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Luciano M, Corley J, Valdés Hernández MC, Craig LCA, McNeill G, Bastin ME, Deary IJ, Cox SR, Wardlaw JM. Mediterranean-Type Diet and Brain Structural Change from 73 to 79 Years in the Lothian Birth Cohort 1936. J Nutr Health Aging 2022; 26:368-372. [PMID: 35450993 DOI: 10.1007/s12603-022-1760-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
OBJECTIVES To test whether Mediterranean-type Diet (MeDi) at age 70 years is associated with longitudinal trajectories of total brain MRI volume over a six-year period from age 73 to 79. DESIGN Cohort study which uses a correlational design. SETTING Participants residing in the Lothian region of Scotland and living independently in the community. PARTICIPANTS A relatively healthy Scottish sample drawn from the Lothian Birth Cohort 1936. MEASUREMENTS Total brain volume measurements were available at ages 73, 76 and 79 (N ranged 332 to 563). Adherence to the MeDi was based on food frequency questionnaire data collected three years before the baseline imaging scans, and was used in growth curve models to predict the trajectory of total brain volume change. RESULTS No association was found (p>.05) between adherence to the MeDi at age 70 and total brain volume change from 73 to 79 years in minimally-adjusted (sex) or fully adjusted models controlling for additional health confounders. CONCLUSIONS Variation in adherence to the MeDi was not predictive of total brain atrophy over a six-year period. This suggests that previous findings of dietary associations with brain volume are not long lasting or become less important as ageing-related conditions account for greater variation in brain volume change. More frequent collection of dietary intake data is needed to clarify these findings.
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Affiliation(s)
- M Luciano
- Michelle Luciano, Psychology, 7 George Square, University of Edinburgh, Edinburgh, EH9 8JZ, Phone +44 (0)131 6503630,
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Hamilton O, Cox SR, Ballerini L, Bastin ME, Corley J, Gow AJ, Muñoz Maniega S, Redmond P, Valdés Hernández MDC, Wardlaw JM, Deary IJ. Associations between total MRI-visible small vessel disease burden and domain-specific cognitive abilities in a community-dwelling older-age cohort. Neurobiol Aging 2021; 105:25-34. [PMID: 34022536 PMCID: PMC8345313 DOI: 10.1016/j.neurobiolaging.2021.04.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 01/27/2021] [Accepted: 04/13/2021] [Indexed: 01/08/2023]
Abstract
Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized β: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics.
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Affiliation(s)
- Okl Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - S R Cox
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - L Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - M E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - J Corley
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - A J Gow
- Department of Psychology and the Centre for Applied Behavioural Sciences, School of Social Sciences, Heriot-Watt University, Edinburgh, UK, EH14 4AS
| | - S Muñoz Maniega
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - P Redmond
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - M Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - J M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ.
| | - I J Deary
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ.
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Cox SR, Harris MA, Ritchie SJ, Buchanan CR, Valdés Hernández MC, Corley J, Taylor AM, Madole JW, Harris SE, Whalley HC, McIntosh AM, Russ TC, Bastin ME, Wardlaw JM, Deary IJ, Tucker-Drob EM. Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life. Mol Psychiatry 2021; 26:2651-2662. [PMID: 33398085 PMCID: PMC8254824 DOI: 10.1038/s41380-020-00975-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 11/17/2020] [Accepted: 11/30/2020] [Indexed: 12/28/2022]
Abstract
Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflate information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the eighth decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging.
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Affiliation(s)
- S. R. Cox
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Department of Psychology, The University of Edinburgh, Edinburgh, UK ,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - M. A. Harris
- grid.4305.20000 0004 1936 7988Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
| | - S. J. Ritchie
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK
| | - C. R. Buchanan
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Department of Psychology, The University of Edinburgh, Edinburgh, UK ,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - M. C. Valdés Hernández
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - J. Corley
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - A. M. Taylor
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - J. W. Madole
- grid.55460.320000000121548364Department of Psychology, University of Texas, Austin, TX USA
| | - S. E. Harris
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - H. C. Whalley
- grid.4305.20000 0004 1936 7988Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
| | - A. M. McIntosh
- grid.4305.20000 0004 1936 7988Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
| | - T. C. Russ
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Division of Psychiatry, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | - M. E. Bastin
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - J. M. Wardlaw
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK
| | - I. J. Deary
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts Group, The University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - E. M. Tucker-Drob
- grid.55460.320000000121548364Department of Psychology, University of Texas, Austin, TX USA
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Batty GD, Deary IJ, Luciano M, Altschul DM, Kivimäki M, Gale CR. Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study based on a community sample. Brain Behav Immun 2020; 89:569-578. [PMID: 32561221 PMCID: PMC7297693 DOI: 10.1016/j.bbi.2020.06.021] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 06/14/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND While certain infectious diseases have been linked to socioeconomic disadvantage, mental health problems, and lower cognitive function, relationships with COVID-19 are either uncertain or untested. Our objective was to examine the association of a range of psychosocial factors with hospitalisation for COVID-19. METHODS UK Biobank, a prospective cohort study, comprises around half a million people who were aged 40-69 years at study induction between 2006 and 2010 when information on psychosocial factors and covariates were captured. Hospitalisations for COVID-19 were ascertained between 16th March and 26th April 2020. RESULTS There were 908 hospitalisations for COVID-19 in an analytical sample of 431,051 England-based study members. In age- and sex-adjusted analyses, an elevated risk of COVID-19 was related to disadvantaged levels of education (odds ratio; 95% confidence interval: 2.05; 1.70, 2.47), income (2.00; 1.63, 2,47), area deprivation (2.20; 1.86, 2.59), occupation (1.39; 1.14, 1.69), psychological distress (1.58; 1.32, 1.89), mental health (1.50; 1.25, 1.79), neuroticism (1.19; 1.00, 1.42), and performance on two tests of cognitive function - verbal and numerical reasoning (2.66; 2.06, 3.34) and reaction speed (1.27; 1.08, 1.51). These associations were graded (p-value for trend ≤ 0.038) such that effects were apparent across the full psychosocial continua. After mutual adjustment for these characteristics plus ethnicity, comorbidity, and lifestyle factors, only the relationship between lower cognitive function as measured using the reasoning test and risk of the infection remained (1.98; 1.38, 2.85). CONCLUSIONS A range of psychosocial factors revealed associations with hospitalisation for COVID-19 of which the relation with cognitive function, a marker of health literacy, was most robust.
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Affiliation(s)
- G D Batty
- Department of Epidemiology and Public Health, University College London, UK.
| | - I J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK.
| | - M Luciano
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.
| | - D M Altschul
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.
| | - M Kivimäki
- Department of Epidemiology and Public Health, University College London, UK.
| | - C R Gale
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK; MRC Lifecourse Epidemiology Unit, University of Southampton, UK.
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Alloza C, Blesa-Cábez M, Bastin ME, Madole JW, Buchanan CR, Janssen J, Gibson J, Deary IJ, Tucker-Drob EM, Whalley HC, Arango C, McIntosh AM, Cox SR, Lawrie SM. Psychotic-like experiences, polygenic risk scores for schizophrenia, and structural properties of the salience, default mode, and central-executive networks in healthy participants from UK Biobank. Transl Psychiatry 2020; 10:122. [PMID: 32341335 PMCID: PMC7186224 DOI: 10.1038/s41398-020-0794-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 03/11/2020] [Accepted: 03/25/2020] [Indexed: 02/07/2023] Open
Abstract
Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank, N = 3875) including information on PLEs (obtained from the Mental Health Questionnaire (MHQ); UKBiobank Category: 144; N auditory hallucinations = 55, N visual hallucinations = 79, N persecutory delusions = 16, N delusions of reference = 13), polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode, and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations, both negative and positive, with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus, and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. Generally, these results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and may predispose to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.
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Affiliation(s)
- C Alloza
- Division of Psychiatry, The University of Edinburgh, Edinburgh, UK.
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.
- Ciber del Area de Salud Mental (CIBERSAM), Madrid, Spain.
| | - M Blesa-Cábez
- MRC Centre for Reproductive Health, The University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - J W Madole
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - C R Buchanan
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK
| | - J Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- Ciber del Area de Salud Mental (CIBERSAM), Madrid, Spain
| | - J Gibson
- Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - E M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - H C Whalley
- Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
| | - C Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- Ciber del Area de Salud Mental (CIBERSAM), Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - A M McIntosh
- Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK
| | - S M Lawrie
- Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
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Kilgour AHM, Redmond P, Taylor A, Deary IJ, Starr JM, Shenkin SD. 70 Prevalence of Sarcopenia in A Longitudinal UK Cohort Study Using Ewgsop2 Criteria Varies Widely Depending on Which Measures of Muscle Strength and Performance are Used. Age Ageing 2020. [DOI: 10.1093/ageing/afz188.01] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Background
The European Working Group on Sarcopenia in Older People 2 (EWGSOP2) guidelines have recently been published to aid diagnosis of sarcopenia in the clinical setting and to allow for better comparison between research studies. The guidelines recommend several different tests for diagnosing sarcopenia. We hypothesised that the prevalence of sarcopenia might vary depending on which tests are used.
Methods
We used data from Wave 3 of the Lothian Birth Cohort 1936 study, a longitudinal ageing study of healthy, community dwelling older adults (n= 697, 52% men, mean age 76y), to assess the prevalence of sarcopenia using the suggested cut-offs in the EWGSOP2 guidelines. Probable sarcopenia was defined as low muscle strength (measured by handgrip strength and 5x chair stand test), confirmed sarcopenia was defined as low muscle strength + low lean mass (measured by bioimpedance analysis), and severe sarcopenia was defined as confirmed sarcopenia + low muscle performance (measured by gait speed and short physical performance battery score). SPSS version 24.0 was used for statistical analysis.
Results
The maximum prevalence of probable sarcopenia was 24.2% in men and 24.8% in women, of confirmed sarcopenia was 7.4% in men and 11.0% in women, and of severe sarcopenia was 4.6% in men and 5.9% in women, when either of the cut-offs for muscle strength +/- muscle performance were met. When using only one measure of muscle strength +/- performance, rates of probable sarcopenia ranged from 7.7% to 21.1% in men and 5.9% to 21.3% in women; rates of confirmed sarcopenia ranged from 3.9% to 5.3% in men and 5.1% to 9% in women; and rates of severe sarcopenia ranged from 1.4% to 3.9% in men and from 2.0% to 5.1% in women.
Conclusions
In a UK-based longitudinal ageing study we found that the prevalence of probable, confirmed and severe sarcopenia varied widely using the EWGSOP2 guidelines depending on which identifying tests were used. We found that the cut-off points suggested for some of the measures in the guidelines are not comparable and may lead to differing groups being identified as sarcopenic between different trials. We suggest modification of the cut-offs to adjust for this.
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Affiliation(s)
- A H M Kilgour
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Geriatric Medicine Unit, University of Edinburgh, UK
| | - P Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Department of Psychology, University of Edinburgh, UK
| | - A Taylor
- Department of Psychology, University of Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Department of Psychology, University of Edinburgh, UK
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Geriatric Medicine Unit, University of Edinburgh, UK
| | - S D Shenkin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Geriatric Medicine Unit, University of Edinburgh, UK
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Wragg D, Liu Q, Lin Z, Riggio V, Pugh CA, Beveridge AJ, Brown H, Hume DA, Harris SE, Deary IJ, Tenesa A, Prendergast JGD. Using regulatory variants to detect gene-gene interactions identifies networks of genes linked to cell immortalisation. Nat Commun 2020; 11:343. [PMID: 31953380 PMCID: PMC6969137 DOI: 10.1038/s41467-019-13762-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 11/19/2019] [Indexed: 12/30/2022] Open
Abstract
The extent to which the impact of regulatory genetic variants may depend on other factors, such as the expression levels of upstream transcription factors, remains poorly understood. Here we report a framework in which regulatory variants are first aggregated into sets, and using these as estimates of the total cis-genetic effects on a gene we model their non-additive interactions with the expression of other genes in the genome. Using 1220 lymphoblastoid cell lines across platforms and independent datasets we identify 74 genes where the impact of their regulatory variant-set is linked to the expression levels of networks of distal genes. We show that these networks are predominantly associated with tumourigenesis pathways, through which immortalised cells are able to rapidly proliferate. We consequently present an approach to define gene interaction networks underlying important cellular pathways such as cell immortalisation.
