Splice modulating therapies for human disease.

Dysregulation of splicing and alternative splicing underlies many genetic and acquired diseases. We present an overview of recent strategies and successes in modulating splicing therapeutically in clinical and preclinical contexts. Effective approaches include restoring open reading frames, influencing alternative splicing, and inducing exon inclusion to generate beneficial proteins and remove deleterious ones.

Negative Binomial mixed models estimated with the maximum likelihood method can be used for longitudinal RNAseq data.

Time-course RNAseq experiments, where tissues are repeatedly collected from the same subjects, e.g. humans or animals over time or under several different experimental conditions, are becoming more popular due to the reducing sequencing costs. Such designs offer the great potential to identify genes that change over time or progress differently in time across experimental groups. Modelling of the longitudinal gene expression in such time-course RNAseq data is complicated by the serial correlations, missing values due to subject dropout or sequencing errors, long follow up with potentially non-linear progression in time and low number of subjects. Negative Binomial mixed models can address all these issues. However, such models under the maximum likelihood (ML) approach are less popular for RNAseq data due to convergence issues (see, e.g. [1]). We argue in this paper that it is the use of an inaccurate numerical integration method in combination with the typically small sample sizes which causes such mixed models to fail for a great portion of tested genes. We show that when we use the accurate adaptive Gaussian quadrature approach to approximate the integrals over the random-effects terms, we can successfully estimate the model parameters with the maximum likelihood method. Moreover, we show that the boostrap method can be used to preserve the type I error rate in small sample settings. We evaluate empirically the small sample properties of the test statistics and compare with state-of-the-art approaches. The method is applied on a longitudinal mice experiment to study the dynamics in Duchenne Muscular Dystrophy. Contact:s.tsonaka@lumc.nl Roula Tsonaka is an assistant professor at the Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center. Her research focuses on statistical methods for longitudinal omics data. Pietro Spitali is an assistant professor at the Department of Human Genetics, Leiden University Medical Center. His research focuses on the identification of biomarkers for neuromuscular disorders.

Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers.

BACKGROUND: Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools. METHODS: Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS). RESULTS: Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml. CONCLUSIONS: These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Premature termination codons in the DMD gene cause reduced local mRNA synthesis.

Duchenne muscular dystrophy (DMD) is caused by mutations in the DMD gene leading to the presence of premature termination codons (PTC). Previous transcriptional studies have shown reduced DMD transcript levels in DMD patient and animal model muscles when PTC are present. Nonsense-mediated decay (NMD) has been suggested to be responsible for the observed reduction, but there is no experimental evidence supporting this claim. In this study, we aimed to investigate the mechanism responsible for the drop in DMD expression levels in the presence of PTC. We observed that the inhibition of NMD does not normalize DMD gene expression in DMD. Additionally, in situ hybridization showed that DMD messenger RNA primarily localizes in the nuclear compartment, confirming that a cytoplasmic mechanism like NMD indeed cannot be responsible for the observed reduction. Sequencing of nascent RNA to explore DMD transcription dynamics revealed a lower rate of DMD transcription in patient-derived myotubes compared to healthy controls, suggesting a transcriptional mechanism involved in reduced DMD transcript levels. Chromatin immunoprecipitation in muscle showed increased levels of the repressive histone mark H3K9me3 in mdx mice compared to wild-type mice, indicating a chromatin conformation less prone to transcription in mdx mice. In line with this finding, treatment with the histone deacetylase inhibitor givinostat caused a significant increase in DMD transcript expression in mdx mice. Overall, our findings show that transcription dynamics across the DMD locus are affected by the presence of PTC, hinting at a possible epigenetic mechanism responsible for this process.

Longitudinal metabolomic analysis of plasma enables modeling disease progression in Duchenne muscular dystrophy mouse models.

