Danielle Posthuma

Meta-analysis of the heritability of human traits based on fifty years of twin studies

Despite a century of research on complex traits in humans, the relative importance and specific nature of the influences of genes and environment on human traits remain controversial. We report a meta-analysis of twin correlations and reported variance components for 17,804 traits from 2,748 publications including 14,558,903 partly dependent twin pairs, virtually all published twin studies of complex traits. Estimates of heritability cluster strongly within functional domains, and across all traits the reported heritability is 49%. For a majority (69%) of traits, the observed twin correlations are consistent with a simple and parsimonious model where twin resemblance is solely due to additive genetic variation. The data are inconsistent with substantial influences from shared environment or non-additive genetic variation. This study provides the most comprehensive analysis of the causes of individual differences in human traits thus far and will guide future gene-mapping efforts. All the results can be visualized using the MaTCH webtool.

Netherlands Twin Register: From Twins to Twin Families

In the late 1980s The Netherlands Twin Register (NTR) was established by recruiting young twins and multiples at birth and by approaching adolescent and young adult twins through city councils. The Adult NTR (ANTR) includes twins, their parents, siblings, spouses and their adult offspring. The number of participants in the ANTR who take part in survey and / or laboratory studies is over 22,000 subjects. A special group of participants consists of sisters who are mothers of twins. In the Young NTR (YNTR), data on more than 50,000 young twins have been collected. Currently we are extending the YNTR by including siblings of twins. Participants in YNTR and ANTR have been phenotyped every 2 to 3 years in longitudinal survey studies, since 1986 and 1991 for the YNTR and ANTR, respectively. The resulting large population-based datasets are used for genetic epidemiological studies and also, for example, to advance phenotyping through the development of new syndrome scales based on existing items from other inventories. New research developments further include brain imaging studies in selected and unselected groups, clinical assessment of psychopathology through interviews, and cross-referencing the NTR database to other national databases. A large biobank enterprise is ongoing in the ANTR in which blood and urine samples are collected for genotyping, expression analysis, and metabolomics studies. In this paper we give an update on the YNTR and ANTR phenotyping and on the ongoing ANTR biobank studies.

Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo

Major depressive disorder (MDD) is a common complex trait with enormous public health significance. As part of the Genetic Association Information Network initiative of the US Foundation for the National Institutes of Health, we conducted a genome-wide association study of 435 291 single nucleotide polymorphisms (SNPs) genotyped in 1738 MDD cases and 1802 controls selected to be at low liability for MDD. Of the top 200, 11 signals localized to a 167 kb region overlapping the gene piccolo (PCLO, whose protein product localizes to the cytomatrix of the presynaptic active zone and is important in monoaminergic neurotransmission in the brain) with P-values of 7.7 × 10−7 for rs2715148 and 1.2 × 10−6 for rs2522833. We undertook replication of SNPs in this region in five independent samples (6079 MDD independent cases and 5893 controls) but no SNP exceeded the replication significance threshold when all replication samples were analyzed together. However, there was heterogeneity in the replication samples, and secondary analysis of the original sample with the sample of greatest similarity yielded P=6.4 × 10−8 for the nonsynonymous SNP rs2522833 that gives rise to a serine to alanine substitution near a C2 calcium-binding domain of the PCLO protein. With the integrated replication effort, we present a specific hypothesis for further studies.

Theory and Practice in Quantitative Genetics

With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper.

The heritability of general cognitive ability increases linearly from childhood to young adulthood

Although common sense suggests that environmental influences increasingly account for individual differences in behavior as experiences accumulate during the course of life, this hypothesis has not previously been tested, in part because of the large sample sizes needed for an adequately powered analysis. Here we show for general cognitive ability that, to the contrary, genetic influence increases with age. The heritability of general cognitive ability increases significantly and linearly from 41% in childhood (9 years) to 55% in adolescence (12 years) and to 66% in young adulthood (17 years) in a sample of 11 000 pairs of twins from four countries, a larger sample than all previous studies combined. In addition to its far-reaching implications for neuroscience and molecular genetics, this finding suggests new ways of thinking about the interface between nature and nurture during the school years. Why, despite lifes ‘slings and arrows of outrageous fortune’, do genetically driven differences increasingly account for differences in general cognitive ability? We suggest that the answer lies with genotype–environment correlation: as children grow up, they increasingly select, modify and even create their own experiences in part based on their genetic propensities.

