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Howrigan DP, Simonson MA, Davies G, Harris SE, Tenesa A, Starr JM, Liewald DC, Deary IJ, McRae A, Wright MJ, Montgomery GW, Hansell N, Martin NG, Payton A, Horan M, Ollier WE, Abdellaoui A, Boomsma DI, DeRosse P, Knowles EEM, Glahn DC, Djurovic S, Melle I, Andreassen OA, Christoforou A, Steen VM, Hellard SL, Sundet K, Reinvang I, Espeseth T, Lundervold AJ, Giegling I, Konte B, Hartmann AM, Rujescu D, Roussos P, Giakoumaki S, Burdick KE, Bitsios P, Donohoe G, Corley RP, Visscher PM, Pendleton N, Malhotra AK, Neale BM, Lencz T, Keller MC. Genome-wide autozygosity is associated with lower general cognitive ability. Mol Psychiatry 2016; 21:837-43. [PMID: 26390830 PMCID: PMC4803638 DOI: 10.1038/mp.2015.120] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Revised: 05/23/2015] [Accepted: 07/13/2015] [Indexed: 01/12/2023]
Abstract
Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.
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Affiliation(s)
- D P Howrigan
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Genetics, Broad Institute of Harvard and MIT, Cambridge Center, Cambridge, MA, USA
| | - M A Simonson
- Division of Data Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - G Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - A Tenesa
- Institute of Genetics and Molecular Medicine, MRC Human Genetics Unit, Western General Hospital, University of Edinburgh, Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, UK
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A McRae
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - G W Montgomery
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N Hansell
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - A Payton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - M Horan
- Centre for Clinical and Cognitive Neurosciences, Institute of Brain Behaviour and Mental Health, University of Manchester, Salford Royal NHS Foundation Trust, Salford, UK
| | - W E Ollier
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - A Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, The Netherlands
| | - P DeRosse
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Hofstra North Shore - LIJ School of Medicine, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA
| | - E E M Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - D C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - S Djurovic
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Oslo University Hospital, Oslo, Norway
| | - I Melle
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Oslo University Hospital, Oslo, Norway
- University of Oslo, Oslo, Norway
| | - O A Andreassen
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Oslo University Hospital, Oslo, Norway
- University of Oslo, Oslo, Norway
| | - A Christoforou
- K.G. Jebsen Centre for Psychosis Research, Dr. Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - V M Steen
- K.G. Jebsen Centre for Psychosis Research, Dr. Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - S L Hellard
- K.G. Jebsen Centre for Psychosis Research, Dr. Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - K Sundet
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - T Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway
| | - A J Lundervold
- K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Kavli Research Centre for Aging and Dementia, Haraldsplass Deaconess Hospital, Bergen, Norway
| | - I Giegling
- Department of Psychiatry, University of Halle, Halle, Germany
| | - B Konte
- Department of Psychiatry, University of Halle, Halle, Germany
| | - A M Hartmann
- Department of Psychiatry, University of Halle, Halle, Germany
| | - D Rujescu
- Department of Psychiatry, University of Halle, Halle, Germany
| | - P Roussos
- Department of Psychiatry, Friedman Brain Institute, Department of Genetics and Genomic Sciences, and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Mental Illness Research Education and Clinical Center (MIRECC), Bronx, NY, USA
| | - S Giakoumaki
- Department of Psychology, University of Crete, Rethymno, Crete, Greece
| | - K E Burdick
- Department of Psychiatry, Friedman Brain Institute, Department of Genetics and Genomic Sciences, and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - P Bitsios
- Department of Psychiatry, Faculty of Medicine, University of Crete, Heraklion, Crete, Greece
- Computational Medicine Laboratory, Institute of Computer Science at FORTH, Heraklion, Greece
| | - G Donohoe
- School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - R P Corley
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - P M Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - N Pendleton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - A K Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Hofstra North Shore - LIJ School of Medicine, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA
| | - B M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Genetics, Broad Institute of Harvard and MIT, Cambridge Center, Cambridge, MA, USA
| | - T Lencz
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Hofstra North Shore - LIJ School of Medicine, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA
| | - M C Keller
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
- Department of Psychology, University of Colorado at Boulder, Boulder, CO, USA
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2
