Objective: To determine a pathophysiological panel of biomarkers significantly associated with the severity and the disease progression of Parkinson’s disease.
Background: Detecting, monitoring and predicting the progression of neurodegeneration in Parkinson’s disease (PD) is a major issue with crucial relevance of patient’s management and success of future therapeutical trials.
Method: Sera samples, DNA and MRI were collected as part of a large prospective multi-centric cohort of PD patients at the stage of severe motor fluctuations (Predistim: N=617, mean age: 60,6 yo, mean disease duration: 10 y). Clinical parameters to score motor and non-motors symptoms, to score cognitive impairment and to assess quality of life were used as proxy of severity and disease progression to assess the prognostic value of candidate multi-modal biomarkers. Markers related to the main physiopathological abnormalities e.g.: neurodegeneration (NfL, neurogranin), lipid peroxidation (selenium, 4-HNE, GPx activity, SNP ACSL4, SNP GPx4), inflammation (IL-6, TNF-a, Fractalkine, GFAP), iron dyshomeostasis (ferritin, iron load) and protein dyshomeostasis (a-synuclein) will be assessed by electrochemiluminescence or Elisa on sera, by MRI measurements on 3DT2* images, by genetic polymorphisms on DNA. Statistical approaches with joint latent class analyses, linear mix model analyses and machine learning will be used.
Results: NfL, 4-HNE, Il-6 and a-synuclein were positively correlated with MDS-UPDRSIII worst-off score and MDS-UPDRS total score; NfL, IL-6, TNF-a and a-synuclein were positively correlated with Hoehn & Yahr in univariate analysis with adjustment on age and disease duration. Also, NfL and alpha-synuclein were positively correlated with MDS-UPDRS total score and TNF-a correlated with Hoehn & Yahr in multivariate analysis. We will now analyze and correlate genetic and imaging data.
Conclusion: This multi-modal analysis will allow to propose a combination of pathophysiological markers, more powerful than a single one, to define a prognosis in terms of the progression of functional disability. Further analysis on longitudinal data and other cohorts of patients need will then be assess to confirm their prognostic value and their potential use in clinical trial.
To cite this abstract in AMA style:
AS. Rolland, M. Dutheil, O. Simonin, R. Viard, V. Huin, M. Kyheng, C. Moreau, S. Thobois, A. Eusebio, E. Hainque, I. Benatru, D. Maltete, C. Giordana, M. Tir, C. Hubsch, B. Jarraya, F. Durif, C. Brefel-Courbon, O. Rascol, JC. Corvol, G. Garçon, D. Devos. Multi-modal prognostic biomarkers for Parkinson’s disease progression and severity [abstract]. Mov Disord. 2022; 37 (suppl 2). https://www.mdsabstracts.org/abstract/multi-modal-prognostic-biomarkers-for-parkinsons-disease-progression-and-severity/. Accessed June 14, 2025.« Back to 2022 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/multi-modal-prognostic-biomarkers-for-parkinsons-disease-progression-and-severity/