Exploring public genomics data for population pharmacogenomics

Genetic ancestry in population pharmacogenomics unravels distinct geographical patterns related to drug toxicity

Genetic ancestry plays a major role in pharmacogenomics, and a deeper understanding of the genetic diversity among individuals holds immerse promise for reshaping personalized medicine. In this pivotal study, we have conducted a large-scale genomic analysis of 1,136 pharmacogenomic variants employing machine learning algorithms on 3,714 individuals from publicly available datasets to assess the risk proximity of experiencing drug-related adverse events. Our findings indicate that Admixed Americans and Europeans have demonstrated a higher risk of experiencing drug toxicity, whereas individuals with East Asian ancestry and, to a lesser extent, Oceanians displayed a lower risk proximity. Polygenic risk scores for drug-gene interactions did not necessarily follow similar assumptions, reflecting distinct genetic patterns and population-specific differences that vary depending on the drug class. Overall, our results provide evidence that genetic ancestry is a pivotal factor in population pharmacogenomics and should be further exploited to strengthen even more personalized drug therapy.

Pharmacogenetic analysis of structural variation in the 1000 genomes project using whole genome sequences

While significant strides have been made in understanding pharmacogenetics (PGx) and gene-drug interactions, there remains limited characterization of population-level PGx variation. This study aims to comprehensively profile global star alleles (haplotype patterns) and phenotype frequencies in 58 pharmacogenes associated with drug absorption, distribution, metabolism, and excretion. PyPGx, a star-allele calling tool, was employed to identify star alleles within high-coverage whole genome sequencing (WGS) data from the 1000 Genomes Project (N = 2504; 26 global populations). This process involved detecting structural variants (SVs), such as gene deletions, duplications, hybrids, as well as single nucleotide variants and insertion-deletion variants. The majority of our PyPGx calls for star alleles and phenotype frequencies aligned with the Pharmacogenomics Knowledge Base, although notable population-specific frequencies differed at least twofold. Validation efforts confirmed known SVs while uncovering several novel SVs currently undefined as star alleles. Additionally, we identified 210 small nucleotide variants associated with severe functional consequences that are not defined as star alleles. The study serves as a valuable resource, providing updated population-level star allele and phenotype frequencies while incorporating SVs. It also highlights the burgeoning potential of cost-effective WGS for PGx genotyping, offering invaluable insights to improve tailored drug therapies across diverse populations.

Genetic diversity of variants involved in drug response among Tunisian and Italian populations toward personalized medicine

Adverse drug reactions (ADR) represent a significant contributor to morbidity and mortality, imposing a substantial financial burden. Genetic ancestry plays a crucial role in drug response. The aim of this study is to characterize the genetic variability of selected pharmacogenes involved with ADR in Tunisians and Italians, with a comparative analysis against global populations. A cohort of 135 healthy Tunisians and 737 Italians were genotyped using a SNP array. Variants located in 25 Very Important Pharmacogenes implicated in ADR were extracted from the genotyping data. Distribution analysis of common variants in Tunisian and Italian populations in comparison to 24 publicly available worldwide populations was performed using PLINK and R software. Results from Principle Component and ADMIXTURE analyses showed a high genetic similarity among Mediterranean populations, distinguishing them from Sub-Saharan African and Asian populations. The Fst comparative analysis identified 27 variants exhibiting significant differentiation between the studied populations. Among these variants, four SNPs rs622342, rs3846662, rs7294, rs5215 located in SLC22A1, HMGCR, VKORC1 and KCNJ11 genes respectively, are reported to be associated with ethnic variability in drug responses. In conclusion, correlating the frequencies of genotype risk variants with their associated ADRs would enhance drug outcomes and the implementation of personalized medicine in the studied populations.

Utilizing Pharmacogenomic Data for a Safer Use of Statins among the Emirati Population

BACKGROUND

Statins are the most prescribed lipid-lowering drugs worldwide. The associated adverse events, especially muscle symptoms, have been frequently reported despite their perceived safety. Three pharmacogenes, the solute carrier organic anion transporter family member 1B1 (SLCO1B1), ATP-binding cassette subfamily G member 2 (ABCG2), and cytochrome P450 2C9 (CYP2C9) are suggested as safety biomarkers for statins. The Clinical Pharmacogenomic Implementation Consortium (CPIC) issued clinical guidelines for statin use based on these three genes.

OBJECTIVES

The present study aimed to examine variants in these pharmacogenes to predict the safety of statin use among the Emirati population.

