Phenotyping of Indian Polycystic Ovarian Syndrome on the basis of Biochemical Parameters: A retrospective analysis via Hierarchical Cluster Classification

ABSTRACT Objective We aimed to phenotype the Indian PCOS population based on their etiology for an effective treatment regimen. Design Retrospective analysis of biochemical data. Setting PCOS clinics in Tamil Nadu, India Population or Sample Girls and women in age group 18 to 30 diagnosed as PCOS by RC. Method The statistical analysis was done using two-way cluster analysis function of SPSS v.22 to identify the phenotypes and the resolving biochemical parameter. Also, the population was segregated into three cohorts based on their age for further analysis. Main outcome measure Endocrine parameters like LH, FSH, estradiol, testosterone and thyroid profile. Biochemical parameters like complete lipid profile, blood glucose and insulin fasting. Body Mass Index (BMI). Results The statistical analysis reported two phenotypes among the Indian PCOS population, segregated based on their LH: FSH ratio. The phenotype with LH: FSH >2, had a hormonal imbalance and may have its etiology from Hypothalamus – Pituitary - Ovarian axis. The phenotype with LH: FSH < 2 had significant markers indicating the incidence of metabolic syndrome and may follow an insulin – dependent pathway for PCOS manifestation. Conclusion The PCOS population needs a comprehensive screening before deciding on a treatment regimen. All the PCOS patients need to be recommended to follow an active lifestyle since 80% of them are predisposed to a metabolic syndrome in their later ages.