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Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE, Gibson J, Henders AK, Redmond P, Cox SR, Pattie A, Corley J, Murphy L, Martin NG, Montgomery GW, Feinberg AP, Fallin MD, Multhaup ML, Jaffe AE, Joehanes R, Schwartz J, Just AC, Lunetta KL, Murabito JM, Starr JM, Horvath S, Baccarelli AA, Levy D, Visscher PM, Wray NR, Deary IJ. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol 2015; 16:25. [PMID: 25633388 PMCID: PMC4350614 DOI: 10.1186/s13059-015-0584-6] [Citation(s) in RCA: 733] [Impact Index Per Article: 81.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Accepted: 01/12/2015] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. RESULTS Here we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. CONCLUSIONS DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.
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Affiliation(s)
- Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK. .,Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. .,Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia.
| | - Sonia Shah
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia. .,University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, Brisbane, 4072, QLD, Australia.
| | - Allan F McRae
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia. .,University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, Brisbane, 4072, QLD, Australia.
| | - Brian H Chen
- The NHLBI's Framingham Heart Study, Framingham, MA, 01702, USA. .,Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, 01702, USA.
| | - Elena Colicino
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK. .,Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | - Jude Gibson
- Wellcome Trust Clinical Research Facility, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.
| | - Anjali K Henders
- Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, 4029, QLD, Australia.
| | - Paul Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK. .,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
| | - Janie Corley
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
| | - Lee Murphy
- Wellcome Trust Clinical Research Facility, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.
| | - Nicholas G Martin
- Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, 4029, QLD, Australia.
| | - Grant W Montgomery
- Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, 4029, QLD, Australia.
| | - Andrew P Feinberg
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. .,Departments of Medicine, Molecular Biology/Genetics, Oncology, and Biostatistics, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
| | - M Daniele Fallin
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. .,Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
| | - Michael L Multhaup
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
| | - Andrew E Jaffe
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, 21205, USA. .,Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.
| | - Roby Joehanes
- The NHLBI's Framingham Heart Study, Framingham, MA, 01702, USA. .,Harvard Medical School, Boston, MA, 02115, USA. .,Hebrew Senior Life, Boston, MA, 02131, USA.
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. .,Department of Epidemiology, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA, 02115, USA.
| | - Allan C Just
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
| | - Kathryn L Lunetta
- The NHLBI's Framingham Heart Study, Framingham, MA, 01702, USA. .,Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA.
| | - Joanne M Murabito
- The NHLBI's Framingham Heart Study, Framingham, MA, 01702, USA. .,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA.
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK. .,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
| | - Steve Horvath
- Human Genetics, Gonda Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095-7088, USA. .,Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Andrea A Baccarelli
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. .,Department of Epidemiology, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA, 02115, USA.
| | - Daniel Levy
- The NHLBI's Framingham Heart Study, Framingham, MA, 01702, USA. .,Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, 01702, USA.
| | - Peter M Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK. .,Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia. .,University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, Brisbane, 4072, QLD, Australia.
| | - Naomi R Wray
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia.
| | - Ian 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, Edinburgh, EH8 9JZ, UK.
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202
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Marioni RE, Shah S, McRae AF, Ritchie SJ, Muniz-Terrera G, Harris SE, Gibson J, Redmond P, Cox SR, Pattie A, Corley J, Taylor A, Murphy L, Starr JM, Horvath S, Visscher PM, Wray NR, Deary IJ. The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936. Int J Epidemiol 2015; 44:1388-96. [PMID: 25617346 PMCID: PMC4588858 DOI: 10.1093/ije/dyu277] [Citation(s) in RCA: 380] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/19/2014] [Indexed: 12/05/2022] Open
Abstract
Background: The DNA methylation-based ‘epigenetic clock’ correlates strongly with chronological age, but it is currently unclear what drives individual differences. We examine cross-sectional and longitudinal associations between the epigenetic clock and four mortality-linked markers of physical and mental fitness: lung function, walking speed, grip strength and cognitive ability. Methods: DNA methylation-based age acceleration (residuals of the epigenetic clock estimate regressed on chronological age) were estimated in the Lothian Birth Cohort 1936 at ages 70 (n = 920), 73 (n = 299) and 76 (n = 273) years. General cognitive ability, walking speed, lung function and grip strength were measured concurrently. Cross-sectional correlations between age acceleration and the fitness variables were calculated. Longitudinal change in the epigenetic clock estimates and the fitness variables were assessed via linear mixed models and latent growth curves. Epigenetic age acceleration at age 70 was used as a predictor of longitudinal change in fitness. Epigenome-wide association studies (EWASs) were conducted on the four fitness measures. Results: Cross-sectional correlations were significant between greater age acceleration and poorer performance on the lung function, cognition and grip strength measures (r range: −0.07 to −0.05, P range: 9.7 x 10−3 to 0.024). All of the fitness variables declined over time but age acceleration did not correlate with subsequent change over 6 years. There were no EWAS hits for the fitness traits. Conclusions: Markers of physical and mental fitness are associated with the epigenetic clock (lower abilities associated with age acceleration). However, age acceleration does not associate with decline in these measures, at least over a relatively short follow-up.
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Affiliation(s)
- Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK, Queensland Brain Institute, and
| | - Sonia Shah
- Queensland Brain Institute, and Translational Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - Allan F McRae
- Queensland Brain Institute, and Translational Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - Stuart J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Department of Psychology, University of Edinburgh, Edinburgh, UK
| | | | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Jude Gibson
- Wellcome Trust Clinical Research Facility, and
| | - Paul Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Adele Taylor
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Lee Murphy
- Wellcome Trust Clinical Research Facility, and
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK and
| | - Steve Horvath
- Gonda Research Center, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Peter M Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Queensland Brain Institute, and Translational Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - Naomi R Wray
- Translational Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, and Department of Psychology, University of Edinburgh, Edinburgh, UK,
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203
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Mõttus R, Luciano M, Sarr JM, McCarthy MI, Deary IJ. Childhood cognitive ability moderates later-life manifestation of type 2 diabetes genetic risk. Health Psychol 2015; 34:915-9. [PMID: 25603418 PMCID: PMC4562329 DOI: 10.1037/hea0000184] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Objective: The study investigated whether childhood cognitive ability moderates Type 2 diabetes polygenic risk manifestation in older age. Method: In 940 relatively healthy people (mean age 69.55 ± 0.85), we tested whether self-reported diabetes and hemoglobin HbA1c (HbA1c) levels were predicted by diabetes polygenic risk, cognitive ability measured about 60 years earlier, and their interaction. Polygenic risk scores aggregated the small effects of up to nearly 121,000 single-nucleotide polymorphisms (SNPs). Participants’ cognitive ability was measured at age 11. Results: Both polygenic risk and low childhood cognitive ability significantly predicted diabetes diagnosis. Polygenic risk interacted with cognitive ability (p = .02), predicting HbA1c levels more strongly in people with below-median cognitive ability (effect r = .21) than in people with above-median cognitive ability (effect r = .10). The interaction term was not significant for self-reported diabetes (p = .34), although the genetic risk-diabetes association showed a tendency of being stronger among those with below-median cognitive ability. Conclusions: Higher premorbid cognitive ability may provide some environmental protection against the manifestation of Type 2 diabetes genetic risk. This information may improve early identification of diabetes risk and inform intervention development.
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204
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Lopez LM, Hill WD, Harris SE, Valdes Hernandez M, Munoz Maniega S, Bastin ME, Bailey E, Smith C, McBride M, McClure J, Graham D, Dominiczak A, Yang Q, Fornage M, Ikram MA, Debette S, Launer L, Bis JC, Schmidt R, Seshadri S, Porteous DJ, Starr J, Deary IJ, Wardlaw JM. Genes from a translational analysis support a multifactorial nature of white matter hyperintensities. Stroke 2015; 46:341-7. [PMID: 25586835 PMCID: PMC4306534 DOI: 10.1161/strokeaha.114.007649] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Supplemental Digital Content is available in the text. Background and Purpose— White matter hyperintensities (WMH) of presumed vascular origin increase the risk of stroke and dementia. Despite strong WMH heritability, few gene associations have been identified. Relevant experimental models may be informative. Methods— We tested the associations between genes that were differentially expressed in brains of young spontaneously hypertensive stroke–prone rats and human WMH (using volume and visual score) in 621 subjects from the Lothian Birth Cohort 1936 (LBC1936). We then attempted replication in 9361 subjects from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE). We also tested the subjects from LBC1936 for previous genome-wide WMH associations found in subjects from CHARGE. Results— Of 126 spontaneously hypertensive stroke–prone rat genes, 10 were nominally associated with WMH volume or score in subjects from LBC1936, of which 5 (AFP, ALB, GNAI1, RBM8a, and MRPL18) were associated with both WMH volume and score (P<0.05); 2 of the 10 (XPNPEP1, P=6.7×10−5; FARP1, P=0.024) plus another spontaneously hypertensive stroke–prone rat gene (USMG5, P=0.00014), on chromosomes 10, 13, and 10 respectively, were associated with WMH in subjects from CHARGE. Gene set enrichment showed significant associations for downregulated spontaneously hypertensive stroke–prone rat genes with WMH in humans. In subjects from LBC1936, we replicated CHARGE’s genome-wide WMH associations on chromosomes 17 (TRIM65 and TRIM47) and, for the first time, 1 (PMF1). Conclusions— Despite not passing multiple testing thresholds individually, these genes collectively are relevant to known WMH associations, proposed WMH mechanisms, or dementia: associations with Alzheimer's disease, late-life depression, ATP production, osmotic regulation, neurodevelopmental abnormalities, and cognitive impairment. If replicated further, they suggest a multifactorial nature for WMH and argue for more consideration of vascular contributions to dementia.
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Affiliation(s)
- Lorna M Lopez
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - W David Hill
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Sarah E Harris
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Maria Valdes Hernandez
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Susana Munoz Maniega
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Mark E Bastin
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Emma Bailey
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Colin Smith
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Martin McBride
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - John McClure
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Delyth Graham
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Anna Dominiczak
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Qiong Yang
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Myriam Fornage
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - M Arfan Ikram
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Stephanie Debette
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Lenore Launer
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Joshua C Bis
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Reinhold Schmidt
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Sudha Seshadri
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - David J Porteous
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - John Starr
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Ian J Deary
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
| | - Joanna M Wardlaw
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., M.V.H., S.M.M., M.E.B., J.S., I.J.D., J.M.W.), Division of Neuroimaging Sciences, Brain Research Imaging Centre, (M.V.H., S.M.M., M.E.B., J.M.W.) and Academic Neuropathology (C.S.), Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom (W.D.H., S.E.H., D.J.P.); Department of Bioengineering, Imperial College London, London, United Kingdom (E.B.); BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (M.M., J.M., D.G., A.D.); Department of Biostatistics, Boston University School of Public Health, MA (Q.Y.); The Framingham Heart Study, Boston, MA (Q.Y., S.S.); The Human Genetics Center and Institute of Molecular Medicine, The University of Texas Health Science Center, Houston (M.F.); Departments of Epidemiology, Radiology and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands (M.A.I.); Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (M.A.I.); 12 INSERM U740 (Paris 7 University) and U708 (Bordeaux University), Bordeaux, France (S.D.); Department of Neurology, Lariboisière Hospital, 7 University, DHU Neurovasc Paris Sorbonne, Paris, France (S.D.); University of Versailles Saint-Quentin-en-Yvelines, Versailles, France (S.D.); Department of Neurology, Boston University School of Medicine, MA (S.D., S.S.); Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD (L.L.); Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.C.B.); and Clinical Division of Neurogeri
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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] [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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Aslan AKD, Starr JM, Pattie A, Deary I. Cognitive consequences of overweight and obesity in the ninth decade of life? Age Ageing 2015; 44:59-65. [PMID: 25249169 DOI: 10.1093/ageing/afu108] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND/OBJECTIVES the association between late-life obesity and late-life cognitive abilities is poorly understood. We studied the association between body mass index (BMI) and cognitive change in longitudinal population-based study spanning over the ninth decade of life. SUBJECTS/METHODS in total, 475 participants free of dementia at baseline from the Lothian Birth Cohort 1921 (mean age: 79.1 years, SD: 0.6) were included. Height and weight were assessed at baseline. BMI was calculated as kg/m(2). Cognitive abilities were assessed at age ∼11 years and at age ∼79, ∼83, ∼87 and ∼90 years. RESULTS latent growth models showed that men being overweight and obese had a 0.65 (SD: 0.3) and 1.10 (SD: 0.5) points less steep decline in general cognitive ability (as measured by the Moray House Test) for each year than people of normal weight. These associations were to some extent confounded by childhood intelligence. No other association between BMI and cognition was significant, either for men or women. People who were obese in old age had significantly lower childhood intelligence (m = 43.6, SD: 1.3) than people who were normal in weight (m = 47.0, SD: 0.8) and persons being overweight (m = 47.5, SD: 0.8), F (472, 3) = 3.2, P = 0.043. CONCLUSIONS the current study shows weak or no evidence for an association between BMI in old age and cognitive function, especially not when childhood intelligence is controlled for. Lower intelligence at the age of 11 years predicted obesity at the age of 79 years.
