Population structure, migration, and diversifying selection in the Netherlands

Evidence of Assortative Mating in Autism Spectrum Disorder

BACKGROUND

Assortative mating is a nonrandom mating system in which individuals with similar genotypes and/or phenotypes mate with one another more frequently than would be expected in a random mating system. Assortative mating has been hypothesized to play a role in autism spectrum disorder (ASD) in an attempt to explain some of the increase in the prevalence of ASD that has recently been observed. ASD is considered to be a heritable neurodevelopmental disorder, but there is limited understanding of its causes. Assortative mating can be explored through both phenotypic and genotypic data, but up until now it has never been investigated through genotypic measures in ASD.

METHODS

We investigated genotypically similar mating pairs using genome-wide single nucleotide polymorphism data on trio families (Autism Genome Project data [1590 parents] and Simons Simplex Collection data [1962 parents]). To determine whether or not an excess in genetic similarity was present, we employed kinship coefficients and examined spousal correlation between the principal components in both the Autism Genome Project and Simons Simplex Collection datasets. We also examined assortative mating using phenotype data on the parents to detect any correlation between ASD traits.

RESULTS

We found significant evidence of genetic similarity between the parents of ASD offspring using both methods in the Autism Genome Project dataset. In the Simons Simplex Collection, there was also significant evidence of genetic similarity between the parents when explored through spousal correlation.

CONCLUSIONS

This study gives further support to the hypothesis that positive assortative mating plays a role in ASD.

Genetic Similarity Assessment of Twin-Family Populations by Custom-Designed Genotyping Array

Twin registries often take part in large collaborative projects and are major contributors to genome-wide association (GWA) meta-analysis studies. In this article, we describe genotyping of twin-family populations from Australia, the Midwestern USA (Avera Twin Register), the Netherlands (Netherlands Twin Register), as well as a sample of mothers of twins from Nigeria to assess the extent, if any, of genetic differences between them. Genotyping in all cohorts was done using a custom-designed Illumina Global Screening Array (GSA), optimized to improve imputation quality for population-specific GWA studies. We investigated the degree of genetic similarity between the populations using several measures of population variation with genotype data generated from the GSA. Visualization of principal component analysis (PCA) revealed that the Australian, Dutch and Midwestern American populations exhibit negligible interpopulation stratification when compared to each other, to a reference European population and to globally distant populations. Estimations of fixation indices (FST values) between the Australian, Midwestern American and Netherlands populations suggest minimal genetic differentiation compared to the estimates between each population and a genetically distinct cohort (i.e., samples from Nigeria genotyped on GSA). Thus, results from this study demonstrate that genotype data from the Australian, Dutch and Midwestern American twin-family populations can be reasonably combined for joint-genetic analysis.

The Effect of Neutral Recombination Variation on Genome Scans for Selection

Recently, there has been an increasing interest in identifying the role that regions of low recombination or inversion play in adaptation of species to local environments. Many examples of groups of adapted genes located within inversions are arising in the literature, in part inspired by theory that predicts the evolution of these so-called “supergenes.” We still, however, have a poor understanding of how genomic heterogeneity, such as varying rates of recombination, may confound signals of selection. Here, I evaluate the effect of neutral inversions and recombination variation on genome scans for selection, including tests for selective sweeps, differentiation outlier tests, and association tests. There is considerable variation among methods in their performance, with some methods being unaffected and some showing elevated false positive signals within a neutral inversion or region of low recombination. In some cases the false positive signal can be dampened or removed, if it is possible to use a quasi-independent set of SNPs to parameterize the model before performing the test. These results will be helpful to those seeking to understand the importance of regions of low recombination in adaptation.

A Genetic Investigation of the Well-Being Spectrum

The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we constructed polygenic risk scores for the 3-WBS and used this score to predict a series of traits that have been associated with well-being in the literature. We included information on loneliness, big five personality traits, self-rated health, and flourishing. The 3-WBS polygenic score predicted all the original 3-WBS traits and additionally loneliness, self-rated health, and extraversion (R² between 0.62% and 1.58%). Next, using LD score regression, we calculated genetic correlations between the 3-WBS and the traits of interest. From all candidate traits, loneliness and self-rated health were found to have the strongest genetic correlations (r_g = - 0.79, and r_g= 0.64, respectively) with the 3-WBS. Lastly, we use Genomic SEM to investigate the factor structure of the proposed spectrum. The best model fit was obtained for a two-factor model including the 5-WBS traits, with two highly correlated factors representing the negative- and positive end of the spectrum. Based on these analyses we propose to include loneliness and self-rated health in the WBS and use a 5-phenotype well-being spectrum in future studies to gain more insight into the determinants of human well-being.

Association Between Population Density and Genetic Risk for Schizophrenia

Importance

Urban life has been proposed as an environmental risk factor accounting for the increased prevalence of schizophrenia in urban areas. An alternative hypothesis is that individuals with increased genetic risk tend to live in urban/dense areas.

Objective

To assess whether adults with higher genetic risk for schizophrenia have an increased probability to live in more populated areas than those with lower risk.

Design, Setting, and Participants

Four large, cross-sectional samples of genotyped individuals of European ancestry older than 18 years with known addresses in Australia, the United Kingdom, and the Netherlands were included in the analysis. Data were based on the postcode of residence at the time of last contact with the participants. Community-based samples who took part in studies conducted by the Queensland Institute for Medical Research Berghofer Medical Research Institute (QIMR), UK Biobank (UKB), Netherlands Twin Register (NTR), or QSkin Sun and Health Study (QSKIN) were included. Genome-wide association analysis and mendelian randomization (MR) were included. The study was conducted between 2016 and 2018.

Exposures

Polygenic risk scores for schizophrenia derived from genetic data (genetic risk is independently measured from the occurrence of the disease). Socioeconomic status of the area was included as a moderator in some of the models.

Main Outcomes and Measures

Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested.

Results

The QIMR participants (15 544; 10 197 [65.6%] women; mean [SD] age, 54.4 [13.2] years) living in more densely populated areas (people per square kilometer) had a higher genetic loading for schizophrenia (r2 = 0.12%; P = 5.69 × 10-5), a result that was replicated across all 3 other cohorts (UKB: 345 246; 187 469 [54.3%] women; age, 65.7 [8.0] years; NTR: 11 212; 6727 [60.0%] women; age, 48.6 [17.5] years; and QSKIN: 15 726; 8602 [54.7%] women; age, 57.0 [7.9] years). This genetic association could account for 1.7% (95% CI, 0.8%-3.2%) of the schizophrenia risk. Estimates from MR analyses performed in the UKB sample were significant (b = 0.049; P = 3.7 × 10-7 using GSMR), suggesting that the genetic liability to schizophrenia may have a causal association with the tendency to live in urbanized locations.

Conclusions and Relevance

The results of this study appear to support the hypothesis that individuals with increased genetic risk tend to live in urban/dense areas and suggest the need to refine the social stress model for schizophrenia by including genetics as well as possible gene-environment interactions.

Associations between loneliness and personality are mostly driven by a genetic association with Neuroticism

OBJECTIVE

Loneliness is an aversive response to a discrepancy between desired and actual social relationships and correlates with personality. We investigate the relationship of loneliness and personality in twin family and molecular genetic data.

METHOD

Phenotypic correlations between loneliness and the Big Five personality traits were estimated in 29,625 adults, and in a group with genome-wide genotype data (N = 4,222), genetic correlations were obtained. We explored whether genetic correlations may reflect causal relationships by investigating within monozygotic twin pair differences (N_pairs  = 2,662), by longitudinal within-subject changes in personality and loneliness (N = 4,260-9,238 longitudinal comparisons), and by longitudinal cross-lagged panel analyses (N = 15,628). Finally, we tested whether genetic correlations were due to cross-trait assortative mating (N_{spouse pairs}  = 4,436).