METHODS

Analyzing 242 whole exome sequencing data at the three genes enabled the determination of the frequencies of the single nucleotide polymorphisms (SNPs), annotating the haplotypes and the predicted functions of their proteins.

RESULTS

In our cohort, 29.8% and 5.4% had SLCO1B1 decreased and poor function, respectively. The high frequency warns of the possibility of significant side effects of some statins and the importance of pharmacogenomic testing. We found a low frequency (6%) of the ABCG2:rs2231142 variant, which indicates the low probability of Emirati patients being recommended against higher rosuvastatin doses compared with other populations with higher frequencies of this variant. In contrast, we found high frequencies of the functionally impaired CYP2C9 alleles, which makes fluvastatin a less favorable choice.

CONCLUSION

Among the sparse studies available, the present one demonstrates all SLCO1B1 and CYP2C9 function-impairing alleles among Emiratis. We highlighted how population-specific pharmacogenomic data can predict safer choices of statins, especially in understudied populations.

The Prevalence of Pharmacogenomics Variants and Their Clinical Relevance Among the Pakistani Population

Background:

Pharmacogenomics (PGx), forming the basis of precision medicine, has revolutionized traditional medical practice. Currently, drug responses such as drug efficacy, drug dosage, and drug adverse reactions can be anticipated based on the genetic makeup of the patients. The pharmacogenomic data of Pakistani populations are limited. This study investigates the frequencies of pharmacogenetic variants and their clinical relevance among ethnic groups in Pakistan.

Methods:

The Pharmacogenomics Knowledge Base (PharmGKB) database was used to extract pharmacogenetic variants that are involved in medical conditions with high (1A + 1B) to moderate (2A + 2B) clinical evidence. Subsequently, the allele frequencies of these variants were searched among multiethnic groups of Pakistan (Balochi, Brahui, Burusho, Hazara, Kalash, Pashtun, Punjabi, and Sindhi) using the 1000 Genomes Project (1KGP) and ALlele FREquency Database (ALFRED). Furthermore, the published Pharmacogenomics literature on the Pakistani population was reviewed in PubMed and Google Scholar.

Results:

Our search retrieved (n = 29) pharmacogenetic genes and their (n = 44) variants with high to moderate evidence of clinical association. These pharmacogenetic variants correspond to drug-metabolizing enzymes (n = 22), drug-metabolizing transporters (n = 8), and PGx gene regulators, etc. (n = 14). We found 5 pharmacogenetic variants present at >50% among 8 ethnic groups of Pakistan. These pharmacogenetic variants include CYP2B6 (rs2279345, C; 70%-86%), CYP3A5 (rs776746, C; 64%-88%), FLT3 (rs1933437, T; 54%-74%), CETP (rs1532624, A; 50%-70%), and DPP6 (rs6977820, C; 61%-86%) genes that are involved in drug response for acquired immune deficiency syndrome, transplantation, cancer, heart disease, and mental health therapy, respectively.

Conclusions:

This study highlights the frequency of important clinical pharmacogenetic variants (1A, 1B, 2A, and 2B) among multi-ethnic Pakistani populations. The high prevalence (>50%) of single nucleotide pharmacogenetic variants may contribute to the drug response/diseases outcome. These PGx data could be used as pharmacogenetic markers in the selection of appropriate therapeutic regimens for specific ethnic groups of Pakistan.

Exploring the Kinh Vietnamese genomic database for the polymorphisms of the P450 genes toward precision public health

BACKGROUND

Human cytochrome P450 (CYPs) genes are essential in metabolizing drugs. Due to their high polymorphism, population-specific studies are of great interest.

AIM

This research examined the six CYP genes, including CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5, and CYP4F2 in the Kinh Vietnamese (KHV) for population-scale precision medicine.

SUBJECTS AND METHODS

We processed data from a genomics database of 206 healthy and unrelated KHV individuals to calculate CYP allele frequencies. First, we compared the CYP genes of the KHV to six other populations retrieved from the 1000 Genomes Project. Second, we searched the PharmGBK database for drug-CYP interaction data to compile a drug dosage recommendation for KHV.

RESULTS

We observed diverging trends in the genetic variations of CYP2B6, CYP2D6, and CYP3A5 in KHV. In terms of the phenotypic drug responses in KHV, CYP2C19 exhibited all of the metabolic phenotypes at a non-trivial frequency. CYP3A5 metabolized drugs at a lower rate than the other five CYPs.

CONCLUSION

This is the first large-scale study to investigate multiple CYP genes in the KHV for precision medicine from a public health perspective. Differences found in the distributions of metabolizers for the KHV suggest careful prescriptions for CYP2C19 and CYP3A5-metabolized drugs.

