Abstract
Objective: Aspartylglucosaminuria is an inherited, lysosomal storage disease causing progressive decline in cognitive and motor functions. The aim of this study was to evaluate volumes of subcortical gray matter structures and white matter microstructure in aspartylglucosaminuria in adolescence in a longitudinal study for the first time.
Methods: A boy with aspartylglucosaminuria and his healthy twin brother were imaged twice with a 3.0 T MRI scanner at the ages of 10 and 15 years. Subcortical gray matter structure volumes were measured using an atlas-based automatic method, and diffusion tensor imaging was used to evaluate the white matter microstructure of the corpus callosum and the thalamocortical pulvinar tracts.
Results: The subcortical gray matter structures were smaller at onset and diminished at follow-up in the affected twin, with the exception of the amygdala which was larger and remained the size. The largest difference in volume between the twins was found in the thalami. The total gray and white matter volumes decreased in the affected twin. In diffusion tensor imaging analysis, the fractional anisotropy was decreased at onset in the affected twin compared to the healthy brother in the evaluated tracts. The axial, radial and mean diffusivity values were increased in the affected twin. The difference between the twins increased slightly at follow-up.
Interpretation: The findings suggest that volumetric measurements and diffusion tensor imaging based microstructural analysis may be useful modalities for monitoring disease progression and response to emerging treatment in aspartylglucosaminuria, but further studies with more subjects are necessary to confirm the results.
The original version of this chapter was revised: The Acknowledgement and Funding information was included. The erratum to this chapter is available at DOI 10.1007/8904_2017_18
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References
Arvio P, Arvio M (2002) Progressive nature of aspartylglucosaminuria. Acta Paediatr 91:255–257
Autti T, Raininko R, Haltia M et al (1997) Aspartylglucosaminuria: radiologic course of the disease with histopathologic correlation. J Child Neurol 12:369–375
Autti T, Lonnqvist T, Joensuu R (2008) Bilateral pulvinar signal intensity decrease on T2-weighted images in patients with aspartylglucosaminuria. Acta Radiol 49:687–692
Banning A, Gulec C, Rouvinen J et al (2016) Identification of small molecule compounds for farmacological chaperone therapy of aspartylglucosaminuria. Nat Sci Rep 6:37583
Barnea-Goraly N, Menon V, Eckert M et al (2005) White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cereb Cortex 15:1848–1854
Basser PJ, Pierpaoli C (1996) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 111:209–219
Bava S, Theilmann RJ, Sach M et al (2010) Developmental changes in cerebral white matter microstructure in a disorder of lysosomal storage. Cortex 46:206–216
Chiang MC, McMahon KL, de Zubicaray GI et al (2011) Genetics of white matter development: a DTI study of 705 twins and their siblings aged 12 to 29. Neuroimage 54:2308–2317
Davies EH, Seunarine KK, Banks T, Clark CA, Vellodi A (2011) Brain white matter abnormalities in paediatric Gaucher type I and type III using diffusion tensor imaging. J Inherit Metab Dis 34:549–553
Dunder U, Kaartinen V, Valtonen P et al (2000) Enzyme replacement therapy in a mouse model of aspartylglycosaminuria. FASEB J 14:361–367
Escolar ML, Poe MD, Smith JK et al (2009) Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile Krabbe disease. AJNR Am J Neuroradiol 30:1017–1021
Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30:1323–1341
Fischl B, Salat DH, Busa E et al (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33:341–355
Giedd JN (2004) Structural magnetic resonance imaging of the adolescent brain. Ann N Y Acad Sci 1021:77–85
Giedd JN, Blumenthal J, Jeffries NO et al (1999) Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci 2:861–863
Giedd JN, Schmitt JE, Neale MC (2007) Structural brain magnetic resonance imaging of pediatric twins. Hum Brain Mapp 28:474–481
Gogtay N, Giedd JN, Lusk L et al (2004) Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci U S A 101:8174–8179
Gonzalez-Gomez I, Mononen I, Heisterkamp N et al (1998) Progressive neurodegeneration in aspartylglycosaminuria mice. Am J Pathol 153:1293–1300
Halle M, Talos I, Jakab M et al (2015) Multi-modality MRI-based atlas of the brain. SPL, Boston
Haltia M, Palo J, Autio S (1975) Aspartylclucosaminuria: a generalized storage disease. Morphological and histochemical studies. Acta Neuropathol 31:243–255
Huang H, Zhang J, Jiang H et al (2005) DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus callosum. Neuroimage 26:195–205
Jalanko A, Tenhunen K, McKinney C et al (1998) Mice with an aspartylglucosaminuria mutation similar to humans replicate the pathophysiology in patients. Hum Mol Genet 7:265–272
Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM (2012) FSL. Neuroimage 62:782–790
Kochunov P, Jahanshad N, Marcus D et al (2015) Heritability of fractional anisotropy in human white matter: a comparison of human connectome project and ENIGMA-DTI data. Neuroimage 111:300–311
