1
|
Mathieson I, Day FR, Barban N, Tropf FC, Brazel DM, Vaez A, van Zuydam N, Bitarello BD, Gardner EJ, Akimova ET, Azad A, Bergmann S, Bielak LF, Boomsma DI, Bosak K, Brumat M, Buring JE, Cesarini D, Chasman DI, Chavarro JE, Cocca M, Concas MP, Davey Smith G, Davies G, Deary IJ, Esko T, Faul JD, Franco O, Ganna A, Gaskins AJ, Gelemanovic A, de Geus EJC, Gieger C, Girotto G, Gopinath B, Grabe HJ, Gunderson EP, Hayward C, He C, van Heemst D, Hill WD, Hoffmann ER, Homuth G, Hottenga JJ, Huang H, Hyppӧnen E, Ikram MA, Jansen R, Johannesson M, Kamali Z, Kardia SLR, Kavousi M, Kifley A, Kiiskinen T, Kraft P, Kühnel B, Langenberg C, Liew G, Lind PA, Luan J, Mägi R, Magnusson PKE, Mahajan A, Martin NG, Mbarek H, McCarthy MI, McMahon G, Medland SE, Meitinger T, Metspalu A, Mihailov E, Milani L, Missmer SA, Mitchell P, Møllegaard S, Mook-Kanamori DO, Morgan A, van der Most PJ, de Mutsert R, Nauck M, Nolte IM, Noordam R, Penninx BWJH, Peters A, Peyser PA, Polašek O, Power C, Pribisalic A, Redmond P, Rich-Edwards JW, Ridker PM, Rietveld CA, Ring SM, Rose LM, Rueedi R, Shukla V, Smith JA, Stankovic S, Stefánsson K, Stöckl D, Strauch K, Swertz MA, Teumer A, Thorleifsson G, Thorsteinsdottir U, Thurik AR, Timpson NJ, Turman C, Uitterlinden AG, Waldenberger M, Wareham NJ, Weir DR, Willemsen G, Zhao JH, Zhao W, Zhao Y, Snieder H, den Hoed M, Ong KK, Mills MC, Perry JRB. Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus. Nat Hum Behav 2023; 7:790-801. [PMID: 36864135 DOI: 10.1038/s41562-023-01528-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 01/12/2023] [Indexed: 03/04/2023]
Abstract
Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success.
Collapse
Affiliation(s)
- Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Nicola Barban
- Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Felix C Tropf
- Nuffield College, University of Oxford, Oxford, UK
- École Nationale de la Statistique et de L'administration Économique (ENSAE), Paris, France
- Center for Research in Economics and Statistics (CREST), Paris, France
| | - David M Brazel
- Nuffield College, University of Oxford, Oxford, UK
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Natalie van Zuydam
- Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Bárbara D Bitarello
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Eugene J Gardner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Evelina T Akimova
- Nuffield College, University of Oxford, Oxford, UK
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK
| | - Ajuna Azad
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Lawrence F Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands
| | | | - Marco Brumat
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Julie E Buring
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - David Cesarini
- Department of Economics, New York University, New York, NY, USA
- Research Institute for Industrial Economics, Stockholm, Sweden
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Daniel I Chasman
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jorge E Chavarro
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Massimiliano Cocca
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | | | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Oscar Franco
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Andrea Ganna
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Audrey J Gaskins
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | | | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Giorgia Girotto
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Bamini Gopinath
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Erica P Gunderson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chunyan He
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Department of Internal Medicine, Division of Medical Oncology, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - W David Hill
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Eva R Hoffmann
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Hongyang Huang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Elina Hyppӧnen
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Annette Kifley
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Gerald Liew
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Qatar Genome Programme, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - George McMahon
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | | | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Stacey A Missmer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Adolescent and Young Adult Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Obstetrics, Gynecology, and Reproductive Biology, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Paul Mitchell
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Stine Møllegaard
- Department of Sociology, University of Copenhagen, Copenhagen, Denmark
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Anna Morgan
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, the Netherlands
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Chris Power
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | | | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janet W Rich-Edwards
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Paul M Ridker
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Cornelius A Rietveld
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Applied Economics, Erasmus School of Economics, Rotterdam, the Netherlands
| | - Susan M Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | | | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Vallari Shukla
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Stasa Stankovic
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Doris Stöckl
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany
| | - Morris A Swertz
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | | | | | - A Roy Thurik
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Applied Economics, Erasmus School of Economics, Rotterdam, the Netherlands
- Montpellier Business School, Montpellier, France
| | | | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - André G Uitterlinden
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jing Hau Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Yajie Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marcel den Hoed
- Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Melinda C Mills
- Nuffield College, University of Oxford, Oxford, UK.
