The primary cause of Duchenne muscular dystrophy (DMD) is a mutation in the dystrophin gene leading to the absence of the corresponding RNA transcript and protein. Absence of dystrophin leads to disruption of the dystrophin-associated protein complex and substantial changes in skeletal muscle pathology. Although the histological pathology of dystrophic tissue has been well documented, the underlying molecular pathways remain poorly understood. To examine the pathogenic pathways and identify new or modifying factors involved in muscular dystrophy, expression microarrays were used to compare individual gene expression profiles of skeletal muscle biopsies from 12 DMD patients and 12 unaffected control patients. Two separate statistical analysis methods were used to interpret the resulting data: t test analysis to determine the statistical significance of differential expression and geometric fold change analysis to determine the extent of differential expression. These analyses identified 105 genes that differ significantly in expression level between unaffected and DMD muscle. Many of the differentially expressed genes reflect changes in histological pathology. For instance, immune response signals and extracellular matrix genes are overexpressed in DMD muscle, an indication of the infiltration of inflammatory cells and connective tissue. Significantly more genes are overexpressed than are underexpressed in dystrophic muscle, with dystrophin underexpressed, whereas other genes encoding muscle structure and regeneration processes are overexpressed, reflecting the regenerative nature of the disease.

Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad selection of data sets from the Microarray Quality Control Phase II (MAQC-II) effort, generated on three microarray platforms with different causes of batch effects to assess the efficacy of their removal. Two data sets from cross-tissue and cross-platform experiments are also included. Of the 120 cases studied using Support vector machines (SVM) and K nearest neighbors (KNN) as classifiers and Matthews correlation coefficient (MCC) as performance metric, we find that Ratio-G, Ratio-A, EJLR, mean-centering and standardization methods perform better or equivalent to no batch effect removal in 89, 85, 83, 79 and 75% of the cases, respectively, suggesting that the application of these methods is generally advisable and ratio-based methods are preferred.

Skeletal muscle contraction is triggered by the excitation-contraction (E-C) coupling machinery residing at the triad, a membrane structure formed by the juxtaposition of T-tubules and sarcoplasmic reticulum (SR) cisternae. The formation and maintenance of this structure is key for muscle function but is not well characterized. We have investigated the mechanisms leading to X-linked myotubular myopathy (XLMTM), a severe congenital disorder due to loss of function mutations in the MTM1 gene, encoding myotubularin, a phosphoinositide phosphatase thought to have a role in plasma membrane homeostasis and endocytosis. Using a mouse model of the disease, we report that Mtm1 -deficient muscle fibers have a decreased number of triads and abnormal longitudinally oriented T-tubules. In addition, SR Ca ²⁺ release elicited by voltage-clamp depolarizations is strongly depressed in myotubularin-deficient muscle fibers, with myoplasmic Ca ²⁺ removal and SR Ca ²⁺ content essentially unaffected. At the molecular level, Mtm1 -deficient myofibers exhibit a 3-fold reduction in type 1 ryanodine receptor (RyR1) protein level. These data reveal a critical role of myotubularin in the proper organization and function of the E-C coupling machinery and strongly suggest that defective RyR1-mediated SR Ca ²⁺ release is responsible for the failure of muscle function in myotubular myopathy.

To describe the use of large-scale gene expression profiles to distinguish broad categories of myopathy and subtypes of inflammatory myopathies (IM) and to provide insight into the pathogenesis of inclusion body myositis (IBM), polymyositis, and dermatomyositis. Using Affymetrix GeneChip microarrays, the authors measured the simultaneous expression of approximately 10,000 genes in muscle specimens from 45 patients in four major disease categories (dystrophy, congenital myopathy, inflammatory myopathy, and normal). The authors separately analyzed gene expression in 14 patients limited to the three major subtypes of IM. Bioinformatics techniques were used to classify specimens with similar expression profiles based on global patterns of gene expression and to identify genes with significant differential gene expression compared with normal. Ten of 11 patients with IM, all normals and nemaline myopathies, and 10 of 12 patients with Duchenne muscular dystrophy were correctly classified by this approach. The various subtypes of inflammatory myopathies have distinct gene expression signatures. Specific sets of immune-related genes allow for molecular classification of patients with IBM, polymyositis, and dermatomyositis. Analysis of differential gene expression identifies as relevant to disease pathogenesis previously reported cytokines, major histocompatibility complex class I and II molecules, granzymes, and adhesion molecules, as well as newly identified members of these categories. Increased expression of actin cytoskeleton genes is also identified. The molecular profiles of muscle tissue in patients with inflammatory myopathies are distinct and represent molecular signatures from which diagnostic insight may follow. Large numbers of differentially expressed genes are rapidly identified.