Publications by authors named "Michel G Nivard"

62 Publications

Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data.

Nat Commun 2021 09 14;12(1):5420. Epub 2021 Sep 14.

Institute for Molecular Biosciences, The University of Queensland, St Lucia, QLD, Australia.

Estimation of direct and indirect (i.e. parental and/or sibling) genetic effects on phenotypes is becoming increasingly important. We compare several multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate direct and indirect genetic effects. Using data from the UK Biobank, we contrast point estimates and standard errors at individual loci compared to those obtained using individual level data. We show that Genomic structural equation modelling (SEM) outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We apply Genomic SEM to fertility data in the UK Biobank and partition the genetic effect into female and male fertility and a sibling specific effect. We identify a novel locus for fertility and genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We recommend Genomic SEM be used to partition genetic effects into direct and indirect components when using summary results from genome-wide association studies.
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http://dx.doi.org/10.1038/s41467-021-25723-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440517PMC
September 2021

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.

Nat Genet 2021 09 2;53(9):1300-1310. Epub 2021 Sep 2.

Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
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http://dx.doi.org/10.1038/s41588-021-00913-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432599PMC
September 2021

Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course.

Behav Genet 2021 Sep 14;51(5):592-606. Epub 2021 Aug 14.

Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.

We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.
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http://dx.doi.org/10.1007/s10519-021-10076-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390412PMC
September 2021

Genetic association study of childhood aggression across raters, instruments, and age.

Transl Psychiatry 2021 07 30;11(1):413. Epub 2021 Jul 30.

Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGG) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGG. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E-06), PCDH7 (P = 2.0E-06), and IPO13 (P = 2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (r) among rater-specific assessment of AGG ranged from r = 0.46 between self- and teacher-assessment to r = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range [Formula: see text]: 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (r = ~-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range [Formula: see text]: 0.46-0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.
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http://dx.doi.org/10.1038/s41398-021-01480-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8324785PMC
July 2021

Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure.

Twin Res Hum Genet 2021 04;24(2):103-109

Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands.

There are research questions whose answers require record linkage of multiple databases that 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 large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study 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 single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions.
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http://dx.doi.org/10.1017/thg.2021.18DOI Listing
April 2021

Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts.

Am J Psychiatry 2021 May 14:appiajp202020091390. Epub 2021 May 14.

Department of Psychology, University of Texas at Austin (Mallard, Grotzinger, Harden); Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam (Savage); Department of Psychiatry, Washington University School of Medicine, Saint Louis (Johnson, Anokhin, Agrawal); Department of Psychiatry (Huang, Jennings, Palmer, Sanchez-Roige) and Institute for Genomic Medicine (Palmer), University of California San Diego, La Jolla; Virginia Institute for Psychiatric and Behavioral Genetics, Richmond (Edwards); Department of Biological Psychiatry, Vrije Universiteit Amsterdam (Hottenga, Nivard, de Geus, Boomsma); Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Gustavson, Davis, Sanchez-Roige); Department of Psychology, Virginia Commonwealth University, Richmond (Dick); Department of Biochemistry and Molecular Biology (Edenberg) and Department of Medical and Molecular Genetics (Lai), Indiana University School of Medicine, Indianapolis; Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City (Kramer); Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, N.Y. (Meyers, Pandey); Department of Psychiatry and Behavioral Sciences and Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tenn. (Davis); Division of Psychiatry, University of Edinburgh, Edinburgh, U.K. (Clarke).

Objective: Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen 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 may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT.

Methods: To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases.

Results: The authors 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," r=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (r=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health.

Conclusions: This 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.
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http://dx.doi.org/10.1176/appi.ajp.2020.20091390DOI Listing
May 2021

Genetic analyses identify widespread sex-differential participation bias.

Nat Genet 2021 05 22;53(5):663-671. Epub 2021 Apr 22.

Faculty of Behavioural and Movement Sciences, Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands.

Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index-increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 × 10). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.
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http://dx.doi.org/10.1038/s41588-021-00846-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611642PMC
May 2021

Response to Comment on "Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior".

Science 2021 03;371(6536)

Centre for Psychology and Evolution, School of Psychology, University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia.

