Maciej Trzaskowski

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method

Significance We identify several common genetic variants associated with cognitive performance using a two-stage approach: we conduct a genome-wide association study of educational attainment to generate a set of candidates, and then we estimate the association of these variants with cognitive performance. In older Americans, we find that these variants are jointly associated with cognitive health. Bioinformatics analyses implicate a set of genes that is associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory. In addition to the substantive contribution, this work also serves to show a proxy-phenotype approach to discovering common genetic variants that is likely to be useful for many phenotypes of interest to social scientists (such as personality traits). We identify common genetic variants associated with cognitive performance using a two-stage approach, which we call the proxy-phenotype method. First, we conduct a genome-wide association study of educational attainment in a large sample (n = 106,736), which produces a set of 69 education-associated SNPs. Second, using independent samples (n = 24,189), we measure the association of these education-associated SNPs with cognitive performance. Three SNPs (rs1487441, rs7923609, and rs2721173) are significantly associated with cognitive performance after correction for multiple hypothesis testing. In an independent sample of older Americans (n = 8,652), we also show that a polygenic score derived from the education-associated SNPs is associated with memory and absence of dementia. Convergent evidence from a set of bioinformatics analyses implicates four specific genes (KNCMA1, NRXN1, POU2F3, and SCRT). All of these genes are associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory.

Socioeconomic Status (SES) and Children's Intelligence (IQ): In a UK-Representative Sample SES Moderates the Environmental, Not Genetic, Effect on IQ

Background The environment can moderate the effect of genes - a phenomenon called gene-environment (GxE) interaction. Several studies have found that socioeconomic status (SES) modifies the heritability of childrens intelligence. Among low-SES families, genetic factors have been reported to explain less of the variance in intelligence; the reverse is found for high-SES families. The evidence however is inconsistent. Other studies have reported an effect in the opposite direction (higher heritability in lower SES), or no moderation of the genetic effect on intelligence. Methods Using 8716 twin pairs from the Twins Early Development Study (TEDS), we attempted to replicate the reported moderating effect of SES on childrens intelligence at ages 2, 3, 4, 7, 9, 10, 12 and 14: i.e., lower heritability in lower-SES families. We used a twin model that allowed for a main effect of SES on intelligence, as well as a moderating effect of SES on the genetic and environmental components of intelligence. Results We found greater variance in intelligence in low-SES families, but minimal evidence of GxE interaction across the eight ages. A power calculation indicated that a sample size of about 5000 twin pairs is required to detect moderation of the genetic component of intelligence as small as 0.25, with about 80% power - a difference of 11% to 53% in heritability, in low- (−2 standard deviations, SD) and high-SES (+2 SD) families. With samples at each age of about this size, the present study found no moderation of the genetic effect on intelligence. However, we found the greater variance in low-SES families is due to moderation of the environmental effect – an environment-environment interaction. Conclusions In a UK-representative sample, the genetic effect on intelligence is similar in low- and high-SES families. Childrens shared experiences appear to explain the greater variation in intelligence in lower SES.

The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence

Significance Differences among children in educational achievement are highly heritable from the early school years until the end of compulsory education at age 16, when UK students are assessed nationwide with standard achievement tests [General Certificate of Secondary Education (GCSE)]. Genetic research has shown that intelligence makes a major contribution to the heritability of educational achievement. However, we show that other broad domains of behavior such as personality and psychopathology also account for genetic influence on GCSE scores beyond that predicted by intelligence. Together with intelligence, these domains account for 75% of the heritability of GCSE scores. These results underline the importance of genetics in educational achievement and its correlates. The results also support the trend in education toward personalized learning. Because educational achievement at the end of compulsory schooling represents a major tipping point in life, understanding its causes and correlates is important for individual children, their families, and society. Here we identify the general ingredients of educational achievement using a multivariate design that goes beyond intelligence to consider a wide range of predictors, such as self-efficacy, personality, and behavior problems, to assess their independent and joint contributions to educational achievement. We use a genetically sensitive design to address the question of why educational achievement is so highly heritable. We focus on the results of a United Kingdom-wide examination, the General Certificate of Secondary Education (GCSE), which is administered at the end of compulsory education at age 16. GCSE scores were obtained for 13,306 twins at age 16, whom we also assessed contemporaneously on 83 scales that were condensed to nine broad psychological domains, including intelligence, self-efficacy, personality, well-being, and behavior problems. The mean of GCSE core subjects (English, mathematics, science) is more heritable (62%) than the nine predictor domains (35–58%). Each of the domains correlates significantly with GCSE results, and these correlations are largely mediated genetically. The main finding is that, although intelligence accounts for more of the heritability of GCSE than any other single domain, the other domains collectively account for about as much GCSE heritability as intelligence. Together with intelligence, these domains account for 75% of the heritability of GCSE. We conclude that the high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.

