-
CNS Neuroscience & Therapeutics Oct 2011Schizophrenia (SCZ) is among the most disabling of mental disorders. Several neurobiological hypotheses have been postulated as responsible for SCZ pathogenesis:... (Review)
Review
Schizophrenia (SCZ) is among the most disabling of mental disorders. Several neurobiological hypotheses have been postulated as responsible for SCZ pathogenesis: polygenic/multifactorial genomic defects, intrauterine and perinatal environment-genome interactions, neurodevelopmental defects, dopaminergic, cholinergic, serotonergic, gamma-aminobutiric acid (GABAergic), neuropeptidergic and glutamatergic/N-Methyl-D-Aspartate (NMDA) dysfunctions, seasonal infection, neuroimmune dysfunction, and epigenetic dysregulation. SCZ has a heritability estimated at 60-90%. Genetic studies in SCZ have revealed the presence of chromosome anomalies, copy number variants, multiple single-nucleotide polymorphisms of susceptibility distributed across the human genome, aberrant single nucleotide polymorphisms (SNPs) in microRNA genes, mitochondrial DNA mutations, and epigenetic phenomena. Pharmacogenetic studies of psychotropic drug response have focused on determining the relationship between variation in specific candidate genes and the positive and adverse effects of drug treatment. Approximately, 18% of neuroleptics are major substrates of CYP1A2 enzymes, 40% of CYP2D6, and 23% of CYP3A4; 24% of antidepressants are major substrates of CYP1A2 enzymes, 5% of CYP2B6, 38% of CYP2C19, 85% of CYP2D6, and 38% of CYP3A4; 7% of benzodiazepines are major substrates of CYP2C19 enzymes, 20% of CYP2D6, and 95% of CYP3A4. About 10-20% of Western populations are defective in genes of the CYP superfamily. Only 26% of Southern Europeans are pure extensive metabolizers for the trigenic cluster integrated by the CYP2D6+CYP2C19+CYP2C9 genes. The pharmacogenomic response of SCZ patients to conventional psychotropic drugs also depends on genetic variants associated with SCZ-related genes. Consequently, the incorporation of pharmacogenomic procedures both to drugs in development and drugs on the market would help to optimize therapeutics in SCZ and other central nervous system (CNS) disorders.
Topics: Animals; Aryl Hydrocarbon Hydroxylases; Cytochrome P-450 CYP2C19; Genomics; Humans; Pharmacogenetics; Polymorphism, Single Nucleotide; Schizophrenia
PubMed: 20718829
DOI: 10.1111/j.1755-5949.2010.00187.x -
Genetics in Medicine : Official Journal... Dec 2011Clinical genetic testing has grown substantially over the past 30 years as the causative mutations for Mendelian diseases have been identified, particularly aided in... (Review)
Review
Clinical genetic testing has grown substantially over the past 30 years as the causative mutations for Mendelian diseases have been identified, particularly aided in part by the recent advances in molecular-based technologies. Importantly, the adoption of new tests and testing strategies (e.g., diagnostic confirmation, prenatal testing, and population-based carrier screening) has often been met with caution and careful consideration before clinical implementation, which facilitates the appropriate use of new genetic tests. Although the field of pharmacogenetics was established in the 1950s, clinical testing for constitutional pharmacogenetic variants implicated in interindividual drug response variability has only recently become available to help clinicians guide pharmacotherapy, in part due to US Food and Drug Administration-mediated product insert revisions that include pharmacogenetic information for selected drugs. However, despite pharmacogenetic associations with adverse outcomes, physician uptake of clinical pharmacogenetic testing has been slow. Compared with testing for Mendelian diseases, pharmacogenetic testing for certain indications can have a lower positive predictive value, which is one reason for underutilization. A number of other barriers remain with implementing clinical pharmacogenetics, including clinical utility, professional education, and regulatory and reimbursement issues, among others. This review presents some of the current opportunities and challenges with implementing clinical pharmacogenetic testing.
Topics: Alleles; Cytochrome P-450 CYP2D6; Ethnicity; Evidence-Based Medicine; Gene Frequency; Genetic Testing; Genetic Variation; Humans; Pharmacogenetics; Precision Medicine; Predictive Value of Tests; Prescription Drugs; United States; United States Food and Drug Administration
PubMed: 22095251
DOI: 10.1097/GIM.0b013e318238b38c -
Pharmacogenetics and Genomics Feb 2022Evaluations from pharmacogenetics implementation programs at major US medical centers have reported variability in the clinical adoption of pharmacogenetics across...
