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Systematic meta-analyses and field synopsis of genetic association studies of violence and aggression. Mol Psychiatry 2014; 19:471-7. [PMID: 23546171 PMCID: PMC3965568 DOI: 10.1038/mp.2013.31] [Citation(s) in RCA: 100] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2012] [Revised: 01/21/2013] [Accepted: 02/01/2013] [Indexed: 12/15/2022]
Abstract
A large number of candidate gene studies for aggression and violence have been conducted. Successful identification of associations between genetic markers and aggression would contribute to understanding the neurobiology of antisocial behavior and potentially provide useful tools for risk prediction and therapeutic targets for high-risk groups of patients and offenders. We systematically reviewed the literature and assessed the evidence on genetic association studies of aggression and related outcomes in order to provide a field synopsis. We searched PubMed and Huge Navigator databases and sought additional data through reviewing reference lists and correspondence with investigators. Genetic association studies were included if outcome data on aggression or violent behavior either as a binary outcome or as a quantitative trait were provided. From 1331 potentially relevant investigations, 185 studies constituting 277 independent associations on 31 genes fulfilled the predetermined selection criteria. Data from variants investigated in three or more samples were combined in meta-analyses and potential sources of heterogeneity were investigated using subgroup analyses. In the primary analyses, which used relaxed inclusion criteria, we found no association between any polymorphism analyzed and aggression at the 5% level of significance. Subgroup analyses, including by severity of outcome, age group, characteristics of the sample and ethnicity, did not demonstrate any consistent findings. Current evidence does not support the use of such genes to predict dangerousness or as markers for therapeutic interventions.
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152
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Calati R, Signorelli MS, Gressier F, Bianchini O, Porcelli S, Comings DE, Girolamo GD, Aguglia E, MacMurray J, Serretti A. Modulation of a number of genes on personality traits in a sample of healthy subjects. Neurosci Lett 2014; 566:320-5. [DOI: 10.1016/j.neulet.2014.02.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2013] [Revised: 01/24/2014] [Accepted: 02/02/2014] [Indexed: 12/17/2022]
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153
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Bartholdi D, Stray-Pedersen A, Azzarello-Burri S, Kibaek M, Kirchhoff M, Oneda B, Rødningen O, Schmitt-Mechelke T, Rauch A, Kjaergaard S. A newly recognized 13q12.3 microdeletion syndrome characterized by intellectual disability, microcephaly, and eczema/atopic dermatitis encompassing the HMGB1 and KATNAL1 genes. Am J Med Genet A 2014; 164A:1277-83. [PMID: 24664804 DOI: 10.1002/ajmg.a.36439] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2013] [Accepted: 12/29/2013] [Indexed: 12/21/2022]
Abstract
Proximal deletions of the long arm of chromosome 13 have been reported only rarely. Here we present three unrelated patients with heterozygous, apparently de novo deletions encompassing 13q12.3. The patients present with moderate demonstrated or apparent intellectual disability, postnatal microcephaly, and eczema/atopic dermatitis as the predominant symptoms. In addition, they had pronounced feeding difficulties in early infancy. They displayed similar facial features such as malar flattening, a prominent nose with underdeveloped alae nasi, a smooth philtrum, and a thin vermillion of the upper lip. The proximal and distal breakpoints were clustered and the deletions spanned from 1.4 to 1.7 Mb, comprising at least 11 RefSeq genes. However, heterozygous deletions partially overlapping those observed in the present patients have been described in healthy parents of patients with Peters-Plus syndrome, an autosomal recessive disorder caused by inactivation of the B3GALTL gene. We therefore propose that the critical region of the 13q12.3 microdeletion syndrome contains only three genes, namely, KATNAL1, HMGB1, and LINC00426, a non-protein coding RNA. The KATNAL1 protein belongs to a family of microtubule severing enzymes that have been implicated in CNS plasticity in experimental models, but little is known about its function in humans. The HMGB1 protein is an evolutionarily conserved chromatin-associated protein involved in many biologically important processes. In summary, we propose that microdeletion 13q12.3 represents a novel clinically recognizable condition and that the microtubule severing gene KATNAL1 and the chromatin-associated gene HMGB1 are candidate genes for intellectual disability inherited in an autosomal dominant pattern.
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Affiliation(s)
- Deborah Bartholdi
- Institute of Medical Genetics, University of Zürich, Zurich, Switzerland
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154
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Terracciano A, Sutin AR, An Y, O'Brien RJ, Ferrucci L, Zonderman AB, Resnick SM. Personality and risk of Alzheimer's disease: new data and meta-analysis. Alzheimers Dement 2014; 10:179-86. [PMID: 23706517 PMCID: PMC3783589 DOI: 10.1016/j.jalz.2013.03.002] [Citation(s) in RCA: 212] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2012] [Revised: 02/20/2013] [Accepted: 03/03/2013] [Indexed: 10/26/2022]
Abstract
BACKGROUND We examine whether broad factors and specific facets of personality are associated with increased risk of incident Alzheimer's disease (AD) in a long-run longitudinal study and a meta-analysis of published studies. METHODS Participants (n = 1671) were monitored for up to 22 years from a baseline personality assessment. The meta-analysis pooled results from up to five prospective studies (n = 5054). RESULTS Individuals with scores in the top quartile of neuroticism (hazard ratio = 3.1; 95% confidence interval = 1.6-6.0) or the lowest quartile of conscientiousness (hazard ratio = 3.3; 95% confidence interval = 1.4-7.4) had a threefold increased risk of incident AD. Among the components of these traits, self-discipline and depression had the strongest associations with incident AD. The meta-analysis confirmed the associations of neuroticism (P = 2 × 10(-9)) and conscientiousness (P = 2 × 10(-6)), along with weaker effects for openness and agreeableness (P < .05). CONCLUSIONS The current study and meta-analysis indicate that personality traits are associated with increased risk of AD, with effect sizes similar to those of well-established clinical and lifestyle risk factors.
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Affiliation(s)
- Antonio Terracciano
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA; Florida State University College of Medicine, Tallahassee, FL, USA.
| | - Angelina R Sutin
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA; Florida State University College of Medicine, Tallahassee, FL, USA
| | - Yang An
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Richard J O'Brien
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Alan B Zonderman
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Susan M Resnick
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
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155
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The effect of paternal age on offspring intelligence and personality when controlling for paternal trait level. PLoS One 2014; 9:e90097. [PMID: 24587224 PMCID: PMC3934965 DOI: 10.1371/journal.pone.0090097] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Accepted: 01/28/2014] [Indexed: 12/02/2022] Open
Abstract
Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father’s age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents’ trait levels measured with the same precision as offspring’s. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ) had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents’ intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (<1% of variance explained) on intelligence. We discuss future avenues for studies of paternal age effects and suggest that stronger research designs are needed to rule out confounding factors involving birth order and the Flynn effect.
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156
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Leitsalu L, Haller T, Esko T, Tammesoo ML, Alavere H, Snieder H, Perola M, Ng PC, Mägi R, Milani L, Fischer K, Metspalu A. Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol 2014; 44:1137-47. [PMID: 24518929 DOI: 10.1093/ije/dyt268] [Citation(s) in RCA: 284] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/03/2013] [Indexed: 01/05/2023] Open
Abstract
The Estonian Biobank cohort is a volunteer-based sample of the Estonian resident adult population (aged ≥18 years). The current number of participants-close to 52000--represents a large proportion, 5%, of the Estonian adult population, making it ideally suited to population-based studies. General practitioners (GPs) and medical personnel in the special recruitment offices have recruited participants throughout the country. At baseline, the GPs performed a standardized health examination of the participants, who also donated blood samples for DNA, white blood cells and plasma tests and filled out a 16-module questionnaire on health-related topics such as lifestyle, diet and clinical diagnoses described in WHO ICD-10. A significant part of the cohort has whole genome sequencing (100), genome-wide single nucleotide polymorphism (SNP) array data (20 000) and/or NMR metabolome data (11 000) available (http://www.geenivaramu.ee/for-scientists/data-release/). The data are continuously updated through periodical linking to national electronic databases and registries. A part of the cohort has been re-contacted for follow-up purposes and resampling, and targeted invitations are possible for specific purposes, for example people with a specific diagnosis. The Estonian Genome Center of the University of Tartu is actively collaborating with many universities, research institutes and consortia and encourages fellow scientists worldwide to co-initiate new academic or industrial joint projects with us.
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Affiliation(s)
- Liis Leitsalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Divisions of Endocrinology, Boston Children's Hospital, Boston, MA, USA, Department of Genetics, Harvard Medical School, Boston, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, US
| | | | - Helene Alavere
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Harold Snieder
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Epidemiology, University of Groningen, Groningen, The Netherlands
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, University of Helsinki, Institute for Molecular Medicine, Helsinki, Finland
| | - Pauline C Ng
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Genome Institute of Singapore, Singapore and
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia, Estonian Biocentre, Tartu, Estonia
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157
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Bjornsdottir G, Jonsson FH, Hansdottir I, Almarsdottir AB, Heimisdottir M, Tyrfingsson T, Runarsdottir VA, Kristjansson K, Stefansson H, Thorgeirsson TE. Psychometric properties of the Icelandic NEO-FFI in a general population sample compared to a sample recruited for a study on the genetics of addiction. PERSONALITY AND INDIVIDUAL DIFFERENCES 2014; 58. [PMID: 24415821 DOI: 10.1016/j.paid.2013.10.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Personality traits are major determinants of social behavior influencing various diseases including addiction. Twin and family studies suggest personality and addiction to be under genetic influence. Identification of DNA susceptibility variants relies on valid and reliable phenotyping approaches. We present results of psychometric testing of the Icelandic NEO-FFI in a population sample (N=657) and a sample recruited for a study on addiction genetics (N=3,804). The Icelandic NEO-FFI demonstrated internal consistency and temporal stability. Factor analyses supported the five-factor structure. Icelandic norms were compared to American norms and language translations selected for geographical and cultural proximity to Iceland. Multiple discriminant function analysis using NEO-FFI trait scores and gender as independent variables predicted membership in recruitment groups for 47.3% of addiction study cases (N=3,804), with accurate predictions made for 69.5% of individuals with treated addiction and 43.3% of their first-degree relatives. Correlations between NEO-FFI scores and the discriminant function suggested a combination of high neuroticism, low conscientiousness and low agreeableness predicted membership in the Treated group.
