A genome-wide association study of plasma concentrations of warfarin enantiomers and metabolites in sub-Saharan black-African patients

Local ancestry informed GWAS of warfarin dose requirement in African Americans identifies a novel CYP2C19 splice QTL

African Americans (AAs) are underrepresented in pharmacogenomics which has led to a significant gap in knowledge. AAs are admixed and can inherit specific loci from either their African or European ancestor, known as local ancestry (LA). A previous study in AAs identified single nucleotide polymorphisms (SNPs) located in the CYP2C cluster that are associated with warfarin dose. However, LA was not considered in this study. An IWPC cohort (N=340) was used to determine the LA-adjusted association with warfarin dose. Ancestry-specific GWAS's were conducted with TRACTOR and ancestry tracts were meta-analyzed using METAL. We replicated top associations in the independent ACCOuNT cohort of AAs (N=309) and validated associations in a warfarin pharmacokinetic study in AAs. To elucidate functional roles of top associations, we performed short-read RNA-sequencing from AA hepatocytes carrying each genotype for expression of CYP2C9 and CYP2C19. We identified 6 novel genome-wide significant SNPs (P<5E-8) in the CYP2C locus (lead SNP, rs7906871 (P=3.14E-8)). These associations were replicated (P≤2.76E-5) and validated with a pharmacokinetic association for S-Warfarin concentration in plasma (P=0.048). rs7906871 explains 6.0% of the variability in warfarin dose in AAs. Multivariate regression including rs7906871, previously associated SNPs, clinical and demographic factors explain 37% of dose variability, greater than previously reported studies in AAs. RNA-seq data in AA hepatocytes identified a significant alternate exon inclusion event between exons 6 and 7 in CYP2C19 for carriers of rs7906871. In conclusion, we have found and replicated a novel CYP2C variant associated with warfarin dose requirement and potential functional consequences to CYP2C19.

A meta-analysis and polygenic score study identifies novel genetic markers for waist-hip ratio in African populations

OBJECTIVE

Understanding the genetic underpinnings of anthropometric traits in diverse populations is crucial for gaining insights into their biological mechanisms and potential implications for health.

METHODS

We conducted a genome-wide association study, meta-analysis, and gene set analysis of waist-hip ratio (WHR), WHR adjusted for BMI (WHRadjBMI), waist circumference, BMI, and height using the African Collaborative Center for Microbiome and Genomics Research (ACCME) cohort (n = ~11,000) for discovery and polygenic score target analyses and the Africa America Diabetes Mellitus (AADM) study (n = ~5200) for replication and polygenic score validation. We generated and compared polygenic scores from European, African, Afro-Caribbean, and multiethnic ancestry populations.

RESULTS

The top loci associated with each trait in the meta-analysis were in CD36 (rs3211826 [p = 5.90 × 10-12] for WHR and rs73709003 [p = 1.75 × 10-13] for WHRadjBMI), IFI27L1 (rs59775050 [p = 2.66 × 10-08] for waist circumference), INPP4B (rs2636629 [p = 1.44 × 10-09] for BMI), and HMGA1 (rs6937622 [p = 1.40 × 10-15] for height) gene regions. A novel variant rs7797157, near GNAT3, was also significantly associated with WHR (p = 2.50 × 10-10) and WHRadjBMI (p = 2.66 × 10-11). The ancestry-specific parameters for the best predictive polygenic scores were European ancestry (R2 = 0.68%; p = 1.63 × 10-16) and multiethnic ancestry (R2 = 0.06%; p = 1.29 × 10-02) for WHR; European ancestry (R2 = 1.36%; p = 2.94 × 10-31) and multiethnic ancestry (R2 = 1.12%; p = 3.52 × 10-25) for BMI; and European ancestry (R2 = 3.16%; p = 2.95 × 10-73), African ancestry (R2 = 4.16%; p = 1.75 × 10-96), and African and Afro-Caribbean ancestry (R2 = 2.67%; p = 4.35 × 10-62) for height.

CONCLUSIONS

The discovery of a novel locus for WHR and genetic signals for each trait and the assessment of polygenic score performance underscore the importance of conducting well-powered studies in diverse populations.

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

ABSTRACT

Warfarin dose requirements are highly variable because of clinical and genetic factors. Although 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 (GWASs) in 4 African cohorts from Uganda, South Africa, and Zimbabwe, totaling 989 warfarin-treated participants who reached stable dose and had international normalized ratios within therapeutic ranges. We also included 2 African American cohorts recruited by the International Warfarin Pharmacogenetics Consortium (n = 316) and the University of Alabama at Birmingham (n = 199). After the GWAS, we performed standard error-weighted meta-analyses and then conducted stepwise conditional analyses to account for known loci in chromosomes 10 and 16. The genome-wide significance threshold was set at P < 5 × 10-8. The meta-analysis, comprising 1504 participants, identified 242 significant SNPs across 3 genomic loci, with 99.6% of these located within known loci on chromosomes 10 (top SNP: rs58800757, P = 4.27 × 10-13) and 16 (top SNP: rs9925964, P = 9.97 × 10-16). Adjustment for the VKORC1 SNP -1639G>A 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, we reaffirmed the importance of CYP2C9 and VKORC1 in influencing warfarin dose requirements, and identified a new locus (MALL), that still requires direct evidence of biological plausibility.

