in South Africa 400
Decentring Leadership 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7809727
求助须知:如何正确求助?哪些是违规求助? 9341798
关于积分的说明 20508686
捐赠科研通 7402530
什么是DOI,文献DOI怎么找? 3329203
关于科研通互助平台的介绍 2476038
邀请新用户注册赠送积分活动 2347980