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Affiliation(s)
- Gyda Bjornsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland ; Public Health Sciences, University of Iceland
| | - Fridrik H Jonsson
- School of Health Sciences, Faculty of Psychology, University of Iceland
| | - Ingunn Hansdottir
- School of Health Sciences, Faculty of Psychology, University of Iceland ; SAA-National Center of Addiction Medicine, Reykjavik, Iceland
| | - Anna B Almarsdottir
- Faculty of Pharmaceutical Sciences, School of Health Sciences, University of Iceland
| | - Maria Heimisdottir
- Faculty of Medicine, School of Health Sciences, University of Iceland ; Landspitali University Hospital, Reykjavik, Iceland
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158
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Affiliation(s)
- Stephen B. Manuck
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260;
| | - Jeanne M. McCaffery
- Department of Psychiatry and Human Behavior, The Miriam Hospital, and Warren Alpert School of Medicine at Brown University, Providence, Rhode Island 02903;
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159
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Abstract
OBJECTIVE Previous longitudinal studies suggest that depression and anxiety are associated with risk for cardiovascular disease. The aim of the present study was to test whether an association between depression and anxiety symptoms and retinal vessel caliber, an indicator of subclinical cardiovascular risk, is apparent as early as adolescence and young adulthood. METHODS Participants were 865 adolescents and young adults who participated in the Brisbane Longitudinal Twin Study and the Twin Eye Study in Tasmania. Participants completed an assessment of depression/anxiety symptoms (the Somatic and Psychological Health Report) when they were 16.5 years old (mean age), and they underwent retinal imaging, on average, 2.5 years later (range, 2 years before to 7 years after the depression/anxiety assessment). Retinal vessel caliber was assessed using computer software. RESULTS Depression and anxiety symptoms were associated with wider retinal arteriolar caliber in this sample of adolescents and young adults (β = 0.09, p = .016), even after adjusting for other cardiovascular risk factors (β = 0.08, p = .025). Multiple regression analyses revealed that affective symptoms of depression/anxiety were associated with retinal vessel caliber independently of somatic symptoms. CONCLUSIONS Depression and anxiety symptoms are associated with measurable signs in the retinal microvasculature in early life, suggesting that pathological microvascular mechanisms linking depression/anxiety and cardiovascular disease may be operative from a young age.
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160
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Sherman RA, Wood D. Estimating the Expected Replicability of a Pattern of Correlations and Other Measures of Association. MULTIVARIATE BEHAVIORAL RESEARCH 2014; 49:17-40. [PMID: 26745671 DOI: 10.1080/00273171.2013.822785] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Replication is at the heart of all empirical sciences. However, there are no standard procedures for establishing the replicability of a pattern of correlations found linking a particular variable to an inventory or battery of other measures. This article introduces 2 statistics for quantifying the expected replicability of a pattern of associations (i.e., correlations, slope coefficients) between a variable of interest and a SET of other variables, items, measures, and so on. Using simulations and real data, we illustrate that these statistics are highly accurate estimates of the expected replicability of an observed pattern of correlations. These statistics can readily be used to indicate the replicability of patterns of association indexed by other statistics (e.g., regression slopes or covariances) and can be applied to other contexts, such as estimating the reliability of profile correlations. It is recommended that these statistics are regularly reported in such studies.
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Affiliation(s)
- Ryne A Sherman
- a Department of Psychology , Florida Atlantic University
| | - Dustin Wood
- b Department of Psychology , Wake Forest University
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161
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Roberts AL, Glymour MM, Koenen KC. Considering alternative explanations for the associations among childhood adversity, childhood abuse, and adult sexual orientation: reply to Bailey and Bailey (2013) and Rind (2013). ARCHIVES OF SEXUAL BEHAVIOR 2014; 43:191-196. [PMID: 24366661 PMCID: PMC3951775 DOI: 10.1007/s10508-013-0239-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Affiliation(s)
- Andrea L Roberts
- Department of Social and Behavioral Sciences, School of Public Health, Harvard University, Kresge Building, 677 Huntington Ave., Boston, MA, 02115, USA,
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162
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Terracciano A, Piras MG, Lobina M, Mulas A, Meirelles O, Sutin AR, Chan W, Sanna S, Uda M, Crisponi L, Schlessinger D. Genetics of serum BDNF: meta-analysis of the Val66Met and genome-wide association study. World J Biol Psychiatry 2013; 14:583-9. [PMID: 22047184 PMCID: PMC3288597 DOI: 10.3109/15622975.2011.616533] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVES Lower levels of serum brain derived neurotrophic factor (BDNF) is one of the best known biomarkers of depression. To identify genetic variants associated with serum BDNF, we tested the Val66Met (rs6265) functional variant and conducted a genome-wide association scan (GWAS). METHODS In a community-based sample (N = 2054; aged 19-101, M = 51, SD = 15) from Sardinia, Italy, we measured serum BDNF concentration and conducted a GWAS. RESULTS We estimated the heritability of serum BDNF to be 0.48 from sib-pairs. There was no association between serum BDNF and Val66Met in the SardiNIA sample and in a meta-analysis of published studies (k = 13 studies, total n = 4727, P = 0.92). Although no genome-wide significant associations were identified, some evidence of association was found in the BDNF gene (rs11030102, P = 0.001) and at two loci (rs7170215, P = 4.8 × 10⁻⁵ and rs11073742 P = 1.2 × 10⁻⁵) near and within NTRK3 gene, a neurotrophic tyrosine kinase receptor. CONCLUSIONS Our study and meta-analysis of the literature indicate that the BDNF Val66Met variant is not associated with serum BDNF, but other variants in the BDNF and NTRK3 genes might regulate the level of serum BDNF.
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Affiliation(s)
| | - Maria Grazia Piras
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy
| | - Monia Lobina
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy
| | | | | | - Wayne Chan
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy
| | - Manuela Uda
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy
| | - Laura Crisponi
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy
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163
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DeYoung CG. The neuromodulator of exploration: A unifying theory of the role of dopamine in personality. Front Hum Neurosci 2013; 7:762. [PMID: 24294198 PMCID: PMC3827581 DOI: 10.3389/fnhum.2013.00762] [Citation(s) in RCA: 153] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2013] [Accepted: 10/23/2013] [Indexed: 12/22/2022] Open
Abstract
The neuromodulator dopamine is centrally involved in reward, approach behavior, exploration, and various aspects of cognition. Variations in dopaminergic function appear to be associated with variations in personality, but exactly which traits are influenced by dopamine remains an open question. This paper proposes a theory of the role of dopamine in personality that organizes and explains the diversity of findings, utilizing the division of the dopaminergic system into value coding and salience coding neurons (Bromberg-Martin et al., 2010). The value coding system is proposed to be related primarily to Extraversion and the salience coding system to Openness/Intellect. Global levels of dopamine influence the higher order personality factor, Plasticity, which comprises the shared variance of Extraversion and Openness/Intellect. All other traits related to dopamine are linked to Plasticity or its subtraits. The general function of dopamine is to promote exploration, by facilitating engagement with cues of specific reward (value) and cues of the reward value of information (salience). This theory constitutes an extension of the entropy model of uncertainty (EMU; Hirsh et al., 2012), enabling EMU to account for the fact that uncertainty is an innate incentive reward as well as an innate threat. The theory accounts for the association of dopamine with traits ranging from sensation and novelty seeking, to impulsivity and aggression, to achievement striving, creativity, and cognitive abilities, to the overinclusive thinking characteristic of schizotypy.
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Affiliation(s)
- Colin G. DeYoung
- Department of Psychology, University of MinnesotaMinneapolis, MN, USA
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164
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Franić S, Borsboom D, Dolan CV, Boomsma DI. The big five personality traits: psychological entities or statistical constructs? Behav Genet 2013; 44:591-604. [PMID: 24162101 DOI: 10.1007/s10519-013-9625-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2013] [Accepted: 10/14/2013] [Indexed: 11/25/2022]
Abstract
The present study employed multivariate genetic item-level analyses to examine the ontology and the genetic and environmental etiology of the Big Five personality dimensions, as measured by the NEO Five Factor Inventory (NEO-FFI) [Costa and McCrae, Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO-FFI) professional manual, 1992; Hoekstra et al., NEO personality questionnaires NEO-PI-R, NEO-FFI: manual, 1996]. Common and independent pathway model comparison was used to test whether the five personality dimensions fully mediate the genetic and environmental effects on the items, as would be expected under the realist interpretation of the Big Five. In addition, the dimensionalities of the latent genetic and environmental structures were examined. Item scores of a population-based sample of 7,900 adult twins (including 2,805 complete twin pairs; 1,528 MZ and 1,277 DZ) on the Dutch version of the NEO-FFI were analyzed. Although both the genetic and the environmental covariance components display a 5-factor structure, applications of common and independent pathway modeling showed that they do not comply with the collinearity constraints entailed in the common pathway model. Implications for the substantive interpretation of the Big Five are discussed.
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Affiliation(s)
- Sanja Franić
- Department of Biological Psychology, Faculty of Psychology and Education, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands,
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166
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A twin-sibling study on the relationship between exercise attitudes and exercise behavior. Behav Genet 2013; 44:45-55. [PMID: 24072598 DOI: 10.1007/s10519-013-9617-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 09/14/2013] [Indexed: 12/18/2022]
Abstract
Social cognitive models of health behavior propose that individual differences in leisure time exercise behavior are influenced by the attitudes towards exercise. At the same time, large scale twin-family studies show a significant influence of genetic factors on regular exercise behavior. This twin-sibling study aimed to unite these findings by demonstrating that exercise attitudes can be heritable themselves. Secondly, the genetic and environmental cross-trait correlations and the monozygotic (MZ) twin intrapair differences model were used to test whether the association between exercise attitudes and exercise behavior can be causal. Survey data were obtained from 5,095 twins and siblings (18-50 years). A genetic contribution was found for exercise behavior (50 % in males, 43 % in females) and for the six exercise attitude components derived from principal component analysis: perceived benefits (21, 27 %), lack of skills, support and/or resources (45, 48 %), time constraints (25, 30 %), lack of energy (34, 44 %), lack of enjoyment (47, 44 %), and embarrassment (42, 49 %). These components were predictive of leisure time exercise behavior (R(2) = 28 %). Bivariate modeling further showed that all the genetic (0.36 < |rA| < 0.80) and all but two unique environmental (0.00 < |rE| < 0.27) correlations between exercise attitudes and exercise behavior were significantly different from zero, which is a necessary condition for the existence of a causal effect driving the association. The correlations between the MZ twins' difference scores were in line with this finding. It is concluded that exercise attitudes and exercise behavior are heritable, that attitudes and behavior are partly correlated through pleiotropic genetic effects, but that the data are compatible with a causal association between exercise attitudes and behavior.
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167
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Turkheimer E, Pettersson E, Horn EE. A phenotypic null hypothesis for the genetics of personality. Annu Rev Psychol 2013; 65:515-40. [PMID: 24050184 DOI: 10.1146/annurev-psych-113011-143752] [Citation(s) in RCA: 147] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We review the genetically informed literature on the genetics of personality. Over the past century, quantitative genetic studies, using identical and fraternal twins, have demonstrated that differences in human personality are substantially heritable. We focus on more contemporary questions to which that basic observation has led. We examine whether differences in the heritability of personality are replicable across different traits, samples, and studies; how the heritability of personality relates to its reliability; and how behavior genetics can be employed in studies of validity, and we discuss the stability of personality in genetic and environmental variance. The appropriate null hypothesis in behavior genetics is not that genetic or environmental influence on personality is zero. Instead, we offer a phenotypic null hypothesis, which states that genetic variance is not an independent mechanism of individual differences in personality but rather a reflection of processes that are best conceptualized at the phenotypic level.
