Assessment of Susceptibility Risk Factors for ADHD in Imaging Genetic Studies

6533b834fe1ef96bd129cd6a

RESEARCH PRODUCT

Assessment of Susceptibility Risk Factors for ADHD in Imaging Genetic Studies

Silvia Alemany Jesús Pujol Jordi Sunyer Juan R. González Alejandro Cáceres Mario Murcia Joan Forns Dídac Macià Natalia Vilor-tejedor

subject

Male Genotype Imaging genetics Population Negative binomial distribution Polymorphism Single Nucleotide ADHD symptoms Imaging Genetics 03 medical and health sciences Imaging Three-Dimensional 0302 clinical medicine Overdispersion Risk Factors Statistics mental disorders Developmental and Educational Psychology Statistical inference Humans Genetic Predisposition to Disease 0501 psychology and cognitive sciences Genetic Testing Longitudinal Studies Poisson Distribution Prospective Studies p-value MAPRE2 Child education childhood zero-inflated negative binomial education.field_of_study Models Statistical basal ganglia perivascular volumes 05 social sciences Magnetic Resonance Imaging count data Virchow-Robin space Binomial Distribution Clinical Psychology Attention Deficit Disorder with Hyperactivity Child Preschool Probability distribution Female Psychology 030217 neurology & neurosurgery 050104 developmental & child psychology Count data

description

Objective: ADHD consists of a count of symptoms that often presents heterogeneity due to overdispersion and excess of zeros. Statistical inference is usually based on a dichotomous outcome that is underpowered. The main goal of this study was to determine a suited probability distribution to analyze ADHD symptoms in Imaging Genetic studies. Method: We used two independent population samples of children to evaluate the consistency of the standard probability distributions based on count data for describing ADHD symptoms. Results: We showed that the zero-inflated negative binomial (ZINB) distribution provided the best power for modeling ADHD symptoms. ZINB reveals a genetic variant, rs273342 (Microtubule-Associated Protein [MAPRE2]), associated with ADHD ( p value = 2.73E-05). This variant was also associated with perivascular volumes (Virchow–Robin spaces; p values < 1E-03). No associations were found when using dichotomous definition. Conclusion: We suggest that an appropriate modeling of ADHD symptoms increases statistical power to establish significant risk factors.

year	journal	country	edition	language
2019-01-01

https://fundanet.fisabio.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=1654