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European Journal of Human Genetics :... Mar 2024The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to...
The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.
Topics: Humans; Antipsychotic Agents; Aripiprazole; Clopenthixol; Clozapine; Cytochrome P-450 CYP1A2; Cytochrome P-450 CYP2D6; Cytochrome P-450 CYP3A; Drug Interactions; Haloperidol; Olanzapine; Pharmacogenetics; Pimozide; Quetiapine Fumarate; Quinolones; Risperidone; Thiophenes
PubMed: 37002327
DOI: 10.1038/s41431-023-01347-3 -
Current Neuropharmacology 2023Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML)...
Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML) techniques and related algorithms play a central role as diagnostic, prognostic, and decision-making tools in this field. Another promising area becoming part of everyday clinical practice is personalized therapy and pharmacogenomics. Applying ML to pharmacogenomics opens new frontiers to tailored therapeutical strategies to help clinicians choose drugs with the best response and fewer side effects, operating with genetic information and combining it with the clinical profile. This systematic review aims to draw up the state-of-the-art ML applied to pharmacogenomics in psychiatry. Our research yielded fourteen papers; most were published in the last three years. The sample comprises 9,180 patients diagnosed with mood disorders, psychoses, or autism spectrum disorders. Prediction of drug response and prediction of side effects are the most frequently considered domains with the supervised ML technique, which first requires training and then testing. The random forest is the most used algorithm; it comprises several decision trees, reduces the training set's overfitting, and makes precise predictions. ML proved effective and reliable, especially when genetic and biodemographic information were integrated into the algorithm. Even though ML and pharmacogenomics are not part of everyday clinical practice yet, they will gain a unique role in the next future in improving personalized treatments in psychiatry.
Topics: Humans; Pharmacogenetics; Precision Medicine; Machine Learning; Mental Disorders; Psychiatry
PubMed: 37559539
DOI: 10.2174/1570159X21666230808170123 -
Journal of Psychiatric Research Nov 2021Ketamine is a dissociative anesthetic used worldwide for anesthesia, pain management, treatment resistant depression (TRD) and suicidality. Predictors of antidepressant... (Review)
Review
Ketamine is a dissociative anesthetic used worldwide for anesthesia, pain management, treatment resistant depression (TRD) and suicidality. Predictors of antidepressant response and adverse effects to ketamine remain poorly understood due to contradictory results. The objective of the systematic review herein is to identify and evaluate the extant literature assessing pharmacogenomic predictors of ketamine clinical benefits and adverse effects. Electronic databases were searched from inception to July 2021 to identify relevant articles. Twelve articles involving 1,219 participants with TRD, 75 who underwent elective surgeries and received ketamine as an anesthetic, 49 with pain, and 68 healthy participants met the inclusion criteria and enrolled to this review. While identified articles reported mixed results, three predictors emerged: 1) Val66Met (rs6265) brain derived neurotrophic factor (BDNF; Met allele) was associated with reduced antidepressant and anti-suicidal effects, 2) CYP2B6*6 (e.g., CYB2B6 metabolizer) was associated with more severe dissociative effects and 3) NET allelic (rs28386840) variant were associated with greater cardiovascular complications (e.g., moderate to severe treatment emergent hypertension). Several important limitations were identified, most notably the small sample sizes and heterogeneity of study design and results. Taken together, preliminary evidence suggests the potential for pharmacogenomic testing to inform clinical practices; however, further research is needed to better determine genetic variants of greatest importance and the clinical validity of pharmacogenomics to help guide ketamine treatment planning.
PubMed: 34844049
DOI: 10.1016/j.jpsychires.2021.11.036 -
British Journal of Clinical Pharmacology Apr 2021Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the... (Review)
Review
AIMS
Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the covariates, performances and risk of bias of these algorithms.
METHODS
We systematically searched MEDLINE up to 20 May 2020 and selected studies describing the development, external validation or clinical utility of a multivariable warfarin dosing algorithm. Two investigators conducted data extraction and quality assessment.
