Front Immunol. 2022 Feb 16;13:809837. doi: 10.3389/fimmu.2022.809837. eCollection 2022.

ABSTRACT

OBJECTIVE: EVA1B, a protein coding gene, is a critical paralog of EVA1A gene. Herein, our study was conducted to investigate the role of EVA1B in colorectal cancer (CRC) progression and prognosis.

METHODS: Pan-cancer analysis was conducted to analyze expression, genetic and epigenetic alterations, and immunological characteristics of EVA1B. Especially, immunological characteristics and mutational landscape were compared between high and low EVA1B expression groups in the combined TCGA-COAD and TCGA-READ datasets. Through random survival forest analysis, an EVA1B-derived genomic model was developed, and its prognostic value was verified in the external datasets (GSE14333, GSE39582, and GSE87211). Drug sensitivity was compared between high- and low-risk subpopulations. A nomogram was conducted through integrating independent factors.

RESULTS: EVA1B expression presented a remarkable upregulation in most cancer types, especially CRC. EVA1B expression was significantly correlated to DNA methyltransferases, DNA mismatch repair genes, m6A regulators, TMB, and MSI across pan-cancer. High EVA1B expression indicated an undesirable CRC patients' prognosis. Additionally, its upregulation was correlated to enhanced immune cell infiltration, increased stromal and immune activation, and elevated activities of cancer immunity cycle. Higher frequencies of amplification and deletion were investigated in high EVA1B expression subpopulation. Following verification, the EVA1B-derived genomic model reliably predicted patients' prognosis and drug responses. The nomogram (age, stage, EVA1B-derived risk score) was conducted to quantify an individual's survival probability. Furthermore, our experimental validation based on immunohistochemistry indicated that EVA1B overexpression is correlated with CRC tumorigenesis and poor outcomes in our CRC patients' cohort.

CONCLUSION: Collectively, our findings provided valuable resource for guiding the mechanisms and therapeutic analysis of EVA1B in CRC.

PMID:35250982 | PMC:PMC8888821 | DOI:10.3389/fimmu.2022.809837

Front Pharmacol. 2022 Feb 18;13:835136. doi: 10.3389/fphar.2022.835136. eCollection 2022.

ABSTRACT

Many drugs are being administered to tackle coronavirus disease 2019 (COVID-19) pandemic situations without establishing clinical effectiveness or tailoring safety. A repurposing strategy might be more effective and successful if pharmacogenetic interventions are being considered in future clinical studies/trials. Although it is very unlikely that there are almost no pharmacogenetic data for COVID-19 drugs, however, from inferring the pharmacokinetic (PK)/pharmacodynamic(PD) properties and some pharmacogenetic evidence in other diseases/clinical conditions, it is highly likely that pharmacogenetic associations are also feasible in at least some COVID-19 drugs. We strongly mandate to undertake a pharmacogenetic assessment for at least these drug-gene pairs (atazanavir-UGT1A1, ABCB1, SLCO1B1, APOA5; efavirenz-CYP2B6; nevirapine-HLA, CYP2B6, ABCB1; lopinavir-SLCO1B3, ABCC2; ribavirin-SLC28A2; tocilizumab-FCGR3A; ivermectin-ABCB1; oseltamivir-CES1, ABCB1; clopidogrel-CYP2C19, ABCB1, warfarin-CYP2C9, VKORC1; non-steroidal anti-inflammatory drugs (NSAIDs)-CYP2C9) in COVID-19 patients for advancing precision medicine. Molecular docking and computational studies are promising to achieve new therapeutics against SARS-CoV-2 infection. The current situation in the discovery of anti-SARS-CoV-2 agents at four important targets from in silico studies has been described and summarized in this review. Although natural occurring compounds from different herbs against SARS-CoV-2 infection are favorable, however, accurate experimental investigation of these compounds is warranted to provide insightful information. Moreover, clinical considerations of drug-drug interactions (DDIs) and drug-herb interactions (DHIs) of the existing repurposed drugs along with pharmacogenetic (e.g., efavirenz and CYP2B6) and herbogenetic (e.g., andrographolide and CYP2C9) interventions, collectively called multifactorial drug-gene interactions (DGIs), may further accelerate the development of precision COVID-19 therapies in the real-world clinical settings.

