Biology subjects

de Zeeuw, E. L.

Publications and source records attributed to de Zeeuw, E. L..

8 recordsLinked to original sources

bioRxiv2025

Genome-wide analysis of social behaviour in context: a meta-regression approach across social domains, reporters and developmental stages

Social behaviour is a heritable, context-dependent trait that changes across social settings and development, influencing wellbeing and mental health. We present the first genome-wide meta-regression study of social behaviour from infancy to early adulthood, leveraging 491,246 repeat measures of low prosocial behaviour and peer/social difficulties in European-ancestry cohorts (Neff=121,777, Nind=73,321). We modelled heterogeneity in genetic effects across social domains, informants, and ages (2-29 years), capturing social context through genomic influences. Six loci were identified, including variation within CADM2 (p=2.51x10-9). The SNP-based heritability was modest (2-7%), and the genetic architecture of social behaviour multidimensional. Polygenic scores demonstrated predictability and accuracy in independent European-ancestry cohorts and, partially, in African-ancestry cohorts (Nind=16,305). Genetic correlations with later-life and mental health outcomes showed context-dependent patterns. Modelling predicted onsets of associations with social behaviour revealed distinct profiles, as observed for autism, ADHD, depression and schizophrenia, highlighting novel opportunities to genetically proxy developmental trajectories.

genomics↗

bioRxiv2021

Genome-wide association analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 x 10-8) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13-0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

genomics↗

bioRxiv2020

Multilevel Twin Models: Geographical Region as a Third Level Variable

The classical twin model can be reparametrized as an equivalent multilevel model. The multilevel parameterization has underexplored advantages, such as the possibility to include higher-level clustering variables in which lower levels are nested. When this higher-level clustering is not modeled, its variance is captured by the common environmental variance component. In this paper we illustrate the application of a 3-level multilevel model to twin data by analyzing the regional clustering of 7-year-old childrens height in the Netherlands. Our findings show that 1.8%, of the phenotypic variance in childrens height is attributable to regional clustering, which is 7% of the variance explained by between-family or common environmental components. Since regional clustering may represent ancestry, we also investigate the effect of region after correcting for genetic principal components, in a subsample of participants with genome-wide SNP data. After correction, region did no longer explain variation in height. Our results suggest that the phenotypic variance explained by region actually represent ancestry effects on height.

genetics↗

bioRxiv2020

Genetic evidence for bidirectional causal effects between resilience and well-being.

Resilience and well-being are strongly related. People with higher levels of well-being are more resilient after stressful life events or trauma and vice versa. Less is known about the underlying sources of overlap and causality between the constructs. In a sample of 11.304 twins and 2.572 siblings from the Netherlands Twin Register, we investigated the overlap and possible direction of causation between resilience (i.e. the absence of psychiatric symptoms despite negative life events) and well-being (i.e. satisfaction with life) using polygenic score (PGS) prediction, twin-sibling modelling, and the Mendelian Randomization Direction of Causality (MR-DoC) model. Longitudinal twin-sibling models showed significant phenotypic correlations between resilience and well-being (.41/.51 at time 1 and 2). Well-being PGS were predictive for both well-being and resilience, indicating that genetic factors influencing well-being also predict resilience. Twin-sibling modeling confirmed this genetic correlation (.71) and showed a strong environmental correlation (.93). In line with causality, both genetic (51%) and environmental (49%) factors contributed significantly to the covariance between resilience and well-being. Furthermore, the results of within-subject and MZ twin differences analyses were in line with bidirectional causality. Additionally, we used the MR-DoC model combining both molecular and twin data to test causality, while correcting for pleiotropy. We confirmed the causal effect from well-being to resilience, with the direct effect of well-being explaining 11% (T1) and 20% (T2) of the variance in resilience. Data limitations prevented us to test the directional effect from resilience to well-being with the MR-DoC model. To conclude, we showed a strong relation between well-being and resilience. A first attempt to quantify the direction of this relationship points towards a bidirectional causal effect. If replicated, the potential mutual effects can have implications for interventions to lower psychopathology vulnerability, as resilience and well-being are both negatively related to psychopathology.

genetics↗

bioRxiv2020

Safe linkage of cohort and population-based register data in a genome-wide association study on health care expenditure

