Genetic variant in folate homeostasis is associated with lower warfarin dose in African Americans

Being precise with anticoagulation to reduce adverse drug reactions: are we there yet?

Anticoagulants are potent therapeutics widely used in medical and surgical settings, and the amount spent on anticoagulation is rising. Although warfarin remains a widely prescribed oral anticoagulant, prescriptions of direct oral anticoagulants (DOACs) have increased rapidly. Heparin-based parenteral anticoagulants include both unfractionated and low molecular weight heparins (LMWHs). In clinical practice, anticoagulants are generally well tolerated, although interindividual variability in response is apparent. This variability in anticoagulant response can lead to serious incident thrombosis, haemorrhage and off-target adverse reactions such as heparin-induced thrombocytopaenia (HIT). This review seeks to highlight the genetic, environmental and clinical factors associated with variability in anticoagulant response, and review the current evidence base for tailoring the drug, dose, and/or monitoring decisions to identified patient subgroups to improve anticoagulant safety. Areas that would benefit from further research are also identified. Validated variants in VKORC1, CYP2C9 and CYP4F2 constitute biomarkers for differential warfarin response and genotype-informed warfarin dosing has been shown to reduce adverse clinical events. Polymorphisms in CES1 appear relevant to dabigatran exposure but the genetic studies focusing on clinical outcomes such as bleeding are sparse. The influence of body weight on LMWH response merits further attention, as does the relationship between anti-Xa levels and clinical outcomes. Ultimately, safe and effective anticoagulation requires both a deeper parsing of factors contributing to variable response, and further prospective studies to determine optimal therapeutic strategies in identified higher risk subgroups.

Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry

Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.

Genetic Factors Influencing Warfarin Dose in Han Chinese Population: A Systematic Review and Meta-Analysis of Cohort Studies

OBJECTIVE

To investigate the association of single nucleotide polymorphisms (SNPs) of various genes known to influence mean daily warfarin dose (MDWD) in the Han Chinese population.

METHODS

The study is a systematic review and meta-analysis. Selected studies retrieved by searching Pubmed, Embase (Ovid), Medline, CNKI, Wanfang data, and SinoMed (from their inception to 31 August 2022) for the cohort studies assessing genetic variations that may possibly influence MDWD in Chinese patients were included.

RESULT

A total of 46 studies including a total of 10,102 Han Chinese adult patients were finally included in the meta-analysis. The impact of 20 single nucleotide polymorphisms (SNPs) in 8 genes on MDWD was analyzed. The significant impact of some of these SNPs on MDWD requirements was demonstrated. Patients with CYP4F2 rs2108622 TT, EPHX1 rs2260863 GC, or NQO1 rs1800566 TT genotype required more than 10% higher MDWD. Furthermore, patients with ABCB1 rs2032582 GT or GG, or CALU rs2290228 TT genotype required more than 10% lower MDWD. Subgroup analysis showed that patients with EPHX1 rs2260863 GC genotype required 7% lower MDWD after heart valve replacement (HVR).

CONCLUSION

This is the first systematic review and meta-analysis assessing the association between single nucleotide polymorphisms (SNPs) of various genes known to influence MDWD besides CYP2C9 and VKORC1 in the Han Chinese population. CYP4F2 (rs2108622), GGCX (rs12714145), EPHX1 (rs2292566 and rs2260863), ABCB1 (rs2032582), NQO1 (rs1800566), and CALU (rs2290228) SNPs might be moderate factors affecting MDWD requirements.

REGISTERED INFORMATION

PROSPERO International Prospective Register of Systematic Reviews (CRD42022355130).

Targeted next-generation sequencing of genes involved in Warfarin Pharmacodynamics and pharmacokinetics pathways using the Saudi Warfarin Pharmacogenetic study (SWAP)

BACKGROUND

Warfarin is an oral anticoagulant commonly used for treatment and prophylaxis against thromboembolic events. Warfarins's narrow therapeutic index window is one of the main challenges in clinical practice; thus, it requires frequent monitoring and dose adjustment to maintain patients' therapeutic range. Warfarin dose variation and response are attributed to several inter-and intra-individuals factors, including genetic variants in enzymes involved in warfarin pharmacokinetics (PK) and pharmacodynamics (PD) pathways. Thus, we aim to utilize the next-generation sequencing (NGS) approach to identify rare and common genetic variants that might be associated with warfarin responsiveness.

METHOD AND RESULTS

A predesigned NGS panel that included 16 genes involved in Warfarin PK/PD pathways was used to sequence 786 patients from the Saudi Warfarin Pharmacogenetic Cohort (SWAP). Identified variants were annotated using several annotation tools to identify the pathogenicity and allele frequencies of these variants. We conducted variants-level association tests with warfarin dose. We identified 710 variants within the sequenced genes; 19% were novel variants, with the vast majority being scarce variants. The genetic association tests showed that VKORC1 (rs9923231, and rs61742245), CYP2C9 (rs98332238, rs9332172, rs1057910, rs9332230, rs1799853, rs1057911, and rs9332119), CYP2C19 (rs28399511, and rs3758581), and CYP2C8 (rs11572080 and rs10509681) were significantly associated with warfarin weekly dose. Our model included genetics, and non-genetic factors explained 40.1% of warfarin dose variation.

CONCLUSION

The study identifies novel variants associated with warfarin dose in the Saudi population. These variants are more likely to be population-specific variants, suggesting that population-specific studies should be conducted before adopting a universal warfarin genotype-guided dosing algorithm.

