Myopathology in the times of modern genetics

Expression pattern of mitochondrial respiratory chain enzymes in skeletal muscle of patients with mitochondrial myopathy associated with the homoplasmic m.14674T>C variant

Two homoplasmic variants in tRNA^Glu (m.14674T>C/G) are associated with reversible infantile respiratory chain deficiency. This study sought to further characterize the expression of the individual mitochondrial respiratory chain complexes and to describe the natural history of the disease. Seven patients from four families with mitochondrial myopathy associated with the homoplasmic m.14674T>C variant were investigated. All patients underwent skeletal muscle biopsy and mtDNA sequencing. Whole-genome sequencing was performed in one family. Western blot and immunohistochemical analyses were used to characterize the expression of the individual respiratory chain complexes. Patients presented with hypotonia and feeding difficulties within the first weeks or months of life, except for one patient who first showed symptoms at 4 years of age. Histopathological findings in muscle included lipid accumulation, numerous COX-deficient fibers, and mitochondrial proliferation. Ultrastructural abnormalities included enlarged mitochondria with concentric cristae and dense mitochondrial matrix. The m.14674T>C variant in MT-TE was identified in all patients. Immunohistochemistry and immunoblotting demonstrated pronounced deficiency of the complex I subunit NDUFB8. The expression of MTCO1, a complex IV subunit, was also decreased, but not to the same extent as NDUFB8. Longitudinal follow-up data demonstrated that not all features of the disorder are entirely transient, that the disease may be progressive, and that signs and symptoms of myopathy may develop during childhood. This study sheds new light on the involvement of complex I in reversible infantile respiratory chain deficiency, it shows that the disorder may be progressive, and that myopathy can develop without an infantile episode.

Evaluating next-generation sequencing in neuromuscular diseases with neonatal respiratory distress

With the exception of infantile spinal muscular atrophy (SMA) and congenital myotonic dystrophy 1 (DM1), congenital myopathies and muscular dystrophies with neonatal respiratory distress pose diagnostic challenges. Next-generation sequencing (NGS) provides hope for the diagnosis of these rare diseases. We evaluated the efficiency of next-generation sequencing (NGS) in ventilated newborns with peripheral hypotonia. We compared the results of our previous study in a cohort of 19 patients analysed by Sanger sequencing from 2007 to 2012, with a diagnostic yield of 26% (5/19), and those of a new retrospective study in 28 patients from 2007 to 2018 diagnosed using MyoPanel, a neuromuscular disease panel, with a diagnostic yield of 43% (12/28 patients). Pathogenic variants were found in five genes: ACTA1 (n = 4 patients), RYR1 (n = 2), CACNA1S (n = 1), NEB (n = 3), and MTM1 (n = 2). Myopanel increased the diagnosis of congenital neuromuscular diseases, but more than half the patients remained undiagnosed. Whole exome sequencing did not seem to fully respond to this diagnostic limitation. Therefore, explorations with whole genome sequencing will be the next step.

[Application of RNA sequencing in clinical diagnosis of Mendelian disease]

Gene panel and whole exome sequencing are now commonly used to detect Mendelian disease, but the current molecular diagnostic rate of DNA sequencing is only 35%-50%. In recent years, RNA sequencing emerges as a promising diagnostic method. It can detect new pathogenic mutations, and analyze allele-specific expression. This will be helpful to understand the relationship between disease genotype and phenotype, and can complement genome sequencing in order to expand the traditional genomic diagnostic methods of Mendelian disease. RNA sequencing is expected to become a routine tool for diagnosing Mendelian diseases. This article reviews the application of RNA sequencing in the clinical diagnosis of Mendelian disease.

Accuracy of a machine learning muscle MRI-based tool for the diagnosis of muscular dystrophies

OBJECTIVE

Genetic diagnosis of muscular dystrophies (MDs) has classically been guided by clinical presentation, muscle biopsy, and muscle MRI data. Muscle MRI suggests diagnosis based on the pattern of muscle fatty replacement. However, patterns overlap between different disorders and knowledge about disease-specific patterns is limited. Our aim was to develop a software-based tool that can recognize muscle MRI patterns and thus aid diagnosis of MDs.

METHODS

We collected 976 pelvic and lower limbs T1-weighted muscle MRIs from 10 different MDs. Fatty replacement was quantified using Mercuri score and files containing the numeric data were generated. Random forest supervised machine learning was applied to develop a model useful to identify the correct diagnosis. Two thousand different models were generated and the one with highest accuracy was selected. A new set of 20 MRIs was used to test the accuracy of the model, and the results were compared with diagnoses proposed by 4 specialists in the field.

RESULTS

A total of 976 lower limbs MRIs from 10 different MDs were used. The best model obtained had 95.7% accuracy, with 92.1% sensitivity and 99.4% specificity. When compared with experts on the field, the diagnostic accuracy of the model generated was significantly higher in a new set of 20 MRIs.

CONCLUSION

Machine learning can help doctors in the diagnosis of muscle dystrophies by analyzing patterns of muscle fatty replacement in muscle MRI. This tool can be helpful in daily clinics and in the interpretation of the results of next-generation sequencing tests.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that a muscle MRI-based artificial intelligence tool accurately diagnoses muscular dystrophies.

