Muscle diffusion MRI reveals autophagic buildup in a mouse model for Pompe disease

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 (Gaa6neo/6neo) and wildtype mice (age 1-8 months) were conducted using diffusion MRI, T2-mapping, and Dixon-based water-fat imaging on a 7 T scanner. Immunofluorescence studies on quadriceps muscles were analyzed for lysosomal accumulations and autophagic buildup and correlated with MRI outcome measures. Fat fraction and water-T2 did not differ between groups and remained stable over time. In Pompe mice, fractional anisotropy increased, while mean diffusivity (MD) and radial diffusivity (RD) decreased in all observed muscles. Autophagic marker and muscle fibre diameter revealed significant negative correlations with reduced RD and MD, while lysosomal marker did not show any change or correlation. Using qMRI, we showed diffusion changes in muscles of presymptomatic Pompe mice without fat-infiltrated muscles and correlated them to autophagic markers and fibre diameter, indicating diffusion MRI reveals autophagic buildup.

Dysregulation of Metabolism and Proteostasis in Skeletal Muscle of a Presymptomatic Pompe Mouse Model

Pompe disease is a rare genetic metabolic disorder caused by mutations in acid-alpha glucoside (GAA) leading to pathological lysosomal glycogen accumulation associated with skeletal muscle weakness, respiratory difficulties and cardiomyopathy, dependent from the GAA residual enzyme activity. This study aimed to investigate early proteomic changes in a mouse model of Pompe disease and identify potential therapeutic pathways using proteomic analysis of skeletal muscles from pre-symptomatic Pompe mice. For this purpose, quadriceps samples of Gaa^6neo/6neo mutant (Pompe) and wildtype mice, at the age of six weeks, were studied with three biological replicates for each group. The data were validated with skeletal muscle morphology, immunofluorescence studies and western blot analysis. Proteomic profiling identified 538 significantly upregulated and 16 significantly downregulated proteins in quadriceps muscles derived from Pompe animals compared to wildtype mice. The majority of significantly upregulated proteins were involved in metabolism, translation, folding, degrading and vesicular transport, with some having crucial roles in the etiopathology of other neurological or neuromuscular diseases. This study highlights the importance of the early diagnosis and treatment of Pompe disease and suggests potential add-on therapeutic strategies targeting protein dysregulations.

Quantitative muscle magnetic resonance imaging depicts microstructural abnormalities but no signs of inflammation or dystrophy in post-COVID-19 condition

BACKGROUND AND PURPOSE

Post-COVID-19 condition (PCC) has high impact on quality of life, with myalgia and fatigue affecting at least 25% of PCC patients. This case-control study aims to noninvasively assess muscular alterations via quantitative muscle magnetic resonance imaging (MRI) as possible mechanisms for ongoing musculoskeletal complaints and premature exhaustion in PCC.

METHODS

Quantitative muscle MRI was performed on a 3 Tesla MRI scanner of the whole legs in PCC patients compared to age- and sex-matched healthy controls, including a Dixon sequence to determine muscle fat fraction (FF), a multi-echo spin-echo sequence for quantitative water mapping reflecting putative edema, and a diffusion-weighted spin-echo echo-planar imaging sequence to assess microstructural alterations. Clinical examination, nerve conduction studies, and serum creatine kinase were performed in all patients. Quantitative muscle MRI results were correlated to the results of the 6-min walk test and standardized questionnaires assessing quality of life, fatigue, and depression.

RESULTS

Twenty PCC patients (female: n = 15, age = 48.8 ± 10.1 years, symptoms duration = 13.4 ± 4.2 months, body mass index [BMI] = 28.8 ± 4.7 kg/m² ) were compared to 20 healthy controls (female: n = 15, age = 48.1 ± 11.1 years, BMI = 22.9 ± 2.2 kg/m² ). Neither FF nor T2 revealed signs of muscle degeneration or inflammation in either study groups. Diffusion tensor imaging (DTI) revealed reduced mean, axial, and radial diffusivity in the PCC group.