PMID:35250581 | PMC:PMC8894812 | DOI:10.3389/fphar.2022.835136

J Asthma Allergy. 2022 Feb 26;15:281-302. doi: 10.2147/JAA.S274524. eCollection 2022.

ABSTRACT

Over the past decade, the role of proton pump inhibitor (PPI) medication has evolved from a diagnostic tool for Eosinophilic Esophagitis (EoE), by excluding patients with PPI responsive esophageal eosinophilia (PPI-REE), to a therapy for EoE. This transition resulted from the Updated International Consensus Diagnostic Criteria for Eosinophilic Esophagitis: Proceedings of the Appraisal of Guidelines for Research and Evaluation II (AGREE) Conference to support PPI therapy for EoE in children and adults. Additional recent advances have suggested a role for genetic variations that might impact response to PPI therapy for EoE. This review article will explore a brief background of EoE, the evolution of PPI therapy for EoE and its proposed mechanisms, efficacy and safety in children and adults, and considerations for future PPI precision medicine in patients with EoE.

PMID:35250281 | PMC:PMC8892718 | DOI:10.2147/JAA.S274524

BMC Med Genomics. 2022 Mar 6;15(1):48. doi: 10.1186/s12920-022-01203-1.

ABSTRACT

BACKGROUND: Besides binding to proteins, the most recent advances in pharmacogenomics indicate drugs can regulate the expression of non-coding RNAs (ncRNAs). The polypharmacological feature in drugs enables us to find new uses for existing drugs (namely drug repositioning). However, current computational methods for drug repositioning mainly consider proteins as drug targets. Meanwhile, these methods identify only statistical relationships between drugs and diseases. They provide little information about how drug-disease associations are formed at the molecular target level.

METHODS: Herein, we first comprehensively collect proteins and two categories of ncRNAs as drug targets from public databases to construct drug-target interactions. Experimentally confirmed drug-disease associations are downloaded from an established database. A canonical correlation analysis (CCA) based method is then applied to the two datasets to extract correlated sets of targets and diseases. The correlated sets are regarded as canonical components, and they are used to investigate drug's mechanism of actions. We finally develop a strategy to predict novel drug-disease associations for drug repositioning by combining all the extracted correlated sets.

RESULTS: We receive 400 canonical components which correlate targets with diseases in our study. We select 4 components for analysis and find some top-ranking diseases in an extracted set might be treated by drugs interfacing with the top-ranking targets in the same set. Experimental results from 10-fold cross-validations show integrating different categories of target information results in better prediction performance than only using proteins or ncRNAs as targets. When compared with 3 state-of-the-art approaches, our method receives the highest AUC value 0.8576. We use our method to predict new indications for 789 drugs and confirm 24 predictions in the top 1 predictions.

CONCLUSIONS: To the best of our knowledge, this is the first computational effort which combines both proteins and ncRNAs as drug targets for drug repositioning. Our study provides a biologically relevant interpretation regarding the forming of drug-disease associations, which is useful for guiding future biomedical tests.

PMID:35249529 | DOI:10.1186/s12920-022-01203-1

Leuk Lymphoma. 2022 Mar 6:1-2. doi: 10.1080/10428194.2022.2045601. Online ahead of print.

NO ABSTRACT

PMID:35249444 | DOI:10.1080/10428194.2022.2045601

Compr Psychiatry. 2022 Feb 26;115:152301. doi: 10.1016/j.comppsych.2022.152301. Online ahead of print.

ABSTRACT

BACKGROUND: Sertraline is a selective serotonin reuptake inhibitor with specific indications in child and adolescent psychiatry. Notwithstanding its frequent use and clinical benefits, the relationship between pharmacokinetics, pharmacodynamics, efficacy, and tolerability of sertraline across indications, particularly in non-adult patients, is not fully understood.

METHOD: This naturalistic therapeutic drug monitoring (TDM) study was conducted in a transdiagnostic sample of children and adolescents treated with sertraline (n = 78; mean age, 14.22 ± 2.39; range, 7-18 years) within the prospective multicenter "TDM-VIGIL" project. Associations between dose, serum concentration, and medication-specific therapeutic and side effects based on the Clinical Global Impression scale were examined. Tolerability was measured qualitatively with the 56-item Pediatric Adverse Event Rating Scale.

