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Cerebellum & Ataxias

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Neural correlates of ataxia severity in spinocerebellar ataxia type 3/Machado-Joseph disease

  • Carlos R. Hernandez-Castillo1,
  • Rosalinda Diaz2,
  • Aurelio Campos-Romo3 and
  • Juan Fernandez-Ruiz2Email author
Cerebellum & Ataxias20174:7

https://doi.org/10.1186/s40673-017-0065-7

Received: 18 May 2017

Accepted: 29 May 2017

Published: 6 June 2017

Abstract

Background

Spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) is an autosomal dominant inherited neurodegenerative disorder. Several post-mortem and imaging studies have shown cerebellar and brainstem atrophy. A number of studies have used volumetric regional information to investigate the relationship between neurodegeneration and the ataxia severity. However, regional analysis can obscure the specific location in which the degenerative process is affecting the brain tissue, which can be crucial for the development of new target treatments for this disease.

Here we explored the relationship between the gray matter degeneration and the ataxia severity on a cohort of SCA3 patients using a voxel-wise approach.

Methods

Seventeen patients with molecular diagnose of SCA3 and 17 matched healthy controls participated in this study. Magnetic resonance imaging (MRI) brain images were acquired and voxel-based morphometry was used to obtain the grey matter volume of each participant. Ataxia severity in the patient group was evaluated using the scale for the assessment and rating of ataxia (SARA).

Results

Group comparison revealed significant atrophy in SCA3 including bilateral cerebellum, vermis, brainstem, and occipital cortex. Significant negative correlations between gray matter volume and SARA scores were found in the cerebellum and the cingulate gyrus.

Conclusions

These findings highlight the specific contribution of the cerebellum and the cingulate cortex to the ataxia deficits among the other regions showing neurodegeneration in SCA3 patients.

Keywords

AtrophyMachado-JosephSARASpinocerebellar ataxiaVBM

Background

Spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) is an autosomal dominant inherited neurodegenerative disorder with a wide range of clinical manifestations [1]. SCA3/MJD is caused by an unstable CAG trinucleotide repeat expansion within the coding region of a gene located on chromosome 14q32.1 [2]. The predominant symptoms are progressive ataxia, ophthalmoplegia, spastic gait and peripheral neuropathy [13]. Previous morphometric SCA3/MJD MRI analysis revealed significant atrophy of the cerebellar hemispheres, cerebellar vermis, pontine base, middle cerebellar peduncle, medulla oblongata, cervical spinal cord and enlargement of the fourth ventricle [39]. However, only few studies have analyzed the possible relationship between brain degeneration and the ataxia severity in this disease [79]. In those reports, researchers have used manually predefined anatomical landmarks to segment and calculate the total volume of different anatomical structures [7], automated region segmentation to calculate cortical thickness and volume [8] or atlas predefined regions to later group them into one single region [9]. Those analyses led to broad correlations between volume of the cerebellum, brainstem and other cortical regions and the ataxia impairment.

However, a more accurate mapping of the disease-related degeneration and its association with the symptoms is key for the development of possible treatments/therapies for this specific type of patients. Here, we assessed the ataxia severity and gray matter degeneration in a cohort of SCA3/MJD patients by using the scale for the assessment and rating of ataxia (SARA) and whole brain voxel based-morphometry (VBM) to find voxel-wise associations between brain atrophy and motor impairment.

Methods

Participants

The patient group consisted of seventeen patients with a molecular diagnosis of SCA3/MJD (10 female; right-handed; mean age/SD, 40.1/11.9 years, for more detailed information look at Table 1). Motor impairment was measured using SARA [10], which has eight items, including tests of gait, stance, sitting, and speech, as well as a finger-chase test, finger-nose test, fast alternating movements, and heel-shin test. The control group consisted of 17 healthy volunteers that were age and gender matched. All participants gave written, informed consent before entering the study. The procedures carried out were in accordance with the ethical standards of the committees on human experimentation of the Universidad Nacional Autonoma de Mexico.
Table 1

Demographics of the patient group

ID

Gender

Age

Age at onset

SARA

P01

F

49

39

26

P02

M

58

47

19.5

P03

F

45

25

26

P04

M

37

32

12.5

P05

F

35

33

6.5

P06

F

23

20

6

P07

F

42

35

12

P08

F

24

20

9

P09

F

18

16

2.5

P10

F

45

39

8

P11

M

43

40

14.5

P12

M

34

29

18

P13

M

59

49

19.5

P14

M

33

28

9.5

P15

F

40

30

20

P16

M

56

46

14.5

P17

F

46

41

1.5

Image acquisition

All images were acquired using a 32-channel quadrature head coil in a 3.0-T Achieva MRI scanner (Phillips Medical Systems, Eindhoven, The Netherlands). Foam-rubber cushion was used for fixing the head of the subject in place, so as to minimize any head movements. The high-resolution anatomical acquisition consisted of a 3-D T1 Fast Field-Echo sequence, with TR/TE of 8/3.7 ms, FOV of 256 × 256 mm, flip angle 25° and an acquisition and reconstruction matrix of 256 × 256, resulting in an isometric resolution of 1 × 1 × 1 mm.