Satiety Mechanisms in Genetic Risk of Obesity

IMPORTANCE A better understanding of the cause of obesity is a clinical priority. Obesity is highly heritable, and specific genes are being identified. Discovering the mechanisms through which obesity-related genes influence weight would help pinpoint novel targets for intervention. One potential mechanism is satiety responsiveness. Lack of satiety characterizes many monogenic obesity disorders, and lower satiety responsiveness is linked with weight gain in population samples. OBJECTIVE To test the hypothesis that satiety responsiveness is an intermediate behavioral phenotype associated with genetic predisposition to obesity in children. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional observational study of a population-based cohort of twins born January 1, 1994, to December 31, 1996 (Twins Early Development Study). Participants included 2258 unrelated children (53.3% female; mean [SD] age, 9.9 [0.8] years), one randomly selected from each twin pair. EXPOSURE Genetic predisposition to obesity. We created a polygenic risk score (PRS) comprising 28 common obesity-related single-nucleotide polymorphisms identified in a meta-analysis of obesity-related genome-wide association studies. MAIN OUTCOMES AND MEASURES Satiety responsiveness was indexed with a standard psychometric scale (Child Eating Behavior Questionnaire). Using 1990 United Kingdom reference data, body mass index SD scores and waist SD scores were calculated from parent-reported anthropometric data for each child. Information on satiety responsiveness, anthropometrics, and genotype was available for 2258 children. We examined associations among the PRS, adiposity, and satiety responsiveness. RESULTS The PRS was negatively related to satiety responsiveness (β coefficient, -0.060; 95% CI, -0.019 to -0.101) and positively related to adiposity (β coefficient, 0.177; 95% CI, 0.136-0.218 for body mass index SD scores and β coefficient, 0.167; 95% CI, 0.126-0.208 for waist SD scores). More children in the top 25% of the PRS were overweight than in the lowest 25% (18.5% vs 7.2%; odds ratio, 2.90; 95% CI, 1.98-4.25). Associations between the PRS and adiposity were significantly mediated by satiety responsiveness (P = .006 for body mass index SD scores and P = .005 for waist SD scores). CONCLUSIONS AND RELEVANCE These results support the hypothesis that low satiety responsiveness is one of the mechanisms through which genetic predisposition leads to weight gain in an environment rich with food. Strategies to enhance satiety responsiveness could help prevent weight gain in genetically at-risk children.

Finding the missing heritability in pediatric obesity: the contribution of genome-wide complex trait analysis

Known single-nucleotide polymorphisms (SNPs) explain <2% of the variation in body mass index (BMI) despite the evidence of >50% heritability from twin and family studies, a phenomenon termed ‘missing heritability’. Using DNA alone for unrelated individuals, a novel method (in a software package called Genome-wide Complex Trait Analysis, GCTA) estimates the total additive genetic influence due to common SNPs on whole-genome arrays. GCTA has made major inroads into explaining the ‘missing heritability’ of BMI in adults. This study provides the first GCTA estimate of genetic influence on adiposity in children. Participants were from the Twins Early Development Study (TEDS), a British twin birth cohort. BMI s.d. scores (BMI-SDS) were obtained from validated parent-reported anthropometric measures when children were about 10 years old (mean=9.9; s.d.=0.84). Selecting one child per family (n=2269), GCTA results from 1.7 million DNA markers were used to quantify the additive genetic influence of common SNPs. For direct comparison, a standard twin analysis in the same families estimated the additive genetic influence as 82% (95% CI: 0.74–0.88, P<0.001). GCTA explained 30% of the variance in BMI-SDS (95% CI: 0.02–0.59; P=0.02). These results indicate that 37% of the twin-estimated heritability (30/82%) can be explained by additive effects of multiple common SNPs, and provide compelling evidence for strong genetic influence on adiposity in childhood.

DNA evidence for strong genetic stability and increasing heritability of intelligence from age 7 to 12

Two genetic findings from twin research have far-reaching implications for understanding individual differences in the development of brain function as indexed by general cognitive ability (g, aka intelligence): (1) The same genes affect g throughout development, even though (2) heritability increases. It is now possible to test these hypotheses using DNA alone. From 1.7 million DNA markers and g scores at ages 7 and 12 on 2875 children, the DNA genetic correlation from age 7 to 12 was 0.73, highly similar to the genetic correlation of 0.75 estimated from 6702 pairs of twins from the same sample. DNA-estimated heritabilities increased from 0.26 at age 7 to 0.45 at age 12; twin-estimated heritabilities also increased from 0.35 to 0.48. These DNA results confirm the results of twin studies indicating strong genetic stability but increasing heritability for g, despite mean changes in brain structure and function from childhood to adolescence.