RESULTS: A strong linear positive dose-serum concentration relationship (with dose explaining 45% of the variance in concentration) and significant effects of weight and co-medication were found. Neither dose nor serum concentration were associated with side effects. An overall mild-to-moderate tolerability profile of sertraline was observed. In contrast with the transdiagnostic analysis that did not indicate an effect of concentration, when split into depression (MDD) and obsessive-compulsive disorder (OCD) diagnoses, the probability of clinical improvement significantly increased as both dose and concentration increased for OCD, but not for MDD.

CONCLUSIONS: This TDM-flexible-dose study revealed a significant diagnosis-specific effect between sertraline serum concentration and clinical efficacy for pediatric OCD. While TDM already guides clinical decision-making regarding compliance, dose calibration, and drug-drug interactions, combining TDM with other methods, such as pharmacogenetics, may facilitate a personalized medicine approach in psychiatry.

PMID:35248877 | DOI:10.1016/j.comppsych.2022.152301

Psychiatry Res. 2022 Feb 26;311:114482. doi: 10.1016/j.psychres.2022.114482. Online ahead of print.

ABSTRACT

BACKGROUND: Bipolar Disorder (BD) and Major Depressive Disorder (MDD) have a huge impact on functioning and quality of life; moreover, they are linked to extensive direct and indirect costs. This systematic review with meta-analysis aims to evaluate the utility of pharmacogenetic tests (PGT) in terms of efficacy and tolerability into the routine clinical treatment of mood disorders.

MATERIALS AND METHODS: The first part of the review is a qualitative overview of the PGTs used in the included studies. The second part aims to compare, in terms of efficacy and tolerability, patients affected by BD and MDD treated as usual (TAU), according to the clinicians' prescribing attitude, versus patients whose psychopharmacological treatments were set up following the PGT suggestions.

RESULTS: 6 studies on MDD and 2 studies on BD were included. Regarding MDD, the meta-analysis shows a significantly higher number of patients achieving better outcome in terms of efficacy, through the evaluation of response rate and remission rate at the HDRS (Hamilton Depression Rating Scale) in the group of patients treated under the PGT suggestions; regarding BD the meta-analysis does not show any significant difference in terms of efficacy. In terms of adverse events, the available data suggest promising results about the utility of PGT to set more tolerated therapies.

CONCLUSIONS: Although the limited number of studies, results confirm the importance of PGT in setting up psychopharmacological therapies as a support to clinicians' choices.

PMID:35247747 | DOI:10.1016/j.psychres.2022.114482

J Affect Disord. 2022 Mar 2:S0165-0327(22)00223-3. doi: 10.1016/j.jad.2022.02.074. Online ahead of print.

ABSTRACT

BACKGROUND: There are few available antidepressants for pediatric Major Depressive Disorder (MDD). The objective of this systematic review and meta-analysis was to review industry-funded studies of antidepressants in children and adolescents with MDD, and to better understand the contribution of study design and placebo response to the findings of these studies.

METHODS: Randomized, double-blind, placebo-controlled clinical trials that compared antidepressant with placebo for the acute treatment of MDD in children and/or adolescents were selected. Estimates of the standardized mean difference (SMD) in change in Children's Depression Rating Scale-Revised scores were pooled, after examining for heterogeneity. A random-effects meta-analysis was completed.

RESULTS: Thirty-four antidepressant-placebo comparisons, involving 6161 subjects, were included. The SMD among all studies was 0.12 (CI 0.08, 0.17; p < 0.001), a very small effect size, lower than that seen in studies of adults with MDD. When the meta-analysis was limited to studies with a low mean placebo response, the SMD increased to 0.19 and further increased to 0.22 when studies with at least a 50% chance of receiving placebo were included.

LIMITATIONS: Many studies focused on older children and younger adolescents. Our findings may not reflect antidepressant efficacy in older adolescents.

CONCLUSIONS: The modest SMD identified in this analysis may reflect study design factors and the application of antidepressants developed for adults to pediatric patients. Given the urgent clinical need for more pediatric MDD treatments, the influence of placebo response and the need for drug development tailored to this population should be considered in pediatric MDD trial design.

PMID:35247482 | DOI:10.1016/j.jad.2022.02.074

Sci Adv. 2022 Mar 4;8(9):eabm5386. doi: 10.1126/sciadv.abm5386. Epub 2022 Mar 4.

