Characterization of age/sex and the regional distribution of mGluR5 availability in the healthy human brain measured by high-resolution [11C]ABP688 PET

  • Jonathan M. DuBois
  • Olivier G. Rousset
  • Jared Rowley
  • Manuel Porras-Betancourt
  • Andrew J. Reader
  • Aurelie Labbe
  • Gassan Massarweh
  • Jean-Paul Soucy
  • Pedro Rosa-Neto
  • Eliane Kobayashi
Original Article

Abstract

Purpose

Metabotropic glutamate receptor type 5 (mGluR5) is a G protein-coupled receptor that has been implicated in several psychiatric and neurological diseases. The radiopharmaceutical [11C]ABP688 allows for in vivo quantification of mGluR5 availability using positron emission tomography (PET). In this study, we aimed to detail the regional distribution of [11C]ABP688 binding potential (BPND) and the existence of age/sex effects in healthy individuals.

Methods

Thirty-one healthy individuals aged 20 to 77 years (men, n = 18, 45.3 ± 18.2 years; females, n = 13, 41.5 ± 19.6 years) underwent imaging with [11C]ABP688 using the high-resolution research tomograph (HRRT). We developed an advanced partial volume correction (PVC) method using surface-based analysis in order to accurately estimate the regional variation of radioactivity. BPND was calculated using the simplified reference tissue model, with the cerebellum as the reference region. Surface-based and volume-based analyses were performed for 39 cortical and subcortical regions of interest per hemisphere.

Results

We found the highest [11C]ABP688 BPND in the lateral prefrontal and anterior cingulate cortices. The lowest [11C]ABP688 BPND was observed in the pre- and post-central gyri as well as the occipital lobes and the thalami. No sex effect was observed. Associations between age and [11C]ABP688 BPND without PVC were observed in the right amygdala and left putamen, but were not significant after multiple comparisons correction.

Conclusions

The present results highlight complexities underlying brain adaptations during the aging process, and support the notion that certain aspects of neurotransmission remain stable during the adult life span.

Keywords

Healthy controls Positron emission tomography [11C]ABP688 Metabotropic glutamate receptor 5 

Notes

Compliance with Ethical Standards

Funding

The study was funded by the Savoy Foundation for Epilepsy (www.savoy-foundation.ca) (pilot project grant to EK and PRN and PhD studentship to JMD), and partially by the American Epilepsy Society (www.aesnet.org) (Early Career Physician Scientist Award to EK), Canadian Institutes of Health Research (CIHR) (www.cihr-irsc.gc.ca) [MOP-115131 to PRN and MOP-93614 to EK], and the Fonds de la recherche en santé du Québec (www.frqs.gouv.qc.ca) (PRN, research fellow).

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Montreal Neurological Institute Research Ethics Board and the institutional review board of McGill University, and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

259_2015_3167_Fig5_ESM.gif (464 kb)
Online Resource 1

Simplified representation of volume-to-surface sampling method. (a) Left hemisphere shown in the coronal plane of a single subject’s T1 MRI. (b) Enlarged view of the anterior portion of the temporal lobe. A white line denotes the white matter surface and a blue line denotes the pial surface. An RBV-PVC BPND image (in yellow-red color scale) is co-registered and superimposed over the T1 MRI. The black dotted line represents corresponding vertices, with the midpoint indicated by the black circular point. In this example, BPND values are sampled from the midpoint to the surface mesh. The vertex corresponding to the midpoint is denoted by the green circle on the magnified surface mesh (c). The smaller white box denotes the region of the anterior temporal lobe that the magnified surface mesh corresponds to. RBV-PVC BPND values for all vertices are shown on the lateral left hemisphere pial surface of the same subject (d). (GIF 464 kb)

259_2015_3167_MOESM1_ESM.tiff (2.9 mb)
High-resolution image (TIFF 3017 kb)

