Molecular Neurobiology

, Volume 56, Issue 3, pp 2092–2100 | Cite as

MTOR Pathway-Based Discovery of Genetic Susceptibility to L-DOPA-Induced Dyskinesia in Parkinson’s Disease Patients

  • Núria Martín-Flores
  • Rubén Fernández-Santiago
  • Francesa Antonelli
  • Catalina Cerquera
  • Verónica Moreno
  • Maria Josep Martí
  • Mario Ezquerra
  • Cristina MalageladaEmail author


Dyskinesia induced by L-DOPA administration (LID) is one of the most invalidating adverse effects of the gold standard treatment restoring dopamine transmission in Parkinson’s disease (PD). However, LID manifestation in parkinsonian patients is variable and heterogeneous. Here, we performed a candidate genetic pathway analysis of the mTOR signaling cascade to elucidate a potential genetic contribution to LID susceptibility, since mTOR inhibition ameliorates LID in PD animal models. We screened 64 single nucleotide polymorphisms (SNPs) mapping to 57 genes of the mTOR pathway in a retrospective cohort of 401 PD cases treated with L-DOPA (70 PD with moderate/severe LID and 331 with no/mild LID). We performed classic allelic, genotypic, and epistatic analyses to evaluate the association of individual or combinations of SNPs with LID onset and with LID severity after initiation of L-DOPA treatment. As for the time to LID onset, we found significant associations with SNP rs1043098 in the EIF4EBP2 gene and also with an epistatic interaction involving EIF4EBP2 rs1043098, RICTOR rs2043112, and PRKCA rs4790904. For LID severity, we found significant association with HRAS rs12628 and PRKN rs1801582 and also with a four-loci epistatic combination involving RPS6KB1 rs1292034, HRAS rs12628, RPS6KA2 rs6456121, and FCHSD1 rs456998. These findings indicate that the mTOR pathway contributes genetically to LID susceptibility. Our study could help to identify the most susceptible PD patients to L-DOPA in order to prevent the appearance of early and/or severe LID in a future. This information could also be used to stratify PD patients in clinical trials in a more accurate way.


mTOR L-DOPA Dyskinesia Single nucleotide polymorphism Parkinson’s disease Epistasia 







L-DOPA-induced dyskinesia


Minor allele frequency


Multifactorial dimensionality reduction


Mechanistic target of rapamycin complex


Parkinson’s disease


Single nucleotide polymorphisms


Time to dyskinesia


Time to L-DOPA


Time to LID Peak


L-DOPA equivalent dose



We thank Dr. Jason H. Moore and Dr. Peter Andrews for their kind assessment with the MDR software use and helpful discussion. We also thank Dr. Roger Anglada from the Genomics Core Facility from the Universitat Pompeu Fabra (Barcelona) for his work and helpful assessment with sample analysis. We acknowledge the CERCA Program from the Generalitat de Catalunya and the FEDER Program from the European Union to IDIBAPS.

Compliance of Ethical Standards

All subjects were recruited at the Movement Disorders Unit from the Hospital Clínic Provincial de Barcelona. Written informed consent and whole blood samples were obtained from each subject. The study was approved by the Ethics Committee of the Hospital Clínic de Barcelona.

Conflict of Interest

This work has been granted by the Michael J. Fox Foundation, Dyskinesia Challenge 2014. The technology derived from this work has been filed for a European patent application (File number: EP17382248), to develop a diagnostics method of personalized medicine for PD patients.

Supplementary material

12035_2018_1219_Fig1_ESM.png (7.9 mb)
Figure 1

Illustration of the mTOR pathway with the proteins encoded by the genes with the selected SNPs for the analyses. The illustration contains 64 proteins directly or closely related to the mTOR pathway. For the analyses, SNPs from the genes coding for these proteins were selected. (PNG 8102 kb)

12035_2018_1219_MOESM1_ESM.tif (9 mb)
High Resolution (TIF 9198 kb)
12035_2018_1219_Fig2_ESM.png (792 kb)
Figure 2

Association of the SNPs rs1043098 in EIF4EBP2, rs2043112 in RICTOR and rs4790904 in PRKCA genes with LID onset. (A) SNP interaction map with LID onset. The nodes were obtained in the epistatic analyses with the MDR software and represent the polymorphisms, including the genes that contain the SNP, while the numeric values inside represent the main information gain. The links show the interaction between SNPs. The color of the lines indicates the type of interaction explaining synergy or redundancy (yellow = independency, blue = correlation and orange = synergistic relationship). (B) Localization in the mTOR pathway of the proteins translated from the genes with SNPs significantly associated with LID onset. In color are highlighted the proteins 4EBP2 (orange), Rictor (pink) and PKCα (green) that are the product of the genes EIF4EBP2, RICTOR and PRKCA, respectively. (PNG 791 kb)

12035_2018_1219_MOESM2_ESM.tif (11.9 mb)
High Resolution (TIF 12235 kb)
12035_2018_1219_Fig3_ESM.png (24 kb)
Figure 3