ABSTRACT

More than 50 neurological and neuromuscular diseases are caused by short tandem repeat (STR) expansions, with 37 different genes implicated to date. We describe the use of programmable targeted long-read sequencing with Oxford Nanopore's ReadUntil function for parallel genotyping of all known neuropathogenic STRs in a single assay. Our approach enables accurate, haplotype-resolved assembly and DNA methylation profiling of STR sites, from a list of predetermined candidates. This correctly diagnoses all individuals in a small cohort (n = 37) including patients with various neurogenetic diseases (n = 25). Targeted long-read sequencing solves large and complex STR expansions that confound established molecular tests and short-read sequencing and identifies noncanonical STR motif conformations and internal sequence interruptions. We observe a diversity of STR alleles of known and unknown pathogenicity, suggesting that long-read sequencing will redefine the genetic landscape of repeat disorders. Last, we show how the inclusion of pharmacogenomic genes as secondary ReadUntil targets can further inform patient care.

PMID:35245110 | DOI:10.1126/sciadv.abm5386

Heart Rhythm O2. 2021 Nov 14;3(1):40-49. doi: 10.1016/j.hroo.2021.11.005. eCollection 2022 Feb.

ABSTRACT

BACKGROUND: Heart failure (HF) patients with atrial fibrillation (AF) often have conduction system disorders, which may be worsened by β-blocker therapy.

OBJECTIVE: In a post hoc analysis we examined the prevalence of bradycardia and its association with adverse events (AEs) and failure to achieve target dose in the GENETIC-AF trial.

METHODS: Patients randomized to metoprolol (n = 125) or bucindolol (n = 131) entering 24-week efficacy follow-up and receiving study medication were evaluated. Bradycardia was defined as an electrocardiogram (ECG) heart rate (HR) <60 beats per minute (bpm) and severe bradycardia <50 bpm.

RESULTS: Mean HR in sinus rhythm (SR) was 62.6 ± 12.5 bpm for metoprolol and 68.3 ± 11.1 bpm for bucindolol (P < .0001), but in AF HRs were not different (87.5 bpm vs 89.7 bpm, respectively). Episodes per patient for bucindolol vs metoprolol were 0.82 vs 2.08 (P < .001) for bradycardia and 0.24 vs 0.57 for severe bradycardia (P < .001), with 98.9% of the episodes occurring in SR. Patients experiencing bradycardia had a 4.15-fold higher prevalence of study medication dose reduction (P <.0001) compared to patients without bradycardia. Fewer patients receiving metoprolol were at target dose (61.7% vs 74.9% for bucindolol, P < .0001) at ECG recordings, and bradycardia AEs were more prevalent in the metoprolol group (13 vs 1 for bucindolol, P = .001). On multivariate analysis of 21 candidate bradycardia predictors including presence of a device with pacing capability, bucindolol treatment was associated with the greatest degree of prevention (Zodds ratio -4.24, P < .0001).

CONCLUSION: In AF-prone HF patients bradycardia may limit the effectiveness of β blockers, and this property is agent-dependent.

PMID:35243434 | PMC:PMC8859785 | DOI:10.1016/j.hroo.2021.11.005

Transl Lung Cancer Res. 2022 Jan;11(1):117-121. doi: 10.21037/tlcr-22-27.

NO ABSTRACT

PMID:35242633 | PMC:PMC8825659 | DOI:10.21037/tlcr-22-27

BMJ Open. 2022 Mar 3;12(3):e055821. doi: 10.1136/bmjopen-2021-055821.

ABSTRACT

INTRODUCTION: The combination of a CDK4/6 inhibitor with an aromatase inhibitor (AI) has recently become the gold standard for AI-sensitive first line treatment of oestrogen receptor-positive (ER+) HER2-negative (HER2-) advanced breast cancer. However, most patients receiving this combination will ultimately progress and require further therapies.Several studies have demonstrated that the onset of a ESR1 gene mutation lead to AIs resistance in the advanced setting. ESR1 mutations can be detected in circulating tumour DNA (ctDNA) using a digital PCR assay. Our study aims to prove the clinical efficacy of periodic monitoring for emerging or rise of ESR1 mutations in ctDNA to trigger an early change from AI plus palbociclib to fulvestrant plus palbociclib treatment while assessing global safety.