References

  1. 1.
    Anwyl R. Metabotropic glutamate receptors: electrophysiological properties and role in plasticity. Brain Res Rev. 1999;29(1):83–120.CrossRefPubMedGoogle Scholar
  2. 2.
    Cartmell J, Schoepp DD. Regulation of neurotransmitter release by metabotropic glutamate receptors. J Neurochem. 2000;75(3):889–907.CrossRefPubMedGoogle Scholar
  3. 3.
    Hermans E, Challiss RA. Structural, signalling and regulatory properties of the group I metabotropic glutamate receptors: prototypic family C G-protein-coupled receptors. Biochem J. 2001;359(Pt 3):465–84.PubMedCentralCrossRefPubMedGoogle Scholar
  4. 4.
    Waung MW, Huber KM. Protein translation in synaptic plasticity: mGluR-LTD, Fragile X. Curr Opin Neurobiol. 2009;19(3):319–26.PubMedCentralCrossRefPubMedGoogle Scholar
  5. 5.
    Benarroch EE. Metabotropic glutamate receptors: synaptic modulators and therapeutic targets for neurologic disease. Neurology. 2008;70(12):964–8.CrossRefPubMedGoogle Scholar
  6. 6.
    Ametamey SM. Radiosynthesis and Preclinical Evaluation of 11C-ABP688 as a Probe for Imaging the Metabotropic Glutamate Receptor Subtype 5. J Nucl Med. 2006;47(4):698–705.PubMedGoogle Scholar
  7. 7.
    Ametamey SM, Treyer V, Streffer J, Wyss MT, Schmidt M, Blagoev M, et al. Human PET studies of metabotropic glutamate receptor subtype 5 with 11C-ABP688. J Nucl Med. 2007;48(2):247–52.PubMedGoogle Scholar
  8. 8.
    Treyer V, Streffer J, Wyss MT, Bettio A, Ametamey SM, Fischer U, et al. Evaluation of the metabotropic glutamate receptor subtype 5 using PET and 11C-ABP688: assessment of methods. J Nucl Med. 2007;48(7):1207–15.CrossRefPubMedGoogle Scholar
  9. 9.
    Hu Y, Xu Q, Li K, Zhu H, Qi R, Zhang Z, et al. Gender differences of brain glucose metabolic networks revealed by FDG-PET: evidence from a large cohort of 400 young adults. PLoS One. 2013;8(12), e83821.PubMedCentralCrossRefPubMedGoogle Scholar
  10. 10.
    Madsen K, Haahr MT, Marner L, Keller SH, Baare WF, Svarer C, et al. Age and sex effects on 5-HT(4) receptors in the human brain: a [(11)C]SB207145 PET study. J Cereb Blood Flow Metab. 2011;31(6):1475–81.PubMedCentralCrossRefPubMedGoogle Scholar
  11. 11.
    Grove-Strawser D, Boulware MI, Mermelstein PG. Membrane estrogen receptors activate the metabotropic glutamate receptors mGluR5 and mGluR3 to bidirectionally regulate CREB phosphorylation in female rat striatal neurons. Neuroscience. 2010;170(4):1045–55.PubMedCentralCrossRefPubMedGoogle Scholar
  12. 12.
    Deschwanden A, Karolewicz B, Feyissa AM, Treyer V, Ametamey SM, Johayem A, et al. Reduced metabotropic glutamate receptor 5 density in major depression determined by [(11)C]ABP688 PET and postmortem study. Am J Psychiatry. 2011;168(7):727–34.PubMedCentralCrossRefPubMedGoogle Scholar
  13. 13.
    Hulka LM, Treyer V, Scheidegger M, Preller KH, Vonmoos M, Baumgartner MR, et al. Smoking but not cocaine use is associated with lower cerebral metabotropic glutamate receptor 5 density in humans. Mol Psychiatr. 2014;19(5):625–32.CrossRefGoogle Scholar
  14. 14.
    DeLorenzo C, Kumar JS, Mann JJ, Parsey RV. In vivo variation in metabotropic glutamate receptor subtype 5 binding using positron emission tomography and [11C]ABP688. J Cereb Blood Flow Metab. 2011;31(11):2169–80.PubMedCentralCrossRefPubMedGoogle Scholar