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Affiliation(s)
- D. Wragg
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - Q. Liu
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - Z. Lin
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - V. Riggio
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - C. A. Pugh
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - A. J. Beveridge
- 0000 0001 2193 314Xgrid.8756.cGlasgow Polyomics, College of Medical, Veterinary and Life Science, University of Glasgow, Glasgow, UK
| | - H. Brown
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - D. A. Hume
- 0000000406180938grid.489335.0Mater Research Institute-University of Queensland, Translational Research Institute, Woolloongabba, QLD 4102 Australia
| | - S. E. Harris
- 0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - I. J. Deary
- 0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - A. Tenesa
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
| | - J. G. D. Prendergast
- 0000 0004 1936 7988grid.4305.2The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG UK
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Abstract
The associations between indices of brain structure and measured intelligence are unclear. This is partly because the evidence to-date comes from mostly small and heterogeneous studies. Here, we report brain structure-intelligence associations on a large sample from the UK Biobank study. The overall N = 29,004, with N = 18,426 participants providing both brain MRI and at least one cognitive test, and a complete four-test battery with MRI data available in a minimum N = 7201, depending upon the MRI measure. Participants' age range was 44–81 years (M = 63.13, SD = 7.48). A general factor of intelligence (g) was derived from four varied cognitive tests, accounting for one third of the variance in the cognitive test scores. The association between (age- and sex- corrected) total brain volume and a latent factor of general intelligence is r = 0.276, 95% C.I. = [0.252, 0.300]. A model that incorporated multiple global measures of grey and white matter macro- and microstructure accounted for more than double the g variance in older participants compared to those in middle-age (13.6% and 5. 4%, respectively). There were no sex differences in the magnitude of associations between g and total brain volume or other global aspects of brain structure. The largest brain regional correlates of g were volumes of the insula, frontal, anterior/superior and medial temporal, posterior and paracingulate, lateral occipital cortices, thalamic volume, and the white matter microstructure of thalamic and association fibres, and of the forceps minor. Many of these regions exhibited unique contributions to intelligence, and showed highly stable out of sample prediction. We used a large sample from UK Biobank (N = 29,004, age range = 44–81 years). The association between brain volume and intelligence (‘g’) was r = 0.276. Multiple global tissue measures explained twice the g variance in older than middle age. The size of the association between g and global brain measures did not vary by sex. We investigate the regional cortical, subcortical and white matter correlates of g.
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Affiliation(s)
- S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, UK.,Department of Psychology, The University of Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - S J Ritchie
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - C Fawns-Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, UK.,Department of Psychology, The University of Edinburgh, UK
| | - E M Tucker-Drob
- Department of Psychology, University of Texas, Austin, TX, USA
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, UK.,Department of Psychology, The University of Edinburgh, UK
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9
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Navrady LB, Wolters MK, MacIntyre DJ, Clarke TK, Campbell AI, Murray AD, Evans KL, Seckl J, Haley C, Milburn K, Wardlaw JM, Porteous DJ, Deary IJ, McIntosh AM. Cohort Profile: Stratifying Resilience and Depression Longitudinally (STRADL): a questionnaire follow-up of Generation Scotland: Scottish Family Health Study (GS:SFHS). Int J Epidemiol 2019; 47:13-14g. [PMID: 29040551 PMCID: PMC5837716 DOI: 10.1093/ije/dyx115] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/06/2017] [Indexed: 11/14/2022] Open
Affiliation(s)
- L B Navrady
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - M K Wolters
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - D J MacIntyre
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - T-K Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - A I Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Generation Scotland, Centre for Genetics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - A D Murray
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - K L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - J Seckl
- Endocrinology Unit, Centre for Cardiovascular Science, Queen's Medical Research Institute, Edinburgh, UK
| | - C Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - K Milburn
- Health Informatics Centre, University of Dundee, Dundee, UK
| | - J M Wardlaw
- Brain Research Imaging Centre, School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - D J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Generation Scotland, Centre for Genetics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Generation Scotland, Centre for Genetics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK.,Generation Scotland, Centre for Genetics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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10
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Hafferty JD, Navrady LB, Adams MJ, Howard DM, Campbell AI, Whalley HC, Lawrie SM, Nicodemus KK, Porteous DJ, Deary IJ, McIntosh AM. The role of neuroticism in self-harm and suicidal ideation: results from two UK population-based cohorts. Soc Psychiatry Psychiatr Epidemiol 2019; 54:1505-1518. [PMID: 31123787 PMCID: PMC6858388 DOI: 10.1007/s00127-019-01725-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 05/13/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND Self-harm is common, debilitating and associated with completed suicide and increased all-cause mortality, but there is uncertainty about its causal risk factors, limiting risk assessment and effective management. Neuroticism is a stable personality trait associated with self-harm and suicidal ideation, and correlated with coping styles, but its value as an independent predictor of these outcomes is disputed. METHODS Prior history of hospital-treated self-harm was obtained by record-linkage to administrative health data in Generation Scotland:Scottish Family Health Study (N = 15,798; self-harm cases = 339) and by a self-report variable in UK Biobank (N = 35,227; self-harm cases = 772). Neuroticism in both cohorts was measured using the Eysenck Personality Questionnaire-Short Form. Associations of neuroticism with self-harm were tested using multivariable regression following adjustment for age, sex, cognitive ability, educational attainment, socioeconomic deprivation, and relationship status. A subset of GS:SFHS was followed-up with suicidal ideation elicited by self-report (n = 3342, suicidal ideation cases = 158) and coping styles measured by the Coping Inventory for Stressful Situations. The relationship of neuroticism to suicidal ideation, and the role of coping style, was then investigated using multivariable logistic regression. RESULTS Neuroticism was positively associated with hospital-associated self-harm in GS:SFHS (per EPQ-SF unit odds ratio 1.2 95% credible interval 1.1-1.2, pFDR 0.0003) and UKB (per EPQ-SF unit odds ratio 1.1 95% confidence interval 1.1-1.2, pFDR 9.8 × 10-17). Neuroticism, and the neuroticism-correlated coping style, emotion-oriented coping (EoC), were also associated with suicidal ideation in multivariable models. CONCLUSIONS Neuroticism is an independent predictor of hospital-treated self-harm risk. Neuroticism and emotion-orientated coping styles are also predictive of suicidal ideation.
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Affiliation(s)
- Jonathan D. Hafferty
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK
| | - L. B. Navrady
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK
| | - M. J. Adams
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK
| | - D. M. Howard
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK
| | - A. I. Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - H. C. Whalley
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK
| | - S. M. Lawrie
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK
| | - K. K. Nicodemus
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - D. J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK ,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - I. J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A. M. McIntosh
- Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF UK ,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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11
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Corley J, Shivappa N, Hébert JR, Starr JM, Deary IJ. Associations between Dietary Inflammatory Index Scores and Inflammatory Biomarkers among Older Adults in the Lothian Birth Cohort 1936 Study. J Nutr Health Aging 2019; 23:628-636. [PMID: 31367727 PMCID: PMC6675764 DOI: 10.1007/s12603-019-1221-y] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 02/25/2019] [Indexed: 01/05/2023]
Abstract
OBJECTIVES Chronic low-grade inflammation is a key underlying mechanism in several age-related chronic conditions and previous studies have shown that diet can modulate the inflammatory process. We investigated the ability of the Dietary Inflammatory Index (DII®), a summary measure of dietary inflammatory potential, to predict concentrations of plasma inflammatory markers in a sample of older people. DESIGN Cross-sectional and 3-year follow-up analysis of Lothian Birth Cohort 1936 (LBC1936) study data. SETTING Baseline data collection occurred between 2004 and 2007 in Edinburgh, Scotland. PARTICIPANTS Men and women (n 928, age ~70 at baseline) living in Edinburgh and surrounding regions who are surviving participants of the Scottish Mental Survey of 1947. MEASUREMENTS Energy-adjusted DII (E-DII) scores at age 70 (derived from a food-frequency questionnaire), plasma concentrations of inflammatory biomarkers at age 70 (C-reactive protein (CRP), fibrinogen) and age 73 (CRP, fibrinogen, hs-CRP, Interleukin-6 (IL-6)). Analyses were performed using multivariable logistic regression adjusting for age, sex, smoking, body mass index, physical activity, and hypercholesterolaemia. RESULTS Higher E-DII scores (pro-inflammatory diet) were associated with increased odds of elevated CRP (>3mg/L) at age 70 (OR 1.12; 95% CI: 1.02, 1.24, P = 0.02), and elevated IL-6 (>1.6pg/ml) at age 73 (OR 1.11; 95% CI: 1.00, 1.23, P = 0.04), but not with fibrinogen. CONCLUSION These results are consistent with the ability of the DII to predict inflammatory biomarker concentrations and suggest that diet plays a role in the regulation of inflammation, even after controlling for potential confounders. This validation study provides support for using the DII in research among older populations.
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Affiliation(s)
- J Corley
- Dr Janie Corley, Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, Scotland, UK. Phone: +44-131-650-1683.
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12
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Alloza C, Cox SR, Blesa Cábez M, Redmond P, Whalley HC, Ritchie SJ, Muñoz Maniega S, Valdés Hernández MDC, Tucker-Drob EM, Lawrie SM, Wardlaw JM, Deary IJ, Bastin ME. Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study. Neuroimage 2018; 183:884-896. [PMID: 30179718 PMCID: PMC6215331 DOI: 10.1016/j.neuroimage.2018.08.075] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 08/28/2018] [Accepted: 08/31/2018] [Indexed: 12/14/2022] Open
Abstract
Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (β = 0.132, pFDR = 0.040), arcuate (β = 0.291, pFDR = 0.040), anterior thalamic radiations (β = 0.215, pFDR = 0.040) and cingulum (β = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (β = -0.039, pFDR = 0.048) and strength (β = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.
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Affiliation(s)
- C Alloza
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK.
| | - S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, UK
| | - P Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - H C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - S J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - M Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - E M Tucker-Drob
- Department of Psychology, University of Texas, Austin, TX, USA
| | - S M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - J M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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13
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Laukka EJ, Dykiert D, Allerhand M, Starr JM, Deary IJ. Effects of between-person differences and within-person changes in symptoms of anxiety and depression on older age cognitive performance. Psychol Med 2018; 48:1350-1358. [PMID: 29039283 PMCID: PMC6088541 DOI: 10.1017/s0033291717002896] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Revised: 08/28/2017] [Accepted: 09/05/2017] [Indexed: 11/21/2022]
Abstract
BACKGROUND Anxiety and depression are both important correlates of cognitive function. However, longitudinal studies investigating how they covary with cognition within the same individual are scarce. We aimed to simultaneously estimate associations of between-person differences and within-person variability in anxiety and depression with cognitive performance in a sample of non-demented older people. METHODS Participants in the Lothian Birth Cohort 1921 study, a population-based narrow-age sample (mean age at wave 1 = 79 years, n = 535), were examined on five occasions across 13 years. Anxiety and depression were measured with the Hospital Anxiety and Depression Scale (HADS) and cognitive performance was assessed with tests of reasoning, logical memory, and letter fluency. Data were analyzed using two-level linear mixed-effects models with within-person centering. RESULTS Divergent patterns were observed for anxiety and depression. For anxiety, between-person differences were more influential; people who scored higher on HADS anxiety relative to other same-aged individuals demonstrated poorer cognitive performance on average. For depression, on the other hand, time-varying within-person differences were more important; scoring higher than usual on HADS depression was associated with poorer cognitive performance relative to the average level for that participant. Adjusting for gender, childhood mental ability, emotional stability, and disease burden attenuated these associations. CONCLUSIONS The results from this study highlight the importance of addressing both between- and within-person effects of negative mood and suggest that anxiety and depression affect cognitive function in different ways. The current findings have implications for assessment and treatment of older age cognitive deficits.
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Affiliation(s)
- E. J. Laukka
- Department of Neurobiology, Care Sciences, and Society (NVS), Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - D. Dykiert
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M. Allerhand
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - J. M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Geriatric Medicine Unit, University of Edinburgh, Edinburgh, UK
| | - I. J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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14
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Cole JH, Ritchie SJ, Bastin ME, Valdés Hernández MC, Muñoz Maniega S, Royle N, Corley J, Pattie A, Harris SE, Zhang Q, Wray NR, Redmond P, Marioni RE, Starr JM, Cox SR, Wardlaw JM, Sharp DJ, Deary IJ. Brain age predicts mortality. Mol Psychiatry 2018; 23:1385-1392. [PMID: 28439103 PMCID: PMC5984097 DOI: 10.1038/mp.2017.62] [Citation(s) in RCA: 362] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 01/18/2017] [Accepted: 02/17/2017] [Indexed: 12/30/2022]
Abstract
Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.
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Affiliation(s)
- J H Cole
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, UK,Medicine, Imperial College London, Computational, Cognitive and Clinical Neuroimaging Laboratory, Burlington Danes Building, Du Cane Road, London W12 0NN, UK. E-mail:
| | - S J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - M C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - N Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Centre for Genomic and Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Q Zhang
- Institute for Molecular Bioscience, The University of Queensland, QLD, Australia
| | - N R Wray
- Institute for Molecular Bioscience, The University of Queensland, QLD, Australia,Queensland Brain Institute, The University of Queensland, QLD, Australia
| | - P Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Centre for Genomic and Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, QLD, Australia
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - J M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - D J Sharp
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
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15
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Teng S, Thomson PA, McCarthy S, Kramer M, Muller S, Lihm J, Morris S, Soares DC, Hennah W, Harris S, Camargo LM, Malkov V, McIntosh AM, Millar JK, Blackwood DH, Evans KL, Deary IJ, Porteous DJ, McCombie WR. Rare disruptive variants in the DISC1 Interactome and Regulome: association with cognitive ability and schizophrenia. Mol Psychiatry 2018; 23:1270-1277. [PMID: 28630456 PMCID: PMC5984079 DOI: 10.1038/mp.2017.115] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 03/20/2017] [Accepted: 03/27/2017] [Indexed: 12/20/2022]
Abstract
Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWERacross), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWERacross P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWERacross P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.
