Precision Medicine for Rare Diseases: Classifying Patients with Limb-Girdle Muscular Dystrophy Aimed in Proposing Applicable Therapeutic Strategies for Each Subtype

Precision Medicine for Rare Diseases: Classifying Patients with Limb-Girdle Muscular Dystrophy Aimed in Proposing Applicable Therapeutic Strategies for Each Subtype
Mohammad Hossein Afsharinia,^1,* Javad Zahiri,² Masoud Garshasbi,³
1. Department of Biophysics, Bioinformatics and Computational Omics Lab (BioCOOL), Faculty of Biological Sciences, Tarbiat Modares University
2. Department of Biophysics, Bioinformatics and Computational Omics Lab (BioCOOL), Faculty of Biological Sciences, Tarbiat Modares University
3. Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University
Introduction: Since therapeutic approaches are rarely developed for single individuals, it is necessary to assign each drug or therapeutic strategy to a subgroup of patients. Precision medicine (PM), also known as personalized medicine, refers to the understanding diseases at a deeper level in order to develop more targeted therapies. Herein, we demonstrated how PM can be beneficial for patients with “Limb-Girdle Muscular Dystrophy” (LGMD). LGMD belongs to a heterogeneous group of diseases called Muscular dystrophies which are characterized by progressive muscle wasting. There are 9 major types of muscular dystrophy, all of which cause muscle weakness, but the areas affected and the severity of the symptoms are different. Among these various types, Duchenne is the most common, and limb-girdle is the most heterogeneous disease with more than 30 subtypes depending on the different genes involved. LGMD is caused by mutations leading to the abnormal protein synthesis in the various parts of the muscle fiber including the nucleus, sarcoplasm, sarcomere, sarcolemma, and extracellular matrix. In this project we aimed to classify patients with each subtype of limb-girdle, based on more detailed aspects such as mutation types, in order to propose applicable therapeutic approaches.
Methods: At first, we searched literature using the “Limb-Girdle Muscular Dystrophy” or “LGMD” keywords in Pubmed database. Totally, 1725 article were identified. Then we extracted potential therapeutic approaches from these articles. These data were subsequently categorized into 3 main therapeutic strategies: 1- Pharmacological approach 2- Antisense Therapy 3- Genome-Based Therapy Then we designed an algorithm based on different rules from each categories as an eligibility criteria to check whether an individual with a specific mutation in a specific gene, is a potential candidate for receiving any of these three therapeutic strategies. Additionally, we employed machine learning models based on the variants have been annotated in ClinVar database to predict the pathogenicity outcome of all variants cataloged in dbSNP. The algorithm for predicting proper therapeutic strategy was applied on all those variants predicted to be pathogenic.
Results: By applying our machine learning algorithm on all the variants reported in dbSNP for all the genes known so far for LGMD, we could determine potential pathogenic variants. Using our algorithm to predict proper therapeutic approaches we could propose appropriate strategies such as using glucocorticoids, anti-myostatin drugs, ASOs to target mRNA aimed in exon/multi-exon skipping and viral vectors for precise gene-delivery for these variants. Some of the variants had more than one predicted approaches.
Conclusion: Due to high attrition rates, substantial costs and slow pace of new drug discovery or therapeutic strategy development, repurposing of old drugs and available therapeutic strategies is essential to treat diseases. On the other hand, despite necessity for investment in the development of treatments for people with rare disorders, the rarity of diseases makes them less attractive for pharmaceuticals. About a heterogeneous condition like limb-girdle muscular dystrophy it is even more difficult to find a cure for patients. Although not many studies have been performed on each subtype of LGMD, but various drugs and strategies have been proposed for this disease. We have classified LGMD patients to different subgroups that have differential features and treatment implications based on their mutation types in order to propose applicable therapeutic strategies for each subtype. This brings us closer to the treating and managing more LGMD patients.
Keywords: Precision medicine, LGMD, muscular dystrophy, classification, variant