Publications by authors named "Iryna O Fedko"

28 Publications

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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

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

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 architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes.

Nat Genet 2019 07 28;51(7):1137-1148. Epub 2019 Jun 28.

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

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.
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http://dx.doi.org/10.1038/s41588-019-0457-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6640048PMC
July 2019

Genome-wide association meta-analysis of age at first cannabis use.

Addiction 2018 11 19;113(11):2073-2086. Epub 2018 Aug 19.

Brain and Mind Research Institute, University of Sydney, Sydney, NSW, Australia.

Background And Aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants.

Methods: A twin-based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome-wide association meta-analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals.

Results: The twin-based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19-60%]. Shared and unique environmental factors explained 39% (95% CI = 20-56%) and 22% (95% CI = 16-29%). The genome-wide association meta-analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high linkage disequilibrium (LD) (r  > 0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant.

Conclusion: Age at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.
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http://dx.doi.org/10.1111/add.14368DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087375PMC
November 2018

Polygenic risk for alcohol consumption and its association with alcohol-related phenotypes: Do stress and life satisfaction moderate these relationships?

Drug Alcohol Depend 2018 02 2;183:7-12. Epub 2017 Dec 2.

Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands. Electronic address:

Background: Genetic and environmental factors contribute about equally to alcohol-related phenotypes in adulthood. In the present study, we examined whether more stress at home or low satisfaction with life might be associated with heavier drinking or more alcohol-related problems in individuals with a high genetic susceptibility to alcohol use.

Methods: Information on polygenic scores and drinking behavior was available in 6705 adults (65% female; 18-83 years) registered with the Netherlands Twin Register. Polygenic risk scores (PRSs) were constructed for all subjects based on the summary statistics of a large genome-wide association meta-analysis on alcohol consumption (grams per day). Outcome measures were quantity of alcohol consumption and alcohol-related problems assessed with the Alcohol Use Disorders Identification Test (AUDIT). Stress at home and life satisfaction were moderating variables whose significance was tested by Generalized Estimating Equation analyses taking familial relatedness, age and sex into account.

Results: PRSs for alcohol were significantly associated with quantity of alcohol consumption and alcohol-related problems in the past year (R=0.11% and 0.10% respectively). Participants who reported to have experienced more stress in the past year and lower life satisfaction, scored higher on alcohol-related problems (R=0.27% and 0.29 respectively), but not on alcohol consumption. Stress and life satisfaction did not moderate the association between PRSs and the alcohol outcome measures.

Conclusions: There were significant main effects of polygenic scores and of stress and life satisfaction on drinking behavior, but there was no support for PRS-by-stress or PRS-by-life satisfaction interactions on alcohol consumption and alcohol-related problems.
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http://dx.doi.org/10.1016/j.drugalcdep.2017.10.018DOI Listing
February 2018

Dopaminergic Genetic Variants and Voluntary Externally Paced Exercise Behavior.

Med Sci Sports Exerc 2018 04;50(4):700-708

Department of Biological Psychology, VU University Amsterdam, Amsterdam, THE NETHERLANDS.

Purpose: Most candidate gene studies on the neurobiology of voluntary exercise behavior have focused on the dopaminergic signaling pathway and its role in the mesolimbic reward system. We hypothesized that dopaminergic candidate genes may influence exercise behavior through additional effects on executive functioning and that these effects are only detected when the types of exercise activity are taken into account.

