Publications by authors named "Michelle Luciano"

110 Publications

Predictors of Mild Cognitive Impairment Stability, Progression, or Reversion in the Lothian Birth Cohort 1936.

J Alzheimers Dis 2021 ;80(1):225-232

Lothian Birth Cohorts, School of Philosophy, Psychology & Language Sciences, University of Edinburgh, Edinburgh, UK.

Background: Mild cognitive impairment (MCI) describes a borderland between healthy cognition and dementia. Progression to and reversion from MCI is relatively common but more research is required to understand the factors affecting this fluidity and improve clinical care interventions.

Objective: We explore these transitions in MCI status and their predictive factors over a six-year period in a highly-phenotyped longitudinal study, the Lothian Birth Cohort 1936.

Methods: MCI status was derived in the LBC1936 at ages 76 (n = 567) and 82 years (n = 341) using NIA-AA diagnostic guidelines. Progressions and reversions between healthy cognition and MCI over the follow-up period were assessed. Multinomial logistic regression assessed the effect of various predictors on the likelihood of progressing, reverting, or maintaining cognitive status.

Results: Of the 292 participants who completed both time points, 41 (14%) participants had MCI at T1 and 56 (19%) at T2. Over the follow-up period, 74%remained cognitively healthy, 12%transitioned to MCI, 7%reverted to healthy cognition, and 7%maintained their baseline MCI status. Findings indicated that membership of these transition groups was affected by age, cardiovascular disease, and number of depressive symptoms.

Conclusion: Findings that higher baseline depressive symptoms increase the likelihood of reverting from MCI to healthy cognition indicate that there may be an important role for the treatment of depression for those with MCI. However, further research is required to identify prevention strategies for those at high risk of MCI and inform effective interventions that increase the likelihood of reversion to, and maintenance of healthy cognition.
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http://dx.doi.org/10.3233/JAD-201282DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075399PMC
January 2021

Prevalence of Mild Cognitive Impairment in the Lothian Birth Cohort 1936.

Alzheimer Dis Assoc Disord 2021 Jan 20. Epub 2021 Jan 20.

Lothian Birth Cohorts, Department of Psychology Edinburgh Dementia Prevention Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK.

Background: The Lothian Birth Cohort 1936 (LBC1936) is a highly phenotyped longitudinal study of cognitive and brain ageing. Given its substantial clinical importance, we derived an indicator of mild cognitive impairment (MCI) and amnestic and nonamnestic subtypes at 3 time points.

Methods: MCI status was derived at 3 waves of the LBC1936 at ages 76 (n=567), 79 (n=441), and 82 years (n=341). A general MCI category was derived as well as amnestic MCI (aMCI) and nonamnestic MCI (naMCI). A comparison was made between MCI derivations using normative data from the LBC1936 cohort versus the general UK population.

Results: MCI rates showed a proportional increase at each wave between 76 and 82 years from 15% to 18%. Rates of MCI subtypes also showed a proportional increase over time: aMCI 4% to 6%; naMCI 12% to 16%. Higher rates of MCI were found when using the LBC1936 normative data to derive MCI classification rather than UK-wide norms.

Conclusions: We found that MCI and aMCI rates in the LBC1936 were consistent with previous research. However, naMCI rates were higher than expected. Future LBC1936 research should assess the predictive factors associated with MCI prevalence to validate previous findings and identify novel risk factors.
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http://dx.doi.org/10.1097/WAD.0000000000000433DOI Listing
January 2021

Links between perinatal risk factors and maternal psychological distress: A network analysis.

Acta Obstet Gynecol Scand 2021 05 5;100(5):917-926. Epub 2021 Jan 5.

Department of Psychology, University of Edinburgh, Edinburgh, UK.

Introduction: This paper explores a range of perinatal risk factors that may increase maternal vulnerability to postnatal psychological distress in a sample of 17 531 women participating in the Millennium Cohort Study, a diverse British, longitudinal birth cohort study.

Material And Methods: Using a graphical network modeling framework, this study models the links between postnatal psychological distress and perinatal risk factors, while controlling for sociodemographic factors and history of depression and anxiety. Postnatal psychological distress was assessed at 9 months postpartum using the Rutter Malaise Inventory.