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK.
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Department of Economics, Econometrics and Finance, University of Groningen, Groningen, the Netherlands.
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
| |
Collapse
|
2
|
Mills MC, Tropf FC, Brazel DM, van Zuydam N, Vaez A, Pers TH, Snieder H, Perry JRB, Ong KK, den Hoed M, Barban N, Day FR. Identification of 371 genetic variants for age at first sex and birth linked to externalising behaviour. Nat Hum Behav 2021; 5:1717-1730. [PMID: 34211149 PMCID: PMC7612120 DOI: 10.1038/s41562-021-01135-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 05/14/2021] [Indexed: 02/06/2023]
Abstract
Age at first sexual intercourse and age at first birth have implications for health and evolutionary fitness. In this genome-wide association study (age at first sexual intercourse, N = 387,338; age at first birth, N = 542,901), we identify 371 single-nucleotide polymorphisms, 11 sex-specific, with a 5-6% polygenic score prediction. Heritability of age at first birth shifted from 9% [CI = 4-14%] for women born in 1940 to 22% [CI = 19-25%] for those born in 1965. Signals are driven by the genetics of reproductive biology and externalising behaviour, with key genes related to follicle stimulating hormone (FSHB), implantation (ESR1), infertility and spermatid differentiation. Our findings suggest that polycystic ovarian syndrome may lead to later age at first birth, linking with infertility. Late age at first birth is associated with parental longevity and reduced incidence of type 2 diabetes and cardiovascular disease. Higher childhood socioeconomic circumstances and those in the highest polygenic score decile (90%+) experience markedly later reproductive onset. Results are relevant for improving teenage and late-life health, understanding longevity and guiding experimentation into mechanisms of infertility.
Collapse
Affiliation(s)
- Melinda C Mills
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, United Kingdom.
- Nuffield College, University of Oxford, Oxford, United Kingdom.
| | - Felix C Tropf
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, United Kingdom
- Nuffield College, University of Oxford, Oxford, United Kingdom
- École Nationale de la Statistique et de L'administration Économique (ENSAE), Paris, France
- Center for Research in Economics and Statistics (CREST), Paris, France
| | - David M Brazel
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, United Kingdom
- Nuffield College, University of Oxford, Oxford, United Kingdom
| | - Natalie van Zuydam
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Tune H Pers
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Nicola Barban
- Department of Statistical Sciences, University of Bologna, Bologna, Italy
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom.
| |
Collapse
|
3
|
Mills MC, Tropf FC, Brazel DM, van Zuydam N, Vaez A, Pers TH, Snieder H, Perry JRB, Ong KK, den Hoed M, Barban N, Day FR. Publisher Correction: Identification of 371 genetic variants for age at first sex and birth linked to externalising behavior. Nat Hum Behav 2021; 5:1111. [PMID: 34321615 DOI: 10.1038/s41562-021-01179-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Melinda C Mills
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, United Kingdom. .,Nuffield College, University of Oxford, Oxford, United Kingdom.
| | - Felix C Tropf
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, United Kingdom.,Nuffield College, University of Oxford, Oxford, United Kingdom.,École Nationale de la Statistique et de L'administration Économique (ENSAE), Paris, France.,Center for Research in Economics and Statistics (CREST), Paris, France
| | - David M Brazel
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, United Kingdom.,Nuffield College, University of Oxford, Oxford, United Kingdom
| | - Natalie van Zuydam
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | | | | | | | - Tune H Pers
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Nicola Barban
- Department of Statistical Sciences, University of Bologna, Bologna, Italy
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom.