The association between brain volume and intelligence is of genetic origin

83 TO THE EDITOR—The recent study by Thompson and colleagues1 reported high heritability of gray-matter volume in several cortical regions using voxel-based MRI techniques. Gray matter substantially correlated with general intelligence, or ‘g’. These findings prompt three major questions: (i) is the high heritability specific to gray-matter volume, (ii) is the correlation with g specific to gray-matter volume and (iii) is the correlation between gray-matter volume and g of genetic or environmental origin? We addressed the first question in a large Dutch sample of twins and their siblings (258 Dutch adults from 112 extended twin families)2. We found high heritability for total brain gray-matter volume (Table 1), comparable to the estimate reported by Thompson and colleagues1. In addition, we found high heritability for total brain white-matter volume. As stated in a commentary3 on the recent report in Nature Neuroscience1, high heritability of gray matter implies that interindividual variation in cell-body volume is not modified by experience. Because white matter reflects the degree of interconnection between different neurons, interindividual variance in whitematter volume might be expected to be more under the influence of experience and less under genetic control. Our results clearly suggest otherwise. Either environmental experience barely contributes to interindividual variation in white-matter volume or, alternatively, with the genes that influence g. The extent of the overlap is reflected by the magnitude of the genetic correlation. When the cross-trait/cross-twin correlations are similar for MZ and DZ twins, this suggests that environmental factors contribute to the observed phenotypic correlation between brain volume and g. Given a heritability of 0.85 for brain volume2, a heritability of 0.80 for g (ref. 5) and a correlation between brain volume and g of 0.40 (ref. 7), at least 17 MZ and 17 DZ pairs are needed to detect a genetic correlation with 80% power (and α = 0.05) that explains the observed correlation. In 24 MZ pairs, 31 DZ pairs and 25 additional siblings, we decomposed the correlation between brain volumes and g into genetic and environmental components by using structural equation modeling for a multivariate genetic design (gray matter, white matter and g)6. This showed that the correlation between gray-matter volume and g was due completely to genetic factors and not to environmental factors. We obtained the same result for the correlation between white-matter volume and g. Thus, the answer to the third question is The association between brain volume and intelligence is of genetic origin

A note on the statistical power in extended twin designs.

The power to detect sources of genetic and environmental variance varies with sample size, study design, effect size and the statistical significance level chosen. We explored whether the power of the classical twin study may be increased by adding non-twin siblings to the classical twin design. Sample sizes to detect genetic and shared environmental variation were compared for kinships with only twins, kinships consisting of twins and one additional sibling, and kinships with twins and two additional siblings. The effect of adding siblings to the classical twin design was considered for univariate and bivariate analyses. For the univariate case, adding one non-twin sibling resulted in a decrease in sample size needed to detect additive genetic influences in the presence of environmental influences. However, adding two additional siblings did not decrease the number of subjects as compared to the classical twin design. The sample size required to detect common environmental factors was also greatly decreased by adding one non-twin sibling. Adding two non-twin siblings resulted in a small additional decrease. In models including additive genetic, dominant genetic, and unique environmental effects, adding one sibling to a twin family decreased the required sample size to detect dominant genetic influences. Adding two siblings to a twin family resulted in only a slight additional decrease in sample size. In the bivariate case a similar pattern of results was found, in addition to the observation that the overall required sample size, as expected, was lower than in the univariate case. The decrease in sample size from bivariate testing was more pronounced in a design with one or two additional siblings, as compared to a design with twins only. It is concluded that a well considered choice of family design, i.e. including families with twins and one or two additional siblings increases the statistical power to detect sources of variance due to additive and non-additive genetic influences, and common environment.

