Early Life Determinants of Metabolic and Reproductive Health Benjamin Carver Hollis University of Cambridge St. Edmund’s College December 2019 This thesis is submitted for the degree of Doctor of Philosophy 2 Declaration This thesis is my own work and includes nothing which is the outcome of work done in collaboration except as declared in the ‘Contributions and Collaborations’ sections at the beginning of each chapter or as specified in the text. No part of this thesis is substantially similar to any work that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution. It does not exceed the limit of 60,000 words prescribed by the Degree Committee of the Faculties of Clinical Medicine and Veterinary Medicine. 3 4 Benjamin Carver Hollis MRC-Epidemiology Unit Dissertation title: “Early Life Determinants of Metabolic and Reproductive Health” Events in early life have consistently been associated with health outcomes in later life. The ‘developmental origins’ theory first hypothesised that adverse conditions in-utero can lead to physiological adaptations in the developing foetus which have long lasting influences on health. This concept has been extended to early childhood and adolescence, whereby exposures during critical periods of development can impact health throughout the life course of an individual. In particular, a secular trend for a decreasing age of puberty onset has been linked to the global increases in prevalence of cardio-metabolic diseases and cancer. It has been suggested that childhood obesity and lifetime sex hormone exposure may act as key mediating factors in this relationship. As the prevalence of obesity continues to rise globally and consequent comorbidities place an increasing burden on healthcare systems, understanding the mechanisms that link early life events to later life health have become of increasing importance. While environmental exposures are often cited as being highly influential on growth and development, the role of genetics has become gradually more apparent in recent years. This has been aided by the availability of increasingly large data resources. Genetic studies have shown that many developmental traits are highly heritable and share genetic determinants with metabolic and reproductive health outcomes. In this thesis I use data from large-scale, population-based resources to further elucidate the role of genetic and epigenetic factors in explaining observed associations between developmental traits and later life metabolic and reproductive health. I begin by examining the genetic aetiology of puberty timing in men, a key stage of sexual development which is understudied compared to women. I identify 29 novel genes involved in the control of puberty timing, implicating new biological pathways and demonstrate genetic correlations between earlier age of puberty and adverse health in adulthood. I then expand on the theme of genetic discovery by conducting genome-wide association studies (GWAS) for reproductive traits in the UK Biobank study. These outcomes have important societal and public health impacts but many have not previously been investigated from a genetic perspective. I identify over 800 variant-trait associations, highlighting genomic regions with highly pleiotropic influences on a diverse range of reproductive traits. This data is then leveraged to construct a framework for conducting phenome-wide association studies (PheWAS), which is used to explore the extent to which both BMI and sex hormone exposure act as mediating factors to explain the link between earlier puberty and heightened reproductive health risks. 5 I go on to examine mechanisms linking early life markers of development to adult health. I investigate the association between weight at birth and body composition in adulthood, determining that foetal and maternal-specific genetic determinants of birth weight have differential influences on fat and lean mass distribution. Downstream analyses suggest that these operate through distinct biological pathways, adding to our understanding of the association between low birth weight and poor health. Finally, I conduct an epigenome-wide association study (EWAS) as a complementary approach to GWAS for both BMI and puberty timing to identify additional genomic loci associated with both traits. Using EWAS data I present evidence for a casual epigenetic effect on puberty timing, functioning through both BMI-mediated and independent pathways. The findings from this thesis contribute to the understanding of the genetic determinants of early life developmental processes and their relationship with later health, which have important implications for the improvement of individualised disease prevention and management. 6 Acknowledgements This thesis is the culmination of three delightful, hard-working years at the MRC Epidemiology Unit, and I am grateful to have worked alongside a number of inspiring, brilliant and talented individuals whom I’m honoured to consider my peers and friends. To my supervisor John Perry, thank you for giving me this opportunity and for your guidance throughout the process. Additionally to the members of the Growth and Development group, principally Ken Ong for his input and assistance with various aspects of this dissertation. To my colleagues and collaborators, your knowledge and enthusiasm is greatly appreciated. To the friends I’ve made along the way, you have made this experience ever more enjoyable and I will cherish our times spent together these last three years. To my family, thank you for your unwavering support. To Alice, for putting up with the ups and downs (mostly ups though), for your love and support that helps keep me going. And finally to Felix – this dissertation might have materialised without you, but I choose not to imagine what it would have been like without your guidance, tutelage and friendship. 7 8 Publications The following papers related to chapters of this thesis have been published or are in the process of submission for publication at the time of writing: Hollis B., Day F.R., Busch, A.S., Thompson D., Soares A.L.G., Timmers P.R.J.H., Kwong A., Easton D.P., Joshi P.K., Timpson N.J., The PRACTICAL CONSORTIUM, 23andMe Research Team, Ong K.K., Perry J.R.B. Expanded genomic analysis for male voice-breaking highlights a shared phenotypic and genetic basis between puberty timing and natural hair colour. Nat Commun. 11; 1536 (2020). Busch A.S., Hollis B., Day F.R., Sorensen K, Aksglaede L., Perry J.R.B., Ong K.K., Juul A., Hagen C.P. Voice break in boys – temporal relations with other pubertal milestones and likely causal effects of BMI. Human Reproduction. 34(8);1514-1522 (2019). Ruth K.S., Day F.R., Tyrrell J, Thompson D.J., [6 authors], Hollis B., [6 authors], Murray A., Ong K.K., Frayling T.M., Perry J.R.B. Using human genetics to understand the disease impacts of testosterone in men and women. (Accepted at Nature Medicine). 9 10 Commonly Used Abbreviations AAM…………………………. Age at menarche AFB………………………….. Age at first birth AFS…………………………... Age at first sexual intercourse BMI………………………….. Body mass index Bp……………………………. Base-pair Chr…………………………… Chromosome CI……………………………... Confidence interval CVD………………………….. Cardiovascular disease DEXA……………..…………. Dual energy x-ray absorptiometry DOHaD……………………... Developmental Origins of Health and Disease EA……………………………. Effect allele EAF………………………….. Effect allele frequency eQTL………………………… Expression quantitative trait loci GIANT………………………. Genetic Investigation of Anthropometric Traits GTEx……………………….. Genotype-Tissue Expression FDR…………………………. False discovery rate FH……………………………. Facial Hair GRS…………………………...Genetic risk score GWAS……………………….. Genome-wide association study HES………………………….. Hospital Episode Statistics HLA………………………….. Human leukocyte antigen HRC………………………….. Haplotype Reference Consortium HWE………………………… Hardy-Weinberg equilibrium IVW…………………………. Inverse variance weighted LD……………………………. Linkage disequilibrium MAF………………………… Minor allele frequency MB…………………………... Mega-base MR…………………………... Mendelian randomisation OA……………………………. Other allele OR……………………………. Odds ratio PC…………………………….. Principal component QC…………………………… Quality control SD……………………………. Standard deviation SE…………………………….. Standard error SNP…………………………. Single nucleotide polymorphism T2D…………………………. Type 2 diabetes 11 UKBB………………………. UK Biobank VB……………………………. Voice breaking 12 Table of Contents Declaration .................................................................................................................................................. 3 Thesis Summary ......................................................................................................................................... 5 Acknowledgements ................................................................................................................................... 7 Publications ................................................................................................................................................. 9 Commonly Used Abbreviations .......................................................................................................... 11 List oF Figures ........................................................................................................................................... 17 List oF Tables ...........................................................................................................................................