RESULTS

The strongest correlations with loneliness were observed for Neuroticism (r = .55) and Extraversion (r = -.33). Only Neuroticism showed a high correlation with loneliness independent of other personality traits (r = .50), so follow-up analyses focused on Neuroticism. The genetic correlation between loneliness and Neuroticism from genotyped variants was .71; a significant reciprocal causal relationship and nonsignificant cross-trait assortative mating imply that this is at least partly due to mediated pleiotropy.

CONCLUSIONS

We show that the relationship between loneliness and personality is largely explained by its relationship with Neuroticism, which is substantially genetic in nature.

Associations between Oxytocin Receptor (OXTR) Genotype and Elementary School Children's Likability, Dis-likability and Friendship among Classroom Peers: A Longitudinal Study

The single nucleotide polymorphism rs53576 of the oxytocin receptor (OXTR) gene is involved in forming and maintaining relationships in various social contexts. However, this has not been studied in the childhood peer context. The present study followed 359 children (51.6% girls) from age 9 to 12 to explore associations between OXTR rs53576 genotype (i.e., AA, AG or GG genotype) and three indicators of children’s relationships with peers: likability and dis-likability among, and friendship with, classroom peers. Our results showed that OXTR rs53576 was associated with likability among boys, but not with dis-likability and friendship or among girls. Boys with an A and a G allele (i.e., AG genotype) became increasingly more liked by their peers across the four-year studied period than those with two A alleles or two G alleles (i.e., AA and GG genotype). This study indicates that OXTR rs53576 genotype might influence children’s peer relationships, particularly their likeability among peers. Associations between OXTR rs53576 and peer relationships may differ depending on children’s sex and the specific type of peer-relationship under scrutiny.

Predicting loneliness with polygenic scores of social, psychological and psychiatric traits

Loneliness is a heritable trait that accompanies multiple disorders. The association between loneliness and mental health indices may partly be due to inherited biological factors. We constructed polygenic scores for 27 traits related to behavior, cognition and mental health and tested their prediction for self-reported loneliness in a population-based sample of 8798 Dutch individuals. Polygenic scores for major depressive disorder (MDD), schizophrenia and bipolar disorder were significantly associated with loneliness. Of the Big Five personality dimensions, polygenic scores for neuroticism and conscientiousness also significantly predicted loneliness, as did the polygenic scores for subjective well-being, tiredness and self-rated health. When including all polygenic scores simultaneously into one model, only 2 major depression polygenic scores remained as significant predictors of loneliness. When controlling only for these 2 MDD polygenic scores, only neuroticism and schizophrenia remain significant. The total variation explained by all polygenic scores collectively was 1.7%. The association between the propensity to feel lonely and the susceptibility to psychiatric disorders thus pointed to a shared genetic etiology. The predictive power of polygenic scores will increase as the power of the genome-wide association studies on which they are based increases and may lead to clinically useful polygenic scores that can inform on the genetic predisposition to loneliness and mental health.

Dopaminergic Genetic Variants and Voluntary Externally Paced Exercise Behavior

PURPOSE

Most candidate gene studies on the neurobiology of voluntary exercise behavior have focused on the dopaminergic signaling pathway and its role in the mesolimbic reward system. We hypothesized that dopaminergic candidate genes may influence exercise behavior through additional effects on executive functioning and that these effects are only detected when the types of exercise activity are taken into account.

METHODS

Data on voluntary exercise behavior and at least one single-nucleotide polymorphism/variable number of tandem repeat (VNTR) were available for 12,929 participants of the Netherlands Twin Registry. Exercise activity was classified as externally paced if a high level of executive function skill was required. The total volume of voluntary exercise (minutes per week) as well as the volume specifically spent on externally paced activities were tested for association with nine functional dopaminergic polymorphisms (DRD1: rs265981, DRD2/ANKK1: rs1800497, DRD3: rs6280, DRD4: VNTR 48 bp, DRD5: VNTR 130-166 bp, DBH: rs2519152, DAT1: VNTR 40 bp, COMT: rs4680, MAOA: VNTR 30 bp), a polygenic score (PGS) based on nine alleles leading to lower dopamine responsiveness, and a PGS based on three alleles associated with both higher reward sensitivity and better executive functioning (DRD2/ANKK1: "G" allele, COMT: Met allele, DAT1: 440-bp allele).

RESULTS

No association with total exercise volume or externally paced exercise volume was found for individual alleles or the nine-allele PGS. The volume of externally paced exercise behavior was significantly associated with the reward and executive function congruent PGS. This association was driven by the DAT1 440-bp and COMT Met allele, which acted as increaser alleles for externally paced exercise behavior.

CONCLUSIONS

Taking into account the types of exercise activity may increase the success of identifying genetic variants and unraveling the neurobiology of voluntary exercise behavior.

Polygenic risk for alcohol consumption and its association with alcohol-related phenotypes: Do stress and life satisfaction moderate these relationships?

BACKGROUND

Genetic and environmental factors contribute about equally to alcohol-related phenotypes in adulthood. In the present study, we examined whether more stress at home or low satisfaction with life might be associated with heavier drinking or more alcohol-related problems in individuals with a high genetic susceptibility to alcohol use.

METHODS

Information on polygenic scores and drinking behavior was available in 6705 adults (65% female; 18-83 years) registered with the Netherlands Twin Register. Polygenic risk scores (PRSs) were constructed for all subjects based on the summary statistics of a large genome-wide association meta-analysis on alcohol consumption (grams per day). Outcome measures were quantity of alcohol consumption and alcohol-related problems assessed with the Alcohol Use Disorders Identification Test (AUDIT). Stress at home and life satisfaction were moderating variables whose significance was tested by Generalized Estimating Equation analyses taking familial relatedness, age and sex into account.

RESULTS

PRSs for alcohol were significantly associated with quantity of alcohol consumption and alcohol-related problems in the past year (R²=0.11% and 0.10% respectively). Participants who reported to have experienced more stress in the past year and lower life satisfaction, scored higher on alcohol-related problems (R²=0.27% and 0.29 respectively), but not on alcohol consumption. Stress and life satisfaction did not moderate the association between PRSs and the alcohol outcome measures.

CONCLUSIONS

There were significant main effects of polygenic scores and of stress and life satisfaction on drinking behavior, but there was no support for PRS-by-stress or PRS-by-life satisfaction interactions on alcohol consumption and alcohol-related problems.

The black legend on the Spanish presence in the low countries: Verifying shared beliefs on genetic ancestry

OBJECTIVES

War atrocities committed by the Spanish army in the Low Countries during the 16th century are so ingrained in the collective memory of Belgian and Dutch societies that they generally assume a signature of this history to be present in their genetic ancestry. Historians claim this assumption is a consequence of the so-called "Black Legend" and negative propaganda portraying and remembering Spanish soldiers as extreme sexual aggressors. The impact of the presence of Spaniards during the Dutch Revolt on the genetic variation in the Low Countries has been verified in this study.

MATERIALS AND METHODS

A recent population genetic analysis of Iberian-associated Y-chromosomal variation among Europe is enlarged with representative samples of Dutch (N = 250) and Flemish (N = 1,087) males. Frequencies of these variants are also compared between donors whose oldest reported paternal ancestors lived in-nowadays Flemish-cities affected by so-called Spanish Furies (N = 116) versus other patrilineages in current Flemish territory (N = 971).

RESULTS

The frequencies of Y-chromosomal markers Z195 and SRY2627 decline steeply going north from Spain and the data for the Flemish and Dutch populations fits within this pattern. No trend of higher frequencies of these variants has been found within the well-ascertained samples associated with Spanish Fury cities.

