Molecular Neurobiology

, Volume 54, Issue 7, pp 5361–5374 | Cite as

Omics to Explore Amyotrophic Lateral Sclerosis Evolution: the Central Role of Arginine and Proline Metabolism

  • Franck PatinEmail author
  • Philippe Corcia
  • Patrick Vourc’h
  • Lydie Nadal-Desbarats
  • Thomas Baranek
  • Jean-François Goossens
  • Sylviane Marouillat
  • Anne-Frédérique Dessein
  • Amandine Descat
  • Blandine Madji Hounoum
  • Clément Bruno
  • Samuel Leman
  • Christian R Andres
  • Hélène Blasco


In amyotrophic lateral sclerosis (ALS), motor neuron degeneration is associated with systemic metabolic impairment. However, the evolution of metabolism alteration is partially unknown and its link with disease progression has never been described. For the first time, we ran a study focused on (1) the evolution of metabolism disturbance during disease progression through omics approaches and (2) the relation between metabolome profile and clinical evolution. SOD1-G93A (mSOD1) transgenic mice (n = 11) and wild-type (WT) littermates (n = 17) were studied during 20 weeks. Metabolomic profile of muscle and cerebral cortex was analysed at week 20, and plasma samples were assessed at four time points over 20 weeks. The relevant metabolic pathways highlighted by metabolomic analysis were explored by a targeted transcriptomic approach in mice. Plasma metabolomics were also performed in 24 ALS patients and 24 gender- and age-matched controls. Metabolomic analysis of muscle and cerebral cortex enabled an excellent discrimination between mSOD1 and WT mice (p < 0.001). These alterations included especially tryptophan, arginine, and proline metabolism pathways (including polyamines) as also revealed by transcriptomic analysis and findings in ALS patients. Multivariate models performed to explain clinical findings in ALS mice, and patients were excellent (p < 0.01) and highlighted three main metabolic pathways: arginine and proline, tryptophan, and branched amino acid metabolism. This work is the first longitudinal study that evaluates metabolism alteration in ALS, including the analysis of different tissues and using a combination of omics methods. We particularly identified arginine and proline metabolism. This pathway is also associated with disease progression and may open new perspectives of therapeutic targets.


Amyotrophic lateral sclerosis Metabolomics Transcriptomics Arginine Polyamine Biomarker 



The authors thank Pr Hervé Watier for his invaluable assistance in preparing this manuscript. The authors thank Nowoczyn Marie who performed spectrometry analysis. The authors would especially like to thank the Fondation Brou de Laurières and the French “Association pour la Recherche sur la Sclérose Latérale Amyotrophique et autres maladies du motoneurone” (ARSLA) for their support of this project.

Authors’ Contributions

Franck Patin performed experiments involving animals, statistical analysis and interpretation of data and wrote the first draft of the manuscript. Philippe Corcia enrolled patients and revised the manuscript for important intellectual content. Patrick Vourc’h critically revised the manuscript for important intellectual content. Lydie Nadal-Desbarats supervised NMR analysis and critically revised the manuscript for important intellectual content. Thomas Baranek critically revised the manuscript for important intellectual content. Jean-François Goossens supervised mass spectroscopy analysis and revised the manuscript for important intellectual content. Sylviane Marouillat supervised experiments involving gene expression profiles. Anne-Frédérique Dessein supervised mass spectroscopy analysis and revised the manuscript for important intellectual content. Amandine Descat participated to mass spectroscopy analysis. Blandine Madji Hounoum revised the manuscript for important intellectual content. Clément Bruno participated experiments and revised the manuscript for important intellectual content. Samuel Leman supervised the rotarod experiments and revised the manuscript for important intellectual content. Christian Andres revised the manuscript for important intellectual content. Hélène Blasco analysed and interpreted data and critically revised the manuscript for important intellectual content.

AD Alzheimer disease, ADMA asymmetric dimethyl arginine, ALS amyotrophic lateral sclerosis, ALSFRS ALS Functional Rating Scale, BCAA branched chain amino acids, CSF cerebrospinal fluid, HPLC high-performance liquid chromatography, mSOD1 SOD1-G93A, MUFA monounsaturated fatty acids, NMDA N-methyl d-aspartic acid, NMR nuclear magnetic resonance spectroscopy, OPLS-DA orthogonal partial least square discriminant analysis, PCA principal component analysis, PDC pyruvate dehydrogenase complex, PDH pyruvate dehydrogenase, PUFA polyunsaturated fatty acids, QC quality control, ROS reactive oxygen species, SALS sporadic amyotrophic lateral sclerosis, SCD1 stearoyl-CoA desaturase, SDMA symmetric dimethyl arginine, SFA saturated fatty acids, VFC vital forced capacity, WT wild type

Compliance with Ethical Standards


Conflict of interest

The authors declare that no conflict of interest exists in relation to the present manuscript.


