Different Underlying Mechanism Might Explain the Absence of a Significant Difference in Area Under the Concentration-Time Curve of Linezolid for Different ABCB1 Genotypes.

Ther Drug Monit. 2019 04;41(2):254-255

Authors: Allegra S, Di Paolo A, Cusato J, Fatiguso G, Arrigoni E, Danesi R, Corcione S, DʼAvolio A

PMID: 30883522 [PubMed - indexed for MEDLINE]

Zebrafish: A Pharmacogenetic Model for Anesthesia.

Methods Enzymol. 2018;602:189-209

Authors: Bedell V, Buglo E, Marcato D, Pylatiuk C, Mikut R, Stegmaier J, Scudder W, Wray M, Züchner S, Strähle U, Peravali R, Dallman JE

Abstract
General anesthetics are small molecules that interact with and effect the function of many different proteins to promote loss of consciousness, amnesia, and sometimes, analgesia. Owing to the complexity of this state transition and the transient nature of these drug/protein interactions, anesthetics can be difficult to study. The zebrafish is an emerging model for the discovery of both new genes required for the response to and side effects of anesthesia. Here we discuss the tools available to manipulate the zebrafish genome, including both genetic screens and genome engineering approaches. Additionally, there are various robust behavior assays available to study anesthetic and other drug responses. These assays are available for single-gene study or high throughput for genetic or drug discovery. Finally, we present a case study of using propofol as an anesthetic in the zebrafish. These techniques and protocols make the zebrafish a powerful model to study anesthetic mechanisms and drug discovery.

PMID: 29588029 [PubMed - indexed for MEDLINE]

Implementation of Standardized Clinical Processes for TPMT Testing in a Diverse Multidisciplinary Population: Challenges and Lessons Learned.

Clin Transl Sci. 2018 03;11(2):175-181

Authors: Weitzel KW, Smith DM, Elsey AR, Duong BQ, Burkley B, Clare-Salzler M, Gong Y, Higgins TA, Kong B, Langaee T, McDonough CW, Staley BJ, Vo TT, Wake DT, Cavallari LH, Johnson JA

Abstract
Although thiopurine S-methyltransferase (TPMT) genotyping to guide thiopurine dosing is common in the pediatric cancer population, limited data exist on TPMT testing implementation in diverse, multidisciplinary settings. We established TPMT testing (genotype and enzyme) with clinical decision support, provider/patient education, and pharmacist consultations in a tertiary medical center and collected data over 3 years. During this time, 834 patients underwent 873 TPMT tests (147 (17%) genotype, 726 (83%) enzyme). TPMT tests were most commonly ordered for gastroenterology, rheumatology, dermatology, and hematology/oncology patients (661 of 834 patients (79.2%); 580 outpatient vs. 293 inpatient; P < 0.0001). Thirty-nine patients had both genotype and enzyme tests (n = 2 discordant results). We observed significant differences between TPMT test use and characteristics in a diverse, multispecialty environment vs. a pediatric cancer setting, which led to unique implementation needs. As pharmacogenetic implementations expand, disseminating lessons learned in diverse, real-world environments will be important to support routine adoption.

PMID: 29351371 [PubMed - indexed for MEDLINE]

Genome-wide and Phenome-wide Approaches to Understand Variable Drug Actions in Electronic Health Records.

Clin Transl Sci. 2018 03;11(2):112-122

Authors: Robinson JR, Denny JC, Roden DM, Van Driest SL

PMID: 29148204 [PubMed - indexed for MEDLINE]

The safety of treating newly diagnosed epilepsy.

Expert Opin Drug Saf. 2019 Apr 04;:

Authors: Sharma S, Kwan P

Abstract
INTRODUCTION: Epilepsy is a serious chronic neurological disorder manifested by an enduring symptomatic predisposition to seizures. Newly diagnosed individuals face increased morbidity, mortality and socio-economic costs. Anti-epileptic drug therapy is the treatment usually prescribed, which has efficacy in seizure control and mitigating long-term mortality. Areas covered: Safety of anti-epileptic drug therapy in adults with focus in newly diagnosed patients. Areas covered include the most commonly experienced adverse drug effects, as well as those with the highest impacts on drug tolerability, quality of life, morbidity and mortality. Evidence was also reviewed to identify clinical strategies to improve the safety of anti-epileptic drug therapy. Expert opinion: Anti-epileptic drugs (AEDs) are mostly effective and well tolerated. However, a lack of standardised reporting of adverse drug effects in trials and in clinical practice provides an obstacle for evaluation of which adverse drug effects need to be prioritised in management. Improvement in the reporting of cognitive and other effects, as well as improved precision medicine and pharmacogenomics to target the incidence of high-mortality idiosyncratic reactions, will help to reduce the harm of AEDs in people newly diagnosed with epilepsy.

