To identify genetic variants that influence steady-state etonogestrel concentrations among contraceptive implant users.
We enrolled healthy, reproductive-age women in our pharmacogenomic study using etonogestrel implants for 12–36 months without concomitant use of hepatic enzyme inducers or inhibitors. We collected participant characteristics, measured serum etonogestrel concentrations, and genotyped each participant for 120 single nucleotide variants in 14 genes encoding proteins involved in steroid hormone (ie, estrogens, progestins) metabolism, regulation, or function. We performed generalized linear modeling to identify genetic variants associated with steady-state etonogestrel concentrations.
We enrolled 350 women, who had a median serum etonogestrel concentration of 137.4 pg/mL (range 55.8–695.1). Our final generalized linear model contained three genetic variants associated with serum etonogestrel concentrations: NR1I2(PXR) rs2461817 (β=13.36, P=.005), PGR rs537681 (β=−29.77, P=.007), and CYP3A7*1C (β=−35.06, P=.025). Variant allele frequencies were 69.4%, 84.9%, and 5.1%, respectively. Our linear model also contained two nongenetic factors associated with etonogestrel concentrations: body mass index (BMI) (β=−3.08, P=7.0×10−7) and duration of implant use (β=−1.60, P=5.8×10−5); R2 for the model =0.17.
Only BMI and duration of implant use remained significantly associated with steady-state etonogestrel concentrations. Of the three novel genetic associations found, one variant associated with increased etonogestrel metabolism (CYP3A7*1C) causes adult expression of fetal CYP3A7 proteins and can consequently alter steroid hormone metabolism. Women with this variant may potentially have increased metabolism of all steroid hormones, as 27.8% (5/18) of CYP3A7*1C carriers had serum etonogestrel concentrations that fell below the threshold for consistent ovulatory suppression (less than 90 pg/mL). More pharmacogenomic investigations are needed to advance our understanding of how genetic variation can influence the effectiveness and safety of hormonal contraception, and lay the groundwork for personalized medicine approaches in women's health.
Some genetic variants, such as those influencing cytochrome P450 enzyme function, can affect steroid hormone drug concentrations and may decrease the efficacy of hormonal contraceptive methods.
Division of Family Planning, Department of Obstetrics and Gynecology, and the Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
Corresponding author: Aaron Lazorwitz, MD, MSCS, Division of Family Planning, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, 12631 E 17th Ave, B198-6, Aurora, CO 80045; email: Aaron.firstname.lastname@example.org.
Supported by the Society of Family Planning Research Fund (Grant number SFPRF17-3). This work was also supported by NIH/NCATS Colorado CTSA Grant Number UL1 TR001082. Contents are the authors' sole responsibility and do not necessarily represent official NIH views.
Financial Disclosure Dr. Teal has served on scientific advisory boards of Allergan and Bayer Healthcare, and serves on a Data Monitoring Board for a study funded by Merck and Co. Dr. Teal and Dr. Lazorwitz receive research funding from Merck and Co. for an Investigator Initiated Study on drug–drug interactions with the etonogestrel contraceptive implant. The University of Colorado, Department of Obstetrics and Gynecology has received research funding from Bayer, Agile Therapeutics, Merck and Co, and Medicines360. Dr. Guiahi's time was supported by the Society of Family Planning Junior Investigator Career Grant SFPRF10-JI1. The other authors did not report any potential conflicts of interest.
Presented at the North American Forum on Family Planning, October 20–22, 2018, New Orleans, Louisiana.
The authors thank Dr. Serge Cremers at the Biomarkers Core Laboratory at Columbia University for assisting with the etonogestrel analysis and Dr. Derek Warner at the Genomics Core Facility at the University of Utah for assisting with the genotyping.
Peer reviews and author correspondence are available at http://links.lww.com/AOG/B321.