Results: Results of the graphical network models indicate that lower levels of happiness about the pregnancy (Edge weight [w] = 0.084, 95% CI = 0.069-0.100, b = 0.095), smoking during pregnancy (w = 0.026, 95% CI = -0.009-0.060, b = 0.029), infection during pregnancy (w = 0.071, 95% CI = 0.024-0.118, b = 0.090), hyperemesis gravidarum (w = 0.068, 95% CI = 0.013-0.123, b = 0.083), baby in special care (w = 0.048, 95% CI = -0.004-0.099, b = 0.062), not being white (w = 0.101, 95% CI = 0.062-0.140, b = 0.118), being from a more deprived area (w = -0.028, 95% CI = -0.051 to -0.005, b = -0.039), lower income (w = -0.025, 95% CI = -0.055-0.005, b = -0.036), and history of depression or anxiety (w = 0.574, 95% CI = 0.545-0.603, b = 0.764) were associated with increased psychological distress.

Conclusions: Some perinatal risk factors may be directly associated with postnatal psychological distress, but many risk factors appear to be primarily associated with demographic factors. This emphasizes the importance of taking a holistic approach when evaluating an individual's risk of developing postnatal psychological distress.
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http://dx.doi.org/10.1111/aogs.14056DOI Listing
May 2021

Longitudinal effects of breast feeding on parent-reported child behaviour.

Arch Dis Child 2021 04 9;106(4):355-360. Epub 2020 Nov 9.

School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK.

Objective: Shorter breastfeeding duration has been linked to a range of difficulties in children. However, evidence linking shorter breastfeeding duration to child behavioural problems has been inconclusive. Owing to an almost exclusive focus on early childhood in previous research, little is known about breastfeeding effects on behaviour throughout childhood and adolescence. This study examines the longitudinal effect of breast feeding on parent-reported behaviour in children aged 3-14.

Design: Data come from the Millennium Cohort Study, a large, prospective, UK birth cohort study.

Participants: 11 148 children, their parents and teachers.

Methods: This study maps the effect of breastfeeding duration on parent-reported child behaviour longitudinally, using latent growth curve modelling and on teacher-reported child behaviour using multiple regression analyses. Breastfeeding duration was assessed through parent interviews when the child was 9 months old. Children's behavioural development was measured using parent-reported Strengths and Difficulties Questionnaires (SDQ) at 3, 5, 7, 11 and 14 years and teacher-reported SDQs at 7 and 11 years.

Results: Breast feeding was associated with fewer parent-reported behavioural difficulties at all ages even after adjusting for potential confounders (<2 months: =-0.22, 95% CI -0.39 to -0.04; 2-4 months: =-0.53, 95% CI -0.75 to -0.32; 4-6 months: =-1.07, 95% CI -1.33 to -0.81; >6 months: =-1.24, 95% CI -1.44 to -1.04; =adjusted mean difference of raw SDQ scores at age 3, reference: never breast fed).

Conclusion: This study provides further evidence supporting links between breastfeeding duration and children's socioemotional behavioural development. Potential implications include intervention strategies encouraging breast feeding.
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http://dx.doi.org/10.1136/archdischild-2020-319038DOI Listing
April 2021

Genome-wide association study identifies 48 common genetic variants associated with handedness.

Nat Hum Behav 2021 01 28;5(1):59-70. Epub 2020 Sep 28.

Institute of Biological Psychiatry, Mental Health Services of Copenhagen, Copenhagen, Denmark.

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.
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http://dx.doi.org/10.1038/s41562-020-00956-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116623PMC
January 2021

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Nat Commun 2020 09 22;11(1):4796. Epub 2020 Sep 22.

Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
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http://dx.doi.org/10.1038/s41467-020-18367-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508833PMC
September 2020

Association of common genetic variants with brain microbleeds: A genome-wide association study.

Neurology 2020 12 10;95(24):e3331-e3343. Epub 2020 Sep 10.

