Establishing and orienting causal relationships between sleep characteristics and reproductive function

Rationale

A large body of literature from animal studies has highlighted the role of core clock genes in relation to reproductive function [1]. In contrast, only a few epidemiological studies have implicated the circadian clock with human reproduction. These have largely focused on investigating the modification of menstrual cycle patterns in relation to shift work [2,3]. Circadian dysregulation as captured by sleep traits have also been associated with menstrual-related disorders [4] and fertility [5]. In turn, menstrual cycle characteristics 6 and reproductive events such as menopause [7] have been previously linked to changes in sleep, which may imply a bi-directional relationship.

Large epidemiological resources such as ALSPAC and the UK Biobank include detailed data on both sleep characteristics, reproductive traits and menstrual disorders which may be used to investigate associations between these traits. Genetic variants for a range of sleep characteristics, reproductive traits and menstrual conditions have been identified in recent genome-wide association studies (GWAS) which can be used establish and orient causal relationships. In particular, bivariate LD score regression calculates the genetic correlation between two traits [8] and Mendelian randomization (MR) uses those genetic variants most strongly associated with one trait to establish a causal effect on another [9-11].

Aims and Objectives

To use observational and genetic epidemiological approaches within UK Biobank, ALSPAC, and other genetic studies and consortia (ReproGen, Human Reproductive Behaviour consortium, FinnGen) to: i) investigate cross sectional and prospective associations between sleep characteristics and reproductive/menstrual traits , ii) estimate the genetic correlations between sleep characteristics and reproductive/menstrual traits and iii) evaluate causal effects of sleep on reproductive traits and vice-versa.

Methods

1) Derive sleep, reproductive and menstrual measures from ALSPAC and UK Biobank

2) Perform multivariable regression analyses to investigate the associations between these traits, both cross sectionally and prospectively

3) Identify genome-wide association studies related to a series of sleep characteristics (insomnia, chronotype, sleep duration, daytime sleepiness, circadian disruption), reproductive traits (age at menarche, age at menopause, age at first birth, number of births, infertility, sex hormones) and menstrual conditions (dysmenorrhea, PCOS, endometriosis, menstrual cycle length) from GWAS data repositories, specifically the GWAS Catalog (ebi.ac.uk/gwas) and IEU Open GWAS (gwas.mrcieu.ac.uk/).

4) Perform bivariate LD score regression analysis to investigate genetic correlations between sleep and reproductive traits.

5) Extract genome-wide significant genetic variants related to those traits where there is evidence for genetic correlation.

6) Perform both one- and two-sample MR analyses to establish causal relationships.

7) Conduct sensitivity analyses to evaluate the robustness of findings.

8) Compare MR estimates with those obtained from multivariable regression.

This project will be based in Bristol Medical School - Population Health Sciences in the Faculty of Health Sciences at the University of Bristol.

If you have secured your own sponsorship or can self-fund this PhD please visit our information page here for further information on the department of Population Health Science and how to apply.