RESULTS
Of 10 035 screened records, 266 articles were included in the review, describing the development of 433 dosing algorithms, 481 external validations and 52 clinical utility assessments. Most developed algorithms were for dose initiation (86%), developed by multiple linear regression (65%) and mostly applicable to Asians (49%) or Whites (43%). The most common demographic/clinical/environmental covariates were age (included in 401 algorithms), concomitant medications (270 algorithms) and weight (229 algorithms) while CYP2C9 (329 algorithms), VKORC1 (319 algorithms) and CYP4F2 (92 algorithms) variants were the most common genetic covariates. Only 26% and 7% algorithms were externally validated and evaluated for clinical utility, respectively, with <2% of algorithm developments and external validations being rated as having a low risk of bias.
CONCLUSION
Most warfarin dosing algorithms have been developed in Asians and Whites and may not be applicable to under-served populations. Few algorithms have been externally validated, assessed for clinical utility, and/or have a low risk of bias which makes them unreliable for clinical use. Algorithm development and assessment should follow current methodological recommendations to improve reliability and applicability, and under-represented populations should be prioritized.
Topics: Algorithms; Anticoagulants; Cytochrome P-450 CYP2C9; Dose-Response Relationship, Drug; Genotype; Humans; Pharmacogenetics; Reproducibility of Results; Vitamin K Epoxide Reductases; Warfarin
PubMed: 33080066
DOI: 10.1111/bcp.14608 -
Journal of Personalized Medicine Jun 2022Pharmacogenetics research on leukotriene modifiers (LTMs) for asthma has been developing rapidly, although pharmacogenetic testing for LTMs is not yet used in clinical...
Pharmacogenetics research on leukotriene modifiers (LTMs) for asthma has been developing rapidly, although pharmacogenetic testing for LTMs is not yet used in clinical practice. We performed a systematic review and meta-analysis on the impact of pharmacogenomics on LTMs response. Studies published until May 2022 were searched using PubMed, EMBASE, and Cochrane databases. Pharmacogenomics/genetics studies of patients with asthma using LTMs with or without other anti-asthmatic drugs were included. Statistical tests of the meta-analysis were performed with Review Manager (Revman, version 5.4, The Cochrane Collaboration, Copenhagen, Denmark) and R language and environment for statistical computing (version 4.1.0 for Windows, R Core Team, Vienna, Austria) software. In total, 31 studies with 8084 participants were included in the systematic review and five studies were also used to perform the meta-analysis. Two included studies were genome-wide association studies (GWAS), which showed different results. Furthermore, none of the SNPs investigated in candidate gene studies were identified in GWAS. In candidate gene studies, the most widely studied SNPs were ALOX5 (tandem repeats of the Sp1-binding domain and rs2115819), LTC4S-444A/C (rs730012), and SLCO2B1 (rs12422149), with relatively inconsistent conclusions. LTC4S-444A/C polymorphism did not show a significant effect in our meta-analysis (AA vs. AC (or AC + CC): −0.06, 95%CI: −0.16 to 0.05, p = 0.31). AA homozygotes had smaller improvements in parameters pertaining to lung functions (−0.14, 95%CI: −0.23 to −0.05, p = 0.002) in a subgroup of patients with non-selective CysLT receptor antagonists and patients without inhaled corticosteroids (ICS) (−0.11, 95%CI: −0.14 to −0.08, p < 0.00001), but not in other subgroups. Variability exists in the pharmacogenomics of LTMs treatment response. Our meta-analysis and systematic review found that LTC4S-444A/C may influence the treatment response of patients taking non-selective CysLT receptor antagonists for asthma, and patients taking LTMs not in combination with ICS for asthma. Future studies are needed to validate the pharmacogenomic influence on LTMs response.
