Molecular Assessment of Proadipogenic Effects for Common-Use Contraceptives and Their Mixtures

Yu-Ting Tiffany Chiang, Christopher D Kassotis
Endocrinology, Volume 165, Issue 6, June 2024, bqae050
https://doi.org/10.1210/endocr/bqae050

Abstract

Hormonal contraceptives are widely prescribed due to their effectiveness and convenience and have become an integral part of family planning strategies worldwide. In the United States, approximately 65% of reproductive-aged women are estimated to be using contraceptive options, with approximately 33% using one or a combination of hormonal contraceptives. While these methods have undeniably contributed to improved reproductive health, recent studies have raised concerns regarding their potential effect on metabolic health. Despite widespread anecdotal reports, epidemiological research has been mixed as to whether hormonal contraceptives contribute to metabolic health effects. As such, the goals of this study were to assess the adipogenic activity of common hormonal contraceptive chemicals and their mixtures. Five different models of adipogenesis were used to provide a rigorous assessment of metabolism-disrupting effects. Interestingly, every individual contraceptive (both estrogens and progestins) and each mixture promoted significant adipogenesis (e.g., triglyceride accumulation and/or preadipocyte proliferation). These effects appeared to be mediated in part through estrogen receptor signaling, particularly for the contraceptive mixtures, as cotreatment with fulvestrant acted to inhibit contraceptive-mediated proadipogenic effects on triglyceride accumulation. In conclusion, this research provides valuable insights into the complex interactions between hormonal contraceptives and adipocyte development. The results suggest that both progestins and estrogens within these contraceptives can influence adipogenesis, and the specific effects may vary based on the receptor disruption profiles. Further research is warranted to establish translation of these findings to in vivo models and to further assess causal mechanisms underlying these effects.

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