Hamer argue that the variable "ever versus never had a same-sex partner" does not capture the complexity of human sexuality. We agree and said so in our paper. But Hamer neglect to mention that we also reported follow-up analyses showing substantial overlap of the genetic influences on our main variable and on more nuanced measures of sexual behavior, attraction, and identity.
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http://dx.doi.org/10.1126/science.aba5693DOI Listing
March 2021

Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits.

Nat Hum Behav 2021 08 8;5(8):1065-1073. Epub 2021 Mar 8.

QIMR Berghofer, Translational Neurogenomics Group, Brisbane, Queensland, Australia.

Epidemiological studies show high comorbidity between different mental health problems, indicating that individuals with a diagnosis of one disorder are more likely to develop other mental health problems. Genetic studies reveal substantial sharing of genetic factors across mental health traits. However, mental health is also genetically correlated with socio-economic status (SES), and it is therefore important to investigate and disentangle the genetic relationship between mental health and SES. We used summary statistics from large genome-wide association studies (average N ~ 160,000) to estimate the genetic overlap across nine psychiatric disorders and seven substance use traits and explored the genetic influence of three different indicators of SES. Using genomic structural equation modelling, we show significant changes in patterns of genetic correlations after partialling out SES-associated genetic variation. Our approach allows the separation of disease-specific genetic variation and genetic variation shared with SES, thereby improving our understanding of the genetic architecture of mental health.
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http://dx.doi.org/10.1038/s41562-021-01053-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376746PMC
August 2021

Onset of Preclinical Alzheimer Disease in Monozygotic Twins.

Ann Neurol 2021 05 4;89(5):987-1000. Epub 2021 Mar 4.

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands.

Objective: The present work was undertaken to study the genetic contribution to the start of Alzheimer's disease (AD) with amyloid and tau biomarkers in cognitively intact older identical twins.

Methods: We studied in 96 monozygotic twin-pairs relationships between amyloid-beta (Aβ) aggregation as measured by the Aβ1-42/1-40 ratio in cerebrospinal fluid (CSF; n = 126) and positron emission tomography (PET, n = 194), and CSF markers for Aβ production (beta-secretase 1, Aβ1-40, and Aβ1-38) and CSF tau. Associations among markers were tested with generalized estimating equations including a random effect for twin status, adjusted for age, gender, and apolipoprotein E ε4 genotype. We used twin analyses to determine relative contributions of genetic and/or environmental factors to AD pathophysiological processes.

Results: Twenty-seven individuals (14%) had an abnormal amyloid PET, and 14 twin-pairs (15%) showed discordant amyloid PET scans. Within twin-pairs, Aβ production markers and total-tau (t-tau) levels strongly correlated (r range = 0.73-0.86, all p < 0.0001), and Aβ aggregation markers and 181-phosphorylated-tau (p-tau) levels correlated moderately strongly (r range = 0.50-0.64, all p < 0.0001). Cross-twin cross-trait analysis showed that Aβ1-38 in one twin correlated with Aβ1-42/1-40 ratios, and t-tau and p-tau levels in their cotwins (r range = -0.28 to 0.58, all p < .007). Within-pair differences in Aβ production markers related to differences in tau levels (r range = 0.49-0.61, all p < 0.0001). Twin discordance analyses suggest that Aβ production and tau levels show coordinated increases in very early AD.

Interpretation: Our results suggest a substantial genetic/shared environmental background contributes to both Aβ and tau increases, suggesting that modulation of environmental risk factors may aid in delaying the onset of AD pathophysiological processes. ANN NEUROL 2021;89:987-1000.
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http://dx.doi.org/10.1002/ana.26048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8251701PMC
May 2021

Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction.

Nat Genet 2021 01 7;53(1):35-44. Epub 2021 Jan 7.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success.
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http://dx.doi.org/10.1038/s41588-020-00754-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116735PMC
January 2021

Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses.

Nat Commun 2020 07 14;11(1):3519. Epub 2020 Jul 14.

Medical Research Council Integrative Epidemiology Unit, University of Bristol, BS8 2BN, Bristol, UK.

Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.
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http://dx.doi.org/10.1038/s41467-020-17117-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7360778PMC
July 2020

Genetic Associations Between Childhood Psychopathology and Adult Depression and Associated Traits in 42 998 Individuals: A Meta-analysis.