METHODS: PADA-1 is a randomised, open-label, multicentric, phase III trial conducted in patients receiving AI and palbociclib as first line therapy for metastatic ER +HER2- breast cancer. 1000 patients will be included and treated with palbociclib in combination with an AI. Patients will be screened for circulating blood ESR1 mutation detection at regular intervals. Patients for whom a rising circulating ESR1 mutation is detected without tumour progression (up to N=200) will be randomised (1:1) between (1) Arm A: no modification of therapy; and (2) Arm B: palbociclib in combination with fulvestrant, a selective ER down-regulator. At tumour progression, an optional crossover will be offered to patients randomised in arm A. The coprimary endpoints are (1) Grade ≥3 haematological toxicities and their associations with baseline characteristics and (2) progression-free survival in randomised patients.

ETHICS AND DISSEMINATION: The study has been approved by the French medicines agency (ANSM) and by an ethics committee (ref 01/17_1 CPP Ouest-IV Nantes) in January 2017. The trial results will be published in academic conference presentations and international peer-reviewed journals.

TRIAL REGISTRATION NUMBERS: EudraCT: 2016-004360-18; NCT03079011.

PMID:35241469 | DOI:10.1136/bmjopen-2021-055821

Pharmacogenomics. 2022 Mar 3. doi: 10.2217/pgs-2022-0018. Online ahead of print.

ABSTRACT

The gut microbiota has a fundamental role in regulating the homeostasis of brain function and behavior. Indeed, alterations in the gut microbiota have been linked to pathological processes affecting the brain, such as those occurring in severe psychiatric disorders. Although these data can potentially reveal a wealth of information related to the underlying biological mechanisms linking psychiatric diseases to the gut microbiome, the implication for clinical guidelines and care is still unclear. This is an unsettling reality even for phenotypic manifestations of severe mental disorders associated with increased illness burden, such as treatment-resistant forms. In this editorial, we list some of the obstacles affecting gut microbiota research in psychiatry, especially with regard to treatment-resistant forms, and suggest some strategies to overcome them.

PMID:35238627 | DOI:10.2217/pgs-2022-0018

Nephrology (Carlton). 2022 Mar 3. doi: 10.1111/nep.14035. Online ahead of print.

ABSTRACT

With advances in immunosuppressive therapy, there have been significant improvements in acute rejection rates and short-term allograft survival in kidney transplant recipients. However, this success has not been translated into long-term benefits by the same magnitude. Optimization of immunosuppression is important to improve the clinical outcome of transplant recipients. It is important to note that each patient has unique attributes and immunosuppression management should not be a one-size-fits-all approach. Elderly transplant patients are less likely to develop acute rejection but more likely to die from infectious and cardiovascular causes than younger patients. For those with post-transplant cancers and BK polyomavirus-associated nephropathy, reduction of immunosuppression can increase the risk of rejection. Therapeutic drug monitoring (TDM) is routinely used for dosage adjustment of several immunosuppressive drugs. It has been hoped that pharmacogenetics can be used to complement TDM in optimizing drug exposure. Among the various drug-genotype pairs being investigated, tacrolimus and CYP3A5 gives the most promising results. Different studies have consistently shown that CYP3A5 expressers require a higher tacrolimus dose and take longer time to achieve target blood tacrolimus levels than nonexpressers. However, for pharmacogenetics to be widely used clinically, further trials are necessary to demonstrate the clinical benefits of genotype-guided dosing such as reduction of rejection and drug-related toxicities. The development of different biomarkers in recent years may help to achieve true personalized therapy in transplant patients.

PMID:35238110 | DOI:10.1111/nep.14035

Sci Rep. 2022 Mar 1;12(1):3410. doi: 10.1038/s41598-022-07476-x.

ABSTRACT

Fetal behavioural states (fBS) describe periods of fetal wakefulness and sleep and are commonly defined by features such as body and eye movements and heart rate. Automatic state detection through algorithms relies on different parameters and thresholds derived from both the heart rate variability (HRV) and the actogram, which are highly dependent on the specific datasets and are prone to artefacts. Furthermore, the development of the fetal states is dynamic over the gestational period and the evaluation usually only separated into early and late gestation (before and after 32 weeks). In the current work, fBS detection was consistent between the classification algorithm and visual inspection in 87 fetal magnetocardiographic data segments between 27 and 39 weeks of gestational age. To identify how automated fBS detection could be improved, we first identified commonly used parameters for fBS classification in both the HRV and the actogram, and investigated their distribution across the different fBS. Then, we calculated a receiver operating characteristics (ROC) curve to determine the performance of each parameter in the fBS classification. Finally, we investigated the development of parameters over gestation through linear regression. As a result, the parameters derived from the HRV have a higher classification accuracy compared to those derived from the body movement as defined by the actogram. However, the overlapping distributions of several parameters across states limit a clear separation of states based on these parameters. The changes over gestation of the HRV parameters reflect the maturation of the fetal autonomic nervous system. Given the higher classification accuracy of the HRV in comparison to the actogram, we suggest to focus further research on the HRV. Furthermore, we propose to develop probabilistic fBS classification approaches to improve classification in less prototypical datasets.