Methods: Data on voluntary exercise behavior and at least one single-nucleotide polymorphism/variable number of tandem repeat (VNTR) were available for 12,929 participants of the Netherlands Twin Registry. Exercise activity was classified as externally paced if a high level of executive function skill was required. The total volume of voluntary exercise (minutes per week) as well as the volume specifically spent on externally paced activities were tested for association with nine functional dopaminergic polymorphisms (DRD1: rs265981, DRD2/ANKK1: rs1800497, DRD3: rs6280, DRD4: VNTR 48 bp, DRD5: VNTR 130-166 bp, DBH: rs2519152, DAT1: VNTR 40 bp, COMT: rs4680, MAOA: VNTR 30 bp), a polygenic score (PGS) based on nine alleles leading to lower dopamine responsiveness, and a PGS based on three alleles associated with both higher reward sensitivity and better executive functioning (DRD2/ANKK1: "G" allele, COMT: Met allele, DAT1: 440-bp allele).

Results: No association with total exercise volume or externally paced exercise volume was found for individual alleles or the nine-allele PGS. The volume of externally paced exercise behavior was significantly associated with the reward and executive function congruent PGS. This association was driven by the DAT1 440-bp and COMT Met allele, which acted as increaser alleles for externally paced exercise behavior.

Conclusions: Taking into account the types of exercise activity may increase the success of identifying genetic variants and unraveling the neurobiology of voluntary exercise behavior.
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http://dx.doi.org/10.1249/MSS.0000000000001479DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856580PMC
April 2018

Testing Familial Transmission of Smoking With Two Different Research Designs.

Nicotine Tob Res 2018 06;20(7):836-842

Radboud University Nijmegen, Behavioural Science Institute, the Netherlands.

Introduction: Classical twin studies show that smoking is heritable. To determine if shared family environment plays a role in addition to genetic factors, and if they interact (G×E), we use a children-of-twins design. In a second sample, we measure genetic influence with polygenic risk scores (PRS) and environmental influence with a question on exposure to smoking during childhood.

Methods: Data on smoking initiation were available for 723 children of 712 twins from the Netherlands Twin Register (64.9% female, median birth year 1985). Children were grouped in ascending order of risk, based on smoking status and zygosity of their twin-parent and his/her co-twin: never smoking twin-parent with a never smoking co-twin; never smoking twin-parent with a smoking dizygotic co-twin; never smoking twin-parent with a smoking monozygotic co-twin; and smoking twin-parent with a smoking or never smoking co-twin. For 4072 participants from the Netherlands Twin Register (67.3% female, median birth year 1973), PRS for smoking were computed and smoking initiation, smoking heaviness, and exposure to smoking during childhood were available.

Results: Patterns of smoking initiation in the four group children-of-twins design suggested shared familial influences in addition to genetic factors. PRS for ever smoking were associated with smoking initiation in all individuals. PRS for smoking heaviness were associated with smoking heaviness in individuals exposed to smoking during childhood, but not in non-exposed individuals.

Conclusions: Shared family environment influences smoking, over and above genetic factors. Genetic risk of smoking heaviness was only important for individuals exposed to smoking during childhood, versus those not exposed (G×E).

Implications: This study adds to the very few existing children-of-twins (CoT) studies on smoking and combines a CoT design with a second research design that utilizes polygenic risk scores and data on exposure to smoking during childhood. The results show that shared family environment affects smoking behavior over and above genetic factors. There was also evidence for gene-environment interaction (G×E) such that genetic risk of heavy versus light smoking was only important for individuals who were also exposed to (second-hand) smoking during childhood. Together, these findings give additional incentive to recommending parents not to expose their children to cigarette smoking.
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http://dx.doi.org/10.1093/ntr/ntx121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685054PMC
June 2018

Heritability and GWAS Studies for Monocyte-Lymphocyte Ratio.

Twin Res Hum Genet 2017 04 14;20(2):97-107. Epub 2017 Feb 14.

