Simon R. Cox

ORCID: 0000-0003-4036-3642
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About
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Research Areas
  • Functional Brain Connectivity Studies
  • Advanced Neuroimaging Techniques and Applications
  • Epigenetics and DNA Methylation
  • Dementia and Cognitive Impairment Research
  • Genetic Associations and Epidemiology
  • Health, Environment, Cognitive Aging
  • Advanced MRI Techniques and Applications
  • Cognitive Abilities and Testing
  • Birth, Development, and Health
  • Genetics and Neurodevelopmental Disorders
  • Tryptophan and brain disorders
  • Health disparities and outcomes
  • Alzheimer's disease research and treatments
  • Intergenerational Family Dynamics and Caregiving
  • Diet and metabolism studies
  • Neonatal and fetal brain pathology
  • Cerebrovascular and Carotid Artery Diseases
  • Frailty in Older Adults
  • Aging and Gerontology Research
  • Mental Health Research Topics
  • Bioinformatics and Genomic Networks
  • Stress Responses and Cortisol
  • Pharmaceutical Practices and Patient Outcomes
  • Neural dynamics and brain function
  • Blood Pressure and Hypertension Studies

University of Edinburgh
2016-2025

NHS Lothian
2019-2025

University of Lausanne
2024

University of Oslo
2024

Cohort (United Kingdom)
2021-2024

GNS Science
2023

Crown Research Institutes
2023

Edinburgh Cancer Research
2023

SIB Swiss Institute of Bioinformatics
2022

ORCID
2022

Abstract Background DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on levels. It is not yet known whether captures aspects biological Results Here we test differences between people’s ages and estimated ages, age, predict all-cause mortality in later life. The difference (Δ ) was calculated four longitudinal cohorts older people. Meta-analysis proportional hazards models from the used to determine association Δ mortality. A 5-year...

10.1186/s13059-015-0584-6 article EN cc-by Genome Biology 2015-01-29
Aysu Okbay Bart M. L. Baselmans Jan-Emmanuel De Neve Patrick Turley Michel G. Nivard and 95 more Mark Alan Fontana S Fleur W Meddens Richard Karlsson Linnér Cornelius A. Rietveld Jaime Derringer Jacob Gratten James J. Lee Jimmy Z. Liu Ronald de Vlaming Tarunveer S. Ahluwalia Jadwiga Buchwald Alana Cavadino Alexis C. Wood Nicholas A. Furlotte Victoria Garfield Marie Henrike Geisel Juan R Gonzalez Saskia Haitjema Robert Karlsson Sander W. van der Laan Karl-Heinz Ladwig Jari Lahti Sven J. van der Lee Penelope A. Lind Tian Liu Lindsay Matteson Evelin Mihailov Michael Miller Camelia C. Minică Ilja M. Nolte Dennis O. Mook‐Kanamori Peter J. van der Most Christopher Oldmeadow Yong Qian Olli Raitakari Rajesh Rawal Anu Realo Rico Rueedi Börge Schmidt Albert V. Smith Evie Stergiakouli Toshiko Tanaka Kent D. Taylor Gudmar Thorleifsson Juho Wedenoja Juergen Wellmann Harm-Jan Westra Sara M. Willems Wei Zhao Najaf Amin Andrew Bakshi Sven Bergmann Gyða Björnsdóttir Patricia A. Boyle Samantha Cherney Simon R. Cox Gail Davies Oliver S. P. Davis Jun Ding Neşe Direk Peter Eibich Rebecca T. Emeny Ghazaleh Fatemifar Jessica D. Faul Luigi Ferrucci Andreas J. Forstner Christian Gieger Richa Gupta Tamara B Harris Juliette Harris Elizabeth G. Holliday Jouke-Jan Hottenga Philip L De Jager Marika Kaakinen Eero Kajantie Ville Karhunen Ivana Kolčić Meena Kumari Lenore J Launer Lude Franke Ruifang Li‐Gao David C. Liewald Marisa Koini Anu Loukola Pedro Marques‐Vidal Grant W. Montgomery Miriam A. Mosing Lavinia Paternoster Alison Pattie Katja Petrovic Laura Pulkki-Råback Lydia Quaye Katri Räikkönen Igor Rudan Rodney J. Scott

10.1038/ng.3552 article EN Nature Genetics 2016-04-18

Sex differences in the human brain are of interest for many reasons: example, there sex observed prevalence psychiatric disorders and some psychological traits that might help to explain. We report largest single-sample study structural functional (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, surface areas, white matter fractional anisotropy; females cortical thickness tract complexity. There was considerable distributional...

10.1093/cercor/bhy109 article EN cc-by Cerebral Cortex 2018-04-20

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological process needed to help identify at increased risk age-associated physical cognitive impairments ultimately, death. Here, we present such biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated machine-learning analysis, trained neuroimaging data from large healthy...

10.1038/mp.2017.62 article EN cc-by Molecular Psychiatry 2017-04-25

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 four mortality-linked markers of physical mental fitness: lung function, walking speed, grip strength cognitive ability. Methods: age acceleration (residuals estimate regressed on age) were estimated in Lothian Birth Cohort 1936 at ages 70 (n =...

