Pharmacogenomics in Pregnancy

Abstract

Objective:

Pregnant women frequently take prescription and over the counter medications. The efficacy of medications is affected by the many physiological changes during pregnancy, and these events may be further impacted by genetic factors.

Findings:

Research on pharmacogenomic and pharmacokinetic influences on drug disposition during pregnancy has lagged behind other fields. Clinical investigators have demonstrated altered activity of several drug metabolizing enzymes during pregnancy. Emerging evidence also supports the influence of pharmacogenomic variability in drug response for many important classes of drugs commonly used in pregnancy.

Conclusion:

Prescribing medications during pregnancy requires an understanding of the substantial dynamic physiologic and metabolic changes that occur during gestation. Pharmacogenomics also contributes to the inter-individual variability in response to many medications, and more research is needed to understand how best to manage drug therapy in pregnant women.

Inter-individual variability in drug response is a central feature of all pharmacotherapies administered to healthy persons. Physiological changes during pregnancy amplify drug response variability, which creates challenges to effective and safe use of drugs. In addition to physiological changes, variants in genes encoding proteins involved with absorption, metabolism and elimination of drugs, or in genes coding for drug targets, contribute substantially to variable efficacy and differing susceptibilities to adverse reactions. The emerging discipline of pharmacogenomics seeks to understand the impact of genetic variation on drug responses and promote an individualized approach to treatments. Investigating pharmacogenomics in pregnancy represents an important research opportunity. This article highlights basic principles of pharmacogenomics and reviews the state of knowledge in the application of these principles to the pregnant condition.

Principles of pharmacogenetics and pharmacogenomics

The term pharmacogenetics was originally coined as the study of unusual drug response traits exhibiting Mendelian inheritance in families. Specific examples include glucose-6-phosphate dehydrogenase deficiency, pseudocholinesterase deficiency, and malignant hyperthermia susceptibility. By contrast, the concept of pharmacogenomics has emerged from population-based studies defining genes or genomic loci associated with differences in drug responses among groups of unrelated individuals. Although these terms have mostly historical importance and reflect distinct gene discovery paradigms, one could define pharmacogenetics as the study of drug response phenotypes determined largely by single genes, whereas pharmacogenomics relates to the study of drug responses influenced by multiple genes.

The clinical application of pharmacogenomics holds great promise for promoting personalized therapy and precision medicine. Rather than a ‘one-size-fits-all’ approach to prescribing medications, the use of genomic information obtained from individuals can improve the likelihood of effective treatment and lower risks for adverse drug reactions (ADRs), a major cause of mortality. More than 125 drugs approved by the Food and Drug Administration (FDA) have pharmacogenomic information in their product labeling, including some with ‘boxed warnings’ advising physicians to acquire specific genomic data on patients for whom the drug is being considered. The Clinical Pharmacogenetics Implementation Consortium (CPIC) formed by the NIH-funded Pharmacogenomics Research Network¹ has developed a series of evidence-based, consensus guidelines to enable the translation of clinical genetic test results into actionable prescribing decisions for specific drugs.^2–14

Strategies for implementing pharmacogenomics in clinical settings have either adopted a one gene at a time approach (e.g., test for genetic variants relevant to each prescribed drug)^15,16 or advocated for preemptive testing of multiple variants.^17–19 Clinical decision support has been demonstrated to be essential for educating providers about interpretation of test results and for presenting specific prescribing actions. Physician adoption and utilization of pharmacogenomics testing can be high in settings where point-of-care decision support is provided,²⁰ but somewhat less effective when results are delivered to providers several days later.²¹ Randomized clinical trials and other experimental designs to determine the value of pharmacogenomics in clinical practice are emerging.

Genetically-based variability in drug responses (efficacy or toxicity) is often explained by genes affecting the plasma drug concentration (pharmacokinetics) or its direct effects on the intended molecular target (pharmacodynamics). Variability in pharmacokinetics is most often due to genetic variation in genes encoding drug metabolizing enzymes important for either biotransformation or elimination of drugs. Additional risk for adverse drug reactions can sometimes be attributed to genes contributing to immune hypersensitivity.

Genetic variability in drug metabolizing enzymes gives rise to subsets of patients in whom different levels of drug metabolizing capacity are evident (e.g., normal or extensive, poor, ultra-rapid, and intermediate metabolizers) with consequences for effectiveness and risk for toxicity depending on the type of drug (Table 1). For example, a poor metabolizer of a standard drug (e.g., the administered form of the drug is active), may be at greater risk for toxicity owing to inefficient elimination of the active drug from the circulation. By contrast, a poor metabolizer of a prodrug (e.g., a precursor form of the drug is administered), may have a poor response owing to the insufficient activation of the precursor compound.

Table 1.

Consequences of various drug metabolizer phenotypes.

