Determinants of reproductive function & health in young women

PhD project (3/4 yr research project leading to independent research at the doctorate level)

Dr. Abigail Fraser, Dr. Laura Howe, Prof Debbie Lawlor

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The principal determinants of reproductive health and potential remain to be clarified. This is of particular importance in light of societal change and increasing maternal age. Age at first birth is now at an all-time high; 29.8 years in England and Wales in 2012 and 20% of babies are born to mothers 35 years or older[1]. Whilst genetics contribute to determining the age menarche and menopause,[2] as with other complex traits, genetic variation is not the main driver of women’s reproductive lifespan and health. Risk factors for early age at menarche include young maternal age, smoking, and adverse health in pregnancy[3], higher childhood socio-economic position, greater adiposity and exposure to psychosocial stress[4]. Evidence of associations with earlier age at menopause is inconsistent for some risk factors such as adiposity but more robust for others such as lower educational attainment, smoking, nulliparity and nonuse of oral contraceptives[5,6].

Aims & objectives

To study the lifecourse epidemiology of reproductive markers (AMH, oestradiol, FSH, LH, SHBG, androgens) in 25 years old women. Potential objectives:
1.To study prenatal exposures in relation to reproductive hormones.
2.To study modifiable behaviours (e.g. diet, smoking), stress, growth, adiposity (height, weight) measured repeatedly in relation to outcomes.
3.To study associations of menstrual characteristics with outcomes.
4.To study the role of epigenetics in women’s reproductive health.


ALSPAC is a prospective population-based birth cohort that recruited 14,541 pregnant women resident in Avon, UK with expected dates of delivery 1st April 1991 to 31st December 1992 ( As part of the ARIES project, 1000 mother-child pairs from ALSPAC have genome-wide methylation data at several time points (for the children these are: at birth, age 7 and age 15-17).

The student will use appropriate statistical modelling techniques such as multivariable regression, bivariate linear spline models[7] and a structured life course approach[8] to examine repeatedly measured exposures and their associations with measures of reproductive health. A quantitative EWAS of reproductive hormone profiles will be undertaken using data from the ARIES resource.


1 2 Hartge. Nat Genet 2009. 3 D'Aloisio. Epidemiol 2013. 4 Mishra. Womens Health 2009. 5 Mishra. Maturitas 2013. 6 Gold. AJE 2013. 7 Palmer. Stata J 2014. 8 Smith. Epidemiol In press.

Created on Oct. 1, 2015, 9 a.m.