Developing a phenotype risk score for tic disorders in a large, clinical biobank

Area of Science:

• Neuroscience
• Genetics
• Clinical Informatics

Background:

• Tics are common in early-onset neurodevelopmental disorders, affecting up to 2% of children.
• The genetic basis and underlying causes of tic disorders are not well understood.
• Understanding tic disorder phenotypes is crucial for diagnosis and treatment.

Purpose of the Study:

• To leverage dense phenotype information from clinical biobanks to identify key features of tic disorders.
• To perform a phenome-wide association study (PheWAS) to find enriched features in tic disorder cases.
• To develop and validate a phenotype risk score (PheRS) for tic disorder identification.

Main Methods:

• Utilized de-identified electronic health records (EHRs) to identify individuals with tic disorder diagnosis codes.
• Conducted a PheWAS comparing tic disorder cases (n=1406) with controls (n=7030).
• Generated a PheRS using enriched features and validated it in an independent cohort (n=90,051).

Main Results:

• PheWAS revealed significant comorbidity of tic disorders with obsessive-compulsive disorder, ADHD, autism spectrum disorder, and anxiety (p < 7.396 × 10⁻⁵).
• The developed tic disorder PheRS was significantly higher in clinician-validated tic cases compared to non-cases (p = 4.787 × 10⁻¹⁵¹).
• The PheRS demonstrated strong predictive power (β = 1.68, SE = 0.06) in identifying tic disorder cases.

Conclusions:

• Large-scale medical databases and EHRs are valuable tools for understanding phenotypically complex conditions like tic disorders.
• The identified comorbid phenotypes provide insights into the neurodevelopmental context of tic disorders.
• The validated PheRS shows potential for improving the identification of underdiagnosed tic disorders.