A qualitative approach to assess the opinion of physicians about the challenges and prospects of pharmacogenomic testing implementation in clinical practice in Greece.

BACKGROUND: Pharmacogenomics (PGx) constitutes an important part of personalized medicine and has several clinical applications. PGx role in clinical practice is known, however, it has not been widely adopted yet. In this study, we aim to investigate the perspectives of Greek physicians regarding the implementation of PGx testing in clinical practice and the key issues associated with it. METHODS: Fourteen interviews were conducted with physicians of various specialties for which PGx applications are available. A semi-structured interview guide was utilized based on the Consolidated Framework for Implementation Research (CFIR) context and the Diffusion of Innovation model. Transcripts were coded independently and compared by two members of the research team. Descriptive statistics were generated using Microsoft Excel. RESULTS: Six main themes emerged: awareness and use of PGx testing; source of information; key stakeholders of the PGx supply chain, their interactions and change agents; clinical benefit and significance of PGx testing; barriers and lack of reimbursement; and recommendations to boost the PGx adoption rate. Most respondents were aware of PGx applications, but only three had already recommended PGx testing. Peer-reviewed journals along with clinical guidelines were regarded as the most used source of information while stakeholders of the PGx supply chain were discussed. PGx was considered that promote patient-centered care, enhance medication clinical effectiveness, decrease the risk of side effects, and reduce healthcare costs. Lack of reimbursement, scarcity of resources, and high PGx cost were the foremost barriers affecting PGx adoption. CONCLUSIONS: It was concluded that if case PGx testing is reimbursed and physicians' training is reinforced, PGx implementation will be boosted and improved shortly.

Meta-analysis of genomic variants in power and endurance sports to decode the impact of genomics on athletic performance and success.

Association between genomic variants and athletic performance has seen a high degree of controversy, as there is often conflicting data as far as the association of genomic variants with endurance, speed and strength is concerned. Here, findings from a thorough meta-analysis from 4228 articles exploring the association of genomic variants with athletic performance in power and endurance sports are summarized, aiming to confirm or overrule the association of genetic variants with athletic performance of all types. From the 4228 articles, only 107 were eligible for further analysis, including 37 different genes. From these, there were 21 articles for the ACE gene, 29 articles for the ACTN3 gene and 8 articles for both the ACE and ACTN3 genes, including 54,382 subjects in total, from which 11,501 were endurance and power athletes and 42,881 control subjects. These data show that there is no statistically significant association between genomic variants and athletic performance either for endurance or power sports, underlying the fact that it is highly risky and even unethical to make such genetic testing services for athletic performance available to the general public. Overall, a strict regulatory monitoring should be exercised by health and other legislative authorities to protect the public from such services from an emerging discipline that still lacks the necessary scientific evidence and subsequent regulatory approval.

The diversity and clinical implications of genetic variants influencing clopidogrel bioactivation and response in the Emirati population.

BACKGROUND: Clopidogrel is a widely prescribed prodrug that requires activation via specific pharmacogenes to exert its anti-platelet function. Genetic variations in the genes encoding its transporter, metabolizing enzymes, and target receptor lead to variability in its activation and platelet inhibition and, consequently, its efficacy. This variability increases the risk of secondary cardiovascular events, and therefore, some variations have been utilized as genetic biomarkers when prescribing clopidogrel. METHODS: Our study examined clopidogrel-related genes (CYP2C19, ABCB1, PON1, and P2Y12R) in a cohort of 298 healthy Emiratis individuals. The study used whole exome sequencing (WES) data to comprehensively analyze pertinent variations of these genes, including their minor allele frequencies, haplotype distribution, and their resulting phenotypes. RESULTS: Our data shows that approximately 37% (n = 119) of the cohort are likely to benefit from the use of alternative anti-platelet drugs due to their classification as intermediate or poor CYP2C19 metabolizers. Additionally, more than 50% of the studied cohort exhibited variants in ABCB1, PON1, and P2YR12 genes, potentially influencing clopidogrel's transport, enzymatic clearance, and receptor performance. CONCLUSIONS: Recognizing these alleles and genotype frequencies may explain the clinical differences in medication response across different ethnicities and predict adverse events. Our findings underscore the need to consider genetic variations in prescribing clopidogrel, with potential implications for implementing personalized anti-platelet therapy among Emiratis based on their genetic profiles.

