medRxiv : the preprint server for health sciences · 2025
Identifying Distinct Tourette Disorder Subtypes using Clinical Data.
СтатьяПрепринтНазвание и аннотация: Перевод в очереди
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Krishnamurthy Subramanian, Tourette International Collaborative Genetics (TIC Genetics), King Robert A, Tischfield Jay A, Heiman Gary A, Xing Jinchuan
Аннотация
BACKGROUND: Tourette Disorder (TD), or Tourette Syndrome, is a highly heterogeneous childhood-onset neurodevelopmental disorder with a global prevalence of 0.5%. TD's large phenotypic heterogeneity, variable heritability patterns, and frequent but varied comorbidity with other neurodevelopmental disorders indicate that different TD patients might have different etiologies.
OBJECTIVES: In this study, we performed unsupervised clustering of clinical data, such as categorical diagnoses and comorbidities, from 865 subjects with TD from the Tourette International Collaborative Genetics (TIC Genetics) study to detect Tourette Disorder subtypes.
METHODS: We used two different clustering methods, K-Means and Bayesian Hierarchical Clustering to detect phenotypic subtypes.
RESULTS: We identified five distinct, clinically relevant subtypes. These subtypes are characterized by both previously described TD comorbidities, such as Obsessive-Compulsive Disorder (OCD) and Attention Deficit/Hyperactivity Disorder (ADHD), as well as other characteristics, such as sex and region.
CONCLUSIONS: Defining clinically relevant TD subtypes could enable better diagnostics, treatment, and the understanding of TD etiology. In addition, stratified analysis of genetic data based on these phenotypic subtypes may help identify genes contributing to each TD subtype and provide insights into the disease variability.
OBJECTIVES: In this study, we performed unsupervised clustering of clinical data, such as categorical diagnoses and comorbidities, from 865 subjects with TD from the Tourette International Collaborative Genetics (TIC Genetics) study to detect Tourette Disorder subtypes.
METHODS: We used two different clustering methods, K-Means and Bayesian Hierarchical Clustering to detect phenotypic subtypes.
RESULTS: We identified five distinct, clinically relevant subtypes. These subtypes are characterized by both previously described TD comorbidities, such as Obsessive-Compulsive Disorder (OCD) and Attention Deficit/Hyperactivity Disorder (ADHD), as well as other characteristics, such as sex and region.
CONCLUSIONS: Defining clinically relevant TD subtypes could enable better diagnostics, treatment, and the understanding of TD etiology. In addition, stratified analysis of genetic data based on these phenotypic subtypes may help identify genes contributing to each TD subtype and provide insights into the disease variability.