10.1093/ije/dyu277 article EN cc-by International Journal of Epidemiology 2015-01-22

Quantifying the microstructural properties of human brain's connections is necessary for understanding normal ageing and disease. Here we examine brain white matter magnetic resonance imaging (MRI) data in 3,513 generally healthy people aged 44.64-77.12 years from UK Biobank. Using conventional water diffusion measures newer, rarely studied indices neurite orientation dispersion density imaging, document large age associations with microstructure. Mean diffusivity most age-sensitive measure,...

10.1038/ncomms13629 article EN cc-by Nature Communications 2016-12-15

People's differences in cognitive functions are partly heritable and associated with important life outcomes. Previous genome-wide association (GWA) studies of have found evidence for polygenic effects yet, to date, there few replicated genetic associations. Here we use data from the UK Biobank sample investigate contributions variation tests three educational attainment. GWA analyses were performed verbal–numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483)...

10.1038/mp.2016.45 article EN cc-by Molecular Psychiatry 2016-04-05

Abstract Aims Several factors are known to increase risk for cerebrovascular disease and dementia, but there is limited evidence on associations between multiple vascular (VRFs) detailed aspects of brain macrostructure microstructure in large community-dwelling populations across middle older age. Methods results Associations VRFs (smoking, hypertension, pulse pressure, diabetes, hypercholesterolaemia, body mass index, waist–hip ratio) structural diffusion MRI markers were examined UK...

10.1093/eurheartj/ehz100 article EN cc-by European Heart Journal 2019-02-19

The COVID-19 pandemic has affected many aspects of people's lives. Lockdown measures to reduce the spread have been more stringent for those aged over 70, at highest risk disease. Here, we examine whether home garden usage is associated with self-reported mental and physical wellbeing in older adults, during lockdown Scotland. This study analysed data from 171 individuals (mean age 84 ± 0.5 years) Lothian Birth Cohort 1936 who completed an online survey approximately two months after...

10.1016/j.jenvp.2020.101545 article EN cc-by Journal of Environmental Psychology 2020-12-11

Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people ASD compared controls, but consistent evidence lacking. Few studies have examined the genetic overlap between cognitive ability ASD/ADHD. The aim this study was to examine polygenic ASD/ADHD from general population. Polygenic risk for ADHD calculated...

10.1038/mp.2015.12 article EN cc-by Molecular Psychiatry 2015-03-10

The associations between indices of brain structure and measured intelligence are unclear. This is partly because the evidence to-date comes from mostly small heterogeneous studies. Here, we report structure-intelligence on a large sample UK Biobank study. overall N = 29,004, with 18,426 participants providing both MRI at least one cognitive test, complete four-test battery data available in minimum 7201, depending upon measure. Participants' age range was 44–81 years (M 63.13, SD 7.48). A...

10.1016/j.intell.2019.101376 article EN cc-by Intelligence 2019-07-19

Aging | doi:10.18632/aging.204434. Ake T. Lu, Alexandra M. Binder, Joshua Zhang, Qi Yan, Alex P. Reiner, Simon R. Cox, Janie Corley, Sarah E. Harris, Pei-Lun Kuo, Ann Z. Moore, Stefania Bandinelli, James D. Stewart, Cuicui Wang, Elissa J. Hamlat, S. Epel, Joel Schwartz, Eric A. Whitsel, Adolfo Correa, Luigi Ferrucci, Riccardo Marioni, Steve Horvath

10.18632/aging.204434 article EN cc-by Aging 2022-12-14

Clonal hematopoiesis of indeterminate potential (CHIP) increases rapidly in prevalence beyond age 60 and has been associated with increased risk for malignancy, heart disease ischemic stroke. CHIP is driven by somatic mutations hematopoietic stem progenitor cells (HSPCs). Because HSPCs often drive leukemia, we hypothesized that HSPC fitness substantially contributes to transformation from leukemia. defined as the proliferative advantage over carrying no or only neutral mutations. If...

10.1038/s41591-022-01883-3 article EN cc-by Nature Medicine 2022-07-01

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of circulating proteome and incident diseases. Using from four cohorts, trained tested scores (EpiScores) for 953 plasma proteins, identifying 109 that explained 1% 58% variance in protein levels after adjusting known quantitative...

10.7554/elife.71802 article EN cc-by eLife 2022-01-13

Abstract Background Epigenetic clocks can track both chronological age (cAge) and biological (bAge). The latter is typically defined by physiological biomarkers risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates cAge bAge become more precise. Here, we aim to develop accurate epigenetic predictors bAge, whilst improving our understanding their epigenomic architecture. Methods First, perform large-scale ( N = 18,413) epigenome-wide...

10.1186/s13073-023-01161-y article EN cc-by Genome Medicine 2023-02-28

Physical fitness is a well-known correlate of health and the aging process DNA methylation (DNAm) data can capture via epigenetic clocks. However, current clocks did not yet use measures mobility, strength, lung, or endurance in their construction. We develop blood-based DNAm biomarkers for parameters gait speed (walking speed), maximum handgrip forced expiratory volume one second (FEV1), maximal oxygen uptake (VO2max) which have modest correlation with five large-scale validation datasets...

