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The augmented multiple regression model for the analysis of data from selected
twin pairs was extended to facilitate analyses of data from twin pairs and
nontwin siblings. Fitting this extended model to data from both selected twin
pairs and siblings yields direct estimates of heritability (h2) and
the difference between environmental influences shared by members of twin pairs
and those of sib or twin–sib pairs (i.e., c2(t)
– c2 (s)). When this model was fitted to reading
performance data from 293 monozygotic and 436 dizygotic pairs selected for
reading difficulties, and 291 of their nontwin siblings, h2 = .48
± .22, p = .03, and c2 (t) –
c2 (s) = .22 ± .12, p = .06. Although the test
for differential shared environmental influences is only marginally significant,
the results of this analysis suggest that environmental influences on reading
performance that are shared by members of twin pairs (.36) may be substantially
greater than those for less contemporaneous twin–sibling pairs
(.14).

AbstractThe Academic Development Study of Australian Twins was established in 2012 with the purpose of investigating the relative influence of genes and environments in literacy and numeracy capabilities across two primary and two secondary school grades in Australia. It is the first longitudinal twin project of its kind in Australia and comprises a sample of 2762 twin pairs, 40 triplet sets and 1485 nontwin siblings. Measures include standardized literacy and numeracy test data collected at Grades 3, 5, 7 and 9 as part of the National Assessment Program: Literacy and Numeracy. A range of demographic and behavioral data was also collected, some at multiple longitudinal time points. This article outlines the background and rationale for the study and provides an overview for the research design, sample and measures collected. Findings emerging from the project and future directions are discussed.

Because of recent concerns about the replication of published results in the behavioral and biomedical sciences (Ioannidis, PLoS Medicine, Vol. 2, 2005, p. e124; Open Science Collaboration, Science, Vol. 349, 2015, p. 943; Pashler & Wagenmakers, Perspectives on Psychological Science, Vol. 7, 2012, pp. 528–530), we have conducted a replication of our recently published analyses of longitudinal reading performance and attention deficit-hyperactivity disorder data from twin pairs selected for reading difficulties (Wadsworth et al., Twin Research and Human Genetics, Vol. 18, 2015, pp. 755–761). Results obtained from univariate and bivariate (DeFries & Fulker, Behavior Genetics, Vol. 15, 1985, pp. 467–473; Acta Geneticae Medicae et Gemellologiae: Twin Research, Vol. 37, 1988, pp. 205–216) analyses of data from a subset of twin pairs tested in the International Longitudinal Twin Study of Early Reading Development at post-4th grade, and its continuation into high school at post-9th grade, were compared to those from our previous report. Similar measures of reading performance, the same measures of inattention and hyperactivity/impulsivity, and similar selection criteria were used in the two studies. In general, the patterns of results obtained from these two independent studies were highly similar. Thus, these results clearly illustrate the principle that findings from studies in quantitative behavioral genetics often replicate (Plomin et al., Perspectives on Psychological Science, Vol. 11, 2016, pp. 3–23).

Approximately 60% of children with reading difficulties (RD) meet criteria for at least one co-occurring disorder. The most common of these, attention deficit-hyperactivity disorder (ADHD), occurs in 20–40% of individuals with RD. Recent studies have suggested that genetic influences are responsible. To assess the genetic etiologies of RD and the comorbidity of RD and two ADHD symptom dimensions –– inattention (IN) and hyperactivity/impulsivity (H/I) –– we are conducting the first longitudinal twin study of RD and ADHD. Data from twin pairs in which at least one member of the pair met criteria for proband status for RD at initial assessment, and were reassessed 5 years later, were subjected to DeFries-Fulker (DF) analysis. Analyses of reading composite data indicated that over 60% of the proband deficit at initial assessment was due to genetic influences, and that reading deficits at follow-up were due substantially to the same genetic influences. When a bivariate DF model was fitted to reading performance and IN data, genetic influences accounted for 60% of contemporaneous comorbidity and over 60% of the longitudinal relationship. In contrast, analysis of the comorbidity between reading performance and H/I indicated that common genetic influences accounted for only about 20% of the contemporaneous and about 10% of the longitudinal relationships. Results indicate that (1) genetic influences on RD are substantial and highly stable; (2) the comorbidity between RD and IN is due largely to genetic influences, both contemporaneously and longitudinally; and (3) genetic influences contribute significantly less to the comorbidity between RD and H/I.

AbstractPrevious research has established that learning to read improves children's performance on reading‐related phonological tasks, including phoneme awareness (PA) and nonword repetition. Few studies have investigated whether literacy acquisition also promotes children's rapid automatized naming (RAN). We tested the hypothesis that literacy acquisition should influence RAN in an international, longitudinal population sample of twins. Cross‐lagged path models evaluated the relationships among literacy, PA, and RAN across four time points from pre‐kindergarten through grade 4. Consistent with previous research, literacy showed bidirectional relationships with reading‐related oral language skills. We found novel evidence for an effect of earlier literacy on later RAN, which was most evident in children at early phases of literacy development. In contrast, the influence of earlier RAN on later literacy was predominant among older children. These findings imply that the association between these two related skills is moderated by development. Implications for models of reading development and for dyslexia research are discussed.

AbstractIn this article we report on reading ability of twin children in kindergarten to Grade 2 as a function of whether members of the pairs are assigned to the same or different classrooms. All analyses were run using mixed model regressions to account for the interdependence between twin pairs. The samples, total N = 1505, are from Australia and the United States. We found a close-to-significant difference in favor of same-class children in kindergarten and Grade 1. However, when results were adjusted to take account of pre-existing differences in disruptive behavior and in preliteracy ability, the class assignment effects disappeared. We suggest that these pre-existing differences, particularly disruptive behavior, are influencing decisions about whether to separate twins or not and also affecting early reading performance, a conclusion supported by significant correlations between the behavioral measures, preliteracy, and school-based reading. We conclude that, on average, early literacy in twins is not directly affected by their assignment to the same or different classrooms.

Funding: AG and TFMA were supported by the Munich Cluster for Systems Neurology (SyNergy). AG 535 was supported by Fondazione Umberto Veronesi. SP is a Royal Society University Research fellow. BMM, CF, BSP and SEF are supported by the Max Planck Society. AW, BM and HK were funded by the Fraunhofer Society and the Max Planck Society within the 'Pakt für Forschung und Innovation'. HK was also supported by LIFE – Leipzig Research Center for Civilization Diseases funded by means of the European Union; the European Regional Development Fund (ERDF); and the Free State of Saxony within the excellence initiative. FR is supported by Agence Nationale de la Recherche (ANR-06-NEURO-019-01, ANR-17-EURE-542 0017 IEC, ANR-10-IDEX-0001-02 PSL, ANR-11-BSV4-014-01), European Commission (LSHM-CT-2005-018696). TFMA was supported by the BMBF through the DIFUTURE consortium of the Medical Informatics Initiative Germany (grant 01ZZ1804A) and by the European Union's Horizon 2020 Research and Innovation Programme (grant MultipleMS, EU RIA 733161). ; Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40–60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10−6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20–25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10−13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10−43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10−22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10−12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10−4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10−7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10−29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence. ; Publisher PDF ; Peer reviewed