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Crouse JJ, Ho N, Scott J, Martin NG, Couvy-Duchesne B, Hermens DF, Parker R, Gillespie NA, Medland SE, Hickie IB. Days out of role and somatic, anxious-depressive, hypo-manic, and psychotic-like symptom dimensions in a community sample of young adults. Transl Psychiatry 2021; 11:285. [PMID: 33986245 PMCID: PMC8119948 DOI: 10.1038/s41398-021-01390-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/25/2021] [Accepted: 04/14/2021] [Indexed: 02/03/2023] Open
Abstract
Improving our understanding of the causes of functional impairment in young people is a major global challenge. Here, we investigated the relationships between self-reported days out of role and the total quantity and different patterns of self-reported somatic, anxious-depressive, psychotic-like, and hypomanic symptoms in a community-based cohort of young adults. We examined self-ratings of 23 symptoms ranging across the four dimensions and days out of role in >1900 young adult twins and non-twin siblings participating in the "19Up" wave of the Brisbane Longitudinal Twin Study. Adjusted prevalence ratios (APR) and 95% confidence intervals (95% CI) quantified associations between impairment and different symptom patterns. Three individual symptoms showed significant associations with days out of role, with the largest association for impaired concentration. When impairment was assessed according to each symptom dimension, there was a clear stepwise relationship between the total number of somatic symptoms and the likelihood of impairment, while individuals reporting ≥4 anxious-depressive symptoms or five hypomanic symptoms had greater likelihood of reporting days out of role. Furthermore, there was a stepwise relationship between the total number of undifferentiated symptoms and the likelihood of reporting days out of role. There was some suggestion of differences in the magnitude and significance of associations when the cohort was stratified according to sex, but not for age or twin status. Our findings reinforce the development of early intervention mental health frameworks and, if confirmed, support the need to consider interventions for subthreshold and/or undifferentiated syndromes for reducing disability among young people.
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Affiliation(s)
- Jacob J Crouse
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia.
| | - Nicholas Ho
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Jan Scott
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
- Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle, UK
- Diderot University, Paris, France
- Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Baptiste Couvy-Duchesne
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- ARAMIS Laboratory, Paris Brain Institute, Paris, France
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, Birtinya, Australia
| | - Richard Parker
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Virginia, USA
| | - Sarah E Medland
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Ian B Hickie
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
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Lazaroo NK, Bates TC, Hansell NK, Wright MJ, Martin NG, Luciano M. Genetic Structure of IQ, Phonemic Decoding Skill, and Academic Achievement. Front Genet 2019; 10:195. [PMID: 30949193 PMCID: PMC6436069 DOI: 10.3389/fgene.2019.00195] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 02/25/2019] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to examine whether phonemic decoding skill (deficits of which characterize dyslexia) shares genetic and/or environmental covariance with scholastic abilities independent of general intelligence. Non-word reading ability, verbal and non-verbal IQ, and standardized academic achievement (Queensland Core Skills Test; QCST) were measured in Australian twins (up to 876 twin pairs and 80 singleton twins). Multivariate genetic analysis showed the presence of a general genetic factor, likely reflecting crystallized ability, which accounted for 45-76% of phenotypic variance in QCST scores, 62% of variance in Verbal IQ, 23% of variance in Performance IQ, and 19% of variance in phonological reading ability. The phonemic decoding genetic factor (explaining 48% of variance in phonemic decoding) was negatively associated with mathematical achievement scores (0.4%). Shared effects of common environment did not explain the relationship between reading ability and academic achievement beyond those also influencing IQ. The unique environmental reading factor (accounting for 26% of variance) influenced academic abilities related to written expression. Future research will need to address whether these reading-specific genetic and unique environment relationships arise from causal effects of reading on scholastic abilities, or whether both share a common influence, such as pleiotropic genes/environmental factors.
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Affiliation(s)
- Nikita K. Lazaroo
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Timothy C. Bates
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Narelle K. Hansell
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Margaret J. Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Michelle Luciano
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
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Fernández E, Collins MO, Frank RAW, Zhu F, Kopanitsa MV, Nithianantharajah J, Lemprière SA, Fricker D, Elsegood KA, McLaughlin CL, Croning MDR, Mclean C, Armstrong JD, Hill WD, Deary IJ, Cencelli G, Bagni C, Fromer M, Purcell SM, Pocklington AJ, Choudhary JS, Komiyama NH, Grant SGN. Arc Requires PSD95 for Assembly into Postsynaptic Complexes Involved with Neural Dysfunction and Intelligence. Cell Rep 2018; 21:679-691. [PMID: 29045836 PMCID: PMC5656750 DOI: 10.1016/j.celrep.2017.09.045] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Revised: 08/03/2017] [Accepted: 09/13/2017] [Indexed: 12/12/2022] Open
Abstract
Arc is an activity-regulated neuronal protein, but little is known about its interactions, assembly into multiprotein complexes, and role in human disease and cognition. We applied an integrated proteomic and genetic strategy by targeting a tandem affinity purification (TAP) tag and Venus fluorescent protein into the endogenous Arc gene in mice. This allowed biochemical and proteomic characterization of native complexes in wild-type and knockout mice. We identified many Arc-interacting proteins, of which PSD95 was the most abundant. PSD95 was essential for Arc assembly into 1.5-MDa complexes and activity-dependent recruitment to excitatory synapses. Integrating human genetic data with proteomic data showed that Arc-PSD95 complexes are enriched in schizophrenia, intellectual disability, autism, and epilepsy mutations and normal variants in intelligence. We propose that Arc-PSD95 postsynaptic complexes potentially affect human cognitive function. TAP tag and purification of endogenous Arc protein complexes from the mouse brain PSD95 is the major Arc binding protein, and both assemble into 1.5-MDa supercomplexes PSD95 is essential for recruitment of Arc to synapses Mutations and genetic variants in Arc-PSD95 are linked to cognition
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Affiliation(s)
- Esperanza Fernández
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; KU Leuven, Center for Human Genetics and Leuven Institute for Neurodegenerative Diseases (LIND), and VIB Center for the Biology of Disease, Leuven, Belgium
| | - Mark O Collins
- Proteomic Mass Spectrometry, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK
| | - René A W Frank
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Fei Zhu
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Maksym V Kopanitsa
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Synome Ltd., Moneta Building, Babraham Research Campus, Cambridge, UK
| | - Jess Nithianantharajah
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Sarah A Lemprière
- Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - David Fricker
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Synome Ltd., Moneta Building, Babraham Research Campus, Cambridge, UK
| | - Kathryn A Elsegood
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Catherine L McLaughlin
- Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Mike D R Croning
- Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Colin Mclean
- School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh, UK
| | - J Douglas Armstrong
- School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh, UK
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, UK
| | - Giulia Cencelli
- KU Leuven, Center for Human Genetics and Leuven Institute for Neurodegenerative Diseases (LIND), and VIB Center for the Biology of Disease, Leuven, Belgium; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Claudia Bagni
- KU Leuven, Center for Human Genetics and Leuven Institute for Neurodegenerative Diseases (LIND), and VIB Center for the Biology of Disease, Leuven, Belgium; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Menachem Fromer
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Shaun M Purcell
- Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Andrew J Pocklington
- Institute of Psychological Medicine & Clinical Neurosciences, University of Cardiff, Cardiff, Wales, UK
| | - Jyoti S Choudhary
- Proteomic Mass Spectrometry, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK
| | - Noboru H Komiyama
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Seth G N Grant
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK.
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Couvy-Duchesne B, O’Callaghan V, Parker R, Mills N, Kirk KM, Scott J, Vinkhuyzen A, Hermens DF, Lind PA, Davenport TA, Burns JM, Connell M, Zietsch BP, Scott J, Wright MJ, Medland SE, McGrath J, Martin NG, Hickie IB, Gillespie NA. Nineteen and Up study (19Up): understanding pathways to mental health disorders in young Australian twins. BMJ Open 2018; 8:e018959. [PMID: 29550775 PMCID: PMC5875659 DOI: 10.1136/bmjopen-2017-018959] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
PURPOSE The Nineteen and Up study (19Up) assessed a range of mental health and behavioural problems and associated risk factors in a genetically informative Australian cohort of young adult twins and their non-twin siblings. As such, 19Up enables detailed investigation of genetic and environmental pathways to mental illness and substance misuse within the Brisbane Longitudinal Twin Sample (BLTS). PARTICIPANTS Twins and their non-twin siblings from Queensland, Australia; mostly from European ancestry. Data were collected between 2009 and 2016 on 2773 participants (age range 18-38, 57.8% female, 372 complete monozygotic pairs, 493 dizygotic pairs, 640 non-twin siblings, 403 singleton twins). FINDINGS TO DATE A structured clinical assessment (Composite International Diagnostic Interview) was used to collect lifetime prevalence of diagnostic statistical manual (4th edition) (DSM-IV) diagnoses of major depressive disorder, (hypo)mania, social anxiety, cannabis use disorder, alcohol use disorder, panic disorder and psychotic symptoms. Here, we further describe the comorbidities and ages of onset for these mental disorders. Notably, two-thirds of the sample reported one or more lifetime mental disorder.In addition, the 19Up study assessed general health, drug use, work activity, education level, personality, migraine/headaches, suicidal thoughts, attention deficit hyperactivity disorder (ADHD) symptomatology, sleep-wake patterns, romantic preferences, friendships, familial environment, stress, anorexia and bulimia as well as baldness, acne, asthma, endometriosis, joint flexibility and internet use.The overlap with previous waves of the BLTS means that 84% of the 19Up participants are genotyped, 36% imaged using multimodal MRI and most have been assessed for psychological symptoms at up to four time points. Furthermore, IQ is available for 57%, parental report of ADHD symptomatology for 100% and electroencephalography for 30%. FUTURE PLANS The 19Up study complements a phenotypically rich, longitudinal collection of environmental and psychological risk factors. Future publications will explore hypotheses related to disease onset and development across the waves of the cohort. A follow-up study at 25+years is ongoing.
