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1. Assessing polygenic risk score models for applications in populations with under-represented genomics data: an example of Vietnam

Author

Duy Pham, Buu Truong, Khai Tran, Guiyan Ni, Dat Nguyen, Trang T H Tran, Mai H Tran, Duong Nguyen Thuy, Nam S Vo, Quan Nguyen, Pham, Duy, Truong, Buu, Tran, Khai, Ni, Guiyan, Nguyen, Dat, Tran, Trang TH, Tran, Mai H, Nguyen Thuy, Duong, Vo, Nam S, and Nguyen, Quan

Subjects
Multifactorial Inheritance, across-population, Genomics, PRS, trans-ethnic, Polymorphism, Single Nucleotide, Vietnam, Risk Factors, Humans, GWAS, Genetic Predisposition to Disease, Molecular Biology, Genome-Wide Association Study, Information Systems
Abstract

Most polygenic risk score (PRS)models have been based on data from populations of European origins (accounting for the majority of the large genomics datasets, e.g. >78% in the UK Biobank and >85% in the GTEx project). Although several large-scale Asian biobanks were initiated (e.g. Japanese, Korean, Han Chinese biobanks), most other Asian countries have little or near-zero genomics data. To implement PRS models for under-represented populations, we explored transfer learning approaches, assuming that information from existing large datasets can compensate for the small sample size that can be feasibly obtained in developing countries, like Vietnam. Here, we benchmark 13 common PRS methods in meta-population strategy (combining individual genotype data from multiple populations) and multi-population strategy (combining summary statistics from multiple populations). Our results highlight the complementarity of different populations and the choice of methods should depend on the target population. Based on these results, we discussed a set of guidelines to help users select the best method for their datasets. We developed a robust and comprehensive software to allow for benchmarking comparisons between methods and proposed a computational framework for improving PRS performance in a dataset with a small sample size. This work is expected to inform the development of genomics applications in under-represented populations. PRSUP framework is available at: https://github.com/BiomedicalMachineLearning/VGP

Published
2022
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2. The genetic relationship between female reproductive traits and six psychiatric disorders

Author

Xuan Zhou, Natalie T. Mills, Jacob Gratten, Guiyan Ni, Azmeraw T. Amare, Sang Hong Lee, Ni, Guiyan, Amare, Azmeraw T, Zhou, Xuan, Mills, Natalie, Gratten, Jacob, and Lee, S Hong

Subjects
Male, 0301 basic medicine, Multifactorial Inheritance, lcsh:Medicine, 0302 clinical medicine, Risk Factors, Databases, Genetic, Young adult, lcsh:Science, Reproductive health, 0303 health sciences, Multidisciplinary, Mental Disorders, Reproduction, bipolar affective-disorder, health, Genomics, Middle Aged, 3. Good health, Schizophrenia, Major depressive disorder, Female, Adult, medicine.medical_specialty, Adolescent, Offspring, Biology, Genetic correlation, Article, Young Adult, 03 medical and health sciences, Quantitative Trait, Heritable, medicine, Humans, Genetic Predisposition to Disease, Psychiatry, Genetic Association Studies, 030304 developmental biology, Genetic association study, Aged, Reproductive success, business.industry, lcsh:R, medicine.disease, Genetic architecture, schizophrenia, Sexual intercourse, 030104 developmental biology, maternal age, mendelian randomization, lcsh:Q, business, 030217 neurology & neurosurgery
Abstract

Female reproductive behaviors have an important implication in evolutionary fitness and health of offspring. Previous studies have shown that age at first birth of women (AFB) is genetically associated with schizophrenia (SCZ). However, for most other psychiatric disorders and reproductive traits, the latent shared genetic architecture is largely unknown. Here we used the second wave of UK Biobank data (N=220,685) to evaluate the association between five female reproductive traits and polygenetic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N=429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with AFB (genetic correlation of −0.68 ± 0.03 with p-value = 1.86E-89), age at first sexual intercourse (AFS) (−0.56 ± 0.03 with p-value = 3.42E-60), number of live births (NLB) (0.36 ± 0.04 with p-value = 4.01E-17) and age at menopause (−0.27 ± 0.04 with p-value = 5.71E-13). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (genetic correlation of 0.35 ± 0.06), ED and AFS (0.19 0.06), Major depressive disorder (MDD) and AFB (−0.27 ± 0.07), MDD and AFS (− 0.27 ± 0.03) and SCZ and AFS (−0.10 ± 0.03). Our findings reveal the shared genetic architecture between the five reproductive traits in women and six psychiatric disorders, which have a potential implication that helps to improve reproductive health in women, hence better child outcomes. Our findings may also explain, at least in part, an evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.

Published
2019
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3. A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

Author

Guiyan Ni, Jian Zeng, Joana A. Revez, Ying Wang, Zhili Zheng, Tian Ge, Restuadi Restuadi, Jacqueline Kiewa, Dale R. Nyholt, Jonathan R.I. Coleman, Jordan W. Smoller, Jian Yang, Peter M. Visscher, Naomi R. Wray, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberley D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Psychosis Endophenotypes International Consortium, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Kari Stefansson, Wellcome Trust Case-Control Consortium, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, Maciej Trzaskowski, Enda M. Byrne, Abdel Abdellaoui, Mark J. Adams, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Andreas J. Forstner, Héléna A. Gaspar, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G. Nivard, Paul F. O’Reilly, Hogni Oskarsson, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, John P. Rice, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Fabian Streit, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M. van Hemert, Alexander Viktorin, Yunpeng Wang, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Futao Zhang, Volker Arolt, Bernhard T. Baune, Klaus Berger, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Katharina Domschke, Hans J. Grabe, Steven P. Hamilton, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Nicholas G. Martin, Preben Bo Mortensen, Merete Nordentoft, Sara A. Paciga, Nancy L. Pedersen, Adult Psychiatry, APH - Mental Health, ANS - Complex Trait Genetics, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, Ni, Guiyan, Zeng, Jian, Revez, Joana A., Wang, Ying, Zhili, Zheng, Ge, Tian, Restuadi, Restuadi, Kiewa, Jacqueline, Nyholt, Dale R, Coleman, Jonathan RI, Smoller, Jordan W, Lee, S Hong, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Econometrics, Psychiatry, Department of Technology and Operations Management, Child and Adolescent Psychiatry / Psychology, Epidemiology, Erasmus MC other, Urology, Internal Medicine, Medical Informatics, Immunology, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
0301 basic medicine, Multifactorial Inheritance, medicine.medical_specialty, LDpred2, BF, Genomics, Disease, Major depressive disorder, risk prediction, 03 medical and health sciences, 0302 clinical medicine, MegaPRS, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Genetic risk, Psychiatry, Biological Psychiatry, Genetic association, Depressive Disorder, Major, business.industry, Mental Disorders, medicine.disease, Genetic architecture, Polygenic scores, Risk prediction, polygenic scores, PRS-CS, psychiatric disorders, 030104 developmental biology, SBayesR, Schizophrenia, Cohort, Lassosum, RC0321, business, Psychiatric disorders, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

BACKGROUND: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.METHODS: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared.RESULTS: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively.CONCLUSIONS: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.

Published
2021
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4. Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations

Author

Loic Yengo, Ying Wang, Jing Guo, Guiyan Ni, Peter M. Visscher, and Jian Yang

Subjects
Male, 0301 basic medicine, Multifactorial Inheritance, Linkage disequilibrium, Statistical methods, General Physics and Astronomy, Genome-wide association study, 030105 genetics & heredity, Genome-wide association studies, Linkage Disequilibrium, Body Mass Index, Gene Frequency, lcsh:Science, 10. No inequality, 2. Zero hunger, 0303 health sciences, education.field_of_study, Multidisciplinary, 030305 genetics & heredity, Middle Aged, Prognosis, Europe, Cholesterol, Hypertension, Female, lipids (amino acids, peptides, and proteins), Adult, Risk, musculoskeletal diseases, Asia, Science, Population, Single-nucleotide polymorphism, Biology, Quantitative trait locus, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Quantitative Trait, Heritable, Genetic variation, SNP, Humans, Computer Simulation, Allele, education, Allele frequency, Alleles, 030304 developmental biology, Aged, Genetic association, Models, Genetic, General Chemistry, Heritability, Asthma, Minor allele frequency, 030104 developmental biology, Diabetes Mellitus, Type 2, Evolutionary biology, Africa, lcsh:Q, Genome-Wide Association Study
Abstract

Polygenic scores (PGS) have been widely used to predict disease risk using variants identified from genome-wide association studies (GWAS). To date, most GWAS have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European ancestry populations. Here, we derive a theoretical model of the relative accuracy (RA) of PGS across ancestries. We show through extensive simulations that the RA of PGS based on genome-wide significant SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of causal SNP effects and heritability. We find that LD and MAF differences between ancestries can explain between 70 and 80% of the loss of RA of European-based PGS in African ancestry for traits like body mass index and type 2 diabetes. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWAS are mostly shared across continents., Polygenic scores (PGS) are often based on GWAS data from individuals of European ancestry, thus limiting their use in populations of non-European ancestry. Here, the authors predict the relative accuracy of PGS across ancestries and suggest that causal variants are mostly shared across continents.

Published
2020
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5. Whole-genome approach discovers novel genetic and nongenetic variance components modulated by lifestyle for cardiovascular health

Author

Guiyan Ni, Xuan Zhou, Kristin Carson-Chahhoud, John J. McGrath, S. Hong Lee, Elina Hyppönen, Julius H. J. van der Werf, Zhou, Xuan, van der Werf, J, Carson-Chahhoud, K, Ni, G, McGrath, John, Hyppönen, Elina, and Lee, S Hong

Subjects
Adult, Male, lifestyle, Heredity, residual–lifestyle interaction, Cardiovascular health, cardiovascular traits, 030204 cardiovascular system & hematology, Bioinformatics, Risk Assessment, Genome, Genetic, Association Studies, 03 medical and health sciences, 0302 clinical medicine, Genetics, Humans, Medicine, Genetic Predisposition to Disease, Healthy Lifestyle, whole‐genome approach, Aged, Original Research, 030304 developmental biology, 0303 health sciences, business.industry, genotype–lifestyle interaction, Middle Aged, Protective Factors, United Kingdom, United States, Cardiovascular Diseases, Heart Disease Risk Factors, Variance components, Female, Gene-Environment Interaction, Disease prevention, Cardiology and Cardiovascular Medicine, business, Risk Reduction Behavior, Basic Science Research, Genome-Wide Association Study
Abstract

Background Both genetic and nongenetic factors can predispose individuals to cardiovascular risk. Finding ways to alter these predispositions is important for cardiovascular disease prevention. Methods and Results We used a novel whole‐genome approach to estimate the genetic and nongenetic effects on—and hence their predispositions to—cardiovascular risk and determined whether they vary with respect to lifestyle factors such as physical activity, smoking, alcohol consumption, and dietary intake. We performed analyses on the ARIC (Atherosclerosis Risk in Communities) Study (N=6896–7180) and validated findings using the UKBB (UK Biobank, N=14 076–34 538). Lifestyle modulation was evident for many cardiovascular traits such as body mass index and resting heart rate. For example, alcohol consumption modulated both genetic and nongenetic effects on body mass index, whereas smoking modulated nongenetic effects on heart rate, pulse pressure, and white blood cell count. We also stratified individuals according to estimated genetic and nongenetic effects that are modulated by lifestyle factors and showed distinct phenotype–lifestyle relationships across the stratified groups. Finally, we showed that neglecting lifestyle modulations of cardiovascular traits would on average reduce single nucleotide polymorphism heritability estimates of these traits by a small yet significant amount, primarily owing to the overestimation of residual variance. Conclusions Lifestyle changes are relevant to cardiovascular disease prevention. Individual differences in the genetic and nongenetic effects that are modulated by lifestyle factors, as shown by the stratified group analyses, implies a need for personalized lifestyle interventions. In addition, single nucleotide polymorphism–based heritability of cardiovascular traits without accounting for lifestyle modulations could be underestimated.

Published
2020

6. Genotype-covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model

Author

Sang Hong Lee, Guiyan Ni, Xuan Zhou, Julius Hj van der Werf, Elina Hyppönen, Naomi R. Wray, Ni, Guiyan, van der Werf, Julius, Zhou, Xuan, Hyppönen, Elina, Wray, Naomi R, and Lee, S Hong

Subjects
0301 basic medicine, Multivariate statistics, Multivariate analysis, Genotype, Restricted maximum likelihood, genotype, Science, General Physics and Astronomy, Context (language use), 02 engineering and technology, Residual, Risk Assessment, Article, smoking, General Biochemistry, Genetics and Molecular Biology, Body Mass Index, Cigarette Smoking, Correlation, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Covariate, Statistics, Genetics, Humans, lcsh:Science, Additive model, 030304 developmental biology, Mathematics, 0303 health sciences, Multidisciplinary, Models, Genetic, Contrast (statistics), Genomics, General Chemistry, 021001 nanoscience & nanotechnology, Genetic architecture, Regression, Computational biology and bioinformatics, 030104 developmental biology, Multivariate Analysis, lcsh:Q, 0210 nano-technology, 030217 neurology & neurosurgery, genetic susceptibility
Abstract

The genomics era has brought useful tools to dissect the genetic architecture of complex traits. Here we propose a multivariate reaction norm model (MRNM) to tackle genotype–covariate (G–C) correlation and interaction problems. We apply MRNM to the UK Biobank data in analysis of body mass index using smoking quantity as a covariate, finding a highly significant G–C correlation, but only weak evidence for G–C interaction. In contrast, G–C interaction estimates are inflated in existing methods. It is also notable that there is significant heterogeneity in the estimated residual variances (i.e., variances not attributable to factors in the model) across different covariate levels, i.e., residual–covariate (R–C) interaction. We also show that the residual variances estimated by standard additive models can be inflated in the presence of G–C and/or R–C interactions. We conclude that it is essential to correctly account for both interaction and correlation in complex trait analyses., Complex traits are often influenced by genetic and non-genetic factors (such as environmental exposures), which are themselves interconnected. Here, the authors develop a method for disentangling genotype–covariate correlation and interaction, and investigate their effects on estimating statistical genetic parameters.

Published
2018
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7. Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

Author

Guiyan Ni, Gerhard Moser, Naomi R. Wray, S. Hong Lee, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Juliá, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsda, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olinc, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papio, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinenl, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stah, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Kari Stefansson, Peter M. Visscher, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarrol, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietsche, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, APH - Mental Health, ANS - Complex Trait Genetics, Adult Psychiatry, Ni, Guiyan, Moser, Gerhard, Wray, Naomi R, Lee, S Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Clinicum, Department of Psychiatry, and HUS Psychiatry

Subjects
0301 basic medicine, Linkage disequilibrium, Schizophrenia/genetics, INFORMATION, Restricted maximum likelihood, Inheritance Patterns, linkage disequilibrium score regression, Bioinformatics, Medical and Health Sciences, 3124 Neurology and psychiatry, Linkage Disequilibrium, biasedness, 0302 clinical medicine, Statistics, Databases, Genetic, WIDE ASSOCIATION, Genetics(clinical), PARTITIONING HERITABILITY, Genetics (clinical), Genetics & Heredity, education.field_of_study, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Likelihood Functions, Genome, Body Height/genetics, accuracy, Regression analysis, Single Nucleotide, Biological Sciences, Polymorphism, Single Nucleotide/genetics, genetic correlation, Regression, STATISTICS, genomic restricted maximum likelihood, Mental Health, Phenotype, Regression Analysis, COMPLEX HUMAN TRAITS, Single Nucleotide/genetics, Human, Adult, SUSCEPTIBILITY LOCI, Genotype, SNP heritability, body mass index, genome-wide SNPs, height, schizophrenia, Population, Haplotypes/genetics, Biology, Genetic correlation, Polymorphism, Single Nucleotide, 03 medical and health sciences, Databases, Genetic, ddc:570, Report, Genetics, Humans, Linkage Disequilibrium/genetics, Computer Simulation, Polymorphism, education, linkage disequilibrium score regression (LDSC), Genome, Human, Human Genome, genetic architecture, Genetic architecture, Body Height, Brain Disorders, Inheritance Patterns/genetics, BODY-MASS INDEX, 030104 developmental biology, Haplotypes, Sample size determination, Schizophrenia, 3111 Biomedicine, HUMAN HEIGHT, 030217 neurology & neurosurgery
Abstract

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen. Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

Published
2017
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8. Age at first birth in women is genetically associated with increased risk of schizophrenia

Author

Fritz Zimprich, Manuel Mattheisen, Edward M. Scolnick, Ayman H. Fanous, Henrik B. Rasmussen, Steven A. McCarroll, Ingrid Agartz, Carmel M. Loughland, Aiden Corvin, Ann Olincy, Anders D. Børglum, F. Anthony O'Neill, T. Scott Stroup, Elizabeth Bevilacqua, Sandra Meier, Ulrich Schall, Jouko Lönnqvist, Jianxin Shi, C. Robert Cloninger, Judit Bene, Veikko Salomaa, George N. Papadimitriou, Milica Pejovic-Milovancevic, Béla Melegh, Kari Stefansson, Brendan Bulik-Sullivan, Janis Klovins, Enrico Domenici, Sibylle G. Schwab, Dai Wang, Assen Jablensky, Mari Nelis, Sang Yun Oh, Peter Holmans, Aaron R. Wolen, Hualin Simon Xi, Eric Strengman, Bryan J. Mowry, Michael Gill, Kung Yee Liang, William Byerley, Rolf Adolfsson, Hugh Gurling, Joseph I. Friedman, Andrew Pocklington, Brien P. Riley, Engilbert Sigurdsson, Benjamin M. Neale, Miaoxin Li, Michael Davidson, Bernard Lerer, Michele T. Pato, Xuebin Zheng, Patrick F. Sullivan, Frans Henskens, Madeline Alexander, Andrew M. McIntosh, Inez Myin-Germeys, Draga Toncheva, Liene Nikitina-Zake, Kenneth S. Kendler, Carin J. Meijer, Robin M. Murray, Richard E. Straub, Ann E. Pulver, Menachem Fromer, Derek W. Morris, Douglas M. Ruderfer, Mythily Subramaniam, Paul Cormican, Lyudmila Georgieva, Giulio Genovese, Brion S. Maher, Stanley V. Catts, David St Clair, Robert W. McCarley, David Cohen, Nancy G. Buccola, Dan Rujescu, Carlos N. Pato, Kristin K. Nicodemus, Josef Frank, Claudine Laurent, Dominique Campion, Guiyan Ni, James L. Kennedy, Sena Karachanak-Yankova, Nicholas John Craddock, Peter M. Visscher, Valentina Escott-Price, Jeffrey A. Lieberman, Deborah A. Nertney, Bertram Müller-Myhsok, Marcella Rietschel, Dimitris Dikeos, Stephanie Godard, Stephanie Williams, Andres Metspalu, John L. Waddington, Sophie E. Legge, Roel A. Ophoff, Jonathan Pimm, Richard Bruggeman, Tim B. Bigdeli, Gerald Nestadt, Mark Weiser, Kieran C. Murphy, Eric F.C. Cheung, Kang Sim, Jordan W. Smoller, David J. Kavanagh, Inge Joa, Jens R. Wendland, Thomas G. Schulze, Richard A. Belliveau, Sarah E. Bergen, Ditte Demontis, David Curtis, Todd Lencz, Danielle Posthuma, René S. Kahn, Lili Milani, Randy L. Buckner, Jianjun Liu, Petr Slominsky, Wiepke Cahn, Hana Kuzelova-Ptackova, Sergi Papiol, Tune H. Pers, Stephan Ripke, Rita M. Cantor, Ariel Darvasi, Christina M. Hultman, Larry J. Seidman, Eli A. Stahl, David A. Collier, Michael Conlon O'Donovan, Svetlana A. Limborska, James T.R. Walters, Farooq Amin, Noa Carrera, Ronald Y.L. Chen, Pablo V. Gejman, Joel N. Hirschhorn, Zita Ausrele Kucinskiene, Michael John Owen, Ina Giegling, Stephanie H. Witt, Timothy G. Dinan, Margot Albus, Wei Cheng, Marian L. Hamshere, Markus M. Nöthen, Thomas Werge, Guiqing Cai, Raquelle I. Mesholam-Gately, Annette M. Hartmann, Ingrid Melle, Ole A. Andreassen, Preben Bo Mortensen, Hannelore Ehrenreich, Tiina Paunio, James A. Knowles, Pak C. Sham, Marion Friedl, Teimuraz Silagadze, Dermot Walsh, Emily H. M. Wong, Igor Nenadic, Matthew C. Keller, John Powell, Naomi R. Wray, Patricia T. Michie, Bradley T. Webb, Lude Franke, Mark Hansen, Masashi Ikeda, Sven Cichon, Elvira Bramon, Frank Dudbridge, Erik G. Jönsson, Annelie Nordin, Wolfgang Maier, Peter Eichhammer, Christian R. Schubert, J. Mallet, Jacob Gratten, Andrey Khrunin, Jacqueline I. Goldstein, Panos Roussos, Pamela Sklar, Diana O. Perkins, Srdjan Djurovic, Phil Lee, Elodie Drapeau, Douglas F. Levinson, Nadine Cohen, Luba Kalaydjieva, Brandon Wormley, Tao Li, Tõnu Esko, Alexander Richards, Srihari Gopal, Jubao Duan, Anil K. Malhotra, Elisabeth Stögmann, Gary Donohoe, Kimberly Chambert, Sara Marsal, Hreinn Stefansson, Jo Knight, Ole Mors, Per Hoffmann, Dieter B. Wildenauer, James J. Crowley, Srinivas Thirumalai, Vahram Haroutunian, A. Hofman, Hailiang Huang, Thomas Hansen, Daniel R. Weinberger, Andrew McQuillin, Vaughan J. Carr, Vaidutis Kučinskas, Jimmy Lee Chee Keong, Digby Quested, Aarno Palotie, Robert Freedman, Hon-Cheong So, Jennifer L. Moran, Donald W. Black, Mark Reimers, Abraham Reichenberg, Jurgen Del Favero, Paola Giusti-Rodríguez, Tracey L. Petryshen, Olli Pietiläinen, Franziska Degenhardt, Laurent Essioux, Esben Agerbo, Qiang Wang, Jana Strohmaier, Siow Ann Chong, Johan G. Eriksson, Martin Begemann, Younes Mokrab, Colm McDonald, Silviu Alin Bacanu, Martilias S. Farrell, Christos Pantelis, Kai How Farh, Line Olsen, Naser Durmishi, Antonio Julià, Stefan Herms, Qingqin S. Li, Bettina Konte, George Kirov, Rodney J. Scott, Nelson B. Freimer, Mads V. Hollegaard, Shaun Purcell, Erik Söderman, Dragan M. Svrakic, Patrik K. E. Magnusson, Douglas Blackwood, Jin P. Szatkiewicz, Sang Hong Lee, Yunjung Kim, Colm O'Dushlaine, Morten Mattingsdal, Jim van Os, Sarah Tosato, Milan Macek, Joshua L. Roffman, Jan Lubinski, Eadbhard O'Callaghan, Juha Karjalainen, Vera Golimbet, Anna K. Kähler, Clement C. Zai, Nigel Williams, Joseph D. Buxbaum, Laura Nisenbaum, Eric Y.H. Chen, David M. Hougaard, Jaana Suvisaari, Chris C. A. Spencer, Alan R. Sanders, Alkes L. Price, Vihra Milanova, Juha Veijola, Christian Hammer, Raymond C.K. Chan, Stacy Steinberg, Nakao Iwata, Jeremy M. Silverman, Mark J. Daly, Elena Parkhomenko, Kenneth L. Davis, Lieuwe de Haan, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Reproduction & Development (AR&D), Kučinskas, Vaidutis, Kučinskienė, Zita Aušrelė, Ni, Guiyan, Gratten, Jacob, Wray, Naomi R, Lee, Sang Hong, Germeys, Inez, Complex Trait Genetics, Háskóli Íslands, University of Iceland, Child and Adolescent Psychiatry / Psychology, Research Programs Unit, Diabetes and Obesity Research Program, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, University Management, Department of Psychiatry, Center for Population, Health and Society, Department of Public Health, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, and Genomics of Neurological and Neuropsychiatric Disorders

Subjects
0301 basic medicine, Multifactorial Inheritance, PATERNAL-AGE, 3124 Neurology and psychiatry, COMMON SNPS, fluids and secretions, 0302 clinical medicine, CHILD, Risk Factors, Pregnancy, 2.1 Biological and endogenous factors, Medicine, Aetiology, Pediatric, PROPORTION, Schizophrenia Working Group of the Psychiatric Genomics Consortium, 0303 health sciences, Multidisciplinary, PSYCHIATRIC-DISORDERS, BIPOLAR DISORDER, Biobank, 3. Good health, AFB, Mental Health, Schizophrenia, Female, Erfðarannsóknir, Psychosocial, TRAITS, schizophrenia, age at birth, AFB, Maternal Age, Adult, age at first birth in women, genetic association, Offspring, Science, Genetic correlation, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Geðklofi, Genetics, age at birth, Humans, Genetic Predisposition to Disease, Bipolar disorder, General, Biology, Genetic association study, 030304 developmental biology, Genetic association, business.industry, Genetic heterogeneity, Prevention, average aged parents, Parturition, SCORE REGRESSION, bacterial infections and mycoses, medicine.disease, Mental health, Brain Disorders, respiratory tract diseases, schizophrenia, Good Health and Well Being, 030104 developmental biology, younger and older parents, DE-NOVO MUTATIONS, ddc:000, Human medicine, business, 030217 neurology & neurosurgery, Demography
Abstract

Publisher's version (útgefin grein), Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is −0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health., This research is supported by the Australian National Health and Medical Research Council (1080157, 1087889, 1103418, 1127440), and the Australian Research Council (DP160102126, FT160100229). This research has been conducted using the UK Biobank Resource. UK Biobank (http://www.ukbiobank.ac.uk) Research Ethics Committee (REC) approval number is 11/NW/0382. Our reference number approved by UK Biobank is 14575.

Published
2017
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