Duchenne muscular dystrophy is a severe pediatric neuromuscular disorder caused by the lack of dystrophin. Identification of biomarkers is needed to support and accelerate drug development. Alterations of metabolites levels in muscle and plasma have been reported in pre-clinical and clinical cross-sectional comparisons. We present here a 7-month longitudinal study comparing plasma metabolomic data in wild-type and mdx mice. A mass spectrometry approach was used to study metabolites in up to five time points per mouse at 6, 12, 18, 24 and 30 weeks of age, providing an unprecedented in depth view of disease trajectories. A total of 106 metabolites were studied. We report a signature of 31 metabolites able to discriminate between healthy and disease at various stages of the disease, covering the acute phase of muscle degeneration and regeneration up to the deteriorating phase. We show how metabolites related to energy production and chachexia (e.g. glutamine) are affected in mdx mice plasma over time. We further show how the signature is connected to molecular targets of nutraceuticals and pharmaceutical compounds currently in development as well as to the nitric oxide synthase pathway (e.g. arginine and citrulline). Finally, we evaluate the signature in a second longitudinal study in three independent mouse models carrying 0, 1 or 2 functional copies of the dystrophin paralog utrophin. In conclusion, we report an in-depth metabolomic signature covering previously identified associations and new associations, which enables drug developers to peripherally assess the effect of drugs on the metabolic status of dystrophic mice.

Simultaneous Enrichment Analysis of all Possible Gene-sets: Unifying Self-Contained and Competitive Methods.

Studying sets of genomic features is increasingly popular in genomics, proteomics and metabolomics since analyzing at set level not only creates a natural connection to biological knowledge but also offers more statistical power. Currently, there are two gene-set testing approaches, self-contained and competitive, both of which have their advantages and disadvantages, but neither offers the final solution. We introduce simultaneous enrichment analysis (SEA), a new approach for analysis of feature sets in genomics and other omics based on a new unified null hypothesis, which includes the self-contained and competitive null hypotheses as special cases. We employ closed testing using Simes tests to test this new hypothesis. For every feature set, the proportion of active features is estimated, and a confidence bound is provided. Also, for every unified null hypotheses, a $P$-value is calculated, which is adjusted for family-wise error rate. SEA does not need to assume that the features are independent. Moreover, users are allowed to choose the feature set(s) of interest after observing the data. We develop a novel pipeline and apply it on RNA-seq data of dystrophin-deficient mdx mice, showcasing the flexibility of the method. Finally, the power properties of the method are evaluated through simulation studies.

Penalized regression calibration: A method for the prediction of survival outcomes using complex longitudinal and high-dimensional data.

Longitudinal and high-dimensional measurements have become increasingly common in biomedical research. However, methods to predict survival outcomes using covariates that are both longitudinal and high-dimensional are currently missing. In this article, we propose penalized regression calibration (PRC), a method that can be employed to predict survival in such situations. PRC comprises three modeling steps: First, the trajectories described by the longitudinal predictors are flexibly modeled through the specification of multivariate mixed effects models. Second, subject-specific summaries of the longitudinal trajectories are derived from the fitted mixed models. Third, the time to event outcome is predicted using the subject-specific summaries as covariates in a penalized Cox model. To ensure a proper internal validation of the fitted PRC models, we furthermore develop a cluster bootstrap optimism correction procedure that allows to correct for the optimistic bias of apparent measures of predictiveness. PRC and the CBOCP are implemented in the R package pencal, available from CRAN. After studying the behavior of PRC via simulations, we conclude by illustrating an application of PRC to data from an observational study that involved patients affected by Duchenne muscular dystrophy, where the goal is predict time to loss of ambulation using longitudinal blood biomarkers.

Pathway testing for longitudinal metabolomics.

We propose a top-down approach for pathway analysis of longitudinal metabolite data. We apply a score test based on a shared latent process mixed model which can identify pathways with differentially progressing metabolites. The strength of our approach is that it can handle unbalanced designs, deals with potential missing values in the longitudinal markers, and gives valid results even with small sample sizes. Contrary to bottom-up approaches, correlations between metabolites are explicitly modeled leveraging power gains. For large pathway sizes, a computationally efficient solution is proposed based on pseudo-likelihood methodology. We demonstrate the advantages of the proposed method in identification of differentially expressed pathways through simulation studies. Finally, longitudinal metabolite data from a mice experiment is analyzed to demonstrate our methodology.