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Affiliation(s)
- Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden Institute of Gerontology, School of Health Sciences, Box 1026, Jönköping 551 11, Sweden
| | - John M Starr
- Geriatric Medicine, University of Edinburgh, Royal Victoria Hospital, Craigleith Road, Edinburgh EH4 2DN, UK Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ian Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
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207
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Bigler ED, Stern Y. Traumatic brain injury and reserve. HANDBOOK OF CLINICAL NEUROLOGY 2015; 128:691-710. [DOI: 10.1016/b978-0-444-63521-1.00043-1] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Abstract
Objective: To examine associations between complexity of main lifetime occupation and cognitive performance in later life. Methods: Occupational complexity ratings for data, people, and things were collected from the Dictionary of Occupational Titles for 1,066 individuals (men = 534, women = 532) in the Lothian Birth Cohort 1936. IQ data were available from mean age 11 years. Cognitive ability data across the domains of general ability, processing speed, and memory were available at mean age 70 years. Results: General linear model analyses indicated that complexity of work with people and data were associated with better cognitive performance at age 70, after including age 11 IQ, years of education, and social deprivation. Conclusions: The current findings are supportive of the differential preservation hypotheses that more stimulating environments preserve cognitive ability in later life, although the continued effects into old age are still debated. Studies that have early-life cognitive ability measures are rare, and the current study offers interesting prospects for future research that may further the understanding of successful aging.
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Affiliation(s)
- Emily L Smart
- From the Department of Psychology (E.L.S., I.J.D.), and Centre for Cognitive Ageing and Cognitive Epidemiology (A.J.G., I.J.D.), University of Edinburgh; and Department of Psychology (A.J.G.), School of Life Sciences, Heriot-Watt University, Edinburgh, UK
| | - Alan J Gow
- From the Department of Psychology (E.L.S., I.J.D.), and Centre for Cognitive Ageing and Cognitive Epidemiology (A.J.G., I.J.D.), University of Edinburgh; and Department of Psychology (A.J.G.), School of Life Sciences, Heriot-Watt University, Edinburgh, UK.
| | - Ian J Deary
- From the Department of Psychology (E.L.S., I.J.D.), and Centre for Cognitive Ageing and Cognitive Epidemiology (A.J.G., I.J.D.), University of Edinburgh; and Department of Psychology (A.J.G.), School of Life Sciences, Heriot-Watt University, Edinburgh, UK
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209
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Automated segmentation of multifocal basal ganglia T2*-weighted MRI hypointensities. Neuroimage 2014; 105:332-46. [PMID: 25451469 PMCID: PMC4275576 DOI: 10.1016/j.neuroimage.2014.10.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2014] [Revised: 09/08/2014] [Accepted: 10/03/2014] [Indexed: 12/17/2022] Open
Abstract
Multifocal basal ganglia T2*-weighted (T2*w) hypointensities, which are believed to arise mainly from vascular mineralization, were recently proposed as a novel MRI biomarker for small vessel disease and ageing. These T2*w hypointensities are typically segmented semi-automatically, which is time consuming, associated with a high intra-rater variability and low inter-rater agreement. To address these limitations, we developed a fully automated, unsupervised segmentation method for basal ganglia T2*w hypointensities. This method requires conventional, co-registered T2*w and T1-weighted (T1w) volumes, as well as region-of-interest (ROI) masks for the basal ganglia and adjacent internal capsule generated automatically from T1w MRI. The basal ganglia T2*w hypointensities were then segmented with thresholds derived with an adaptive outlier detection method from respective bivariate T2*w/T1w intensity distributions in each ROI. Artefacts were reduced by filtering connected components in the initial masks based on their standardised T2*w intensity variance. The segmentation method was validated using a custom-built phantom containing mineral deposit models, i.e. gel beads doped with 3 different contrast agents in 7 different concentrations, as well as with MRI data from 98 community-dwelling older subjects in their seventies with a wide range of basal ganglia T2*w hypointensities. The method produced basal ganglia T2*w hypointensity masks that were in substantial volumetric and spatial agreement with those generated by an experienced rater (Jaccard index = 0.62 ± 0.40). These promising results suggest that this method may have use in automatic segmentation of basal ganglia T2*w hypointensities in studies of small vessel disease and ageing. A novel method segmented focal T2*-weighted MRI hypointensities automatically. The method was validated with MRI of a novel phantom and 98 elderly subjects. The subject masks from the method and an experienced rater overlapped substantially. The method is potentially useful for research into small vessel disease and ageing.
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210
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Parikh J, Thrippleton MJ, Murray C, Armitage PA, Harris BA, Andrews PJD, Wardlaw JM, Starr JM, Deary IJ, Marshall I. Proton spectroscopic imaging of brain metabolites in basal ganglia of healthy older adults. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2014; 28:251-7. [PMID: 25312604 PMCID: PMC4445772 DOI: 10.1007/s10334-014-0465-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Revised: 08/28/2014] [Accepted: 09/23/2014] [Indexed: 11/26/2022]
Abstract
Object
We sought to measure brain metabolite levels in healthy older people. Materials and methods Spectroscopic imaging at the level of the basal ganglia was applied in 40 participants aged 73–74 years. Levels of the metabolites N-acetyl aspartate (NAA), choline, and creatine were determined in "institutional units" (IU) corrected for T1 and T2 relaxation effects. Structural imaging enabled determination of grey matter (GM), white matter (WM), and cerebrospinal fluid content. ANOVA analysis was carried out for voxels satisfying quality criteria. Results Creatine levels were greater in GM than WM (57 vs. 44 IU, p < 0.001), whereas choline and NAA levels were greater in WM than GM [13 vs. 10 IU (p < 0.001) and 76 versus 70 IU (p = 0.03), respectively]. The ratio of NAA/cre was greater in WM than GM (2.1 vs. 1.4, p = 0.001) as was that of cho/cre (0.32 vs. 0.16, p < 0.001). A low voxel yield was due to brain atrophy and the difficulties of shimming over an extended region of brain. Conclusion This study addresses the current lack of information on brain metabolite levels in older adults. The normal features of ageing result in a substantial loss of reliable voxels and should be taken into account when planning studies. Improvements in shimming are also required before the methods can be applied more widely.
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Affiliation(s)
- Jehill Parikh
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, Edinburgh, EH16 4SB UK
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, Edinburgh, EH16 4SB UK
| | - Catherine Murray
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul A. Armitage
- Academic Unit of Radiology, Department of Cardiovascular Science, University of Sheffield, Sheffield, UK
| | - Bridget A. Harris
- Critical Care Medicine, NHS Lothian and University of Edinburgh, Edinburgh, UK
| | - Peter J. D. Andrews
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, Edinburgh, EH16 4SB UK
- Critical Care Medicine, NHS Lothian and University of Edinburgh, Edinburgh, UK
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, Edinburgh, EH16 4SB UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian J. Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, Edinburgh, EH16 4SB UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Maniega SM, Valdés Hernández MC, Clayden JD, Royle NA, Murray C, Morris Z, Aribisala BS, Gow AJ, Starr JM, Bastin ME, Deary IJ, Wardlaw JM. White matter hyperintensities and normal-appearing white matter integrity in the aging brain. Neurobiol Aging 2014; 36:909-18. [PMID: 25457555 PMCID: PMC4321830 DOI: 10.1016/j.neurobiolaging.2014.07.048] [Citation(s) in RCA: 189] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2013] [Revised: 07/10/2014] [Accepted: 07/16/2014] [Indexed: 11/08/2022]
Abstract
White matter hyperintensities (WMH) of presumed vascular origin are a common finding in brain magnetic resonance imaging of older individuals and contribute to cognitive and functional decline. It is unknown how WMH form, although white matter degeneration is characterized pathologically by demyelination, axonal loss, and rarefaction, often attributed to ischemia. Changes within normal-appearing white matter (NAWM) in subjects with WMH have also been reported but have not yet been fully characterized. Here, we describe the in vivo imaging signatures of both NAWM and WMH in a large group of community-dwelling older people of similar age using biomarkers derived from magnetic resonance imaging that collectively reflect white matter integrity, myelination, and brain water content. Fractional anisotropy (FA) and magnetization transfer ratio (MTR) were significantly lower, whereas mean diffusivity (MD) and longitudinal relaxation time (T1) were significantly higher, in WMH than NAWM (p < 0.0001), with MD providing the largest difference between NAWM and WMH. Receiver operating characteristic analysis on each biomarker showed that MD differentiated best between NAWM and WMH, identifying 94.6% of the lesions using a threshold of 0.747 × 10−9 m2s−1 (area under curve, 0.982; 95% CI, 0.975–0.989). Furthermore, the level of deterioration of NAWM was strongly associated with the severity of WMH, with MD and T1 increasing and FA and MTR decreasing in NAWM with increasing WMH score, a relationship that was sustained regardless of distance from the WMH. These multimodal imaging data indicate that WMH have reduced structural integrity compared with surrounding NAWM, and MD provides the best discriminator between the 2 tissue classes even within the mild range of WMH severity, whereas FA, MTR, and T1 only start reflecting significant changes in tissue microstructure as WMH become more severe.
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Affiliation(s)
- Susana Muñoz Maniega
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK
| | - Maria C Valdés Hernández
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK
| | | | - Natalie A Royle
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK
| | - Catherine Murray
- Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Zoe Morris
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | | | - Alan J Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK; Department of Psychology, School of Life Sciences, Heriot-Watt University, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK.
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK
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Lyall DM, Harris SE, Bastin ME, Muñoz Maniega S, Murray C, Lutz MW, Saunders AM, Roses AD, Valdés Hernández MDC, Royle NA, Starr JM, Porteous DJ, Wardlaw JM, Deary IJ. Are APOE ɛ genotype and TOMM40 poly-T repeat length associations with cognitive ageing mediated by brain white matter tract integrity? Transl Psychiatry 2014; 4:e449. [PMID: 25247594 PMCID: PMC4203017 DOI: 10.1038/tp.2014.89] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2013] [Revised: 07/08/2014] [Accepted: 08/07/2014] [Indexed: 12/20/2022] Open
Abstract
Genetic polymorphisms in the APOE ɛ and TOMM40 '523' poly-T repeat gene loci have been associated with significantly increased risk of Alzheimer's disease. This study investigated the independent effects of these polymorphisms on human cognitive ageing, and the extent to which nominally significant associations with cognitive ageing were mediated by previously reported genetic associations with brain white matter tract integrity in this sample. Most participants in the Lothian Birth Cohort 1936 completed a reasoning-type intelligence test at age 11 years, and detailed cognitive/physical assessments and structural diffusion tensor brain magnetic resonance imaging at a mean age of 72.70 years (s.d.=0.74). Participants were genotyped for APOE ɛ2/ɛ3/ɛ4 status and TOMM40 523 poly-T repeat length. Data were available from 758-814 subjects for cognitive analysis, and 522-543 for mediation analysis with brain imaging data. APOE genotype was significantly associated with performance on several different tests of cognitive ability, including general factors of intelligence, information processing speed and memory (raw P-values all<0.05), independently of childhood IQ and vascular disease history. Formal tests of mediation showed that several significant APOE-cognitive ageing associations--particularly those related to tests of information processing speed--were partially mediated by white matter tract integrity. TOMM40 523 genotype was not associated with cognitive ageing. A range of brain phenotypes are likely to form the anatomical basis for significant associations between APOE genotype and cognitive ageing, including white matter tract microstructural integrity.
