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Pharmacogenomics Jun 2021Combination drug therapies have become an integral part of precision oncology, and while evidence of clinical effectiveness continues to grow, the underlying mechanisms... (Review)
Review
Combination drug therapies have become an integral part of precision oncology, and while evidence of clinical effectiveness continues to grow, the underlying mechanisms supporting synergy are poorly understood. Immortalized human lymphoblastoid cell lines (LCLs) have been proven as a particularly useful, scalable and low-cost model in pharmacogenetics research, and are suitable for elucidating the molecular mechanisms of synergistic combination therapies. In this review, we cover the advantages of LCLs in synergy pharmacogenomics and consider recent studies providing initial evidence of the utility of LCLs in synergy research. We also discuss several opportunities for LCL-based systems to address gaps in the research through the expansion of testing regimens, assessment of new drug classes and higher-order combinations, and utilization of integrated omics technologies.
Topics: Antineoplastic Combined Chemotherapy Protocols; Cell Line, Tumor; Humans; Lymphocytes; Pharmacogenomic Testing
PubMed: 34044623
DOI: 10.2217/pgs-2020-0160 -
The Journal of Molecular Diagnostics :... Mar 2022Clinical pharmacogenomic testing typically uses targeted genotyping, which only detects variants included in the test design and may vary among laboratories. To evaluate...
Clinical pharmacogenomic testing typically uses targeted genotyping, which only detects variants included in the test design and may vary among laboratories. To evaluate the potential patient impact of genotyping compared with sequencing, which can detect common and rare variants, an in silico targeted genotyping panel was developed based on the variants most commonly included in clinical tests and applied to a cohort of 10,030 participants who underwent sequencing for CYP1A2, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, DPYD, SLCO1B1, TPMT, UGT1A1, and VKORC1. The results of in silico targeted genotyping were compared with the clinically reported sequencing results. Of the 10,030 participants, 2780 (28%) had at least one potentially clinically relevant variant/allele identified by sequencing that would not have been detected in a standard targeted genotyping panel. The genes with the largest number of participants with variants only detected by sequencing were SLCO1B1, DPYD, and CYP2D6, which affected 13%, 6.3%, and 3.5% of participants, respectively. DPYD (112 variants) and CYP2D6 (103 variants) had the largest number of unique variants detected only by sequencing. Although targeted genotyping detects most clinically significant pharmacogenomic variants, sequencing-based approaches are necessary to detect rare variants that collectively affect many patients. However, efforts to establish pharmacogenomic variant classification systems and nomenclature to accommodate rare variants will be required to adopt sequencing-based pharmacogenomics.
Topics: Alleles; Cytochrome P-450 CYP2D6; Genotype; Humans; Liver-Specific Organic Anion Transporter 1; Pharmacogenetics; Pharmacogenomic Testing; Vitamin K Epoxide Reductases
PubMed: 35041929
DOI: 10.1016/j.jmoldx.2021.11.008 -
Human Genomics Jan 2024Community pharmacists must be well-equipped to advance pharmacogenomics services. Nevertheless, limited data is available regarding pharmacists' knowledge and attitudes...
BACKGROUND
Community pharmacists must be well-equipped to advance pharmacogenomics services. Nevertheless, limited data is available regarding pharmacists' knowledge and attitudes toward pharmacogenomics testing. The present study aimed to evaluate community pharmacists' knowledge and attitudes toward pharmacogenomics testing in the UAE.
METHODS
In this cross-sectional study, a validated, online, self-administered survey, was randomly distributed to community pharmacists across the United Arab Emirates (UAE).