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

The monocyte-lymphocyte ratio (MLR) is a useful biomarker for disease development, but little is known about the extent to which genetic and environmental factors influence MLR variation. Here, we study the genetic architecture of MLR and determine the influence of demographic and lifestyle factors on MLR in data from a Dutch non-patient twin-family population. Data were obtained in 9,501 individuals from the Netherlands Twin Register. We used regression analyses to determine the effects of age, sex, smoking, and body mass index (BMI) on MLR and its subcomponents. Data on twins, siblings and parents (N = 7,513) were analyzed by genetic structural equation modeling to establish heritability and genome wide single nucleotide polymorphism (SNP) data from a genotyped subsample (N = 5,892) and used to estimate heritability explained by SNPs. SNP and phenotype data were also analyzed in a genome-wide association study to identify the genes involved in MLR. Linkage disequilibrium (LD) score regression and expression quantitative trait loci (eQTL) analyses were performed to further explore the genetic findings. Results showed that age, sex, and age × sex interaction effects were present for MLR and its subcomponents. Variation in MLR was not related to BMI, but smoking was positively associated with MLR. Heritability was estimated at 40% for MLR, 58% for monocyte, and 58% for lymphocyte count. The Genome-wide association study (GWAS) identified a locus on ITGA4 that was associated with MLR and only marginally significantly associated with monocyte count. For monocyte count, additional genetic variants were identified on ITPR3, LPAP1, and IRF8. For lymphocyte count, GWAS provided no significant findings. Taking all measured SNPs together, their effects accounted for 13% of the heritability of MLR, while all known and identified genetic loci explained 1.3% of variation in MLR. eQTL analyses showed that these genetic variants were unlikely to be eQTLs. In conclusion, variation in MLR level in the general population is heritable and influenced by age, sex, and smoking. We identified gene variants in the ITGA4 gene associated with variation in MLR. The significant SNP-heritability indicates that more genetic variants are likely to be involved.
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http://dx.doi.org/10.1017/thg.2017.3DOI Listing
April 2017

Novel genetic loci associated with hippocampal volume.

Nat Commun 2017 01 18;8:13624. Epub 2017 Jan 18.

Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
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http://dx.doi.org/10.1038/ncomms13624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253632PMC
January 2017

A method to customize population-specific arrays for genome-wide association testing.

Eur J Hum Genet 2017 02 23;25(2):267-270. Epub 2016 Nov 23.

The Netherlands Twin Register, Vrije Universiteit (VU), Amsterdam, The Netherlands.

As an example of optimizing population-specific genotyping assays using a whole-genome sequence reference set, we detail the approach that followed to design the Axiom-NL array which is characterized by an improved imputation backbone based on the Genome of the Netherlands (GoNL) reference sequence and, compared with earlier arrays, a more comprehensive inclusion of SNPs on chromosomes X, Y, and the mitochondria. Common variants on the array were selected to be compatible with the Illumina Psych Array and the Affymetrix UK Biobank Axiom array. About 3.5% of the array (23 977 markers) represents SNPs from the GWAS catalog, including SNPs at FTO, APOE, Ion-channels, killer-cell immunoglobulin-like receptors, and HLA. Around 26 000 markers associated with common psychiatric disorders are included, as well as 6705 markers suggested to be associated with fertility and twinning. The platform can thus be used for risk profiling, detection of new variants, as well as ancestry determination. Results of coverage tests in 249 unrelated subjects with GoNL-based sequence data show that after imputation with 1000G as a reference, the median concordance between original and imputed genotypes is above 98%. The median imputation quality R for MAF thresholds of 0.001, 0.01, 0.05, and >0.05 are 0.05, 0.28, 0.80, 0.99, respectively, for the 1000G imputed SNPs, with a similar quality for the autosomes and X chromosome, showing a good genome-wide coverage for association studies after imputation.
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http://dx.doi.org/10.1038/ejhg.2016.152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5255952PMC
February 2017

Heritability of Behavioral Problems in 7-Year Olds Based on Shared and Unique Aspects of Parental Views.

Behav Genet 2017 03 28;47(2):152-163. Epub 2016 Oct 28.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 1, 1081BT, Amsterdam, The Netherlands.

