five

Salivary Proteome and Peptidome Profiling in Type 1 Diabetes Mellitus Using a Quantitative Approach

收藏
NIAID Data Ecosystem2026-03-07 收录
下载链接:
https://figshare.com/articles/dataset/Salivary_Proteome_and_Peptidome_Profiling_in_Type_1_Diabetes_Mellitus_Using_a_Quantitative_Approach/2427886
下载链接
链接失效反馈
官方服务:
资源简介:
In the present study, we applied iTRAQ-based quantitative approach to explore the salivary proteome and peptidome profile in selected subjects with type 1 diabetes, with and without microvascular complications, aiming to identify disease-related markers. From a total of 434 distinct proteins, bactericidal/permeability-increasing protein-like 1 and pancreatic adenocarcinoma up-regulated factor were found in higher levels in the saliva of all patients while increased content of other proteins like alpha-2-macroglobulin, defensin alpha 3 neutrophil-specific, leukocyte elastase inhibitor, matrix metalloproteinase-9, neutrophil elastase, plastin-2, protein S100-A8 and protein S100-A9 were related with microvascular complications as retinopathy and nephropathy. Protein–protein interaction network analysis suggests the functional clusters defense, inflammation and response to wounding as the most significantly associated with type 1 diabetes pathogenesis. Peptidome data not only support a diabetes-related higher susceptibility of salivary proteins to proteolysis (mainly of aPRP, bPRP1 and bPRP2), but also evidenced an increased content of some specific protein fragments known to be related with bacterial attachment and the accumulation of phosphopeptides involved in tooth protection. Overall, the salivary protein and peptide profile highlights the importance of the innate immune system in the pathogenesis of type 1 diabetes mellitus and related complications. This study provides an integrated perspective of salivary proteome and peptidome that should be further explored in future studies targeting specific disease markers.
创建时间:
2016-02-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作