Genetic contributions to human brain morphology and intelligence

Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology of specific GM areas in the brain have been studied, the heritability of focal WM is unknown. Similarly, it is unresolved whether there is a common genetic origin of focal GM and WM structures with intelligence. We explored the genetic influence on focal GM and WM densities in magnetic resonance brain images of 54 monozygotic and 58 dizygotic twin pairs and 34 of their siblings. For genetic analyses, we used structural equation modeling and voxel-based morphometry. To explore the common genetic origin of focal GM and WM areas with intelligence, we obtained cross-trait/cross-twin correlations in which the focal GM and WM densities of each twin are correlated with the psychometric intelligence quotient of his/her cotwin. Genes influenced individual differences in left and right superior occipitofrontal fascicle (heritability up to 0.79 and 0.77), corpus callosum (0.82, 0.80), optic radiation (0.69, 0.79), corticospinal tract (0.78, 0.79), medial frontal cortex (0.78, 0.83), superior frontal cortex (0.76, 0.80), superior temporal cortex (0.80, 0.77), left occipital cortex (0.85), left postcentral cortex (0.83), left posterior cingulate cortex (0.83), right parahippocampal cortex (0.69), and amygdala (0.80, 0.55). Intelligence shared a common genetic origin with superior occipitofrontal, callosal, and left optical radiation WM and frontal, occipital, and parahippocampal GM (phenotypic correlations up to 0.35). These findings point to a neural network that shares a common genetic origin with human intelligence.

Poor replication of candidate genes for major depressive disorder using genome-wide association data.

Data from the Genetic Association Information Network (GAIN) genome-wide association study (GWAS) in major depressive disorder (MDD) were used to explore previously reported candidate gene and single-nucleotide polymorphism (SNP) associations in MDD. A systematic literature search of candidate genes associated with MDD in case–control studies was performed before the results of the GAIN MDD study became available. Measured and imputed candidate SNPs and genes were tested in the GAIN MDD study encompassing 1738 cases and 1802 controls. Imputation was used to increase the number of SNPs from the GWAS and to improve coverage of SNPs in the candidate genes selected. Tests were carried out for individual SNPs and the entire gene using different statistical approaches, with permutation analysis as the final arbiter. In all, 78 papers reporting on 57 genes were identified, from which 92 SNPs could be mapped. In the GAIN MDD study, two SNPs were associated with MDD: C5orf20 (rs12520799; P=0.038; odds ratio (OR) AT=1.10, 95% CI 0.95–1.29; OR TT=1.21, 95% confidence interval (CI) 1.01–1.47) and NPY (rs16139; P=0.034; OR C allele=0.73, 95% CI 0.55–0.97), constituting a direct replication of previously identified SNPs. At the gene level, TNF (rs76917; OR T=1.35, 95% CI 1.13–1.63; P=0.0034) was identified as the only gene for which the association with MDD remained significant after correction for multiple testing. For SLC6A2 (norepinephrine transporter (NET)) significantly more SNPs (19 out of 100; P=0.039) than expected were associated while accounting for the linkage disequilibrium (LD) structure. Thus, we found support for involvement in MDD for only four genes. However, given the number of candidate SNPs and genes that were tested, even these significant may well be false positives. The poor replication may point to publication bias and false-positive findings in previous candidate gene studies, and may also be related to heterogeneity of the MDD phenotype as well as contextual genetic or environmental factors.

Physical Activity and Cognitive Function in a Cross-Section of Younger and Older Community-Dwelling Individuals

Previous reports have indicated a small, positive relationship between physical activity and cognition. However, the majority of research has focused on older adults, with few studies examining this relationship during earlier periods of the life span. This study examined the relationship of physical activity to cognition in a cross-section of 241 community-dwelling individuals 15-71 years of age with a task requiring variable amounts of executive control. Data were analyzed with multiple regression, which controlled for age, sex, and IQ. Participants reported their physical activity behavior and were tested for reaction time (RT) and response accuracy on congruent and incongruent conditions of a flanker task, which manipulates interference control. After controlling for confounding variables, an age-related slowing of RT was observed during both congruent and incongruent flanker conditions. However, physical activity was associated with faster RT during these conditions, regardless of age. Response accuracy findings indicated that increased physical activity was associated with better performance only during the incongruent condition for the older cohort. Findings suggest that physical activity may be beneficial to both general and selective aspects of cognition, particularly among older adults.