  15. 15.
    Akkus F, Ametamey SM, Treyer V, Burger C, Johayem A, Umbricht D, et al. Marked global reduction in mGluR5 receptor binding in smokers and ex-smokers determined by [11C]ABP688 positron emission tomography. Proc Natl Acad Sci U S A. 2013;110(2):737–42.PubMedCentralCrossRefPubMedGoogle Scholar
  16. 16.
    Matuskey D, Pittman B, Planeta-Wilson B, Walderhaug E, Henry S, Gallezot JD, et al. Age effects on serotonin receptor 1B as assessed by PET. J Nucl Med. 2012;53(9):1411–4.PubMedCentralCrossRefPubMedGoogle Scholar
  17. 17.
    Moses-Kolko EL, Price JC, Shah N, Berga S, Sereika SM, Fisher PM, et al. Age, sex, and reproductive hormone effects on brain serotonin-1A and serotonin-2A receptor binding in a healthy population. Neuropsychopharmacology. 2011;36(13):2729–40.PubMedCentralCrossRefPubMedGoogle Scholar
  18. 18.
    Engman J, Ahs F, Furmark T, Linnman C, Pissiota A, Appel L, et al. Age, sex and NK1 receptors in the human brain -- a positron emission tomography study with [(1)(1)C]GR205171. Eur Neuropsychopharm. 2012;22(8):562–8.CrossRefGoogle Scholar
  19. 19.
    Fowler J, Volkow N, Wang G-J, Logan J, Pappas N, Shea C, et al. Age-related increases in brain monoamine oxidase B in living healthy human subjects. Neurobiol Aging. 1997;18(4):431–5.CrossRefPubMedGoogle Scholar
  20. 20.
    Erlandsson K, Buvat I, Pretorius PH, Thomas BA, Hutton BF. A review of partial volume correction techniques for emission tomography and their applications in neurology, cardiology and oncology. Phys Med Biol. 2012;57(21):R119–59.CrossRefPubMedGoogle Scholar
  21. 21.
    Uchida H, Chow TW, Mamo DC, Kapur S, Mulsant BH, Houle S, et al. Effects of aging on 5-HT(2A) R binding: a HRRT PET study with and without partial volume corrections. Int J Geriatr Psychiatry. 2011;26(12):1300–8.CrossRefPubMedGoogle Scholar
  22. 22.
    Greve DN, Svarer C, Fisher PM, Feng L, Hansen AE, Baare W, et al. Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data. NeuroImage. 2014;92:225–36.PubMedCentralCrossRefPubMedGoogle Scholar
  23. 23.
    Thomas BA, Erlandsson K, Modat M, Thurfjell L, Vandenberghe R, Ourselin S, et al. The importance of appropriate partial volume correction for PET quantification in Alzheimer's disease. Eur J Nucl Med Mol Imaging. 2011;38(6):1104–19.CrossRefPubMedGoogle Scholar
  24. 24.
    Elmenhorst D, Minuzzi L, Aliaga A, Rowley J, Massarweh G, Diksic M, et al. In vivo and in vitro validation of reference tissue models for the mGluR(5) ligand [(11)C]ABP688. J Cereb Blood Flow Metab. 2010;30(8):1538–49.PubMedCentralCrossRefPubMedGoogle Scholar
  25. 25.
    Hong I, Chung S, Kim H, Kim Y, Son Y, Cho Z. Ultra fast symmetry and SIMD-based projection-backprojection (SSP) algorithm for 3-D PET image reconstruction. IEEE Trans Med Imaging. 2007;26(6):789–803.CrossRefPubMedGoogle Scholar
  26. 26.
    Comtat C, Sureau F, Sibomana M, Hong I, Sjöholm N, Trebossen R. Image based resolution modeling for the HRRT OSEM reconstructions software. IEEE Nucl Sci Symp Conf Rec. 2008;4120–23.Google Scholar
  27. 27.
    Sureau FC, Reader AJ, Comtat C, Leroy C, Ribeiro MJ, Buvat I, et al. Impact of image-space resolution modeling for studies with the high-resolution research tomograph. J Nucl Med. 2008;49(6):1000–8.CrossRefPubMedGoogle Scholar
