15 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

pharmacogenomics

These pubmed results were generated on 2018/10/23

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

CYP1A1 and 1B1-mediated metabolic pathways of dolutegravir, an HIV-1 integrase inhibitor.

Biochem Pharmacol. 2018 Oct 17;:

Authors: Zhu J, Wang P, Li F, Lu J, Shehu AI, Xie W, McMahon D, Ma X

Abstract
Dolutegravir (DTG), a potent integrase inhibitor, is part of a recommended initial regimen for the treatment of human immunodeficiency virus (HIV). Prior reports demonstrated that the clearance of DTG was higher in current smokers than non- smokers, but the mechanism remains unclear. Using a metabolomic approach, M4 (an aldehyde) was identified as a novel metabolite of DTG. In addition, the formation of M4 was found to be mediated by cytochrome P450 (CYP) 1A1 and 1B1, the enzymes that can be highly induced by cigarette smoking. CYP1A1 and 1B1 were also identified as the major enzymes contributing to the formation of M1 (an N-dealkylated metabolite of DTG) and M5 (an aldehyde). Furthermore, the production of M1 and M4 was significantly increased in the lung of mice treated with 2,3,7,8-tetrachlorodibenzo-p-dioxin, an inducer of CYP1A1 and 1B1. In summary, the current study uncovered the CYP1A1 and 1B1-mediated metabolic pathways of DTG. These data suggest that persons with HIV infection receiving DTG should be cautious to cigarettes, and drugs, or exposure to environmental chemicals that induce CYP1A1 and 1B1.

PMID: 30342022 [PubMed - as supplied by publisher]

Pharmacogenomics and Biomarkers of Depression.

Handb Exp Pharmacol. 2018 Oct 20;:

Authors: Jha MK, Trivedi MH

Abstract
The standard of care for antidepressant treatment in major depressive disorder (MDD) is a trial-and-error approach. Patients often have to undergo multiple medication trials for weeks to months before finding an effective treatment. Clinical factors such as severity of baseline symptoms and the presence of specific individual (anhedonia or insomnia) or cluster (atypical, melancholic, or anxious) of symptoms are commonly used without any evidence of their utility in selecting among currently available antidepressants. Genomic and proteomic biomarker have gained recent attention for their potential in informing antidepressant medication selection. In this report, we have reviewed some of the major pharmacogenomics studies along with individual genetic and proteomic biomarker of antidepressant response. Additionally, we have reviewed the blood-based protein biomarkers that can inform selection of one antidepressant over another. Among all currently available biomarkers, C-reactive protein (CRP) appears to be the most promising and pragmatic choice. Low CRP (<1 mg/L) in patients with MDD predicts better response to escitalopram while higher levels are associated with better response to noradrenergic/dopaminergic antidepressants. Future studies are needed to demonstrate the superiority of a CRP-based treatment assignment over high-quality measurement-based care in real-world clinical practices.

PMID: 30341727 [PubMed - as supplied by publisher]

Big Data and Targeted Machine Learning in action to assist medical decision in the ICU.

Anaesth Crit Care Pain Med. 2018 Oct 16;:

Authors: Romain P, Cohen MJ, Ivana M, Jonathan C, Antoine C, Cannesson M, Lee C, Matthieu RR, Alan H, ACTERREA Research Group

Abstract
Historically, personalised medicine has been synonymous with pharmacogenomics and oncology. We argue for a new framework for personalised medicine analytics that capitalises on more detailed patient-level data and leverages recent advances in causal inference and machine learning tailored towards decision support applicable to critically ill patients. We discuss how advances in data technology and statistics are providing new opportunities for asking more targeted questions regarding patient treatment, and how this can be applied in the intensive care unit to better predict patient-centred outcomes, help in the discovery of new treatment regimens associated with improved outcomes, and ultimately how these rules can be learned in real-time for the patient.

PMID: 30339893 [PubMed - as supplied by publisher]

Wide Variation in the Use and Understanding of Therapeutic Drug Monitoring for Anti-TNF Agents in Inflammatory Bowel Disease: An Inexact Science?