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Affiliation(s)
- D M Lyall
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK [3] Department of Psychology, University of Edinburgh, Edinburgh, UK [4] Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, UK
| | - S E Harris
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, UK
| | - M E Bastin
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK [3] Department of Neuroimaging Sciences, Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, The University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK [3] Department of Neuroimaging Sciences, Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, The University of Edinburgh, Edinburgh, UK
| | - C Murray
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M W Lutz
- Joseph & Kathleen Bryan Alzheimer's Disease Research Center, Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - A M Saunders
- Joseph & Kathleen Bryan Alzheimer's Disease Research Center, Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - A D Roses
- 1] Joseph & Kathleen Bryan Alzheimer's Disease Research Center, Department of Neurology, Duke University Medical Center, Durham, NC, USA [2] Zinfandel Pharmaceuticals, Durham, NC, USA
| | - M del C Valdés Hernández
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK [3] Department of Neuroimaging Sciences, Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, The University of Edinburgh, Edinburgh, UK
| | - N A Royle
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK [3] Department of Neuroimaging Sciences, Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, The University of Edinburgh, Edinburgh, UK
| | - J M Starr
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Alzheimer Scotland Dementia Research Centre, Edinburgh, UK
| | - D J Porteous
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, UK
| | - J M Wardlaw
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK [3] Department of Neuroimaging Sciences, Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, The University of Edinburgh, Edinburgh, UK
| | - I J Deary
- 1] Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh, Edinburgh, UK [2] Department of Psychology, University of Edinburgh, Edinburgh, UK
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Shah S, McRae AF, Marioni RE, Harris SE, Gibson J, Henders AK, Redmond P, Cox SR, Pattie A, Corley J, Murphy L, Martin NG, Montgomery GW, Starr JM, Wray NR, Deary IJ, Visscher PM. Genetic and environmental exposures constrain epigenetic drift over the human life course. Genome Res 2014; 24:1725-33. [PMID: 25249537 PMCID: PMC4216914 DOI: 10.1101/gr.176933.114] [Citation(s) in RCA: 109] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Epigenetic mechanisms such as DNA methylation (DNAm) are essential for regulation of gene expression. DNAm is dynamic, influenced by both environmental and genetic factors. Epigenetic drift is the divergence of the epigenome as a function of age due to stochastic changes in methylation. Here we show that epigenetic drift may be constrained at many CpGs across the human genome by DNA sequence variation and by lifetime environmental exposures. We estimate repeatability of DNAm at 234,811 autosomal CpGs in whole blood using longitudinal data (2–3 repeated measurements) on 478 older people from two Scottish birth cohorts—the Lothian Birth Cohorts of 1921 and 1936. Median age was 79 yr and 70 yr, and the follow-up period was ∼10 yr and ∼6 yr, respectively. We compare this to methylation heritability estimated in the Brisbane Systems Genomics Study, a cross-sectional study of 117 families (offspring median age 13 yr; parent median age 46 yr). CpG repeatability in older people was highly correlated (0.68) with heritability estimated in younger people. Highly heritable sites had strong underlying cis-genetic effects. Thirty-seven and 1687 autosomal CpGs were associated with smoking and sex, respectively. Both sets were strongly enriched for high repeatability. Sex-associated CpGs were also strongly enriched for high heritability. Our results show that a large number of CpGs across the genome, as a result of environmental and/or genetic constraints, have stable DNAm variation over the human lifetime. Moreover, at a number of CpGs, most variation in the population is due to genetic factors, despite some sites being highly modifiable by the environment.
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Affiliation(s)
- Sonia Shah
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Queensland, Australia
| | - Allan F McRae
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Queensland, Australia
| | - Riccardo E Marioni
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Queensland, Australia; Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Sarah E Harris
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Jude Gibson
- Wellcome Trust Clinical Research Facility, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, United Kingdom
| | - Anjali K Henders
- QIMR Berghofer Medical Research Institute, Brisbane, 4029, Queensland, Australia
| | - Paul Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Simon 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
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Janie Corley
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Lee Murphy
- Wellcome Trust Clinical Research Facility, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, United Kingdom
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, 4029, Queensland, Australia
| | - Grant W Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, 4029, Queensland, Australia
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Naomi R Wray
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Queensland, Australia
| | - Ian 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
| | - Peter M Visscher
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Queensland, Australia; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom; University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, Brisbane, 4072, Queensland, Australia
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214
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Aribisala BS, Royle NA, Valdés Hernández MC, Murray C, Penke L, Gow A, Maniega SM, Starr JM, Bastin M, Deary I, Wardlaw J. Potential effect of skull thickening on the associations between cognition and brain atrophy in ageing. Age Ageing 2014; 43:712-6. [PMID: 24936580 DOI: 10.1093/ageing/afu070] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND intracranial volume (ICV) is commonly used as a marker of premorbid brain size in neuroimaging studies as it is thought to remain fixed throughout adulthood. However, inner skull table thickening would encroach on ICV and could mask actual brain atrophy. OBJECTIVE we investigated the effect that thickening might have on the associations between brain atrophy and cognition. METHODS the sample comprised 57 non-demented older adults who underwent structural brain MRI at mean age 72.7 ± 0.7 years and were assessed on cognitive ability at mean age 11 and 73 years. Principal component analysis was used to derive factors of general cognitive ability (g), information processing speed and memory from the recorded cognitive ability data. The total brain tissue volume and ICV with (estimated original ICV) and without (current ICV) adjusting for the effects of inner table skull thickening were measured. General linear modelling was used to test for associations. RESULTS all cognitive ability variables were significantly (P < 0.01) associated with percentage total brain volume in ICV measured without adjusting for skull thickening (g: η(2) = 0.177, speed: η(2) = 0.264 and memory: η(2) = 0.132). After accounting for skull thickening, only speed was significantly associated with percentage total brain volume in ICV (η(2) = 0.085, P = 0.034), not g or memory. CONCLUSIONS not accounting for skull thickening when computing ICV can distort the association between brain atrophy and cognitive ability in old age. Larger samples are required to determine the true effect.
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Affiliation(s)
- Benjamin Segun Aribisala
- Brain Research Imaging Centre, Brain Research Imaging Centre Neuroimaging Sciences University of Edinburgh, Western General Hospital, University of Edinburgh, Edinburgh, Scotland EH4 2XU, UK Computer Science Department, Faculty of Science PMB 001 LASU Post Office, Lagos State University, Ojo Lagos, Lagos, Lagos PMB 001 LASU, Nigeria
| | - Natalie A Royle
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, Scotland, UK
| | | | - Catherine Murray
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - Lars Penke
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - Alan Gow
- School of Life Sciences, Heriot-Watt University, Edinburgh, Scotland, UK Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | | | - John M Starr
- Geriatric Medicine, University of Edinburgh, Royal Victoria Hospital Craigleith Road, Edinburgh EH4 2DN, UK
| | - Mark Bastin
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, Scotland, UK
| | - Ian Deary
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - Joanna Wardlaw
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, Scotland, UK
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215
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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, AND BEHAVIOR 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] [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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216
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Cox SR, MacPherson SE, Ferguson KJ, Nissan J, Royle NA, MacLullich AM, Wardlaw JM, Deary IJ. Correlational structure of 'frontal' tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age. INTELLIGENCE 2014; 46:94-106. [PMID: 25278641 PMCID: PMC4175012 DOI: 10.1016/j.intell.2014.05.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2014] [Revised: 05/05/2014] [Accepted: 05/08/2014] [Indexed: 12/01/2022]
Abstract
Both general fluid intelligence (gf) and performance on some 'frontal tests' of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and gf share neurobiological variance. To this end, we examined relationships between gf and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). gf correlated significantly and positively (.24 ≤ r ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for gf. Principal component analysis of test scores identified units of gf-common and gf-independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact.
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Affiliation(s)
- Simon R. Cox
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Department of Psychology, University of Edinburgh, UK
| | - Sarah E. MacPherson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Department of Psychology, University of Edinburgh, UK
| | - Karen J. Ferguson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Geriatric Medicine, University of Edinburgh, UK
| | - Jack Nissan
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
| | - Natalie A. Royle
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Scottish Imaging Network, a Platform for Scientific Excellence (SINAPSE) Collaboration, UK
| | - Alasdair M.J. MacLullich
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Geriatric Medicine, University of Edinburgh, UK
- Endocrinology Unit, University of Edinburgh, UK
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Scottish Imaging Network, a Platform for Scientific Excellence (SINAPSE) Collaboration, UK
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
- Department of Psychology, University of Edinburgh, UK
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217
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Cox SR, Bastin ME, Ferguson KJ, Maniega SM, MacPherson SE, Deary IJ, Wardlaw JM, MacLullich AMJ. Brain white matter integrity and cortisol in older men: the Lothian Birth Cohort 1936. Neurobiol Aging 2014; 36:257-64. [PMID: 25066239 PMCID: PMC4274312 DOI: 10.1016/j.neurobiolaging.2014.06.022] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2014] [Revised: 06/06/2014] [Accepted: 06/24/2014] [Indexed: 02/01/2023]
Abstract
Elevated glucocorticoid (GC) levels are hypothesized to be deleterious to some brain regions, including white matter (WM). Older age is accompanied by increased between-participant variation in GC levels, yet relationships between WM integrity and cortisol levels in older humans are underexplored. Moreover, it is unclear whether GC-WM associations might be general or pathway specific. We analyzed relationships between salivary cortisol (diurnal and reactive) and general measures of brain WM hyperintensity (WMH) volume, fractional anisotropy (gFA), and mean diffusivity (gMD) in 90 males, aged 73 years. Significant associations were predominantly found between cortisol measures and WMHs and gMD but not gFA. Higher cortisol at the start of a mild cognitive stressor was associated with higher WMH and gMD. Higher cortisol at the end was associated with greater WMHs. A constant or increasing cortisol level during cognitive testing was associated with lower gMD. Tract-specific bases of these associations implicated anterior thalamic radiation, uncinate, and arcuate and inferior longitudinal fasciculi. The cognitive sequelae of these relationships, above other covariates, are a priority for future study. We correlated salivary cortisol and brain white matter (WM) measures in older males. Cortisol was measured diurnally and in reaction to a cognitive challenge. Diffusion tensor magnetic resonance imaging (fractional anisotropy and mean diffusivity) and total hyperintensity volume measured WM integrity. WM-cortisol relations were found for mean diffusivity and hyperintensity volume but not fractional anisotropy. Higher cortisol in response to cognitive stressor denoted lower WM integrity.
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Affiliation(s)
- Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK.
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Karen J Ferguson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Edinburgh Delirium Research Group, Geriatric Medicine Unit, University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Edinburgh Delirium Research Group, Geriatric Medicine Unit, University of Edinburgh, Edinburgh, UK
| | - Sarah E MacPherson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Alasdair M J MacLullich
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Edinburgh Delirium Research Group, Geriatric Medicine Unit, University of Edinburgh, Edinburgh, UK; Endocrinology Unit, University of Edinburgh, Edinburgh, UK
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218
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The attitudes to ageing questionnaire: Mokken scaling analysis. PLoS One 2014; 9:e99100. [PMID: 24892302 PMCID: PMC4043998 DOI: 10.1371/journal.pone.0099100] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2014] [Accepted: 05/11/2014] [Indexed: 11/23/2022] Open
Abstract
Background Hierarchical scales are useful in understanding the structure of underlying latent traits in many questionnaires. The Attitudes to Ageing Questionnaire (AAQ) explored the attitudes to ageing of older people themselves, and originally described three distinct subscales: (1) Psychosocial Loss (2) Physical Change and (3) Psychological Growth. This study aimed to use Mokken analysis, a method of Item Response Theory, to test for hierarchies within the AAQ and to explore how these relate to underlying latent traits. Methods Participants in a longitudinal cohort study, the Lothian Birth Cohort 1936, completed a cross-sectional postal survey. Data from 802 participants were analysed using Mokken Scaling analysis. These results were compared with factor analysis using exploratory structural equation modelling. Results Participants were 51.6% male, mean age 74.0 years (SD 0.28). Three scales were identified from 18 of the 24 items: two weak Mokken scales and one moderate Mokken scale. (1) ‘Vitality’ contained a combination of items from all three previously determined factors of the AAQ, with a hierarchy from physical to psychosocial; (2) ‘Legacy’ contained items exclusively from the Psychological Growth scale, with a hierarchy from individual contributions to passing things on; (3) ‘Exclusion’ contained items from the Psychosocial Loss scale, with a hierarchy from general to specific instances. All of the scales were reliable and statistically significant with ‘Legacy’ showing invariant item ordering. The scales correlate as expected with personality, anxiety and depression. Exploratory SEM mostly confirmed the original factor structure. Conclusions The concurrent use of factor analysis and Mokken scaling provides additional information about the AAQ. The previously-described factor structure is mostly confirmed. Mokken scaling identifies a new factor relating to vitality, and a hierarchy of responses within three separate scales, referring to vitality, legacy and exclusion. This shows what older people themselves consider important regarding their own ageing.