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Clarke TK, Lupton MK, Fernandez-Pujals AM, Starr J, Davies G, Cox S, Pattie A, Liewald DC, Hall LS, MacIntyre DJ, Smith BH, Hocking LJ, Padmanabhan S, Thomson PA, Hayward C, Hansell NK, Montgomery GW, Medland SE, Martin NG, Wright MJ, Porteous DJ, Deary IJ, McIntosh AM. Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population. Mol Psychiatry 2016; 21:419-25. [PMID: 25754080 PMCID: PMC4759203 DOI: 10.1038/mp.2015.12] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Revised: 11/25/2014] [Accepted: 12/19/2014] [Indexed: 12/16/2022]
Abstract
Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people with ASD compared with controls, but consistent evidence is lacking. Few studies have examined the genetic overlap between cognitive ability and ASD/ADHD. The aim of this study was to examine the polygenic overlap between ASD/ADHD and cognitive ability in individuals from the general population. Polygenic risk for ADHD and ASD was calculated from genome-wide association studies of ASD and ADHD conducted by the Psychiatric Genetics Consortium. Risk scores were created in three independent cohorts: Generation Scotland Scottish Family Health Study (GS:SFHS) (n=9863), the Lothian Birth Cohorts 1936 and 1921 (n=1522), and the Brisbane Adolescent Twin Sample (BATS) (n=921). We report that polygenic risk for ASD is positively correlated with general cognitive ability (beta=0.07, P=6 × 10(-7), r(2)=0.003), logical memory and verbal intelligence in GS:SFHS. This was replicated in BATS as a positive association with full-scale intelligent quotient (IQ) (beta=0.07, P=0.03, r(2)=0.005). We did not find consistent evidence that polygenic risk for ADHD was associated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=-0.08, Z=-3.3, P=0.001) was observed in the Lothian Birth Cohorts. These findings are in individuals from the general population, suggesting that the relationship between genetic risk for ASD and intelligence is partly independent of clinical state. These data suggest that common genetic variation relevant for ASD influences general cognitive ability.
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Affiliation(s)
- T-K Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK,Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK. E-mail:
| | - M K Lupton
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - J Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - S Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - L S Hall
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - D J MacIntyre
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - B H Smith
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - L J Hocking
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - S Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - P A Thomson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK,Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - C Hayward
- Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,MRC Human Genetics, MRC IGMM, University of Edinburgh, Edinburgh, Scotland, UK
| | - N K Hansell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - G W Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - S E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - N G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - M J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - D J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK,Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,MRC Human Genetics, MRC IGMM, University of Edinburgh, Edinburgh, Scotland, UK,Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK,Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,MRC Human Genetics, MRC IGMM, University of Edinburgh, Edinburgh, Scotland, UK,Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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3
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Rentería ME, Hansell NK, Strike LT, McMahon KL, de Zubicaray GI, Hickie IB, Thompson PM, Martin NG, Medland SE, Wright MJ. Genetic architecture of subcortical brain regions: common and region-specific genetic contributions. Genes Brain Behav 2014; 13:821-30. [PMID: 25199620 DOI: 10.1111/gbb.12177] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Revised: 09/01/2014] [Accepted: 09/07/2014] [Indexed: 11/27/2022]
Abstract
Understanding the aetiology of patterns of variation within and covariation across brain regions is key to advancing our understanding of the functional, anatomical and developmental networks of the brain. Here we applied multivariate twin modelling and principal component analysis (PCA) to investigate the genetic architecture of the size of seven subcortical regions (caudate nucleus, thalamus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens) in a genetically informative sample of adolescents and young adults (N = 1038; mean age = 21.6 ± 3.2 years; including 148 monozygotic and 202 dizygotic twin pairs) from the Queensland Twin IMaging (QTIM) study. Our multivariate twin modelling identified a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In addition, we also found substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52). This provides further insight into the extent and organization of subcortical genetic architecture, which includes developmental and general growth pathways, as well as the functional specialization and maturation trajectories that influence each subcortical region.
