Muscle diffusion MRI reveals autophagic buildup in a mouse model for Pompe disease.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
20 Dec 2023
20 Dec 2023
Historique:
received:
29
08
2023
accepted:
14
12
2023
medline:
22
12
2023
pubmed:
22
12
2023
entrez:
21
12
2023
Statut:
epublish
Résumé
Quantitative muscle MRI is increasingly important in the non-invasive evaluation of neuromuscular disorders and their progression. Underlying histopathotological alterations, leading to changes in qMRI parameters are incompletely unraveled. Early microstructural differences of unknown origin reflected by Diffusion MRI in non-fat infiltrated muscles were detected in Pompe patients. This study employed a longitudinal approach with a Pompe disease mouse model to investigate the histopathological basis of these changes. Monthly scans of Pompe (Gaa
Identifiants
pubmed: 38129558
doi: 10.1038/s41598-023-49971-9
pii: 10.1038/s41598-023-49971-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
22822Subventions
Organisme : Deutsche Gesellschaft für Muskelkranke
ID : GU1/2
Organisme : Medizinische Fakultät, Ruhr-Universität Bochum
ID : FoRUM F960R-2020
Organisme : NWO-AES
ID : 18929
Organisme : Deutsche Forschungsgemeinschaft
ID : 122679504 - TPA5
Informations de copyright
© 2023. The Author(s).
Références
Carlier, P. G. et al. Skeletal muscle quantitative nuclear magnetic resonance imaging follow-up of adult Pompe patients. J. Inherit. Metab. Dis. 38, 565–572. https://doi.org/10.1007/s10545-015-9825-9 (2015).
doi: 10.1007/s10545-015-9825-9
pubmed: 25749708
pmcid: 4432102
van der Ploeg, A. et al. Prospective exploratory muscle biopsy, imaging, and functional assessment in patients with late-onset Pompe disease treated with alglucosidase alfa: The EMBASSY Study. Mol. Genet. Metab. 119, 115–123. https://doi.org/10.1016/j.ymgme.2016.05.013 (2016).
doi: 10.1016/j.ymgme.2016.05.013
pubmed: 27473031
Melkus, G. et al. Quantitative vs qualitative muscle MRI: Imaging biomarker in patients with Oculopharyngeal Muscular Dystrophy (OPMD). Neuromusc. Disord. 33, 24–31. https://doi.org/10.1016/J.NMD.2022.09.010 (2023).
doi: 10.1016/J.NMD.2022.09.010
pubmed: 36462961
Kim, H. K. et al. T2 mapping in duchenne muscular dystrophy: Distribution of disease activity and correlation with clinical assessments. Radiology 255, 899–908. https://doi.org/10.1148/RADIOL.10091547 (2010).
doi: 10.1148/RADIOL.10091547
pubmed: 20501727
Rehmann, R. et al. Muscle Diffusion tensor imaging reveals changes in non-fat infiltrated muscles in late-onset Pompe disease. Musc. Nerve 62, 541–549. https://doi.org/10.1002/mus.27021 (2020).
doi: 10.1002/mus.27021
Deniz, G. et al. Fatty degeneration and atrophy of the rotator cuff muscles after arthroscopic repair: Does it improve, halt or deteriorate?. Arch. Orthop. Trauma Surg. 134, 985–990. https://doi.org/10.1007/s00402-014-2009-5 (2014).
doi: 10.1007/s00402-014-2009-5
pubmed: 24845686
Butt, U. et al. Muscle regeneration following repair of the rotator cuff. Bone Jt J. 98B, 1389–1394. https://doi.org/10.1302/0301-620X.98B10.37231 (2016).
doi: 10.1302/0301-620X.98B10.37231
Lim, J. A., Li, L. & Raben, N. Pompe disease: From pathophysiology to therapy and back again. Front. Aging Neurosci. 6, 1–14. https://doi.org/10.3389/fnagi.2014.00177 (2014).
doi: 10.3389/fnagi.2014.00177
Schüller, A. et al. Toward deconstructing the phenotype of late-onset pompe disease cohorts found in the literature. Am. J. Med. Genet. Part C 9, 80–88. https://doi.org/10.1002/ajmc.31322 (2012).