JAMA Psychiatry 2020 07;77(7):715-728

University of Bristol School of Psychological Science, Bristol, United Kingdom.

Importance: Adult mood disorders are often preceded by behavioral and emotional problems in childhood. It is yet unclear what explains the associations between childhood psychopathology and adult traits.

Objective: To investigate whether genetic risk for adult mood disorders and associated traits is associated with childhood disorders.

Design, Setting, And Participants: This meta-analysis examined data from 7 ongoing longitudinal birth and childhood cohorts from the UK, the Netherlands, Sweden, Norway, and Finland. Starting points of data collection ranged from July 1985 to April 2002. Participants were repeatedly assessed for childhood psychopathology from ages 6 to 17 years. Data analysis occurred from September 2017 to May 2019.

Exposures: Individual polygenic scores (PGS) were constructed in children based on genome-wide association studies of adult major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI).

Main Outcomes And Measures: Regression meta-analyses were used to test associations between PGS and attention-deficit/hyperactivity disorder (ADHD) symptoms and internalizing and social problems measured repeatedly across childhood and adolescence and whether these associations depended on childhood phenotype, age, and rater.

Results: The sample included 42 998 participants aged 6 to 17 years. Male participants varied from 43.0% (1040 of 2417 participants) to 53.1% (2434 of 4583 participants) by age and across all cohorts. The PGS of adult major depression, neuroticism, BMI, and insomnia were positively associated with childhood psychopathology (β estimate range, 0.023-0.042 [95% CI, 0.017-0.049]), while associations with PGS of subjective well-being and educational attainment were negative (β, -0.026 to -0.046 [95% CI, -0.020 to -0.057]). There was no moderation of age, type of childhood phenotype, or rater with the associations. The exceptions were stronger associations between educational attainment PGS and ADHD compared with internalizing problems (Δβ, 0.0561 [Δ95% CI, 0.0318-0.0804]; ΔSE, 0.0124) and social problems (Δβ, 0.0528 [Δ95% CI, 0.0282-0.0775]; ΔSE, 0.0126), and between BMI PGS and ADHD and social problems (Δβ, -0.0001 [Δ95% CI, -0.0102 to 0.0100]; ΔSE, 0.0052), compared with internalizing problems (Δβ, -0.0310 [Δ95% CI, -0.0456 to -0.0164]; ΔSE, 0.0074). Furthermore, the association between educational attainment PGS and ADHD increased with age (Δβ, -0.0032 [Δ 95% CI, -0.0048 to -0.0017]; ΔSE, 0.0008).

Conclusions And Relevance: Results from this study suggest the existence of a set of genetic factors influencing a range of traits across the life span with stable associations present throughout childhood. Knowledge of underlying mechanisms may affect treatment and long-term outcomes of individuals with psychopathology.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.0527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160753PMC
July 2020

Content, diagnostic, correlational, and genetic similarities between common measures of childhood aggressive behaviors and related psychiatric traits.

J Child Psychol Psychiatry 2020 12 20;61(12):1328-1338. Epub 2020 Feb 20.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Background: Given the role of childhood aggressive behavior (AGG) in everyday child development, precise and accurate measurement is critical in clinical practice and research. This study aims to quantify agreement among widely used measures of childhood AGG regarding item content, clinical concordance, correlation, and underlying genetic construct.

Methods: We analyzed data from 1254 Dutch twin pairs (age 8-10 years, 51.1% boys) from a general population sample for whom both parents completed the A-TAC, CBCL, and SDQ at the same occasion.

Results: There was substantial variation in item content among AGG measures, ranging from .00 (i.e., mutually exclusive) to .50 (moderate agreement). Clinical concordance (i.e., do the same children score above a clinical threshold among AGG measures) was very weak to moderate with estimates ranging between .01 and .43 for mother-reports and between .12 and .42 for father-reports. Correlations among scales were weak to strong, ranging from .32 to .70 for mother-reports and from .32 to .64 for father-reports. We found weak to very strong genetic correlations among the measures, with estimates between .65 and .84 for mother-reports and between .30 and .87 for father-reports.

