Childhood intelligence is heritable, highly polygenic and associated with FNBP1L.

Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.

Trajectories of maternal depressive symptoms predict child problem behaviour: the Generation R study.

BACKGROUND: It is unclear how the course of maternal depressive symptoms affects child development. We modelled trajectories of maternal depressive symptoms from mid-pregnancy to 3 years after childbirth to better determine their associations with child problem behaviour. METHOD: Mother-child dyads (n = 4167) participated in a population-based prospective cohort in The Netherlands. Depressive symptoms were assessed with the Brief Symptom Inventory during pregnancy and at 2, 6 and 36 months postnatally. When children were 3 years old, problem behaviour was assessed with the Child Behaviour Checklist completed by each parent. A group-based modelling technique was used to model trajectories of maternal depressive symptoms and to examine their association with child problem behaviour. The added value of trajectory modelling was determined with successive linear regressions. RESULTS: We identified four trajectories of maternal depressive symptoms; 'no' (34%), 'low' (54%), 'moderate' (11%) and 'high' (1.5%). Child problem behaviour varied as a function of maternal trajectory membership. Whether rated by mother or father, children of mothers assigned to higher trajectories had significantly more problem behaviours than children of mothers assigned to lower trajectories. The model including trajectories had additive predictive value over a model relying only on a summed repeated measure of severity and a predefined chronicity variable. CONCLUSIONS: Depending on their course, maternal depressive symptoms have different effects on child problem behaviour. More information is gained by studying trajectories of symptoms, than only predefined measures of severity and chronicity. Moreover, trajectories can help identifying clinically depressed mothers who are possible candidates for early interventions.