Proteomic analysis of retinopathy-related plasma biomarkers in diabetic patients

Lu, Chieh-Hsiang; Lin, Szu‐Ting; Chou, Hsiu‐Chuan; Lee, Ying‐Ray; Chan, Hong‐Lin

doi:10.1016/j.abb.2012.11.004

Cited by 32 publications

(21 citation statements)

References 51 publications

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“…The number of plasma proteomics studies is few. In a study of patients with type 1 or type 2 diabetes, 28 unique plasma proteins mostly representing inflammatory response and coagulation proteins were identified for the screening and detection of diabetic retinopathy [26]. In a study conducted at the Steno Diabetes Center, 10 single plasma peptides and 3 multipeptide candidate biomarkers were identified for diabetic nephropathy in patients with type 1 diabetes, ranging from having normoalbuminuria, microalbuminuria, and diabetic nephropathy [27].…”

Section: Discussionmentioning

confidence: 99%

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

Pena

Jankowski

Heinze

et al. 2015

Journal of Hypertension

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Section: Discussionmentioning

confidence: 99%

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

Pena

Jankowski

Heinze

et al. 2015

Journal of Hypertension

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“…Heterodimer of S100-A9 and S100-A8 known as myeloid-related protein-8/14 (MRP8/14) binds to receptor for advanced glycation end-products and Toll-like receptor-4 (TLR-4) thereby initiating the intracellular inflammatory signaling cascade ( Caseiro et al, 2013 ). Alpha 2-macroglobulin has been suggested to be a potential biomarker for diabetic retinopathy and other diabetic complications ( Lu et al, 2013 ). Neutrophil elastase was reported to be a marker for the development of diabetic angiopathy ( Piwowar, Knapik-Kordecka & Warwas, 2000 ).…”

Section: Discussionmentioning

confidence: 99%

Association of potential salivary biomarkers with diabetic retinopathy and its severity in type-2 diabetes mellitus: a proteomic analysis by mass spectrometry

Chee

Chang

Loke

et al. 2016

PeerJ

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Aim/hypothesis: The aim of our study was to characterize the human salivary proteome and determine the changes in protein expression in two different stages of diabetic retinopathy with type-2 diabetes mellitus: (1) with non-proliferative diabetic retinopathy (NPDR) and (2) with proliferative diabetic retinopathy (PDR). Type-2 diabetes mellitus without diabetic retinopathy (XDR) was designated as control.Method: In this study, 45 saliva samples were collected (15 samples from XDR control group, 15 samples from NPDR disease group and 15 samples from PDR disease group). Salivary proteins were extracted, reduced, alkylated, trypsin digested and labeled with an isobaric tag for relative and absolute quantitation (iTRAQ) before being analyzed by an Orbitrap fusion tribrid mass spectrometer. Protein annotation, fold change calculation and statistical analysis were interrogated by Proteome Discoverer. Biological pathway analysis was performed by Ingenuity Pathway Analysis. Data are available via ProteomeXchange with identifiers –.Results: A total of 315 proteins were identified from the salivary proteome and 119 proteins were found to be differentially expressed. The differentially expressed proteins from the NPDR disease group and the PDR disease group were assigned to respective canonical pathways indicating increased Liver X receptor/Retinoid X receptor (LXR/RXR) activation, Farnesoid X receptor/Retinoid X receptor (FXR/RXR) activation, acute phase response signaling, sucrose degradation V and regulation of actin-based motility by Rho in the PDR disease group compared to the NPDR disease group.Conclusions/Interpretation: Progression from non-proliferative to proliferative retinopathy in type-2 diabetic patients is a complex multi-mechanism and systemic process. Furthermore, saliva was shown to be a feasible alternative sample source for diabetic retinopathy biomarkers.

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“…Afamin (+C/−DM1) is a protein linked to vitamin E that can be carried in body fluids under conditions where the system does not contain sufficient lipoproteins. Afamin has already been reported to be an ovarian cancer marker [45], but its relationship to diabetes has not been previously reported. In this study, it was shown to be downregulated, which may have resulted in increased oxidative stress in diabetes due to the overproduction of reactive oxygen species (ROS) and decreased efficiency of antioxidant defenses.…”

Section: Differences In Protein Expression and Quantitative Analysis mentioning

confidence: 94%

Metalloproteomic and differential expression in plasma in a rat model of type 1 diabetes

Braga

Vieira

Leite

et al. 2017

International Journal of Biological Macromolecules

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Type 1 diabetes is characterized by hyperglycemia, which in the chronic stage is associated with abnormalities in lipids, protein and, carbohydrate metabolism, as well as oxidative stress. New strategies for prevention and treatment are needed, as type 1 diabetes affects life quality and survival, and involves high-cost treatment. Proteomic and metalloproteomic studies can elucidate the functional and physiological aspects of biomolecules. In the present study, differential proteomics was used to identify potential biomarkers of diabetes in rat plasma associated with copper, selenium, zinc, and magnesium fractionation in control and diabetic rats, as well as diabetic rats treated with insulin. 2D-PAGE was used in the plasma protein fractionation; graphite furnace atomic absorption spectrometry (GFAAS) and flame atomic absorption spectrometry (FAAS) were used for quantitative determination of copper, magnesium, selenium, and zinc in the spots that showed different expression; and protein spots were characterized by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) after tryptic digestion. ESI-MS/MS analysis characterized 35 different proteins, indicating alpha-1-macroglobulin and haptoglobulin as potential candidates as biomarkers for diabetes treated with insulin; also, 2-deoxynucleoside 5-phosphate Nhydrolase 1, transmembrane protein 11, serum amyloid P component, vitamin D-binding protein, and biliverdin reductase were identified as potential candidates as biomarkers for uncontrolled diabetes.

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Proteomic analysis of retinopathy-related plasma biomarkers in diabetic patients

Cited by 32 publications

References 51 publications

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

Association of potential salivary biomarkers with diabetic retinopathy and its severity in type-2 diabetes mellitus: a proteomic analysis by mass spectrometry

Metalloproteomic and differential expression in plasma in a rat model of type 1 diabetes

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