PubMed: 35887565
DOI: 10.3390/jpm12071068 -
Biomedicine & Pharmacotherapy =... Sep 2022Multiple sclerosis is a chronic inflammatory neurological disease, and siponimod (Mayzent) is the first oral treatment option for adult patients with secondary... (Review)
Review
Multiple sclerosis is a chronic inflammatory neurological disease, and siponimod (Mayzent) is the first oral treatment option for adult patients with secondary progressive multiple sclerosis. We performed a systematic review of the pharmacogenetics of Siponimod, and we found that (430 C>T; rs1799853) and CYP2C9 * 3 (1075 A>C; rs1057910), both translated no-function alleles, have been related to a lower metabolism of siponimod by CYP2C9 enzyme. The FDA-approved drug label and EMA risk management plan for siponimod require testing patients for CYP2C9 genotype before treatment starts. The FDA drug label states that siponimod is contraindicated in patients carrying a CYP2C9 * 3/* 3 genotype, and a daily maintenance dose of 1 mg in patients with CYP2C9 * 1/* 3 and * 2/* 3 genotypes. The EMA reported the potential long-term safety implications in CYP2C9 poor metabolizer patients treated with this drug. Based on this systematic review we concluded that CYP2C9 SNPs influence on siponimod response might be stated by assessing not only CYP2C9 * 2 and CYP2C9 * 3 but other genetic variants resulting in CYP2C9 IM/PM status. CYP2C9 IM phenotype translated from the CYP2C9 * 2 genotype should be revised since it is contradictory compared to other CYP2C9 no-function alleles, and CYP2C9 * 2 might be excluded from PGx testing recommendation before treatment starts with siponimod since it is not translated into a therapeutic recommendation.
Topics: Azetidines; Benzyl Compounds; Cytochrome P-450 CYP2C9; Genotype; Pharmacogenetics
PubMed: 36076616
DOI: 10.1016/j.biopha.2022.113536 -
Pharmacogenomics Mar 2022Pharmacogenomics (PGx) is a rising scientific area in many countries, such as Brazil. To identify biomarkers, therapeutic areas, probe drugs and regions/ethnicities... (Review)
Review
Pharmacogenomics (PGx) is a rising scientific area in many countries, such as Brazil. To identify biomarkers, therapeutic areas, probe drugs and regions/ethnicities most studied in the country in order to guide future studies. Systematic review of 1060 studies (from 1968 to 2020) comprising 80 genes, six probe drugs and 3,819,233 individuals. and were the most studied genes and metoprolol and dextromethorphan the most studied probe drugs. Oncology was the most studied therapeutic area considering PGx biomarkers. The country's regions and ethnic groups were studied unevenly, with south/southeast and White people over-represented in respect to their demographic relevance, in detriment of the center-west/northeast/north and Black/mixed individuals. Many of the gaps and possible paths to be covered to reach even PGx data are pointed out by this review.
Topics: Brazil; Ethnicity; HLA-B Antigens; Humans; Medical Oncology; Pharmacogenetics
PubMed: 35187980
DOI: 10.2217/pgs-2021-0128 -
Pharmacology Research & Perspectives Dec 2023Pharmacogenomics remains underutilized in clinical practice, despite the existence of internationally recognized, evidence-based guidelines. This systematic review aims... (Review)
Review
Pharmacogenomics remains underutilized in clinical practice, despite the existence of internationally recognized, evidence-based guidelines. This systematic review aims to understand enablers and barriers to pharmacogenomics implementation in pediatric oncology by assessing the knowledge, attitudes, and practice of healthcare professionals and consumers. Medline, Embase, Emcare, and PsycINFO database searches identified 146 relevant studies of which only three met the inclusion criteria. These studies reveal that consumers were concerned with pharmacogenomic test costs, insurance discrimination, data sharing, and privacy. Healthcare professionals possessed mostly positive attitudes toward pharmacogenomic testing yet identified lack of experience and training as barriers to implementation. Education emerged as the key enabler, reported in all three studies and both healthcare professionals and consumer groups. However, despite the need for education, no studies utilizing a pediatric oncology consumer or healthcare professional group have reported on the implementation or analysis of a pharmacogenomic education program in pediatric oncology. Increased access to guidelines, expert collaborations and additional guidance interpreting results were further enablers established by healthcare professionals. The themes identified mirror those reported in broader pediatric genetic testing literature. As only a small number of studies met inclusion criteria for this review, further research is warranted to elicit implementation determinants and advance pediatric pharmacogenomics.
