Aaron Lazorwitz1, Eva Dindinger2, Margaret Harrison3, Christina L Aquilante4, Jeanelle Sheeder5, Stephanie Teal6. 1. University of Colorado Anschutz Medical Campus, Department of Obstetrics and Gynecology, Division of Family Planning, 12631 E 17th Ave, B198-2, Aurora, CO 80045, USA. Electronic address: aaron.lazorwitz@cuanschutz.edu. 2. University of Colorado Anschutz Medical Campus, Department of Obstetrics and Gynecology, Division of Family Planning, 12631 E 17th Ave, B198-2, Aurora, CO 80045, USA. Electronic address: eva.dinginder@cuanschutz.edu. 3. University of Colorado Anschutz Medical Campus, Department of Obstetrics and Gynecology, Division of Family Planning, 12631 E 17th Ave, B198-2, Aurora, CO 80045, USA. Electronic address: Margaret.harrison@cuanschutz.edu. 4. University of Colorado Anschutz Medical Campus, Skaggs School of Pharmacy and Pharmaceutical Sciences, Department of Pharmaceutical Sciences, 12850 E Montview Blvd, Aurora, CO 80045, USA. Electronic address: Christina.aquilante@cuanschutz.edu. 5. University of Colorado Anschutz Medical Campus, Department of Obstetrics and Gynecology, Division of Family Planning, 12631 E 17th Ave, B198-2, Aurora, CO 80045, USA. Electronic address: jeanelle.sheeder@cuanschutz.edu. 6. University of Colorado Anschutz Medical Campus, Department of Obstetrics and Gynecology, Division of Family Planning, 12631 E 17th Ave, B198-2, Aurora, CO 80045, USA. Electronic address: Stephanie.teal@cuanschutz.edu.
Abstract
OBJECTIVE: To identify genetic variants associated with weight gain related to etonogestrel contraceptive implant use. STUDY DESIGN: We conducted a retrospective analysis from a parent pharmacogenomic study of healthy, reproductive-aged women using etonogestrel implants. We reviewed medical records to calculate objective weight changes from implant insertion to study enrollment and asked participants about subjective weight gain (yes/no) during contraceptive implant use. We used genotyping data (99 genetic variants) from the parent study to conduct backward-stepwise generalized linear modeling to identify genetic variants associated with objective weight changes. RESULTS: Among 276 ethnically diverse participants, median body-mass index (BMI) was 25.8 kg/m2 (range 18.5-48.1). We found a median weight change of +3.2 kg (range -27.6 to +26.5) from implant insertion to study enrollment. Report of subjective weight gain had minimal agreement with measured weight gain during implant use (Cohen's kappa = 0.21). Our final generalized linear model contained two variables associated with objective weight change that met conservative statistical significance (p < 5.0 × 10-4). Participants with two copies (homozygous) of the ESR1 rs9340799 variant on average gained 14.1 kg more than all other participants (p = 1.4 × 10-4). Higher enrollment BMI was also associated with objective weight gain (β = 0.54, p = 9.4 × 10-12). CONCLUSION: Genetic variants in the estrogen receptor 1 (ESR1) do not have known associations with obesity or metabolic syndrome, but there is physiologic plausibility for a progestin-mediated genetic association between ESR1 and weight gain. Additional genetic research is needed to substantiate our findings and elucidate further advances in individualized counseling on the risk of weight gain with exogenous steroid hormones. IMPLICATIONS: Genetic variation in the estrogen receptor 1 gene may account for variability in weight gain among etonogestrel contraceptive implant users. If these findings can be replicated with other progestin-containing medications, we may be able to better individualize contraceptive counseling.
OBJECTIVE: To identify genetic variants associated with weight gain related to etonogestrel contraceptive implant use. STUDY DESIGN: We conducted a retrospective analysis from a parent pharmacogenomic study of healthy, reproductive-aged women using etonogestrel implants. We reviewed medical records to calculate objective weight changes from implant insertion to study enrollment and asked participants about subjective weight gain (yes/no) during contraceptive implant use. We used genotyping data (99 genetic variants) from the parent study to conduct backward-stepwise generalized linear modeling to identify genetic variants associated with objective weight changes. RESULTS: Among 276 ethnically diverse participants, median body-mass index (BMI) was 25.8 kg/m2 (range 18.5-48.1). We found a median weight change of +3.2 kg (range -27.6 to +26.5) from implant insertion to study enrollment. Report of subjective weight gain had minimal agreement with measured weight gain during implant use (Cohen's kappa = 0.21). Our final generalized linear model contained two variables associated with objective weight change that met conservative statistical significance (p < 5.0 × 10-4). Participants with two copies (homozygous) of the ESR1rs9340799 variant on average gained 14.1 kg more than all other participants (p = 1.4 × 10-4). Higher enrollment BMI was also associated with objective weight gain (β = 0.54, p = 9.4 × 10-12). CONCLUSION: Genetic variants in the estrogen receptor 1 (ESR1) do not have known associations with obesity or metabolic syndrome, but there is physiologic plausibility for a progestin-mediated genetic association between ESR1 and weight gain. Additional genetic research is needed to substantiate our findings and elucidate further advances in individualized counseling on the risk of weight gain with exogenous steroid hormones. IMPLICATIONS: Genetic variation in the estrogen receptor 1 gene may account for variability in weight gain among etonogestrel contraceptive implant users. If these findings can be replicated with other progestin-containing medications, we may be able to better individualize contraceptive counseling.
Authors: M Whirl-Carrillo; E M McDonagh; J M Hebert; L Gong; K Sangkuhl; C F Thorn; R B Altman; T E Klein Journal: Clin Pharmacol Ther Date: 2012-10 Impact factor: 6.875
Authors: Hisham Mohammed; I Alasdair Russell; Rory Stark; Oscar M Rueda; Theresa E Hickey; Gerard A Tarulli; Aurelien A Serandour; Aurelien A A Serandour; Stephen N Birrell; Alejandra Bruna; Amel Saadi; Suraj Menon; James Hadfield; Michelle Pugh; Ganesh V Raj; Gordon D Brown; Clive D'Santos; Jessica L L Robinson; Grace Silva; Rosalind Launchbury; Charles M Perou; John Stingl; Carlos Caldas; Wayne D Tilley; Jason S Carroll Journal: Nature Date: 2015-07-08 Impact factor: 49.962
Authors: Aaron Lazorwitz; Christina L Aquilante; Jonathan A Shortt; Jeanelle Sheeder; Stephanie Teal; Christopher R Gignoux Journal: Clin Transl Sci Date: 2021-05-02 Impact factor: 4.689