Publication:

Metabolic syndrome and insulin resistance in PCOS phenotypes

Background Polycystic ovary syndrome(PCOS) is an endocrine metabolic disorder which is rapidly gaining epidemic proportions. Hyperinsulinemia and insulin resistance (IR) are thought to be key pathological factors. This study was undertaken to characterize the phenotypes of PCOS and to determine the prevalence of metabolic syndrome (MetS) and insulin resistance in them.

Methods This observational cross-sectional study was undertaken to assess the distribution of the Rotterdam PCOS phenotypes and to report the prevalence and risk factors for MetS syndrome and insulin resistance using homeostasis model assesment for insulin resistance (HOMA-IR). 90 women aged 18-35 years newly diagnosed with PCOS were classified into one of the four potential PCOS phenotypes based on history, examination and investigations.

Results Phenotype A was the most prevalent phenotype (45.5%). Prevalence of insulin resistance in our study was 31% using HOMA- IR cutoff of 2.5, with highest prevalence in phenotype A and least in phenotype D. The overall prevalence of MetS was 36% with a two- to six-fold higher prevalence in hyperandrogenic phenotypes compared to the non-hyperandrogenic phenotype. Highest mean hs- CRP was found in phenotype A which could possibly indicate greater cardiovascular risk in future. Univariate logistic regression for predictive association of MetS parameters was significantly high for deranged parameters i.e. WC≥80cm, fasting plasma glucose ≥100mg/dl, HDL ≤50mg/dl and WHR ≥0.85. Strong positive association was found with all these parameters (p<0.001) Hirsutism (modified Ferriman Gallwey score ≥8) was strongly associated with MetS (p=0.005).

Conclusions An appropriate diagnosis of PCOS and accurate dentification of phenotype is important as it has long-term health implications for women. We recommend screening all hyperandrogenic PCOS women for IR and metabolic abnormalities. This study has shown that HOMA-IR is a valuable tool in identifying PCOS women with metabolic syndrome and also serve to identify PCOS subtype at high risk of future metabolic syndrome.