Voxel-based morphometry

Gray matter volume (GMV) measurements were performed using voxel based morphometry (VBM) as implemented on FSL (FMRIB, Oxford, UK) following the standard procedure as previously reported [11]. Using the FSL randomise tool, a two-sample t test was performed between the SCA3 group and controls. Significance was defined as p < 0.05 after correcting for multiple comparisons using the randomized permutation method (TFCE). For the SCA3 group, whole-brain correlation maps were created by calculating the Pearson’s partial correlation between the GMV and SARA scores including age in the analysis. Partial correlation maps were corrected for multiple comparisons by using false discovery rate (FDR) with a p value < 0.05.

Results

VBM analysis revealed gray matter atrophy in SCA3 patients compared to the control group (Fig. 1a) involving bilateral cerebellum, vermis, brainstem and the occipital cortex (Table 2). Four significant negative correlations were found between GMV and SARA scores in the SCA3 group (Fig. 1b) in regions of the cerebellum and the cingulate gyrus (Table 3).
Fig. 1

Brain regions showing gray matter atrophy and SARA-GMV correlation. a Significant gray matter atrophy in patients compared with controls; b significant partial correlations between patients’ GMV and SARA

Table 2

Brain regions showing significant gray matter degeneration in SCA3/MJD patients

Anatomical region

X

Y

Z

Cluster

t

Left posterior cerebellum Crus II

−26

−86

−36

2633

7.73

Right posterior cerebellum Crus II

20

−88

−32

1419

7.31

Right brainstem

4

−14

−22

224

6.59

Vermis IX

−2

−54

−34

114

6.45

Pons

2

−14

−24

219

6.19

Right anterior cerebellum lobule V

12

−58

−20

160

5.1

Left lingual gyrus BA17

−12

−100

−4

132

4.42

Left anterior cerebellum lobule I-IV

−8

−46

−22

213

3.59

Coordinates in MNI space in mm. BA = Brodmann Area

Table 3

Brain regions showing significant correlation between GMV and SARA

Anatomical region

X

Y

Z

Cluster

PC

Right cerebellum declive lobule VI

32

−64

−14

191

−0.825

Left cerebellum culmen lobule VI

−28

−50

−18

180

−0.816

Left cerebellum tonsil lobule IX

−8

−58

−38

155

−0.792

Right paracentral lobule BA6

4

−8

48

132

−0.779

Coordinates in MNI space in mm. BA = Brodmann Area, PC = partial correlation

Discussion

In this study, we analyzed the relationship between gray matter loss and SARA scores in SCA3 patients. As expected, significant negative correlations between SARA scores and GMV were found in the cerebellum, but also in the cingulate cortex.

Previous reports have shown the close relationship between the extent of the brain atrophy, predominately in the cerebellum, and a variety of symptoms in different SCA subtypes [79, 12, 13]. Accordingly, our analysis showed a significant negative correlation between GMV and the SARA score in the bilateral lobule VI, extending to lobule V, which are involved in sensorimotor processing as suggested by deficits in stroke patients [14, 15]. Lobule IX, which its GMV also correlated with SARA, is not only considered essential for visual guidance of movement [14], but its damage has been related to gait and balance impairment [15].

The only extra-cerebellar region where the GMV correlated with SARA score was the dorsal anterior cingulate, known to be critically involved in motor functions [16]. A previous report showed a significant degeneration in SCA3 in this area [6], however, our analysis also showed a negative correlation between GMV and the ataxia score, corroborating the functional relevance of this deterioration as shown by patients with lesions in this area, whom often show deficits in spontaneous initiation of movement and speech, as well as inability to suppress externally triggered motor subroutines [16].

Conclusions

In Conclusion, we report specific key areas where the GMV shows a close relationship with the ataxia impairment in SCA3. These findings add to previous reports [7, 9], while providing a more accurate localization of the SCA3/MJD ataxia-related areas.

Abbreviations

FDR: 

False Discovery Rate

GMV: 

Gray Matter Volume

MDJ: 

Machado-Joseph Disease

MRI: 

Magnetic Resonance Imaging

SARA: 

Scale for Assessing and Rating of Ataxia

SCA3: 

Spinocerebellar Ataxia 3

VBM: 

voxel-Based Morphometry

Declarations

Acknowledgements

We want to thank all the patients and their caregivers for their participation in this study.

Funding

This study was founded in part by CONACYT 220871, PAPIIT IN214716 to JFR, and CONACYT 222009 to ACR.

Availability of data and materials

Please contact the corresponding author for data requests.

Authors’ contributions

CRHC designed the study Analyze the data and produced the first draft of the manuscript. JFR designed the study and provided expertise in brain imaging. RD and ACR were in charge of logistics as well as supervised and acquired data from patients. All authors read and approved the final manuscript.

