Comparative effectiveness of glycyrrhizic acid preparations aimed at preventing and treating anti-tuberculosis drug-induced liver injury: A network meta-analysis of 97 randomized controlled trials.

BACKGROUND AND OBJECTIVES: Clinical guidelines and expert consensus do not yet recommend glycyrrhizic acid (GA) preparations, such as compound glycyrrhizin, diammonium glycyrrhizin, magnesium isoglycyrrhizinate (MGIG), et al., for the prevention of anti-tuberculosis(anti-TB) drug-induced liver injury (DILI) due to insufficient evidence. Although these GA preparations are recommended for the treatment of anti-TB DILI, which one performs best is unclear. Previous conventional meta-analyses did not summarize the results of simultaneous comparisons of different glycyrrhizinate preparations. Therefore, we aimed to compare and rank different GA preparations on preventing and treating the anti-TB DILI by network meta-analysis (NMA). METHODS: A systematic search on PubMed, Web of Science, Embase, the Cochrane Library, China National Knowledge Infrastructure, SinoMed, Chongqing VIP and, the Wanfang Database was performed up to December 19, 2020. The literature was screened according to predefined inclusion and exclusion criteria to extract important information. The outcomes were the incidence of liver injury (prevention section) and treatment response rate (treatment section). The NMA was conducted with a random-effects model under the Bayesian framework to calculate risk ratios (RRs) with 95% credible intervals (95% CrIs) using R software (version 3.6.1). RESULTS: From 1,411 publications, we included 97 relevant randomized clinical trials (RCTs) (10,923 participants). In terms of preventing anti-TB DILI (33 RCTs, comprising 5,762 patients), CGC, DGC, DGEC, and DGI, but not CGI, significantly reduced the incidence of liver injury than control group (RRs ranged from 0.26 to 0.58); CGC and DGEC were superior to DGC (RRs = 0.50 and 0.58, respectively). In terms of treating anti-TB DILI (64 RCTs, comprising 5,161 patients), MGIG was most effective among all regimens (RRs ranged from 1.15 to 1.72) while DGC ranked last (RRs ranged from 0.58 to 0.83). CONCLUSIONS: All GA preparations except for CGI were effective in preventing the incidence of anti-TB DILI and CGC was superior to DGC. MGIG seems to be the best choice among all GA preparations for the treatment of anti-TB DILI. Future clinical practice guidelines should factor in these novel findings to improve patient outcomes; however, further high-quality trials are needed to validate these results.

Pharmacomicrobiomics: Exploiting the Drug-Microbiota Interactions in Antihypertensive Treatment.

Hypertension is a leading risk factor for cardiovascular diseases and can reduce life expectancy. Owing to the widespread use of antihypertensive drugs, patients with hypertension have improved blood pressure control over the past few decades. However, for a considerable part of the population, these drugs still cannot significantly improve their symptoms. In order to explore the reasons behind, pharmacomicrobiomics provide unique insights into the drug treatment of hypertension by investigating the effect of bidirectional interaction between gut microbiota and antihypertensive drugs. This review discusses the relationship between antihypertensive drugs and the gut microbiome, including changes in drug pharmacokinetics and gut microbiota composition. In addition, we highlight how our current knowledge of antihypertensive drug-microbiota interactions to develop gut microbiota-based personalized ways for disease management, including antihypertensive response biomarker, microbial-targeted therapies, probiotics therapy. Ultimately, a better understanding of the impact of pharmacomicrobiomics in the treatment of hypertension will provide important information for guiding rational clinical use and individualized use.

Population Pharmacokinetics and Dosage Optimization of Linezolid in Patients with Liver Dysfunction.