Expert Opin Biol Ther. 2018 Oct 19;:

Authors: Samaan MA, Arkir Z, Ahmad T, Irving PM

Abstract
Background We aimed to understand the way in which therapeutic drug monitoring (TDM) is used, understood and interpreted for anti-TNF agents in IBD. Research Design and Methods We designed an 18-question survey that included 5 TDM-based clinical scenarios, for which the 'most appropriate' responses were based on the BRIDGe groups 'Anti-TNF Optimizer'. This resource combines TDM evidence with expert consensus. Results We received 110 complete responses: 50 (45%) consultants, 30 (27%) trainees, 25 (23%) IBD nurse specialists and 5 (5%) gastroenterology pharmacists. Over half (61, 55%) only carry out TDM in non-response. The remainder use TDM routinely, including during stable maintenance therapy for patients in remission. Lower therapeutic thresholds used were variable. Most (82, 75%) were unsure whether their laboratory uses a drug-tolerant or drug-sensitive antidrug antibody assay and few (15, 14%) understand the difference. Consultants, high-frequency users (>3requests/month) and clinicians with larger anti-TNF cohorts (>100) were significantly more likely to select the 'most appropriate' answer to at least 1 of the 5 TDM-based clinical scenarios. Conclusions There exists marked heterogeneity in the practical use, understanding and interpretation of biologic TDM. Biologic decision-making, informed by TDM, should involve consultation with experienced clinicians who are frequent TDM users, ideally, as part of a multidisciplinary, biologics-focused IBD meeting.

PMID: 30339466 [PubMed - as supplied by publisher]

The genotype for DPYD risk variants in colorectal cancer patients and the related toxicity management costs in clinical practice.

Clin Pharmacol Ther. 2018 Oct 19;:

Authors: Toffoli G, Innocenti F, Polesel J, De Mattia E, Sartor F, Fratte CD, Ecca F, Dreussi E, Palazzari E, Guardascione M, Buonadonna A, Foltran L, Garziera M, Bignucolo A, Nobili S, Mini E, Favaretto A, Berretta M, D'Andrea M, De Paoli A, Roncato R, Cecchin E

Abstract
Lack of information on the clinical utility of preemptive DPYD screening prior to fluoropyrimidine treatment is a major barrier preventing its utilization in clinical practice. This study aimed to define the association between DPYD variants and fluoropyrimidine-related toxicity management costs. A cost analysis was conducted on the toxicities experienced by 550 colorectal cancer patients treated with fluoropyrimidine-based chemotherapy. Genotyping for DPYD*2A, DPYD*13, DPYDc.2846A>T, DPYD-HapB3, and UGT1A1*28 was done retrospectively, and did not affect patients' treatments. Carriers of at least one DPYD variant experienced higher toxicity management costs (2,972€, 95%CI 2,456-3,505) than noncarriers (825€, 95%CI 785-864) (P<0.0001) and had a higher risk for toxicity requiring hospitalization (OR=4.14, 95%CI 1.87-9.14). In patients receiving fluoropyrimidine/irinotecan, the incremental cost between DPYD variant and UGT1A1*28/*28 carriers and noncarriers was 2,975€. This study suggests that the toxicity management costs during fluoropyrimidine-based therapy are associated with DPYD and UGT1A1*28 variants, and supports the utility of genotyping. This article is protected by copyright. All rights reserved.

PMID: 30339275 [PubMed - as supplied by publisher]

Effects of ABCB1 genotypes on the pharmacokinetics and clinical outcomes of new oral anticoagulants: A systematic review and meta-analysis.

Curr Pharm Des. 2018 Oct 18;:

Authors: Xie Q, Xiang Q, Mu G, Ma L, Chen S, Zhou S, Hu K, Zhang Z, Cui Y, Jian J

