journal article Open Access Jan 04, 2022

Neurodegenerative and functional signatures of the cerebellar cortex in m.3243A > G patients

View at Publisher Save 10.1093/braincomms/fcac024
Abstract
Abstract
Mutations of the mitochondrial DNA are an important cause of inherited diseases that can severely affect the tissue’s homeostasis and integrity. The m.3243A > G mutation is the most commonly observed across mitochondrial disorders and is linked to multisystemic complications, including cognitive deficits. In line with in vitro experiments demonstrating the m.3243A > G’s negative impact on neuronal energy production and integrity, m.3243A > G patients show cerebral grey matter tissue changes. However, its impact on the most neuron dense, and therefore energy-consuming brain structure—the cerebellum—remains elusive. In this work, we used high-resolution structural and functional data acquired using 7 T MRI to characterize the neurodegenerative and functional signatures of the cerebellar cortex in m.3243A > G patients. Our results reveal altered tissue integrity within distinct clusters across the cerebellar cortex, apparent by their significantly reduced volume and longitudinal relaxation rate compared with healthy controls, indicating macroscopic atrophy and microstructural pathology. Spatial characterization reveals that these changes occur especially in regions related to the frontoparietal brain network that is involved in information processing and selective attention. In addition, based on resting-state functional MRI data, these clusters exhibit reduced functional connectivity to frontal and parietal cortical regions, especially in patients characterized by (i) a severe disease phenotype and (ii) reduced information-processing speed and attention control. Combined with our previous work, these results provide insight into the neuropathological changes and a solid base to guide longitudinal studies aimed to track disease progression.
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References
100
[1]
Taylor "Mitochondrial DNA mutations in human disease" Nat Rev Genet (2005) 10.1038/nrg1606
[2]
Goto "A mutation in the tRNA(Leu)(UUR) gene associated with the MELAS subgroup of mitochondrial encephalomyopathies" Nature (1990) 10.1038/348651a0
[3]
Manwaring "Population prevalence of the MELAS A3243G mutation" Mitochondrion (2007) 10.1016/j.mito.2006.12.004
[4]
Nesbitt "The UK MRC mitochondrial disease patient cohort study: Clinical phenotypes associated with the m.3243A" J Neurol Neurosurg Psychiatry (2013) 10.1136/jnnp-2012-303528
[5]
de Laat "Clinical features and heteroplasmy in blood, urine and saliva in 34 Dutch families carrying the m.3243A" J Inherit Metab Dis (2012) 10.1007/s10545-012-9465-2
[6]
Hirano "Melas: An original case and clinical criteria for diagnosis" Neuromuscul Disord (1992) 10.1016/0960-8966(92)90045-8
[7]
de Laat "Six-year prospective follow-up study in 151 carriers of the mitochondrial DNA 3243 A>G variant" J Med Genet (2021) 10.1136/jmedgenet-2019-106800
[8]
Mutation in mitochondrial tRNALeu(UUR) gene in a large pedigree with maternally transmitted type II diabetes mellitus and deafness

J.M.W. van den Ouweland, H.H.P.J. Lemkes, W. Ruitenbeek et al.

Nature Genetics 1992 10.1038/ng0892-368
[9]
Lindroos "Cerebral oxygen and glucose metabolism in patients with mitochondrial m.3243A > G mutation" Brain (2009) 10.1093/brain/awp259
[10]
Tschampa "Neuroimaging characteristics in mitochondrial encephalopathies associated with the m.3243A > G MTTL1 mutation" J Neurol (2013) 10.1007/s00415-012-6763-4
[11]
Tsujikawa "Distinctive distribution of brain volume reductions in MELAS and mitochondrial DNA A3243G mutation carriers: A voxel-based morphometric study" Mitochondrion (2016) 10.1016/j.mito.2016.08.011
[12]
Rodan "Cerebral hyperperfusion and decreased cerebrovascular reactivity correlate with neurologic disease severity in MELAS" Mitochondrion (2015) 10.1016/j.mito.2015.03.002
[13]
Kraya "Cognitive impairment, clinical severity and MRI changes in MELAS syndrome" Mitochondrion (2019) 10.1016/j.mito.2017.12.012
[14]
Bhatia "Acute cortical lesions in MELAS syndrome: Anatomic distribution, symmetry, and evolution" Am J Neuroradiol (2020) 10.3174/ajnr.a6325
[15]
Van den Ameele "[11C]PK11195-PET brain imaging of the mitochondrial translocator protein in mitochondrial disease" Neurology 10.1212/wnl.0000000000012033
[16]
Haast "Anatomic & metabolic brain markers of the m.3243A > G mutation: A multi-parametric 7 T MRI study" Neuroimage Clin (2018) 10.1016/j.nicl.2018.01.017
[17]
Lax "Cerebellar ataxia in patients with mitochondrial DNA disease: A molecular clinicopathological study" J Neuropathol Exp Neurol (2012) 10.1097/nen.0b013e318244477d
[18]
Picard "Mitochondria impact brain function and cognition" Proc Natl Acad Sci USA (2014) 10.1073/pnas.1321881111
[19]
Sereno "The human cerebellum has almost 80% of the surface area of the neocortex" Proc Natl Acad Sci USA (2020) 10.1073/pnas.2002896117
[20]
Consensus Paper: Roles of the Cerebellum in Motor Control—The Diversity of Ideas on Cerebellar Involvement in Movement

Mario Manto, James M. Bower, Adriana Bastos Conforto et al.