Phenotype	Standard Drugs	Pro-drugs
Normal	Performs according to FDA label
Poor	Decreased elimination rate Increased toxicity risk	Decreased activation Reduced effectiveness
Intermediate	Potential for increased toxicity	Possible reduced effectiveness
Rapid/Ultra-rapid	Increased elimination rate Reduced effectiveness	Increased activation Increased toxicity risk

There are several hundred known genetic variants in genes encoding drug metabolizing enzymes and a standard nomenclature has been developed. For cytochrome P450 enzymes, the gene symbol (for example: CYP2D6) is followed by an asterisk or ‘star’ (*) and an Arabic number (1,2,3, etc.) to designate the specific allele. The notation *1 designates the reference allele, which encodes the enzyme having a standardized level of activity. Other notations (*2, *3, *4, etc.) represent variant alleles. Many variant alleles are single nucleotide polymorphisms (SNPs), but others consist of multiple SNPs arranged in haplotypes. More complex sequence differences such as copy number variations (CNVs) in which entire genes are deleted or duplicated may also comprise certain alleles. An extensive database of known P450 gene variants is available (http://www.cypalleles.ki.se/). Several other gene families contribute to inter-individual variability in drug responses. These other families include genes encoding enzymes responsible for glucuronidation of drugs or their metabolites to facilitate elimination, and drug transporters that mediate movement of drugs across cellular barriers.

Drug metabolism during pregnancy

Pregnancy is a time of substantial endocrine and physiological change. Hormonal shifts, expanded plasma volume, increased renal clearance, changes in protein binding and hepatic metabolism all support the concept that pregnant women represent a special population. Chemical modification by cytochrome P450 enzymes and glucuronidation are major metabolic pathways for drug metabolism occurring primarily in the liver. Many medications utilize one or both for metabolism, and enzyme activities can vary during pregnancy due to hormonal influences. For example, glucuronidation is the major pathway of metabolism for lamotrigine. Estrogen, a potent inducer of uridine diphosphate-glucuronosyltransferase (UGT)1A4,²² is increased during pregnancy and contributes to decreasing lamotrigine concentrations during pregnancy²³ and with concurrent use of estrogen containing contraceptives.²⁴ A similar mechanism has been described with progesterone induced metabolism at UGTA1, which is involved in the metabolism of labetalol.²⁵

CYP3A4 is the most abundant CYP²⁶ and is involved in the metabolism of more than half of all approved drugs.²⁷ CYP3A4 has been noted to have increased activity during pregnancy, as has been demonstrated in the use of nifedipine for the treatment of hypertension during pregnancy.²⁸ CYP2D6 is a common hepatic metabolic pathway and is involved in the metabolism of an estimated 25% of medications including many that are commonly prescribed to pregnant women.²⁹ CYP2D6 metabolism is influenced by pregnancy^30–32 with its activity beginning to rise in the second trimester and continuing to increase into the third trimester.³² Women who are CYP2D6 extensive metabolizers have demonstrated higher enzymatic activity during pregnancy.³⁰ Conversely, women who are CYP2D6 poor metabolizers have lower enzymatic activity throughout pregnancy.³³ The CYP2D6 metabolizer status may impact the efficacy of medications commonly prescribed to pregnant women.

CYP1A2 and CYP2C19 have been associated with lower activity during pregnancy.^{32, 34, 35} CYP1A2 is important for the metabolism several psychiatric and asthma medications as well as caffeine. Women in their third trimester of pregnancy have a 65% lower metabolism of caffeine compared to their non-pregnant, postpartum state.³⁶ Pregnancy has an inhibitory effect on CYP2C19 extensive metabolizers,³⁷ although not yet studied, this could potentially impact the efficacy of omeprazole and other proton-pump inhibitors used during pregnancy.³⁵

There is substantial genetic variability in metabolism mediated by the CYP systems which contributes to the inter-individual variability in drug responses and may contribute to inconsistent risks for drug-related adverse events. Genetic testing is available to evaluate an individual’s genotype of specific CYP genes. Clinicians must understand when pharmacogenomic information is be clinically actionable and be able to properly interpret pharmacogenomic test results.

Applications of pharmacogenomics in pregnancy

Understanding pharmacogenetic liability is especially important, given that medication use during pregnancy is common and increasing. Approximately 80% of women take at least one medication (prescription or over the counter, not including vitamins or iron) during the first trimester.³⁸ Polypharmacy is also common and nearly 30% of women have exposure to four or more medications (prescription or over the counter) during the first trimester.³⁸ Antibiotics, antiemetics, and medications used to treat chronic conditions such as asthma, depression, anxiety, hypothyroidism, and pain are among the most common prescription medications during pregnancy.^{38, 39} Many of these medications carry known pharmacogenomic liabilities according to FDA drug labeling and CPIC guidelines (Table 2). FDA labeling is designed to alert clinicians to potential treatment concerns based on pharmacogenomic information and, in some instances, alert clinicians to when to obtain genetic testing prior to prescribing a medication. CPIC guidelines are designed to help clinicians understand how to use available genetic information to maximize efficacy and decrease the likelihood of adverse events. At this time, there are no prescribing guidelines specific to pharmacogenomics and pregnancy.

