Clinical Genomic, phenotype and epigenetic insights into the pathology, autoimmunity and weight management of patients with Myasthenia Gravis (Review).

Myasthenia Gravis (MG) is an autoimmune disease that affects neuromuscular junctions and is characterized by muscle weakness as a result of autoantibodies against certain proteins. As a heterogeneous disorder, MG presents with different types, including neonatal, ocular and generalized in both juveniles and adults. Different types of antibodies serve a role in how MG presents. The main biological characteristic of MG is the production of antibodies against the muscular acetylcholine receptor; however, other types of antibody have been associated with the disorder. The role of the thymus gland has been established and thymectomy is a possible treatment of the disease, along with traditional medication such as pyridostigmine bromide (Mestinon) and immunosuppresants. In recent years, steps have been made towards developing more sensitive diagnostic methods. Additionally, novel treatments have demonstrated promising results. Developing new assays may lead to an increased understanding of the disease and to unravelling the genetic pathway that leads to the development of neuromuscular diseases.

Demetra Application: An integrated genotype analysis web server for clinical genomics in endometriosis.

Demetra Application is a holistic integrated and scalable bioinformatics web­based tool designed to assist medical experts and researchers in the process of diagnosing endometriosis. The application identifies the most prominent gene variants and single nucleotide polymorphisms (SNPs) causing endometriosis using the genomic data provided for the patient by a medical expert. The present study analyzed >28.000 endometriosis­related publications using data mining and semantic techniques aimed towards extracting the endometriosis­related genes and SNPs. The extracted knowledge was filtered, evaluated, annotated, classified, and stored in the Demetra Application Database (DAD). Moreover, an updated gene regulatory network with the genes implements in endometriosis was established. This was followed by the design and development of the Demetra Application, in which the generated datasets and results were included. The application was tested and presented herein with whole­exome sequencing data from seven related patients with endometriosis. Endometriosis­related SNPs and variants identified in genome­wide association studies (GWAS), whole­genome (WGS), whole­exome (WES), or targeted sequencing information were classified, annotated and analyzed in a consolidated patient profile with clinical significance information. Probable genes associated with the patient's genomic profile were visualized using several graphs, including chromosome ideograms, statistic bars and regulatory networks through data mining studies with relative publications, in an effort to obtain a representative number of the most credible candidate genes and biological pathways associated with endometriosis. An evaluation analysis was performed on seven patients from a three­generation family with endometriosis. All the recognized gene variants that were previously considered to be associated with endometriosis were properly identified in the output profile per patient, and by comparing the results, novel findings emerged. This novel and accessible webserver tool of endometriosis to assist medical experts in the clinical genomics and precision medicine procedure is available at http://geneticslab.aua.gr/.