As the third most common movement disorder, dystonias collectively affect more than 2 million people worldwide. Despite their high prevalence, their biological roots are largely unknown. Both genetic and environmental influences are suggested in familial studies, however, no specific genetic variants or environmental factors are responsible for a significant proportion of identified cases. Metabolomic profile of peripheral blood can be influenced by environmental and genetic factors, as well as physiological condition of an individual. Studying the metabolomic profile is an important component to understand the biological systems linking the environment, genomics and the development of dystonias. Molecular and system understanding of the dystonias would enhance the clinical practice of accurate diagnosis and effective treatment. Previous genome-wide association studies of the dystonias were limited by smaller sample size and lack of coverage of rare variants. No metabolomic study of the dystonias has been conducted to investigate the role of small molecules. In this study, we will use a high-throughput genomic and metabolomic approach to effectively investigate relationships between over 1.7 million genetic variations and over 20,000 metabolomic features. We will conduct targeted analyses of candidate genes, as well as agnostic searches for any genomic and metabolomic associations with the dystonias in the largest sample of dystonia patients available in the US.
Dystonia is the third most common movement disorder. However, the biological roots are largely unknown, which delays diagnosis and limits effective treatment. Both genetic and environmental influences are hinted, however, no specific factor explains a significant proportion of cases. Metabolomic profile is influenced by environmental and genetic factors, as well as physiological condition, but its role in the dystonias is unclear. Previous genetics studies of the dystonias were limited by small sample size and genomic coverage. We aim to investigate millions of common and rare genetic variations and over 20,000 metabolomic features for their functional roles in the dystonias, using the largest sample of dystonia patients available in the US.
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