DISCUSSION

Although sexual aggression did occur in the 16th century, these activities did not leave a traceable "Spanish" genetic signature in the autochthonous genome of the Low Countries. Our results support the view that the 'Black Legend' and historical propaganda on sexual aggression have nurtured today's incorrect assumptions regarding genetic ancestry.

2SNP heritability and effects of genetic variants for neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are important biomarkers for disease development and progression. To gain insight into the genetic causes of variance in NLR and PLR in the general population, we conducted genome-wide association (GWA) analyses and estimated SNP heritability in a sample of 5901 related healthy Dutch individuals. GWA analyses identified a new genome-wide significant locus on the HBS1L-MYB intergenic region for PLR, which replicated in a sample of 2538 British twins. For platelet count, we replicated three known genome-wide significant loci in our cohort (at CCDC71L-PIK3CG, BAK1 and ARHGEF3). For neutrophil count, we replicated the PSMD3 locus. For the identified top SNPs, we found significant cis and trans expression quantitative trait loci effects for several loci involved in hematological and immunological pathways. Linkage Disequilibrium score (LD) regression analyses for PLR and NLR confirmed that both traits are heritable, with a polygenetic SNP heritability for PLR of 14.1%, and for NLR of 2.4%. Genetic correlations were present between ratios and the constituent counts, with the genetic correlation (r=0.45) of PLR with platelet count reaching statistical significance. In conclusion, we established that two important biomarkers have a significant heritable SNP component, and identified the first genome-wide locus for PLR.

HPA Axis Genes, and Their Interaction with Childhood Maltreatment, are Related to Cortisol Levels and Stress-Related Phenotypes

Stress responses are controlled by the hypothalamus pituitary adrenal (HPA)-axis and maladaptive stress responses are associated with the onset and maintenance of stress-related disorders such as major depressive disorder (MDD). Genes that play a role in the HPA-axis regulation may likely contribute to the relation between relevant neurobiological substrates and stress-related disorders. Therefore, we performed gene-wide analyses for 30 a priori literature-based genes involved in HPA-axis regulation in 2014 subjects (34% male; mean age: 42.5) to study the relations with lifetime MDD diagnosis, cortisol awakening response, and dexamethasone suppression test (DST) levels (subsample N=1472) and hippocampal and amygdala volume (3T MR images; subsample N=225). Additionally, gene by childhood maltreatment (CM) interactions were investigated. Gene-wide significant results were found for dexamethasone suppression (CYP11A1, CYP17A1, POU1F1, AKR1D1), hippocampal volume (CYP17A1, CYP11A1, HSD3B2, PROP1, AVPRA1, SRD5A1), amygdala volume (POMC, CRH, HSD3B2), and lifetime MDD diagnosis (FKBP5 and CRH), all permutation p-values<0.05. Interactions with CM were found for several genes; the strongest interactions were found for NR3C2, where the minor allele of SNP rs17581262 was related to smaller hippocampal volume, smaller amygdala volume, higher DST levels, and higher odds of MDD diagnosis only in participants with CM. As hypothesized, several HPA-axis genes are associated with stress-related endophenotypes including cortisol response and reduced brain volumes. Furthermore, we found a pleiotropic interaction between CM and the mineralocorticoid receptor gene, suggesting that this gene plays an important moderating role in stress and stress-related disorders.

The Genetic Overlap Between Hair and Eye Color

We identified the genetic variants for eye color by Genome-Wide Association Study (GWAS) in a Dutch Caucasian family-based population sample and examined the genetic correlation between hair and eye color using data from unrelated participants from the Netherlands Twin Register. With the Genome-wide Complex Trait Analysis software package, we found strong genetic correlations between various combinations of hair and eye colors. The strongest positive correlations were found for blue eyes with blond hair (0.87) and brown eyes with dark hair (0.71), whereas blue eyes with dark hair and brown eyes with blond hair showed the strongest negative correlations (-0.64 and -0.94, respectively). Red hair with green/hazel eyes showed the weakest correlation (-0.14). All analyses were corrected for age and sex, and we explored the effects of correcting for principal components (PCs) that represent ancestry and describe the genetic stratification of the Netherlands. When including the first three PCs as covariates, the genetic correlations between the phenotypes disappeared. This is not unexpected since hair and eye colors strongly indicate the ancestry of an individual. This makes it difficult to separate the effects of population stratification and the true genetic effects of variants on these particular phenotypes.

The association of childhood maltreatment with depression and anxiety is not moderated by the oxytocin receptor gene

BACKGROUND

The oxytocin receptor (OXTR) gene may be involved in resilience or vulnerability towards stress, and hence in the development of stress-related disorders. There are indications that OXTR single nucleotide polymorphisms (SNPs) interact with early life stressors in predicting levels of depression and anxiety. To replicate and extend these findings, we examined whether three literature-based OXTR SNPs (rs2254298, rs53576, rs2268498) interact with childhood maltreatment in the development of clinically diagnosed depression and anxiety disorders.

METHODS

We included 2567 individuals from the Netherlands Study of Depression and Anxiety. This sample consisted of 387 healthy controls, 428 people with a current or past depressive disorder, 243 people with a current or past anxiety disorder, and 1509 people with both lifetime depression and anxiety diagnoses. Childhood maltreatment was measured with both an interview and via self-report. Additional questionnaires measured depression and anxiety sensitivity.

RESULTS

Childhood maltreatment was strongly associated with both lifetime depression and anxiety diagnoses, as well as with depression and anxiety sensitivity. However, the OXTR SNPs did not moderate these associations nor had main effects on outcomes.

CONCLUSIONS

The three OXTR gene SNPs did not interact with childhood maltreatment in predicting lifetime depression and anxiety diagnoses or sensitivity. This stresses the importance of replication studies with regard to OXTR gene variants in general populations as well as in clearly established clinical samples.

Associations between subjective well-being and subcortical brain volumes

To study the underpinnings of individual differences in subjective well-being (SWB), we tested for associations of SWB with subcortical brain volumes in a dataset of 724 twins and siblings. For significant SWB-brain associations we probed for causal pathways using Mendelian Randomization (MR) and estimated genetic and environmental contributions from twin modeling. Another independent measure of genetic correlation was obtained from linkage disequilibrium (LD) score regression on published genome-wide association summary statistics. Our results indicated associations of SWB with hippocampal volumes but not with volumes of the basal ganglia, thalamus, amygdala, or nucleus accumbens. The SWB-hippocampus relations were nonlinear and characterized by lower SWB in subjects with relatively smaller hippocampal volumes compared to subjects with medium and higher hippocampal volumes. MR provided no evidence for an SWB to hippocampal volume or hippocampal volume to SWB pathway. This was in line with twin modeling and LD-score regression results which indicated non-significant genetic correlations. We conclude that low SWB is associated with smaller hippocampal volume, but that genes are not very important in this relationship. Instead other etiological factors, such as exposure to stress and stress hormones, may exert detrimental effects on SWB and the hippocampus to bring about the observed association.

Conditional eQTL analysis reveals allelic heterogeneity of gene expression

In recent years, multiple eQTL (expression quantitative trait loci) catalogs have become available that can help understand the functionality of complex trait-related single nucleotide polymorphisms (SNPs). In eQTL catalogs, gene expression is often strongly associated with multiple SNPs, which may reflect either one or multiple independent associations. Conditional eQTL analysis allows a distinction between dependent and independent eQTLs. We performed conditional eQTL analysis in 4,896 peripheral blood microarray gene expression samples. Our analysis showed that 35% of genes with a cis eQTL have at least two independent cis eQTLs; for several genes up to 13 independent cis eQTLs were identified. Also, 12% (671) of the independent cis eQTLs identified in conditional analyses were not significant in unconditional analyses. The number of GWAS catalog SNPs identified as eQTL in the conditional analyses increases with 24% as compared to unconditional analyses. We provide an online conditional cis eQTL mapping catalog for whole blood (https://eqtl.onderzoek.io/), which can be used to lookup eQTLs more accurately than in standard unconditional whole blood eQTL databases.

