Verify any claim · lenz.io
Claim analyzed
Health“The CYP2C19 gene has high genetic variability, with 39 possible alleles that influence the rate of medication metabolism.”
Submitted by Quick Eagle 31d2
The conclusion
Open in workbench →Evidence from NHS England and peer-reviewed pharmacogenomics reviews supports that CYP2C19 is highly variable and that 39 identified or characterized alleles/haplotypes have been linked to differences in drug metabolism. The main caveat is wording: these are catalogued variants from a specific time point, not all theoretically possible alleles, and the count can change as databases are updated.
Caveats
- The number 39 is time-bound; allele counts can change as PharmVar and related databases update nomenclature and add variants.
- The evidence supports 39 identified or characterized alleles/haplotypes, not literally all "possible" alleles.
- Different sources may count star alleles, suballeles, and deletion or structural variants differently, so exact totals are definition-dependent.
This analysis is for informational purposes only and does not constitute health or medical advice, diagnosis, or treatment. Always consult a qualified healthcare professional before making health-related decisions.
Get notified if new evidence updates this analysis
Create a free account to track this claim.
Sources
Sources used in the analysis
CYP2C19 is highly polymorphic: 39 haplotypes have been characterised by their impact on drug metabolism. This genetic heterogeneity is associated with significant pharmacokinetic variation between individuals, which affects drug efficacy and the risk of adverse effects.
The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C19 gene. CYP2C19 genetic variation is associated with altered drug metabolism and response. As of February 2020, the CYP2C19 expert panel has designated two novel alleles (*36 and *37) and three new suballeles. Considering CYP2C19*1 through *35 (excluding the CYP2C19*36 and *37 deletion alleles), hundreds of allele combinations are possible, and thus, the number of genotypes in a population or patient cohort can be quite large.
This CPIC resource provides an updated "CYP2C19 allele frequency table" that lists the defined CYP2C19 star alleles, their functional status (normal, no function, increased function, etc.), and calculated allele frequencies across multiple biogeographical populations. The accompanying CPIC documentation explains that these allele frequency tables are used in CPIC guidelines to assign metabolizer phenotypes (poor, intermediate, normal, rapid, and ultrarapid metabolizers) based on CYP2C19 diplotypes.
The normal "wild type" allele is CYP2C19*1 and is reported when no variant is detected. The table lists selected CYP2C19 alleles and their nomenclature, supporting the point that CYP2C19 has multiple recognized star alleles with different functional effects.
CYP2C19 drug metabolism is variable among individuals. Some individuals have CYP2C19 genetic variants that lead to severely diminished or absent CYP2C19 catalytic activity (ie, poor metabolizers).
The CYP2C19 gene is located on chromosome 10q23.33 and to date, **39 alleles and 2000 SNPs have been identified** (Shao et al., 2020). Among these variants, CYP2C19*2 and CYP2C19*3 are the most frequent and have received the greatest attention, as they identify poor metabolizers. Understanding CYP2C19 as a metabolizing enzyme will enable healthcare professionals to make decisions regarding drug selection and dosing based on each individual’s genetic makeup to reach a safe and effective treatment.
The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP2C19 gene. CYP2C19 genetic variation is associated with altered drug metabolism and response for many commonly prescribed medications, including proton pump inhibitors, antiplatelet agents, and certain antidepressants and anticonvulsants. Alleles are assigned function (e.g., normal, no, decreased, increased function) which is used in clinical pharmacogenetic implementation guidelines.
The ClinPGx CPIC gene page for CYP2C19 links to "gene-specific information tables (i.e. CYP2C19 allele definition, allele functionality, frequency and diplotype-phenotype tables)." These tables describe how specific CYP2C19 star alleles are classified by function and how combinations of alleles (diplotypes) are translated into metabolizer phenotypes that affect drug metabolism (e.g., poor, intermediate, normal, rapid, ultrarapid).
The PharmVar "Gene Info" document for CYP2C19 notes that "Allele frequencies CYP2C19 allele frequency tables have been developed for CPIC guidelines and are available through the PharmGKB" and that "A comprehensive list of frequencies and references can be found in the CYP2C19 allele frequency Table in the source tab." It also states that "For some alleles, the assigned activity may differ" and that activity of particular alleles and substrates should be extrapolated with caution, underscoring that multiple CYP2C19 alleles with different activities influence drug metabolism.
The purpose of this study is to assess the frequencies of several actionable variants in the highly polymorphic CYP2C19 gene in a large unselected sample. The well-characterized variants of CYP2C19 are the increased-function allele *17 and the no-function alleles *2 and *3, and these allelic combinations correspond to different phenotypic metabolism rates.
