Genomic prediction of cognitive traits in childhood and adolescence.

Recent advances in genomics are producing powerful DNA predictors of complex traits, especially cognitive abilities. Here, we leveraged summary statistics from the most recent genome-wide association studies of intelligence and educational attainment, with highly genetically correlated traits, to build prediction models of general cognitive ability and educational achievement. To this end, we compared the performances of multi-trait genomic and polygenic scoring methods. In a representative UK sample of 7,026 children at ages 12 and 16, we show that we can now predict up to 11% of the variance in intelligence and 16% in educational achievement. We also show that predictive power increases from age 12 to age 16 and that genomic predictions do not differ for girls and boys. We found that multi-trait genomic methods were effective in boosting predictive power. Prediction accuracy varied across polygenic score approaches, however results were similar for different multi-trait and polygenic score methods. We discuss general caveats of multi-trait methods and polygenic score prediction, and conclude that polygenic scores for educational attainment and intelligence are currently the most powerful predictors in the behavioural sciences.

Predicting educational achievement from DNA.

This corrects the article DOI: 10.1038/mp.2016.107.

Predicting educational achievement from DNA.

A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences.

Phenome-wide analysis of genome-wide polygenic scores.

Genome-wide polygenic scores (GPS), which aggregate the effects of thousands of DNA variants from genome-wide association studies (GWAS), have the potential to make genetic predictions for individuals. We conducted a systematic investigation of associations between GPS and many behavioral traits, the behavioral phenome. For 3152 unrelated 16-year-old individuals representative of the United Kingdom, we created 13 GPS from the largest GWAS for psychiatric disorders (for example, schizophrenia, depression and dementia) and cognitive traits (for example, intelligence, educational attainment and intracranial volume). The behavioral phenome included 50 traits from the domains of psychopathology, personality, cognitive abilities and educational achievement. We examined phenome-wide profiles of associations for the entire distribution of each GPS and for the extremes of the GPS distributions. The cognitive GPS yielded stronger predictive power than the psychiatric GPS in our UK-representative sample of adolescents. For example, education GPS explained variation in adolescents' behavior problems (~0.6%) and in educational achievement (~2%) but psychiatric GPS were associated with neither. Despite the modest effect sizes of current GPS, quantile analyses illustrate the ability to stratify individuals by GPS and opportunities for research. For example, the highest and lowest septiles for the education GPS yielded a 0.5 s.d. difference in mean math grade and a 0.25 s.d. difference in mean behavior problems. We discuss the usefulness and limitations of GPS based on adult GWAS to predict genetic propensities earlier in development.

Weak associations between pubertal development and psychiatric and behavioral problems.

Pubertal development has been associated with adverse outcomes throughout adolescence and adulthood. However, much of the previous literature has categorized outcome variables and pubertal timing measures for ease of mean difference or odds ratio interpretation. We use a UK-representative sample of over 5000 individuals drawn from the Twins Early Development Study to extend this literature by adopting an individual differences approach and emphasizing effect sizes. We investigate a variety of psychiatric and behavioral measures collected longitudinally at ages 11, 14 and 16, for multiple raters and for males and females separately. In addition, we use two measures of pubertal development: the Pubertal Development Scale at each age, as well as the age of menarche for girls. We found that pubertal development, however assessed, was linearly associated with a range of psychiatric and behavioral outcomes; however, the effect sizes of these associations were modest for both males and females with most correlations between -0.10 and 0.10. Our systematic analysis of associations between pubertal development, and psychiatric and behavioral problems is the most comprehensive to date. The results showing linearity of the effects of pubertal development support an individual differences approach, treating both pubertal development and associated outcomes as continuous rather than categorical variables. We conclude that pubertal development explains little variance in psychiatric and behavioral outcomes (<1% on average). The small effect sizes indicate that the associations are weak and should not warrant major concern at least in non-clinical populations.

How specific is second language-learning ability? A twin study exploring the contributions of first language achievement and intelligence to second language achievement.

Learning a second language is crucially important in an increasingly global society, yet surprisingly little is known about why individuals differ so substantially in second language (SL) achievement. We used the twin design to assess the nature, nurture and mediators of individual differences in SL achievement. For 6263 twin pairs, we analyzed scores from age 16 UK-wide standardized tests, the General Certificate of Secondary Education (GCSE). We estimated genetic and environmental influences on the variance of SL for specific languages, the links between SL and English and the extent to which the links between SL and English are explained by intelligence. All SL measures showed substantial heritability, although heritability was nonsignificantly lower for German (36%) than the other languages (53-62%). Multivariate genetic analyses indicated that a third of genetic influence in SL is shared with intelligence, a third with English independent of intelligence and a further third is unique to SL.