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219
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Bak TH, Nissan JJ, Allerhand MM, Deary IJ. Does bilingualism influence cognitive aging? Ann Neurol 2014; 75:959-63. [PMID: 24890334 PMCID: PMC4320748 DOI: 10.1002/ana.24158] [Citation(s) in RCA: 193] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Revised: 03/25/2014] [Accepted: 04/13/2014] [Indexed: 12/04/2022]
Abstract
Recent evidence suggests a positive impact of bilingualism on cognition, including later onset of dementia. However, monolinguals and bilinguals might have different baseline cognitive ability. We present the first study examining the effect of bilingualism on later-life cognition controlling for childhood intelligence. We studied 853 participants, first tested in 1947 (age = 11 years), and retested in 2008–2010. Bilinguals performed significantly better than predicted from their baseline cognitive abilities, with strongest effects on general intelligence and reading. Our results suggest a positive effect of bilingualism on later-life cognition, including in those who acquired their second language in adulthood.
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Affiliation(s)
- Thomas H Bak
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
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220
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Bak TH, Nissan JJ, Allerhand MM, Deary IJ. Does bilingualism influence cognitive aging? Ann Neurol 2014. [PMID: 24890334 DOI: 10.1002/ana.v75.610.1002/ana.24158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Recent evidence suggests a positive impact of bilingualism on cognition, including later onset of dementia. However, monolinguals and bilinguals might have different baseline cognitive ability. We present the first study examining the effect of bilingualism on later-life cognition controlling for childhood intelligence. We studied 853 participants, first tested in 1947 (age = 11 years), and retested in 2008-2010. Bilinguals performed significantly better than predicted from their baseline cognitive abilities, with strongest effects on general intelligence and reading. Our results suggest a positive effect of bilingualism on later-life cognition, including in those who acquired their second language in adulthood.
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Affiliation(s)
- Thomas H Bak
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
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221
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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] [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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Lyall DM, Harris SE, Bastin ME, Muñoz Maniega S, Murray C, Lutz MW, Saunders AM, Roses AD, Valdés Hernández MDC, Royle NA, Starr JM, Porteous DJ, Wardlaw JM, Deary IJ. Alzheimer's disease susceptibility genes APOE and TOMM40, and brain white matter integrity in the Lothian Birth Cohort 1936. Neurobiol Aging 2014; 35:1513.e25-33. [PMID: 24508314 PMCID: PMC3969262 DOI: 10.1016/j.neurobiolaging.2014.01.006] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2013] [Revised: 12/02/2013] [Accepted: 01/04/2014] [Indexed: 12/14/2022]
Abstract
Apolipoprotein E (APOE) ε genotype has previously been significantly associated with cognitive, brain imaging, and Alzheimer's disease-related phenotypes (e.g., age of onset). In the TOMM40 gene, the rs10524523 ("523") variable length poly-T repeat polymorphism has more recently been associated with similar ph/enotypes, although the allelic directions of these associations have varied between initial reports. Using diffusion magnetic resonance imaging tractography, the present study aimed to investigate whether there are independent effects of apolipoprotein E (APOE) and TOMM40 genotypes on human brain white matter integrity in a community-dwelling sample of older adults, the Lothian Birth Cohort 1936 (mean age = 72.70 years, standard deviation = 0.74, N approximately = 640-650; for most analyses). Some nominally significant effects were observed (i.e., covariate-adjusted differences between genotype groups at p < 0.05). For APOE, deleterious effects of ε4 "risk" allele presence (vs. absence) were found in the right ventral cingulum and left inferior longitudinal fasciculus. To test for biologically independent effects of the TOMM40 523 repeat, participants were stratified into APOE genotype subgroups, so that any significant effects could not be attributed to APOE variation. In participants with the APOE ε3/ε4 genotype, effects of TOMM40 523 status were found in the left uncinate fasciculus, left rostral cingulum, left ventral cingulum, and a general factor of white matter integrity. In all 4 of these tractography measures, carriers of the TOMM40 523 "short" allele showed lower white matter integrity when compared with carriers of the "long" and "very-long" alleles. Most of these effects survived correction for childhood intelligence test scores and vascular disease history, though only the effect of TOMM40 523 on the left ventral cingulum integrity survived correction for false discovery rate. The effects of APOE in this older population are more specific and restricted compared with those reported in previous studies, and the effects of TOMM40 on white matter integrity appear to be novel, although replication is required in large independent samples.
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Affiliation(s)
- Donald M Lyall
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK; Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine, Western General Hospital, Edinburgh, UK; MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine, Western General Hospital, Edinburgh, UK; MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, The University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, The University of Edinburgh, Edinburgh, UK
| | - Catherine Murray
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Michael W Lutz
- Department of Neurology, Joseph & Kathleen Bryan Alzheimer's Disease Research Center, Durham, NC, USA; Duke University Medical Center, Durham, NC, USA
| | - Ann M Saunders
- Department of Neurology, Joseph & Kathleen Bryan Alzheimer's Disease Research Center, Durham, NC, USA
| | - Allen D Roses
- Department of Neurology, Joseph & Kathleen Bryan Alzheimer's Disease Research Center, Durham, NC, USA; Duke University Medical Center, Durham, NC, USA; Zinfandel Pharmaceuticals, Inc, Durham, NC, USA
| | - Maria del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, The University of Edinburgh, Edinburgh, UK
| | - Natalie A Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, The University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Medical Genetics Section, University of Edinburgh Centre for Genomics and Experimental Medicine, Western General Hospital, Edinburgh, UK; MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, The University of Edinburgh, Edinburgh, UK
| | - Ian 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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Abstract
The challenge of devising a set of biomarkers capable of measuring the ageing rate in human subjects was articulated long ago. In recent years, progress in the basic biology of ageing suggests the realistic possibility of preventive or restaurative interventions that may extend healthy lifespan in mammals including human subjects. Specifically, frailty is being increasingly recognised as a clinically relevant syndrome that may be therapeutically addressed. This greatly enhances the need for sensitive and specific biomarkers of healthy ageing that are validated in both experimental animals and, importantly, in human subjects over the whole age range. Here, we will discuss the present challenges and requirements for biomarker validation in human subjects. We propose the central requirements for a validated biomarker of healthy ageing as: (i) better predictive power than chronological age for multiple dimensions of ageing; (ii) identification of the age range in which the marker is informative; (iii) establishment of sensitivity/specificity as indicators of its predictive power at the level of the individual; (iv) minimisation of methodological variation between laboratories.
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224
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Karama S, Bastin ME, Murray C, Royle NA, Penke L, Muñoz Maniega S, Gow AJ, Corley J, Valdés Hernández M, Lewis JD, Rousseau MÉ, Lepage C, Fonov V, Collins DL, Booth T, Rioux P, Sherif T, Adalat R, Starr JM, Evans AC, Wardlaw JM, Deary IJ. Childhood cognitive ability accounts for associations between cognitive ability and brain cortical thickness in old age. Mol Psychiatry 2014; 19:555-9. [PMID: 23732878 PMCID: PMC3998074 DOI: 10.1038/mp.2013.64] [Citation(s) in RCA: 82] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2013] [Revised: 03/14/2013] [Accepted: 04/08/2013] [Indexed: 11/28/2022]
Abstract
Associations between brain cortical tissue volume and cognitive function in old age are frequently interpreted as suggesting that preservation of cortical tissue is the foundation of successful cognitive aging. However, this association could also, in part, reflect a lifelong association between cognitive ability and cortical tissue. We analyzed data on 588 subjects from the Lothian Birth Cohort 1936 who had intelligence quotient (IQ) scores from the same cognitive test available at both 11 and 70 years of age as well as high-resolution brain magnetic resonance imaging data obtained at approximately 73 years of age. Cortical thickness was estimated at 81 924 sampling points across the cortex for each subject using an automated pipeline. Multiple regression was used to assess associations between cortical thickness and the IQ measures at 11 and 70 years. Childhood IQ accounted for more than two-third of the association between IQ at 70 years and cortical thickness measured at age 73 years. This warns against ascribing a causal interpretation to the association between cognitive ability and cortical tissue in old age based on assumptions about, and exclusive reference to, the aging process and any associated disease. Without early-life measures of cognitive ability, it would have been tempting to conclude that preservation of cortical thickness in old age is a foundation for successful cognitive aging when, instead, it is a lifelong association. This being said, results should not be construed as meaning that all studies on aging require direct measures of childhood IQ, but as suggesting that proxy measures of prior cognitive function can be useful to take into consideration.
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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
| | - M E Bastin
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - C Murray
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - N A Royle
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - L Penke
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - A J Gow
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - J Corley
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - MdelC Valdés Hernández
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - J D Lewis
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - M-É Rousseau
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - C Lepage
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - V Fonov
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - D L Collins
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - T Booth
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - P Rioux
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - T Sherif
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - R Adalat
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - J M Starr
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A C Evans
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - J M Wardlaw
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Department of Psychology, Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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225
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Zammit AR, Starr JM, Johnson W, Deary IJ. Patterns and associates of cognitive function, psychosocial wellbeing and health in the Lothian Birth Cohort 1936. BMC Geriatr 2014; 14:53. [PMID: 24754844 PMCID: PMC3999738 DOI: 10.1186/1471-2318-14-53] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Accepted: 04/08/2014] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Cognitive function, psychosocial wellbeing and health are important domains of function. Consistencies and inconsistencies in patterns of wellbeing across these domains may be informative about wellbeing in old age and the ways it is manifested amongst individuals. In this study we investigated whether there were groups of individuals with different profiles of scores across these domains. We also aimed to identify characteristics of any evident groups by comparing them on variables that were not used in identifying the groups. METHODS The sample was the Lothian Birth Cohort 1936, which included 1091 participants born in 1936. They are a community-dwelling, narrow-age-range sample of 70-year-olds. Most had taken part in the Scottish Mental Survey 1947 at an average age of 11, making available a measure of childhood intelligence. We used latent class analysis (LCA) to explore possible profiles using 9 variables indicating cognitive functioning, psychosocial wellbeing and health status. Demographic, personality, and lifestyle variables - none of which were used in the LCA - were used to characterize the resulting profile groups. RESULTS We accepted a 3-group solution, which we labeled High Wellbeing (65.3%), Low Cognition (20.3%), and Low Bio-Psychosocial (14.5%). Notably, the High Wellbeing group had significantly higher childhood IQ, lower Neuroticism scores, and a lower percentage of current smokers than the other 2 groups. CONCLUSION The majority of individuals were functioning generally well; however, there was evidence of the presence of groups with different profiles, which may be explained in part in terms of cognitive ability differences. Results suggested that higher life-long intelligence, personality traits associated with less mental distress, and basic health practices such as avoiding smoking are important associates of wellbeing in old age.
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Affiliation(s)
- Andrea R Zammit
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
- Albert Einstein College Medicine, New York, USA
| | - John M Starr
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, Scotland, UK
| | - Wendy Johnson
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, Scotland, UK
| | - Ian J Deary
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, Scotland, UK
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226
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Marioni RE, Penke L, Davies G, Huffman JE, Hayward C, Deary IJ. The total burden of rare, non-synonymous exome genetic variants is not associated with childhood or late-life cognitive ability. Proc Biol Sci 2014; 281:20140117. [PMID: 24573858 PMCID: PMC3953855 DOI: 10.1098/rspb.2014.0117] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2014] [Accepted: 01/27/2014] [Indexed: 11/22/2022] Open
Abstract
Human cognitive ability shows consistent, positive associations with fitness components across the life-course. Underlying genetic variation should therefore be depleted by selection, which is not observed. Genetic variation in general cognitive ability (intelligence) could be maintained by a mutation-selection balance, with rare variants contributing to its genetic architecture. This study examines the association between the total number of rare stop-gain/loss, splice and missense exonic variants and cognitive ability in childhood and old age in the same individuals. Exome array data were obtained in the Lothian Birth Cohorts of 1921 and 1936 (combined N = 1596). General cognitive ability was assessed at age 11 years and in late life (79 and 70 years, respectively) and was modelled against the total number of stop-gain/loss, splice, and missense exonic variants, with minor allele frequency less than or equal to 0.01, using linear regression adjusted for age and sex. In both cohorts and in both the childhood and late-life models, there were no significant associations between rare variant burden in the exome and cognitive ability that survived correction for multiple testing. Contrary to our a priori hypothesis, we observed no evidence for an association between the total number of rare exonic variants and either childhood cognitive ability or late-life cognitive ability.