From the Departments of Epidemiology (M.J.K., H.H.H.A., D.V., S.J.v.d.L., P.Y., M.W.V., N.A., C.M.v.D., M.A.I.), Radiology and Nuclear Medicine (H.H.H.A., P.Y., A.v.d.L., M.W.V.), and Clinical Genetics (H.H.H.A.), Erasmus MC University Medical Center, Rotterdam, the Netherlands; Stroke Research Group, Department of Clinical Neurosciences (D.L., M.T., J.L., D.J.T., H.S.M.), University of Cambridge, UK; Department of Neurology (J.R.J.R., C.L.S., J.J.H., A.S.B., C.D., S. Seshadri), Boston University School of Medicine; The Framingham Heart Study (J.R.J.R., C.L.S., J.J.H., A.S.B., S. Seshadri), MA; Department of Biostatistics (A.V.S.), University of Michigan, Ann Arbor; Icelandic Heart Association (A.V.S., S. Sigurdsson, V.G.), Kopavogur, Iceland; Brown Foundation Institute of Molecular Medicine, McGovern Medical School (M.F.), and Human Genetics Center, School of Public Health (M.F.), University of Texas Health Science Center at Houston; Clinical Division of Neurogeriatrics, Department of Neurology (E.H., L.P., R.S.), Institute for Medical Informatics, Statistics and Documentation (E.H.), and Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry (Y.S., H.S.), Medical University of Graz, Austria; Center of Cerebrovascular Diseases, Department of Neurology (J.L.), West China Hospital, Sichuan University, Chengdu; Stroke Research Centre, Queen Square Institute of Neurology (I.C.H., D.W., H.H., D.J.W.), University College London, UK; Department of Neurosurgery (I.C.H.), Klinikum rechts der Isar, University of Munich, Germany; Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology (M.L., D.C.M.L., M.E.B., I.J.D., J.M.W.), and Centre for Clinical Brain Sciences, Edinburgh Imaging, UK Dementia Research Institute (M.E.B., J.M.W.), University of Edinburgh, UK; Department of Internal Medicine, Section of Gerontology and Geriatrics (S.T.), Department of Cardiology (S.T., J.v.d.G., J.W.J.), Section of Molecular Epidemiology, Biomedical Data Sciences (E.B.v.d.A., M.B., P.E.S.), Leiden Computational Biology Center, Biomedical Data Sciences (E.B.v.d.A.), Department of Radiology (J.v.d.G.), and Einthoven Laboratory for Experimental Vascular Medicine (J.W.J.), Leiden University Medical Center, the Netherlands; Department of Neurology (A.-K.G., N.S.R.), Massachusetts General Hospital, Harvard Medical School, Boston; Memory Aging and Cognition Center (S.H., C.C.), National University Health System, Singapore; Department of Pharmacology (S.H., C.C.) and Saw Swee Hock School of Public Health (S.H.), National University of Singapore and National University Health System, Singapore; Pattern Recognition & Bioinformatics (E.B.v.d.A.), Delft University of Technology, the Netherlands; Department of Biostatistics (S.L., J.J.H., Q.Y., A.S.B.), Boston University School of Public Health, MA; Department of Radiology (C.R.J., K.K.), Mayo Clinic, Rochester, MN; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.L.S., S. Seshadri), UT Health San Antonio, TX; Department of Medicine, Division of Geriatrics (B.G.W., T.H.M), and Memory Impairment and Neurodegenerative Dementia (MIND) Center (T.H.M.), University of Mississippi Medical Center, Jackson; Singapore Eye Research Institute (C.Y.C., J.Y.K., T.Y.W.); Department of Neuroradiology (Z.M., J.M.W.), NHS Lothian, Edinburgh; Institute of Cardiovascular and Medical Sciences (D.J.S.), College of Medical, Veterinary and Life Sciences, University of Glasgow, UK; Division of Cerebrovascular Neurology (R.F.G.), Johns Hopkins University, Baltimore, MD; Department of Neuroradiology (A.D.M.), Atkinson Morley Neurosciences Centre, St George's NHS Foundation Trust, London, UK; Department of Neurology (C.D.), University of California at Davis; Nuffield Department of Population Health (C.M.v.D.), University of Oxford, UK; Laboratory of Epidemiology and Population Sciences (L.J.L.), National Institute on Aging, Baltimore, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik, Iceland.

Objective: To identify common genetic variants associated with the presence of brain microbleeds (BMBs).

Methods: We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.

Results: BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the region reached genome-wide significance for its association with BMB (lead rs769449; odds ratio [OR] [95% confidence interval (CI)] 1.33 [1.21-1.45]; = 2.5 × 10). ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; = 1.0 × 10) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; = 0.68). ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.

Conclusions: Genetic variants in the region are associated with the presence of BMB, most likely due to the ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
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http://dx.doi.org/10.1212/WNL.0000000000010852DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836652PMC
December 2020

Inflammation as a risk factor for the development of frailty in the Lothian Birth Cohort 1936.

Exp Gerontol 2020 10 11;139:111055. Epub 2020 Aug 11.

Lothian Birth Cohorts, School of Philosophy, Psychology & Language Sciences, 7 George Square, University of Edinburgh, Edinburgh, UK.

Background: Research suggests that frailty is associated with higher inflammation levels. We investigated the longitudinal association between chronic inflammation and frailty progression.

