Projects

Project 1: Improving the Diagnostic Yield of Dystonia in Indian Patients Using Short- and Long-Read Sequencing Technologies.

Funding: ANRF IRG

Dystonia is a heterogeneous group of movement disorders characterized by sustained or intermittent muscle contractions that lead to abnormal movements and postures. Although several genes have been implicated, a significant proportion of patients remain without a definitive molecular diagnosis. Advances in next-generation sequencing technologies provide an opportunity to better understand the genetic architecture of dystonia and improve diagnostic yield, particularly in underrepresented populations such as those in India.

Our research focus on identifying pathogenic variants associated with dystonia using genomic approaches. We apply a multi-tiered approach to interpret and reclassify variants of uncertain significance and ultimately improve the diagnostic yield through the use of whole-exome, whole-genome, and long-read sequencing technologies. 

Project 2: Deep Learning-Driven Genotype-Phenotype Mapping for Improved Dystonia Diagnosis and Stratification.

Funding: CSIR OLP

Clinical assessment of dystonia relies largely on visual examination and rating scales, which can be subjective and may not capture subtle motor abnormalities. To address this, we incorporate video-based analysis, which allows systematic evaluation of patient movements using recorded clinical examinations, while kinematic analysis uses motion-tracking technologies and computational methods to measure parameters such as movement velocity, amplitude, and joint angles. These approaches will provide us with quantitative insights into motor dysfunction, help in better phenotyping of patients, and facilitate more precise genotype–phenotype correlations in dystonia research.