Lebel C, Walker L, Leemans A, Phillips L, Beaulieu C (2008) Microstructural maturation of the human brain from childhood to adulthood. Neuroimage 40:1044–1055
Mukherjee P, Chung SW, Berman JI, Hess CP, Henry RG (2008) Diffusion tensor MR imaging and fiber tractography: technical considerations. AJNR Am J Neuroradiol 29:843–852
Paavilainen T, Lepomaki V, Saunavaara J et al (2013) Diffusion tensor imaging and brain volumetry in Fabry disease patients. Neuroradiology 55:551–558
Paus T (2010) Growth of white matter in the adolescent brain: myelin or axon? Brain Cogn 72:26–35
Saarela J, Laine M, Oinonen C et al (2001) Molecular pathogenesis of a disease: structural consequences of aspartylglucosaminuria mutations. Hum Mol Genet 10:983–995
Schiffmann R, Mayfield J, Swift C, Nestrasil I (2014) Quantitative neuroimaging in mucolipidosis type IV. Mol Genet Metab 111:147–151
Sowell ER, Thompson PM, Toga AW (2004) Mapping changes in the human cortex throughout the span of life. Neuroscientist 10:372–392
Tenhunen K, Uusitalo A, Autti T et al (1998) Monitoring the CNS pathology in aspartylglucosaminuria mice. J Neuropathol Exp Neurol 57:1154–1163
Thompson P, Cannon TD, Toga AW (2002) Mapping genetic influences on human brain structure. Ann Med 34:523–536
Tokola AM, Aberg LE, Autti TH (2015) Brain MRI findings in aspartylglucosaminuria. J Neuroradiol 42:345–357
Virta S, Rapola J, Jalanko A, Laine M (2006) Use of nonviral promoters in adenovirus-mediated gene therapy: reduction of lysosomal storage in the aspartylglucosaminuria mouse. J Gene Med 8:699–706
Walterfang M, Fahey M, Desmond P et al (2010) White and gray matter alterations in adults with Niemann-pick disease type C: a cross-sectional study. Neurology 75:49–56
Wierenga L, Langen M, Ambrosino S, van Dijk S, Oranje B, Durston S (2014) Typical development of basal ganglia, hippocampus, amygdala and cerebellum from age 7 to 24. Neuroimage 96:67–72
Zhang Y, Brady M, Smith S (2001) Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 20:45–57
Acknowledgements
The authors wish to thank the twins and their family for participating in the study and PhD Jaana Hiltunen for her assistance.
Funding
This study was supported by Finnish Brain Foundation, Arvo and Lea Ylppö Foundation, Yrjö Jahnsson Foundation and Helsinki University Hospital Research Funds, Department of Radiology. No financial or other relationships that might lead to perceived conflict of interest exist.
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Communicated by: Nicole Wolf, M.D., Ph.D.
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Supplementary Fig. 1
The masks used for the tractograpy. The examples shown are from the healthy twin brother at the age of 10. The regions of interest (ROIs) are superimposed on T1-weighted images. The frontal projections of corpus callosum were divided into three parts which were analyzed separately. First, the corpus callosum was delineated on the midsagittal plane and used as a seed ROI (first row, picture on the left). For the anterior projections, an inclusion ROI was drawn on a coronal plane anterior to the cingulate gyrus covering the frontal lobes in total (first row, two pictures from the right). For the superior projections, an inclusion ROI was drawn on the most inferior axial slice in which the central sulcus could be clearly identified by its omega shape, dx and sin separately (second row, two pictures from the left). For the lateral projections, an inclusion ROI was drawn on the sagittal plane lateral to corona radiata, dx and sin separately (second row, picture on the right). For the pulvinar thalamocortical tracts, the pulvinar area was used as a seed ROI and it was drawn on one axial slice above the level of the anterior commissura, dx and sin separately (third row, two pictures from the left). The inclusion ROIs for the corpus callosum frontal projections served as exclusion ROIs, and additional exclusion ROIs were drawn in the brainstem (third row, picture on the right) and the midsagittal line (TIFF 3719 kb)
Supplementary Table 1
Results for the quantitative diffusion tensor imaging of the pulvinar tratcs (DOCX 17 kb)
Supplementary Table 2
Results for the quantitative diffusion tensor imaging of the corpus callosum frontal projections (DOCX 17 kb)
Author Contributions
Author Contributions
Conception and design of the study (TA, AT, NB, AH, ES), acquisition and analysis of data (AT, AH, NB, ES, LÅ), drafting the manuscript or figures (AT, NB, ES, AH, LÅ).
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Anna, T., Nina, B., Antti, H., Eero, S., Laura, Å., Taina, A. (2017). White Matter Microstructure and Subcortical Gray Matter Structure Volumes in Aspartylglucosaminuria; a 5-Year Follow-up Brain MRI Study of an Adolescent with Aspartylglucosaminuria and His Healthy Twin Brother. In: Morava, E., Baumgartner, M., Patterson, M., Rahman, S., Zschocke, J., Peters, V. (eds) JIMD Reports, Volume 35. JIMD Reports, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/8904_2016_36
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DOI: https://doi.org/10.1007/8904_2016_36
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