Distribution of high-risk and low-risk genotypes in the interaction of rs1043098 in EIF4EBP2, rs2043112 in RICTOR and rs4790904 in PRKCA with LID onset. Light gray boxes present combinations for early LID onset and dark gray boxes present the combinations for late LID onset. In each cell is shown the TTD average (7,62 years) in a horizontal line and in vertical the difference in years in each combination from the global mean. (PNG 23.5 kb)

12035_2018_1219_MOESM3_ESM.tif (1.7 mb)
High Resolution (TIF 1771 kb)
12035_2018_1219_Fig4_ESM.png (852 kb)
Figure 4

Association of the SNPs rs12628 in HRAS, rs5456121 in RPS6KA2, rs1292034 in RPS6KB1 and rs456998 in FCHSD1 genes with LID severity. (A) SNP interaction map with LID onset. The nodes were obtained in the epistatic analyses with the MDR software and represent the polymorphisms, including the gene that contain the SNP, while the numeric values inside represent the main information gain. The links show the interaction between SNPs. The color of the lines indicates the type of interaction explaining synergy or redundancy (yellow = independency, blue = correlation and orange = synergistic relationship). (B) Localization in the mTOR pathway of the proteins translated from the genes with SNPs significantly associated with LID severity. In color are highlighted the proteins H-Ras (light blue), ribosomal protein S6 kinase beta-1, S6 K1, and ribosomal protein S6 kinase alpha-2, S6 K2, (green and pink) and FCHSD1 (red) that are encoded by the genes HRAS, RPS6KB1, RPS6KA2 and FCHSD1, respectively. (PNG 851 kb)

12035_2018_1219_MOESM4_ESM.tif (11.9 mb)
High Resolution (TIF 12235 kb)
12035_2018_1219_Fig5_ESM.png (53 kb)
Figure 5

Distribution of high-risk and low-risk genotypes in the interaction of rs1292034 in RPS6KB1, rs12628 in HRAS, rs6456121 in RPS6KA2 and rs456998 in FCHSD1 with LID severity. Dark gray boxes present the high-risk factor combinations (moderate/severe LID severity) and light gray boxes present the low risk factor combinations (no/mild LID severity). Each cell shows the number of PD patients with moderate/severe LID with that specific genotype on the left bar and control group with no/mild LID on the right bar. (PNG 53.4 kb)

12035_2018_1219_MOESM5_ESM.tif (5.5 mb)
High Resolution (TIF 5661 kb)
12035_2018_1219_MOESM6_ESM.docx (23 kb)
ESM 1 SNPs in the genes of the mTOR pathway and PD related genes selected for the analyses. (DOCX 22.9 kb)
12035_2018_1219_MOESM7_ESM.docx (19 kb)
ESM 2 Distribution of genotypes in the interaction of rs1043098 in EIF4EBP2, rs2043112 in RICTOR and rs4790904 in PRKCA with LID onset. (DOCX 18.6 kb)
12035_2018_1219_MOESM8_ESM.docx (15 kb)
ESM 3 MDR analysis of SNP-SNP interaction with LID severity considering no LID as the control group. (DOCX 15.3 kb)
12035_2018_1219_MOESM9_ESM.docx (23 kb)
ESM 4 Distribution of genotypes in the interaction of rs1292034 in RPS6KB1, rs12628 in HRAS, rs6456121 in RPS6KA2 and rs456998 in FCHSD1 with LID severity. (DOCX 23.1 kb)
12035_2018_1219_MOESM10_ESM.docx (17 kb)
ESM 5 MDR forced analysis for the interaction between rs1292034 RPS6KB1, rs12628 HRAS, rs6456121 RPS6KA2 and rs456998 FCHSD1 with LID with severity as main variable. (DOCX 16.9 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Núria Martín-Flores
    • 1
    • 2
  • Rubén Fernández-Santiago
    • 3
    • 4
    • 5
  • Francesa Antonelli
    • 4
  • Catalina Cerquera
    • 4
    • 6
  • Verónica Moreno
    • 4
  • Maria Josep Martí
    • 3
    • 4
    • 5
  • Mario Ezquerra
    • 3
    • 4
    • 5
  • Cristina Malagelada
    • 1
    • 2
    Email author
  1. 1.Department of Biomedicine, Unit of Biochemistry, Faculty of MedicineUniversitat de BarcelonaBarcelonaSpain
  2. 2.Institut de NeurociènciesUniversitat de BarcelonaBarcelonaSpain
  3. 3.IDIBAPS-Institut d’Investigacions Biomèdiques August Pi i SunyerBarcelonaSpain
  4. 4.Neurology ServiceHospital Clínic de BarcelonaBarcelonaSpain
  5. 5.Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
  6. 6.Neurology Unit, Medical SchoolHospital Universitario San Ignacio, Pontificia Universidad JaverianaBogotáColombia

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