Linezolid is the first synthetic oxazolidone agent to treat infections caused by Gram-positive pathogens. Infected patients with liver dysfunction (LD) are more likely to suffer from adverse reactions, such as thrombocytopenia, when standard-dose linezolid is used than patients with LD who did not use linezolid. Currently, pharmacokinetics data of linezolid in patients with LD are limited. This study aimed to characterize pharmacokinetics parameters of linezolid in patients with LD, identify the factors influencing the pharmacokinetics, and propose an optimal dosage regimen. We conducted a prospective study and established a population pharmacokinetics model with the Phoenix NLME software. The final model was evaluated by goodness-of-fit plots, bootstrap analysis, and prediction corrected-visual predictive check. A total of 163 concentration samples from 45 patients with LD were adequately described by a one-compartment model with first-order elimination along with prothrombin activity (PTA) and creatinine clearance as significant covariates. Linezolid clearance (CL) was 2.68 liters/h (95% confidence interval [CI], 2.34 to 3.03 liters/h); the volume of distribution (V) was 58.34 liters (95% CI, 48.00 to 68.68 liters). Model-based simulation indicated that the conventional dose was at risk for overexposure in patients with LD or severe renal dysfunction; reduced dosage (300 mg/12 h) would be appropriate to achieve safe (minimum steady-state concentration [Cmin,ss] at 2 to 8 µg/ml) and effective targets (the ratio of area under the concentration-time curve from 0 to 24 h [AUC0-24] at steady state to MIC, 80 to 100). In addition, for patients with severe LD (PTA, ≤20%), the dosage (400 mg/24 h) was sufficient at an MIC of ≤2 µg/ml. This study recommended therapeutic drug monitoring for patients with LD. (This study has been registered in the Chinese Clinical Trial Registry under no. ChiCTR1900022118.).

Incorporation of Gene-Environment Interaction Terms Improved the Predictive Accuracy of Tacrolimus Stable Dose Algorithms in Chinese Adult Renal Transplant Recipients.

The narrow therapeutic window of tacrolimus necessitates daily monitoring and predictive algorithms based on genetic and nongenetic factors. In this study, we constructed predictive algorithms for tacrolimus stable dose in a retrospective cohort of 1045 Chinese renal transplant recipients. All patients were genotyped for CYP3A4 20230T>C (rs2242480), CYP3A4 T>C (rs4646437), CYP3A5*3 6898A>G (rs776746), ABCB1 129T>C (rs3213619); ABCB1 c.1236C>T (rs01128503), ABCB1 c.2677G>T/A (rs2032582) and ABCB1 c.3435C>T (rs1045642) polymorphisms, and the effects of gene-gene and gene-environment interactions on the predictive accuracy of algorithm were evaluated. In wild-type CYP3A4 rs2242480 (TT) carriers, patients who took calcium channel blockers had lower tacrolimus stable doses than those without the concomitant medications (P < 1 × 10-4 ). In contrast, there was no significant difference in mutant type patients. Similarly, the tacrolimus stable doses in wild-type CYP3A5 rs776746 carriers who had hypertension were higher than those without hypertension (P = 4.10 × 10-3 ). More importantly, dose-predictive algorithms with interaction terms showed higher accuracy and better performance than those without interaction terms. Our finding suggested that wild-type CYP3A4 rs2242480 (TT) carriers should be more cautious to take tacrolimus when they are coadministrated with calcium channel blockers, and CYP3A5 rs776746 (AA) carriers may need higher tacrolimus dosage when they are in combination with hypertension.

MIR4532 gene variant rs60432575 influences the expression of KCNJ11 and the sulfonylureas-stimulated insulin secretion.

PURPOSE: Diabetes mellitus is a major chronic disease and causes over one million deaths. KCNJ11 genetic polymorphisms influence the response of first-line oral antidiabetic agent sulfonylureas. Hsa-miR-4532 correlates with diabetic nephropathy and has a high abundance in urine. MIR4532 rs60452575 G>A variant changes the mature sequence of hsa-miR-4532. We studied whether the genetic polymorphisms of MIR4532 rs60452575 would influence KCNJ11 expression and sulfonylurea-stimulated insulin secretion or not. METHODS: To estimate the influence that rs60452575 G>A variant has on the interaction of hsa-miR-4532 and KCNJ11, we constructed a pmirGLO vector containing 3' UTR of KCNJ11 and co-transfected it with wild-type and mutant hsa-miR-4532 mimics into HEK293 cells; and we overexpressed wild-type and mutant hsa-miR-4532 mimics into HEK293 cells and MIN6 cells to access its effects on KCNJ11 expression and response of sulfonylureas. RESULTS: MIR4532 rs60452575 G>A variant appeared to disrupt the repression of KCNJ11 expression in both cell lines, and reduce the sulfonylurea-stimulated insulin secretion by breaking the binding of the hsa-miR-4532 to 3' UTR of KCNJ11 in MIN6 cells. CONCLUSIONS: Our study indicates that MIR4532 rs60452575 variant influences KCNJ11 expression and sulfonylurea response. It might be a potential predictive factor of sulfonylureas therapy.