OBJECTIVES
Evaluations from pharmacogenetics implementation programs at major US medical centers have reported variability in the clinical adoption of pharmacogenetics across therapeutic areas. A potential cause for this variability may involve therapeutic area-specific differences in published pharmacogenetics recommendations to clinicians. To date, however, the potential for differences in clinical pharmacogenetics recommendations by therapeutic areas from prominent US guidance sources has not been assessed. Accordingly, our objective was to comprehensively compare essential elements from clinical pharmacogenetics recommendations contained within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and clinical practice guidelines from US professional medical organizations across therapeutic areas.
METHODS
We analyzed clinical pharmacogenetics recommendation elements within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and professional clinical practice guidelines through 05/24/19.
RESULTS
We identified 606 unique clinical pharmacogenetics recommendations, with the most recommendations involving oncology (217 recommendations), hematology (79), psychiatry (65), cardiovascular (43) and anesthetic (37) medications. Within our analyses, we observed considerable variability across therapeutic areas within the following essential pharmacogenetics recommendation elements: the recommended clinical management strategy; the relevant genetic biomarkers; the organizations providing pharmacogenetics recommendations; whether routine genetic screening was recommended; and the time since recommendations were published.
CONCLUSIONS
On the basis of our results, we infer that observed differences in clinical pharmacogenetics recommendations across therapeutic areas may result from specific factors associated with individual disease states, the associated genetic biomarkers, and the characteristics of the organizations providing recommendations.
Topics: Genetic Markers; Genetic Testing; Humans; Pharmacogenetics; Pharmacogenomic Testing
PubMed: 34412102
DOI: 10.1097/FPC.0000000000000452 -
Pharmaceutical Research Aug 2017While recent discoveries have paved the way for the use of genotype-guided prescribing in some clinical environments, significant debate persists among clinicians and... (Review)
Review
While recent discoveries have paved the way for the use of genotype-guided prescribing in some clinical environments, significant debate persists among clinicians and researchers about the optimal approach to pharmacogenetic testing in clinical practice. One crucial factor in this debate surrounds the timing and methodology of genotyping, specifically whether genotyping should be performed reactively for targeted genes when a single drug is prescribed, or preemptively using a panel-based approach prior to drug prescribing. While early clinical models that employed a preemptive approach were largely developed in academic health centers through multidisciplinary efforts, increasing examples of pharmacogenetic testing are emerging in community-based and primary care practice environments. However, educational and practice-based resources for these clinicians remain largely nonexistent. As such, there is a need for the health care system to shift its focus from debating about preemptive genotyping to developing and disseminating needed resources to equip frontline clinicians for clinical implementation of pharmacogenetics. Providing tools and guidance to support these emerging models of care will be essential to support the thoughtful, evidence-based use of pharmacogenetic information in diverse clinical practice environments. Specifically, the creation of efficient and accurate point-of-care resources, practice-based tools, and clinical models is needed, along with identification and dissemination of sustainable avenues for pharmacogenetic test reimbursement.
Topics: Dose-Response Relationship, Drug; Genotype; Humans; Pharmacogenetics; Pharmacogenomic Testing; Precision Medicine
PubMed: 28466392
DOI: 10.1007/s11095-017-2163-x -
American Journal of Health-system... Dec 2016Both regulatory science and clinical practice rely on best available scientific data to guide decision-making. However, changes in clinical practice may be driven by... (Review)
Review
PURPOSE
Both regulatory science and clinical practice rely on best available scientific data to guide decision-making. However, changes in clinical practice may be driven by numerous other factors such as cost. In this review, we reexamine noteworthy examples where pharmacogenetic testing information was added to drug labeling to explore how the available evidence, potential public health impact, and predictive utility of each pharmacogenetic biomarker impacts clinical uptake.
SUMMARY
Advances in the field of pharmacogenetics have led to new discoveries about the genetic basis for variability in drug response. The Food and Drug Administration recognizes the value of pharmacogenetic testing strategies and has been proactive about incorporating pharmacogenetic information into the labeling of both new drugs and drugs already on the market. Although some examples have readily translated to routine clinical practice, clinical uptake of genetic testing for many drugs has been limited.
CONCLUSION
Both regulatory science and clinical practice rely on data-driven approaches to guide decision making; however, additional factors are also important in clinical practice that do not impact regulatory decision making, and these considerations may result in heterogeneity in clinical uptake of pharmacogenetic testing.