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Affiliation(s)
- M E Rentería
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia; School of Psychology, University of Queensland, St Lucia, QLD, Australia
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4
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Benyamin B, Pourcain BS, Davis OS, Davies G, Hansell NK, Brion MJA, Kirkpatrick RM, Cents RAM, Franić S, Miller MB, Haworth CMA, Meaburn E, Price TS, Evans DM, Timpson N, Kemp J, Ring S, McArdle W, Medland SE, Yang J, Harris SE, Liewald DC, Scheet P, Xiao X, Hudziak JJ, de Geus EJC, Jaddoe VWV, Starr JM, Verhulst FC, Pennell C, Tiemeier H, Iacono WG, Palmer LJ, Montgomery GW, Martin NG, Boomsma DI, Posthuma D, McGue M, Wright MJ, Smith GD, Deary IJ, Plomin R, Visscher PM. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol Psychiatry 2014; 19:253-8. [PMID: 23358156 PMCID: PMC3935975 DOI: 10.1038/mp.2012.184] [Citation(s) in RCA: 167] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Revised: 10/28/2012] [Accepted: 11/12/2012] [Indexed: 01/11/2023]
Abstract
Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.
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Affiliation(s)
- B Benyamin
- The University of Queensland, Queensland Brain Institute, St Lucia, Queensland, Australia
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - BSt Pourcain
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - OS Davis
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - G Davies
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - NK Hansell
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - M-JA Brion
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
- School of Women's and Infants' Health, The University of Western Australia, Perth, Western Australia, Australia
| | - RM Kirkpatrick
- Department of Psychology, University of Minnesota, St Paul, MN, USA
| | - RAM Cents
- The Generation R Study Group, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - S Franić
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - MB Miller
- Department of Psychology, University of Minnesota, St Paul, MN, USA
| | - CMA Haworth
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - E Meaburn
- Department of Psychology, Birkbeck University of London, London, UK
| | - TS Price
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - DM Evans
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - N Timpson
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - J Kemp
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - S Ring
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - W McArdle
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - SE Medland
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - J Yang
- The University of Queensland Diamantina Institute, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - SE Harris
- Molecular Medicine Centre, Institute for Genetics and Molecular Medicine Centre, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - DC Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - P Scheet
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - X Xiao
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - JJ Hudziak
- Department of Psychiatry, College of Medicine, University of Vermont, Burlington, VT, USA
| | - EJC de Geus
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - VWV Jaddoe
- The Generation R Study Group, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - JM Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - FC Verhulst
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - C Pennell
- School of Women's and Infants' Health, The University of Western Australia, Perth, Western Australia, Australia
| | - H Tiemeier
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - WG Iacono
- Department of Psychology, University of Minnesota, St Paul, MN, USA
| | - LJ Palmer
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research, University of Toronto, Toronto, Ontario, Canada
- Samuel Lunenfeld Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - GW Montgomery
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - NG Martin
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - DI Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - D Posthuma
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Neuroscience Campus Amsterdam (NCA), VU University Amsterdam and VU Medical Centre, Amsterdam, The Netherlands
- Department of Clinical Genetics, Section Medical Genomics, VU Medical Centre, Amsterdam, The Netherlands
| | - M McGue
- Department of Psychology, University of Minnesota, St Paul, MN, USA
- Department of Epidemiology, University of Southern Denmark, Odense, Denmark
| | - MJ Wright
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - G Davey Smith
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - IJ Deary
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - R Plomin
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - PM Visscher
- The University of Queensland, Queensland Brain Institute, St Lucia, Queensland, Australia
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
- The University of Queensland Diamantina Institute, Princess Alexandra Hospital, Brisbane, Queensland, Australia
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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5
