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AbstractThe purpose ofBehavioral Genetics5th edition (BG) is to cover the knowns and unknowns of behavior genetics, conveying the excitement of the field, its prospects, and something of the methods. Like the importantAmerican Psychologist(AP) paper 'Intelligence: Knowns and Unknowns' (Neisser et al., 1996), BG is designed to convey a consensus, in this case across fields as diverse as autism and xenophobia. Establishing and communicating this consensus is especially important for behavior genetics when many students are relatively unaware of the existence of biological differences. To meet this bold purpose the book needs to be accessible to those new to genetics while remaining accurate, and this goal is met admirably. The text is suffused with a calm and even handed approach that allows it to address its pedagogical task far better than most texts. It has been honed across the decades, including a complete rewrite (3rd edition), and, now, two rounds of fine-tuning. This polish pays off: the book reads very well, is well indexed, and integrated.

AbstractRecounts how our collaboration with Nick Martin was shaped over two decades, leading to the first studies of predictions from the 'Dual Route Cascaded' computational model of reading in twins, and extending into the molecular work, first linkage, fine mapping of genes identified in pedigree studies, into now the genomewide association study era and the first polygenic risk scores for reading and their potential in early clarifying causality and validating interventions, as well as for future global collaborations in improving these predictors and identifying causal variants. We highlight Nick's warm, future-focused optimism, support and inclusive approach without which none of this would have been possible. The circle of Nick asking, over half a century ago, 'What genes do you think make some kids get better grades?' has built a diverse scientific legacy involving thousands of papers and collaborations. The (heritable) traits of curiosity, boldness, warmth, interest in societally important questions, openness to new methods, ambition and collaborative skill to bring into being the infrastructure and samples needed for this research are rare, and we are grateful.

AbstractErikson asked what makes some people care for the future of the species and others not, calling this 'generativity vs. stagnation'. In three studies, we addressed structure of this trait and its heritability. Study 1 (N = 1570), using structural models of the Loyola Generativity Scale , revealed three correlated factors consisting of (1) Establishing and aiding the next generation; (2) Maintaining the world; and (3) Symbolic immortality through a positive legacy. Study 2 (N = 311) successfully replicated this structure in an independent UK sample. Study 3 tested genetic and environmental influences on generativity. All three factors showed significant and substantial heritable influence. A general factor was required, which was also heritable. In resolving previous uncertainty over the transmission of generativity across generations, shared environmental transmission models fit poorly. Substantial unique environmental effects suggest strong cultural impacts on concern for the species. Generativity researchers may usefully adopt this three-factor scoring system, allowing research on the predictive power of each component of generativity as well as molecular genetic or biological studies.

AbstractStructural equation modeling (SEM) is an important research tool, both for path-based model specification (common in the social sciences) and also for matrix-based models (in heavy use in behavior genetics). We developed umx to give more immediate access, relatively concise syntax and helpful defaults for users in these two broad disciplines. umx supports development, modification and comparison of models, as well as both graphical and tabular outputs. The second major focus of umx, behavior genetic models, is supported via functions implementing standard multigroup twin models. These functions support raw and covariance data, including joint ordinal data, and give solutions for ACE models, including support for covariates, common- and independent-pathway models, and gene × environment interaction models. A tutorial site and question forum are also available.

With climate change and its consequences believed to be among the most vital challenges for humanity and the Earth's ecosystem, it is important to understand why individuals do or do not adopt proenvironmental attitudes and behaviors. Personality traits are well suited for this purpose. Because no recent work has systematically combined the accumulating evidence on this topic, we aimed to meta-analyze the associations of the Big Five and HEXACO personality domains with proenvironmental attitudes and behaviors. A meta-analysis of 38 sources (N = 44,993) implicated openness and honesty-humility as the strongest correlates of proenvironmental attitudes (r = .22 and .20) and behaviors (r = .21 and .25). Agreeableness, conscientiousness, and, to a lesser extent, extraversion were also associated with proenvironmental attitudes (r = .15, .12, and .09) and behaviors (r = .10, .11, and .10). Heterogeneity among effect sizes was partly explained by samples' gender ratio, age, and country of origin and by the personality model. P-curve analyses, funnel plots, and Egger's tests indicated significant but sporadic and small publication bias. As a validity test, the meta-analytic associations collectively provided substantial predictive accuracy for proenvironmental attitudes (r = .44-.45) and behaviors (r = .28-.43) in independent holdout samples.

AbstractReading difficulties are prevalent worldwide, including in economically developed countries, and are associated with low academic achievement and unemployment. Longitudinal studies have identified several early childhood predictors of reading ability, but studies frequently lack genotype data that would enable testing of predictors with heritable influences. The National Child Development Study (NCDS) is a UK birth cohort study containing direct reading skill variables at every data collection wave from age 7 years through to adulthood with a subsample (finaln= 6431) for whom modern genotype data are available. It is one of the longest running UK cohort studies for which genotyped data are currently available and is a rich dataset with excellent potential for future phenotypic and gene-by-environment interaction studies in reading. Here, we carry out imputation of the genotype data to the Haplotype Reference Panel, an updated reference panel that offers greater imputation quality. Guiding phenotype choice, we report a principal components analysis of nine reading variables, yielding a composite measure of reading ability in the genotyped sample. We include recommendations for use of composite scores and the most reliable variables for use during childhood when conducting longitudinal, genetically sensitive analyses of reading ability.

