Generalist genes analysis of DNA markers associated with mathematical ability and disability reveals shared influence across ages and abilities

Background The Generalist Genes Hypothesis is based upon quantitative genetic findings which indicate that many of the same genes influence diverse cognitive abilities and disabilities across age. In a recent genome-wide association study of mathematical ability in 10-year-old children, 43 SNP associations were nominated from scans of pooled DNA, 10 of which were validated in an individually genotyped sample. The 4927 children in this genotyped sample have also been studied at 7, 9 and 12 years of age on measures of mathematical ability, as well as on other cognitive and learning abilities. Results Using these data we have explored the Generalist Genes Hypothesis by assessing the association of the available measures of ability at age 10 and other ages with two composite 'SNP-set' scores, formed from the full set of 43 nominated SNPs and the sub-set of 10 SNPs that were previously found to be associated with mathematical ability at age 10. Both SNP sets yielded significant associations with mathematical ability at ages 7, 9 and 12, as well as with reading and general cognitive ability at age 10. Conclusions Although effect sizes are small, our results correspond with those of quantitative genetic research in supporting the Generalist Genes Hypothesis. SNP sets identified on the basis of their associations with mathematical ability at age 10 show associations with mathematical ability at earlier and later ages and show associations of similar magnitude with reading and general cognitive ability. With small effect sizes expected in such complex traits, future studies may be able to capitalise on power by searching for 'generalist genes' using longitudinal and multivariate approaches

Why do spatial abilities predict mathematical performance?

Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance. Using data on two aspects of spatial ability and three domains of mathematical ability from 4174 pairs of 12-year-old twins, we examined the relative genetic and environmental contributions to variation in spatial ability and to its relationship with different aspects of mathematics. Environmental effects explained most of the variation in spatial ability (~70%) and in mathematical ability (~60%) at this age, and the effects were the same for boys and girls. Genetic factors explained about 60% of the observed relationship between spatial ability and mathematics, with a substantial portion of the relationship explained by common environmental influences (26% and 14% by shared and non-shared environments respectively). These findings call for further research aimed at identifying specific environmental mediators of the spatial–mathematics relationship

Genetic factors underlie the association between anxiety, attitudes and performance in mathematics

Students struggling with mathematics anxiety (MA) tend to show lower levels of mathematics self-efficacy and interest as well as lower performance. The current study addresses: (1) how MA relates to different aspects of mathematics attitudes (self-efficacy and interest), ability (understanding numbers, problem solving ability, and approximate number sense) and achievement (exam scores); (2) to what extent these observed relations are explained by overlapping genetic and environmental factors; and (3) the role of general anxiety in accounting for these associations. The sample comprised 3,410 twin pairs aged 16-21 years, from the Twins Early Development Study. Negative associations of comparable strength emerged between MA and the two measures of mathematics attitudes, phenotypically (~ -.45) and genetically (~ -.70). Moderate negative phenotypic (~ -.35) and strong genetic (~ -.70) associations were observed between MA and measures of mathematics performance. The only exception was approximate number sense whose phenotypic (-.10) and genetic (-.31) relation with MA was weaker. Multivariate quantitative genetic analyses indicated that all mathematics related measures combined accounted for ~75% of the genetic variance in MA and ~20% of its environmental variance. Genetic effects were largely shared across all measures of mathematics anxiety, attitudes, abilities and achievement, with the exception of approximate number sense. This genetic overlap was not accounted for by general anxiety. These results have important implications for future genetic research concerned with identifying the genetic underpinnings of individual variation in mathematics-related traits, as well as for developmental research into how children select and modify their mathematics-related experiences partly based on their genetic predispositions

