Pathway analysis of genome-wide data improves warfarin dose prediction

Background: Many genome-wide association studies focus on associating single loci with target phenotypes. However, in the setting of rare variation, accumulating sufficient samples to assess these associations can be difficult. Moreover, multiple variations in a gene or a set of genes within a pathway may all contribute to the phenotype, suggesting that the aggregation of variations found over the gene or pathway may be useful for improving the power to detect associations. Results: Here, we present a method for aggregating single nucleotide polymorphisms (SNPs) along biologically relevant pathways in order to seek genetic associations with phenotypes. Our method uses all available genetic variants and does not remove those in linkage disequilibrium (LD). Instead, it uses a novel SNP weighting scheme to down-weight the contributions of correlated SNPs. We apply our method to three cohorts of patients taking warfarin: two European descent cohorts and an African American cohort. Although the clinical covariates and key pharmacogenetic loci for warfarin have been characterized, our association metric identifies a significant association with mutations distributed throughout the pathway of warfarin metabolism. We improve dose prediction after using all known clinical covariates and pharmacogenetic variants in VKORC1 and CYP2C9. In particular, we find that at least 1% of the missing heritability in warfarin dose may be due to the aggregated effects of variations in the warfarin metabolic pathway, even though the SNPs do not individually show a significant association. Conclusions: Our method allows researchers to study aggregative SNP effects in an unbiased manner by not preselecting SNPs. It retains all the available information by accounting for LD-structure through weighting, which eliminates the need for LD pruning

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them

Genetic factors influencing warfarin dose in Black-African patients: a systematic review and meta-analysis.

Warfarin is the most commonly used oral anticoagulant in sub-Saharan Africa. Dosing is challenging due to a narrow therapeutic index and high inter-individual variability in dose requirements. To evaluate the genetic factors affecting warfarin dosing in Black-Africans, we performed a meta-analysis of 48 studies (2,336 patients). Significant predictors for CYP2C9 and stable dose included rs1799853 (CYP2C9*2), rs1057910 (CYP2C9*3), rs28371686 (CYP2C9*5), rs9332131 (CYP2C9*6), and rs28371685 (CYP2C9*11) reducing dose by 6.8, 12.5, 13.4, 8.1, and 5.3 mg/week respectively. VKORC1 variants rs9923231 (-1639G>A), rs9934438 (1173C>T), rs2359612 (2255C>T), rs8050894 (1542G>C), and rs2884737 (497T>G) decreased dose by 18.1, 21.6, 17.3, 11.7, and 19.6 mg/week, respectively while rs7294 (3730G>A) increased dose by 6.9 mg/week. Finally, rs12777823 (CYP2C gene cluster) was associated with a dose reduction of 12.7 mg/week. Few studies were conducted in Africa, and patient numbers were small, highlighting the need for further work in Black Africans to evaluate genetic factors determining warfarin response

Meta-analysis of genome-wide association studies of stable warfarin dose in patients of African ancestry.

Warfarin dose requirements are highly variable due to clinical and genetic factors. While genetic variants influencing warfarin dose have been identified in European and East Asian populations, more work is needed to identify African-specific genetic variants to help optimize warfarin dosing. We performed genome-wide association studies (GWAS) in four African cohorts from Uganda, South Africa, and Zimbabwe, totalling 989 warfarin-treated participants who reached stable dose and had international normalized ratios within therapeutic ranges. We also included two African American cohorts recruited by the International Warfarin Pharmacogenetics Consortium (n=316) and the University of Alabama at Birmingham (n=199). Following the GWAS, we performed standard error-weighted meta-analyses and then conducted stepwise conditional analyses to account for known loci (the CYP2C cluster SNP rs12777823 and CYP2C9 in chromosome 10; VKORC1 in chromosome 16). The genome-wide significance threshold was set at PA revealed an additional locus on chromosome 2 (top SNPs rs116057875/rs115254730/rs115240773, P=3.64×10-8), implicating the MALL gene, that could indirectly influence warfarin response through interactions with caveolin-1. In conclusion, our meta-analysis of six cohorts of warfarin-treated patients of African ancestry reaffirmed the importance of CYP2C9 and VKORC1 in influencing warfarin dose requirements. We also identified a new locus (MALL), that still requires direct evidence of biological plausibility

The Role of Pharmacogenomics in the Management of Traditional and Novel Oral Anticoagulants

Warfarin is the most commonly prescribed oral anticoagulant. However, it remains a difficult drug to manage mostly because of its narrow therapeutic index and wide inter-patient variability in anticoagulant effects. Over the past decade, there has been substantial progress in our understanding of genetic contributions to variable warfarin response, particularly in regard to warfarin dose requirements. The genes encoding for cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex 1 (VKORC1) are the major genetic determinants of warfarin pharmacokinetics and pharmacodynamics, respectively. Numerous studies have demonstrated significant contributions of these genes to warfarin dose requirements. The CYP2C9 gene has also been associated with bleeding risk with warfarin. The CYP4F2 gene influences vitamin K availability and makes minor contributions to warfarin dose requirements. Less is known about genes influencing warfarin response in African Americans compared to other racial groups, but this is the focus of on-going research. Several warfarin pharmacogenetic dosing algorithms and FDA-cleared genotyping tests are available for clinical use. Clinical trials are on-going to determine the clinical utility and cost effectiveness of genotype-guided warfarin dosing. Results from these trials will likely influence clinical uptake and third party payer reimbursement for genotype-guided warfarin therapy. Currently, there is a lack of pharmacogenetic data with the newly approved oral anticoagulant, dabigatran, and with other oral anticoagulants in the research and development pipeline

Discovery of novel hepatocyte eQTLs in African Americans.

African Americans (AAs) are disproportionately affected by metabolic diseases and adverse drug events, with limited publicly available genomic and transcriptomic data to advance the knowledge of the molecular underpinnings or genetic associations to these diseases or drug response phenotypes. To fill this gap, we obtained 60 primary hepatocyte cultures from AA liver donors for genome-wide mapping of expression quantitative trait loci (eQTL) using LAMatrix. We identified 277 eGenes and 19,770 eQTLs, of which 67 eGenes and 7,415 eQTLs are not observed in the Genotype-Tissue Expression Project (GTEx) liver eQTL analysis. Of the eGenes found in GTEx only 25 share the same lead eQTL. These AA-specific eQTLs are less correlated to GTEx eQTLs. in effect sizes and have larger Fst values compared to eQTLs found in both cohorts (overlapping eQTLs). We assessed the overlap between GWAS variants and their tagging variants with AA hepatocyte eQTLs and demonstrated that AA hepatocyte eQTLs can decrease the number of potential causal variants at GWAS loci. Additionally, we identified 75,002 exon QTLs of which 48.8% are not eQTLs in AA hepatocytes. Our analysis provides the first comprehensive characterization of AA hepatocyte eQTLs and highlights the unique discoveries that are made possible due to the increased genetic diversity within the African ancestry genome