N Vilor-Tejedor1,2,3, S Alemany1,2,3, J Forns1,2,3,4, A Cáceres1,2,3, M Murcia3,5, D Macià6, J Pujol6, J Sunyer1,2,3,7, J R González1,2,3. 1. 1 SGlobal - Centre for Research in Environmental Epidemiology, Barcelona, Spain. 2. 2 Universitat Pompeu Fabra, Barcelona, Spain. 3. 3 CIBER Epidemiología y Salud Pública, Barcelona, Spain. 4. 4 Norwegian Institute of Public Health, Oslo, Norway. 5. 5 FISABIO-Universitat Jaume I-Universitat de València Joint Research Unit of Epidemiology and Environmental Health, Valencia, Spain. 6. 6 Hospital del Mar, Cibersam G21, Barcelona, Spain. 7. 7 Hospital del Mar Medical Research Institute, Barcelona, Spain.
Abstract
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.
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.
Authors: Natalia Vilor-Tejedor; Mohammad Arfan Ikram; Gennady Roshchupkin; Elisabeth J Vinke; Meike W Vernooij; Hieab H H Adams Journal: Front Psychiatry Date: 2020-06-29 Impact factor: 4.157
Authors: Silvia Alemany; Natàlia Vilor-Tejedor; Raquel García-Esteban; Mariona Bustamante; Payam Dadvand; Mikel Esnaola; Marion Mortamais; Joan Forns; Barend L van Drooge; Mar Álvarez-Pedrerol; Joan O Grimalt; Ioar Rivas; Xavier Querol; Jesus Pujol; Jordi Sunyer Journal: Environ Health Perspect Date: 2018-08-02 Impact factor: 9.031