PD-PCOS

  • Research type

    Research Study

  • Full title

    Prediction of Diabetes in women with Polycystic Ovary Syndrome: a pilot study (PD-PCOS)

  • IRAS ID

    163859

  • Contact name

    Pensee Wu

  • Contact email

    p.wu@keele.ac.uk

  • Sponsor organisation

    University Hospital of North Midlands NHS Trust

  • Duration of Study in the UK

    1 years, 5 months, 31 days

  • Research summary

    Research Summary:
    We wish to explore if there is evidence that an epigenetic signature exists which discriminate polycystic ovary syndrome (PCOS) women with type 2 diabetes mellitus (T2DM) from PCOS women without T2DM. As a secondary aim, we will compare the candidate genes, which form a part of the identified epigenetic signature, with existing literature to see whether any genes overlap with those previously implicated in T2DM and validate these genes. Our longer term aim is to identify an epigenetic signature that predicts T2DM in PCOS patients.

    We will take blood samples from 12 women with PCOS and T2DM, and 12 women with PCOS only as controls. Clinical data such as year of PCOS diagnosis, age, and body mass index will be recorded. DNA will be extracted from the blood samples and used to examine the difference in methylation patterns between the 2 groups of women.

    Summary of Reslts:
    Background Polycystic ovarian syndrome (PCOS) is a common endocrine disorder characterised by ovarian morphological, systemic biochemical, and menstrual changes. Women with PCOS are at significantly increased risk of raised fasting glucose, impaired glucose tolerance, and diabetes. Recognition of these complications and early intervention are key to good health outcomes, however individual risk-stratification in clinical practice is difficult. We therefore sought to identify DNA methylation patterns that may predict future diabetes onset in this high-risk PCOS population.

    Patients and Methods
    Peripheral blood samples from six matched pairs (women with PCOS and those with PCOS who later developed diabetes), were analysed by Illumina HumanMethylation450 BeadChip-arrays. Bisulphite-Pyrosequencing™ was subsequently used to validate and confirm array methylation data.

    Results
    Technical validation confirmed that Pyrosequening™-derived methylation correlated with array-derived β-values (p<0.001). Array filtering identified 19 differentially methylated CpG loci between women with PCOS and those with PCOS and diabetes (≥0.2 β-value change in the same direction in five or more matched pairs). The three best putative CpG loci prognostic biomarkers (cg11897887, cg02819655, and cg25542007) were analysed for potential clinical performance. Hypomethylation of cg25542007 in combination with either hypermethylation at cg11897887 or hypomethylation at cg02819655 predicted future diabetes onset with 83.3% sensitivity and specificity, and positive and negative predictive values of 35.7% and 97.8%, respectively.

    Conclusions
    This is the first genome-wide DNA methylation analyses in a unique cohort of matched PCOS women with or without diabetes. Our analyses have identified novel and potentially clinically useful methylation biomarkers that could predict future onset of diabetes in this high-risk population. It is possible that early identification of PCOS women likely to develop diabetes by methylation analysis, may facilitate timely educational/dietary/exercise interventions that could reduce future morbidity.

  • REC name

    West Midlands - Solihull Research Ethics Committee

  • REC reference

    15/WM/0162

  • Date of REC Opinion

    22 Jun 2015

  • REC opinion

    Further Information Favourable Opinion