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.