Biology subjects

Rietveld, C. A.

Publications and source records attributed to Rietveld, C. A..

9 recordsLinked to original sources

bioRxiv2026

Sex-specific associations between education-related genetic factors and fertility extend beyond educational attainment

Educational attainment (EA) is strongly associated with fertility, yet the mechanisms underlying this relationship remain poorly understood. Using data from ~40,000 women and ~10,000 men in the Estonian Biobank, we examine sex-specific associations between EA polygenic scores (EA PGS) and completed fertility. The EA PGS captures an individual's genetic predisposition to completing higher levels of education, and can also be constructed separately for cognitive and non-cognitive EA components. We find that EA PGS is negatively associated with fertility among women, with a significantly stronger association for the non-cognitive than the cognitive EA polygenic score. The association of EA PGS with fertility is only partly explained by EA and is moderated by EA and reproductive timing, changing sign across age-at-first-pregnancy strata. Within-family estimates are not attenuated relative to population estimates, consistent with a predominant role of direct genetic effects. Among men, associations between EA PGS and fertility are non-significant or slightly positive. Overall, education-related genetic variation is associated with fertility through pathways largely independent of EA, operating through sex-specific and timing-dependent mechanisms. These results contribute to our understanding of the micro-level mechanisms shaping macro-level demographic change.

genetics↗

bioRxiv2025

Parental Influence on Children's Educational Achievements: Analysing Direct and Indirect Genetic Effects through Trio-GCTA

Educational achievement is a key predictor of later-life outcomes, including financial security, social mobility, health, and mortality. Knowing its familial determinants, such as genetic predispositions, is crucial for understanding intergenerational educational mobility and addressing educational inequality. Here, we disentangle direct and indirect genetic effects on educational achievement using trio genome-wide complex trait analysis (Trio-GCTA). Leveraging up to 23,200 genotyped parent-offspring trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa), we find that direct genetic effects explain 15-21% of the variance in educational achievements, including 8th-grade national assessments in Math, Reading, and English, and 10th-grade grade point average (GPA). Notably, indirect genetic effects additionally explain 7-15% of the variance. Both mothers and fathers exert notable influences, exceeding those suggested in previous studies. Moreover, positive gene-environment correlations between parents and offspring show that the intrafamilial environment and childrens genetic predisposition are dependent and mutually reinforcing.

genetics↗

bioRxiv2022

Rank concordance of polygenic indices: Implications for personalised intervention and gene-environment interplay

Polygenic indices (PGIs) are increasingly used to identify individuals at high risk of developing diseases and disorders and are advocated as a screening tool for personalised intervention in medicine and education. The performance of PGIs is typically assessed in terms of the amount of phenotypic variance they explain in independent prediction samples. However, the correct ranking of individuals in the PGI distribution is a more important performance metric when identifying individuals at high genetic risk. We empirically assess the rank concordance between PGIs that are created with different construction methods and discovery samples, focusing on cardiovascular disease (CVD) and educational attainment (EA). We find that the rank correlations between the constructed PGIs vary strongly (Spearman correlations between 0.17 and 0.94 for CVD, and between 0.40 and 0.85 for EA), indicating highly unstable rankings across different PGIs for the same trait. Simulations show that measurement error in PGIs is responsible for a substantial part of PGI rank discordance. Potential consequences for personalised medicine in CVD and research on gene-environment (GxE) interplay are illustrated using data from the UK Biobank.

genomics↗

bioRxiv2021

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior

Human variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce multivariate genomic-relatedness restricted maximum likelihood (MGREML) and provide estimates of the heritability of grey-matter volume in 74 regions of interest (ROIs) in the brain. We map genetic correlations between these ROIs and health-relevant behavioral outcomes including intelligence. We find four genetically distinct clusters in the brain that are aligned with standard anatomical subdivision in neuroscience. Behavioral traits have distinct genetic correlations with brain morphology which suggests trait-specific relevance of ROIs.

genetics↗

bioRxiv2021

Stop Meta-Analyzing, Start Instrumenting: Maximizing the Predictive Power of Polygenic Scores

Measurement error in polygenic indices (PGIs) attenuates the estimation of their effects in regression models. While this measurement error shrinks with growing Genome-wide Association Study (GWAS) sample sizes, the marginal returns to bigger sample sizes are rapidly decreasing. We analyze and compare two alternative approaches to reduce measurement error: Obviously Related Instrumental Variables (ORIV) and the PGI Repository Correction (PGI-RC). Through simulations, we show that both approaches outperform the typical (meta-analysis based) PGI in terms of bias and root mean squared error. Between families, the PGI-RC performs slightly better than ORIV, unless the prediction sample is very small (N < 1, 000), or when there is considerable assortative mating. Within families, ORIV is the default choice since the PGI-RC is not available in this setting. We verify the empirical validity of the simulations by predicting educational attainment (EA) and height in a sample of siblings from the UK Biobank. We show that applying ORIV between families increases the standardized effect of the PGI by 12% (height) and by 22% (EA) compared to a meta-analysis-based PGI, yet remains slightly below the PGI-RC estimates. Furthermore, within-family ORIV regression provides the tightest lower bound for the direct genetic effect, increasing the lower bound for the direct genetic effect on EA from 0.14 to 0.18, and for height from 0.54 to 0.61 compared to a meta-analysis-based PGI.

genetics↗

bioRxiv2018

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

We conducted genome-wide association study (GWAS) meta-analyses of relative caloric intake from fat, protein, carbohydrates and sugar in over 235,000 individuals. We identified 21 approximately independent lead SNPs. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg {approx} 0.15 - 0.5). Relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood poverty (|rg| {approx} 0.1 - 0.3). Overall, our results show that the relative intake of each macronutrient has a distinct genetic architecture and pattern of genetic correlations suggestive of health implications beyond caloric content.

genetics↗

bioRxiv2018

Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated ([Formula] to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

genetics↗

bioRxiv2017

Genetics of educational attainment aid in identifying biological subcategories of schizophrenia

Higher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigated possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1,169 controls; 1,067 cases) with deeply phenotyped SZ patients. We found strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Genetic heterogeneity of SZ contributes to this finding. We demonstrate this by showing that the polygenic prediction of clinical SZ symptoms can be improved by taking the sign concordance of loci for EA and SZ into account. Furthermore, using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ.

genetics↗

bioRxiv2017

An epigenome-wide association study of educational attainment (n = 10,767)

The epigenome has been shown to be influenced by biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption, and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here, we provide evidence on the associations between epigenetic modifications--in our case, CpG methylation--and educational attainment (EA), a biologically distal environmental factor that is arguably among of the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10,767 individuals. While we find that 9 CpG probes are significantly associated with EA, only two remain associated when we restrict the sample to never-smokers. These two are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, their effect sizes on EA are far smaller than the known associations between CpG probes and biologically proximal environmental factors. Two analyses that combine the effects of many probes--polygenic methylation score and epigenetic-clock analyses--both suggest small associations with EA. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

genetics↗