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Pharmacogenomics

Not a medical test — for research and educational use only

Yeliztli analyses consumer genotyping-array data (23andMe / AncestryDNA), which is not a clinical-grade test. Results are not diagnostic, are not clinically validated, and must not be used to make medical decisions. Array data is especially unreliable for rare, disease-causing variants. Always confirm any finding with an accredited clinical laboratory and discuss it with a qualified clinician or genetic counsellor before acting on it. See the Intended use & disclaimers page for the details and the evidence behind this warning.

Pharmacogenomics looks at genes that affect how your body processes certain medications, and surfaces the relevant CPIC prescribing guidance.

What it looks at

11 CPIC pharmacogenes: CYP2D6, CYP2C19, CYP2C9, CYP3A5, SLCO1B1, DPYD, TPMT, UGT1A1, NUDT15, NAT2, and CYP2B6.

What you'll see

  • Star-allele diplotypes (e.g. *1/*4) and the resulting CPIC phenotype or functional status. Genes reported with metabolizer phenotypes use Poor Metabolizer, Intermediate Metabolizer, Normal Metabolizer, Rapid Metabolizer, and Ultrarapid Metabolizer.
  • Rapid and ultrarapid are separate metabolizer categories, so a result such as CYP2C19 *1/*17 is reported as Rapid Metabolizer, while *17/*17 is reported as Ultrarapid Metabolizer.4 Other pharmacogenes use different CPIC status families, including SLCO1B1 Normal function, Decreased function, and Poor function, and NAT2 Rapid Acetylator, Intermediate Acetylator, and Slow Acetylator.
  • Some cards also show an activity score. This is a gene-specific numeric summary of allele function that Yeliztli uses only with that gene's diplotype-to-phenotype table. In activity-score systems, allele values are commonly summed from 0 for no-function alleles, fractional values for reduced-function alleles, and 1 for normal-function alleles; copy-number gains can raise the total when known. The thresholds that turn that number into a phenotype are gene-specific, so compare the displayed score only within the same gene and rely on the adjacent CPIC phenotype/status for interpretation.5
  • A three-state call confidence — Complete, Partial, or Insufficient — so you know how much to trust each call.
  • A card tint that summarizes the metabolizer result, separate from call confidence: green means a normal/routine result, amber means a non-normal phenotype or functional status worth reviewing in the context of the affected drugs, and red means no phenotype could be determined for that gene. Amber is deliberately broad: it can cover reduced, increased, or otherwise non-normal statuses, so read the phenotype text and any drug alerts for the direction of effect.
  • Per-drug prescribing alerts based on CPIC guidelines, with the CPIC level mapped to an evidence rating, plus context from PharmGKB, DPWG, and FDA labels.
  • A consolidated medication-safety summary grouping the actionable interactions.

Good to know

  • Arrays can't see everything. They cannot resolve CYP2D6/CYP2B6 copy-number changes or gene conversions, so those calls are Partial at best. They also cannot genotype the UGT1A1 *28 promoter TA-repeat from SNP array data, so that reduced-function allele remains indeterminate when only array calls are available.1
  • A normal result isn't a guarantee. For DPYD, only a handful of variants are typed — a normal call does not rule out DPD deficiency, which matters for certain chemotherapy drugs. For UGT1A1, a normal *1/*1 call does not rule out reduced UGT1A1 activity from untyped *28, which matters for irinotecan and atazanavir prescribing context.23
  • Some diplotypes are inferred from unphased data and carry phase ambiguity.

Never change a medication based on this

Pharmacogenomic results here are research/educational. Do not start, stop, or change any medication without your prescriber, who can order a clinical PGx test if warranted.

  1. Correlation between the UDP-glucuronosyltransferase (UGT1A1) TATAA box polymorphism and carcinogen detoxification phenotype (Fang & Lazarus, 2004, Cancer Epidemiology, Biomarkers & Prevention; PMID 14744740) describes UGT1A1*28 as an additional (TA) repeat in the promoter TATA box linked to lower UGT1A1 expression/activity. ↩

  2. Dutch Pharmacogenetics Working Group guideline for the gene-drug interaction between UGT1A1 and irinotecan (Hulshof et al., 2023, European Journal of Human Genetics; PMID 36443464) describes UGT1A1 poor metabolizers and genotype-informed irinotecan starting-dose adjustment. ↩

  3. Clinical Pharmacogenetics Implementation Consortium guideline for UGT1A1 and atazanavir prescribing (Gammal et al., 2016, Clinical Pharmacology & Therapeutics; PMID 26417955) summarizes atazanavir prescribing recommendations when UGT1A1 genotype is known. ↩

  4. Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC) (Caudle et al., 2017, Genetics in Medicine) defines consensus pharmacogenetic phenotype terminology for consistent PGx interpretation. ↩

  5. Standardizing CYP2D6 Genotype to Phenotype Translation: Consensus Recommendations from the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group (Caudle et al., 2020, Clinical and Translational Science; PMID 31647186; PMCID PMC6951851) describes the CYP2D6 activity-score system as summed allele activity values and explains that phenotype translation depends on consensus, gene-specific thresholds. ↩