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Affiliation(s)
- Eric Turkheimer
- Department of Psychology, University of Virginia, Charlottesville, Virginia 22904;
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168
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Vinkhuyzen AAE, Wray NR, Yang J, Goddard ME, Visscher PM. Estimation and partition of heritability in human populations using whole-genome analysis methods. Annu Rev Genet 2013; 47:75-95. [PMID: 23988118 PMCID: PMC4037293 DOI: 10.1146/annurev-genet-111212-133258] [Citation(s) in RCA: 123] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Understanding genetic variation of complex traits in human populations has moved from the quantification of the resemblance between close relatives to the dissection of genetic variation into the contributions of individual genomic loci. However, major questions remain unanswered: How much phenotypic variation is genetic; how much of the genetic variation is additive and can be explained by fitting all genetic variants simultaneously in one model, and what is the joint distribution of effect size and allele frequency at causal variants? We review and compare three whole-genome analysis methods that use mixed linear models (MLMs) to estimate genetic variation. In all methods, genetic variation is estimated from the relationship between close or distant relatives on the basis of pedigree information and/or single nucleotide polymorphisms (SNPs). We discuss theory, estimation procedures, bias, and precision of each method and review recent advances in the dissection of genetic variation of complex traits in human populations. By using genome-wide data, it is now established that SNPs in total account for far more of the genetic variation than the statistically highly significant SNPs that have been detected in genome-wide association studies. All SNPs together, however, do not account for all of the genetic variance estimated by pedigree-based methods. We explain possible reasons for this remaining "missing heritability."
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Affiliation(s)
- Anna AE Vinkhuyzen
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Naomi R Wray
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Jian Yang
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
- The University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane, Queensland, Australia
| | - Michael E Goddard
- University of Melbourne, Department of Food and Agricultural Systems, Parkville, Victoria, Australia
- Biosciences Research Division, Department of Primary Industries,Bundoora, Victoria, Australia
| | - Peter M Visscher
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
- The University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane, Queensland, Australia
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169
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Chabris CF, Lee JJ, Benjamin DJ, Beauchamp JP, Glaeser EL, Borst G, Pinker S, Laibson DI. Why it is hard to find genes associated with social science traits: theoretical and empirical considerations. Am J Public Health 2013; 103 Suppl 1:S152-66. [PMID: 23927501 DOI: 10.2105/ajph.2013.301327] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
OBJECTIVES We explain why traits of interest to behavioral scientists may have a genetic architecture featuring hundreds or thousands of loci with tiny individual effects rather than a few with large effects and why such an architecture makes it difficult to find robust associations between traits and genes. METHODS We conducted a genome-wide association study at 2 sites, Harvard University and Union College, measuring more than 100 physical and behavioral traits with a sample size typical of candidate gene studies. We evaluated predictions that alleles with large effect sizes would be rare and most traits of interest to social science are likely characterized by a lack of strong directional selection. We also carried out a theoretical analysis of the genetic architecture of traits based on R.A. Fisher's geometric model of natural selection and empirical analyses of the effects of selection bias and phenotype measurement stability on the results of genetic association studies. RESULTS Although we replicated several known genetic associations with physical traits, we found only 2 associations with behavioral traits that met the nominal genome-wide significance threshold, indicating that physical and behavioral traits are mainly affected by numerous genes with small effects. CONCLUSIONS The challenge for social science genomics is the likelihood that genes are connected to behavioral variation by lengthy, nonlinear, interactive causal chains, and unraveling these chains requires allying with personal genomics to take advantage of the potential for large sample sizes as well as continuing with traditional epidemiological studies.
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Affiliation(s)
- Christopher F Chabris
- Christopher F. Chabris is with the Department of Psychology, Union College, Schenectady, NY. James J. Lee, Gregoire Borst, and Steven Pinker are with the Department of Psychology, Harvard University, Cambridge, MA. Daniel J. Benjamin is with the Department of Economics, Cornell University, Ithaca, NY. Jonathan P. Beauchamp, Edward L. Glaeser, and David I. Laibson are with the Department of Economics, Harvard University
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170
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Kim HN, Roh SJ, Sung YA, Chung HW, Lee JY, Cho J, Shin H, Kim HL. Genome-wide association study of the five-factor model of personality in young Korean women. J Hum Genet 2013; 58:667-74. [PMID: 23903073 DOI: 10.1038/jhg.2013.75] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2013] [Revised: 05/30/2013] [Accepted: 06/07/2013] [Indexed: 12/30/2022]
Abstract
Personality is a determinant of behavior and lifestyle associated with health and human diseases. Although personality is known to be a heritable trait, its polygenic nature has made the identification of genetic variants elusive. We performed a genome-wide association study on 1089 Korean women aged 18-40 years whose personality traits were measured with the Revised NEO Personality Inventory for the five-factor model of personality. To reduce environmental factors that may influence personality traits, this study was restricted to young adult women. In the discovery phase, we identified variants of PTPRD (protein tyrosine phosphatase, receptor type D) that associated this gene with the Openness domain. Other genes that were previously reported to be associated with neurological phenotypes were also associated with personality traits. In particular, DRD1 and OR1A2 were linked to Neuroticism, NKAIN2 with Extraversion, HTR5A with Openness and DRD3 with Agreeableness. Data from our replication study of 2090 subjects confirmed the association between OR1A2 and Neuroticism. We first identified and confirmed a novel region on OR1A2 associated with Neuroticism [corrected]. Candidate genes for psychiatric disorders were also enriched. These findings contribute to our understanding of the genetic architecture of personality traits and provide critical clues to the neurobiological mechanisms that influence them.
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Affiliation(s)
- Han-Na Kim
- Department of Biochemistry, School of Medicine, Ewha Womans University, Seoul, Korea
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171
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Rietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, Westra HJ, Shakhbazov K, Abdellaoui A, Agrawal A, Albrecht E, Alizadeh BZ, Amin N, Barnard J, Baumeister SE, Benke KS, Bielak LF, Boatman JA, Boyle PA, Davies G, de Leeuw C, Eklund N, Evans DS, Ferhmann R, Fischer K, Gieger C, Gjessing HK, Hägg S, Harris JR, Hayward C, Holzapfel C, Ibrahim-Verbaas CA, Ingelsson E, Jacobsson B, Joshi PK, Jugessur A, Kaakinen M, Kanoni S, Karjalainen J, Kolcic I, Kristiansson K, Kutalik Z, Lahti J, Lee SH, Lin P, Lind PA, Liu Y, Lohman K, Loitfelder M, McMahon G, Vidal PM, Meirelles O, Milani L, Myhre R, Nuotio ML, Oldmeadow CJ, Petrovic KE, Peyrot WJ, Polašek O, Quaye L, Reinmaa E, Rice JP, Rizzi TS, Schmidt H, Schmidt R, Smith AV, Smith JA, Tanaka T, Terracciano A, van der Loos MJ, Vitart V, Völzke H, Wellmann J, Yu L, Zhao W, Allik J, Attia JR, Bandinelli S, Bastardot F, Beauchamp J, Bennett DA, Berger K, Bierut LJ, Boomsma DI, Bültmann U, Campbell H, Chabris CF, Cherkas L, Chung MK, Cucca F, de Andrade M, De Jager PL, De Neve JE, Deary IJ, Dedoussis GV, Deloukas P, Dimitriou M, Eiriksdottir G, Elderson MF, Eriksson JG, et alRietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, Westra HJ, Shakhbazov K, Abdellaoui A, Agrawal A, Albrecht E, Alizadeh BZ, Amin N, Barnard J, Baumeister SE, Benke KS, Bielak LF, Boatman JA, Boyle PA, Davies G, de Leeuw C, Eklund N, Evans DS, Ferhmann R, Fischer K, Gieger C, Gjessing HK, Hägg S, Harris JR, Hayward C, Holzapfel C, Ibrahim-Verbaas CA, Ingelsson E, Jacobsson B, Joshi PK, Jugessur A, Kaakinen M, Kanoni S, Karjalainen J, Kolcic I, Kristiansson K, Kutalik Z, Lahti J, Lee SH, Lin P, Lind PA, Liu Y, Lohman K, Loitfelder M, McMahon G, Vidal PM, Meirelles O, Milani L, Myhre R, Nuotio ML, Oldmeadow CJ, Petrovic KE, Peyrot WJ, Polašek O, Quaye L, Reinmaa E, Rice JP, Rizzi TS, Schmidt H, Schmidt R, Smith AV, Smith JA, Tanaka T, Terracciano A, van der Loos MJ, Vitart V, Völzke H, Wellmann J, Yu L, Zhao W, Allik J, Attia JR, Bandinelli S, Bastardot F, Beauchamp J, Bennett DA, Berger K, Bierut LJ, Boomsma DI, Bültmann U, Campbell H, Chabris CF, Cherkas L, Chung MK, Cucca F, de Andrade M, De Jager PL, De Neve JE, Deary IJ, Dedoussis GV, Deloukas P, Dimitriou M, Eiriksdottir G, Elderson MF, Eriksson JG, Evans DM, Faul JD, Ferrucci L, Garcia ME, Grönberg H, Gudnason V, Hall P, Harris JM, Harris TB, Hastie ND, Heath AC, Hernandez DG, Hoffmann W, Hofman A, Holle R, Holliday EG, Hottenga JJ, Iacono WG, Illig T, Järvelin MR, Kähönen M, Kaprio J, Kirkpatrick RM, Kowgier M, Latvala A, Launer LJ, Lawlor DA, Lehtimäki T, Li J, Lichtenstein P, Lichtner P, Liewald DC, Madden PA, Magnusson PKE, Mäkinen TE, Masala M, McGue M, Metspalu A, Mielck A, Miller MB, Montgomery GW, Mukherjee S, Nyholt DR, Oostra BA, Palmer LJ, Palotie A, Penninx B, Perola M, Peyser PA, Preisig M, Räikkönen K, Raitakari OT, Realo A, Ring SM, Ripatti S, Rivadeneira F, Rudan I, Rustichini A, Salomaa V, Sarin AP, Schlessinger D, Scott RJ, Snieder H, Pourcain BS, Starr JM, Sul JH, Surakka I, Svento R, Teumer A, The LifeLines Cohort Study, Tiemeier H, Rooij FJA, Van Wagoner DR, Vartiainen E, Viikari J, Vollenweider P, Vonk JM, Waeber G, Weir DR, Wichmann HE, Widen E, Willemsen G, Wilson JF, Wright AF, Conley D, Davey-Smith G, Franke L, Groenen PJF, Hofman A, Johannesson M, Kardia SL, Krueger RF, Laibson D, Martin NG, Meyer MN, Posthuma D, Thurik AR, Timpson NJ, Uitterlinden AG, van Duijn CM, Visscher PM, Benjamin DJ, Cesarini D, Koellinger PD. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 2013; 340:1467-71. [PMID: 23722424 PMCID: PMC3751588 DOI: 10.1126/science.1235488] [Show More Authors] [Citation(s) in RCA: 505] [Impact Index Per Article: 42.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
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Affiliation(s)
- Cornelius A. Rietveld
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Sarah E. Medland
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Jaime Derringer
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80309–0447, USA
| | - Jian Yang
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Nicolas W. Martin
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland 4072, Australia
| | - Harm-Jan Westra
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Konstantin Shakhbazov
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Abdel Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Behrooz Z. Alizadeh
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - John Barnard
- Heart and Vascular and Lerner Research Institutes, Cleveland Clinic, Cleveland, OH 44195, USA
| | | | - Kelly S. Benke
- Samuel Lunenfeld Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario M5G 1X5, Canada
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Jeffrey A. Boatman
- Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Patricia A. Boyle
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL 60612, USA
| | - Gail Davies
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - Christiaan de Leeuw
- Department of Functional Genomics, VU University Amsterdam and VU Medical Center, 1081 HV Amsterdam, The Netherlands
| | - Niina Eklund
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA 94107–1728, USA
| | - Rudolf Ferhmann
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Håkon K. Gjessing
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Sara Hägg
- Molecular Epidemiology, Department of Medical Sciences, Uppsala University, 751 85 Uppsala, Sweden
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 751 23 Uppsala, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Jennifer R. Harris
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Caroline Hayward
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Christina Holzapfel
- Else Kroener-Fresenius-Centre for Nutritional Medicine, Technische Universität München, 81675 Munich, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Carla A. Ibrahim-Verbaas
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Erik Ingelsson
- Molecular Epidemiology, Department of Medical Sciences, Uppsala University, 751 85 Uppsala, Sweden
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 751 23 Uppsala, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Bo Jacobsson
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
- Department of Obstetrics and Gynecology, Institute of Public Health, Sahlgrenska Academy, Sahgrenska University Hospital, Gothenburg, 413 45, Sweden
| | - Peter K. Joshi
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Astanand Jugessur
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Marika Kaakinen
- Institute of Health Sciences, University of Oulu, Oulu 90014, Finland
- Biocenter Oulu, University of Oulu, Oulu 90014, Finland
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
| | - Juha Karjalainen
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Ivana Kolcic
- Faculty of Medicine, University of Split, 21000 Split, Croatia
| | - Kati Kristiansson
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Zoltán Kutalik
