GENETIC VARIANTS AND METHODS OF SELECTING CONTRACEPTION RELATED TO THE SAME CROSS-REFERENCE TO RELATED APPLICATION [0001] This application claims the benefit of U.S. Provisional Application No.63/186,936 filed on May 11, 2021, the content of which is hereby incorporated herein in its entirety. COPYRIGHT [0002] This disclosure contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure as it appears in the U.S. Patent and Trademark Office patent file or records, but otherwise reserves any and all copyright rights. BACKGROUND [0003] Weight gain remains a rare primary reason for etonogestrel contraceptive implant (NEXPLANON®, Merck & Co., Whitehouse Station NJ) discontinuation [1,2]. However, etonogestrel implant users experience wide inter-individual variability in weight changes [3–7]. The largest study with a non-hormonal comparison group found etonogestrel implant users had a greater mean weight increase (3.0 kg versus 1.1 kg) after 36 months of use, but similarly wide variability in individual weight changes (24 kg to +25 kg versus 18 kg to +20 kg) [3]. Although the average weight gain associated with etonogestrel implant use may not be clinically significant, reproductive-aged women experiencing a 25 kg weight gain likely face additional health risks [8]. [0004] Means to determine the risk of weight gain are currently lacking for an individual considering an etonogestrel implant or other hormonal contraceptive methods, though individual patient characteristics like race can affect this risk [7]. Pharmacogenomics, the study of how genetic variants affect drug metabolism and side effects, may help elucidate if and how individual genetic differences contribute to variability in hormonal drug-related weight gain [9]. For example, studies using pharmacogenomic methods have identified genetic variants associated with antipsychotic drug-related weight gain [10]. [0005] Accordingly, there remains a need for improved methods of selecting, recommending, and/or prescribing contraception for subjects seeking and/or in need of the same. SUMMARY [0006] Aspects of the present inventive concept relate to methods of selecting, recommending, and/or prescribing contraceptives, methods of minimizing side effects associated with a contraceptive selected, recommended, and/or prescribed, methods of administering a contraceptive, and methods of minimizing side effects associated with administering a contraceptive in a subject based on analysis of genetic background/variation possessed by the subject. [0007] According to an aspect of the inventive concept, provided is a method for selecting, recommending, and/or prescribing a contraceptive for a subject including: identifying any genetic variant or genetic variants of, for example, any one gene, or a set of genes including ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses; and selecting, recommending, and/or prescribing the contraceptive depending on the genetic variant or the genetic variants of ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses. In some aspects of the inventive concept, the gene is ESR1, and/or genetic variants thereof. In some aspects of the inventive concept, the gene is CYP2C19, and/or genetic variants thereof. [0008] According to another aspect of the inventive concept, provided is a method of minimizing side effects of a contraceptive selected, recommended, and/or prescribed for a subject including: identifying any genetic variant or genetic variants of, for example, any one gene, or a set of genes including ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses; and selecting, recommending. and/or prescribing the contraceptive depending on the genetic variant or the genetic variants of ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses. In some aspects of the inventive concept, the gene is ESR1, and/or genetic variants thereof. In some aspects of the inventive concept, the gene is CYP2C19, and/or genetic variants thereof. [0009] According to another aspect of the inventive concept, provided is a method of administering a contraceptive to a subject including: identifying any genetic variant or genetic variants of, for example, any one gene, or a set of genes including ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses; and selecting a contraceptive depending on the genetic variant or the genetic variants of ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses; and administering the contraceptive to the subject. In some aspects of the inventive concept, the gene is ESR1, and/or genetic variants thereof. In some aspects of the inventive concept, the gene is CYP2C19, and/or genetic variants thereof. [0010] According to another aspect of the inventive concept, provided is a method of minimizing side effects associated with administering a contraceptive to a subject including: identifying any genetic variant or genetic variants of, for example, any one gene, or a set of genes including ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses; and selecting a contraceptive depending on the genetic variant or genetic variants of ESR1, CYP2C19, CYP3A7, HSD3B1, LRP2, PXR, CYP3A4, and/or CYP2C9, or a combination of more than one thereof the subject possesses; and administering the contraceptive to the subject. In some aspects of the inventive concept, the gene is ESR1, and/or genetic variants thereof. In some aspects of the inventive concept, the gene is CYP2C19, and/or genetic variants thereof. BRIEF DESCRIPTION OF THE DRAWINGS [0011] FIG.1. Histogram of weight change from implant insertion to study enrollment for all 276 participants with available medical records. [0012] FIG.2. Box plots of weight change from implant insertion to study enrollment among participants with the CYP2C19 rs7088784 wild-type genotype (n = 248) compared with CYP2C19 rs7088784 variant carriers (n = 48), excluding those with unknown genotype for this single nucleotide polymorphism (n = 54). The box represents the first and third quartiles with the band inside the box representing the median for each respective group. The whiskers represent the data within 1.5 interquartile range of the upper and lower quartile. Circles indicate outliers with values between 1.5 times and 3 times the IQR and asterisks indicate outliers with values greater than 3 times the IQR. [0013] FIG.3. Box plots of weight change from implant insertion to study enrollment among participants homozygous for the ESR1 rs9340799 variant