Fatigue in Parkinson's Disease: A Proteomic Study of Cerebrospinal Fluid

Many factors have been linked to fatigue in patients with Parkinson's disease (PD), including age, female sex, disease severity, depression, cognition, sleep disturbances, activities of daily living, and the use of dopamine agonists.1, 2 While these sociodemographic and non-motor phenomena undoubtedly impact fatigue, they do not elucidate the molecular mechanisms underlying it. To the best of our knowledge, no previous studies have investigated the cerebrospinal fluid (CSF) proteome in patients with PD, specifically focusing on fatigue. Therefore, we aimed to perform an exploratory proteomic study of the CSF to gain more knowledge of the biological mechanisms of fatigue in this disease. Patients with PD were recruited from the Norwegian ParkWest study.3 We dichotomized CSF samples into 10 patients with low and 9 with high fatigue scores for further label-free liquid chromatography with tandem mass spectrometry analyses (supplementary file for complete methods). Fatigue severity was assessed using the generic and unidimensional Fatigue Severity Scale (FSS) instrument.4 Supervised partial least squares discriminant analysis (PLS-DA) modeling was performed to optimize the separation between the two fatigue groups and simultaneously identify the proteins that contributed the most to this separation. A PLS-DA score plot (Fig. 1A) demonstrated the separation between the two groups (classification error rate 0.322 [permutation test P-value 0.474]). Owing to the risk of overfitting in the PLS-DA model, we further examined the feasibility of separating the patients into two fatigue groups by performing an unsupervised principal component analysis (PCA) using the expression level data from the top 20 discriminatory proteins identified by PLS-DA (Fig. 1B). The main finding of this study revealed that the presence of 20 differentially expressed proteins in the CSF enables the separation of patients with PD into high and low fatigue groups. Several of these proteins are involved in innate immunity, cellular stress responses, and cerebral functions related to the sickness behavioral response components (innate immunity [alpha-mannosidase 2, complement C1q subcomponent subunit C, immunoglobulin J chain, plastin-2], cellular stress responses [autotaxin, N-myc downstream-regulated gene (NDRG) family member 4, prosaposin], and cerebral functions related to elements of the sickness behavioral response [netrin receptor DCC, neuromodulin, transmembrane protein 132D, transthyretin]). This finding indicates that the molecular composition of the CSF in patients with PD reflects biological processes associated with fatigue. Some of the proteins we identified may be involved in primary PD disease mechanisms, neuronal degeneration, or other non-fatigue processes. A major limitation is that the sample size is too low to adjust for relevant covariates such as higher age, more severe depression, worse sleep state, more progressed disease stage, and higher motor severity as observed in the high fatigue group. Conversely, fatigue in patients with PD has been reported to be an independent non-motor phenomenon, indicating that factors other than those that are psychosocial and demographic could contribute to fatigue generators.1, 5 These findings emphasize the fundamental biological nature of fatigue and call for further investigations in a larger cohort to unveil pathways and mechanisms through which fatigue is generated in the brain. Mass spectrometry-based proteomic analyses were performed by the Proteomics Unit at the University of Bergen, a member of the National Network of Advanced Proteomics Infrastructure (NAPI). NAPI is funded by the Research Council of Norway (INFRASTRUKTUR-program project number 295910). (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the First Draft, B. Review and Critique. L.E.E.: 1A, 1B, 1C, 2A, 2B, 3A. E.B.: 1C, 2C, 3B. M.A.: 2A, 2B, SC, 3B. K.B.: 2A, 2B, 2C, 3B. J.L.: 1B, 3B. G.A.: 1A, 1B, 1C, 3B. F.B.: 1A, 3B. M.M.N.: 2A, 2C, 3A, 3B. K.H.: 1B, 3B. O.-B.T.:1B, 3B. R.O.:1A, 1B, 2A, 2C, 3A, 3B. L.E.E.: Stock Ownership in Medically-related Fields: ContextVision AB and Inify Laboratories; Intellectual Property Rights: none; Consultancies: none; Expert Testimony: none; Advisory Boards: none; Employment: Helse Stavanger HF; Partnerships: none; Inventions: none; Contracts: none; Honoraria: none; Royalties: none; Patents: none; Grants: Western Norway Regional Health Authority (WNRHA, ‘Helse Vest’, grant number 12507); Other: none. M.A.: Stock Ownership in Medically-related Fields: Novo Nordisk; Intellectual Property Rights: none; Consultancies: none; Expert Testimony: none; Advisory Boards: none; Employment: Helse Stavanger HF; Partnerships: none; Inventions: none; Contracts: none; Honoraria: none; Royalties: none; Patents: none; Grants: Western Norway Regional Health Authority (WNRHA, ‘Helse Vest’, grant number 912307); Other: none. R.O.: Stock Ownership in Medically-related Fields: Nycode Therapeutics ASA, Photocure ASA; Intellectual Property Rights: none; Consultancies: none; Expert Testimony: none; Advisory Boards: none; Employment: Helse Stavanger HF; Partnerships: none; Inventions: none; Contracts: none; Honoraria: none; Royalties: none; Patents: none; Other: none. All other authors have listed ‘None’ for all financial disclosure categories. The data that support the findings of this study are available from the corresponding author upon reasonable request. Data S1. Supporting information. Table S1. Selected patient data for 20 Parkinson's disease patients with high and low fatigue. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.