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von Hinke S, Vitt N. An analysis of the accuracy of retrospective birth location recall using sibling data. Nat Commun 2024; 15:2665. [PMID: 38531849 DOI: 10.1038/s41467-024-46781-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 03/06/2024] [Indexed: 03/28/2024] Open
Abstract
Many surveys ask participants to retrospectively record their location of birth. This paper examines the accuracy of such data in the UK Biobank using a sample of full siblings. Comparison of reported birth locations for siblings with different age gaps allows us to estimate the probabilities of household moves and of misreported birth locations. Our first contribution is to show that there are inaccuracies in retrospective birth location data, showing a sizeable probability of misreporting, with 28% of birth coordinates, 16% of local districts and 6% of counties of birth being incorrectly reported. Our second contribution is to show that such error can lead to substantial attenuation bias when investigating the impacts of location-based exposures, especially when there is little spatial correlation and limited time variation in the exposure variable. Sibling fixed effect models are shown to be particularly vulnerable to the attenuation bias. Our third contribution is to highlight possible solutions to the attenuation bias and sensitivity analyses to the reporting error.
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Affiliation(s)
- Stephanie von Hinke
- School of Economics, University of Bristol, Bristol, United Kingdom.
- Institute for Fiscal Studies, London, United Kingdom.
- Institute for the Study of Labor (IZA), Bonn, Germany.
| | - Nicolai Vitt
- School of Economics, University of Bristol, Bristol, United Kingdom.
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2
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Gadd DA, Hillary RF, McCartney DL, Shi L, Stolicyn A, Robertson NA, Walker RM, McGeachan RI, Campbell A, Xueyi S, Barbu MC, Green C, Morris SW, Harris MA, Backhouse EV, Wardlaw JM, Steele JD, Oyarzún DA, Muniz-Terrera G, Ritchie C, Nevado-Holgado A, Chandra T, Hayward C, Evans KL, Porteous DJ, Cox SR, Whalley HC, McIntosh AM, Marioni RE. Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health. Nat Commun 2022; 13:4670. [PMID: 35945220 PMCID: PMC9363452 DOI: 10.1038/s41467-022-32319-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 07/25/2022] [Indexed: 12/04/2022] Open
Abstract
Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.
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Affiliation(s)
- Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Aleks Stolicyn
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Neil A Robertson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Rosie M Walker
- Centre for Clinical Brain Sciences, Chancellor's Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB, UK
| | - Robert I McGeachan
- Centre for Discovery Brain Sciences, University of Edinburgh, 1 George Square, Edinburgh, EH8 9JZ, UK
- The Hospital for Small Animals, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Edinburgh, EH25 9RG, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Shen Xueyi
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Miruna C Barbu
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Claire Green
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Mathew A Harris
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences, Chancellor's Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Chancellor's Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - J Douglas Steele
- Division of Imaging Science and Technology, Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Diego A Oyarzún
- School of Informatics, University of Edinburgh, Edinburgh, EH8 9AB, UK
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH3 3JF, UK
- The Alan Turing Institute, 96 Euston Road, London, NW1 2DB, UK
| | - Graciela Muniz-Terrera
- Centre for Clinical Brain Sciences, Edinburgh Dementia Prevention, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Department of Social Medicine, Ohio University, Athens, OH, 45701, USA
| | - Craig Ritchie
- Centre for Clinical Brain Sciences, Edinburgh Dementia Prevention, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | | | - Tamir Chandra
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Simon R Cox
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
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3
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Barbu MC, Amador C, Kwong ASF, Shen X, Adams MJ, Howard DM, Walker RM, Morris SW, Min JL, Liu C, van Dongen J, Ghanbari M, Relton C, Porteous DJ, Campbell A, Evans KL, Whalley HC, McIntosh AM. Complex trait methylation scores in the prediction of major depressive disorder. EBioMedicine 2022; 79:104000. [PMID: 35490552 PMCID: PMC9062752 DOI: 10.1016/j.ebiom.2022.104000] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/28/2022] [Accepted: 03/29/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. METHODS Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPACadults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). FINDINGS Each trait MS was significantly associated with its corresponding phenotype in GS (βrange=0.089-1.457) and in ALSPAC (βrange=0.078-2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (βrange=0.053-0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MSp-value<0.01-0.5; βrange=-0.069-0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. INTERPRETATION We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (pnominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (NALSPAC=565; NGS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. FUNDING Wellcome Trust.
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Affiliation(s)
- Miruna C Barbu
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom.
| | - Carmen Amador
- MRC Human Genetics Unit, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Alex S F Kwong
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - Xueyi Shen
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - Mark J Adams
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - David M Howard
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Josine L Min
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; The Framingham Heart Study, Framingham, MA, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, the Netherlands
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - Andrew M McIntosh
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
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4
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Gadd DA, Hillary RF, McCartney DL, Zaghlool SB, Stevenson AJ, Cheng Y, Fawns-Ritchie C, Nangle C, Campbell A, Flaig R, Harris SE, Walker RM, Shi L, Tucker-Drob EM, Gieger C, Peters A, Waldenberger M, Graumann J, McRae AF, Deary IJ, Porteous DJ, Hayward C, Visscher PM, Cox SR, Evans KL, McIntosh AM, Suhre K, Marioni RE. Epigenetic scores for the circulating proteome as tools for disease prediction. eLife 2022; 11:e71802. [PMID: 35023833 PMCID: PMC8880990 DOI: 10.7554/elife.71802] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 01/11/2022] [Indexed: 11/13/2022] Open
Abstract
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 the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.
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Affiliation(s)
- Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Shaza B Zaghlool
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education CityDohaQatar
- Computer Engineering Department, Virginia TechBlacksburgUnited States
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Chloe Fawns-Ritchie
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
- Department of Psychology, University of EdinburghEdinburghUnited Kingdom
| | - Cliff Nangle
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Robin Flaig
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Sarah E Harris
- Department of Psychology, University of EdinburghEdinburghUnited Kingdom
- Lothian Birth Cohorts, University of EdinburghEdinburghUnited Kingdom
| | - Rosie M Walker
- Centre for Clinical Brain Sciences, Chancellor’s Building, University of EdinburghEdinburghUnited Kingdom
| | - Liu Shi
- Department of Psychiatry, University of OxfordOxfordUnited Kingdom
| | - Elliot M Tucker-Drob
- Department of Psychology, The University of Texas at AustinAustinUnited States
- Population Research Center, The University of Texas at AustinAustinUnited States
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- German Center for Cardiovascular Research (DZHK), partner site Munich Heart AllianceMunichGermany
- German Center for Diabetes Research (DZD)NeuherbergGermany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- German Center for Cardiovascular Research (DZHK), partner site Munich Heart AllianceMunichGermany
- German Center for Diabetes Research (DZD)NeuherbergGermany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- German Center for Cardiovascular Research (DZHK), partner site Munich Heart AllianceMunichGermany
| | - Johannes Graumann
- Scientific Service Group Biomolecular Mass Spectrometry, Max Planck Institute for Heart and Lung Research, W.G. Kerckhoff InstituteBad NauheimGermany
- German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, Max Planck Institute of Heart and Lung ResearchBad NauheimGermany
| | - Allan F McRae
- Institute for Molecular Bioscience, University of QueenslandBrisbaneAustralia
| | - Ian J Deary
- Department of Psychology, University of EdinburghEdinburghUnited Kingdom
- Lothian Birth Cohorts, University of EdinburghEdinburghUnited Kingdom
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of QueenslandBrisbaneAustralia
| | - Simon R Cox
- Department of Psychology, University of EdinburghEdinburghUnited Kingdom
- Lothian Birth Cohorts, University of EdinburghEdinburghUnited Kingdom
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh HospitalEdinburghUnited Kingdom
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education CityDohaQatar
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghEdinburghUnited Kingdom
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Oppong RF, Boutin T, Campbell A, McIntosh AM, Porteous D, Hayward C, Haley CS, Navarro P, Knott S. SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): Joint Mapping of Common and Rare Variation Affecting Complex Traits. Front Genet 2022; 12:791712. [PMID: 35069690 PMCID: PMC8770330 DOI: 10.3389/fgene.2021.791712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022] Open
Abstract
We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value < 1 × 10-5) for MDD. These significant regions have genes mapped to within 400 kb of them. The genes mapped for height have been reported to be associated with height in humans. Similarly, those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.