allele (n = 7) versus carriers of at least one wild-type allele (n = 324), excluding those with unknown genotype for this single nucleotide polymorphism (n = 19). The box represents the first and third quartiles with the band inside the box representing the median for each respective group. The whiskers represent the data within 1.5 interquartile range of the upper and lower quartile. Circles indicate outliers with values between 1.5 times and 3 times the IQR and asterisks indicate outliers with values greater than 3 times the IQR. DETAILED DESCRIPTION [0014] The foregoing and other aspects of the present invention will now be described in more detail with respect to other embodiments described herein. It should be appreciated that the invention can be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. [0015] The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the description of the invention and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Additionally, as used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items and may be abbreviated as "/". [0016] The term "comprise," and its equivalents, as used herein, in addition to its regular meaning, may also include, and, in some embodiments, may specifically refer to the expressions "consist essentially of" and/or "consist of." Thus, the expression "comprise" can also refer to, in some embodiments, the specifically listed elements of that which is claimed and does not include further elements, as well as embodiments in which the specifically listed elements of that which is claimed may and/or does encompass further elements, or embodiments in which the specifically listed elements of that which is claimed may encompass further elements that do not materially affect the basic and novel characteristic(s) of that which is claimed. For example, that which is claimed, such as a composition, formulation, method, system, etc. "comprising" listed elements also encompasses, for example, a composition, formulation, method, kit, etc. "consisting of," i.e., wherein that which is claimed does not include further elements, and a composition, formulation, method, kit, etc. "consisting essentially of," i.e., wherein that which is claimed may include further elements that do not materially affect the basic and novel characteristic(s) of that which is claimed. [0017] The term "about" generally refers to a range of numeric values that one of skill in the art would consider equivalent to the recited numeric value or having the same function or result. For example, "about" may refer to a range that is within ± 1%, ± 2%, ± 5%, ± 10%, ± 15%, or even ± 20% of the indicated value, depending upon the numeric values that one of skill in the art would consider equivalent to the recited numeric value or having the same function or result. Furthermore, in some embodiments, a numeric value modified by the term "about" may also include a numeric value that is "exactly" the recited numeric value. In addition, any numeric value presented without modification will be appreciated to include numeric values "about" the recited numeric value, as well as include "exactly" the recited numeric value. Similarly, the term "substantially" means largely, but not wholly, the same form, manner or degree and the particular element will have a range of configurations as a person of ordinary skill in the art would consider as having the same function or result. When a particular element is expressed as an approximation by use of the term "substantially," it will be understood that the particular element forms another embodiment. [0018] "Administering" and methods of administration of, for example, a contraceptive or contraceptives as described herein are not particularly limited, and any method that would be appreciated by one of skill in the art may be used for administering a contraceptive or contraceptives, such as a progestin-only contraceptive including, but not limited to desogestrel, etonogestrel, levonorgestrel, and/or norethindrone as described herein without departing from the spirit and scope of the inventive concept. In some embodiments, the contraceptive, for example, etonogestrel, may be administered by an implant, such as NEXPLANON®. In some embodiments, the contraceptive may be administered, for example, orally, parenterally, subcutaneously, topically/transdermally, and/or vaginally to the subject. [0019] "Subject" as used herein may be a patient, such as a patient seeking and/or in need of contraception. In some embodiments, the subject is a human; however, a subject of this disclosure can include animal subjects, particularly mammalian subjects such as canines, felines, bovines, caprines, equines, ovines, porcines, rodents (e.g., rats and mice), lagomorphs, primates (including non-human primates), etc., including domesticated animals, companion animals and wild animals for veterinary medicine, for treatment, or for research and development purposes. [0020] The subjects relevant to this disclosure may be human, more particularly female, and may be of any race or ethnicity, including, but not limited to, Caucasian, African-American, Native American, African, Asian, Hispanic, Indian, etc., as well as of combined backgrounds. Although human subjects within the scope of the inventive concept may conceivably be of any age, e.g., newborn, neonate, infant, child, adolescent, adult, and geriatric, embodiments of the inventive concept generally relate to subjects that are adolescent and/or adult female humans subjects, i.e., female human subjects of child-reproducing age, for example, female human subjects between about 15–49 years in age. [0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. [0022] Embodiments of the present inventive concept provide methods of selecting, recommending, and/or prescribing contraceptives, and methods of administering contraceptives to a subject based on genetic variations that the subject may have. Embodiments of the inventive concept include, for example, selecting, recommending, and/or prescribing particular contraceptives dependent on may have, for example, two copies of a variant allele is homozygous in genotype for a genetic variant vs., for example, the wild-type genotype, and/or having one copy of a variant allele, i.e., heterozygous in genotype for a particular gene or particular genes. A subject having a "variant" or "genetic variant" for a particular gene or particular genes, as