Pharmacogenomics and public health: implementing 'populationalized' medicine

Pharmacogenomics and health disparities, are we helping?

Pharmacogenomics has been at the forefront of precision medicine during the last few decades. Precision medicine carries the potential of improving health outcomes at both the individual as well as population levels. To harness the benefits of its initiatives, careful dissection of existing health disparities as they relate to precision medicine is of paramount importance. Attempting to address the existing disparities at the early stages of design and implementation of these efforts is the only guarantee of a successful just outcome. In this review, we glance at a few determinants of existing health disparities as they intersect with pharmacogenomics research and implementation. In our opinion, highlighting these disparities is imperative for the purpose of researching meaningful solutions. Failing to identify, and hence address, these disparities in the context of the current and future precision medicine initiatives would leave an already strained health system, even more inundated with inequality.

Population pharmacogenomics: an update on ethnogeographic differences and opportunities for precision public health

Both safety and efficacy of medical treatment can vary depending on the ethnogeographic background of the patient. One of the reasons underlying this variability is differences in pharmacogenetic polymorphisms in genes involved in drug disposition, as well as in drug targets. Knowledge and appreciation of these differences is thus essential to optimize population-stratified care. Here, we provide an extensive updated analysis of population pharmacogenomics in ten pharmacokinetic genes (CYP2D6, CYP2C19, DPYD, TPMT, NUDT15 and SLC22A1), drug targets (CFTR) and genes involved in drug hypersensitivity (HLA-A, HLA-B) or drug-induced acute hemolytic anemia (G6PD). Combined, polymorphisms in the analyzed genes affect the pharmacology, efficacy or safety of 141 different drugs and therapeutic regimens. The data reveal pronounced differences in the genetic landscape, complexity and variant frequencies between ethnogeographic groups. Reduced function alleles of CYP2D6, SLC22A1 and CFTR were most prevalent in individuals of European descent, whereas DPYD and TPMT deficiencies were most common in Sub-Saharan Africa. Oceanian populations showed the highest frequencies of CYP2C19 loss-of-function alleles while their inferred CYP2D6 activity was among the highest worldwide. Frequencies of HLA-B*15:02 and HLA-B*58:01 were highest across Asia, which has important implications for the risk of severe cutaneous adverse reactions upon treatment with carbamazepine and allopurinol. G6PD deficiencies were most frequent in Africa, the Middle East and Southeast Asia with pronounced differences in variant composition. These variability data provide an important resource to inform cost-effectiveness modeling and guide population-specific genotyping strategies with the goal of optimizing the implementation of precision public health.

A population study of clinically actionable genetic variation affecting drug response from the Middle East

Clinical implementation of pharmacogenomics will help in personalizing drug prescriptions and alleviate the personal and financial burden due to inefficacy and adverse reactions to drugs. However, such implementation is lagging in many parts of the world, including the Middle East, mainly due to the lack of data on the distribution of actionable pharmacogenomic variation in these ethnicities. We analyzed 6,045 whole genomes from the Qatari population for the distribution of allele frequencies of 2,629 variants in 1,026 genes known to affect 559 drugs or classes of drugs. We also performed a focused analysis of genotypes or diplotypes of 15 genes affecting 46 drugs, which have guidelines for clinical implementation and predicted their phenotypic impact. The allele frequencies of 1,320 variants in 703 genes affecting 299 drugs or class of drugs were significantly different between the Qatari population and other world populations. On average, Qataris carry 3.6 actionable genotypes/diplotypes, affecting 13 drugs with guidelines for clinical implementation, and 99.5% of the individuals had at least one clinically actionable genotype/diplotype. Increased risk of simvastatin-induced myopathy could be predicted in ~32% of Qataris from the diplotypes of SLCO1B1, which is higher compared to many other populations, while fewer Qataris may need tacrolimus dosage adjustments for achieving immunosuppression based on the CYP3A5 diplotypes compared to other world populations. Distinct distribution of actionable pharmacogenomic variation was also observed among the Qatari subpopulations. Our comprehensive study of the distribution of actionable genetic variation affecting drugs in a Middle Eastern population has potential implications for preemptive pharmacogenomic implementation in the region and beyond.

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.

Genetic variation in human drug-related genes

Background

Variability in drug efficacy and adverse effects are observed in clinical practice. While the extent of genetic variability in classic pharmacokinetic genes is rather well understood, the role of genetic variation in drug targets is typically less studied.

Methods

Based on 60,706 human exomes from the ExAC dataset, we performed an in-depth computational analysis of the prevalence of functional variants in 806 drug-related genes, including 628 known drug targets. We further computed the likelihood of 1236 FDA-approved drugs to be affected by functional variants in their targets in the whole ExAC population as well as different geographic sub-populations.