Abstract
Background New oral anticoagulants (NOACs) are effective and widely used to prevent and treat thromboembolic diseases, but the response to NOACs differs according to ABCB1 genotypes. Objective We investigated the effects of ABCB1 genotypes on the pharmacokinetics and clinical outcomes of NOACs. Methods We searched PubMed, Embase, and the Cochrane Library for studies on ABCB1 genotypes published from the inception of these databases till May 23, 2018. The weighted mean difference (WMD) and odds ratio (OR) with 95% confidence interval (CI) were calculated for continuous and dichotomous data, respectively. Summary results were calculated using a random effects model. Results Ten studies involving 2609 individuals were included in the systematic review, and three studies involving 535 individuals were included in the meta-analysis. Overall, four ABCB1 single-nucleotide polymorphisms were identified in the review. Carriers of the ABCB1 rs1045642 CC genotype had lower maximum plasma concentration (Cmax) than those of TT (WMD = -16.99 ng/mL; 95% CI = -33.39 to -0.59; P = 0.04), and carriers of the rs2032582 GG genotype showed lower Cmax than those of the A/T allele (WMD = -19.21 ng/mL; 95% CI = -36.62 to -1.80; P = 0.03). Carriers of the rs1045642 CC genotype showed lower area under the curve from time 0 to infinity (AUC0-∞) than those of the T allele (WMD = -78.58 ng•h/mL; 95% CI = -151.14 to -6.01; P = 0.03). ABCB1 rs4148738 genotypes did not affect the risks of ischemic stroke or systemic embolism (OR = 0.88), ischemic events (OR = 0.98), bleeding (OR = 0.94), major bleeding (OR = 1.14), or minor bleeding (OR = 0.94) in patients treated with dabigatran. Conclusions Cmax was lower in carriers of ABCB1 rs1045642 CC than in those of TT and in carriers of rs2032582 GG than in those of the A/T allele, and AUC0-∞ was lower in carriers of rs1045642 CC than in those of TT. Conversely, ABCB1 rs4148738 genotypes did not affect primary clinical endpoints in dabigatran-administered patients. Future studies should analyze the relationships of ABCB1 genotypes with the pharmacokinetics and clinical outcomes of specific NOACs.

PMID: 30338730 [PubMed - as supplied by publisher]

Aberration in translation initiation and associated diseases: Role of the eukaryotic translation initiation factor 3A.

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2017 Oct 28;42(10):1204-1211

Authors: Zhu T, Gao Y, Li L, Wang L, Yin J, Zhou H, Zhang W, Liu Z

Abstract
Translation control in eukaryotes contributes significantly to gene expression regulation during cellular processes, which enables rapid changes of specific proteins to maintain cellular homeostasis. Eukaryotic translation is a multiple-step process that comprised of four phases: initiation, elongation, termination and ribosome recycling. The initiation phase is rate-limiting and orchestrated by a set of eukaryotic translation initiation factors (eIFs). Defects in translation initiation can result in a series of diseases. Among all eIFs, eIF3 is the largest and less-known initiation factor due to its intrinsic complexity. Aberration in eIF3A, the largest subunit of eIF3, is known to contribute to carcinogenesis and protection against evolution into higher-grade malignancy, and the altered expression or mutation of eIF3A affects the responses of cancer patients to platinum-based chemotherapy. Besides its role in cancinogenesis, eIF3A is also implicated in fibrosis, and the agents inhibiting eIF3A delay the progression of this disorder. The dual roles of eIF3A in tumorigenesis are probably due to the regulation of translation of different mRNAs at different stages of tumor progression by eIF3A. In turn the encoded products serve as pro-tumor or anti-tumor proteins at different stages.

PMID: 29093254 [PubMed - indexed for MEDLINE]

Leveraging electronic health records to assess the role of ADRB2 single nucleotide polymorphisms in predicting exacerbation frequency in asthma patients.

Pharmacogenet Genomics. 2018 Nov;28(11):256-259

Authors: Sood N, Connolly JJ, Mentch FD, Vazquez L, Sleiman PMA, Hysinger EB, Hakonarson H, eMERGE Outcomes Workgroup

Abstract
Asthma is the leading chronic disease in children. Several studies have identified genetic biomarkers associated with susceptibility and severity in both adult and pediatric cases. In this study, we evaluated outcomes in 400 African American and European American pediatric cases all of whom were regular users of inhaled corticosteroids. Patients were stratified by genotype using two single nucleotide polymorphisms in the β-2-adrenergic receptor (ADRB2) gene - rs1042713 and rs1042714, previously associated with asthma outcome. These correspond to nonsynonymous single nucleotide polymorphisms at positions 16 [arginine to glycine (Arg16Gly); rs1042713] and 27 [glutamic acid to glutamine (Glu27Gln); rs1042714], which are relatively common (minor allele frequencies ∼40-50%), and have been well characterized in asthma pharmacogenetics. We controlled for adherence to the National Heart, Lung and Blood Institute guidelines using deep mining of electronic health record data to determine treatment course. We found no significant effect for rs1042713 (Arg16Gly) but did identify an effect for rs1042714, where participants homozygous for Gln27 had increased exacerbations while taking inhaled corticosteroids in comparison with those who were either heterozygous or homozygous for Glu27. This is consistent with previous studies and demonstrates for the first time that the Glu27 variant in the ADRB2 gene is associated with increased frequencies of asthma exacerbations. Moreover, this study also lends an important proof-of-principle on how electronic health records linked to genotype can be efficiently and systematically mined to delineate health outcomes.