referred to herein, in some embodiments, means that the subject has: two copies of/is homozygous in genotype for, a genetic variant of the particular gene, as opposed to having a wild-type genotype for the particular gene. Nevertheless, it will also be appreciated that, in some embodiments, a subject having a variant or genetic variant for a particular gene or particular genes may mean that the subject has: one copy of/is heterozygous in genotype for a genetic variant of the particular gene, as opposed to having a wild-type genotype for the particular gene, and, in some embodiments, a subject having a variant or genetic variant for a particular gene or particular genes may mean that the subject has at least one copy of/is either heterozygous or homozygous in genotype for a genetic variant of the particular gene, as opposed to having a wild-type genotype for the particular gene. Genes that are encompassed by the inventive concept include, for example, any one gene, at least one gene, or a set of genes including, but not necessarily limited to: ESR1; CYP2C19; CYP3A7; HSD3B1; LRP2, PXR, CYP3A4, and/or CYPC9, or any combination of more than one thereof, and in some embodiments, identifying any genetic variant or genetic variants thereof that a subject may have. In some embodiments, the gene is ESR1, and/or genetic variants thereof. In some embodiments, the gene is CYP2C19, and/or genetic variants thereof. In some embodiments, the gene is CYP3A7, and/or genetic variants thereof. In some embodiments, the gene is HSD3B1, and/or genetic variants thereof. In some embodiments, the gene is LRP2, and/or genetic variants thereof. In some embodiments, the gene is PXR, and/or genetic variants thereof. In some embodiments, the gene is CYP3A4, and/or genetic variants thereof. In some embodiments, the gene is CYPC9, and/or genetic variants thereof. Genetic variants of these genes include, but are not necessarily limited to, for example: ESR1 rs9340799; CYP2C19 rs7088784; LRP2 rs2075252; HSD3B1 rs7553527; CYP2C19*19; CYP3A7*1C; and PXR rs2471817, CYP3A4*1G (rs2242480); CYP2C9 rs9332238; or a combination of more than one thereof, such as, in some embodiments, CYP2C19*19, CYP3A7*1C, and PXR rs2471817. [0023] Determining, methods of determination of, and methods of identifying, for example, the genotype of a subject and/or identifying any genetic variant or variants a subject may possess may be accomplished/performed by any method available and/or known to one of skill in the art without departing from the spirit and scope of the inventive concept. [0024] In some embodiments, the contraceptive selected, recommended, and/or prescribed may be a hormonal contraceptive. Hormonal contraceptives include hormone active agents such as estrogens and/or progestins, and may be in the form of, for example, combined contraceptives, such as combined oral contraceptives containing both estrogens and progestins ("the pill"); and progestin-only contraceptives, such as pills containing only progestins (progestin-only pills), progestin-only implants, such as the etonogestrel contraceptive implant NEXPLANON®, and the vaginal ring (NUVARING®). In some embodiments, the contraceptive, such as a hormonal contraceptive, that is selected, recommended, and/or prescribed is a progestin-only contraceptive that is and/or includes a progestin, such as, but not limited to, for example, desogestrel, etonogestrel, levonorgestrel, and/or norethindrone. It will be appreciated that selecting, recommending, and/or prescribing a contraceptive to a subject may refer to, in some embodiments, selecting, recommending, and/or prescribing an active agent, such as a progestin, for example, etonogestrel, or the like, as well as may refer to, in some embodiments, selecting, recommending, and/or prescribing compositions, formulations, and/or devices that may deliver/administer said active agent, such as a contraceptive implant, for example, the etonogestrel contraceptive implant NEXPLANON®, as would be understood in the context of the discussion and/or description. [0025] In some embodiments, a contraceptive, such as a progestin, for example, but not limited to desogestrel, etonogestrel, levonorgestrel, and/or norethindrone is selected, recommended and/or prescribed for the subject, and in some embodiments administered to the subject if the subject has, for example, a wild-type genotype for a gene or genes from the set of genes as set forth herein. In some embodiments, the contraceptive selected, recommended, and/or prescribed is a progestin-only contraceptive, such as a progestin-only contraceptive that includes etonogestrel. In some embodiments, the contraceptive selected, recommended, and/or prescribed if the subject has, for example, a wild-type genotype for a gene or genes from the set of genes as set forth herein is etonogestrel. In some embodiments, an alternative contraceptive, such as an alternative contraceptive to, a progestin, for example, but not limited to desogestrel, etonogestrel, levonorgestrel, and/or northindrone is selected, recommended, and/or prescribed for the subject, and in some embodiments administered to the subject if the subject has, for example, a variant genotype for a gene or genes from the set of genes as described herein. The alternative contraceptive selected, recommended, and/or prescribed is not particularly limited. In some embodiments, the alternative contraceptive selected, recommended, and/or prescribed is a non-hormonal contraceptive, such as an IUD, cervical cap, diaphragm, and/or is phexxi. In some embodiments, the IUD selected, recommended and/or prescribed include copper-containing IUDs. However, the IUD selected, recommended, and/or prescribed as an alternative contraceptive to, for example, etonogestrel, may also include, in some embodiments, levonorgestrel-releasing IUDs, in that the much lower systemic hormone release associated with a levonorgestrel-releasing IUD may result in lower side effects than those associated with administration of levonorgestrel/progestins in pill, implant, and/or vaginal ring form. In some embodiments, a contraceptive, such as a hormonal contraceptive, for example, a progestin, such as, but not limited to desogestrel, etonogestrel, levonorgestrel, and/or norethindrone is selected, recommended and/or prescribed for the subject, and in some embodiments administered to the subject if the subject has, for example, a variant genotype for a gene from the