AUTHOR=Manjunath Usha , R Venkatesh , Kulkarni Sacheta Sudhendra , Reddy Harshatha N. , Anil Anupama , Mishra Rakesh Kumar , Iyer Gayatri Rangarajan 

TITLE=NMPhenogen: a comprehensive database for genotype–phenotype correlation in neuromuscular genetic disorders

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 19 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1696899

DOI=10.3389/fnins.2025.1696899

ISSN=1662-453X

ABSTRACT=Neuromuscular genetic disorders (NMGDs) are genetically and clinically diverse group of inherited diseases that affect approximately 1 in 1,000 people worldwide with a calculated prevalence of 37 per 10,000 in the general population. These disorders arise from a variety of genetic changes such as insertions, deletions, duplications and expansions of repeats in more than 747 nuclear and mitochondrial genes critical for the function of peripheral nerves, motor neurons, neuromuscular junctions or skeletal muscles, leading to progressive weakness and degeneration of muscles. Major subtypes include muscular dystrophies, congenital myopathies, motor neuron diseases, peripheral neuropathies, and mitochondrial myopathies. Clinical presentation of NMGDs is highly variable in the age of onset, severity and pattern of muscle involvement, often leading to prolonged and complex diagnostic process. Conventional diagnostic methods have relied on clinical history, physical examination and invasive procedures like muscle biopsy. But the development of next-generation sequencing (NGS) has transformed diagnostics by enabling comprehensive analysis of NMGD-related genes. Despite this advancement, interpreting the numerous variants identified by NGS remains challenging. The guidelines of the American College of Medical Genetics and Genomics (ACMG) offer a standardized approach to variant classification as pathogenic, likely pathogenic, variant of uncertain significance, likely benign and benign. However, this requires the integration of complex evidence from population data, computational predictions, and functional assays. The major challenge is the robust correlation of genotypic information with the huge phenotypic range of NMGDs which is a task complicated by the unavailability of population-specific genetic databases. To address these issues, we have developed NMPhenogen (https://gi-lab-tigs.github.io/Homepage/), a new database designed to enhance the diagnosis and understanding of NMGDs. NMPhenogen is a centralized repository for data related to NMGD-associated genes and variants along with their clinical presentations. It includes two primary modules: NMPhenoscore, which enhances disease-phenotype correlations, and a Variant classifier, which facilitates standardized variant classification based on published guidelines. This combined resource aims to streamline the diagnostic process, support clinical decision-making, and eventually contribute to improving patient care and genetic counseling.