AI Article Synopsis

  • Differentiating between progressive supranuclear palsy (PSP) and Parkinson's disease (PD) is difficult due to similar symptoms, prompting a search for reliable biomarkers.
  • Researchers analyzed serum samples from patients and healthy controls using a proximity elongation assay (PEA) and machine learning techniques to identify key protein differences, leading to the discovery of five promising proteins.
  • Notably, levels of TFF3, CPB1, and OPG varied between the two conditions, but ELISA tests revealed no differences in the three most significant biomarkers, raising concerns about the reliability of translating proteomic data into clinical applications.

Article Abstract

Clinical differentiation of progressive supranuclear palsy (PSP) from Parkinson's disease (PD) is challenging due to overlapping phenotypes and late onset of PSP specific symptoms, highlighting the need for easily assessable biomarkers. We used proximity elongation assay (PEA) to analyze 460 proteins in serum samples from 46 PD, 30 PSP patients, and 24 healthy controls. ANCOVA was used to identify the most promising proteins and machine learning (ML) XGBoost and random forest algorithms to assess their classification performance. Promising proteins were also quantified by ELISA. Moreover, correlations between serum biomarkers and biological and clinical features were investigated. We identified five proteins (TFF3, CPB1, OPG, CNTN1, TIMP4) showing different levels between PSP and PD, which achieved good performance (AUC: 0.892) when combined by ML. On the other hand, when the three most significant biomarkers (TFF3, CPB1 and OPG) were analyzed by ELISA, there was no difference between groups. Serum levels of TFF3 positively correlated with age in all subjects' groups, while for OPG and CPB1 such a correlation occurred in PSP patients only. Moreover, CPB1 positively correlated with disease severity in PD, while no correlations were observed in the PSP group. Overall, we identified CPB1 correlating with PD severity, which may support clinical staging of PD. In addition, our results showing discrepancy between PEA and ELISA technology suggest that caution should be used when translating proteomic findings into clinical practice.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11546529PMC
http://dx.doi.org/10.3390/ijms252111663DOI Listing

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