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Hill WD, Davies G, van de Lagemaat LN, Christoforou A, Marioni RE, Fernandes CPD, Liewald DC, Croning MDR, Payton A, Craig LCA, Whalley LJ, Horan M, Ollier W, Hansell NK, Wright MJ, Martin NG, Montgomery GW, Steen VM, Le Hellard S, Espeseth T, Lundervold AJ, Reinvang I, Starr JM, Pendleton N, Grant SGN, Bates TC, Deary IJ. Human cognitive ability is influenced by genetic variation in components of postsynaptic signalling complexes assembled by NMDA receptors and MAGUK proteins. Transl Psychiatry 2014; 4:e341. [PMID: 24399044 PMCID: PMC3905224 DOI: 10.1038/tp.2013.114] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2013] [Revised: 09/12/2013] [Accepted: 10/21/2013] [Indexed: 12/11/2022] Open
Abstract
Differences in general cognitive ability (intelligence) account for approximately half of the variation in any large battery of cognitive tests and are predictive of important life events including health. Genome-wide analyses of common single-nucleotide polymorphisms indicate that they jointly tag between a quarter and a half of the variance in intelligence. However, no single polymorphism has been reliably associated with variation in intelligence. It remains possible that these many small effects might be aggregated in networks of functionally linked genes. Here, we tested a network of 1461 genes in the postsynaptic density and associated complexes for an enriched association with intelligence. These were ascertained in 3511 individuals (the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium) phenotyped for general cognitive ability, fluid cognitive ability, crystallised cognitive ability, memory and speed of processing. By analysing the results of a genome wide association study (GWAS) using Gene Set Enrichment Analysis, a significant enrichment was found for fluid cognitive ability for the proteins found in the complexes of N-methyl-D-aspartate receptor complex; P=0.002. Replication was sought in two additional cohorts (N=670 and 2062). A meta-analytic P-value of 0.003 was found when these were combined with the CAGES consortium. The results suggest that genetic variation in the macromolecular machines formed by membrane-associated guanylate kinase (MAGUK) scaffold proteins and their interaction partners contributes to variation in intelligence.
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Affiliation(s)
- W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, Edinburgh, UK
| | - L N van de Lagemaat
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - A Christoforou
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - C P D Fernandes
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M D R Croning
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - A Payton
- Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK
| | - L C A Craig
- Public Health Nutrition Research Group Section of Population Health, University of Aberdeen, Aberdeen, UK
| | - L J Whalley
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - M Horan
- Centre for Clinical and Cognitive Neurosciences, Institute Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - W Ollier
- Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK
| | - N K Hansell
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - N G Martin
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - G W Montgomery
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - V M Steen
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - S Le Hellard
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - T Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway,KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway,Kavli Research Centre for Aging and Dementia, Haraldplass Hospital, Bergen, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - N Pendleton
- Centre for Clinical and Cognitive Neurosciences, Institute Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - S G N Grant
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - T C Bates
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK. E-mail:
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Luciano M, Evans DM, Hansell NK, Medland SE, Montgomery GW, Martin NG, Wright MJ, Bates TC. A genome-wide association study for reading and language abilities in two population cohorts. Genes Brain Behav 2013; 12:645-52. [PMID: 23738518 PMCID: PMC3908370 DOI: 10.1111/gbb.12053] [Citation(s) in RCA: 82] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2012] [Revised: 03/04/2013] [Accepted: 05/24/2013] [Indexed: 01/21/2023]
Abstract
Candidate genes have been identified for both reading and language, but most of the heritable variance in these traits remains unexplained. Here, we report a genome-wide association meta-analysis of two large cohorts: population samples of Australian twins and siblings aged 12–25 years (n = 1177 from 538 families), and a younger cohort of children of the UK Avon Longitudinal Study of Parents and their Children (aged 8 and 9 years; maximum n = 5472). Suggestive association was indicated for reading measures and non-word repetition (NWR), with the greatest support found for single nucleotide polymorphisms (SNPs) in the pseudogene, ABCC13 (P = 7.34 × 10−8), and the gene, DAZAP1 (P = 1.32 × 10−6). Gene-based analyses showed significant association (P < 2.8 × 10−6) for reading and spelling with genes CD2L1, CDC2L2 and RCAN3 in two loci on chromosome 1. Some support was found for the same SNPs having effects on both reading skill and NWR, which is compatible with behavior genetic evidence for influences of reading acquisition on phonological-task performance. The results implicate novel candidates for study in additional cohorts for reading and language abilities.
