Residency · Residency · Pathology

Pharmacogenomics in Pathology Practice

Introduction

Pharmacogenomics (PGx) studies the influence of genetic variation on drug response, encompassing drug metabolism, efficacy, and adverse effects. As pathology laboratories increasingly offer PGx testing, understanding the key gene-drug interactions, testing methodologies, and clinical implementation frameworks is essential.

Fundamental Concepts

Pharmacokinetics vs. Pharmacodynamics

Pharmacokinetic genes affect drug absorption, distribution, metabolism, and excretion (ADME), while pharmacodynamic genes affect drug targets, receptors, and downstream signaling pathways. Most clinically implemented PGx tests focus on drug-metabolizing enzymes and drug transporters. Genetic variation explains 20-95% of drug response variability depending on the medication.

Key Terminology

An allele is a variant form of a gene, designated by star () alleles (for example, CYP2D64). The phenotype is the predicted metabolic activity based on the diplotype. Poor metabolizer (PM) indicates little or no enzyme activity from two loss-of-function alleles. Intermediate metabolizer (IM) reflects reduced activity. Normal (extensive) metabolizer (NM/EM) is typical activity. Ultrarapid metabolizer (UM) shows increased activity from gene duplications or gain-of-function alleles. The diplotype is the combination of two alleles (one from each parent) that determines the phenotype.

Clinically Important Gene-Drug Pairs

CYP2D6

CYP2D6 is highly polymorphic with over 130 described alleles and common copy number variations. It metabolizes approximately 25% of all prescribed drugs. Key substrates include codeine, tramadol, tamoxifen, atomoxetine, many antidepressants (fluoxetine, paroxetine), and antipsychotics (haloperidol, risperidone). Codeine in PMs results in minimal conversion to morphine and therapeutic failure. Codeine in UMs causes excessive morphine production and respiratory depression, prompting an FDA black box warning in children. Tamoxifen is a prodrug activated by CYP2D6 to endoxifen, and PMs may have reduced efficacy.

CYP2C19

Key substrates include clopidogrel, proton pump inhibitors, voriconazole, and some antidepressants (escitalopram, sertraline). Clopidogrel in PMs leads to reduced conversion to the active metabolite and increased risk of cardiovascular events, carrying an FDA boxed warning. Common loss-of-function alleles are CYP2C192 and CYP2C193, while CYP2C1917* is a gain-of-function allele causing ultrarapid metabolism. Voriconazole management is also affected, as PMs have elevated drug levels with toxicity risk while UMs have sub-therapeutic levels.

CYP2C9 and VKORC1

Warfarin dosing is influenced by CYP2C9 (metabolism) and VKORC1 (pharmacodynamic target). CYP2C92 and 3 variants reduce metabolism and require lower doses. The VKORC1 -1639G>A polymorphism affects vitamin K epoxide reductase expression, and the AA genotype requires significantly lower doses. FDA-approved dosing tables incorporate genotype, though adoption has been gradual.

DPYD

Dihydropyrimidine dehydrogenase metabolizes fluoropyrimidines (5-FU, capecitabine). The DPYD*2A variant (IVS14+1G>A) causes complete loss of function, and homozygotes are at risk of fatal toxicity. European guidelines recommend pre-treatment DPYD genotyping before fluoropyrimidine therapy, with dose reduction of 50% for heterozygous carriers and contraindication in homozygous or compound heterozygous PMs.

UGT1A1

UGT1A1 metabolizes the irinotecan active metabolite SN-38. The UGT1A128 variant (7 TA repeats in the promoter) reduces expression and increases the risk of severe neutropenia and diarrhea. The FDA label includes pharmacogenomic information, and dose reduction is recommended for 28/*28 homozygotes.

TPMT and NUDT15

Thiopurine methyltransferase (TPMT) and NUDT15 metabolize thiopurines (azathioprine, 6-mercaptopurine, thioguanine). Deficient patients are at high risk for severe myelosuppression. TPMT deficiency occurs in approximately 1 in 300 individuals (homozygous PM). NUDT15 variants are more prevalent in East Asian populations. CPIC guidelines recommend genotype-guided dosing for all patients before initiating thiopurines.