PMID: 30943798 [PubMed - as supplied by publisher]

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.

PLoS One. 2018;13(10):e0205872

Authors: Ma Z, Wang P, Gao Z, Wang R, Khalighi K

Abstract
Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with devastating adverse events. Remarkable efforts have been made to develop the machine learning based warfarin dosing algorithms incorporating clinical factors and genetic variants such as polymorphisms in CYP2C9 and VKORC1. The most widely validated pharmacogenetic algorithm is the IWPC algorithm based on multivariate linear regression (MLR). However, with only a single algorithm, the prediction performance may reach an upper limit even with optimal parameters. Here, we present novel algorithms using stacked generalization frameworks to estimate the warfarin dose, within which different types of machine learning algorithms function together through a meta-machine learning model to maximize the prediction accuracy. Compared to the IWPC-derived MLR algorithm, Stack 1 and 2 based on stacked generalization frameworks performed significantly better overall. Subgroup analysis revealed that the mean of the percentage of patients whose predicted dose of warfarin within 20% of the actual stable therapeutic dose (mean percentage within 20%) for Stack 1 was improved by 12.7% (from 42.47% to 47.86%) in Asians and by 13.5% (from 22.08% to 25.05%) in the low-dose group compared to that for MLR, respectively. These data suggest that our algorithms would especially benefit patients requiring low warfarin maintenance dose, as subtle changes in warfarin dose could lead to adverse clinical events (thrombosis or bleeding) in patients with low dose. Our study offers novel pharmacogenetic algorithms for clinical trials and practice.

PMID: 30339708 [PubMed - indexed for MEDLINE]

12 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 2019/04/04

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 2019/04/04

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.

4-Hydroxytamoxifen enhances sensitivity of estrogen receptor α-positive breast cancer to docetaxel in an estrogen and ZNF423 SNP-dependent fashion.

Breast Cancer Res Treat. 2019 Apr 01;:

Authors: Wang G, Qin S, Zayas J, Ingle JN, Liu M, Weinshilboum RM, Shen K, Wang L

Abstract
PURPOSE: In early stage, ERα-positive breast cancer, concurrent use of endocrine therapy and chemotherapy has not been shown to be superior to sequential use. We hypothesized that genetic biomarkers can aid in selecting patients who would benefit from chemo-endocrine therapy. Our previous studies revealed that ZNF423 is a transcription factor for BRCA1 and an intronic single nucleotide polymorphism (SNP) in ZNF423, rs9940645, determines tamoxifen response. Here, we identified mitosis-related genes that are regulated by ZNF423 which led us to investigate taxane response in a rs9940645 SNP- and tamoxifen-dependent fashion.
METHODS: The Cancer Genome Atlas (TCGA) breast cancer dataset was used to identify genes correlated with ZNF423. Quantitative reverse transcription PCR, chromatin immunoprecipitation, and luciferase reporter assays were used to validate the gene regulation. We used CRISPR/Cas9 to engineer paired ZR-75-1 cells which differ only in ZNF423 rs9940645 SNP genotype to test SNP-dependent phenotypes including cell cycle and cell viability. We validated our findings in an additional two breast cancer cell lines, Hs578T-ERα and HCC1500.
RESULTS: Mitosis-related genes VRK1 and PBK, which encode histone H3 kinases, were experimentally validated to be regulated by ZNF423. ZNF423 knockdown decreased VRK1 and PBK expression and activity. Additionally, ZNF423 knockdown enhanced docetaxel-induced G2/M arrest and cytotoxicity through VRK1 or PBK regulation. Lastly, cells carrying the rs9940645 variant genotype had increased G2/M arrest and decreased cell viability when treated with docetaxel in combination with estradiol and 4-OH-TAM.
CONCLUSIONS: We identified ZNF423 regulated genes involved in the G2/M phase of the cell cycle. 4-OH-TAM sensitized ERα-positive breast cancer cells to docetaxel in a ZNF423 SNP-dependent manner. Our findings suggest that patients with rs9940645 variant genotype may benefit from concurrent tamoxifen and docetaxel. This would impact a substantial proportion of patients because this SNP has a minor allele frequency of 0.47.

