Escitalopram and CYP2C19

Zachary Lin, Pharm.D. Candidate; Lydia Diep, Pharm.D. Candidate; Melanie Jensen, Pharm.D. Candidate

About the Drug

Escitalopram (Lexapro®) is mainly used as an antidepressant. It also can be used for generalized anxiety disorder (GAD), hot flashes, panic disorder, obsessive compulsive disorder (OCD), and post-traumatic stress disorder (PTSD). It works by selectively inhibiting the reuptake of serotonin in the brain. This leads to more serotonin being available. Serotonin is a neurotransmitter that’s responsible for mood regulation; a deficit in serotonin can lead to depression. Full response to escitalopram may not be seen until even 8-12 weeks after the initial treatment.

About the Gene

CYP2C19 (pronounced “sip two see nineteen”) is an enzyme found in your liver that helps metabolize several drugs, including escitalopram. Metabolism is a process in which a drug is converted to other compounds, often to aid in removal from the body. The function of an individual’s CYP2C19 enzyme is dependent on their specific genetic makeup. Different gene variants for CYP2C19 can affect how your body metabolizes escitalopram, either increasing or decreasing the rate at which this occurs.

About the Drug-Gene Interaction

CYP2C19 affects the metabolism of escitalopram. The gene itself can have different polymorphisms, or variants: CYP2C19*1, a normal metabolizer; CYP2C19*17, an ultra-rapid metabolizer (one that breaks down the drug faster); and CYP2C19*2 and CYP2C19*3, both of which are variants that lead to poor breakdowns of escitalopram.

A variation of CYP2C19 that causes rapid drug breakdown will decrease drug levels in the body. Conversely, a variation that causes poor drug breakdown will increase drug levels. These differences can create a need to either increase or decrease doses. It is suggested that patients with CYP2C19*2 or CYP2C19*3, which both poorly break down escitalopram, have their initial dosage be reduced by 50%. For example, instead of starting off at 10 mg, they would start off at 5 mg. However, for those with the CYP2C19*17 variant, the ultra-rapid metabolizer, a patient may need to instead increase their dose by 150%.

Drug-Gene Interaction Example

Sarah, a 30-year-old Asian female, has recently been diagnosed with generalized anxiety disorder and was prescribed escitalopram for treatment. During her visit, she was told of the possibility of poor therapeutic outcomes and an increased risk of adverse effects due to the high chance of a genetic mutation. The physician suggests to run genetic testing in order to specialize her pharmacologic therapy to her genotype. Sarah refuses the genetic testing since her insurance does not cover the test. Six weeks after initiating therapy, Sarah presents to the office with severe nausea, diarrhea, headache, and insomnia. Sarah opts to have the genetic testing done after her physician reiterates the possibility of her genotype affecting therapy. The results show a CYP2C19*2/*2 genetic variant associated with poor metabolism of escitalopram. The genetic polymorphism Sarah exhibits causes increased concentrations of the drug, thereby increasing risk of adverse effects. Sarah was prescribed another SSRI that is not highly metabolized via CYP2C19 and did not experience any further side effects.

Eric, a 25 year old white male, is visiting the same primary care provider for the treatment of major depressive disorder. Eric requested to initiate therapy with escitalopram after hearing positive results from his friend who is currently on the medication. The physician explains to Eric the possibilities of genetic polymorphisms that may affect metabolism of the drug. Eric agrees to have the genetic testing done because of a family history of metabolic deficiencies. The results show Eric is an ultrarapid metabolizer as indicated by CYP2C19*17/*17. Escitalopram is metabolized to a compound that confers less serotonin reuptake inhibition producing subtherapeutic effects in ultrarapid metabolizers. Ultrarapid metabolizers (CYP2C19*17) experience significantly lower exposure to escitalopram as compared to extensive metabolizers yielding a higher risk of therapy failure. Due to Eric’s high risk of ineffective pharmacologic therapy with escitalopram, the physician initiated a different SSRI that is not affected by CYP2C19. Eric showed moderate mood improvement in the following 4 weeks.

CYP2C19 genetic testing does not completely rule out the risks of taking escitalopram, nor does it guarantee the medication will work for you. Genetic testing is a guide to personalize the treatment of patients, maximizing benefit, and minimizing harm.

Provider Information

The links below provide access to important articles and information relative to escitalopram. The links are to external websites and will be checked regularly for consistency.

Sources of Information

Bell DJ, Singh H. Genetic factors in drug metabolism. Am Fam Physician. 2008 Jun 1;77(11):1553-60.

Chang M. Impact of cytochrome P450 2C19 polymorphisms on citalopram/escitalopram exposure: A systematic review and meta-analysis. Clin Pharmcokinet. 2014 Sep;53(9):801-11.

Hicks JK, Bishop JR, Sangkuhl K, et al. Clinical Pharmacogenetic Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and dosing of selective serotonin reuptake inhibitors. Clin Pharmacol Ther. 2015 Aug;98(2):127-34.

Lexicomp Online [Internet]. Hudson, (OH): Wolters Kluwer Clinical Drug Information Inc. c1979-2017. Escitalopram; [cited 2017 Jan 15]. Available from:

Li-Wan-Po A, Girard T, Farndon P, Cooley C, Lithgow J. Pharmacogenetics of CYP2C19: functional and clinical implications of a new variant CYP2C19*17. Br J Clin Pharmacol. 2010 Mar;69(3):222-30.

Sangkuhl K, Klein TE, Altman RB. PharmGKB summary: citalopram pharmacokinetics pathway. Pharmacogenet Genomics. 2011 Nov;21(11):769-72.

UFHealth [Internet]. Gainsville (FL): University of Florida Health; c2018. Escitalopram, citalopram: are higher doses needed in CYP2C19 ultrarapid metabolizers?; 2014 Oct 31 [cited 2017 Jan 16]; [about 2 screens]. Available from:

Whirl-Carrillo M, McDonagh EM, Hebert JM, Gong L, Sangkuhl K, Thorn CF, Altman RB, Klein TE. Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2012 Oct;92(4):414-7.