A metabolic biomarker predicts Parkinson’s disease at the early stages in patients and animal models
David Mallet, … , Florence Fauvelle, Sabrina Boulet
David Mallet, … , Florence Fauvelle, Sabrina Boulet
Published December 16, 2021
Citation Information: J Clin Invest. 2022;132(4):e146400. https://doi.org/10.1172/JCI146400.
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Clinical Research and Public Health Metabolism Neuroscience

A metabolic biomarker predicts Parkinson’s disease at the early stages in patients and animal models

Abstract

Background Care management of Parkinson’s disease (PD) patients currently remains symptomatic, mainly because diagnosis relying on the expression of the cardinal motor symptoms is made too late. Earlier detection of PD therefore represents a key step for developing therapies able to delay or slow down its progression.Methods We investigated metabolic markers in 3 different animal models of PD, mimicking different phases of the disease assessed by behavioral and histological evaluation, and in 3 cohorts of de novo PD patients and matched controls (n = 129). Serum and brain tissue samples were analyzed by nuclear magnetic resonance spectroscopy and data submitted to advanced multivariate statistics.Results Our translational strategy reveals common metabolic dysregulations in serum of the different animal models and PD patients. Some of them were mirrored in the tissue samples, possibly reflecting pathophysiological mechanisms associated with PD development. Interestingly, some metabolic dysregulations appeared before motor symptom emergence and could represent early biomarkers of PD. Finally, we built a composite biomarker with a combination of 6 metabolites. This biomarker discriminated animals mimicking PD from controls, even from the first, nonmotor signs and, very interestingly, also discriminated PD patients from healthy subjects.Conclusion From our translational study, which included 3 animal models and 3 de novo PD patient cohorts, we propose a promising biomarker exhibiting a high accuracy for de novo PD diagnosis that may possibly predict early PD development, before motor symptoms appear.Funding French National Research Agency (ANR), DOPALCOMP, Institut National de la Santé et de la Recherche Médicale, Université Grenoble Alpes, Association France Parkinson.

Authors

David Mallet, Thibault Dufourd, Mélina Decourt, Carole Carcenac, Paola Bossù, Laure Verlin, Pierre-Olivier Fernagut, Marianne Benoit-Marand, Gianfranco Spalletta, Emmanuel L. Barbier, Sebastien Carnicella, Véronique Sgambato, Florence Fauvelle, Sabrina Boulet

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Figure 3

Serum metabolic profile of 6-OHDA rats evolves with PD progression.

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Serum metabolic profile of 6-OHDA rats evolves with PD progression. (A) ...
(A) Example of 1HNMR spectrum at 950 MHz (δ0.5–4.7 ppm and δ6–8.5 ppm) using CPMG pulse sequence. Assignment was as follows: 1, isoleucine; 2, leucine; 3, valine; 4, BHB; 5, lactate; 6, alanine; 7, arginine; 8, lysine; 9, acetate; 10, glutamine; 11, methionine; 12, acetone; 13, acetoacetate; 14, glutamate; 15, pyruvate; 16, citrate; 17, asparagine; 18, creatine; 19, phosphocreatine; 20, DMSO2; 21, choline; 22, PC; 23, glucose; 24, betaine; 25, myoinositol; 26, glycine; 27, glycerol; 28, threonine; 29, glycerophosphocholine; 30, serine; 31, ascorbate; 32, glycerate; 33, proline; 34, deoxycytidine triphosphate; 35, tyrosine; 36, histidine; 37-phenylalanine; 38, formate. Macromolecules are not specified (see Supplemental Table 2). (B and C) OPLS model built with 1HNMR spectra of serum samples from 6-OHDA (n = 29) and sham-operated (n = 22) rats and their PDP scores: the 6-OHDA serum OPLS model. R2Y = 0.926; Q2 = 0.604; 1 predictive and 3 orthogonal components; CV-ANOVA, P = 3.47 × 10–7. (B) Score plot versus the first predictive and first orthogonal components. A clear gradation of color is observed from left to right, showing that metabolic profiles evolve with PD progression. (C) Loadings plotted in 1D with NMR variables color coded for their correlation with PD score from green (low correlation) to red (high correlation). Positive peaks indicate upregulated metabolites along with increasing PDP score, while negative peaks indicate downregulated metabolites along with PDP score evolution. (D) Relative amplitude of the metabolites most involved in metabolic gradation in 6-OHDA animals, i.e., alanine, betaine, BHB, DMSO2, glycine, lactate, pyruvate, serine, threonine, and valine in sham-operated (n = 22), prodromal-like (n = 14), and clinical-like (n = 15) animals. Data are represented as mean ± SEM, 1-way ANOVA followed by Tukey’s post hoc test and correction for multiple comparisons. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001.