PMID: 30937657 [PubMed - as supplied by publisher]

Metformin Pharmacogenetics: Effects of SLC22A1, SLC22A2, and SLC22A3 Polymorphisms on Glycemic Control and HbA1c Levels.

J Pers Med. 2019 Mar 25;9(1):

Authors: Al-Eitan LN, Almomani BA, Nassar AM, Elsaqa BZ, Saadeh NA

Abstract
Type 2 diabetes mellitus (T2DM) constitutes a major portion of Jordan's disease burden, and incidence rates are rising at a rapid rate. Due to variability in the drug's response between ethnic groups, it is imperative that the pharmacogenetics of metformin be investigated in the Jordanian population. The objective of this study was to investigate the relationship between twenty-one single nucleotide polymorphisms (SNPs) in the SLC22A1, SLC22A2, and SLC22A3 genes and their effects on metformin pharmacogenetics in Jordanian patients diagnosed with type 2 diabetes mellitus. Blood samples were collected from 212 Jordanian diabetics who fulfilled the inclusion criteria, which were then used in SNP genotyping and determination of HbA1c levels. The rs12194182 SNP in the SLC22A3 gene was found to have a significant association (p < 0.05) with lower mean HbA1c levels, and this association more pronounced in patients with the CC genotype (i.e., p-value was significant before correcting for multiple testing). Moreover, the multinomial logistic regression analysis showed that SNP genotypes within the SLC22A1, SLC22A2, and SLC22A3 genes, body mass index (BMI) and age of diagnosis were significantly associated with glycemic control (p < 0.05). The results of this study can be used to predict response to metformin and other classes of T2DM drugs, making treatment more individualized and resulting in better clinical outcomes.

PMID: 30934600 [PubMed]

Warfarin dose requirement in patients having severe thrombosis or thrombophilia.

Br J Clin Pharmacol. 2019 Apr 01;:

Authors: Helin TA, Joutsi-Korhonen L, Asmundela H, Niemi M, Orpana A, Lassila R

Abstract
AIMS: Warfarin dose requirement varies significantly. We compared the clinically established international normalized ratio (INR) -based doses among patients with severe thrombosis and/or thrombophilia with estimates from genetic dosing algorithms.
METHODS: Fifty patients with severe thrombosis and/or thrombophilia requiring permanent anticoagulation, referred to the Helsinki University Hospital Coagulation Center, were screened for thrombophilias and genotyped for CYP2C9*2 (c.430C>T, rs1799853), CYP2C9*3 (c.1075A>C, rs1057910) and VKORC1 c.-1639G>A (rs9923231) variants. The warfarin maintenance doses (target INR 2.0-3.0 in 94%, 2.5-3.5 in 6%) were estimated by the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) algorithms. The individual warfarin maintenance dose was tailored, supplementing estimates with comprehensive clinical evaluation and INR data.
RESULTS: Mean patient age was 47 years (range, 20-76), and BMI 27 (SD 6), 68% being women. Forty-six (92%) had previous venous or arterial thrombosis, and 26 (52%) had a thrombophilia, with 22% having concurrent aspirin. A total of 40% carried the CYP2C9*2 or *3 allele and 54% carried the VKORC1-1639A allele. The daily mean maintenance dose of warfarin estimated by the Gage algorithm was 5.4 mg (95% CI 4.9-5.9 mg,), and by the IWPC algorithm was 5.2 mg (95% CI 4.7-5.7 mg,). The daily warfarin maintenance dose after clinical visits and follow-up was higher than the estimates, mean 6.9 mg (95% CI 5.6-8.2 mg, p<0.006), with highest dose in patients having multiple thrombophilic factors (p<0.03).
CONCLUSIONS: In severe thrombosis and/or thrombophilia, variation in thrombin generation and pharmacodynamics influences warfarin response. Pharmacogenetic dosing algorithms seem to underestimate dose requirement.