A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study.

BACKGROUND: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. METHODS: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING: European Union Horizon 2020.

Cost-effectiveness analysis of CYP3A5 genotype-guided tacrolimus dosing in solid organ transplantation using real-world data.

The objective of this study was to estimate the cost-effectiveness of CYP3A5 genotype-guided tacrolimus dosing in kidney, liver, heart, and lung transplant recipients relative to standard of care (SOC) tacrolimus dosing, from a US healthcare payer perspective. We developed decision-tree models to compare economic and clinical outcomes between CYP3A5 genotype-guided and SOC tacrolimus therapy in the first six months post-transplant. We derived inputs for CYP3A5 phenotype frequencies and physician use of genotype test results to inform clinical care from literature; tacrolimus exposure [high vs low tacrolimus time in therapeutic range using the Rosendaal algorithm (TAC TTR-Rosendaal)] and outcomes (incidences of acute tacrolimus nephrotoxicity, acute cellular rejection, and death) from real-world data; and costs from the Medicare Fee Schedule and literature. We calculated cost per avoided event and performed sensitivity analyses to evaluate the robustness of the results to changes in inputs. Incremental costs per avoided event for CYP3A5 genotype-guided vs SOC tacrolimus dosing were $176,667 for kidney recipients, $364,000 for liver recipients, $12,982 for heart recipients, and $93,333 for lung recipients. The likelihood of CYP3A5 genotype-guided tacrolimus dosing leading to cost-savings was 19.8% in kidney, 32.3% in liver, 51.8% in heart, and 54.1% in lung transplant recipients. Physician use of genotype results to guide clinical care and the proportion of patients with a high TAC TTR-Rosendaal were key parameters driving the cost-effectiveness of CYP3A5 genotype-guided tacrolimus therapy. Relative to SOC, CYP3A5 genotype-guided tacrolimus dosing resulted in a slightly greater benefit at a higher cost. Further economic evaluations examining intermediary outcomes (e.g., dose modifications) are needed, particularly in populations with higher frequencies of CYP3A5 expressers.

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living.

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

Pharmacy students' attitudes and intentions of pursuing postgraduate studies and training in pharmacogenomics and personalised medicine.

BACKGROUND: Pharmacists' contribution to pharmacogenomics (PGx) implementation in clinical practice is vital, but a great proportion of them are not aware of PGx and its applications. This highlights the university education's crucial role to prepare pharmacists to face future challenges in such a constantly evolving and demanding environment. OBJECTIVES: Our study aims to examine pharmacy students' training satisfaction, knowledge, self-confidence and attitudes towards PGx on their intentions for postgraduate training in PGx and personalised medicine (PM). METHODS: An initial model on students' intention to pursue postgraduate training in PGx and PM and its predicting factors, based on the Theory of Planned Behaviour (TPB), was proposed. Based on it, a questionnaire was developed and distributed to 346 pharmacy students of all study years, capturing the selected factors influencing students' intentions to postgraduate training in PGx and PM, as well as their demographics. Structural equation modelling (SEM) analysis was employed to determine the effects of both the examined factors and demographics on students' intentions. RESULTS: Students did not consider themselves adequately prepared for using PGx in clinical practice. Their attitudes towards PGx implementation were the most important factor influencing their intentions to pursue postgraduate training in PGx and PM. Other factors such as self-confidence and training satisfaction also affected students' intentions, but to a lower extent. Students of the last two study years (40% of the whole sample) and male (36%) students stated to be less willing to pursue PGx-related studies in the future. Only 10% of the participants claimed to have undergone a recent PGx or genetic test, but this did not affect their intentions. CONCLUSION: There is an important gap in pharmacy school curriculum regarding PGx and PM training which coupled with the slow rate of PGx and PM implementation into clinical practice seems to restrain students' aspiration to further expand their knowledge and horizons in terms of PGx and PM.

Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics.

BACKGROUND: This pilot study aims to identify and functionally assess pharmacovariants in whole exome sequencing data. While detection of known variants has benefited from pharmacogenomic-dedicated bioinformatics tools before, in this paper we have tested novel deep computational analysis in addition to artificial intelligence as possible approaches for functional analysis of unknown markers within less studied drug-related genes. METHODS: Pharmacovariants from 1800 drug-related genes from 100 WES data files underwent (a) deep computational analysis by eight bioinformatic algorithms (overall containing 23 tools) and (b) random forest (RF) classifier as the machine learning (ML) approach separately. ML model efficiency was calculated by internal and external cross-validation during recursive feature elimination. Protein modelling was also performed for predicted highly damaging variants with lower frequencies. Genotype-phenotype correlations were implemented for top selected variants in terms of highest possibility of being damaging. RESULTS: Five deleterious pharmacovariants in the RYR1, POLG, ANXA11, CCNH, and CDH23 genes identified in step (a) and subsequent analysis displayed high impact on drug-related phenotypes. Also, the utilization of recursive feature elimination achieved a subset of 175 malfunction pharmacovariants in 135 drug-related genes that were used by the RF model with fivefold internal cross-validation, resulting in an area under the curve of 0.9736842 with an average accuracy of 0.9818 (95% CI: 0.89, 0.99) on predicting whether a carrying individuals will develop adverse drug reactions or not. However, the external cross-validation of the same model indicated a possible false positive result when dealing with a low number of observations, as only 60 important variants in 49 genes were displayed, giving an AUC of 0.5384848 with an average accuracy of 0.9512 (95% CI: 0.83, 0.99). CONCLUSION: While there are some technologies for functionally assess not-interpreted pharmacovariants, there is still an essential need for the development of tools, methods, and algorithms which are able to provide a functional prediction for every single pharmacovariant in both large-scale datasets and small cohorts. Our approaches may bring new insights for choosing the right computational assessment algorithms out of high throughput DNA sequencing data from small cohorts to be used for personalized drug therapy implementation.

Knowledge, attitudes, and perceptions of the multi-ethnic population of the United Arab Emirates on genomic medicine and genetic testing.

INTRODUCTION: The adoption and implementation of genomic medicine and pharmacogenomics (PGx) in healthcare systems have been very slow and limited worldwide. Major barriers to knowledge translation into clinical practice lie in the level of literacy of the public of genetics and genomics. The aim of this study was to assess the knowledge, attitudes, and perceptions of the United Arab Emirates (UAE) multi-ethnic communities toward genomic medicine and genetic testing. METHOD: A cross-sectional study using validated questionnaires was distributed to the participants. Descriptive statistics were performed, and multivariable logistic regression models were used to identify factors associated with knowledge of genomics. RESULTS: 757 individuals completed the survey. Only 7% of the participants had a good knowledge level in genetics and genomics (95% CI 5.3-9.0%). However, 76.9% of the participants were willing to take a genetic test if their relatives had a genetic disease. In addition, the majority indicated that they would disclose their genetic test results to their spouses (61.5%) and siblings (53.4%). CONCLUSIONS: This study sets the stage for the stakeholders to plan health promotion and educational campaigns to improve the genomic literacy of the community of the UAE as part of their efforts for implementing precision and personalized medicine in the country.

Genome-wide analysis toward the epigenetic aetiology of myelodysplastic syndrome disease progression and pharmacoepigenomic basis of hypomethylating agents drug treatment response.