The Extent and Impact of Variation in ADME Genes in Sub-Saharan African Populations

Introduction: Investigating variation in genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs are key to characterizing pharmacogenomic (PGx) relationships. ADME gene variation is relatively well characterized in European and Asian populations, but data from African populations are under-studied-which has implications for drug safety and effective use in Africa. Results: We identified significant ADME gene variation in African populations using data from 458 high-coverage whole genome sequences, 412 of which are novel, and from previously available African sequences from the 1,000 Genomes Project. ADME variation was not uniform across African populations, particularly within high impact coding variation. Copy number variation was detected in 116 ADME genes, with equal ratios of duplications/deletions. We identified 930 potential high impact coding variants, of which most are discrete to a single African population cluster. Large frequency differences (i.e., >10%) were seen in common high impact variants between clusters. Several novel variants are predicted to have a significant impact on protein structure, but additional functional work is needed to confirm the outcome of these for PGx use. Most variants of known clinical outcome are rare in Africa compared to European populations, potentially reflecting a clinical PGx research bias to European populations. Discussion: The genetic diversity of ADME genes across sub-Saharan African populations is large. The Southern African population cluster is most distinct from that of far West Africa. PGx strategies based on European variants will be of limited use in African populations. Although established variants are important, PGx must take into account the full range of African variation. This work urges further characterization of variants in African populations including in vitro and in silico studies, and to consider the unique African ADME landscape when developing precision medicine guidelines and tools for African populations.

Strategies to Improve the Clinical Outcomes for Direct-to-Consumer Pharmacogenomic Tests

Direct-to-consumer genetic tests (DTC-GT) have become a bridge between marketing and traditional healthcare services. After earning FDA endorsement for such facilities, several fast-developing companies started to compete in the related area. Pharmacogenomic (PGx) tests have been introduced as potentially one of the main medical services of such companies. Most of the individuals will be interested in finding out about the phenotypic consequences of their genetic variants and molecular risk factors against diverse medicines they take or will take later. Direct-to-consumer pharmacogenomic tests (DTC-PT) is still in its young age, however it is expected to expand rapidly through the industry in the future. The result of PGx tests could be considered as the main road toward the implementation of personalized and precision medicine in the clinic. This narrative critical review study provides a descriptive overview on DTC-GT, then focuses on DTC-PT, and also introduces and suggests the potential approaches for improving the clinical related outcomes of such tests on healthcare systems.

Genetic ancestry plays a central role in population pharmacogenomics

Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD (http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/).

Hsin-Chou Yang et al. examine population structure in several genomic databases and identify that pharmacogenetic loci are enriched for markers of genetic ancestry. Their results suggest that genetic ancestry must be carefully considered in population pharmacogenetics studies.

Variation in 100 relevant pharmacogenes among emiratis with insights from understudied populations

Genetic variations have an established impact on the pharmacological response. Investigating this variation resulted in a compilation of variants in "pharmacogenes". The emergence of next-generation sequencing facilitated large-scale pharmacogenomic studies and exhibited the extensive variability of pharmacogenes. Some rare and population-specific variants proved to be actionable, suggesting the significance of population pharmacogenomic research. A profound gap exists in the knowledge of pharmacogenomic variants enriched in some populations, including the United Arab Emirates (UAE). The current study aims to explore the landscape of variations in relevant pharmacogenes among healthy Emiratis. Through the resequencing of 100 pharmacogenes for 100 healthy Emiratis, we identified 1243 variants, of which 63% are rare (minor allele frequency ≤ 0.01), and 30% were unique. Filtering the variants according to Pharmacogenomics Knowledge Base (PharmGKB) annotations identified 27 diplotypes and 26 variants with an evident clinical relevance. Comparison with global data illustrated a significant deviation of allele frequencies in the UAE population. Understudied populations display a distinct allelic architecture and various rare and unique variants. We underscored pharmacogenes with the highest variation frequencies and provided investigators with a list of candidate genes for future studies. Population pharmacogenomic studies are imperative during the pursuit of global pharmacogenomics implementation.

Population structure and pharmacogenomic risk stratification in the United States

BACKGROUND

Pharmacogenomic (PGx) variants mediate how individuals respond to medication, and response differences among racial/ethnic groups have been attributed to patterns of PGx diversity. We hypothesized that genetic ancestry (GA) would provide higher resolution for stratifying PGx risk, since it serves as a more reliable surrogate for genetic diversity than self-identified race/ethnicity (SIRE), which includes a substantial social component. We analyzed a cohort of 8628 individuals from the United States (US), for whom we had both SIRE information and whole genome genotypes, with a focus on the three largest SIRE groups in the US: White, Black (African-American), and Hispanic (Latino). Our approach to the question of PGx risk stratification entailed the integration of two distinct methodologies: population genetics and evidence-based medicine. This integrated approach allowed us to consider the clinical implications for the observed patterns of PGx variation found within and between population groups.