10.18632/aging.204538 article EN cc-by Aging 2023-02-22

Epigenetic mechanisms such as DNA methylation (DNAm) are essential for regulation of gene expression. DNAm is dynamic, influenced by both environmental and genetic factors. drift the divergence epigenome a function age due to stochastic changes in methylation. Here we show that epigenetic may be constrained at many CpGs across human genome sequence variation lifetime exposures. We estimate repeatability 234,811 autosomal whole blood using longitudinal data (2–3 repeated measurements) on 478...

10.1101/gr.176933.114 article EN cc-by-nc Genome Research 2014-09-23

It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models data from a narrow-age cohort measured on multi-domain IQ measure at 11 years and comprehensive battery of thirteen measures visuospatial, memory, crystallized, processing speed ages 70, 73, 76 (n = 1091 70). found that 48% the variance in change performance was shared across all measures, an additional 26% specific four ability domains, test-specific. tested...

10.1016/j.intell.2016.08.007 article EN cc-by Intelligence 2016-09-13
Aldi T. Kraja Chunyu Liu Jessica L. Fetterman Mariaelisa Graff Henri Theil and 95 more C. Charles Gu Lisa R. Yanek Mary F. Feitosa Dan E. Arking Daniel I. Chasman Kristin L. Young Symen Ligthart W. David Hill Stefan Weiß Jian’an Luan Franco Giulianini Ruifang Li‐Gao Fernando Pires Hartwig Shiow J. Lin Lihua Wang Tom G. Richardson Jie Yao Eliana Portilla-Fernández Mohsen Ghanbari Mary K. Wojczynski Wen‐Jane Lee Maria Argos Sebastian M. Armasu Ruteja A. Barve Kathleen A. Ryan Ping An Thomas Baranski Suzette J. Bielinski Donald W. Bowden Ulrich Broeckel Kaare Christensen Audrey Y. Chu Janie Corley Simon R. Cox André G. Uitterlinden Fernando Rivadeneira Cheryl D. Cropp E. Warwick Daw Diana van Heemst Lisa de las Fuentes He Gao Ioanna Tzoulaki Tarunveer S. Ahluwalia Renée de Mutsert Leslie Emery A. Mesut Erzurumluoglu James A. Perry Mao Fu Nita G. Forouhi Zhenglong Gu Yang Hai Sarah E. Harris Gibran Hemani Steven C. Hunt Marguerite R. Irvin Anna Jonsson Anne E. Justice Nicola D. Kerrison Nicholas B. Larson Keng-Hung Lin Latisha Love‐Gregory Rasika A. Mathias Joseph H. Lee Matthias Nauck Raymond Noordam Ken K. Ong James S. Pankow Amit Patki Alison Pattie Astrid Petersmann Qibin Qi Rasmus Ribel‐Madsen Rebecca Rohde Kevin Sandow Theresia M. Schnurr Tamar Sofer John M. Starr Adele M. Taylor Alexander Teumer Nicholas J. Timpson Hugoline G. de Haan Yujie Wang Peter Weeke Christine A. Williams Hongsheng Wu Wei Yang Donglin Zeng Daniel R. Witte Bruce S. Weir Nicholas J. Wareham Henrik Vestergaard Stephen T. Turner Christian Torp‐Pedersen Evie Stergiakouli Wayne Huey‐Herng Sheu

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear (MT-nDNA). In CHARGEmtDNA+ Consortium, we studied associations mtDNA MT-nDNA with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation imputation variants was followed single-variant gene-based...

10.1016/j.ajhg.2018.12.001 article EN cc-by The American Journal of Human Genetics 2018-12-27

<h3>Objective:</h3> To assess the association between Mediterranean-type diet (MeDi) and change in brain MRI volumetric measures mean cortical thickness across a 3-year period older age (73–76 years). <h3>Methods:</h3> We focused on 2 longitudinal volumes (total gray matter; n = 401 398, respectively) plus measurement of (n 323), for which previous cross-sectional evidence an with MeDi was strongest. Adherence to calculated from data gathered food frequency questionnaire at 70, 3 years prior...

10.1212/wnl.0000000000003559 article EN cc-by Neurology 2017-01-05

Abstract Previous reports of altered grey and white matter structure in Major Depressive Disorder (MDD) have been inconsistent. Recent meta-analyses have, however, reported reduced hippocampal volume MDD integrity several brain regions. The use different diagnostic criteria, scanners imaging sequences may, obscure further anatomical differences. In this study, we tested for differences subcortical (n = 1157) 1089) between depressed individuals controls the subset 8590 UK Biobank Imaging...

10.1038/s41598-017-05507-6 article EN cc-by Scientific Reports 2017-07-11

Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise the nature of tracking procedure result in an unknown proportion spurious white matter connections. Faithful disentanglement genuine connections is hindered by a lack comprehensive anatomical information at network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it not yet clear how different strategies...

10.1016/j.neuroimage.2019.116443 article EN cc-by-nc-nd NeuroImage 2020-01-10
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