Warfarin Dosing in Patients with CYP2C9*5 Variant Alleles

Pharmacogenetic dosing improves the accuracy of warfarin dosing, but current pharmacogenetic dosing algorithms are less accurate in populations of African ancestry. The cytochrome P450 2C9*5 (CYP2C9*5) allele is found almost exclusively in populations of African ancestry, and in-vitro studies suggest CYP2C9*5 is associated with reduced clearance of warfarin. The clinical relevance of this SNP is uncertain. In this multi-centered study of 2298 patients (49% female, 35% Black) taking warfarin, we quantified the association between the CYP2C9*5 allele and warfarin requirements. The CYP2C9*5 SNP was present in 2.3% of Black and 0.07% of White patients. Without taking CYP2C9*5 into account, pharmacogenetic algorithms that include other SNPs overestimated the warfarin dose by 30% (95% CI [19%-40%], p<0.001), an average of 1.87 mg/d (SD 1.64) in heterozygotes (p < 0.001). Non-carriers required a slightly (0.23 mg/d, SD 2.09) higher than predicted dose. Genotyping for CYP2C9*5 corrected the potential overdose and halved overall dosing error in heterozygotes. Patients carrying CYP2C9*5 require a clinically relevant reduction in warfarin dose. Given the potential to improve the accuracy and safety of warfarin dosing in populations of African ancestry, we have incorporated this SNP into a non-profit website to assist warfarin initiation (www.WarfarinDosing.org).

Genomewide Association Studies in Pharmacogenomics

The increasing availability of genotype data linked with information about drug-response phenotypes has enabled genomewide association studies (GWAS) that uncover genetic determinants of drug response. GWAS have discovered associations between genetic variants and both drug efficacy and adverse drug reactions. Despite these successes, the design of GWAS in pharmacogenomics (PGx) faces unique challenges. In this review, we analyze the last decade of GWAS in PGx. We review trends in publications over time, including the drugs and drug classes studied and the clinical phenotypes used. Several data sharing consortia have contributed substantially to the PGx GWAS literature. We anticipate increased focus on biobanks and highlight phenotypes that would best enable future PGx discoveries.

Pharmacogenomics in Cardiovascular Diseases

Cardiovascular pharmacogenomics is the study and identification of genomic markers that are associated with variability in cardiovascular drug response, cardiovascular drug-related outcomes, or cardiovascular drug-related adverse events. This overview presents an introduction and historical background to cardiovascular pharmacogenomics, and a protocol for designing a cardiovascular pharmacogenomics study. Important considerations are also included for constructing a cardiovascular pharmacogenomics phenotype, designing the replication or validation strategy, common statistical approaches, and how to put the results in context with the cardiovascular drug or cardiovascular disease under investigation. © 2021 Wiley Periodicals LLC. Basic Protocol: Designing a cardiovascular pharmacogenomics study.

Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine

Response to medications, the principal treatment modality for acute and chronic diseases, is highly variable, with 40-70% of patients exhibiting lack of efficacy or adverse drug reactions. With ~ 15-30% of this variability explained by genetic variants, pharmacogenomics has become a valuable tool in our armamentarium for optimizing treatments and is poised to play an increasing role in clinical care. This review presents the progress made toward elucidating genetic underpinnings of drug response including discovery of race/ancestry-specific pharmacogenetic variants and discusses the current evidence and evidence framework for actionability. The review is framed in the context of changing demographics and evolving views related to race and ancestry. Finally, it highlights the vital role played by cohort studies in elucidating genetic differences in drug response across race and ancestry and the informal collaborations that have enabled the field to bridge the "bench to bedside" translational gap.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

Variant discovery using next-generation sequencing and its future role in pharmacogenetics

Next-generation sequencing (NGS) has enabled the discovery of a multitude of novel and mostly rare variants in pharmacogenes that may alter a patient’s therapeutic response to drugs. In addition to single nucleotide variants, structural variation affecting the number of copies of whole genes or parts of genes can be detected. While current guidelines concerning clinical implementation mostly act upon well-documented, common single nucleotide variants to guide dosing or drug selection, in silico and large-scale functional assessment of rare variant effects on protein function are at the forefront of pharmacogenetic research to facilitate their clinical integration. Here, we discuss the role of NGS in variant discovery, paving the way for more comprehensive genotype-guided pharmacotherapy that can translate to improved clinical care.

The Genetics of Warfarin Dose-Response Variability in Africans: An Expert Perspective on Past, Present, and Future

Coumarins such as warfarin are prescribed for prevention and treatment of thromboembolic disorders. Warfarin remains the most widely prescribed and an anticoagulant of choice in Africa. Warfarin use is, however, limited by interindividual variability in pharmacokinetics and a narrow therapeutic index. The difference in patients' pharmacodynamic responses to warfarin has been attributed to genetic variation in warfarin metabolism and molecular targets (e.g., CYP2C9 and VKORC1) and host-environment interactions. This expert review offers a synthesis of human genetics studies in Africans with respect to pharmacogenetics-informed warfarin dosing. We identify areas that need future research attention or could benefit from harnessing existing pharmacogenetics knowledge toward rational and optimal therapeutics with warfarin in African patients. A literature search was conducted until January 2019. A total of 343 articles were retrieved from nine African countries: Botswana, Ethiopia, Egypt, Ghana, Kenya, South Africa, Sudan, Tanzania, and Mozambique. We found 19 studies on genetics of warfarin treatment specifically among Africans. Genes examined included CYP2C9, VKORC1, CYP4F2, APOE, CALU, GGCX, and EPHX1. CYP2C9*2 and *3 alleles were highly frequent among Egyptians, while rare in other African populations. CYP2C9*5, *8, *9, and *11, and VKORC1 Asp36Tyr genetic variants explained warfarin variability in Africans better, compared to CYP2C9*2 and *3. In Africa, there is limited pharmacogenetics data on warfarin. Therefore, future research and funding commitments should be prioritized to ensure safe and effective use of warfarin in Africa. Lessons learned in Africa from the science of pharmacogenetics would inform rational therapeutics in hematology, cardiology, and surgical specialties worldwide.