RESULTS
The participants demonstrated poor knowledge about pharmacogenomic testing (median score < 8). Having 10-29 (Adjusted odds ration [AOR]: 0.038; 95% CI: 0.01-0.146, p = 0.001) and 30-49 (AOR: 0.097; 95% CI: 0.04-0.237, p = 0.001) patients per day was associated with poorer knowledge. Also, receiving 10-29 (AOR: 0.046; 95% CI: 0.005-0.401, p = 0.005), 30-49 (AOR: 0.025; 95% CI: 0.003-0.211, p = 0.001), and > 50 (AOR: 0.049; 95% CI: 0.005-0.458, p = 0.008) prescriptions decreased the odds of having good knowledge. Around half (43.9%) of the participants did not show a positive attitude toward pharmacogenomic testing (median score < 11). Having 30-49 patients per day (AOR: 5.351; 95% CI: 2.414-11.860, p = 0.001) increased the odds of good knowledge while receiving 10-29 (AOR: 0.133; 95% CI: 0.056-0.315, p = 0.001) and 30-49 (AOR: 0.111; 95% CI: 0.049-0.252, p = 0.001) prescriptions a day were associated with decreased odds of positive attitude toward the pharmacogenomics testing.
CONCLUSIONS
The findings indicate a lack of knowledge and less-than-ideal attitudes among community pharmacists regarding pharmacogenomics testing. Enhanced efforts focused on educational initiatives and training activities related to pharmacogenomics testing is needed. Additionally, reducing workload can facilitate better knowledge acquisition and help mitigate unfavorable attitudes.
Topics: Humans; Pharmacogenetics; Pharmacogenomic Testing; Pharmacists; Cross-Sectional Studies; Health Knowledge, Attitudes, Practice
PubMed: 38291455
DOI: 10.1186/s40246-024-00574-z -
Molecular Omics Aug 2018The toxicogenomics field aims to understand and predict toxicity by using 'omics' data in order to study systems-level responses to compound treatments. In recent years... (Review)
Review
The toxicogenomics field aims to understand and predict toxicity by using 'omics' data in order to study systems-level responses to compound treatments. In recent years there has been a rapid increase in publicly available toxicological and 'omics' data, particularly gene expression data, and a corresponding development of methods for its analysis. In this review, we summarize recent progress relating to the analysis of RNA-Seq and microarray data, review relevant databases, and highlight recent applications of toxicogenomics data for understanding and predicting compound toxicity. These include the analysis of differentially expressed genes and their enrichment, signature matching, methods based on interaction networks, and the analysis of co-expression networks. In the future, these state-of-the-art methods will likely be combined with new technologies, such as whole human body models, to produce a comprehensive systems-level understanding of toxicity that reduces the necessity of in vivo toxicity assessment in animal models.
Topics: Animals; Databases, Genetic; Drug Discovery; Gene Expression Profiling; Gene Expression Regulation; Gene Regulatory Networks; Humans; Pharmacogenomic Testing; Systems Biology; Toxicity Tests; Toxicogenetics
PubMed: 29917034
DOI: 10.1039/c8mo00042e -
Clinical Pharmacology and Therapeutics Sep 2021Pharmacogenetics (PGx) seeks to enable selection of the right dose of the right drug for each patient to optimize therapeutic outcomes. Most PGx focuses on... (Review)
Review
Pharmacogenetics (PGx) seeks to enable selection of the right dose of the right drug for each patient to optimize therapeutic outcomes. Most PGx focuses on pharmacokinetics (PKs), due to our relatively advanced understanding of the genes involved in PKs and the causative effects of variants in those genes. Genetic variants can also affect pharmacodynamics (PDs), but relatively few PGx-PD associations have been identified. This is partially due to a more limited understanding of the relevant genes and the consequences of genetic variation, but is also due in part to the potential confounding of PK variability in assessments of clinical outcomes that have a contribution from both PKs and PDs. For example, it is challenging to confirm the effect of mu opioid receptor (OPRM1) genetic variation on opioid response due to the contribution of CYP2D6 genotype to bioactivation of some opioid drugs (i.e., codeine and tramadol). The objectives of this mini-review are to describe several recent efforts to discover and validate PGx-PD that disentangle the influence of PK variability and propose potential approaches that could be used in future PGx-PD analyses. We use the effect of OPRM1 genetics on opioid response to illustrate how these analyses could be conducted and conclude by discussing how PGx-PD could be translated into clinical practice to improve therapeutic outcomes.
Topics: Analgesics, Opioid; Genetic Variation; Genotype; Humans; Pharmacogenetics; Pharmacogenomic Testing; Receptors, Opioid, mu
PubMed: 34043820
DOI: 10.1002/cpt.2312 -
Genetics in Medicine : Official Journal... Apr 2021Pharmacogenomic biomarkers are increasingly listed on medication labels and authoritative guidelines but pharmacogenomic-guided prescribing is not yet common. Our...