Table 2.

Pharmacogenomic liability of medications commonly prescribed during pregnancy

Medication Class	Medication	Biomarker	Associated pharmacogenetic liability
Antimicrobials	Nitrofurantoina	Gluocose-6-phosphatedhydrogenasedeficiency) G6PD	Hemolytic anemia risk
Antidepressants	Citalopram/escitalopramb,(50)	CYP2C19	CYP2C19 ultrarapid metabolizers have lower plasma concentrations, increasing likelihood of treatment failure.
			CYP2C19 poor metabolizers have higher plasma concentrations; consider a 50% reduction of starting dose.
	Paroxetineb,(50)	CYP2D6	CYP2D6 ultrarapid metabolizers have lower plasma levels, increasing the probability of treatment failure.
			CYP2D6 Intermediate and poor metabolizers may have higher plasma concentrations and an increased risk of side effects. Consider a 50% reduction of starting dose in poor metabolizers.
Antiepileptics	Carbamazepinea	HLA	HLA-B*15:02 is associated with greater risk of Stevens-Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN)
			HLA-A*31:01 is associated with greater risk of maculopapular exanthema, drug reaction with eosinophilia, and SJS/TEN
	Oxcarbazepinea	HLA	HLA-B*15:02 is associated with greater risk of Stevens-Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN)
Antihypertensives	Metoprolola	CYP2D6	Poor metabolizers and extensive metabolizers who concomitantly use CYP2D6 inhibiting drugs will have increased metoprolol levels
Gastroenterology	Metoclopramidea	CYP2D6	CYP2D6 Poor metabolizers at are at potentially increased risk of dystonic and other adverse reactions. Lower maximum daily dose recommended in CYP2D6 metabolizers.
	Omeprazolea	CYP2C19	Systemic exposure to omeprazole varies with patient’s metabolism status at CYP2C19
	Ondansteronb,(44)	CYP2D6	Increased metabolism in CYP2D6 ultrarapid metabolizers, associated with decreased response to medication
Opioids	Codeinea,b,(12)	CYP2D6	CYP2D6 Ultra-rapid metabolizers can have higher than expected serum morphine levels, leading to respiratory depression. Ultra-rapid metabolizers may have higher levels of morphine in breastmilk, leading to infant respiratory depression.
	Codeinea	UGTB7*2	Infants who are breastfeeding and have the UGTB7*2 genotype have potentially reduced activity. In combination with a mother who is an ultrarapid metabolizer, this may lead to toxicity of morphine in the infant.

^aFDA Pharmacogenomic biomarkers in drug labeling: https://www.fda.gov/Drugs/ScienceResearch/ucm572698.htm

^bCPIC guidelines: https://cpicpgx.org/guidelines/

⁽ⁿ⁾Correlates to reference number in bibliography

Commonly used medications during pregnancy with pharmacogenomic liability

Opioids.

Codeine, hydromorphone, and tramadol are commonly prescribed oral analgesics administered as prodrugs. Activation to more potent analgesic drugs occurs by drug metabolism. For example, CYP2D6 converts codeine to morphine. Women who are CYP2D6 poor metabolizers may experience poor therapeutic responses to codeine, whereas CYP2D6 ultrarapid metabolizers may be at risk for toxicity including respiratory depression due to rapid elevation of morphine in plasma. This is clinically relevant during breastfeeding when the higher plasma concentration of morphine may be transferred to the infant.¹² There are case reports of infant respiratory depression associated with maternal codeine use in mothers who are CYP2D6 ultrarapid metabolizers.⁴⁰ Guidelines now recommend limited use or avoidance of codeine postpartum^{41, 42} and consideration for maternal genotyping.⁴¹ Tramadol undergoes similar conversion to an active metabolite by CYP2D6 and caries the same concerns regarding maternal CYP2D6 ultrarapid metabolizers.⁴²

Antiemetics.