PMID: 30933373 [PubMed - as supplied by publisher]

The Low Molecular Weight Brain Derived Neurotrophic Factor Mimetics With Antidepressant-Like Activity.

Curr Pharm Des. 2019 Mar 29;:

Authors: Gudasheva TA, Povarnina P, Tarasiuk AV, Seredenin SB

Abstract
The search for new highly-effective, fast-acting antidepressant drugs is extremely relevant. Brain derived neurotrophic factor (BDNF) and signaling through its tropomyosin-related tyrosine kinase B (TrkB) receptor, represents one of the most promising therapeutic targets for treating depression. BDNF is a key regulator of neuroplasticity in the hippocampus and the prefrontal cortex, the dysfunction of which is considered to be the main pathophysiological hallmark of this disorder. BDNF itself has no favorable drug-like properties due to poor pharmacokinetics and possible adverse effects. The design of small, proteolytically stable BDNF mimetics might provide a useful approach for the development of therapeutic agents. There are two small molecule BDNF mimetics with antidepressant-like activity reported - 7, 8-dihydroxyflavone and the dimeric dipeptide mimetic of BDNF loop 4, GSB-106. The article reflects on current literature on the role of BDNF as a promising therapeutic target in the treatment of depression and on the current advances in development of small molecules on the base of this neurotrophin as potential antidepressants.

PMID: 30931847 [PubMed - as supplied by publisher]

NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis.

Nucleic Acids Res. 2019 Apr 01;:

Authors: Zhou G, Soufan O, Ewald J, Hancock REW, Basu N, Xia J

Abstract
The growing application of gene expression profiling demands powerful yet user-friendly bioinformatics tools to support systems-level data understanding. NetworkAnalyst was first released in 2014 to address the key need for interpreting gene expression data within the context of protein-protein interaction (PPI) networks. It was soon updated for gene expression meta-analysis with improved workflow and performance. Over the years, NetworkAnalyst has been continuously updated based on community feedback and technology progresses. Users can now perform gene expression profiling for 17 different species. In addition to generic PPI networks, users can now create cell-type or tissue specific PPI networks, gene regulatory networks, gene co-expression networks as well as networks for toxicogenomics and pharmacogenomics studies. The resulting networks can be customized and explored in 2D, 3D as well as Virtual Reality (VR) space. For meta-analysis, users can now visually compare multiple gene lists through interactive heatmaps, enrichment networks, Venn diagrams or chord diagrams. In addition, users have the option to create their own data analysis projects, which can be saved and resumed at a later time. These new features are released together as NetworkAnalyst 3.0, freely available at https://www.networkanalyst.ca.

PMID: 30931480 [PubMed - as supplied by publisher]

PLCE1 Polymorphisms and Risk of Esophageal and Gastric Cancer in a Northwestern Chinese Population.

Biomed Res Int. 2019;2019:9765191

Authors: Liang P, Zhang W, Wang W, Dai P, Wang Q, Yan W, Wang W, Lei X, Cui D, Yan Z

Abstract
The reported risk susceptibility between phospholipase C epsilon 1 (PLCE1) polymorphisms and esophageal cancer (EC) and gastric cancer (GC) remained inconsistent and controversial, especially on variants other than rs2274223. The relationship between PLCE1 polymorphisms and gene expression is also unclear. Here we conducted a case-control study from northwest China, genotyped seven tag single nucleotide polymorphisms (SNPs) in PLCE1 with multiplexed SNP MassARRAY assay. Stratified analysis was carried out and PLCE1 expression was evaluated in specified groups with the method of qRT-PCR and immunohistochemistry. Results showed that the minor alleles of rs3765524, rs2274223, and rs10509670 were associated with increased risk of EC and GC. Linkage disequilibrium analysis revealed protective haplotypes of CCAAGTC and CCAA. By stratification, a more significant association was found in subgroups of male, age ≥ 54, tumor stages of I-II and tumor size ≤ 5 cm, EC and cardia cancer (CC) of stomach, and moderate to well differentiated squamous carcinoma. In addition, a significant association for rs3765524 with noncardia cancer (NCC) and adenocarcinoma which is predominant in China was also observed. Further expression analysis identified that PLCE1 was downregulated in NCC tissues comparing to their adjacent noncancerous tissues, and its protein expression was higher in genotype rs3765524 CT/TT than in rs3765524 CC. In summary, our study suggests that PLCE1 polymorphisms may affect its gene expression and are associated with not only EC and CC, but also, to some extent, NCC risk in this study population.

