Publications by authors named "Jouke-Jan Hottenga"

250 Publications

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Nat Genet 2021 Sep 6;53(9):1311-1321. Epub 2021 Sep 6.

Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.
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http://dx.doi.org/10.1038/s41588-021-00923-xDOI Listing
September 2021

Predicting Complex Traits and Exposures From Polygenic Scores and Blood and Buccal DNA Methylation Profiles.

Front Psychiatry 2021 29;12:688464. Epub 2021 Jul 29.

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

We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6%) of which 54.4% was captured by the MS. The two predictors captured 16% of former vs. never smoking initiation variance (MS:15.5%, PGS: 0.5%), 17.7% of prenatal maternal smoking variance (MS:16.9%, PGS: 0.8%), 11.9% of BMI variance (MS: 6.4%, PGS 5.5%), and 1.9% of birth weight variance (MS: 0.4%, PGS: 1.5%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6%), where the MSs contributed 1.5%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.
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http://dx.doi.org/10.3389/fpsyt.2021.688464DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357987PMC
July 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
September 2021

Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility.

PLoS One 2021 11;16(8):e0255402. Epub 2021 Aug 11.

Helix OpCo LLC, San Mateo, California, United States of America.

Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255402PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357137PMC
August 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

Implementation and implications for polygenic risk scores in healthcare.

Hum Genomics 2021 Jul 20;15(1):46. Epub 2021 Jul 20.

Avera Institute for Human Genetics, Avera McKennan & University Health Center, Sioux Falls, SD, USA.

Increasing amounts of genetic data have led to the development of polygenic risk scores (PRSs) for a variety of diseases. These scores, built from the summary statistics of genome-wide association studies (GWASs), are able to stratify individuals based on their genetic risk of developing various common diseases and could potentially be used to optimize the use of screening and preventative treatments and improve personalized care for patients. Many challenges are yet to be overcome, including PRS validation, healthcare professional and patient education, and healthcare systems integration. Ethical challenges are also present in how this information is used and the current lack of diverse populations with PRSs available. In this review, we discuss the topics above and cover the nature of PRSs, visualization schemes, and how PRSs can be improved. With these tools on the horizon for multiple diseases, scientists, clinicians, health systems, regulatory bodies, and the public should discuss the uses, benefits, and potential risks of PRSs.
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http://dx.doi.org/10.1186/s40246-021-00339-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8290135PMC
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

Expanding the environmental scope: an environment-wide association study for mental well-being.

J Expo Sci Environ Epidemiol 2021 Jun 14. Epub 2021 Jun 14.

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

Background: Identifying modifiable factors associated with well-being is of increased interest for public policy guidance. Developments in record linkage make it possible to identify what contributes to well-being from a myriad of factors. To this end, we link two large-scale data resources; the Geoscience and Health Cohort Consortium, a collection of geo-data, and the Netherlands Twin Register, which holds population-based well-being data.

Objective: We perform an Environment-Wide Association Study (EnWAS), where we examine 139 neighbourhood-level environmental exposures in relation to well-being.

Methods: First, we performed a generalized estimation equation regression (N = 11,975) to test for the effects of environmental exposures on well-being. Second, to account for multicollinearity amongst exposures, we performed principal component regression. Finally, using a genetically informative design, we examined whether environmental exposure is driven by genetic predisposition for well-being.

Results: We identified 21 environmental factors that were associated with well-being in the domains: housing stock, income, core neighbourhood characteristics, livability, and socioeconomic status. Of these associations, socioeconomic status and safety are indicated as the most important factors to explain differences in well-being. No evidence of gene-environment correlation was found.

Significance: These observed associations, especially neighbourhood safety, could be informative for policy makers and provide public policy guidance to improve well-being. Our results show that linking databases is a fruitful exercise to identify determinants of mental health that would remain unknown by a more unilateral approach.
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http://dx.doi.org/10.1038/s41370-021-00346-0DOI Listing
June 2021

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
March 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Genetic meta-analysis of twin birth weight shows high genetic correlation with singleton birth weight.

Hum Mol Genet 2021 Sep;30(19):1894-1905

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Birth weight (BW) is an important predictor of newborn survival and health and has associations with many adult health outcomes, including cardiometabolic disorders, autoimmune diseases and mental health. On average, twins have a lower BW than singletons as a result of a different pattern of fetal growth and shorter gestational duration. Therefore, investigations into the genetics of BW often exclude data from twins, leading to a reduction in sample size and remaining ambiguities concerning the genetic contribution to BW in twins. In this study, we carried out a genome-wide association meta-analysis of BW in 42 212 twin individuals and found a positive correlation of beta values (Pearson's r = 0.66, 95% confidence interval [CI]: 0.47-0.77) with 150 previously reported genome-wide significant variants for singleton BW. We identified strong positive genetic correlations between BW in twins and numerous anthropometric traits, most notably with BW in singletons (genetic correlation [rg] = 0.92, 95% CI: 0.66-1.18). Genetic correlations of BW in twins with a series of health-related traits closely resembled those previously observed for BW in singletons. Polygenic scores constructed from a genome-wide association study on BW in the UK Biobank demonstrated strong predictive power in a target sample of Dutch twins and singletons. Together, our results indicate that a similar genetic architecture underlies BW in twins and singletons and that future genome-wide studies might benefit from including data from large twin registers.
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http://dx.doi.org/10.1093/hmg/ddab121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444448PMC
September 2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Transl Psychiatry 2021 03 22;11(1):182. Epub 2021 Mar 22.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
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http://dx.doi.org/10.1038/s41398-021-01213-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985307PMC
March 2021

Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.