Methods: Participants of the Lothian Birth Cohort 1936, aged 70 at baseline were tested four times over 12 years (wave 1: n = 1091, wave 4: n = 550). Frailty was assessed by; the Frailty Index at waves 1-4 and Fried phenotype at waves 1, 3 and 4. Two blood-based inflammatory biomarkers were measured at wave 1: Fibrinogen and C-reactive protein (CRP).

Results: Fully-adjusted, linear mixed effects models showed higher Fibrinogen was significantly associated with higher wave 1 Frailty Index score (β = 0.011, 95% CI[0.002,0.020], p < .05). Over 12 year follow-up, higher wave 1 CRP (β = 0.001, 95% CI[0.000,0.002], p < .05) and Fibrinogen (β = 0.004, 95% CI[0.001,0.007], p < .05) were significantly associated with increased Frailty Index change. For the Fried phenotype, wave 1 Pre-frail and Frail participants had higher CRP and Fibrinogen than Non-frail participants (p < .001). Logistic regression models calculated risk of worsening frailty over follow-up and we observed no significant association of CRP or Fibrinogen in minimally-adjusted nor fully-adjusted models.

Conclusions: Findings showed a longitudinal association of higher wave 1 CRP and Fibrinogen on worsening frailty in the Frailty Index, but not Fried Phenotype. A possible explanation for this disparity may lie in the conceptual differences between frailty measures (a biopsychosocial vs physical approach). Future research, which further explores different domains of frailty, as well the associations between improving frailty and inflammation levels, may elucidate the pathway through which inflammation influences frailty progression. This may improve earlier identification of those at high frailty risk.
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http://dx.doi.org/10.1016/j.exger.2020.111055DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456784PMC
October 2020

Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study of the general population.

medRxiv 2020 Jun 1. Epub 2020 Jun 1.

Objective: To examine the association of a range of psychosocial factors with hospitalisation for COVID-19.

Design: Prospective cohort study.

Setting: England.

Participants: UK Biobank comprises around half a million people who were aged 40 to 69 years at study induction between 2006 and 2010 when information on psychosocial factors and covariates were captured.

Main Outcome Measure: Hospitalisation for COVID-19 in England between 16th March and 26th April 2020 as provided by Public Health England.

Results: There were 908 hospitalisations for COVID-19 in an analytical sample of 431,051 people. In age- and sex-adjusted analyses, an elevated risk of COVID-19 was related to disadvantaged levels of education (odds ratio; 95% confidence interval: 2.05; 1.70, 2.47), income (2.00; 1.63, 2,47), area deprivation (2.20; 1.86, 2.59), occupation (1.39; 1.14, 1.69), psychological distress (1.58; 1.32, 1.89), mental health (1.50; 1.25, 1.79), neuroticism (1.19; 1.00, 1.42), and performance on two tests of cognitive function: verbal and numerical reasoning (2.66; 2.06, 3.34) and reaction speed (1.27; 1.08, 1.51). These associations were graded (p-value for trend <=0.038) such that effects were apparent across the full psychosocial continua. After mutual adjustment for these characteristics plus ethnicity, comorbidity, and lifestyle factors, only the relationship between lower cognitive function as measured using the reasoning test and a doubling in the risk of the infection remained (1.98; 1.38, 2.85).

Conclusion: A range of psychosocial factors revealed associations with hospitalisations for COVID-19 of which the relation with cognitive function was most robust to statistical adjustment.
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http://dx.doi.org/10.1101/2020.05.29.20100735DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302298PMC
June 2020

Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities.

Stroke 2020 07 10;51(7):2111-2121. Epub 2020 Jun 10.

Department of Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, CA.

Background And Purpose: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings.

Methods: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC.

Results: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (), 10q23.1 (), and 10q24.33 ( In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 () and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: (2q32.1), (3q27.1), (5q27.1), and (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype.

Conclusions: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
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http://dx.doi.org/10.1161/STROKEAHA.119.027544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365038PMC
July 2020

A Systematic Review of Frailty Trajectories: Their Shape And Influencing Factors.

Gerontologist 2020 Jun 2. Epub 2020 Jun 2.

Edinburgh Dementia Prevention, University of Edinburgh, BioCube 1, Little France Road, Edinburgh, UK.

Background And Objectives: Frailty describes an increased vulnerability to adverse events such as disease or injury. Combatting this state remains a major challenge for geriatric research. By exploring how and why frailty changes throughout later life we will be better positioned to improve ways of identifying and treating those at high risk.

Research Design And Methods: We systematically reviewed publications that captured rate of frailty progression over time and established any associated risk or protective factors that affected this progression. We included longitudinal observational studies which quantified frailty trajectories in adults aged 50+ using any validated continuous frailty measurement tool.