In studies of child psychopathology, phenotypes of interest are often obtained by parental ratings. When behavioral ratings are obtained in the context of a twin study, this allows for the decomposition of the phenotypic variance, into a genetic and a non-genetic part. If a phenotype is assessed by a single rater, heritability is based on the child's behavior as expressed in the presence of that particular rater, whereas heritability based on assessments by multiple raters allows for the estimation of the heritability of the phenotype based on rater agreement, as well as the heritability of the rater specific view of the behavior. The aim of this twin study was to quantify the rater common and rater specific contributions to the variation in children's behavioral problems. We estimated the heritability of maternal and paternal ratings of the Child Behavior Checklist (CBCL) 6-18 empirical emotional and behavioral problem scales in a large sample of 12,310 7-year old Dutch twin pairs. Between 30 and 59% of variation in the part of the phenotype parents agree upon was explained by genetic effects. Common environmental effects that make children in the same family similar explained less variance, ranging between 0 and 32%. For unique views of their children's behavioral problems, heritability ranged between 0 and 20% for maternal and between 0 and 22% for paternal views. Between 7 and 24% of the variance was accounted for by common environmental factors specific to mother and father's views. The proportion of rater shared and rater specific heritability can be translated into genetic correlations between parental views and inform the design and interpretation of results of molecular genetic studies. Genetic correlations were nearly or above 0.7 for all CBCL based psychopathology scales. Such large genetic correlations suggest two practical guidelines for genome-wide association studies (GWAS): when studies have collected data from either fathers or mothers, the shared genetic aetiology in parental ratings indicates that is possible to analyze paternal and maternal assessments in a single GWAS or meta-analysis. Secondly, if a study has collected information from both parents, a gain in statistical power may be realized in GWAS by the simultaneous analysis of the data.
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http://dx.doi.org/10.1007/s10519-016-9823-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306273PMC
March 2017

Novel genetic loci underlying human intracranial volume identified through genome-wide association.

Nat Neurosci 2016 12 3;19(12):1569-1582. Epub 2016 Oct 3.

Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht, the Netherlands.

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.
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http://dx.doi.org/10.1038/nn.4398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5227112PMC
December 2016

Psychopathology in 7-year-old children: Differences in maternal and paternal ratings and the genetic epidemiology.

Am J Med Genet B Neuropsychiatr Genet 2017 Apr 24;174(3):251-260. Epub 2016 Oct 24.

Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.

The assessment of children's psychopathology is often based on parental report. Earlier studies have suggested that rater bias can affect the estimates of genetic, shared environmental and unique environmental influences on differences between children. The availability of a large dataset of maternal as well as paternal ratings of psychopathology in 7-year old children enabled (i) the analysis of informant effects on these assessments, and (ii) to obtain more reliable estimates of the genetic and non-genetic effects. DSM-oriented measures of affective, anxiety, somatic, attention-deficit/hyperactivity, oppositional-defiant, conduct, and obsessive-compulsive problems were rated for 12,310 twin pairs from the Netherlands Twin Register by mothers (N = 12,085) and fathers (N = 8,516). The effects of genetic and non-genetic effects were estimated on the common and rater-specific variance. For all scales, mean scores on maternal ratings exceeded paternal ratings. Parents largely agreed on the ranking of their child's problems (r 0.60-0.75). The heritability was estimated over 55% for maternal and paternal ratings for all scales, except for conduct problems (44-46%). Unbiased shared environmental influences, i.e., on the common variance, were significant for affective (13%), oppositional (13%), and conduct problems (37%). In clinical settings, different cutoffs for (sub)clinical scores could be applied to paternal and maternal ratings of their child's psychopathology. Only for conduct problems, shared environmental and genetic influences explain an equal amount in differences between children. For the other scales, genetic factors explain the majority of the variance, especially for the common part that is free of rater bias. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/ajmg.b.32500DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5413051PMC
April 2017

A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts.

