Biology subjects

de Geus, E. J.

Publications and source records attributed to de Geus, E. J..

9 recordsLinked to original sources

bioRxiv2021

Large-scale genome-wide association study of food liking reveals genetic determinants and genetic correlations with distinct neurophysiological traits.

Variable preferences for different foods are among the main determinants of their intake and are influenced by many factors, including genetics. Despite considerable twins heritability, studies aimed at uncovering food-liking genetics have focused mostly on taste receptors. Here, we present the first results of a large-scale genome-wide association study of food liking conducted on 161,625 participants from UK Biobank. Liking was assessed over 139 specific foods using a 9-point hedonic scale. After performing GWAS, we used genetic correlations coupled with structural equation modelling to create a multi-level hierarchical map of food liking. We identified three main dimensions: high caloric foods defined as "Highly palatable", strong-tasting foods ranging from alcohol to pungent vegetables, defined as "Learned" and finally "Low caloric" foods such as fruit and vegetables. The "Highly palatable" dimension was genetically uncorrelated from the other two, suggesting that two independent processes underlie liking high reward foods and the Learned/Low caloric ones. Genetic correlation analysis with the corresponding food consumption traits revealed a high correlation, while liking showed twice the heritability compared to consumption. For example, fresh fruit liking and consumption showed a genetic correlation of 0.7 with heritabilities of 0.1 and 0.05, respectively. GWAS analysis identified 1401 significant food-liking associations located in 173 genomic loci, with only 11 near taste or olfactory receptors. Genetic correlation with morphological and functional brain data (33,224 UKB participants) uncovers associations of the three food-liking dimensions with non-overlapping, distinct brain areas and networks, suggestive of separate neural mechanisms underlying the liking dimensions. In conclusion, we created a comprehensive and data-driven map of the genetic determinants and associated neurophysiological factors of food liking beyond taste receptor genes.

genetics↗

bioRxiv2021

Within-sibship GWAS improve estimates of direct genetic effects

Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.

genetics↗

bioRxiv2020

Multivariate GWAS elucidates the genetic architecture of alcohol consumption and misuse, corrects biases, and reveals novel associations with disease

Genome-wide association studies (GWASs) of the Alcohol Use Disorder Identification Test (AUDIT), a ten-item screener for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders/medical conditions. To explore these unexpected differences in genetic correlations, we conducted the first item-level and largest GWAS of AUDIT items (N=160,824), and applied a multivariate framework to mitigate previous biases. In doing so, we identified novel patterns of similarity (and dissimilarity) among the AUDIT items, and found evidence of a correlated two-factor structure at the genetic level (Consumption and Problems, rg=.80). Moreover, by applying empirically-derived weights to each of the AUDIT items, we constructed an aggregate measure of alcohol consumption that is strongly associated with alcohol dependence (rg=.67) and several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by performing polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, we identified novel genetic associations between alcohol consumption, alcohol misuse, and human health. Our work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD, and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.

genetics↗

bioRxiv2020

Genome-wide association studies identify 137 loci for DNA methylation biomarkers of ageing

Biological ageing estimators derived from DNA methylation (DNAm) data are heritable and correlate with morbidity and mortality. Leveraging DNAm and SNP data from >41,000 individuals, we identify 137 genome-wide significant loci (113 novel) from meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We report strong genetic correlations with longevity and lifestyle factors such as smoking, education, and obesity. Significant associations are observed in polygenic risk score analysis and to a lesser extent in Mendelian randomization analyses. This study illuminates the genetic architecture underlying epigenetic ageing and its shared genetic contributions with lifestyle factors and longevity.

genetics↗

bioRxiv2019

Genome-wide association study identifies 49 common genetic variants associated with handedness.

Handedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the worlds largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5x10-8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% - 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% - 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 - 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.

genetics↗

bioRxiv2019

Genetic meta-analysis of obsessive-compulsive disorder and self-report compulsive symptoms.

We investigated whether obsessive compulsive (OC) symptoms from a population-based sample could be analyzed to detect genetic variants influencing OCD. We performed a GWAS on the obsession (rumination and impulsions) and compulsion (checking, washing, and ordering/precision) subscales of an abbreviated version of the Padua Inventory (N=8267 with genome-wide genotyping and phenotyping). The compulsion subscale showed a substantial and significant positive genetic correlation with an OCD case-control GWAS (rG=0.61, p=0.017) previously published by the Psychiatric Genomics Consortium (PGC-OCD). The obsession subscale and the total Padua score showed no significant genetic correlations (rG=-0.02 and rG=0.42, respectively). A meta-analysis of the compulsive symptoms GWAS with the PGC-OCD revealed no genome-wide significant SNPs (combined N=17992, indicating that the power is still low for individual SNP effects). A gene-based association analysis, however, yielded two novel genes (WDR7 and ADCK1). The top 250 genes in the gene-based test also showed significant increase in enrichment for psychiatric and brain-expressed genes. S-Predixcan testing showed that for genes expressed in hippocampus, amygdala, and caudate nucleus significance increased in the meta-analysis with compulsive symptoms compared to the original PGC-OCD GWAS. Thus, inclusion of dimensional symptom data in genome-wide association on clinical case-control GWAS of OCD may be useful to find genes for OCD if the data are based on quantitative indices of compulsive behavior. SNP-level power increases were limited, but aggregate, gene-level analyses showed increased enrichment for brain-expressed genes related to psychiatric disorders, and increased association with gene-expression in brain tissues with known emotional, reward processing, memory, and fear-formation functions.

genetics↗

bioRxiv2019

The genomic architecture of blood metabolites based on a decade of genome-wide analyses

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes and lipid species. We performed a review of all genetic association studies, and identified > 800 class-specific metabolite loci that influence metabolite levels. In a twin-family cohort (N = 5,117), these metabolite loci were leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study revealed significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation had higher h2Metabolite-hits estimates than phosphatidylcholines with a low degree of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes and lipid species.

genetics↗

bioRxiv2017

Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity

Oscillations in neuronal activity are widely thought to play a crucial role in information processing and cortical communication 1-8. Brain oscillations have been widely investigated as biomarkers of psychiatric disorders and variation in normal human behavior 9, 10, including intelligence 11, 12, schizophrenia 13, 14, attentional deficits 15, 16, and substance use 17, 18. Beyond the biomarker, oscillatory activity may indeed cause variation in behavior, as it has been shown that disrupting oscillatory activity by blocking GABAergic fast-spiking interneurons in the frontal cortex of mice impairs behavioral flexibility8, consistent with ...

genetics↗

bioRxiv2017

Multivariate Genome-Wide and Integrated Transcriptome and Epigenome-Wide Analyses of the Well-being Spectrum.

Phenotypes related to well-being (life satisfaction, positive affect, neuroticism, and depressive symptoms), are genetically highly correlated (| rg | > .75). Multivariate genome-wide analyses (Nobs = 958,149) of these traits, collectively referred to as the well-being spectrum, reveals 63 significant independent signals, of which 29 were not previously identified. Transcriptome and epigenome analyses implicate variation in gene expression at 8 additional loci and CpG methylation at 6 additional loci in the etiology of well-being. We leverage an anatomically comprehensive survey of gene expression in the brain to annotate our findings, showing that SNPs within genes excessively expressed in the cortex and part of the hippocampal formation are enriched in their effect on well-being.

genetics↗