Genetic associations with childhood brain growth, defined in two longitudinal cohorts
Genetic Epidemiology , Volume 42 - Issue 4 p. 405- 414
Genome-wide association studies (GWASs) are unraveling the genetics of adult brain neuroanatomy as measured by cross-sectional anatomic magnetic resonance imaging (aMRI). However, the genetic mechanisms that shape childhood brain development are, as yet, largely unexplored. In this study we identify common genetic variants associated with childhood brain development as defined by longitudinal aMRI. Genome-wide single nucleotide polymorphism (SNP) data were determined in two cohorts: one enriched for attention-deficit/hyperactivity disorder (ADHD) (LONG cohort: 458 participants; 119 with ADHD) and the other from a population-based cohort (Generation R: 257 participants). The growth of the brain's major regions (cerebral cortex, white matter, basal ganglia, and cerebellum) and one region of interest (the right lateral prefrontal cortex) were defined on all individuals from two aMRIs, and a GWAS and a pathway analysis were performed. In addition, association between polygenic risk for ADHD and brain growth was determined for the LONG cohort. For white matter growth, GWAS meta-analysis identified a genome-wide significant intergenic SNP (rs12386571, P = 9.09 × 10−9), near AKR1B10. This gene is part of the aldo-keto reductase superfamily and shows neural expression. No enrichment of neural pathways was detected and polygenic risk for ADHD was not associated with the brain growth phenotypes in the LONG cohort that was enriched for the diagnosis of ADHD. The study illustrates the use of a novel brain growth phenotype defined in vivo for further study.
|ADHD, brain development, children, GWAS, pathway analysis, polygenic score|
|Organisation||Generation R Study Group|
Székely, E, Schwantes-An, T.-H, Justice, C.M. (Cristina M.), Sabourin, J.A. (Jeremy A.), Jansen, P.R, Muetzel, R.L, … Shaw, P. (Philip). (2018). Genetic associations with childhood brain growth, defined in two longitudinal cohorts. Genetic Epidemiology, 42(4), 405–414. doi:10.1002/gepi.22122