Impact of CYP2C9, VKORC1, ApoE and ABCB1 polymorphisms on stable warfarin dose requirements in elderly Chinese patients

Aim: To analyze the impact of nongenetic factors and gene polymorphisms on warfarin dose requirements in elderly Shanghai Han Chinese patients. Materials & methods: Genotypes of CYP2C9 (rs1799853 and rs1057910), FPGS (rs7856096), ApoE (rs7412 and rs429358), GGCX (rs699664 and rs12714145), EPHX1 (rs4653436, rs1877724, rs1051740 and rs1131873), NQO1 (rs1800566 and rs10517), ABCB1 (rs1045642), VKORC1 (rs9923231) and CYP4F2 (rs2108622) in 214 patients with stable warfarin dose were determined and their demographic characteristics were recorded. Results: Multiple linear regression analysis revealed that VKORC1 rs9923231, CYP2C9*3 rs1057910, ApoE rs7412, age, BMI and concomitant amiodarone could explain 37.0% of the individual variations of daily stable warfarin dose. Conclusion: VKORC1 rs9923231, CYP2C9*3 rs1057910, ApoE rs7412, age, BMI and concomitant amiodarone play an important role in stable dose variation of warfarin in elderly Shanghai Han Chinese patients, whereas ABCB1 rs1045642 is not a significant genetic factor.

Identifying mutation-driven changes in gene functionality that lead to venous thromboembolism

Venous thromboembolism (VTE) is a common hematological disorder. VTE affects millions of people around the world each year and can be fatal. Earlier studies have revealed the possible VTE genetic risk factors in Europeans. The 2018 Critical Assessment of Genome Interpretation (CAGI) challenge had asked participants to distinguish between 66 VTE and 37 non-VTE African American (AA) individuals based on their exome sequencing data. We used variants from AA VTE association studies and VTE genes from DisGeNET database to evaluate VTE risk via four different approaches; two of these methods were most successful at the task. Our best performing method represented each exome as a vector of predicted functional effect scores of variants within the known genes. These exome vectors were then clustered with k-means. This approach achieved 70.8% precision and 69.7% recall in identifying VTE patients. Our second-best ranked method had collapsed the variant effect scores into gene-level function changes, using the same vector clustering approach for patient/control identification. These results show predictability of VTE risk in AA population and highlight the importance of variant-driven gene functional changes in judging disease status. Of course, more in-depth understanding of AA VTE pathogenicity is still needed for more precise predictions.

Predicting venous thromboembolism risk from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges

Genetics play a key role in venous thromboembolism (VTE) risk, however established risk factors in European populations do not translate to individuals of African descent because of the differences in allele frequencies between populations. As part of the fifth iteration of the Critical Assessment of Genome Interpretation, participants were asked to predict VTE status in exome data from African American subjects. Participants were provided with 103 unlabeled exomes from patients treated with warfarin for non-VTE causes or VTE and asked to predict which disease each subject had been treated for. Given the lack of training data, many participants opted to use unsupervised machine learning methods, clustering the exomes by variation in genes known to be associated with VTE. The best performing method using only VTE related genes achieved an area under the ROC curve of 0.65. Here, we discuss the range of methods used in the prediction of VTE from sequence data and explore some of the difficulties of conducting a challenge with known confounders. In addition, we show that an existing genetic risk score for VTE that was developed in European subjects works well in African Americans.

Identifying core biological processes distinguishing human eye tissues with precise systems-level gene expression analyses and weighted correlation networks

The human eye is built from several specialized tissues which direct, capture and pre-process information to provide vision. The gene expression of the different eye tissues has been extensively profiled with RNA-seq across numerous studies. Large consortium projects have also used RNA-seq to study gene expression patterning across many different human tissues, minus the eye. There has not been an integrated study of expression patterns from multiple eye tissues compared with other human body tissues. We have collated all publicly available healthy human eye RNA-seq datasets as well as dozens of other tissues. We use this fully integrated dataset to probe the biological processes and pan expression relationships between the cornea, retina, retinal pigment epithelium (RPE)-choroid complex, and the rest of the human tissues with differential expression, clustering and gene ontology term enrichment tools. We also leverage our large collection of retina and RPE-choroid tissues to build the first human weighted gene correlation networks and use them to highlight known biological pathways and eye gene disease enrichment. We also have integrated publicly available single-cell RNA-seq data from mouse retina into our framework for validation and discovery. Finally, we make all these data, analyses and visualizations available via a powerful interactive web application (https://eyeintegration.nei.nih.gov/).

A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)

Genome-wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression-free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab-paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease-free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.

Pharmacogenomics in dermatology: tools for understanding gene-drug associations

Pharmacogenomics aims to associate human genetic variability with differences in drug phenotypes in order to tailor drug treatment to individual patients. The massive amount of genetic data generated from large cohorts of patients with variable drug phenotypes have led to advances in this field. Understanding the application of pharmacogenomics in dermatology could inform clinical practice and provide insight for future research. The Pharmacogenomics Knowledge Base and the Clinical Pharmacogenetics Implementation Consortium are among the resources to help clinicians and researchers navigate the many gene-drug associations that have already been discovered. The implementation of clinical pharmacogenomics within health care systems remains an area of ongoing development. This review provides an introduction to the field of pharmacogenomics and to current pharmacogenomics resources using examples of gene-drug associations relevant to the field of dermatology.