set of genes as described herein. In some embodiments, a contraceptive, such as a hormonal contraceptive, for example, a progestin, such as, but not limited to desogestrel, etonogestrel, levonorgestrel, and/or norethindrone is selected, recommended, and/or prescribed for the subject, and in some embodiments administered to the subject if the subject has, for example, a variant genotype for a gene from the set of genes as described herein, in combination a wild-type genotype of another gene or genes from the set of genes as described herein. [0026] In some embodiments, a hormonal contraceptive, such as a hormonal contraceptive, for example, a progestin, such as desogestrel, etonogestrel, levonorgestrel, and/or northindrone is selected, recommended, and/or prescribed for the subject, and in some embodiments administered to the subject if the subject has, for example, a wild-type ESR1 or LRP2 genotype. In some embodiments, a contraceptive, such as a hormonal contraceptive, for example, a progestin, such as desogestrel, etonogestrel, levonorgestrel, and/or northindrone is selected, recommended, and/or prescribed for the subject if the subject has, for example, a variant LRP2 rs2075252 genotype or a CYP2C19 rs7088784 genotype. In some embodiments, a contraceptive, such as a hormonal contraceptive, for example, a progestin, such as desogestrel, etonogestrel, levonorgestrel, and/or northindrone is selected, recommended, and/or prescribed for the subject if the subject has, for example, a wild-type CYP2C19*19, and wild-type PXR rs2471817 genotypes. In some embodiments, a contraceptive, such as a hormonal contraceptive, for example, a progestin, such as desogestrel, etonogestrel, levonorgestrel, and/or northindrone is selected, recommended, and/or prescribed for a subject, and in some embodiments administered to the subject if the subject has a variant CYP3A7*1C genotype and a wild-type CYP2C19*19 genotype. In some embodiments, a contraceptive, such as a hormonal contraceptive, for example, a progestin, such as desogestrel, etonogestrel, levonorgestrel, and/or northindrone is selected, recommended, and/or prescribed for a subject, and in some embodiments administered to the subject if the subject has a variant CYP2C9 rs9332238 genotype. [0027] In some embodiments, an alternative contraceptive, such as an alternative to etonogestrel, such as a non-hormonal contraceptive, is selected, recommended, and/or prescribed, for example, if the subject has a variant ESR1 rs9340799 genotype. In some embodiments, an alternative contraceptive to etonogestrel, such as a non-hormonal contraceptive, is selected, recommended, and/or prescribed for a subject, and in some embodiments administered to the subject, for example, if the subject has a variant LRP2 rs2075252 genotype. In some embodiments, an alternative contraceptive to etonogestrel, such as a non-hormonal contraceptive, is selected, recommended, and/or prescribed, for example, if the subject has a variant HSD3B1 rs7553527 genotype. In some embodiments, an alternative contraceptive to etonogestrel, such as a non-hormonal contraceptive, is selected, recommended, and/or prescribed for a subject, and in some embodiments administered to the subject, for example, if the subject has a variant CYP2C19*19, and variant PXR rs2471817 genotypes. In some embodiments, an alternative contraceptive to etonogestrel, such as a non-hormonal contraceptive, is selected, recommended, and/or prescribed for a subject, and in some embodiments administered to the subject, for example, if the subject has a variant CYP3A4*1G rs2242480 genotype. [0028] Further embodiments of the inventive concept include methods of minimizing side effects, such as, for example, weight gain, mood changes, abnormal bleeding, and/or breast tenderness, of a contraceptive selected, recommended, and/or prescribed for a subject, methods of administering a contraceptive to a subject, and methods of minimizing side effects associated with administering a contraceptive to a subject including selecting, for example, etonogestrel or an alternative to etonogestrel as described herein. [0029] The present invention is more particularly described in the following examples, which is intended to be illustrative only, since numerous modifications and variations therein will be apparent to those skilled in the art. EXAMPLE 1 - ANALYSIS OF THE INFLUENCE OF GENETIC VARIANTS ON WEIGHT GAIN AMONG ETONOGESTREL CONTRACEPTIVE IMPLANT USERS Materials and Methods [0030] This was a retrospective analysis of a parent pharmacogenomic association study [11]. The candidate gene methodology for this study has been previously published [11]. Participants were reproductive aged women (18–45 years old) with an etonogestrel contraceptive implant in place for at least 12 months and no more than 36 months at the time of enrollment (the steady- state period of the implant's pharmacokinetics) [12,13]. Of particular pertinence to this study, the parent study excluded women with a measured body-mass index (BMI) less than 18.5 kg/m ² due to concerns for altered etonogestrel metabolism among underweight women; there was no upper BMI limit. The hypotheses tested in this analysis were pre-specified secondary outcomes of the parent study [11]. The protocol was approved by the Colorado Multiple Institutional Review Board and all participants gave written informed consent before study initiation. Participants were recruited through community advertising and contraceptive clinics at the University of Colorado Anschutz Medical Campus. [0031] At the time of enrollment, participants' height and weight were measured and their BMI was calculated. For all participants, an electronic medical record review was performed to capture their weight at the time of implant insertion if available. The weight change was then calculated from time of implant insertion to study enrollment for participants with documented weight in the electronic medical record for the initial time point. Participants also completed a brief questionnaire to obtain self-reported demographics and side effect information, including if participants had experienced ‘‘weight gain" (yes/no) while using their contraceptive implant. [0032] The full genotyping methodology for this study has been published [11]. See Table 5 for the full list of single nucleotide polymorphisms (SNPs) selected for this study and their reference (rs) ID numbers. Allele and genotype