Conclusions: Our results demonstrated that degree of agreement between measures of AGG depends on the type (i.e., item content, clinical concordance, correlation, genetic correlation) of agreement considered. Because agreement was higher for correlations compared to clinical concordance (i.e., above or below a clinical cutoff), we propose the use of continuous scores to assess AGG, especially for combining data with different measures. Although item content can be different and agreement among observed measures may not be high, the genetic correlations indicate that the underlying genetic liability for childhood AGG is consistent across measures.
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http://dx.doi.org/10.1111/jcpp.13218DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754303PMC
December 2020

Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug-metabolite atlas.

Nat Med 2020 01 13;26(1):110-117. Epub 2020 Jan 13.

Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.

Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug-metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug-metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).
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http://dx.doi.org/10.1038/s41591-019-0722-xDOI Listing
January 2020

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies.

Nat Commun 2020 01 7;11(1):39. Epub 2020 Jan 7.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

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. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h), and the proportion of heritability captured by known metabolite loci (h) for 309 lipids and 52 organic acids. Our study reveals significant differences in h among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.
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http://dx.doi.org/10.1038/s41467-019-13770-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6946682PMC
January 2020

Genetic correlates of social stratification in Great Britain.

Nat Hum Behav 2019 12 21;3(12):1332-1342. Epub 2019 Oct 21.

Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia.

Human DNA polymorphisms vary across geographic regions, with the most commonly observed variation reflecting distant ancestry differences. Here we investigate the geographic clustering of common genetic variants that influence complex traits in a sample of ~450,000 individuals from Great Britain. Of 33 traits analysed, 21 showed significant geographic clustering at the genetic level after controlling for ancestry, probably reflecting migration driven by socioeconomic status (SES). Alleles associated with educational attainment (EA) showed the most clustering, with EA-decreasing alleles clustering in lower SES areas such as coal mining areas. Individuals who leave coal mining areas carry more EA-increasing alleles on average than those in the rest of Great Britain. The level of geographic clustering is correlated with genetic associations between complex traits and regional measures of SES, health and cultural outcomes. Our results are consistent with the hypothesis that social stratification leaves visible marks in geographic arrangements of common allele frequencies and gene-environment correlations.
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http://dx.doi.org/10.1038/s41562-019-0757-5DOI Listing
December 2019

A characterization of cis- and trans-heritability of RNA-Seq-based gene expression.

Eur J Hum Genet 2020 02 26;28(2):253-263. Epub 2019 Sep 26.

Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Insights into individual differences in gene expression and its heritability (h) can help in understanding pathways from DNA to phenotype. We estimated the heritability of gene expression of 52,844 genes measured in whole blood in the largest twin RNA-Seq sample to date (1497 individuals including 459 monozygotic twin pairs and 150 dizygotic twin pairs) from classical twin modeling and identity-by-state-based approaches. We estimated for each gene h, composed of cis-heritability (h, the variance explained by single nucleotide polymorphisms in the cis-window of the gene), and trans-heritability (h, the residual variance explained by all other genome-wide variants). Mean h was 0.26, which was significantly higher than heritability estimates earlier found in a microarray-based study using largely overlapping (>60%) RNA samples (mean h = 0.14, p = 6.15 × 10). Mean h was 0.06 and strongly correlated with beta of the top cis expression quantitative loci (eQTL, ρ = 0.76, p < 10) and with estimates from earlier RNA-Seq-based studies. Mean h was 0.20 and correlated with the beta of the corresponding trans-eQTL (ρ = 0.04, p < 1.89 × 10) and was significantly higher for genes involved in cytokine-cytokine interactions (p = 4.22 × 10), many other immune system pathways, and genes identified in genome-wide association studies for various traits including behavioral disorders and cancer. This study provides a thorough characterization of cis- and trans-h estimates of gene expression, which is of value for interpretation of GWAS and gene expression studies.
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http://dx.doi.org/10.1038/s41431-019-0511-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974598PMC
February 2020

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness.

Hum Mol Genet 2019 11;28(22):3853-3865

Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands.

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.
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http://dx.doi.org/10.1093/hmg/ddz219DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935385PMC
November 2019

A role for vitamin D and omega-3 fatty acids in major depression? An exploration using genomics.