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Affiliation(s)
- M Luciano
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK.
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7
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Hansell NK, Wright MJ, Medland SE, Davenport TA, Wray NR, Martin NG, Hickie IB. Genetic co-morbidity between neuroticism, anxiety/depression and somatic distress in a population sample of adolescent and young adult twins. Psychol Med 2012; 42:1249-1260. [PMID: 22051348 DOI: 10.1017/s0033291711002431] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Genetic studies in adults indicate that genes influencing the personality trait of neuroticism account for substantial genetic variance in anxiety and depression and in somatic health. Here, we examine for the first time the factors underlying the relationship between neuroticism and anxiety/depressive and somatic symptoms during adolescence. METHOD The Somatic and Psychological Health Report (SPHERE) assessed symptoms of anxiety/depression (PSYCH-14) and somatic distress (SOMA-10) in 2459 adolescent and young adult twins [1168 complete pairs (35.4% monozygotic, 53% female)] aged 12-25 years (mean=15.5 ± 2.9). Differences between boys and girls across adolescence were explored for neuroticism, SPHERE-34, and the subscales PSYCH-14 and SOMA-10. Trivariate analyses partitioned sources of covariance in neuroticism, PSYCH-14 and SOMA-10. RESULTS Girls scored higher than boys on both neuroticism and SPHERE, with SPHERE scores for girls increasing slightly over time, whereas scores for boys decreased or were unchanged. Neuroticism and SPHERE scores were strongly influenced by genetic factors [heritability (h(2)) = 40-52%]. A common genetic source influenced neuroticism, PSYCH-14 and SOMA-10 (impacting PSYCH-14 more than SOMA-10). A further genetic source, independent of neuroticism, accounted for covariation specific to PSYCH-14 and SOMA-10. Environmental influences were largely specific to each measure. CONCLUSIONS In adolescence, genetic risk factors indexed by neuroticism contribute substantially to anxiety/depression and, to a lesser extent, perceived somatic health. Additional genetic covariation between anxiety/depressive and somatic symptoms, independent of neuroticism, had greatest influence on somatic distress, where it was equal in influence to the factor shared with neuroticism.
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Affiliation(s)
- N K Hansell
- Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia
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8
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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: 93] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Hansell NK, James MR, Duffy DL, Birley AJ, Luciano M, Geffen GM, Wright MJ, Montgomery GW, Martin NG. Effect of the BDNF V166M polymorphism on working memory in healthy adolescents. Genes Brain Behav 2007; 6:260-8. [PMID: 16848784 DOI: 10.1111/j.1601-183x.2006.00254.x] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Brain-derived neurotrophic factor (BDNF) may play a role in modulating memory function and there is growing evidence that the BDNF V166M polymorphism may influence episodic memory in humans. However, previous association studies examining this polymorphism and working memory are inconsistent. The current study examined this association in a large sample of adolescent twin-pairs and siblings (785 individuals from 439 families). A range of measures (event-related potential, general performance and reaction time) was obtained from a delayed-response working-memory task and total association was examined using the quantitative transmission disequilibrium tests (QTDT) program. Analyses had approximately 93-97% power (alpha= 0.05) to detect an association accounting for as little as 2% of the variance in the phenotypes examined. Results indicated that the BDNF V166M polymorphism is not associated with variation in working memory in healthy adolescents.
