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

Deshmukh, Harshal; Akbar, Shahzad; Bhaiji, Amira; Saeed, Yamna; Shah, Najeeb; Adeleke, Kazeem; Papageorgiou, Maria; Atkin, Stephen; Sathyapalan, Thozhukat

Abstract

Introduction: 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 MS and whether routinely measured hormonal parameters impacted the metabolic syndrome score (siMS). Methods: 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. Results: 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.

Citation

Deshmukh, H., Akbar, S., Bhaiji, A., Saeed, Y., Shah, N., Adeleke, K., Papageorgiou, M., Atkin, S., & Sathyapalan, T. (2023). Assessing the androgenic and metabolic heterogeneity in polycystic ovary syndrome using cluster analysis. Clinical Endocrinology, 98(3), 400-406. https://doi.org/10.1111/cen.14847

• Journal Article Type: Article
• Acceptance Date: Nov 7, 2022
• Online Publication Date: Nov 13, 2022
• Publication Date: 2023-03
• Deposit Date: Jan 12, 2023
• Publicly Available Date: Nov 14, 2023
• Journal: Clinical Endocrinology
• Print ISSN: 0300-0664
• Electronic ISSN: 1365-2265
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 98
• Issue: 3
• Pages: 400-406
• DOI: https://doi.org/10.1111/cen.14847
• Keywords: Androstenedione; Clusters; DHEAS; FAI; Ovary; PCOS
• Public URL: https://hull-repository.worktribe.com/output/4136038