frequencies and Hardy-Weinberg equilibrium calculations were also included in this publication [11]. Ultimately, included 99 genetic variants were included for statistical analysis after excluding nineteen variants not present in this study population and two variants with significant deviation from Hardy-Weinberg equilibrium [11]. The methodology for serum etonogestrel concentration analysis is previously described [11,13]. [0033] IBM SPSS version 25 statistical software was used for these analyses. Descriptive frequencies were performed, and Cohen's kappa coefficient was utilized to determine agreement between objective and subjective weight gain. A simple linear modeling was then conducted to identify genetic variants associated with objective weight change. For multivariable analysis of objective weight change, a generalized linear model was used due to the non-normal distribution of this outcome [14]. In the generalized linear modeling, genetic variants significantly associated with weight change in simple linear modeling (p-value cut-off of 0.05 for inclusion) and the continuous variables of age, BMI, duration of implant use, and serum etonogestrel concentration, and the categorical variables of self-reported race and ethnicity were included. A backward- stepwise approach was utilized to create the final linear model based on Akaike's Information Criterion [15]. Given the multiple hypothesis testing performed using simple logistic regression (99 independent analyses), a Bonferroni corrected p-value cut-off of 5.0 x 10 ^-4 was determined. This corrected p-value was used to determine overall significance for the variables included in the final generalized linear model. The sample size (N = 350) was determined a priori based on the primary outcome of the parent pharmacogenomic study [11]. [0034] Clinical Trial Registration: Clinicaltrials.gov, NCT03092037. Results [0035] The available medical records were reviewed for all 350 participants from the parent study for inclusion in this analysis [11]. Weight at the time of implant insertion was available for 276 participants (78.9%). Table 1 shows pertinent patient characteristics and demographics for these 276 participants. Participants' median age was 22.3 years (range 18.0–39.1) and median duration of implant use was 27.0 months (range 12–36). Approximately 57% reported their ethnicity as Hispanic/Latina and 43% self-reported their race as White or Caucasian. The median BMI at enrollment was 25.8 kg/m ² (range 18.5–48.1). Table 1 demonstrates the BMI categories of participants [8]. The median duration of implant use and median BMI at the time of enrollment were not statistically different between participants from the parent study with or without insertion weight data (Independent-samples median test, p = 0.42 and p = 0.36, respectively). [0036] Simple linear regression was performed to test for genetic associations with objective weight change from contraceptive implant insertion to study enrollment. Seven genetic variants had significant associations (p < 0.05): CYP2C19 rs11568732, AKR1C3 rs12529, ESR1 rs2077647, ESR1 rs2228480, CYP2C19 rs7088784, ESR1 rs9322335, and ESR1 rs9340799. Table 2 shows the unadjusted beta-coefficients for all patient characteristics and demographics and Table 3 contains the unadjusted beta-coefficients for these seven genetic variants. Using generalized linear modeling BMI at time of enrollment and two genetic variants (CYP2C19 rs7088784 and ESR19340799) remained in the final model (Table 4). For every 1 kg/m ² increase in enrollment BMI, the average weight gain from contraceptive implant insertion to study enrollment increased by 0.54 kg. [0037] The median weight change from implant insertion to study enrollment was +3.2 kg (range 27.6 kg to +26.5 kg) with an interquartile range of 8.3. Fig.1 shows the distribution of weight changes. Though only 43.1% (119/276) of participants with objective weight data reported subjective weight gain with the implant, the majority of participants had objective weight gain since implant insertion (73.9%, 204/276). A report of subjective weight gain had only minimal agreement with measured weight gain during implant use (Cohen's kappa = 0.21). [0038] CYP2C19 rs7088784 had an overall variant allele frequency of 8.3% among the participants successfully genotyped for this SNP (n = 296) with 15.9% (n = 47) having one variant allele (heterozygous) and 0.3% (n = 1) having two variant alleles. ESR1 rs9340799 had an overall variant allele frequency of 22.5% among the participants successfully genotyped for this SNP (n = 331) with 40.8% (n = 135) having one variant allele (heterozygous) and 2.1% (n = 7) having two variant alleles (homozygous variant). Participants with at least one CYP2C19 rs7088784 variant allele (carriers) had on average less weight gain compared to participants homozygous for the wild-type genotype (mean weight change +0.97 kg versus +4.28 kg, respectively, Fig.2). Participants with two copies of the ESR1 rs9340799 variant (homozygous variant) on average gained 14.1 kg more weight than participants with at least one wild-type allele (Fig.3). Using a conservative Bonferroni corrected p-value of 5.0 x 10 ^-4 , only the associations with BMI and ESR1 rs9340799 remained statistically significant. [0039] Multivariable logistic regression was also performed to test for genetic associations with subjective weight gain during contraceptive implant use. Given the differences between primary objective weight change outcome and subjective weight gain, these data are presented in EXAMPLE 2. Discussion [0040] This study was undertaken to assess a pharmacogenomic approach could help our understanding of contraceptive-associated weight changes. Among a large, diverse group of etonogestrel contraceptive implant users, unique genetic variants were identified with clinically significant associations for objective weight change. Objective weight changes were found among our participants that closely match the findings of prior studies [2,3]. As measured weight gain has only minimal agreement with reporting subjective weight gain, our study highlights that the perception of weight gain with the contraceptive implant may be inaccurate, which is consistent with previously published data [16]. BMI at time of enrollment was the only non- genetic variable found to be significantly associated with objective weight change while controlling for all other