Estimation and partition of heritability in human populations using whole-genome analysis methods.

Understanding genetic variation of complex traits in human populations has moved from the quantification of the resemblance between close relatives to the dissection of genetic variation into the contributions of individual genomic loci. However, major questions remain unanswered: How much phenotypic variation is genetic; how much of the genetic variation is additive and can be explained by fitting all genetic variants simultaneously in one model, and what is the joint distribution of effect size and allele frequency at causal variants? We review and compare three whole-genome analysis methods that use mixed linear models (MLMs) to estimate genetic variation. In all methods, genetic variation is estimated from the relationship between close or distant relatives on the basis of pedigree information and/or single nucleotide polymorphisms (SNPs). We discuss theory, estimation procedures, bias, and precision of each method and review recent advances in the dissection of genetic variation of complex traits in human populations. By using genome-wide data, it is now established that SNPs in total account for far more of the genetic variation than the statistically highly significant SNPs that have been detected in genome-wide association studies. All SNPs together, however, do not account for all of the genetic variance estimated by pedigree-based methods. We explain possible reasons for this remaining "missing heritability."

Dominance genetic variation contributes little to the missing heritability for human complex traits.

For human complex traits, non-additive genetic variation has been invoked to explain "missing heritability," but its discovery is often neglected in genome-wide association studies. Here we propose a method of using SNP data to partition and estimate the proportion of phenotypic variance attributed to additive and dominance genetic variation at all SNPs (hSNP(2) and δSNP(2)) in unrelated individuals based on an orthogonal model where the estimate of hSNP(2) is independent of that of δSNP(2). With this method, we analyzed 79 quantitative traits in 6,715 unrelated European Americans. The estimate of δSNP(2) averaged across all the 79 quantitative traits was 0.03, approximately a fifth of that for additive variation (average hSNP(2) = 0.15). There were a few traits that showed substantial estimates of δSNP(2), none of which were replicated in a larger sample of 11,965 individuals. We further performed genome-wide association analyses of the 79 quantitative traits and detected SNPs with genome-wide significant dominance effects only at the ABO locus for factor VIII and von Willebrand factor. All these results suggest that dominance variation at common SNPs explains only a small fraction of phenotypic variation for human complex traits and contributes little to the missing narrow-sense heritability problem.

Genome-wide genetic homogeneity between sexes and populations for human height and body mass index.

Sex-specific genetic effects have been proposed to be an important source of variation for human complex traits. Here we use two distinct genome-wide methods to estimate the autosomal genetic correlation (rg) between men and women for human height and body mass index (BMI), using individual-level (n = ∼44 000) and summary-level (n = ∼133 000) data from genome-wide association studies. Results are consistent and show that the between-sex genetic correlation is not significantly different from unity for both traits. In contrast, we find evidence of genetic heterogeneity between sexes for waist-hip ratio (rg = ∼0.7) and between populations for BMI (rg = ∼0.9 between Europe and the USA) but not for height. The lack of evidence for substantial genetic heterogeneity for body size is consistent with empirical findings across traits and species.

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.

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.

Genes influence the amplitude and timing of brain hemodynamic responses.

In functional magnetic resonance imaging (fMRI), the hemodynamic response function (HRF) reflects regulation of regional cerebral blood flow in response to neuronal activation. The HRF varies significantly between individuals. This study investigated the genetic contribution to individual variation in HRF using fMRI data from 125 monozygotic (MZ) and 149 dizygotic (DZ) twin pairs. The resemblance in amplitude, latency, and duration of the HRF in six regions in the frontal and parietal lobes was compared between MZ and DZ twin pairs. Heritability was estimated using an ACE (Additive genetic, Common environmental, and unique Environmental factors) model. The genetic influence on the temporal profile and amplitude of HRF was moderate to strong (24%-51%). The HRF may be used in the genetic analysis of diseases with a cerebrovascular etiology.

Genetic and environmental contributions to the inverse association between specific autistic traits and experience seeking in adults.

Autistic traits are characterized by social and communication problems, restricted, repetitive and stereotyped patterns of behavior, interests and activities. The relation between autistic traits and personality characteristics is largely unknown. This study focused on the relation between five specific autistic traits measured with the abridged version of the Autism Spectrum Quotient ("social problems," "preference for routine," "attentional switching difficulties," "imagination impairments," "fascination for numbers and patterns") and Experience Seeking (ES) in a general population sample of adults, and subsequently investigated the genetic and environmental etiology between these traits. Self-reported data on autistic traits and ES were collected in a population sample (n = 559) of unrelated individuals, and in a population based family sample of twins and siblings (n = 560). Phenotypic, genetic and environmental associations between traits were examined in a bivariate model, accounting for sex and age differences. Phenotypically, ES correlated significantly with "preference for routine" and "imagination impairments" in both samples but was unrelated to the other autistic traits. Genetic analyses in the family sample revealed that the association between ES and "preference for routine" and "imagination impairments" could largely be explained by a shared genetic factor (89% and 70%, respectively). Our analyses demonstrated at a phenotypic and genetic level an inverse relationship between ES and specific autistic traits in adults. ES is associated with risk taking behavior such as substance abuse, antisocial behavior and financial problems. Future research could investigate whether autistic traits, in particular strong routine preference and impaired imagination skills, serve as protective factors for such risky behaviors. © 2015 Wiley Periodicals, Inc.