- Department of Medical Genetics, University of Lausanne, 1005 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Jari Lahti
- Institute of Behavioral Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Sang H. Lee
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Peng Lin
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Penelope A. Lind
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Division of Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157–1063, USA
| | - Kurt Lohman
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157–1063, USA
| | - Marisa Loitfelder
- Division for Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz 8036, Austria
| | - George McMahon
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Pedro Marques Vidal
- Institute of Social and Preventive Medicine, Lausanne University Hospital, 1005 Lausanne, Switzerland
| | - Osorio Meirelles
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Ronny Myhre
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Marja-Liisa Nuotio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Christopher J. Oldmeadow
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | - Katja E. Petrovic
- Division of General Neurology, Department of Neurology, General Hospital and Medical University of Graz, Graz 8036, Austria
| | - Wouter J. Peyrot
- Department of Psychiatry, VU University Medical Center, 1081 HL Amsterdam, The Netherlands
| | - Ozren Polašek
- Faculty of Medicine, University of Split, 21000 Split, Croatia
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Eva Reinmaa
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - John P. Rice
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Thais S. Rizzi
- Department of Functional Genomics, VU University Amsterdam and VU Medical Center, 1081 HV Amsterdam, The Netherlands
| | - Helena Schmidt
- Institute of Molecular Biology and Biochemistry, Medical University of Graz, Graz 8036, Austria
| | - Reinhold Schmidt
- Division for Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz 8036, Austria
| | - Albert V. Smith
- Icelandic Heart Association, Kopavogur 201, Iceland
- Department of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Toshiko Tanaka
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Antonio Terracciano
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
- College of Medicine, Florida State University, Tallahassee, FL 32306–4300, USA
| | - Matthijs J.H.M. van der Loos
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Veronique Vitart
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany
| | - Jürgen Wellmann
- Institute of Epidemiology and Social Medicine, University of Muenster, 48129 Muenster, Germany
| | - Lei Yu
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL 60612, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Jüri Allik
- Department of Psychology, University of Tartu, Tartu 50410, Estonia
| | - John R. Attia
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | | | - François Bastardot
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | | | - David A. Bennett
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL 60612, USA
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Muenster, 48129 Muenster, Germany
| | - Laura J. Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - Ute Bültmann
- Department of Health Sciences, Community & Occupational Medicine, University Medical Center Groningen, 9700 AD Groningen, The Netherlands
| | - Harry Campbell
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | | | - Lynn Cherkas
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Mina K. Chung
- Heart and Vascular and Lerner Research Institutes, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, 09042, Cagliari, Italy
- Dipartimento di Scienze Biomediche, Università di Sassari, 07100 SS, Italy
| | - Mariza de Andrade
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
| | - Philip L. De Jager
- Program in Translational Neuropsychiatric Genomics, Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Jan-Emmanuel De Neve
- School of Public Policy, University College London, London WC1H 9QU, UK
- Centre for Economic Performance, London School of Economics, London WC2A 2AE, UK
| | - Ian J. Deary
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
- Department of Psychology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - George V. Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
| | - Maria Dimitriou
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece
| | | | - Martin F. Elderson
- LifeLines Cohort Study, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki 00014, Finland
- Unit of General Practice, Helsinki University Central Hospital, Helsinki 00280, Finland
- Folkhälsan Research Center, Helsinki 00250, Finland
- Vaasa Central Hospital, Vaasa 65130, Finland
| | - David M. Evans
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48106, USA
| | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Melissa E. Garcia
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur 201, Iceland
- Department of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Juliette M. Harris
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Tamara B. Harris
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Nicholas D. Hastie
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Andrew C. Heath
- Division of Biology and Biomedical Sciences, Washington University, St. Louis, MO 63110–1093, USA
| | - Dena G. Hernandez
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Wolfgang Hoffmann
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany
| | - Adriaan Hofman
- Faculty of Behavioral and Social Sciences, University of Groningen, 9747 AD Groningen, The Netherlands
| | - Rolf Holle
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Elizabeth G. Holliday
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, 30625 Hannover, Germany
| | - Marjo-Riitta Järvelin
- Institute of Health Sciences, University of Oulu, Oulu 90014, Finland
- Biocenter Oulu, University of Oulu, Oulu 90014, Finland
- Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, Imperial College London, London W2 1PG, UK
- Unit of Primary Care, Oulu University Hospital, Oulu 90220, Finland
- Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu 90101, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Tampere 33520, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
- Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, 00300 Helsinki, Finland
| | | | - Matthew Kowgier
- Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
| | - Antti Latvala
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
- Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, 00300 Helsinki, Finland
| | - Lenore J. Launer
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Debbie A. Lawlor
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere University Hospital, Tampere 33520, Finland
| | - Jingmei Li
- Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Peter Lichtner
- Institute of Human Genetics, Helmholtz Centre Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - David C. Liewald
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - Pamela A. Madden
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Tomi E. Mäkinen
- Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Marco Masala
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, 09042, Cagliari, Italy
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Andreas Mielck
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Michael B. Miller
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - Grant W. Montgomery
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Sutapa Mukherjee
- Western Australia Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia
- Department of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Women’s College Research Institute, University of Toronto, Toronto, Ontario M5G 1N8, Canada
| | - Dale R. Nyholt
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Ben A. Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Lyle J. Palmer
- Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
- Department of Medical Genetics, University of Helsinki, 00014 Helsinki, Finland
| | - Brenda Penninx
- Department of Psychiatry, VU University Medical Center, 1081 HL Amsterdam, The Netherlands
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Martin Preisig
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | - Katri Räikkönen
- Institute of Behavioral Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Anu Realo
- Department of Psychology, University of Tartu, Tartu 50410, Estonia
| | - Susan M. Ring
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Igor Rudan
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Aldo Rustichini
- Department of Economics, University of Minnesota, Minneapolis, MN 55455–0462, USA
| | - Veikko Salomaa
- Chronic Disease Epidemiology Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - David Schlessinger
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Rodney J. Scott
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Beate St Pourcain
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol BS1 2LY, UK
| | - John M. Starr
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - Jae Hoon Sul
- Department of Computer Science, University of California, Los Angeles, CA 90095, USA
| | - Ida Surakka
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Rauli Svento
- Department of Economics, Oulu Business School, University of Oulu, Oulu 90014, Finland
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald 17487, Germany
| | | | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, 3000 CB Rotterdam, The Netherlands
| | - Frank JAan Rooij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - David R. Van Wagoner
- Heart and Vascular and Lerner Research Institutes, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Erkki Vartiainen
- Division of Welfare and Health Promotion, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Jorma Viikari
- Department of Medicine, Turku University Hospital, Turku 20520, Finland
| | - Peter Vollenweider
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | - Judith M. Vonk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Gérard Waeber
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48106, USA
| | - H.-Erich Wichmann
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, 81377 Munich, Germany
- Klinikum Grosshadern, 81377 Munich, Germany
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Centre for Environmental Health, 85764 Neuherberg, Germany
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - James F. Wilson
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Alan F. Wright
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Dalton Conley
- Department of Sociology, New York University, New York, NY 10012, USA
| | - George Davey-Smith
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Patrick J. F. Groenen
- Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam 3000 DR, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm 113 83, Sweden
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Robert F. Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - David Laibson
- Department of Economics, Harvard University, Cambridge, MA 02138, USA
| | - Nicholas G. Martin
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Michelle N. Meyer
- Petrie-Flom Center for Health Law Policy, Biotechnology, & Bioethics, Harvard Law School, Cambridge, MA 02138, USA
- Nelson A. Rockefeller Institute of Government, State University of New York, Albany, NY 12203–1003, USA
| | - Danielle Posthuma
- Department of Functional Genomics, VU University Amsterdam and VU Medical Center, 1081 HV Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, 3000 CB Rotterdam, The Netherlands
- Department of Clinical Genetics, VU University Medical Centrer, 1081 BT Amsterdam, The Netherlands
| | - A. Roy Thurik
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Panteia, Zoetermeer 2701 AA, Netherlands
- GSCM-Montpellier Business School, Montpellier 34185, France
| | - Nicholas J. Timpson
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Centre for Medical Systems Biology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
| | - Peter M. Visscher
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | | | - David Cesarini
- Center for Experimental Social Science, Department of Economics, New York University, New York, NY 10012, USA
- Division of Social Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE
- Research Institute of Industrial Economics, Stockholm 102 15, Sweden
| | - Philipp D. Koellinger
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
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172
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Bae HT, Sebastiani P, Sun JX, Andersen SL, Daw EW, Terracciano A, Ferrucci L, Perls TT. Genome-wide association study of personality traits in the long life family study. Front Genet 2013; 4:65. [PMID: 23658558 PMCID: PMC3647245 DOI: 10.3389/fgene.2013.00065] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2012] [Accepted: 04/09/2013] [Indexed: 11/23/2022] Open
Abstract
Personality traits have been shown to be associated with longevity and healthy aging. In order to discover novel genetic modifiers associated with personality traits as related with longevity, we performed a genome-wide association study (GWAS) on personality factors assessed by NEO-five-factor inventory in individuals enrolled in the Long Life Family Study (LLFS), a study of 583 families (N up to 4595) with clustering for longevity in the United States and Denmark. Three SNPs, in almost perfect LD, associated with agreeableness reached genome-wide significance (p < 10−8) and replicated in an additional sample of 1279 LLFS subjects, although one (rs9650241) failed to replicate and the other two were not available in two independent replication cohorts, the Baltimore Longitudinal Study of Aging and the New England Centenarian Study. Based on 10,000,000 permutations, the empirical p-value of 2 × 10−7 was observed for the genome-wide significant SNPs. Seventeen SNPs that reached marginal statistical significance in the two previous GWASs (p-value <10−4 and 10−5), were also marginally significantly associated in this study (p-value <0.05), although none of the associations passed the Bonferroni correction. In addition, we tested age-by-SNP interactions and found some significant associations. Since scores of personality traits in LLFS subjects change in the oldest ages, and genetic factors outweigh environmental factors to achieve extreme ages, these age-by-SNP interactions could be a proxy for complex gene–gene interactions affecting personality traits and longevity.