J Am Acad Child Adolesc Psychiatry 2016 10 5;55(10):896-905.e6. Epub 2016 Aug 5.

Dr. Middeldorp is with Biological Psychology, Neuroscience Campus Amsterdam, VU University Amsterdam, and GGZinGeest/ VU University Medical Center, Amsterdam. Ms. Hammerschlag is with the Generation R Study Group, Erasmus MC Rotterdam, the Netherlands, and Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam. Mr. Ouwens and Dr. Groen-Blokhuis are with Biological Psychology, VU University Amsterdam, and the EMGO+ Institute for Health and Care Research, VU University Medical Center. Dr. St. Pourcain is with MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, UK, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands, and School of Experimental Psychology, University of Bristol. Dr. Greven is with Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Karakter, Child and Adolescent Psychiatry University Center, Radboud University Nijmegen, and MRC Social Genetic and Developmental Psychiatry Centre, King's College London. Dr. Pappa is with Generation R Study Group, and Pedagogical and Education Science, Erasmus University Rotterdam, The Netherlands. Drs. Tiesler and Thiering are with Institute of Epidemiology I, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany and the Division of Metabolic and Nutritional Medicine, Munich, and Dr. von Hauner Children's Hospital, University of Munich Medical Center, Germany. Mr. Ang, Ms. Wang, and Dr. Pennell are with School of Women's and Infants' Health, University of Western Australia, Perth. Dr. Nolte is with University of Groningen, University Medical Center Groningen, The Netherlands. Ms. Vilor-Tejedor is with Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Universitat Pompeu Fabra (UPF), Barcelona, and CIBER Epidemiology and Public Health (CIBERESP), Madrid. Mr. Bacelis is with Gothenburg University, Sweden. Drs. Ebejer, Martin, and Medland are with QIMR Berghofer Medical Research Institute, Brisbane, Australia. Drs. Zhao and Nyholt are with Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia. Drs. Davies and Ehli are with Avera Institute for Human Genetics, SD. Drs. Evans, Kemp, and Ring are with MRC IEU, School of Social and Community Medicine, and School of Social and Community Medicine, University of Bristol, and Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane. Ms. Fedko is with Biological Psychology, VU University Amsterdam. Dr. Guxens is with CREAL, UPF, CIBERESP, and Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children´s Hospital, The Netherlands. Dr. Hottenga is with Biological Psychology, VU University, and EMGO+ Institute for Health and Care Research, VU University Medical Center. Dr. Hudziak is with Vermont Center for Children, Youth and Families and College of Medicine, University of Vermont, Burlington, and Child and Adolescent Psychiatry, Erasmus Medical Center. Drs. Jugessur, Myhre, and Stoltenberg are with the Norwegian Institute of Public Health, Oslo. Ms. Krapohl and Drs. Trzaskowski and Plomin are with MRC Social, Genetic and Developmental Psychiatry Centre, King's College London. Mr. Murcia is with CIBERESP, and FISABIO-Universitat Jaume I-Universitat de València Joint Research Unit of Epidemiology and Environmental Health, Valencia, Spain. Drs. Ormel and Hartman are with the Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University Medical Center Groningen. Drs. Standl and Heinrich are with Institute of Epidemiology I, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. Drs. Stergiakouli and Timpson are with MRC IEU; Dr. Timpson is also with School of Social and Community Medicine, University of Bristol. Dr. van der Most is with University of Groningen and University Medical Center Groningen. Dr. Neale is with Program in Medical and Population Genetics and Stanley Center for Psychiatric Genetics, Broad Institute of Massachusetts Institute of Technology, Boston, Analytic and Translation Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, and Harvard University, Cambridge, MA. Dr. Jacobsson is with Obstetrics and Gynecology, Gothenburg University, and the Norwegian Institute of Public Health. Dr. Sunyer is with CREAL, IMIM (Hospital del Mar Medical Research Institute), Barcelona, UPF, and CIBERESP. Dr. Whitehouse is with Telethon Kids Institute, University of Western Australia, Perth. Dr. Davey Smith is with MRC IEU, and School of Social and Community Medicine. Dr. Tiemeier is with Epidemiology, Child and Adolescent Psychiatry, and Psychiatry, Erasmus Medical Center. Dr. Posthuma is with the Generation R Study Group, Erasmus MC Rotterdam, the Netherlands, Child and Adolescent Psychiatry, Erasmus Medical Center, Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, and Clinical Genetics, VU University Medical Center. Dr. Boomsma is with Biological Psychology, VU University, Neuroscience Campus Amsterdam, VU University, and EMGO+ Institute for Health and Care Research, VU University Medical Center.