Rimeporide as a first- in-class NHE-1 inhibitor: Results of a phase Ib trial in young patients with Duchenne Muscular Dystrophy.

Rimeporide, a first-in-class sodium/proton exchanger Type 1 inhibitor (NHE-1 inhibitor) is repositioned by EspeRare for patients with Duchenne Muscular Dystrophy (DMD). Historically, NHE-1 inhibitors were developed for cardiac therapeutic interventions. There is considerable overlap in the pathophysiological mechanisms in Congestive Heart Failure (CHF) and in cardiomyopathy in DMD, therefore NHE-1 inhibition could be a promising pharmacological approach to the cardiac dysfunctions observed in DMD. Extensive preclinical data was collected in various animal models including dystrophin-deficient (mdx) mice to characterise Rimeporide's anti-fibrotic and anti-inflammatory properties and there is evidence that NHE-1 inhibitors could play a significant role in modifying DMD cardiac and also skeletal pathologies, as the NHE-1 isoform is ubiquitous. We report here the first study with Rimeporide in DMD patients. This 4-week treatment, open label phase Ib, multiple oral ascending dose study, enrolled 20 ambulant boys with DMD (6-11 years), with outcomes including safety, pharmacokinetic (PK) and pharmacodynamic (PD) biomarkers. Rimeporide was safe and well-tolerated at all doses. PK evaluations showed that Rimeporide was well absorbed orally reaching pharmacological concentrations from the lowest dose, with exposure increasing linearly with dose and with no evidence of accumulation upon repeated dosing. Exploratory PD biomarkers showed positive effect upon a 4-week treatment, supporting its therapeutic potential in patients with DMD, primarily as a cardioprotective treatment, and provide rationale for further efficacy studies.

Association Study of Exon Variants in the NF-κB and TGFß Pathways Identifies CD40 as a Modifier of Duchenne Muscular Dystrophy.

The expressivity of Mendelian diseases can be influenced by factors independent from the pathogenic mutation: in Duchenne muscular dystrophy (DMD), for instance, age at loss of ambulation (LoA) varies between individuals whose DMD mutations all abolish dystrophin expression. This suggests the existence of trans-acting variants in modifier genes. Common single nucleotide polymorphisms (SNPs) in candidate genes (SPP1, encoding osteopontin, and LTBP4, encoding latent transforming growth factor ß [TGFß]-binding protein 4) have been established as DMD modifiers. We performed a genome-wide association study of age at LoA in a sub-cohort of European or European American ancestry (n = 109) from the Cooperative International Research Group Duchenne Natural History Study (CINRG-DNHS). We focused on protein-altering variants (Exome Chip) and included glucocorticoid treatment as a covariate. As expected, due to the small population size, no SNPs displayed an exome-wide significant p value (< 1.8 × 10-6). Subsequently, we prioritized 438 SNPs in the vicinities of 384 genes implicated in DMD-related pathways, i.e., the nuclear-factor-κB and TGFß pathways. The minor allele at rs1883832, in the 5'-untranslated region of CD40, was associated with earlier LoA (p = 3.5 × 10-5). This allele diminishes the expression of CD40, a co-stimulatory molecule for T cell polarization. We validated this association in multiple independent DMD cohorts (United Dystrophinopathy Project, Bio-NMD, and Padova, total n = 660), establishing this locus as a DMD modifier. This finding points to cell-mediated immunity as a relevant pathogenetic mechanism and potential therapeutic target in DMD.

Cross-sectional serum metabolomic study of multiple forms of muscular dystrophy.