doi: 10.1002/ajmc.31322
Kulessa, M. et al. An integrative correlation of myopathology, phenotype and genotype in late onset Pompe disease. Neuropathol. Appl. Neurobiol. 46, 359–374. https://doi.org/10.1111/nan.12580 (2020).
doi: 10.1111/nan.12580
pubmed: 31545528
Raben, N. et al. Suppression of autophagy permits successful enzyme replacement therapy in a lysosomal storage disorder - Murine Pompe disease. Autophagy 6, 1078–1089. https://doi.org/10.4161/auto.6.8.13378 (2010).
doi: 10.4161/auto.6.8.13378
pubmed: 20861693
pmcid: 3039718
Bembi, B. et al. Diagnosis of glycogenosis type II. Neurology 71, S4–S11. https://doi.org/10.1212/WNL.0b013e31818da91e (2008).
doi: 10.1212/WNL.0b013e31818da91e
pubmed: 19047572
Schlaffke, L. et al. Multicenter evaluation of stability and reproducibility of quantitative MRI measures in healthy calf muscles. NMR Biomed. 32, 1–14. https://doi.org/10.1002/nbm.4119 (2019).
doi: 10.1002/nbm.4119
Enax-Krumova, E. et al. Quantitative muscle MRI depicts microstructural abnormalities but no signs of inflammation or dystrophy in Post COVID-19 condition. Eur. J. Neurol. 1, 970–981. https://doi.org/10.1111/ene.15709 (2023).
doi: 10.1111/ene.15709
Raben, N. et al. Targeted disruption of the acid α-glucosidase gene in mice causes an illness with critical features of both infantile and adult human glycogen storage disease type II. J. Biol. Chem. 273, 19086–19092. https://doi.org/10.1074/jbc.273.30.19086 (1998).
doi: 10.1074/jbc.273.30.19086
pubmed: 9668092
Reeder, S. B. et al. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): Application with fast spin-echo imaging. Magn. Reson. Med. 644, 636–644. https://doi.org/10.1002/mrm.20624 (2005).
doi: 10.1002/mrm.20624
Marty, B. et al. Simultaneous muscle water T2 and fat fraction mapping using transverse relaxometry with stimulated echo compensation. NMR Biomed. 29, 431–443. https://doi.org/10.1002/nbm.3459 (2016).
doi: 10.1002/nbm.3459
pubmed: 26814454
Leemans, A. & Jones, D. K. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn. Reson. Med. 61, 1336–1349 (2009).
doi: 10.1002/mrm.21890
pubmed: 19319973
Veraart, J. et al. Denoising of diffusion MRI using random matrix theory. Neuroimage 142, 394–406. https://doi.org/10.1016/j.neuroimage.2016.08.016 (2016).
doi: 10.1016/j.neuroimage.2016.08.016
pubmed: 27523449
Schänzer, A. et al. Quantification of muscle pathology in infantile Pompe disease. Neuromusc. Disord. 27, 141–152. https://doi.org/10.1016/j.nmd.2016.10.010 (2017).
doi: 10.1016/j.nmd.2016.10.010
pubmed: 27927596
Bankhead, P. et al. QuPath: Open source software for digital pathology image analysis. Sci. Rep. 7, 1–7. https://doi.org/10.1038/s41598-017-17204-5 (2017).
doi: 10.1038/s41598-017-17204-5
Schindelin, J. et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 9, 676–682. https://doi.org/10.1038/nmeth.2019 (2012).
doi: 10.1038/nmeth.2019
pubmed: 22743772
Beha, G. et al. FP.19 Quantification of glycogen distribution in late-onset Pompe patients using 7 Tesla C13 NMR spectroscopy. Neuromusc. Disord. 32, S73. https://doi.org/10.1016/j.nmd.2022.07.132 (2022).
doi: 10.1016/j.nmd.2022.07.132
Damon, B. M. Effects of image noise in muscle diffusion tensor (DT)-MRI assessed using numerical simulations. Magn. Reson. Med. 60, 934–944 (2008).