Topics: Humans; Child; Pharmacogenetics; Health Knowledge, Attitudes, Practice; Health Personnel; Medical Oncology; Neoplasms
PubMed: 38013228
DOI: 10.1002/prp2.1150 -
Clinical Pharmacology and Therapeutics Dec 2022The objective of this study was to evaluate the evidence on cost-effectiveness of pharmacogenetic (PGx)-guided treatment for drugs with Clinical Pharmacogenetics...
The objective of this study was to evaluate the evidence on cost-effectiveness of pharmacogenetic (PGx)-guided treatment for drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A systematic review was conducted using multiple biomedical literature databases from inception to June 2021. Full articles comparing PGx-guided with nonguided treatment were included for data extraction. Quality of Health Economic Studies (QHES) was used to assess robustness of each study (0-100). Data are reported using descriptive statistics. Of 108 studies evaluating 39 drugs, 77 (71%) showed PGx testing was cost-effective (CE) (N = 48) or cost-saving (CS) (N = 29); 21 (20%) were not CE; 10 (9%) were uncertain. Clopidogrel had the most articles (N = 23), of which 22 demonstrated CE or CS, followed by warfarin (N = 16), of which 7 demonstrated CE or CS. Of 26 studies evaluating human leukocyte antigen (HLA) testing for abacavir (N = 8), allopurinol (N = 10), or carbamazepine/phenytoin (N = 8), 15 demonstrated CE or CS. Nine of 11 antidepressant articles demonstrated CE or CS. The median QHES score reflected high-quality studies (91; range 48-100). Most studies evaluating cost-effectiveness favored PGx testing. Limited data exist on cost-effectiveness of preemptive and multigene testing across disease states.
Topics: Humans; Pharmacogenomic Testing; Pharmacogenetics; Cost-Benefit Analysis; Warfarin; Carbamazepine
PubMed: 36149409
DOI: 10.1002/cpt.2754 -
The Pharmacogenomics Journal Feb 2020Associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity have been reported. To consolidate the results from all available reports in scientific... (Meta-Analysis)
Meta-Analysis
Associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity have been reported. To consolidate the results from all available reports in scientific databases, systematic review and meta-analysis techniques were used to quantify these associations. Studies investigating associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity were systematically searched in PubMed, Human Genome Epidemiology Network, and the Cochrane Library. Primary outcomes were the associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity. Overall odds ratios (ORs) with the corresponding 95%CIs were calculated using a random-effect model to determine the associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity. A clear association between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity was identified in our analyses. The summary OR was 6.23 (95%CI = 4.11-9.45). Similar associations were also found in the subgroup analyses by lapatinib treatment regimens. ORs were 10.04 (95%CI = 6.15-16.39), 8.65 (95%CI = 4.52-16.58), and 3.88 (95%CI = 2.20-6.82) in the lapatinib group, lapatinib + trastuzumab group, and lapatinib + chemotherapy or lapatinib + trastuzumab + chemotherapy group, respectively. Since HLA-DRB1*07:01 is associated with lapatinib-induced hepatotoxicity, genetic screening of HLA-DRB1*07:01 in breast cancer patients prior to lapatinib therapy is warranted for patient safety. In addition, further studies should define the risk of HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity in specific ethnicities.
Topics: Antineoplastic Agents; Breast Neoplasms; Case-Control Studies; Chemical and Drug Induced Liver Injury; Female; HLA-DRB1 Chains; Humans; Lapatinib
PubMed: 31383939
DOI: 10.1038/s41397-019-0092-2