| |
Collapse
|
4
|
Verweij RM, Mills MC, Stulp G, Nolte IM, Barban N, Tropf FC, Carrell DT, Aston KI, Zondervan KT, Rahmioglu N, Dalgaard M, Skaarup C, Hayes MG, Dunaif A, Guo G, Snieder H. Using Polygenic Scores in Social Science Research: Unraveling Childlessness. Front Sociol 2019; 4:74. [PMID: 33869396 PMCID: PMC8022451 DOI: 10.3389/fsoc.2019.00074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 11/07/2019] [Indexed: 06/12/2023]
Abstract
Biological, genetic, and socio-demographic factors are all important in explaining reproductive behavior, yet these factors are typically studied in isolation. In this study, we explore an innovative sociogenomic approach, which entails including key socio-demographic (marriage, education, occupation, religion, cohort) and genetic factors related to both behavioral [age at first birth (AFB), number of children ever born (NEB)] and biological fecundity-related outcomes (endometriosis, age at menopause and menarche, polycystic ovary syndrome, azoospermia, testicular dysgenesis syndrome) to explain childlessness. We examine the association of all sets of factors with childlessness as well as the interplay between them. We derive polygenic scores (PGS) from recent genome-wide association studies (GWAS) and apply these in the Health and Retirement Study (N = 10,686) and Wisconsin Longitudinal Study (N = 8,284). Both socio-demographic and genetic factors were associated with childlessness. Whilst socio-demographic factors explain 19-46% in childlessness, the current PGS explains <1% of the variance, and only PGSs from large GWASs are related to childlessness. Our findings also indicate that genetic and socio-demographic factors are not independent, with PGSs for AFB and NEB related to education and age at marriage. The explained variance by polygenic scores on childlessness is limited since it is largely a behavioral trait, with genetic explanations expected to increase somewhat in the future with better-powered GWASs. As genotyping of individuals in social science surveys becomes more prevalent, the method described in this study can be applied to other outcomes.
Collapse
Affiliation(s)
- Renske M. Verweij
- Department of Sociology and ICS, University of Groningen, Groningen, Netherlands
- Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - Melinda C. Mills
- Department of Sociology and Nuffield College, University of Oxford, Oxford, United Kingdom
| | - Gert Stulp
- Department of Sociology and ICS, University of Groningen, Groningen, Netherlands
| | - Ilja M. Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Nicola Barban
- Institute of Social and Economic Research, University of Essex, Essex, United Kingdom
| | - Felix C. Tropf
- École Nationale de la Statistique et de L'administration Économique (ENSAE), Paris, France
- Center for Research in Economics and Statistics (CREST), Paris, France
| | - Douglas T. Carrell
- Department of Surgery, University of Utah, Salt Lake City, UT, United States
| | - Kenneth I. Aston
- Department of Surgery, University of Utah, Salt Lake City, UT, United States
| | - Krina T. Zondervan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Nilufer Rahmioglu
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Marlene Dalgaard
- Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark
- Department of Growth and Reproduction, Rigshospitalet, Copenhagen, Denmark
| | - Carina Skaarup
- Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Department of Anthropology, Northwestern University, Evanston, IL, United States
| | - Andrea Dunaif
- Department of Endocrinology, Diabetes and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Guang Guo
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| |
Collapse
|
5
|
Ding X, Barban N, Tropf FC, Mills MC. The relationship between cognitive decline and a genetic predictor of educational attainment. Soc Sci Med 2019; 239:112549. [PMID: 31546143 PMCID: PMC6873779 DOI: 10.1016/j.socscimed.2019.112549] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 09/10/2019] [Accepted: 09/12/2019] [Indexed: 12/24/2022]
Abstract
Genetic and environmental factors both make substantial contributions to the heterogeneity in individuals’ levels of cognitive ability. Many studies have examined the relationship between educational attainment and cognitive performance and its rate of change. Yet there remains a gap in knowledge regarding whether the effect of genetic predictors on individual differences in cognition becomes more or less prominent over the life course. In this analysis of over 5000 older adults from the Health and Retirement Study (HRS) in the U.S., we measured the change in performance on global cognition, episodic memory, attention & concentration, and mental status over 14 years. Growth curve models are used to evaluate the association between a polygenic risk score for education (education PGS) and cognitive change. Using the most recent education PGS, we find that individuals with higher scores perform better across all measures of cognition in later life. Education PGS is associated with a faster decline in episodic memory in old age. The relationships are robust even after controlling for phenotypic educational attainment, and are unlikely to be driven by mortality bias. Future research should consider genetic effects when examining non-genetic factors in cognitive decline. Our findings represent a need to understand the mechanisms between genetic endowment of educational attainment and cognitive decline from a biological angle. Older adults with higher scores perform better across all measures of cognition. The relationship is robust after controlling for phenotypic educational attainment. The genetic effect on episodic memory diminishes with age. Future research should consider genetic effects when examining cognitive decline.
Collapse
Affiliation(s)
- Xuejie Ding
- Department of Sociology, University of Oxford, UK; Nuffield College, University of Oxford, UK.
| | - Nicola Barban
- Institute for Social and Economic Research (ISER), University of Essex, UK
| | - Felix C Tropf
- Center for Research in economics an Statistics (CREST), École Nationale de la Statistique et de L'administration Économique (ENSAE), France
| | - Melinda C Mills
- Department of Sociology, University of Oxford, UK; Nuffield College, University of Oxford, UK; Leverhulme Centre for Demographic Science, University of Oxford, UK
| |
Collapse
|
6
|
Abstract
A large body of literature has demonstrated a positive relationship between education and age at first birth. However, this relationship may be partly spurious because of family background factors that cannot be controlled for in most research designs. We investigate the extent to which education is causally related to later age at first birth in a large sample of female twins from the United Kingdom (N = 2,752). We present novel estimates using within-identical twin and biometric models. Our findings show that one year of additional schooling is associated with about one-half year later age at first birth in ordinary least squares (OLS) models. This estimate reduced to only a 1.5-month later age at first birth for the within-identical twin model controlling for all shared family background factors (genetic and family environmental). Biometric analyses reveal that it is mainly influences of the family environment-not genetic factors-that cause spurious associations between education and age at first birth. Last, using data from the Office for National Statistics, we demonstrate that only 1.9 months of the 2.74 years of fertility postponement for birth cohorts 1944-1967 could be attributed to educational expansion based on these estimates. We conclude that the rise in educational attainment alone cannot explain differences in fertility timing between cohorts.
Collapse
Affiliation(s)
- Felix C Tropf
- Department of Sociology/Nuffield College, University of Oxford, Manor Road, Oxford, OX13UQ, UK.
- University of Groningen/ICS, Grote Rozenstraat 31a, 9712 TG, Groningen, The Netherlands.
| | - Jornt J Mandemakers
- Department of Social Sciences, Wageningen University, Wageningen, The Netherlands
| |
Collapse
|
7
|
Tropf FC, Lee SH, Verweij RM, Stulp G, van der Most PJ, de Vlaming R, Bakshi A, Briley DA, Rahal C, Hellpap R, Iliadou AN, Esko T, Metspalu A, Medland SE, Martin NG, Barban N, Snieder H, Robinson MR, Mills MC. Hidden heritability due to heterogeneity across seven populations. Nat Hum Behav 2017; 1:757-765. [PMID: 29051922 PMCID: PMC5642946 DOI: 10.1038/s41562-017-0195-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Meta-analyses of genome-wide association studies (GWAS), which dominate genetic discovery are based on data from diverse historical time periods and populations. Genetic scores derived from GWAS explain only a fraction of the heritability estimates obtained from whole-genome studies on single populations, known as the ‘hidden heritability’ puzzle. Using seven sampling populations (N=35,062), we test whether hidden heritability is attributed to heterogeneity across sampling populations and time, showing that estimates are substantially smaller from across compared to within populations. We show that the hidden heritability varies substantially: from zero (height), to 20% for BMI, 37% for education, 40% for age at first birth and up to 75% for number of children. Simulations demonstrate that our results more likely reflect heterogeneity in phenotypic measurement or gene-environment interaction than genetic heterogeneity. These findings have substantial implications for genetic discovery, suggesting that large homogenous datasets are required for behavioural phenotypes and that gene-environment interaction may be a central challenge for genetic discovery.
Collapse
Affiliation(s)
- Felix C Tropf
- Department of Sociology/Nuffield College, University of Oxford, Oxford, OX1 3UQ, UK.
| | - S Hong Lee
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Renske M Verweij
- Department of Sociology/Interuniversity Center for Social Science Theory and Methodology, University of Groningen, Groningen, 9712 TG, The Netherlands
| | - Gert Stulp
- Department of Sociology/Interuniversity Center for Social Science Theory and Methodology, University of Groningen, Groningen, 9712 TG, The Netherlands
| | - Peter J van der Most
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
| | - Ronald de Vlaming
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Rotterdam, 3062 PA, The Netherlands.,Department of Complex Trait Genetics, University Amsterdam, Amsterdam, The Netherlands
| | - Andrew Bakshi
- Institute of Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Daniel A Briley
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, 61820-9998, USA
| | - Charles Rahal
- Department of Sociology/Nuffield College, University of Oxford, Oxford, OX1 3UQ, UK
| | - Robert Hellpap
- Department of Sociology/Nuffield College, University of Oxford, Oxford, OX1 3UQ, UK
| | - Anastasia N Iliadou
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, Stockholm, SE-171 77, Sweden
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, 51010, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, 51010, Tartu, Estonia
| | - Sarah E Medland
- Quantitative Genetics Laboratory, Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, QLD, 4029, Australia
| | - Nicholas G Martin
- Quantitative Genetics Laboratory, Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, QLD, 4029, Australia
| | - Nicola Barban
- Department of Sociology/Nuffield College, University of Oxford, Oxford, OX1 3UQ, UK
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
| | - Matthew R Robinson
- Institute of Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.,Department of Computational Biology, University of Lausanne, Lausanne, CH-1015, Switzerland
| | - Melinda C Mills
- Department of Sociology/Nuffield College, University of Oxford, Oxford, OX1 3UQ, UK
| |
Collapse
|
8
|
Verweij RM, Mills MC, Tropf FC, Veenstra R, Nyman A, Snieder H. Sexual dimorphism in the genetic influence on human childlessness. Eur J Hum Genet 2017; 25:1067-1074. [PMID: 28794429 PMCID: PMC5555389 DOI: 10.1038/ejhg.2017.105] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Revised: 05/11/2017] [Accepted: 05/30/2017] [Indexed: 01/19/2023] Open
Abstract
Previous research has found a genetic component of human reproduction and childlessness. Others have argued that the heritability of reproduction is counterintuitive due to a frequent misinterpretation that additive genetic variance in reproductive fitness should be close to zero. Yet it is plausible that different genetic loci operate in male and female fertility in the form of sexual dimorphism and that these genes are passed on to the next generation. This study examines the extent to which genetic factors influence childlessness and provides an empirical test of genetic sexual dimorphism. Data from the Swedish Twin Register (N=9942) is used to estimate a classical twin model, a genomic-relatedness-matrix restricted maximum likelihood (GREML) model on twins and estimates polygenic scores of age at first birth on childlessness. Results show that the variation in individual differences in childlessness is explained by genetic differences for 47% in the twin model and 59% for women and 56% for men using the GREML model. Using a polygenic score (PGS) of age at first birth (AFB), the odds of remaining childless are around 1.25 higher for individuals with 1 SD higher score on the AFB PGS, but only for women. We find that different sets of genes influence childlessness in men and in women. These findings provide insight into why people remain childless and give evidence of genetic sexual dimorphism.
Collapse
Affiliation(s)
- Renske M Verweij
- Department of Sociology and ICS, University of Groningen, Groningen, The Netherlands
| | - Melinda C Mills
- Department of Sociology and Nuffield College, University of Oxford, Oxford, UK
| | - Felix C Tropf
- Department of Sociology and Nuffield College, University of Oxford, Oxford, UK
| | - René Veenstra
- Department of Sociology and ICS, University of Groningen, Groningen, The Netherlands
| | - Anastasia Nyman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands
| |
Collapse
|
9
|
Realo A, van der Most PJ, Allik J, Esko T, Jeronimus BF, Kööts-Ausmees L, Mõttus R, Tropf FC, Snieder H, Ormel J. SNP-Based Heritability Estimates of Common and Specific Variance in Self- and Informant-Reported Neuroticism Scales. J Pers 2017; 85:906-919. [DOI: 10.1111/jopy.12297] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Anu Realo
- University of Warwick
- University of Tartu
| | | | - Jüri Allik
- University of Tartu
- The Estonian Academy of Sciences
| | - Tõnu Esko
- Estonian Genome Centre of University of Tartu
| | - Bertus F. Jeronimus
- University of Groningen, University Medical Center Groningen
- University of Groningen
| | | | | | - Felix C. Tropf
- University of Groningen
- Nuffield College, University of Oxford
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen
- Estonian Genome Centre of University of Tartu
| | - Johan Ormel
- University of Groningen, University Medical Center Groningen
| |
Collapse
|
10
|
Mehta D, Tropf FC, Gratten J, Bakshi A, Zhu Z, Bacanu SA, Hemani G, Magnusson PKE, Barban N, Esko T, Metspalu A, Snieder H, Mowry BJ, Kendler KS, Yang J, Visscher PM, McGrath JJ, Mills MC, Wray NR, Hong Lee S, Bruggeman R, Buxbaum JD, Cairns MJ, Cantor RM, Cloninger CR, Cohen D, Crespo-Facorro B, Darvasi A, DeLisi LE, Dinan T, Djurovic S, Donohoe G, Drapeau E, Escott-Price V, Freimer NB, Georgieva L, de Haan L, Henskens FA, Joa I, Julià A, Khrunin A, Lerer B, Limborska S, Loughland CM, Macek M, Magnusson PKE, Marsal S, McCarley RW, McIntosh AM, McQuillin A, Melegh B, Michie PT, Morris DW, Murphy KC, Myin-Germeys I, Olincy A, Van Os J, Pantelis C, Posthuma D, Quested D, Schall U, Scott RJ, Seidman LJ, Toncheva D, Tooney PA, Waddington J, Weinberger DR, Weiser M, Wu JQ. Evidence for Genetic Overlap Between Schizophrenia and Age at First Birth in Women. JAMA Psychiatry 2016; 73:497-505. [PMID: 27007234 PMCID: PMC5785705 DOI: 10.1001/jamapsychiatry.2016.0129] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
IMPORTANCE A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age. OBJECTIVE To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets. DESIGN, SETTING, AND PARTICIPANTS This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18 957 SCZ cases and 22 673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12 247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study. MAIN OUTCOMES AND MEASURES We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age. RESULTS We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2 = 1.1E-03, P = 4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014. CONCLUSIONS AND RELEVANCE This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers.
Collapse
Affiliation(s)
- Divya Mehta
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Felix C Tropf
- Department of Sociology/ICS, University of Groningen, The Netherlands
| | - Jacob Gratten
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Andrew Bakshi
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Zhihong Zhu
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Silviu-Alin Bacanu
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA,Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, School of Social and Community Medicine, Bristol BS8 1TH, UK
| | - Patrik KE Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nicola Barban
- Nuffield College and Department of Sociology, University of Oxford, Oxford, England
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | | | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Bryan J Mowry
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia,Queensland Centre for Mental Health Research, Wacol, Queensland, Australia
| | - Kenneth S Kendler
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA,Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA,Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Jian Yang
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Peter M Visscher
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - John J McGrath
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Melinda C Mills
- Nuffield College and Department of Sociology, University of Oxford, Oxford, England
| | - Naomi R Wray
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia
| | - S Hong Lee
- The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia,School of Environmental and Rural Science, The University of New England, Armidale, Australia
| | | | - LifeLines Cohort Study
- LifeLines Cohort Study, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | | | - Richard Bruggeman
- University Medical Center Groningen, Department of Psychiatry, University of Groningen, Groningen, the Netherlands
| | - Joseph D Buxbaum
- Department of Human Genetics, Icahn School of Medicine at Mount Sinai, New York, New York18Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York19Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York
| | - Murray J Cairns
- Schizophrenia Research Institute, Sydney, Australia22Priority Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle, Australia23School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, Australia
| | - Rita M Cantor
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles
| | - C Robert Cloninger
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - David Cohen
- Department of Child and Adolescent Psychiatry, Assistance Publique Hôpitaux de Paris, Pierre and Marie Curie University, and Institute for Intelligent Systems and Robotics, Paris, France
| | - Benedicto Crespo-Facorro
- CIBERSAM, University Hospital Marqués de Valdecilla, University of Cantabria-IDIVAL, Department of Psychiatry, Santander, Spain28 Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
| | - Ariel Darvasi
- Department of Genetics, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Lynn E DeLisi
- Schizophrenia Research Institute, Sydney, Australia30VA Boston Health Care System, Brockton, Massachusetts
| | - Timothy Dinan
- Department of Psychiatry, University College Cork, Cork, Ireland
| | - Srdjan Djurovic
- NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway33Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Gary Donohoe
- Cognitive Genetics and Therapy Group, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland35Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Elodie Drapeau
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Valentina Escott-Price
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Lyudmila Georgieva
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, Wales
| | - Lieuwe de Haan
- Department of Psychiatry, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Frans A Henskens
- Schizophrenia Research Institute, Sydney, Australia39School of Electrical Engineering and Computer Science, University of Newcastle, Newcastle, Australia40Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, Australia
| | - Inge Joa
- Regional Centre for Clinical Research in Psychosis, Department of Psychiatry, Stavanger University Hospital, Stavanger, Norway
| | - Antonio Julià
- Rheumatology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Andrey Khrunin
- Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Bernard Lerer
- Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Svetlana Limborska
- Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Carmel M Loughland
- Schizophrenia Research Institute, Sydney, Australia22Priority Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle, Australia
| | - Milan Macek
- Department of Biology and Medical Genetics, Second Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Marsal
- Rheumatology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Robert W McCarley
- VA Boston Health Care System, Brockton, Massachusetts47Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland49Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, England
| | - Bela Melegh
- Department of Medical Genetics, University of Pécs, Pécs, Hungary52Szentagothai Research Center, University of Pécs, Pécs, Hungary
| | - Patricia T Michie
- Schizophrenia Research Institute, Sydney, Australia53School of Psychology, University of Newcastle, Newcastle, Australia
| | - Derek W Morris
- Cognitive Genetics and Therapy Group, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland35Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Kieran C Murphy
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Inez Myin-Germeys
- Center for Contextual Psychiatry, Department of Neuroscience, KU Leuven, Leuven, Belgium
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Denver, Aurora
| | - Jim Van Os
- Institute of Psychiatry, King's College London, London, England58Maastricht University Medical Centre, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht, the Netherlands
| | - Christos Pantelis
- Schizophrenia Research Institute, Sydney, Australia59Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Danielle Posthuma
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, Amsterdam, the Netherlands61Department of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University Medical Center
| | - Digby Quested
- Department of Psychiatry, University of Oxford, Oxford, England
| | - Ulrich Schall
- Schizophrenia Research Institute, Sydney, Australia22Priority Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle, Australia
| | - Rodney J Scott
- Schizophrenia Research Institute, Sydney, Australia23School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, Australia64Hunter New England Health Service, Newcastle, Australia
| | - Larry J Seidman
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts65Massachusetts Mental Health Center Public Psychiatry Division, Beth Israel Deaconess Medical Center, Boston
| | - Draga Toncheva
- Department of Medical Genetics, Medical University, Sofia, Bulgaria
| | - Paul A Tooney
- Schizophrenia Research Institute, Sydney, Australia23School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, Australia67Priority Research Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle
| | - John Waddington
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, Maryland70Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland71Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, Maryland72
| | | | - Jing Qin Wu
- Schizophrenia Research Institute, Sydney, Australia23School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, Australia
| |
Collapse
|
11
|
Abstract
The Dutch are the tallest people on earth. Over the last 200 years, they have grown 20 cm in height: a rapid rate of increase that points to environmental causes. This secular trend in height is echoed across all Western populations, but came to an end, or at least levelled off, much earlier than in The Netherlands. One possibility, then, is that natural selection acted congruently with these environmentally induced changes to further promote tall stature among the people of the lowlands. Using data from the LifeLines study, which follows a large sample of the population of the north of The Netherlands (n = 94 516), we examined how height was related to measures of reproductive success (as a proxy for fitness). Across three decades (1935-1967), height was consistently related to reproductive output (number of children born and number of surviving children), favouring taller men and average height women. This was despite a later age at first birth for taller individuals. Furthermore, even in this low-mortality population, taller women experienced higher child survival, which contributed positively to their increased reproductive success. Thus, natural selection in addition to good environmental conditions may help explain why the Dutch are so tall.
Collapse
Affiliation(s)
- Gert Stulp
- Department of Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK Department of Sociology, University of Groningen, Grote Rozenstraat 31, Groningen 9712 TG, The Netherlands
| | - Louise Barrett
- Department of Psychology, University of Lethbridge, 4401 University Drive West, Lethbridge, Alberta, Canada T1 K 3M4 Applied Behavioural Ecology and Ecosystems Research Unit, University of South Africa, Private Bag X6 Florida 1710, Johannesburg, South Africa
| | - Felix C Tropf
- Department of Sociology, University of Groningen, Grote Rozenstraat 31, Groningen 9712 TG, The Netherlands
| | - Melinda Mills
- Nuffield College/Department of Sociology, Manor Road, Oxford OX1 3UQ, UK
| |
Collapse
|
12
|
Tropf FC, Barban N, Mills MC, Snieder H, Mandemakers JJ. Genetic influence on age at first birth of female twins born in the UK, 1919-68. Popul Stud (Camb) 2015; 69:129-45. [PMID: 26234944 DOI: 10.1080/00324728.2015.1056823] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Using a sample of monozygotic (945, 42 per cent) and dizygotic (1,329, 58 per cent) twin pairs born 1919-68 in the UK, we applied innovative tobit models to investigate genetic and environmental influences on age at first birth (AFB). We found that a substantial part (40 per cent) of the variation in AFB is caused by latent family characteristics. Genetic dispositions (26 per cent) play a more important role than the shared environment of siblings (14 per cent), with the non-shared environment/measurement error having the strongest influence (60 per cent). Like previous studies, this study reveals marked changes in estimates over time, and supports the idea that environmental constraints (war or economic crisis) suppress and normative freedom (sexual revolution) promotes the activation of genetic predispositions that affect fertility. We show that the exclusion of censored information (i.e., on the childless) by previous studies biased their results.
Collapse
|
13
|
Tropf FC, Stulp G, Barban N, Visscher PM, Yang J, Snieder H, Mills MC. Human fertility, molecular genetics, and natural selection in modern societies. PLoS One 2015; 10:e0126821. [PMID: 26039877 PMCID: PMC4454512 DOI: 10.1371/journal.pone.0126821] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2014] [Accepted: 04/08/2015] [Indexed: 12/24/2022] Open
Abstract
Research on genetic influences on human fertility outcomes such as number of children ever born (NEB) or the age at first childbirth (AFB) has been solely based on twin and family-designs that suffer from problematic assumptions and practical limitations. The current study exploits recent advances in the field of molecular genetics by applying the genomic-relationship-matrix based restricted maximum likelihood (GREML) methods to quantify for the first time the extent to which common genetic variants influence the NEB and the AFB of women. Using data from the UK and the Netherlands (N = 6,758), results show significant additive genetic effects on both traits explaining 10% (SE = 5) of the variance in the NEB and 15% (SE = 4) in the AFB. We further find a significant negative genetic correlation between AFB and NEB in the pooled sample of –0.62 (SE = 0.27, p-value = 0.02). This finding implies that individuals with genetic predispositions for an earlier AFB had a reproductive advantage and that natural selection operated not only in historical, but also in contemporary populations. The observed postponement in the AFB across the past century in Europe contrasts with these findings, suggesting an evolutionary override by environmental effects and underscoring that evolutionary predictions in modern human societies are not straight forward. It emphasizes the necessity for an integrative research design from the fields of genetics and social sciences in order to understand and predict fertility outcomes. Finally, our results suggest that we may be able to find genetic variants associated with human fertility when conducting GWAS-meta analyses with sufficient sample size.
Collapse
Affiliation(s)
- Felix C. Tropf
- Department of Sociology/ ICS, University of Groningen, Groningen, Netherlands
- * E-mail:
| | - Gert Stulp
- Department of Population Health, London School of Hygiene and Tropical Medicine, London, England
| | - Nicola Barban
- Department of Sociology/Nuffield College, University of Oxford, Oxford, England
| | - Peter M. Visscher
- The Queensland Brain Institute, University of Queensland, Brisbane, Australia
- The University of Queensland Diamantina Institute, The Translational Research Institute, Brisbane, Australia
| | - Jian Yang
- The Queensland Brain Institute, University of Queensland, Brisbane, Australia
- The University of Queensland Diamantina Institute, The Translational Research Institute, Brisbane, Australia
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Melinda C. Mills
- Department of Sociology/Nuffield College, University of Oxford, Oxford, England
| |
Collapse
|
14
|
Abstract
The social sciences have been reticent to integrate a biodemographic approach to the study of fertility choice and behaviour, resulting in theories and findings that are largely socially-deterministic. The aim of this paper is to first reflect on reasons for this lack of integration, provide a review of previous examinations, take stock of what we have learned until now and propose future research frontiers. We review the early foundations of proximate determinants followed by behavioural genetic (family and twin) studies that isolated the extent of genetic influence on fertility traits. We then discuss research that considers gene and environment interaction and the importance of cohort and country-specific estimates, followed by multivariate models that explore motivational precursors to fertility and education. The next section on molecular genetics reviews fertility-related candidate gene studies and their shortcomings and on-going work on genome wide association studies. Work in evolutionary anthropology and biology is then briefly examined, focusing on evidence for natural selection. Biological and genetic factors are relevant in explaining and predicting fertility traits, with socio-environmental factors and their interaction still key in understanding outcomes. Studying the interplay between genes and the environment, new data sources and integration of new methods will be central to understanding and predicting future fertility trends.
Collapse
Affiliation(s)
- Melinda C. Mills
- Department of Sociology and Nuffield College, University of Oxford, 1 New Road, OX1 1NF Oxford, UK
| | - Felix C. Tropf
- Department of Sociology, Interuniversity Center for Social Science Theory and Methodology (ICS), University of Groningen, Grote Rozenstraat 31, 9712 Groningen, TG The Netherlands
| |
Collapse
|