HLA Alleles and Adverse Drug Reactions

**HLA-B57:01 is associated with abacavir hypersensitivity syndrome, and FDA-mandated testing is required before prescribing. HLA-B15:02 is associated with carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis, prevalent in Southeast Asian populations. HLA-B58:01 is associated with allopurinol hypersensitivity, with higher prevalence in certain ethnic groups. HLA-A31:01** is associated with carbamazepine hypersensitivity in European and Japanese populations.

Testing Methodologies

Targeted Genotyping

Targeted genotyping tests for predefined known variants (star alleles and SNPs) using platforms such as TaqMan real-time PCR, microarray-based systems (Affymetrix DMET, Illumina ADME panel), and mass spectrometry (Agena MassARRAY). Advantages include cost-effectiveness, rapid turnaround, and well-validated protocols. The limitation is that novel or rare variants not included on the panel cannot be detected.

Sequencing Approaches

Sanger sequencing remains the gold standard for single gene confirmatory testing. NGS-based PGx panels provide comprehensive coverage and detect novel variants. Long-read sequencing resolves complex loci such as CYP2D6 with its structural variants, duplications, and gene conversions. CYP2D6 is notoriously difficult to genotype due to its pseudogene (CYP2D7), deletions, duplications, and hybrid alleles.

Copy Number Analysis

Copy number assessment is essential for CYP2D6, covering gene deletions (*5) and duplications or multiplications. Methods include quantitative PCR, MLPA, droplet digital PCR, and array CGH. Copy number must be determined to accurately assign the metabolizer phenotype.

Clinical Implementation

CPIC Guidelines

The Clinical Pharmacogenetics Implementation Consortium (CPIC) provides evidence-based, peer-reviewed guidelines with genotype-to-phenotype translation tables and prescribing recommendations. These guidelines are updated regularly and are available at cpicpgx.org.

Laboratory Reporting

Reports should include the diplotype (for example, CYP2D6 1/4) and the predicted phenotype (for example, intermediate metabolizer). Clinical recommendations aligned with CPIC or DPWG guidelines should be included. The report should state which alleles were tested and note that rare variants may not be detected. An activity score for CYP2D6 interpretation is also recommended.

Electronic Health Record Integration

Clinical decision support (CDS) alerts are triggered by PGx results when relevant medications are prescribed. Pre-emptive testing allows genotyping once and storing results in the EHR for future prescribing decisions throughout the patient's lifetime. Challenges include interoperability, structured data storage, and alert fatigue management.

Clinical Pearls

CYP2D6 is the most polymorphic and clinically impactful drug-metabolizing enzyme, and accurate genotyping requires assessment of both SNPs and copy number variations. Pre-treatment DPYD genotyping before fluoropyrimidine chemotherapy can prevent life-threatening toxicity and is increasingly mandated by guidelines. HLA-B*57:01 testing before abacavir prescription is a mandatory, well-established example of pharmacogenomic testing preventing a severe immune-mediated adverse reaction. Pre-emptive pharmacogenomic testing panels allow results to be stored in the medical record and applied across multiple future prescribing decisions throughout a patient's lifetime.

References

1. Caudle KE, et al. Standardizing CYP2D6 genotype to phenotype translation: consensus recommendations from the CPIC and DPWG. Clin Transl Sci. 2020;13(1):116-124.
2. Relling MV, Klein TE. CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network. Clin Pharmacol Ther. 2011;89(3):464-467.
3. Henricks LM, et al. DPYD genotype-guided dose individualisation of fluoropyrimidine therapy in patients with cancer: a prospective safety analysis. Lancet Oncol. 2018;19(11):1459-1467.
4. PharmGKB (Pharmacogenomics Knowledge Base). Available at: https://www.pharmgkb.org.

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