Sample Report for Jamie Appleseed
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Pain Medication + Genetics Report
Sample pharmacogenomic analysis for 20 pain medications
Research & Education Notice
This is a literature-based report summarizing available pharmacogenomic research. Always consult with your healthcare provider before making any medication decisions. Your unique medical history, current health status, and treatment decisions should be made in partnership with your qualified healthcare provider. This report is only as accurate as the genetic data provided—results depend on the quality and completeness of your uploaded DNA file.
Understanding Your Pain Medication Report
This report analyzes genetic variants in relation to 20 pain medications including opioids, NSAIDs, neuropathic pain agents, muscle relaxants, migraine medications, and medication-assisted treatment options.
Each medication page shows which genes process that medication, how specific variants may influence response, and what research suggests about dosing considerations and drug interactions relevant to your genetic profile.
Key Genes in Pain Pharmacogenomics
Several genes play important roles in how your body processes pain medications:
CYP2D6 — Opioid Activation
Converts codeine and tramadol to their active forms. Poor metabolizers may get little pain relief; ultra-rapid metabolizers may experience increased effects.
CYP2C9 — NSAID Metabolism
Metabolizes celecoxib, ibuprofen, and other NSAIDs. Variants can affect drug clearance and risk of gastrointestinal side effects.
OPRM1 — Opioid Receptor
Encodes the mu-opioid receptor, influencing pain sensitivity and opioid response. Variants may affect analgesic requirements.
CYP1A2 — Muscle Relaxant Metabolism
Metabolizes tizanidine and cyclobenzaprine. Inhibitor interactions can significantly increase drug levels.
Understanding Metabolizer Status
Genetic variants determine how active drug-metabolizing enzymes are. Throughout this report, you will see these categories:
| Status | What It Means |
|---|---|
| Ultrarapid Metabolizer | Enzyme is highly active. Medications may be cleared faster than typical, potentially reducing effectiveness at standard doses. |
| Normal Metabolizer | Enzyme functions as expected. Standard dosing approaches generally apply. |
| Intermediate Metabolizer | Enzyme has reduced activity. Medications may be cleared more slowly, potentially increasing drug levels. |
| Poor Metabolizer | Enzyme has significantly reduced or absent activity. Medications may accumulate, potentially increasing effects and side effects. |
About Our Research
This report synthesizes findings from peer-reviewed research, FDA drug labels, and clinical guidelines including CPIC (Clinical Pharmacogenetics Implementation Consortium). Citations are numbered throughout each medication page, with full references provided at the end of the report.
This report is educational, not clinical advice. Medication decisions should always be made with a healthcare provider, who can consider complete medical history, current medications, and individual circumstances alongside this genetic information.
Evidence Levels
How we classify the strength of pharmacogenomic evidence
Strong Evidence – Clinical Practice Guidelines
CPIC (Clinical Pharmacogenetics Implementation Consortium) or PharmGKB Level 1A has published clinical practice guidelines for this gene-drug relationship. These guidelines are used by healthcare providers to inform prescribing decisions.
Good Evidence – Peer-Reviewed Studies & FDA Labeling
Supported by CPIC moderate-level guidelines, PharmGKB clinical annotations, FDA pharmacogenomic labeling, or multiple peer-reviewed pharmacokinetic studies.
Early Research – Emerging Findings
Gene-drug associations identified in peer-reviewed literature. Findings are promising but additional studies are needed before clinical practice guidelines can be established.
Note: When a medication has evidence from multiple genes, the highest tier is displayed. Detailed evidence sources are shown within each medication's expanded view.
Limited Research: For medications without established pharmacogenomic data for your specific genetic profile, standard prescribing guidance applies. This does not indicate the medication is unsafe—only that genetic research is not yet available.
Research Finding Levels
How we summarize what research has identified for your genetics and each medication
Minimal Findings
Research has identified limited genetic factors relevant to this medication for your profile.
Moderate Findings
Research has identified some genetic factors that may be relevant to this medication for your profile.
Significant Findings
Research has identified important genetic factors relevant to this medication for your profile.
Note: This indicates the amount of research findings, not whether a medication is "good" or "bad" for you. Discuss all findings with your healthcare provider.
Important Medical Disclaimer
This report is for informational and educational purposes only. It is not medical advice and should not be used as a substitute for professional medical consultation. Always consult your pain management specialist or healthcare provider before making any changes to pain medications.
Scientific References
Primary Data Sources
Data Quality & Methodology
This report integrates pharmacogenetic data from 8 primary sources: CPIC guidelines, DPWG guidelines, PharmGKB annotations, FDA pharmacogenomic biomarkers, OnSIDES label-extracted adverse effects, DGIdb gene-drug interactions, PharmVar allele definitions, and peer-reviewed PubMed literature. All genetic variants have been validated against PharmVar reference sequences, and diplotype assignments follow CPIC nomenclature standards. Research citations are automatically verified against PubMed and tiered by evidence strength (Tier 1: CPIC/DPWG guidelines, Tier 2: FDA/PharmGKB, Tier 3: Emerging research).
Last Updated: April 10, 2026. We update our research database quarterly with new CPIC guidelines, FDA label changes, and published studies. For the most current recommendations, please refer to the resources above and consult with your healthcare provider.
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