Dataset Information

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

ABSTRACT: 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.

SUBMITTER: van den Berg SM

PROVIDER: S-EPMC4751159 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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

van den Berg Stéphanie M SM de Moor Marleen H M MH Verweij Karin J H KJ Krueger Robert F RF Luciano Michelle M Arias Vasquez Alejandro A Matteson Lindsay K LK Derringer Jaime J Esko Tõnu T Amin Najaf N Gordon Scott D SD Hansell Narelle K NK Hart Amy B AB Seppälä Ilkka I Huffman Jennifer E JE Konte Bettina B Lahti Jari J Lee Minyoung M Miller Mike M Nutile Teresa T Tanaka Toshiko T Teumer Alexander A Viktorin Alexander A Wedenoja Juho J Abdellaoui Abdel A Abecasis Goncalo R GR Adkins Daniel E DE Agrawal Arpana A Allik Jüri J Appel Katja K Bigdeli Timothy B TB Busonero Fabio F Campbell Harry H Costa Paul T PT Smith George Davey GD Davies Gail G de Wit Harriet H Ding Jun J Engelhardt Barbara E BE Eriksson Johan G JG Fedko Iryna O IO Ferrucci Luigi L Franke Barbara B Giegling Ina I Grucza Richard R Hartmann Annette M AM Heath Andrew C AC Heinonen Kati K Henders Anjali K AK Homuth Georg G Hottenga Jouke-Jan JJ Iacono William G WG Janzing Joost J Jokela Markus M Karlsson Robert R Kemp John P JP Kirkpatrick Matthew G MG Latvala Antti A Lehtimäki Terho T Liewald David C DC Madden Pamela A F PA Magri Chiara C Magnusson Patrik K E PK Marten Jonathan J Maschio Andrea A Mbarek Hamdi H Medland Sarah E SE Mihailov Evelin E Milaneschi Yuri Y Montgomery Grant W GW Nauck Matthias M Nivard Michel G MG Ouwens Klaasjan G KG Palotie Aarno A Pettersson Erik E Polasek Ozren O Qian Yong Y Pulkki-Råback Laura L Raitakari Olli T OT Realo Anu A Rose Richard J RJ Ruggiero Daniela D Schmidt Carsten O CO Slutske Wendy S WS Sorice Rossella R Starr John M JM St Pourcain Beate B Sutin Angelina R AR Timpson Nicholas J NJ Trochet Holly H Vermeulen Sita S Vuoksimaa Eero E Widen Elisabeth E Wouda Jasper J Wright Margaret J MJ Zgaga Lina L Porteous David D Minelli Alessandra A Palmer Abraham A AA Rujescu Dan D Ciullo Marina M Hayward Caroline C Rudan Igor I Metspalu Andres A Kaprio Jaakko J Deary Ian J IJ Räikkönen Katri K Wilson James F JF Keltikangas-Järvinen Liisa L Bierut Laura J LJ Hettema John M JM Grabe Hans J HJ Penninx Brenda W J H BW van Duijn Cornelia M CM Evans David M DM Schlessinger David D Pedersen Nancy L NL Terracciano Antonio A McGue Matt M Martin Nicholas G NG Boomsma Dorret I DI

Behavior genetics 20150911 2

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 inventorie ...[more]

PMID: 26362575

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Project description:Background and purposePrevious studies examining genetic associations with MRI-defined brain infarct have yielded inconsistent findings. We investigated genetic variation underlying covert MRI infarct in persons without histories of transient ischemic attack or stroke. We performed meta-analysis of genome-wide association studies of white participants in 6 studies comprising the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.MethodsUsing 2.2 million genotyped and imputed single nucleotide polymorphisms, each study performed cross-sectional genome-wide association analysis of MRI infarct using age- and sex-adjusted logistic regression models. Study-specific findings were combined in an inverse-variance-weighted meta-analysis, including 9401 participants with mean age 69.7 (19.4% of whom had >or=1 MRI infarct).ResultsThe most significant association was found with rs2208454 (minor allele frequency, 20%), located in intron 3 of MACRO domain containing 2 gene and in the downstream region of fibronectin leucine-rich transmembrane protein 3 gene. Each copy of the minor allele was associated with lower risk of MRI infarcts (odds ratio, 0.76; 95% confidence interval, 0.68-0.84; P=4.64x10(-7)). Highly suggestive associations (P<1.0x10(-5)) were also found for 22 other single nucleotide polymorphisms in linkage disequilibrium (r(2)>0.64) with rs2208454. The association with rs2208454 did not replicate in independent samples of 1822 white and 644 black participants, although 4 single nucleotide polymorphisms within 200 kb from rs2208454 were associated with MRI infarcts in the black population sample.ConclusionsThis first community-based, genome-wide association study on covert MRI infarcts uncovered novel associations. Although replication of the association with top single nucleotide polymorphisms failed, possibly because of insufficient power, results in the black population sample are encouraging, and further efforts at replication are needed.

Project description:IntroductionGene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. Here we propose an enhanced version of Fisher's inverse ?2-method META-GSA, however weighting each study to account for imperfect correlation between association patterns.Simulation and powerWe investigated the performance of META-GSA by simulating GWASs with 500 cases and 500 controls at 100 diallelic markers in 20 different scenarios, simulating different relative risks between 1 and 1.5 in gene sets of 10 genes. Wilcoxon's rank sum test was applied as GSA for each study. We found that META-GSA has greater power to discover truly associated gene sets than simple pooling of the p-values, by e.g. 59% versus 37%, when the true relative risk for 5 of 10 genes was assume to be 1.5. Under the null hypothesis of no difference in the true association pattern between the gene set of interest and the set of remaining genes, the results of both approaches are almost uncorrelated. We recommend not relying on p-values alone when combining the results of independent GSAs.ApplicationWe applied META-GSA to pool the results of four case-control GWASs of lung cancer risk (Central European Study and Toronto/Lunenfeld-Tanenbaum Research Institute Study; German Lung Cancer Study and MD Anderson Cancer Center Study), which had already been analyzed separately with four different GSA methods (EASE; SLAT, mSUMSTAT and GenGen). This application revealed the pathway GO0015291 "transmembrane transporter activity" as significantly enriched with associated genes (GSA-method: EASE, p = 0.0315 corrected for multiple testing). Similar results were found for GO0015464 "acetylcholine receptor activity" but only when not corrected for multiple testing (all GSA-methods applied; p ? 0.02).

Dataset Information

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

Publications

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

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