Identification of a Genomic Region between SLC29A1 and HSP90AB1 Associated with Risk of Bevacizumab-Induced Hypertension: CALGB 80405 (Alliance)

Purpose: Bevacizumab is a VEGF-specific angiogenesis inhibitor indicated as an adjunct to chemotherapy for the treatment of multiple cancers. Hypertension is commonly observed during bevacizumab treatment, and high-grade toxicity can limit therapy or lead to cardiovascular complications. The factors that contribute to interindividual variability in blood pressure rise during bevacizumab treatment are not well understood.Experimental Design: To identify genomic regions associated with bevacizumab-induced hypertension risk, sequencing of candidate genes and flanking regulatory regions was performed on 61 patients treated with bevacizumab (19 cases developed early-onset grade 3 hypertension and 42 controls had no reported hypertension in the first six cycles of treatment). SNP-based tests for common variant associations and gene-based tests for rare variant associations were performed in 174 candidate genes.Results: Four common variants in independent linkage disequilibrium blocks between SLC29A1 and HSP90AB1 were among the top associations. Validation in larger bevacizumab-treated cohorts supported association between rs9381299 with early grade 3+ hypertension (P = 0.01; OR, 2.4) and systolic blood pressure >180 mm Hg (P = 0.02; OR, 2.1). rs834576 was associated with early grade 3+ hypertension in CALGB 40502 (P = 0.03; OR, 2.9). These SNP regions are enriched for regulatory elements that may potentially increase gene expression. In vitro overexpression of SLC29A1 in human endothelial cells disrupted adenosine signaling and reduced nitric oxide levels that were further lowered upon bevacizumab exposure.Conclusions: The genomic region between SLC29A1 and HSP90AB1 and its role in regulating adenosine signaling are key targets for further investigation into the pathogenesis of bevacizumab-induced hypertension. Clin Cancer Res; 24(19); 4734-44. ©2018 AACR.

The Diversity of REcent and Ancient huMan (DREAM): A New Microarray for Genetic Anthropology and Genealogy, Forensics, and Personalized Medicine

The human population displays wide variety in demographic history, ancestry, content of DNA derived from hominins or ancient populations, adaptation, traits, copy number variation, drug response, and more. These polymorphisms are of broad interest to population geneticists, forensics investigators, and medical professionals. Historically, much of that knowledge was gained from population survey projects. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism genotyping, their design specifications are limited and they do not allow a full exploration of biodiversity. We thereby aimed to design the Diversity of REcent and Ancient huMan (DREAM)—an all-inclusive microarray that would allow both identification of known associations and exploration of standing questions in genetic anthropology, forensics, and personalized medicine. DREAM includes probes to interrogate ancestry informative markers obtained from over 450 human populations, over 200 ancient genomes, and 10 archaic hominins. DREAM can identify 94% and 61% of all known Y and mitochondrial haplogroups, respectively, and was vetted to avoid interrogation of clinically relevant markers. To demonstrate its capabilities, we compared its F_ST distributions with those of the 1000 Genomes Project and commercial arrays. Although all arrays yielded similarly shaped (inverse J) F_ST distributions, DREAM’s autosomal and X-chromosomal distributions had the highest mean F_ST, attesting to its ability to discern subpopulations. DREAM performances are further illustrated in biogeographical, identical by descent, and copy number variation analyses. In summary, with approximately 800,000 markers spanning nearly 2,000 genes, DREAM is a useful tool for genetic anthropology, forensic, and personalized medicine studies.

VKORC1-1639A allele influences warfarin maintenance dosage among Blacks receiving warfarin anticoagulation: a retrospective cohort study

AIM

The study objectives were to investigate the association between selected CYP2C9 and VKORC1 single nucleotide polymorphisms with serious bleeding or thrombotic risk, and to estimate mean daily maintenance dose of warfarin and international normalized ratio measurements among Blacks receiving warfarin anticoagulation.

METHODS

We conducted a retrospective cohort study among 230 Black adults receiving warfarin for a minimum of three consecutive months with a confirmed date of first dosage.

RESULTS

A lower mean daily maintenance dosage of warfarin was required to maintain an international normalized ratio measurement within the therapeutic range among Blacks with the VKORC1-1639G>A variant alleles ([G/A vs G/G, p = 0.02], [A/A vs G/A, p = 0.008] and [A/A vs G/G, p = 0.001]).

CONCLUSION

Data indicated that VKORC1-1639A variant allele influenced warfarin daily maintenance dosage among our small, likely admixed Black patient population.

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

Background

Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects.

Methods

Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions.

Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals.

Results

We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations.

Conclusions

Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions.

MATLAB code is available at https://github.com/assafgo/warfarin-cohort

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0495-0) contains supplementary material, which is available to authorized users.

An assessment of the impact of pharmacogenomics on health disparities: a systematic literature review

This review assessed evidence of disparities in benefits of pharmacogenomics related to 'model performance' in subgroups of patients and studies which reported impact on health inequalities. 'Model performance' refers to the ability of algorithms including clinical, environmental and genetic information to guide treatment. A total of 4978 abstracts were screened by one reviewer and 30% (1494) were double screened by a second independent reviewer, after which data extraction was performed. Additional forward and backward citation searching of reference lists was conducted. Investigators independently double rated study quality and applicability of included studies. Only five individual studies were identified which met our inclusion criteria, but were contradictory in their conclusions. While three studies of genotype-guided dosing of warfarin reported that ethnic disparities in healthcare may widen, two other studies (one reporting on warfarin and reporting on clopidogrel) suggested that disparities in healthcare may reduce. There is a paucity of studies which evaluates the impact of pharmacogenomics on health disparities. Further work is required not only to evaluate health disparities between ethnic groups and countries but also within ethnic groups in the same country and solutions need to be identified to overcome these disparities.

Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.

Pannexin1 Single Nucleotide Polymorphism and Platelet Reactivity in a Cohort of Cardiovascular Patients

Pannexin1 (Panx1), a membrane channel-forming protein permitting the passage of small-sized molecules, such as ATP, is expressed in human platelets. Recently, we showed that inhibiting Panx1 affects collagen-induced platelet aggregation but not aggregation triggered by other agonists. We also found that a single nucleotide polymorphism (SNP; rs1138800) in the Panx1 gene encoded for a gain-of-function channel (Panx1-400C) and was associated with enhanced collagen-induced platelet reactivity. Here, we assessed the association of this SNP with platelet reactivity in a cohort of 758 stable cardiovascular patients from the ADRIE study treated with aspirin and/or clopidogrel. We found that presence of the Panx1-400C allele was not associated with platelet reactivity in stable cardiovascular patients, irrespective of the platelet aggregation agonist used (collagen, ADP or arachidonic acid) or the anti-platelet drug regimen. Moreover, the Panx1-400A > C SNP did also not affect the re-occurrence of cardiac ischemic events in the same stable cardiovascular patient cohort.

STRATEGIES FOR EQUITABLE PHARMACOGENOMIC-GUIDED WARFARIN DOSING AMONG EUROPEAN AND AFRICAN AMERICAN INDIVIDUALS IN A CLINICAL POPULATION

The blood thinner warfarin has a narrow therapeutic range and high inter- and intra-patient variability in therapeutic doses. Several studies have shown that pharmacogenomic variants help predict stable warfarin dosing. However, retrospective and randomized controlled trials that employ dosing algorithms incorporating pharmacogenomic variants under perform in African Americans. This study sought to determine if: 1) including additional variants associated with warfarin dose in African Americans, 2) predicting within single ancestry groups rather than a combined population, or 3) using percentage African ancestry rather than observed race, would improve warfarin dosing algorithms in African Americans. Using BioVU, the Vanderbilt University Medical Center biobank linked to electronic medical records, we compared 25 modeling strategies to existing algorithms using a cohort of 2,181 warfarin users (1,928 whites, 253 blacks). We found that approaches incorporating additional variants increased model accuracy, but not in clinically significant ways. Race stratification increased model fidelity for African Americans, but the improvement was small and not likely to be clinically significant. Use of percent African ancestry improved model fit in the context of race misclassification.

Identification of novel variants associated with warfarin stable dosage by use of a two-stage extreme phenotype strategy

Essentials Required warfarin doses for mechanical heart valves vary greatly. A two-stage extreme phenotype design was used to identify novel warfarin dose associated mutation. We identified a group of variants significantly associated with extreme warfarin dose. Four novel identified mutations account for 2.2% of warfarin dose discrepancies.

SUMMARY

Background The variation among patients in warfarin response complicates the management of warfarin therapy, and an improper therapeutic dose usually results in serious adverse events. Objective To use a two-stage extreme phenotype strategy in order to discover novel warfarin dose-associated mutations in heart valve replacement patients. Patients/method A total of 1617 stable-dose patients were enrolled and divided randomly into two cohorts. Stage I patients were genotyped into three groups on the basis of VKORC1-1639G>A and CYP2C9*3 polymorphisms; only patients with the therapeutic dose at the upper or lower 5% of each genotype group were selected as extreme-dose patients for resequencing of the targeted regions. Evaluation of the accuracy of the sequence data and the potential value of the stage I-identified significant mutations were conducted in a validation cohort of 420 subjects. Results A group of mutations were found to be significantly associated with the extreme warfarin dose. The validation work finally identified four novel mutations, i.e. DNMT3A rs2304429 (24.74%), CYP1A1 rs3826041 (47.35%), STX1B rs72800847 (7.01%), and NQO1 rs10517 (36.11%), which independently and significantly contributed to the overall variability in the warfarin dose. After addition of these four mutations, the estimated regression equation was able to account for 56.2% (R2Adj = 0.562) of the overall variability in the warfarin maintenance dose, with a predictive accuracy of 62.4%. Conclusion Our study provides evidence linking genetic variations in STX1B, DNMT3A and CYP1A1 to warfarin maintenance dose. The newly identified mutations together account for 2.2% of warfarin dose discrepancy.

STAMS: STRING-assisted module search for genome wide association studies and application to autism

Motivation: Analyzing genome wide association data in the context of biological pathways helps us understand how genetic variation influences phenotype and increases power to find associations. However, the utility of pathway-based analysis tools is hampered by undercuration and reliance on a distribution of signal across all of the genes in a pathway. Methods that combine genome wide association results with genetic networks to infer the key phenotype-modulating subnetworks combat these issues, but have primarily been limited to network definitions with yes/no labels for gene-gene interactions. A recent method (EW_dmGWAS) incorporates a biological network with weighted edge probability by requiring a secondary phenotype-specific expression dataset. In this article, we combine an algorithm for weighted-edge module searching and a probabilistic interaction network in order to develop a method, STAMS, for recovering modules of genes with strong associations to the phenotype and probable biologic coherence. Our method builds on EW_dmGWAS but does not require a secondary expression dataset and performs better in six test cases.