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Affiliation(s)
- S Teng
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Department of Biology, Howard University, Washington DC, USA
| | - P A Thomson
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - S McCarthy
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - M Kramer
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - S Muller
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - J Lihm
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - S Morris
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - D C Soares
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - W Hennah
- Institute for Molecular Medicine, Finland FIMM, University of Helsinki, Helsinki, Finland
| | - S Harris
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - L M Camargo
- UCB New Medicines, One Broadway, Cambridge, MA, USA
| | - V Malkov
- Genetics and Pharmacogenomics, MRL, Merck & Co, Boston, MA, USA
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - J K Millar
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - D H Blackwood
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - K L Evans
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D J Porteous
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - W R McCombie
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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16
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Dall PM, Skelton DA, Dontje ML, Coulter EH, Stewart S, Cox SR, Shaw RJ, Čukić I, Fitzsimons CF, Greig CA, Granat MH, Der G, Deary IJ, Chastin S. Characteristics of a protocol to collect objective physical activity/sedentary behaviour data in a large study: Seniors USP (understanding sedentary patterns). J Meas Phys Behav 2018; 1:26-31. [PMID: 30159548 PMCID: PMC6110380 DOI: 10.1123/jmpb.2017-0004] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The Seniors USP study measured sedentary behaviour (activPAL3, 9 day wear) in older adults. The measurement protocol had three key characteristics: enabling 24-hour wear (monitor location, waterproofing); minimising data loss (reducing monitor failure, staff training, communication); and quality assurance (removal by researcher, confidence about wear). Two monitors were not returned; 91% (n=700) of returned monitors had 7 valid days of data. Sources of data loss included monitor failure (n=11), exclusion after quality assurance (n=5), early removal for skin irritation (n=8) or procedural errors (n=10). Objective measurement of physical activity and sedentary behaviour in large studies requires decisional trade-offs between data quantity (collecting representative data) and utility (derived outcomes that reflect actual behaviour).
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Affiliation(s)
- P M Dall
- Institute of Applied Health research, School of Health & Life Sciences, Glasgow Caledonian University, Glasgow, UK
| | - D A Skelton
- Institute of Applied Health research, School of Health & Life Sciences, Glasgow Caledonian University, Glasgow, UK
| | - M L Dontje
- Institute of Applied Health research, School of Health & Life Sciences, Glasgow Caledonian University, Glasgow, UK
- School of Population and Global Health, University of Western Australia, Perth, Australia
| | - E H Coulter
- School of Health Sciences, Queen Margaret University, Edinburgh, UK
| | - S Stewart
- Institute of Applied Health research, School of Health & Life Sciences, Glasgow Caledonian University, Glasgow, UK
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - R J Shaw
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - I Čukić
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - C F Fitzsimons
- Department of Sport, Physical Education and Health Sciences, University of Edinburgh, Edinburgh, UK
| | - C A Greig
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK
| | - M H Granat
- School of Health Sciences, University of Salford, Salford, UK
| | - G Der
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Sfm Chastin
- Institute of Applied Health research, School of Health & Life Sciences, Glasgow Caledonian University, Glasgow, UK
- Department of Movement and Sports Sciences, Faculty of Medicine and Health Science, Ghent University, Ghent, Belgium
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17
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Deary V, Hagenaars SP, Harris SE, Hill WD, Davies G, Liewald DCM, McIntosh AM, Gale CR, Deary IJ. Genetic contributions to self-reported tiredness. Mol Psychiatry 2018; 23:609-620. [PMID: 28194004 PMCID: PMC5822465 DOI: 10.1038/mp.2017.5] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2016] [Revised: 12/01/2016] [Accepted: 12/13/2016] [Indexed: 02/07/2023]
Abstract
Self-reported tiredness and low energy, often called fatigue, are associated with poorer physical and mental health. Twin studies have indicated that this has a heritability between 6 and 50%. In the UK Biobank sample (N=108 976), we carried out a genome-wide association study (GWAS) of responses to the question, 'Over the last two weeks, how often have you felt tired or had little energy?' Univariate GCTA-GREML found that the proportion of variance explained by all common single-nucleotide polymorphisms for this tiredness question was 8.4% (s.e.=0.6%). GWAS identified one genome-wide significant hit (Affymetrix id 1:64178756_C_T; P=1.36 × 10-11). Linkage disequilibrium score regression and polygenic profile score analyses were used to test for shared genetic aetiology between tiredness and up to 29 physical and mental health traits from GWAS consortia. Significant genetic correlations were identified between tiredness and body mass index (BMI), C-reactive protein, high-density lipoprotein (HDL) cholesterol, forced expiratory volume, grip strength, HbA1c, longevity, obesity, self-rated health, smoking status, triglycerides, type 2 diabetes, waist-hip ratio, attention deficit hyperactivity disorder, bipolar disorder, major depressive disorder, neuroticism, schizophrenia and verbal-numerical reasoning (absolute rg effect sizes between 0.02 and 0.78). Significant associations were identified between tiredness phenotypic scores and polygenic profile scores for BMI, HDL cholesterol, low-density lipoprotein cholesterol, coronary artery disease, C-reactive protein, HbA1c, height, obesity, smoking status, triglycerides, type 2 diabetes, waist-hip ratio, childhood cognitive ability, neuroticism, bipolar disorder, major depressive disorder and schizophrenia (standardised β's had absolute values<0.03). These results suggest that tiredness is a partly heritable, heterogeneous and complex phenomenon that is phenotypically and genetically associated with affective, cognitive, personality and physiological processes.
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Affiliation(s)
- V Deary
- Department of Psychology, Northumbria University, Newcastle, UK
| | - S P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C M Liewald
- Department of Psychology, Northumbria University, Newcastle, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - International Consortium for Blood Pressure GWAS
- Department of Psychology, Northumbria University, Newcastle, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - CHARGE Consortium Aging and Longevity Group
- Department of Psychology, Northumbria University, Newcastle, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - CHARGE Consortium Inflammation Group
- Department of Psychology, Northumbria University, Newcastle, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - C R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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18
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Chastin SFM, Dontje ML, Skelton DA, Čukić I, Shaw RJ, Gill JMR, Greig CA, Gale CR, Deary IJ, Der G, Dall PM. Systematic comparative validation of self-report measures of sedentary time against an objective measure of postural sitting (activPAL). Int J Behav Nutr Phys Act 2018; 15:21. [PMID: 29482617 PMCID: PMC5828279 DOI: 10.1186/s12966-018-0652-x] [Citation(s) in RCA: 89] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 02/09/2018] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Sedentary behaviour is a public health concern that requires surveillance and epidemiological research. For such large scale studies, self-report tools are a pragmatic measurement solution. A large number of self-report tools are currently in use, but few have been validated against an objective measure of sedentary time and there is no comparative information between tools to guide choice or to enable comparison between studies. The aim of this study was to provide a systematic comparison, generalisable to all tools, of the validity of self-report measures of sedentary time against a gold standard sedentary time objective monitor. METHODS Cross sectional data from three cohorts (N = 700) were used in this validation study. Eighteen self-report measures of sedentary time, based on the TAxonomy of Self-report SB Tools (TASST) framework, were compared against an objective measure of postural sitting (activPAL) to provide information, generalizable to all existing tools, on agreement and precision using Bland-Altman statistics, on criterion validity using Pearson correlation, and on data loss. RESULTS All self-report measures showed poor accuracy compared with the objective measure of sedentary time, with very wide limits of agreement and poor precision (random error > 2.5 h). Most tools under-reported total sedentary time and demonstrated low correlations with objective data. The type of assessment used by the tool, whether direct, proxy, or a composite measure, influenced the measurement characteristics. Proxy measures (TV time) and single item direct measures using a visual analogue scale to assess the proportion of the day spent sitting, showed the best combination of precision and data loss. The recall period (e.g. previous week) had little influence on measurement characteristics. CONCLUSION Self-report measures of sedentary time result in large bias, poor precision and low correlation with an objective measure of sedentary time. Choice of tool depends on the research context, design and question. Choice can be guided by this systematic comparative validation and, in the case of population surveillance, it recommends to use a visual analog scale and a 7 day recall period. Comparison between studies and improving population estimates of average sedentary time, is possible with the comparative correction factors provided.
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Affiliation(s)
- S F M Chastin
- Institute for Applied Health Research, School of Health and life Science, Glasgow Caledonian University, Cowcaddens Road, Glasgow, G4 0BA, Scotland, UK.
- Department of Movement and Sports Sciences, Faculty of Medicine and Health Science, Ghent University, Ghent, Belgium.
| | - M L Dontje
- Institute for Applied Health Research, School of Health and life Science, Glasgow Caledonian University, Cowcaddens Road, Glasgow, G4 0BA, Scotland, UK
- School of Population and Global Health, University of Western Australia, Perth, Australia
| | - D A Skelton
- Institute for Applied Health Research, School of Health and life Science, Glasgow Caledonian University, Cowcaddens Road, Glasgow, G4 0BA, Scotland, UK
| | - I Čukić
- Centre for Cognitive Ageing & Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - R J Shaw
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - J M R Gill
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - C A Greig
- School of Sport, Exercise and Rehabilitation Sciences and MRC-Arthritis Research UK Centre for Musculoskeletal Ageing and Health, University of Birmingham, Birmingham, UK
| | - C R Gale
- Centre for Cognitive Ageing & Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - I J Deary
- Centre for Cognitive Ageing & Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - G Der
- Centre for Cognitive Ageing & Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - P M Dall
- Institute for Applied Health Research, School of Health and life Science, Glasgow Caledonian University, Cowcaddens Road, Glasgow, G4 0BA, Scotland, UK
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19
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Abstract
In the face of shifting demographics and an increase in human longevity, it is important to examine carefully what is known about cognitive ageing, and to identify and promote possibly malleable lifestyle and health-related factors that might mitigate age-associated cognitive decline. The Lothian Birth Cohorts of 1921 (LBC1921, n = 550) and 1936 (LBC1936, n = 1091) are longitudinal studies of cognitive and brain ageing based in Scotland. Childhood IQ data are available for these participants, who were recruited in later life and then followed up regularly. This overview summarises some of the main LBC findings to date, illustrating the possible genetic and environmental contributions to cognitive function (level and change) and brain imaging biomarkers in later life. Key associations include genetic variation, health and fitness, psychosocial and lifestyle factors, and aspects of the brain's structure. It addresses some key methodological issues such as confounding by early-life intelligence and social factors and emphasises areas requiring further investigation. Overall, the findings that have emerged from the LBC studies highlight that there are multiple correlates of cognitive ability level in later life, many of which have small effects, that there are as yet few reliable predictors of cognitive change, and that not all of the correlates have independent additive associations. The concept of marginal gains, whereby there might be a cumulative effect of small incremental improvements across a wide range of lifestyle and health-related factors, may offer a useful way to think about and promote a multivariate recipe for healthy cognitive and brain ageing.
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Affiliation(s)
- J Corley
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
| | - S R Cox
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
| | - I J Deary
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
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20
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Trampush JW, Yang MLZ, Yu J, Knowles E, Davies G, Liewald DC, Starr JM, Djurovic S, Melle I, Sundet K, Christoforou A, Reinvang I, DeRosse P, Lundervold AJ, Steen VM, Espeseth T, Räikkönen K, Widen E, Palotie A, Eriksson JG, Giegling I, Konte B, Roussos P, Giakoumaki S, Burdick KE, Payton A, Ollier W, Horan M, Chiba-Falek O, Attix DK, Need AC, Cirulli ET, Voineskos AN, Stefanis NC, Avramopoulos D, Hatzimanolis A, Arking DE, Smyrnis N, Bilder RM, Freimer NA, Cannon TD, London E, Poldrack RA, Sabb FW, Congdon E, Conley ED, Scult MA, Dickinson D, Straub RE, Donohoe G, Morris D, Corvin A, Gill M, Hariri AR, Weinberger DR, Pendleton N, Bitsios P, Rujescu D, Lahti J, Le Hellard S, Keller MC, Andreassen OA, Deary IJ, Glahn DC, Malhotra AK, Lencz T. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry 2017; 22:1651-1652. [PMID: 29068436 PMCID: PMC5659072 DOI: 10.1038/mp.2017.197] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This corrects the article DOI: 10.1038/mp.2016.244.
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21
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Wigmore EM, Clarke TK, Howard DM, Adams MJ, Hall LS, Zeng Y, Gibson J, Davies G, Fernandez-Pujals AM, Thomson PA, Hayward C, Smith BH, Hocking LJ, Padmanabhan S, Deary IJ, Porteous DJ, Nicodemus KK, McIntosh AM. Do regional brain volumes and major depressive disorder share genetic architecture? A study of Generation Scotland (n=19 762), UK Biobank (n=24 048) and the English Longitudinal Study of Ageing (n=5766). Transl Psychiatry 2017; 7:e1205. [PMID: 28809859 PMCID: PMC5611720 DOI: 10.1038/tp.2017.148] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 05/08/2017] [Accepted: 06/07/2017] [Indexed: 12/23/2022] Open
Abstract
Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium's genome-wide association study of regional brain volume, we sought to test whether there is shared genetic architecture between seven subcortical brain volumes and intracranial volume (ICV) and MDD. We explored this using linkage disequilibrium score regression, polygenic risk scoring (PRS) techniques, Mendelian randomisation (MR) analysis and BUHMBOX. Utilising summary statistics from ENIGMA and Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of the other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. Using PRS analysis, no regional volumetric PRS demonstrated a significant association with MDD or recurrent MDD. MR analysis in hippocampal volume and MDD identified no causal association, however, BUHMBOX analysis identified genetic subgrouping in GS:SFHS MDD cases only (P=0.00281). In this study, we provide some evidence that hippocampal volume and MDD may share genetic architecture in a subgroup of individuals, albeit the genetic correlation did not survive multiple testing correction and genetic subgroup heterogeneity was not replicated. In contrast, we found no evidence to support a shared genetic architecture between MDD and other regional subcortical volumes or ICV.
