The influence of intergenerational transfer of white matter tracts on early reading development

Abstract

Parents have large genetic and environmental influences on their children’s cognition, behavior, and brain. Previous studies have indicated intergenerational transfer of the behavior of reading. Despite a close coupling between brain and behavior however, the intergenerational transfer of reading-related structural brain networks have not been investigated. Therefore, we investigated its parent-child associations for the first time. We examined how white matter tracts i.e., Arcuate Fasciculus (AF) and Inferior Fronto-Occipital Fasciculus (IFOF), are associated with children’s early reading development from Kindergarten to Grade 3 in 33 families. First, we observed in our sample of children -who all had typical reading skills despite half of them having an increased risk for dyslexia- that fractional anisotropy in bilateral IFOF and right AF correlated with reading development. Second, parent-child correlations were observed for bilateral IFOF but not for AF. Finally, we demonstrated that the relation between children’s IFOF and reading development was largely explained by parental IFOF. The findings preliminarily suggest that white matter organization in IFOF represents a pre-existing protective factor in children at risk, as it is mainly determined by biological parental factors. Large-scale intergenerational, multi-level and longitudinal studies are needed to understand the dynamic interrelations between brain, environment and behavior.

Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain’s reading network

“…Intergenerational neuroimaging combines successful features of existing research designs (e.g., family studies, concordance models) to further knowledge of mechanisms promoting brain development. The first studies directly investigating structural and functional brain similarity in parent-child dyads mostly focused on affective ( Yamagata et al, 2016 , Foland-Ross et al, 2015 , Abraham et al, 2020 , Colich et al, 2017 , Wang et al, 2018 ) or cognitive trait transmission ( Vandermosten et al, 2020 , Takagi et al, 2021 ). For example, Foland-Ross and colleagues reported on structural brain similarity by means of cortical thickness in mother-child dyads with and without a history of depression ( Foland-Ross et al, 2015 ).…”

“…For example, Foland-Ross and colleagues reported on structural brain similarity by means of cortical thickness in mother-child dyads with and without a history of depression ( Foland-Ross et al, 2015 ). Similarly, intergenerational transfer effects were studied in developmental disorders, including parents and children with a familial risk for dyslexia ( Vandermosten et al, 2020 ) or a diagnosis of attention deficit hyperactivity disorder ( Poissant et al, 2014 , Casey et al, 2007 ). Parent-child brain similarity is higher than that between randomly selected adult-child pairings, suggesting that the effects are, at least partially, of a familial nature ( Takagi et al, 2021 , Ahtam et al, 2021 ).…”

Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain’s reading network

“…Intergenerational neuroimaging combines successful features of existing research designs (e.g., family studies, concordance models) to further knowledge of mechanisms promoting brain development. The first studies directly investigating structural and functional brain similarity in parent-child dyads mostly focused on affective [1][2][3][4][5] or cognitive trait transmission 6,7 . For example, Foland-Ross and colleagues reported on structural brain similarity by means of cortical thickness in mother-child dyads with and without a history of depression 2 .…”

“…For example, Foland-Ross and colleagues reported on structural brain similarity by means of cortical thickness in mother-child dyads with and without a history of depression 2 . Similarly, intergenerational transfer effects were studied in developmental disorders, including parents and children with a familial risk for dyslexia 6 or a diagnosis of attention deficit hyperactivity disorder 8,9 . Parent-child brain similarity is higher than that between randomly selected adultchild pairings, suggesting that the effects are, at least partially, of a familial nature 7,10 .…”

“…Whereas we acknowledge that white matter development and connectivity measures may significantly benefit the understanding of intergenerational transfer effects on brain structure in parent-child dyads (see for example 6 ), in line with other structural developmental neuroimaging studies 26 , we here focus on cortical brain correlates. Anatomical measures under investigation include local gyrification (lG: inner foldings, impacting surface area), surface area (SA: external area of cortical outer layer), sulcal morphology (characteristic folding or formation of the grooves surrounding a gyri), gray matter volume (GMV: density of brain cells; a product of cortical thickness and surface area), and cortical thickness (CT: thickness of cortical layer; Figure 1).…”