Myelodysplastic syndromes (MDS) consist of a group of hematological malignancies characterized by ineffective hematopoiesis, cytogenetic abnormalities, and often a high risk of transformation to acute myeloid leukemia (AML). So far, there have been only a very limited number of studies assessing the epigenetics component contributing to the pathophysiology of these disorders, but not a single study assessing this at a genome-wide level. Here, we implemented a generic high throughput epigenomics approach, using methylated DNA sequencing (MeD-seq) of LpnPI digested fragments to identify potential epigenomic targets associated with MDS subtypes. Our results highlighted that PCDHG and ZNF gene families harbor potential epigenomic targets, which have been shown to be differentially methylated in a variety of comparisons between different MDS subtypes. Specifically, CpG islands, transcription start sites and post-transcriptional start sites within ZNF124, ZNF497 and PCDHG family are differentially methylated with fold change above 3,5. Overall, these findings highlight important aspects of the epigenomic component of MDS syndromes pathogenesis and the pharmacoepigenomic basis to the hypomethylating agents drug treatment response, while this generic high throughput whole epigenome sequencing approach could be readily implemented to other genetic diseases with a strong epigenetic component.

Economic evaluation of pharmacogenomic-guided antiplatelet treatment in Spanish patients suffering from acute coronary syndrome participating in the U-PGx PREPARE study.

BACKGROUND: Cardiovascular diseases and especially Acute Coronary Syndrome (ACS) constitute a major health issue impacting millions of patients worldwide. Being a leading cause of death and hospital admissions in many European countries including Spain, it accounts for enormous amounts of healthcare expenditures for its management. Clopidogrel is one of the oldest antiplatelet medications used as standard of care in ACS. METHODS: In this study, we performed an economic evaluation study to estimate whether a genome-guided clopidogrel treatment is cost-effective compared to conventional one in a large cohort of 243 individuals of Spanish origin suffering from ACS and treated with clopidogrel. Data were derived from the U-PGx PREPARE clinical trial. Effectiveness was measured as survival of individuals while study data on safety and efficacy, as well as on resource utilization associated with each adverse drug reaction were used to measure costs to treat these adverse drug reactions. A generalized linear regression model was used to estimate cost differences for both study groups. RESULTS: Based on our findings, PGx-guided treatment group is cost-effective. PGx-guided treatment demonstrated to have 50% less hospital admissions, reduced emergency visits and almost 13% less ADRs compared to the non-PGx approach with mean QALY 1.07 (95% CI, 1.04-1.10) versus 1.06 (95% CI, 1.03-1.09) for the control group, while life years for both groups were 1.24 (95% CI, 1.20-1.26) and 1.23 (95% CI, 1.19-1.26), respectively. The mean total cost of PGx-guided treatment was 50% less expensive than conventional therapy with clopidogrel [€883 (95% UI, €316-€1582), compared to €1,755 (95% UI, €765-€2949)]. CONCLUSION: These findings suggest that PGx-guided clopidogrel treatment represents a cost-effective option for patients suffering from ACS in the Spanish healthcare setting.

Roadmap for Establishing Large-Scale Genomic Medicine Initiatives in Low- and Middle-Income Countries.

In the post-genomic era, genomic medicine interventions as a key component of personalized medicine and tailored-made health care are greatly anticipated following recent scientific and technological advances. Indeed, large-scale sequencing efforts that explore human genomic variation have been initiated in several, mostly developed, countries across the globe, such as the United States, the United Kingdom, and a few others. Here, we highlight the successful implementation of large-scale national genomic initiatives, namely the Genome of Greece (GoGreece) and the DNA do Brasil (DNABr), aiming to emphasize the importance of implementing such initiatives in developing countries. Based on this experience, we also provide a roadmap for replicating these projects in other low-resource settings, thereby bringing genomic medicine in these countries closer to clinical fruition.

Using ChatGPT to predict the future of personalized medicine.