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Affiliation(s)
- E M Wigmore
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK,Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK. E-mail:
| | - T-K Clarke
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - D M Howard
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - M J Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - L S Hall
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Y Zeng
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - J Gibson
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A M Fernandez-Pujals
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - P A Thomson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - C Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - B H Smith
- Division of Population Health Sciences, University of Dundee, Dundee, UK
| | - L J Hocking
- Division of Applied Medicine, University of Aberdeen, Aberdeen, UK
| | - S Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - K K Nicodemus
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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22
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Cullen B, Smith DJ, Deary IJ, Evans JJ, Pell JP. The 'cognitive footprint' of psychiatric and neurological conditions: cross-sectional study in the UK Biobank cohort. Acta Psychiatr Scand 2017; 135:593-605. [PMID: 28387438 PMCID: PMC5434825 DOI: 10.1111/acps.12733] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/14/2017] [Indexed: 12/01/2022]
Abstract
OBJECTIVE We aimed to quantify the prevalence of cognitive impairment in adults with a history of mood disorder, schizophrenia, multiple sclerosis or Parkinson's disease, within a large general population cohort. METHOD Cross-sectional study using UK Biobank data (n = 502 642). Psychiatric and neurological exposure status was ascertained via self-reported diagnoses, hospital records and questionnaires. Impairment on reasoning, reaction time and memory tests was defined with reference to a single unexposed comparison group. Results were standardised for age and gender. Sensitivity analyses examined the influence of comorbidity, education, information sources and missing data. RESULTS Relative to the unexposed group, cognitive impairment was least common in major depression (standardised prevalence ratios across tests = 1.00 [95% CI 0.98, 1.02] to 1.49 [95% CI 1.24, 1.79]) and most common in schizophrenia (1.89 [95% CI 1.47, 2.42] to 3.92 [95% CI 2.34, 6.57]). Prevalence in mania/bipolar was similar to that in multiple sclerosis and Parkinson's disease. Estimated population attributable prevalence of cognitive impairment was higher for major depression (256 per 100 000 [95% CI 130, 381]) than for all other disorders. CONCLUSION Although the relative prevalence of cognitive impairment was lowest in major depression, the population attributable prevalence was highest overall for this group.
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Affiliation(s)
- B. Cullen
- Institute of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - D. J. Smith
- Institute of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - I. J. Deary
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
| | - J. J. Evans
- Institute of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - J. P. Pell
- Institute of Health and WellbeingUniversity of GlasgowGlasgowUK
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23
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Trampush JW, Yang MLZ, Yu J, Knowles E, Davies G, Liewald DC, Starr JM, Djurovic S, Melle I, Sundet K, Christoforou A, Reinvang I, DeRosse P, Lundervold AJ, Steen VM, Espeseth T, Räikkönen K, Widen E, Palotie A, Eriksson JG, Giegling I, Konte B, Roussos P, Giakoumaki S, Burdick KE, Payton A, Ollier W, Horan M, Chiba-Falek O, Attix DK, Need AC, Cirulli ET, Voineskos AN, Stefanis NC, Avramopoulos D, Hatzimanolis A, Arking DE, Smyrnis N, Bilder RM, Freimer NA, Cannon TD, London E, Poldrack RA, Sabb FW, Congdon E, Conley ED, Scult MA, Dickinson D, Straub RE, Donohoe G, Morris D, Corvin A, Gill M, Hariri AR, Weinberger DR, Pendleton N, Bitsios P, Rujescu D, Lahti J, Le Hellard S, Keller MC, Andreassen OA, Deary IJ, Glahn DC, Malhotra AK, Lencz T. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry 2017; 22:336-345. [PMID: 28093568 PMCID: PMC5322272 DOI: 10.1038/mp.2016.244] [Citation(s) in RCA: 136] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Revised: 10/30/2016] [Accepted: 11/03/2016] [Indexed: 01/12/2023]
Abstract
The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.
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Affiliation(s)
- J W Trampush
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - M L Z Yang
- Institute of Mental Health, Singapore, Singapore
| | - J Yu
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - E Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - S Djurovic
- Department of Medical Genetics, Oslo University Hospital, University of Bergen, Oslo, Norway,NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway
| | - I Melle
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - K Sundet
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - A Christoforou
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - P DeRosse
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - V M Steen
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - T Espeseth
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - E Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - A Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK,Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland
| | - J G Eriksson
- National Institute for Health and Welfare, Helsinki, Finland,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland,Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - I Giegling
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - B Konte
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - P Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Mental Illness Research, Education, and Clinical Center (VISN 3), James J. Peters VA Medical Center, Bronx, NY, USA
| | - S Giakoumaki
- Department of Psychology, University of Crete, Rethymno, Greece
| | - K E Burdick
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Mental Illness Research, Education, and Clinical Center (VISN 3), James J. Peters VA Medical Center, Bronx, NY, USA
| | - A Payton
- Manchester Centre for Audiology and Deafness, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK,Division of Evolution and Genomic Sciences, School of Biological Sciences, The University of Manchester, Manchester, UK
| | - W Ollier
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - M Horan
- Manchester Medical School, Institute of Brain, Behaviour, and Mental Health, University of Manchester, Manchester, UK
| | - O Chiba-Falek
- Department of Neurology, Bryan Alzheimer's Disease Research Center, and Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA
| | - D K Attix
- Department of Neurology, Bryan Alzheimer's Disease Research Center, and Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA,Division of Medical Psychology, Department of Neurology, Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - A C Need
- Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
| | - E T Cirulli
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - A N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
| | - N C Stefanis
- Department of Psychiatry, University of Athens School of Medicine, Eginition Hospital, Athens, Greece,University Mental Health Research Institute, Athens, Greece,Neurobiology Research Institute, Theodor Theohari Cozzika Foundation, Athens, Greece
| | - D Avramopoulos
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA,Department of Psychiatry and McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - A Hatzimanolis
- Department of Psychiatry, University of Athens School of Medicine, Eginition Hospital, Athens, Greece,University Mental Health Research Institute, Athens, Greece,Neurobiology Research Institute, Theodor Theohari Cozzika Foundation, Athens, Greece
| | - D E Arking
- Department of Psychiatry and McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - N Smyrnis
- Department of Psychiatry, University of Athens School of Medicine, Eginition Hospital, Athens, Greece,University Mental Health Research Institute, Athens, Greece
| | - R M Bilder
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - N A Freimer
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - T D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA
| | - E London
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - R A Poldrack
- Department of Psychology, Stanford University, Palo Alto, CA, USA
| | - F W Sabb
- Robert and Beverly Lewis Center for Neuroimaging, University of Oregon, Eugene, OR, USA
| | - E Congdon
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | | | - M A Scult
- Department of Psychology & Neuroscience, Laboratory of NeuroGenetics, Duke University, Durham, NC, USA
| | - D Dickinson
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA
| | - R E Straub
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - G Donohoe
- Department of Psychology, National University of Ireland, Galway, Ireland
| | - D Morris
- Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - A Corvin
- Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - M Gill
- Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - A R Hariri
- Department of Psychology & Neuroscience, Laboratory of NeuroGenetics, Duke University, Durham, NC, USA
| | - D R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - N Pendleton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK,Manchester Medical School, Institute of Brain, Behaviour, and Mental Health, University of Manchester, Manchester, UK
| | - P Bitsios
- Department of Psychiatry and Behavioral Sciences, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - D Rujescu
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland,Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - S Le Hellard
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - M C Keller
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | - O A Andreassen
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - A K Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - T Lencz
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA,Division of Psychiatry Research, Zucker Hillside Hospital, 75-59 263rd Street, Glen Oaks, NY 11004, USA. E-mail:
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Reus LM, Shen X, Gibson J, Wigmore E, Ligthart L, Adams MJ, Davies G, Cox SR, Hagenaars SP, Bastin ME, Deary IJ, Whalley HC, McIntosh AM. Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank. Sci Rep 2017; 7:42140. [PMID: 28186152 PMCID: PMC5301496 DOI: 10.1038/srep42140] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 01/03/2017] [Indexed: 12/11/2022] Open
Abstract
Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.
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Affiliation(s)
- L. M. Reus
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - X. Shen
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - J. Gibson
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - E. Wigmore
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - L. Ligthart
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - M. J. Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - G. Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - S. R. Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - S. P. Hagenaars
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - M. E. Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - I. J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - H. C. Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - A. M. McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
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25
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Navrady LB, Ritchie SJ, Chan SWY, Kerr DM, Adams MJ, Hawkins EH, Porteous D, Deary IJ, Gale CR, Batty GD, McIntosh AM. Intelligence and neuroticism in relation to depression and psychological distress: Evidence from two large population cohorts. Eur Psychiatry 2017; 43:58-65. [PMID: 28365468 PMCID: PMC5486156 DOI: 10.1016/j.eurpsy.2016.12.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Revised: 12/23/2016] [Accepted: 12/28/2016] [Indexed: 11/28/2022] Open
Abstract
Background Neuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined. Methods Associations and interactions between neuroticism and general intelligence (g) on MDD, self-reported depression, and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, n = 19,200) and UK Biobank (n = 90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS. Results Neuroticism was strongly associated with increased risk for depression and higher psychological distress in both samples. Although intelligence conferred no consistent independent effects on depression, it did increase the risk for depression across samples once neuroticism was adjusted for. Results suggest that higher intelligence may ameliorate the association between neuroticism and self-reported depression although no significant interaction was found for clinical MDD. Intelligence was inversely associated with psychological distress across cohorts. A small interaction was found across samples such that lower psychological distress associates with higher intelligence and lower neuroticism, although effect sizes were small. Conclusions From two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on psychological distress. Intelligence does not confer protection against diagnosis of depression in those high in neuroticism.
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Affiliation(s)
- L B Navrady
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.
| | - S J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; Department of Psychology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK
| | - S W Y Chan
- Section of Clinical Psychology, University of Edinburgh, Medical Quad, Teviot Place, Edinburgh, EH8 9AG, UK
| | - D M Kerr
- NHS Greater Glasgow and Clyde, 1055 Great Western Road, Glasgow, G12 0XH, UK
| | - M J Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - E H Hawkins
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - D Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; Medical Genetics Section, Centre for Genetics and Experimental Medicine, Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK; Generation Scotland, Centre for Genetics and Experimental Medicine, Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; Department of Psychology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; Generation Scotland, Centre for Genetics and Experimental Medicine, Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - C R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, SO16 6YD, UK
| | - G D Batty
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK; Alzheimer Scotland Dementia Research Centre, Department of Psychology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7, George Square, Edinburgh, EH8 9JZ, UK; Generation Scotland, Centre for Genetics and Experimental Medicine, Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
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26
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Del C Valdés Hernández M, Kyle J, Allan J, Allerhand M, Clark H, Muñoz Manieg S, Royle NA, Gow AJ, Pattie A, Corley J, Bastin ME, Starr JM, Wardlaw JM, Deary IJ, Combet E. Dietary Iodine Exposure and Brain Structures and Cognition in Older People. Exploratory Analysis in the Lothian Birth Cohort 1936. J Nutr Health Aging 2017; 21:971-979. [PMID: 29083437 DOI: 10.1007/s12603-017-0954-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND Iodine deficiency is one of the three key micronutrient deficiencies highlighted as major public health issues by the World Health Organisation. Iodine deficiency is known to cause brain structural alterations likely to affect cognition. However, it is not known whether or how different (lifelong) levels of exposure to dietary iodine influences brain health and cognitive functions. METHODS From 1091 participants initially enrolled in The Lothian Birth Cohort Study 1936, we obtained whole diet data from 882. Three years later, from 866 participants (mean age 72 yrs, SD±0.8), we obtained cognitive information and ventricular, hippocampal and normal and abnormal tissue volumes from brain structural magnetic resonance imaging scans (n=700). We studied the brain structure and cognitive abilities of iodine-rich food avoiders/low consumers versus those with a high intake in iodine-rich foods (namely dairy and fish). RESULTS We identified individuals (n=189) with contrasting diets, i) belonging to the lowest quintiles for dairy and fish consumption, ii) milk avoiders, iii) belonging to the middle quintiles for dairy and fish consumption, and iv) belonging to the middle quintiles for dairy and fish consumption. Iodine intake was secured mostly though the diet (n=10 supplement users) and was sufficient for most (75.1%, median 193 µg/day). In individuals from these groups, brain lateral ventricular volume was positively associated with fat, energy and protein intake. The associations between iodine intake and brain ventricular volume and between consumption of fish products (including fish cakes and fish-containing pasties) and white matter hyperintensities (p=0.03) the latest being compounded by sodium, proteins and saturated fats, disappeared after type 1 error correction. CONCLUSION In this large Scottish older cohort, the proportion of individuals reporting extreme (low vs. high)/medium iodine consumption is small. In these individuals, low iodine-rich food intake was associated with increased brain volume shrinkage, raising an important hypothesis worth being explored for designing appropriate guidelines.
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Affiliation(s)
- M Del C Valdés Hernández
- Dr. Maria C. Valdés Hernández, Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK. Telephone:+44-131-4659527, Fax: +44-131-3325150, E-mail:
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27
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Hagenaars SP, Harris SE, Davies G, Hill WD, Liewald DCM, Ritchie SJ, Marioni RE, Fawns-Ritchie C, Cullen B, Malik R, Worrall BB, Sudlow CLM, Wardlaw JM, Gallacher J, Pell J, McIntosh AM, Smith DJ, Gale CR, Deary IJ. Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia. Mol Psychiatry 2016; 21:1624-1632. [PMID: 26809841 PMCID: PMC5078856 DOI: 10.1038/mp.2015.225] [Citation(s) in RCA: 235] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Revised: 11/19/2015] [Accepted: 12/07/2015] [Indexed: 12/23/2022]
Abstract
Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular-metabolic, neuropsychiatric, physiological-anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer's disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples.
