Assessing the androgenic and metabolic heterogeneity in polycystic ovary syndrome using cluster analysis.

Abstract

Some but not all women with polycystic ovary syndrome (PCOS) develop the metabolic syndrome (MS). The objective of this study was to determine if a subset of women with PCOS had higher androgen levels predisposing them to MSand whether routinely measured hormonal parameters impacted the metabolic syndrome score (siMS). We included data from a discovery (PCOS clinic data) and a replication cohort (Hull PCOS Biobank) and utilized eight routinely measured hormonal parameters in our clinics (free androgen index [FAI], sex hormone-binding globulin, dehydroepiandrosterone sulphate (DHEAS), androstenedione, luteinizing hormone [LH], follicular stimulating hormone, anti-Müllerian hormone and 17 hydroxyprogesterone [17-OHP]) to perform a K-means clustering (an unsupervised machine learning algorithm). We used NbClust Package in R to determine the best number of clusters. We estimated the siMS in each cluster and used regression analysis to evaluate the effect of hormonal parameters on SiMS. The study consisted of 310 women with PCOS (discovery cohort: n = 199, replication cohort: n = 111). The cluster analysis identified two clusters in both the discovery and replication cohorts. The discovery cohort identified a larger cluster (n = 137) and a smaller cluster (n = 62), with 31% of the study participants. Similarly, the replication cohort identified a larger cluster (n = 74) and a smaller cluster (n = 37) with 33% of the study participants. The smaller cluster in the discovery cohort had significantly higher levels of LH (7.26 vs. 16.1 IU/L, p < .001), FAI (5.21 vs. 9.22, p < .001), androstenedione (3.93 vs. 7.56 nmol/L, p < .001) and 17-OHP (1.59 vs.3.12 nmol/L, p < .001). These findings were replicated in the replication cohort. The mean (±SD) siMS score was higher in the smaller cluster, 3.1 (±1.1) versus 2.8 (±0.8); however, this was not statistically significant (p = .20). In the regression analysis, higher FAI (β = .05, p = .003) and androstenedione (β = .03, p = .02) were independently associated with a higher risk of SiMS score, while higher DHEAS levels were associated with a lower siMS score (β = -.07, p = .03) CONCLUSION: We identified a subset of women in our PCOS cohort with significantly higher LH, FAI, and androstenedione levels. We show that higher levels of androstenedione and FAI are associated with a higher siMS, while higher DHEAS levels were associated with lower siMS.