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Affiliation(s)
- Harold T Bae
- Department of Biostatistics, Boston University School of Public Health Boston, MA, USA
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173
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van der Loos MJHM, Rietveld CA, Eklund N, Koellinger PD, Rivadeneira F, Abecasis GR, Ankra-Badu GA, Baumeister SE, Benjamin DJ, Biffar R, Blankenberg S, Boomsma DI, Cesarini D, Cucca F, de Geus EJC, Dedoussis G, Deloukas P, Dimitriou M, Eiriksdottir G, Eriksson J, Gieger C, Gudnason V, Höhne B, Holle R, Hottenga JJ, Isaacs A, Järvelin MR, Johannesson M, Kaakinen M, Kähönen M, Kanoni S, Laaksonen MA, Lahti J, Launer LJ, Lehtimäki T, Loitfelder M, Magnusson PKE, Naitza S, Oostra BA, Perola M, Petrovic K, Quaye L, Raitakari O, Ripatti S, Scheet P, Schlessinger D, Schmidt CO, Schmidt H, Schmidt R, Senft A, Smith AV, Spector TD, Surakka I, Svento R, Terracciano A, Tikkanen E, van Duijn CM, Viikari J, Völzke H, Wichmann HE, Wild PS, Willems SM, Willemsen G, van Rooij FJA, Groenen PJF, Uitterlinden AG, Hofman A, Thurik AR. The molecular genetic architecture of self-employment. PLoS One 2013; 8:e60542. [PMID: 23593239 PMCID: PMC3617140 DOI: 10.1371/journal.pone.0060542] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2012] [Accepted: 02/27/2013] [Indexed: 12/15/2022] Open
Abstract
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σ(g)(2)/σ(P)(2) = 25%, h(2) = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10(-5) were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
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Affiliation(s)
- Matthijs J H M van der Loos
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands.
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174
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The Minnesota Center for Twin and Family Research genome-wide association study. Twin Res Hum Genet 2013; 15:767-74. [PMID: 23363460 DOI: 10.1017/thg.2012.62] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
As part of the Genes, Environment and Development Initiative, the Minnesota Center for Twin and Family Research (MCTFR) undertook a genome-wide association study, which we describe here. A total of 8,405 research participants, clustered in four-member families, have been successfully genotyped on 527,829 single nucleotide polymorphism (SNP) markers using lllumina's Human660W-Ouad array. Quality control screening of samples and markers as well as SNP imputation procedures are described. We also describe methods for ancestry control and how the familial clustering of the MCTFR sample can be accounted for in the analysis using a Rapid Feasible Generalized Least Squares algorithm. The rich longitudinal MCTFR assessments provide numerous opportunities for collaboration.
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175
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Richter S, Gorny X, Machts J, Behnisch G, Wüstenberg T, Herbort MC, Münte TF, Seidenbecher CI, Schott BH. Effects of AKAP5 Pro100Leu genotype on working memory for emotional stimuli. PLoS One 2013; 8:e55613. [PMID: 23383244 PMCID: PMC3558499 DOI: 10.1371/journal.pone.0055613] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2012] [Accepted: 12/27/2012] [Indexed: 11/19/2022] Open
Abstract
Recent investigations addressing the role of the synaptic multiadaptor molecule AKAP5 in human emotion and behavior suggest that the AKAP5 Pro100Leu polymorphism (rs2230491) contributes to individual differences in affective control. Carriers of the less common Leu allele show a higher control of anger as indicated by behavioral measures and dACC brain response on emotional distracters when compared to Pro homozygotes. In the current fMRI study we used an emotional working memory task according to the n-back scheme with neutral and negative emotional faces as target stimuli. Pro homozygotes showed a performance advantage at the behavioral level and exhibited enhanced activation of the amygdala and fusiform face area during working memory for emotional faces. On the other hand, Leu carriers exhibited increased activation of the dACC during performance of the 2-back condition. Our results suggest that AKAP5 Pro100Leu effects on emotion processing might be task-dependent with Pro homozygotes showing lower control of emotional interference, but more efficient processing of task-relevant emotional stimuli.
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Affiliation(s)
- Sylvia Richter
- Department of Clinical Psychology, University of Salzburg, Salzburg, Austria
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xenia Gorny
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Judith Machts
- Department of Neurology, University of Magdeburg, Magdeburg, Germany
| | | | - Torsten Wüstenberg
- Department of Psychiatry, Charité – Universitätsmedizin Berlin, Charité Campus Mitte, Berlin, Germany
| | - Maike C. Herbort
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Psychiatry, Charité – Universitätsmedizin Berlin, Charité Campus Mitte, Berlin, Germany
| | - Thomas F. Münte
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | | | - Björn H. Schott
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Neurology, University of Magdeburg, Magdeburg, Germany
- Department of Psychiatry, Charité – Universitätsmedizin Berlin, Charité Campus Mitte, Berlin, Germany
- * E-mail:
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176
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Amin N, Hottenga JJ, Hansell NK, Janssens ACJW, de Moor MHM, Madden PAF, Zorkoltseva IV, Penninx BW, Terracciano A, Uda M, Tanaka T, Esko T, Realo A, Ferrucci L, Luciano M, Davies G, Metspalu A, Abecasis GR, Deary IJ, Raikkonen K, Bierut LJ, Costa PT, Saviouk V, Zhu G, Kirichenko AV, Isaacs A, Aulchenko YS, Willemsen G, Heath AC, Pergadia ML, Medland SE, Axenovich TI, de Geus E, Montgomery GW, Wright MJ, Oostra BA, Martin NG, Boomsma DI, van Duijn CM. Refining genome-wide linkage intervals using a meta-analysis of genome-wide association studies identifies loci influencing personality dimensions. Eur J Hum Genet 2012; 21:876-82. [PMID: 23211697 DOI: 10.1038/ejhg.2012.263] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2011] [Revised: 09/21/2012] [Accepted: 10/26/2012] [Indexed: 11/10/2022] Open
Abstract
Personality traits are complex phenotypes related to psychosomatic health. Individually, various gene finding methods have not achieved much success in finding genetic variants associated with personality traits. We performed a meta-analysis of four genome-wide linkage scans (N=6149 subjects) of five basic personality traits assessed with the NEO Five-Factor Inventory. We compared the significant regions from the meta-analysis of linkage scans with the results of a meta-analysis of genome-wide association studies (GWAS) (N∼17 000). We found significant evidence of linkage of neuroticism to chromosome 3p14 (rs1490265, LOD=4.67) and to chromosome 19q13 (rs628604, LOD=3.55); of extraversion to 14q32 (ATGG002, LOD=3.3); and of agreeableness to 3p25 (rs709160, LOD=3.67) and to two adjacent regions on chromosome 15, including 15q13 (rs970408, LOD=4.07) and 15q14 (rs1055356, LOD=3.52) in the individual scans. In the meta-analysis, we found strong evidence of linkage of extraversion to 4q34, 9q34, 10q24 and 11q22, openness to 2p25, 3q26, 9p21, 11q24, 15q26 and 19q13 and agreeableness to 4q34 and 19p13. Significant evidence of association in the GWAS was detected between openness and rs677035 at 11q24 (P-value=2.6 × 10(-06), KCNJ1). The findings of our linkage meta-analysis and those of the GWAS suggest that 11q24 is a susceptible locus for openness, with KCNJ1 as the possible candidate gene.
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Affiliation(s)
- Najaf Amin
- Unit of Genetic Epidemiology, Department of Epidemiology and Biostatistics, Erasmus University Medical Center, Rotterdam, The Netherlands
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177
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Wahlsten D. The hunt for gene effects pertinent to behavioral traits and psychiatric disorders: from mouse to human. Dev Psychobiol 2012; 54:475-92. [PMID: 22674524 DOI: 10.1002/dev.21043] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The field of behavioral genetics was reviewed in the classic 1960 text by Fuller and Thompson. Since then, there has been remarkable progress in the genetic analysis of animal behavior. Many molecular genetic methods in common use today were not even anticipated in 1960. Animal models for many human psychiatric disorders have been discovered or created. In human behavior genetics, however, powerful new methods have failed to reveal even one bona fide, replicable gene effect pertinent to the normal range of variation in intelligence and personality. There is no explanatory or predictive value in that genetic information. For several psychiatric disorders, including autism and schizophrenia, many large genetic effects arise from de novo mutations. Genetically, the disorders are heterogeneous; different cases with the same diagnosis have different causes. The promises of the molecular genetic revolution have not been fulfilled in behavioral domains of most interest to human psychology.
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Affiliation(s)
- Douglas Wahlsten
- Department of Psychology, University of North Carolina Greensboro, Greensboro, NC 27402, USA.
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178
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Biological pathways and genetic mechanisms involved in social functioning. Qual Life Res 2012; 22:1189-200. [DOI: 10.1007/s11136-012-0277-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2012] [Indexed: 11/12/2022]
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179
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Luciano M, MacLeod AK, Payton A, Davies G, Ke X, Tenesa A, Ollier W, Starr JM, Horan MA, Pendleton N, Thomson PA, Porteous DJ, Deary IJ. Effects of gene copy number variants on personality and mood in ageing cohorts. PERSONALITY AND INDIVIDUAL DIFFERENCES 2012. [DOI: 10.1016/j.paid.2011.12.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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180
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Krueger RF, Derringer J, Markon KE, Watson D, Skodol AE. Initial construction of a maladaptive personality trait model and inventory for DSM-5. Psychol Med 2012; 42:1879-1890. [PMID: 22153017 PMCID: PMC3413381 DOI: 10.1017/s0033291711002674] [Citation(s) in RCA: 1048] [Impact Index Per Article: 80.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND DSM-IV-TR suggests that clinicians should assess clinically relevant personality traits that do not necessarily constitute a formal personality disorder (PD), and should note these traits on Axis II, but DSM-IV-TR does not provide a trait model to guide the clinician. Our goal was to provide a provisional trait model and a preliminary corresponding assessment instrument, in our roles as members of the DSM-5 Personality and Personality Disorders Workgroup and workgroup advisors. METHOD An initial list of specific traits and domains (broader groups of traits) was derived from DSM-5 literature reviews and workgroup deliberations, with a focus on capturing maladaptive personality characteristics deemed clinically salient, including those related to the criteria for DSM-IV-TR PDs. The model and instrument were then developed iteratively using data from community samples of treatment-seeking participants. The analytic approach relied on tools of modern psychometrics (e.g. item response theory models). RESULTS A total of 25 reliably measured core elements of personality description emerged that, together, delineate five broad domains of maladaptive personality variation: negative affect, detachment, antagonism, disinhibition, and psychoticism. CONCLUSIONS We developed a maladaptive personality trait model and corresponding instrument as a step on the path toward helping users of DSM-5 assess traits that may or may not constitute a formal PD. The inventory we developed is reprinted in its entirety in the Supplementary online material, with the goal of encouraging additional refinement and development by other investigators prior to the finalization of DSM-5. Continuing discussion should focus on various options for integrating personality traits into DSM-5.