CYP2C19 is located on chromosome 10q23.33 and belongs to class 2 of the cytochrome P450 superfamily. To date, **39 alleles and 2000 SNPs have been identified** in CYP2C19 (Shao et al., 2020). Among these variants, CYP2C19*2 and CYP2C19*3 are the most frequent and have received the greatest attention, as they identify poor metabolizers.
Table 1 PharmVar gene and membership demographics... CYP2C19 *1-*35 33e haplotypes per gene. Footnote e: The CYP2C19 gene has 33 star alleles (*1 through *35) catalogued at the time of this analysis, excluding some deletion alleles and suballeles. PharmVar continues to add new alleles as they are identified and confirmed.
PharmVar: CYP2C19. The database lists individual star alleles (e.g., CYP2C19*1.005, CYP2C19*1.006, CYP2C19*27, etc.) with unique PharmVar IDs. The star allele list includes alleles from *1 onward and indicates multiple defined alleles and suballeles. Each star allele entry includes function annotations such as normal function, no function, decreased function, or increased function, which are relevant for drug metabolism.
CYP2C19 and CYP2D6 are important drug-metabolizing enzymes involved in the metabolism of around 30% of all medications. The paper describes CYP2C19 as highly polymorphic and examines clinically important allele frequencies across Europe.
The archived CYP2C19 allele table lists star alleles including CYP2C19*1 through CYP2C19*35 (e.g., CYP2C19*29, CYP2C19*30, CYP2C19*31, CYP2C19*32, CYP2C19*33, etc.). The table shows, for each star allele, the defining sequence variants and associated functional annotations such as normal, no function, or decreased function. These star alleles represent different haplotypes of the CYP2C19 gene relevant to variability in drug metabolism.
CYP2C19 is a highly polymorphic gene encoding a cytochrome P450 enzyme involved in the biotransformation of many commonly prescribed drugs. Multiple no-function (e.g., *2, *3), decreased-function (e.g., *9), and increased-function (e.g., *17) alleles have been described. Individuals carrying one or two no-function alleles have reduced or absent CYP2C19 activity and are classified as intermediate or poor metabolizers, whereas carriers of *17 have increased enzyme activity and are classified as rapid or ultrarapid metabolizers.
CYP2C19 is polymorphic, and multiple variant alleles can result in altered enzyme activity. The most common loss-of-function alleles are CYP2C19*2 and CYP2C19*3, which lead to absent enzyme activity. CYP2C19*17 is a gain-of-function allele associated with increased transcription and increased enzyme activity. These genetic differences translate into poor, intermediate, extensive (normal), and ultra-rapid metabolizer phenotypes for CYP2C19 substrates.
This Clinical and Translational Science paper reports allele frequencies for common CYP2C19 variants and notes that across all populations, "the common no-function allele *2 and the increased-function allele *17 were observed at rates of 15.2% and 20.4%, respectively, whereas *3 was rare overall (0.3%)." It emphasizes that these alleles encode different enzyme activities and that genotype combinations correspond to CYP2C19 metabolizer phenotypes with clinical implications for drug metabolism.
The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C19 gene. Numerous variants were subsequently reported and continue to be identified. While many CYP2C19 variants have been reported as having no function, a notable discovery in CYP2C19 pharmacogenetics was the identification of the CYP2C19*17 allele, which is associated with increased enzyme activity and more rapid drug clearance. Genetic variation, contributing to interindividual variability in CYP2C19 activity, is caused by SNVs within coding regions; gene copy number variation may also affect activity in rare cases.
CYP2C19 is highly polymorphic, and genetic variation affects enzyme activity and thus the metabolism of proton pump inhibitors (PPIs) such as omeprazole, lansoprazole, and others. Loss-of-function alleles (e.g., *2, *3) result in decreased or no function, whereas the increased-function allele *17 results in higher CYP2C19 activity. Based on their diplotype, individuals are assigned CYP2C19 metabolizer phenotypes: poor, intermediate, normal, rapid, or ultrarapid metabolizers.
Because the DNA sequence of CYP2C19 is highly polymorphic, this may account for much of the variability in the pharmacokinetics of drugs metabolized by CYP2C19. The phenotype of CYP2C19 metabolic capacity can be categorized based on genotypes and includes extensive metabolizers (two wild-type functional alleles), intermediate metabolizers (two reduced functional alleles or one null allele and a functional allele), and poor metabolizers (two non-functional alleles) of drugs. To date, the pharmacogenetic data on CYP2C19 clearly support that genetic variants alter the drug responses of its substrate drug.
