five

Quantitative Proteomics Analysis of Vitreous Humor from Diabetic Retinopathy Patients

收藏
NIAID Data Ecosystem2026-03-09 收录
下载链接:
https://figshare.com/articles/dataset/Quantitative_Proteomics_Analysis_of_Vitreous_Humor_from_Diabetic_Retinopathy_Patients/2103499
下载链接
链接失效反馈
官方服务:
资源简介:
Initial triggers for diabetic retinopathy (DR) are hyperglycemia-induced oxidative stress and advanced glycation end-products. The most pathological structural changes occur in retinal microvasculature, but the overall development of DR is multifactorial, with a complex interplay of microvascular, neurodegenerative, genetic/epigenetic, immunological, and secondary inflammation-related factors. Although several individual factors and pathways have been associated with retinopathy, a systems level understanding of the disease is lacking. To address this, we performed mass spectrometry based label-free quantitative proteomics analysis of 138 vitreous humor samples from patients with nonproliferative DR or the more severe proliferative form of the disease. Additionally, we analyzed samples from anti-VEGF (vascular endothelial growth factor) (bevacizumab)-treated patients from both groups. In our study, we identified 2482 and quantified the abundancy of 1351 vitreous proteins. Of these, the abundancy of 230 proteins was significantly higher in proliferative retinopathy compared with nonproliferative retinopathy. This specific subset of proteins was linked to inflammation, complement, and coagulation cascade proteins, protease inhibitors, apolipoproteins, immunoglobulins, and cellular adhesion molecules, reflecting the multifactorial nature of the disease. The identification of the key molecules of the disease is critical for the development of new therapeutic molecules and for the new use of existing drugs.
创建时间:
2016-02-12
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