Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biomarker-based diagnostic approaches. This study utilizes UPLC-ESI-QTOF untargeted metabolomics combined with biochemometrics to identify novel serum biomarkers for PD. Analyzing a Brazilian cohort of serum samples from 39 PD patients and 15 healthy controls, we identified fifteen metabolites significantly associated with PD
[doi:10.25345/C5GB1XT9Z]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Metabolomics ; Parkinson's disease ; Biomarkers ; Caffeine metabolism ; Multivariate analysis ; Machine learning.
|
Principal Investigators: (in alphabetical order) |
Albert Katchborian Neto, Federal University of Alfenas, Brazil |
| Submitting User: | albert_katch |
| Number of Files: | |
| Total Size: | |
| Spectra: | |
| Subscribers: | |
| Owner | Reanalyses | |
|---|---|---|
| Experimental Design | ||
|
Conditions:
|
||
|
Biological Replicates:
|
||
|
Technical Replicates:
|
||
| Identification Results | ||
|
Proteins (Human, Remapped):
|
||
|
Proteins (Reported):
|
||
|
Peptides:
|
||
|
Variant Peptides:
|
||
|
PSMs:
|
||
| Quantification Results | ||
|
Differential Proteins:
|
||
|
Quantified Proteins:
|
||
| Browse Dataset Files | |
|
FTP Download Link (click to copy):
|