Personalized medicine is a novel frontier in health care that is based on each person's unique genetic makeup. It represents an exciting opportunity to improve the future of individualized health care for all individuals. Pharmacogenomics, as the main part of personalized medicine, aims to optimize and create a more targeted treatment approach based on genetic variations in drug response. It is predicted that future treatments will be algorithm-based instead of evidence-based that will consider a patient's genetic, transcriptomic, proteomic, epigenetic, and lifestyle factors resulting in individualized medication. A generative pretrained transformer (GPT) is an artificial intelligence (AI) tool that generates language resembling human-like writing enabling users to engage in a manner that is practically identical to speaking with a human being. GPT's predictive algorithms can respond to questions that have never been addressed. Chat Generative Pretrained Transformer (ChatGPT) is an AI chatbot's advanced with conversational capabilities. In the present study, questions were asked from ChatGPT about the future of personalized medicine and pharmacogenomics. ChatGPT predicted both to be a promising approach with a bright future that holds great promises in improving patient outcomes and transforming the field of medicine. But it still has several limitations that need to be solved.

Examining key factors impact on health science students' intentions to adopt genetic and pharmacogenomics testing: a comparative path analysis in two different healthcare settings.

BACKGROUND: There is an increasing interest worldwide in investigating healthcare stakeholders' perceptions and intentions to adopt pharmacogenomics (PGx) into clinical practice. However, the existing inquiries based on well-established theories and models that interpret their intentions to implement PGx are scarce. This study is the first that examines the impact of selected factors on health science students' intention to adopt genetic testing applications using the technology acceptance model while it compares two different cultural groups: Greeks (Europe; Christian) and Malays (Asia; Muslim). RESULTS: Malay students were more persuaded about benefits of genomics for drug management compared to their Greek counterparts. However, participants from both countries appear to be particularly convinced about the benefits of genomics on disease management. Moreover, students from both countries considered the potential misuse of genetic information by corporate or government bodies as their most important concern; Greek students appeared to be considerably less worried than Malay about other probable hazards such as the deficient protection of privacy and confidentiality, which could be attributed to their religious background. Participants from both samples expressed very positive attitudes towards genetic research and testing and their favourable intentions to adopt genetic testing for personal use. Exploratory factors analysis and path analysis yielded quite similar results for both samples. Path analysis revealed that the factors of attitudes, concerns, drug management benefits and disease management benefits significantly influenced students' intentions to adopt genetic testing for personal use, with attitudes being the most inspirational factor with rather high impact, while training did not seem to affect participant's intentions. The squared multiple correlation of both models was quite satisfactory reaching to 0.55 for the Malaysian sample. CONCLUSION: Similarities in the results of the two groups along with the relevant validity and reliability tests indicate that the proposed model is a good fit for future studies to interpret stakeholders' intentions to adopt genetic testing. Therefore, it can provide a promising and reliable basis for future model development to explain the relationships between intentions to adopt genetic testing and its predictors.

Analysis on in vitro effect of lithium on telomere length in lymphoblastoid cell lines from bipolar disorder patients with different clinical response to long-term lithium treatment.

BACKGROUND: It has been suggested that bipolar disorder (BD) is associated with clinical and biological features of accelerated aging. In our previous studies, we showed that long-term lithium treatment was correlated with longer leukocyte telomere length (LTL) in BD patients. A recent study explored the role of TL in BD using patients-derived lymphoblastoid cell lines (LCLs), showing that baseline TL was shorter in BD compared to controls and that lithium in vitro increased TL but only in BD. Here, we used the same cell system (LCLs) to explore if a 7-day treatment protocol with lithium chloride (LiCl) 1 mM was able to highlight differences in TL between BD patients clinically responders (Li-R; n = 15) or non-responders (Li-NR; n = 15) to lithium, and if BD differed from non-psychiatric controls (HC; n = 15). RESULTS: There was no difference in TL between BD patients and HC. Moreover, LiCl did not influence TL in the overall sample, and there was no difference between diagnostic or clinical response groups. Likewise, LiCl did not affect TL in neural precursor cells from healthy donors. CONCLUSIONS: Our findings suggest that a 7-day lithium treatment protocol and the use of LCLs might not represent a suitable approach to deepen our understanding on the role of altered telomere dynamics in BD as previously suggested by studies in vivo.