Results: We show that our algorithm improves over EW_dmGWAS and standard gene-based analysis by measuring precision and recall of each method on separately identified associations. In the Wellcome Trust Rheumatoid Arthritis study, STAMS-identified modules were more enriched for separately identified associations than EW_dmGWAS (STAMS P-value 3.0 × 10⁻⁴; EW_dmGWAS- P-value = 0.8). We demonstrate that the area under the Precision-Recall curve is 5.9 times higher with STAMS than EW_dmGWAS run on the Wellcome Trust Type 1 Diabetes data.

Availability and Implementation: STAMS is implemented as an R package and is freely available at https://simtk.org/projects/stams.

Contact:rbaltman@stanford.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Population differences in S-warfarin pharmacokinetics among African Americans, Asians and whites: their influence on pharmacogenetic dosing algorithms

Using population pharmacokinetic analysis (PPK), we attempted to identify predictors of S-warfarin clearance (CL(S)) and to clarify population differences in S-warfarin pharmacokinetics among a cohort of 378 African American, Asian and white patients. Significant predictors of CL(S) included clinical (age, body weight and sex) and genotypic (CYP2C9*2,*3 and *8) factors, as well as African American ethnicity, the median CL(S) being 30% lower in the latter than in Asians and whites (170 versus 243 and 250 ml h^-1, P<0.01). The plasma S-warfarin (Cp(S)) time courses following the genotype-based dosing algorithms simulated using the PPK estimates showed African Americans with CYP2C9*1/*1 and any of the VKORC1 genotypes would have an average Cp(S) at steady state 1.5-1.8 times higher than in Asians and whites. These results indicate warfarin dosing algorithms should be evaluated in each respective ethnic population. Further study of a large African American cohort will be necessary to confirm the present findings.

Folylpoly-γ-glutamate synthetase: A key determinant of folate homeostasis and antifolate resistance in cancer

Mammalians are devoid of autonomous biosynthesis of folates and hence must obtain them from the diet. Reduced folate cofactors are B9-vitamins which play a key role as donors of one-carbon units in the biosynthesis of purine nucleotides, thymidylate and amino acids as well as in a multitude of methylation reactions including DNA, RNA, histone and non-histone proteins, phospholipids, as well as intermediate metabolites. The products of these S-adenosylmethionine (SAM)-dependent methylations are involved in the regulation of key biological processes including transcription, translation and intracellular signaling. Folate-dependent one-carbon metabolism occurs in several subcellular compartments including the cytoplasm, mitochondria, and nucleus. Since folates are essential for DNA replication, intracellular folate cofactors play a central role in cancer biology and inflammatory autoimmune disorders. In this respect, various folate-dependent enzymes catalyzing nucleotide biosynthesis have been targeted by specific folate antagonists known as antifolates. Currently, antifolates are used in drug treatment of multiple human cancers, non-malignant chronic inflammatory disorders as well as bacterial and parasitic infections. An obligatory key component of intracellular folate retention and intracellular homeostasis is (anti)folate polyglutamylation, mediated by the unique enzyme folylpoly-γ-glutamate synthetase (FPGS), which resides in both the cytoplasm and mitochondria. Consistently, knockout of the FPGS gene in mice results in embryonic lethality. FPGS catalyzes the addition of a long polyglutamate chain to folates and antifolates, hence rendering them polyanions which are efficiently retained in the cell and are now bound with enhanced affinity by various folate-dependent enzymes. The current review highlights the crucial role that FPGS plays in maintenance of folate homeostasis under physiological conditions and delineates the plethora of the molecular mechanisms underlying loss of FPGS function and consequent antifolate resistance in cancer.

Population-specific single-nucleotide polymorphism confers increased risk of venous thromboembolism in African Americans

INTRODUCTION

African Americans have a higher incidence of venous thromboembolism (VTE) than European descent individuals. However, the typical genetic risk factors in populations of European descent are nearly absent in African Americans, and population-specific genetic factors influencing the higher VTE rate are not well characterized.

METHODS

We performed a candidate gene analysis on an exome-sequenced African American family with recurrent VTE and identified a variant in Protein S (PROS1) V510M (rs138925964). We assessed the population impact of PROS1 V510M using a multicenter African American cohort of 306 cases with VTE compared to 370 controls. Additionally, we compared our case cohort to a background population cohort of 2203 African Americans in the NHLBI GO Exome Sequencing Project (ESP).

RESULTS

In the African American family with recurrent VTE, we found prior laboratories for our cases indicating low free Protein S levels, providing functional support for PROS1 V510M as the causative mutation. Additionally, this variant was significantly enriched in the VTE cases of our multicenter case-control study (Fisher's Exact Test, P = 0.0041, OR = 4.62, 95% CI: 1.51-15.20; allele frequencies - cases: 2.45%, controls: 0.54%). Similarly, PROS1 V510M was also enriched in our VTE case cohort compared to African Americans in the ESP cohort (Fisher's Exact Test, P = 0.010, OR = 2.28, 95% CI: 1.26-4.10).

CONCLUSIONS

We found a variant, PROS1 V510M, in an African American family with VTE and clinical laboratory abnormalities in Protein S. Additionally, we found that this variant conferred increased risk of VTE in a case-control study of African Americans. In the ESP cohort, the variant is nearly absent in ESP European descent subjects (n = 3, allele frequency: 0.03%). Additionally, in 1000 Genomes Phase 3 data, the variant only appears in African descent populations. Thus, PROS1 V510M is a population-specific genetic risk factor for VTE in African Americans.