Results: After screening 8,318 publications, 25 met our criteria. Findings show that despite a great degree of heterogeneity in the literature, progression of frailty is unquestionably affected by numerous risk and protective factors, with particular influence exhibited by social demographics, brain pathology, and physical co-morbidities.

Discussion And Implications: Findings that the gradient of frailty progression is affected by various influencing factors are valuable to clinicians and policymakers as will help identify those at highest frailty risk and inform prevention strategies. However, the heterogeneous methodological approaches of the publications included in this review highlights the need for consensus within the field to promote more coordinated research. Improved consistency of methods will enable further data synthesis and facilitate a greater understanding of the shape of frailty over time and the influencing factors contributing to change, the results of which could have crucial implications for frailty risk reduction.
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http://dx.doi.org/10.1093/geront/gnaa061DOI Listing
June 2020

The Genetics of Reading and Language.

Twin Res Hum Genet 2020 04;23(2):101-102

Department of Psychology, University of Edinburgh, UK.

Recounts how our collaboration with Nick Martin was shaped over two decades, leading to the first studies of predictions from the 'Dual Route Cascaded' computational model of reading in twins, and extending into the molecular work, first linkage, fine mapping of genes identified in pedigree studies, into now the genomewide association study era and the first polygenic risk scores for reading and their potential in early clarifying causality and validating interventions, as well as for future global collaborations in improving these predictors and identifying causal variants. We highlight Nick's warm, future-focused optimism, support and inclusive approach without which none of this would have been possible. The circle of Nick asking, over half a century ago, 'What genes do you think make some kids get better grades?' has built a diverse scientific legacy involving thousands of papers and collaborations. The (heritable) traits of curiosity, boldness, warmth, interest in societally important questions, openness to new methods, ambition and collaborative skill to bring into being the infrastructure and samples needed for this research are rare, and we are grateful.
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http://dx.doi.org/10.1017/thg.2020.28DOI Listing
April 2020

The Association of Dyslexia and Developmental Speech and Language Disorder Candidate Genes with Reading and Language Abilities in Adults.

Twin Res Hum Genet 2020 02 6;23(1):23-32. Epub 2020 Apr 6.

Department of Psychology, The University of Edinburgh, Edinburgh, Scotland, UK.

Reading and language abilities are critical for educational achievement and success in adulthood. Variation in these traits is highly heritable, but the underlying genetic architecture is largely undiscovered. Genetic studies of reading and language skills traditionally focus on children with developmental disorders; however, much larger unselected adult samples are available, increasing power to identify associations with specific genetic variants of small effect size. We introduce an Australian adult population cohort (41.7-73.2 years of age, N = 1505) in which we obtained data using validated measures of several aspects of reading and language abilities. We performed genetic association analysis for a reading and spelling composite score, nonword reading (assessing phonological processing: a core component in learning to read), phonetic spelling, self-reported reading impairment and nonword repetition (a marker of language ability). Given the limited power in a sample of this size (~80% power to find a minimum effect size of 0.005), we focused on analyzing candidate genes that have been associated with dyslexia and developmental speech and language disorders in prior studies. In gene-based tests, FOXP2, a gene implicated in speech/language disorders, was associated with nonword repetition (p < .001), phonetic spelling (p = .002) and the reading and spelling composite score (p < .001). Gene-set analyses of candidate dyslexia and speech/language disorder genes were not significant. These findings contribute to the assessment of genetic associations in reading and language disorders, crucial for understanding their etiology and informing intervention strategies, and validate the approach of using unselected adult samples for gene discovery in language and reading.
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http://dx.doi.org/10.1017/thg.2020.7DOI Listing
February 2020

Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes.

Cereb Cortex 2020 06;30(7):4121-4139

Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04109 Leipzig, Germany.

We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one's occupation.
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http://dx.doi.org/10.1093/cercor/bhaa035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7947185PMC
June 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group.

Mol Psychiatry 2019 Dec 6. Epub 2019 Dec 6.

University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany.

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.
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http://dx.doi.org/10.1038/s41380-019-0605-zDOI Listing
December 2019

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Genetic stratification of depression by neuroticism: revisiting a diagnostic tradition.

Psychol Med 2020 11 2;50(15):2526-2535. Epub 2019 Oct 2.

Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.

Background: Major depressive disorder and neuroticism (Neu) share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression.

Methods: We analysed summary statistics from genome-wide association studies (GWAS) of depression (from the Psychiatric Genomics Consortium, 23andMe and UK Biobank) and compared them with GWAS of Neu (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only Neu or with both. Second, we estimated partial genetic correlations to test whether the depression's genetic link with other phenotypes was explained by shared overlap with Neu.