A Genetic Population Isolate in The Netherlands Showing Extensive Haplotype Sharing and Long Regions of Homozygosity

Genetic isolated populations have features that may facilitate genetic analyses and can be leveraged to improve power of mapping genes to complex traits. Our aim was to test the extent to which a population with a former history of geographic isolation and religious endogamy, and currently with one of the highest fertility rates in The Netherlands, shows signs of genetic isolation. For this purpose, genome-wide genotype data was collected of 72 unrelated individuals from this population as well as in a sample of 104 random control subjects from The Netherlands. Additional reference data from different populations and population isolates was available through HapMap and the Human Genome Diversity Project. We performed a number of analyses to compare the genetic structure between these populations: we calculated the pairwise genetic distance between populations, examined the extent of identical-by-descent (IBD) sharing and estimated the effective population size. Genetic analysis of this population showed consistent patterns of a population isolate at all levels tested. We confirmed that this population is most closely related to the Dutch control subjects, and detected high levels of IBD sharing and runs of homozygosity at equal or even higher levels than observed in previously described population isolates. The effective population size of this population was estimated to be several orders of magnitude smaller than that of the Dutch control sample. We conclude that the geographic isolation of this population combined with rapid population growth has resulted in a genetic isolate with great potential value for future genetic studies.

Temporal Genetic Dynamics of an Experimental, Biparental Field Population of Phytophthora capsici

Defining the contributions of dispersal, reproductive mode, and mating system to the population structure of a pathogenic organism is essential to estimating its evolutionary potential. After introduction of the devastating plant pathogen, Phytophthora capsici, into a grower's field, a lack of aerial spore dispersal restricts migration. Once established, coexistence of both mating types results in formation of overwintering recombinant oospores, engendering persistent pathogen populations. To mimic these conditions, in 2008, we inoculated a field with two P. capsici isolates of opposite mating type. We analyzed pathogenic isolates collected in 2009-2013 from this experimental population, using genome-wide single-nucleotide polymorphism markers. By tracking heterozygosity across years, we show that the population underwent a generational shift; transitioning from exclusively F1 in 2009-2010, to multi-generational in 2011, and ultimately all inbred in 2012-2013. Survival of F1 oospores, characterized by heterozygosity excess, coupled with a low rate of selfing, delayed declines in heterozygosity due to inbreeding and attainment of equilibrium genotypic frequencies. Large allele and haplotype frequency changes in specific genomic regions accompanied the generational shift, representing putative signatures of selection. Finally, we identified an approximately 1.6 Mb region associated with mating type determination, constituting the first detailed genomic analysis of a mating type region (MTR) in Phytophthora. Segregation patterns in the MTR exhibited tropes of sex-linkage, where maintenance of allele frequency differences between isolates of opposite mating type was associated with elevated heterozygosity despite inbreeding. Characterizing the trajectory of this experimental system provides key insights into the processes driving persistent, sexual pathogen populations.

Using Clinical Characteristics to Identify Which Patients With Major Depressive Disorder Have a Higher Genetic Load for Three Psychiatric Disorders

BACKGROUND

Limited successes of gene finding for major depressive disorder (MDD) may be partly due to phenotypic heterogeneity. We tested whether the genetic load for MDD, bipolar disorder, and schizophrenia (SCZ) is increased in phenotypically more homogenous MDD patients identified by specific clinical characteristics.

METHODS

Patients (n = 1539) with a DSM-IV MDD diagnosis and control subjects (n = 1792) were from two large cohort studies (Netherlands Study of Depression and Anxiety and Netherlands Twin Register). Genomic profile risk scores (GPRSs) for MDD, bipolar disorder, and SCZ were based on meta-analysis results of the Psychiatric Genomics Consortium. Regression analyses (adjusted for year of birth, sex, three principal components) examined the association between GPRSs with characteristics and GPRSs with MDD subgroups stratified according to the most relevant characteristics. The proportion of liability variance explained by GPRSs for each MDD subgroup was estimated.

RESULTS

GPRS-MDD explained 1.0% (p = 4.19e^-09) of MDD variance, and 1.5% (p = 4.23e^-09) for MDD endorsing nine DSM symptoms. GPRS-bipolar disorder explained 0.6% (p = 2.97e^-05) of MDD variance and 1.1% (p = 1.30e^-05) for MDD with age at onset <18 years. GPRS-SCZ explained 2.0% (p = 6.15e^-16) of MDD variance, 2.6% (p = 2.88e^-10) for MDD with higher symptom severity, and 2.3% (p = 2.26e^-13) for MDD endorsing nine DSM symptoms. An independent sample replicated the same pattern of stronger associations between cases with more DSM symptoms, as compared to overall MDD, and GPRS-SCZ.

CONCLUSIONS

MDD patients with early age at onset and higher symptom severity have an increased genetic risk for three major psychiatric disorders, suggesting that it is useful to create phenotypically more homogenous groups when searching for genes associated with MDD.

Heritability and GWAS Studies for Monocyte-Lymphocyte Ratio

The monocyte-lymphocyte ratio (MLR) is a useful biomarker for disease development, but little is known about the extent to which genetic and environmental factors influence MLR variation. Here, we study the genetic architecture of MLR and determine the influence of demographic and lifestyle factors on MLR in data from a Dutch non-patient twin-family population. Data were obtained in 9,501 individuals from the Netherlands Twin Register. We used regression analyses to determine the effects of age, sex, smoking, and body mass index (BMI) on MLR and its subcomponents. Data on twins, siblings and parents (N = 7,513) were analyzed by genetic structural equation modeling to establish heritability and genome wide single nucleotide polymorphism (SNP) data from a genotyped subsample (N = 5,892) and used to estimate heritability explained by SNPs. SNP and phenotype data were also analyzed in a genome-wide association study to identify the genes involved in MLR. Linkage disequilibrium (LD) score regression and expression quantitative trait loci (eQTL) analyses were performed to further explore the genetic findings. Results showed that age, sex, and age × sex interaction effects were present for MLR and its subcomponents. Variation in MLR was not related to BMI, but smoking was positively associated with MLR. Heritability was estimated at 40% for MLR, 58% for monocyte, and 58% for lymphocyte count. The Genome-wide association study (GWAS) identified a locus on ITGA4 that was associated with MLR and only marginally significantly associated with monocyte count. For monocyte count, additional genetic variants were identified on ITPR3, LPAP1, and IRF8. For lymphocyte count, GWAS provided no significant findings. Taking all measured SNPs together, their effects accounted for 13% of the heritability of MLR, while all known and identified genetic loci explained 1.3% of variation in MLR. eQTL analyses showed that these genetic variants were unlikely to be eQTLs. In conclusion, variation in MLR level in the general population is heritable and influenced by age, sex, and smoking. We identified gene variants in the ITGA4 gene associated with variation in MLR. The significant SNP-heritability indicates that more genetic variants are likely to be involved.

Short communication: Genetic association between schizophrenia and cannabis use

BACKGROUND AND AIM

Previous studies have shown a relationship between schizophrenia and cannabis use. As both traits are substantially heritable, a shared genetic liability could explain the association. We use two recently developed genomics methods to investigate the genetic overlap between schizophrenia and cannabis use.

METHODS

Firstly, polygenic risk scores for schizophrenia were created based on summary statistics from the largest schizophrenia genome-wide association (GWA) meta-analysis to date. We analysed the association between these schizophrenia polygenic scores and multiple cannabis use phenotypes (lifetime use, regular use, age at initiation, and quantity and frequency of use) in a sample of 6,931 individuals. Secondly, we applied LD-score regression to the GWA summary statistics of schizophrenia and lifetime cannabis use to calculate the genome-wide genetic correlation.