CONCLUSIONS

Quantitative muscle MRI did not depict any signs of ongoing inflammation or dystrophic process in the skeletal muscles in PCC patients. However, differences observed in muscle DTI depict microstructural abnormalities, which may reflect potentially reversible fiber hypotrophy due to deconditioning. Further longitudinal and interventional studies should prove this hypothesis.

Robustness and stability of volume-based tractography in a multicenter setting

Muscle diffusion tensor imaging (mDTI)-based tractography is a promising tool with which to detect subclinical changes in muscle injuries and to evaluate pathophysiology in neuromuscular diseases. Classic region of interest (ROI)-based tractography is very time-consuming and requires an examiner with extensive experience. (Semi)automatic approaches such as volume-based tractography (VBT) can diminish this problem but its robustness and stability are unknown. The aim of the current study was to assess the performance of VBT in a multicenter setting and to evaluate semiautomatic segmentation approaches in the analysis of VBT-derived data in terms of the comparability of the outcome measures. Five traveling volunteers underwent 3-T mDTI of seven calf muscles of both legs at six different MR sites. Tract properties and diffusion metrics were calculated using VBT. Within-subject coefficients of variance (wsCVs) and intraclass correlation coefficients (ICCs) were calculated to assess the multicenter reproducibility of tract properties such as tract density (TD), mean tract length, volume and tract propagation angle, and diffusion metrics such as fractional anisotropy, mean diffusivity, axial diffusivity (λ₁ ) and radial diffusivity in traveling subjects. Furthermore, 50 individual datasets from five different centers (10 datasets per center) were pooled to assess the feasibility of VBT with manual and semiautomatic segmentation. To assess the differences of tract properties and diffusion metrics between segmentation approaches an ANOVA was performed, and ICC and Bland-Altman plots were analyzed. wsCVs and ICCs showed good reproducibility of the tract properties TD and volume, as well as diffusion metrics. ANOVA showed no significant differences between manual and semiautomatic approaches. ICCs were excellent (≥ 0.992) and Bland-Altman analysis did not reveal any systemic bias between the methods. Tract properties and diffusion metrics derived from VBT showed good comparability among centers. Semiautomatic approaches revealed excellent agreement with gold standard of manual segmentation. These findings suggest that pooling data from different centers to construct a reference database for tractography results is feasible using semiautomatic segmentation approaches.

3D Automated Segmentation of Lower Leg Muscles Using Machine Learning on a Heterogeneous Dataset

Quantitative MRI combines non-invasive imaging techniques to reveal alterations in muscle pathophysiology. Creating muscle-specific labels manually is time consuming and requires an experienced examiner. Semi-automatic and fully automatic methods reduce segmentation time significantly. Current machine learning solutions are commonly trained on data from healthy subjects using homogeneous databases with the same image contrast. While yielding high Dice scores (DS), those solutions are not applicable to different image contrasts and acquisitions. Therefore, the aim of our study was to evaluate the feasibility of automatic segmentation of a heterogeneous database. To create a heterogeneous dataset, we pooled lower leg muscle images from different studies with different contrasts and fields-of-view, containing healthy controls and diagnosed patients with various neuromuscular diseases. A second homogenous database with uniform contrasts was created as a subset of the first database. We trained three 3D-convolutional neuronal networks (CNN) on those databases to test performance as compared to manual segmentation. All networks, training on heterogeneous data, were able to predict seven muscles with a minimum average DS of 0.75. U-Net performed best when trained on the heterogeneous dataset (DS: 0.80 ± 0.10, AHD: 0.39 ± 0.35). ResNet and DenseNet yielded higher DS, when trained on a heterogeneous dataset (both DS: 0.86), as compared to a homogeneous dataset (ResNet DS: 0.83, DenseNet DS: 0.76). In conclusion, a CNN trained on a heterogeneous dataset achieves more accurate labels for predicting a heterogeneous database of lower leg muscles than a CNN trained on a homogenous dataset. We propose that a large heterogeneous database is needed, to make automated segmentation feasible for different kinds of image acquisitions.