The Cerebellum 2012 10.1007/s12311-011-0331-9
[21]
King "Functional boundaries in the human cerebellum revealed by a multi-domain task battery" Nat Neurosci (2019) 10.1038/s41593-019-0436-x
[22]
Buckner "The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging" Neuron (2013) 10.1016/j.neuron.2013.10.044
[23]
Ramnani "The primate cortico-cerebellar system: Anatomy and function" Nat Rev Neurosci (2006) 10.1038/nrn1953
[24]
Cerebellum and Nonmotor Function

Peter L. Strick, Richard P. Dum, Julie A. Fiez

Annual Review of Neuroscience 2009 10.1146/annurev.neuro.31.060407.125606
[25]
Reeber "New roles for the cerebellum in health and disease" Front Syst Neurosci (2013) 10.3389/fnsys.2013.00083
[26]
Schaefer "Mitochondrial disease in adults: A scale to monitor progression and treatment" Neurology (2006) 10.1212/01.wnl.0000219759.72195.41
[27]
Grady "mtDNA heteroplasmy level and copy number indicate disease burden in m.3243A > G mitochondrial disease" EMBO Mol Med (2018) 10.15252/emmm.201708262
[28]
van der Elst "The letter digit substitution test: Normative data for 1,858 healthy participants aged 24–81 from the maastricht aging study (MAAS): Influence of age, education, and sex" J Clin Exp Neuropsychol (2006) 10.1080/13803390591004428
[29]
Van der Elst "The Stroop color-word test: Influence of age, sex, and education; and normative data for a large sample across the adult age range" Assessment (2006) 10.1177/1073191105283427
[30]
Elst "Rey’s verbal learning test: Normative data for 1855 healthy participants aged 24–81 years and the influence of age, sex, education, and mode of presentation" J Int Neuropsychol Soc (2005) 10.1017/s1355617705050344
[31]
MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field

José P. Marques, Tobias Kober, Gunnar Krueger et al.

NeuroImage 2010 10.1016/j.neuroimage.2009.10.002
[32]
Eggenschwiler "SA2RAGE: A new sequence for fast B1+ -mapping" Magn Reson Med (2012) 10.1002/mrm.23145
[33]
Myelin and iron concentration in the human brain: A quantitative study of MRI contrast

Carsten Stüber, Markus Morawski, Andreas Schäfer et al.

NeuroImage 2014 10.1016/j.neuroimage.2014.02.026
[34]
Teeuwisse "Quantitative assessment of the effects of high-permittivity pads in 7 Tesla MRI of the brain" Magn Reson Med (2012) 10.1002/mrm.23108
[35]
Bazin "A computational framework for ultra-high resolution cortical segmentation at 7 Tesla" Neuroimage (2014) 10.1016/j.neuroimage.2013.03.077
[36]
Marques "New developments and applications of the MP2RAGE sequence—focusing the contrast and high spatial resolution R1 mapping" PLoS One (2013) 10.1371/journal.pone.0069294
[37]
Haast "The impact of B1+ correction on MP2RAGE cortical T1 and apparent cortical thickness at 7T" Hum Brain Mapp (2018) 10.1002/hbm.24011
[38]
FreeSurfer

Bruce Fischl

NeuroImage 2012 10.1016/j.neuroimage.2012.01.021
[39]
The minimal preprocessing pipelines for the Human Connectome Project

Matthew F. Glasser, Stamatios N. Sotiropoulos, J. Anthony Wilson et al.

NeuroImage 2013 10.1016/j.neuroimage.2013.04.127
[40]
A spatially unbiased atlas template of the human cerebellum

Jörn Diedrichsen

NeuroImage 2006 10.1016/j.neuroimage.2006.05.056
[41]
Ashburner "Voxel-based morphometry—the methods" Neuroimage. (2000) 10.1006/nimg.2000.0582
[42]
Romero "CERES: A new cerebellum lobule segmentation method" Neuroimage (2017) 10.1016/j.neuroimage.2016.11.003
[43]
User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability

Paul A. Yushkevich, Joseph Piven, Heather Cody Hazlett et al.

NeuroImage 2006 10.1016/j.neuroimage.2006.01.015
[44]
A fast diffeomorphic image registration algorithm

John Ashburner

NeuroImage 2007 10.1016/j.neuroimage.2007.07.007
[45]
A probabilistic MR atlas of the human cerebellum

Jörn Diedrichsen, Joshua H. Balsters, Jonathan Flavell et al.

NeuroImage 2009 10.1016/j.neuroimage.2009.01.045
[46]
Good "A voxel-based morphometric study of ageing in 465 normal adult human brains" Neuroimage. (2001) 10.1006/nimg.2001.0786
[47]
AFNI: Software for Analysis and Visualization of Functional Magnetic Resonance Neuroimages

Robert W. Cox

Computers and Biomedical Research 1996 10.1006/cbmr.1996.0014
[48]
Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images

Mark Jenkinson, Peter Bannister, Michael Brady et al.

NeuroImage 2002 10.1006/nimg.2002.1132
[49]
How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging

Jesper L.R. Andersson, Stefan Skare, John Ashburner

NeuroImage 2003 10.1016/s1053-8119(03)00336-7
[50]
Accurate and robust brain image alignment using boundary-based registration

Douglas N. Greve, Bruce Fischl

NeuroImage 2009 10.1016/j.neuroimage.2009.06.060

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Published
Jan 04, 2022
Vol/Issue
4(1)
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Funding
The Netherlands Organization for Scientific Research Award: 452-11-002
Maastricht University, Technology Foundation STW
Institute for Basic Science, Suwon, Republic of Korea Award: NeMo
Cite This Article
Roy A. M. Haast, Irenaeus F. M. De Coo, Dimo Ivanov, et al. (2022). Neurodegenerative and functional signatures of the cerebellar cortex in m.3243A > G patients. Brain Communications, 4(1). https://doi.org/10.1093/braincomms/fcac024