PROJECT SUMMARY/ABSTRACT This NIH K23 proposal details a comprehensive five-year training plan for mentored patient-oriented research career development and research to address a major problem in neuromuscular medicine. Over half of patients with clinically suspected Mendelian myopathies do not have a molecular diagnosis, largely due to two challenges: detecting pathogenic non-coding variants, and resolving the pathogenicity of ultra-rare missense variants. Here I propose to address this challenge through the application of genome sequencing (Aim 1), transcriptome sequencing (Aim 2), and proteomic (Aim 3) methods to evaluate the strengths and weakness of each method and to improve the diagnostic yield from a cohort of approximately 200 individuals with unsolved Mendelian myopathies. I hypothesize that since the genetic architecture of Mendelian myopathies implicates large genes that genome sequencing combined with RNA-sequencing (RNA-seq) and proteomics can mitigate the current low diagnostic yield after clinical evaluation of Mendelian myopathies. Through these approaches, I will define best practices in applying technologies in the diagnostic evaluation, discover novel disease variants and genes, and expand our understanding of the genetic architecture of these heterogeneous disorders. Gaining the analytical skills to evaluate the real-world application of multiomic methods will complement both my prior expertise in gene discovery for neurologic disorders and my clinical training in neuromuscular medicine. I am uniquely positioned within the collaborative environment between Brigham and Women’s Hospital, Boston Children’s Hospital, Broad Institute, and Harvard Medical School to facilitate my transition to an independent physician-scientist with a long-term translational research goal of developing a center of excellence in the clinical characterization, molecular diagnosis, and evaluation of targeted gene therapy candidates for patients with Mendelian myopathies.

PROJECT NARRATIVE With clinically-available genetic testing, the majority of patients with suspected monogenic muscle diseases lack a genetic diagnosis which impedes medical management. The goal of this project is to develop best practices for combined analysis of genome (DNA), transcriptome (RNA), and proteome (protein) research technologies to identify novel variants and genes and improve the diagnostic yield for patients with muscle disease.