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Affiliation(s)
- Baptiste Couvy-Duchesne
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Victoria O’Callaghan
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Natalie Mills
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Medicine, University of Adelaide, Adelaide, South Australia, Australia
| | - Katherine M Kirk
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jan Scott
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
- Institute of Neuroscience, Newcastle University, Newcastle, UK
| | - Anna Vinkhuyzen
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Institute of Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Daniel F Hermens
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tracey A Davenport
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Jane M Burns
- Young and Well CRC, University of Melbourne, Melbourne, Victoria, Australia
| | - Melissa Connell
- UQCCR, The University of Queensland, Brisbane, Queensland, Australia
| | - Brendan P Zietsch
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology, The University of Queensland, Brisbane, Queensland, Australia
| | - James Scott
- UQCCR, The University of Queensland, Brisbane, Queensland, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - John McGrath
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Nathan A Gillespie
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
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5
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Couvy-Duchesne B, Davenport TA, Martin NG, Wright MJ, Hickie IB. Validation and psychometric properties of the Somatic and Psychological HEalth REport (SPHERE) in a young Australian-based population sample using non-parametric item response theory. BMC Psychiatry 2017; 17:279. [PMID: 28764680 PMCID: PMC5540428 DOI: 10.1186/s12888-017-1420-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 07/04/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The Somatic and Psychological HEalth REport (SPHERE) is a 34-item self-report questionnaire that assesses symptoms of mental distress and persistent fatigue. As it was developed as a screening instrument for use mainly in primary care-based clinical settings, its validity and psychometric properties have not been studied extensively in population-based samples. METHODS We used non-parametric Item Response Theory to assess scale validity and item properties of the SPHERE-34 scales, collected through four waves of the Brisbane Longitudinal Twin Study (N = 1707, mean age = 12, 51% females; N = 1273, mean age = 14, 50% females; N = 1513, mean age = 16, 54% females, N = 1263, mean age = 18, 56% females). We estimated the heritability of the new scores, their genetic correlation, and their predictive ability in a sub-sample (N = 1993) who completed the Composite International Diagnostic Interview. RESULTS After excluding items most responsible for noise, sex or wave bias, the SPHERE-34 questionnaire was reduced to 21 items (SPHERE-21), comprising a 14-item scale for anxiety-depression and a 10-item scale for chronic fatigue (3 items overlapping). These new scores showed high internal consistency (alpha > 0.78), moderate three months reliability (ICC = 0.47-0.58) and item scalability (Hi > 0.23), and were positively correlated (phenotypic correlations r = 0.57-0.70; rG = 0.77-1.00). Heritability estimates ranged from 0.27 to 0.51. In addition, both scores were associated with later DSM-IV diagnoses of MDD, social anxiety and alcohol dependence (OR in 1.23-1.47). Finally, a post-hoc comparison showed that several psychometric properties of the SPHERE-21 were similar to those of the Beck Depression Inventory. CONCLUSIONS The scales of SPHERE-21 measure valid and comparable constructs across sex and age groups (from 9 to 28 years). SPHERE-21 scores are heritable, genetically correlated and show good predictive ability of mental health in an Australian-based population sample of young people.
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Affiliation(s)
- Baptiste Couvy-Duchesne
- Queensland Brain Institute, the University of Queensland, Brisbane, Australia. .,Centre for Advanced Imaging, the University of Queensland, Brisbane, Australia. .,Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
| | - Tracey A. Davenport
- 0000 0004 1936 834Xgrid.1013.3Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Nicholas G. Martin
- 0000 0001 2294 1395grid.1049.cGenetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Margaret J. Wright
- 0000 0000 9320 7537grid.1003.2Queensland Brain Institute, the University of Queensland, Brisbane, Australia
| | - Ian B. Hickie
- 0000 0004 1936 834Xgrid.1013.3Brain and Mind Centre, The University of Sydney, Sydney, Australia
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Bruce HA, Kochunov P, Paciga SA, Hyde CL, Chen X, Xie Z, Zhang B, Xi HS, O'Donnell P, Whelan C, Schubert CR, Bellon A, Ament SA, Shukla DK, Du X, Rowland LM, O'Neill H, Hong LE. Potassium channel gene associations with joint processing speed and white matter impairments in schizophrenia. GENES BRAIN AND BEHAVIOR 2017; 16:515-521. [PMID: 28188958 DOI: 10.1111/gbb.12372] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2016] [Revised: 01/14/2017] [Accepted: 02/07/2017] [Indexed: 12/17/2022]
Abstract
Patients with schizophrenia show decreased processing speed on neuropsychological testing and decreased white matter integrity as measured by diffusion tensor imaging, two traits shown to be both heritable and genetically associated indicating that there may be genes that influence both traits as well as schizophrenia disease risk. The potassium channel gene family is a reasonable candidate to harbor such a gene given the prominent role potassium channels play in the central nervous system in signal transduction, particularly in myelinated axons. We genotyped members of the large potassium channel gene family focusing on putatively functional single nucleotide polymorphisms (SNPs) in a population of 363 controls, 194 patients with schizophrenia spectrum disorder (SSD) and 28 patients with affective disorders with psychotic features who completed imaging and neuropsychological testing. We then performed three association analyses using three phenotypes - processing speed, whole-brain white matter fractional anisotropy (FA) and schizophrenia spectrum diagnosis. We extracted SNPs showing an association at a nominal P value of <0.05 with all three phenotypes in the expected direction: decreased processing speed, decreased FA and increased risk of SSD. A single SNP, rs8234, in the 3' untranslated region of voltage-gated potassium channel subfamily Q member 1 (KCNQ1) was identified. Rs8234 has been shown to affect KCNQ1 expression levels, and KCNQ1 levels have been shown to affect neuronal action potentials. This exploratory analysis provides preliminary data suggesting that KCNQ1 may contribute to the shared risk for diminished processing speed, diminished white mater integrity and increased risk of schizophrenia.
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Affiliation(s)
- H A Bruce
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - P Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - S A Paciga
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - C L Hyde
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - X Chen
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - Z Xie
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - B Zhang
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - H S Xi
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - P O'Donnell
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | - C Whelan
- Pfizer Inc., Worldwide Research and Development, Cambridge, MA
| | | | - A Bellon
- Department of Psychiatry, Penn State Hershey Medical Center, Hershey, PA, USA
| | - S A Ament
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - D K Shukla
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - X Du
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - L M Rowland
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - H O'Neill
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - L E Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
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7
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Common mechanisms in intelligence and development: A study of ability profiles in mental age-matched primary school children. INTELLIGENCE 2016. [DOI: 10.1016/j.intell.2016.01.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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8
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Ibrahim-Verbaas CA, Bressler J, Debette S, Schuur M, Smith AV, Bis JC, Davies G, Trompet S, Smith JA, Wolf C, Chibnik LB, Liu Y, Vitart V, Kirin M, Petrovic K, Polasek O, Zgaga L, Fawns-Ritchie C, Hoffmann P, Karjalainen J, Lahti J, Llewellyn DJ, Schmidt CO, Mather KA, Chouraki V, Sun Q, Resnick SM, Rose LM, Oldmeadow C, Stewart M, Smith BH, Gudnason V, Yang Q, Mirza SS, Jukema JW, deJager PL, Harris TB, Liewald DC, Amin N, Coker LH, Stegle O, Lopez OL, Schmidt R, Teumer A, Ford I, Karbalai N, Becker JT, Jonsdottir MK, Au R, Fehrmann RSN, Herms S, Nalls M, Zhao W, Turner ST, Yaffe K, Lohman K, van Swieten JC, Kardia SLR, Knopman DS, Meeks WM, Heiss G, Holliday EG, Schofield PW, Tanaka T, Stott DJ, Wang J, Ridker P, Gow AJ, Pattie A, Starr JM, Hocking LJ, Armstrong NJ, McLachlan S, Shulman JM, Pilling LC, Eiriksdottir G, Scott RJ, Kochan NA, Palotie A, Hsieh YC, Eriksson JG, Penman A, Gottesman RF, Oostra BA, Yu L, DeStefano AL, Beiser A, Garcia M, Rotter JI, Nöthen MM, Hofman A, Slagboom PE, Westendorp RGJ, Buckley BM, Wolf PA, Uitterlinden AG, Psaty BM, Grabe HJ, Bandinelli S, Chasman DI, Grodstein F, Räikkönen K, Lambert JC, Porteous DJ, Price JF, Sachdev PS, Ferrucci L, Attia JR, Rudan I, Hayward C, Wright AF, Wilson JF, Cichon S, Franke L, Schmidt H, Ding J, de Craen AJM, Fornage M, Bennett DA, Deary IJ, Ikram MA, Launer LJ, Fitzpatrick AL, Seshadri S, van Duijn CM, Mosley TH. GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Mol Psychiatry 2016; 21:189-197. [PMID: 25869804 PMCID: PMC4722802 DOI: 10.1038/mp.2015.37] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 01/21/2015] [Accepted: 02/11/2015] [Indexed: 01/20/2023]
Abstract
To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.