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Affiliation(s)
- R F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455, USA.
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Luciano M, Huffman JE, Arias-Vásquez A, Vinkhuyzen AAE, Middeldorp CM, Giegling I, Payton A, Davies G, Zgaga L, Janzing J, Ke X, Galesloot T, Hartmann AM, Ollier W, Tenesa A, Hayward C, Verhagen M, Montgomery GW, Hottenga JJ, Konte B, Starr JM, Vitart V, Vos PE, Madden PAF, Willemsen G, Konnerth H, Horan MA, Porteous DJ, Campbell H, Vermeulen SH, Heath AC, Wright A, Polasek O, Kovacevic SB, Hastie ND, Franke B, Boomsma DI, Martin NG, Rujescu D, Wilson JF, Buitelaar J, Pendleton N, Rudan I, Deary IJ. Genome-wide association uncovers shared genetic effects among personality traits and mood states. Am J Med Genet B Neuropsychiatr Genet 2012; 159B:684-95. [PMID: 22628180 PMCID: PMC3795298 DOI: 10.1002/ajmg.b.32072] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2012] [Accepted: 05/03/2012] [Indexed: 12/27/2022]
Abstract
Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (~2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of mood states using genetic polygenic scores for personality. Measures of neuroticism, extraversion, and symptoms of anxiety, depression, and general psychological distress were collected in eight European cohorts (n ranged 546-1,338; maximum total n = 6,268) whose mean age ranged from 55 to 79 years. Meta-analysis of the cohort results was performed, with follow-up associations of the top SNPs and genes investigated in independent cohorts (n = 527-6,032). Suggestive association (P = 8 × 10(-8)) of rs1079196 in the FHIT gene was observed with symptoms of anxiety. Other notable associations (P < 6.09 × 10(-6)) included SNPs in five genes for neuroticism (LCE3C, POLR3A, LMAN1L, ULK3, SCAMP2), KIAA0802 for extraversion, and NOS1 for general psychological distress. An association between symptoms of depression and rs7582472 (near to MGAT5 and NCKAP5) was replicated in two independent samples, but other replication findings were less consistent. Gene-based tests identified a significant locus on chromosome 15 (spanning five genes) associated with neuroticism which replicated (P < 0.05) in an independent cohort. Support for common genetic effects among personality and mood (particularly neuroticism and depressive symptoms) was found in terms of SNP association overlap and polygenic score prediction. The variance explained by individual SNPs was very small (up to 1%) confirming that there are no moderate/large effects of common SNPs on personality and related traits.
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Affiliation(s)
- Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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182
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Hart AB, Engelhardt BE, Wardle MC, Sokoloff G, Stephens M, de Wit H, Palmer AA. Genome-wide association study of d-amphetamine response in healthy volunteers identifies putative associations, including cadherin 13 (CDH13). PLoS One 2012; 7:e42646. [PMID: 22952603 PMCID: PMC3429486 DOI: 10.1371/journal.pone.0042646] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2012] [Accepted: 07/11/2012] [Indexed: 12/11/2022] Open
Abstract
Both the subjective response to d-amphetamine and the risk for amphetamine addiction are known to be heritable traits. Because subjective responses to drugs may predict drug addiction, identifying alleles that influence acute response may also provide insight into the genetic risk factors for drug abuse. We performed a Genome Wide Association Study (GWAS) for the subjective responses to amphetamine in 381 non-drug abusing healthy volunteers. Responses to amphetamine were measured using a double-blind, placebo-controlled, within-subjects design. We used sparse factor analysis to reduce the dimensionality of the data to ten factors. We identified several putative associations; the strongest was between a positive subjective drug-response factor and a SNP (rs3784943) in the 8(th) intron of cadherin 13 (CDH13; P = 4.58×10(-8)), a gene previously associated with a number of psychiatric traits including methamphetamine dependence. Additionally, we observed a putative association between a factor representing the degree of positive affect at baseline and a SNP (rs472402) in the 1(st) intron of steroid-5-alpha-reductase-α-polypeptide-1 (SRD5A1; P = 2.53×10(-7)), a gene whose protein product catalyzes the rate-limiting step in synthesis of the neurosteroid allopregnanolone. This SNP belongs to an LD-block that has been previously associated with the expression of SRD5A1 and differences in SRD5A1 enzymatic activity. The purpose of this study was to begin to explore the genetic basis of subjective responses to stimulant drugs using a GWAS approach in a modestly sized sample. Our approach provides a case study for analysis of high-dimensional intermediate pharmacogenomic phenotypes, which may be more tractable than clinical diagnoses.
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Affiliation(s)
- Amy B. Hart
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Barbara E. Engelhardt
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Department of Computer Science, University of Chicago, Chicago, Illinois, United States of America
| | - Margaret C. Wardle
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States of America
| | - Greta Sokoloff
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Matthew Stephens
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States of America
| | - Abraham A. Palmer
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States of America
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183
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Cramer AOJ, Van Der Sluis S, Noordhof A, Wichers M, Geschwind N, Aggen SH, Kendler KS, Borsboom D. Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't like Parties if you Don't like People. EUROPEAN JOURNAL OF PERSONALITY 2012. [DOI: 10.1002/per.1866] [Citation(s) in RCA: 212] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality as a system of connected affective, cognitive and behavioural components. We hypothesize that these components do not hang together because they measure the same underlying dimension; they do so because they depend on one another directly for causal, homeostatic or logical reasons (e.g. if one does not like people and it is harder to enjoy parties). From this ‘network perspective’, personality dimensions emerge out of the connectivity structure that exists between the various components of personality. After outlining the network theory, we illustrate how it applies to personality research in four domains: (i) the overall organization of personality components; (ii) the distinction between state and trait; (iii) the genetic architecture of personality; and (iv) the relation between personality and psychopathology. Copyright © 2012 John Wiley & Sons, Ltd.
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Affiliation(s)
| | - Sophie Van Der Sluis
- Department of Psychology, University of Amsterdam, The Netherlands
- Complex Trait Genetics, Department of Functional Genomics and Department Clinical Genetics, Center for Neurogenomics and Cognitive Research (CNCR), FALW-VUA, Neuroscience Campus Amsterdam, VU University Medical Center (VUmc), The Netherlands
| | - Arjen Noordhof
- Department of Psychology, University of Amsterdam, The Netherlands
| | - Marieke Wichers
- European Graduate School for Neuroscience, SEARCH, Department of Psychiatry and Psychology, Maastricht University Medical Centre, The Netherlands
| | - Nicole Geschwind
- European Graduate School for Neuroscience, SEARCH, Department of Psychiatry and Psychology, Maastricht University Medical Centre, The Netherlands
- Research Group on Health Psychology, Centre for the Psychology of Learning and Experimental Psychopathology, University of Leuven, Belgium
| | - Steven H. Aggen
- Virginia Institute for Psychiatric and Behavioral Genetics, USA
- Department of Psychiatry, Virginia Commonwealth University, USA
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, USA
- Department of Psychiatry, Virginia Commonwealth University, USA
| | - Denny Borsboom
- Department of Psychology, University of Amsterdam, The Netherlands
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184
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Benjamin DJ, Cesarini D, Chabris CF, Glaeser EL, Laibson DI, Guðnason V, Harris TB, Launer LJ, Purcell S, Smith AV, Johannesson M, Magnusson PKE, Beauchamp JP, Christakis NA, Atwood CS, Hebert B, Freese J, Hauser RM, Hauser TS, Grankvist A, Hultman CM, Lichtenstein P. The Promises and Pitfalls of Genoeconomics*. ANNUAL REVIEW OF ECONOMICS 2012; 4:627-662. [PMID: 23482589 PMCID: PMC3592970 DOI: 10.1146/annurev-economics-080511-110939] [Citation(s) in RCA: 69] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
This article reviews existing research at the intersection of genetics and economics, presents some new findings that illustrate the state of genoeconomics research, and surveys the prospects of this emerging field. Twin studies suggest that economic outcomes and preferences, once corrected for measurement error, appear to be about as heritable as many medical conditions and personality traits. Consistent with this pattern, we present new evidence on the heritability of permanent income and wealth. Turning to genetic association studies, we survey the main ways that the direct measurement of genetic variation across individuals is likely to contribute to economics, and we outline the challenges that have slowed progress in making these contributions. The most urgent problem facing researchers in this field is that most existing efforts to find associations between genetic variation and economic behavior are based on samples that are too small to ensure adequate statistical power. This has led to many false positives in the literature. We suggest a number of possible strategies to improve and remedy this problem: (a) pooling data sets, (b) using statistical techniques that exploit the greater information content of many genes considered jointly, and (c) focusing on economically relevant traits that are most proximate to known biological mechanisms.
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Affiliation(s)
- Daniel J Benjamin
- Department of Economics, Cornell University, Ithaca, New York 14853; National Bureau of Economic Research, Cambridge, Massachusetts 02138;
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185
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Kööts-Ausmees L, Realo A, Allik J. The Relationship Between Life Satisfaction and Emotional Experience in 21 European Countries. JOURNAL OF CROSS-CULTURAL PSYCHOLOGY 2012. [DOI: 10.1177/0022022112451054] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In the current study, the relationship between life satisfaction (LS) and the affective components of subjective well-being (SWB) was examined in a sample of 40,487 people across 21 European countries using data from the European Social Survey. After running multilevel confirmatory factor analyses in order to establish the measurement invariance of the constructs across the countries, the individual-level dataset was linked to available country-level aggregate personality traits, cultural values, and human development index (HDI). Results from hierarchical linear modeling (HLM) analysis showed that LS is best predicted by positive and negative affect (PA and NA, respectively), but may also be predicted by the degree of mixed emotions (ME). At the country level, national mean scores of Extraversion and Neuroticism moderated the relationship between LS and ME in different directions, whereas neither of the two personality traits had a significant impact on the relationship of LS to PA and NA. Survival/self-expression and the HDI ranking influenced the LS-PA and LS-ME relationships, whereas individualism/collectivism did not. Our research indicates that in addition to analyzing separate effects of NA and PA, it is also important to consider emotional complexity in SWB research, whereas these analyses need to take into account the moderating effect of cultural aspects, such as survival/self-expression values and countries’ level of development. Our findings also emphasize the importance of employing representative samples, as the age variance of participants can have a profound impact on results.