Results

We find that most genetic variants in drug-related genes are very rare (f < 0.1%) and thus will likely not be observed in clinical trials. Furthermore, we show that patient risk varies for many drugs and with respect to geographic ancestry. A focused analysis of oncological drug targets indicates that the probability of a patient carrying germline variants in oncological drug targets is, at 44%, high enough to suggest that not only somatic alterations but also germline variants carried over into the tumor genome could affect the response to antineoplastic agents.

Conclusions

This study indicates that even though many variants are very rare and thus likely not observed in clinical trials, four in five patients are likely to carry a variant with possibly functional effects in a target for commonly prescribed drugs. Such variants could potentially alter drug efficacy.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0502-5) contains supplementary material, which is available to authorized users.

Pharmacogenomics education and research at the Department of Pharmacy, University of Patras, Greece

The Pharmacogenomics and Personalized Medicine group belongs to the Laboratory of Molecular Biology and Immunology, Department of Pharmacy and is active since 2009 mainly in the field of pharmacogenomics and personalized medicine. Herein, we describe the research interests, collaborations and accomplishments of the Pharmacogenomics and Personalized Medicine group together with the teaching activities of the group that greatly enhance the pharmacogenomics knowledge of graduate/postgraduate students and healthcare professionals.

ePGA: A Web-Based Information System for Translational Pharmacogenomics

One of the challenges that arise from the advent of personal genomics services is to efficiently couple individual data with state of the art Pharmacogenomics (PGx) knowledge. Existing services are limited to either providing static views of PGx variants or applying a simplistic match between individual genotypes and existing PGx variants. Moreover, there is a considerable amount of haplotype variation associated with drug metabolism that is currently insufficiently addressed. Here, we present a web-based electronic Pharmacogenomics Assistant (ePGA; http://www.epga.gr/) that provides personalized genotype-to-phenotype translation, linked to state of the art clinical guidelines. ePGA's translation service matches individual genotype-profiles with PGx gene haplotypes and infers the corresponding diplotype and phenotype profiles, accompanied with summary statistics. Additional features include i) the ability to customize translation based on subsets of variants of clinical interest, and ii) to update the knowledge base with novel PGx findings. We demonstrate ePGA's functionality on genetic variation data from the 1000 Genomes Project.

Collaborative Crowdsourcing for the Diagnosis of Rare Genetic Syndromes: The DYSCERNE Experience

The big-data revolution is creating a challenge for the provision of services in the health sector to keep pace with the expectations of the general population. Utilization of crowdsourcing can impact positively on the quality, cost and speed of healthcare by involving large sections of professionals and the public and creating novel science within an ethical framework. In 2007, the DYSCERNE project was funded by the European Commission Public Health Executive Agency (EU DG Sanco) aimed at setting up a network of expertise for rare dysmorphic disorders. As part of DYSCERNE, a Dysmorphology Diagnostic System was set up to enable clinicians throughout the EU to submit cases electronically for diagnosis using a secure, web-based interface, hosted at specified access points (submitting nodes), in 26 different European countries. DYSCERNE utilized the process of crowdsourcing international expertise for the clinical diagnosis of very rare genetic syndromes of multiple congenital anomalies. This is the first reported account of collaborative crowd sourcing in dysmorphology, as part of a clinical genetics service.

Personalized pharmacogenomics profiling using whole-genome sequencing

AIM

Pharmacogenomics holds promise to rationalize drug use by minimizing drug toxicity and at the same time increase drug efficacy. There are currently several assays to screen for known pharmacogenomic biomarkers for the most commonly prescribed drugs. However, these genetic screening assays cannot account for other known or novel pharmacogenomic markers.

MATERIALS & METHODS

We analyzed whole-genome sequences of 482 unrelated individuals of various ethnic backgrounds to obtain their personalized pharmacogenomics profiles.

RESULTS

Bioinformatics analysis revealed 408,964 variants in 231 pharmacogenes, from which 26,807 were residing on exons and proximal regulatory sequences, whereas 16,487 were novel. In silico analyses indicated that 1012 novel pharmacogene-related variants possibly abolish protein function. We have also performed whole-genome sequencing analysis in a seven-member family of Greek origin in an effort to explain the variable response rate to acenocoumarol treatment in two family members.

CONCLUSION

Overall, our data demonstrate that whole-genome sequencing, unlike conventional genetic screening methods, is necessary to determine an individual's pharmacogenomics profile in a more comprehensive manner, which, combined with the gradually decreasing whole-genome sequencing costs, would expedite bringing personalized medicine closer to reality.