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Affiliation(s)
- Richard F. Oppong
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
- Institute of Evolutionary Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, The University of Edinburgh, Edinburgh, United Kingdom
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Sara Knott
- Institute of Evolutionary Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom
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6
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Zeng Y, Amador C, Gao C, Walker RM, Morris SW, Campbell A, Frkatović A, Madden RA, Adams MJ, He S, Bretherick AD, Hayward C, Porteous DJ, Wilson JF, Evans KL, McIntosh AM, Navarro P, Haley CS. Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome. EBioMedicine 2021; 74:103730. [PMID: 34883445 PMCID: PMC8654798 DOI: 10.1016/j.ebiom.2021.103730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 11/19/2021] [Accepted: 11/19/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND parent-of-origin effects (POE) play important roles in complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies mainly focused on the detection of genomic regions or phenotypes regulated by POE. Understanding whether POE may be modified by environmental or genetic exposures is important for understanding of the source of POE-associated variation, but only a few case studies addressing modifiable POE exist. METHODS in order to understand this high order of POE regulation, we screened 101 genetic and environmental factors such as 'predicted mRNA expression levels' of DNA methylation/imprinting machinery genes and environmental exposures. POE-mQTL-modifier interaction models were proposed to test the potential of these factors to modify POE at DNA methylation using data from Generation Scotland: The Scottish Family Health Study(N=2315). FINDINGS a set of vulnerable/modifiable POE-CpGs were identified (modifiable-POE-regulated CpGs, N=3). Four factors, 'lifetime smoking status' and 'predicted mRNA expression levels' of TET2, SIRT1 and KDM1A, were found to significantly modify the POE on the three CpGs in both discovery and replication datasets. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs. INTERPRETATION the modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation, motivating future comprehensive evaluation of the role of these modifiers in complex diseases. FUNDING NSFC (81971270),H2020-MSCA-ITN(721815), Wellcome (204979/Z/16/Z,104036/Z/14/Z), MRC (MC_UU_00007/10, MC_PC_U127592696), CSO (CZD/16/6,CZB/4/276, CZB/4/710), SFC (HR03006), EUROSPAN (LSHG-CT-2006-018947), BBSRC (BBS/E/D/30002276), SYSU, Arthritis Research UK, NHLBI, NIH.
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Affiliation(s)
- Yanni Zeng
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China; Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chenhao Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Azra Frkatović
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, 10000 Zagreb, Croatia
| | - Rebecca A Madden
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Shuai He
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, 510060, China
| | - Andrew D Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK; Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK; Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
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7
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Amador C, Zeng Y, Barber M, Walker RM, Campbell A, McIntosh AM, Evans KL, Porteous DJ, Hayward C, Wilson JF, Navarro P, Haley CS. Genome-wide methylation data improves dissection of the effect of smoking on body mass index. PLoS Genet 2021; 17:e1009750. [PMID: 34499657 PMCID: PMC8428545 DOI: 10.1371/journal.pgen.1009750] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 07/28/2021] [Indexed: 11/18/2022] Open
Abstract
Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.
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Affiliation(s)
- Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Yanni Zeng
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, China
| | - Michael Barber
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
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8
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Pairo-Castineira E, Clohisey S, Klaric L, Bretherick AD, Rawlik K, Pasko D, Walker S, Parkinson N, Fourman MH, Russell CD, Furniss J, Richmond A, Gountouna E, Wrobel N, Harrison D, Wang B, Wu Y, Meynert A, Griffiths F, Oosthuyzen W, Kousathanas A, Moutsianas L, Yang Z, Zhai R, Zheng C, Grimes G, Beale R, Millar J, Shih B, Keating S, Zechner M, Haley C, Porteous DJ, Hayward C, Yang J, Knight J, Summers C, Shankar-Hari M, Klenerman P, Turtle L, Ho A, Moore SC, Hinds C, Horby P, Nichol A, Maslove D, Ling L, McAuley D, Montgomery H, Walsh T, Pereira AC, Renieri A, Shen X, Ponting CP, Fawkes A, Tenesa A, Caulfield M, Scott R, Rowan K, Murphy L, Openshaw PJM, Semple MG, Law A, Vitart V, Wilson JF, Baillie JK. Genetic mechanisms of critical illness in COVID-19. Nature 2021; 591:92-98. [PMID: 33307546 DOI: 10.1038/s41586-020-03065-y] [Citation(s) in RCA: 921] [Impact Index Per Article: 230.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 11/30/2020] [Indexed: 02/06/2023]
Abstract
Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 × 10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice.
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Affiliation(s)
- Erola Pairo-Castineira
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Sara Clohisey
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Andrew D Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Konrad Rawlik
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | | | | | - Nick Parkinson
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | | | - Clark D Russell
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - James Furniss
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Anne Richmond
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Elvina Gountouna
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - David Harrison
- Intensive Care National Audit & Research Centre, London, UK
| | - Bo Wang
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Yang Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Alison Meynert
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | | | | | | | | | - Zhijian Yang
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Ranran Zhai
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Chenqing Zheng
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Graeme Grimes
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | | | | | - Barbara Shih
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Sean Keating
- Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Marie Zechner
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Chris Haley
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Julian Knight
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Manu Shankar-Hari
- Department of Intensive Care Medicine, Guy's and St Thomas' NHS Foundation Trust, London, UK
- School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Paul Klenerman
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Lance Turtle
- NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Antonia Ho
- MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Shona C Moore
- NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Charles Hinds
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Peter Horby
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Alistair Nichol
- Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland
- Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Victoria, Australia
- Intensive Care Unit, Alfred Hospital, Melbourne, Victoria, Australia
| | - David Maslove
- Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Lowell Ling
- Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Danny McAuley
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
- Department of Intensive Care Medicine, Royal Victoria Hospital, Belfast, UK
| | - Hugh Montgomery
- UCL Centre for Human Health and Performance, University College London, London, UK
| | - Timothy Walsh
- Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Alexandre C Pereira
- Faculty of Medicine, University of São Paulo, São Paulo, Brazil
- Heart Institute, University of São Paulo, São Paulo, Brazil
| | - Alessandra Renieri
- Medical Genetics, University of Siena, Siena, Italy
- Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Xia Shen
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Chris P Ponting
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Angie Fawkes
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Albert Tenesa
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - Mark Caulfield
- Genomics England, London, UK
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Richard Scott
- Genomics England, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Kathy Rowan
- Intensive Care National Audit & Research Centre, London, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Peter J M Openshaw
- National Heart and Lung Institute, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust London, London, UK
| | - Malcolm G Semple
- NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- Respiratory Medicine, Alder Hey Children's Hospital, Institute in The Park, University of Liverpool, Liverpool, UK
| | - Andrew Law
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - J Kenneth Baillie
- Roslin Institute, University of Edinburgh, Edinburgh, UK.
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK.
- Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK.
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9
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Walker RM, Vaher K, Bermingham ML, Morris SW, Bretherick AD, Zeng Y, Rawlik K, Amador C, Campbell A, Haley CS, Hayward C, Porteous DJ, McIntosh AM, Marioni RE, Evans KL. Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles. Genome Med 2021; 13:1. [PMID: 33397400 PMCID: PMC7784364 DOI: 10.1186/s13073-020-00808-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 11/12/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODS Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTS We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10-100 ≤ P ≤ 2.44 × 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10-4 ≤ P ≤ 3.01 × 10-2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONS APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.