Exome sequencing of extreme clopidogrel response phenotypes identifies B4GALT2 as a determinant of on-treatment platelet reactivity

Interindividual variability in platelet aggregation is common among patients treated with clopidogrel and both high on-treatment platelet reactivity (HTPR) and low on-treatment platelet reactivity (LTPR) increase risks for adverse clinical outcomes. CYP2C19 influences clopidogrel response but only accounts for ∼12% of the variability in platelet reactivity. To identify novel variants implicated in on-treatment platelet reactivity, patients with coronary artery disease (CAD) with extreme pharmacodynamic responses to clopidogrel and wild-type CYP2C19 were subjected to exome sequencing. Candidate variants that clustered in the LTPR subgroup subsequently were genotyped across the discovery cohort (n = 636). Importantly, carriers of B4GALT2 c.909C>T had lower on-treatment P2Y12 reaction units (PRUs; P = 0.0077) and residual platelet aggregation (P = 0.0008) compared with noncarriers, which remained significant after adjusting for CYP2C19 and other clinical variables in both the discovery (P = 0.0298) and replication (n = 160; PRU: P = 0.0001) cohorts. B4GALT2 is a platelet-expressed galactosyltransferase, indicating that B4GALT2 c.909C>T may influence clopidogrel sensitivity through atypical cell-surface glycoprotein processing and platelet adhesion.

Impact of GGCX, STX1B and FPGS Polymorphisms on Warfarin Dose Requirements in European-Americans and Egyptians

Genotype-based algorithms that include VKORC1 and CYP2C9 genotypes are less predictive of warfarin dose variability in Africans as opposed to Europeans. Polymorphisms in GGCX, FPGS, or STX1B are associated with warfarin dose requirements in African-Americans. We sought to determine if they influenced warfarin dose in European-Americans, and another African population, specifically Egyptians. We genotyped 529 adults (n = 325 European-Americans, 204 Egyptians) on a stable warfarin dose for GGCX rs12714145 and rs10654848, FPGS rs7856096, and STX1B rs4889606. Rs12714145, rs10654848, and rs7856096 were not associated with warfarin dose, whereas STX1B rs4889606 was a significant determinant in univariate analysis (P < 0.0001) in both cohorts. However, STX1B rs4889606 was in high linkage disequilibrium with VKORC1-1639 G>A, and was no longer significant after including VKORC1-1639 G>A in the regression model. Based on these data, the polymorphisms do not appear to influence, in a clinically important way, warfarin dose requirements in European-Americans and Egyptians.

Factors influencing pharmacokinetics of warfarin in African-Americans: implications for pharmacogenetic dosing algorithms

AIM

This study attempted to identify predictors of S-warfarin clearance (CL[S]) and to make a pharmacokinetic evaluation of genotype-based dosing algorithms in African-Americans.

METHODS

Using plasma S-warfarin concentration (Cp[S]) at a steady state and eight SNPs previously shown to influence warfarin dose in African-Americans, CL(S) and its predictors were estimated by population pharmacokinetic analysis in 60 African-Americans. The time courses of Cp(S) following either the loading dose or maintenance dose were simulated using the population pharmacokinetic estimates.

RESULTS

CYP2C9*8 and body surface area or body weight were predictors of CL(S) (-30 and -5% per -0.1 m(2)/-10 kg reduction in CL[S], respectively) in African-Americans. Simulations of Cp(S) showed that Cp(S) at steady state was 1.4-times higher in patients with CYP2C9*8 than in those with CYP2C9*1/*1, irrespective of the algorithm for loading dose or maintenance dose.

CONCLUSION

African-Americans possess independent predictors of CL(S), possibly leading to a prediction error of any dosing algorithm that excludes African-specific variant(s). Original submitted 3 September 2014; Revision submitted 3 November 2014.

Cracking the Code of Human Diseases Using Next-Generation Sequencing: Applications, Challenges, and Perspectives

Next-generation sequencing (NGS) technologies have greatly impacted on every field of molecular research mainly because they reduce costs and increase throughput of DNA sequencing. These features, together with the technology's flexibility, have opened the way to a variety of applications including the study of the molecular basis of human diseases. Several analytical approaches have been developed to selectively enrich regions of interest from the whole genome in order to identify germinal and/or somatic sequence variants and to study DNA methylation. These approaches are now widely used in research, and they are already being used in routine molecular diagnostics. However, some issues are still controversial, namely, standardization of methods, data analysis and storage, and ethical aspects. Besides providing an overview of the NGS-based approaches most frequently used to study the molecular basis of human diseases at DNA level, we discuss the principal challenges and applications of NGS in the field of human genomics.

Genotype-based clinical trials in cardiovascular disease

Consensus practice guidelines and the implementation of clinical therapeutic advances are usually based on the results of large, randomized clinical trials (RCTs). However, RCTs generally inform us on an average treatment effect for a presumably homogeneous population, but therapeutic interventions rarely benefit the entire population targeted. Indeed, multiple RCTs have demonstrated that interindividual variability exists both in drug response and in the development of adverse effects. The field of pharmacogenomics promises to deliver the right drug to the right patient. Substantial progress has been made in this field, with advances in technology, statistical and computational methods, and the use of cell and animal model systems. However, clinical implementation of pharmacogenetic principles has been difficult because RCTs demonstrating benefit are lacking. For patients, the potential benefits of performing such trials include the individualization of therapy to maximize efficacy and minimize adverse effects. These trials would also enable investigators to reduce sample size and hence contain costs for trial sponsors. Multiple ethical, legal, and practical issues need to be considered for the conduct of genotype-based RCTs. Whether pre-emptive genotyping embedded in electronic health records will preclude the need for performing genotype-based RCTs remains to be seen.