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Affiliation(s)
- Riccardo E. Marioni
- 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
| | - Lars Penke
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
- Institute of Psychology, Georg August University Göttingen, Goßlerstr. 14, Göttingen 37073, Germany
| | - Gail Davies
- 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
- Medical Genetics Section, Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Jennifer E. Huffman
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Ian 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
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227
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Wardlaw JM, Allerhand M, Doubal FN, Valdes Hernandez M, Morris Z, Gow AJ, Bastin M, Starr JM, Dennis MS, Deary IJ. Vascular risk factors, large-artery atheroma, and brain white matter hyperintensities. Neurology 2014; 82:1331-8. [PMID: 24623838 PMCID: PMC4001185 DOI: 10.1212/wnl.0000000000000312] [Citation(s) in RCA: 164] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2013] [Accepted: 12/29/2013] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine the magnitude of potentially causal relationships among vascular risk factors (VRFs), large-artery atheromatous disease (LAD), and cerebral white matter hyperintensities (WMH) in 2 prospective cohorts. METHODS We assessed VRFs (history and measured variables), LAD (in carotid, coronary, and leg arteries), and WMH (on structural MRI, visual scores and volume) in: (a) community-dwelling older subjects of the Lothian Birth Cohort 1936, and (b) patients with recent nondisabling stroke. We analyzed correlations, developed structural equation models, and performed mediation analysis to test interrelationships among VRFs, LAD, and WMH. RESULTS In subjects of the Lothian Birth Cohort 1936 (n = 881, mean age 72.5 years [SD ±0.7 years], 49% with hypertension, 33% with moderate/severe WMH), VRFs explained 70% of the LAD variance but only 1.4% to 2% of WMH variance, of which hypertension explained the most. In stroke patients (n = 257, mean age 74 years [SD ±11.6 years], 61% hypertensive, 43% moderate/severe WMH), VRFs explained only 0.1% of WMH variance. There was no direct association between LAD and WMH in either sample. The results were the same for all WMH measures used. CONCLUSIONS The small effect of VRFs and LAD on WMH suggests that WMH have a large "nonvascular," nonatheromatous etiology. VRF modification, although important, may be limited in preventing WMH and their stroke and dementia consequences. Investigation of, and interventions against, other suspected small-vessel disease mechanisms should be addressed.
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Affiliation(s)
- Joanna M Wardlaw
- From the Centre for Clinical Brain Sciences (J.M.W., F.N.D., M.V.H., Z.M., M.B., M.S.D.) and Centre for Cognitive Ageing and Cognitive Epidemiology (M.A., M.V.H., A.J.G., M.B., J.M.S., I.J.D.), University of Edinburgh, UK
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228
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Shenkin SD, Laidlaw K, Allerhand M, Mead GE, Starr JM, Deary IJ. Life course influences of physical and cognitive function and personality on attitudes to aging in the Lothian Birth Cohort 1936. Int Psychogeriatr 2014; 26:1-14. [PMID: 24622392 DOI: 10.1017/s1041610214000301] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
ABSTRACT Background: Reports of attitudes to aging from older people themselves are scarce. Which life course factors predict differences in these attitudes is unknown. Methods: We investigated life course influences on attitudes to aging in healthy, community-dwelling people in the UK. Participants in the Lothian Birth Cohort 1936 completed a self-report questionnaire (Attitudes to Aging Questionnaire, AAQ) at around age 75 (n = 792, 51.4% male). Demographic, social, physical, cognitive, and personality/mood predictors were assessed, around age 70. Cognitive ability data were available at age 11. Results: Generally positive attitudes were reported in all three domains: low Psychosocial Loss, high Physical Change, and high Psychological Growth. Hierarchical multiple regression found that demographic, cognitive, and physical variables each explained a relatively small proportion of the variance in attitudes to aging, with the addition of personality/mood variables contributing most significantly. Predictors of attitudes to Psychosocial Loss were high neuroticism; low extraversion, openness, agreeableness, and conscientiousness; high anxiety and depression; and more physical disability. Predictors of attitudes to Physical Change were: high extraversion, openness, agreeableness, and conscientiousness; female sex; social class; and less physical disability. Personality predictors of attitudes to Psychological Growth were similar. In contrast, less affluent environment, living alone, lower vocabulary scores, and slower walking speed predicted more positive attitudes in this domain. Conclusions: Older people's attitudes to aging are generally positive. The main predictors of attitude are personality traits. Influencing social circumstances, physical well-being, or mood may result in more positive attitudes. Alternatively, interventions to influence attitudes may have a positive impact on associated physical and affective changes.
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Affiliation(s)
- Susan D Shenkin
- Department of Geriatric Medicine, University of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SB, UK
| | - Ken Laidlaw
- Clinical Psychology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
| | - Mike Allerhand
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Gillian E Mead
- Department of Geriatric Medicine, University of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SB, UK
| | - John M Starr
- Department of Geriatric Medicine, University of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SB, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
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229
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de Jager CA, Dye L, de Bruin EA, Butler L, Fletcher J, Lamport DJ, Latulippe ME, Spencer JPE, Wesnes K. Criteria for validation and selection of cognitive tests for investigating the effects of foods and nutrients. Nutr Rev 2014; 72:162-79. [DOI: 10.1111/nure.12094] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Celeste A de Jager
- School of Public Health and Family Medicine; University of Cape Town; Cape Town South Africa
| | - Louise Dye
- Institute of Psychological Sciences; Human Appetite Research Unit; University of Leeds; Leeds UK
| | | | - Laurie Butler
- School of Psychology and Clinical Language Sciences; University of Reading; Reading UK
| | - John Fletcher
- Research and Development, Nutrition; PepsiCo Europe; Berkshire UK
| | - Daniel J Lamport
- School of Psychology and Clinical Language Sciences; University of Reading; Reading UK
| | - Marie E Latulippe
- International Life Sciences Institute European Branch; Brussels Belgium
| | - Jeremy PE Spencer
- School of Psychology and Clinical Language Sciences; University of Reading; Reading UK
| | - Keith Wesnes
- Bracket Global; Goring-on-Thames UK
- Centre for Human Psychopharmacology; Swinburne University; Melbourne Australia
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230
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Aribisala BS, Morris Z, Eadie E, Thomas A, Gow A, Valdés Hernández MC, Royle NA, Bastin ME, Starr J, Deary IJ, Wardlaw JM. Blood pressure, internal carotid artery flow parameters, and age-related white matter hyperintensities. Hypertension 2014; 63:1011-8. [PMID: 24470459 DOI: 10.1161/hypertensionaha.113.02735] [Citation(s) in RCA: 96] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
White matter hyperintensities (WMH) are associated with hypertension. We examined interactions among blood pressure (BP), internal carotid artery (ICA) flow velocity parameters, and WMH. We obtained BP measurements from 694 community-dwelling subjects at mean ages 69.6 (±0.8) years and again at 72.6 (±0.7) years, plus brain MRI and ICA ultrasound at age 73±1 years. Diastolic and mean BP decreased and pulse pressure increased, but systolic BP did not change between 70 and 73 years. Multiple linear regression, corrected for vascular disease and risk factors, showed that WMH at the age of 73 years were associated with history of hypertension (β=0.13; P<0.001) and with BP at the age of 70 years (systolic β=0.08, mean β=0.09, diastolic β=0.08; all P<0.05); similar but attenuated associations were seen for BP at the age of 73 years. Lower diastolic BP and higher pulse pressure were associated with higher ICA pulsatility index at the age 73 years (diastolic BP age 70 years: standardized β=-0.24, P<0.001; pulse pressure age 70 years: β=0.19, P<0.001). WMH were associated with higher ICA pulsatility index (β=0.13; P=0.002) after adjusting for BP and correction for multiple testing. Therefore, falling diastolic BP and increased pulse pressure are associated with increased ICA pulsatility index, which in turn is associated with WMH. This suggests that hypertension and WMH may either associate indirectly because hypertension increases arterial stiffness that leads to WMH over time, or coassociate through advancing age and stiffer vessels, or both. Reducing vascular stiffness may reduce WMH progression and should be tested in randomized trials, in addition to testing antihypertensive therapy.
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Affiliation(s)
- Benjamin S Aribisala
- Neuroimaging Sciences, University of Edinburgh, Western General Hospital, Bramwell Dott Bldg, Crewe Rd, Edinburgh EH4 2XU, United Kingdom.
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231
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Aribisala BS, Wiseman S, Morris Z, Valdés-Hernández MC, Royle NA, Maniega SM, Gow AJ, Corley J, Bastin ME, Starr J, Deary IJ, Wardlaw JM. Circulating inflammatory markers are associated with magnetic resonance imaging-visible perivascular spaces but not directly with white matter hyperintensities. Stroke 2014; 45:605-7. [PMID: 24399375 DOI: 10.1161/strokeaha.113.004059] [Citation(s) in RCA: 101] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE White matter hyperintensities (WMH) and perivascular spaces (PVS) are features of small vessel disease, found jointly on MRI of older people. Inflammation is a prominent pathological feature of small vessel disease. We examined the association between inflammation, PVS, and WMH in the Lothian Birth Cohort 1936 (N=634). METHODS We measured plasma fibrinogen, C-reactive protein, and interleukin-6 and rated PVS in 3 brain regions. We measured WMH volumetrically and visually using the Fazekas scale. We derived latent variables for PVS, WMH, and Inflammation from measured PVS, WMH, and inflammation markers and modelled associations using structural equation modelling. RESULTS After accounting for age, sex, stroke, and vascular risk factors, PVS were significantly associated with WMH (β=0.47; P<0.0001); Inflammation was weakly but significantly associated with PVS (β=0.12; P=0.048), but not with WMH (β=0.02; P=NS). CONCLUSIONS Circulating inflammatory markers are weakly associated with MR-visible PVS, but not directly with WMH. Longitudinal studies should examine whether visible PVS predate WMH progression and whether inflammation modulators can prevent small vessel disease.
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Affiliation(s)
- Benjamin S Aribisala
- From Brain Research Imaging Centre (B.S.A., S.W., Z.M., M.C.V.-H., N.A.R., S.M.M., M.E.B., J.M.W.), Centre for Cognitive Ageing and Cognitive Epidemiology (B.S.A., M.C.V.-H., N.A.R., S.M.M., A.J.G., M.E.B., J.S., I.J.D., J.M.W.), Department of Psychology (J.C., I.J.D.), and Geriatric Medicine Unit (J.S.), University of Edinburgh, Edinburgh, United Kingdom; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE), Edinburgh, United Kingdom (B.S.A., M.C.V.-H., N.A.R., S.M.M., M.E.B., J.M.W.); Department of Computer Science, Lagos State University, Nigeria (B.S.A.); and Department of Psychology, Heriot-Watt University, United Kingdom (A.J.G.)
