Genetics and Child Development: Recent Advances and Their Implications for Developmental Research

Armstrong‐Carter, Emma; Wertz, Jasmin; Domingue, Benjamin W.

doi:10.1111/cdep.12400

Cited by 13 publications

(10 citation statements)

References 50 publications

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“…Elucidating genetic and environmental influences on brain development in children and adolescents is an important task for researchers. Recent scientific advances allowing the computation of genome‐wide polygenic scores have led to ground‐breaking insights into genetic effects on cognitive and health outcomes (Armstrong‐Carter et al, 2021; Plomin & von Stumm, 2018). Polygenic scores are derived using genome‐wide association studies (GWAS) by aggregating the contributions of all known genetic variants associated with the phenotype of interest (Plomin & von Stumm, 2018).…”

Section: Introductionmentioning

confidence: 99%

Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

Merz

Strack

Hurtado

et al. 2022

Human Brain Mapping

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Genome‐wide polygenic scores for educational attainment (PGS‐EA) and socioeconomic factors, which are correlated with each other, have been consistently associated with academic achievement and general cognitive ability in children and adolescents. Yet, the independent associations of PGS‐EA and socioeconomic factors with specific underlying factors at the neural and neurocognitive levels are not well understood. The main goals of this study were to examine the unique contributions of PGS‐EA and parental education to cortical structure and neurocognitive skills in children and adolescents, and the associations among PGS‐EA, cortical structure, and neurocognitive skills. Participants were typically developing 3‐ to 21‐year‐olds (53% male; N = 391). High‐resolution, T1‐weighted magnetic resonance imaging data were acquired, and cortical thickness (CT) and surface area (SA) were measured. PGS‐EA were computed based on the EA3 genome‐wide association study of educational attainment. Participants completed executive function, vocabulary, and episodic memory tasks. Higher PGS‐EA and parental education were independently and significantly associated with greater total SA and vocabulary. Higher PGS‐EA was significantly associated with greater SA in the left medial orbitofrontal gyrus and inferior frontal gyrus, which was associated with higher executive function. Higher parental education was significantly associated with greater SA in the left parahippocampal gyrus after accounting for PGS‐EA and total brain volume. These findings suggest that education‐linked genetics may influence SA in frontal regions, leading to variability in executive function. Associations of parental education with cortical structure in children and adolescents remained significant after controlling for PGS‐EA, a source of genetic confounding.

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Section: Introductionmentioning

confidence: 99%

Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

Merz

Strack

Hurtado

et al. 2022

Human Brain Mapping

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“…The approach to initializing generative network models (i.e., the seed) that best mimics developmental trajectories is unknown. Three main approaches have been taken in the literature: (1) The selection of edges that are highly consistent across the sample of empirical connectomes 25,26,29 ; (2) No edges at all, thereby initializing the model with a first calculated 𝑝 ",$ matrix that is equivalent to 𝑑 ",$ matrix 24,28,30,44 and; (3) A theory-driven set of edges (e.g., medio-posterior nodes 23 ).…”

Section: Neonatal Seed Network Generationmentioning

confidence: 99%

The adaptive stochasticity hypothesis: modelling equifinality, multifinality and adaptation to adversity

Carozza

Akarca

Astle

2023

Preprint

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Neural phenotypes are the result of probabilistic developmental processes. This means that stochasticity is an intrinsic aspect of the brain as it self-organizes over a protracted period. In other words, while both genomic and environmental factors shape the developing nervous system, another significant - though often neglected - contributor is the randomness introduced by probability distributions. Using generative modelling of brain networks, we provide a framework for probing the contribution of stochasticity to neurodevelopmental diversity. To mimic the prenatal scaffold of brain structure set by activity-independent mechanisms, we start our simulations from the medio-posterior neonatal rich-club (Developing Human Connectome Project; dHCP, n = 630). From this initial starting point, models implementing Hebbian-like wiring processes generate variable yet consistently plausible brain network topologies. By analyzing repeated runs of the generative process (> 107 simulations), we identify critical determinants and effects of stochasticity. Namely, we find that stochastic variation has a greater impact on brain organization when networks develop under weaker constraints. This heightened stochasticity makes brain networks more robust to random and targeted attacks, but more often results in non-normative phenotypic outcomes. To test our framework empirically, we evaluated whether stochasticity varies according to the experience of early-life deprivation using a cohort of neurodiverse children (Centre for Attention, Learning and Memory; CALM n = 357). We show that low socioeconomic status predicts more stochastic brain wiring. We conclude that stochasticity may be an unappreciated contributor to relevant developmental outcomes, and make specific predictions for future research.

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“…Although this approach offers many advances and has become relatively cost-effective (Tam et al, 2019), most GWAS were conducted on participants of European ancestry (e.g., Armstrong-Carter et al, 2021;Coleman et al, 2020;Direk et al, 2017;Martin et al, 2019).…”

Section: Child Maltreatment and Genetic Influencesmentioning

confidence: 99%

A person‐centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure

Handley

Russotti

Ross

et al. 2023

Developmental Psychobiology

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The present study illustrates the utility of latent class analysis, a person-centered data analytic approach, as an innovative method for identifying naturally occurring patterns of polygenic risk, specifically within the dopaminergic system. Moreover, this study tests whether latent classes of polygenic variation moderate the effect of child maltreatment exposure on internalizing symptoms among African ancestry youth.African ancestry youth were selected for this study because youth of color are overrepresented in the child welfare system and because African ancestry individuals are significantly underrepresented in genomics research. Results identified three latent classes of dopaminergic gene variation. Class 1 was marked predominately by homozygous minor alleles, Class 2 was characterized by homozygous major and heterozygous presentations, and Class 3 was marked by heterozygous alleles on the DAT-1 singlenucleotide polymorphisms (SNPs) and a combination of homozygous major and minor alleles on the other SNPs. Results indicated that a greater number of maltreatment subtypes experienced were associated with higher internalizing symptoms only for children with the latent polygenic Class 2 pattern. This latent class was distinctly characterized by more homozygous major or heterozygous allelic presentations along all three DAT-1 SNPs. This significant latent polygenic class by environment interaction was replicated in an independent replication sample. Together, findings suggest that African ancestry children with a pattern of dopaminergic variation characterized by this specific combination of polygenic variation are more vulnerable to developing internalizing symptoms following maltreatment exposure, relative to their peers with other dopamine-related polygenic patterns.

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Genetics and Child Development: Recent Advances and Their Implications for Developmental Research

Cited by 13 publications

References 50 publications

Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

The adaptive stochasticity hypothesis: modelling equifinality, multifinality and adaptation to adversity

A person‐centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure

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