Identification of genetic and non-genetic factors contributing to female reproductive ageing

Abstract

The aim of my work was to identify additional genetic and non-genetic factors influencing female reproductive ageing in humans. Although approximately 50% of population variation in age at menopause is due to genetics, less than 3% of variation had been accounted for by common genetic variants. Of non-genetic risk factors, only smoking had consistently been found to have a strong effect on age of menopause. In the wider context of female reproduction, our understanding of the role of genetics in determining sex hormone levels was limited. By combining the results of research in these different areas, I hoped to improve our knowledge of the biology of female reproductive ageing. Chapter 1 is an introduction in which I discuss the biology of menopause, describe relationships with health and present current knowledge regarding non-genetic and genetic risk factors influencing menopause age. Chapter 2 is an analysis of the associations between non-genetic risk factors occurring in early life with early menopause. We identified an association between multiple births and early menopause, connecting events pre-birth, when the oocyte pool is formed, with reproductive ageing in later life. Chapter 3 is a genome-wide association study to identify genetic variants associated with levels of nine sex hormone related phenotypes. We highlighted loci of relevance to reproductive function, which suggested overlaps in the genetic basis of hormone regulation. Chapter 4 is a genome-wide association study of menstrual cycle length. We showed that a common genetic variant related to follicle stimulating hormone levels and age at menopause is associated with several reproductive traits including length of menstrual cycle. Chapter 5 is an investigation of the relationship between differences in length of normal FMR1 triplet repeat alleles and timing of menopause. We found no association between the length of normal FMR1 alleles and timing of menopause, contradicting the results of smaller studies and replicating a null result in another large study. Chapter 6 is large genome-wide meta-analysis to identify common and low-frequency genetic variants associated with age at menopause. We identified 44 regions containing 54 independent common signals and two rare missense alleles of large effect. Finally, in Chapter 7 I evaluate how this work has benefitted our knowledge of female reproductive ageing and describe directions for future research.