RESULTS

Polygenic risk scores for schizophrenia were significantly (α<0.05) associated with five of the eight cannabis use phenotypes, including lifetime use, regular use, and quantity of use, with risk scores explaining up to 0.5% of the variance. Associations were not significant for age at initiation of use and two measures of frequency of use analyzed in lifetime users only, potentially because of reduced power due to a smaller sample size. The LD-score regression revealed a significant genetic correlation of r_g=0.22 (SE=0.07, p=0.003) between schizophrenia and lifetime cannabis use.

CONCLUSIONS

Common genetic variants underlying schizophrenia and lifetime cannabis use are partly overlapping. Individuals with a stronger genetic predisposition to schizophrenia are more likely to initiate cannabis use, use cannabis more regularly, and consume more cannabis over their lifetime.

Immunometabolic dysregulation is associated with reduced cortical thickness of the anterior cingulate cortex

BACKGROUND

Immunometabolic dysregulation (low-grade inflammation and metabolic dysregulation) has been associated with the onset and more severe course of multiple psychiatric disorders, partly due to neuroanatomical changes and impaired neuroplasticity. We examined the effect of multiple markers of immunometabolic dysregulation on hippocampal and amygdala volume and anterior cingulate cortex thickness in a large sample of patients with depression and/or anxiety and healthy subjects (N=283).

METHODS

Interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-a), c-reactive protein (CRP), triglyceride levels and HDL-cholesterol and genomic profile risk scores (GPRS) for immunometabolic dysregulation were determined in peripheral blood and T1 MRI scans were acquired at 3T. Regional brain volume and cortical thickness was assessed using FreeSurfer. Covariate-adjusted linear regression analyses were performed to examine the relationship between immunometabolic dysregulation and brain volume/thickness across all subjects.

RESULTS

Multiple immunometabolic dysregulation markers (i.e. triglyceride levels and inflammation) were associated with lower rostral ACC thickness across all subjects. IL-6 was inversely associated with hippocampal and amygdala volume in healthy subjects only. GPRS for immunometabolic dysregulation were not associated with brain volume or cortical thickness.

CONCLUSIONS

Multiple serum, but not genetic immunometabolic dysregulation markers were found to relate to rostral ACC structure, suggesting that inflammation and metabolic dysregulation may impact the ACC through similar mechanisms.

Effect of childhood maltreatment and brain-derived neurotrophic factor on brain morphology

Childhood maltreatment (CM) has been associated with altered brain morphology, which may partly be due to a direct impact on neural growth, e.g. through the brain-derived neurotrophic factor (BDNF) pathway. Findings on CM, BDNF and brain volume are inconsistent and have never accounted for the entire BDNF pathway. We examined the effects of CM, BDNF (genotype, gene expression and protein level) and their interactions on hippocampus, amygdala and anterior cingulate cortex (ACC) morphology. Data were collected from patients with depression and/or an anxiety disorder and healthy subjects within the Netherlands Study of Depression and Anxiety (NESDA) (N = 289). CM was assessed using the Childhood Trauma Interview. BDNF Val66Met genotype, gene expression and serum protein levels were determined in blood and T1 MRI scans were acquired at 3T. Regional brain morphology was assessed using FreeSurfer. Covariate-adjusted linear regression analyses were performed. Amygdala volume was lower in maltreated individuals. This was more pronounced in maltreated met-allele carriers. The expected positive relationship between BDNF gene expression and volume of the amygdala is attenuated in maltreated subjects. Finally, decreased cortical thickness of the ACC was identified in maltreated subjects with the val/val genotype. CM was associated with altered brain morphology, partly in interaction with multiple levels of the BNDF pathway. Our results suggest that CM has different effects on brain morphology in met-carriers and val-homozygotes and that CM may disrupt the neuroprotective effect of BDNF.

The use of vector bootstrapping to improve variable selection precision in Lasso models

The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections. Nesting cross-validation within bootstrapping could provide further improvements in precision, but this has not been investigated systematically. We performed simulation studies of Lasso variable selection precision (VSP) with and without nesting cross-validation within bootstrapping. Data were simulated to represent genomic data under a polygenic model as well as under a model with effect sizes representative of typical GWAS results. We compared these approaches to each other as well as to software defaults for the Lasso. Nested cross-validation had the most precise variable selection at small effect sizes. At larger effect sizes, there was no advantage to nesting. We illustrated the nested approach with empirical data comprising SNPs and SNP-SNP interactions from the most significant SNPs in a GWAS of borderline personality symptoms. In the empirical example, we found that the default Lasso selected low-reliability SNPs and interactions which were excluded by bootstrapping.

Detection of gene-environment interaction in pedigree data using genome-wide genotypes

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits.

Identification of Common Genetic Variants Influencing Spontaneous Dizygotic Twinning and Female Fertility

Spontaneous dizygotic (DZ) twinning occurs in 1%-4% of women, with familial clustering and unknown physiological pathways and genetic origin. DZ twinning might index increased fertility and has distinct health implications for mother and child. We performed a GWAS in 1,980 mothers of spontaneous DZ twins and 12,953 control subjects. Findings were replicated in a large Icelandic cohort and tested for association across a broad range of fertility traits in women. Two SNPs were identified (rs11031006 near FSHB, p = 1.54 × 10(-9), and rs17293443 in SMAD3, p = 1.57 × 10(-8)) and replicated (p = 3 × 10(-3) and p = 1.44 × 10(-4), respectively). Based on ∼90,000 births in Iceland, the risk of a mother delivering twins increased by 18% for each copy of allele rs11031006-G and 9% for rs17293443-C. A higher polygenic risk score (PRS) for DZ twinning, calculated based on the results of the DZ twinning GWAS, was significantly associated with DZ twinning in Iceland (p = 0.001). A higher PRS was also associated with having children (p = 0.01), greater lifetime parity (p = 0.03), and earlier age at first child (p = 0.02). Allele rs11031006-G was associated with higher serum FSH levels, earlier age at menarche, earlier age at first child, higher lifetime parity, lower PCOS risk, and earlier age at menopause. Conversely, rs17293443-C was associated with later age at last child. We identified robust genetic risk variants for DZ twinning: one near FSHB and a second within SMAD3, the product of which plays an important role in gonadal responsiveness to FSH. These loci contribute to crucial aspects of reproductive capacity and health.

The brain-derived neurotrophic factor pathway, life stress, and chronic multi-site musculoskeletal pain

Introduction

Brain-derived neurotrophic factor (BDNF) disturbances and life stress, both independently and in interaction, have been hypothesized to induce chronic pain. We examined whether (a) the BDNF pathway (val⁶⁶met genotype, gene expression, and serum levels), (b) early and recent life stress, and (c) their interaction are associated with the presence and severity of chronic multi-site musculoskeletal pain.

Methods

Cross-sectional data are from 1646 subjects of the Netherlands Study of Depression and Anxiety. The presence and severity of chronic multi-site musculoskeletal pain were determined using the Chronic Pain Grade (CPG) questionnaire. The BDNF val⁶⁶met polymorphism, BDNF gene expression, and BDNF serum levels were measured. Early life stress before the age of 16 was assessed by calculating a childhood trauma index using the Childhood Trauma Interview. Recent life stress was assessed as the number of recent adverse life events using the List of Threatening Events Questionnaire.

Results

Compared to val⁶⁶val, BDNF met carriers more often had chronic pain, whereas no differences were found for BDNF gene expression and serum levels. Higher levels of early and recent stress were both associated with the presence and severity of chronic pain (p < 0.001). No interaction effect was found for the BDNF pathway with life stress in the associations with chronic pain presence and severity.

Conclusions

This study suggests that the BDNF gene marks vulnerability for chronic pain. Although life stress did not alter the impact of BDNF on chronic pain, it seems an independent factor in the onset and persistence of chronic pain.

