Pharmacogenetics and Drug Metabolism

The paper assesses the utility of genetic ancestry for pharmacogenomic risk stratification compared to self-identified race/ethnicity in a U.S. cohort.

The paper evaluates 20 SNP prediction tools on CYP2D6 missense variants, finding FATHMM performs best with a Matthews correlation coefficient of 0.39.

The paper investigates NAT2 polymorphisms and their effect on isoniazid pharmacokinetics in HIV-infected South Africans with tuberculosis, finding no significant genotype-phenotype correlation.

The paper develops a multiplex pharmacogenetics assay using MinION nanopore sequencing to genotype variants related to clopidogrel and warfarin, achieving >90% accuracy for most variants.

This study uses nanopore sequencing to genotype CYP2D6, accurately haplotype alleles, and detect duplications by analyzing allelic balance.

The paper shows that genetic evidence linking drug targets to organ system phenotypes predicts clinical trial side effects in those systems.

This study investigates the association between genetic variants in PMAT and OCT1 transporters and metformin gastrointestinal intolerance in type 2 diabetes patients.

The paper introduces a standardized biogeographic grouping system for pharmacogenetic research to improve consistency in reporting allele frequency variability across populations.

The paper identifies high-impact variants in pharmacogenomic genes using whole-genome sequencing data from the 1000 Genomes Project.

This paper conducts a meta-analysis showing that CYP2C19 poor metabolizers have better antidepressant efficacy but similar side effects compared to extensive metabolizers.

The paper analyzes genetic variation in 806 drug-related genes using 60,706 human exomes, finding that most variants are rare but many patients carry functional variants affecting drug efficacy and risk varies by ancestry.

The paper improves warfarin dose prediction for African Americans by integrating population-specific gene expression imputation with genetic variation data.

DGIdb 3.0 updates and expands the drug-gene interaction database by adding new sources, improving the codebase, and enhancing API features.

This study evaluates the clinical relevance of pharmacogenetic tests offered by 23andMe, finding variability in validity and utility across tests and populations.