Large scale serum proteomics identifies proteins associated with performance decline and clinical milestones in Duchenne muscular dystrophy.

Serum biomarkers are promising minimally invasive outcome measures in clinical studies in Duchenne muscular dystrophy (DMD). However, biomarkers strongly associated with clinical progression and predicting performance decline are lacking. In this study we aimed to identify serum biomarkers associated with clinical performance and able to predict clinical milestones in DMD.

Spatial transcriptomics reveal markers of histopathological changes in Duchenne muscular dystrophy mouse models.

Duchenne muscular dystrophy is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to developing effective therapies.

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.

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.

The neurocognitive profile of adults with Becker muscular dystrophy in the Netherlands.

Background: In Becker muscular dystrophy evidence for neurocognitive and behavioral comorbidity is evolving. More insight into the extend of these problems is of great importance for early detection and remediation in clinical practice.

Objective: In this study we aimed to describe the neurocognitive and behavioral features of a Dutch adult cohort of BMD patients, and to evaluate correlations to motor function outcomes.

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.

Plasma lipidomic analysis shows a disease progression signature in mdx mice.

Duchenne muscular dystrophy (DMD) is a rare genetic disorder affecting paediatric patients. The disease course is characterized by loss of muscle mass, which is rapidly substituted by fibrotic and adipose tissue. Clinical and preclinical models have clarified the processes leading to muscle damage and myofiber degeneration.

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.

Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients.

DMD is a rare disorder characterized by progressive muscle degeneration and premature death. Therapy development is delayed by difficulties to monitor efficacy non-invasively in clinical trials. In this study, we used RNA-sequencing to describe the pathophysiological changes in skeletal muscle of 3 dystrophic mouse models.

Low dystrophin variability between muscles and stable expression over time in Becker muscular dystrophy using capillary Western immunoassay.

Becker muscular dystrophy (BMD) is the milder allelic variant of Duchenne muscular dystrophy, with higher dystrophin levels. To anticipate on results of interventions targeting dystrophin expression it is important to know the natural variation of dystrophin expression between different muscles and over time. Dystrophin was quantified using capillary Western immunoassay (Wes) in the anterior tibial (TA) muscle of 37 BMD patients.

The mRNA Binding Proteome of Proliferating and Differentiated Muscle Cells.

Muscle formation is a coordinated process driven by extensive gene expression changes where single cells fuse together to form multinucleated muscle fibers. Newly synthesized mRNAs are then regulated by RNA binding proteins (RBPs), affecting post-transcriptional transcript metabolism. Here, we determined how large-scale gene expression changes affect the catalog of RBPs by studying proliferating and differentiated muscle cells in healthy and dystrophic conditions.

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.

Evaluation of blood gene expression levels in facioscapulohumeral muscular dystrophy patients.

Facioscapulohumeral muscular dystrophy (FSHD) is caused by the expression of DUX4 in skeletal muscles. A number of therapeutic approaches are being developed to antagonize the events preceding and following DUX4 expression that leads to muscular dystrophy. Currently, the possibility to evaluate treatment response in clinical trials is hampered by the lack of objective molecular biomarkers connecting the disease cause to clinical performance.

Tumor Necrosis Factor Receptor SF10A (TNFRSF10A) SNPs Correlate With Corticosteroid Response in Duchenne Muscular Dystrophy.

Background: Duchenne muscular dystrophy (DMD) is a rare and severe X-linked muscular dystrophy in which the standard of care with variable outcome, also due to different drug response, is chronic off-label treatment with corticosteroids (CS). In order to search for SNP biomarkers for corticosteroid responsiveness, we genotyped variants across 205 DMD-related genes in patients with differential response to steroid treatment.

Methods And Findings: We enrolled a total of 228 DMD patients with identified dystrophin mutations, 78 of these patients have been under corticosteroid treatment for at least 5 years.

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.

Blood-derived biomarkers correlate with clinical progression in Duchenne muscular dystrophy.

Background: Duchenne Muscular Dystrophy is a severe, incurable disorder caused by mutations in the dystrophin gene. The disease is characterized by decreased muscle function, impaired muscle regeneration and increased inflammation. In a clinical context, muscle deterioration, is evaluated using physical tests and analysis of muscle biopsies, which fail to accurately monitor the disease progression.

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.

TCTEX1D1 is a genetic modifier of disease progression in Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is caused by pathogenic variants in the DMD gene leading to the lack of dystrophin. Variability in the disease course suggests that other factors influence disease progression. With this study we aimed to identify genetic factors that may account for some of the variability in the clinical presentation.

Longitudinal serum biomarker screening identifies malate dehydrogenase 2 as candidate prognostic biomarker for Duchenne muscular dystrophy.

Background: Duchenne muscular dystrophy (DMD) is a fatal disease for which no cure is available. Clinical trials have shown to be largely underpowered due to inter-individual variability and noisy outcome measures. The availability of biomarkers able to anticipate clinical benefit is highly needed to improve clinical trial design and facilitate drug development.

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.