Results: We found evidence that most genomic regions (25/37) associated with depression are likely to be shared with Neu. The overlapping common genetic variance of depression and Neu was genetically correlated primarily with psychiatric disorders. We found that the genetic contributions to depression, that were not shared with Neu, were positively correlated with metabolic phenotypes and cardiovascular disease, and negatively correlated with the personality trait conscientiousness. After removing shared genetic overlap with Neu, depression still had a specific association with schizophrenia, bipolar disorder, coronary artery disease and age of first birth. Independent of depression, Neu had specific genetic correlates in ulcerative colitis, pubertal growth, anorexia and education.

Conclusion: Our findings demonstrate that, while genetic risk factors for depression are largely shared with Neu, there are also non-Neu-related features of depression that may be useful for further patient or phenotypic stratification.
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http://dx.doi.org/10.1017/S0033291719002629DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737042PMC
November 2020

Brain Peak Width of Skeletonized Mean Diffusivity (PSMD) and Cognitive Function in Later Life.

Front Psychiatry 2019 26;10:524. Epub 2019 Jul 26.

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom.

It is suggested that the brain's peak width of skeletonized water mean diffusivity (PSMD) is a neuro-biomarker of processing speed, an important aspect of cognitive aging. We tested whether PSMD is more strongly correlated with processing speed than with other cognitive domains, and more strongly than other structural brain MRI indices. Participants were 731 Lothian Birth Cohort 1936 members, mean age = 73 years (SD = 0.7); analytical sample was 656-680. Cognitive domains tested were as follows: processing speed (5 tests), visuospatial (3), memory (3), and verbal (3). Brain-imaging variables included PSMD, white matter diffusion parameters, hyperintensity volumes, gray and white matter volumes, and perivascular spaces. PSMD was significantly associated with processing speed (-0.27), visuospatial ability (-0.23), memory ability (-0.17), and general cognitive ability (-0.25); comparable correlations were found with other brain-imaging measures. In a multivariable model with the other imaging variables, PSMD provided independent prediction of visuospatial ability and general cognitive ability. This incremental prediction, coupled with its ease to compute and possibly better tractability, might make PSMD a useful brain biomarker in studies of cognitive aging.
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http://dx.doi.org/10.3389/fpsyt.2019.00524DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676305PMC
July 2019

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Nat Commun 2019 May 1;10(1):2068. Epub 2019 May 1.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland.

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.
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http://dx.doi.org/10.1038/s41467-019-10160-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494826PMC
May 2019

Genetic Structure of IQ, Phonemic Decoding Skill, and Academic Achievement.

Front Genet 2019 18;10:195. Epub 2019 Mar 18.

Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom.

The aim of this study was to examine whether phonemic decoding skill (deficits of which characterize dyslexia) shares genetic and/or environmental covariance with scholastic abilities independent of general intelligence. Non-word reading ability, verbal and non-verbal IQ, and standardized academic achievement (Queensland Core Skills Test; QCST) were measured in Australian twins (up to 876 twin pairs and 80 singleton twins). Multivariate genetic analysis showed the presence of a general genetic factor, likely reflecting crystallized ability, which accounted for 45-76% of phenotypic variance in QCST scores, 62% of variance in Verbal IQ, 23% of variance in Performance IQ, and 19% of variance in phonological reading ability. The phonemic decoding genetic factor (explaining 48% of variance in phonemic decoding) was negatively associated with mathematical achievement scores (0.4%). Shared effects of common environment did not explain the relationship between reading ability and academic achievement beyond those also influencing IQ. The unique environmental reading factor (accounting for 26% of variance) influenced academic abilities related to written expression. Future research will need to address whether these reading-specific genetic and unique environment relationships arise from causal effects of reading on scholastic abilities, or whether both share a common influence, such as pleiotropic genes/environmental factors.
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http://dx.doi.org/10.3389/fgene.2019.00195DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436069PMC
March 2019

The influence of X chromosome variants on trait neuroticism.

Mol Psychiatry 2021 02 6;26(2):483-491. Epub 2019 Mar 6.

Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK.