Muscular dystrophies are characterized by a progressive loss of muscle tissue and/or muscle function. While metabolic alterations have been described in patients'-derived muscle biopsies, non-invasive readouts able to describe these alterations are needed in order to objectively monitor muscle condition and response to treatment targeting metabolic abnormalities. We used a metabolomic approach to study metabolites concentration in serum of patients affected by multiple forms of muscular dystrophy such as Duchenne and Becker muscular dystrophies, limb-girdle muscular dystrophies type 2A and 2B, myotonic dystrophy type 1 and facioscapulohumeral muscular dystrophy. We show that 15 metabolites involved in energy production, amino acid metabolism, testosterone metabolism and response to treatment with glucocorticoids were differentially expressed between healthy controls and Duchenne patients. Five metabolites were also able to discriminate other forms of muscular dystrophy. In particular, creatinine and the creatine/creatinine ratio were significantly associated with Duchenne patients performance as assessed by the 6-minute walk test and north star ambulatory assessment. The obtained results provide evidence that metabolomics analysis of serum samples can provide useful information regarding muscle condition and response to treatment, such as to glucocorticoids treatment.

Reduced cerebral gray matter and altered white matter in boys with Duchenne muscular dystrophy.

OBJECTIVE: Duchenne muscular dystrophy (DMD) is characterized by progressive muscle weakness caused by DMD gene mutations leading to absence of the full-length dystrophin protein in muscle. Multiple dystrophin isoforms are expressed in brain, but little is known about their function. DMD is associated with specific learning and behavioral disabilities that are more prominent in patients with mutations in the distal part of the DMD gene, predicted to affect expression of shorter protein isoforms. We used quantitative magnetic resonance (MR) imaging to study brain microstructure in DMD. METHODS: T1-weighted and diffusion tensor images were obtained on a 3T MR scanner from 30 patients and 22 age-matched controls (age = 8-18 years). All subjects underwent neuropsychological examination. Group comparisons on tissue volume and diffusion tensor imaging parameters were made between DMD patients and controls, and between 2 DMD subgroups that were classified according to predicted Dp140 isoform expression (DMD_Dp140(+) and DMD_Dp140(-) ). RESULTS: DMD patients had smaller total brain volume, smaller gray matter volume, lower white matter fractional anisotropy, and higher white matter mean and radial diffusivity than healthy controls. DMD patients also performed worse on neuropsychological examination. Subgroup analyses showed that DMD_Dp140(-) subjects contributed most to the gray matter volume differences and performed worse on information processing. INTERPRETATION: Both gray and white matter is affected in boys with DMD at a whole brain level. Differences between the DMD_Dp140(-) subgroup and controls indicate an important role for the Dp140 dystrophin isoform in cerebral development.

Validation of genetic modifiers for Duchenne muscular dystrophy: a multicentre study assessing SPP1 and LTBP4 variants.

OBJECTIVE: Duchenne muscular dystrophy (DMD) is characterised by progressive muscle weakness. It has recently been reported that single nucleotide polymorphisms (SNPs) located in the SPP1 and LTBP4 loci can account for some of the inter-individual variability observed in the clinical disease course. The validation of genetic association in large independent cohorts is a key process for rare diseases in order to qualify prognostic biomarkers and stratify patients in clinical trials. METHODS: Duchenne patients from five European neuromuscular centres were included. Information about age at wheelchair dependence and steroid use was gathered. Melting curve analysis of PCR fragments or Sanger sequencing were used to genotype SNP rs28357094 in the SPP1 gene in 336 patients. The genotype of SNPs rs2303729, rs1131620, rs1051303 and rs10880 in the LTBP4 locus was determined in 265 patients by mass spectrometry. For both loci, a multivariate analysis was performed, using genotype/haplotype, steroid use and cohort as covariates. RESULTS: We show that corticosteroid treatment and the IAAM haplotype of the LTBP4 gene are significantly associated with prolonged ambulation in patients with DMD. There was no significant association between the SNP rs28357094 in the SPP1 gene and the age of ambulation loss. CONCLUSIONS: This study underlines the importance of replicating genetic association studies for rare diseases in large independent cohorts to identify the most robust associations. We anticipate that genotyping of validated genetic associations will become important for the design and interpretation of clinical trials.

DMD transcript imbalance determines dystrophin levels.