The ClinPGx entry for CYP2C19*2 describes it as a "no function" allele and provides allele counts and frequencies across biogeographical groups (e.g., AFR, AMR, EAS, EUR), illustrating that this loss-of-function variant is common in many populations. The functional annotation of CYP2C19*2 as no-function is used in CPIC diplotype-to-phenotype tables to identify poor or intermediate metabolizers, which impacts the metabolism of CYP2C19 substrate medications.
CYP2C19 allele definition tables map variants to star alleles and curate the reference material used to interpret CYP2C19 genotype results. This supports the claim that many CYP2C19 alleles exist and are catalogued for pharmacogenomic use.
CYP2C19 is one of the most extensively studied polymorphic drug-metabolizing enzymes. More than 30 allelic variants of CYP2C19 have been identified, many of which result in altered enzyme activity. These alleles give rise to different metabolizer phenotypes that influence the pharmacokinetics and pharmacodynamics of various drugs, including proton pump inhibitors, antiepileptics, antidepressants, and antiplatelet agents.
PharmGKB’s CYP2C19 reference materials page hosts "gene-specific information tables" that include an allele definition table and an allele functionality table for CYP2C19, along with an allele frequency table. These curated tables list the catalog of CYP2C19 star alleles, classify each allele by predicted function (e.g., normal, no function, increased function), and map diplotypes to metabolizer phenotypes relevant for clinical pharmacogenetic dosing recommendations.
CYP2C19*2 has a minor allele frequency ranging from 13% to 54% in most major racial and ethnic groups, and consequently is the most common CYP2C19 allele in many populations. This shows substantial genetic variability within CYP2C19.
CYP2C19 is a highly polymorphic gene with numerous star alleles identified worldwide. Common loss-of-function alleles include *2 and *3, whereas *17 is a gain-of-function allele. The distribution of these alleles varies substantially across populations and contributes to interindividual and interethnic variability in CYP2C19 metabolizer status and drug response.
CYP2C19 exhibits high genetic variability, with numerous functional variants described. These include nonfunctional alleles (e.g., *2, *3, *4, *5), decreased-function alleles, and the increased-function allele *17. The presence of these alleles results in a spectrum of CYP2C19 metabolic phenotypes, from poor to ultrarapid metabolizers, affecting the metabolism and clinical efficacy of multiple medications.
In addition to the normal CYP2C19*1 allele, the CYP2C19 gene can have **up to 35 different alleles (named in order of discovery)**, many of which are associated with altered enzyme function, resulting in poor, intermediate, rapid, or ultra-rapid drug metabolism. The group’s first set of recommendations identify a minimum set of alleles for inclusion in clinical CYP2C19 genotyping panels. The alleles recommended for inclusion in tier one for clinical CYP2C19 genotyping panels are CYP2C19*2 and CYP2C19*3, which are loss-of-enzymatic-function alleles, and CYP2C19*17, which is associated with increased function of the enzyme.
CYP2C19 is a highly polymorphic gene with numerous genetic variants that can alter the enzyme’s metabolic activity. A common novel CYP2C19 gene variant causes ultra-rapid drug metabolism relevant for the drug response to proton pump inhibitors and antidepressants. Specific star alleles such as CYP2C19*2 and CYP2C19*3 are associated with no function, whereas CYP2C19*17 is associated with increased enzyme activity.
Genetic variation in the CYP2C19 gene plays a major role in inter-individual variability in drug response. Variant CYP2C19 alleles distribute differently across ethnic groups, and the document lists multiple major human CYP2C19 alleles and their associated SNPs.
ClinPGx curates literature and variant information for pharmacogenes including CYP2C19. It describes the identification and functional characterization of new potentially defective alleles of human CYP2C19 and links these haplotypes to altered enzyme activity. The database organizes CYP2C19 variants into haplotypes that are used in pharmacogenetic testing and phenotype prediction.
CYP2C19 is a highly polymorphic cytochrome P450 enzyme used in pharmacogenetics; different star alleles can reduce, eliminate, or increase enzyme activity, changing the metabolism of drugs such as clopidogrel, proton-pump inhibitors, and some antidepressants.
What do you think of the claim?
Your challenge will appear immediately.
Challenge submitted!
For developers
This same pipeline is available via API.
Verify your AI's output programmatically.
/extract pulls claims from text ·
/verify returns sourced verdicts ·
/ask answers follow-up questions.
Continue your research
Verify a related claim next.
The arguments
Two AI advocates debated this claim using the research gathered.