doi: 10.1002/mrm.21707
pubmed: 18816814
pmcid: 2570042
Williams, S. E. et al. Quantitative effects of inclusion of fat on muscle diffusion tensor MRI measurements. J. Magn. Reson. Imaging 38, 1292–1297. https://doi.org/10.1002/jmri.24045 (2013).
doi: 10.1002/jmri.24045
pubmed: 23418124
Otto, L. A. M. et al. Quantitative MRI of skeletal muscle in a cross-sectional cohort of patients with spinal muscular atrophy types 2 and 3. NMR Biomed. 4357, 1–13. https://doi.org/10.1002/nbm.4357 (2020).
doi: 10.1002/nbm.4357
Berry, D. B. et al. Relationships between tissue microstructure and the diffusion tensor in simulated skeletal muscle. Magn. Reson. Med. 80, 317–329 (2018).
doi: 10.1002/mrm.26993
pubmed: 29090480
Paolini, A. et al. Attenuation of autophagy impacts on muscle fibre development, starvation induced stress and fibre regeneration following acute injury. Sci. Rep. 8, 1–12. https://doi.org/10.1038/s41598-018-27429-7 (2018).
doi: 10.1038/s41598-018-27429-7
Raben, N. et al. Modulation of disease severity in mice with targeted disruption of the acid α-glucosidase gene. Neuromuscul. Disord. 10, 283–291. https://doi.org/10.1016/S0960-8966(99)00117-0 (2000).
doi: 10.1016/S0960-8966(99)00117-0
pubmed: 10838256
Lagalice, L. et al. Satellite cells fail to contribute to muscle repair but are functional in Pompe disease (glycogenosis type II). Acta Neuropathol. Commun. 6, 116. https://doi.org/10.1186/s40478-018-0609-y (2018).
doi: 10.1186/s40478-018-0609-y
pubmed: 30382921
pmcid: 6211565
Runwal, G. et al. LC3-positive structures are prominent in autophagy-deficient cells. Sci. Rep. 9, 1–14. https://doi.org/10.1038/s41598-019-46657-z (2019).
doi: 10.1038/s41598-019-46657-z
Nascimbeni, A. C. et al. The role of autophagy in the pathogenesis of glycogen storage disease type II (GSDII). Cell Death Differ. 19, 1698–1708. https://doi.org/10.1038/cdd.2012.52 (2012).
doi: 10.1038/cdd.2012.52
pubmed: 22595755
pmcid: 3438501
Ran, J. et al. T2 mapping in dermatomyositis/polymyositis and correlation with clinical parameters. Clin. Radiol. 73(1057), e13-1057.e18. https://doi.org/10.1016/j.crad.2018.07.106 (2018).
doi: 10.1016/j.crad.2018.07.106
Wang, F. et al. Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation. Eur. Radiol. 33, 2350–2357. https://doi.org/10.1007/s00330-022-09254-9 (2023).
doi: 10.1007/s00330-022-09254-9
pubmed: 36396791
Schlaeger, S. et al. Water T2 mapping in fatty infiltrated thigh muscles of patients with neuromuscular diseases using a T2-prepared 3D turbo spin echo with SPAIR. J. Magn. Reson. Imaging 51, 1727–1736. https://doi.org/10.1002/jmri.27032 (2020).
doi: 10.1002/jmri.27032
pubmed: 31875343
Rehmann, R. et al. Muscle diffusion tensor imaging in glycogen storage disease V (McArdle disease). Eur. Radiol. 29, 3224–3232. https://doi.org/10.1007/s00330-018-5885-1 (2019).
doi: 10.1007/s00330-018-5885-1
pubmed: 30560358
Kiryk, A. et al. Cognitive abilities of Alzheimers disease transgenic mice are modulated by social context and circadian rhythm. Curr. Alzheimer Res. 8, 883–892. https://doi.org/10.2174/156720511798192745 (2011).
doi: 10.2174/156720511798192745
pubmed: 22171952
Kulesskaya, N. et al. Mixed housing with DBA/2 mice induces stress in C57BL/6 mice: Implications for interventions based on social enrichment. Front Behav. Neurosci. 8, 1–15. https://doi.org/10.3389/fnbeh.2014.00257 (2014).
doi: 10.3389/fnbeh.2014.00257