Transl Psychiatry 2019 09 5;9(1):219. Epub 2019 Sep 5.

Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit/GGZ inGeest, Amsterdam, Netherlands.

Trials testing the effect of vitamin D or omega-3 polyunsaturated fatty acid (n3-PUFA) supplementation on major depressive disorder (MDD) reported conflicting findings. These trials were inspired by epidemiological evidence suggesting an inverse association of circulating 25-hydroxyvitamin D (25-OH-D) and n3-PUFA levels with MDD. Observational associations may emerge from unresolved confounding, shared genetic risk, or direct causal relationships. We explored the nature of these associations exploiting data and statistical tools from genomics. Results from genome-wide association studies on 25-OH-D (N = 79 366), n3-PUFA (N = 24 925), and MDD (135 458 cases, 344 901 controls) were applied to individual-level data (>2000 subjects with measures of genotype, DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edition) lifetime MDD diagnoses and circulating 25-OH-D and n3-PUFA) and summary-level data analyses. Shared genetic risk between traits was tested by polygenic risk scores (PRS). Two-sample Mendelian Randomization (2SMR) analyses tested the potential bidirectional causality between traits. In individual-level data analyses, PRS were associated with the phenotype of the same trait (PRS 25-OH-D p = 1.4e - 20, PRS n3-PUFA p = 9.3e - 6, PRS MDD p = 1.4e - 4), but not with the other phenotypes, suggesting a lack of shared genetic effects. In summary-level data analyses, 2SMR analyses provided no evidence of a causal role on MDD of 25-OH-D (p = 0.50) or n3-PUFA (p = 0.16), or for a causal role of MDD on 25-OH-D (p = 0.25) or n3-PUFA (p = 0.66). Applying genomics tools indicated that shared genetic risk or direct causality between 25-OH-D, n3-PUFA, and MDD is unlikely: unresolved confounding may explain the associations reported in observational studies. These findings represent a cautionary tale for testing supplementation of these compounds in preventing or treating MDD.
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http://dx.doi.org/10.1038/s41398-019-0554-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728377PMC
September 2019

Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior.

Science 2019 08;365(6456)

Centre for Psychology and Evolution, School of Psychology, University of Queensland, St. Lucia, Brisbane QLD 4072, Australia.

Twin and family studies have shown that same-sex sexual behavior is partly genetically influenced, but previous searches for specific genes involved have been underpowered. We performed a genome-wide association study (GWAS) on 477,522 individuals, revealing five loci significantly associated with same-sex sexual behavior. In aggregate, all tested genetic variants accounted for 8 to 25% of variation in same-sex sexual behavior, only partially overlapped between males and females, and do not allow meaningful prediction of an individual's sexual behavior. Comparing these GWAS results with those for the proportion of same-sex to total number of sexual partners among nonheterosexuals suggests that there is no single continuum from opposite-sex to same-sex sexual behavior. Overall, our findings provide insights into the genetics underlying same-sex sexual behavior and underscore the complexity of sexuality.
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http://dx.doi.org/10.1126/science.aat7693DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082777PMC
August 2019

Author Correction: GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability.

Nat Neurosci 2019 Jul;22(7):1196

Department of Youth and Family, Utrecht University, Utrecht, the Netherlands.

Several occurrences of the word 'schizophrenia' have been re-worded as 'liability to schizophrenia' or 'schizophrenia risk', including in the title, which should have been "GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability," as well as in Supplementary Figures 1-10 and Supplementary Tables 7-10, to more accurately reflect the findings of the work.
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http://dx.doi.org/10.1038/s41593-019-0402-7DOI Listing
July 2019

Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits.

Nat Hum Behav 2019 05 8;3(5):513-525. Epub 2019 Apr 8.

Department of Psychology, University of Texas at Austin, Austin, TX, USA.