Duchenne and Becker muscular dystrophies are caused by out-of-frame and in-frame mutations, respectively, in the dystrophin encoding DMD gene. Molecular therapies targeting the precursor-mRNA are in clinical trials and show promising results. These approaches will depend on the stability and expression levels of dystrophin mRNA in skeletal muscles and heart. We report that the DMD gene is more highly expressed in heart than in skeletal muscles, in mice and humans. The transcript mutated in the mdx mouse model shows a 5' to 3' imbalance compared with that of its wild-type counterpart and reading frame restoration via antisense-mediated exon skipping does not correct this event. We also report significant transcript instability in 22 patients with Becker dystrophy, clarifying the fact that transcript imbalance is not caused by premature nonsense mutations. Finally, we demonstrate that transcript stability, rather than transcriptional rate, is an important determinant of dystrophin protein levels in patients with Becker dystrophy. We suggest that the availability of the complete transcript is a key factor to determine protein abundance and thus will influence the outcome of mRNA-targeting therapies.

Multiomic characterization of disease progression in mice lacking dystrophin.

Duchenne muscular dystrophy (DMD) is caused by genetic mutations leading to lack of dystrophin in skeletal muscle. A better understanding of how objective biomarkers for DMD vary across subjects and over time is needed to model disease progression and response to therapy more effectively, both in pre-clinical and clinical research. We present an in-depth characterization of disease progression in 3 murine models of DMD by multiomic analysis of longitudinal trajectories between 6 and 30 weeks of age. Integration of RNA-seq, mass spectrometry-based metabolomic and lipidomic data obtained in muscle and blood samples by Multi-Omics Factor Analysis (MOFA) led to the identification of 8 latent factors that explained 78.8% of the variance in the multiomic dataset. Latent factors could discriminate dystrophic and healthy mice, as well as different time-points. MOFA enabled to connect the gene expression signature in dystrophic muscles, characterized by pro-fibrotic and energy metabolism alterations, to inflammation and lipid signatures in blood. Our results show that omic observations in blood can be directly related to skeletal muscle pathology in dystrophic muscle.

Longitudinal Assessment of Creatine Kinase, Creatine/Creatinineratio, and Myostatin as Monitoring Biomarkers in Becker Muscular Dystrophy.

BACKGROUND AND OBJECTIVES: The slow and variable disease progression of Becker muscular dystrophy (BMD) urges the development of biomarkers to facilitate clinical trials. We explored changes in 3 muscle-enriched biomarkers in serum of patients with BMD over 4-year time and studied associations with disease severity, disease progression, and dystrophin levels in BMD. METHODS: We quantitatively measured creatine kinase (CK) using the International Federation of Clinical Chemistry reference method, creatine/creatinineratio (Cr/Crn) using liquid chromatography-tandem mass spectrometry, and myostatin with ELISA in serum and assessed functional performance using the North Star Ambulatory Assessment (NSAA), 10-meter run velocity (TMRv), 6-Minute Walking Test (6MWT), and forced vital capacity in a 4-year prospective natural history study. Dystrophin levels were quantified in the tibialis anterior muscle using capillary Western immunoassay. The correlation between biomarkers, age, functional performance, mean annual change, and prediction of concurrent functional performance was analyzed using linear mixed models. RESULTS: Thirty-four patients with 106 visits were included. Eight patients were nonambulant at baseline. Cr/Crn and myostatin were highly patient specific (intraclass correlation coefficient for both = 0.960). Cr/Crn was strongly negatively correlated, whereas myostatin was strongly positively correlated with the NSAA, TMRv, and 6MWT (Cr/Crn rho = -0.869 to -0.801 and myostatin rho = 0.792 to 0.842, all p < 0.001). CK showed a negative association with age (p = 0.0002) but was not associated with patients' performance. Cr/Crn and myostatin correlated moderately with the average annual change of the 6MWT (rho = -0.532 and 0.555, p = 0.02). Dystrophin levels did not correlate with the selected biomarkers nor with performance. Cr/Crn, myostatin, and age could explain up to 75% of the variance of concurrent functional performance of the NSAA, TMRv, and 6MWT. DISCUSSION: Both Cr/Crn and myostatin could potentially serve as monitoring biomarkers in BMD, as higher Cr/Crn and lower myostatin were associated with lower motor performance and predictive of concurrent functional performance when combined with age. Future studies are needed to more precisely determine the context of use of these biomarkers.