Polygenic dissection of major depression clinical heterogeneity

The molecular mechanisms underlying major depressive disorder (MDD) are largely unknown. Limited success of previous genetics studies may be attributable to heterogeneity of MDD, aggregating biologically different subtypes. We examined the polygenic features of MDD and two common clinical subtypes (typical and atypical) defined by symptom profiles in a large sample of adults with established diagnoses. Data were from 1530 patients of the Netherlands Study of Depression and Anxiety (NESDA) and 1700 controls mainly from the Netherlands Twin Register (NTR). Diagnoses of MDD and its subtypes were based on DSM-IV symptoms. Genetic overlap of MDD and subtypes with psychiatric (MDD, bipolar disorder, schizophrenia) and metabolic (body mass index (BMI), C-reactive protein, triglycerides) traits was evaluated via genomic profile risk scores (GPRS) generated from meta-analysis results of large international consortia. Single nucleotide polymorphism (SNP)-heritability of MDD and subtypes was also estimated. MDD was associated with psychiatric GPRS, while no association was found for GPRS of metabolic traits. MDD subtypes had differential polygenic signatures: typical was strongly associated with schizophrenia GPRS (odds ratio (OR)=1.54, P=7.8e-9), while atypical was additionally associated with BMI (OR=1.29, P=2.7e-4) and triglycerides (OR=1.21, P=0.006) GPRS. Similar results were found when only the highly discriminatory symptoms of appetite/weight were used to define subtypes. SNP-heritability was 32% for MDD, 38% and 43% for subtypes with, respectively, decreased (typical) and increased (atypical) appetite/weight. In conclusion, MDD subtypes are characterized by partially distinct polygenic liabilities and may represent more homogeneous phenotypes. Disentangling MDD heterogeneity may help the psychiatric field moving forward in the search for molecular roots of depression.

Obsessive-compulsive symptoms in a large population-based twin-family sample are predicted by clinically based polygenic scores and by genome-wide SNPs

Variation in obsessive-compulsive symptoms (OCS) has a heritable basis, with genetic association studies starting to yield the first suggestive findings. We contribute to insights into the genetic basis of OCS by performing an extensive series of genetic analyses in a homogeneous, population-based sample from the Netherlands. First, phenotypic and genetic longitudinal correlations over a 6-year period were estimated by modeling OCS data from twins and siblings. Second, polygenic risk scores (PRS) for 6931 subjects with genotype and OCS data were calculated based on meta-analysis results from IOCDF-GC, to investigate their predictive value. Third, the contribution of measured single nucleotide polymorphisms (SNPs) to the heritability was estimated using random-effects modeling. Last, we performed an exploratory genome-wide association study (GWAS) of OCS, testing for SNP- and for gene-based associations. Stability in OCS (test-retest correlation 0.63) was mainly explained by genetic stability. The PRS based on clinical samples predicted OCS in our population-based twin-family sample. SNP-based heritability was estimated at 14%. GWAS revealed one SNP (rs8100480), located within the MEF2BNB gene, associated with OCS (P=2.56 × 10(-8)). Additional gene-based testing resulted in four significantly associated genes, which are located in the same chromosomal region on chromosome 19p13.11: MEF2BNB, RFXANK, MEF2BNB-MEF2B and MEF2B. Thus, common genetic variants explained a significant proportion of OCS trait variation. Genes significantly associated with OCS are expressed in the brain and involved in development and control of immune system functions (RFXANK) and regulation of gene expression of muscle-specific genes (MEF2BNB). MEF2BNB also showed a suggestive association with OCD in an independent case-control study, suggesting a role for this gene in the development of OCS.

Genetic structure of the Newfoundland and Labrador population: founder effects modulate variability

The population of the province of Newfoundland and Labrador (NL) has been a resource for genetic studies because of its historical isolation and increased prevalence of several monogenic disorders. Controversy remains regarding the genetic substructure and the extent of genetic homogeneity, which have implications for disease gene mapping. Population substructure has been reported from other isolated populations such as Iceland, Finland and Sardinia. We undertook this study to further our understanding of the genetic architecture of the NL population. We enrolled 494 individuals randomly selected from NL. Genome-wide SNP data were analyzed together with that from 14 other populations including HapMap3, Ireland, Britain and Native American samples from the Human Genome Diversity Project. Using multidimensional scaling and admixture analysis, we observed that the genetic structure of the NL population resembles that of the British population but can be divided into three clusters that correspond to religious/ethnic origins: Protestant English, Roman Catholic Irish and North American aboriginals. We observed reduced heterozygosity and an increased inbreeding coefficient (mean=0.005), which corresponds to that expected in the offspring of third-cousin marriages. We also found that the NL population has a significantly higher number of runs of homozygosity (ROH) and longer lengths of ROH segments. These results are consistent with our understanding of the population history and indicate that the NL population may be ideal for identifying recessive variants for complex diseases that affect populations of European origin.

The genetics of alcohol dependence: Twin and SNP-based heritability, and genome-wide association study based on AUDIT scores

Alcohol dependence (AD) is among the most common and costly public health problems contributing to morbidity and mortality throughout the world. In this study, we investigate the genetic basis of AD in a Dutch population using data from the Netherlands Twin Register (NTR) and the Netherlands Study of Depression and Anxiety (NESDA). The presence of AD was ascertained via the Alcohol Use Disorders Identification Test (AUDIT) applying cut-offs with good specificity and sensitivity in identifying those at risk for AD. Twin-based heritability of AD-AUDIT was estimated using structural equation modeling of data in 7,694 MZ and DZ twin pairs. Variance in AD-AUDIT explained by all SNPs was estimated with genome-wide complex trait analysis (GCTA). A genome-wide association study (GWAS) was performed in 7,842 subjects. GWAS SNP effect concordance analysis was performed between our GWAS and a recent AD GWAS using DSM-IV diagnosis. The twin-based heritability of AD-AUDIT was estimated at 60% (55-69%). GCTA showed that common SNPs jointly capture 33% (SE = 0.12, P = 0.002) of this heritability. In the GWAS, the top hits were positioned within four regions (4q31.1, 2p16.1, 6q25.1, 7p14.1) with the strongest association detected for rs55768019 (P = 7.58 × 10(-7) ). This first GWAS of AD using the AUDIT measure found results consistent with previous genetic studies using DSM diagnosis: concordance in heritability estimates and direction of SNPs effect and overlap with top hits from previous GWAS. Thus, the use of appropriate questionnaires may represent cost-effective strategies to phenotype samples in large-scale biobanks or other population-based datasets.

The Italian genome reflects the history of Europe and the Mediterranean basin

Recent scientific literature has highlighted the relevance of population genetic studies both for disease association mapping in admixed populations and for understanding the history of human migrations. Deeper insight into the history of the Italian population is critical for understanding the peopling of Europe. Because of its crucial position at the centre of the Mediterranean basin, the Italian peninsula has experienced a complex history of colonization and migration whose genetic signatures are still present in contemporary Italians. In this study, we investigated genomic variation in the Italian population using 2.5 million single-nucleotide polymorphisms in a sample of more than 300 unrelated Italian subjects with well-defined geographical origins. We combined several analytical approaches to interpret genome-wide data on 1272 individuals from European, Middle Eastern, and North African populations. We detected three major ancestral components contributing different proportions across the Italian peninsula, and signatures of continuous gene flow within Italy, which have produced remarkable genetic variability among contemporary Italians. In addition, we have extracted novel details about the Italian population's ancestry, identifying the genetic signatures of major historical events in Europe and the Mediterranean basin from the Neolithic (e.g., peopling of Sardinia) to recent times (e.g., 'barbarian invasion' of Northern and Central Italy). These results are valuable for further genetic, epidemiological and forensic studies in Italy and in Europe.

