Neurological and muscular disorders (NMDs) exhibit profound clinical and genetic heterogeneity, leading to diagnostic delays, prognostic uncertainty, and a lack of effective therapies. A significant fraction of patients lacks a genetic diagnosis, and the biological mechanisms driving variable expressivity in known mutation carriers remain poorly understood.
This project aims to address these challenges by:
1. Enhancing Genetic Diagnosis: Uncover novel disease-associated genes and variants in undiagnosed NMD patients through whole-exome/genome sequencing and advanced bioinformatic pipelines.
2. Mapping the Phenotypic Landscape: Systematically define the clinical spectrum of specific NMDs using deep phenotyping, including neuroimaging, electrophysiological studies, and quantitative muscle function assessments.
3. Discovering Biomarkers: Identify and validate molecular biomarkers (e.g., proteomic, metabolomic, and transcriptomic signatures in biofluids) that correlate with diagnosis, disease subtypes, and progression rates.
4. Elucidating Modifiers: Investigate genetic modifiers and environmental factors that influence age of onset, severity, and penetrance using integrated genomic and clinical data.
We will employ a multi-omics approach, combining genomic, transcriptomic, and proteomic data from well-characterized patient cohorts. Statistical and machine learning methods will be used to integrate these datasets, identify predictive biomarkers, and stratify patients into molecularly defined subgroups.
The ultimate goal is to improve diagnostic yield, unravel underlying pathomechanisms, identify targets for therapeutic intervention, and develop tools for patient stratification and monitoring in clinical trials.