Hum Brain Mapp 2021 Feb 21. Epub 2021 Feb 21.

Center for Neuroimaging, Genetics and Genomics, School of Psychology, NUI Galway, Galway, Ireland.

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
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http://dx.doi.org/10.1002/hbm.25354DOI Listing
February 2021

Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts.

Transl Psychiatry 2021 02 4;11(1):96. Epub 2021 Feb 4.

Institute of Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland.

Studies considering the causal role of body mass index (BMI) for the predisposition of major depressive disorder (MDD) based on a Mendelian Randomization (MR) approach have shown contradictory results. These inconsistent findings may be attributable to the heterogeneity of MDD; in fact, several studies have documented associations between BMI and mainly the atypical subtype of MDD. Using a MR approach, we investigated the potential causal role of obesity in both the atypical subtype and its five specific symptoms assessed according to the Statistical Manual of Mental Disorders (DSM), in two large European cohorts, CoLaus|PsyCoLaus (n = 3350, 1461 cases and 1889 controls) and NESDA|NTR (n = 4139, 1182 cases and 2957 controls). We first tested general obesity measured by BMI and then the body fat distribution measured by waist-to-hip ratio (WHR). Results suggested that BMI is potentially causally related to the symptom increase in appetite, for which inverse variance weighted, simple median and weighted median MR regression estimated slopes were 0.68 (SE = 0.23, p = 0.004), 0.77 (SE = 0.37, p = 0.036), and 1.11 (SE = 0.39, p = 0.004). No causal effect of BMI or WHR was found on the risk of the atypical subtype or for any of the other atypical symptoms. Our findings show that higher obesity is likely causal for the specific symptom of increase in appetite in depressed participants and reiterate the need to study depression at the granular level of its symptoms to further elucidate potential causal relationships and gain additional insight into its biological underpinnings.
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http://dx.doi.org/10.1038/s41398-021-01236-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862438PMC
February 2021

Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Hum Mol Genet 2021 04;30(5):393-409

Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK.

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.
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http://dx.doi.org/10.1093/hmg/ddab023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098112PMC
April 2021

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Nat Commun 2021 01 5;12(1):24. Epub 2021 Jan 5.

Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits.

Nat Commun 2020 11 3;11(1):5562. Epub 2020 Nov 3.

Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159, Mannheim, Germany.

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (r = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking.
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http://dx.doi.org/10.1038/s41467-020-19265-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642344PMC
November 2020

Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits.

PLoS Genet 2020 10 12;16(10):e1008718. Epub 2020 Oct 12.

Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.

The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.
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http://dx.doi.org/10.1371/journal.pgen.1008718DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581004PMC
October 2020

Genome-wide association study identifies 48 common genetic variants associated with handedness.

Nat Hum Behav 2021 01 28;5(1):59-70. Epub 2020 Sep 28.

Institute of Biological Psychiatry, Mental Health Services of Copenhagen, Copenhagen, Denmark.

Handedness has been extensively studied 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 the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.
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http://dx.doi.org/10.1038/s41562-020-00956-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116623PMC
January 2021

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

Am J Med Genet B Neuropsychiatr Genet 2020 09 18;183(6):309-330. Epub 2020 Jul 18.

Max Planck Institute of Psychiatry, Munich, Germany.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.
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http://dx.doi.org/10.1002/ajmg.b.32807DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7991693PMC
September 2020

Illicit drug use and the genetic overlap with Cannabis use.

Drug Alcohol Depend 2020 Jun 10;213:108102. Epub 2020 Jun 10.

Amsterdam UMC, location AMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.

Background: The use of illicit substances is correlated, meaning that individuals who use one illicit substance are more likely to also use another illicit substance. This association could (partly) be explained by overlapping genetic factors. Genetic overlap may indicate a common underlying genetic predisposition, or can be the result of a causal association.

Methods: Polygenic scores for lifetime cannabis use were generated in a sample of Dutch participants (N = 8348). We tested the association of a PGS for cannabis use with ecstasy, stimulants and a broad category of illicit drug use. To explore the nature of the relationship: (1) these analyses were repeated separately in cannabis users and non-users and (2) monozogytic twin pairs discordant for cannabis use were compared on their drug use.