RESULTS

Whole genome genotypes were used to characterize individuals' continental ancestry fractions-European, African, and Native American-and individuals were grouped according to their GA profiles. SIRE and GA groups were found to be highly concordant. Continental ancestry predicts individuals' SIRE with > 96% accuracy, and accordingly, GA provides only a marginal increase in resolution for PGx risk stratification. In light of the concordance between SIRE and GA, taken together with the fact that information on SIRE is readily available to clinicians, we evaluated PGx variation between SIRE groups to explore the potential clinical utility of race and ethnicity. PGx variants are highly diverged compared to the genomic background; 82 variants show significant frequency differences among SIRE groups, and genome-wide patterns of PGx variation are almost entirely concordant with SIRE. The vast majority of PGx variation is found within rather than between groups, a well-established fact for almost all genetic variants, which is often taken to argue against the clinical utility of population stratification. Nevertheless, analysis of highly differentiated PGx variants illustrates how SIRE partitions PGx variation based on groups' characteristic ancestry patterns. These cases underscore the extent to which SIRE carries clinically valuable information for stratifying PGx risk among populations, albeit with less utility for predicting individual-level PGx alleles (genotypes), supporting the concept of population pharmacogenomics.

CONCLUSIONS

Perhaps most interestingly, we show that individuals who identify as Black or Hispanic stand to gain far more from the consideration of race/ethnicity in treatment decisions than individuals from the majority White population.

Pharmacogenomics landscape of COVID-19 therapy response in Serbian population and comparison with worldwide populations

BACKGROUND

Since there are no certified therapeutics to treat COVID-19 patients, drug repurposing became important. With lack of time to test individual pharmacogenomics markers, population pharmacogenomics could be helpful in predicting a higher risk of developing adverse reactions and treatment failure in COVID-19 patients. Aim of our study was to identify pharmacogenes and pharmacogenomics markers associated with drugs recommended for COVID-19 treatment, chloroquine/hydroxychloroquine, azithromycin, lopinavir and ritonavir, in population of Serbia and other world populations.

METHODS

Genotype information of 143 individuals of Serbian origin was extracted from database previously obtained using TruSight One Gene Panel (Illumina). Genotype data of individuals from different world populations were extracted from the 1000 Genome Project. Fisher's exact test was used for comparison of allele frequencies.

RESULTS

We have identified 11 potential pharmacogenomics markers in 7 pharmacogenes relevant for COVID-19 treatment. Based on high alternative allele frequencies in population and the functional effect of the variants, ABCB1 rs1045642 and rs2032582 could be relevant for reduced clearance of azithromycin, lopinavir and ritonavir drugs and UGT1A7 rs17868323 for hyperbilirubinemia in ritonavir treated COVID-19 patients in Serbian population. SLCO1B1 rs4149056 is a potential marker of lopinavir response, especially in Italian population. Our results confirmed that pharmacogenomics profile of African population is different from the rest of the world.

CONCLUSIONS

Considering population specific pharmacogenomics landscape, preemptive testing for pharmacogenes relevant for drugs used in COVID-19 treatment could contribute to better understanding of the inconsistency in therapy response and could be applied to improve the outcome of the COVID-19 patients.

PARC report: health outcomes and value of personalized medicine interventions: impact on patient care

The incorporation of personalized medicine interventions into routine healthcare constitutes an opportunity to improve patients' quality of life, as it empowers implementation of innovative, individualized clinical interventions that maximize efficacy and/or minimize the risk of adverse drug reactions. In order to ensure equal access to genomic testing for all patients, the costs associated with these interventions must be reimbursed by payers and insurance bodies. As such, it is of utmost importance to thoroughly evaluate these interventions both in terms of their clinical effectiveness and their economic cost. This article discusses the impact of personalized medicine interventions in terms of both health outcomes and value, which directly impacts on their pricing and reimbursement by the various national healthcare systems.