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Affiliation(s)
- S P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - C Fawns-Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - B Cullen
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - R Malik
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany
| | - METASTROKE Consortium, International Consortium for Blood Pressure GWAS
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - SpiroMeta Consortium
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - CHARGE Consortium Pulmonary Group, CHARGE Consortium Aging and Longevity Group
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - B B Worrall
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - C L M Sudlow
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Gallacher
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - J Pell
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - D J Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - C R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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28
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Montgomery J, Hendry J, Wilson JA, Deary IJ, MacKenzie K. Pragmatic detection of anxiety and depression in a prospective cohort of voice outpatient clinic attenders. Clin Otolaryngol 2016; 41:2-7. [PMID: 25973976 DOI: 10.1111/coa.12459] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/10/2015] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To evaluate diagnostic performance of the emotional domain of the VoiSS questionnaire compared with the Hospital Anxiety and Depression Scale (HADS). DESIGN Cross-sectional questionnaire study. SETTING Tertiary referral centre voice clinic. PARTICIPANTS 210 consecutive voice clinic patients. MAIN OUTCOME MEASURES Screening with VoiSS and HADS questionnaires. Paired comparison, correlation, multinomial logistic regression and receiver-operating characteristic (ROC) curve analysis. RESULTS A total of 177 returned complete data sets. Ninety-six patients (54.2%) had functional dysphonia, and 81 (45.8%) had organic laryngeal disorders. Mean total VoiSS score = 39.7/120 (standard deviation (sd) 22.2). Mean emotional VoiSS subscale = 7.6/22 (sd 7.5). Mean HADS anxiety = 6.5/21 (sd 5.2) and depression mean = 7.1/21 (sd 4.8). There were 35 (20%) borderline anxiety and/or depression scores and 30 (17%) scores considered positive for 'caseness'. There was strong correlation between emotional VoiSS and HADS anxiety (Spearman's Rho = 0.68, P < 0.001) and HADS depression (Spearman's Rho = 0.62, P < 0.001). ROC curve analysis exhibited significant association between emotional VoiSS and HADS 'caseness' (area under curve = 0.88). In addition, functional dysphonia patients had lower mean VoiSS and HADS scores than patients with identifiable laryngeal abnormalities. CONCLUSION The VoiSS emotional subscale strongly correlates with HADS anxiety and depression scores and could be used as a measure of psychological distress. This could allow targeted psychological strategies, without additional psychometric questionnaires. Functional dysphonia has less association with psychological distress than certain organic laryngological disorders.
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Affiliation(s)
- J Montgomery
- Department of Otolaryngology, Head and Neck surgery, Glasgow Royal Infirmary, Glasgow, UK
| | - J Hendry
- Department of Otolaryngology, Head and Neck surgery, Glasgow Royal Infirmary, Glasgow, UK
| | - J A Wilson
- Department of Otolaryngology, Head and Neck Surgery, Freeman Hospital, University of Newcastle, Newcastle upon Tyne, UK
| | - I J Deary
- MRC Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - K MacKenzie
- Department of Otolaryngology, Head and Neck surgery, Glasgow Royal Infirmary, Glasgow, UK
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29
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Marioni RE, Yang J, Dykiert D, Mõttus R, Campbell A, Davies G, Hayward C, Porteous DJ, Visscher PM, Deary IJ. Assessing the genetic overlap between BMI and cognitive function. Mol Psychiatry 2016; 21:1477-82. [PMID: 26857597 PMCID: PMC4863955 DOI: 10.1038/mp.2015.205] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Revised: 10/22/2015] [Accepted: 11/13/2015] [Indexed: 01/19/2023]
Abstract
Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=-0.11; high body mass index (BMI)-low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)-GREML; independent samples bivariate GCTA-GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of -0.51 (s.e. 0.15) was observed using the same-sample GCTA-GREML approach compared with -0.10 (s.e. 0.08) from the independent-samples GCTA-GREML approach and -0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10(-7)) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10(-5), which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function.
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Affiliation(s)
- R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia,Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, EH4 2XU, UK. E-mail:
| | - J Yang
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - D Dykiert
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - R Mõttus
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - C Hayward
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - D J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - P M Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia,University of Queensland Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK,Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
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30
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Dykiert D, Der G, Starr JM, Deary IJ. Why is Mini-Mental state examination performance correlated with estimated premorbid cognitive ability? Psychol Med 2016; 46:2647-2654. [PMID: 27377546 PMCID: PMC4988266 DOI: 10.1017/s0033291716001045] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Revised: 04/11/2016] [Accepted: 04/21/2016] [Indexed: 11/07/2022]
Abstract
BACKGROUND Tests requiring the pronunciation of irregular words are used to estimate premorbid cognitive ability in patients with clinical diagnoses, and prior cognitive ability in normal ageing. However, scores on these word-reading tests correlate with scores on the Mini-Mental State Examination (MMSE), a widely used screening test for possible cognitive pathology. This study aimed to test whether the word-reading tests' correlations with MMSE scores in healthy older people are explained by childhood IQ or education. METHOD Wechsler Test of Adult Reading (WTAR), National Adult Reading Test (NART), MMSE scores and information about education were obtained from 1024 70-year-olds, for whom childhood intelligence test scores were available. RESULTS WTAR and NART were positively correlated with the MMSE (r ≈ 0.40, p < 0.001). The shared variance of WTAR and NART with MMSE was significantly attenuated by ~70% after controlling for childhood intelligence test scores. Education explained little additional variance in the association between the reading tests and the MMSE. CONCLUSIONS MMSE, which is often used to index cognitive impairment, is associated with prior cognitive ability. MMSE score is related to scores on WTAR and NART largely due to their shared association with prior ability. Obtained MMSE scores should be interpreted in the context of prior ability (or WTAR/NART score as its proxy).
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Affiliation(s)
- D. Dykiert
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EdinburghUK
- Department of Psychology, University of Edinburgh, EdinburghUK
| | - G. Der
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EdinburghUK
- Medical Research Council/Chief Scientist Office Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - J. M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EdinburghUK
- Geriatric Medicine Unit, University of Edinburgh, EdinburghUK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, EdinburghUK
| | - I. J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EdinburghUK
- Department of Psychology, University of Edinburgh, EdinburghUK
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31
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Howrigan DP, Simonson MA, Davies G, Harris SE, Tenesa A, Starr JM, Liewald DC, Deary IJ, McRae A, Wright MJ, Montgomery GW, Hansell N, Martin NG, Payton A, Horan M, Ollier WE, Abdellaoui A, Boomsma DI, DeRosse P, Knowles EEM, Glahn DC, Djurovic S, Melle I, Andreassen OA, Christoforou A, Steen VM, Hellard SL, Sundet K, Reinvang I, Espeseth T, Lundervold AJ, Giegling I, Konte B, Hartmann AM, Rujescu D, Roussos P, Giakoumaki S, Burdick KE, Bitsios P, Donohoe G, Corley RP, Visscher PM, Pendleton N, Malhotra AK, Neale BM, Lencz T, Keller MC. Genome-wide autozygosity is associated with lower general cognitive ability. Mol Psychiatry 2016; 21:837-43. [PMID: 26390830 PMCID: PMC4803638 DOI: 10.1038/mp.2015.120] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Revised: 05/23/2015] [Accepted: 07/13/2015] [Indexed: 01/12/2023]
Abstract
Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.
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Affiliation(s)
- D P Howrigan
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Genetics, Broad Institute of Harvard and MIT, Cambridge Center, Cambridge, MA, USA
| | - M A Simonson
- Division of Data Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - G Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - A Tenesa
- Institute of Genetics and Molecular Medicine, MRC Human Genetics Unit, Western General Hospital, University of Edinburgh, Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, UK
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A McRae
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - G W Montgomery
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N Hansell
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - A Payton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - M Horan
- Centre for Clinical and Cognitive Neurosciences, Institute of Brain Behaviour and Mental Health, University of Manchester, Salford Royal NHS Foundation Trust, Salford, UK
| | - W E Ollier
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - A Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, The Netherlands
| | - P DeRosse
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Hofstra North Shore - LIJ School of Medicine, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA
| | - E E M Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - D C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - S Djurovic
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Oslo University Hospital, Oslo, Norway
| | - I Melle
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Oslo University Hospital, Oslo, Norway
- University of Oslo, Oslo, Norway
| | - O A Andreassen
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Oslo University Hospital, Oslo, Norway
- University of Oslo, Oslo, Norway
| | - A Christoforou
- K.G. Jebsen Centre for Psychosis Research, Dr. Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - V M Steen
- K.G. Jebsen Centre for Psychosis Research, Dr. Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - S L Hellard
- K.G. Jebsen Centre for Psychosis Research, Dr. Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - K Sundet
- NORMENT, KG Jebsen Centre, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - T Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway
| | - A J Lundervold
- K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Kavli Research Centre for Aging and Dementia, Haraldsplass Deaconess Hospital, Bergen, Norway
| | - I Giegling
- Department of Psychiatry, University of Halle, Halle, Germany
| | - B Konte
- Department of Psychiatry, University of Halle, Halle, Germany
| | - A M Hartmann
- Department of Psychiatry, University of Halle, Halle, Germany
| | - D Rujescu
- Department of Psychiatry, University of Halle, Halle, Germany
| | - P Roussos
- Department of Psychiatry, Friedman Brain Institute, Department of Genetics and Genomic Sciences, and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Mental Illness Research Education and Clinical Center (MIRECC), Bronx, NY, USA
| | - S Giakoumaki
- Department of Psychology, University of Crete, Rethymno, Crete, Greece
| | - K E Burdick
- Department of Psychiatry, Friedman Brain Institute, Department of Genetics and Genomic Sciences, and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - P Bitsios
- Department of Psychiatry, Faculty of Medicine, University of Crete, Heraklion, Crete, Greece
- Computational Medicine Laboratory, Institute of Computer Science at FORTH, Heraklion, Greece
| | - G Donohoe
- School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - R P Corley
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - P M Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - N Pendleton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - A K Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Hofstra North Shore - LIJ School of Medicine, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA
| | - B M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Genetics, Broad Institute of Harvard and MIT, Cambridge Center, Cambridge, MA, USA
| | - T Lencz
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Hofstra North Shore - LIJ School of Medicine, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA
| | - M C Keller
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
- Department of Psychology, University of Colorado at Boulder, Boulder, CO, USA
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32
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Gale CR, Hagenaars SP, Davies G, Hill WD, Liewald DCM, Cullen B, Penninx BW, Boomsma DI, Pell J, McIntosh AM, Smith DJ, Deary IJ, Harris SE. Pleiotropy between neuroticism and physical and mental health: findings from 108 038 men and women in UK Biobank. Transl Psychiatry 2016; 6:e791. [PMID: 27115122 PMCID: PMC4872414 DOI: 10.1038/tp.2016.56] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Revised: 01/15/2016] [Accepted: 03/05/2016] [Indexed: 12/14/2022] Open
Abstract
People with higher levels of neuroticism have an increased risk of several types of mental disorder. Higher neuroticism has also been associated, less consistently, with increased risk of various physical health outcomes. We hypothesised that these associations may, in part, be due to shared genetic influences. We tested for pleiotropy between neuroticism and 17 mental and physical diseases or health traits using linkage disequilibrium regression and polygenic profile scoring. Genetic correlations were derived between neuroticism scores in 108 038 people in the UK Biobank and health-related measures from 14 large genome-wide association studies (GWASs). Summary information for the 17 GWASs was used to create polygenic risk scores for the health-related measures in the UK Biobank participants. Associations between the health-related polygenic scores and neuroticism were examined using regression, adjusting for age, sex, genotyping batch, genotyping array, assessment centre and population stratification. Genetic correlations were identified between neuroticism and anorexia nervosa (rg=0.17), major depressive disorder (rg=0.66) and schizophrenia (rg=0.21). Polygenic risk for several health-related measures were associated with neuroticism, in a positive direction in the case of bipolar disorder, borderline personality, major depressive disorder, negative affect, neuroticism (Genetics of Personality Consortium), schizophrenia, coronary artery disease, and smoking (β between 0.009-0.043), and in a negative direction in the case of body mass index (β=-0.0095). A high level of pleiotropy exists between neuroticism and some measures of mental and physical health, particularly major depressive disorder and schizophrenia.
