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Identification of plasma exosomal protein markers associated with diabetic retinopathy progression by proteomic analysis

ABSTRACT: Protein biomarkers derived from plasma exosome have been extensively identified in various diseases. This study aimed to explore the biomarkers at different stages of diabetes retinopathy (DR) progression. Two cohorts, discovery and validation cohorts, were included in this study. The discovery cohort was used for proteomic analysis to screen differentially expressed proteins (DEPs). Hub proteins were identified by Wilcox.test, and their correlation with clinical characteristics were further analyzed. The validation cohort was used for enzyme-linked immunosorbent assay (ELISA) to verify the expression of hub proteins. Receiver operator characteristic (ROC) curve was conducted to evaluate the diagnostic values of hub proteins for DR progression. The correlation with clinical indicators was further analyzed.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: Hang Wu

LAB HEAD: Hang Wu

PROVIDER: PXD064059 | Pride | 2025-06-11

REPOSITORIES: Pride

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Project description:Anthocyanins and flavonols are natural compounds that accumulate preferentially in grapevine flowers and fruits. They are among the most abundant flavonoids and play a very important role in grape and wine quality. In particular, they confer and stabilize colour and contribute to other organoleptic characteristics of the final product. Their complex profile in terms of concentration and relative abundance varies among cultivars and makes wine typicity. The synthesis of these compounds is mainly regulated at transcriptional level. Flavonoids accumulate at specific stages and in specific tissues during flower and berry development, as a consequence of the timely expression of the genes necessary for their synthesis. Although the general flavonoid pathway has been genetically and biochemically elucidated and the main determinants of colour have been identified, the molecular reasons of the fine variation among grape cultivars are still not completely understood. To shed light on this issue, extreme genotypes of a segregating population derived from the cross Syrah x Pinot Noir were characterized at transcriptional level. The transcriptome analysis along three berry developmental stages of these genotypes has allowed the identification of a large set of transcripts differentially modulated between the two groups. A population derived from M-bM-^@M-^XSyrahM-bM-^@M-^Y x M-bM-^@M-^XPinot NoirM-bM-^@M-^Y consisting of 170 F1 individuals plus the parental lines was characterized for the content of flavonols and anthocyanins in the skins of mature berries (38E-L; 18M-BM-0Brix). Based on the biochemical data, 4 high- and 4 low-flavonol producers (HFPs and LFPs: F1 16, F1 56, F1 63, F1 223 and F1 64, F1 256, F1 260, PN), two of which having also either very high or very low anthocyanin content (HAPs and LAPs: F1 63, F1 223 and F1 256, F1 260), were selected for gene expression analysis. A representative sample for each individual (one biological replicate) was collected at three berry developmental stages (hard green berry (33E-L, PV), veraison (35E-L, 50% coloured berries, VER) and maturity (38E-L, 18M-BM-0Brix, MAT)) during the 2007 season.

Project description:Background Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy (LVH). We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death (SCD) risk in adult patients with HCM. The aim of this study was to validate the adult biomarkers and perform new discovery proteomics in childhood-onset HCM. Methods Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel paediatric plasma proteomic biomarker panels.Results Four previously validated adult HCM markers (Aldolase Fructose-Bisphosphate A, Complement C3a, Talin-1 and Thrombospondin 1) and three new markers (Glycogen Phosphorylase B, Lipoprotein A and Profilin 1) were elevated in paediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training dataset (sensitivity 100% [95% confidence interval: 95–100]; specificity 100% [96–100]) and 0.82 in the validation dataset (sensitivity 75% [59–86]; specificity 88% [75–94]). Reduced circulating levels of 4 other peptides (Apolipoprotein L1-, Complement 5b-, Immunoglobulin Heavy Constant Epsilon- and Serum Amyloid A4-peptide) found in children with high SCD risk provided complete separation from the low and intermediate risk groups, and predicted mortality and adverse cardiovascular outcomes (hazard ratio 1.53 [1.2 –2.0], p = 0.001). ConclusionIn children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and a second 4-biomarker panel identifies those at high risk of adverse outcomes, including sudden cardiac death.

			Action	DRS
	DM-LHP_Slot2-35.d.zip	Other
	DM-LJL_Slot2-39.d.zip	Other
	DM-TDL_Slot2-38.d.zip	Other
	DM-WHZ_Slot2-34.d.zip	Other
	DM-YFL_Slot2-36.d.zip	Other

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Identification of plasma exosomal protein markers associated with diabetic retinopathy progression by proteomic analysis

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