Meta-analysis of muscle transcriptome data using the MADMuscle database reveals biologically relevant gene patterns

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc.</p> <p>Description</p> <p>We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (<it>Drosophila melanogaster, Caenorhabditis elegans</it>) and vertebrates (<it>Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus</it>). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies.</p> <p>Conclusions</p> <p>Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.</p

Electrodiagnostic subtyping in Guillain–Barr\ue9 syndrome patients in the International Guillain–Barr\ue9 Outcome Study

\ua9 2024 The Authors. European Journal of Neurology published by John Wiley &amp; Sons Ltd on behalf of European Academy of Neurology.Background and purpose: Various electrodiagnostic criteria have been developed in Guillain–Barr\ue9 syndrome (GBS). Their performance in a broad representation of GBS patients has not been evaluated. Motor conduction data from the International GBS Outcome Study (IGOS) cohort were used to compare two widely used criterion sets and relate these to diagnostic amyotrophic lateral sclerosis criteria. Methods: From the first 1500 patients in IGOS, nerve conduction studies from 1137 (75.8%) were available for the current study. These patients were classified according to nerve conduction studies criteria proposed by Hadden and Rajabally. Results: Of the 1137 studies, 68.3% (N = 777) were classified identically according to criteria by Hadden and Rajabally: 111 (9.8%) axonal, 366 (32.2%) demyelinating, 195 (17.2%) equivocal, 35 (3.1%) inexcitable and 70 (6.2%) normal. Thus, 360 studies (31.7%) were classified differently. The areas of differences were as follows: 155 studies (13.6%) classified as demyelinating by Hadden and axonal by Rajabally; 122 studies (10.7%) classified as demyelinating by Hadden and equivocal by Rajabally; and 75 studies (6.6%) classified as equivocal by Hadden and axonal by Rajabally. Due to more strictly defined cutoffs fewer patients fulfilled demyelinating criteria by Rajabally than by Hadden, making more patients eligible for axonal or equivocal classification by Rajabally. In 234 (68.6%) axonal studies by Rajabally the revised El Escorial (amyotrophic lateral sclerosis) criteria were fulfilled; in axonal cases by Hadden this was 1.8%. Conclusions and discussion: This study shows that electrodiagnosis in GBS is dependent on the criterion set utilized, both of which are based on expert opinion. Reappraisal of electrodiagnostic subtyping in GBS is warranted