Argument for
The claim is directly supported by the NHS England Genomics Education Programme, which states that CYP2C19 is “highly polymorphic” and that 39 haplotypes have been characterized by their impact on drug metabolism (Source 1, Genomics Education Programme (NHS England)). Independent clinical-pharmacogenetics literature likewise reports that “to date, 39 alleles…have been identified” and explains that these variants translate into different metabolizer phenotypes that change medication metabolism rates (Source 6, PubMed Central: From genes to drugs; corroborated by CPIC's allele-function tables used to assign poor-to-ultrarapid metabolizer status in practice in Source 3, CPIC).
The Proponent's argument relies on a false equivalence between the 39 specific haplotypes mentioned in Source 1 and the total number of possible alleles, which actually spans far wider when accounting for the hundreds of suballeles and novel variants cataloged by PharmVar in Source 2 and Source 13. By rigidly defining the gene's variability by this single, arbitrary number, the Proponent ignores the ongoing discovery of new alleles documented in Source 12 and commits a fallacy of exclusion regarding the true scale of CYP2C19's genetic diversity.
Argument against
The claim that the CYP2C19 gene has exactly 39 possible alleles is misleading and outdated, as authoritative databases like PharmVar have cataloged only 33 star alleles (1 through 35, excluding deletion alleles) during detailed analyses, as noted in Source 12. Furthermore, Source 2 and Source 13 clarify that considering these core alleles, hundreds of allele combinations and suballeles exist, making the rigid designation of "39 possible alleles" an inaccurate representation of the gene's true genetic complexity.
The Opponent equivocates between “star alleles catalogued at the time of this analysis” and the motion's broader statement about alleles/haplotypes influencing metabolism: Source 12 is explicitly time-bound and exclusionary (omitting deletion alleles/suballeles), whereas Source 1 (Genomics Education Programme, NHS England) and Source 6 (From genes to drugs) directly state that 39 CYP2C19 haplotypes/alleles have been characterized/identified with pharmacokinetic impact. The Opponent's appeal to “hundreds of allele combinations” in Source 2 (PharmVar GeneFocus) and Source 13 (PharmVar) is a non sequitur—genotype combinatorics and suballele proliferation do not refute that a set of 39 characterized alleles/haplotypes exists and is used to assign metabolizer phenotypes affecting medication metabolism rates (Source 3, CPIC).
Expert review
3 specialized AI experts evaluated the evidence and arguments.
Expert 1 — The Logic Examiner
The logical chain from the evidence to the claim is sound, as multiple high-authority sources explicitly state that 39 alleles/haplotypes have been identified and characterized by their impact on drug metabolism (Source 1, Source 6, Source 11). The opponent's objection is a straw man argument, as the claim asserts the gene has 39 alleles that influence metabolism, not that 39 is the absolute mathematical limit of all possible genetic combinations or suballeles.
Expert 2 — The Source Auditor
High-authority, independent clinical references explicitly support the “39” figure and its pharmacogenetic relevance: NHS England's Genomics Education Programme states CYP2C19 is highly polymorphic with 39 characterized haplotypes affecting drug metabolism (Source 1), and a 2024 peer‑reviewed review (Frontiers; mirrored on PubMed Central) likewise states that to date 39 alleles have been identified and ties variants to metabolizer phenotypes (Sources 6/11). The opponent's counter-sourcing (PharmVar GeneFocus/PharmVar materials, Sources 2/12/13) mainly shows that allele catalogs evolve and include many suballeles/genotypes, but it does not reliably refute that 39 characterized alleles/haplotypes influencing metabolism is a supported statement, so the claim is mostly confirmed with a caveat that counts depend on definitions and date.
Expert 3 — The Precision Analyst
Sources 1, 6, and 11 directly state that 39 alleles/haplotypes have been characterized for CYP2C19, with Source 1 (NHS England Genomics Education Programme) explicitly stating '39 haplotypes have been characterised by their impact on drug metabolism' and Sources 6 and 11 (Frontiers in Pharmacology, 2024) stating '39 alleles and 2000 SNPs have been identified.' The claim's number of 39 is thus directly supported by multiple authoritative sources. The claim uses 'possible alleles' where the evidence says 'characterized haplotypes' or 'identified alleles' — a minor wording difference but not a material distortion. The claim that these alleles 'influence the rate of medication metabolism' is well-supported across all sources. The Opponent's point that PharmVar catalogued only 33 star alleles at one point (Source 12, 2020) reflects a time-bound snapshot excluding deletion alleles and suballeles, while the 39 figure appears in more recent and comprehensive sources. The claim is accurate at its stated strength, with only a minor precision issue around 'possible' vs. 'identified/characterized' alleles, which does not materially change the conclusion.