Introduction
Polycystic ovarian syndrome (PCOS) is a common endocrine disorder that affects 6-15% of women worldwide, and prevalence is steadily increasing[1,2]. It is characterised by oligomenorrhea and/or olig- or an-ovulation, androgen excess, and polycystic ovaries (PCO), manifesting as menstrual irregularities, subfertility, hirsutism, acne, metabolic syndrome, and reduced quality of life[1,2].
PCOS is associated with impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and diabetes, all of which are risk factors for cardiovascular morbidity and mortality, and chronic renal disease[3]. Diabetes is approximately six-times more prevalent in women with PCOS than aged-matched non-PCOS populations, and is the greatest cause of systemic and chronic morbidity in these women[3,4]. As such, primary prevention of diabetes is key in women with PCOS.
Raised body-mass index (BMI), family history, and ethnicity are risk-factors for developing diabetes in women with PCOS[4,5]. However, individual risk-stratification is challenging and many women receive sub-optimal lifestyle (e.g. diet, exercise) advice and delayed intervention, with adverse outcomes[1,5]. Metabolomic and molecular markers have thus far failed to reliably predict development of IGF, IGT or diabetes in women with PCOS[6]. Differential DNA methylation patterns have been found between healthy women and women with PCOS, and between PCOS clinical phenotypes[7]. DNA methylation has also been identified as holding prognostic value in multiple tissue types, including predicting diabetes onset in non-PCOS populations[8].
However, to our knowledge, there are no reports evaluating the prognostic potential of differential methylation in women with PCOS in relation to their risk of developing diabetes. We therefore performed genome-wide (‘450K’ array) DNA methylation assessment comparing women with PCOS and women with PCOS who later developed diabetes, to determine whether novel potentially clinically useful ‘at diagnosis’ biomarkers that might guide early intervention and prevent development of diabetes and associated complications, could be identified.