A Genome-Wide Association Study of Oxypurinol Concentrations in Patients Treated with Allopurinol.

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented with multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p > 5 × 10-8). Our results are consistent with prior findings regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, as well as allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Pharmacogenomic markers of metoprolol and α-OH-metoprolol concentrations: a genome-wide association study.

Aim: Few genome-wide association studies (GWASs) have been conducted to identify predictors of drug concentrations. The authors therefore sought to discover the pharmacogenomic markers involved in metoprolol pharmacokinetics. Patients & methods: The authors performed a GWAS of a cross-sectional study of 993 patients from the Montreal Heart Institute Biobank taking metoprolol. Results: A total of 391 and 444 SNPs reached the significance threshold of 5 × 10-8 for metoprolol and α-OH-metoprolol concentrations, respectively. All were located on chromosome 22 at or near the CYP2D6 gene, encoding CYP450 2D6, metoprolol's main metabolizing enzyme. Conclusion: The results reinforce previous findings of the importance of the CYP2D6 locus for metoprolol concentrations and confirm that large biobanks can be used to identify genetic determinants of drug pharmacokinetics at a GWAS significance level.

Genetics of symptom remission in outpatients with COVID-19.

We conducted a genome-wide association study of time to remission of COVID-19 symptoms in 1723 outpatients with at least one risk factor for disease severity from the COLCORONA clinical trial. We found a significant association at 5p13.3 (rs1173773; P = 4.94 × 10-8) near the natriuretic peptide receptor 3 gene (NPR3). By day 15 of the study, 44%, 54% and 59% of participants with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. In 851 participants not treated with colchicine (placebo), there was a significant association at 9q33.1 (rs62575331; P = 2.95 × 10-8) in interaction with colchicine (P = 1.19 × 10-5) without impact on risk of hospitalisations, highlighting a possibly shared mechanistic pathway. By day 15 of the study, 46%, 62% and 64% of those with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. The findings need to be replicated and could contribute to the biological understanding of COVID-19 symptom remission.

Genetic meta-analysis of cancer diagnosis following statin use identifies new associations and implicates human leukocyte antigen (HLA) in women.

We sought to perform a genomic evaluation of the risk of incident cancer in statin users, free of cancer at study entry. Patients who previously participated in two phase IV trials (TNT and IDEAL) with genetic data were used (npooled = 11,196). A GWAS meta-analysis using Cox modeling for the prediction of incident cancer was conducted in the pooled cohort and sex-stratified. rs13210472 (near HLA-DOA gene) was associated with higher risk of incident cancer amongst women with prevalent coronary artery disease (CAD) taking statins (hazard ratio [HR]: 2.66, 95% confidence interval [CI]: 1.88-3.76, P = 3.5 × 10-8). Using the UK Biobank and focusing exclusively on women statin users with CAD (nfemale = 2952), rs13210472 remained significantly associated with incident cancer (HR: 1.71, 95% CI: 1.14-2.56, P = 9.0 × 10-3). The association was not observed in non-statin users. In this genetic meta-analysis, we have identified a variant in women statin users with prevalent CAD that was associated with incident cancer, possibly implicating the human leukocyte antigen pathway.

Nuclear receptor gene polymorphisms and warfarin dose requirements in the Quebec Warfarin Cohort.

Warfarin is primarily metabolized by cytochrome 2C9, encoded by gene CYP2C9. Here, we investigated whether variants in nuclear receptor genes which regulate the expression of CYP2C9 are associated with warfarin response. We used data from 906 warfarin users from the Quebec Warfarin Cohort (QWC) and tested the association of warfarin dose requirement at 3 months following the initiation of therapy in nine nuclear receptor genes: NR1I3, NR1I2, NR3C1, ESR1, GATA4, RXRA, VDR, CEBPA, and HNF4A. Three correlated SNPs in the VDR gene (rs4760658, rs11168292, and rs11168293) were associated with dose requirements of warfarin (P = 2.68 × 10-5, P = 5.81 × 10-4, and P = 5.94 × 10-4, respectively). Required doses of warfarin were the highest for homozygotes of the minor allele at the VDR variants (P < 0.0026). Variants in the VDR gene were associated with the variability in response to warfarin, emphasizing the possible clinical relevance of nuclear receptor gene variants on the inter-individual variability in drug metabolism.

Development of a broad-based ADME panel for use in pharmacogenomic studies.

AIM: To optimally address the interindividual variability observed in pharmacokinetic drug response, we have created a custom genotyping panel that interrogates most of the key genetic variations present in a set of 181 prioritized genes responsible for the absorption, distribution, metabolism and excretion (ADME) of many therapeutic agents. This consensus list of genes and variants was based on the ADME core and extended gene lists compiled by a group of pharmaceutical companies as having relevance. Although these pharmacokinetic genes and pathways are well known, tools that can interrogate a large number of these genes simultaneously within a single experiment are not currently available. METHODS: Using novel design strategies, we have developed an optimized and validated ADME genotyping panel, encompassing approximately 3000 variants, that has broad applicability to any study or clinical trial that would benefit from the evaluation of an extensive list of ADME genes. RESULTS & CONCLUSION: Over the course of three design iterations, overall assay conversion rates were improved from 83 to 97% resulting in a panel that fills in many of the gaps in coverage present on currently available commercial genotyping assays. The utility of the assay has been demonstrated by the screening of more than 1000 samples resulting in the discovery of novel pharmacogenomic associations. The assay, and the underlying methods, will continue to be a valuable tool for use in future pharmacogenomic studies.