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Affiliation(s)
- N K Hansell
- Genetic Epidemiology, Queensland Institute of Medical Research, University of Queensland, Brisbane, Australia.
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10
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Hansell NK, Wright MJ, Luciano M, Geffen GM, Geffen LB, Martin NG. Genetic covariation between event-related potential (ERP) and behavioral non-ERP measures of working-memory, processing speed, and IQ. Behav Genet 2006; 35:695-706. [PMID: 16273318 DOI: 10.1007/s10519-005-6188-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2004] [Accepted: 06/01/2005] [Indexed: 10/25/2022]
Abstract
The aim of this study was to identify genetic covariants for fundamental measures of brain function (event-related potentials (ERPs): P300 latency and slow wave amplitude recorded in a working-memory task) and more complex cognitive measures (behavioral non-ERP measures: working-memory performance, information processing speed, IQ). Data were collected from 252 monozygotic and 297 dizygotic twin pairs aged 16. Multivariate modeling identified two independent genetic factors associated with processing speed that also influenced working-memory performance (one reflected the duration of neural activity required to evaluate target information, the other reflected more general cognitive and speed-related abilities). However, the allocation of neural resources, as assessed by ERP slow wave amplitude measures, was not associated with the other cognitive measures investigated. Thus, of the ERP measures examined, P300 latency, but not slow wave amplitude, may be an informative measure to include (i.e., with working-memory performance) in future multivariate linkage and association analyses of cognitive function.
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Affiliation(s)
- N K Hansell
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Royal Brisbane Hospital, Post Office, Brisbane, Queensland 4029, Australia.
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11
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Hansell NK, Medland SE, Ferreira MAR, Geffen GM, Zhu G, Montgomery GW, Duffy DL, Wright MJ, Martin NG. Linkage Analyses of Event-Related Potential Slow Wave Phenotypes Recorded in a Working Memory Task. Behav Genet 2005; 36:29-44. [PMID: 16331531 DOI: 10.1007/s10519-005-9002-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2005] [Accepted: 06/20/2005] [Indexed: 10/25/2022]
Abstract
Working memory is an essential component of wide-ranging cognitive functions. It is a complex genetic trait probably influenced by numerous genes that individually have only a small influence. These genes may have an amplified influence on phenotypes closer to the gene action. In this study, event-related potential (ERP) phenotypes recorded during a working-memory task were collected from 656 adolescents from 299 families for whom genotypes were available. Univariate linkage analyses using the MERLIN variance-components method were conducted on slow wave phenotypes recorded at multiple sites while participants were required to remember the location of a target. Suggestive linkage (LOD > 2.2) was found on chromosomes 4, 5, 6, 10, 17, and 20. After correcting for multiple testing, suggestive linkage remained on chromosome 10. Empirical thresholds were computed for the most promising phenotypes. Those on chromosome 10 remained suggestive. A number of genes reported to regulate neural differentiation and function (i.e. NRP1, ANK3, and CHAT) were found under these linkage peaks and may influence the levels of neural activity occurring in individuals participating in a spatial working-memory task.
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Affiliation(s)
- N K Hansell
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
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Abstract
OBJECTIVE Congenital connective tissue dysfunction may partly be responsible for female pelvic organ prolapse and urinary incontinence. We undertook a heritability study to determine whether mobility of the bladder neck, one of the main determinants of stress urinary incontinence, is genetically influenced. DESIGN Heritability study using a twin model and structural equation modelling. SETTING Queensland Institute of Medical Research, Brisbane, Australia. POPULATION One hundred and seventy-eight nulliparous Caucasian female twins and their sisters (46 monozygotic pairs, 24 dizygotic pairs and 38 sisters) aged 18-24 years. METHODS We performed translabial ultrasound, supine and after bladder emptying, for pelvic organ mobility. Urethral rotation and bladder neck descent were calculated using the best of three effective Valsalva manoeuvres. MAIN OUTCOME MEASURES Bladder and urethral mobility on Valsalva assessed by urethral rotation, vertical and oblique bladder neck descent. RESULTS Genetic modelling indicated that additive genes accounted for up to 59% of the variance for bladder neck descent. All remaining variance appeared due to environmental influences unique to the individual, including measurement error. CONCLUSION A significant genetic contribution to the phenotype of bladder neck mobility appears likely.