Exome-Wide Analysis of the DiscovEHR Cohort Reveals Novel Candidate Pharmacogenomic Variants for Clinical Pharmacogenomics

Recent advances in next-generation sequencing technology have led to the production of an unprecedented volume of genomic data, thus further advancing our understanding of the role of genetic variation in clinical pharmacogenomics. In the present study, we used whole exome sequencing data from 50,726 participants, as derived from the DiscovEHR cohort, to identify pharmacogenomic variants of potential clinical relevance, according to their occurrence within the PharmGKB database. We further assessed the distribution of the identified rare and common pharmacogenomics variants amongst different GnomAD subpopulations. Overall, our findings show that the use of publicly available sequence data, such as the DiscovEHR dataset and GnomAD, provides an opportunity for a deeper understanding of genetic variation in pharmacogenes with direct implications in clinical pharmacogenomics.

Pharmacogenomic genotypes define genetic ancestry in patients and enable population-specific genomic implementation

The importance of genetic ancestry characterization is increasing in genomic implementation efforts, and clinical pharmacogenomic guidelines are being published that include population-specific recommendations. Our aim was to test the ability of focused clinical pharmacogenomic SNP panels to estimate individual genetic ancestry (IGA) and implement population-specific pharmacogenomic clinical decision-support (CDS) tools. Principle components and STRUCTURE were utilized to assess differences in genetic composition and estimate IGA among 1572 individuals from 1000 Genomes, two independent cohorts of Caucasians and African Americans (AAs), plus a real-world validation population of patients undergoing pharmacogenomic genotyping. We found that clinical pharmacogenomic SNP panels accurately estimate IGA compared to genome-wide genotyping and identify AAs with ≥70 African ancestry (sensitivity >82%, specificity >80%, PPV >95%, NPV >47%). We also validated a new AA-specific warfarin dosing algorithm for patients with ≥70% African ancestry and implemented it at our institution as a novel CDS tool. Consideration of IGA to develop an institutional CDS tool was accomplished to enable population-specific pharmacogenomic guidance at the point-of-care. These capabilities were immediately applied for guidance of warfarin dosing in AAs versus Caucasians, but also provide a real-world model that can be extended to other populations and drugs as actionable genomic evidence accumulates.

Prioritizing rs7294 as a mirSNP contributing to warfarin dosing variability

Aim: The role of mirSNPs in the 3'UTR of VKORC1, CYP2C9 and CYP4F2 genes that could influence warfarin dose variability via a discrete miRNA-mediated mechanism remains unexplained. Methods: Genotypic data in the 1000 Genomes dataset were analyzed for pair-wise linkage disequilibrium and allelic enrichment. Results: MirSNP rs7294 in the 3'UTR of VKORC1 gene displayed varying strengths of linkage disequilibrium with rs9923231 and rs9934438 across populations, albeit consistently associated with higher warfarin dose requirements based on genome-wide association studies, meta-analysis and population-based association studies. In silico analysis predicted altered hybrid stability for the hsa-miR-133a-3p conserved binding site, providing evidence for miRNA-mediated gene regulation. Conclusion: The results support the inclusion of rs7294 as a functional variable for population-specific dosing algorithms to improve dosing accuracy.

An ancestry informative marker panel design for individual ancestry estimation of Hispanic population using whole exome sequencing data

Background

Europeans and American Indians were major genetic ancestry of Hispanics in the U.S. These ancestral groups have markedly different incidence rates and outcomes in many types of cancers. Therefore, the genetic admixture may cause biased genetic association study with cancer susceptibility variants specifically in Hispanics. For example, the incidence rate of liver cancer has been shown with substantial disparity between Hispanic, Asian and non-Hispanic white populations. Currently, ancestry informative marker (AIM) panels have been widely utilized with up to a few hundred ancestry-informative single nucleotide polymorphisms (SNPs) to infer ancestry admixture. Notably, current available AIMs are predominantly located in intron and intergenic regions, while the whole exome sequencing (WES) protocols commonly used in translational research and clinical practice do not cover these markers. Thus, it remains challenging to accurately determine a patient’s admixture proportion without additional DNA testing.