Objective: The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis.

Method: Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated.

Results: SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46 × 10(-6) and 2.66 × 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96.

Conclusion: The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5068552PMC
http://dx.doi.org/10.1016/j.jaac.2016.05.025DOI Listing
October 2016

The genetics of alcohol dependence: Twin and SNP-based heritability, and genome-wide association study based on AUDIT scores.

Am J Med Genet B Neuropsychiatr Genet 2015 Dec 14;168(8):739-48. Epub 2015 Sep 14.

Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.

Alcohol dependence (AD) is among the most common and costly public health problems contributing to morbidity and mortality throughout the world. In this study, we investigate the genetic basis of AD in a Dutch population using data from the Netherlands Twin Register (NTR) and the Netherlands Study of Depression and Anxiety (NESDA). The presence of AD was ascertained via the Alcohol Use Disorders Identification Test (AUDIT) applying cut-offs with good specificity and sensitivity in identifying those at risk for AD. Twin-based heritability of AD-AUDIT was estimated using structural equation modeling of data in 7,694 MZ and DZ twin pairs. Variance in AD-AUDIT explained by all SNPs was estimated with genome-wide complex trait analysis (GCTA). A genome-wide association study (GWAS) was performed in 7,842 subjects. GWAS SNP effect concordance analysis was performed between our GWAS and a recent AD GWAS using DSM-IV diagnosis. The twin-based heritability of AD-AUDIT was estimated at 60% (55-69%). GCTA showed that common SNPs jointly capture 33% (SE = 0.12, P = 0.002) of this heritability. In the GWAS, the top hits were positioned within four regions (4q31.1, 2p16.1, 6q25.1, 7p14.1) with the strongest association detected for rs55768019 (P = 7.58 × 10(-7) ). This first GWAS of AD using the AUDIT measure found results consistent with previous genetic studies using DSM diagnosis: concordance in heritability estimates and direction of SNPs effect and overlap with top hits from previous GWAS. Thus, the use of appropriate questionnaires may represent cost-effective strategies to phenotype samples in large-scale biobanks or other population-based datasets.
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http://dx.doi.org/10.1002/ajmg.b.32379DOI Listing
December 2015

Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium.

Behav Genet 2016 Mar 11;46(2):170-82. Epub 2015 Sep 11.

Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion.
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http://dx.doi.org/10.1007/s10519-015-9735-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751159PMC
March 2016

Single Nucleotide Polymorphism Heritability of Behavior Problems in Childhood: Genome-Wide Complex Trait Analysis.

J Am Acad Child Adolesc Psychiatry 2015 Sep 20;54(9):737-44. Epub 2015 Jun 20.

VU University Amsterdam; EMGO(+) Institute for Health and Care Research, VU University Medical Center, Amsterdam; Neuroscience Campus Amsterdam.

Objective: Genetic factors contribute to individual differences in behavior problems. In children, genome-wide association studies (GWAS) have yielded the first suggestive results when aiming to identify genetic variants that explain heritability, but the proportion of genetic variance that can be attributed to common single nucleotide polymorphisms (SNPs) remains to be determined, as only a few studies have estimated SNP heritability, with diverging results.