Measuring CHAOS? Evaluating the short-form Confusion, Hubbub And Order Scale

The Confusion, Hubbub and Order Scale (CHAOS) – short form – is a survey tool intended to capture information about home environments. It is widely used in studies of child and adolescent development and psychopathology, particularly twin studies. The original long form of the scale comprised 15 items and was validated in a sample of infants in the 1980s. The short form of the scale was developed in the late 1990s and contains six items, including four from the original scale, and two new items. This short form has not been validated and is the focus of this study. We use five samples (N=10,898) from studies in Australia, the UK, and the USA, to examine the measurement properties of the CHAOS short form. We first compare alternate confirmatory factor models for each group; we next test between-group configural, metric and scalar invariance; finally, we examine predictive validity of the scale in each sample under different conditions. We find evidence that a two-factor configuration of the six items is more appropriate than the commonly used one-factor model. Second, we find measurement non-invariance across groups at the metric invariance step, with items performing differently depending on the sample. By contrast we find longitudinal measurement invariance in two of the three samples with multi-wave data collection on the CHAOS. Finally, we report inconsistent results in tests of predictive validity using family-level socioeconomic status and academic achievement as criterion variables. The results caution the continued use of the short-form CHAOS in its current form and recommend future revisions and development of the scale for use in developmental research

Relations between Home Literacy Environment, Child Characteristics, and Print Knowledge for Preschool Children with Language Impairment

To contribute to the modest body of work examining the home literacy environment (HLE) and emergent literacy outcomes for children with disabilities, this study addressed two aims: (a) to determine the unique contributions of the HLE on print knowledge of preschool children with language impairment (LI); and (b) to identify whether specific child characteristics (oral language ability, print interest) moderated these relations. The sample consisted of 119 preschool children with LI. HLE was conceptualized as frequency of storybook reading and literacy teaching during book reading. Frequency of storybook reading was a unique predictor of print knowledge, which is consistent with research on children with typical language. Literacy teaching did not predict print knowledge, which diverges from research on children with typical language. No interactions between the HLE and child characteristics were significant, but language ability and print interest play a role in understanding individual differences in literacy development

Genetic Effects on Children’s Conversational Language Use

The present study examined the extent of genetic and environmental influences on individual differences in children’s conversational language use

Number Sense and Mathematics: Which, When and How?

Individual differences in number sense correlate with mathematical ability and performance, although the presence and strength of this relationship differs across studies. Inconsistencies in the literature may stem from heterogeneity of number sense and mathematical ability constructs. Sample characteristics may also play a role as changes in the relationship between number sense and mathematics may differ across development and cultural contexts. In this study, 4,984 16-year-old students were assessed on estimation ability, one aspect of number sense. Estimation was measured using two different tasks: number line and dot-comparison. Using cognitive and achievement data previously collected from these students at ages 7, 9, 10, 12, and 14 years of age, the study explored for which of the measures and when in development these links are observed; how strong these links are and how much these links are moderated by other cognitive abilities. The two number sensemeasures correlated modestly with each other (r = .22), but moderately with mathematics at age 16. Both measures were also associated with earlier mathematics; but this association was uneven across development and was moderated by other cognitive abilities

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fected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve

Etiological distinction of working memory components in relation to mathematics.

Working memory has been consistently associated with mathematics achievement, although the etiology of these relations remains poorly understood. The present study examined the genetic and environmental underpinnings of math story problem solving, timed calculation, and untimed calculation alongside working memory components in 12-year-old monozygotic (n = 105) and same-sex dizygotic (n = 143) twin pairs. Results indicated significant phenotypic correlation between each working memory component and all mathematics outcomes (r = 0.18 - 0.33). Additive genetic influences shared between the visuo-spatial sketchpad and mathematics achievement was significant, accounting for roughly 89% of the observed correlation. In addition, genetic covariance was found between the phonological loop and math story problem solving. In contrast, despite there being a significant observed relationship between phonological loop and timed and untimed calculation, there was no significant genetic or environmental covariance between the phonological loop and timed or untimed calculation skills. Further analyses indicated that genetic overlap between the visuo-spatial sketchpad and math story problem solving and math fluency was distinct from general genetic factors, whereas g, phonological loop, and mathematics shared generalist genes. Thus, although each working memory component was related to mathematics, the etiology of their relationships may be distinct