PMID: 30334910 [PubMed - in process]

Pharmacogenomics and implementation of precision therapeutics in the neonatal ICU: a new frontier?

Pharmacogenomics. 2018 Oct 18;:

Authors: Lewis T, Leeder JS

PMID: 30334480 [PubMed - as supplied by publisher]

How to make P-glycoprotein (ABCB1, MDR1) harbor mutations and measure its expression and activity in cell cultures?

Pharmacogenomics. 2018 Oct 18;:

Authors: Zubiaur P, Saiz-Rodríguez M, Koller D, Ovejero-Benito MC, Wojnicz A, Abad-Santos F

Abstract
Several polymorphisms have been identified in ABCB1, the gene encoding for the P-glycoprotein. This transporter alters the pharmacokinetics or effectiveness of drugs by excreting them from cells where it is expressed (e.g., blood-brain barrier, intestine or tumors). No consensus has been reached regarding the functional consequences of these polymorphisms in the transporter's function. The aim of this review was to describe a methodology that allows the assessment of P-gp function when harboring polymorphisms. We describe how to obtain cell lines with high expression levels of the transporter with polymorphisms and several tactics to measure its expression and activity. This methodology may help elucidate the contribution of polymorphisms in ABCB1 to drug pharmacokinetics, effectiveness and safety or to cancer chemotherapy failure.

PMID: 30334473 [PubMed - as supplied by publisher]

A Platform for Comprehensive Genomic Profiling in Human Cancers and Pharmacogenomics Therapy Selection.

Methods Mol Biol. 2018;1825:413-424

Authors: Kou T, Kanai M, Kamada M, Nakatsui M, Matsumoto S, Okuno Y, Muto M

Abstract
Recent innovations in next-generation sequencing (NGS) technologies have enabled comprehensive genomic profiling of human cancers in the clinical setting. The ability to profile has launched a worldwide trend known as precision medicine, and the fusion of genomic profiling and pharmacogenomics is paving the way for precision medicine for cancer. The profiling is coupled with information about chemical therapies available to patients with specific genotypes. As a result, the chemogenomic space in play is not only the standard chemical and genome space but also the mutational genome and chemical space. In this chapter, we introduce clinical genomic profiling using an NGS-based multiplex gene assay (OncoPrime™) at Kyoto University Hospital.

PMID: 30334215 [PubMed - in process]

Role of reciprocal interaction between autophagy and endoplasmic reticulum stress in apoptosis of human bronchial epithelial cells induced by cigarette smoke extract.

IUBMB Life. 2018 Oct 17;:

Authors: He B, Chen Q, Zhou D, Wang L, Liu Z

Abstract
Endoplasmic reticulum stress (ERS)-induced apoptosis of airway epithelial cells plays an important role in the pathogenesis of chronic obstructive pulmonary disease (COPD). Furthermore, autophagy is closely related to ERS under apoptosis. Here, this study aimed to investigate the role of the reciprocal interaction between autophagy and ERS in the cigarette smoke extract (CSE)-induced apoptosis of human bronchial epithelial (HBE) cells. Cell apoptosis was detected by flow cytometry analysis. Protein expression was examined by Western blot. The mRNA expression was detected using real-time quantitative reverse transcription PCR (qRT-PCR). The results showed that CSE treatment induced apoptosis, autophagy, and expression of ERS-related proteins in HBE cells. Furthermore, autophagy inhibition by 3-MA significantly decreased protein expression of GRP78, p-PERK, and p-eIF2α and increased CHOP, ATF4, and caspase-4, whereas ERS inhibition by 4-PBA led to autophagy suppression. Moreover, the CSE-induced autophagy was diminished by knockdown of GRP78, PERK, or eIF2α but enhanced by knockdown of ATF4 or CHOP; however, the CSE-induced HBE apoptosis was enhanced by knockdown of GRP78, PERK, or eIF2α but was attenuated by knockdown of ATF4 or CHOP. Additionally, both sodium hydrosulfide (NaHS) and melatonin attenuated the CSE-induced apoptosis, enhanced the CSE-induced autophagy, increased GRP78, p-PERK, and p-eIF2α, and decreased CHOP, ATF4, and caspase-4, via SIRT1/ORP150 pathway. Collectively, this study provided evidence about the role of the reciprocal interaction between autophagy and ERS in CSE-induced apoptosis of HBE cells. © 2018 IUBMB Life, 2018.