Diffusion-tensor magnetic resonance imaging captures increased skeletal muscle fibre diameters in Becker muscular dystrophy.

BACKGROUND: Becker muscular dystrophy (BMD) is an X-linked disorder characterized by slow, progressive muscle damage and muscle weakness. Hallmarks include fibre-size variation and replacement of skeletal muscle with fibrous and adipose tissues, after repeated cycles of regeneration. Muscle histology can detect these features, but the required biopsies are invasive, are difficult to repeat and capture only small muscle volumes. Diffusion-tensor magnetic resonance imaging (DT-MRI) is a potential non-invasive alternative that can calculate muscle fibre diameters when applied with the novel random permeable barrier model (RPBM). In this study, we assessed muscle fibre diameters using DT-MRI in BMD patients and healthy controls and compared these with histology. METHODS: We included 13 BMD patients and 9 age-matched controls, who underwent water-fat MRI and DT-MRI at multiple diffusion times, allowing RPBM parameter estimation in the lower leg muscles. Tibialis anterior muscle biopsies were taken from the contralateral leg in 6 BMD patients who underwent DT-MRI and from an additional 32 BMD patients and 15 healthy controls. Laminin and Sirius-red stainings were performed to evaluate muscle fibre morphology and fibrosis. Twelve ambulant patients from the MRI cohort underwent the North Star ambulatory assessment, and 6-min walk, rise-from-floor and 10-m run/walk functional tests. RESULTS: RPBM fibre diameter was significantly larger in BMD patients (P = 0.015): mean (SD) = 68.0 (25.3) µm versus 59.4 (19.2) µm in controls. Inter-muscle differences were also observed (P ≤ 0.002). Both inter- and intra-individual RPBM fibre diameter variability were similar between groups. Laminin staining agreed with the RPBM, showing larger median fibre diameters in patients than in controls: 72.5 (7.9) versus 63.2 (6.9) µm, P = 0.006. However, despite showing similar inter-individual variation, patients showed more intra-individual fibre diameter variability than controls-mean variance (SD) = 34.2 (7.9) versus 21.4 (6.9) µm, P < 0.001-and larger fibrosis areas: median (interquartile range) = 21.7 (5.6)% versus 14.9 (3.4)%, P < 0.001. Despite good overall agreement of RPBM and laminin fibre diameters, they were not associated in patients who underwent DT-MRI and muscle biopsy, perhaps due to lack of colocalization of DT-MRI with biopsy samples. CONCLUSIONS: DT-MRI RPBM metrics agree with histology and can quantify changes in muscle fibre size that are associated with regeneration without the need for biopsies. They therefore show promise as imaging biomarkers for muscular dystrophies.

The absence of dystrophin brain isoform expression in healthy human heart ventricles explains the pathogenesis of 5' X-linked dilated cardiomyopathy.

BACKGROUND: In X-linked dilated cardiomyopathy due to dystrophin mutations which abolish the expression of the M isoform (5'-XLDC), the skeletal muscle is spared through the up-regulation of the Brain (B) isoform, a compensatory mechanism that does not appear to occur in the heart of affected individuals. METHODS: We quantitatively studied the expression topography of both B and M isoforms in various human heart regions through in-situ RNA hybridization, Reverse-Transcriptase and Real-Time PCR experiments. We also investigated the methylation profile of the B promoter region in the heart and quantified the B isoform up regulation in the skeletal muscle of two 5'-XLDC patients. RESULTS: Unlike the M isoform, consistently detectable in all the heart regions, the B isoform was selectively expressed in atrial cardiomyocytes, but absent in ventricles and in conduction system structures. Although the level of B isoform messenger in the skeletal muscle of 5'-XLDC patients was lower that of the M messenger present in control muscle, it seems sufficient to avoid an overt muscle pathology. This result is consistent with the protein level in XLDC patients muscles we previously quantified. Methylation studies revealed that the B promoter shows an overall low level of methylation at the CG dinucleotides in both atria and ventricles, suggesting a methylation-independent regulation of the B promoter activity. CONCLUSIONS: The ventricular dilatation seen in 5'-XLDC patients appears to be functionally related to loss of the M isoform, the only isoform transcribed in human ventricles; in contrast, the B isoform is well expressed in heart but confined to the atria. Since the B isoform can functionally replace the M isoform in the skeletal muscle, its expression in the heart could potentially exert the same rescue function. Methylation status does not seem to play a role in the differential B promoter activity in atria and ventricles, which may be governed by other regulatory mechanisms. If these mechanisms could be deduced, de-silencing of the B isoform may represent a therapeutic strategy in 5'-XLDC patients.