Method: Genomic-relationship-matrix restricted maximum likelihood (GREML) as implemented in the software Genome-Wide Complex Trait Analysis (GCTA) was used to estimate SNP heritability (SNP h(2)) for multiple phenotypes within 4 broad domains of children's behavioral problems (attention-deficit/hyperactivity symptoms, internalizing, externalizing, and pervasive developmental problems) and cognitive function. We combined phenotype and genotype data from 2 independent, population-based Dutch cohorts, yielding a total number of 1,495 to 3,175 of 3-, 7-, and 9-year-old children.

Results: Significant SNP heritability estimates were found for attention-deficit/hyperactivity symptoms (SNP h(2) = 0.37-0.71), externalizing problems (SNP h(2) = 0.44), and total problems (SNP h(2) = 0.18), rated by mother or teacher. Sensitivity analyses with exclusion of extreme cases and quantile normalization of the phenotype data decreased SNP h(2) as expected under genetic inheritance, but they remained statistically significant for most phenotypes.

Conclusion: We provide evidence of the influence of common SNPs on child behavior problems in an ethnically homogenous sample. These results support the continuation of large GWAS collaborative efforts to unravel the genetic basis of complex child behaviors.
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http://dx.doi.org/10.1016/j.jaac.2015.06.004DOI Listing
September 2015

Heritability and Genome-Wide Association Studies for Hair Color in a Dutch Twin Family Based Sample.

Genes (Basel) 2015 Jul 13;6(3):559-76. Epub 2015 Jul 13.

Department of Biological Psychology, VU University, Amsterdam 1081 BT, The Netherlands.

Hair color is one of the most visible and heritable traits in humans. Here, we estimated heritability by structural equation modeling (N = 20,142), and performed a genome wide association (GWA) analysis (N = 7091) and a GCTA study (N = 3340) on hair color within a large cohort of twins, their parents and siblings from the Netherlands Twin Register (NTR). Self-reported hair color was analyzed as five binary phenotypes, namely "blond versus non-blond", "red versus non-red", "brown versus non-brown", "black versus non-black", and "light versus dark". The broad-sense heritability of hair color was estimated between 73% and 99% and the genetic component included non-additive genetic variance. Assortative mating for hair color was significant, except for red and black hair color. From GCTA analyses, at most 24.6% of the additive genetic variance in hair color was explained by 1000G well-imputed SNPs. Genome-wide association analysis for each hair color showed that SNPs in the MC1R region were significantly associated with red, brown and black hair, and also with light versus dark hair color. Five other known genes (HERC2, TPCN2, SLC24A4, IRF4, and KITLG) gave genome-wide significant hits for blond, brown and light versus dark hair color. We did not find and replicate any new loci for hair color.
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http://dx.doi.org/10.3390/genes6030559DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4584317PMC
July 2015

Estimation of Genetic Relationships Between Individuals Across Cohorts and Platforms: Application to Childhood Height.

Behav Genet 2015 Sep 3;45(5):514-28. Epub 2015 Jun 3.

Department of Biological Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081BT, Amsterdam, The Netherlands,