Mapping the Pharmacogenetic Landscape in a Ugandan Population: Implications for Personalized Medicine in an Underrepresented Population

Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience widespread polypharmacy. As population-specific genetic studies are crucial to understanding unique genetic profiles and optimizing treatments to reduce medication-related complications in this diverse population, the present study aims to characterize the pharmacogenomics profile of a rural Ugandan population. We analyzed low-pass whole genome sequencing data from 1998 Ugandans to investigate 18 clinically actionable pharmacogenes in this population. We utilized PyPGx to identify star alleles (haplotype patterns) and compared allele frequencies across populations using the Pharmacogenomics Knowledgebase PharmGKB. Clinical interpretations of the identified alleles were conducted following established dosing guidelines. Over 99% of participants displayed actionable phenotypes across the 18 pharmacogenes, averaging 3.5 actionable genotypes per individual. Several variant alleles known to affect drug metabolism (i.e., CYP3A5*1, CYP2B6*9, CYP3A5*6, CYP2D6*17, CYP2D6*29, and TMPT*3C)-which are generally more prevalent in African individuals-were notably enriched in the Ugandan cohort, beyond reported frequencies in other African peoples. More than half of the cohort exhibited a predicted impaired drug response associated with CFTR, IFNL3, CYP2B6, and CYP2C19, and approximately 31% predicted altered CYP2D6 metabolism. Potentially impaired CYP2C9, SLCO1B1, TPMT, and DPYD metabolic phenotypes were also enriched in Ugandans compared with other African populations. Ugandans exhibit distinct allele profiles that could impact drug efficacy and safety. Our findings have important implications for pharmacogenomics in Uganda, particularly with respect to the treatment of prevalent communicable and non-communicable diseases, and they emphasize the potential of pharmacogenomics-guided therapies to optimize healthcare outcomes and precision medicine in Uganda.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

LA-GEM: imputation of gene expression with incorporation of Local Ancestry

Gene imputation and TWAS have become a staple in the genomics medicine discovery space; helping to identify genes whose regulation effects may contribute to disease susceptibility. However, the cohorts on which these methods are built are overwhelmingly of European Ancestry. This means that the unique regulatory variation that exist in non-European populations, specifically African Ancestry populations, may not be included in the current models. Moreover, African Americans are an admixed population, with a mix of European and African segments within their genome. No gene imputation model thus far has incorporated the effect of local ancestry (LA) on gene expression imputation. As such, we created LA-GEM which was trained and tested on a cohort of 60 African American hepatocyte primary cultures. Uniquely, LA-GEM include local ancestry inference in its prediction of gene expression. We compared the performance of LA-GEM to PrediXcan trained the same dataset (with no inclusion of local ancestry) We were able to reliably predict the expression of 2559 genes (1326 in LA-GEM and 1236 in PrediXcan). Of these, 546 genes were unique to LA-GEM, including the CYP3A5 gene which is critical to drug metabolism. We conducted TWAS analysis on two African American clinical cohorts with pharmacogenomics phenotypic information to identity novel gene associations. In our IWPC warfarin cohort, we identified 17 transcriptome-wide significant hits. No gene reached are prespecified significance level in the clopidogrel cohort. We did see suggestive association with RAS3A to P2RY12 Reactivity Units (PRU), a clinical measure of response to anti-platelet therapy. This method demonstrated the need for the incorporation of LA into study in admixed populations.

Novel Gene Polymorphisms for Stable Warfarin Dose in a Korean Population: Genome-Wide Association Study

Warfarin has a narrow therapeutic window and high intra- and inter-individual variability. Considering that many published papers on genotype-guided dosing are derived from European populations, the aim of this study was to investigate novel genetic variants associated with the variability of stable warfarin dose in the Korean population with cardiac valve replacement, using the GWAS approach. This retrospective cohort study was performed from January 1982 to December 2020 at the Severance Cardiovascular Hospital of Yonsei University College of Medicine. GWAS was performed to identify associations between genotypes and the warfarin maintenance dose, by comparing the allele frequency of genetic variants between individuals. Then, the extent of genetic and non-genetic factors on the dose variability was determined by multivariable regression analysis. The study enrolled 214 participants, and the most robust signal cluster was detected on chromosome 16 around VKORC1. Followed by VKORC1, three novel variants (NKX2-6 rs310279, FRAS1 rs4386623, and FAM201A rs1890109) showed an association with stable warfarin dose requirement in univariate analysis. The algorithm was constructed by using multivariable analysis that includes genetic and non-genetic factors, and it could explain 58.5% of the variations in stable warfarin doses. In this variability, VKORC1 rs9934438 and FRAS1 rs4386623 accounted for 33.0% and 9.9%, respectively. This GWAS analysis identified the fact that three novel variants (NKX2-6 rs310279, FRAS1 rs4386623, and FAM201A rs1890109) were associated with stable warfarin doses. Additional research is necessary to validate the results and establish personalized treatment strategies for the Korean population.

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.