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Affiliation(s)
- CA Ibrahim-Verbaas
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - J Bressler
- Human Genetics Center, School of Public Health, University of
Texas Health Science Center at Houston, Houston, TX, USA
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Debette
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA
- Institut National de la Santé et de la Recherche
Médicale (INSERM), U897, Epidemiology and Biostatistics, University of Bordeaux,
Bordeaux, France
- Department of Neurology, Bordeaux University Hospital, Bordeaux,
France
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - M Schuur
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - AV Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik,
Iceland
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - JC Bis
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Trompet
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands
- Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - JA Smith
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - C Wolf
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - LB Chibnik
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Y Liu
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - V Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - M Kirin
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - K Petrovic
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - O Polasek
- Department of Public Health, University of Split, Split,
Croatia
| | - L Zgaga
- Department of Public Health and Primary Care, Trinity College
Dublin, Dublin, Ireland
| | - C Fawns-Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - P Hoffmann
- Institute of Neuroscience and Medicine (INM -1), Research
Center Juelich, Juelich, Germany
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - J Karjalainen
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
| | - DJ Llewellyn
- Institute of Biomedical and Clinical Sciences, University of
Exeter Medical School, Exeter, UK
| | - CO Schmidt
- Institute for Community Medicine, University Medicine
Greifswald, Greifswald, Germany
| | - KA Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
| | - V Chouraki
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - Q Sun
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - SM Resnick
- Laboratory of Behavioral Neuroscience, National Institute on
Aging, NIH, Baltimore, MD, USA
| | - LM Rose
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - C Oldmeadow
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - M Stewart
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - BH Smith
- Medical Research Institute, University of Dundee, Dundee,
UK
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik,
Iceland
| | - Q Yang
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - SS Mirza
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - JW Jukema
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands
| | - PL deJager
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - TB Harris
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - DC Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - LH Coker
- Division of Public Health Sciences and Neurology, Wake Forest
School of Medicine, Winston-Salem, NC, USA
| | - O Stegle
- Max Planck Institute for Developmental Biology, Max Planck
Institute for Intelligent Systems, Tübingen, Germany
| | - OL Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA
| | - R Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - A Teumer
- Interfaculty Institute for Genetics and Functional Genomics,
University Medicine Greifswald, Greifswald, Germany
| | - I Ford
- Robertson Center for biostatistics, University of Glasgow,
Glasgow, UK
| | - N Karbalai
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - JT Becker
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh,
PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh,
PA, USA
| | | | - R Au
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - RSN Fehrmann
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - S Herms
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - M Nalls
- Laboratory of Neurogenetics, National Institute on Aging,
Bethesda, MD, USA
| | - W Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - ST Turner
- Division of Nephrology and Hypertension, Department of Internal
Medicine, Mayo Clinic, Rochester, MN, USA
| | - K Yaffe
- Departments of Psychiatry, Neurology and Epidemiology,
University of California, San Francisco and San Francisco VA Medical Center, San Francisco,
CA, USA
| | - K Lohman
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - JC van Swieten
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - SLR Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - DS Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - WM Meeks
- Department of Medicine, Division of Geriatrics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - G Heiss
- Department of Epidemiology, Gillings School of Global Public
Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - EG Holliday
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - PW Schofield
- School of Medicine and Public Health, Faculty of Health,
University of Newcastle, Newcastle, SW, Australia
| | - T Tanaka
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - DJ Stott
- Department of Cardiovascular and Medical Sciences, University
of Glasgow, Glasgow, UK
| | - J Wang
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - P Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - AJ Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - JM Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Research Centre, Edinburgh, UK
| | - LJ Hocking
- Division of Applied Medicine, University of Aberdeen, Aberdeen,
UK
| | - NJ Armstrong
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
- Cancer Research Program, Garvan Institute of Medical Research,
Sydney, NSW, Australia
- School of Mathematics & Statistics and Prince of Wales
Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - S McLachlan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - JM Shulman
- Department of Neurology, Baylor College of Medicine, Houston,
TX, USA
- Department of Molecular and Human Genetics, The Jan and Dan
Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - LC Pilling
- Epidemiology and Public Health Group, University of Exeter
Medical School, Exeter, UK
| | | | - RJ Scott
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - NA Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - A Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus,
Cambridge, UK
- Institute for Molecular Medicine Finland (FIMM), University of
Helsinki, Helsinki, Finland
- Department of Medical Genetics, University of Helsinki and
University Central Hospital, Helsinki, Finland
| | - Y-C Hsieh
- School of Public Health, Taipei Medical University, Taipei,
Taiwan
| | - JG Eriksson
- Folkhälsan Research Centre, Helsinki, Finland
- Department of General Practice and Primary Health Care,
University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki,
Finland
- Helsinki University Central Hospital, Unit of General Practice,
Helsinki, Finland
- Vasa Central Hospital, Vasa, Finland
| | - A Penman
- Center of Biostatistics and Bioinformatics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - RF Gottesman
- Department of Neurology, Johns Hopkins University School of
Medicine, Baltimore, MD, USA
| | - BA Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - L Yu
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - AL DeStefano
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - A Beiser
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - M Garcia
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - JI Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los
Angeles, CA, USA
- Institute for Translational Genomics and Population Sciences,
Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA,
USA
- Division of Genetic Outcomes, Department of Pediatrics,
Harbor-UCLA Medical Center, Torrance, CA, USA
| | - MM Nöthen
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn,
Germany
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - PE Slagboom
- Department of Molecular Epidemiology, Leiden University Medical
Center, Leiden, The Netherlands
| | - RGJ Westendorp
- Leiden Academy of Vitality and Ageing, Leiden, The
Netherlands
| | - BM Buckley
- Department of Pharmacology and Therapeutics, University College
Cork, Cork, Ireland
| | - PA Wolf
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - AG Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
- Department of Internal Medicine, Erasmus University Medical
Center, Rotterdam, The Netherlands
| | - BM Psaty
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle,
WA, USA
- Department of Health Services, University of Washington,
Seattle, WA, USA
- Group Health Research Institute, Group Health, Seattle, WA,
USA
| | - HJ Grabe
- Department of Psychiatry and Psychotherapy, University Medicine
Greifswald, HELIOS-Hospital Stralsund, Stralsund, Germany
| | - S Bandinelli
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - DI Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - F Grodstein
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland
| | - J-C Lambert
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - DJ Porteous
- Centre for Genomic and Experimental Medicine, Institute of
Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - JF Price
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - PS Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - L Ferrucci
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - JR Attia
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - I Rudan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - AF Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - JF Wilson
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - S Cichon
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center
Juelich, Juelich, Germany
| | - L Franke
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - H Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - J Ding
- Department of Internal Medicine, Wake Forest University School
of Medicine, Winston-Salem, NC, USA
| | - AJM de Craen
- Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - M Fornage
- Institute for Molecular Medicine and Human Genetics Center,
University of Texas Health Science Center at Houston, Houston, TX, USA
| | - DA Bennett
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - IJ Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - MA Ikram
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
- Department of Radiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - LJ Launer
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - AL Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle,
WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - CM van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - TH Mosley
- Department of Medicine and Neurology, University of Mississippi
Medical Center, Jackson, MS, USA
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9
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Examining non-syndromic autosomal recessive intellectual disability (NS-ARID) genes for an enriched association with intelligence differences. INTELLIGENCE 2016; 54:80-89. [PMID: 26912939 PMCID: PMC4725222 DOI: 10.1016/j.intell.2015.11.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Two themes are emerging regarding the molecular genetic aetiology of intelligence. The first is that intelligence is influenced by many variants and those that are tagged by common single nucleotide polymorphisms account for around 30% of the phenotypic variation. The second, in line with other polygenic traits such as height and schizophrenia, is that these variants are not randomly distributed across the genome but cluster in genes that work together. Less clear is whether the very low range of cognitive ability (intellectual disability) is simply one end of the normal distribution describing individual differences in cognitive ability across a population. Here, we examined 40 genes with a known association with non-syndromic autosomal recessive intellectual disability (NS-ARID) to determine if they are enriched for common variants associated with the normal range of intelligence differences. The current study used the 3511 individuals of the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium. In addition, a text mining analysis was used to identify gene sets biologically related to the NS-ARID set. Gene-based tests indicated that genes implicated in NS-ARID were not significantly enriched for quantitative trait loci (QTL) associated with intelligence. These findings suggest that genes in which mutations can have a large and deleterious effect on intelligence are not associated with variation across the range of intelligence differences. Only three loci have been associated with intelligence. In traits such as height common variants are found in the same genes as rare variants. We hypothesise that intelligence may also follow this trend. We examine genes where rare variants can produce large deleterious effects on IQ. No enrichment was found for the non-syndromic intellectual disability gene set.
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10
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Glahn DC, Knowles EEM, Pearlson GD. Genetics of cognitive control: Implications for Nimh's research domain criteria initiative. Am J Med Genet B Neuropsychiatr Genet 2016; 171B:111-20. [PMID: 26768522 DOI: 10.1002/ajmg.b.32345] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Accepted: 06/29/2015] [Indexed: 12/31/2022]
Abstract
Cognitive control refers to a set of mental processes that modulate other cognitive and emotional systems in service of goal-directed adaptive behavior. There is growing support for the notion that cognitive control abnormalities are a central component of many of the neuropsychological deficits observed in individuals with mental illnesses, particularly those with psychotic disorders. NIMH's research domain criteria (RDoC) initiative, which is designed to develop biologically informed constructs to better understand psychopathology, designated cognitive control a construct within the cognitive systems domain. Identification of genes that influence cognitive control or its supportive brain systems will improve our understating of the RDoC construct and provide candidate genes for psychotic disorders. We examine evidence for cognitive control deficits in psychosis, determine if these measures could be useful endophenotypes, and explore work linking genetic variation to cognitive control performance. While there is a wealth of evidence to support the notion the cognitive control is a valid endophenotype for psychosis, its genetic underpinning remains ill characterized. However, existing work provides a promising foundation on which future endeavors might build. Confirming existing individual gene associations will go some way to expanding our understanding of the genetics of cognitive control, and by extension, psychotic disorders. Yet, to truly understand the molecular underpinnings of such complex traits, it may be necessary to evaluate genes in tandem, focusing not on single genes but rather on empirically derived gene sets or on functionally defined networks of genes.
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Affiliation(s)
- David C Glahn
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, Connecticut.,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Emma E M Knowles
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, Connecticut.,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Godfrey D Pearlson
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, Connecticut.,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
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11
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Gialluisi A, Newbury DF, Wilcutt EG, Olson RK, DeFries JC, Brandler WM, Pennington BF, Smith SD, Scerri TS, Simpson NH, Luciano M, Evans DM, Bates TC, Stein JF, Talcott JB, Monaco AP, Paracchini S, Francks C, Fisher SE. Genome-wide screening for DNA variants associated with reading and language traits. GENES BRAIN AND BEHAVIOR 2014; 13:686-701. [PMID: 25065397 PMCID: PMC4165772 DOI: 10.1111/gbb.12158] [Citation(s) in RCA: 76] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Revised: 07/20/2014] [Accepted: 07/24/2014] [Indexed: 01/04/2023]
Abstract
Reading and language abilities are heritable traits that are likely to share some genetic influences with each other. To identify pleiotropic genetic variants affecting these traits, we first performed a genome-wide association scan (GWAS) meta-analysis using three richly characterized datasets comprising individuals with histories of reading or language problems, and their siblings. GWAS was performed in a total of 1862 participants using the first principal component computed from several quantitative measures of reading- and language-related abilities, both before and after adjustment for performance IQ. We identified novel suggestive associations at the SNPs rs59197085 and rs5995177 (uncorrected P ≈ 10–7 for each SNP), located respectively at the CCDC136/FLNC and RBFOX2 genes. Each of these SNPs then showed evidence for effects across multiple reading and language traits in univariate association testing against the individual traits. FLNC encodes a structural protein involved in cytoskeleton remodelling, while RBFOX2 is an important regulator of alternative splicing in neurons. The CCDC136/FLNC locus showed association with a comparable reading/language measure in an independent sample of 6434 participants from the general population, although involving distinct alleles of the associated SNP. Our datasets will form an important part of on-going international efforts to identify genes contributing to reading and language skills.