PMID:35233073 | DOI:10.1038/s41598-022-07476-x

Am J Health Syst Pharm. 2022 Mar 1:zxac064. doi: 10.1093/ajhp/zxac064. Online ahead of print.

ABSTRACT

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PURPOSE: Healthcare professionals need a clear understanding of information about gene-drug interactions in order to make optimal use of pharmacogenetic (PGx) testing. In this report, we compare PGx information in the US Food and Drug Administration (FDA) Table of Pharmacogenetic Associations with information presented in Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines.

SUMMARY: Information from CPIC guidelines and the FDA Table of Pharmacogenetic Associations do not have a high level of concordance. Many drugs mentioned in CPIC guidelines are not listed in the FDA table and vice versa, and the same gene-drug association and dosing recommendation was reported for only 5 of the 126 drugs included in either source. Furthermore, classification of drugs in specific sections of the FDA table does not correlate well with CPIC-assigned or provisionally assigned clinical actionability levels. The Pharmacogenomics Knowledge Base (PharmGKB) clinical annotation levels are generally high for drugs mentioned in CPIC guidelines. PharmGKB clinical annotation levels are often unassigned or are lower level for drugs listed on the FDA table but not in CPIC guidelines. These differences may be due in part to FDA having access to PGx information that is unavailable in published literature and/or because PGx classifications are based on criteria other than clinical actionability.

CONCLUSION: There are important differences between the PGx information presented in the FDA Table of Pharmacogenetic Associations and in CPIC guidelines. FDA and CPIC have different perspectives when evaluating PGx associations and use different approaches and information resources when considering clinical validity related to specific medicines. Understanding how information sources developed by each group differ and can be used together to form a holistic view of PGx may be helpful in increasing adoption of these information sources in practice.

PMID:35230418 | DOI:10.1093/ajhp/zxac064

Pharmacogenomics. 2022 Mar 1. doi: 10.2217/pgs-2021-0146. Online ahead of print.

ABSTRACT

Background: Plasmodium vivax malaria is endemic in Madagascar, where populations have genetic inheritance from Southeast Asia and East Africa. Primaquine, a drug of choice for vivax malaria, is metabolized principally via CYP2D6. CYP2D6 variation was characterized by locus-specific gene sequencing and was compared with TaqMan™ genotype data. Materials & methods: Long-range PCR amplicons were generated from 96 Malagasy samples and subjected to next-generation sequencing. Results: The authors observed high concordance between TaqMan™-based CYP2D6 genotype calls and the base calls from sequencing. In addition, there are new variants and haplotypes present in the Malagasy. Conclusion: Sequencing unique admixed populations provides more detailed and accurate insights regarding CYP2D6 variability, which may help optimize primaquine treatment across human genetic diversity.

PMID:35230160 | DOI:10.2217/pgs-2021-0146

JBMR Plus. 2021 Oct 6;6(2):e10557. doi: 10.1002/jbm4.10557. eCollection 2022 Feb.

ABSTRACT

Voriconazole-associated periostitis (VAP) is an underrecognized and unpredictable side effect of long-term voriconazole therapy. We report two cases of VAP occurring in the post-transplant setting: a 68-year-old lung transplant recipient who required ongoing voriconazole therapy, in whom urinary alkalinization was used to promote fluoride excretion and minimize voriconazole-related skeletal toxicity, and a 68-year-old stem-cell transplant recipient with a high voriconazole dose requirement, identified on pharmacogenomic testing to be a CYP2C19 ultrarapid metabolizer, the dominant enzyme in voriconazole metabolism. This is the first reported case of pharmacogenomic profiling in VAP and may explain the variability in individual susceptibility to this uncommon adverse effect. Our findings provide new insights into both the management and underlying pathophysiology of VAP. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

PMID:35229058 | PMC:PMC8861987 | DOI:10.1002/jbm4.10557

Value Health. 2022 Mar;25(3):461-472. doi: 10.1016/j.jval.2021.09.013. Epub 2021 Dec 2.