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Affiliation(s)
- Liisi Kööts-Ausmees
- University of Tartu, Tartu, Estonia
- The Estonian Center of Behavioral and Health Sciences, Tartu, Estonia
| | - Anu Realo
- University of Tartu, Tartu, Estonia
- The Estonian Center of Behavioral and Health Sciences, Tartu, Estonia
| | - Jüri Allik
- University of Tartu, Tartu, Estonia
- The Estonian Center of Behavioral and Health Sciences, Tartu, Estonia
- Estonian Academy of Sciences, Tallinn, Estonia
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186
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Briley DA, Tucker-Drob EM. Broad bandwidth or high fidelity? Evidence from the structure of genetic and environmental effects on the facets of the five factor model. Behav Genet 2012; 42:743-63. [PMID: 22695681 DOI: 10.1007/s10519-012-9548-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2011] [Accepted: 05/17/2012] [Indexed: 11/27/2022]
Abstract
The Five Factor Model of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. For three of the Big Five domains, models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality.
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Affiliation(s)
- Daniel A Briley
- Department of Psychology and Population Research Center, University of Texas at Austin, 108 E. Dean Keeton Stop A8000, Austin, TX 78712-0187, USA.
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187
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Benjamin DJ, Cesarini D, van der Loos MJHM, Dawes CT, Koellinger PD, Magnusson PKE, Chabris CF, Conley D, Laibson D, Johannesson M, Visscher PM. The genetic architecture of economic and political preferences. Proc Natl Acad Sci U S A 2012; 109:8026-31. [PMID: 22566634 PMCID: PMC3361436 DOI: 10.1073/pnas.1120666109] [Citation(s) in RCA: 123] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.
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188
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Verweij KJH, Yang J, Lahti J, Veijola J, Hintsanen M, Pulkki-Råback L, Heinonen K, Pouta A, Pesonen AK, Widen E, Taanila A, Isohanni M, Miettunen J, Palotie A, Penke L, Service SK, Heath AC, Montgomery GW, Raitakari O, Kähönen M, Viikari J, Räikkönen K, Eriksson JG, Keltikangas-Järvinen L, Lehtimäki T, Martin NG, Järvelin MR, Visscher PM, Keller MC, Zietsch BP. Maintenance of genetic variation in human personality: testing evolutionary models by estimating heritability due to common causal variants and investigating the effect of distant inbreeding. Evolution 2012; 66:3238-51. [PMID: 23025612 DOI: 10.1111/j.1558-5646.2012.01679.x] [Citation(s) in RCA: 147] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Personality traits are basic dimensions of behavioral variation, and twin, family, and adoption studies show that around 30% of the between-individual variation is due to genetic variation. There is rapidly growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome-wide single nucleotide polymorphism (SNP) data from > 8000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation-selection balance.
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Affiliation(s)
- Karin J H Verweij
- Genetic Epidemiology, Molecular Epidemiology, and Queensland Statistical Genetics Laboratories, Queensland Institute of Medical Research, Herston 4006, Brisbane, Queensland, Australia
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189
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Service SK, Verweij KJH, Lahti J, Congdon E, Ekelund J, Hintsanen M, Räikkönen K, Lehtimäki T, Kähönen M, Widen E, Taanila A, Veijola J, Heath AC, Madden PAF, Montgomery GW, Sabatti C, Järvelin MR, Palotie A, Raitakari O, Viikari J, Martin NG, Eriksson JG, Keltikangas-Järvinen L, Wray NR, Freimer NB. A genome-wide meta-analysis of association studies of Cloninger's Temperament Scales. Transl Psychiatry 2012; 2:e116. [PMID: 22832960 PMCID: PMC3365256 DOI: 10.1038/tp.2012.37] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Temperament has a strongly heritable component, yet multiple independent genome-wide studies have failed to identify significant genetic associations. We have assembled the largest sample to date of persons with genome-wide genotype data, who have been assessed with Cloninger's Temperament and Character Inventory. Sum scores for novelty seeking, harm avoidance, reward dependence and persistence have been measured in over 11,000 persons collected in four different cohorts. Our study had >80% power to identify genome-wide significant loci (P<1.25 × 10(-8), with correction for testing four scales) accounting for ≥0.4% of the phenotypic variance in temperament scales. Using meta-analysis techniques, gene-based tests and pathway analysis we have tested over 1.2 million single-nucleotide polymorphisms (SNPs) for association to each of the four temperament dimensions. We did not discover any SNPs, genes, or pathways to be significantly related to the four temperament dimensions, after correcting for multiple testing. Less than 1% of the variability in any temperament dimension appears to be accounted for by a risk score derived from the SNPs showing strongest association to the temperament dimensions. Elucidation of genetic loci significantly influencing temperament and personality will require potentially very large samples, and/or a more refined phenotype. Item response theory methodology may be a way to incorporate data from cohorts assessed with multiple personality instruments, and might be a method by which a large sample of a more refined phenotype could be acquired.
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Affiliation(s)
- S K Service
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA, USA
| | - K J H Verweij
- Genetic Epidemiology, Molecular Epidemiology and Psychiatric Genetics Laboratories, Queensland Institute of Medical Research, Brisbane, QLD, Australia,School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - E Congdon
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA, USA
| | - J Ekelund
- Department of Psychiatry, University of Helsinki and Finland National Public Health Institute, Helsinki, Finland,Finland Vaasa Hospital District, Vaasa, Finland
| | - M Hintsanen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland,Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - T Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere University Hospital, Tampere, Finland,University of Tampere School of Medicine, Tampere, Finland
| | - M Kähönen
- University of Tampere School of Medicine, Tampere, Finland,Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - E Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - A Taanila
- Institute of Health Sciences, Public Health and General Practice, University of Oulu, Oulu, Finland
| | - J Veijola
- Department of Psychiatry, Institute of Clinical Medicine, University of Oulu, Oulu, Finland
| | - A C Heath
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - P A F Madden
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - G W Montgomery
- Genetic Epidemiology, Molecular Epidemiology and Psychiatric Genetics Laboratories, Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - C Sabatti
- Department of Health and Research Policy, Stanford University, Stanford, CA, USA,Department of Statistics, Stanford University, Stanford, CA, USA
| | - M-R Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-HPA Centre for Environment and Health, Imperial College London, London, UK,Institute of Health Sciences, University of Oulu, Oulu, Finland,Biocenter Oulu, University of Oulu, Oulu, Finland,Department of Lifecourse and Services, National Institute of Health and Welfare, Oulu Finland
| | - A Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK,Department of Medical Genetics, University of Helsinki, Helsinki, Finland,University Central Hospital, Helsinki, Finland
| | - O Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - J Viikari
- Department of Medicine, Turku University Hospital, Turku, Finland,University of Turku, Turku, Finland
| | - N G Martin
- Genetic Epidemiology, Molecular Epidemiology and Psychiatric Genetics Laboratories, Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - J G Eriksson
- Finland Vaasa Hospital District, Vaasa, Finland,National Institute for Health and Welfare, Helsinki, Finland,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland,Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland,Folkhalsan Research Centre, Helsinki, Finland
| | | | - N R Wray
- Genetic Epidemiology, Molecular Epidemiology and Psychiatric Genetics Laboratories, Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - N B Freimer
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA, USA,The Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA,Department of Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA,Center for Neurobehavioral Genetics, University of California, Gonda Center Room 3506, 695 Charles E Young Dr South, Box 951761, Los Angeles, CA 90095, USA. E-mail:
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190
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Vinkhuyzen AAE, Pedersen NL, Yang J, Lee SH, Magnusson PKE, Iacono WG, McGue M, Madden PAF, Heath AC, Luciano M, Payton A, Horan M, Ollier W, Pendleton N, Deary IJ, Montgomery GW, Martin NG, Visscher PM, Wray NR. Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion. Transl Psychiatry 2012; 2:e102. [PMID: 22832902 PMCID: PMC3337075 DOI: 10.1038/tp.2012.27] [Citation(s) in RCA: 146] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The personality traits of neuroticism and extraversion are predictive of a number of social and behavioural outcomes and psychiatric disorders. Twin and family studies have reported moderate heritability estimates for both traits. Few associations have been reported between genetic variants and neuroticism/extraversion, but hardly any have been replicated. Moreover, the ones that have been replicated explain only a small proportion of the heritability (<~2%). Using genome-wide single-nucleotide polymorphism (SNP) data from ~12,000 unrelated individuals we estimated the proportion of phenotypic variance explained by variants in linkage disequilibrium with common SNPs as 0.06 (s.e. = 0.03) for neuroticism and 0.12 (s.e. = 0.03) for extraversion. In an additional series of analyses in a family-based sample, we show that while for both traits ~45% of the phenotypic variance can be explained by pedigree data (that is, expected genetic similarity) one third of this can be explained by SNP data (that is, realized genetic similarity). A part of the so-called 'missing heritability' has now been accounted for, but some of the reported heritability is still unexplained. Possible explanations for the remaining missing heritability are that: (i) rare variants that are not captured by common SNPs on current genotype platforms make a major contribution; and/ or (ii) the estimates of narrow sense heritability from twin and family studies are biased upwards, for example, by not properly accounting for nonadditive genetic factors and/or (common) environmental factors.
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Affiliation(s)
- A A E Vinkhuyzen
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia.
| | - N L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - J Yang
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - S H Lee
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia,The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - P K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - W G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - M McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - P A F Madden
- Washington University School of Medicine, St Louis, MO, USA
| | - A C Heath
- Washington University School of Medicine, St Louis, MO, USA
| | - M Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A Payton
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - M Horan
- School of Medicine, The University of Manchester, Manchester, UK
| | - W Ollier
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - N Pendleton
- School of Medicine, The University of Manchester, Manchester, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - G W Montgomery
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - N G Martin
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - P M Visscher
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - N R Wray
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia,The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
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191
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Luciano M, Lopez LM, de Moor MHM, Harris SE, Davies G, Nutile T, Krueger RF, Esko T, Schlessinger D, Toshiko T, Derringer JL, Realo A, Hansell NK, Pergadia ML, Pesonen AK, Sanna S, Terracciano A, Madden PAF, Penninx B, Spinhoven P, Hartman CA, Oostra BA, Janssens ACJW, Eriksson JG, Starr JM, Cannas A, Ferrucci L, Metspalu A, Wright MJ, Heath AC, van Duijn CM, Bierut LJ, Raikkonen K, Martin NG, Ciullo M, Rujescu D, Boomsma DI, Deary IJ. Longevity candidate genes and their association with personality traits in the elderly. Am J Med Genet B Neuropsychiatr Genet 2012; 159B:192-200. [PMID: 22213687 PMCID: PMC3583011 DOI: 10.1002/ajmg.b.32013] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2011] [Accepted: 12/05/2011] [Indexed: 11/08/2022]
Abstract
Human longevity and personality traits are both heritable and are consistently linked at the phenotypic level. We test the hypothesis that candidate genes influencing longevity in lower organisms are associated with variance in the five major dimensions of human personality (measured by the NEO-FFI and IPIP inventories) plus related mood states of anxiety and depression. Seventy single nucleotide polymorphisms (SNPs) in six brain expressed, longevity candidate genes (AFG3L2, FRAP1, MAT1A, MAT2A, SYNJ1, and SYNJ2) were typed in over 1,000 70-year old participants from the Lothian Birth Cohort of 1936 (LBC1936). No SNPs were associated with the personality and psychological distress traits at a Bonferroni corrected level of significance (P < 0.0002), but there was an over-representation of nominally significant (P < 0.05) SNPs in the synaptojanin-2 (SYNJ2) gene associated with agreeableness and symptoms of depression. Eight SNPs which showed nominally significant association across personality measurement instruments were tested in an extremely large replication sample of 17,106 participants. SNP rs350292, in SYNJ2, was significant: the minor allele was associated with an average decrease in NEO agreeableness scale scores of 0.25 points, and 0.67 points in the restricted analysis of elderly cohorts (most aged >60 years). Because we selected a specific set of longevity genes based on functional genomics findings, further research on other longevity gene candidates is warranted to discover whether they are relevant candidates for personality and psychological distress traits.