Results: The lifetime prevalence was 24.8 % for cannabis, 6.2 % for ecstasy, 6.5 % for stimulants and 7.1 % for any illicit drug use. Significant, positive associations were found between PGS for cannabis use with ecstasy use, stimulants and any illicit drug use. These associations seemed to be stronger in cannabis users compared to non-users for both ecstasy and stimulant use, but only in people born after 1968 and not significant after correction for multiple testing. The discordant twin pair analyses suggested that cannabis use could play a causal role in drug use.

Conclusions: The genetic liability underlying cannabis use significantly explained variability in ecstasy, stimulant and any illicit drug use. Further research should further explore the underlying mechanism to understand the nature of the association.
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http://dx.doi.org/10.1016/j.drugalcdep.2020.108102DOI Listing
June 2020

Urinary Amine and Organic Acid Metabolites Evaluated as Markers for Childhood Aggression: The ACTION Biomarker Study.

Front Psychiatry 2020 31;11:165. Epub 2020 Mar 31.

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

Biomarkers are of interest as potential diagnostic and predictive instruments in personalized medicine. We present the first urinary metabolomics biomarker study of childhood aggression. We aim to examine the association of urinary metabolites and neurotransmitter ratios involved in key metabolic and neurotransmitter pathways in a large cohort of twins ( = 1,347) and clinic-referred children ( = 183) with an average age of 9.7 years. This study is part of ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies), in which we developed a standardized protocol for large-scale collection of urine samples in children. Our analytical design consisted of three phases: a discovery phase in twins scoring low or high on aggression ( = 783); a replication phase in twin pairs discordant for aggression ( = 378); and a validation phase in clinical cases and matched twin controls ( = 367). In the discovery phase, 6 biomarkers were significantly associated with childhood aggression, of which the association of O-phosphoserine (β = 0.36; = 0.09; = 0.004), and gamma-L-glutamyl-L-alanine (β = 0.32; = 0.09; = 0.01) remained significant after multiple testing. Although non-significant, the directions of effect were congruent between the discovery and replication analyses for six biomarkers and two neurotransmitter ratios and the concentrations of 6 amines differed between low and high aggressive twins. In the validation analyses, the top biomarkers and neurotransmitter ratios, with congruent directions of effect, showed no significant associations with childhood aggression. We find suggestive evidence for associations of childhood aggression with metabolic dysregulation of neurotransmission, oxidative stress, and energy metabolism. Although replication is required, our findings provide starting points to investigate causal and pleiotropic effects of these dysregulations on childhood aggression.
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http://dx.doi.org/10.3389/fpsyt.2020.00165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138132PMC
March 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

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Substance use: Interplay between polygenic risk and neighborhood environment.

Drug Alcohol Depend 2020 04 28;209:107948. Epub 2020 Feb 28.

Behavioural Science Institute, Radboud University Nijmegen, the Netherlands.

Background: Tobacco, alcohol, and cannabis use are prevalent behaviors that pose considerable health risks. Genetic vulnerability and characteristics of the neighborhood of residence form important risk factors for substance use. Possibly, these factors do not act in isolation. This study tested the interaction between neighborhood characteristics and genetic risk (gene-environment interaction, GxE) and the association between these classes of risk factors (gene-environment correlation, rGE) in substance use.

Methods: Two polygenic scores (PGS) each (based on different discovery datasets) were created for smoking initiation, cigarettes per day, and glasses of alcohol per week based on summary statistics of different genome-wide association studies (GWAS). For cannabis initiation one PGS was created. These PGS were used to predict their respective phenotype in a large population-based sample from the Netherlands Twin Register (N = 6,567). Neighborhood characteristics as retrieved from governmental registration systems were factor analyzed and resulting measures of socioeconomic status (SES) and metropolitanism were used as predictors.

Results: There were (small) main effects of neighborhood characteristics and PGS on substance use. One of the 14 tested GxE effects was significant, such that the PGS was more strongly associated with alcohol use in individuals with high SES. This was effect was only significant for one out of two PGS. There were weak indications of rGE, mainly with age and cohort covariates.

Conclusion: We conclude that both genetic and neighborhood-level factors are predictors for substance use. More research is needed to establish the robustness of the findings on the interplay between these factors.
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http://dx.doi.org/10.1016/j.drugalcdep.2020.107948DOI Listing
April 2020

Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length.

Am J Hum Genet 2020 03 27;106(3):389-404. Epub 2020 Feb 27.

Department of Cardiovascular Sciences, University of Leicester, LE3 9QP, United Kingdom; NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, United Kingdom.

Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.
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http://dx.doi.org/10.1016/j.ajhg.2020.02.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058826PMC
March 2020

Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report).

Psychol Med 2020 Feb 27:1-10. Epub 2020 Feb 27.

Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam, The Netherlands.

Background: Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression.

Methods: Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS).

Results: Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15-1.32, R2 = 1.47%).

Conclusions: By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.
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http://dx.doi.org/10.1017/S0033291720000100DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8223240PMC
February 2020

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Addict Biol 2021 01 16;26(1):e12880. Epub 2020 Feb 16.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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http://dx.doi.org/10.1111/adb.12880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429266PMC
January 2021
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