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Affiliation(s)
- Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Present Address: Centre for Clinical Brain Sciences, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Kadi Vaher
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Present Address: MRC Centre for Reproductive Health, The Queen’s Medical Research Institute, Edinburgh BioQuarter, 47 Little France Crescent, Edinburgh, EH16 4TJ UK
| | - Mairead L. Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Stewart W. Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Andrew D. Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Yanni Zeng
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Present address: Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, 74 Zhongshan 2nd Road, Guangzhou, 510080 China
| | - Konrad Rawlik
- Division of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Roslin, UK
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Archie Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
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10
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Seeboth A, McCartney DL, Wang Y, Hillary RF, Stevenson AJ, Walker RM, Campbell A, Evans KL, McIntosh AM, Hägg S, Deary IJ, Marioni RE. DNA methylation outlier burden, health, and ageing in Generation Scotland and the Lothian Birth Cohorts of 1921 and 1936. Clin Epigenetics 2020; 12:49. [PMID: 32216821 PMCID: PMC7098133 DOI: 10.1186/s13148-020-00838-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 03/09/2020] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND DNA methylation outlier burden has been suggested as a potential marker of biological age. An outlier is typically defined as DNA methylation levels at any one CpG site that are three times beyond the inter-quartile range from the 25th or 75th percentiles compared to the rest of the population. DNA methylation outlier burden (the number of such outlier sites per individual) increases exponentially with age. However, these findings have been observed in small samples. RESULTS Here, we showed an association between age and log10-transformed DNA methylation outlier burden in a large cross-sectional cohort, the Generation Scotland Family Health Study (N = 7010, β = 0.0091, p < 2 × 10-16), and in two longitudinal cohort studies, the Lothian Birth Cohorts of 1921 (N = 430, β = 0.033, p = 7.9 × 10-4) and 1936 (N = 898, β = 0.0079, p = 0.074). Significant confounders of both cross-sectional and longitudinal associations between outlier burden and age included white blood cell proportions, body mass index (BMI), smoking, and batch effects. In Generation Scotland, the increase in epigenetic outlier burden with age was not purely an artefact of an increase in DNA methylation level variability with age (epigenetic drift). Log10-transformed DNA methylation outlier burden in Generation Scotland was not related to self-reported, or family history of, age-related diseases, and it was not heritable (SNP-based heritability of 4.4%, p = 0.18). Finally, DNA methylation outlier burden was not significantly related to survival in either of the Lothian Birth Cohorts individually or in the meta-analysis after correction for multiple testing (HRmeta = 1.12; 95% CImeta = [1.02; 1.21]; pmeta = 0.021). CONCLUSIONS These findings suggest that, while it does not associate with ageing-related health outcomes, DNA methylation outlier burden does track chronological ageing and may also relate to survival. DNA methylation outlier burden may thus be useful as a marker of biological ageing.
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Affiliation(s)
- Anne Seeboth
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
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11
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Abstract
Britain and Ireland are known to show population genetic structure; however, large swathes of Scotland, in particular, have yet to be described. Delineating the structure and ancestry of these populations will allow variant discovery efforts to focus efficiently on areas not represented in existing cohorts. Thus, we assembled genotype data for 2,554 individuals from across the entire archipelago with geographically restricted ancestry, and performed population structure analyses and comparisons to ancient DNA. Extensive geographic structuring is revealed, from broad scales such as a NE to SW divide in mainland Scotland, through to the finest scale observed to date: across 3 km in the Northern Isles. Many genetic boundaries are consistent with Dark Age kingdoms of Gaels, Picts, Britons, and Norse. Populations in the Hebrides, the Highlands, Argyll, Donegal, and the Isle of Man show characteristics of isolation. We document a pole of Norwegian ancestry in the north of the archipelago (reaching 23 to 28% in Shetland) which complements previously described poles of Germanic ancestry in the east, and "Celtic" to the west. This modern genetic structure suggests a northwestern British or Irish source population for the ancient Gaels that contributed to the founding of Iceland. As rarer variants, often with larger effect sizes, become the focus of complex trait genetics, more diverse rural cohorts may be required to optimize discoveries in British and Irish populations and their considerable global diaspora.
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12
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Welsh P, Preiss D, Hayward C, Shah ASV, McAllister D, Briggs A, Boachie C, McConnachie A, Padmanabhan S, Welsh C, Woodward M, Campbell A, Porteous D, Mills NL, Sattar N. Cardiac Troponin T and Troponin I in the General Population. Circulation 2019; 139:2754-2764. [PMID: 31014085 PMCID: PMC6571179 DOI: 10.1161/circulationaha.118.038529] [Citation(s) in RCA: 226] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND There is great interest in widening the use of high-sensitivity cardiac troponins for population cardiovascular disease (CVD) and heart failure screening. However, it is not clear whether cardiac troponin T (cTnT) and troponin I (cTnI) are equivalent measures of risk in this setting. We aimed to compare and contrast (1) the association of cTnT and cTnI with CVD and non-CVD outcomes, and (2) their determinants in a genome-wide association study. METHODS High-sensitivity cTnT and cTnI were measured in serum from 19 501 individuals in Generation Scotland Scottish Family Health Study. Median follow-up was 7.8 years (quartile 1 to quartile 3, 7.1-9.2). Associations of each troponin with a composite CVD outcome (1177 events), CVD death (n=266), non-CVD death (n=374), and heart failure (n=216) were determined by using Cox models. A genome-wide association study was conducted using a standard approach developed for the cohort. RESULTS Both cTnI and cTnT were strongly associated with CVD risk in unadjusted models. After adjusting for classical risk factors, the hazard ratio for a 1 SD increase in log transformed troponin was 1.24 (95% CI, 1.17-1.32) and 1.11 (1.04-1.19) for cTnI and cTnT, respectively; ratio of hazard ratios 1.12 (1.04-1.21). cTnI, but not cTnT, was associated with myocardial infarction and coronary heart disease. Both cTnI and cTnT had strong associations with CVD death and heart failure. By contrast, cTnT, but not cTnI, was associated with non-CVD death; ratio of hazard ratios 0.77 (0.67-0.88). We identified 5 loci (53 individual single-nucleotide polymorphisms) that had genome-wide significant associations with cTnI, and a different set of 4 loci (4 single-nucleotide polymorphisms) for cTnT. CONCLUSIONS The upstream genetic causes of low-grade elevations in cTnI and cTnT appear distinct, and their associations with outcomes also differ. Elevations in cTnI are more strongly associated with some CVD outcomes, whereas cTnT is more strongly associated with the risk of non-CVD death. These findings help inform the selection of an optimal troponin assay for future clinical care and research in this setting.
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Affiliation(s)
- Paul Welsh
- Institute of Cardiovascular and Medical Sciences (P.W., S.P., C.W., N.S.), University of Glasgow, United Kingdom
| | - David Preiss
- MRC Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit (D. Preiss), University of Oxford, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine (C.H.), University of Edinburgh, United Kingdom
| | - Anoop S V Shah
- BHF Centre for Cardiovascular Science (A.S.V.S., N.L.M.), University of Edinburgh, United Kingdom
| | - David McAllister
- Institute of Cardiovascular and Medical Sciences (P.W., S.P., C.W., N.S.), University of Glasgow, United Kingdom
| | - Andrew Briggs
- Institute of Health and Wellbeing (A.B.), University of Glasgow, United Kingdom
| | - Charles Boachie
- Robertson Centre for Biostatistics (C.B., A.M.), University of Glasgow, United Kingdom
| | - Alex McConnachie
- Robertson Centre for Biostatistics (C.B., A.M.), University of Glasgow, United Kingdom
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences (P.W., S.P., C.W., N.S.), University of Glasgow, United Kingdom
| | - Claire Welsh
- Institute of Cardiovascular and Medical Sciences (P.W., S.P., C.W., N.S.), University of Glasgow, United Kingdom
| | - Mark Woodward
- The George Institute for Global Health (M.W.), University of Oxford, United Kingdom.,The George Institute for Global Health, University of New South Wales, Sydney, Australia (M.W.).,Department of Epidemiology, Johns Hopkins University, Baltimore, MD (M.W.)
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine (A.C., D. Porteous), University of Edinburgh, United Kingdom.,Usher Institute for Population Health Sciences and Informatics (A.C.), University of Edinburgh, United Kingdom
| | - David Porteous
- Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine (A.C., D. Porteous), University of Edinburgh, United Kingdom
| | - Nicholas L Mills
- BHF Centre for Cardiovascular Science (A.S.V.S., N.L.M.), University of Edinburgh, United Kingdom
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences (P.W., S.P., C.W., N.S.), University of Glasgow, United Kingdom
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13
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Zeng Y, Amador C, Xia C, Marioni R, Sproul D, Walker RM, Morris SW, Bretherick A, Canela-Xandri O, Boutin TS, Clark DW, Campbell A, Rawlik K, Hayward C, Nagy R, Tenesa A, Porteous DJ, Wilson JF, Deary IJ, Evans KL, McIntosh AM, Navarro P, Haley CS. Parent of origin genetic effects on methylation in humans are common and influence complex trait variation. Nat Commun 2019; 10:1383. [PMID: 30918249 PMCID: PMC6437195 DOI: 10.1038/s41467-019-09301-y] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 02/28/2019] [Indexed: 01/11/2023] Open
Abstract
Parent-of-origin effects (POE) exist when there is differential expression of alleles inherited from the two parents. A genome-wide scan for POE on DNA methylation at 639,238 CpGs in 5,101 individuals identifies 733 independent methylation CpGs potentially influenced by POE at a false discovery rate ≤ 0.05 of which 331 had not previously been identified. Cis and trans methylation quantitative trait loci (mQTL) regulate methylation variation through POE at 54% (399/733) of the identified POE-influenced CpGs. The combined results provide strong evidence for previously unidentified POE-influenced CpGs at 171 independent loci. Methylation variation at 14 of the POE-influenced CpGs is associated with multiple metabolic traits. A phenome-wide association analysis using the POE mQTL SNPs identifies a previously unidentified imprinted locus associated with waist circumference. These results provide a high resolution population-level map for POE on DNA methylation sites, their local and distant regulators and potential consequences for complex traits.
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Affiliation(s)
- Yanni Zeng
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Carmen Amador
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Charley Xia
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Riccardo Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Duncan Sproul
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XR, UK
| | - Rosie M Walker
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Andrew Bretherick
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Oriol Canela-Xandri
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Thibaud S Boutin
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - David W Clark
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Konrad Rawlik
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Caroline Hayward
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Reka Nagy
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Albert Tenesa
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - James F Wilson
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Kathryn L Evans
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Pau Navarro
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Chris S Haley
- MRC Human Genetic Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, EH25 9RG, UK.
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14
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Arnau-Soler A, Adams MJ, Clarke TK, MacIntyre DJ, Milburn K, Navrady L, Hayward C, McIntosh A, Thomson PA. A validation of the diathesis-stress model for depression in Generation Scotland. Transl Psychiatry 2019; 9:25. [PMID: 30659167 PMCID: PMC6338746 DOI: 10.1038/s41398-018-0356-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 11/28/2018] [Accepted: 12/10/2018] [Indexed: 11/11/2022] Open
Abstract
Depression has well-established influences from genetic and environmental risk factors. This has led to the diathesis-stress theory, which assumes a multiplicative gene-by-environment interaction (GxE) effect on risk. Recently, Colodro-Conde et al. empirically tested this theory, using the polygenic risk score for major depressive disorder (PRS, genes) and stressful life events (SLE, environment) effects on depressive symptoms, identifying significant GxE effects with an additive contribution to liability. We have tested the diathesis-stress theory on an independent sample of 4919 individuals. We identified nominally significant positive GxE effects in the full cohort (R2 = 0.08%, p = 0.049) and in women (R2 = 0.19%, p = 0.017), but not in men (R2 = 0.15%, p = 0.07). GxE effects were nominally significant, but only in women, when SLE were split into those in which the respondent plays an active or passive role (R2 = 0.15%, p = 0.038; R2 = 0.16%, p = 0.033, respectively). High PRS increased the risk of depression in participants reporting high numbers of SLE (p = 2.86 × 10-4). However, in those participants who reported no recent SLE, a higher PRS appeared to increase the risk of depressive symptoms in men (β = 0.082, p = 0.016) but had a protective effect in women (β = -0.061, p = 0.037). This difference was nominally significant (p = 0.017). Our study reinforces the evidence of additional risk in the aetiology of depression due to GxE effects. However, larger sample sizes are required to robustly validate these findings.
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Affiliation(s)
- Aleix Arnau-Soler
- Medical Genetics Section, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
| | - Mark J Adams
- Division of Psychiatry, Deanery of Clinical Sciences, Royal Edinburgh Hospital, University of Edinburgh, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, Deanery of Clinical Sciences, Royal Edinburgh Hospital, University of Edinburgh, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Donald J MacIntyre
- Division of Psychiatry, Deanery of Clinical Sciences, Royal Edinburgh Hospital, University of Edinburgh, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Keith Milburn
- Health Informatics Centre, University of Dundee, Dundee, UK
| | - Lauren Navrady
- Division of Psychiatry, Deanery of Clinical Sciences, Royal Edinburgh Hospital, University of Edinburgh, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew McIntosh
- Division of Psychiatry, Deanery of Clinical Sciences, Royal Edinburgh Hospital, University of Edinburgh, Morningside Park, Edinburgh, EH10 5HF, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Pippa A Thomson
- Medical Genetics Section, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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15
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Clarke TK, Zeng Y, Navrady L, Xia C, Haley C, Campbell A, Navarro P, Amador C, Adams MJ, Howard DM, Soler A, Hayward C, Thomson PA, Smith BH, Padmanabhan S, Hocking LJ, Hall LS, Porteous DJ, Deary IJ, McIntosh AM. Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism. Wellcome Open Res 2019; 3:11. [PMID: 30756089 DOI: 10.12688/wellcomeopenres.13893.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/08/2018] [Indexed: 01/06/2023] Open
Abstract
Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r 2=1.1%, p=2.5 x 10 -25) and neuroticism (β =0.13, r 2=1.9%, p=1.04 x 10 -37) at the phenotypic level. Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10 -4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r 2=0.3%, p=3 x 10 -5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (r G=0.33, S.E.=0.08 ) and neuroticism (r G=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.
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Affiliation(s)
- Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Yanni Zeng
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Lauren Navrady
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Charley Xia
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Chris Haley
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Archie Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Pau Navarro
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Carmen Amador
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - David M Howard
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Aleix Soler
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, 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
| | - Pippa A Thomson
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Blair H Smith
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Division of Population Health Sciences, University of Dundee, Dundee, DD1 9SY, UK
| | - Sandosh Padmanabhan
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, G51 4TF, UK
| | - Lynne J Hocking
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, AB24 3FX, UK
| | - Lynsey S Hall
- Institute for Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, CF24 4HQ, UK
| | - David J Porteous
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | | | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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16
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Clarke TK, Zeng Y, Navrady L, Xia C, Haley C, Campbell A, Navarro P, Amador C, Adams MJ, Howard DM, Soler A, Hayward C, Thomson PA, Smith BH, Padmanabhan S, Hocking LJ, Hall LS, Porteous DJ, Deary IJ, McIntosh AM. Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism. Wellcome Open Res 2019; 3:11. [PMID: 30756089 PMCID: PMC6352921 DOI: 10.12688/wellcomeopenres.13893.2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2019] [Indexed: 11/20/2022] Open
Abstract
Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r
2=1.1%, p=2.5 x 10
-25) and neuroticism (β =0.13, r
2=1.9%, p=1.04 x 10
-37) at the phenotypic level. Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10
-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r
2=0.3%, p=3 x 10
-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (r
G=0.33, S.E.=0.08 ) and neuroticism (r
G=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.
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Affiliation(s)
- Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Yanni Zeng
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Lauren Navrady
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Charley Xia
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Chris Haley
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Archie Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Pau Navarro
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Carmen Amador
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - David M Howard
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Aleix Soler
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, 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
| | - Pippa A Thomson
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Blair H Smith
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Division of Population Health Sciences, University of Dundee, Dundee, DD1 9SY, UK
| | - Sandosh Padmanabhan
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, G51 4TF, UK
| | - Lynne J Hocking
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Division of Applied Health Sciences, University of Aberdeen, Aberdeen, AB24 3FX, UK
| | - Lynsey S Hall
- Institute for Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, CF24 4HQ, UK
| | - David J Porteous
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | | | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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17
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Arnau-Soler A, Adams MJ, Generation Scotland, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Hayward C, Thomson PA. Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder. PLoS One 2018; 13:e0209160. [PMID: 30571770 PMCID: PMC6301766 DOI: 10.1371/journal.pone.0209160] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 12/02/2018] [Indexed: 01/31/2023] Open
Abstract
Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity.
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Affiliation(s)
- Aleix Arnau-Soler
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark J. Adams
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
| | | | | | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Pippa A. Thomson
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
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18
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Hill WD, Arslan RC, Xia C, Luciano M, Amador C, Navarro P, Hayward C, Nagy R, Porteous DJ, McIntosh AM, Deary IJ, Haley CS, Penke L. Genomic analysis of family data reveals additional genetic effects on intelligence and personality. Mol Psychiatry 2018; 23:2347-2362. [PMID: 29321673 PMCID: PMC6294741 DOI: 10.1038/s41380-017-0005-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Revised: 11/08/2017] [Accepted: 11/21/2017] [Indexed: 12/17/2022]
Abstract
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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Affiliation(s)
- W David Hill
- 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.
| | - Ruben C Arslan
- Georg Elias Müller Institute of Psychology, Georg August University Göttingen, Göttingen, Germany
- Leibniz Science Campus, Primate Cognition, Göttingen, Germany
- Center for Adaptive Rationality Max Planck Institute for Human Development Lentzeallee, 94, 14195, Berlin, Germany
| | - Charley Xia
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Michelle Luciano
- 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
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Reka Nagy
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, 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
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, UK
| | - Lars Penke
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Georg Elias Müller Institute of Psychology, Georg August University Göttingen, Göttingen, Germany
- Leibniz Science Campus, Primate Cognition, Göttingen, Germany
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19
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McCartney DL, Hillary RF, Stevenson AJ, Ritchie SJ, Walker RM, Zhang Q, Morris SW, Bermingham ML, Campbell A, Murray AD, Whalley HC, Gale CR, Porteous DJ, Haley CS, McRae AF, Wray NR, Visscher PM, McIntosh AM, Evans KL, Deary IJ, Marioni RE. Epigenetic prediction of complex traits and death. Genome Biol 2018; 19:136. [PMID: 30257690 PMCID: PMC6158884 DOI: 10.1186/s13059-018-1514-1] [Citation(s) in RCA: 125] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 08/22/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications. RESULTS Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios. CONCLUSIONS DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.
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Affiliation(s)
- Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Anna J. Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Stuart J. Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Qian Zhang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Stewart W. Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Mairead L. Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Alison D. Murray
- Aberdeen Biomedical Imaging Centre, Lilian Sutton Building, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD UK
| | - Heather C. Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF UK
| | - Catharine R. Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Allan F. McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Peter M. Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Andrew M. McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, 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, Edinburgh, EH8 9JZ UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
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20
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Marioni RE, Campbell A, Hagenaars SP, Nagy R, Amador C, Hayward C, Porteous DJ, Visscher PM, Deary IJ. Genetic Stratification to Identify Risk Groups for Alzheimer's Disease. J Alzheimers Dis 2018; 57:275-283. [PMID: 28222519 PMCID: PMC5345653 DOI: 10.3233/jad-161070] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Stratification by genetic risk factors for Alzheimer’s disease (AD) may help identify groups with the greatest disease risk. Biological changes that cause late-onset AD are likely to occur years, if not decades prior to diagnosis. Here, we select a subset of the Generation Scotland: Scottish Family Health Study cohort in a likely preclinical age-range of 60–70 years (subset n = 3,495 with cognitive and genetic data). We test for cognitive differences by polygenic risk scores for AD. The polygenic scores are constructed using all available SNPs, excluding those within a 500 kb distance of the APOE locus. Additive and multiplicative effects of APOE status on these associations are investigated. Small memory decrements were observed in those with high polygenic risk scores for AD (standardized beta –0.04, p = 0.020). These associations were independent of APOE status. There was no difference in AD polygenic scores across APOE haplotypes (p = 0.72). Individuals with high compared to low polygenic risk scores for AD (top and bottom 5% of the distribution) show cognitive decrements, albeit much smaller than for APOE ɛ4ɛ4 compared to ɛ3ɛ3 individuals (2.3 versus 3.5 fewer points on the processing speed test, and 1.8 versus 2.8 fewer points on the memory test). Polygenic risk scores for AD may help identify older individuals at greatest risk of cognitive decline and preclinical AD.
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Affiliation(s)
- Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Archie Campbell
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK.,Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Reka Nagy
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Carmen Amador
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Peter M Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - 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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21
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Navrady LB, Zeng Y, Clarke TK, Adams MJ, Howard DM, Deary IJ, McIntosh AM. Genetic and environmental contributions to psychological resilience and coping. Wellcome Open Res 2018; 3:12. [PMID: 30345373 PMCID: PMC6192447 DOI: 10.12688/wellcomeopenres.13854.1] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/06/2018] [Indexed: 11/20/2022] Open
Abstract
Background: Twin studies indicate that genetic and environmental factors contribute to both psychological resilience and coping style, but estimates of their relative molecular and shared environmental contributions are limited. The degree of overlap in the genetic architectures of these traits is also unclear. Methods: Using data from a large population- and family-based cohort Generation Scotland (N = 8,734), we estimated the genetic and shared environmental variance components for resilience, task-, emotion-, and avoidance-oriented coping style in a linear mixed model (LMM). Bivariate LMM analyses were used to estimate the genetic correlations between these traits. Resilience and coping style were measured using the Brief Resilience Scale and Coping Inventory for Stressful Situations, respectively. Results: The greatest proportion of the phenotypic variance in resilience remained unexplained, although significant contributions from common genetic variants and family-shared environment were found. Both task- and avoidance-oriented coping had significant contributions from common genetic variants, sibling- and couple-shared environments, variance in emotion-oriented coping was attributable to common genetic variants, family- and couple-shared environments. The estimated correlation between resilience and emotion-oriented coping was high for both common-variant-associated genetic effects (r
G = -0.79, se = 0.19), and for the additional genetic effects from the pedigree (r
K = -0.94, se = 0.30). Genetic correlations between resilience and task- and avoidance-oriented coping did not meet statistical significance. Conclusions: Both genetics and shared environmental effects were major contributing factors to coping style, whilst the variance in resilience remains largely unexplained. Strong genetic overlap between resilience and emotion-oriented coping suggests a relationship whereby genetic factors that increase negative emotionality also lead to decreased resilience. We suggest that genome-wide family-based studies of resilience and coping may help to elucidate tractable methodologies to identify genetic architectures and modifiable environmental risk factors to protect against psychiatric illness, although further work with larger sample sizes is needed.
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Affiliation(s)
- Lauren B Navrady
- Division of Psychiatry, University of Edinburgh, Edinburgh , EH10 5HF, UK
| | - Yanni Zeng
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh , EH10 5HF, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh , EH10 5HF, UK
| | - David M Howard
- Division of Psychiatry, University of Edinburgh, Edinburgh , EH10 5HF, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9XF, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Generation Scotland, Centre for Genetics and Experimental Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh , EH10 5HF, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9XF, UK.,Generation Scotland, Centre for Genetics and Experimental Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
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22
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Russ TC, Murianni L, Icaza G, Slachevsky A, Starr JM. Geographical Variation in Dementia Mortality in Italy, New Zealand, and Chile: The Impact of Latitude, Vitamin D, and Air Pollution. Dement Geriatr Cogn Disord 2018; 42:31-41. [PMID: 27536986 DOI: 10.1159/000447449] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/03/2016] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Dementia risk is reported as being higher in the north compared to the south, which may be related to vitamin D deficiency. If this were the case, an opposite gradient of risk would be observed in the southern hemisphere, but this has not been investigated previously. METHODS We calculated standardised mortality ratios (SMRs) for deaths in 2012 where dementia (Alzheimer's disease, vascular or unspecified dementia) was recorded as the underlying cause for 20 regions in Italy, 20 District Health Board areas in New Zealand and 29 Health Service areas in Chile. RESULTS Dementia SMRs were higher in northern than central or southern Italy. The inverse pattern was seen in women in New Zealand, with rates higher on South Island than North Island. However, dementia risk was raised in eight regions in the north and centre of Chile in both men and women. CONCLUSIONS Geographical variation plays a key role in dementia risk, but patterns vary in men and women. In the northern hemisphere, dementia mortality is higher in the north, but the pattern in the southern hemisphere is more complex.
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Affiliation(s)
- Tom C Russ
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
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23
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Hall LS, Adams MJ, Arnau-Soler A, Clarke TK, Howard DM, Zeng Y, Davies G, Hagenaars SP, Maria Fernandez-Pujals A, Gibson J, Wigmore EM, Boutin TS, Hayward C, Scotland G, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Porteous DJ, Deary IJ, Thomson PA, Haley CS, McIntosh AM. Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank. Transl Psychiatry 2018; 8:9. [PMID: 29317602 PMCID: PMC5802463 DOI: 10.1038/s41398-017-0034-1] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 07/28/2017] [Accepted: 08/25/2017] [Indexed: 11/10/2022] Open
Abstract
Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.
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Affiliation(s)
- Lynsey S. Hall
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK ,0000 0001 0462 7212grid.1006.7Institute of Genetic Medicine, Newcastle University, NE1 7RU Newcastle upon Tyne, UK
| | - Mark J. Adams
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK
| | - Aleix Arnau-Soler
- 0000 0004 1936 7988grid.4305.2Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Toni-Kim Clarke
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK
| | - David M. Howard
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK
| | - Yanni Zeng
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Gail Davies
- 0000 0004 1936 7988grid.4305.2Department of Psychology, University of Edinburgh, EH8 9YL Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Saskia P. Hagenaars
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Department of Psychology, University of Edinburgh, EH8 9YL Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Ana Maria Fernandez-Pujals
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK
| | - Jude Gibson
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK
| | - Eleanor M. Wigmore
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK
| | - Thibaud S. Boutin
- 0000 0004 1936 7988grid.4305.2Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Caroline Hayward
- 0000 0004 1936 7988grid.4305.2Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK ,A collaboration between the University Medical Schools and National Health Service in Aberdeen, Dundee, Edinburgh and Glasgow UK
| | - Generation Scotland
- A collaboration between the University Medical Schools and National Health Service in Aberdeen, Dundee, Edinburgh and Glasgow UK
| | | | - David J. Porteous
- 0000 0004 1936 7988grid.4305.2Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Ian J. Deary
- 0000 0004 1936 7988grid.4305.2Department of Psychology, University of Edinburgh, EH8 9YL Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Pippa A. Thomson
- 0000 0004 1936 7988grid.4305.2Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Chris S. Haley
- 0000 0004 1936 7988grid.4305.2Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Andrew M. McIntosh
- 0000 0004 1936 7988grid.4305.2Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, EH10 5HF Edinburgh, UK ,0000 0004 1936 7988grid.4305.2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
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24
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Allardyce J, Leonenko G, Hamshere M, Pardiñas AF, Forty L, Knott S, Gordon-Smith K, Porteous DJ, Haywood C, Di Florio A, Jones L, McIntosh AM, Owen MJ, Holmans P, Walters JTR, Craddock N, Jones I, O’Donovan MC, Escott-Price V. Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder. JAMA Psychiatry 2018; 75:28-35. [PMID: 29167880 PMCID: PMC5833541 DOI: 10.1001/jamapsychiatry.2017.3485] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 09/24/2017] [Indexed: 11/14/2022]
Abstract
Importance Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes and mechanisms. Objective To investigate the association between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRSs), and psychotic presentations of BD. Design, Setting, and Participants This case-control study in the United Kingdom used multinomial logistic regression to estimate differential PRS associations across categories of cases and controls. Participants included in the final analyses were 4436 cases of BD from the Bipolar Disorder Research Network. These cases were compared with the genotypic data for 4976 cases of schizophrenia and 9012 controls from the Type 1 Diabetes Genetics Consortium study and the Generation Scotland study. Data were collected between January 1, 2000, and December 31, 2013. Data analysis was conducted from March 1, 2016, to February 28, 2017. Exposures Standardized PRSs, calculated using alleles with an association threshold of P < .05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, were adjusted for the first 10 population principal components and genotyping platforms. Main Outcomes and Measures Multinomial logit models estimated PRS associations with BD stratified by Research Diagnostic Criteria subtypes of BD, by lifetime occurrence of psychosis, and by lifetime mood-incongruent psychotic features. Ordinal logistic regression examined PRS associations across levels of mood incongruence. Ratings were derived from the Schedules for Clinical Assessment in Neuropsychiatry interview and the Bipolar Affective Disorder Dimension Scale. Results Of the 4436 cases of BD, 2966 (67%) were female patients, and the mean (SD) age at interview was 46 [12] years. Across clinical phenotypes, there was an exposure-response gradient, with the strongest PRS association for schizophrenia (risk ratio [RR] = 1.94; 95% CI, 1.86-2.01), followed by schizoaffective BD (RR = 1.37; 95% CI, 1.22-1.54), bipolar I disorder subtype (RR = 1.30; 95% CI, 1.24-1.36), and bipolar II disorder subtype (RR = 1.04; 95% CI, 0.97-1.11). Within BD cases, there was an effect gradient, indexed by the nature of psychosis. Prominent mood-incongruent psychotic features had the strongest association (RR = 1.46; 95% CI, 1.36-1.57), followed by mood-congruent psychosis (RR = 1.24; 95% CI, 1.17-1.33) and BD with no history of psychosis (RR = 1.09; 95% CI, 1.04-1.15). Conclusions and Relevance For the first time to date, a study shows a polygenic-risk gradient across schizophrenia and BD, indexed by the occurrence and level of mood-incongruent psychotic symptoms.
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Affiliation(s)
- Judith Allardyce
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Ganna Leonenko
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Marian Hamshere
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Antonio F. Pardiñas
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Liz Forty
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Sarah Knott
- Department of Psychological Medicine, University of Worcester, Worcester, England
| | | | - David J. Porteous
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland
| | - Caroline Haywood
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland
| | - Arianna Di Florio
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Lisa Jones
- Department of Psychological Medicine, University of Worcester, Worcester, England
| | - Andrew M. McIntosh
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland
- Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland
| | - Michael J. Owen
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Peter Holmans
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - James T. R. Walters
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Nicholas Craddock
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Ian Jones
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Michael C. O’Donovan
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Valentina Escott-Price
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
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Genome-wide haplotype-based association analysis of major depressive disorder in Generation Scotland and UK Biobank. Transl Psychiatry 2017; 7:1263. [PMID: 29187746 PMCID: PMC5802488 DOI: 10.1038/s41398-017-0010-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Revised: 08/16/2017] [Accepted: 08/20/2017] [Indexed: 12/22/2022] Open
Abstract
Genome-wide association studies using genotype data have had limited success in the identification of variants associated with major depressive disorder (MDD). Haplotype data provide an alternative method for detecting associations between variants in weak linkage disequilibrium with genotyped variants and a given trait of interest. A genome-wide haplotype association study for MDD was undertaken utilising a family-based population cohort, Generation Scotland: Scottish Family Health Study (n = 18,773), as a discovery cohort with UK Biobank used as a population-based replication cohort (n = 25,035). Fine mapping of haplotype boundaries was used to account for overlapping haplotypes potentially tagging the same causal variant. Within the discovery cohort, two haplotypes exceeded genome-wide significance (P < 5 × 10-8) for an association with MDD. One of these haplotypes was nominally significant in the replication cohort (P < 0.05) and was located in 6q21, a region which has been previously associated with bipolar disorder, a psychiatric disorder that is phenotypically and genetically correlated with MDD. Several haplotypes with P < 10-7 in the discovery cohort were located within gene coding regions associated with diseases that are comorbid with MDD. Using such haplotypes to highlight regions for sequencing may lead to the identification of the underlying causal variants.
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26
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Regional variation in health is predominantly driven by lifestyle rather than genetics. Nat Commun 2017; 8:801. [PMID: 28986520 PMCID: PMC5630587 DOI: 10.1038/s41467-017-00497-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 07/05/2017] [Indexed: 12/16/2022] Open
Abstract
Regional differences in health-related phenotypes have been detected between and within countries. In Scotland, regions differ for a variety of health-related traits and display differences in mean lifespan of up to 7.5 years. Both genetics and lifestyle differences are potential causes of this variation. Using data on obesity-related traits of ~11,000 Scottish individuals with genome-wide genetic information and records of lifestyle and socioeconomic factors, we explored causes of regional variation by using models that incorporate genetic and environmental information jointly. We found that variation between individuals within regions showed substantial influence of both genetic variation and family environment. Regional variation for most obesity traits was associated with lifestyle and socioeconomic variables, such as smoking, diet and deprivation which are potentially modifiable. There was limited evidence that regional differences were of genetic origin. This has important implications for healthcare policies, suggesting that inequalities can be tackled with appropriate social and economic interventions. Health-related traits are known to vary geographically. Here, Amador and colleagues show that regional variation of obesity-related traits in a Scottish population is influenced more by lifestyle differences than it is by genetic differences.
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Howard DM, Adams MJ, Clarke TK, Wigmore EM, Zeng Y, Hagenaars SP, Lyall DM, Thomson PA, Evans KL, Porteous DJ, Nagy R, Hayward C, Haley CS, Smith BH, Murray AD, Batty GD, Deary IJ, McIntosh AM. Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank. Wellcome Open Res 2017; 2:61. [PMID: 28989979 PMCID: PMC5605947 DOI: 10.12688/wellcomeopenres.12171.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/07/2017] [Indexed: 01/07/2023] Open
Abstract
Background: Cognitive ability is a heritable trait with a polygenic architecture, for which several associated variants have been identified using genotype-based and candidate gene approaches. Haplotype-based analyses are a complementary technique that take phased genotype data into account, and potentially provide greater statistical power to detect lower frequency variants. Methods: In the present analysis, three cohort studies (n
total = 48,002) were utilised: Generation Scotland: Scottish Family Health Study (GS:SFHS), the English Longitudinal Study of Ageing (ELSA), and the UK Biobank. A genome-wide haplotype-based meta-analysis of cognitive ability was performed, as well as a targeted meta-analysis of several gene coding regions. Results: None of the assessed haplotypes provided evidence of a statistically significant association with cognitive ability in either the individual cohorts or the meta-analysis. Within the meta-analysis, the haplotype with the lowest observed
P-value overlapped with the D-amino acid oxidase activator (
DAOA) gene coding region. This coding region has previously been associated with bipolar disorder, schizophrenia and Alzheimer’s disease, which have all been shown to impact upon cognitive ability. Another potentially interesting region highlighted within the current genome-wide association analysis (GS:SFHS:
P = 4.09 x 10
-7), was the butyrylcholinesterase (
BCHE) gene coding region. The protein encoded by
BCHE has been shown to influence the progression of Alzheimer’s disease and its role in cognitive ability merits further investigation. Conclusions: Although no evidence was found for any haplotypes with a statistically significant association with cognitive ability, our results did provide further evidence that the genetic variants contributing to the variance of cognitive ability are likely to be of small effect.
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Affiliation(s)
- David M Howard
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Eleanor M Wigmore
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Yanni Zeng
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.,Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Saskia P Hagenaars
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Donald M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Pippa A Thomson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Reka Nagy
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Generation Scotland, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Chris S Haley
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Blair H Smith
- Generation Scotland, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Division of Population Health Sciences, University of Dundee, Dundee, UK
| | - Alison D Murray
- Generation Scotland, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.,Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - G David Batty
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK.,Generation Scotland, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Generation Scotland, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
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28
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Nagy R, Boutin TS, Marten J, Huffman JE, Kerr SM, Campbell A, Evenden L, Gibson J, Amador C, Howard DM, Navarro P, Morris A, Deary IJ, Hocking LJ, Padmanabhan S, Smith BH, Joshi P, Wilson JF, Hastie ND, Wright AF, McIntosh AM, Porteous DJ, Haley CS, Vitart V, Hayward C. Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants. Genome Med 2017; 9:23. [PMID: 28270201 PMCID: PMC5339960 DOI: 10.1186/s13073-017-0414-4] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 02/09/2017] [Indexed: 01/31/2023] Open
Abstract
Background The Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based population cohort with DNA, biological samples, socio-demographic, psychological and clinical data from approximately 24,000 adult volunteers across Scotland. Although data collection was cross-sectional, GS:SFHS became a prospective cohort due to of the ability to link to routine Electronic Health Record (EHR) data. Over 20,000 participants were selected for genotyping using a large genome-wide array. Methods GS:SFHS was analysed using genome-wide association studies (GWAS) to test the effects of a large spectrum of variants, imputed using the Haplotype Research Consortium (HRC) dataset, on medically relevant traits measured directly or obtained from EHRs. The HRC dataset is the largest available haplotype reference panel for imputation of variants in populations of European ancestry and allows investigation of variants with low minor allele frequencies within the entire GS:SFHS genotyped cohort. Results Genome-wide associations were run on 20,032 individuals using both genotyped and HRC imputed data. We present results for a range of well-studied quantitative traits obtained from clinic visits and for serum urate measures obtained from data linkage to EHRs collected by the Scottish National Health Service. Results replicated known associations and additionally reveal novel findings, mainly with rare variants, validating the use of the HRC imputation panel. For example, we identified two new associations with fasting glucose at variants near to Y_RNA and WDR4 and four new associations with heart rate at SNPs within CSMD1 and ASPH, upstream of HTR1F and between PROKR2 and GPCPD1. All were driven by rare variants (minor allele frequencies in the range of 0.08–1%). Proof of principle for use of EHRs was verification of the highly significant association of urate levels with the well-established urate transporter SLC2A9. Conclusions GS:SFHS provides genetic data on over 20,000 participants alongside a range of phenotypes as well as linkage to National Health Service laboratory and clinical records. We have shown that the combination of deeper genotype imputation and extended phenotype availability make GS:SFHS an attractive resource to carry out association studies to gain insight into the genetic architecture of complex traits. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0414-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Reka Nagy
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Thibaud S Boutin
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Jonathan Marten
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Jennifer E Huffman
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Shona M Kerr
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - Louise Evenden
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK
| | - Jude Gibson
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK
| | - Carmen Amador
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - David M Howard
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Pau Navarro
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Andrew Morris
- Farr Institute of Health Informatics Research, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Lynne J Hocking
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - Sandosh Padmanabhan
- Division of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Blair H Smith
- Medical Research Institute, University of Dundee, Dundee, UK
| | - Peter Joshi
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - James F Wilson
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Nicholas D Hastie
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Alan F Wright
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Chris S Haley
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.
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29
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Marioni RE, Ritchie SJ, Joshi PK, Hagenaars SP, Okbay A, Fischer K, Adams MJ, Hill WD, Davies G, Nagy R, Amador C, Läll K, Metspalu A, Liewald DC, Campbell A, Wilson JF, Hayward C, Esko T, Porteous DJ, Gale CR, Deary IJ. Genetic variants linked to education predict longevity. Proc Natl Acad Sci U S A 2016; 113:13366-13371. [PMID: 27799538 PMCID: PMC5127357 DOI: 10.1073/pnas.1605334113] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.
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Affiliation(s)
- Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom;
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Stuart J Ritchie
- 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 K Joshi
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH16 4UX, United Kingdom
| | - Saskia P Hagenaars
- 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
- Division of Psychiatry, University of Edinburgh, Edinburgh EH8 9YL, United Kingdom
| | - Aysu Okbay
- Department of Applied Economics, Erasmus School of Economics, Erasmus University, 3062 PA Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, 3015 CE Rotterdam, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam 3062 PA, The Netherlands
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh EH8 9YL, United Kingdom
| | - W David Hill
- 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
| | - Gail Davies
- 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
| | - Reka Nagy
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Carmen Amador
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Kristi Läll
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute of Mathematical Statistics, University of Tartu, Tartu 50409, Estonia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - David C Liewald
- 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
| | - Archie Campbell
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - James F Wilson
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH16 4UX, United Kingdom
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute of Mathematical Statistics, University of Tartu, Tartu 50409, Estonia
- Broad Institute, Cambridge, MA 02142
- Department of Endocrinology, Children's Hospital Boston, Boston, MA 02115
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Catharine R Gale
- 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
- Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - 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
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30
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Shared Genetics and Couple-Associated Environment Are Major Contributors to the Risk of Both Clinical and Self-Declared Depression. EBioMedicine 2016; 14:161-167. [PMID: 27838479 PMCID: PMC5161419 DOI: 10.1016/j.ebiom.2016.11.003] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Revised: 11/01/2016] [Accepted: 11/02/2016] [Indexed: 01/12/2023] Open
Abstract
Background Both genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. Methods Using data from a large Scottish family-based cohort (GS:SFHS, N = 19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM). Findings Both MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r = 1.00, se = 0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r = 0.57, se = 0.08) and the couple-shared environmental effect (r = 0.53, se = 0.22). Interpretation Both genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression. Shared genetics and couple-associated environment are major contributors to the risk of depression. The common-variant-associated genetic correlation between MDD and SDD was very high (r = 1.00, se = 0.20). Lower correlations were detected for pedigree-associated genetics and couple-shared environmental components.
It is important to understand the differences between clinical depression (MDD) and self-declared depression (SDD) for which there has been recent genetics progress. We found major contributions from genetics and couple-shared environment to both traits. There is a very high correlation between the traits associated with common genetic variants but a lower correlation for other (probably rarer) genetic variation. MDD and SDD also likely differ in their shared environmental risk factors. Thus for studies of common genetic variation, SDD is a potential alternative to MDD. In clinical practice and research, the spousal depression status should also be considered a risk indicator.
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31
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Xia C, Amador C, Huffman J, Trochet H, Campbell A, Porteous D, Generation Scotland, Hastie ND, Hayward C, Vitart V, Navarro P, Haley CS. Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation. PLoS Genet 2016; 12:e1005804. [PMID: 26836320 PMCID: PMC4737500 DOI: 10.1371/journal.pgen.1005804] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Accepted: 12/21/2015] [Indexed: 01/12/2023] Open
Abstract
Genome-wide association studies have successfully identified thousands of loci for a range of human complex traits and diseases. The proportion of phenotypic variance explained by significant associations is, however, limited. Given the same dense SNP panels, mixed model analyses capture a greater proportion of phenotypic variance than single SNP analyses but the total is generally still less than the genetic variance estimated from pedigree studies. Combining information from pedigree relationships and SNPs, we examined 16 complex anthropometric and cardiometabolic traits in a Scottish family-based cohort comprising up to 20,000 individuals genotyped for ~520,000 common autosomal SNPs. The inclusion of related individuals provides the opportunity to also estimate the genetic variance associated with pedigree as well as the effects of common family environment. Trait variation was partitioned into SNP-associated and pedigree-associated genetic variation, shared nuclear family environment, shared couple (partner) environment and shared full-sibling environment. Results demonstrate that trait heritabilities vary widely but, on average across traits, SNP-associated and pedigree-associated genetic effects each explain around half the genetic variance. For most traits the recently-shared environment of couples is also significant, accounting for ~11% of the phenotypic variance on average. On the other hand, the environment shared largely in the past by members of a nuclear family or by full-siblings, has a more limited impact. Our findings point to appropriate models to use in future studies as pedigree-associated genetic effects and couple environmental effects have seldom been taken into account in genotype-based analyses. Appropriate description of the trait variation could help understand causes of intra-individual variation and in the detection of contributing loci and environmental factors. Unravelling overall trait architecture of complex traits and diseases is important for phenotype prediction and disease prevention and correct modelling of the trait will further aid discovery of causative loci. Here we take advantage of genome-wide data and a large family-based study to examine the role of common genetic variants, pedigree-associated genetic variants, shared family environment, shared couple environment and shared sibling environment on 16 anthropometric and cardiometabolic traits. By analysing up to ~20,000 Scottish individuals, we find that common genetic variants, pedigree-associated genetic variants and recently-shared environment of couples are the most important contributors to variation in these traits, while past family and sibling environment have a limited impact. Further studies on the pedigree-associated genetic variation and the shared couple environment effect are needed, as little research has been devoted to them so far.
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Affiliation(s)
- Charley Xia
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Carmen Amador
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennifer Huffman
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Holly Trochet
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Archie Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - David Porteous
- Generation Scotland, Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Generation Scotland
- A collaboration between the University Medical School and NHS in Aberdeen, Dundee, Edinburgh and Glasgow, Scotland, United Kingdom
| | - Nicholas D. Hastie
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
- The Roslin Institute and R(D)SVS, University of Edinburgh, Midlothian, United Kingdom
- * E-mail: ;
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32
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Tenesa A, Rawlik K, Navarro P, Canela-Xandri O. Genetic determination of height-mediated mate choice. Genome Biol 2016; 16:269. [PMID: 26781582 PMCID: PMC4717574 DOI: 10.1186/s13059-015-0833-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 11/12/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Numerous studies have reported positive correlations among couples for height. This suggests that humans find individuals of similar height attractive. However, the answer to whether the choice of a mate with a similar phenotype is genetically or environmentally determined has been elusive. RESULTS Here we provide an estimate of the genetic contribution to height choice in mates in 13,068 genotyped couples. Using a mixed linear model we show that 4.1% of the variation in the mate height choice is determined by a person's own genotype, as expected in a model where one's height determines the choice of mate height. Furthermore, the genotype of an individual predicts their partners' height in an independent dataset of 15,437 individuals with 13% accuracy, which is 64% of the theoretical maximum achievable with a heritability of 0.041. Theoretical predictions suggest that approximately 5% of the heritability of height is due to the positive covariance between allelic effects at different loci, which is caused by assortative mating. Hence, the coupling of alleles with similar effects could substantially contribute to the missing heritability of height. CONCLUSIONS These estimates provide new insight into the mechanisms that govern mate choice in humans and warrant the search for the genetic causes of choice of mate height. They have important methodological implications and contribute to the missing heritability debate.
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Affiliation(s)
- Albert Tenesa
- The Roslin Institute, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK. .,MRC HGU at the MRC IGMM, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, Scotland, UK. .,Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK.
| | - Konrad Rawlik
- The Roslin Institute, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK.,Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK
| | - Pau Navarro
- MRC HGU at the MRC IGMM, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, Scotland, UK
| | - Oriol Canela-Xandri
- The Roslin Institute, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK.,Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK
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