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Affiliation(s)
- Michelle Luciano
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, UK.
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192
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de Moor MHM, Vink JM, van Beek JHDA, Geels LM, Bartels M, de Geus EJC, Willemsen G, Boomsma DI. Heritability of problem drinking and the genetic overlap with personality in a general population sample. Front Genet 2011; 2:76. [PMID: 22303371 PMCID: PMC3268629 DOI: 10.3389/fgene.2011.00076] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2011] [Accepted: 10/16/2011] [Indexed: 12/13/2022] Open
Abstract
This study examined the heritability of problem drinking and investigated the phenotypic and genetic relationships between problem drinking and personality. In a sample of 5,870 twins and siblings and 4,420 additional family members from the Netherlands Twin Register. Data on problem drinking (assessed with the AUDIT and CAGE; 12 items) and personality [NEO Five-Factor Inventory (FFI); 60 items] were collected in 2009/2010 by surveys. Confirmatory factor analysis on the AUDIT and CAGE items showed that the items clustered on two separate but highly correlated (r = 0.74) underlying factors. A higher-order factor was extracted that reflected those aspects of problem drinking that are common to the AUDIT and CAGE, which showed a heritability of 40%. The correlations between problem drinking and the five dimensions of personality were small but significant, ranging from 0.06 for Extraversion to −0.12 for Conscientiousness. All personality dimensions (with broad-sense heritabilities between 32 and 55%, and some evidence for non-additive genetic influences) were genetically correlated with problem drinking. The genetic correlations were small to modest (between |0.12| and |0.41|). Future studies with longitudinal data and DNA polymorphisms are needed to determine the biological mechanisms that underlie the genetic link between problem drinking and personality.
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Affiliation(s)
- Marleen H M de Moor
- Department of Biological Psychology, VU University Amsterdam Amsterdam, Netherlands
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193
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Middeldorp CM, de Moor MHM, McGrath LM, Gordon SD, Blackwood DH, Costa PT, Terracciano A, Krueger RF, de Geus EJC, Nyholt DR, Tanaka T, Esko T, Madden PAF, Derringer J, Amin N, Willemsen G, Hottenga JJ, Distel MA, Uda M, Sanna S, Spinhoven P, Hartman CA, Ripke S, Sullivan PF, Realo A, Allik J, Heath AC, Pergadia ML, Agrawal A, Lin P, Grucza RA, Widen E, Cousminer DL, Eriksson JG, Palotie A, Barnett JH, Lee PH, Luciano M, Tenesa A, Davies G, Lopez LM, Hansell NK, Medland SE, Ferrucci L, Schlessinger D, Montgomery GW, Wright MJ, Aulchenko YS, Janssens ACJW, Oostra BA, Metspalu A, Abecasis GR, Deary IJ, Räikkönen K, Bierut LJ, Martin NG, Wray NR, van Duijn CM, Smoller JW, Penninx BWJH, Boomsma DI. The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data. Transl Psychiatry 2011; 1:e50. [PMID: 22833196 PMCID: PMC3309491 DOI: 10.1038/tp.2011.45] [Citation(s) in RCA: 85] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2011] [Revised: 08/19/2011] [Accepted: 08/31/2011] [Indexed: 12/20/2022] Open
Abstract
The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.
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Affiliation(s)
- C M Middeldorp
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.
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194
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Terracciano A, Esko T, Sutin AR, de Moor MHM, Meirelles O, Zhu G, Tanaka T, Giegling I, Nutile T, Realo A, Allik J, Hansell NK, Wright MJ, Montgomery GW, Willemsen G, Hottenga JJ, Friedl M, Ruggiero D, Sorice R, Sanna S, Cannas A, Räikkönen K, Widen E, Palotie A, Eriksson JG, Cucca F, Krueger RF, Lahti J, Luciano M, Smoller JW, van Duijn CM, Abecasis GR, Boomsma DI, Ciullo M, Costa PT, Ferrucci L, Martin NG, Metspalu A, Rujescu D, Schlessinger D, Uda M. Meta-analysis of genome-wide association studies identifies common variants in CTNNA2 associated with excitement-seeking. Transl Psychiatry 2011; 1:e49. [PMID: 22833195 PMCID: PMC3309493 DOI: 10.1038/tp.2011.42] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
The tendency to seek stimulating activities and intense sensations define excitement-seeking, a personality trait akin to some aspects of sensation-seeking. This trait is a central feature of extraversion and is a component of the multifaceted impulsivity construct. Those who score high on measures of excitement-seeking are more likely to smoke, use other drugs, gamble, drive recklessly, have unsafe/unprotected sex and engage in other risky behaviors of clinical and social relevance. To identify common genetic variants associated with the Excitement-Seeking scale of the Revised NEO Personality Inventory, we performed genome-wide association studies in six samples of European ancestry (N=7860), and combined the results in a meta-analysis. We identified a genome-wide significant association between the Excitement-Seeking scale and rs7600563 (P=2 × 10(-8)). This single-nucleotide polymorphism maps within the catenin cadherin-associated protein, alpha 2 (CTNNA2) gene, which encodes for a brain-expressed α-catenin critical for synaptic contact. The effect of rs7600563 was in the same direction in all six samples, but did not replicate in additional samples (N=5105). The results provide insight into the genetics of excitement-seeking and risk-taking, and are relevant to hyperactivity, substance use, antisocial and bipolar disorders.
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Affiliation(s)
- A Terracciano
- National Institute on Aging, NIH, DHHS, Baltimore, MD 21224, USA.
| | - T Esko
- University of Tartu, Tartu, Estonia,Estonian Biocenter, Tartu, Estonia
| | - A R Sutin
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - M H M de Moor
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - O Meirelles
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - G Zhu
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - T Tanaka
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - I Giegling
- Department of Psychiatry, University of Munich, Munich, Germany
| | - T Nutile
- Institute of Genetics and Biophysics A Buzzati-Traverso, CNR, Naples, Italy
| | - A Realo
- University of Tartu, Tartu, Estonia
| | - J Allik
- University of Tartu, Tartu, Estonia
| | - N K Hansell
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - G W Montgomery
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - G Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - J-J Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - M Friedl
- Department of Psychiatry, University of Munich, Munich, Germany
| | - D Ruggiero
- Institute of Genetics and Biophysics A Buzzati-Traverso, CNR, Naples, Italy
| | - R Sorice
- Institute of Genetics and Biophysics A Buzzati-Traverso, CNR, Naples, Italy
| | - S Sanna
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Cagliari, Italy
| | - A Cannas
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Cagliari, Italy
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - E Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - A Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK
| | - J G Eriksson
- National Institute for Health and Welfare, Helsinki, Finland
| | - F Cucca
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Cagliari, Italy
| | - R F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - M Luciano
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
| | - J W Smoller
- Department of Psychiatry and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
| | - C M van Duijn
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands and
| | - G R Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - M Ciullo
- Institute of Genetics and Biophysics A Buzzati-Traverso, CNR, Naples, Italy
| | - P T Costa
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - L Ferrucci
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - N G Martin
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - A Metspalu
- University of Tartu, Tartu, Estonia,Estonian Biocenter, Tartu, Estonia
| | - D Rujescu
- Department of Psychiatry, University of Munich, Munich, Germany
| | - D Schlessinger
- National Institute on Aging, NIH, DHHS, Baltimore, MD, USA
| | - M Uda
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Cagliari, Italy
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195
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Abstract
Hostility is a multidimensional personality trait with changing expression over the life course. We performed a genome-wide association study (GWAS) of the components of hostility in a population-based sample of Finnish men and women for whom a total of 2.5 million single-nucleotide polymorphisms (SNPs) were available through direct or in silico genotyping. Hostility dimensions (anger, cynicism and paranoia) were assessed at four time points over a 15-year interval (age range 15-30 years at phase 1 and 30-45 years at phase 4) in 982-1780 participants depending on the hostility measure. Few promising areas from chromosome 14 at 99 cM (top SNPs rs3783337, rs7158754, rs3783332, rs2181102, rs7159195, rs11160570, rs941898, P values <3.9 × 10(-8) with nearest gene Enah/Vasp-like (EVL)) were found suggestively to be related to paranoia and from chromosome 7 at 86 cM (top SNPs rs802047, rs802028, rs802030, rs802026, rs802036, rs802025, rs802024, rs802032, rs802049, rs802051, P values <6.9 × 10(-7) with nearest gene CROT (carnitine O-octanoyltransferase)) to cynicism, respectively. Some shared suggestive genetic influence for both paranoia and cynicism was also found from chromosome 17 at 2.8 cM (SNPs rs12936442, rs894664, rs6502671, rs7216028) and chromosome 22 at 43 cM (SNPs rs7510759, rs7510924, rs7290560), with nearest genes RAP1 GTPase activating protein 2 (RAP1GAP2) and KIAA1644, respectively. These suggestive associations did not replicate across all measurement times, which warrants further study on these SNPs in other populations.
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196
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Roberts B, Jackson JJ, Duckworth AL, Von Culin K. Personality Measurement and Assessment in Large Panel Surveys*. Forum Health Econ Policy 2011; 14:1268. [PMID: 23503719 PMCID: PMC3595542 DOI: 10.2202/1558-9544.1268] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Personality tests are being added to large panel studies with increasing regularity, such as the Health and Retirement Study (HRS). To facilitate the inclusion and interpretation of these tests, we provide some general background on personality psychology, personality assessment, and the validity of personality tests. In this review, we provide background on definitions of personality, the strengths and weaknesses of the self-report approaches to personality testing typically used in large panel studies, and the validity of personality tests for three outcomes: genetics, income, and health. We conclude with recommendations on how to improve personality assessment in future panel studies.
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