PMID: 30931333 [PubMed - in process]

Actionable Pharmacogenetic Variation in the Slovenian Genomic Database.

Front Pharmacol. 2019;10:240

Authors: Hočevar K, Maver A, Peterlin B

Abstract
Background: Genetic variability in some of the genes that affect absorption, distribution, metabolism, and elimination ("pharmacogenes") can significantly influence an individual's response to the drug and consequently the effectiveness of treatment and possible adverse drug events. The rapid development of sequencing methods in recent years and consequently the increased integration of next-generation sequencing technologies into the clinical settings has enabled extensive genotyping of pharmacogenes for personalized treatment. The aim of the present study was to investigate the frequency and variety of potentially actionable pharmacogenetic findings in the Slovenian population. Methods: De-identified data from diagnostic exome sequencing in 1904 cases submitted to our institution were analyzed for variants within 293 genes associated with drug response. Filtered variants were classified according to population frequency, variant type, the functional impact of the variant, pathogenicity predictions and characterization in the Pharmacogenomics Knowledgebase (PharmGKB) and ClinVar. Results: We observed a total of 24 known actionable pharmacogenetic variants (PharmGKB 1A or 1B level of evidence), comprising approximately 26 drugs, of which, 12 were rare, with the population frequency below 1%. Furthermore, we identified an additional 61 variants with PharmGKB 2A or 2B clinical annotations. We detected 308 novel/rare potentially actionable variants: 177 protein-truncating variants and 131 missense variants predicted to be pathogenic based on several pathogenicity predictions. Conclusion: In the present study, we estimated the burden of pharmacogenetic variants in nationally based exome sequencing data and investigated the potential clinical usefulness of detected findings for personalized treatment. We provide the first comprehensive overview of known pharmacogenetic variants in the Slovenian population, as well as reveal a great proportion of novel/rare variants with a potential to influence drug response.

PMID: 30930780 [PubMed]

Dual Functional Immunostimulatory Polymeric Prodrug Carrier with Pendent Indoximod for Enhanced Cancer Immunochemotherapy.

Acta Biomater. 2019 Mar 28;:

Authors: Wan Z, Sun J, Xu J, Moharil P, Chen J, Xu J, Zhu J, Li J, Huang Y, Xu P, Ma X, Xie W, Lu B, Li S

Abstract
Immunotherapy based on checkpoint blockade has been regarded as one of the most promising approaches towards many types of cancers. However, low response rate hinders its application due to insufficient tumor immunogenicity and immunosuppressive tumor microenvironment. To achieve an overall enhanced therapeutic outcome, we developed a dual-functional immuno-stimulatory polymeric prodrug carrier modified with pendent indoximod, an indoleamine 2,3-dioxygenase (IDO) inhibitor that can be used to reverse immune suppression, for co-delivery of Doxorubicin (Dox), a hydrophobic anticancer agent that can promote immunogenic cell death (ICD) and elicit antitumor immunity. The resulted carrier denoted as POEG-b-PVBIND, consisting of poly (oligo (ethylene glycol) methacrylate) (POEG) hydrophilic blocks and indoximod conjugated hydrophobic blocks, is rationally designed to improve immunotherapy by synergistically modulating the tumor microenvironment (TME). Our data showed that Dox-triggered ICD promoted intra-tumoral infiltration of CD8+ T cells and IFN-γ-production by CD8+ T cells. Meanwhile, cleaved indoximod significantly increased CD8+ T cell infiltration while reducing the immunosuppressive T regulatory cells (Tregs). More importantly, Dox/POEG-b-PVBIND micelles led to significantly improved tumor regression in an orthotopic murine breast cancer model compared to both Dox-loaded POEG-b-PVB micelles (a control inert carrier) and POEG-b-PVBIND micelles alone, confirming combination effect of indoximod and Dox in improving the overall antitumor activity. STATEMENT OF SIGNIFICANCE: Indoleamine 2,3-dioxygenase (IDO) is an enzyme that can induce immune suppressive microenvironment in tumors. As a well-studied IDO inhibitor, indoximod (IND) represents a promising agent for cancer immunotherapy and could be particularly useful in combination with other chemotherapeutic agents. However, three major problems hinder its application: (1) IND is barely soluble in water; (2) IND delivery efficiency is limited (3) simultaneous delivery of two agents into tumor site is still challenging. Currently, most reports largely focus on improving the pharmacokinetic profile of IND alone via different formulations such as IND prodrug and IND nanocrystal. However, there is limited information about IND based co-delivery systems, especially for delivering hydrophobic chemotherapeutic agents. Here, we developed a new dual-functional polymeric prodrug carrier modified with a number of pendent IND units (denoted as POEG-b-PVBIND). POEG-b-PVBIND shows immunostimulatory and antitumor activities by itself. More importantly, POEG-b-PVBIND polymer is able to self-assemble into nano-sized micelles that are highly effective in formulating and codelivering other hydrophobic agents including doxorubicin (Dox), sunitinib (Sun), and daunorubicin (Dau), which can elicit antitumor immunity via promoting immunogenic cell death (ICD). We have shown that our new combination therapy led to a significantly improved antitumor activity in an aggressive murine breast cancer model (4T1.2).