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Affiliation(s)
- A Gialluisi
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
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12
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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] [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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13
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von Bastian CC, Oberauer K. Effects and mechanisms of working memory training: a review. PSYCHOLOGICAL RESEARCH 2013; 78:803-20. [PMID: 24213250 DOI: 10.1007/s00426-013-0524-6] [Citation(s) in RCA: 174] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2013] [Accepted: 10/19/2013] [Indexed: 11/29/2022]
Abstract
Can cognitive abilities such as reasoning be improved through working memory training? This question is still highly controversial, with prior studies providing contradictory findings. The lack of theory-driven, systematic approaches and (occasionally serious) methodological shortcomings complicates this debate even more. This review suggests two general mechanisms mediating transfer effects that are (or are not) observed after working memory training: enhanced working memory capacity, enabling people to hold more items in working memory than before training, or enhanced efficiency using the working memory capacity available (e.g., using chunking strategies to remember more items correctly). We then highlight multiple factors that could influence these mechanisms of transfer and thus the success of training interventions. These factors include (1) the nature of the training regime (i.e., intensity, duration, and adaptivity of the training tasks) and, with it, the magnitude of improvements during training, and (2) individual differences in age, cognitive abilities, biological factors, and motivational and personality factors. Finally, we summarize the findings revealed by existing training studies for each of these factors, and thereby present a roadmap for accumulating further empirical evidence regarding the efficacy of working memory training in a systematic way.
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Affiliation(s)
- Claudia C von Bastian
- Department of Psychology, University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Binzmühlestrasse 14/22, 8050, Zurich, Switzerland,
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14
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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 AND BEHAVIOR 2013; 12:645-52. [PMID: 23738518 PMCID: PMC3908370 DOI: 10.1111/gbb.12053] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [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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15
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McRae AF, Wright MJ, Hansell NK, Montgomery GW, Martin NG. No association between general cognitive ability and rare copy number variation. Behav Genet 2013; 43:202-7. [PMID: 23417127 DOI: 10.1007/s10519-013-9587-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2012] [Accepted: 02/06/2013] [Indexed: 11/26/2022]
Abstract
There is increasing evidence for the role of rare copy-number variation (CNV) in the development of neuropsychiatric disorders. It is likely that such variants also have an effect on the variation of cognition in what is considered the "normal" phenotypic range. The role of rare CNV (>20 KB in length; frequency <5 %) on general cognitive ability is investigated in a sample of 800 individuals (mean age = 16.5, SD = 1.2) using copy-number variants called from the Illumina 610K SNP genotyping array with the software QuantiSNP. We assessed three measures of CNV burden--total CNV length, number of CNV and average CNV length--for both deletions and duplications in combination and separately. No correlation was found between any of the measures of CNV burden and IQ, or when comparing the top and bottom 10 % of the sample for IQ, both on a genome-wide scale and at individual positions across the genome.
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Affiliation(s)
- Allan F McRae
- University of Queensland Diamantina Institute, Brisbane, QLD, Australia.
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16
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Kim HY, Hwang JY, Han BG, Lee JY, Park EK, Kim BJ, Lee SH, Kim GS, Kim SY, Koh JM. Association of ADIPOR1 polymorphisms with bone mineral density in postmenopausal Korean women. Exp Mol Med 2012; 44:394-402. [PMID: 22495003 PMCID: PMC3389078 DOI: 10.3858/emm.2012.44.6.045] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Adiponectin may affect bone through interactions with two known receptors, adiponectin receptors (ADIPOR) 1 and 2. We examined the association between polymorphisms of ADIPOR1 and ADIPOR2 and bone mineral density (BMD) in postmenopausal Korean women. Six polymorphisms in ADIPOR1 and four polymorphisms in ADIPOR2 were selected and genotyped in all study participants (n = 1,329). BMD at the lumbar spine and femur neck were measured using dual-energy X-ray absorptiometry. Lateral thoracolumbar (T4-L4) radiographs were obtained for vertebral fracture assessment and the occurrence of non-vertebral fractures examined using self-reported data. P values were adjusted for multiple testing using Bonferroni correction (Pcorr). ADIPOR1rs16850799 and rs34010966 polymorphisms were significantly associated with femur neck BMD (Pcorr = 0.036 in the dominant model; Pcorr = 0.024 and Pcorr = 0.006 in the additive and dominant models, respectively). Subjects with the rare allele of each polymorphism had lower BMD, and association of rs34010966 with BMD showed a gene dosage effect. However, ADIPOR2 single nucleotide polymorphisms and haplotypes were not associated with BMD at any site. Our results suggest that ADIPOR1 polymorphisms present a useful genetic marker for BMD in postmenopausal Korean women.
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Affiliation(s)
- Ha Young Kim
- Division of Endocrinology and Metabolism, Sanbon Medical Center, University of Wonkwang College of Medicine, Iksan, Korea
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17
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Yu CC, Furukawa M, Kobayashi K, Shikishima C, Cha PC, Sese J, Sugawara H, Iwamoto K, Kato T, Ando J, Toda T. Genome-wide DNA methylation and gene expression analyses of monozygotic twins discordant for intelligence levels. PLoS One 2012; 7:e47081. [PMID: 23082141 PMCID: PMC3474830 DOI: 10.1371/journal.pone.0047081] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2012] [Accepted: 09/11/2012] [Indexed: 01/05/2023] Open
Abstract
Human intelligence, as measured by intelligence quotient (IQ) tests, demonstrates one of the highest heritabilities among human quantitative traits. Nevertheless, studies to identify quantitative trait loci responsible for intelligence face challenges because of the small effect sizes of individual genes. Phenotypically discordant monozygotic (MZ) twins provide a feasible way to minimize the effects of irrelevant genetic and environmental factors, and should yield more interpretable results by finding epigenetic or gene expression differences between twins. Here we conducted array-based genome-wide DNA methylation and gene expression analyses using 17 pairs of healthy MZ twins discordant intelligently. ARHGAP18, related to Rho GTPase, was identified in pair-wise methylation status analysis and validated via direct bisulfite sequencing and quantitative RT-PCR. To perform expression profile analysis, gene set enrichment analysis (GSEA) between the groups of twins with higher IQ and their co-twins revealed up-regulated expression of several ribosome-related genes and DNA replication-related genes in the group with higher IQ. To focus more on individual pairs, we conducted pair-wise GSEA and leading edge analysis, which indicated up-regulated expression of several ion channel-related genes in twins with lower IQ. Our findings implied that these groups of genes may be related to IQ and should shed light on the mechanism underlying human intelligence.
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Affiliation(s)
- Chih-Chieh Yu
- Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Mari Furukawa
- Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Kazuhiro Kobayashi
- Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe University, Kobe, Japan
| | | | - Pei-Chieng Cha
- Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Jun Sese
- Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan
| | - Hiroko Sugawara
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Brain Science Institute, Saitama, Japan
| | - Kazuya Iwamoto
- Department of Molecular Psychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tadafumi Kato
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Brain Science Institute, Saitama, Japan
| | - Juko Ando
- Faculty of Letters, Keio University, Tokyo, Japan
| | - Tatsushi Toda
- Division of Neurology/Molecular Brain Science, Kobe University Graduate School of Medicine, Kobe University, Kobe, Japan
- * E-mail:
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18
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Yeh TK, Hu CY, Yeh TC, Lin PJ, Wu CH, Lee PL, Chang CY. Association of polymorphisms in BDNF, MTHFR, and genes involved in the dopaminergic pathway with memory in a healthy Chinese population. Brain Cogn 2012; 80:282-9. [PMID: 22940753 DOI: 10.1016/j.bandc.2012.06.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2010] [Revised: 06/04/2012] [Accepted: 06/11/2012] [Indexed: 11/16/2022]
Abstract
The contribution of genetic factors to the memory is widely acknowledged. Research suggests that these factors include genes involved in the dopaminergic pathway, as well as the genes for brain-derived neurotrophic factor (BDNF) and methylenetetrahydrofolate reductase (MTHFR). The activity of the products of these genes is affected by single nucleotide polymorphisms (SNPs) within the genes. This study investigates the association between memory and SNPs in genes involved in the dopaminergic pathway, as well as in the BDNF and MTHFR genes, in a sample of healthy individuals. The sample includes 134 Taiwanese undergraduate volunteers of similar cognitive ability. The Chinese versions of the Wechsler Memory Scale (WMS-III) and Wechsler Adult Intelligence Scale (WAIS-III) were employed. Our findings indicate that the BDNF Met66Val polymorphism and dopamine receptor D3 (DRD3) Ser9Gly polymorphism are associated significantly with long-term auditory memory. Further analysis detects no significant associations in the other polymorphisms and indices. Future replicated studies with larger sample sizes, and studies that consider different ethnic groups, are encouraged.
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Affiliation(s)
- Ting-Kuang Yeh
- Science Education Center and Graduate Institute of Science Education, National Taiwan Normal University, Taiwan, ROC.
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19
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The Brisbane Systems Genetics Study: genetical genomics meets complex trait genetics. PLoS One 2012; 7:e35430. [PMID: 22563384 PMCID: PMC3338511 DOI: 10.1371/journal.pone.0035430] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2011] [Accepted: 03/16/2012] [Indexed: 01/08/2023] Open
Abstract
There is growing evidence that genetic risk factors for common disease are caused by hereditary changes of gene regulation acting in complex pathways. Clearly understanding the molecular genetic relationships between genetic control of gene expression and its effect on complex diseases is essential. Here we describe the Brisbane Systems Genetics Study (BSGS), a family-based study that will be used to elucidate the genetic factors affecting gene expression and the role of gene regulation in mediating endophenotypes and complex diseases. BSGS comprises of a total of 962 individuals from 314 families, for which we have high-density genotype, gene expression and phenotypic data. Families consist of combinations of both monozygotic and dizygotic twin pairs, their siblings, and, for 72 families, both parents. A significant advantage of the inclusion of parents is improved power to disentangle environmental, additive genetic and non-additive genetic effects of gene expression and measured phenotypes. Furthermore, it allows for the estimation of parent-of-origin effects, something that has not previously been systematically investigated in human genetical genomics studies. Measured phenotypes available within the BSGS include blood phenotypes and biochemical traits measured from components of the tissue sample in which transcription levels are determined, providing an ideal test case for systems genetics approaches. We report results from an expression quantitative trait loci (eQTL) analysis using 862 individuals from BSGS to test for associations between expression levels of 17,926 probes and 528,509 SNP genotypes. At a study wide significance level approximately 15,000 associations were observed between expression levels and SNP genotypes. These associations corresponded to a total of 2,081 expression quantitative trait loci (eQTL) involving 1,503 probes. The majority of identified eQTL (87%) were located within cis-regions.
