Anna A. E. Vinkhuyzen

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60–70% for height and 30–40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.

Research Review: Polygenic methods and their application to psychiatric traits

BACKGROUND Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years. METHODS AND SCOPE We review the methods investigating the polygenic nature of complex disorders. We provide mini-guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNPs; a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still-missing heritability. FINDINGS Genome-wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. Sample sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs. CONCLUSIONS Increasing the sample size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as sample sizes increase and as sample resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.

Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples

We have recently developed analysis methods (GREML) to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP) data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (co)variation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases) in particular when the traits (diseases) are not measured on the same samples.

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.

Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion

The personality traits of neuroticism and extraversion are predictive of a number of social and behavioural outcomes and psychiatric disorders. Twin and family studies have reported moderate heritability estimates for both traits. Few associations have been reported between genetic variants and neuroticism/extraversion, but hardly any have been replicated. Moreover, the ones that have been replicated explain only a small proportion of the heritability (<∼2%). Using genome-wide single-nucleotide polymorphism (SNP) data from ∼12 000 unrelated individuals we estimated the proportion of phenotypic variance explained by variants in linkage disequilibrium with common SNPs as 0.06 (s.e.=0.03) for neuroticism and 0.12 (s.e.=0.03) for extraversion. In an additional series of analyses in a family-based sample, we show that while for both traits ∼45% of the phenotypic variance can be explained by pedigree data (that is, expected genetic similarity) one third of this can be explained by SNP data (that is, realized genetic similarity). A part of the so-called ‘missing heritability’ has now been accounted for, but some of the reported heritability is still unexplained. Possible explanations for the remaining missing heritability are that: (i) rare variants that are not captured by common SNPs on current genotype platforms make a major contribution; and/ or (ii) the estimates of narrow sense heritability from twin and family studies are biased upwards, for example, by not properly accounting for nonadditive genetic factors and/or (common) environmental factors.

The Construction and Validation of an Abridged Version of the Autism-Spectrum Quotient (AQ-Short).

This study reports on the development and validation of an abridged version of the 50-item Autism-Spectrum Quotient (AQ), a self-report measure of autistic traits. We aimed to reduce the number of items whilst retaining high validity and a meaningful factor structure. The item reduction procedure was performed on data from 1,263 Dutch students and general population adults. The resulting 28-item AQ-Short was subsequently validated in 3 independent samples, both clinical and controls, from the Netherlands and the UK. The AQ-Short comprises two higher-order factors assessing ‘social behavioral difficulties’ and ‘a fascination for numbers/patterns’. The clear factor structure of the AQ-Short and its high sensitivity and specificity make the AQ-Short a useful alternative to the full 50-item version.

Population genetic differentiation of height and body mass index across Europe

Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10−8; BMI, P < 5.95 × 10−4), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).

Genome-wide association uncovers shared genetic effects among personality traits and mood states.

Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome‐wide SNP (∼2.5 million) and gene‐based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of mood states using genetic polygenic scores for personality. Measures of neuroticism, extraversion, and symptoms of anxiety, depression, and general psychological distress were collected in eight European cohorts (n ranged 546–1,338; maximum total n = 6,268) whose mean age ranged from 55 to 79 years. Meta‐analysis of the cohort results was performed, with follow‐up associations of the top SNPs and genes investigated in independent cohorts (n = 527–6,032). Suggestive association (P = 8 × 10−8) of rs1079196 in the FHIT gene was observed with symptoms of anxiety. Other notable associations (P < 6.09 × 10−6) included SNPs in five genes for neuroticism (LCE3C, POLR3A, LMAN1L, ULK3, SCAMP2), KIAA0802 for extraversion, and NOS1 for general psychological distress. An association between symptoms of depression and rs7582472 (near to MGAT5 and NCKAP5) was replicated in two independent samples, but other replication findings were less consistent. Gene‐based tests identified a significant locus on chromosome 15 (spanning five genes) associated with neuroticism which replicated (P < 0.05) in an independent cohort. Support for common genetic effects among personality and mood (particularly neuroticism and depressive symptoms) was found in terms of SNP association overlap and polygenic score prediction. The variance explained by individual SNPs was very small (up to 1%) confirming that there are no moderate/large effects of common SNPs on personality and related traits.

Maternal vitamin D concentrations during pregnancy, fetal growth patterns, and risks of adverse birth outcomes

BACKGROUND Maternal vitamin D deficiency during pregnancy may affect fetal outcomes. OBJECTIVE The objective of this study was to examine whether maternal 25-hydroxyvitamin D [25(OH)D] concentrations in pregnancy affect fetal growth patterns and birth outcomes. DESIGN This was a population-based prospective cohort in Rotterdam, Netherlands in 7098 mothers and their offspring. We measured 25(OH)D concentrations at a median gestational age of 20.3 wk (range: 18.5-23.3 wk). Vitamin D concentrations were analyzed continuously and in quartiles. Fetal head circumference and body length and weight were estimated by repeated ultrasounds, and preterm birth (gestational age <37 wk) and small size for gestational age (less than the fifth percentile) were determined. RESULTS Adjusted multivariate regression analyses showed that, compared with mothers with second-trimester 25(OH)D concentrations in the highest quartile, those with 25(OH)D concentrations in the lower quartiles had offspring with third-trimester fetal growth restriction, leading to a smaller head circumference, shorter body length, and lower body weight at birth (all P < 0.05). Mothers who had 25(OH)D concentrations in the lowest quartile had an increased risk of preterm delivery (OR: 1.72; 95% CI: 1.14, 2.60) and children who were small for gestational age (OR: 2.07; 95% CI: 1.33, 3.22). The estimated population attributable risk of 25(OH)D concentrations <50 nmol/L for preterm birth or small size for gestational age were 17.3% and 22.6%, respectively. The observed associations were not based on extreme 25(OH)D deficiency, but presented within the common ranges. CONCLUSIONS Low maternal 25(OH)D concentrations are associated with proportional fetal growth restriction and with an increased risk of preterm birth and small size for gestational age at birth. Further studies are needed to investigate the causality of these associations and the potential for public health interventions.

Genetic influences on 'environmental’ factors

Childhood environment, social environment and behavior, leisure time activities and life events have been hypothesized to contribute to individual differences in cognitive abilities and physical and emotional well‐being. These factors are often labeled ‘environmental’, suggesting they shape but not reflect individual differences in behavior. The aim of this study is to test the hypothesis that these factors are not randomly distributed across the population but reflect heritable individual differences. Self‐report data on Childhood Environment, Social Environment and Behavior, Leisure Time Activities and Life Events were obtained from 560 adult twins and siblings (mean age 47.11 years). Results clearly show considerable genetic influences on these factors with mean broad heritability of 0.49 (0.00–0.87). This suggests that what we think of as measures of ‘environment’ are better described as external factors that might be partly under genetic control. Understanding causes of individual differences in external factors may aid in clarifying the intricate nature between genetic and environmental influences on complex traits.