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232
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Davies G, Harris SE, Reynolds CA, Payton A, Knight HM, Liewald DC, Lopez LM, Luciano M, Gow AJ, Corley J, Henderson R, Murray C, Pattie A, Fox HC, Redmond P, Lutz MW, Chiba-Falek O, Linnertz C, Saith S, Haggarty P, McNeill G, Ke X, Ollier W, Horan M, Roses AD, Ponting CP, Porteous DJ, Tenesa A, Pickles A, Starr JM, Whalley LJ, Pedersen NL, Pendleton N, Visscher PM, Deary IJ. A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing. Mol Psychiatry 2014; 19. [PMID: 23207651 PMCID: PMC7321835 DOI: 10.1038/mp.2012.159] [Citation(s) in RCA: 124] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cognitive decline is a feared aspect of growing old. It is a major contributor to lower quality of life and loss of independence in old age. We investigated the genetic contribution to individual differences in nonpathological cognitive ageing in five cohorts of older adults. We undertook a genome-wide association analysis using 549 692 single-nucleotide polymorphisms (SNPs) in 3511 unrelated adults in the Cognitive Ageing Genetics in England and Scotland (CAGES) project. These individuals have detailed longitudinal cognitive data from which phenotypes measuring each individual's cognitive changes were constructed. One SNP--rs2075650, located in TOMM40 (translocase of the outer mitochondrial membrane 40 homolog)--had a genome-wide significant association with cognitive ageing (P=2.5 × 10(-8)). This result was replicated in a meta-analysis of three independent Swedish cohorts (P=2.41 × 10(-6)). An Apolipoprotein E (APOE) haplotype (adjacent to TOMM40), previously associated with cognitive ageing, had a significant effect on cognitive ageing in the CAGES sample (P=2.18 × 10(-8); females, P=1.66 × 10(-11); males, P=0.01). Fine SNP mapping of the TOMM40/APOE region identified both APOE (rs429358; P=3.66 × 10(-11)) and TOMM40 (rs11556505; P=2.45 × 10(-8)) as loci that were associated with cognitive ageing. Imputation and conditional analyses in the discovery and replication cohorts strongly suggest that this effect is due to APOE (rs429358). Functional genomic analysis indicated that SNPs in the TOMM40/APOE region have a functional, regulatory non-protein-coding effect. The APOE region is significantly associated with nonpathological cognitive ageing. The identity and mechanism of one or multiple causal variants remain unclear.
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Affiliation(s)
- Gail Davies
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Sarah E Harris
- Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Chandra A Reynolds
- Department of Psychology, University of California - Riverside, Riverside, CA 92521
| | - Antony Payton
- Centre for Integrated Genomic Medical Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT
| | - Helen M Knight
- CGAT, MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road Oxford OX1 3PT, UK
| | - David C Liewald
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Lorna M Lopez
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Michelle Luciano
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Alan J Gow
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Janie Corley
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Ross Henderson
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Catherine Murray
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Alison Pattie
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Helen C. Fox
- Institute of Applied Health Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD
| | - Paul Redmond
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Michael W Lutz
- Division of Neurology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA,Joseph and Kathleen Bryan Alzheimer’s Disease Research Center, Duke University, Durham, NC 27705, USA
| | - Ornit Chiba-Falek
- Division of Neurology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA,Joseph and Kathleen Bryan Alzheimer’s Disease Research Center, Duke University, Durham, NC 27705, USA
| | - Colton Linnertz
- Division of Neurology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - Sunita Saith
- Division of Neurology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - Paul Haggarty
- Nutrition and Epigenetics Group, Rowett Institute of Nutrition and Health, University of Aberdeen, Greenburn Road, Bucksburn, Aberdeen, UK
| | - Geraldine McNeill
- Institute of Applied Health Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD
| | - Xiayi Ke
- Institute of Child Health, University College London, London, UK
| | - William Ollier
- Centre for Integrated Genomic Medical Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT
| | - Michael Horan
- School of Community-Based Medicine, Neurodegeneration Research Group, University of Manchester, Clinical sciences Building, Salford Royal NHS Foundation Trust, Salford M6 8HD
| | - Allen D Roses
- Division of Neurology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA,Joseph and Kathleen Bryan Alzheimer’s Disease Research Center, Duke University, Durham, NC 27705, USA,Zinfandel Pharmaceuticals, Chapel Hill, NC, USA
| | - Chris P Ponting
- CGAT, MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road Oxford OX1 3PT, UK
| | - David J Porteous
- Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Albert Tenesa
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK,The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Roslin, UK
| | - Andrew Pickles
- Clinical Trials Unit, Institute of Psychiatry Room S 2.03, Kings College London
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK,Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Lawrence J Whalley
- Institute of Applied Health Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Department of Psychology, University of Southern California, Los Angeles CA, USA
| | - Neil Pendleton
- School of Community-Based Medicine, Neurodegeneration Research Group, University of Manchester, Clinical sciences Building, Salford Royal NHS Foundation Trust, Salford M6 8HD
| | - Peter M Visscher
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia.,University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland, Australia,The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Ian J Deary
- Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
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233
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Hill WD, Davies G, van de Lagemaat LN, Christoforou A, Marioni RE, Fernandes CPD, Liewald DC, Croning MDR, Payton A, Craig LCA, Whalley LJ, Horan M, Ollier W, Hansell NK, Wright MJ, Martin NG, Montgomery GW, Steen VM, Le Hellard S, Espeseth T, Lundervold AJ, Reinvang I, Starr JM, Pendleton N, Grant SGN, Bates TC, Deary IJ. Human cognitive ability is influenced by genetic variation in components of postsynaptic signalling complexes assembled by NMDA receptors and MAGUK proteins. Transl Psychiatry 2014; 4:e341. [PMID: 24399044 PMCID: PMC3905224 DOI: 10.1038/tp.2013.114] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2013] [Revised: 09/12/2013] [Accepted: 10/21/2013] [Indexed: 12/11/2022] Open
Abstract
Differences in general cognitive ability (intelligence) account for approximately half of the variation in any large battery of cognitive tests and are predictive of important life events including health. Genome-wide analyses of common single-nucleotide polymorphisms indicate that they jointly tag between a quarter and a half of the variance in intelligence. However, no single polymorphism has been reliably associated with variation in intelligence. It remains possible that these many small effects might be aggregated in networks of functionally linked genes. Here, we tested a network of 1461 genes in the postsynaptic density and associated complexes for an enriched association with intelligence. These were ascertained in 3511 individuals (the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium) phenotyped for general cognitive ability, fluid cognitive ability, crystallised cognitive ability, memory and speed of processing. By analysing the results of a genome wide association study (GWAS) using Gene Set Enrichment Analysis, a significant enrichment was found for fluid cognitive ability for the proteins found in the complexes of N-methyl-D-aspartate receptor complex; P=0.002. Replication was sought in two additional cohorts (N=670 and 2062). A meta-analytic P-value of 0.003 was found when these were combined with the CAGES consortium. The results suggest that genetic variation in the macromolecular machines formed by membrane-associated guanylate kinase (MAGUK) scaffold proteins and their interaction partners contributes to variation in intelligence.
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Affiliation(s)
- W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, Edinburgh, UK
| | - L N van de Lagemaat
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - A Christoforou
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, The University of Edinburgh Molecular Medicine Centre, Institute of Genetics and Molecular Medicine, Western General Hospital Edinburgh, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - C P D Fernandes
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M D R Croning
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - A Payton
- Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK
| | - L C A Craig
- Public Health Nutrition Research Group Section of Population Health, University of Aberdeen, Aberdeen, UK
| | - L J Whalley
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - M Horan
- Centre for Clinical and Cognitive Neurosciences, Institute Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - W Ollier
- Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK
| | - N K Hansell
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - N G Martin
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - G W Montgomery
- Queensland Institute of Medical Research, Brisbane, QLD, Australia
| | - V M Steen
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - S Le Hellard
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway,Dr E. Martens Research Group for Biological Psychiatry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - T Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway,KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway,Kavli Research Centre for Aging and Dementia, Haraldplass Hospital, Bergen, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - N Pendleton
- Centre for Clinical and Cognitive Neurosciences, Institute Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - S G N Grant
- Genes to Cognition Programme, Centre for Clinical Brain Sciences and Centre for Neuroregeneration The University of Edinburgh, Edinburgh, UK
| | - T C Bates
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK. E-mail:
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234
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Aribisala BS, Royle NA, Maniega SM, Valdés Hernández MC, Murray C, Penke L, Gow A, Starr JM, Bastin ME, Deary IJ, Wardlaw JM. Quantitative multi-modal MRI of the Hippocampus and cognitive ability in community-dwelling older subjects. Cortex 2013; 53:34-44. [PMID: 24561387 PMCID: PMC3979658 DOI: 10.1016/j.cortex.2013.12.012] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2013] [Revised: 11/26/2013] [Accepted: 12/19/2013] [Indexed: 11/29/2022]
Abstract
Hippocampal structural integrity is commonly quantified using volumetric measurements derived from brain magnetic resonance imaging (MRI). Previously reported associations with cognitive decline have not been consistent. We investigate hippocampal integrity using quantitative MRI techniques and its association with cognitive abilities in older age. Participants from the Lothian Birth Cohort 1936 underwent brain MRI at mean age 73 years. Longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) were measured in the hippocampus. General factors of fluid-type intelligence (g), cognitive processing speed (speed) and memory were obtained at age 73 years, as well as childhood IQ test results at age 11 years. Amongst 565 older adults, multivariate linear regression showed that, after correcting for ICV, gender and age 11 IQ, larger left hippocampal volume was significantly associated with better memory ability (β = .11, p = .003), but not with speed or g. Using quantitative MRI and after correcting for multiple testing, higher T1 and MD were significantly associated with lower scores of g (β range = −.11 to −.14, p < .001), speed (β range = −.15 to −.20, p < .001) and memory (β range = −.10 to −.12, p < .001). Higher MTR and FA in the hippocampus were also significantly associated with higher scores of g (β range = .17 to .18, p < .0001) and speed (β range = .10 to .15, p < .0001), but not memory. Quantitative multi-modal MRI assessments were more sensitive at detecting cognition-hippocampal integrity associations than volumetric measurements, resulting in stronger associations between MRI biomarkers and age-related cognition changes.
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Affiliation(s)
- Benjamin S Aribisala
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK; Department of Computer Science, Lagos State University, Lagos, Nigeria
| | - Natalie A Royle
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK
| | - Susana Muñoz Maniega
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK
| | - Maria C Valdés Hernández
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK
| | - Catherine Murray
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Lars Penke
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK; Institute of Psychology, Georg August University Göttingen, Göttingen, Germany
| | - Alan Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Psychology, School of Life Sciences, Herriot-Watt University, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Geriatric Medicine Unit, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Edinburgh, UK.
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235
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Rowe SJ, Rowlatt A, Davies G, Harris SE, Porteous DJ, Liewald DC, McNeill G, Starr JM, Deary IJ, Tenesa A. Complex variation in measures of general intelligence and cognitive change. PLoS One 2013; 8:e81189. [PMID: 24349040 PMCID: PMC3865348 DOI: 10.1371/journal.pone.0081189] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2013] [Accepted: 10/20/2013] [Indexed: 11/18/2022] Open
Abstract
Combining information from multiple SNPs may capture a greater amount of genetic variation than from the sum of individual SNP effects and help identifying missing heritability. Regions may capture variation from multiple common variants of small effect, multiple rare variants or a combination of both. We describe regional heritability mapping of human cognition. Measures of crystallised (gc) and fluid intelligence (gf) in late adulthood (64-79 years) were available for 1806 individuals genotyped for 549,692 autosomal single nucleotide polymorphisms (SNPs). The same individuals were tested at age 11, enabling us the rare opportunity to measure cognitive change across most of their lifespan. 547,750 SNPs ranked by position are divided into 10, 908 overlapping regions of 101 SNPs to estimate the genetic variance each region explains, an approach that resembles classical linkage methods. We also estimate the genetic variation explained by individual autosomes and by SNPs within genes. Empirical significance thresholds are estimated separately for each trait from whole genome scans of 500 permutated data sets. The 5% significance threshold for the likelihood ratio test of a single region ranged from 17-17.5 for the three traits. This is the equivalent to nominal significance under the expectation of a chi-squared distribution (between 1 df and 0) of P<1.44×10(-5). These thresholds indicate that the distribution of the likelihood ratio test from this type of variance component analysis should be estimated empirically. Furthermore, we show that estimates of variation explained by these regions can be grossly overestimated. After applying permutation thresholds, a region for gf on chromosome 5 spanning the PRRC1 gene is significant at a genome-wide 10% empirical threshold. Analysis of gene methylation on the temporal cortex provides support for the association of PRRC1 and fluid intelligence (P = 0.004), and provides a prime candidate gene for high throughput sequencing of these uniquely informative cohorts.
