PHARMACOGENOMICS OF OPIOID RESPONSE IN EUROPEAN ADVANCED CANCER PATIENTS
type: CreativeWork
description: Background: Strong opioids, which are drugs in the third step of the World Health Organization’s analgesic ladder, are the standard of care for treating pain in advanced cancer patients. Unfortunately, a significant minority of them do not benefit from analgesic therapy, or experience several side effects, such as nausea and vomiting. Genetics might play a role in predisposing patients to a good or poor response to opioids. To investigate this issue, two different genome-wide association studies (GWAS) were conducted to identify genetic variants modulating opioid efficacy and toxicity. Methods: We genotyped over two thousand European patients with advanced cancer, treated with morphine, buprenorphine, fentanyl, and oxycodone. Data about toxicity (nausea-vomiting score, NVS) and efficacy (pain intensity, PI) and other relevant clinical information were collected. We carried out two whole genome regression models (using REGENIE software) to test the association between genotypes and the two opioid response phenotypes, both defined as numerical scores, one measuring patient pain intensity and the other nausea/vomiting intensity. To understand the functional role of the variants significantly associated with opioid response, several “in silico” post-GWAS analyses were conducted. Colocalization between pain intensity phenotype and gene expression was explored, as well as the tissue-type enrichment for our significant variants, using stratified linkage disequilibrium score regression (sLDSC). Finally, Mendelian randomization, using our pain intensity GWAS datasets, was performed to investigate causal relationships between putative pain risk factors, such as inflammation, sleep alteration, and psychiatric conditions, and cancer pain intensity. Results: For the opioid-induced toxicity phenotype, 65 variants associated with NVS (at Pvalue < 1.0 × 10−5) were found. Among these, 14 variants on chromosome 2 mapped in intronic regions of NPAS2 gene, which encodes a circadian tra…
abstract: Background: Strong opioids, which are drugs in the third step of the World Health Organization’s analgesic ladder, are the standard of care for treating pain in advanced cancer patients. Unfortunately, a significant minority of them do not benefit from analgesic therapy, or experience several side effects, such as nausea and vomiting. Genetics might play a role in predisposing patients to a good or poor response to opioids. To investigate this issue, two different genome-wide association studies (GWAS) were conducted to identify genetic variants modulating opioid efficacy and toxicity. Methods: We genotyped over two thousand European patients with advanced cancer, treated with morphine, buprenorphine, fentanyl, and oxycodone. Data about toxicity (nausea-vomiting score, NVS) and efficacy (pain intensity, PI) and other relevant clinical information were collected. We carried out two whole genome regression models (using REGENIE software) to test the association between genotypes and the two opioid response phenotypes, both defined as numerical scores, one measuring patient pain intensity and the other nausea/vomiting intensity. To understand the functional role of the variants significantly associated with opioid response, several “in silico” post-GWAS analyses were conducted. Colocalization between pain intensity phenotype and gene expression was explored, as well as the tissue-type enrichment for our significant variants, using stratified linkage disequilibrium score regression (sLDSC). Finally, Mendelian randomization, using our pain intensity GWAS datasets, was performed to investigate causal relationships between putative pain risk factors, such as inflammation, sleep alteration, and psychiatric conditions, and cancer pain intensity. Results: For the opioid-induced toxicity phenotype, 65 variants associated with NVS (at Pvalue < 1.0 × 10−5) were found. Among these, 14 variants on chromosome 2 mapped in intronic regions of NPAS2 gene, which encodes a circadian tra…
author: MINNAI, FRANCESCA
language: eng
keywords: Settore MEDS-01/A - Genetica medica, Settore MEDS-09/A - Oncologia medica, Settore BIOS-14/A - Genetica
date published: 2026-01-21
date modified: 2026-07-27T20:19:05Z
provider: Università degli Studi di Milano
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Università degli Studi di Milano

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property ID: Handle
value: https://hdl.handle.net/2434/1205650