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20
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Evidence of differential allelic effects between adolescents and adults for plasma high-density lipoprotein. PLoS One 2012; 7:e35605. [PMID: 22530058 PMCID: PMC3329456 DOI: 10.1371/journal.pone.0035605] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2011] [Accepted: 03/22/2012] [Indexed: 01/22/2023] Open
Abstract
A recent meta-analysis of genome-wide association (GWA) studies identified 95 loci that influence lipid traits in the adult population and found that collectively these explained about 25–30% of heritability for each trait. Little is known about how these loci affect lipid levels in early life, but there is evidence that genetic effects on HDL- and LDL-cholesterol (HDL-C, LDL-C) and triglycerides vary with age. We studied Australian adults (N = 10,151) and adolescents (N = 2,363) who participated in twin and family studies and for whom we have lipid phenotypes and genotype information for 91 of the 95 genetic variants. Heterogeneity tests between effect sizes in adult and adolescent cohorts showed an excess of heterogeneity for HDL-C (pHet<0.05 at 5 out of 37 loci), but no more than expected by chance for LDL-C (1 out of 14 loci), or trigycerides (0 out 24). There were 2 (out of 5) with opposite direction of effect in adolescents compared to adults for HDL-C, but none for LDL-C. The biggest difference in effect size was for LDL-C at rs6511720 near LDLR, adolescents (0.021±0.033 mmol/L) and adults (0.157±0.023 mmol/L), pHet = 0.013; followed by ZNF664 (pHet = 0.018) and PABPC4 (pHet = 0.034) for HDL-C. Our findings suggest that some of the previously identified variants associate differently with lipid traits in adolescents compared to adults, either because of developmental changes or because of greater interactions with environmental differences in adults.
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Coolen MW, Statham AL, Qu W, Campbell MJ, Henders AK, Montgomery GW, Martin NG, Clark SJ. Impact of the genome on the epigenome is manifested in DNA methylation patterns of imprinted regions in monozygotic and dizygotic twins. PLoS One 2011; 6:e25590. [PMID: 21991322 PMCID: PMC3184992 DOI: 10.1371/journal.pone.0025590] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2011] [Accepted: 09/06/2011] [Indexed: 01/13/2023] Open
Abstract
One of the best studied read-outs of epigenetic change is the differential expression of imprinted genes, controlled by differential methylation of imprinted control regions (ICRs). To address the impact of genotype on the epigenome, we performed a detailed study in 128 pairs of monozygotic (MZ) and 128 pairs of dizygotic (DZ) twins, interrogating the DNA methylation status of the ICRs of IGF2, H19, KCNQ1, GNAS and the non-imprinted gene RUNX1. While we found a similar overall pattern of methylation between MZ and DZ twins, we also observed a high degree of variability in individual CpG methylation levels, notably at the H19/IGF2 loci. A degree of methylation plasticity independent of the genome sequence was observed, with both local and regional CpG methylation changes, discordant between MZ and DZ individual pairs. However, concordant gains or losses of methylation, within individual twin pairs were more common in MZ than DZ twin pairs, indicating that de novo and/or maintenance methylation is influenced by the underlying DNA sequence. Specifically, for the first time we showed that the rs10732516 [A] polymorphism, located in a critical CTCF binding site in the H19 ICR locus, is strongly associated with increased hypermethylation of specific CpG sites in the maternal H19 allele. Together, our results highlight the impact of the genome on the epigenome and demonstrate that while DNA methylation states are tightly maintained between genetically identical and related individuals, there remains considerable epigenetic variation that may contribute to disease susceptibility.
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Affiliation(s)
- Marcel W. Coolen
- Epigenetics Research Group, Cancer Program, Garvan Institute of Medical Research, Sydney, Australia
- Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Aaron L. Statham
- Epigenetics Research Group, Cancer Program, Garvan Institute of Medical Research, Sydney, Australia
| | - Wenjia Qu
- Epigenetics Research Group, Cancer Program, Garvan Institute of Medical Research, Sydney, Australia
| | - Megan J. Campbell
- Genetic and Molecular Epidemiology Laboratories, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Anjali K. Henders
- Genetic and Molecular Epidemiology Laboratories, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Grant W. Montgomery
- Genetic and Molecular Epidemiology Laboratories, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Nick G. Martin
- Genetic and Molecular Epidemiology Laboratories, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Susan J. Clark
- Epigenetics Research Group, Cancer Program, Garvan Institute of Medical Research, Sydney, Australia
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia
- * E-mail:
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22
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Middelberg RPS, Ferreira MAR, Henders AK, Heath AC, Madden PAF, Montgomery GW, Martin NG, Whitfield JB. Genetic variants in LPL, OASL and TOMM40/APOE-C1-C2-C4 genes are associated with multiple cardiovascular-related traits. BMC MEDICAL GENETICS 2011; 12:123. [PMID: 21943158 PMCID: PMC3189113 DOI: 10.1186/1471-2350-12-123] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2011] [Accepted: 09/24/2011] [Indexed: 01/24/2023]
Abstract
BACKGROUND Genome-wide association studies (GWAS) have become a major strategy for genetic dissection of human complex diseases. Analysing multiple phenotypes jointly may improve both our ability to detect genetic variants with multiple effects and our understanding of their common features. Allelic associations for multiple biochemical traits (serum alanine aminotransferase, aspartate aminotransferase, butrylycholinesterase (BCHE), C-reactive protein (CRP), ferritin, gamma glutamyltransferase (GGT), glucose, high-density lipoprotein cholesterol (HDL), insulin, low-density lipoprotein cholesterol (LDL), triglycerides and uric acid), and body-mass index, were examined. METHODS We aimed to identify common genetic variants affecting more than one of these traits using genome-wide association analysis in 2548 adolescents and 9145 adults from 4986 Australian twin families. Multivariate and univariate associations were performed. RESULTS Multivariate analyses identified eight loci, and univariate association analyses confirmed two loci influencing more than one trait at p < 5 × 10-8. These are located on chromosome 8 (LPL gene affecting HDL and triglycerides) and chromosome 19 (TOMM40/APOE-C1-C2-C4 gene cluster affecting LDL and CRP). A locus on chromosome 12 (OASL gene) showed effects on GGT, LDL and CRP. The loci on chromosomes 12 and 19 unexpectedly affected LDL cholesterol and CRP in opposite directions. CONCLUSIONS We identified three possible loci that may affect multiple traits and validated 17 previously-reported loci. Our study demonstrated the usefulness of examining multiple phenotypes jointly and highlights an anomalous effect on CRP, which is increasingly recognised as a marker of cardiovascular risk as well as of inflammation.
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Affiliation(s)
- Rita P S Middelberg
- Genetic Epidemiology Unit, Queensland Institute of Medical Research, Brisbane, Australia.
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Kim BJ, Kim SY, Cho YS, Kim BJ, Han BG, Park EK, Lee SH, Kim HY, Kim GS, Lee JY, Koh JM. Association of Paraoxonase 1 (PON1) polymorphisms with osteoporotic fracture risk in postmenopausal Korean women. Exp Mol Med 2011; 43:71-81. [PMID: 21187701 DOI: 10.3858/emm.2011.43.2.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
There is increasing evidence of a biochemical link between lipid oxidation and bone metabolism. Paraoxonase 1 (PON1) prevents the oxidation of low-density lipoprotein (LDL) and metabolizes biologically active phospholipids in oxidized LDLs. Here, we performed association analyses of genetic variation in PON1 to ascertain its contribution to osteoporotic fractures (OFs) and bone mineral density (BMD). We directly sequenced the PON1 gene in 24 Korean individuals and identified 26 sequence variants. A large population of Korean postmenopausal women (n=1,329) was then genotyped for eight selected PON1 polymorphisms. BMD at the lumbar spine and femoral neck was measured using dual-energy X-ray absorptiometry. Lateral thoracolumbar (T4-L4) radiographs were obtained for vertebral fracture assessment, and the occurrence of non-vertebral fractures (i.e., wrist, hip, forearm, humerus, rib, and pelvis) was examined using self-reported data. Multivariate analyses showed that none of the polymorphisms was associated with BMD at either site. However, +5989A>G and +26080T>C polymorphisms were significantly associated with non-vertebral and vertebral fractures, respectively, after adjustment for covariates. Specifically, the minor allele of +5989A>G exerted a highly protective effect against non-vertebral fractures (OR=0.59, P=0.036), whereas the minor allele of +26080T>C was associated with increased susceptibility to vertebral fractures (OR=1.73, P=0.020). When the risk for any OFs (i.e., vertebral or non-vertebral) was considered, the statistical significance of both polymorphisms persisted (P=0.002-0.010). These results suggest that PON1 polymorphisms could be one of useful genetic markers for OF risk in postmenopausal women.
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Affiliation(s)
- Beom-Jun Kim
- Division of Endocrinology and Metabolism, Asan Medical Center, University of Ulsan College of Medicine, Seoul 138-736, Korea
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Bellander M, Brehmer Y, Westerberg H, Karlsson S, Fürth D, Bergman O, Eriksson E, Bäckman L. Preliminary evidence that allelic variation in the LMX1A gene influences training-related working memory improvement. Neuropsychologia 2011; 49:1938-42. [DOI: 10.1016/j.neuropsychologia.2011.03.021] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2010] [Revised: 01/28/2011] [Accepted: 03/16/2011] [Indexed: 01/09/2023]
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25
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Li J, Chen C, Chen C, He Q, Li H, Li J, Moyzis RK, Xue G, Dong Q. Neurotensin receptor 1 gene (NTSR1) polymorphism is associated with working memory. PLoS One 2011; 6:e17365. [PMID: 21394204 PMCID: PMC3048867 DOI: 10.1371/journal.pone.0017365] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2010] [Accepted: 02/01/2011] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Recent molecular genetics studies showed significant associations between dopamine-related genes (including genes for dopamine receptors, transporters, and degradation) and working memory, but little is known about the role of genes for dopamine modulation, such as those related to neurotensin (NT), in working memory. A recent animal study has suggested that NT antagonist administration impaired working memory in a learning task. The current study examined associations between NT genes and working memory among humans. METHODS Four hundred and sixty healthy undergraduate students were assessed with a 2-back working memory paradigm. 5 SNPs in the NTSR1 gene were genotyped. 5 ANOVA tests were conducted to examine whether and how working memory differed by NTSR1 genotype, with each SNP variant as the independent variable and the average accuracy on the working memory task as the dependent variable. RESULTS ANOVA results suggested that two SNPs in the NTSR1 gene (rs4334545 and rs6090453) were significantly associated with working memory. These results survived corrections for multiple comparisons. CONCLUSIONS Our results demonstrated that NTSR1 SNP polymorphisms were significantly associated with variance in working memory performance among healthy adults. This result extended previous rodent studies showing that the NT deficiency impairs the working memory function. Future research should replicate our findings and extend to an examination of other dopamine modulators.