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Affiliation(s)
- Suzanne J. Rowe
- The Roslin Institute, The University of Edinburgh, Roslin, Scotland, United Kingdom
| | - Amy Rowlatt
- The Roslin Institute, The University of Edinburgh, Roslin, Scotland, United Kingdom
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Sarah E. Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Medical Genetics Section, The University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - David J. Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Medical Genetics Section, The University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - David C. Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Geraldine McNeill
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Albert Tenesa
- The Roslin Institute, The University of Edinburgh, Roslin, Scotland, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- * E-mail:
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236
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Laukka EJ, Starr JM, Deary IJ. Lower ankle-brachial index is related to worse cognitive performance in old age. Neuropsychology 2013; 28:281-9. [PMID: 24295206 PMCID: PMC3942013 DOI: 10.1037/neu0000028] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Objective: We aimed to study the associations between peripheral artery disease (PAD) and ankle-brachial index (ABI) and performance in a range of cognitive domains in nondemented elderly persons. Methods: Data were collected within the Lothian Birth Cohort 1921 and 1936 studies. These are two narrow-age cohorts at age 87 (n = 170) and 73 (n = 748) years. ABI was analyzed as a dichotomous (PAD vs. no PAD) and a continuous measure. PAD was defined as having an ABI less than 0.90. Measures of nonverbal reasoning, verbal declarative memory, verbal fluency, working memory, and processing speed were administered. Both samples were screened for dementia. Results: We observed no significant differences in cognitive performance between persons with or without PAD. However, higher ABI was associated with better general cognition (β = .23, p = .02, R2 change = .05) and processing speed (β = .29, p < .01, R2 change = .08) in the older cohort and better processing speed (β = .12, p < .01, R2 change = .01) in the younger cohort. This was after controlling for age, sex, and childhood mental ability and excluding persons with abnormally high ABI (>1.40) and a history of cardiovascular or cerebrovascular disease. Conclusion: Lower ABI is associated with worse cognitive performance in old age, especially in the oldest old (>85 years), possibly because of long-term exposure to atherosclerotic disease. Interventions targeting PAD in persons free of manifest cardiovascular and cerebrovascular disease may reduce the incidence of cognitive impairment and dementia.
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Affiliation(s)
- Erika J Laukka
- Aging Research Center, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet and Stockholm University
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh
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Lyall DM, Royle NA, Harris SE, Bastin ME, Maniega SM, Murray C, Lutz MW, Saunders AM, Roses AD, del Valdés Hernández MC, Starr JM, Porteous DJ, Wardlaw JM, Deary IJ. Alzheimer's disease susceptibility genes APOE and TOMM40, and hippocampal volumes in the Lothian birth cohort 1936. PLoS One 2013; 8:e80513. [PMID: 24260406 PMCID: PMC3829876 DOI: 10.1371/journal.pone.0080513] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Accepted: 10/04/2013] [Indexed: 12/12/2022] Open
Abstract
The APOE ε and TOMM40 rs10524523 (‘523’) variable length poly-T repeat gene loci have been significantly and independently associated with Alzheimer’s disease (AD) related phenotypes such as age of clinical onset. Hippocampal atrophy has been significantly associated with memory impairment, a characteristic of AD. The current study aimed to test for independent effects of APOE ε and TOMM40 ‘523’ genotypes on hippocampal volumes as assessed by brain structural MRI in a relatively large sample of community-dwelling older adults. As part of a longitudinal study of cognitive ageing, participants in the Lothian Birth Cohort 1936 underwent genotyping for APOE ε2/ε3/ε4 status and TOMM40 ‘523’ poly-T repeat length, and detailed structural brain MRI at a mean age of 72.7 years (standard deviation = 0.7, N range = 624 to 636). No significant effects of APOE ε or TOMM40 523 genotype were found on hippocampal volumes when analysed raw, or when adjusted for either intracranial or total brain tissue volumes. In summary, in a large community-dwelling sample of older adults, we found no effects of APOE ε or TOMM40 523 genotypes on hippocampal volumes. This is discrepant with some previous reports of significant association between APOE and left/right hippocampal volumes, and instead echoes other reports that found no association. Previous significant findings may partly reflect type 1 error. Future studies should carefully consider: 1) their specific techniques in adjusting for brain size; 2) assessing more detailed sub-divisions of the hippocampal formation; and 3) testing whether significant APOE-hippocampal associations are independent of generalised brain atrophy.
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Affiliation(s)
- Donald M. Lyall
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
- Medical Genetics Section, Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Natalie A. Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah E. Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Medical Genetics Section, Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E. Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Catherine Murray
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael W. Lutz
- Joseph & Kathleen Bryan Alzheimer’s Disease Research Center, Department of Neurology, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Ann M. Saunders
- Joseph & Kathleen Bryan Alzheimer’s Disease Research Center, Department of Neurology, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Allen D. Roses
- Joseph & Kathleen Bryan Alzheimer’s Disease Research Center, Department of Neurology, Duke University Medical Center, Durham, North Carolina, United States of America
- Zinfandel Pharmaceuticals, Inc., Durham, North Carolina, United States of America
| | - Maria C. del Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - David. J. Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Medical Genetics Section, Centre for Genomics and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail:
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238
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Aribisala BS, Gow AJ, Bastin ME, del Carmen Valdés Hernández M, Murray C, Royle NA, Muñoz Maniega S, Starr JM, Deary IJ, Wardlaw JM. Associations between level and change in physical function and brain volumes. PLoS One 2013; 8:e80386. [PMID: 24265818 PMCID: PMC3827194 DOI: 10.1371/journal.pone.0080386] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2013] [Accepted: 10/02/2013] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Higher levels of fitness or physical function are positively associated with cognitive outcomes but the potential underlying mechanisms via brain structure are still to be elucidated in detail. We examined associations between brain structure and physical function (contemporaneous and change over the previous three years) in community-dwelling older adults. METHODOLOGY/PRINCIPAL FINDINGS Participants from the Lothian Birth Cohort 1936 (N=694) underwent brain MRI at age 73 years to assess intracranial volume, and the volumes of total brain tissue, ventricles, grey matter, normal-appearing white matter, and white matter lesions. At ages 70 and 73, physical function was assessed by 6-meter walk, grip strength, and forced expiratory volume. A summary 'physical function factor' was derived from the individual measures using principal components analysis. Performance on each individual physical function measure declined across the three year interval (p<0.001). Higher level of physical function at ages 70 and 73 was associated with larger total brain tissue and white matter volumes, and smaller ventricular and white matter lesion volumes (standardized β ranged in magnitude from 0.07 to 0.17, p<0.001 to 0.034). Decline in physical function from age 70 to 73 was associated with smaller white matter volume (0.08, p<0.01, though not after correction for multiple testing), but not with any other brain volumetric measurements. CONCLUSIONS/SIGNIFICANCE Physical function was related to brain volumes in community-dwelling older adults: declining physical function was associated with less white matter tissue. Further study is required to explore the detailed mechanisms through which physical function might influence brain structure, and vice versa.
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Affiliation(s)
- Benjamin S. Aribisala
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Edinburgh, United Kingdom
- Department of Computer Science, Faculty of Science, Lagos State University, Lagos, Nigeria
| | - Alan J. Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, School of Life Sciences, Heriot-Watt University, Edinburgh, United Kingdom
| | - Mark E. Bastin
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Edinburgh, United Kingdom
| | - Maria del Carmen Valdés Hernández
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Edinburgh, United Kingdom
| | - Catherine Murray
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Natalie A. Royle
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Edinburgh, United Kingdom
| | - Susana Muñoz Maniega
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Edinburgh, United Kingdom
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom,
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) Collaboration, Edinburgh, United Kingdom
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Valdés Hernández MDC, Glatz A, Kiker AJ, Dickie DA, Aribisala BS, Royle NA, Muñoz Maniega S, Bastin ME, Deary IJ, Wardlaw JM. Differentiation of calcified regions and iron deposits in the ageing brain on conventional structural MR images. J Magn Reson Imaging 2013; 40:324-33. [PMID: 24923620 DOI: 10.1002/jmri.24348] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2013] [Accepted: 07/26/2013] [Indexed: 11/10/2022] Open
Abstract
PURPOSE In the human brain, minerals such as iron and calcium accumulate increasingly with age. They typically appear hypointense on T2*-weighted MRI sequences. This study aims to explore the differentiation and association between calcified regions and noncalcified iron deposits on clinical brain MRI in elderly, otherwise healthy subjects. MATERIALS AND METHODS Mineral deposits were segmented on co-registered T1- and T2*-weighted sequences from 100 1.5 Tesla MRI datasets of community-dwelling individuals in their 70s. To differentiate calcified regions from noncalcified iron deposits we developed a method based on their appearance on T1-weighted images, which was validated with a purpose-designed phantom. Joint T1- and T2*-weighted intensity histograms were constructed to measure the similarity between the calcified and noncalcified iron deposits using a Euclidean distance based metric. RESULTS We found distinct distributions for calcified regions and noncalcified iron deposits in the cumulative joint T1- and T2*-weighted intensity histograms across all subjects (correlations ranging from 0.02 to 0.86; mean = 0.26 ± 0.16; t = 16.93; P < 0.001) consistent with differences in iron and calcium signal in the phantom. The mean volumes of affected tissue per subject for calcified and noncalcified deposits were 236.74 ± 309.70 mm(3) and 283.76 ± 581.51 mm(3); respectively. There was a positive association between the mineral depositions (β = 0.32, P < 0.005), consistent with existing literature reports. CONCLUSION Calcified mineral deposits and noncalcified iron deposits can be distinguished from each other by signal intensity changes on conventional 1.5T T1-weighted MRI and are significantly associated in brains of elderly, otherwise healthy subjects.
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Affiliation(s)
- Maria del C Valdés Hernández
- Brain Research Imaging Centre, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom; SINAPSE (Scottish Imaging Network, A Platform for Scientific Excellence) collaboration, Scotland, United Kingdom
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Hall PA, Fong GT, Epp LJ. Cognitive and personality factors in the prediction of health behaviors: an examination of total, direct and indirect effects. J Behav Med 2013; 37:1057-68. [PMID: 24072429 DOI: 10.1007/s10865-013-9535-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2013] [Accepted: 08/23/2013] [Indexed: 10/26/2022]
Abstract
Conscientiousness reliably predicts health behavioral patterns, and the same is true of executive function. However, few investigations have examined their relative predictive power, or probed for possible indirect effects and age-moderated effects. In the current study, we examined the predictive validity of all Big Five personality traits, executive function and IQ in relation to an index of health behaviors in an age-stratified community sample. Results indicated that conscientiousness, neuroticism and executive function were significant predictors of health behavior in age-corrected regression analyses. Using bootstrapping methods, we found that executive function partially explains the relationship between both personality dimensions and health behavior. Moderational analyses revealed that effects of personality traits on health behavior were uniformly modest across the age span, whereas the predictive power of executive function became more amplified with increasing age. Both conscientiousness and neuroticism predict health behavior patterns, though their magnitude of association is significantly weaker than executive function and some of their effects are explained by executive function.
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Affiliation(s)
- Peter A Hall
- Faculty of Applied Health Sciences, University of Waterloo, Waterloo, ON, N2E 3G1, Canada,
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Abstract
BACKGROUND Evidence from observational studies to date suggests that healthy dietary patterns are associated with better cognitive performance in later life. We examined the extent to which childhood intelligence quotient (IQ) and socioeconomic status account for this association. METHODS Analyses were carried out on 882 participants in the Lothian Birth Cohort 1936 Study. Four dietary patterns were extracted using principal components analysis of a food frequency questionnaire, namely "Mediterranean-style," "health aware," "traditional," and "sweet foods." Cognitive function was assessed at the age of 70 years, including general (g) cognitive ability, processing speed, memory, and verbal ability. RESULTS Before adjustment for childhood IQ and socioeconomic status, the "Mediterranean-style" dietary pattern was associated with significantly better cognitive performance (effect size as partial eta-square (ηp(2)) range = 0.005 to 0.055), and the "traditional" dietary pattern was associated with poorer performance on all cognitive domains measured in old age (ηp(2) = 0.009 to 0.103). After adjustment for childhood IQ (measured at the age of 11 years) and socioeconomic status, statistical significance was lost for most associations, with the exception of verbal ability and the "Mediterranean-style" pattern (National Adult Reading Test (NART) ηp(2) = 0.006 and Wechsler Test of Adult Reading (WTAR) ηp(2) = 0.013), and the "traditional" pattern (NART ηp(2) = 0.035 and WTAR ηp(2) = 0.027). CONCLUSIONS Our results suggest a pattern of reverse causation or confounding; a higher childhood cognitive ability (and adult socioeconomic status) predicts adherence to a "healthy" diet and better cognitive performance in old age. Our models show no direct link between diet and cognitive performance in old age; instead they are related via the lifelong-stable trait of intelligence.
