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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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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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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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