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Affiliation(s)
- Jin Li
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
- Department of Psychology and Social Behavior, University of California Irvine, Irvine, California, United States of America
| | - Chuansheng Chen
- Department of Psychology and Social Behavior, University of California Irvine, Irvine, California, United States of America
| | - Chunhui Chen
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
| | - Qinghua He
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
- Department of Psychology, University of Southern California, Los Angeles, California, United States of America
| | - He Li
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
| | - Jun Li
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
| | - Robert K. Moyzis
- Department of Biological Chemistry, University of California Irvine, Irvine, California, United States of America
| | - Gui Xue
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
- Department of Psychology, University of Southern California, Los Angeles, California, United States of America
| | - Qi Dong
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China
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Bates TC, Luciano M, Medland SE, Montgomery GW, Wright MJ, Martin NG. Genetic variance in a component of the language acquisition device: ROBO1 polymorphisms associated with phonological buffer deficits. Behav Genet 2011; 41:50-7. [PMID: 20949370 DOI: 10.1007/s10519-010-9402-9] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2010] [Accepted: 09/28/2010] [Indexed: 01/11/2023]
Abstract
The region containing ROBO1 (Chromosome 3p12.3) has been implicated as a susceptibility gene for reading disorder and language deficit by translocation and linkage data. No association studies have yet been reported supporting any candidate gene. Here we report the first association of this gene with language deficits, specifically with phonological buffer deficits (a phenotype implicated in language acquisition, Specific Language Impairment and Speech Sound Disorder) and dyslexia (reading and spelling ability traits) in an unselected sample of adolescent twins and their siblings. Family-based analyses were performed on 144 tag SNPs in ROBO1, typed in 538 families with up to five offspring and tested for association with a developmental marker of language impairment (phonological buffer capacity, assessed using non word repetition). A reading and spelling ability measure--based on validated measures of lexical processing (irregular word) and grapheme-phoneme decoding (pseudo word)--and measures of short-term and working memory were also analysed. Significant association for phonological buffer capacity was observed for 21 of 144 SNPs tested, peaking at 8.70 × 10(-05) and 9.30 × 10(-05) for SNPs rs6803202 and rs4535189 respectively for nonword repetition, values that survive correction for multiple testing. Twenty-two SNPs showed significant associations for verbal storage (forward digit span)--a trait linked to phonological span. By contrast, just 5 SNPs reached nominal significance for working-memory, not surviving correction, and, importantly, only one SNP in the 144 tested reached nominal significance (0.04) for association with reading and spelling ability. These results provide strong support for ROBO1 as a gene involved in a core trait underpinning language acquisition, with a specific function in supporting a short-term buffer for arbitrary phonological strings. These effects of ROBO1 appear to be unrelated to brain mechanisms underpinning reading ability, at least by adolescence. While replication will be critical, the present results strongly support ROBO1 as the first gene discovered to be associated with language deficits affecting normal variation in language ability. Its functional role in neuronal migration underlying bilateral symmetry and lateralization of neuronal function further suggests a role in the evolution of human language ability.
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Affiliation(s)
- Timothy C Bates
- Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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Luciano M, Hansell NK, Lahti J, Davies G, Medland SE, Räikkönen K, Tenesa A, Widen E, McGhee KA, Palotie A, Liewald D, Porteous DJ, Starr JM, Montgomery GW, Martin NG, Eriksson JG, Wright MJ, Deary IJ. Whole genome association scan for genetic polymorphisms influencing information processing speed. Biol Psychol 2010; 86:193-202. [PMID: 21130836 DOI: 10.1016/j.biopsycho.2010.11.008] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2010] [Revised: 11/19/2010] [Accepted: 11/25/2010] [Indexed: 12/22/2022]
Abstract
Processing speed is an important cognitive function that is compromised in psychiatric illness (e.g., schizophrenia, depression) and old age; it shares genetic background with complex cognition (e.g., working memory, reasoning). To find genes influencing speed we performed a genome-wide association scan in up to three cohorts: Brisbane (mean age 16 years; N = 1659); LBC1936 (mean age 70 years, N = 992); LBC1921 (mean age 82 years, N = 307), and; HBCS (mean age 64 years, N =1080). Meta-analysis of the common measures highlighted various suggestively significant (p < 1.21 × 10⁻⁵) SNPs and plausible candidate genes (e.g., TRIB3). A biological pathways analysis of the speed factor identified two common pathways from the KEGG database (cell junction, focal adhesion) in two cohorts, while a pathway analysis linked to the GO database revealed common pathways across pairs of speed measures (e.g., receptor binding, cellular metabolic process). These highlighted genes and pathways will be able to inform future research, including results for psychiatric disease.
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Affiliation(s)
- Michelle Luciano
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Scotland, UK.
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Chiang MC, McMahon KL, de Zubicaray GI, Martin NG, Hickie I, Toga AW, Wright MJ, Thompson PM. Genetics of white matter development: a DTI study of 705 twins and their siblings aged 12 to 29. Neuroimage 2010; 54:2308-17. [PMID: 20950689 DOI: 10.1016/j.neuroimage.2010.10.015] [Citation(s) in RCA: 182] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2010] [Revised: 09/18/2010] [Accepted: 10/05/2010] [Indexed: 11/15/2022] Open
Abstract
White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12-29; 290 M/415 F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 80% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity.
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Affiliation(s)
- Ming-Chang Chiang
- Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095-7332, USA
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Abstract
The kidney and brain expressed protein gene (KIBRA) and the calsyntenin 2 gene (CLSTN2) are reportedly involved in synaptic plasticity. Single nucleotide polymorphisms (SNPs) rs17070145 (KIBRA) and rs6439886 (CLSTN2) have been found to affect memory performance measures. This study examined the association of KIBRA SNP rs17070145 and CLSTN2 SNPs rs6439886 and rs17348572 (a nonsynonymous variant) with cognitive flexibility in 674 African Americans (AAs; 526 current smokers) and 419 European Americans (EAs; 318 current smokers). The subjects' cognitive flexibility was assessed using the Wisconsin Card Sorting Test. The effects on cognitive flexibility of sex, age, education, and tobacco recency (a possible mediator of gene effects in smokers), the three SNPs, and the interaction of each SNP with tobacco recency were analyzed using multivariate analysis of variance. In AAs, there were no main or interaction effects of the SNPs on cognitive flexibility. In EAs, the two CLSTN2 SNPs showed no main effect on cognitive flexibility. However, among EAs, individuals with the KIBRA rs17070145 T allele made significantly more perseverative responses (P=0.002) and perseverative errors (P=0.002) than those with no T allele. Furthermore, among EAs with the rs17070145 T allele, current smokers made significantly fewer perseverative responses (P<0.001) and perseverative errors (P<0.001) than past smokers. Nongenetic factors (age, education, and tobacco recency) had substantial effects on cognitive flexibility in both AAs and EAs. We conclude that variation in KIBRA influences cognitive flexibility in a population-specific way, and that current smoking status moderates this effect.
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Gong P, Li J, Dai L, Zhang K, Zheng Z, Gao X, Zhang F. Genetic variations in FTSJ1 influence cognitive ability in young males in the Chinese Han population. J Neurogenet 2009; 22:277-87. [PMID: 19012053 DOI: 10.1080/01677060802337299] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Human cognitive ability is a trait that is known to be significantly influenced by genetic factors. Previous linkage data provide evidence suggesting that gene FtsJ homolog 1 (Escherichia coli) is associated with mental retardation. The gene may have a relation to individual differences in cognitive ability because it is most critical for brain development. In the present research, three tag single-nucleotide polymorphism (SNPs) (rs2268954, rs2070991, and rs5905692) in FtsJ homolog 1 (E. coli) are selected and genotyped by the PCR-SSCP method. An analysis of variance is performed to determine the relationship between the SNPs and cognitive ability of the Chinese Han population of youth in Qinba mountain. There are significant correlations between the variance in FtsJ homolog 1 (E. coli) and general cognitive ability, verbal comprehension, and preceptual organization. These findings suggest that genetic variations in FtsJ homolog 1 (E. coli) possibly influence human cognitive ability.
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Affiliation(s)
- Pingyuan Gong
- School of Life Science, Institute of Population and Health, Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Ministry of Education, Xi'an, China
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Familial aggregation of clinical and neurocognitive features in sibling pairs with and without schizophrenia. Schizophr Res 2009; 111:159-66. [PMID: 19398304 PMCID: PMC2813565 DOI: 10.1016/j.schres.2009.03.030] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2008] [Revised: 03/19/2009] [Accepted: 03/20/2009] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Neurocognitive impairment was found to be heritable in individuals with schizophrenia and their relatives. However, the heritability of neurocognitive measures in families with and without schizophrenia has not been directly compared. In this study, we examined the genetic structure of clinical and neurocognitive measures in sibling pairs with and without schizophrenia to test the hypothesis that the familial aggregation of such measures may be altered by having schizophrenia. METHOD A total of 278 subjects including patients with schizophrenia and their non-psychotic full siblings, healthy controls, and their full siblings were recruited. Heritability was estimated for working memory, episodic memory, executive function and attention, as well as clinical features, such as positive, negative and disorganization symptoms. RESULTS Many clinical and cognitive domains were impaired in subjects with schizophrenia and their non psychotic siblings. Negative symptoms, working memory, episodic memory and executive function, but not positive, disorganization symptoms and attention, were found to be significantly heritable in all sibling pairs. However, the heritability of working memory function was significantly (chi(2)((d.f.=6))=13.9, p=.031) decreased in proband sibling pairs (h(2)=.38) as compared to control sibling pairs (h(2)=.95). Significant genetic correlations were observed between negative symptoms and the cluster of working memory, episodic memory and executive function. CONCLUSIONS Several neurocognitive measures were heritable in sibling pairs with and without schizophrenia. However, schizophrenia reduced the heritability of working memory, perhaps due to disease-related environmental or genetic factors. Evidence for potential pleiotropy will inform future phenotypic studies.
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Brun CC, Leporé N, Pennec X, Lee AD, Barysheva M, Madsen SK, Avedissian C, Chou YY, de Zubicaray GI, McMahon KL, Wright MJ, Toga AW, Thompson PM. Mapping the regional influence of genetics on brain structure variability--a tensor-based morphometry study. Neuroimage 2009; 48:37-49. [PMID: 19446645 DOI: 10.1016/j.neuroimage.2009.05.022] [Citation(s) in RCA: 69] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2008] [Revised: 05/04/2009] [Accepted: 05/05/2009] [Indexed: 11/29/2022] Open
Abstract
Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8+/-1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.
