A Comprehensive Quantitative Genetic Analysis of Cerebral Surface Area in Youth

Abstract

The genetics of cortical arealization in youth is not well understood. In this study, we use a genetically informative sample of 677 typically developing children and adolescents (mean age 12.72 years), high-resolution MRI, and quantitative genetic methodology to address several fundamental questions on the genetics of cerebral surface area. We estimate that Ͼ85% of the phenotypic variance in total brain surface area in youth is attributable to additive genetic factors. We also observed pronounced regional variability in the genetic influences on surface area, with the most heritable areas seen in primary visual and visual association cortex. A shared global genetic factor strongly influenced large areas of the frontal and temporal cortex, mirroring regions that are the most evolutionarily novel in humans relative to other primates. In contrast to studies on older populations, we observed statistically significant genetic correlations between measures of surface area and cortical thickness (r G ϭ 0.63), suggestive of overlapping genetic influences between these endophenotypes early in life. Finally, we identified strong and highly asymmetric genetically mediated associations between Full-Scale Intelligence Quotient and left perisylvian surface area, particularly receptive language centers. Our findings suggest that spatially complex and temporally dynamic genetic factors are influencing cerebral surface area in our species.Over evolution, the human cortex has undergone massive expansion. In humans, patterns of neurodevelopmental expansion mirror evolutionary changes. However, there is a sparsity of information on how genetics impacts surface area maturation. Here, we present a systematic analysis of the genetics of cerebral surface area in youth. We confirm prior research that implicates genetics as the dominant force influencing individual differences in global surface area. We also find evidence that evolutionarily novel brain regions share common genetics, that overlapping genetic factors influence both area and thickness in youth, and the presence of strong genetically mediated associations between intelligence and surface area in language centers. These findings further elucidate the complex role that genetics plays in brain development and function.

Variability of the Surface Area of the V1, V2, and V3 Maps in a Large Sample of Human Observers

“…Although the similarity between twin pairs in the sizes of V1, V2, and V3 is not explained by similarity in total cortical area, the total cortical area is in fact highly similar between twin pairs. Notably, the correlation for the full cortical surface is substantially higher than that for any other region and is substantially higher in MZ twins (rICC = 0.93) than in DZ twins (rICC = 0.73), consistent with prior reports showing high heritability of cortical surface area (Panizzon et al, 2009;Winkler et al, 2010;Gomez-Robles et al, 2015;Schmitt et al, 2019) (Fig. 8E).…”

Gene-experience correlation during cognitive development: Evidence from the Adolescent Brain Cognitive Development (ABCD) StudySM

“…A recent study, however, in children reported that at age 9 there was no significant relationship between intelligence and cortical thickness, but at age 12 a negative correlation between intelligence and thickness across the cortex was observed 16 . Conversely, cortical area has been shown to be positively associated with intelligence scores in adolescents 17 . Both thickness and area have been shown to be genetically correlated with intelligence in children and adolescents 16,17 .…”

“…Conversely, cortical area has been shown to be positively associated with intelligence scores in adolescents 17 . Both thickness and area have been shown to be genetically correlated with intelligence in children and adolescents 16,17 . These findings suggest that brain morphology is related to intelligence and that the two share a common genetic basis.…”

A simple permutation-based test of intermodal correspondence

“…Since the advent of the spin test, numerous neuroimaging experiments have adopted it to corroborate claims about intermodal similarities (Lefèvre et al 2018;Paquola et al 2019;Schmitt et al 2019;Shafiei et al 2020;Cui et al 2020;Stoecklein et al 2020) and have extended its implementation to regionally parcellated maps (Váša et al 2018;Vázquez-Rodríguez et al 2019;Cornblath et al 2020).…”