Genetic correlations estimated from genome-wide association studies (GWASs) reveal pervasive pleiotropy across a wide variety of phenotypes. We introduce genomic structural equation modelling (genomic SEM): a multivariate method for analysing the joint genetic architecture of complex traits. Genomic SEM synthesizes genetic correlations and single-nucleotide polymorphism heritabilities inferred from GWAS summary statistics of individual traits from samples with varying and unknown degrees of overlap. Genomic SEM can be used to model multivariate genetic associations among phenotypes, identify variants with effects on general dimensions of cross-trait liability, calculate more predictive polygenic scores and identify loci that cause divergence between traits. We demonstrate several applications of genomic SEM, including a joint analysis of summary statistics from five psychiatric traits. We identify 27 independent single-nucleotide polymorphisms not previously identified in the contributing univariate GWASs. Polygenic scores from genomic SEM consistently outperform those from univariate GWASs. Genomic SEM is flexible and open ended, and allows for continuous innovation in multivariate genetic analysis.
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http://dx.doi.org/10.1038/s41562-019-0566-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6520146PMC
May 2019

Biological insights into multiple birth: genetic findings from UK Biobank.

Eur J Hum Genet 2019 06 13;27(6):970-979. Epub 2019 Feb 13.

Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands.

The tendency to conceive spontaneous dizygotic (DZ) twins is a complex trait with important contributions from both environmental factors and genetic disposition. In earlier work, we identified the first two genes as maternal susceptibility loci for DZ twinning. The aim of this study was to identify genetic variants influencing multiple births and to genetically correlate the findings across a broad range of traits. We performed a genome-wide association study (GWAS) in 8962 participants with Caucasian ancestry from UK Biobank who reported being part of a multiple birth, and 409,591 singleton controls. We replicated the association between FSHB, SMAD3 and twinning in the gene-based (but not SNP-based) test, which had been established in previous genome-wide association analyses in mothers with dizygotic twin offspring. Additionally, we report a novel genetic variant associated with multiple birth, rs428022 at 15q23 (p = 2.84 × 10) close to two genes: PIAS1 and SKOR1. Finally, we identified meaningful genetic correlations between being part of a multiple birth and other phenotypes (anthropometric traits, health-related traits, and fertility-related measures). The outcomes of this study provide important new insights into the genetic aetiology of multiple births and fertility, and open up novel directions for fertility and reproduction research.
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http://dx.doi.org/10.1038/s41431-019-0355-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777609PMC
June 2019

Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences.

Nat Genet 2019 02 14;51(2):245-257. Epub 2019 Jan 14.

Team Loyalty BV, Hoofddorp, the Netherlands.

Humans vary substantially in their willingness to take risks. In a combined sample of over 1 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. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.
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http://dx.doi.org/10.1038/s41588-018-0309-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713272PMC
February 2019

Multivariate genome-wide analyses of the well-being spectrum.

Nat Genet 2019 03 14;51(3):445-451. Epub 2019 Jan 14.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

We introduce two novel methods for multivariate genome-wide-association meta-analysis (GWAMA) of related traits that correct for sample overlap. A broad range of simulation scenarios supports the added value of our multivariate methods relative to univariate GWAMA. We applied the novel methods to life satisfaction, positive affect, neuroticism, and depressive symptoms, collectively referred to as the well-being spectrum (N = 2,370,390), and found 304 significant independent signals. Our multivariate approaches resulted in a 26% increase in the number of independent signals relative to the four univariate GWAMAs and in an ~57% increase in the predictive power of polygenic risk scores. Supporting transcriptome- and methylome-wide analyses (TWAS and MWAS, respectively) uncovered an additional 17 and 75 independent loci, respectively. Bioinformatic analyses, based on gene expression in brain tissues and cells, showed that genes differentially expressed in the subiculum and GABAergic interneurons are enriched in their effect on the well-being spectrum.
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http://dx.doi.org/10.1038/s41588-018-0320-8DOI Listing
March 2019

DNA methylation signatures of educational attainment.

NPJ Sci Learn 2018 23;3. Epub 2018 Mar 23.

1Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs ( = 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.
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http://dx.doi.org/10.1038/s41539-018-0020-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6220239PMC
March 2018

GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia.

Nat Neurosci 2018 09 27;21(9):1161-1170. Epub 2018 Aug 27.

Department of Youth and Family, Utrecht University, Utrecht, the Netherlands.

Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.
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http://dx.doi.org/10.1038/s41593-018-0206-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386176PMC
September 2018
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