This study was supported by the Fondation Brou de Laurières (Périgueux, France).

Supplementary material

12035_2016_78_MOESM1_ESM.jpg (318 kb)
Fig. S1 a Body weight data. b Slow rotarod performance (JPEG 317 kb)
12035_2016_78_MOESM2_ESM.bmp (1 mb)
Fig. S2 Metabolome of cerebral cortex samples of mSOD1 mice analysed by unsupervised analysis. Principal Component Analysis (PCA) plot for cerebral cortex metabolome measured by High Performance Liquid Chromatography (HPLC) coupled to Mass Spectroscopy and obtained 36/40 from a mSOD1 mice (n = 11), in blue, and b WT mice (n = 17), in green. The two first components accounted for 76 % of the total dataset variance. (BMP 1054 kb)
12035_2016_78_Fig6_ESM.gif (175 kb)
Fig. S3

a Fold change mSOD1 versus WT. b Fold change according to clinical findings (age at beginning of weight loss). (GIF 175 kb)

12035_2016_78_MOESM3_ESM.tif (148 kb)
High resolution image (TIFF 147 kb)
12035_2016_78_Fig7_ESM.gif (172 kb)
Fig. S4

Multivariate model to explain VFC evolution during disease progression of ALS patients. a Score scatter plot from 12 metabolites showing the discrimination of ALS patients according to VFC evolution. b Loading score plot showing the relevance of the main metabolites involved in this model. (GIF 171 kb)

12035_2016_78_MOESM4_ESM.tif (171 kb)
High-resolution image (TIFF 171 kb)
12035_2016_78_MOESM5_ESM.doc (226 kb)
Table S1 List of all metabolites analysed. (DOC 226 kb)
12035_2016_78_MOESM6_ESM.doc (92 kb)
Table S2 List of all genes analysed. Fold change was calculated using the ΔΔCt method. Genes with fold changes (2-ΔΔCt) greater than 2 or lesser than 0.5 were reported as up- or down-regulated. (DOC 91 kb)
12035_2016_78_MOESM7_ESM.doc (737 kb)
Table S3 Univariate findings from metabolomic data. All tests with a p value inferior to 0.05 are given. Bonferroni’s correction was used to determine the appropriate threshold for p value for each analytical platform. Only results with a p value inferior to threshold after correction were reported in the rest of the study. (DOC 737 kb)
12035_2016_78_MOESM8_ESM.doc (49 kb)
Table S4 Multivariate models-orthogonal partial least square-discriminant analysis. All models used in this study are given. For each condition, model characteristics are given before and after automated variable selection, and most discriminant metabolites identified by this method are listed in last column. (DOC 49 kb)


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Franck Patin
    • 1
    • 2
    Email author
  • Philippe Corcia
    • 1
    • 3
  • Patrick Vourc’h
    • 1
    • 2
    • 4
  • Lydie Nadal-Desbarats
    • 1
    • 4
  • Thomas Baranek
    • 5
  • Jean-François Goossens
    • 6
  • Sylviane Marouillat
    • 1
  • Anne-Frédérique Dessein
    • 7
  • Amandine Descat
    • 6
  • Blandine Madji Hounoum
    • 1
  • Clément Bruno
    • 1
    • 2
  • Samuel Leman
    • 1
  • Christian R Andres
    • 1
    • 2
  • Hélène Blasco
    • 1
    • 2
  1. 1.Imagerie et Cerveau, UMR U930INSERM, Université François RabelaisToursFrance
  2. 2.Laboratoire de Biochimie et Biologie moléculaireHôpital Bretonneau, CHRU de ToursToursFrance
  3. 3.Fédération des CRCSLA Tours-Limoges (LITORALS)ToursFrance
  4. 4.Analyse des systèmes biologiques PPFUniversité François Rabelais de ToursToursFrance
  5. 5.Centre d’étude des Pathologies RespiratoiresUMR 1100, INSERM, Université François RabelaisToursFrance
  6. 6.Centre Universitaire de Mesures et d’Analyses (CUMA)Université de Lille 2LilleFrance
  7. 7.Centre de Biologie et de PathologieCHRU de LilleLilleFrance

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