Dataset Information

Proteomic analysis of urinary microvesicles reveal biomarkers for neurologic disease

ABSTRACT: Background- Extracellular vesicles (EVs) harbor thousands of proteins that hold promise for biomarker development. Usually difficult to purify, EVs in urine are relatively easily obtained and have demonstrated efficacy for kidney disease prediction. Herein, we further characterize the proteome of urinary EVs to explore the potential for biomarkers unrelated to kidney dysfunction, focusing on Parkinson’s disease (PD). Methods- Using a quantitative mass spectrometry approach, we measured urinary EV proteins from a discovery cohort of 50 subjects. EVs in urine were classified into subgroups and EV proteins were ranked by abundance and variability over time. Enriched pathways and ontologies in stable EV proteins were identified and proteins that predict PD were further measured in a cohort of 108 subjects. Findings- Hundreds of commonly expressed urinary EV proteins with stable expression over time were distinguished from proteins expressed in few individual with high variability over time. Bioinformatic analyses reveal a striking enrichment of endolysosomal proteins linked to Parkinson’s, Alzheimer’s, Huntington’s disease, and other neurologic disorders. Tissue and biofluid enrichment analyses show broad representation of EVs from across the body without bias towards kidney or urine proteins. Among the proteins linked to neurological diseases, SNAP23 and calbindin were the most elevated in PD cases with 86% prediction success for disease diagnosis in the discovery cohort and 76% prediction success in the replication cohort.

INSTRUMENT(S): LTQ

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Urine, Extracellular Vesicle

DISEASE(S): Parkinson's Disease

SUBMITTER: james mobley

LAB HEAD: James A. Mobley

PROVIDER: PXD013710 | Pride | 2019-11-12

REPOSITORIES: Pride

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Dataset's files

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			Action	DRS
	Mudpit_gb_20140815_ETD_West_UrinaryExosome_115_1.mzid.gz	Mzid
	Mudpit_gb_20140815_ETD_West_UrinaryExosome_115_1.mzid_Mudpit_gb_20140815_ETD_West_UrinaryExosome_115_1.MGF	Mzid
	Mudpit_gb_20140815_ETD_West_UrinaryExosome_115_1.mzid_Mudpit_gb_20140815_ETD_West_UrinaryExosome_115_1.pride.mgf.gz	Mzid
	Mudpit_gb_20140815_ETD_West_UrinaryExosome_115_1.pride.mztab.gz	Mztab
	Mudpit_gb_20140815_ETD_West_UrinaryExosome_116_1.mzid.gz	Mzid

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Publications

Proteomic analysis of urinary extracellular vesicles reveal biomarkers for neurologic disease.

Wang Shijie S Kojima Kyoko K Mobley James A JA West Andrew B AB

EBioMedicine 20190620

<h4>Background</h4>Extracellular vesicles (EVs) harbor thousands of proteins that hold promise for biomarker development. Usually difficult to purify, EVs in urine are relatively easily obtained and have demonstrated efficacy for kidney disease prediction. Herein, we further characterize the proteome of urinary EVs to explore the potential for biomarkers unrelated to kidney dysfunction, focusing on Parkinson's disease (PD).<h4>Methods</h4>Using a quantitative mass spectrometry approach, we measu ...[more]

PMID: 31229437

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Project description:Objectives: Secretion of extracellular vesicles (EV) and associated micro-RNAs (miR) is altered during cellular stress and may serve as biomarkers of organ injury. We hypothesized that measuring changes in urinary levels of EV and miR will predict the onset of acute kidney injury in cardiac surgery patients. Design: Predictive accuracy biomarker study performed in the cohort of the REVAKI-2 trial Setting: Single center ICU between September 2015 and September 2018 Interventions: Intravenous sildenafil citrate 12.5 mg kg-1 over 150 min or dextrose 5% at the commencement of surgery. Measurements and main results: Urine samples were collected before and 24 hours after the procedure from 93 cardiac surgery patients. Urine EV concentrations and size distribution were assessed using NanoSight. EV derivation and levels were measured using flow cytometry. Samples from 10 selected patients were sequenced to detect differentially expressed miR. Verification was performed with advanced TaqMan assays in samples from all patients. Urine EV concentrations significantly increased in patients with AKI after surgery, with the percentage of EV positive for aquaporin-2 and β1-integrin also increasing. Pre surgery podocalyxin-positive EV were significantly lower, and β1-integrin EV werehigher in patients with AKI. The levels of the former correlated with the severity of theinjury. miR-125a-5p was expressed at higher levels in urine from patients with AKI stage 2/3. Levels of miR-10a-5p decreased after surgery in AKI patients; its levels correlated with the severity of the injury. Preoperative levels of podocalyxin EVs and miR-125a-5p had moderate AKI predictive value and, in a logistic model together with ICU lactate levels, offered good (AUC = 80.9%) AKI prediction. Conclusions: Lower levels of podocalyxin-positive EV at baseline predict the severity of post-surgery AKI. Urine EV concentrations and miR expression offer excellent predictive accuracy when combined with commonly measured biomarkers.