Intelligence: shared genetic basis between Mendelian disorders and a polygenic trait

Multiple inquiries into the genetic etiology of human traits indicated an overlap between genes underlying monogenic disorders (eg, skeletal growth defects) and those affecting continuous variability of related quantitative traits (eg, height). Extending the idea of a shared genetic basis between a Mendelian disorder and a classic polygenic trait, we performed an association study to examine the effect of 43 genes implicated in autosomal recessive cognitive disorders on intelligence in an unselected Dutch population (N=1316). Using both single-nucleotide polymorphism (SNP)- and gene-based association testing, we detected an association between intelligence and the genes of interest, with genes ELP2, TMEM135, PRMT10, and RGS7 showing the strongest associations. This is a demonstration of the relevance of genes implicated in monogenic disorders of intelligence to normal-range intelligence, and a corroboration of the utility of employing knowledge on monogenic disorders in identifying the genetic variability underlying complex traits.

Heritability and Genome-Wide Association Studies for Hair Color in a Dutch Twin Family Based Sample

Hair color is one of the most visible and heritable traits in humans. Here, we estimated heritability by structural equation modeling (N = 20,142), and performed a genome wide association (GWA) analysis (N = 7091) and a GCTA study (N = 3340) on hair color within a large cohort of twins, their parents and siblings from the Netherlands Twin Register (NTR). Self-reported hair color was analyzed as five binary phenotypes, namely “blond versus non-blond”, “red versus non-red”, “brown versus non-brown”, “black versus non-black”, and “light versus dark”. The broad-sense heritability of hair color was estimated between 73% and 99% and the genetic component included non-additive genetic variance. Assortative mating for hair color was significant, except for red and black hair color. From GCTA analyses, at most 24.6% of the additive genetic variance in hair color was explained by 1000G well-imputed SNPs. Genome-wide association analysis for each hair color showed that SNPs in the MC1R region were significantly associated with red, brown and black hair, and also with light versus dark hair color. Five other known genes (HERC2, TPCN2, SLC24A4, IRF4, and KITLG) gave genome-wide significant hits for blond, brown and light versus dark hair color. We did not find and replicate any new loci for hair color.

Estimation of Genetic Relationships Between Individuals Across Cohorts and Platforms: Application to Childhood Height

Combining genotype data across cohorts increases power to estimate the heritability due to common single nucleotide polymorphisms (SNPs), based on analyzing a Genetic Relationship Matrix (GRM). However, the combination of SNP data across multiple cohorts may lead to stratification, when for example, different genotyping platforms are used. In the current study, we address issues of combining SNP data from different cohorts, the Netherlands Twin Register (NTR) and the Generation R (GENR) study. Both cohorts include children of Northern European Dutch background (N = 3102 + 2826, respectively) who were genotyped on different platforms. We explore imputation and phasing as a tool and compare three GRM-building strategies, when data from two cohorts are (1) just combined, (2) pre-combined and cross-platform imputed and (3) cross-platform imputed and post-combined. We test these three strategies with data on childhood height for unrelated individuals (N = 3124, average age 6.7 years) to explore their effect on SNP-heritability estimates and compare results to those obtained from the independent studies. All combination strategies result in SNP-heritability estimates with a standard error smaller than those of the independent studies. We did not observe significant difference in estimates of SNP-heritability based on various cross-platform imputed GRMs. SNP-heritability of childhood height was on average estimated as 0.50 (SE = 0.10). Introducing cohort as a covariate resulted in ≈2 % drop. Principal components (PCs) adjustment resulted in SNP-heritability estimates of about 0.39 (SE = 0.11). Strikingly, we did not find significant difference between cross-platform imputed and combined GRMs. All estimates were significant regardless the use of PCs adjustment. Based on these analyses we conclude that imputation with a reference set helps to increase power to estimate SNP-heritability by combining cohorts of the same ethnicity genotyped on different platforms. However, important factors should be taken into account such as remaining cohort stratification after imputation and/or phenotypic heterogeneity between and within cohorts. Whether one should use imputation, or just combine the genotype data, depends on the number of overlapping SNPs in relation to the total number of genotyped SNPs for both cohorts, and their ability to tag all the genetic variance related to the specific trait of interest.

Heritability, SNP- and Gene-Based Analyses of Cannabis Use Initiation and Age at Onset

Prior searches for genetic variants (GVs) implicated in initiation of cannabis use have been limited to common single nucleotide polymorphisms (SNPs) typed in HapMap samples. Denser SNPs are now available with the completion of the 1000 Genomes and the Genome of the Netherlands projects. More densely distributed SNPs are expected to track the causal variants better. Therefore we extend the search for variants implicated in early stages of cannabis use to previously untagged common and low-frequency variants. We run heritability, SNP and gene-based analyses of initiation and age at onset. This is the first genome-wide study of age at onset to date. Using GCTA and a sample of distantly related individuals from the Netherlands Twin Register, we estimated that the currently measured (and tagged) SNPs collectively explain 25 % of the variance in initiation (SE = 0.088; P = 0.0016). Chromosomes 4 and 18, previously linked with cannabis use and other addiction phenotypes, account for the largest amount of variance in initiation (6.8 %, SE = 0.025, P = 0.002 and 3.6 %, SE = 0.01, P = 0.012, respectively). No individual SNP- or gene-based test reached genomewide significance in the initiation or age at onset analyses. Our study detected association signal in the currently measured SNPs. A comparison with prior SNP-heritability estimates suggests that at least part of the signal is likely coming from previously untyped common and low frequency variants. Our results do not rule out the contribution of rare variants of larger effect—a plausible source of the difference between the twin-based heritability estimate and that from GCTA. The causal variants are likely of very small effect (i.e., <1 % explained variance) and are uniformly distributed over the genome in proportion to chromosomes’ length. Similar to other complex traits and diseases, detecting such small effects is to be expected in sufficiently large samples.

Glucocorticoid and mineralocorticoid receptor polymorphisms and recurrence of major depressive disorder

OBJECTIVE

Previous research found that variants of the glucocorticoid receptor (GR) (9β, ER22/23EK, BclI, TthIIIl, NR3C1-1 and N363S) and mineralocorticoid receptor (MR) gene polymorphism (-2 C/G and I180V) are associated with both glucocorticoid (GC) sensitivity and major depressive disorder (MDD). There are no data which investigated prospectively whether these variants are associated with recurrence of MDD.

METHODS

Data were derived from the Netherlands Study of Depression and Anxiety (NESDA) which used the Composite International Diagnostic Interview (CIDI) to determine MDD. Polymorphisms in the GR and MR gene were determined and haplotypes were characterized. We analyzed in retrospect whether recurrent MDD (n=951) in comparison with first onset MDD (n=919) was associated with polymorphisms in the GR and MR gene. Furthermore, we analyzed prospectively for 4 years the time to recurrence among 683 subjects with a remitted MDD diagnosis. Time to recurrence of MDD was assessed using the CIDI and a life chart interview. Additionally, we analyzed interactions of the investigated polymorphisms with childhood trauma and recent negative life events.

RESULTS

GR and MR gene polymorphisms and derived haplotypes were not associated with recurrence of depression in both retrospective and prospective analyses. In addition, no consistent interactions between GR and MR polymorphisms and childhood trauma or life events were found.

CONCLUSION

This study did not find consistent associations between GR and MR gene polymorphisms, interactions between GR and MR haplotypes and stressful conditions and recurrence of MDD.

In Silico Post Genome-Wide Association Studies Analysis of C-Reactive Protein Loci Suggests an Important Role for Interferons

BACKGROUND

Genome-wide association studies (GWASs) have successfully identified several single nucleotide polymorphisms (SNPs) associated with serum levels of C-reactive protein (CRP). An important limitation of GWASs is that the identified variants merely flag the nearby genomic region and do not necessarily provide a direct link to the biological mechanisms underlying their corresponding phenotype. Here we apply a bioinformatics-based approach to uncover the functional characteristics of the 18 SNPs that had previously been associated with CRP at a genome-wide significant level.