Pharmacogenomics implementation in cardiovascular disease in a highly diverse population: initial findings and lessons learned from a pilot study in United Arab Emirates.

BACKGROUND: Pharmacogenomic (PGx) testing has proved its utility and cost-effectiveness for some commonly prescribed cardiovascular disease (CVD) medications. In addition, PGx-guided dosing guidelines are now available for multiple CVD drugs, including clopidogrel, warfarin, and statins. The United Arab Emirates (UAE) population is diverse and multiethnic, with over 150 nationalities residing in the country. PGx-testing is not part of the standard of care in most global healthcare settings, including the UAE healthcare system. The first pharmacogenomic implementation clinical study in CVD has been approved recently, but multiple considerations needed evaluation before commencing. The current report appraises the PGx-clinical implementation procedure and the potential benefits of pursuing PGx-implementation initiatives in the UAE with global implications. METHODS: Patients prescribed one or more of the following drugs: clopidogrel, atorvastatin, rosuvastatin, and warfarin, were recruited. Genotyping selected genetic variants at genes interacting with the study drugs was performed by real-time PCR. RESULTS: For the current pilot study, 160 patients were recruited. The genotypes and inferred haplotypes, diplotypes, and predicted phenotypes revealed that 11.9% of the participants were poor CYP2C19 metabolizers, 35% intermediate metabolizers, 28.1% normal metabolizers, and 25% rapid or ultrarapid metabolizers. Notably, 46.9% of our cohort should receive a recommendation to avoid using clopidogrel or consider an alternative medication. Regarding warfarin, only 20% of the participants exhibited reference alleles at VKORC1-1639G > A, CYP2C9*2, and CYP2C9*3, leaving 80% with alternative genotypes at any of the two genes that can be integrated into the warfarin dosing algorithms and can be used whenever the patient receives a warfarin prescription. For statins, 31.5% of patients carried at least one allele at the genotyped SLCO1B1 variant (rs4149056), increasing their risk of developing myopathy. 96% of our cohort received at least one PGx-generated clinical recommendation for the studied drugs. CONCLUSION: The current pilot analysis verified the feasibility of PGx-testing and the unforeseen high frequencies of patients currently treated with suboptimal drug regimens, which may potentially benefit from PGx testing.

Cost-utility analysis and cross-country comparison of pharmacogenomics-guided treatment in colorectal cancer patients participating in the U-PGx PREPARE study.