PMID: 30332528 [PubMed - as supplied by publisher]

Pharmacogenetic testing in oncology: a Brazilian perspective.

Clinics (Sao Paulo). 2018 Oct 11;73(suppl 1):e565s

Authors: Suarez-Kurtz G

Abstract
Pharmacogenetics, a major component of individualized or precision medicine, relies on human genetic diversity. The remarkable developments in sequencing technologies have revealed that the number of genetic variants modulating drug action is much higher than previously thought and that a true personalized prediction of drug response requires attention to rare mutations (minor allele frequency, MAF<1%) in addition to polymorphisms (MAF>1%) in pharmacogenes. This has major implications for the conceptual development and clinical implementation of pharmacogenetics. Drugs used in cancer treatment have been major targets of pharmacogenetics studies, encompassing both germline polymorphisms and somatic variants in the tumor genome. The present overview, however, has a narrower scope and is focused on germline cancer pharmacogenetics, more specifically, on drug/gene pairs for which pharmacogenetics-informed prescription guidelines have been published by the Clinical Pharmacogenetics Implementation Consortium and/or the Dutch Pharmacogenetic Working Group, namely, thiopurines/TPMT, fluoropyrimidines/UGT1A1, irinotecan/UGT1A1 and tamoxifen/CYP2D6. I begin by reviewing the general principles of pharmacogenetics-informed prescription, pharmacogenetics testing and the perceived barriers to the adoption of routine pharmacogenetics testing in clinical practice. Then, I highlight aspects of the pharmacogenetics testing of the selected drug-gene pairs and finally present pharmacogenetics data from Brazilian studies pertinent to these drug-gene pairs. I conclude with the notion that pharmacogenetics testing has the potential to greatly benefit patients by enabling precision medicine applied to drug therapy, ensuring better efficacy and reducing the risk of adverse effects.

PMID: 30328952 [PubMed - in process]

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions.

Genet Med. 2018 Oct 16;:

Authors: Reisberg S, Krebs K, Lepamets M, Kals M, Mägi R, Metsalu K, Lauschke VM, Vilo J, Milani L

Abstract
PURPOSE: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations.
METHODS: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia.
RESULTS: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants.
CONCLUSION: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.

PMID: 30327539 [PubMed - as supplied by publisher]

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

Genet Med. 2018 06;20(6):655-663

Authors: Orlando LA, Sperber NR, Voils C, Nichols M, Myers RA, Wu RR, Rakhra-Burris T, Levy KD, Levy M, Pollin TI, Guan Y, Horowitz CR, Ramos M, Kimmel SE, McDonough CW, Madden EB, Damschroder LJ

Abstract
PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network's efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

PMID: 28914267 [PubMed - indexed for MEDLINE]

[Genetic aspects of binge eating disorder Part 2. Molecular genetics and pharmacogenetic approaches].

Zh Nevrol Psikhiatr Im S S Korsakova. 2016;116(8):102-108

Authors: Kibitov АО, Мazo GE

Abstract
Genetic risk of binge eating disorder (ВЕD) is a consequence of joint participation of many genes, the contribution of each one is small, but the total (additive) effect is significant and greatly influences the age at onset, clinical dynamics and the level of treatment resistance. It is assumed that the carriers of different polymorphic variants of genes and their combinations have different levels of genetic risk. No Genom Wide Association studies of ВЕD has been performed and the analysis of the results of candidate genes studies gives reason to believe that pathogenetically substantiated panel of genes, including serotonin system, BDNF and, especially dopamine and endogenous opioid system, would be most useful, taking into account the mechanism of action of drugs for the ВЕD treatment. Genetic studies with this panel if using evidence-based design, detailed and quantitative analysis of the family history of binge eating can give good results for: 1) assessment of the genetic risk of ВЕD for primary prevention programs; 2) identification of the specific clinical forms of development and course of ВЕD with significant genetic influence; 3) identification of the specific genetic variants that increase the effectiveness of personalized pharmacotherapy of ВЕD within pharmacogenetic approach.

PMID: 28635745 [PubMed - indexed for MEDLINE]

11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

pharmacogenomics

These pubmed results were generated on 2018/10/17

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

pharmacogenomics

These pubmed results were generated on 2018/10/17

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

pharmacogenomics

These pubmed results were generated on 2018/10/16

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.