Diffusion Kurtosis Imaging Detects Microstructural Changes in a Methamphetamine-Induced Mouse Model of Parkinson’s Disease
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Methamphetamine (METH) abuse is known to increase the risk of Parkinson’s disease (PD) due to its dopaminergic neurotoxicity. This is the rationale for the METH model of PD developed by toxic METH dosing (10 mg/kg four times every 2 h) which features robust neurodegeneration and typical motor impairment in mice. In this study, we used diffusion kurtosis imaging to reveal microstructural brain changes caused by METH-induced neurodegeneration. The METH-treated mice and saline-treated controls underwent diffusion kurtosis imaging scanning using the Bruker Avance 9.4 Tesla MRI system at two time-points: 5 days and 1 month to capture both early and late changes induced by METH. At 5 days, we found a decrease in kurtosis in substantia nigra, striatum and sensorimotor cortex, which is likely to indicate loss of DAergic neurons. At 1 month, we found an increase of kurtosis in striatum and sensorimotor cortex and hippocampus, which may reflect certain recovery processes. Furthermore, we performed tract-based spatial statistics analysis in the white matter and at 1 month, we observed increased kurtosis in ventral nucleus of the lateral lemniscus and some of the lateral thalamic nuclei. No changes were present at the early stage. This study confirms the ability of diffusion kurtosis imaging to detect microstructural pathological processes in both grey and white matter in the METH model of PD. The exact mechanisms underlying the kurtosis changes remain to be elucidated but kurtosis seems to be a valuable biomarker for tracking microstructural brain changes in PD and potentially other neurodegenerative disorders.
KeywordsBehaviour Diffusion kurtosis imaging Methamphetamine Mice MRI Parkinson’s disease Tract-based spatial statistics
The authors are grateful to Dr. Peter Latta for his valuable technical support and help with the MRI scanning and a professional data analyst Ms. Daniela Kuruczova for her advice on statistical analysis. The behavioural apparatuses for the challenging beam traversal and grid test were kindly provided by Jiri Kucera, Environmental Measuring Systems, Brno, Czech Republic.
This study was performed at Masaryk University as part of the project “Pharmacological research in the field of pharmacokinetics, neuropsychopharmacology and oncology”, number MUNI/A/1550/2018, with the support of the Specific University Research Grant, as provided by the Ministry of Education, Youth and Sports of the Czech Republic in the year 2019 and also supported by funds from the Faculty of Medicine MU to junior researcher Jana Ruda-Kucerova. The work was also supported from European Regional Development Fund-Project “National infrastructure for biological and medical imaging” (No. CZ.02.1.01/0.0/0.0/16_013/0001775). We acknowledge the core facility MAFIL of CEITEC and the MR unit and the animal facility (CZ62760225) of ISI CAS, both supported by the Czech-BioImaging large RI project (LM2015062 funded by MEYS CR), for their support with obtaining scientific data presented in this paper. Nikoletta Szabo was supported by NAP 2.0 (2017-1.2.1-NKP-2017-00002), EFOP-3.6.1-16-2016-00008 and KTIA_13_NAP-A-II/20. The ISI CAS support was further co-financed by MEYS CR and EC (CZ.1.05/2.1.00/01.0017) and by the CAS (RVO:68081731).
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
- Chuhutin A, Hansen B, Jespersen SN (2017) Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection. NMR Biomed 30(11):e3777Google Scholar
- Fornai F, Lenzi P, Ferrucci M, Lazzeri G, Poggio AB, Natale G, Busceti CL, Biagioni F, Giusiani M, Ruggieri S, Paparelli A (2005) Occurrence of neuronal inclusions combined with increased nigral expression of alpha-Synuclein within dopaminergic neurons following treatment with amphetamine derivatives in mice. Brain Res Bull 65(5):405–413PubMedGoogle Scholar
- Franklin, K. B. J. and G. Paxinos (2013). Paxinos and Franklin’s the mouse brain in stereotaxic coordinatesGoogle Scholar
- Granado N, Ares-Santos S, O’Shea E, Vicario-Abejón C, Colado MI, Moratalla R (2010) Selective vulnerability in striosomes and in the nigrostriatal dopaminergic pathway after methamphetamine administration: early loss of TH in striosomes after methamphetamine. Neurotox Res 18(1):48–58PubMedGoogle Scholar
- Hansen B, Jespersen SN (2017) Recent developments in fast kurtosis imaging. Front Phys 5(40)Google Scholar
- Kamagata, K., A. Zalesky, et al. (2017). "Gray matter abnormalities in idiopathic Parkinson’s disease: evaluation by diffusional kurtosis imaging and neurite orientation dispersion and density imaging." Hum Brain MappGoogle Scholar
- Khairnar A, Latta P, Drazanova E, Ruda-Kucerova J, Szabó N, Arab A, Hutter-Paier B, Havas D, Windisch M, Sulcova A, Starcuk Z, Rektorova I (2015) Diffusion kurtosis imaging detects microstructural alterations in brain of alpha-Synuclein overexpressing transgenic mouse model of Parkinson’s disease: a pilot study. Neurotox Res 28(4):281–289PubMedGoogle Scholar
- Khairnar A, Ruda-Kucerova J, Drazanova E, Szabó N, Latta P, Arab A, Hutter-Paier B, Havas D, Windisch M, Sulcova A, Starcuk Z Jr, Király A, Rektorova I (2016) Late-stage alpha-Synuclein accumulation in TNWT-61 mouse model of Parkinson’s disease detected by diffusion kurtosis imaging. J Neurochem 136(6):1259–1269PubMedGoogle Scholar
- Khairnar A, Ruda-Kucerova J, Szabó N, Drazanova E, Arab A, Hutter-Paier B, Neddens J, Latta P, Starcuk Z Jr, Rektorova I (2017) Early and progressive microstructural brain changes in mice overexpressing human alpha-Synuclein detected by diffusion kurtosis imaging. Brain Behav Immun 61:197–208PubMedGoogle Scholar
- London ED, Simon SL, Berman SM, Mandelkern MA, Lichtman AM, Bramen J, Shinn AK, Miotto K, Learn J, Dong Y, Matochik JA, Kurian V, Newton T, Woods R, Rawson R, Ling W (2004) Mood disturbances and regional cerebral metabolic abnormalities in recently abstinent methamphetamine abusers. Arch Gen Psychiatry 61(1):73–84PubMedGoogle Scholar
- Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17(3):143–155Google Scholar
- Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TEJ (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31(4):1487–1505Google Scholar