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Affiliation(s)
- Caroline C Brun
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive South Suite 225, Los Angeles, CA 90095-7334, USA
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Bates TC, Luciano M, Lind PA, Wright MJ, Montgomery GW, Martin NG. Recently-derived variants of brain-size genes ASPM, MCPH1, CDK5RAP and BRCA1 not associated with general cognition, reading or language. INTELLIGENCE 2008. [DOI: 10.1016/j.intell.2008.04.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Anderson CA, Zhu G, Falchi M, van den Berg SM, Treloar SA, Spector TD, Martin NG, Boomsma DI, Visscher PM, Montgomery GW. A genome-wide linkage scan for age at menarche in three populations of European descent. J Clin Endocrinol Metab 2008; 93:3965-70. [PMID: 18647812 PMCID: PMC2579643 DOI: 10.1210/jc.2007-2568] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT Age at menarche (AAM) is an important trait both biologically and socially, a clearly defined event in female pubertal development, and has been associated with many clinically significant phenotypes. OBJECTIVE The objective of the study was to identify genetic loci influencing variation in AAM in large population-based samples from three countries. DESIGN/PARTICIPANTS Recalled AAM data were collected from 13,697 individuals and 4,899 pseudoindependent sister-pairs from three different populations (Australia, The Netherlands, and the United Kingdom) by mailed questionnaire or interview. Genome-wide variance components linkage analysis was implemented on each sample individually and in combination. RESULTS The mean, sd, and heritability of AAM across the three samples was 13.1 yr, 1.5 yr, and 0.69, respectively. No loci were detected that reached genome-wide significance in the combined analysis, but a suggestive locus was detected on chromosome 12 (logarithm of the odds = 2.0). Three loci of suggestive significance were seen in the U.K. sample on chromosomes 1, 4, and 18 (logarithm of the odds = 2.4, 2.2 and 3.2, respectively). CONCLUSIONS There was no evidence for common highly penetrant variants influencing AAM. Linkage and association suggest that one trait locus for AAM is located on chromosome 12, but further studies are required to replicate these results.
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Affiliation(s)
- Carl A Anderson
- Queensland Institute of Medical Research, Royal Brisbane Hospital, Queensland 4029, Australia
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35
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Genetic influences on handedness: data from 25,732 Australian and Dutch twin families. Neuropsychologia 2008; 47:330-7. [PMID: 18824185 DOI: 10.1016/j.neuropsychologia.2008.09.005] [Citation(s) in RCA: 193] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2008] [Revised: 08/12/2008] [Accepted: 09/02/2008] [Indexed: 11/23/2022]
Abstract
Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.
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Gene-environment interaction in adults' IQ scores: measures of past and present environment. Behav Genet 2008; 38:348-60. [PMID: 18535898 PMCID: PMC2480605 DOI: 10.1007/s10519-008-9212-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2008] [Accepted: 05/22/2008] [Indexed: 11/30/2022]
Abstract
Gene-environment interaction was studied in a sample of young (mean age 26 years, N = 385) and older (mean age 49 years, N = 370) adult males and females. Full scale IQ scores (FSIQ) were analyzed using biometric models in which additive genetic (A), common environmental (C), and unique environmental (E) effects were allowed to depend on environmental measures. Moderators under study were parental and partner educational level, as well as urbanization level and mean real estate price of the participants’ residential area. Mean effects were observed for parental education, partner education and urbanization level. On average, FSIQ scores were roughly 5 points higher in participants with highly educated parents, compared to participants whose parents were less well educated. In older participants, IQ scores were about 2 points higher when their partners were highly educated. In younger males, higher urbanization levels were associated with slightly higher FSIQ scores. Our analyses also showed increased common environmental variation in older males whose parents were more highly educated, and increased unique environmental effects in older males living in more affluent areas. Contrary to studies in children, however, the variance attributable to additive genetic effects was stable across all levels of the moderators under study. Most results were replicated for VIQ and PIQ.
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Friedman NP, Miyake A, Young SE, DeFries JC, Corley RP, Hewitt JK. Individual differences in executive functions are almost entirely genetic in origin. J Exp Psychol Gen 2008; 137:201-225. [PMID: 18473654 PMCID: PMC2762790 DOI: 10.1037/0096-3445.137.2.201] [Citation(s) in RCA: 889] [Impact Index Per Article: 55.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Recent psychological and neuropsychological research suggests that executive functions--the cognitive control processes that regulate thought and action--are multifaceted and that different types of executive functions are correlated but separable. The present multivariate twin study of 3 executive functions (inhibiting dominant responses, updating working memory representations, and shifting between task sets), measured as latent variables, examined why people vary in these executive control abilities and why these abilities are correlated but separable from a behavioral genetic perspective. Results indicated that executive functions are correlated because they are influenced by a highly heritable (99%) common factor that goes beyond general intelligence or perceptual speed, and they are separable because of additional genetic influences unique to particular executive functions. This combination of general and specific genetic influences places executive functions among the most heritable psychological traits. These results highlight the potential of genetic approaches for uncovering the biological underpinnings of executive functions and suggest a need for examining multiple types of executive functions to distinguish different levels of genetic influences.
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Affiliation(s)
| | - Akira Miyake
- Department of Psychology, University of Colorado
| | - Susan E Young
- Institute for Behavioral Genetics, University of Colorado
| | - John C DeFries
- Institute for Behavioral Genetics, University of Colorado
| | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado
| | - John K Hewitt
- Institute for Behavioral Genetics, University of Colorado
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Medland SE, Loehlin JC, Martin NG. No effects of prenatal hormone transfer on digit ratio in a large sample of same- and opposite-sex dizygotic twins. PERSONALITY AND INDIVIDUAL DIFFERENCES 2008. [DOI: 10.1016/j.paid.2007.11.017] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Kremen WS, Xian H, Jacobson KC, Eaves LJ, Franz CE, Panizzon MS, Eisen SA, Crider A, Lyons MJ. Storage and executive components of working memory: integrating cognitive psychology and behavior genetics in the study of aging. J Gerontol B Psychol Sci Soc Sci 2008; 63:P84-91. [PMID: 18441269 PMCID: PMC2945700 DOI: 10.1093/geronb/63.2.p84] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We combined experimental cognitive and behavior genetic methods to investigate storage and executive components of working memory in 663 middle-aged male twins. A single latent factor model indicated that digits forward (storage) and two-digit transformation (executive + storage) scores were influenced by the same genes. Additional executive demands in digit transformation appeared to increase the variance of individual genetic differences from 25% for digits forward to 48% and 53% for the digit transformation scores. Although it was not the best model, a two-factor model also provided a good fit to the data. This model suggested the possibility of a second set of genes specifically influencing the executive component. We discuss the findings in the context of research suggesting that new genetic influences come into play if demand continues to increase beyond a certain threshold, a threshold that may change with task difficulty and with age.
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Affiliation(s)
- William S Kremen
- Department of Psychiatry, Center for Behavioral Genomics, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA, USA.
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Francks C, Maegawa S, Laurén J, Abrahams BS, Velayos-Baeza A, Medland SE, Colella S, Groszer M, McAuley EZ, Caffrey TM, Timmusk T, Pruunsild P, Koppel I, Lind PA, Matsumoto-Itaba N, Nicod J, Xiong L, Joober R, Enard W, Krinsky B, Nanba E, Richardson AJ, Riley BP, Martin NG, Strittmatter SM, Möller HJ, Rujescu D, St Clair D, Muglia P, Roos JL, Fisher SE, Wade-Martins R, Rouleau GA, Stein JF, Karayiorgou M, Geschwind DH, Ragoussis J, Kendler KS, Airaksinen MS, Oshimura M, DeLisi LE, Monaco AP. LRRTM1 on chromosome 2p12 is a maternally suppressed gene that is associated paternally with handedness and schizophrenia. Mol Psychiatry 2007; 12:1129-39, 1057. [PMID: 17667961 PMCID: PMC2990633 DOI: 10.1038/sj.mp.4002053] [Citation(s) in RCA: 227] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Left-right asymmetrical brain function underlies much of human cognition, behavior and emotion. Abnormalities of cerebral asymmetry are associated with schizophrenia and other neuropsychiatric disorders. The molecular, developmental and evolutionary origins of human brain asymmetry are unknown. We found significant association of a haplotype upstream of the gene LRRTM1 (Leucine-rich repeat transmembrane neuronal 1) with a quantitative measure of human handedness in a set of dyslexic siblings, when the haplotype was inherited paternally (P=0.00002). While we were unable to find this effect in an epidemiological set of twin-based sibships, we did find that the same haplotype is overtransmitted paternally to individuals with schizophrenia/schizoaffective disorder in a study of 1002 affected families (P=0.0014). We then found direct confirmatory evidence that LRRTM1 is an imprinted gene in humans that shows a variable pattern of maternal downregulation. We also showed that LRRTM1 is expressed during the development of specific forebrain structures, and thus could influence neuronal differentiation and connectivity. This is the first potential genetic influence on human handedness to be identified, and the first putative genetic effect on variability in human brain asymmetry. LRRTM1 is a candidate gene for involvement in several common neurodevelopmental disorders, and may have played a role in human cognitive and behavioral evolution.
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Affiliation(s)
- C Francks
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
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Medland SE, Loesch DZ, Mdzewski B, Zhu G, Montgomery GW, Martin NG. Linkage analysis of a model quantitative trait in humans: finger ridge count shows significant multivariate linkage to 5q14.1. PLoS Genet 2007; 3:1736-44. [PMID: 17907812 PMCID: PMC1994711 DOI: 10.1371/journal.pgen.0030165] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2007] [Accepted: 08/08/2007] [Indexed: 11/19/2022] Open
Abstract
The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers. Finger ridge count (an index of the size of the fingerprint pattern) has been used as a model trait for the study of human quantitative genetics for over 80 years. Here, we present the first genome-wide linkage scan for finger ridge count in a large sample of 2,114 offspring from 922 nuclear families. Our results illustrate the increase in power and information that can be gained from a multivariate linkage analysis of ridge counts of individual fingers as compared to a univariate analysis of a summary measure (absolute ridge count). The strongest evidence for linkage was seen at 5q14.1, and the pattern of loadings was consistent with a developmental field factor whose influence is greatest on the ring finger, falling off to either side, which is consistent with previous findings that heritability for ridge count is higher for the middle three fingers. We feel that the paper will be of specific methodological interest to those conducting linkage and association analyses with summary measures. In addition, given the frequency with which this phenotype is used as a didactic example in genetics courses we feel that this paper will be of interest to the general scientific community.
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Affiliation(s)
- Sarah E Medland
- Genetic Epidemiology Unit, Queensland Institute of Medical Research, Brisbane, Australia.