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Affiliation(s)
- C R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK,MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK,MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK. E-mail:
| | - S P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK,Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - B Cullen
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - B W Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands
| | | | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - J Pell
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - D J Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
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33
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Clarke TK, Lupton MK, Fernandez-Pujals AM, Starr J, Davies G, Cox S, Pattie A, Liewald DC, Hall LS, MacIntyre DJ, Smith BH, Hocking LJ, Padmanabhan S, Thomson PA, Hayward C, Hansell NK, Montgomery GW, Medland SE, Martin NG, Wright MJ, Porteous DJ, Deary IJ, McIntosh AM. Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population. Mol Psychiatry 2016; 21:419-25. [PMID: 25754080 PMCID: PMC4759203 DOI: 10.1038/mp.2015.12] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Revised: 11/25/2014] [Accepted: 12/19/2014] [Indexed: 12/16/2022]
Abstract
Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people with ASD compared with controls, but consistent evidence is lacking. Few studies have examined the genetic overlap between cognitive ability and ASD/ADHD. The aim of this study was to examine the polygenic overlap between ASD/ADHD and cognitive ability in individuals from the general population. Polygenic risk for ADHD and ASD was calculated from genome-wide association studies of ASD and ADHD conducted by the Psychiatric Genetics Consortium. Risk scores were created in three independent cohorts: Generation Scotland Scottish Family Health Study (GS:SFHS) (n=9863), the Lothian Birth Cohorts 1936 and 1921 (n=1522), and the Brisbane Adolescent Twin Sample (BATS) (n=921). We report that polygenic risk for ASD is positively correlated with general cognitive ability (beta=0.07, P=6 × 10(-7), r(2)=0.003), logical memory and verbal intelligence in GS:SFHS. This was replicated in BATS as a positive association with full-scale intelligent quotient (IQ) (beta=0.07, P=0.03, r(2)=0.005). We did not find consistent evidence that polygenic risk for ADHD was associated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=-0.08, Z=-3.3, P=0.001) was observed in the Lothian Birth Cohorts. These findings are in individuals from the general population, suggesting that the relationship between genetic risk for ASD and intelligence is partly independent of clinical state. These data suggest that common genetic variation relevant for ASD influences general cognitive ability.
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Affiliation(s)
- T-K Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK,Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK. E-mail:
| | - M K Lupton
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - J Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - S Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - L S Hall
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - D J MacIntyre
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - B H Smith
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - L J Hocking
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - S Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - P A Thomson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK,Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - C Hayward
- Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,MRC Human Genetics, MRC IGMM, University of Edinburgh, Edinburgh, Scotland, UK
| | - N K Hansell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - G W Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - S E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - N G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - M J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - D J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK,Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,MRC Human Genetics, MRC IGMM, University of Edinburgh, Edinburgh, Scotland, UK,Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK,Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,MRC Human Genetics, MRC IGMM, University of Edinburgh, Edinburgh, Scotland, UK,Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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34
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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: 103] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [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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Cullen B, Nicholl BI, Mackay DF, Martin D, Ul-Haq Z, McIntosh A, Gallacher J, Deary IJ, Pell JP, Evans JJ, Smith DJ. Cognitive function and lifetime features of depression and bipolar disorder in a large population sample: Cross-sectional study of 143,828 UK Biobank participants. Eur Psychiatry 2015; 30:950-8. [PMID: 26647871 DOI: 10.1016/j.eurpsy.2015.08.006] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Accepted: 08/18/2015] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND This study investigated differences in cognitive performance between middle-aged adults with and without a lifetime history of mood disorder features, adjusting for a range of potential confounders. METHODS Cross-sectional analysis of baseline data from the UK Biobank cohort. Adults aged 40-69 (n=143,828) were assessed using measures of reasoning, reaction time and memory. Self-reported data on lifetime features of major depression and bipolar disorder were used to construct groups for comparison against controls. Regression models examined the association between mood disorder classification and cognitive performance, adjusting for sociodemographic, lifestyle and clinical confounders. RESULTS Inverse associations between lifetime history of bipolar or severe recurrent depression features and cognitive performance were attenuated or reversed after adjusting for confounders, including psychotropic medication use and current depressive symptoms. Participants with a lifetime history of single episode or moderate recurrent depression features outperformed controls to a small (but statistically significant) degree, independent of adjustment for confounders. There was a significant interaction between use of psychotropic medication and lifetime mood disorder features, with reduced cognitive performance observed in participants taking psychotropic medication. CONCLUSIONS In this general population sample of adults in middle age, lifetime features of recurrent depression or bipolar disorder were only associated with cognitive impairment within unadjusted analyses. These findings underscore the importance of adjusting for potential confounders when investigating mood disorder-related cognitive function.
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Affiliation(s)
- B Cullen
- Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Ground Floor, Office Block, Queen Elizabeth University Hospital, Glasgow, G51 4TF UK.
| | - B I Nicholl
- General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - D F Mackay
- Public Health, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - D Martin
- Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Ground Floor, Office Block, Queen Elizabeth University Hospital, Glasgow, G51 4TF UK
| | - Z Ul-Haq
- Public Health, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK; Institute of Public Health and Social Sciences, Khyber Medical University, Peshawar, Pakistan
| | - A McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - J Gallacher
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - J P Pell
- Public Health, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - J J Evans
- Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Ground Floor, Office Block, Queen Elizabeth University Hospital, Glasgow, G51 4TF UK
| | - D J Smith
- Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Ground Floor, Office Block, Queen Elizabeth University Hospital, Glasgow, G51 4TF UK
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36
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Der G, Deary IJ. OP31 Cognitive ability and reaction time are associated with major causes of mortality: evidence from a population based prospective cohort study. Br J Soc Med 2015. [DOI: 10.1136/jech-2015-206256.30] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Karama S, Ducharme S, Corley J, Chouinard-Decorte F, Starr JM, Wardlaw JM, Bastin ME, Deary IJ. Cigarette smoking and thinning of the brain's cortex. Mol Psychiatry 2015; 20:778-85. [PMID: 25666755 PMCID: PMC4430302 DOI: 10.1038/mp.2014.187] [Citation(s) in RCA: 118] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2014] [Revised: 11/04/2014] [Accepted: 11/28/2014] [Indexed: 12/30/2022]
Abstract
Cigarette smoking is associated with cognitive decline and dementia, but the extent of the association between smoking and structural brain changes remains unclear. Importantly, it is unknown whether smoking-related brain changes are reversible after smoking cessation. We analyzed data on 504 subjects with recall of lifetime smoking data and a structural brain magnetic resonance imaging at age 73 years from which measures of cortical thickness were extracted. Multiple regression analyses were performed controlling for gender and exact age at scanning. To determine dose-response relationships, the association between smoking pack-years and cortical thickness was tested and then repeated, while controlling for a comprehensive list of covariates including, among others, cognitive ability before starting smoking. Further, we tested associations between cortical thickness and number of years since last cigarette, while controlling for lifetime smoking. There was a diffuse dose-dependent negative association between smoking and cortical thickness. Some negative dose-dependent cortical associations persisted after controlling for all covariates. Accounting for total amount of lifetime smoking, the cortex of subjects who stopped smoking seems to have partially recovered for each year without smoking. However, it took ~25 years for complete cortical recovery in affected areas for those at the mean pack-years value in this sample. As the cortex thins with normal aging, our data suggest that smoking is associated with diffuse accelerated cortical thinning, a biomarker of cognitive decline in adults. Although partial recovery appears possible, it can be a long process.
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Affiliation(s)
- S Karama
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Verdun, QC, Canada,Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada H3A 2B4. E-mail: or
| | - S Ducharme
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Psychiatry, McGill University Health Centre, Montreal, QC, Canada,Department of Psychiatry and Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA,Department of Neurology, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - J Corley
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - F Chouinard-Decorte
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - J M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Radiology, Division of Neuroimaging Sciences, Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Radiology, Division of Neuroimaging Sciences, Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Davies G, Armstrong N, Bis JC, Bressler J, Chouraki V, Giddaluru S, Hofer E, Ibrahim-Verbaas CA, Kirin M, Lahti J, van der Lee SJ, Le Hellard S, Liu T, Marioni RE, Oldmeadow C, Postmus I, Smith AV, Smith JA, Thalamuthu A, Thomson R, Vitart V, Wang J, Yu L, Zgaga L, Zhao W, Boxall R, Harris SE, Hill WD, Liewald DC, Luciano M, Adams H, Ames D, Amin N, Amouyel P, Assareh AA, Au R, Becker JT, Beiser A, Berr C, Bertram L, Boerwinkle E, Buckley BM, Campbell H, Corley J, De Jager PL, Dufouil C, Eriksson JG, Espeseth T, Faul JD, Ford I, Scotland G, Gottesman RF, Griswold ME, Gudnason V, Harris TB, Heiss G, Hofman A, Holliday EG, Huffman J, Kardia SLR, Kochan N, Knopman DS, Kwok JB, Lambert JC, Lee T, Li G, Li SC, Loitfelder M, Lopez OL, Lundervold AJ, Lundqvist A, Mather KA, Mirza SS, Nyberg L, Oostra BA, Palotie A, Papenberg G, Pattie A, Petrovic K, Polasek O, Psaty BM, Redmond P, Reppermund S, Rotter JI, Schmidt H, Schuur M, Schofield PW, Scott RJ, Steen VM, Stott DJ, van Swieten JC, Taylor KD, Trollor J, Trompet S, Uitterlinden AG, Weinstein G, Widen E, Windham BG, Jukema JW, Wright AF, Wright MJ, Yang Q, Amieva H, Attia JR, Bennett DA, Brodaty H, de Craen AJM, Hayward C, Ikram MA, Lindenberger U, Nilsson LG, Porteous DJ, Räikkönen K, Reinvang I, Rudan I, Sachdev PS, Schmidt R, Schofield PR, Srikanth V, Starr JM, Turner ST, Weir DR, Wilson JF, van Duijn C, Launer L, Fitzpatrick AL, Seshadri S, Mosley TH, Deary IJ. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949). Mol Psychiatry 2015; 20:183-92. [PMID: 25644384 PMCID: PMC4356746 DOI: 10.1038/mp.2014.188] [Citation(s) in RCA: 260] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Revised: 11/11/2014] [Accepted: 11/24/2014] [Indexed: 01/14/2023]
Abstract
General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53,949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10(-9), MIR2113; rs17522122, P=2.55 × 10(-8), AKAP6; rs10119, P=5.67 × 10(-9), APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10(-6)). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10(-17)). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C.
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Affiliation(s)
- G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - N Armstrong
- School of Mathematics and Statistics, University of Sydney, Sydney, NSW, Australia
| | - J C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - J Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - V Chouraki
- Inserm-UMR744, Institut Pasteur de Lille, Unité d'Epidémiologie et de Santé Publique, Lille, France,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - S Giddaluru
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - E Hofer
- Department of Neurology, Medical University of Graz, Graz, Austria,Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - C A Ibrahim-Verbaas
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands,Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Kirin
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - S J van der Lee
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - S Le Hellard
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - T Liu
- Max Planck Institute for Human Development, Berlin, Germany,Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - C Oldmeadow
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - I Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - A V Smith
- Icelandic Heart Association, Kopavogur, Iceland,University of Iceland, Reykjavik, Iceland
| | - J A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - A Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - R Thomson
- Menzies Research Institute, Hobart, Tasmania
| | - V Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - J Wang
- Framingham Heart Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - L Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - L Zgaga
- Department of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland,Andrija Stampar School of Public Health, Medical School, University of Zagreb, Zagreb, Croatia
| | - W Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - R Boxall
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - W D Hill
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - M Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - H Adams
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - D Ames
- National Ageing Research Institute, Royal Melbourne Hospital, Melbourne, VIC, Australia,Academic Unit for Psychiatry of Old Age, St George's Hospital, University of Melbourne, Kew, Australia
| | - N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - P Amouyel
- Inserm-UMR744, Institut Pasteur de Lille, Unité d'Epidémiologie et de Santé Publique, Lille, France
| | - A A Assareh
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - R Au
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - J T 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
| | - A Beiser
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - C Berr
- Inserm, U106, Montpellier, France,Université Montpellier I, Montpellier, France
| | - L Bertram
- Max Planck Institute for Molecular Genetics, Berlin, Germany,Faculty of Medicine, School of Public Health, Imperial College, London, UK
| | - E Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA,Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, University of Texas Health Science Center at Houston, Houston, TX, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - B M Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - H Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - J Corley
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - P L De Jager
- Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - C Dufouil
- Inserm U708, Neuroepidemiology, Paris, France,Inserm U897, Université Bordeaux Segalen, Bordeaux, France
| | - J G Eriksson
- Folkhälsan Research Centre, Helsinki, Finland,National Institute for Health and Welfare, Helsinki, Finland,Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland,Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
| | - T Espeseth
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre For Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - J D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - I Ford
- Robertson Center for Biostatistics, Glasgow, UK
| | - Generation Scotland
- Generation Scotland, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - R F Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - M E Griswold
- Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, MS, USA
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland,University of Iceland, Reykjavik, Iceland
| | - T B Harris
- Intramural Research Program National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - G Heiss
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - E G Holliday
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - J Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - S L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - N Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - J B Kwok
- Neuroscience Research Australia, Randwick, NSW, Australia,School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - J-C Lambert
- Inserm-UMR744, Institut Pasteur de Lille, Unité d'Epidémiologie et de Santé Publique, Lille, France
| | - T Lee
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - G Li
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - S-C Li
- Max Planck Institute for Human Development, Berlin, Germany,Technische Universität Dresden, Dresden, Germany
| | - M Loitfelder
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - O L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway,Kavli Research Centre for Aging and Dementia, Haraldsplass Deaconess Hospital, Bergen, Norway,K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
| | - A Lundqvist
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - K A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - S S Mirza
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - L Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden,Department of Radiation Sciences, Umeå University, Umeå, Sweden,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - B A Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - 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
| | - G Papenberg
- Max Planck Institute for Human Development, Berlin, Germany,Karolinska Institutet, Aging Research Center, Stockholm University, Stockholm, Sweden
| | - A Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - K Petrovic
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - O Polasek
- Faculty of Medicine, Department of Public Health, University of Split, Split, Croatia
| | - B M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA,Deparment of Epidemiology, University of Washington, Seattle, WA, USA,Deparment of Health Services, University of Washington, Seattle, WA, USA,Group Health Research Unit, Group Health Cooperative, Seattle, WA, USA
| | - P Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S Reppermund
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - J I Rotter
- Institute for Translational Genomics and Population Sciences Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Los Angeles, CA, USA,Division of Genetic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, USA
| | - H Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria,Centre for Molecular Medicine, Institute of Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - M Schuur
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands,Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - P W Schofield
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - R J Scott
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - V M Steen
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - D J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - J C van Swieten
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - K D Taylor
- Institute for Translational Genomics and Population Sciences Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Los Angeles, CA, USA,Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, USA
| | - J Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - S Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands,Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - A G 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
| | - G Weinstein
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - E Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - B G Windham
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - J W Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands,Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands,Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
| | - A F Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M J Wright
- Neuroimaging Genetics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Q Yang
- Framingham Heart Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - H Amieva
- Inserm U897, Université Bordeaux Segalen, Bordeaux, France
| | - J R Attia
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - D A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - H Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Dementia Collaborative Research Centre, University of New South Wales, Sydney, NSW, Australia
| | - A J M de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M A 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
| | - U Lindenberger
- Max Planck Institute for Human Development, Berlin, Germany
| | - L-G Nilsson
- ARC, Karolinska Institutet, Stockholm and UFBI, Umeå University, Umeå, Sweden
| | - D J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK,Generation Scotland, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - I Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - P S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - R Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - P R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia,Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - V Srikanth
- Menzies Research Institute, Hobart, Tasmania,Stroke and Ageing Research, Medicine, Southern Clinical School, Monash University, Melbourne, VIC, Australia
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - S T Turner
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - D R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - J F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - C van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - L Launer
- Intramural Research Program National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - A L Fitzpatrick
- Deparment of Epidemiology, University of Washington, Seattle, WA, USA,Department of Global Health, University of Washington, Seattle, WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - T H Mosley
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,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, Scotland, UK. E-mail:
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39
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Abstract
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for 'positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the 'missing heritability' gap.