PMID: 30930305 [PubMed - as supplied by publisher]

Predicting CYP3A-mediated midazolam metabolism in critically ill neonates, infants, children and adults with inflammation and organ failure.

Br J Clin Pharmacol. 2018 02;84(2):358-368

Authors: Brussee JM, Vet NJ, Krekels EHJ, Valkenburg AJ, Jacqz-Aigrain E, van Gerven JMA, Swart EL, van den Anker JN, Tibboel D, de Hoog M, de Wildt SN, Knibbe CAJ

Abstract
AIMS: Inflammation and organ failure have been reported to have an impact on cytochrome P450 (CYP) 3A-mediated clearance of midazolam in critically ill children. Our aim was to evaluate a previously developed population pharmacokinetic model both in critically ill children and other populations, in order to allow the model to be used to guide dosing in clinical practice.
METHODS: The model was evaluated externally in 136 individuals, including (pre)term neonates, infants, children and adults (body weight 0.77-90 kg, C-reactive protein level 0.1-341 mg l-1 and 0-4 failing organs) using graphical and numerical diagnostics.
RESULTS: The pharmacokinetic model predicted midazolam clearance and plasma concentrations without bias in postoperative or critically ill paediatric patients and term neonates [median prediction error (MPE) <30%]. Using the model for extrapolation resulted in well-predicted clearance values in critically ill and healthy adults (MPE <30%), while clearance in preterm neonates was over predicted (MPE >180%).
CONCLUSION: The recently published pharmacokinetic model for midazolam, quantifying the influence of maturation, inflammation and organ failure in children, yields unbiased clearance predictions and can therefore be used for dosing instructions in term neonates, children and adults with varying levels of critical illness, including healthy adults, but not for extrapolation to preterm neonates.

PMID: 29072785 [PubMed - indexed for MEDLINE]

Testing the role of genetic variation of the MC4R gene in Chinese population in antipsychotic-induced metabolic disturbance.

Sci China Life Sci. 2019 Mar 26;:

Authors: Zhang Y, Ren H, Wang Q, Deng W, Yue W, Yan H, Tan L, Chen Q, Yang G, Lu T, Wang L, Zhang F, Yang J, Li K, Lv L, Tan Q, Zhang H, Ma X, Yang F, Li L, Wang C, Zhang D, Zhao L, Wang H, Li X, Guo W, Hu X, Tian Y, Ma X, Li T, Chinese Antipsychotics Pharmacogenomics Consortium