patient characteristics and demographics. [0041] One genetic variant associated with objective weight change in contraceptive implant users that met our conservative threshold for statistical significance was identified: ESR1 rs9340799. Estrogen receptor 1 (ESR1) found on chromosome 6, encodes an estrogen receptor involved in cellular hormone binding and DNA transcription when activated [17]. Though ESR1 rs9340799 is located in the intronic region of ESR1, prior studies have found pharmacogenomic associations between this variant and other medications. Postmenopausal women with the homozygous variant ESR1 rs9340799 genotype (GG) treated with conjugated estrogens and medroxyprogesterone had greater increases in spine bone mineral density as compared to similar women with the homozygous wild-type genotype (AA) [18]. In this same study, women with the homozygous variant genotype (GG) also had smaller decreases in spine bone mineral density when left untreated compared to women with the homozygous wild-type genotype (AA) [18]. These findings demonstrate an increased response to both exogenous and endogenous estrogen among women with the ESR1 rs9340799 variant genotype, supporting an association between this variant and either upregulation of ESR1 transcription or a more responsive estrogen receptor 1 protein. Additional pharmacogenomic studies further support that the ESR1 rs9340799 variant genotype confers an increased clinical response to estrogen agonists [19,20]. [0042] ESR1 rs9340799 has no known associations with obesity or metabolic syndrome and large studies have failed to find a consistent association between any ESR1 SNPs and obesity [21,22]. The negative findings of these studies with the general population lend support to our discovery of a progestin-dependent effect between variants in ESR1 and weight gain. Though etonogestrel has no binding affinity to estrogen receptors [23], research on breast cancer has found that the activated progesterone receptor can directly modulate estrogen receptor 1 transcriptional activity [24]. Thus, these ESR1 intronic variants or an exonic variant in linkage disequilibrium may lead to an estrogen receptor 1 protein with greater sensitivity to this progesterone receptor modulated relationship. As etonogestrel has a high binding affinity to the progesterone receptor (3 times higher than endogenous progesterone) [23], this ligand-mediated effect may be dependent on this increased binding affinity, thus potentially accounting for the lack of association between ESR1 variants and obesity in the absence of exogenous progestins. However, this research on the interplay between the progesterone and estrogen receptors primarily comes from tumor cell lines, which may not accurately reflect the signaling and expression patterns of normal cells [24]. More mechanistic research is needed to elucidate the functional impact of these genetic variants on the transcription and activity of the estrogen receptor 1 protein, particularly as related to interactions with the progesterone receptor. [0043] The other genetic variant found that was associated with objective weight change (CYP2C19 rs7088784). CYP2C19 encodes a metabolic enzyme that may play a role in steroid hormone metabolism, however, this variant was not associated with serum etonogestrel concentrations among our study participants [11]. CYP2C19 rs7088784 currently has no published pharmacogenomic associations. [0044] The major strength of this study was in the selection of SNPs from genes encoding proteins with known involvement in steroid hormone pharmacokinetics and pharmacodynamics. Also, a diverse cohort of contraceptive implant users was able to be recruited, and sufficient power was available to detect significant associations between genetic variants and our outcomes of interest. The participants were also representative of the general population of etonogestrel implant users, being relatively young with a wide distribution in BMI [25]. [0045] The BMI cut-off for the parent study (18.5 kg/m ² ) and exclusion of underweight implant users limits the generalizability of our findings to such women. Underweight women were excluded to avoid issues of altered metabolism for the parent study's primary pharmacokinetic outcome [11]. The lack of a control group also limits our ability to state that these genetic variants have an association with weight change dependent on etonogestrel exposure. As non-hormonal intrauterine device users also demonstrate wide variability in weight changes [3], more research on the genetic variants associated with weight change among both hormonal and non-hormonal contraceptive users is needed to substantiate a progestin-dependent effect. In addition, weight intention (i.e., gain, loss, maintain) was not collected from the participants, and potential confounding due to diet and exercise differences during implant use was not controlled. Only participants with at least 12 months of contraceptive implants use were enrolled, thus limiting data on early implant discontinuers, however ensuring at least 12 months of opportunity for weight changes. Finally, the candidate gene approach used in this study prevented the identifying novel genetic loci associated with progestin-mediated weight changes and did not allow for controlling for population stratification, which is confounding by genetic ancestry. [0046] In this analysis, variants in ESR1 accounted for four of the seven SNPs associated with weight change, all associated with increased objective weight gain. The ESR1 rs9340799 variant, in particular, was associated with both a statistically and clinically significant increase in average weight gain of 14 kg among contraceptive implant users with two copies of this variant allele. Exogenous steroid hormone medications are used for various indications throughout a woman's lifespan. It is imperative to understand how individual genetic variation may influence a woman's risk of adverse weight gain while using them. Our results support the pursuit of definitive mechanistic and clinical research to determine the actual influence of ESR1 variants on progestin-associated weight gain. As our understanding of pharmacogenomics in women's health expands, individualized counseling can be developed that can reduce the incidence of hormone- related adverse effects, improve patient satisfaction, and help prevent future health risks associated with weight gain.