Heritability of Transforming Growth Factor-ß1 and Tumor Necrosis Factor-Receptor Type 1 Expression and Vitamin D Levels in Healthy Adolescent Twins.

Cytokines and vitamin D both have a role in modulating the immune system, and are also potentially useful biomarkers in mental illnesses such as major depressive disorder (MDD) and schizophrenia. Studying the variability of cytokines and vitamin D in a healthy population sample may add to understanding the association between these biomarkers and mental illness. To assess genetic and environmental contributions to variation in circulating levels of cytokines and vitamin D (25-hydroxy vitamin D: 25(OH)D3), we analyzed data from a healthy adolescent twin cohort (mean age 16.2 years; standard deviation 0.25). Plasma cytokine measures were available for 400 individuals (85 MZ, 115 DZ pairs), dried blood spot sample vitamin D measures were available for 378 individuals (70 MZ, 118 DZ pairs). Heritability estimates were moderate but significant for the cytokines transforming growth factor-ß1 (TGF-ß1), 0.57 (95% CI 0.26-0.80) and tumor necrosis factor-receptor type 1 (TNFR1), 0.50 (95% CI 0.11-0.63) respectively. Measures of 25(OH)D3 were within normal range and heritability was estimated to be high (0.86, 95% CI 0.61-0.94). Assays of other cytokines did not generate meaningful results. These potential biomarkers may be useful in mental illness, with further research warranted in larger sample sizes. They may be particularly important in adolescents with mental illness where diagnostic uncertainty poses a significant clinical challenge.

Replicability and robustness of genome-wide-association studies for behavioral traits.

A recent genome-wide-association study of educational attainment identified three single-nucleotide polymorphisms (SNPs) whose associations, despite their small effect sizes (each R (2) ≈ 0.02%), reached genome-wide significance (p < 5 × 10(-8)) in a large discovery sample and were replicated in an independent sample (p < .05). The study also reported associations between educational attainment and indices of SNPs called "polygenic scores." In three studies, we evaluated the robustness of these findings. Study 1 showed that the associations with all three SNPs were replicated in another large (N = 34,428) independent sample. We also found that the scores remained predictive (R (2) ≈ 2%) in regressions with stringent controls for stratification (Study 2) and in new within-family analyses (Study 3). Our results show that large and therefore well-powered genome-wide-association studies can identify replicable genetic associations with behavioral traits. The small effect sizes of individual SNPs are likely to be a major contributing factor explaining the striking contrast between our results and the disappointing replication record of most candidate-gene studies.

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.

The genetic aetiology of cannabis use initiation: a meta-analysis of genome-wide association studies and a SNP-based heritability estimation.

While initiation of cannabis use is around 40% heritable, not much is known about the underlying genetic aetiology. Here, we meta-analysed two genome-wide association studies of initiation of cannabis use with > 10 000 individuals. None of the genetic variants reached genome-wide significance. We also performed a gene-based association test, which also revealed no significant effects of individual genes. Finally, we estimated that only approximately 6% of the variation in cannabis initiation is due to common genetic variants. Future genetic studies using larger sample sizes and different methodologies (including sequencing) might provide more insight in the complex genetic aetiology of cannabis use.

Reconsidering the heritability of intelligence in adulthood: taking assortative mating and cultural transmission into account.

Heritability estimates of general intelligence in adulthood generally range from 75 to 85%, with all heritability due to additive genetic influences, while genetic dominance and shared environmental factors are absent, or too small to be detected. These estimates are derived from studies based on the classical twin design and are based on the assumption of random mating. Yet, considerable positive assortative mating has been reported for general intelligence. Unmodeled assortative mating may lead to biased estimates of the relative magnitude of genetic and environmental factors. To investigate the effects of assortative mating on the estimates of the variance components of intelligence, we employed an extended twin-family design. Psychometric IQ data were available for adult monozygotic and dizygotic twins, their siblings, the partners of the twins and siblings, and either the parents or the adult offspring of the twins and siblings (N = 1314). Two underlying processes of assortment were considered: phenotypic assortment and social homogamy. The phenotypic assortment model was slightly preferred over the social homogamy model, suggesting that assortment for intelligence is mostly due to a selection of mates on similarity in intelligence. Under the preferred phenotypic assortment model, the variance of intelligence in adulthood was not only due to non-shared environmental (18%) and additive genetic factors (44%) but also to non-additive genetic factors (27%) and phenotypic assortment (11%).This non-additive nature of genetic influences on intelligence needs to be accommodated in future GWAS studies for intelligence.