A set of 10 SNPs associated with reading ability in 7-year-olds was reported based on initial pooled analyses of 100K SNP chip data, with follow-up testing stages using pooling and individual testing. Here we examine this association in an adolescent population sample of Australian twins and siblings (N= 1177) aged 12 to 25 years. One (rs1842129) of the 10 SNPs approached significance (P= .05) but no support was found for the remaining 9 SNPs or the SNP set itself. Results indicate that these SNPs are not associated with reading ability in an Australian population. The results are interpreted as supporting use of much larger SNP sets in common disorders where effects are small.

AbstractReading and language abilities are critical for educational achievement and success in adulthood. Variation in these traits is highly heritable, but the underlying genetic architecture is largely undiscovered. Genetic studies of reading and language skills traditionally focus on children with developmental disorders; however, much larger unselected adult samples are available, increasing power to identify associations with specific genetic variants of small effect size. We introduce an Australian adult population cohort (41.7–73.2 years of age, N = 1505) in which we obtained data using validated measures of several aspects of reading and language abilities. We performed genetic association analysis for a reading and spelling composite score, nonword reading (assessing phonological processing: a core component in learning to read), phonetic spelling, self-reported reading impairment and nonword repetition (a marker of language ability). Given the limited power in a sample of this size (~80% power to find a minimum effect size of 0.005), we focused on analyzing candidate genes that have been associated with dyslexia and developmental speech and language disorders in prior studies. In gene-based tests, FOXP2, a gene implicated in speech/language disorders, was associated with nonword repetition (p < .001), phonetic spelling (p = .002) and the reading and spelling composite score (p < .001). Gene-set analyses of candidate dyslexia and speech/language disorder genes were not significant. These findings contribute to the assessment of genetic associations in reading and language disorders, crucial for understanding their etiology and informing intervention strategies, and validate the approach of using unselected adult samples for gene discovery in language and reading.

Research on environmental and genetic pathways to complex traits such as educational attainment (EA) is confounded by uncertainty over whether correlations reflect effects of transmitted parental genes, causal family environments, or some, possibly interactive, mixture of both. Thus, an aggregate of thousands of alleles associated with EA (a polygenic risk score; PRS) may tap parental behaviors and home environments promoting EA in the offspring. New methods for unpicking and determining these causal pathways are required. Here, we utilize the fact that parents pass, at random, 50% of their genome to a given offspring to create independent scores for the transmitted alleles (conventional EA PRS) and a parental score based on allelesnot transmittedto the offspring (EA VP_PRS). The formal effect of non-transmitted alleles on offspring attainment was tested in 2,333 genotyped twins for whom high-quality measures of EA, assessed at age 17 years, were available, and whose parents were also genotyped. Four key findings were observed. First, the EA PRS and EA VP_PRS were empirically independent, validating the virtual-parent design. Second, in this family-based design, children's own EA PRS significantly predicted their EA (β = 0.15), ruling out stratification confounds as a cause of the association of attainment with the EA PRS. Third, parental EA PRS predicted the SES environment parents provided to offspring (β = 0.20), and parental SES and offspring EA were significantly associated (β = 0.33). This would suggest that the EA PRS is at least as strongly linked to social competence as it is to EA, leading to higher attained SES in parents and, therefore, a higher experienced SES for children. In a full structural equation model taking account of family genetic relatedness across multiple siblings the non-transmitted allele effects were estimated at similar values; but, in this more complex model, confidence intervals included zero. A test using the forthcoming EA3 PRS may clarify this outcome. The virtual-parent method may be applied to clarify causality in other phenotypes where observational evidence suggests parenting may moderate expression of other outcomes, for instance in psychiatry.

AbstractWe recently reported an association of offspring educational attainment with polygenic risk scores (PRS) computed on parent's non-transmitted alleles for educational attainment using the second GWAS meta-analysis article on educational attainment published by the Social Science Genetic Association Consortium. Here we test the replication of these findings using a more powerful PRS from the third GWAS meta-analysis article by the Consortium. Each of the key findings of our previous paper is replicated using this improved PRS (N = 2335 adolescent twins and their genotyped parents). The association of children's attainment with their own PRS increased substantially with the standardized effect size, moving from β = 0.134, 95% CI = 0.079, 0.188 for EA2, to β = 0.223, 95% CI = 0.169, 0.278, p < .001, for EA3. Parent's PRS again predicted the socioeconomic status (SES) they provided to their offspring and increased from β = 0.201, 95% CI = 0.147, 0.256 to β = 0.286, 95% CI = 0.239, 0.333. Importantly, the PRS for alleles not transmitted to their offspring — therefore acting via the parenting environment — was increased in effect size from β = 0.058, 95% CI = 0.003, 0.114 to β = 0.067, 95% CI = 0.012, 0.122, p = .016. As previously found, this non-transmitted genetic effect was fully accounted for by parental SES. The findings reinforce the conclusion that genetic effects of parenting are substantial, explain approximately one-third the magnitude of an individual's own genetic inheritance and are mediated by parental socioeconomic competence.