  28. 28.
    Costes N, Dagher A, Larcher K, Evans AC, Collins DL, Reilhac A. Motion correction of multi-frame PET data in neuroreceptor mapping: simulation based validation. NeuroImage. 2009;47(4):1496–505.CrossRefPubMedGoogle Scholar
  29. 29.
    Gunn RN, Lammertsma AA, Hume SP, Cunningham VJ. Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. NeuroImage. 1997;6(4):279–87.CrossRefPubMedGoogle Scholar
  30. 30.
    Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab. 2007;27(9):1533–9.CrossRefPubMedGoogle Scholar
  31. 31.
    Milella M, Reader A, Albrechtsons D, Minuzi L, Soucy J, Benkelfat C. Human PET validation study of reference tissue models for the mGluR5 ligand [11C] ABP688. Paper presented at Society for Neuroscience Annual Meeting. Washington, DC; 2011. 946.06/AAA31.Google Scholar
  32. 32.
    Lammertsma AA, Hume SP. Simplified reference tissue model for PET receptor studies. NeuroImage. 1996;4(3 Pt 1):153–8. doi:10.1006/nimg.1996.0066. PubMed.CrossRefPubMedGoogle Scholar
  33. 33.
    Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage. 1999;9(2):179–94.CrossRefPubMedGoogle Scholar
  34. 34.
    Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33(3):341–55.CrossRefPubMedGoogle Scholar
  35. 35.
    Fischl B, Sereno MI, Dale AM. Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. NeuroImage. 1999;9(2):195–207.CrossRefPubMedGoogle Scholar
  36. 36.
    Segonne F, Dale AM, Busa E, Glessner M, Salat D, Hahn HK, et al. A hybrid approach to the skull stripping problem in MRI. NeuroImage. 2004;22(3):1060–75.CrossRefPubMedGoogle Scholar
  37. 37.
    Fischl B, Liu A, Dale AM. Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Trans Med Imaging. 2001;20(1):70–80.CrossRefPubMedGoogle Scholar
  38. 38.
    Segonne F, Pacheco J, Fischl B. Geometrically accurate topology-correction of cortical surfaces using nonseparating loops. IEEE Trans Med Imaging. 2007;26(4):518–29.CrossRefPubMedGoogle Scholar
  39. 39.
    Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A. 2000;97(20):11050–5.PubMedCentralCrossRefPubMedGoogle Scholar
  40. 40.
    Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage. 2006;31(3):968–80.CrossRefPubMedGoogle Scholar
  41. 41.
    Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. NeuroImage. 2009;48(1):63–72.PubMedCentralCrossRefPubMedGoogle Scholar
  42. 42.
    Rousset OG, Ma Y, Evans AC. Correction for partial volume effects in PET: principle and validation. J Nucl Med. 1998;39(5):904–11.PubMedGoogle Scholar
  43. 43.
    Muller-Gartner HW, Links JM, Prince JL, Bryan RN, McVeigh E, Leal JP, et al. Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects. J Cereb Blood Flow Metab. 1992;12(4):571–83.CrossRefPubMedGoogle Scholar
  44. 44.
    Rousset O, Rahmim A, Alavi A, Zaidi H. Partial Volume Correction Strategies in PET. PET Clin. 2007;2(2):235–49.CrossRefGoogle Scholar
  45. 45.
    Ashburner J, Friston KJ. Unified segmentation. NeuroImage. 2005;26(3):839–51.CrossRefPubMedGoogle Scholar
  46. 46.
    Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: a Practical and Powerful Approach to Multiple Testing. J R Stat Soc. 1995;57(1):289–300.Google Scholar
  47. 47.
    R Development Core Team. R: a language and environment for statistical computing. 2013. http://www.R-project.org/.