Histone deacetylase inhibitors improve antisense-mediated exon-skipping efficacy in mdx mice.

Antisense-mediated exon skipping is one of the most promising therapeutic strategies for Duchenne muscular dystrophy (DMD), and some antisense oligonucleotide (ASO) drugs have already been approved by the US FDA despite their low efficacy. The potential of this therapy is still limited by several challenges, including the reduced expression of the dystrophin transcript and the strong 5'-3' imbalance in mutated transcripts. We therefore hypothesize that increasing histone acetylation using histone deacetylase inhibitors (HDACi) could correct the transcript imbalance, offering more available pre-mRNA target and ultimately increasing dystrophin rescue. Here, we evaluated the impact of such a combined therapy on the Dmd transcript imbalance phenomenon and on dystrophin restoration levels in mdx mice. Analysis of the Dmd transcript levels at different exon-exon junctions revealed a tendency to correct the 5'-3' imbalance phenomenon following treatment with HDACi. Significantly higher levels of dystrophin restoration (up to 74% increase) were obtained with givinostat and valproic acid compared with mice treated with ASO alone. Additionally, we demonstrate an increase in H3K9 acetylation in human myocytes after treatment with valproic acid. These findings indicate that HDACi can improve the therapeutic potential of exon-skipping approaches, offering promising perspectives for the treatment of DMD.

Value of Global Longitudinal Strain for Identification and Monitoring of Left Ventricular Dysfunction in Becker Muscular Dystrophy.

Cardiac involvement is the main cause of death in Becker muscular dystrophy (BMD). Identification of left ventricular (LV) function is crucial, but standard echocardiographic measurements such as LV ejection fraction (LVEF) might not be sensitive enough to detect early myocardial dysfunction. We explored the value of LV global longitudinal strain (GLS) as a more accurate echocardiographic parameter to detect and monitor LV dysfunction in BMD. Furthermore, we studied possible factors associated with LV dysfunction and progression. A total of 40 patients with BMD (age 39.0 ± 13.2 years) and 21 matched controls were included. Clinical variables, pulmonary tests, serum biomarkers, and echocardiograms were collected at baseline and after 2 years. LV systolic function was assessed by LVEF and LV GLS; a significant progression in LV dysfunction was defined as an absolute LV GLS deterioration ≥15%. Responsiveness to cardiac disease progression was determined using standardized response means. Patients showed impaired LVEF and LV GLS compared with controls (p <0.001). Of interest, 31 patients (77.5%) showed impaired LV GLS (defined as greater than -18%), whereas only 24 patients (60%) had reduced LVEF. LV GLS and LVEF correlated with troponin I (ρ = 0.553 and -0.523) and N-terminal pro-b-type natriuretic peptide (ρ = 0.506 and -0.585), but not with skeletal muscle or pulmonary function. At follow-up (2.0 ± 0.5 years, n = 29), LV GLS worsened significantly (-1.3 ± 0.8%, p = 0.002, standardized response mean = 0.70, annually = 0.60%), whereas LVEF remained stable. No risk factors for LV dysfunction progression were identified. In BMD, LV GLS is frequently impaired and shows deterioration over time compared with LVEF. LV GLS could be used as a more sensitive parameter to identify and monitor LV dysfunction.