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Affiliation(s)
- R Plomin
- King's College London, MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, DeCrespigny Park, London, UK
| | - I J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Hernández MDCV, Allan J, Glatz A, Kyle J, Corley J, Brett CE, Maniega SM, Royle NA, Bastin ME, Starr JM, Deary IJ, Wardlaw JM. Exploratory analysis of dietary intake and brain iron accumulation detected using magnetic resonance imaging in older individuals: the Lothian Birth Cohort 1936. J Nutr Health Aging 2015; 19:64-9. [PMID: 25560818 DOI: 10.1007/s12603-014-0523-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
CONTEXT Brain Iron Deposits (IDs) are associated with neurodegenerative diseases and impaired cognitive function in later life, but their cause is unknown. Animal studies have found evidence of relationships between dietary iron, calorie and cholesterol intake and brain iron accumulation. OBJECTIVES To investigate the relationship between iron, calorie, and cholesterol intake, blood indicators of iron status, and brain IDs in humans. DESIGN, SETTING AND PARTICIPANTS Cohort of 1063 community-dwelling older individuals born in 1936 (mean age 72.7years, SD=0.7) with dietary information, results from blood sample analyses and brain imaging data contemporaneously in old age. MEASUREMENTS Magnetic Resonance Imaging was used to assess regional volumes of brain IDs in basal ganglia, brainstem, white matter, thalamus, and cortex/border with the corticomedullary junction, using a fully automatic assessment procedure followed by individual checking/correction where necessary. Haemoglobin, red cell count, haematocrit, mean cell volume, ferritin and transferrin were obtained from blood samples and typical daily intake of iron, calories, and cholesterol were calculated from a validated food-frequency questionnaire. RESULTS Overall, 72.8% of the sample that had valid MRI (n=676) had brain IDs. The median total volume of IDs was 40mm3, inter-quartile range (IQR)=196. Basal ganglia IDs (median=35, IQR=159.5 mm3), were found in 70.6% of the sample. IDs in the brainstem were found in 12.9% of the sample, in the cortex in 1.9%, in the white matter in 6.1% and in the thalamus in 1.0%. The median daily intake of calories was 1808.5kcal (IQR=738.5), of cholesterol was 258.5mg (IQR=126.2) and of total iron was 11.7mg (IQR=5). Iron, calorie or cholesterol intake were not directly associated with brain IDs. However, caloric intake was associated with ferritin, an iron storage protein (p=0.01). CONCLUSION Our results suggest that overall caloric, iron and cholesterol intake are not associated with IDs in brains of healthy older individuals but caloric intake could be associated with iron storage. Further work is required to corroborate our findings on other samples and investigate the underlying mechanisms of brain iron accumulation.
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Affiliation(s)
- M del C Valdés Hernández
- Dr. Maria C. Valdés Hernández, Brain Research Imaging Centre, Department of Neuroimaging Sciences, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK. Telephone: +44-131-537-3093, Fax: +44-131-332-5150, E-mail:
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Christoforou A, Espeseth T, Davies G, Fernandes CPD, Giddaluru S, Mattheisen M, Tenesa A, Harris SE, Liewald DC, Payton A, Ollier W, Horan M, Pendleton N, Haggarty P, Djurovic S, Herms S, Hoffman P, Cichon S, Starr JM, Lundervold A, Reinvang I, Steen VM, Deary IJ, Le Hellard S. GWAS-based pathway analysis differentiates between fluid and crystallized intelligence. Genes Brain Behav 2014; 13:663-74. [PMID: 24975275 PMCID: PMC4261989 DOI: 10.1111/gbb.12152] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Revised: 05/11/2014] [Accepted: 06/25/2014] [Indexed: 01/26/2023]
Abstract
Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.
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Affiliation(s)
- A Christoforou
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical ScienceUniversity of Bergen
- Dr. Einar Martens Research Group for Biological PsychiatryCentre for Medical Genetics and Molecular Medicine, Haukeland University Hospital Bergen
| | - T Espeseth
- Department of PsychologyUniversity of Oslo
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University HospitalOslo, Norway
| | - G Davies
- Department of PsychologyUniversity of Edinburgh
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of Edinburgh
- Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General HospitalEdinburgh, UK
| | - C P D Fernandes
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical ScienceUniversity of Bergen
- Dr. Einar Martens Research Group for Biological PsychiatryCentre for Medical Genetics and Molecular Medicine, Haukeland University Hospital Bergen
| | - S Giddaluru
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical ScienceUniversity of Bergen
- Dr. Einar Martens Research Group for Biological PsychiatryCentre for Medical Genetics and Molecular Medicine, Haukeland University Hospital Bergen
| | - M Mattheisen
- Department of Genomics, Life & Brain Center, University of BonnBonn, Germany
- Department of Biomedicine and the Centre for Integrative Sequencing, Aarhus UniversityAarhus, Denmark
- Institute for Genomic Mathematics, University of BonnBonn, Germany
| | - A Tenesa
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, University of EdinburghEdinburgh
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of EdinburghRoslin
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of Edinburgh
- Medical Genetics Section, Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General HospitalEdinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of Edinburgh
| | - A Payton
- Centre for Integrated Genomic Medical Research, Institute for Population HealthUniversity of Manchester
| | - W Ollier
- Centre for Integrated Genomic Medical Research, Institute for Population HealthUniversity of Manchester
| | - M Horan
- Centre for Clinical and Cognitive Neurosciences, Institute of Brain Behaviour and Mental Health, University of ManchesterManchester
| | - N Pendleton
- Centre for Clinical and Cognitive Neurosciences, Institute of Brain Behaviour and Mental Health, University of ManchesterManchester
| | - P Haggarty
- Nutrition and Epigenetics Group, Rowett Institute of Nutrition and Health, University of AberdeenAberdeen, UK
| | - S Djurovic
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University HospitalOslo, Norway
| | - S Herms
- Department of Genomics, Life & Brain Center, University of BonnBonn, Germany
- Institute of Human Genetics, University of BonnBonn, Germany
- Division of Medical Genetics, Department of Biomedicine, University of BaselBasel, Switzerland
| | - P Hoffman
- Department of Genomics, Life & Brain Center, University of BonnBonn, Germany
- Institute of Human Genetics, University of BonnBonn, Germany
- Division of Medical Genetics, Department of Biomedicine, University of BaselBasel, Switzerland
- Institute of Neuroscience and Medicine (INM-1), Research Center JuelichJuelich, Germany
| | - S Cichon
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical ScienceUniversity of Bergen
- Department of Genomics, Life & Brain Center, University of BonnBonn, Germany
- Institute of Human Genetics, University of BonnBonn, Germany
- Division of Medical Genetics, Department of Biomedicine, University of BaselBasel, Switzerland
- Institute of Neuroscience and Medicine (INM-1), Research Center JuelichJuelich, Germany
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of Edinburgh
| | - A Lundervold
- Department of Biological and Medical PsychologyUniversity of Bergen
- Kavli Research Centre for Aging and DementiaHaraldsplass Deaconess Hospital
- K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of BergenBergen, Norway
| | - I Reinvang
- Department of PsychologyUniversity of Oslo
| | - V M Steen
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical ScienceUniversity of Bergen
- Dr. Einar Martens Research Group for Biological PsychiatryCentre for Medical Genetics and Molecular Medicine, Haukeland University Hospital Bergen
| | - I J Deary
- Department of PsychologyUniversity of Edinburgh
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of Edinburgh
| | - S Le Hellard
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical ScienceUniversity of Bergen
- Dr. Einar Martens Research Group for Biological PsychiatryCentre for Medical Genetics and Molecular Medicine, Haukeland University Hospital Bergen
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Cooper R, Benzeval M, Deary IJ, Dennison EM, Der G, Gale CR, Inskip HM, Jagger C, Kirkwood TB, Lawlor DA, Robinson SM, Starr JM, Steptoe A, Tilling K, Kuh D, Cooper C, Aihie Sayer A, Dodds RM, Syddall HE. OP02 Grip strength across the life course: normative data from twelve British studies. Br J Soc Med 2014. [DOI: 10.1136/jech-2014-204726.5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Shenkin SD, Laidlaw K, Allerhand M, Mead GE, Starr JM, Deary IJ. 117 * LIFE COURSE INFLUENCES OF PHYSICAL AND COGNITIVE FUNCTION AND PERSONALITY ON ATTITUDES TO AGING IN THE LOTHIAN BIRTH COHORT 1936. Age Ageing 2014. [DOI: 10.1093/ageing/afu045.4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Thomson PA, Parla JS, McRae AF, Kramer M, Ramakrishnan K, Yao J, Soares DC, McCarthy S, Morris SW, Cardone L, Cass S, Ghiban E, Hennah W, Evans KL, Rebolini D, Millar JK, Harris SE, Starr JM, MacIntyre DJ, McIntosh AM, Watson JD, Deary IJ, Visscher PM, Blackwood DH, McCombie WR, Porteous DJ. 708 Common and 2010 rare DISC1 locus variants identified in 1542 subjects: analysis for association with psychiatric disorder and cognitive traits. Mol Psychiatry 2014; 19:668-75. [PMID: 23732877 PMCID: PMC4031635 DOI: 10.1038/mp.2013.68] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2012] [Revised: 04/22/2013] [Accepted: 04/23/2013] [Indexed: 12/16/2022]
Abstract
A balanced t(1;11) translocation that transects the Disrupted in schizophrenia 1 (DISC1) gene shows genome-wide significant linkage for schizophrenia and recurrent major depressive disorder (rMDD) in a single large Scottish family, but genome-wide and exome sequencing-based association studies have not supported a role for DISC1 in psychiatric illness. To explore DISC1 in more detail, we sequenced 528 kb of the DISC1 locus in 653 cases and 889 controls. We report 2718 validated single-nucleotide polymorphisms (SNPs) of which 2010 have a minor allele frequency of <1%. Only 38% of these variants are reported in the 1000 Genomes Project European subset. This suggests that many DISC1 SNPs remain undiscovered and are essentially private. Rare coding variants identified exclusively in patients were found in likely functional protein domains. Significant region-wide association was observed between rs16856199 and rMDD (P=0.026, unadjusted P=6.3 × 10(-5), OR=3.48). This was not replicated in additional recurrent major depression samples (replication P=0.11). Combined analysis of both the original and replication set supported the original association (P=0.0058, OR=1.46). Evidence for segregation of this variant with disease in families was limited to those of rMDD individuals referred from primary care. Burden analysis for coding and non-coding variants gave nominal associations with diagnosis and measures of mood and cognition. Together, these observations are likely to generalise to other candidate genes for major mental illness and may thus provide guidelines for the design of future studies.