Abstract
Antipsychotic-induced metabolic disturbance (AIMD) is a common adverse effect of antipsychotics with genetics partly underpinning variation in susceptibility among schizophrenia patients. Melanocortin4 receptor (MC4R) gene, one of the candidate genes for AIMD, has been under-studied in the Chinese patients. We conducted a pharmacogenetic study in a large cohort of Chinese patients with schizophrenia. In this study, we investigated the genetic variation of MC4R in Chinese population by genotyping two SNPs (rs489693 and rs17782313) in 1,991 Chinese patients and examined association of these variants with the metabolic effects that were often observed to be related to AIMD. Metabolic measures, including body mass index (BMI), waist circumference (WC), glucose, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were assessed at baseline and after 6-week antipsychotic treatment. We found that interaction of SNP×medication status (drug-naïve/medicated) was significantly associated with BMI, WC, and HDL change %, respectively. Both SNPs were significantly associated with baseline BMI and WC in the medicated group. Moderate association of rs489693 with WC, Triglyceride, and HDL change % were observed in the whole sample. In the drug-naïve group, we found recessive effects of rs489693 on BMI gain more than 7%, WC and Triglyceride change %, with AA incurring more metabolic adverse effects. In conclusion, the association between rs489693 and the metabolic measures is ubiquitous but moderate. Rs17782313 is less involved in AIMD. Two SNPs confer risk of AIMD to patients treated with different antipsychotics in a similar way.

PMID: 30929193 [PubMed - as supplied by publisher]

Germline Genetic Variants in GATA3 and Breast Cancer Treatment Outcomes in SWOG S8897 Trial and the Pathways Study.

Clin Breast Cancer. 2019 Mar 06;:

Authors: Larsen V, Barlow WE, Yang JJ, Zhu Q, Liu S, Kwan ML, Ergas IJ, Roh JM, Hutchins LF, Kadlubar SA, Albain KS, Rae JM, Yeh IT, Ravdin PM, Martino S, Lyss AP, Osborne CK, Hortobagyi GN, Kushi LH, Hayes DF, Ambrosone CB, Yao S

Abstract
INTRODUCTION: GATA3 is a critical transcription factor in maintaining the differentiated state of luminal mammary epithelial cells. We sought to determine the prognostic and predictive roles of GATA3 genotypes for breast cancer.
PATIENTS AND METHODS: Twelve single nucleotide polymorphisms (SNPs) were genotyped in 2 breast cancer cohorts, including the SWOG S8897 trial where patients were treated with adjuvant chemotherapy (CAF [cyclophosphamide, doxorubicin, 5-fluorouracil] vs. CMF [cyclophosphamide, methotrexate, 5-fluorouracil]) or untreated, and the observational Pathways Study.
RESULTS: In the S8897 trial, rs3802604 and rs568727 were associated with disease-free survival and overall survival in the treated group, regardless of chemotherapy regimen. The GG genotype of rs3802604 conferred poorer overall survival (adjusted hazard ratio, 2.45; 95% confidence interval, 1.48-4.05) and disease-free survival (adjusted hazard ratio, 1.95; 95% confidence interval, 1.27-2.99) compared with the AA genotype. Similar associations were found for rs568727. In contrast, no association with either SNP was found in the untreated group. Subgroup analyses indicated that these 2 SNPs more strongly influenced outcomes in the patients who also received tamoxifen. However, the associations in the subgroup with tamoxifen treatment were not replicated in the Pathways Study, possibly owing to substantial differences between the 2 patient cohorts, such as chemotherapy regimen and length of follow-up. Results from joint analyses across these 2 cohorts were marginally significant, driven by the results in S8897. Bioinformatic analyses support potential functional disruption of the GATA3 SNPs in breast tissue.
CONCLUSIONS: The present study provides some evidence for the predictive value of GATA3 genotypes for breast cancer adjuvant therapies. Future replication studies in appropriate patient populations are warranted.

PMID: 30928413 [PubMed - as supplied by publisher]

Biotechnology, Big Data and Artificial Intelligence.

Biotechnol J. 2019 Mar 30;:e1800613

Authors: Oliveira AL

Abstract
Developments in biotechnology are increasingly dependent on the extensive use of big data, generated by modern high-throughput instrumentation technologies and stored in thousands of databases, public and private. Future developments in this area depend, critically, on the ability of biotechnology researchers to master the skills required to effectively integrate their own contributions with the large amounts of information available in these databases. This article offers a perspective of the relations that exist between the fields of big data and biotechnology, including the related technologies of artificial intelligence and machine learning, and describes how data integration, data exploitation and process optimization correspond to three essential steps in any future biotechnology project. The article also lists a number of application areas where the ability to use big data will become a key factor, including drug discovery, drug recycling, drug safety, functional and structural genomics, proteomics, pharmacogenetics and pharmacogenomics, among others. This article is protected by copyright. All rights reserved.

PMID: 30927505 [PubMed - as supplied by publisher]