Competing interest

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

All participants gave written, informed consent before entering the study. The procedures carried out were in accordance with the ethical standards of the committees on human experimentation of the Universidad Nacional Autonoma de Mexico.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
CONACYT – Instituto de Neuroetología - Universidad Veracruzana
(2)
Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autonoma de México, UNAM
(3)
Unidad Periférica de Neurociencias, Facultad de Medicina, Universidad Nacional Autónoma de México, en el Instituto Nacional de Neurología y Neurocirugía “Manuel Velasco Suárez”

References

  1. Matilla T, McCall A, Subramony SH, Zoghbi HY. Molecular and clinical correlations in spinocerebellar ataxia type 3 and Machado‐Joseph disease. Ann Neurol. 1995;38(1):68–72.View ArticlePubMedGoogle Scholar
  2. Kawaguchi Y, Okamoto T, Taniwakiz M, Aizawa M. CAG expansions in a novel gene for Machado-Joseph disease at. Nat Genet. 1994;8(3):221–8.View ArticlePubMedGoogle Scholar
  3. Bürk K, Abele M, Fetter M, Dichgans J, Skalej M, Laccone F, Didierjean O, Brice A, Klockgether T. Autosomal dominant cerebellar ataxia type I clinical features and MRI in families with SCA1, SCA2 and SCA3. Brain. 1996;119(5):1497–505.View ArticlePubMedGoogle Scholar
  4. Lukas C, Schöls L, Bellenberg B, Rüb U, Przuntek H, Schmid G, Köster O, Suchan B. Dissociation of grey and white matter reduction in spinocerebellar ataxia type 3 and 6: a voxel-based morphometry study. Neurosci Lett. 2006;408(3):230–5.View ArticlePubMedGoogle Scholar
  5. Goel G, Pal PK, Ravishankar S, Venkatasubramanian G, Jayakumar PN, Krishna N, Purushottam M, Saini J, Faruq M, Mukherji M, Jain S. Gray matter volume deficits in spinocerebellar ataxia: an optimized voxel based morphometric study. Parkinsonism Relat Disord. 2011;17(7):521–7.View ArticlePubMedGoogle Scholar
  6. Guimarães RP, D'Abreu A, Yasuda CL, França MC, Silva BH, Cappabianco FA, Bergo FP, Lopes‐Cendes IT, Cendes F. A multimodal evaluation of microstructural white matter damage in spinocerebellar ataxia type 3. Mov Disord. 2013;28(8):1125–32.View ArticlePubMedGoogle Scholar
  7. Schulz JB, Borkert J, Wolf S, Schmitz-Hübsch T, Rakowicz M, Mariotti C, Schoels L, Timmann D, van de Warrenburg B, Dürr A, Pandolfo M. Visualization, quantification and correlation of brain atrophy with clinical symptoms in spinocerebellar ataxia types 1, 3 and 6. Neuroimage. 2010;49(1):158–68.View ArticlePubMedGoogle Scholar
  8. Rezende TJ, D'abreu A, Guimaraes RP, Lopes TM, Lopes‐Cendes I, Cendes F, Castellano G, França MC. Cerebral cortex involvement in Machado − Joseph disease. Eur J Neurol. 2015;22(2):277–e24.View ArticlePubMedGoogle Scholar
  9. D’Abreu A, Franca Jr MC, Yasuda CL, Campos BA, Lopes‐Cendes I, Cendes F. Neocortical Atrophy in Machado‐Joseph Disease: A Longitudinal Neuroimaging Study. J Neuroimaging. 2012;22(3):285–91.View ArticlePubMedGoogle Scholar
  10. Schmitz-Hübsch T, Du Montcel ST, Baliko L, Berciano J, Boesch S, Depondt C, Giunti P, Globas C, Infante J, Kang JS, Kremer B. Scale for the assessment and rating of ataxia Development of a new clinical scale. Neurology. 2006;66(11):1717–20.View ArticlePubMedGoogle Scholar
  11. Ashburner J, Friston KJ. Voxel-based morphometry—the methods. Neuroimage. 2000;11(6):805–21.View ArticlePubMedGoogle Scholar
  12. Hernandez-Castillo CR, Galvez V, Diaz R, Fernandez-Ruiz J. Specific cerebellar and cortical degeneration correlates with ataxia severity in spinocerebellar ataxia type 7. Brain Imaging Behav. 2016;10(1):252–7.View ArticlePubMedGoogle Scholar
  13. Reetz K, Lencer R, Hagenah JM, Gaser C, Tadic V, Walter U, Wolters A, Steinlechner S, Zühlke C, Brockmann K, Klein C. Structural changes associated with progression of motor deficits in spinocerebellar ataxia 17. The Cerebellum. 2010;9(2):210–7.View ArticlePubMedGoogle Scholar
  14. Stoodley CJ, Schmahmann JD. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing. Cortex. 2010;46(7):831–44.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Ilg W, Giese MA, Gizewski ER, Schoch B, Timmann D. The influence of focal cerebellar lesions on the control and adaptation of gait. Brain. 2008;131(11):2913–27.View ArticlePubMedGoogle Scholar
  16. Paus TS. Primate anterior cingulate cortex: where motor control, drive and cognition interface. Nat Rev Neurosci. 2001;2(6):417–24.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2017

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