Expanding the Boundaries of RNA Sequencing as a Diagnostic Tool for Rare Mendelian Disease

Gene-panel and whole-exome analyses are now standard methodologies for mutation detection in Mendelian disease. However, the diagnostic yield achieved is at best 50%, leaving the genetic basis for disease unsolved in many individuals. New approaches are thus needed to narrow the diagnostic gap. Whole-genome sequencing is one potential strategy, but it currently has variant-interpretation challenges, particularly for non-coding changes. In this study we focus on transcriptome analysis, specifically total RNA sequencing (RNA-seq), by using monogenetic neuromuscular disorders as proof of principle. We examined a cohort of 25 exome and/or panel "negative" cases and provided genetic resolution in 36% (9/25). Causative mutations were identified in coding and non-coding exons, as well as in intronic regions, and the mutational pathomechanisms included transcriptional repression, exon skipping, and intron inclusion. We address a key barrier of transcriptome-based diagnostics: the need for source material with disease-representative expression patterns. We establish that blood-based RNA-seq is not adequate for neuromuscular diagnostics, whereas myotubes generated by transdifferentiation from an individual's fibroblasts accurately reflect the muscle transcriptome and faithfully reveal disease-causing mutations. Our work confirms that RNA-seq can greatly improve diagnostic yield in genetically unresolved cases of Mendelian disease, defines strengths and challenges of the technology, and demonstrates the suitability of cell models for RNA-based diagnostics. Our data set the stage for development of RNA-seq as a powerful clinical diagnostic tool that can be applied to the large population of individuals with undiagnosed, rare diseases and provide a framework for establishing minimally invasive strategies for doing so.

Effectiveness of whole exome sequencing in unsolved patients with a clinical suspicion of a mitochondrial disorder in Estonia

OBJECTIVE

Reaching a genetic diagnosis of mitochondrial disorders (MDs) is challenging due to their broad phenotypic and genotypic heterogeneity. However, there is growing evidence that the use of whole exome sequencing (WES) for diagnosing patients with a clinical suspicion of an MD is effective (39-60%). We aimed to study the effectiveness of WES in clinical practice in Estonia, in patients with an unsolved, but suspected MD. We also show our first results of mtDNA analysis obtained from standard WES reads.

METHODS

Retrospective cases were selected from a database of 181 patients whose fibroblast cell cultures had been stored from 2003 to 2013. Prospective cases were selected during the period of 2014-2016 from patients referred to a clinical geneticist in whom an MD was suspected. We scored each patient according to the mitochondrial disease criteria (MDC) (Morava et al., 2006) after re-evaluation of their clinical data, and then performed WES analysis.

RESULTS

A total of 28 patients were selected to the study group. A disease-causing variant was found in 16 patients (57%) using WES. An MD was diagnosed in four patients (14%), with variants in the SLC25A4, POLG, SPATA5, and NDUFB11 genes. Other variants found were associated with a neuromuscular disease (SMN1, MYH2, and LMNA genes), neurodegenerative disorder (TSPOAP1, CACNA1A, ALS2, and SCN2A genes), multisystemic disease (EPG5, NKX1-2, ATRX, and ABCC6 genes), and one in an isolated cardiomyopathy causing gene (MYBPC3). The mtDNA point mutation was found in the MT-ATP6 gene of one patient upon mtDNA analysis.

CONCLUSIONS

The diagnostic yield of WES in our cohort was 57%, proving to be a very good effectiveness. However, MDs were found in only 14% of the patients. We suggest WES analysis as a first-tier method in clinical genetic practice for children with any multisystem, neurological, and/or neuromuscular problem, as nuclear DNA variants are more common in children with MDs; a large number of patients harbor disease-causing variants in genes other than the mitochondria-related ones, and the clinical presentation might not always point towards an MD. We have also successfully conducted analysis of mtDNA from standard WES reads, providing further evidence that this method could be routinely used in the future.

Impact of muscle biopsy on diagnosis and management of children with neuromuscular diseases: A 10-year retrospective critical review

BACKGROUND

Muscle biopsy facilitates morphologic, biochemical, and ultrastructural analysis of muscle for the purpose of making definitive neuromuscular diagnosis. However, muscle biopsy is an expensive, invasive, time-consuming, and resource-dependent procedure. The need for general anesthesia in children also increases the risks associated with this procedure. The aim of this study was to investigate the benefits of muscle biopsies performed over a 10-year period, with a focus on indications, suspected and histopathologic diagnosis, and impact on diagnosis and management decisions.

METHODS

We retrospectively reviewed results of muscle biopsies performed in children at our center during the 2004 to 2014 study period. Clinical presentations, biopsy complications, pathologic results, and changes in management decision were reviewed and analyzed.

RESULTS

Biopsies from 92 patients were included. Mean age of patients was 7.1years, and 66.3% were male. There were no perioperative complications, and definitive diagnosis was made in 74 patients. Regardless of whether pathologic changes were found or not, information gained from muscle biopsy significantly impacted prognosis and subsequent genetic counseling.

CONCLUSIONS

Muscle biopsy is a safe and useful diagnostic tool in children suspected of having neuromuscular diseases, especially in those with muscle diseases. Definitive pathologic diagnosis helps to optimize treatment, counseling, and surveillance.

THE TYPE OF STUDY AND LEVEL OF EVIDENCE

Study of diagnostic test: level 1.