Diffusion Tensor Imaging Shows Differences Between Myotonic Dystrophy Type 1 and Type 2

BACKGROUND

Myotonic Dystrophies type 1 and type 2 are hereditary myopathies with dystrophic muscle degeneration in varying degrees. Differences in muscle diffusion between both diseases have not been evaluated yet.

OBJECTIVE

To evaluate the ability to of muscle diffusion tensor imaging (mDTI) and Dixon fat-quantification to distinguish between Myotonic dystrophy (DM) type 1 and type 2 and if both diseases show distinct muscle involvement patterns.

METHODS

We evaluated 6 thigh and 7 calf muscles (both legs) of 10 DM 1 and 13 DM 2 and 28 healthy controls (HC) with diffusion tensor imaging, T1w and mDixonquant sequences in a 3T MRI scanner. The quantitative mDTI-values axial diffusivity (λ1), mean diffusivity (MD), radial diffusivity (RD) and fractional anisotropy (FA) as well as fat-fraction were analysed. CTG-Triplett repeat-length of DM 1 patients was correlated to diffusion metrics and fat-fraction.

RESULTS

mDTI showed significant differences between DM 1 and DM 2 vs. healthy controls in diffusion parameters of the thigh (all p < 0.001) except for FA (p = 0.0521 / 0.8337). In calf muscles mDTI showed significant differences between DM 1 and DM 2 patients (all p < 0.0001) as well as between DM 1 patients and controls (all p = 0.0001). Thigh muscles had a significant higher fat-fraction in both groups vs. controls (p < 0.05). There was no correlation of CTG triplet length with mDTI values and fat-fraction.

DISCUSSION

mDTI reveals specific changes of the diffusion parameters and fat-fraction in muscles of DM 1 and DM 2 patients. Thus, the quantitative MRI methods presented in this study provide a powerful tool in differential diagnosis and follow-up of DM 1 and DM 2, however, the data must be validated in larger studies.

Quantitative Muscle-MRI Correlates with Histopathology in Skeletal Muscle Biopsies

BACKGROUND

Skeletal muscle biopsy is one of the gold standards in the diagnostic workup of muscle disorders. By histopathologic analysis, characteristic features like inflammatory cellular infiltrations, fat and collagen replacement of muscle tissue or structural defects of the myofibers can be detected. In the past years, novel quantitative MRI (qMRI) techniques have been developed to quantify tissue parameters, thus providing a non-invasive diagnostic tool in several myopathies.

OBJECTIVE

This proof-of-principle study was performed to validate the qMRI-techniques to skeletal muscle biopsy results.

METHODS

Ten patients who underwent skeletal muscle biopsy for diagnostic purposes were examined by qMRI. Fat fraction, water T2-time and diffusion parameters were measured in the muscle from which the biopsy was taken. The proportion of fat tissue, the severity of degenerative and inflammatory parameters and the amount of type 1- and type 2- muscle fibers were determined in all biopsy samples. The qMRI-data were then correlated to the histopathological findings.

RESULTS

The amount of fat tissue in skeletal muscle biopsy correlated significantly with the fat fraction derived from the Dixon sequence. The water T2-time, a parameter for tissue edema, correlated with the amount of vacuolar changes of myofibers and endomysial macrophages in the histopathologic analysis. No significant correlations were found for diffusion parameters.

CONCLUSION

In this proof-of-principle study, qMRI techniques were related to characteristic histopathologic features in neuromuscular disorders. The study provides the basis for further development of qMRI methods in the follow-up of patients with neuromuscular disorders, especially in the context of emerging treatment strategies.

Evaluation of interrater reliability of different muscle segmentation techniques in diffusion tensor imaging

INTRODUCTION

Muscle diffusion tensor imaging (mDTI) is a quantitative MRI technique that can provide information about muscular microstructure and integrity. Ultrasound and DTI studies have shown intramuscular differences, and therefore separation of different muscles for analysis is essential. The commonly used methods to assess DTI metrics in muscles are manual segmentation and tract-based analysis. Recently methods such as volume-based tractography have been applied to optimize muscle architecture estimation, but can also be used to assess DTI metrics.