Table 1

Table 2

Table 3 Table 5 List of single nucleotide polymorphisms (SNPs) included in this study

* Information obtained from https://www.ncbi.nlm.nih.gov/snp/ Kitts A, Phan L, Ward M, Holmes JB. The Database of Short Genetic Variation (dbSNP). In: The NCBI Handbook [Internet].2nd ed. Bethesda (MD): National Center for Biotechnology Information (US)2013-. p. The NCBI Handbook [Internet]. References 1. H.B. Croxatto, J. Urbancsek, R. Massai, H.C. Bennink, A. van Beek A multicentre efficacy and safety study of the single contraceptive implant Implanon® Hum Reprod, 14 (1999), pp.976-981. 2. L.M. Lopez, S. Ramesh, M. Chen, A. Edelman, C. Otterness, J. Trussell, et al. Progestin- only contraceptives: effects on weight Cochrane Database Syst Rev, 8 (2016), p. CD008815. 3. L. Bahamondes, V. Brache, M. Ali, N. Habib A multicenter randomized clinical trial of etonogestrel and levonorgestrel contraceptive implants with nonrandomized copper intrauterine device controls: effect on weight variations up to 3 years after placement Contraception, 98 (2018), pp.181-187. 4. U.S. Food and Drug Administration. Drug Development and Drug Interactions: Table of Substrates, Inhibitors, and Inducers, https://www.fda.gov/drugs/drug-interactions-labeling/drug- development-and-drug-interactions-table-substrates-inhibitor s-and-inducers; 2020 [accessed 15 March 2020]. 5. W. Modesto, N. Dal Ava, I. Monteiro, L. Bahamondes Body composition and bone mineral density in users of the etonogestrel-releasing contraceptive implant Arch Gynecol Obstet, 292 (2015), pp.1387-1391. 6. M.E. Romano, D.K. Braun-Courville Assessing weight status in adolescent and young adult users of the etonogestrel contraceptive implant J Pediatr Adolesc Gynecol, 32 (2019), pp. 409-414. 7. Z. Vickery, T. Madden, Q. Zhao, G.M. Secura, J.E. Allsworth, J.F. Peipert Weight change at 12 months in users of three progestin-only contraceptive methods Contraception, 88 (2013), pp.503-508. 8. C.M. Hales, M.D. Carroll, C.D. Fryar, C. Ogden Prevalence of obesity among adults and youth: United Stated, 2015–2016. NCHS data brief, no 288 National Center for Health Statistics, Hyattsville, MD (2017). 9. M. Whirl-Carrillo, E.M. McDonagh, J.M. Hebert, L. Gong, K. Sangkuhl, C.F. Thorn, et al. Pharmacogenomics knowledge for personalized medicine Clin Pharmacol Ther, 92 (2012), pp.414-417. 10. J.P. Zhang, T. Lencz, R.X. Zhang, M. Nitta, L. Maayan, M. John, et al. Pharmacogenetic associations of antipsychotic drug-related weight gain: a systematic review and meta-analysis Schizophr Bull, 42 (2016), pp.1418-1437. 11. A. Lazorwitz, C.L. Aquilante, K. Oreschak, J. Sheeder, M. Guiahi, S. Teal Influence of genetic variants on steady-state etonogestrel concentrations among contraceptive implant users Obstet Gynecol, 133 (2019), pp.783-794. 12. J. Le, C. Tsourounis Implanon: a critical review Ann Pharmacother, 35 (2001), pp.329- 336. 13. A. Lazorwitz, C.L. Aquilante, J. Sheeder, M. Guiahi, S. Teal Relationship between patient characteristics and serum etonogestrel concentrations in contraceptive implant users Contraception, 100 (2019), pp.37-41. 14. C. Feng, H. Wang, N. Lu, T. Chen, H. He, Y. Lu, et al. Log-transformation and its implications for data analysis Shanghai Arch Psychiatry, 26 (2014), pp.105-109. 15. K.P. Burnham, D.R. Anderson Multimodel inference: understanding AIC and BIC in model selection Sociological Methods Res, 33 (2004), pp.261-304. 16. M.F. Gallo, J. Legardy-Williams, T. Hylton-Kong, C. Rattray, A.P. Kourtis, D.J. Jamieson, et al. Association of progestin contraceptive implant and weight gain Obstet Gynecol, 127 (2016), pp.573-576. 17. S. Green, P. Walter, V. Kumar, A. Krust, J.M. Bornert, P. Argos, et al. Human oestrogen receptor cDNA: sequence, expression and homology to v-erb-A Nature, 320 (1986), pp.134- 139. 18. H.W. Deng, J. Li, J.L. Li, M. Johnson, G. Gong, K.M. Davis, et al. Change of bone mass in postmenopausal Caucasian women with and without hormone replacement therapy is associated with vitamin D receptor and estrogen receptor genotypes Hum Genet, 103 (1998), pp. 576-585. 19. V. Dziedziejko, M. Kurzawski, K. Safranow, D. Chlubek, A. Pawlik The effect of ESR1 and ESR2 gene polymorphisms on the outcome of rheumatoid arthritis treatment with leflunomide Pharmacogenomics, 12 (2011), pp.41-47. 20. N.I. Ntukidem, A.T. Nguyen, V. Stearns, M. Rehman, A. Schott, T. Skaar, et al. Estrogen receptor genotypes, menopausal status, and the lipid effects of tamoxifen Clin Pharmacol Ther, 83 (2008), pp.702-710. 21. M. Correa-Rodriguez, J. Schmidt-RioValle, E. Gonzalez-Jimenez, B. Rueda-Medina Estrogen receptor 1 (ESR1) gene polymorphisms and obesity phenotypes in a population of young adults Clin Nurs Res, 27 (2018), pp.936-949. 22. M. Nilsson, I. Dahlman, H. Jiao, J.A. Gustafsson, P. Arner, K. Dahlman-Wright Impact of estrogen receptor gene polymorphisms and mRNA levels on obesity and lipolysis–a cohort study BMC Med Genet, 8 (2007), p.73. 23. H. Kuhl Pharmacology of estrogens and progestogens: influence of different routes of administration Climacteric, 8 (Suppl 1) (2005), pp.3-63. 24. H. Mohammed, I.A. Russell, R. Stark, O.M. Rueda, T.E. Hickey, G.A. Taruli, et al. Progesterone receptor modulates ERalpha action in breast cancer Nature, 523 (2015), pp.313- 317. 