No Genetic Influence for Childhood Behavior Problems From DNA Analysis

Objective Twin studies of behavior problems in childhood point to substantial genetic influence. It is now possible to estimate genetic influence using DNA alone in samples of unrelated individuals, not relying on family-based designs such as twins. A linear mixed model, which incorporates DNA microarray data, has confirmed twin results by showing substantial genetic influence for diverse traits in adults. Here we present direct comparisons between twin and DNA heritability estimates for childhood behavior problems as rated by parents, teachers, and children themselves. Method Behavior problem data from 2,500 UK-representative 12-year-old twin pairs were used in twin analyses; DNA analyses were based on 1 member of the twin pair with genotype data for 1.7 million DNA markers. Diverse behavior problems were assessed, including autistic, depressive, and hyperactive symptoms. Genetic influence from DNA was estimated using genome-wide complex trait analysis (GCTA), and the twin estimates of heritability were based on standard twin model fitting. Results Behavior problems in childhood—whether rated by parents, teachers, or children themselves—show no significant genetic influence using GCTA, even though twin study estimates of heritability are substantial in the same sample, and even though both GCTA and twin study estimates of genetic influence are substantial for cognitive and anthropometric traits. Conclusions We suggest that this new type of “missing heritability,” that is, the gap between GCTA and twin study estimates for behavior problems in childhood, is due to nonadditive genetic influence, which will make it more difficult to identify genes responsible for heritability.

Strong Genetic Influence on a UK Nationwide Test of Educational Achievement at the End of Compulsory Education at Age 16

We have previously shown that individual differences in educational achievement are highly heritable in the early and middle school years in the UK. The objective of the present study was to investigate whether similarly high heritability is found at the end of compulsory education (age 16) for the UK-wide examination, called the General Certificate of Secondary Education (GCSE). In a national twin sample of 11,117 16-year-olds, heritability was substantial for overall GCSE performance for compulsory core subjects (58%) as well as for each of them individually: English (52%), mathematics (55%) and science (58%). In contrast, the overall effects of shared environment, which includes all family and school influences shared by members of twin pairs growing up in the same family and attending the same school, accounts for about 36% of the variance of mean GCSE scores. The significance of these findings is that individual differences in educational achievement at the end of compulsory education are not primarily an index of the quality of teachers or schools: much more of the variance of GCSE scores can be attributed to genetics than to school or family environment. We suggest a model of education that recognizes the important role of genetics. Rather than a passive model of schooling as instruction (instruere, ‘to build in’), we propose an active model of education (educare, ‘to bring out’) in which children create their own educational experiences in part on the basis of their genetic propensities, which supports the trend towards personalized learning.

First Genome-Wide Association Study on Anxiety-Related Behaviours in Childhood

Background Twin studies have shown that anxiety in a general population sample of children involves both domain-general and trait-specific genetic effects. For this reason, in an attempt to identify genes responsible for these effects, we investigated domain-general and trait-specific genetic associations in the first genome-wide association (GWA) study on anxiety-related behaviours (ARBs) in childhood. Methods The sample included 2810 7-year-olds drawn from the Twins Early Development Study (TEDS) with data available for parent-rated anxiety and genome-wide DNA markers. The measure was the Anxiety-Related Behaviours Questionnaire (ARBQ), which assesses four anxiety traits and also yields a general anxiety composite. Affymetrix GeneChip 6.0 DNA arrays were used to genotype nearly 700,000 single-nucleotide polymorphisms (SNPs), and IMPUTE v2 was used to impute more than 1 million SNPs. Several GWA associations from this discovery sample were followed up in another TEDS sample of 4804 children. In addition, Genome-wide Complex Trait Analysis (GCTA) was used on the discovery sample, to estimate the total amount of variance in ARBs that can be accounted for by SNPs on the array. Results No SNP associations met the demanding criterion of genome-wide significance that corrects for multiple testing across the genome (p<5×10−8). Attempts to replicate the top associations did not yield significant results. In contrast to the substantial twin study estimates of heritability which ranged from 0.50 (0.03) to 0.61 (0.01), the GCTA estimates of phenotypic variance accounted for by the SNPs were much lower 0.01 (0.11) to 0.19 (0.12). Conclusions Taken together, these GWAS and GCTA results suggest that anxiety – similar to height, weight and intelligence − is affected by many genetic variants of small effect, but unlike these other prototypical polygenic traits, genetic influence on anxiety is not well tagged by common SNPs.

Genetics of callous-unemotional behavior in children.

Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU.