This electronic thesis or dissertation has been downloaded from Explore Bristol Research, http://research-information.bristol.ac.uk Author: Haworth, Simon Title: The use of genetic data in dental epidemiology to explore the causes and consequences of caries and periodontitis General rights Access to the thesis is subject to the Creative Commons Attribution - NonCommercial-No Derivatives 4.0 International Public License. A copy of this may be found at https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode This license sets out your rights and the restrictions that apply to your access to the thesis so it is important you read this before proceeding. Take down policy Some pages of this thesis may have been removed for copyright restrictions prior to having it been deposited in Explore Bristol Research. 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The use of genetic data in dental epidemiology to explore the causes and consequences of caries and periodontitis Simon Haworth A dissertation submitted to the University of Bristol in accordance with the requirements for award of the degree of PhD in the Faculty of Health Sciences, September 2019 Word count: 77,472 words 1 Abstract The major dental diseases are caries and periodontitis. These two common conditions are important public health problems and have complex, multifactorial aetiology. Study designs which use genetic data can provide evidence about the molecular and biological basis of disease and also help prioritize modifiable risk factors which have causal relevance for disease. To date these approaches have had limited success in dental epidemiology, possibly due to the lack of large studies with genetic data and dental phenotypes. Through a theoretical review and a pair of applied illustrations, I argue that questionnaire- derived and index-linked dental data provide a valuable resource for the application of modern epidemiological methods. Using these data for genetic association discovery, the main findings are novel risk loci for caries in both adult and paediatric populations, and evidence suggesting that the genetic risk factors for caries and periodontitis are partially overlapping with a range of other health traits. These newly discovered risk loci can act as proxies for variation in dental disease experience using current methods for causal effect estimation. I test the reciprocal hypotheses that dental diseases have downstream effects on cardio-metabolic traits, and that metabolic traits influence risk of dental diseases, finding some evidence supporting existing beliefs that dental diseases may have undesirable downstream effects on health. Together, the results suggest that studies which use genetic data will have an important role in the future of dental epidemiology and can help improve understanding of both the molecular and broader health and social aetiology of caries and periodontitis. Unlocking the full potential of these methods will require the community to support still-larger studies and adopt modern working practices in dental epidemiology. 2 Dedication To my family – Christopher, Katherine and Jennifer 3 Acknowledgements Personal thanks First, I would like to thank my supervisors for their enthusiasm and energy throughout this project. I am very grateful for the opportunity to work on this project, and would particularly like to thank Ingegerd Johansson and Paul Franks (representing the GLIDE consortium), and Nic Timpson and Steve Thomas (representing the University of Bristol), who encouraged me to plan a collaborative project and supported me at every stage of the project. As well as this day to day support from specific individuals, I am grateful for the institutional support from Wellcome (who funded my research training through the clinical research training fellowship scheme), the University of Bristol, Umeå University and Lund University. I would like to thank Jonathan Sandy, George Davey Smith and Debbie Lawlor for their feedback and guidance both through the formal student review process and informal mentorship. Finally, I would like to thank all the research participants who contributed their data to this project for their generosity. Scientific input Many people have helped with specific parts of this project by contributing analysis or providing advice on analysis or interpretation. It is not possible to acknowledge all these personally, but I would like to highlight a small number of people who have been particularly helpful. Dmitry Shungin made major contributions to GWAS meta-analysis in GLIDE, Tom Dudding helped plan and perform analysis in ALSPAC, Ruth Mitchell provided support for analysis of genetic data in UK Biobank, Margaret May provided advice on longitudinal modelling approaches, Min-Jeong Shin provided access to KNHANES data and an analytical team to perform analysis, Erik Ingelssson provided advice on cardiometabolic traits, Justin van der Tas, John Shaffer and Kimon Divaris provided particularly helpful input during manuscript preparation and revision. A full description of the contributions of each person is provided in the publications listed in section 1.6. Support for underlying resources Data described in this dissertation were contributed by many studies. Specific acknowledgements for each study are provided in the relevant results chapter or appendix. 4 Author’s declaration I declare that the work in this dissertation was carried out in accordance with the requirements of the University's Regulations and Code of Practice for Research Degree Programmes and that it has not been submitted for any other academic award. Except where indicated by specific reference in the text, the work is the candidate's own work. Work done in collaboration with, or with the assistance of, others, is indicated as such. Any views expressed in the dissertation are those of the author. SIGNED: …………………………………………………… DATE:…………………………… 5 Table of contents, list of tables and illustrative material Table of Contents Abstract ............................................................................................................................................ 2 Dedication ......................................................................................................................................... 3 Acknowledgements ........................................................................................................................... 4 Author’s declaration .......................................................................................................................... 5 Table of contents, list of tables and illustrative material .................................................................... 6 Table of Contents .......................................................................................................................... 6 List of tables and illustrative material .......................................................................................... 10 List of abbreviations .................................................................................................................... 13 Chapter 1: Introduction ................................................................................................................... 16 1.1: The aetiology of caries and periodontitis............................................................................... 16 1.2: Genetic evidence as a method to refine understanding of disease mechanisms and biology . 19 1.3: Genetic association studies for dental caries and periodontitis ............................................. 20 1.4: Causal inference is valuable for prioritizing interventions ...................................................... 24 1.5: Commentary ......................................................................................................................... 26 1.6: Projects contributing to this dissertation ............................................................................... 27 Chapter 2: Use of questionnaire-derived and index-linked dental phenotypes ................................. 31 2.1: Theoretical considerations relating to sampling and measurement ....................................... 32 2.1.1: The importance of sample size ....................................................................................... 32 2.1.2: The importance of sampling frame ................................................................................. 33 2.1.3: Importance of subgroups within the study population ................................................... 35 2.1.4: Importance of environment within a study..................................................................... 37 2.1.5: Intersection of studies with different populations .......................................................... 38 2.1.6: Distinction between random and non-random measurement error ............................... 39 2.1.7: Compromise