Dr. Kiran Polavarapu is a clinician (MBBS, Bachelor of Medicine and Bachelor of Surgery) who shifted his focus to research in genomics of neuromuscular disorders (NMDs) and neurogenetics. He completed PhD in 2019 along with residency in neurology at the National Institute of Mental Health and Neurosciences (NIMHANS), India, where his doctoral work focused on NGS-based diagnostics and genotype-phenotype correlations in Duchenne muscular dystrophy (DMD) and other NMDs. After five years as a postdoctoral fellow in the Lochmüller Lab, Dr Polavarapu was appointed to his first independent academic position as Scientist at the CHEO Research Institute in January 2026.
Dr. Polavarapu has extensive expertise in neuromuscular genetics, deep clinical phenotyping, and advanced genomic and bioinformatic analysis. He has contributed to the analysis of more than 3,000 neuromuscular disease families, helping establish over 1,000 genetic diagnoses, and was actively involved in multidisciplinary neuromuscular clinics. Prior to joining CHEO RI, he also worked as a clinical geneticist in a high-throughput genetic diagnostics laboratory, leading genome analysis teams and gaining industry-level experience in variant analysis, interpretation and quality control.
As a postdoctoral fellow at CHEO RI, Dr. Polavarapu held a CIHR Postdoctoral Fellowship and played a key role in international rare disease initiatives, including the pan-European Solve-RD consortium. His independent research program integrates deep phenotyping, genomics and transcriptomics, and functional validation to improve diagnostic yield, enable novel gene discovery, and develop open-source variant interpretation workflows for inherited neuromuscular disorders, including multisystem brain-heart-muscle phenotypes.
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Research Projects
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Genomic Reanalysis of a Pan-European Rare Disease Resource Yields New Diagnoses
17/01/2025
The purpose of this work is to address the persistent diagnostic gap in rare diseases by systematically reanalyzing existing exome and genome sequencing data from undiagnosed individuals across Europe. Leveraging the pan-European infrastructure of the Solve-RD project and the expertise of multiple European Reference Networks (ERNs), this study aims to improve molecular diagnostic rates through large-scale, standardized reanalysis that integrates updated genomic knowledge, enhanced bioinformatic methods, and structured phenotype and pedigree data. This study demonstrates the value of coordinated, large-scale reanalysis of genomic data in improving genetic diagnoses for individuals affected by rare diseases. By systematically reanalyzing data from 6,004 previously undiagnosed rare-disease families, Solve-RD provides evidence that diagnostic yield can be increased without additional sequencing, instead through improved interpretation and collaboration. The resulting dataset represents a significant resource for the global rare-disease research community and highlights the importance of sustained data sharing, multidisciplinary expertise, and European-wide collaboration to advance rare-disease diagnosis and care.