Identification and clinical characterization of Charcot-Marie-Tooth disease type 1C patients with LITAF p.G112S mutation

Current Treatment Methods for Charcot-Marie-Tooth Diseases

Charcot-Marie-Tooth (CMT) disease, the most common inherited neuromuscular disorder, exhibits a wide phenotypic range, genetic heterogeneity, and a variable disease course. The diverse molecular genetic mechanisms of CMT were discovered over the past three decades with the development of molecular biology and gene sequencing technologies. These methods have brought new options for CMT reclassification and led to an exciting era of treatment target discovery for this incurable disease. Currently, there are no approved disease management methods that can fully cure patients with CMT, and rehabilitation, orthotics, and surgery are the only available treatments to ameliorate symptoms. Considerable research attention has been given to disease-modifying therapies, including gene silencing, gene addition, and gene editing, but most treatments that reach clinical trials are drug treatments, while currently, only gene therapies for CMT2S have reached the clinical trial stage. In this review, we highlight the pathogenic mechanisms and therapeutic investigations of different subtypes of CMT, and promising therapeutic approaches are also discussed.

Efficient data labeling strategies for automated muscle segmentation in lower leg MRIs of Charcot-Marie-Tooth disease patients

We aimed to develop efficient data labeling strategies for ground truth segmentation in lower-leg magnetic resonance imaging (MRI) of patients with Charcot-Marie-Tooth disease (CMT) and to develop an automated muscle segmentation model using different labeling approaches. The impact of using unlabeled data on model performance was further examined. Using axial T1-weighted MRIs of 120 patients with CMT (60 each with mild and severe intramuscular fat infiltration), we compared the performance of segmentation models obtained using several different labeling strategies. The effect of leveraging unlabeled data on segmentation performance was evaluated by comparing the performances of few-supervised, semi-supervised (mean teacher model), and fully-supervised learning models. We employed a 2D U-Net architecture and assessed its performance by comparing the average Dice coefficients (ADC) using paired t-tests with Bonferroni correction. Among few-supervised models utilizing 10% labeled data, labeling three slices (the uppermost, central, and lowermost slices) per subject exhibited a significantly higher ADC (90.84±3.46%) compared with other strategies using a single image slice per subject (uppermost, 87.79±4.41%; central, 89.42±4.07%; lowermost, 89.29±4.71%, p < 0.0001) or all slices per subject (85.97±9.82%, p < 0.0001). Moreover, semi-supervised learning significantly enhanced the segmentation performance. The semi-supervised model using the three-slices strategy showed the highest segmentation performance (91.03±3.67%) among 10% labeled set models. Fully-supervised model showed an ADC of 91.39±3.76. A three-slice-based labeling strategy for ground truth segmentation is the most efficient method for developing automated muscle segmentation models of CMT lower leg MRI. Additionally, semi-supervised learning with unlabeled data significantly enhances segmentation performance.

INF2 mutations in patients with a broad phenotypic spectrum of Charcot-Marie-Tooth disease and focal segmental glomerulosclerosis

Mutations in INF2 are associated with the complex symptoms of Charcot-Marie-Tooth disease (CMT) and focal segmental glomerulosclerosis (FSGS). To date, more than 100 and 30 genes have been reported to cause these disorders, respectively. This study aimed to identify INF2 mutations in Korean patients with CMT. This study was conducted with 743 Korean families with CMT who were negative for PMP22 duplication. In addition, a family with FSGS was included in this study. INF2 mutations were screened using whole exome sequencing (WES) and filtering processes. As the results, four pathogenic INF2 mutations were identified in families with different clinical phenotypes: p.L78P and p.L132P in families with symptoms of both CMT and FSGS; p.C104Y in a family with CMT; and p.R218Q in a family with FSGS. Moreover, different CMT types were observed in families with CMT symptoms: CMT1 in two families and Int-CMT in another family. Hearing loss was observed in two families with CMT1. Pathogenicity was predicted by in silico analyses, and considerable conformational changes were predicted in the mutant proteins. Two mutations (p.L78P and p.C104Y) were unreported, and three families showed de novo mutations that were putatively occurred from fathers. This study suggests that patients with INF2 mutations show a broad phenotypic spectrum: CMT1, CMT1 + FSGS, CMTDIE + FSGS, and FSGS. Therefore, the genotype-phenotype correlation may be more complex than previously recognized. We believe that this study expands the clinical spectrum of patients with INF2 mutations and will be helpful in the molecular diagnosis of CMT and FSGS.

Peripheral Myelin Protein 22 Gene Mutations in Charcot-Marie-Tooth Disease Type 1E Patients

Duplication and deletion of the peripheral myelin protein 22 (PMP22) gene cause Charcot-Marie-Tooth disease type 1A (CMT1A) and hereditary neuropathy with liability to pressure palsies (HNPP), respectively, while point mutations or small insertions and deletions (indels) usually cause CMT type 1E (CMT1E) or HNPP. This study was performed to identify PMP22 mutations and to analyze the genotype−phenotype correlation in Korean CMT families. By the application of whole-exome sequencing (WES) and targeted gene panel sequencing (TS), we identified 14 pathogenic or likely pathogenic PMP22 mutations in 21 families out of 850 CMT families who were negative for 17p12 (PMP22) duplication. Most mutations were located in the well-conserved transmembrane domains. Of these, eight mutations were not reported in other populations. High frequencies of de novo mutations were observed, and the mutation sites of c.68C>G and c.215C>T were suggested as the mutational hotspots. Affected individuals showed an early onset-severe phenotype and late onset-mild phenotype, and more than 40% of the CMT1E patients showed hearing loss. Physical and electrophysiological symptoms of the CMT1E patients were more severely damaged than those of CMT1A while similar to CMT1B caused by MPZ mutations. Our results will be useful for the reference data of Korean CMT1E and the molecular diagnosis of CMT1 with or without hearing loss.