Results

In this study we designed an unique AIM panel that infers 3-way genetic admixture from three distinct and selective continental populations (African (AFR), European (EUR), and East Asian (EAS)) within evolutionarily conserved exonic regions. Initially, about 1 million exonic SNPs from selective three populations in the 1000 Genomes Project were trimmed by their linkage disequilibrium (LD), restricted to biallelic variants, and finally we optimized to an AIM panel with 250 SNP markers, or the UT-AIM250 panel, using their ancestral informativeness statistics. Comparing to published AIM panels, UT-AIM250 performed better accuracy when we tested with three ancestral populations (accuracy: 0.995 ± 0.012 for AFR, 0.997 ± 0.007 for EUR, and 0.994 ± 0.012 for EAS). We further demonstrated the performance of the UT-AIM250 panel to admixed American (AMR) samples of the 1000 Genomes Project and obtained similar results (AFR, 0.085 ± 0.098; EUR, 0.665 ± 0.182; and EAS, 0.250 ± 0.205) to previously published AIM panels (Phillips-AIM34: AFR, 0.096 ± 0.127, EUR, 0.575 ± 0.290, and EAS, 0.330 ± 0.315; Wei-AIM278: AFR, 0.070 ± 0.096, EUR, 0.537 ± 0.267, and EAS, 0.393 ± 0.300). Subsequently, we applied the UT-AIM250 panel to a clinical dataset of 26 self-reported Hispanic patients in South Texas with hepatocellular carcinoma (HCC). We estimated the admixture proportions using WES data of adjacent non-cancer liver tissues (AFR, 0.065 ± 0.043; EUR, 0.594 ± 0.150; and EAS, 0.341 ± 0.160). Similar admixture proportions were identified from corresponding tumor tissues. In addition, we estimated admixture proportions of The Cancer Genome Atlas (TCGA) collection of hepatocellular carcinoma (TCGA-LIHC) samples (376 patients) using the UT-AIM250 panel. The panel obtained consistent admixture proportions from tumor and matched normal tissues, identified 3 possible incorrectly reported race/ethnicity, and/or provided race/ethnicity determination if necessary.

Conclusions

Here we demonstrated the feasibility of using evolutionarily conserved exonic regions to infer admixture proportions and provided a robust and reliable control for sample collection or patient stratification for genetic analysis. R implementation of UT-AIM250 is available at https://github.com/chenlabgccri/UT-AIM250.

Pharmaco-Geno-Proteo-Metabolomics and Translational Research in Cancer

The diagnosis, prognosis and treatment of cancer has had a great improvement due to the "omics" technologies such as genomics, proteomics, epigenomics, pharmacogenomics, and metabolomics. The technological progress of these technologies has allowed precision medicine to become a clinical reality. The study of different biomolecules such as DNA, RNA and proteins has helped to detect alterations in genes, changes in gene expression profiles and loss or gain of protein function, which allows us to make associations and better understand the cancer biology. Data obtained from different "omics" technologies gives a complementary spectrum of information that helps us to understand and unveil new information for a better diagnosis, prognosis, prediction of new molecular targets of anticancer therapies, etc. This chapter presents a general landscape of the interaction between the Pharmaco-Geno-Proteo-Metabolomic and translational medicine research in cancer.

Concepts Driving Pharmacogenomics Implementation Into Everyday Healthcare

Pharmacogenomics (PGx) is often promoted as the domain of precision medicine with the greatest potential to readily impact everyday healthcare. Rapid advances in PGx knowledge derived from extensive basic and clinical research along with decreasing costs of laboratory testing have led to an increased interest in PGx and expectations of imminent clinical translation with substantial clinical impact. However, the implementation of PGx into clinical workflows is neither simple nor straightforward, and comprehensive processes and multidisciplinary collaboration are required. Several national and international institutions have pioneered models for implementing clinical PGx, and these initial models have led to a better understanding of unresolved challenges. In this review, we have categorized and explored the most relevant of these challenges to highlight potential gaps and present possible solutions. We describe the ongoing need for basic and clinical research to drive further developments in evidence-based medicine. Integration into daily clinical workflows introduces new challenges requiring innovative solutions; specifically those related to the electronic health record and embedded clinical decision support. We describe advances in PGx testing and result reporting and describe the critical need for increased standardization in these areas across laboratories. We also explore the complexity of the PGx knowledge required for clinical practice and the need for educational strategies to ensure adequate understanding among members of current and future healthcare teams. Finally, we evaluate knowledge obtained from previous implementation efforts and discuss how to best apply these learnings to future projects. Despite these challenges, the future of precision medicine appears promising due to the rapidity of recent advances in the field and current multidisciplinary efforts to effectively translate PGx to everyday clinical practice.