Interaction between experience seeking and genetic and environmental influences on general cognitive ability.

Although it is well established that experience seeking behavior (ES) is positively related to cognitive functioning, the mechanisms underlying this association are not clearly understood. In a large sample of adult twins and siblings (N = 864, age range 23-75), we studied the causes of covariation between ES and general cognitive ability and we studied whether ES moderates the genetic and environmental causes of variation in general cognitive ability. Results demonstrate a phenotypic correlation of .17 (p <.001) between general cognitive ability and ES, with a common genetic and common environmental background. Moreover, the extent to which genetic and environmental factors are shared between general cognitive ability and ES is increased in individuals with either lower or higher levels of ES. In addition, the extent to which genetic and environmental factors influence individual differences in general cognitive ability in adults partly depended on ES. Standardized influences of additive genetic factors on general cognitive ability ranged from 13% to 99%, with lower estimates in higher levels of ES, while standardized estimates of environmental factors ranged from almost 1% to 87%, with higher estimates in higher levels of ES. Hence, ES and cognitive ability are not only associated through common genetic and environmental factors, but also via moderating effects of genetic and environmental influences on cognitive ability by ES. These findings have implications for future studies on the association between ES and general cognitive ability, and for future research on the genetics of cognitive ability.

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.

Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. METHODS: Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. RESULTS: The ASD (p = 6.1e-13), sibling (p = 4.9e-3) and unrelated (p = 3.0e-3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height-a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e-3) and parents (r = 0.17, p = 8.0e-7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e-3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. LIMITATIONS: This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. CONCLUSIONS: We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair).

Individual differences in processing speed and working memory speed as assessed with the Sternberg memory scanning task.

The Sternberg Memory Scanning (SMS) task provides a measure of processing speed (PS) and working memory retrieval speed (WMS). In this task, participants are presented with sets of stimuli that vary in size. After a delay, one item is presented, and participants indicate whether or not the item was part of the set. Performance is assessed by speed and accuracy for both the positive (item is part of the set) and the negative trials (items is not part of the set). To examine the causes of variation in PS and WMS, 623 adult twins and their siblings completed the SMS task. A non-linear growth curve (nLGC) model best described the increase in reaction time with increasing set size. Genetic analyses showed that WMS (modeled as the Slope in the nLGC model) has a relatively small variance which is not due to genetic variation while PS (modeled as the Intercept in the nLGC model) showed large individual differences, part of which could be attributed to additive genetic factors. Heritability was 38% for positive and 32% for negative trials. Additional multivariate analyses showed that the genetic effects on PS for positive and negative trials were completely shared. We conclude that genetic influences on working memory performance are more likely to act upon basic processing speed and (pre)motoric processes than on the speed with which an item is retrieved from short term memory.

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration.

Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identify 143 independent loci in 112 1-Mb regions, providing insights into the physiology of vitamin D and implicating genes involved in lipid and lipoprotein metabolism, dermal tissue properties, and the sulphonation and glucuronidation of 25OHD. Mendelian randomization models find no robust evidence that 25OHD concentration has causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes have (direct or indirect) causal effects on 25OHD concentration, clarifying the epidemiological relationship between 25OHD status and the health outcomes examined in this study.

Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis.

We conducted DNA methylation association analyses using Illumina 450K data from whole blood for an Australian amyotrophic lateral sclerosis (ALS) case-control cohort (782 cases and 613 controls). Analyses used mixed linear models as implemented in the OSCA software. We found a significantly higher proportion of neutrophils in cases compared to controls which replicated in an independent cohort from the Netherlands (1159 cases and 637 controls). The OSCA MOMENT linear mixed model has been shown in simulations to best account for confounders. When combined in a methylation profile score, the 25 most-associated probes identified by MOMENT significantly classified case-control status in the Netherlands sample (area under the curve, AUC = 0.65, CI95% = [0.62-0.68], p = 8.3 × 10-22). The maximum AUC achieved was 0.69 (CI95% = [0.66-0.71], p = 4.3 × 10-34) when cell-type proportion was included in the predictor.

The heritability of aptitude and exceptional talent across different domains in adolescents and young adults.

The origin of individual differences in aptitude, defined as a domain-specific skill within the normal ability range, and talent, defined as a domain specific skill of exceptional quality, is under debate. The nature of the variation in aptitudes and exceptional talents across different domains was investigated in a population based twin sample. Self-report data from 1,685 twin pairs (12-24 years) were analyzed for Music, Arts, Writing, Language, Chess, Mathematics, Sports, Memory, and Knowledge. The influence of shared environment was small for both aptitude and talent. Additive and non-additive genetic effects explained the major part of the substantial familial clustering in the aptitude measures with heritability estimates ranging between .32 and .71. Heritability estimates for talents were higher and ranged between .50 and .92. In general, the genetic architecture for aptitude and talent was similar in men and women. Genetic factors contribute to a large extent to variation in aptitude and talent across different domains of intellectual, creative, and sports abilities.