Ondansetron is frequently prescribed for pregnancy associated nausea. The drug is normally metabolized by CYP3A4, CYP1A2, and CYP2D6. Decreased efficacy of ondansetron has been described in CYP2D6 ultrarapid metabolizers.⁴³ CPIC guidelines note this concern and suggest considering an alternative antiemetic in these individuals.⁴⁴ Interestingly, the FDA does not share this concern and describes CYP2D6 as having a minor role in ondansetron metabolism and notes that the pharmacokinetics of intravenous ondansetron did not differ between CYP2D6 poor and extensive metabolizers.⁴⁵ Metoclopramide is also used during pregnancy for nausea control. Individuals who are CYP2D6 poor metabolizers have slower elimination of metoclopramide and may be at risk for side effects including dystonic reactions.⁴⁶ At a minimum, practitioners should be aware if patients have had prior pharmacogenomic testing so that they can provide appropriate anticipatory guidance to patients around medication efficacy and side effects.

Antihypertensives.

Metoprolol is a commonly used antihypertensive that is metabolized primarily by CYP2D6. As drug clearance increases during pregnancy, metoprolol is eliminated more rapidly and puts women at risk for breakthrough hypertension.^47,48 This decreased efficacy may be especially notable for patients who are CYP2D6 ultrarapid metabolizers. The FDA also notes that individuals who are CYP2D6 poor metabolizers have higher plasma metoprolol concentrations, and this may be associated with less cardioselectivity and potentially a higher frequency of side effects.⁴⁹ Clonidine and propranolol are also metabolized by CYP2D6 and are subject changes in concentration and efficacy during pregnancy.

Antidepressants.

Ververs and colleagues investigated associations of CYP2D6 genotype with plasma paroxetine levels in pregnant women taking this antidepressant medication.³³ Extensive and ultra-rapid metabolizers for CYP2D6 demonstrated decreasing paroxetine concentrations over time during pregnancy. Intermediate and poor metabolizers demonstrated increasing concentrations during pregnancy. In extensive and ultra-rapid metabolizers, lower concentrations of paroxetine were associated with more frequent depressive symptoms. Consistent with this, CPIC guidelines suggest that individuals who are CYP2D6 ultrarapid metabolizers are at greater risk of treatment failure due to low plasma concentrations of paroxetine.⁵⁰ CPIC guidelines also note that individuals who are CYP2D6 poor metabolizers may be at risk for medication-related side effects secondary to higher plasma concentrations and suggest reducing the starting dose of paroxetine by 50% for those individuals.⁵⁰ Importantly, these guidelines are not specifically for pregnant women.

Fluoxetine has also demonstrated CYP2D6 dependent changes in concentration during pregnancy.⁵¹ Fluoxetine is metabolized by n-demethylation to norfluoxetine, which is also pharmacologically active.^{52, 53} Fluoxetine dosed at 20 mg to 40 mg daily during pregnancy has been associated with low fluoxetine and norfluoxetine concentrations, suggesting a vulnerability for relapse of depressive symptoms during pregnancy.⁵¹

Other antidepressants have been classified as having actionable or informative prescribing data based on patient genotype. Citalopram and the related drug escitalopram are primarily metabolized by CYP2C19. CPIC guidelines note that CYP2C19 intermediate and poor metabolizers have reduced metabolism (implying lower rate of elimination) of citalopram and escitalopram. The guidelines suggest that poor metabolizers initiate treatment at 50% of the recommended starting dose.⁵⁰ Amitriptyline is a tricyclic antidepressant metabolized by CYP2C19 to nortriptyline. The activity of CYP2C19 impacts the ratio of amitriptyline to nortriptyline and may influence the clinical response and tolerability. For CYP2C19 poor metabolizers, CPIC guidelines recommend considering an alternative to amitriptyline or considering a 50% dose reduction of starting dose and monitoring drug concentrations.⁵⁴ CYP2C19 ultrarapid and rapid metabolizers may have suboptimal responses due to increased metabolism, prompting consideration for an alternative medication.⁵⁴ CPIC guidelines use amitriptyline as the example drug, but also note that the recommendations apply to other tricyclics including clomipramine, doxepin, imipramine, and trimipramine. CYP2D6 also impacts amitriptyline clearance. CYP2D6 ultrapraid metabolizers have lower concentrations of active drug, increasing the likelihood the drug will be ineffective. CPIC guidelines recommend considering an alternative drug or using higher doses.⁵⁴

Conclusions and future directions

Our understanding of pharmacogenomic liability continues to expand, but pregnant women remain a unique population with limited data to support prescribing practices. Getting the right drug at the right dose is especially important during this time. The NICHD-funded Optimal Medication Management for Mothers with Depression (OPTI-MOM) aims to further investigate pharmacokinetic changes during pregnancy and the impact of pharmacogenomics with a goal of generating treatment guidelines for proactive management during pregnancy.⁵⁵ Research studies such as OPTI-MOM will help to decrease the burden of maternal illness, and by extension, lower rates of drug-related fetal and infant illness by better understanding how to adequately treat women during pregnancy. Research that includes pharmacokinetic and pharmacogenomic measures of drugs during pregnancy will continue to inform practice and prescribing choices.