Variation in Actionable Pharmacogenetic Markers in Natives and Mestizos From Mexico

The identification and characterization of pharmacogenetic variants in Latin American populations is still an ongoing endeavor. Here, we investigated SNVs on genes listed by the Pharmacogenomics Knowledge Base in 1284 Mestizos and 94 Natives from Mexico. Five institutional cohorts with NGS data were retrieved from different research projects at INMEGEN, sequencing files were filtered for 55 pharmacogenes present in all cohorts to identify novel and known variation. Bioinformatic tools VEP, PROVEAN, and FATHMM were used to assess, in silico, the functional impact of this variation. Next, we focused on 17 genes with actionable variants that have been clinically implemented. Allele frequencies were compared with major continental groups and differences discussed in the scope of a pharmacogenomic impact. We observed a wide genetic variability for known and novel SNVs, the largest variation was on UGT1A > ACE > COMT > ABCB1 and the lowest on APOE and NAT2. Although with allele frequencies around 1%, novel variation was observed in 16 of 17 PGKB genes. In Natives we identified 59 variants and 58 in Mestizos. Several genes did not show novel variation, on CYP2B6, CYP2D6, and CYP3A4 in Natives; and APOE, UGT1A, and VKORC1 in Mestizos. Similarities in allele frequency, comparing major continental groups for VIP pharmacogenes, hint towards a comparable PGx for drugs metabolized by UGT1A1, DPYD, ABCB1, CBR3, COMT, and TPMT; in contrast to variants on CYP3A5 and CYP2B6 for which significant MAF differences were identified. Our observations offer some discernment into the extent of pharmacogenetic variation registered up-to-date in Mexicans and contribute to quantitatively dissect actionable pharmacogenetic variants in Natives and Mestizos.

Copy number variation profiling in pharmacogenetics CYP-450 and GST genes in Colombian population

BACKGROUND

Copy Number variation (CNVs) in genes related to drug absorption, distribution, metabolism and excretion (ADME) are relevant in the interindividual variability of drug response. Studies of the CNVs in ADME genes in Latin America population are lacking. The objective of the study was to identify the genetic variability of CNVs in CYP-450 and GST genes in a subgroup of individuals of Colombian origin.

METHODS

Genomic DNA was isolated from 123 healthy individuals from a Colombian population. Multiplex Ligation-Dependent Probe Amplification (MLPA) was performed for the identification of CNVs in 40 genomic regions of 11 CYP-450 and 3 GST genes. The genetic variability, allelic and genotypic frequencies were analyzed.

RESULTS

We found that 13 out of 14 genes had CNVs: 5 (35.7%) exhibited deletions and duplications, while 8 (57.1%) presented either deletions or duplications.. 33.3% of individuals carried deletions and duplications while 49.6% had a unique type of CNV (deletion or duplication). The allelic frequencies of the CYP and GST genes were 0 to 47.6% (allele null), 0 to 17.5% (duplicated alleles) and 37 to 100% (normal alleles).

CONCLUSIONS

Our results describe, for the first time, the genomic profile of CNVs in a subgroup of Colombian population in GST and CYP-450 genes. GST genes indicated greater genetic variability than CYP-450 genes. The data obtained contributes to the knowledge of genetic profiles in Latin American subgroups. Although the clinical relevance of CNVs has not been fully established, it is a valuable source of pharmacogenetic variability data with potential involvement in the response to medications.

Inconsistency in race and ethnic classification in pharmacogenetics studies and its potential clinical implications

Introduction

Racial and ethnic categories are frequently used in pharmacogenetics literature to stratify patients; however, these categories can be inconsistent across different studies. To address the ongoing debate on the applicability of traditional concepts of race and ethnicity in the context of precision medicine, we aimed to review the application of current racial and ethnic categories in pharmacogenetics and its potential impact on clinical care.

Methods

One hundred and three total pharmacogenetics papers involving the CYP2C9, CYP2C19, and CYP2D6 genes were analyzed for their country of origin, racial, and ethnic categories used, and allele frequency data. Correspondence between the major continental racial categories promulgated by National Institutes of Health (NIH) and those reported by the pharmacogenetics papers was evaluated.

Results

The racial and ethnic categories used in the papers we analyzed were highly heterogeneous. In total, we found 66 different racial and ethnic categories used which fall under the NIH race category “White”, 47 different racial and ethnic categories for “Asian”, and 62 different categories for “Black”. The number of categories used varied widely based on country of origin: Japan used the highest number of different categories for “White” with 17, Malaysia used the highest number for “Asian” with 24, and the US used the highest number for “Black” with 28. Significant variation in allele frequency between different ethnic subgroups was identified within 3 major continental racial categories.

Conclusion

Our analysis showed that racial and ethnic classification is highly inconsistent across different papers as well as between different countries. Evidence-based consensus is necessary for optimal use of self-identified race as well as geographical ancestry in pharmacogenetics. Common taxonomy of geographical ancestry which reflects specifics of particular countries and is accepted by the entire scientific community can facilitate reproducible pharmacogenetic research and clinical implementation of its results.