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Affiliation(s)
- H P Dietz
- University of Sydney, NSW 2751, Australia
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Abstract
The P3(00) event-related potential (ERP) component is widely used as a measure of cognitive functioning and provides a sensitive electrophysiological index of the attentional and working memory demands of a task. This study investigated what proportion of the variance in the amplitude and latency of the P3, elicited in a delayed response working memory task, could be attributed to genetic factors. In 335 adolescent twin pairs and 48 siblings, the amplitude and latency of the P3 were examined at frontal, central, and parietal sites. Additive genetic factors accounted for 48% to 61% of the variance in P3 amplitude. Approximately one-third of the genetic variation at frontal sites was mediated by a common genetic factor that also influenced the genetic variation at parietal and central sites. Familial resemblance in P3 latency was due to genetic influence that accounted for 44% to 50% of the variance. Genetic covariance in P3 latency across sites was substantial, with a large part of the variance found at parietal, central, and frontal sites attributed to a common genetic factor. The findings provide further evidence that the P3 is a promising phenotype of neural activity of the brain and has the potential to be used in linkage and association analysis in the search for quantitative trait loci (QTLs) influencing cognition.
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Affiliation(s)
- M J Wright
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Royal Brisbane Hospital, Australia.
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14
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Abstract
Individual differences in the variance of event-related potential (ERP) slow wave (SW) measures were examined. SW was recorded at prefrontal and parietal sites during memory and sensory trials of a delayed-response task in 391 adolescent twin pairs. Familial resemblance was identified and there was a strong suggestion of genetic influence. A common genetic factor influencing memory and sensory SW was identified at the prefrontal site (accounting for an estimated 35%-37% of the reliable variance) and at the parietal site (51%-52% of the reliable variance). Remaining reliable variance was influenced by unique environmental factors. Measurement error accounted for 24% to 30% of the total variance of each variable. The results show genetic independence for recording site, but not trial type, and suggest that the genetic factors identified relate more directly to brain structures, as defined by the cognitive functions they support, than to the cognitive networks that link them.
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Affiliation(s)
- N K Hansell
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Royal Brisbane Hospital, Australia.
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Wright M, De Geus E, Ando J, Luciano M, Posthuma D, Ono Y, Hansell N, Van Baal C, Hiraishi K, Hasegawa T, Smith G, Geffen G, Geffen L, Kanba S, Miyake A, Martin N, Boomsma D. Genetics of cognition: outline of a collaborative twin study. Twin Res 2001; 4:48-56. [PMID: 11665325 DOI: 10.1375/1369052012146] [Citation(s) in RCA: 62] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
A multidisciplinary collaborative study examining cognition in a large sample of twins is outlined. A common experimental protocol and design is used in The Netherlands, Australia and Japan to measure cognitive ability using traditional IQ measures (i.e., psychometric IQ), processing speed (e.g., reaction time [RT] and inspection time [IT]), and working memory (e.g., spatial span, delayed response [DR] performance). The main aim is to investigate the genetic covariation among these cognitive phenotypes in order to use the correlated biological markers in future linkage and association analyses to detect quantitative-trait loci (QTLs). We outline the study and methodology, and report results from our preliminary analyses that examines the heritability of processing speed and working memory indices, and their phenotypic correlation with IQ. Heritability of Full Scale IQ was 87% in the Netherlands, 83% in Australia, and 71% in Japan. Heritability estimates for processing speed and working memory indices ranged from 33-64%. Associations of IQ with RT and IT (-0.28 to -0.36) replicated previous findings with those of higher cognitive ability showing faster speed of processing. Similarly, significant correlations were indicated between IQ and the spatial span working memory task (storage [0.31], executive processing [0.37]) and the DR working memory task (0.25), with those of higher cognitive ability showing better memory performance. These analyses establish the heritability of the processing speed and working memory measures to be used in our collaborative twin study of cognition, and support the findings that individual differences in processing speed and working memory may underlie individual differences in psychometric IQ.
