Centre-based landscape of muscular dystrophies in Gujarat: insight into genetic diagnosis and management

DNA, RNA, or protein errors can lead to globally prevalent genetic disorders, though precise rates are difficult to determine due to underreporting. In India, the burden is intensified by a large population, consanguineous marriages, and high genetic diversity; Gujarat also faces challenges in reporting rare genetic disorders. Population-based OMIC studies are needed, but progress is slow due to the time, cost, and effort. In light of this, muscular dystrophies (MDs) are rare neuromuscular diseases characterized by progressive muscle degradation, weakness, cardiac and respiratory issues, and loss of ambulation. Most MDs are caused by disruptions in the dystrophin-glycoprotein complex (DGC), which is crucial for skeletal muscle fibre integrity. This study aims to investigate the clinical manifestations, epidemiology, and genetic variants associated with MDs. Additionally, it seeks to evaluate current diagnostic approaches to improve early detection and inform targeted therapeutic strategies. This study was conducted at the Indian Muscular Dystrophy Society (IMDS) and Research Center in Ahmedabad, Gujarat, India, in a cohort of 511 participants. Clinical evaluations and advanced genetic testing, including multiplex polymerase chain reaction (MPCR), multiplex ligation-dependent probe amplification (MLPA), and next-generation sequencing (NGS), were employed to identify and classify genetic variants. This cohort included various MDs such as Duchenne muscular dystrophy (DMD), Becker muscular dystrophy (BMD), limb-girdle muscular dystrophy (LGMD), and congenital muscular dystrophy (CMD). Our findings revealed that DMD was the most prevalent, with 393 cases, followed by other types. Genetic analysis identified 235 pathogenic variants in MDs, including exonic deletions, duplications, and point variants. This study sheds light on the genetic landscape of MDs in Gujarat, advocating for the importance of comprehensive genetic screening for accurate diagnosis and management of MDs. This meta-analysis could help reduce the burden of MDs by emphasizing the need for early diagnosis, personalized treatment, and informed family planning, thereby improving patient outcomes and quality of life (QoL).