PURPOSE
Pharmacogenomic biomarkers are increasingly listed on medication labels and authoritative guidelines but pharmacogenomic-guided prescribing is not yet common. Our objective was to assess the potential for incorporating knowledge of patients' genomic characteristics into prescribing practices.
METHODS
We performed a retrospective analysis of claims data for 2,096,971 beneficiaries with pharmacy coverage from a national, commercial health insurance plan between January 2017 and December 2019. Children between 0 and 17 years comprised 21% of the cohort. Adults were age 18 to 64. Medications with actionable pharmacogenomic biomarkers (MAPBs) were identified using public information from the US Food and Drug Administration (FDA), Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB.
RESULTS
MAPBs were dispensed to 63% of the adults and 29% of the children in the cohort. Most frequently dispensed were ibuprofen, ondansetron, codeine, and oxycodone. Most common were medications with CYP2D6, G6PD, or CYPC19 pharmacogenomic biomarkers. Ten percent of the cohort were codispensed more than one MAPB for at least 30 days.
CONCLUSION
The number of people who might benefit from pharmacogenomic-guided prescribing is substantial. Future work should address obstacles to integrating genomic data into prescriber workflows, complex factors contributing to the magnitude of benefit, and the clinical availability of reliable on-demand or pre-emptive pharmacogenomic testing.
Topics: Adolescent; Adult; Biomarkers; Child; Drug Labeling; Humans; Middle Aged; Pharmacogenetics; Pharmacogenomic Testing; Retrospective Studies; Young Adult
PubMed: 33420348
DOI: 10.1038/s41436-020-01044-2 -
Clinical Pharmacokinetics Apr 2016It is well established that variations in genes can alter the pharmacokinetic and pharmacodynamic profile of a drug and immunological responses to it. Early advances in... (Review)
Review
It is well established that variations in genes can alter the pharmacokinetic and pharmacodynamic profile of a drug and immunological responses to it. Early advances in pharmacogenetics were made with traditional genetic techniques such as functional cloning of genes using knowledge gained from purified proteins, and candidate gene analysis. Over the past decade, techniques for analysing the human genome have accelerated greatly as knowledge and technological capabilities have grown. These techniques were initially focussed on understanding genetic factors of disease, but increasingly they are helping to clarify the genetic basis of variable drug responses and adverse drug reactions (ADRs). We examine genetic methods that have been applied to the understanding of ADRs, review the current state of knowledge of genetic factors that influence ADR development, and discuss how the application of genome-wide association studies and next-generation sequencing approaches is supporting and extending existing knowledge of pharmacogenetic processes leading to ADRs. Such approaches have identified single genes that are major contributing genetic risk factors for an ADR, (such as flucloxacillin and drug-induced liver disease), making pre-treatment testing a possibility. They have contributed to the identification of multiple genetic determinants of a single ADR, some involving both pharmacologic and immunological processes (such as phenytoin and severe cutaneous adverse reactions). They have indicated that rare genetic variants, often not previously reported, are likely to have more influence on the phenotype than common variants that have been traditionally tested for. The problem of genotype/phenotype discordance affecting the interpretation of pharmacogenetic screening and the future of genome-based testing applied to ADRs are also discussed.
Topics: Drug-Related Side Effects and Adverse Reactions; Genetic Variation; Genome-Wide Association Study; Genomics; Genotype; Humans; Pharmacogenomic Testing
PubMed: 26369774
DOI: 10.1007/s40262-015-0324-9 -
Clinical and Translational Science Jan 2021Interindividual variability in drug efficacy and toxicity is a major challenge in clinical practice. Variations in drug pharmacokinetics (PKs) and pharmacodynamics (PDs)... (Review)
Review
Interindividual variability in drug efficacy and toxicity is a major challenge in clinical practice. Variations in drug pharmacokinetics (PKs) and pharmacodynamics (PDs) can be, in part, explained by polymorphic variants in genes encoding drug metabolizing enzymes and transporters (absorption, distribution, metabolism, and excretion) or in genes encoding drug receptors. Pharmacogenomics (PGx) has allowed the identification of predictive biomarkers of drug PKs and PDs and the current knowledge of genome-disease and genome-drug interactions offers the opportunity to optimize tailored drug therapy. High-throughput PGx genotyping, from targeted to more comprehensive strategies, allows the identification of PK/PD genotypes to be developed as clinical predictive biomarkers. However, a biomarker needs a robust process of validation followed by clinical-grade assay development and must comply to stringent regulatory guidelines. We here discuss the methodological challenges and the emerging technological tools in PGx biomarker discovery and validation, at the crossroad among molecular genetics, bioinformatics, and clinical medicine.