ABSTRACT

OBJECTIVES: This study aimed to examine the extent and quality of evidence from economic evaluations (EEs) of genetic-guided pharmacotherapy (PGx) for atrial fibrillation (AF) and to identify variables influential in changing base-case conclusions.

METHODS: From systematic searches, we included EEs of existing PGx testing to guide pharmacotherapy for AF, without restrictions on population characteristics or language. Articles excluded were genetic tests used to guide device-based therapy or focused on animals.

RESULTS: We found 18 EEs (46 comparisons), all model-based cost-utility analysis with or without cost-effectiveness analysis mostly from health system's perspectives, of PGx testing to determine coumadin/direct-acting anticoagulant (DOAC) dosing (14 of 18), to stratify patients into coumadin/DOACs (3 of 18), or to increase patients' adherence to coumadin (1 of 18) versus non-PGx. Most PGx to determine coumadin dosing found PGx more costly and more effective than standard or clinical coumadin dosing (19 of 24 comparisons) but less costly and less effective than standard DOAC dosing (14 of 14 comparisons). The remaining comparisons were too few to observe any trend. Of 61 variables influential in changing base-case conclusions, effectiveness of PGx testing was the most common (37%), accounted for in the models using time-based or medication-based approaches or relative risk. The cost of PGx testing has decreased and plateaued over time.

CONCLUSIONS: EEs to date only partially inform decisions on selecting optimal PGx testing for AF, because most evidence focuses on PGx testing to determine coumadin dosing, but less on other purposes. Future EE may refer to the list of influential variables and the approaches used to account for the effect of PGx testing to inform data collection and study design.

PMID:35227459 | DOI:10.1016/j.jval.2021.09.013

Nutr Hosp. 2022 Mar 1. doi: 10.20960/nh.03918. Online ahead of print.

ABSTRACT

OBJECTIVE: bioinformatic methods and molecular docking technology were used to predict the active components, targets, and related biological pathways of the Xiexin capsule in the intervention for dyslipidemia, exploring its mechanism.

METHODS: the active components and targets of the Xiexin capsule were screened by the TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform )database. Genecards (The Human Gene Database), OMIM (Online Mendelian Inheritance in Man), PharmGkb (Pharmacogenomics Knowledge Base database), TTD (Therapeutic Target Database), and Drugbank platforms were used to search the disease targets of dyslipidemia. The Cytoscape 3.8.0 software was used to construct the 'component-target' network diagram, and the STRING (functional protein association networks) platform was used to analyze protein-protein interaction (PPI). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG) enrichment analyses were performed by R language data packets to predict the mechanism of action. The AutoDockVina and PyMol software were used to dock the key active components in the Xiexin capsule and the core proteins in PPI.

RESULTS: a total of 66 effective components were screened, involving 114 targets; 87 key active compounds were screened from the 'drug-component-target' diagram. The PPI network mainly involved core proteins such as PTGS2 (prostaglandin-endoperoxide synthase 2), PTGS1 (prostaglandin-endoperoxide synthase 1), and HSP90AA1 (heat shock protein 90 alpha family class A member 1). GO and KEGG enrichment analysis results of common targets mainly involved hormone-mediated signaling pathway, steroid hormone response, lipid transport and metabolism, regulation of cholesterol storage, cyclooxygenase pathway, and other biological pathways, as well asMM PPAR (peroxisome proliferators-activated receptor) signaling pathway, IL-17 (interleukin 17) signaling pathway, PI3K-Akt (protein kinase b) signaling pathway, FcεRI signaling pathway, and other related pathways. Molecular docking verification showed that quercetin had the best binding with the core target protein HSP90AA1, and HSP90AA1 was the target protein with the best binding activity for the key chemical components in Xiexin capsules.

CONCLUSION: the main chemical components in the Xiexin capsules may participate in the regulation of PPAR and other signaling pathways by regulating key genes such as ESR1 (estrogen receptor 1), MAPK14 (mitogen-activated protein kinase 14), and HSP90AA1, to exert the pharmacological effect of the intervention on dyslipidemia.

PMID:35227068 | DOI:10.20960/nh.03918