METHODS AND RESULTS

In the first phase of in silico sequencing, we explore the vicinity of GWAS SNPs to identify all linked variants. In the second phase of expression quantitative trait loci analysis, we attempt to identify all nearby genes whose expression levels are associated with the corresponding GWAS SNPs. These 2 phases generate several relevant genes that serve as input to the next phase of functional network analysis. Our in silico sequencing analysis using 1000 Genomes Project data identified 7 nonsynonymous SNPs, which are in moderate to high linkage disequilibrium (r(2)>0.5) with the GWAS SNPs. Our expression quantitative trait loci analysis, which was based on one of the largest single data sets of genome-wide expression probes (n>5000) identified 23 significantly associated expression probes belonging to 15 genes (false discovery rate <0.01). The final phase of functional network analysis revealed 93 significantly enriched biological processes (false discovery rate <0.01).

CONCLUSIONS

Our post-GWAS analysis of CRP GWAS SNPs confirmed the previously known overlap between CRP and lipids biology. Additionally, it suggested an important role for interferons in the metabolism of CRP.

Educational attainment influences levels of homozygosity through migration and assortative mating

Individuals with a higher education are more likely to migrate, increasing the chance of meeting a spouse with a different ancestral background. In this context, the presence of strong educational assortment can result in greater ancestry differences within more educated spouse pairs, while less educated individuals are more likely to mate with someone with whom they share more ancestry. We examined the association between educational attainment and F_roh (= the proportion of the genome consisting of runs of homozygosity [ROHs]) in ~2,000 subjects of Dutch ancestry. The subjects’ own educational attainment showed a nominally significant negative association with F_roh (p = .045), while the contribution of parental education to offspring F_roh was highly significant (father: p < 10^-5; mother: p = 9×10^-5), with more educated parents having offspring with fewer ROHs. This association was significantly and fully mediated by the physical distance between parental birthplaces (paternal education: p_mediation = 2.4 × 10^-4; maternal education: p_mediation = 2.3 × 10^-4), which itself was also significantly associated with F_roh (p = 9 × 10^-5). Ancestry-informative principal components from the offspring showed a significantly decreasing association with geography as parental education increased, consistent with the significantly higher migration rates among more educated parents. Parental education also showed a high spouse correlation (Spearman’s ρ = .66, p = 3 × 10^-262). We show that less educated parents are less likely to mate with the more mobile parents with a higher education, creating systematic differences in homozygosity due to ancestry differences not directly captured by ancestry-informative principal components (PCs). Understanding how behaviors influence the genomic structure of a population is highly valuable for studies on the genetic etiology of behavioral, cognitive, and social traits.

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.

Attention-deficit/hyperactivity disorder polygenic risk scores predict attention problems in a population-based sample of children

OBJECTIVE

Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age.

METHOD

The Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and 13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated in this meta-analysis were used to obtain individual polygenic risk scores in an independent population-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems (AP) scale scores by the polygenic risk scores was estimated by linear mixed modeling.

RESULTS

The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children.

CONCLUSION

These results indicate genetic overlap between a diagnosis of ADHD and AP scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.

Fine-scale human genetic structure in Western France

The difficulties arising from association analysis with rare variants underline the importance of suitable reference population cohorts, which integrate detailed spatial information. We analyzed a sample of 1684 individuals from Western France, who were genotyped at genome-wide level, from two cohorts D.E.S.I.R and CavsGen. We found that fine-scale population structure occurs at the scale of Western France, with distinct admixture proportions for individuals originating from the Brittany Region and the Vendée Department. Genetic differentiation increases with distance at a high rate in these two parts of Northwestern France and linkage disequilibrium is higher in Brittany suggesting a lower effective population size. When looking for genomic regions informative about Breton origin, we found two prominent associated regions that include the lactase region and the HLA complex. For both the lactase and the HLA regions, there is a low differentiation between Bretons and Irish, and this is also found at the genome-wide level. At a more refined scale, and within the Pays de la Loire Region, we also found evidence of fine-scale population structure, although principal component analysis showed that individuals from different departments cannot be confidently discriminated. Because of the evidence for fine-scale genetic structure in Western France, we anticipate that rare and geographically localized variants will be identified in future full-sequence analyses.

Genome scans for detecting footprints of local adaptation using a Bayesian factor model

There is a considerable impetus in population genomics to pinpoint loci involved in local adaptation. A powerful approach to find genomic regions subject to local adaptation is to genotype numerous molecular markers and look for outlier loci. One of the most common approaches for selection scans is based on statistics that measure population differentiation such as FST. However, there are important caveats with approaches related to FST because they require grouping individuals into populations and they additionally assume a particular model of population structure. Here, we implement a more flexible individual-based approach based on Bayesian factor models. Factor models capture population structure with latent variables called factors, which can describe clustering of individuals into populations or isolation-by-distance patterns. Using hierarchical Bayesian modeling, we both infer population structure and identify outlier loci that are candidates for local adaptation. In order to identify outlier loci, the hierarchical factor model searches for loci that are atypically related to population structure as measured by the latent factors. In a model of population divergence, we show that it can achieve a 2-fold or more reduction of false discovery rate compared with the software BayeScan or with an FST approach. We show that our software can handle large data sets by analyzing the single nucleotide polymorphisms of the Human Genome Diversity Project. The Bayesian factor model is implemented in the open-source PCAdapt software.

Polygenic scores associated with educational attainment in adults predict educational achievement and ADHD symptoms in children

The American Psychiatric Association estimates that 3 to 7 per cent of all school aged children are diagnosed with attention deficit hyperactivity disorder (ADHD). Even after correcting for general cognitive ability, numerous studies report a negative association between ADHD and educational achievement. With polygenic scores we examined whether genetic variants that have a positive influence on educational attainment have a protective effect against ADHD. The effect sizes from a large GWA meta-analysis of educational attainment in adults were used to calculate polygenic scores in an independent sample of 12-year-old children from the Netherlands Twin Register. Linear mixed models showed that the polygenic scores significantly predicted educational achievement, school performance, ADHD symptoms and attention problems in children. These results confirm the genetic overlap between ADHD and educational achievement, indicating that one way to gain insight into genetic variants responsible for variation in ADHD is to include data on educational achievement, which are available at a larger scale.

Effect of polygenic risk scores on depression in childhood trauma

BACKGROUND

Research on gene × environment interaction in major depressive disorder (MDD) has thus far primarily focused on candidate genes, although genetic effects are known to be polygenic.

AIMS

To test whether the effect of polygenic risk scores on MDD is moderated by childhood trauma.

METHOD

The study sample consisted of 1645 participants with a DSM-IV diagnosis of MDD and 340 screened controls from The Netherlands. Chronic or remitted episodes (severe MDD) were present in 956 participants. The occurrence of childhood trauma was assessed with the Childhood Trauma Interview and the polygenic risk scores were based on genome-wide meta-analysis results from the Psychiatric Genomics Consortium.

RESULTS

The polygenic risk scores and childhood trauma independently affected MDD risk, and evidence was found for interaction as departure from both multiplicativity and additivity, indicating that the effect of polygenic risk scores on depression is increased in the presence of childhood trauma. The interaction effects were similar in predicting all MDD risk and severe MDD risk, and explained a proportion of variation in MDD risk comparable to the polygenic risk scores themselves.

CONCLUSIONS

The interaction effect found between polygenic risk scores and childhood trauma implies that (1) studies on direct genetic effect on MDD gain power by focusing on individuals exposed to childhood trauma, and that (2) individuals with both high polygenic risk scores and exposure to childhood trauma are particularly at risk for developing MDD.