Combining genotype data across cohorts increases power to estimate the heritability due to common single nucleotide polymorphisms (SNPs), based on analyzing a Genetic Relationship Matrix (GRM). However, the combination of SNP data across multiple cohorts may lead to stratification, when for example, different genotyping platforms are used. In the current study, we address issues of combining SNP data from different cohorts, the Netherlands Twin Register (NTR) and the Generation R (GENR) study. Both cohorts include children of Northern European Dutch background (N = 3102 + 2826, respectively) who were genotyped on different platforms. We explore imputation and phasing as a tool and compare three GRM-building strategies, when data from two cohorts are (1) just combined, (2) pre-combined and cross-platform imputed and (3) cross-platform imputed and post-combined. We test these three strategies with data on childhood height for unrelated individuals (N = 3124, average age 6.7 years) to explore their effect on SNP-heritability estimates and compare results to those obtained from the independent studies. All combination strategies result in SNP-heritability estimates with a standard error smaller than those of the independent studies. We did not observe significant difference in estimates of SNP-heritability based on various cross-platform imputed GRMs. SNP-heritability of childhood height was on average estimated as 0.50 (SE = 0.10). Introducing cohort as a covariate resulted in ≈2 % drop. Principal components (PCs) adjustment resulted in SNP-heritability estimates of about 0.39 (SE = 0.11). Strikingly, we did not find significant difference between cross-platform imputed and combined GRMs. All estimates were significant regardless the use of PCs adjustment. Based on these analyses we conclude that imputation with a reference set helps to increase power to estimate SNP-heritability by combining cohorts of the same ethnicity genotyped on different platforms. However, important factors should be taken into account such as remaining cohort stratification after imputation and/or phenotypic heterogeneity between and within cohorts. Whether one should use imputation, or just combine the genotype data, depends on the number of overlapping SNPs in relation to the total number of genotyped SNPs for both cohorts, and their ability to tag all the genetic variance related to the specific trait of interest.
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http://dx.doi.org/10.1007/s10519-015-9725-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561077PMC
September 2015

Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder.

JAMA Psychiatry 2015 Jul;72(7):642-50

Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.

Importance: Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases).

Objectives: To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD.

Design, Setting, And Participants: Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014.

Main Outcomes And Measures: Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts.

Results: A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts.

Conclusions And Relevance: This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.
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http://dx.doi.org/10.1001/jamapsychiatry.2015.0554DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667957PMC
July 2015

Heritability, SNP- and Gene-Based Analyses of Cannabis Use Initiation and Age at Onset.

Behav Genet 2015 Sep 19;45(5):503-13. Epub 2015 May 19.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands,

Prior searches for genetic variants (GVs) implicated in initiation of cannabis use have been limited to common single nucleotide polymorphisms (SNPs) typed in HapMap samples. Denser SNPs are now available with the completion of the 1000 Genomes and the Genome of the Netherlands projects. More densely distributed SNPs are expected to track the causal variants better. Therefore we extend the search for variants implicated in early stages of cannabis use to previously untagged common and low-frequency variants. We run heritability, SNP and gene-based analyses of initiation and age at onset. This is the first genome-wide study of age at onset to date. Using GCTA and a sample of distantly related individuals from the Netherlands Twin Register, we estimated that the currently measured (and tagged) SNPs collectively explain 25 % of the variance in initiation (SE = 0.088; P = 0.0016). Chromosomes 4 and 18, previously linked with cannabis use and other addiction phenotypes, account for the largest amount of variance in initiation (6.8 %, SE = 0.025, P = 0.002 and 3.6 %, SE = 0.01, P = 0.012, respectively). No individual SNP- or gene-based test reached genomewide significance in the initiation or age at onset analyses. Our study detected association signal in the currently measured SNPs. A comparison with prior SNP-heritability estimates suggests that at least part of the signal is likely coming from previously untyped common and low frequency variants. Our results do not rule out the contribution of rare variants of larger effect-a plausible source of the difference between the twin-based heritability estimate and that from GCTA. The causal variants are likely of very small effect (i.e., <1 % explained variance) and are uniformly distributed over the genome in proportion to chromosomes' length. Similar to other complex traits and diseases, detecting such small effects is to be expected in sufficiently large samples.
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http://dx.doi.org/10.1007/s10519-015-9723-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561059PMC
September 2015

Common genetic variants influence human subcortical brain structures.

Nature 2015 Apr 21;520(7546):224-9. Epub 2015 Jan 21.

1] Department of Human Genetics, Radboud university medical center, Nijmegen 6500 HB, The Netherlands. [2] Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6500 GL, The Netherlands.

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.
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http://dx.doi.org/10.1038/nature14101DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4393366PMC
April 2015
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