PXD006438 is an
original dataset announced via ProteomeXchange.
Dataset Summary
Title | Quantitative label-free proteomic analysis of human urine to identify novel protein biomarkers for schistosomiasis |
Description | Background: Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population, and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. Methodology: A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. Results: A total of 1306 proteins and 8752 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). Conclusion: These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis. |
HostingRepository | PRIDE |
AnnounceDate | 2017-10-24 |
AnnouncementXML | Submission_2017-10-24_07:03:53.xml |
DigitalObjectIdentifier | |
ReviewLevel | Peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Unsupported dataset by repository |
PrimarySubmitter | Bridget Calder |
SpeciesList | scientific name: Homo sapiens (Human); NCBI TaxID: 9606; scientific name: Schistosoma haematobium; NCBI TaxID: 6185; |
ModificationList | No PTMs are included in the dataset |
Instrument | Q Exactive |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
0 | 2017-05-03 03:40:10 | ID requested | |
⏵ 1 | 2017-10-24 07:03:54 | announced | |
2 | 2019-02-12 08:22:31 | announced | Updated publication reference for PubMed record(s): 29117212. |
Publication List
Dataset with its publication pending |
Keyword List
curator keyword: Biomedical |
submitter keyword: schistosomiasis, Schistosoma haematobium, bladder cancer, QExactive, discovery proteomics, biomarkers |
Contact List
Jonathan Blackburn |
contact affiliation | Department of Integrative Biomedical Sciences & Institute of Infectious Disease & Molecular Medicine Faculty of Health Sciences, University of Cape Town Anzio, Observatory Cape Town 7925 South Africa |
contact email | jonathan.blackburn@uct.ac.za |
lab head | |
Bridget Calder |
contact affiliation | University of Cape Town |
contact email | bridget.calder@uct.ac.za |
dataset submitter | |
Full Dataset Link List
Dataset FTP location
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PRIDE project URI |
Repository Record List
[ + ]
[ - ]
- PRIDE
- PXD006438
- Label: PRIDE project
- Name: Quantitative label-free proteomic analysis of human urine to identify novel protein biomarkers for schistosomiasis