Topics: Clinical Decision-Making; Genetic Testing; Humans; Pharmacogenetics; Pharmacogenomic Testing; United States; United States Food and Drug Administration
PubMed: 27864207
DOI: 10.2146/ajhp160476 -
The Journal of Molecular Diagnostics :... Mar 2022Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing...
Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing that could help inform medication selection or dosing throughout the lifespan. Implementation of pharmacogenomic reporting must address several challenges, including inherent limitations in short-read genome sequencing methods, gene and variant selection, standardization of genotype and phenotype nomenclature, and choice of guidelines and drugs to report. An automated pipeline, lmPGX, was developed as an end-to-end solution that produces two versions of a pharmacogenomic report, presenting either Clinical Pharmacogenetics Implementation Consortium or US Food and Drug Administration guidelines for 12 genes. The pipeline was validated for performance using reference samples and pharmacogenetic data from the Genetic Testing Reference Materials Coordination Program. To determine performance and limitations, lmPGX was compared with three additional publicly available pharmacogenomic pipelines. The lmPGX pipeline offers clinical laboratories an opportunity for seamless integration of pharmacogenomic results with genome reporting.
Topics: Genetic Testing; Genotype; Humans; Pharmacogenetics; Pharmacogenomic Testing; Phenotype
PubMed: 35041930
DOI: 10.1016/j.jmoldx.2021.12.001 -
Pharmacogenomics May 2018This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants... (Review)
Review
This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepigenomics; patient stratification from medical records; and the mechanistic prediction of drug response, targets and their interactions. Deep learning encapsulates a family of machine learning algorithms that has transformed many important subfields of artificial intelligence over the last decade, and has demonstrated breakthrough performance improvements on a wide range of tasks in biomedicine. We anticipate that in the future, deep learning will be widely used to predict personalized drug response and optimize medication selection and dosing, using knowledge extracted from large and complex molecular, epidemiological, clinical and demographic datasets.
Topics: Algorithms; Databases as Topic; Deep Learning; Humans; Models, Educational; Neural Networks, Computer; Pharmacogenetics
PubMed: 29697304
DOI: 10.2217/pgs-2018-0008 -
Clinical Pharmacology and Therapeutics Apr 2018Both the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group provide therapeutic recommendations for well-known gene-drug... (Review)
Review
Both the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group provide therapeutic recommendations for well-known gene-drug pairs. Published recommendations show a high rate of concordance. However, as a result of different guideline development methods used by these two consortia, differences between the published guidelines exist. The aim of this paper is to compare both initiatives and explore these differences, with the objective to achieve harmonization.
Topics: Genetic Testing; Humans; Netherlands; Pharmacogenetics; Practice Guidelines as Topic; Practice Patterns, Physicians'; Precision Medicine; Translational Research, Biomedical; United States
PubMed: 28994452
DOI: 10.1002/cpt.762 -
Molecular Psychiatry Jun 2015After decades of research, the mechanism of action of lithium in preventing recurrences of bipolar disorder remains only partially understood. Lithium research is... (Review)
Review
After decades of research, the mechanism of action of lithium in preventing recurrences of bipolar disorder remains only partially understood. Lithium research is complicated by the absence of suitable animal models of bipolar disorder and by having to rely on in vitro studies of peripheral tissues. A number of distinct hypotheses emerged over the years, but none has been conclusively supported or rejected. The common theme emerging from pharmacological and genetic studies is that lithium affects multiple steps in cellular signaling, usually enhancing basal and inhibiting stimulated activities. Some of the key nodes of these regulatory networks include GSK3 (glycogen synthase kinase 3), CREB (cAMP response element-binding protein) and Na(+)-K(+) ATPase. Genetic and pharmacogenetic studies are starting to generate promising findings, but remain limited by small sample sizes. As full responders to lithium seem to represent a unique clinical population, there is inherent value and need for studies of lithium responders. Such studies will be an opportunity to uncover specific effects of lithium in those individuals who clearly benefit from the treatment.
Topics: Antimanic Agents; Bipolar Disorder; Humans; Lithium Compounds; Pharmacogenetics
PubMed: 25687772
DOI: 10.1038/mp.2015.4 -
The British Journal of General Practice... Jun 2015
Topics: Cost-Benefit Analysis; Genetic Testing; Genome, Human; Humans; Pharmacogenetics; Precision Medicine; United Kingdom
PubMed: 26009508
DOI: 10.3399/bjgp15X685153