Details

Autor(en) / Beteiligte

• Høberg, André
• Solberg, Berit S.
• Haavik, Jan
• Smajlagic, Dinka
• Havdahl, Alexandra
• Bekkhus, Mona
• Corfield, Elizabeth C.
• Zayats, Tetyana

Titel

GENETICALLY INFORMED EARLY IDENTIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER SYMPTOMS IN THE NORWEGIAN MOTHER, FATHER AND CHILD COHORT STUDY (MOBA)

Ist Teil von

• European neuropsychopharmacology, 2023-10, Vol.75, p.S22-S23

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Attention-Deficit/Hyperactivity Disorder (ADHD) is among the most common and heritable neurodevelopmental conditions characterized by atypical attention and/or hyperactivity/impulsivity. ADHD is associated with several genetic and environmental risk factors, including gestational age, birthweight, parental age at birth, and other socio-economic factors. Despite the high prevalence and recent advances in psychiatric research, the capacity of polygenic scores (PGS) and environmental risk factors to aid early detection of ADHD has not been examined comprehensively. This study aims to identify genetic and environmental markers that can be useful in early recognition of children at high likelihood of developing ADHD symptoms. We first derived subclasses of levels of ADHD symptoms in children at age 3, 5 and 8 years, using Latent Class Analyses and the full Norwegian Mother, Father and Child Cohort (MoBa) sample with ADHD phenotypes (N=64,098). A subset of this sample with both phenotypic and genotypic data (N=21,852, 49.2% girls) was used for the remaining analyses. We then carried out multinomial regression with ADHD-PGS, z-score of birthweight by gestational age, maternal education attainment, and parental age at birth as predictors and symptom-class as outcome to investigate if these predictors could differentiate between children with different levels of ADHD symptoms at the examined timepoints. ADHD-scores at 3, 5 and 8 years of age were also analyzed within the classes with the same predictors. We were able to identify ADHD symptom classes in boys and girls individually, and performed the analyses stratified by sex. Overall, three classes were noted: high, medium, and low symptom classes. We found that ADHD-PGS (ORboys= 1.31 (95% CI1.18-1.47) and ORgirls=1.30 (1.16-1.46)), z-score of birthweight by gestational age (ORboys= 0.93 (0.89-0.98) and ORgirls=0.87 (0.79-0.95)) and maternal attained education (ORboys= 0.82 (0.75-0.89) and ORgirls=0.75 (0.63-0.90)) predicted belonging to the highest symptom class in both sexes. In within-classes analyses, only maternal education was associated with ADHD-symptoms in the high class of either sex, while ADHD-PGS, z-score of birthweight by gestational age, maternal education and parental age were associated with ADHD-symptoms at different ages in the low- and medium-classes. We found that ADHD-PGS, z-score of birthweight by gestational age and maternal education contribute to identifying children with higher symptom levels. We plan to expand our analyses by including more genetic and environmental factors pertinent to ADHD - such as PGS on neurodevelopment, brain volumes and cognition, and measurements of body mass index - in our model as well as increasing our phenotype measures by including those at 1.5 years. We will also include analyses of identification accuracy, such as area under the receiver operating curve, sensitivity, specificity, and negative and positive predictive values. The model built in this study will help identify important factors associated with the development of ADHD symptoms in children.