Topics: Biomarkers, Pharmacological; Computational Biology; Drug Interactions; Feasibility Studies; Genome-Wide Association Study; Genotyping Techniques; High-Throughput Nucleotide Sequencing; Humans; Pharmacogenetics; Pharmacogenomic Testing; Pharmacogenomic Variants; Translational Research, Biomedical; Validation Studies as Topic
PubMed: 33089968
DOI: 10.1111/cts.12869 -
Journal of Affective Disorders Aug 2024Pharmacotherapy is one of the primary treatment modalities for depression. However, there is considerable variability in the individual response to antidepressant... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Pharmacotherapy is one of the primary treatment modalities for depression. However, there is considerable variability in the individual response to antidepressant medications. Personalized medicine guided by pharmacogenomic testing may hold promise in addressing this issue.
METHODS
In this study, 665 depressive patients were randomly enrolled into two groups: the pharmacogenomic testing group (n = 333) and the control group (n = 332). In the testing group, participants underwent pharmacogenomic testing, and clinicians customized the treatment plan with the result, while the control group relied solely on clinicians' experience. The primary outcomes were the proportion of remission and response, assessed with Hamilton Depression Rating Scale (HDRS). The secondary outcomes included changes in HDRS scores over time and frequency of adverse drug reactions by the participants.
RESULTS
At week 8, the pharmacogenomic testing group showed significantly higher remission rates (24.0 % v.s. 15.1 %; RR = 1.117; P = 0.007) and response rates (39.3 % v.s. 25.7 %; RR = 1.225; P < 0.001) compared to the control group. By week 12, the pharmacogenomic testing group continued to demonstrate significant advantages in remission (31.0 % v.s. 20.0 %; RR = 1.159; P = 0.003) and response (48.7 % v.s. 37.3 %; RR = 1.224; P = 0.006). Additionally, adverse drug reactions were less frequent in the pharmacogenomic testing group.
LIMITATIONS
This study is not blind to clinicians and it's a single-center study.
CONCLUSIONS
Pharmacogenomic testing-guided drug therapy can provide greater assistance in the treatment of depression.
Topics: Humans; Female; Male; Pharmacogenomic Testing; Adult; Middle Aged; Antidepressive Agents; Depressive Disorder, Major; Treatment Outcome; Psychiatric Status Rating Scales; Precision Medicine; Depressive Disorder; Remission Induction
PubMed: 38762035
DOI: 10.1016/j.jad.2024.05.063 -
Scientific Data Sep 2019The field of pharmacogenomics presents great challenges for researchers that are willing to make their studies reproducible and shareable. This is attributed to the...
The field of pharmacogenomics presents great challenges for researchers that are willing to make their studies reproducible and shareable. This is attributed to the generation of large volumes of high-throughput multimodal data, and the lack of standardized workflows that are robust, scalable, and flexible to perform large-scale analyses. To address this issue, we developed pharmacogenomic workflows in the Common Workflow Language to process two breast cancer datasets in a reproducible and transparent manner. Our pipelines combine both pharmacological and molecular profiles into a portable data object that can be used for future analyses in cancer research. Our data objects and workflows are shared on Harvard Dataverse and Code Ocean where they have been assigned a unique Digital Object Identifier, providing a level of data provenance and a persistent location to access and share our data with the community.
Topics: Computational Biology; Humans; Information Dissemination; Pharmacogenomic Testing; Software; Workflow
PubMed: 31481707
DOI: 10.1038/s41597-019-0174-7