PURPOSE

To evaluate diffusion metrics obtained using three different methods-volume-based tractography, manual segmentation-based analysis and tract-based analysis-with respect to their interrater reliability and their ability to detect intramuscular variance.

MATERIALS AND METHODS

30 volunteers underwent an MRI examination in a 3 T scanner using a 16-channel Torso XL coil. Diffusion-weighted images were acquired to obtain DTI metrics. These metrics were evaluated in six thigh muscles using volume-based tractography, manual segmentation and standard tractography. All three methods were performed by two independent raters to assess interrater reliability by ICC analysis and Bland-Altman plots. Ability to assess intramuscular variance was compared using an ANOVA with muscle as a between-subjects factor.

RESULTS

Interrater reliability for all methods was found to be excellent. The highest interrater reliability was found for volume-based tractography (ICC ≥ 0.967). Significant differences for the factor muscle in all examined diffusion parameters were shown in muscles using all methods (main effect p < 0.001).

CONCLUSIONS

Diffusion data can be assessed by volume tractography, standard tractography and manual segmentation with high interrater reliability. Each method produces different results for the investigated DTI parameters. Volume-based tractography was superior to conventional manual segmentation and tractography regarding interrater reliability and detection of intramuscular variance, while tract-based analysis showed the lowest coefficients of variation.

Diffusion tensor imaging reveals changes in non-fat infiltrated muscles in late onset Pompe disease

MRI is a helpful tool for monitoring disease progression in late-onset Pompe disease (LOPD). Our study aimed to evaluate if muscle diffusion tensor imaging (mDTI) shows alterations in muscles of LOPD patients with <10% fat-fraction. We evaluated 6 thigh and 7 calf muscles (both legs) of 18 LOPD and 29 healthy controls (HC) with muscle diffusion tensor imaging (mDTI), T1w, and mDixonquant sequences in a 3T MRI scanner. The quantitative mDTI-values axial diffusivity (λ₁ ), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA) as well as fat-fraction were analyzed. 6-Minute Walk Test (6-MWT) data were correlated to diffusion metrics. We found that mDTI showed significant differences between LOPD and HC in diffusion parameters (P < .05). Thigh muscles with <10% fat-fraction showed significant differences in MD, RD, and λ_1-3 . MD positively correlated with 6-MWT (P = .06). To conclude, mDTI reveals diffusion restrictions in muscles of LOPD with and without fat-infiltration and reflects structural changes prior to fatty degeneration.

Multi-center evaluation of stability and reproducibility of quantitative MRI measures in healthy calf muscles

The purpose of this study was to evaluate temporal stability, multi-center reproducibility and the influence of covariates on a multimodal MR protocol for quantitative muscle imaging and to facilitate its use as a standardized protocol for evaluation of pathology in skeletal muscle. Quantitative T2, quantitative diffusion and four-point Dixon acquisitions of the calf muscles of both legs were repeated within one hour. Sixty-five healthy volunteers (31 females) were included in one of eight 3-T MR systems. Five traveling subjects were examined in six MR scanners. Average values over all slices of water-T2 relaxation time, proton density fat fraction (PDFF) and diffusion metrics were determined for seven muscles. Temporal stability was tested with repeated measured ANOVA and two-way random intraclass correlation coefficient (ICC). Multi-center reproducibility of traveling volunteers was assessed by a two-way mixed ICC. The factors age, body mass index, gender and muscle were tested for covariance. ICCs of temporal stability were between 0.963 and 0.999 for all parameters. Water-T2 relaxation decreased significantly (P < 10^-3 ) within one hour by ~ 1 ms. Multi-center reproducibility showed ICCs within 0.879-0.917 with the lowest ICC for mean diffusivity. Different muscles showed the highest covariance, explaining 20-40% of variance for observed parameters. Standardized acquisition and processing of quantitative muscle MRI data resulted in high comparability among centers. The imaging protocol exhibited high temporal stability over one hour except for water T2 relaxation times. These results show that data pooling is feasible and enables assembling data from patients with neuromuscular diseases, paving the way towards larger studies of rare muscle disorders.