Autosomal variants have successfully been associated with trait neuroticism in genome-wide analysis of adequately powered samples. But such studies have so far excluded the X chromosome from analysis. Here, we report genetic association analyses of X chromosome and XY pseudoautosomal single nucleotide polymorphisms (SNPs) and trait neuroticism using UK Biobank samples (N = 405,274). Significant association was found with neuroticism on the X chromosome for 204 markers found within three independent loci (a further 783 were suggestive). Most of the lead neuroticism-related X chromosome variants were located in intergenic regions (n = 397). Involvement of HS6ST2, which has been previously associated with sociability behaviour in the dog, was supported by single SNP and gene-based tests. We found that the amino acid and nucleotide sequences are highly conserved between dogs and humans. From the suggestive X chromosome variants, there were 19 nearby genes which could be linked to gene ontology information. Molecular function was primarily related to binding and catalytic activity; notable biological processes were cellular and metabolic, and nucleic acid binding and transcription factor protein classes were most commonly involved. X-variant heritability of neuroticism was estimated at 0.22% (SE = 0.05) from a full dosage compensation model. A polygenic X-variant score created in an independent sample (maximum N ≈ 7,300) did not predict significant variance in neuroticism, psychological distress, or depressive disorder. We conclude that the X chromosome harbours significant variants influencing neuroticism, and might prove important for other quantitative traits and complex disorders.
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http://dx.doi.org/10.1038/s41380-019-0388-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850965PMC
February 2021

Author Correction: Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism.

Nat Genet 2019 03;51(3):577

Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK.

In the version of this article initially published, in Table 2, the descriptions of pathways and definitions in the first and last columns did not correctly correspond to the values in the other columns. The error has been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-019-0357-3DOI Listing
March 2019

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

Neurology 2019 Jan 16. Epub 2019 Jan 16.

Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.

Methods: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.

Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, = 1.77 × 10; and LINC00539/ZDHHC20, = 5.82 × 10. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits ( value for BI, = 9.38 × 10; = 5.23 × 10 for hypertension), smoking ( = 4.4 × 10; = 1.2 × 10), diabetes ( = 1.7 × 10; = 2.8 × 10), previous cardiovascular disease ( = 1.0 × 10; = 2.3 × 10), stroke ( = 3.9 × 10; = 3.2 × 10), and MRI-defined white matter hyperintensity burden ( = 1.43 × 10; = 3.16 × 10), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI ( ≤ 0.0022), without indication of directional pleiotropy.

Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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http://dx.doi.org/10.1212/WNL.0000000000006851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369905PMC
January 2019

Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume.

Nat Commun 2018 09 26;9(1):3945. Epub 2018 Sep 26.

Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald 17475, Germany.

The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρ = -0.59, p-value = 3.14 × 10), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.
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http://dx.doi.org/10.1038/s41467-018-06234-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6158214PMC
September 2018

Interaction of Physical Activity and Personality in the Subjective Wellbeing of Older Adults in Hong Kong and the United Kingdom.

Behav Sci (Basel) 2018 Aug 6;8(8). Epub 2018 Aug 6.

Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK.

Subjective wellbeing (SWB) has been widely accepted as one of the most important elements of successful ageing. The present study explores the impact of two well-established correlates of SWB: physical activity and personality. Physical activity and each of the Big Five personality traits are consistent predictors of SWB, but there has been little research on whether certain personality traits enhance or hinder the psychological benefits of physical activity in older adults. This study examines the interactions of leisure-time physical activity and personality traits on SWB, and whether such interactions vary between older adults in Hong Kong (HK) and older adults in the United Kingdom (UK). Altogether, 349 participants (178 HK, 171 UK; 157 males, 192 female) aged 50 years or above (mean age = 61.84 ± 8.46 years old) completed an online assessment of: (1) leisure-time physical activity (Godin⁻Shephard Leisure-Time Physical Activity Questionnaire); (2) personality traits (Big Five Inventory); and (3) SWB (Satisfaction with Life Scale, Positive and Negative Affect Schedule). Results showed that agreeableness, conscientiousness, extraversion, neuroticism, openness to experience, and physical activity were all significantly related to SWB in the expected direction. The relationship between physical activity and SWB was moderated by extraversion and by openness to experience: higher levels of these two traits significantly enhanced the relationship. None of the interactions varied between the HK and UK samples. The expected negative relationship between neuroticism and SWB, however, was significantly stronger in the UK sample than in the HK sample. The findings of the present study indicate that personality needs to be considered when promoting and providing physical activity for older adults, although more research is needed to further explore how this can work effectively.
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http://dx.doi.org/10.3390/bs8080071DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116082PMC
August 2018

DNA Methylation Signatures of Depressive Symptoms in Middle-aged and Elderly Persons: Meta-analysis of Multiethnic Epigenome-wide Studies.