Population pharmacokinetic/pharmacogenetic model of lopinavir/ritonavir in HIV-infected patients

AIM

This study aims to develop a population pharmacokinetic/pharmacogenetic model for lopinavir/ritonavir (LPV/r) in European HIV-infected patients.

MATERIALS & METHODS

A total of 693 LPV/r plasma concentrations were assessed and 15 single-nucleotide polymorphisms were genotyped. The population pharmacokinetic/pharmacogenetic model was created using a nonlinear mixed-effect approach (NONMEM^® v.7.2.0., ICON Development Solutions, Dublin, Ireland).

RESULTS

Covariates significantly related to LPV/r apparent clearance (CL/F) were ritonavir trough concentration (RTC), BMI, high-density lipoprotein cholesterol (HDL-C) and certain single-nucleotide polymorphisms in genes encoding for metabolizing enzymes, which are representable as follows: CL/F = (0.216BMI + 0.0125HDL-C) × 0.713^RTC × 1.26^{rs28371764[C/T]} × 0.528^{rs6945984[C/C]} × 0.302 ^{CYP3A4[1461insA/del]} Conclusion: The LPV/r standard dose appears to be appropriate for the rs28371764[C/T] genotype. However, lower doses should be recommended for the rs6945984[C/C] and CYP3A4[1461insA/del] genotypes and even for those patients without any of these variants, as the standard dose seems to be higher than that which is required in order to achieve therapeutic levels.

Bridging genomics research between developed and developing countries: the Genomic Medicine Alliance

The Genomic Medicine Alliance is a global academic research network that aims to establish and strengthen collaborative ties between the various genomic medicine stakeholders. Its focus lies on the translation of scientific research findings into clinical practice. It brings together experts from disciplines including genome informatics, pharmacogenomics, public health genomics, ethics in genomics and health economics, and it is supervised by a 14-member International Scientific Advisory Committee comprising internationally renowned scientists. The Alliance's official journal, Public Health Genomics, offers members a highly respected publication forum for their original research findings. In the short-to-medium term, the Genomic Medicine Alliance hopes to harmonize research activities between developed and developing countries and to organize educational activities in the field of genomic medicine.

Genomics into Healthcare: the 5th Pan Arab Human Genetics Conference and 2013 Golden Helix Symposium

The joint 5th Pan Arab Human Genetics conference and 2013 Golden Helix Symposium, "Genomics into Healthcare" was coorganized by the Center for Arab Genomic Studies (http://www.cags.org.ae) in collaboration with the Golden Helix Foundation (http://www.goldenhelix.org) in Dubai, United Arab Emirates from 17 to 19 November, 2013. The meeting was attended by over 900 participants, doctors and biomedical students from over 50 countries and was organized into a series of nine themed sessions that covered cancer genomics and epigenetics, genomic and epigenetic studies, genomics of blood and metabolic disorders, cytogenetic diagnosis and molecular profiling, next-generation sequencing, consanguinity and hereditary diseases, clinical genomics, clinical applications of pharmacogenomics, and genomics in public health.

A logistic equation to determine the validity of tramadol from related gene polymorphisms and psychological factors

Aim: This study was performed to develop an algorithm using polymorphisms of CYP2D6, p-gp, OPRM1, COMT and psychological variables to predict tramadol response in Chinese patients recovering from upper limb fracture internal fixation surgery. Methods: A total of 250 Han Chinese patients recovering from fracture in the upper limb were enrolled. CYP2D6*10, p-gp G2677T, p-gp C3435T, OPRM1 A118G and COMT Val158Met were detected by the ligase detection reaction (LDR) method. The algorithm was developed with binary logistic regression in cohort 1 (200 patients) and assessed with Wilcoxon signed-rank test in cohort 2 (50 patients). Results: According to cohort 1, the predictive equation was calculated with the following logistic regression parameters: Logit (1) = 2.304–4.841 × (anxiety I) – 23.709 × (anxiety II) + 2.823 × (p-gp 3435CT) + 5.737 × (p-gp 3435 TT) – 1.586 × (CYP2D6*10 CT) – 4.542 × (CYP2D6*10 TT). The cutoff point for the prediction was defined as a probability value ≥0.5. The equation’s positive predictive value is 90%. When applied to a new sample, the equation’s positive predictive value is 86%. The Nagelkerke R2 of the model is 0.819, the results of the Hosmer and Leme test show a value of 0.981. The nonparametric correlations between predicted and observed response showed significant correlation (coefficient = 0.879; p < 0.001). Conclusion: The algorithm we have developed might predict tramadol response in Chinese upper limb fracture patients.

Original submitted 24 April 2013; Revision submitted 24 January 2014