Progress in understanding the genomic basis for adverse drug reactions: a comprehensive review and focus on the role of ethnicity

A major goal of the field of pharmacogenomics is to identify the genomic causes of serious adverse drug reactions (ADRs). Increasingly, genome-wide association studies (GWAS) have been used to achieve this goal. In this article, we review recent progress in the identification of genetic variants associated with ADRs using GWAS and discuss emerging themes from these studies. We also compare aspects of GWAS for ADRs to GWAS for common diseases. In the second part of the article, we review progress in performing pharmacogenomic research in multi-ethnic populations and discuss the challenges and opportunities of investigating genetic causes of ADRs in ethnically diverse patient populations.

Use of genetic data to guide therapy in arterial disease

There is considerable interindividual variation in the response to antiplatelet and anticoagulant therapies. It has been proposed that this variability in drug response may be attributable to genetic variants. Thus, pharmacogenetics may help to accurately predict response to cardiovascular disease (CVD) therapies in order to maximize drug efficacy, minimize drug toxicity, and to tailor personalized care for these patients. Although the clinical utility of pharmacogenetics is promising, its adoption in clinical practice has been slow. This resistance may stem from sometimes conflicting findings among pharmacogenetic studies. Thus, this review focuses on the genetic determinants of commonly used platelet antagonists and anticoagulants including aspirin, clopidogrel, dabigatran, and warfarin. We also explore the clinical translation of pharmacogenetics in the management of patients with CVD.

Race influences warfarin dose changes associated with genetic factors

Warfarin dosing algorithms adjust for race, assigning a fixed effect size to each predictor, thereby attenuating the differential effect by race. Attenuation likely occurs in both race groups but may be more pronounced in the less-represented race group. Therefore, we evaluated whether the effect of clinical (age, body surface area [BSA], chronic kidney disease [CKD], and amiodarone use) and genetic factors (CYP2C9*2, *3, *5, *6, *11, rs12777823, VKORC1, and CYP4F2) on warfarin dose differs by race using regression analyses among 1357 patients enrolled in a prospective cohort study and compared predictive ability of race-combined vs race-stratified models. Differential effect of predictors by race was assessed using predictor-race interactions in race-combined analyses. Warfarin dose was influenced by age, BSA, CKD, amiodarone use, and CYP2C9*3 and VKORC1 variants in both races, by CYP2C9*2 and CYP4F2 variants in European Americans, and by rs12777823 in African Americans. CYP2C9*2 was associated with a lower dose only among European Americans (20.6% vs 3.0%, P < .001) and rs12777823 only among African Americans (12.3% vs 2.3%, P = .006). Although VKORC1 was associated with dose decrease in both races, the proportional decrease was higher among European Americans (28.9% vs 19.9%, P = .003) compared with African Americans. Race-stratified analysis improved dose prediction in both race groups compared with race-combined analysis. We demonstrate that the effect of predictors on warfarin dose differs by race, which may explain divergent findings reported by recent warfarin pharmacogenetic trials. We recommend that warfarin dosing algorithms should be stratified by race rather than adjusted for race.

Oral anticoagulation: a critique of recent advances and controversies

There have recently been significant advances in the field of oral anticoagulation, but these have also led to many controversies. Warfarin is still the commonest drug used for clotting disorders but its use is complicated owing to wide inter-individual variability in dose requirement and its narrow therapeutic index. Warfarin dose requirement can be influenced by both genetic and environmental factors. Two recent randomized controlled trials (RCTs) came to different conclusion regarding the utility of genotype-guided dosing; we critically explore the reasons for the differences. The new generation of oral anticoagulants have been demonstrated to be as efficacious as warfarin, but further work is needed to evaluate their safety in real clinical settings.

A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children

BACKGROUND

Warfarin is the most widely prescribed anticoagulant for the prevention and treatment of thromboembolic events. Although highly effective, the use of warfarin is limited by a narrow therapeutic range combined with a more than ten-fold difference in the dose required for adequate anticoagulation in adults. An optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding as measured by the prothrombin time International Normalised Ratio (INR) must be found for each patient. A model describing the time-course of the INR response can be used to aid dose selection before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision).

RESULTS

In this paper we describe a warfarin decision support tool. It was transferred from a population PKPD-model for warfarin developed in NONMEM to a platform independent tool written in Java. The tool proved capable of solving a system of differential equations that represent the pharmacokinetics and pharmacodynamics of warfarin with a performance comparable to NONMEM. To estimate an a priori dose the user enters information on body weight, age, baseline and target INR, and optionally CYP2C9 and VKORC1 genotype. By adding information about previous doses and INR observations, the tool will suggest a new dose a posteriori through Bayesian forecasting. Results are displayed as the predicted dose per day and per week, and graphically as the predicted INR curve. The tool can also be used to predict INR following any given dose regimen, e.g. a fixed or an individualized loading-dose regimen.

CONCLUSIONS

We believe that this type of mechanism-based decision support tool could be useful for initiating and maintaining warfarin therapy in the clinic. It will ensure more consistent dose adjustment practices between prescribers, and provide efficient and truly individualized warfarin dosing in both children and adults.

Genes affecting warfarin response-interactive or additive?

Genotypes for cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase complex 1 (VKORC1) contribute significantly to the inter-patient variability in warfarin dose requirements. These genotypes in addition to clinical factors explain approximately 50% of the dose variability in Europeans, but less in other populations. Thus, a large portion of the variability remains unexplained and has been the focus of on-going research. Trials evaluating the clinical utility of genotype-guided warfarin dosing have shown a benefit in Europeans, but not in an ethnically diverse cohort. Identifying and accounting for variants important in non-European populations will likely be necessary before a benefit with genotype-guided dosing will be realized in these populations.