BackgroundThere are research questions whose answers require record linkage of multiple databases which may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run analyses in a high performance computing (HPC) environment. MethodsAfter successful record linkage genome-wide association (GWA) analyses were carried out on expenditure for total health, mental health, primary and hospital care and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and SNP-based heritability. ResultsThe total heritability of expenditure ranged between 29.4 (SE 0.8) and 37.5 (SE 0.8) per cent, but GWA analyses did not identify single SNPs or genes that were genome-wide significantly associated with health care expenditure. SNP-based heritability was between 0.0 (SE 3.5) and 5.4 (SE 4.0) per cent and was different from zero for mental health care and primary care expenditure. ConclusionsWe successfully linked genotype data to administrative health care expenditure data from Statistics Netherlands and performed a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analysing linked data in large-scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions. Key messagesO_LICohort data of the Netherlands Twin Register were safely linked to population-based register data of Statistics Netherlands C_LIO_LIOn the ODISSEI Secure Supercomputer (OSSC) platform genome-wide association analyses were carried out on linked genotype and health care expenditure data C_LIO_LIVariation in health care expenditure was for approximately one third explained by family-based heritability, but SNP-heritability based on genetic similarity across unrelated individuals explained only a very small proportion of variance C_LIO_LIThe newly developed platform can serve as a prototype for realizing genome-wide association studies with sensitive data C_LI

genetics↗

bioRxiv2020

Parental influences on offspring education: indirect genetic effects of non-cognitive skills

Understanding how parents cognitive and non-cognitive skills influence offspring education is vital for educational, family and economic policy. We use genetics (GWAS-by-subtraction) to assess a latent, broad non-cognitive skills dimension. To index parental effects controlling for genetic transmission, we estimate indirect parental genetic effects of polygenic scores on childhood and adulthood educational outcomes, using siblings (N=47,459), adoptees (N=6,407), and parent-offspring trios (N=2,534) in three UK and Dutch cohorts. We find that parental cognitive and non-cognitive skills affect offspring education through their environment: on average across cohorts and designs, indirect genetic effects explain 36-40% of population polygenic score associations. However, indirect genetic effects are lower for achievement in the Dutch cohort, and for the adoption design. We identify causes of higher sibling- and trio-based estimates: prenatal indirect genetic effects, population stratification, and assortative mating. Our phenotype-agnostic, genetically sensitive approach has established overall environmental effects of parents skills, facilitating future mechanistic work.

genetics↗

bioRxiv2020

Investigating the Genetic Architecture of Non-Cognitive Skills Using GWAS-by-Subtraction

Educational attainment (EA) is influenced by cognitive abilities and by other characteristics and traits. However little is known about the genetic architecture of these "non-cognitive" contributions to EA. Here, we use Genomic Structural Equation Modelling and results of prior genome-wide association studies (GWASs) of EA (N = 1,131,881) and cognitive test performance (N = 257,841) to estimate SNP associations with variation in EA that is independent of cognitive ability. We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in EA. Phenotypic and biological annotation revealed that (1) both cognitive and non-cognitive contributions to EA were genetically correlated with socioeconomic success and longevity; and (2) non-cognitive contributions to EA were related to personality, decision making, risk-behavior, and increased risk for psychiatric disorders; (3) non-cognitive and cognitive contributions to EA were enriched in the same tissues and cell types, but (4) showed different associations with gray-matter neuroimaging phenotypes.

genetics↗

bioRxiv2019

Intergenerational transmission of education and ADHD: Effects of parental genotypes

It is challenging to study whether children resemble their parents due to nature, nurture, or a mixture of both. Here we used a novel design that employs the fact that parents transmit 50% of their alleles to their offspring. The combined effect of these transmitted and non-transmitted alleles on a trait are summarized in a polygenic score (PGS). The non-transmitted PGS can only affect offspring through the environment, via genetically influenced behaviours in the parents, called genetic nurturing. For genotyped mother-father-offspring trios (1,120-2,518 per analysis) we calculated transmitted and non-transmitted PGSs for adult educational attainment (EA) and childhood ADHD and tested if these predicted outcomes in offspring. In adults, both transmitted (R2 = 7.6%) and non-transmitted (R2 = 1.7%) EA PGSs predicted offspring EA, evidencing genetic nurturing. In children around age 12, academic achievement was predicted only by transmitted EA PGSs (R2 = 5.7%), but we did not find genetic nurturing (R2 [~] 0.1%). The ADHD PGSs did not significantly predict academic achievement (R2 [~] 0.6%). ADHD symptoms in children were predicted by transmitted EA PGSs and ADHD PGSs (R2 = 1-2%). Based on these results, we conclude that previously reported associations between parent characteristics and offspring outcomes seem to be mainly a marker of genetic effects shared by parents and children.

genomics↗