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242
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Abstract
OBJECTIVES There is a widespread consensus that diabetes impairs cognitive functioning. However, some recent findings have shown that many health conditions generally thought to be detrimental to cognitive functioning are in fact linked to pre-morbid cognitive ability, suggesting reverse causation. To better understand the causality in diabetes-cognition relationship, this study investigates the association of older-age diabetes with concurrent and childhood cognitive functioning. METHODS Lothian Birth Cohort 1936 participants (N=1017) completed the same general cognitive ability test at ages 11 and 70 years. Scores were compared between those with and without diabetes at age 70. Diabetes status was based on self-reports and haemoglobin A1c levels. RESULTS People with diabetes had lower mean cognitive ability scores at ages 11 and 70 when compared with those without diabetes. The effect size was roughly similar at both ages (Cohen's d≈0.32). When adjusted for age-11 cognitive ability, diabetes status was not associated with cognitive ability at age 70. The association between childhood cognitive ability and older-age diabetes was partly accounted for by body mass index and cholesterol level in older-age. CONCLUSION In this sample, diabetes was associated with poorer cognitive ability in old age but this was because of life-long lower cognitive ability in people with diabetes instead of diabetes impairing cognitive functioning.
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Sandeman EM, Hernandez MDCV, Morris Z, Bastin ME, Murray C, Gow AJ, Corley J, Henderson R, Deary IJ, Starr JM, Wardlaw JM. Incidental findings on brain MR imaging in older community-dwelling subjects are common but serious medical consequences are rare: a cohort study. PLoS One 2013; 8:e71467. [PMID: 23967214 PMCID: PMC3744549 DOI: 10.1371/journal.pone.0071467] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2013] [Accepted: 06/29/2013] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVES Incidental findings in neuroimaging occur in 3% of volunteers. Most data come from young subjects. Data on their occurrence in older subjects and their medical, lifestyle and financial consequences are lacking. We determined the prevalence and medical consequences of incidental findings found in community-dwelling older subjects on brain magnetic resonance imaging. DESIGN Prospective cohort observational study. SETTING Single centre study with input from secondary care. PARTICIPANTS Lothian Birth Cohort 1936, a study of cognitive ageing. MAIN OUTCOME MEASURES Incidental findings identified by two consultant neuroradiologists on structural brain magnetic resonance imaging at age 73 years; resulting medical referrals and interventions. PRIMARY AND SECONDARY OUTCOME MEASURES PREVALENCE OF INCIDENTAL FINDINGS BY INDIVIDUAL CATEGORIES: neoplasms, cysts, vascular lesions, developmental, ear, nose or throat anomalies, by intra- and extracranial location; visual rating of white matter hyperintensities and brain atrophy. RESULTS There were 281 incidental findings in 223 (32%) of 700 subjects, including 14 intra- or extracranial neoplasms (2%), 15 intracranial vascular anomalies (2%), and 137 infarcts or haemorrhages (20%). Additionally, 153 had moderate/severe deep white matter hyperintensities (22%) and 176 had cerebral atrophy at, or above, the upper limit of normal (25%) compared with a normative population template. The incidental findings were unrelated to white matter hyperintensities or atrophy; about a third of subjects had both incidental findings and moderate or severe WMH and a quarter had incidental findings and atrophy. The incidental findings resulted in one urgent and nine non-urgent referrals for further medical assessment, but ultimately in no new treatments. CONCLUSIONS In community-dwelling older subjects, incidental findings, including white matter hyperintensities and atrophy, were common. However, many findings were not of medical importance and, in this age group, most did not result in further assessment and none in change of treatment.
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Affiliation(s)
- Elaine M. Sandeman
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria del Carmen Valdes Hernandez
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Clinical Neurosciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Zoe Morris
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Clinical Neurosciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E. Bastin
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Clinical Neurosciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Catherine Murray
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Alan J. Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Janie Corley
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Ross Henderson
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Department of Medicine for the Elderly Western General Hospital, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Clinical Neurosciences, The University of Edinburgh, Edinburgh, United Kingdom
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244
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Kilgour AH, Firth C, Harrison R, Moss P, Bastin ME, Wardlaw JM, Deary IJ, Starr JM. Seropositivity for CMV and IL-6 levels are associated with grip strength and muscle size in the elderly. IMMUNITY & AGEING 2013; 10:33. [PMID: 23938060 PMCID: PMC3765201 DOI: 10.1186/1742-4933-10-33] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/05/2012] [Accepted: 08/12/2013] [Indexed: 12/25/2022]
Abstract
BACKGROUND Sarcopenia is an important cause of morbidity and mortality in older adults, with immunosenescence and inflammation being possible underlying mechanisms. We investigated the relationship between latent cytomegalovirus (CMV) infection, Interleukin 6 (IL-6) levels, muscle size and strength in a group of healthy older community-dwelling people. METHODS Participants were healthy volunteers from the Lothian Birth Cohort 1936 study. Participants had IL-6 level and CMV antibody titre measured at age 70 years and grip strength and a volumetric T1-weighted MRI brain scan (allowing measurement of neck muscle cross-sectional area (CSA)) at age 73. Markers of childhood deprivation were adjusted for in the analysis due to correlations between childhood deprivation and latent CMV infection. RESULTS 866 participants were studied; 448 men (mean age 72.48 years, sd 0.70) and 418 women (mean age 72.51 years, sd 0.72). In men, CMV seropositivity was associated with smaller neck muscle CSA (p = 0.03, partial eta squared = 0.01), even after adjustment for IL-6 levels. Neck muscle CSA was not associated with CMV seropositivity in women, or CMV antibody titre or IL-6 level in either sex. Grip strength associated negatively with IL-6 level (right grip strength p<0.00001, partial eta squared 0.032 and left grip strength p<0.00001, partial eta squared 0.027) with or without adjustment for CMV serostatus or antibody titre. CMV status and antibody titre were not significantly associated with grip strength in either hand. CONCLUSION These findings support the hypothesis that there is a relationship between markers of immunosenescence (i.e. CMV serostatus and IL6 level) and low muscle mass and strength and longitudinal studies in older cohorts are now required to investigate these relationships further.
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Affiliation(s)
- Alixe Hm Kilgour
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK.
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245
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Booth T, Bastin ME, Penke L, Maniega SM, Murray C, Royle NA, Gow AJ, Corley J, Henderson RD, Hernández MDCV, Starr JM, Wardlaw JM, Deary IJ. Brain white matter tract integrity and cognitive abilities in community-dwelling older people: the Lothian Birth Cohort, 1936. Neuropsychology 2013; 27:595-607. [PMID: 23937481 PMCID: PMC3780714 DOI: 10.1037/a0033354] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Objective: The present study investigates associations between brain white matter tract integrity and cognitive abilities in community-dwelling older people (N = 655). We explored two potential confounds of white matter tract−cognition associations in later life: (a) whether the associations between tracts and specific cognitive abilities are accounted for by general cognitive ability (g); and (b) how the presence of atrophy and white matter lesions affect these associations. Method: Tract integrity was determined using quantitative diffusion magnetic resonance imaging tractography (tract-averaged fractional anisotropy [FA]). Using confirmatory factor analysis, we compared first-order and bifactor models to investigate whether specific tract-ability associations were accounted for by g. Results: Significant associations were found between g and FA in bilateral anterior thalamic radiations (r range: .16−.18, p < .01), uncinate (r range: .19−.26, p < .001), arcuate fasciculi (r range: .11−.12, p < .05), and the splenium of corpus callosum (r = .14, p < .01). After controlling for g within the bifactor model, some significant specific cognitive domain associations remained. Results also suggest that the primary effects of controlling for whole brain integrity were on g associations, not specific abilities. Conclusion: Results suggest that g accounts for most of, but not all, the tract−cognition associations in the current data. When controlling for age-related overall brain structural changes, only minor attenuations of the tract−cognition associations were found, and these were primarily with g. In totality, the results highlight the importance of controlling for g when investigating associations between specific cognitive abilities and neuropsychology variables.
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Affiliation(s)
- Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh
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246
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Valdés Hernández MDC, Booth T, Murray C, Gow AJ, Penke L, Morris Z, Maniega SM, Royle NA, Aribisala BS, Bastin ME, Starr JM, Deary IJ, Wardlaw JM. Brain white matter damage in aging and cognitive ability in youth and older age. Neurobiol Aging 2013; 34:2740-7. [PMID: 23850341 PMCID: PMC3898072 DOI: 10.1016/j.neurobiolaging.2013.05.032] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2013] [Revised: 05/23/2013] [Accepted: 05/30/2013] [Indexed: 11/14/2022]
Abstract
Cerebral white matter hyperintensities (WMH) reflect accumulating white matter damage with aging and impair cognition. The role of childhood intelligence is rarely considered in associations between cognitive impairment and WMH. We studied community-dwelling older people all born in 1936, in whom IQ had been assessed at age 11 years. We assessed medical histories, current cognitive ability and quantified WMH on MR imaging. Among 634 participants, mean age 72.7 (SD 0.7), age 11 IQ was the strongest predictor of late life cognitive ability. After accounting for age 11 IQ, greater WMH load was significantly associated with lower late life general cognitive ability (β = −0.14, p < 0.01) and processing speed (β = −0.19, p < 0.001). WMH were also associated independently with lower age 11 IQ (β = −0.08, p < 0.05) and hypertension. In conclusion, having more WMH is significantly associated with lower cognitive ability, after accounting for prior ability, age 11IQ. Early-life IQ also influenced WMH in later life. Determining how lower IQ in youth leads to increasing brain damage with aging is important for future successful cognitive aging.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Brain Research Imaging Centre, Department of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
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247
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Royle NA, Booth T, Valdés Hernández MC, Penke L, Murray C, Gow AJ, Maniega SM, Starr J, Bastin ME, Deary IJ, Wardlaw JM. Estimated maximal and current brain volume predict cognitive ability in old age. Neurobiol Aging 2013; 34:2726-33. [PMID: 23850342 PMCID: PMC3988920 DOI: 10.1016/j.neurobiolaging.2013.05.015] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2012] [Revised: 05/07/2013] [Accepted: 05/16/2013] [Indexed: 11/16/2022]
Abstract
Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging.
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Affiliation(s)
- Natalie A Royle
- Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
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248
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Laude A, Lascaratos G, Henderson RD, Starr JM, Deary IJ, Dhillon B. Retinal nerve fiber layer thickness and cognitive ability in older people: the Lothian Birth Cohort 1936 study. BMC Ophthalmol 2013; 13:28. [PMID: 23822668 PMCID: PMC3706226 DOI: 10.1186/1471-2415-13-28] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2012] [Accepted: 06/25/2013] [Indexed: 11/20/2022] Open
Abstract
Background This study aims to examine the relationship between the retinal nerve fiber layer (RNFL) thickness as measured by optical coherence tomography (OCT) and lifetime cognitive change in healthy older people. Methods In a narrow-age sample population from the Lothian Birth Cohort 1936 who were all aged approximately 72 years when tested, participants underwent RNFL measurements using OCT. General linear modeling was used to calculate the effect of RNFL thickness on three domains; general cognitive ability (g-factor), general processing speed (g-speed) and general memory ability (g-memory) using age at time of assessment and gender as co-variates. Results Of 105 participants, 96 completed OCT scans that were of suitable quality for assessment were analyzed. Using age and gender as covariates, we found only one significant association, between the inferior area RNFL thickness and g-speed (p = 0.049, η2 = 0.045). Interestingly, when we included age 11 IQ as a covariate in addition to age and gender, there were several statistically significant associations (p = 0.029 to 0.048, η2 = 0.00 to 0.059) in a negative direction; decreasing scores on measures of g-factor and g-speed were associated with increasing RNFL thickness (r = −0.229 to −0.243, p < 0.05). No significant associations were found between RNFL thickness and g-memory ability. When we considered the number of years of education as a covariate, we found no significant associations between the RNFL thickness and cognitive scores. Conclusions In a community dwelling cohort of healthy older people, increased RNFL thickness appeared to be associated with lower general processing speed and lower general cognitive ability when age 11 IQ scores were included as a covariate.
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Chin KS, Trucco E, Tan L, Wilson PJ. Automatic fovea location in retinal images using anatomical priors and vessel density. Pattern Recognit Lett 2013. [DOI: 10.1016/j.patrec.2013.03.016] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Bartholomew DJ, Allerhand M, Deary IJ. Measuring mental capacity: Thomson's Bonds model and Spearman's g-model compared. INTELLIGENCE 2013. [DOI: 10.1016/j.intell.2013.03.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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