  48. 48.
    Tukey JW. Exploratory data analysis. Reading, MA: Addison-Wesley; 1977.Google Scholar
  49. 49.
    Elston GN, Rockland KS. The pyramidal cell of the sensorimotor cortex of the macaque monkey: phenotypic variation. Cereb Cortex. 2002;12(10):1071–8.CrossRefPubMedGoogle Scholar
  50. 50.
    Elston GN. Cortical heterogeneity: implications for visual processing and polysensory integration. J Neurocytol. 2002;31(3–5):317–35.CrossRefPubMedGoogle Scholar
  51. 51.
    Niswender CM, Conn PJ. Metabotropic glutamate receptors: physiology, pharmacology, and disease. Annu Rev Pharmacol. 2010;50:295–322.CrossRefGoogle Scholar
  52. 52.
    Romano C, Sesma MA, McDonald CT, O'Malley K, Van den Pol AN, Olney JW. Distribution of metabotropic glutamate receptor mGluR5 immunoreactivity in rat brain. J Comp Neurol. 1995;355(3):455–69.CrossRefPubMedGoogle Scholar
  53. 53.
    Hadel S, Wirth C, Rapp M, Gallinat J, Schubert F. Effects of age and sex on the concentrations of glutamate and glutamine in the human brain. JMRI-J Magn Reson Imaging. 2013;38(6):1480–7.CrossRefGoogle Scholar
  54. 54.
    Sailasuta N, Ernst T, Chang L. Regional variations and the effects of age and gender on glutamate concentrations in the human brain. Magn Reson Imaging. 2008;26(5):667–75.PubMedCentralCrossRefPubMedGoogle Scholar
  55. 55.
    Tsamis KI, Mytilinaios DG, Njau SN, Baloyannis SJ. Glutamate Receptors in Human Caudate Nucleus in Normal Aging and Alzheimer’s Disease. Curr Alzheimer Res. 2013;10(5):469–75.CrossRefPubMedGoogle Scholar
  56. 56.
    Price DL, Rockenstein E, Ubhi K, Phung V, MacLean-Lewis N, Askay D, et al. Alterations in mGluR5 expression and signaling in Lewy body disease and in transgenic models of alpha-synucleinopathy–implications for excitotoxicity. PLoS One. 2010;5(11), e14020.PubMedCentralCrossRefPubMedGoogle Scholar
  57. 57.
    Notenboom RG, Hampson DR, Jansen GH, van Rijen PC, van Veelen CW, van Nieuwenhuizen O, et al. Up-regulation of hippocampal metabotropic glutamate receptor 5 in temporal lobe epilepsy patients. Brain. 2006;129(Pt 1):96–107.PubMedGoogle Scholar
  58. 58.
    Menard C, Quirion R. Successful cognitive aging in rats: a role for mGluR5 glutamate receptors, homer 1 proteins and downstream signaling pathways. PLoS One. 2012;7(1), e28666.PubMedCentralCrossRefPubMedGoogle Scholar
  59. 59.
    Car H, Stefaniuk R, Wiśniewska R. Effect of MPEP in Morris water maze in adult and old rats. Pharmacol Rep. 2006;59(1):88–93.Google Scholar
  60. 60.
    Leuzy A, Zimmer ER, Dubois J, Pruessner J, Cooperman C, Soucy JP, et al. In vivo characterization of metabotropic glutamate receptor type 5 abnormalities in behavioral variant FTD. Brain Struct Funct. 2015. doi:10.1007/s00429-014-0978-3.
  61. 61.
    Rousset OG, Collins DL, Rahmim A, Wong DF. Design and implementation of an automated partial volume correction in PET: application to dopamine receptor quantification in the normal human striatum. J Nucl Med. 2008;49(7):1097–106.PubMedCentralCrossRefPubMedGoogle Scholar
  62. 62.
    Kagedal M, Cselenyi Z, Nyberg S, Raboisson P, Stahle L, Stenkrona P, et al. A positron emission tomography study in healthy volunteers to estimate mGluR5 receptor occupancy of AZD2066 - estimating occupancy in the absence of a reference region. NeuroImage. 2013;82:160–9.CrossRefPubMedGoogle Scholar