OBJECTIVES: A cost-utility analysis was conducted to evaluate pharmacogenomic (PGx)-guided treatment compared to the standard-of-care intervention among patients diagnosed with colorectal cancer (CRC) in Italy. METHODS: Data derived from a prospective, open-label, block randomized clinical trial, as a part of the largest PGx study worldwide (355 patients in both arms) were used. Mortality was used as the primary health outcome to estimate life years (LYs) gained in treatment arms within a survival analysis context. PGx-guided treatment was based on established drug-gene interactions between capecitabine, 5-fluorouracil and irinotecan with DPYD and/or UGT1A1 genomic variants. Utility values for the calculation of Quality Adjusted Life Year (QALY) was based on Visual Analog Scale (VAS) score. Missing data were imputed via the Multiple Imputation method and linear interpolation, when possible, while censored cost data were corrected via the Replace-From-The-Right algorithm. The Incremental Cost-Effectiveness Ratio (ICER) was calculated for QALYs. Raw data were bootstrapped 5000 times in order to produce 95% Confidence Intervals based on non-parametric percentile method and to construct a cost-effectiveness acceptability curve. Cost differences for study groups were investigated via a generalized linear regression model analysis. Total therapy cost per patient reflected all resources expended in the management of any adverse events, including medications, diagnostics tests, devices, surgeries, the utilization of intensive care units, and wards. RESULTS: The total cost of the study arm was estimated at €380 (∼ US$416; 95%CI: 195-596) compared to €565 (∼ US$655; 95%CI: 340-724) of control arm while the mean survival in study arm was estimated at 1.58 (+0.25) LYs vs 1.50 (+0.26) (Log Rank test, X2 = 4.219, df=1, p-value=0.04). No statistically significant difference was found in QALYs. ICER was estimated at €13418 (∼ US$14695) per QALY, while the acceptability curve indicated that when the willingness-to-pay was under €5000 (∼ US$5476), the probability of PGx being cost-effective overcame 70%. The most frequent adverse drug event in both groups was neutropenia of severity grade 3 and 4, accounting for 82.6% of total events in the study arm and 65.0% in the control arm. Apart from study arm, smoking status, Body-Mass-Index and Cumulative Actionability were also significant predictors of total cost. Subgroup analysis conducted in actionable patients (7.9% of total patients) indicated that PGx-guided treatment was a dominant option over its comparator with a probability greater than 92%. In addition, a critical literature review was conducted, and these findings are in line with those reported in other European countries. CONCLUSION: PGx-guided treatment strategy may represent a cost-saving option compared to the existing conventional therapeutic approach for colorectal cancer patient management in the National Health Service of Italy.

Clinically relevant updates of the HbVar database of human hemoglobin variants and thalassemia mutations.

HbVar (http://globin.bx.psu.edu/hbvar) is a widely-used locus-specific database (LSDB) launched 20 years ago by a multi-center academic effort to provide timely information on the numerous genomic variants leading to hemoglobin variants and all types of thalassemia and hemoglobinopathies. Here, we report several advances for the database. We made clinically relevant updates of HbVar, implemented as additional querying options in the HbVar query page, allowing the user to explore the clinical phenotype of compound heterozygous patients. We also made significant improvements to the HbVar front page, making comparative data querying, analysis and output more user-friendly. We continued to expand and enrich the regular data content, involving 1820 variants, 230 of which are new entries. We also increased the querying potential and expanded the usefulness of HbVar database in the clinical setting. These several additions, expansions and updates should improve the utility of HbVar both for the globin research community and in a clinical setting.

The Utility of CYP2D6 and CYP2C19 Variants to Guide Pharmacological Treatment in Complex Unipolar Major Depression: A Pilot Longitudinal Study.

Major depression is a frequent condition which variably responds to treatment. In view of its high prevalence, the presence of treatment resistance in major depression significantly impacts on quality of life. Tailoring pharmacological treatment based on genetic polymorphisms is a current trend to personalizing pharmacological treatment in patients with major depressive disorders. Current guidelines for the use of genetic tests in major depression issued by the Clinical Pharmacogenomics Implementation Consortium (CPIC) are based on CYP2D6 and CYP2C19 polymorphisms which constitute the strongest evidence for pharmacogenomic guided treatment. There is evidence of increased clinical response to pharmacological treatment in major depression although largely in non-treatment resistant patients from Western countries. In this study, well characterised participants (N = 15) with complex, largely treatment resistant unipolar major depression were investigated, and clinical improvement was measured at baseline and at week-8 after the pharmacogenomics-guided treatment with the Montgomery Åsberg Depression Rating Scale (MÅDRS). Results suggested a statistically significant improvement (p = 0.01) of 16% at endpoint in the whole group and a larger effect in case of changes in medication regime (28%, p = 0.004). This small but appreciable effect can be understood in the context of the level of treatment resistance in the group. To our knowledge, this is the first study from the Middle East demonstrating the feasibility of this approach in the treatment of complex major depressive disorders.

Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide.

Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.