The microRNA miR-375-3p and the Tumor Suppressor NDRG2 are Involved in Sporadic Amyotrophic Lateral Sclerosis

BACKGROUND/AIMS

Amyotrophic lateral sclerosis (ALS) is the most common degenerative motor neuron disease in humans. However, the pathogenesis of ALS is not yet understood. The wobbler mouse is considered as an animal model for the sporadic form of ALS due to its spontaneous mutation in the Vps54 gene. Due to transactivation of NDRG2 by p53, this tumor suppressor might play a functional role in stress induced cell death in wobbler mice as well as ALS patients. Furthermore, deregulated microRNAs are often related to neurodegenerative diseases. Thus, the NDRG2 linked miR-375-3p was of interest for this study.

METHODS

Here, we investigated the relevance of NDRG2 and miR-375-3p for the pathomechanism of the motor neuronal degeneration in wobbler mice by investigating expression level via qPCR and Western Blot as well as localization of these molecules in the cervical spinal cord by in situ hybridization, immunostaining and mass spectrometric analysis.

RESULTS

We were able to show a differential regulation of the expression of NDRG2 as well as miR-375-3p in the cervical part of the spinal cord of wobbler mice. In addition, for the first time we were able to demonstrate an expression of NDRG2 in motor neurons using different techniques.

CONCLUSION

The present study has shown NDRG2 and miR-375-3p to be promising targets for further research of the pathogenesis of sporadic ALS in the wobbler mouse model. Based on these results and in combination with previous published data we could develop a putative pro-apoptotic mechanism in the spinal cord of the wobbler mouse.

Regulation of mRNA Translation by MID1: A Common Mechanism of Expanded CAG Repeat RNAs

Expansion of CAG repeats, which code for the disease-causing polyglutamine protein, is a common feature in polyglutamine diseases. RNA-mediated mechanisms that contribute to neuropathology in polyglutamine diseases are important. RNA-toxicity describes a phenomenon by which the mutant CAG repeat RNA recruits RNA-binding proteins, thereby leading to aberrant function. For example the MID1 protein binds to mutant huntingtin (HTT) RNA, which is linked to Huntington's disease (HD), at its CAG repeat region and induces protein synthesis of mutant protein. But is this mechanism specific to HD or is it a common mechanism in CAG repeat expansion disorders? To answer this question, we have analyzed the interaction between MID1 and three other CAG repeat mRNAs, Ataxin2 (ATXN2), Ataxin3 (ATXN3), and Ataxin7 (ATXN7), that all differ in the sequence flanking the CAG repeat. We show that ATXN2, ATXN3, and ATXN7 bind to MID1 in a CAG repeat length-dependent manner. Furthermore, we show that functionally, in line with what we have previously observed for HTT, the binding of MID1 to ATXN2, ATXN3, and ATXN7 mRNA induces protein synthesis in a repeat length-dependent manner. Our data suggest that regulation of protein translation by the MID1 complex is a common mechanism for CAG repeat containing mRNAs.

β-Cell dysfunction in diabetes: a crisis of identity?

Type 2 diabetes is characterized by insulin resistance and a progressive loss of β-cell function induced by a combination of both β-cell loss and impaired insulin secretion from remaining β-cells. Here, we review the fate of the β-cell under chronic hyperglycaemic conditions with regard to β-cell mass, gene expression, hormone content, secretory capacity and the ability to de- or transdifferentiate into other cell types. We compare data from various in vivo and in vitro models of diabetes with a novel mouse model of inducible, reversible hyperglycaemia (βV59M mice). We suggest that insulin staining using standard histological methods may not always provide an accurate estimation of β-cell mass or number. We consider how β-cell identity is best defined, and whether expression of transcription factors normally found in islet progenitor cells, or in α-cells, implies that mature β-cells have undergone dedifferentiation or transdifferentiation. We propose that even in long-standing diabetes, β-cells predominantly remain β-cells-but not as we know them.