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Ha KS, Yoo HK, Lyoo IK, Jeong DU. Computerized assessment of cognitive impairment in narcoleptic patients. Acta Neurol Scand 2007; 116:312-6. [PMID: 17854401 DOI: 10.1111/j.1600-0404.2007.00891.x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVES - This study was aimed to investigate the comprehensive range of cognitive performance using the objective computerized assessment system in narcolepsy and age, gender, and IQ-matched healthy comparison. MATERIALS AND METHODS - The cognitive functions of 24 patients with narcolepsy and 24 healthy comparison subjects were assessed. RESULTS - Narcoleptics performed more frequent omission and commission errors in the vigilance test, and more frequent omission errors in the continuous performance test. Narcoleptics' response time was slower than healthy volunteers, and the differences were more exaggerated in more complex tasks. The simple repetitious working performance was more impaired in the narcoleptic subjects than in healthy comparison subjects. Narcolepsy group showed worse performances in the determination unit than the comparison group, and this impairment became more salient in faster stimuli relative to slower ones. CONCLUSIONS - Narcoleptics have deficits of efficiency in attention allocation and execution as well as simple vigilance problem.
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Affiliation(s)
- K S Ha
- Department of Psychiatry, Seoul National University College of Medicine, Seoul National University Bungdang Hospital, Kyeonggi, Korea
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Luciano M, Lind PA, Duffy DL, Castles A, Wright MJ, Montgomery GW, Martin NG, Bates TC. A haplotype spanning KIAA0319 and TTRAP is associated with normal variation in reading and spelling ability. Biol Psychiatry 2007; 62:811-7. [PMID: 17597587 DOI: 10.1016/j.biopsych.2007.03.007] [Citation(s) in RCA: 78] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2006] [Revised: 09/12/2006] [Accepted: 10/30/2006] [Indexed: 10/23/2022]
Abstract
BACKGROUND KIAA0319 (6p22.2) has recently been implicated as a susceptibility gene for dyslexia. We aimed to find further support for this gene by examining its association with reading and spelling ability in adolescent twins and their siblings unselected for dyslexia. METHODS Ten single nucleotide polymorphisms (SNPs) in or near the KIAA0319 gene were typed in 440 families with up to five offspring who had been tested on reading and spelling tasks. Family-based association analyses were performed, including a univariate analysis of the principal component reading and spelling score derived from the Components of Reading Examination (CORE) test battery and a bivariate analysis of whole-word reading tests measured in a slightly larger sample. RESULTS Significant association with rs2143340 (TTRAP) and rs6935076 (KIAA0319) and with a three-SNP haplotype spanning KIAA0319 and TTRAP was observed. The association with rs2143340 was found in both analyses, although the effect was in the opposite direction to that previously reported. The effect of rs6935076 on the principal component was in the same direction as past findings. Two of the three significant individual haplotypes showed effects in the opposite direction to the two prior reports. CONCLUSIONS These results suggest that a multilocus effect in or near KIAA0319 may influence variation in reading ability.
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Affiliation(s)
- Michelle Luciano
- Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia.
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Dobson-Stone C, Gatt JM, Kuan SA, Grieve SM, Gordon E, Williams LM, Schofield PR. Investigation of MCPH1 G37995C and ASPM A44871G polymorphisms and brain size in a healthy cohort. Neuroimage 2007; 37:394-400. [PMID: 17566767 DOI: 10.1016/j.neuroimage.2007.05.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2007] [Accepted: 05/13/2007] [Indexed: 11/26/2022] Open
Abstract
Loss-of-function mutations in MCPH1 and ASPM are responsible for some cases of autosomal recessive primary microcephaly. Recent studies have indicated that certain common variants of these genes have been positively selected for during the evolution of modern humans. It is therefore possible that these variants may predispose to an increase in brain size in the normal human population. We genotyped the MCPH1 G37995C and ASPM A44871G polymorphisms in a cohort of 118 healthy people who had undergone structural magnetic resonance imaging analysis. We did not detect significant association of either MCPH1 G37995C or ASPM A44871G genotype with whole brain volume, cerebral cortical volume or proportion of grey matter in this cohort. Nor did we detect an association of combined MCPH1 37995C and ASPM 44871G allele dosage with these brain measurements. These results were also confirmed in an age-restricted subcohort of 94 individuals. This study suggests that phenotypes other than brain size may have been selected for in ASPM and MCPH1 variants during evolution of modern humans.
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Affiliation(s)
- C Dobson-Stone
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia
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Wolkowitz OM, Lupien SJ, Bigler ED. The "steroid dementia syndrome": a possible model of human glucocorticoid neurotoxicity. Neurocase 2007; 13:189-200. [PMID: 17786779 DOI: 10.1080/13554790701475468] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Glucocorticoid medications cause neurotoxicity in animals under certain circumstances, but it is not known if this occurs in humans. We present the case of a 10-year-old boy with no prior psychiatric history and no prior exposure to glucocorticoid medication who received a single 5-week course of glucocorticoids for an acute asthma flare. Beginning during steroid treatment, and persisting for over 3 years after stopping treatment, he showed a significant decline from his pre-morbid academic performance and estimated IQ, verified by longitudinally administered testing and school records. Neuropsychological tests that are sensitive to glucocorticoid-induced cognitive impairments revealed global cognitive deficits consistent with primary hippocampal and prefrontal cortical dysfunction. The patient has a fraternal twin brother, who had previously achieved academic milestones in parallel with him; the patient began falling behind his twin in academic, developmental and social areas shortly after the steroid treatment. In the 3 years since stopping steroid medication, the patient has shown gradual but possibly incomplete resolution of his cognitive deficits. Quantitative brain magnetic resonance imaging (MRI), performed 38 months after steroid exposure revealed no gross abnormalities, but the patient's hippocampal volume was 19.5% smaller than that of his twin, despite the patient having a larger overall intracranial volume. Single photon emission computed tomography (SPECT) imaging, performed at the same time, suggested subtly decreased activity in the left posterior frontal and left parietal lobes. This case, along with others reported in the literature, suggests that certain individuals develop a "steroid dementia syndrome" after glucocorticoid treatment. Although this syndrome is uncommon, it is consistent with evolving theories of the neurotoxic or neuroendangering potential of glucocorticoids in some situations.
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Affiliation(s)
- Owen M Wolkowitz
- Department of Psychiatry, Medical Center, University of California, San Francisco, San Francisco, CA, USA.
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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 AND BEHAVIOR 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] [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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Lessov-Schlaggar CN, Swan GE, Reed T, Wolf PA, Carmelli D. Longitudinal genetic analysis of executive function in elderly men. Neurobiol Aging 2006; 28:1759-68. [PMID: 16965841 DOI: 10.1016/j.neurobiolaging.2006.07.018] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2006] [Revised: 07/24/2006] [Accepted: 07/28/2006] [Indexed: 11/24/2022]
Abstract
The objective of this study was to characterize the relative contribution of genetic and environmental influences to individual differences in longitudinal performance and decline of executive function (EF) using a population-based prospective study of male, WWII veteran twins (NHLBI twin study). Three tests of EF were administered when the twins were 59-70 years old, with 9- and 13-year follow-up. APOE epsilon4 allele status was incorporated in the genetic models to determine its contribution to longitudinal genetic variability. Mean EF performance significantly worsened over time. EF performance was highly genetically correlated across repeat assessment. There were significant genetic influences on 9- and 13-year decline in digit symbol performance. For all tasks decline over the last 4-year follow-up was influenced by individual-specific environmental effects. Controlling for APOE epsilon4 allele presence did not appreciably change the magnitude of genetic effects. These results suggest that common genetic factors underlie longitudinal EF task performance. Genetic influences on EF decline, however, appear to be evident at longer time intervals between assessments.
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Abstract
Classical genetic studies document strong complex genetic contributions to abuse of multiple addictive substances, to mnemonic processes that are likely to include those involved in substance dependence, and to the volumes of brain gray matter in regions that are likely to contribute to mnemonic/cognitive and to addictive processes. The working idea that these three heritable phenotypes are likely to share some of the same complex genetic underpinnings is presented. This review contains association-based molecular genetic studies of addiction that largely derive from my laboratory and their fit with linkage data from other laboratories. These combined results now identify many of the loci and genes that contain allelic variants that are likely to provide the heritable components of human addiction vulnerability. These data are also likely to have broad implications for neurotherapeutics. Drugs with potential abuse liabilities are widely used for indications that include pain, anxiety, sleep, seizure, and attentional disorders. There is increasing nonmedical use of these prescribed substances. Increasing information about addiction vulnerability gene variants should help to improve management of risks of dependence in individuals who receive such therapeutics. In addition, since mnemonic components that correlate well with individual differences in brain regional volumes are likely to play major roles in addiction processes, many addiction vulnerability genes are also good candidates to contribute to individual differences in mnemonic processes. Recently elucidation of addiction-associated haplotypes for the "cell adhesion" NrCAM gene illustrate several of these points.
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Affiliation(s)
- George R Uhl
- Molecular Neurobiology Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland, USA.
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Hansen JL, Reed DR, Wright MJ, Martin NG, Breslin PAS. Heritability and genetic covariation of sensitivity to PROP, SOA, quinine HCl, and caffeine. Chem Senses 2006; 31:403-13. [PMID: 16527870 PMCID: PMC1475779 DOI: 10.1093/chemse/bjj044] [Citation(s) in RCA: 83] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The perceived bitterness intensity for bitter solutions of propylthiouracil (PROP), sucrose octa-acetate (SOA), quinine HCl and caffeine were examined in a genetically informative sample of 392 females and 313 males (mean age of 17.8 +/- 3.1 years), including 62 monozygotic and 131 dizygotic twin pairs and 237 sib pairs. Broad-sense heritabilities were estimated at 0.72, 0.28, 0.34, and 0.30 for PROP, SOA, quinine, and caffeine, respectively, for perceived intensity measures. Modeling showed 1) a group factor which explained a large amount of the genetic variation in SOA, quinine, and caffeine (22-28% phenotypic variation), 2) a factor responsible for all the genetic variation in PROP (72% phenotypic variation), which only accounted for 1% and 2% of the phenotypic variation in SOA and caffeine, respectively, and 3) a modest specific genetic factor for quinine (12% phenotypic variation). Unique environmental influences for all four compounds were due to a single factor responsible for 7-22% of phenotypic variation. The results suggest that the perception of PROP and the perception of SOA, quinine, and caffeine are influenced by two distinct sets of genes.
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Affiliation(s)
- Jonathan L Hansen
- Genetic Epidemiology Group, Queensland Institute of Medical Research, Brisbane, Australia.
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Luciano M, Wainwright MA, Wright MJ, Martin NG. The heritability of conscientiousness facets and their relationship to IQ and academic achievement. PERSONALITY AND INDIVIDUAL DIFFERENCES 2006. [DOI: 10.1016/j.paid.2005.10.013] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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