25. R.A. Hatcher, J. Trussell, A.L. Nelson, W. Cates, F. Stewart, D. Kowal, et al. Contraceptive technology Ardent Media, Inc, New York (2011). EXAMPLE 2 - THE INFLUENCE OF GENETIC VARIANTS ON WEIGHT GAIN AMONG ETONOGESTREL CONTRACEPTIVE IMPLANT USERS - OBJECTIVE VS. SUBJECTIVE WEIGHT GAIN Methods [0047] For these additional analyses, subjective weight gain responses (yes/no) were utilized from all 350 participants in the parent study [11]. Participants were given a questionnaire at time of enrollment that included a specific question asking if they had experienced "weight gain" while using their contraceptive implant. IBM SPSS® version 25 statistical software was used for these supplemental analyses. Descriptive frequencies were performed and conducted simple logistic regression was conducted to identify genetic variants associated with patient-reported subjective weight gain (yes/no). Multivariable logistic regression analysis was then performed including genetic variants significantly associated with subjective weight gain (p-value cut-off of 0.05 for inclusion) and the continuous variables of age, BMI, duration of implant use, and serum etonogestrel concentration, and the categorical variables of self-reported race and ethnicity. A backward-stepwise conditional approach was then utilized to create our final logistic regression model where all variables were entered into the model initially. variables without significant associations (p<0.05) until a model with maximum log-likelihood value was obtained. Given the multiple hypothesis testing performed using simple logistic regression (99 independent analyses), a Bonferroni corrected p-value cut-off of 5.0x10 ^-4 was determined. This corrected p- value was used to determine overall significance for the variables included in our final logistic regression model. Results [0048] Overall, 41.4% of participants (141/350) reported having experienced "weight gain" during contraceptive implant use. The median BMI at enrollment for all 350 participants was 25.7kg/m ² (range 18.5-52.0). Simple logistic regression was performed with the 99 genetic variants included in this analysis to test for associations with patient-reported weight gain. Five genetic variants had significant associations (p<0.05): CYP3A5 rs15524, CYP3A4 rs2242480 (designated CYP3A4*1G), CYP3A4 rs2246709, CYP3A4 rs4646440, and ESR1 rs9322335. Table 6 shows the crude odds ratios for all patient characteristics and demographics and Table 7 contains the crude odds ratios for these five genetic variants. Using multivariable logistic regression modeling as outlined in the methods, BMI at time of enrollment, Hispanic/Latina ethnicity, and two genetic variants (CYP3A4*1G and ESR1 rs9322335) remained in the final model (Table 8). For every 1kg/m ² increase in enrollment BMI, the odds of reporting weight gain increased by 1.1 times, and participants who self-reported as Hispanic/Latina had 2.7 times the odds of reporting weight gain as compared to all other individuals. [0049] CYP3A4*1G had an overall variant allele frequency of 33.3% among our participants successfully genotyped for this SNP (n=329) with 41% (n=135) having one variant allele (heterozygous) and 12.8% (n=42) having two variant alleles. ESR1 rs9322335 had an overall variant allele frequency of 68.1% among our participants successfully genotyped for this SNP (n=332) with 47.6% (n=158) having one variant allele (heterozygous) and 44.3% (n=147) having two variant alleles (homozygous variant). Participants that had at least one CYP3A4*1G allele (carriers) had 2.6 times the odds of reporting weight gain compared to participants homozygous for the wild-type gene, while participants with two copies of the ESR1 rs9322335 variant (homozygous variant) had 2.7 times the odds of subjective weight gain compared to all other Participants were then sequentially removed. All of these associations remained significant using a Bonferroni corrected p-value cut-off of 5.0x10 ^-4 . [0050] Linkage disequilibrium was evaluated for between ESR1 rs9340799 (SNP associated with objective weight gain) and ESR1 rs9322335 (SNP associated with subjective weight gain) using Ensembl 94 (https://www.ensembl.org/Homo_sapiens/Tools/LD). A D' (coefficient of linkage disequilibrium) of 0.59 and r ² of 0.05 was found between these two SNPs. This D' value indicates at least moderate linkage disequilibrium between these variants, but with a relatively low correlation (r ² ) between the two due to the lower variant allele frequency of ESR1 rs9340799. Thus, these variants are often inherited together, but do not provide identical information. Table 7 Unadjusted associations between all patient characteristics and demographics and subjective weight gain in a study of etonogestrel implant users Performed by simple logistic regression * Each race category was dummy coded for comparison to all other participants † Statistically significant using p-value cut-off <0.05 Table 8 Unadjusted associations between genetic variants and subjective weight gain in a study of etonogestrel implant users Performed by simple logistic regression † Statistically significant using p-value cut-off <0.05 * Genetic variant grouped as participants with two copies of variant allele (homozygous variant) versus all others § Genetic variant grouped as participants with at least one copy of the variant allele (carriers) versus all others Table 9 Adjusted associations between patient characteristics and genetic variants and subjective weight gain in a study of etonogestrel implant users Performed by multivariable logistic regression using a backward-stepwise approach † Statistically significant using Bonferroni corrected p-value cut-off of < 5.0 x 10 ^-4 [0051] The foregoing is illustrative of the present inventive concept and is not to be construed as limiting thereof. Further embodiments of the present inventive concept are exemplified in the following claims.