JAMA Psychiatry 2018 09;75(9):949-959

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Importance: Depressive disorders arise from a combination of genetic and environmental risk factors. Epigenetic disruption provides a plausible mechanism through which gene-environment interactions lead to depression. Large-scale, epigenome-wide studies on depression are missing, hampering the identification of potentially modifiable biomarkers.

Objective: To identify epigenetic mechanisms underlying depression in middle-aged and elderly persons, using DNA methylation in blood.

Design, Setting, And Participants: To date, the first cross-ethnic meta-analysis of epigenome-wide association studies (EWAS) within the framework of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was conducted. The discovery EWAS included 7948 individuals of European origin from 9 population-based cohorts. Participants who were assessed for both depressive symptoms and whole-blood DNA methylation were included in the study. Results of EWAS were pooled using sample-size weighted meta-analysis. Replication of the top epigenetic sites was performed in 3308 individuals of African American and European origin from 2 population-based cohorts.

Main Outcomes And Measures: Whole-blood DNA methylation levels were assayed with Illumina-Infinium Human Methylation 450K BeadChip and depressive symptoms were assessed by questionnaire.

Results: The discovery cohorts consisted of 7948 individuals (4104 [51.6%] women) with a mean (SD) age of 65.4 (5.8) years. The replication cohort consisted of 3308 individuals (2456 [74.2%] women) with a mean (SD) age of 60.3 (6.4) years. The EWAS identified methylation of 3 CpG sites to be significantly associated with increased depressive symptoms: cg04987734 (P = 1.57 × 10-08; n = 11 256; CDC42BPB gene), cg12325605 (P = 5.24 × 10-09; n = 11 256; ARHGEF3 gene), and an intergenic CpG site cg14023999 (P = 5.99 × 10-08; n = 11 256; chromosome = 15q26.1). The predicted expression of the CDC42BPB gene in the brain (basal ganglia) (effect, 0.14; P = 2.7 × 10-03) and of ARHGEF3 in fibroblasts (effect, -0.48; P = 9.8 × 10-04) was associated with major depression.

Conclusions And Relevance: This study identifies 3 methylated sites associated with depressive symptoms. All 3 findings point toward axon guidance as the common disrupted pathway in depression. The findings provide new insights into the molecular mechanisms underlying the complex pathophysiology of depression. Further research is warranted to determine the utility of these findings as biomarkers of depression and evaluate any potential role in the pathophysiology of depression and their downstream clinical effects.
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http://dx.doi.org/10.1001/jamapsychiatry.2018.1725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142917PMC
September 2018

The Influence of Dyslexia Candidate Genes on Reading Skill in Old Age.

Behav Genet 2018 09 29;48(5):351-360. Epub 2018 Jun 29.

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK.

A number of candidate genes for reading and language impairment have been replicated, primarily in samples of children with developmental disability or delay, although these genes are also supported in adolescent population samples. The present study used a systematic approach to test 14 of these candidate genes for association with reading assessed in late adulthood (two cohorts with mean ages of 70 and 79 years). Gene-sets (14 candidates, axon-guidance and neuron migration pathways) and individual SNPs within each gene of interest were tested for association using imputed data referenced to the 1000 genomes European panel. Using the results from the genome-wide association (GWA) meta-analysis of the two cohorts (N = 1217), a competitive gene-set analysis showed that the candidate gene-set was associated with the reading index (p = .016) at a family wise error rate corrected significance level. Neither axon guidance nor neuron migration pathways were significant. Whereas individual SNP associations within CYP19A1, DYX1C1, CNTNAP2 and DIP2A genes (p < .05) did not reach corrected significance their allelic effects were in the same direction as past available reports. These results suggest that reading skill in normal adults shares the same genetic substrate as reading in adolescents, and clinically disordered reading, and highlights the utility of adult samples to increase sample sizes in the genetic study of developmental disorders.
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http://dx.doi.org/10.1007/s10519-018-9913-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097729PMC
September 2018

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Nat Commun 2018 05 29;9(1):2098. Epub 2018 May 29.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland.

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.
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http://dx.doi.org/10.1038/s41467-018-04362-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5974083PMC
May 2018

Genomic analysis of family data reveals additional genetic effects on intelligence and personality.

Mol Psychiatry 2018 12 10;23(12):2347-2362. Epub 2018 Jan 10.

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.

Pedigree-based analyses of intelligence have reported that genetic differences account for 50-80% of the phenotypic variation. For personality traits these effects are smaller, with 34-48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance.
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http://dx.doi.org/10.1038/s41380-017-0005-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294741PMC
December 2018
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