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Affiliation(s)
- M Wright
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia.
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Hansell N. Approaching long-term neuroleptic treatment of schizophrenia. JAMA 1979; 242:1293-4. [PMID: 39181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Neuroleptic therapy can prevent some acute episodes and may improve the level of function in some cases of chronic schizophrenia. The hazards of tardive dyskinesia require a rigorous design for any long-term use of neuroleptics. The protocol includes narrow indications, demonstrations of efficacy and necessity, and arrangements for surveillance, cooperation, and emergency. Patient instruction improves the precision of medication use and may increase adaptive efforts during episodes.
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Abstract
Mental health services in the 1960s reflected then-current beliefs in the effectiveness of crisis-oriented services and broad social programming to treat and even prevent serious mental disorders. The result was an unwarranted emphasis on the single-episode user of services and lack of interest in patients such as schizophrenics who needed repeated services. Numerous more recent studies indicate that many cases of schizophrenia have a heritable biological component and respond well to neuroleptic medication. For effective out patient treatment of schizophrenics who might otherwise be repeated users of hospital service, the author advocates a program of continuous, or nearly continuous, neuroleptic medication, combined with counseling and social and crisis services. The patient would be educated to take a role in self-regulation of medication, within a prescribed range, which would appear to improve safety, precision, and reliability.
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Abstract
The authors discuss the treatment of 575 schizophrenic patients over the past 15 years. They describe a shift the patients have experiences from reliance on inpatient treatment to heavy use of outpatient services. The have found that effective outpatient treatment for these patients involves a program of nearly continuous administration of neuroleptic medication combined with counseling and social and crisis services. A major component of the outpatient management of these schizophrenic patients is the education of the patients in how to regulate their own medication within a prescribed range. This educational component appears to add a measure of precision that enhances the safety and reliability of the treatment program.
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Hansell N. Next steps for mental health service in Illinois--an assessment of several policy instruments. IMJ Ill Med J 1976; 149:241-4. [PMID: 5351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Hansell N, Benson ML. Interrupting long-term patienthood: a cohort study. From the comfort of shelter to a taste for life? Arch Gen Psychiatry 1971; 24:238-43. [PMID: 4322496 DOI: 10.1001/archpsyc.1971.01750090044006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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Hansell N, Hart DW. Local service growth: the Illinois Zone Plan. Am J Psychiatry 1970; 127:686-90. [PMID: 5491547 DOI: 10.1176/ajp.127.5.686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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Hansell N, Wodarczyk M, Visotsky HM. The mental health expediter. A review after two years of the project and one year of the expediter in action. Arch Gen Psychiatry 1968; 18:392-9. [PMID: 5645148 DOI: 10.1001/archpsyc.1968.01740040008002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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Abstract
The current phase of rapid growth in mental health services requires an increased emphasis on the systematic estimation of effectiveness. Serious evaluation requires the specification of goals in measurable categories and the setting up of a data-gathering and processing capacity. The argument is advanced that epidemiologic rates describing a variety of types of social disability need to be monitored in order to have a truly territorial description of mental health casualties.Summaries of casualty flow rates in relation to the deployment of resources can lead to useful estimates of productivity, or return-on-effort. The evaluation process has scientific, clinical, and managerial aspects.
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Affiliation(s)
- W G Smith
- Research and Evaluation Services, Illinois Department of Mental Health, 61103, Rockford, Ill
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