Objective: The aim of this work was to identify proteomic profiles associated with specific Parkinson’s disease (PD) clinical groups in leukocytes of patients from Rio de Janeiro in order to recognise putative disease biomarkers.

Background: PD is the second most incident neurodegenerative disease worldwide. Its diagnosis is based only on clinical symptoms such as bradykinesia, resting tremor or muscular rigidity and for this reason many patients are being misdiagnosed leading to inappropriate treatments. This proves the importance of identifying biomarkers for an accurate diagnose as well as for new treatment development. Regarding the biomarkers identification, proteomics allows the identification of the protein expression profile present in a given biological sample unequivocally, providing valuable information about signalling pathways presents in different groups of patients. Thus, a research design that includes clinical features and high resolution mass spectrometry strategies is extremely important to identify proteins as putative biomarkers.

Method: The normal onset patients blood samples (42) were classified into 3 clinical groups: akinetic-rigid (AR), tremordominant (TD) and classic (C) patients according to their symptoms. Samples were then processed to obtain their leukocytes. All groups had their protein extracted, quantified and digested. After purification, the samples were analysed by label-free Liquid Chromatography – High resolution Mass Spectrometry (LC-MS/MS) with Q-Exactive Plus (Thermo). Results were further analysed by functional bioinformatic softwares.

Results: We identified 490 proteins in each clinical group and healthy controls (HC). We identified exclusive proteins for each group: HC (117), C (129), TD (43), AR (34). Functional in silico analysis comparing the clinical subtypes together with healthy controls revealed as major alterations in neutrophil degranulation, protein folding and post-translational modifications. It was also possible to identify alteration in nucleosome assembly for classic subtype; FOXA1 transcriptional factor signalling for akinetic-rigid subtype and IL-8 and CXCR2 signalling for tremordominant subtype.

Conclusion: Our data contributes to identification of different biological processes in leukocytes of PD patients with different clinical features suggesting new putative biomarkers.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/functional-proteomic-analysis-of-leukocytes-from-parkinsons-disease-patients-a-clinical-perspective-on-biomarkers-identification/