Population Pharmacogenomics for Precision Public Health in Colombia

While genomic approaches to precision medicine hold great promise, they remain prohibitively expensive for developing countries. The precision public health paradigm, whereby healthcare decisions are made at the level of populations as opposed to individuals, provides one way for the genomics revolution to directly impact health outcomes in the developing world. Genomic approaches to precision public health require a deep understanding of local population genomics, which is still missing for many developing countries. We are investigating the population genomics of genetic variants that mediate drug response in an effort to inform healthcare decisions in Colombia. Our work focuses on two neighboring populations with distinct ancestry profiles: Antioquia and Chocó. Antioquia has primarily European genetic ancestry followed by Native American and African components, whereas Chocó shows mainly African ancestry with lower levels of Native American and European admixture. We performed a survey of the global distribution of pharmacogenomic variants followed by a more focused study of pharmacogenomic allele frequency differences between the two Colombian populations. Worldwide, we found pharmacogenomic variants to have both unusually high minor allele frequencies and high levels of population differentiation. A number of these pharmacogenomic variants also show anomalous effect allele frequencies within and between the two Colombian populations, and these differences were found to be associated with their distinct genetic ancestry profiles. For example, the C allele of the single nucleotide polymorphism (SNP) rs4149056 [Solute Carrier Organic Anion Transporter Family Member 1B1 (SLCO1B1)^∗5], which is associated with an increased risk of toxicity to a commonly prescribed statin, is found at relatively high frequency in Antioquia and is associated with European ancestry. In addition to pharmacogenomic alleles related to increased toxicity risk, we also have evidence that alleles related to dosage and metabolism have large frequency differences between the two populations, which are associated with their specific ancestries. Using these findings, we have developed and validated an inexpensive allele-specific PCR assay to test for the presence of such population-enriched pharmacogenomic SNPs in Colombia. These results serve as an example of how population-centered approaches to pharmacogenomics can help to realize the promise of precision medicine in resource-limited settings.

Population-scale genomics-Enabling precision public health

The current excitement for affordable genomics technologies and national precision medicine initiatives marks a turning point in worldwide healthcare practices. The last decade of global population sequencing efforts has defined the enormous extent of genetic variation in the human population resulting in insights into differential disease burden and response to therapy within and between populations. Population-scale pharmacogenomics helps to provide insights into the choice of optimal therapies and an opportunity to estimate, predict and minimize adverse events. Such an approach can potentially empower countries to formulate national selection and dosing policies for therapeutic agents thereby promoting public health with precision. We review the breadth and depth of worldwide population-scale sequencing efforts and its implications for the implementation of clinical pharmacogenetics toward making precision medicine a reality.

Characterization of ADME genes variation in Roma and 20 populations worldwide

The products of the polymorphic ADME genes are involved in Absorption, Distribution, Metabolism, and Excretion of drugs. The pharmacogenetic data have been studied extensively due to their clinical importance in the appropriate drug prescription, but such data from the isolated populations are rather scarce. We analyzed the distribution of 95 polymorphisms in 31 core ADME genes in 20 populations worldwide and in newly genotyped samples from the Roma (Gypsy) population living in Croatia. Global distribution of ADME core gene loci differentiated three major clusters; (1) African, (2) East Asian, and (3) joint European, South Asian and South American cluster. The SLCO1B3 (rs4149117) and CYP3A4 (rs2242480) genes differentiated at the highest level the African group of populations, while NAT2 gene loci (rs1208, rs1801280, and rs1799929) and VKORC1 (rs9923231) differentiated East Asian populations. The VKORC1 rs9923231 was among the investigated loci the one with the largest global minor allele frequency (MAF) range; its MAF ranged from 0.027 in Nigeria to 0.924 in Han Chinese. The distribution of the investigated gene loci positions Roma population within the joined European and South Asian clusters, suggesting that their ADME gene pool is a combination of ancestral (Indian) and more recent (European) surrounding, as it was already implied by other genetic markers. However, when compared to the populations worldwide, the Croatian Roma have extreme MAF values in 10 out of the 95 investigated ADME core gene loci. Among loci which have extraordinary MAFs in Roma population two have strong proof of clinical importance: rs1799853 (CYP2C9) for warfarin dosage, and rs12248560 (CYP2C19) for clopidogrel dosage, efficacy and toxicity. This finding confirms the importance of taking the Roma as well as the other isolated populations`genetic profiles into account in pharmaco-therapeutic practice.

Genetic variation in the Estonian population: pharmacogenomics study of adverse drug effects using electronic health records

Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel loss-of-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.