  63. 63.
    DeLorenzo C, Milak MS, Brennan KG, Kumar JS, Mann JJ, Parsey RV. In vivo positron emission tomography imaging with [(1)(1)C]ABP688: binding variability and specificity for the metabotropic glutamate receptor subtype 5 in baboons. Eur J Nucl Med Mol Imaging. 2011;38(6):1083–94.PubMedCentralCrossRefPubMedGoogle Scholar
  64. 64.
    Mathews WB, Kuwabara H, Stansfield K, Valentine H, Alexander M, Kumar A, et al. Dose-dependent, saturable occupancy of the metabotropic glutamate subtype 5 receptor by fenobam as measured with [11C] ABP688 PET imaging. Synapse. 2014;68(12):565–73.Google Scholar
  65. 65.
    Daggett L, Sacaan A, Akong M, Rao S, Hess S, Liaw C, et al. Molecular and functional characterization of recombinant human metabotropic glutamate receptor subtype 5. Neuropharmacology. 1995;34(8):871–86.CrossRefPubMedGoogle Scholar
  66. 66.
    Patel S, Hamill TG, Connolly B, Jagoda E, Li W, Gibson RE. Species differences in mGluR5 binding sites in mammalian central nervous system determined using in vitro binding with [18F]F-PEB. Nucl Med Biol. 2007;34(8):1009–17.CrossRefPubMedGoogle Scholar
  67. 67.
    DeLorenzo C, DellaGioia N, Bloch M, Sanacora G, Nabulsi N, Abdallah C, et al. In vivo ketamine-induced changes in [11C]ABP688 binding to metabotropic glutamate receptors subtype 5. Biol Psychiatry. 2015;77(3):266–75.Google Scholar
  68. 68.
    Wyckhuys T, Verhaeghe J, Wyffels L, Langlois X, Schmidt M, Stroobants S, et al. N-acetylcysteine- and MK-801-induced changes in glutamate levels do not affect in vivo binding of metabotropic glutamate 5 receptor radioligand 11C-ABP688 in rat brain. J Nucl Med. 2013;54(11):1954–61.CrossRefPubMedGoogle Scholar
  69. 69.
    Zimmer ER, Parent MJ, Leuzy A, Aliaga A, Aliaga A, Moquin L, et al. Imaging in vivo glutamate fluctuations with [C]ABP688: a GLT-1 challenge with ceftriaxone. J Cereb Blood Flow Metab. 2015;35:1169–74.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Jonathan M. DuBois
    • 1
  • Olivier G. Rousset
    • 2
  • Jared Rowley
    • 3
  • Manuel Porras-Betancourt
    • 1
  • Andrew J. Reader
    • 4
    • 5
  • Aurelie Labbe
    • 6
    • 7
  • Gassan Massarweh
    • 1
  • Jean-Paul Soucy
    • 1
  • Pedro Rosa-Neto
    • 1
    • 3
  • Eliane Kobayashi
    • 1
  1. 1.Department of Neurology and Neurosurgery, Montreal Neurological InstituteMcGill UniversityMontrealCanada
  2. 2.The Russell H. Morgan Department of Radiology and Radiological ScienceJohns Hopkins UniversityBaltimoreUSA
  3. 3.Translational Neuroimaging Laboratory, McGill Center for Studies in Aging, Douglas Mental Health University InstituteMcGill UniversityMontrealCanada
  4. 4.PET Unit, McConnell Brain Imaging Center, Montreal Neurological InstituteMcGill UniversityMontrealCanada
  5. 5.Division of Imaging Sciences and Biomedical EngineeringKing’s College London, St. Thomas’ HospitalLondonUK
  6. 6.Department of Epidemiology, Biostatistics and Occupational healthMcGill UniversityMontrealCanada
  7. 7.Department of PsychiatryDouglas Mental Health University Institute / Douglas Institut Universitaire en Santé MentaleMontrealCanada

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