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Affiliation(s)
- P A Thomson
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - J S Parla
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - A F McRae
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - M Kramer
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - K Ramakrishnan
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - J Yao
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - D C Soares
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - S McCarthy
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - S W Morris
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - L Cardone
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - S Cass
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - E Ghiban
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - W Hennah
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- Institute for Molecular Medicine, Finland FIMM, University of Helsinki, Helsinki, Finland
| | - K L Evans
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - D Rebolini
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - J K Millar
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - S E Harris
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - D J MacIntyre
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Generation Scotland7
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, QLD, Australia
- Institute for Molecular Medicine, Finland FIMM, University of Helsinki, Helsinki, Finland
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Generation Scotland, A Collaboration between the University Medical Schools and NHS, Aberdeen, Dundee, Edinburgh and Glasgow, UK
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - J D Watson
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - P M Visscher
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - D H Blackwood
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - W R McCombie
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - D J Porteous
- Medical Genetics Section, University of Edinburgh Molecular Medicine Centre, MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
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Luciano M, Mõttus R, Harris SE, Davies G, Payton A, Ollier WER, Horan MA, Starr JM, Porteous DJ, Pendleton N, Deary IJ. Predicting cognitive ability in ageing cohorts using Type 2 diabetes genetic risk. Diabet Med 2014; 31:714-20. [PMID: 24344862 DOI: 10.1111/dme.12389] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Revised: 10/29/2013] [Accepted: 12/12/2013] [Indexed: 02/06/2023]
Abstract
AIMS To investigate whether there is overlap in the genetic determinants of Type 2 diabetes and cognitive ageing by testing whether a genetic risk score for Type 2 diabetes can predict variation in cognitive function in older people without dementia. METHODS Type 2 diabetes genetic risk scores were estimated using various single nucleotide polymorphism significance inclusion criteria from an initial genome-wide association study, the largest in Type 2 diabetes to date. Scores were available for 2775-3057 individuals, depending on the cognitive trait. RESULTS Type 2 diabetes genetic risk was associated with self-reported diabetes mellitus. Across varying single nucleotide polymorphism-inclusion levels, a significant association between Type 2 diabetes genetic risk and change in general cognitive function was found (median r = 0.04); however, this was such that higher Type 2 diabetes genetic risk related to higher cognitive scores. CONCLUSIONS To investigate more fully the source of the often observed comorbidity between Type 2 diabetes and cognitive impairment, one direction for future research will be to use cognitive ability polygenic risk scores to predict Type 2 diabetes in line with the reverse causation hypothesis that people with lower pre-morbid cognitive ability are more likely to develop Type 2 diabetes.
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Affiliation(s)
- M Luciano
- Department of Psychology, The University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
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Abstract
BACKGROUND Observations that older people who enjoy life more tend to live longer suggest that psychological well-being may be a potential resource for healthier ageing. We investigated whether psychological well-being was associated with incidence of physical frailty. METHOD We used multinomial logistic regression to examine the prospective relationship between psychological well-being, assessed using the CASP-19, a questionnaire that assesses perceptions of control, autonomy, self-realization and pleasure, and incidence of physical frailty or pre-frailty, defined according to the Fried criteria (unintentional weight loss, weakness, self-reported exhaustion, slow walking speed and low physical activity), in 2557 men and women aged 60 to ≥ 90 years from the English Longitudinal Study of Ageing (ELSA). RESULTS Men and women with higher levels of psychological well-being were less likely to become frail over the 4-year follow-up period. For a standard deviation higher score in psychological well-being at baseline, the relative risk ratio (RR) for incident frailty, adjusted for age, sex and baseline frailty status, was 0.46 [95% confidence interval (CI) 0.40-0.54]. There was a significant association between psychological well-being and risk of pre-frailty (RR 0.69, 95% CI 0.63-0.77). Examination of scores for hedonic (pleasure) and eudaimonic (control, autonomy and self-realization) well-being showed that higher scores on both were associated with decreased risk. Associations were partially attenuated by further adjustment for other potential confounding factors but persisted. Incidence of pre-frailty or frailty was associated with a decline in well-being, suggesting that the relationship is bidirectional. CONCLUSIONS Maintaining a stronger sense of psychological well-being in later life may protect against the development of physical frailty. Future research needs to establish the mechanisms underlying these findings.
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Affiliation(s)
- C R Gale
- MRC Lifecourse Epidemiology Unit, University of Southampton, UK
| | - C Cooper
- MRC Lifecourse Epidemiology Unit, University of Southampton, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, UK
| | - A Aihie Sayer
- MRC Lifecourse Epidemiology Unit, University of Southampton, UK
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Benyamin B, Pourcain BS, Davis OS, Davies G, Hansell NK, Brion MJA, Kirkpatrick RM, Cents RAM, Franić S, Miller MB, Haworth CMA, Meaburn E, Price TS, Evans DM, Timpson N, Kemp J, Ring S, McArdle W, Medland SE, Yang J, Harris SE, Liewald DC, Scheet P, Xiao X, Hudziak JJ, de Geus EJC, Jaddoe VWV, Starr JM, Verhulst FC, Pennell C, Tiemeier H, Iacono WG, Palmer LJ, Montgomery GW, Martin NG, Boomsma DI, Posthuma D, McGue M, Wright MJ, Smith GD, Deary IJ, Plomin R, Visscher PM. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol Psychiatry 2014; 19:253-8. [PMID: 23358156 PMCID: PMC3935975 DOI: 10.1038/mp.2012.184] [Citation(s) in RCA: 167] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Revised: 10/28/2012] [Accepted: 11/12/2012] [Indexed: 01/11/2023]
Abstract
Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.
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Affiliation(s)
- B Benyamin
- The University of Queensland, Queensland Brain Institute, St Lucia, Queensland, Australia
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - BSt Pourcain
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - OS Davis
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - G Davies
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - NK Hansell
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - M-JA Brion
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
- School of Women's and Infants' Health, The University of Western Australia, Perth, Western Australia, Australia
| | - RM Kirkpatrick
- Department of Psychology, University of Minnesota, St Paul, MN, USA
| | - RAM Cents
- The Generation R Study Group, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - S Franić
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - MB Miller
- Department of Psychology, University of Minnesota, St Paul, MN, USA
| | - CMA Haworth
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - E Meaburn
- Department of Psychology, Birkbeck University of London, London, UK
| | - TS Price
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - DM Evans
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - N Timpson
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - J Kemp
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - S Ring
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - W McArdle
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - SE Medland
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - J Yang
- The University of Queensland Diamantina Institute, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - SE Harris
- Molecular Medicine Centre, Institute for Genetics and Molecular Medicine Centre, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - DC Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - P Scheet
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - X Xiao
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - JJ Hudziak
- Department of Psychiatry, College of Medicine, University of Vermont, Burlington, VT, USA
| | - EJC de Geus
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - VWV Jaddoe
- The Generation R Study Group, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - JM Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - FC Verhulst
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - C Pennell
- School of Women's and Infants' Health, The University of Western Australia, Perth, Western Australia, Australia
| | - H Tiemeier
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - WG Iacono
- Department of Psychology, University of Minnesota, St Paul, MN, USA
| | - LJ Palmer
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research, University of Toronto, Toronto, Ontario, Canada
- Samuel Lunenfeld Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - GW Montgomery
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - NG Martin
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - DI Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - D Posthuma
- Department of Child and Adolescent Psychiatry, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Neuroscience Campus Amsterdam (NCA), VU University Amsterdam and VU Medical Centre, Amsterdam, The Netherlands
- Department of Clinical Genetics, Section Medical Genomics, VU Medical Centre, Amsterdam, The Netherlands
| | - M McGue
- Department of Psychology, University of Minnesota, St Paul, MN, USA
- Department of Epidemiology, University of Southern Denmark, Odense, Denmark
| | - MJ Wright
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - G Davey Smith
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK
| | - IJ Deary
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - R Plomin
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - PM Visscher
- The University of Queensland, Queensland Brain Institute, St Lucia, Queensland, Australia
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia
- The University of Queensland Diamantina Institute, Princess Alexandra Hospital, Brisbane, Queensland, Australia
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Hill WD, Davies G, van de Lagemaat LN, Christoforou A, Marioni RE, Fernandes CPD, Liewald DC, Croning MDR, Payton A, Craig LCA, Whalley LJ, Horan M, Ollier W, Hansell NK, Wright MJ, Martin NG, Montgomery GW, Steen VM, Le Hellard S, Espeseth T, Lundervold AJ, Reinvang I, Starr JM, Pendleton N, Grant SGN, Bates TC, Deary IJ. Human cognitive ability is influenced by genetic variation in components of postsynaptic signalling complexes assembled by NMDA receptors and MAGUK proteins. Transl Psychiatry 2014; 4:e341. [PMID: 24399044 PMCID: PMC3905224 DOI: 10.1038/tp.2013.114] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2013] [Revised: 09/12/2013] [Accepted: 10/21/2013] [Indexed: 12/11/2022] Open
Abstract
Differences in general cognitive ability (intelligence) account for approximately half of the variation in any large battery of cognitive tests and are predictive of important life events including health. Genome-wide analyses of common single-nucleotide polymorphisms indicate that they jointly tag between a quarter and a half of the variance in intelligence. However, no single polymorphism has been reliably associated with variation in intelligence. It remains possible that these many small effects might be aggregated in networks of functionally linked genes. Here, we tested a network of 1461 genes in the postsynaptic density and associated complexes for an enriched association with intelligence. These were ascertained in 3511 individuals (the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium) phenotyped for general cognitive ability, fluid cognitive ability, crystallised cognitive ability, memory and speed of processing. By analysing the results of a genome wide association study (GWAS) using Gene Set Enrichment Analysis, a significant enrichment was found for fluid cognitive ability for the proteins found in the complexes of N-methyl-D-aspartate receptor complex; P=0.002. Replication was sought in two additional cohorts (N=670 and 2062). A meta-analytic P-value of 0.003 was found when these were combined with the CAGES consortium. The results suggest that genetic variation in the macromolecular machines formed by membrane-associated guanylate kinase (MAGUK) scaffold proteins and their interaction partners contributes to variation in intelligence.
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Affiliation(s)
- W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, Edinburgh, UK
| | - L N van de Lagemaat
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - A Christoforou
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - C P D Fernandes
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M D R Croning
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - A Payton
- Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK
| | - L C A Craig
- Public Health Nutrition Research Group Section of Population Health, University of Aberdeen, Aberdeen, UK
| | - L J Whalley
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - M Horan
- Centre for Clinical and Cognitive Neurosciences, Institute Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - W Ollier
- Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK
| | - N K Hansell
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - N G Martin
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - G W Montgomery
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - V M Steen
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - S Le Hellard
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - T Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway,KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway,Kavli Research Centre for Aging and Dementia, Haraldplass Hospital, Bergen, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - N Pendleton
- Centre for Clinical and Cognitive Neurosciences, Institute Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - S G N Grant
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - T C Bates
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK. E-mail:
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49
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Abstract
Cognitive deficits are core to the disability associated with many psychiatric disorders. Both variation in cognition and psychiatric risk show substantial heritability, with overlapping genetic variants contributing to both. Unsurprisingly, therefore, these fields have been mutually beneficial : just as cognitive studies of psychiatric risk variants may identify genes involved in cognition, so too can genome-wide studies based on cognitive phenotypes lead to genes relevant to psychiatric aetiology. The purpose of this review is to consider the main issues involved in the phenotypic characterization of cognition, and to describe the challenges associated with the transition to genomewide approaches. We conclude by describing the approaches currently being taken by the international consortia involving many investigators in the field internationally (e.g. Cognitive Genomics Consortium; COGENT) to overcome these challenges.
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Affiliation(s)
- G Donohoe
- Department of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Republic of Ireland.
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50
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Valdés Hernández MC, Piper RJ, Bastin ME, Royle NA, Maniega SM, Aribisala BS, Murray C, Deary IJ, Wardlaw JM. Morphologic, distributional, volumetric, and intensity characterization of periventricular hyperintensities. AJNR Am J Neuroradiol 2013; 35:55-62. [PMID: 23811980 DOI: 10.3174/ajnr.a3612] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE White matter hyperintensities are characteristic of old age and identifiable on FLAIR and T2-weighted MR imaging. They are typically separated into periventricular or deep categories. It is unclear whether the innermost segment of periventricular white matter hyperintensities is truly abnormal or is imaging artifacts. MATERIALS AND METHODS We used FLAIR MR imaging from 665 community-dwelling subjects 72-73 years of age without dementia. Periventricular white matter hyperintensities were visually allocated into 4 categories: 1) thin white line; 2) thick rim; 3) penetrating toward or confluent with deep white matter hyperintensities; and 4) diffuse ill-defined, labeled as "subtle extended periventricular white matter hyperintensities." We measured the maximum intensity and width of the periventricular white matter hyperintensities, mapped all white matter hyperintensities in 3D, and investigated associations between each category and hypertension, stroke, diabetes, hypercholesterolemia, cardiovascular disease, and total white matter hyperintensity volume. RESULTS The intensity patterns and morphologic features were different for each periventricular white matter hyperintensity category. Both the widths (r = 0.61, P < .001) and intensities (r = 0.51, P < .001) correlated with total white matter hyperintensity volume and with each other (r = 0.55, P < .001) for all categories with the exception of subtle extended periventricular white matter hyperintensities, largely characterized by evidence of erratic, ill-defined, and fragmented pale white matter hyperintensities (width: r = 0.02, P = .11; intensity: r = 0.02, P = .84). The prevalence of hypertension, hypercholesterolemia, and neuroradiologic evidence of stroke increased from periventricular white matter hyperintensity categories 1 to 3. The mean periventricular white matter hyperintensity width was significantly larger in subjects with hypertension (mean difference = 0.5 mm, P = .029) or evidence of stroke (mean difference = 1 mm, P < .001). 3D mapping revealed that periventricular white matter hyperintensities were discontinuous with deep white matter hyperintensities in all categories, except only in particular regions in brains with category 3. CONCLUSIONS Periventricular white matter hyperintensity intensity levels, distribution, and association with risk factors and disease suggest that in old age, these are true tissue abnormalities and therefore should not be dismissed as artifacts. Dichotomizing periventricular and deep white matter hyperintensities by continuity from the ventricle edge toward the deep white matter is possible.
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