Association of PON2 Gene Polymorphisms (Ser311Cys and Ala148Gly) With the Risk of Developing Type 2 Diabetes Mellitus in the Chinese Population.

Background: The association between paraoxonase 2 (PON2) gene polymorphisms and type 2 diabetes mellitus (T2DM) has been extensively investigated in the Chinese population with conflicting results. In this study, we systematically evaluated the association between PON2 Ser311Cys and Ala148Gly polymorphisms and T2DM risk by pooling all relevant studies. Methods: We searched PubMed, Embase, CNKI, and Wanfang databases for the studies. The strength of association was determined by the allelic, homozygous, heterozygous, recessive, and dominant genetic models and measured as odds ratio (OR) and 95% confidence interval (CI), under fixed- or random-effect models. Results: There was no significant association between PON2 Ser311Cys polymorphism and T2DM under any of the genetic models: allelic (OR = 1.06, 95% CI = 0.77-1.45; P = 0.721), heterozygous (OR = 1.13, 95% CI = 0.87-1.45; P = 0.362), dominant (OR = 1.10, 95% CI = 0.80-1.51; P = 0.562), recessive (OR = 0.87, 95% CI = 0.48-1.58; P = 0.648), homozygous (OR = 0.94, 95% CI = 0.47-1.89; P = 0.865). Similarly, no significant association was found in PON2 Arg148Gly polymorphism under any of the models: allelic (OR = 1.17, 95% CI = 0.91-1.50; P = 0.218), heterozygous (OR = 1.28, 95% CI = 0.94-1.74; P = 0.117), dominant (OR = 1.25, 95% CI = 0.93-1.67; P = 0.142), recessive (OR = 0.99, 95% CI = 0.52-1.88; P = 0.973), homozygous (OR = 1.08, 95% CI = 0.57-2.07; P = 0.808). Conclusions: The PON2 Ser311Cys and Ala148Gly polymorphisms were not associated with the risk of developing T2DM in the Chinese population.

Drug-induced hyperglycaemia and diabetes: pharmacogenomics perspectives.

Drug-induced diabetes is widely reported in clinical conditions, and it is becoming a global issue because of its potential to increase the risk of severe cardiovascular complications. However, which drug mechanisms exert their diabetogenic effects and why the effects present significant inter-individual differences remain largely unknown. Pharmacogenomics, which is the study of how genomic variation influences drug responses, provides an explanation for individual differences in drug-induced diabetes. We highlight that pharmacogenomics can be involved in regulating the expression of genes in signaling pathways related to the pharmacokinetics or pharmacodynamics of drugs or the pathogenesis of diabetes, contributing to the differences in drug-induced glucose impairment. The pharmacogenomics studies of the major diabetogenic drugs are reviewed, including calcineurin inhibitors, antipsychotics, hormones, and antihypertensive drugs. We intend to elucidate the genetic basis of drug-induced diabetes and pave the way for the precise use of these drugs in the clinic.

European versus Asian differences for the associations between paraoxonase-1 genetic polymorphisms and susceptibility to type 2 diabetes mellitus.

Many studies have examined the associations between paraoxonase-1 (PON1) genetic polymorphisms (Q192R, rs662 and L55M, rs854560) and the susceptibility to type 2 diabetes mellitus (T2DM) across different ethnic populations. However, the evidence for the associations remains inconclusive. In this study, we performed a meta-analysis to clarify the association of the two PON1 variants with T2DM risk. We carried out a systematic search of PubMed, Embase, CNKI and Wanfang databases for studies published before June 2017. The pooled odds ratios (ORs) for the association and their corresponding 95% confidence intervals (CIs) were calculated by a random- or fixed-effect model. A total of 50 eligible studies, including 34 and 16 studies were identified for the PON1 Q192R (rs662) and L55M (rs854560) polymorphism, respectively. As for the PON1 Q192R polymorphism, the 192R allele was a susceptible factor of T2DM in the South or East Asian population (OR > 1, P < 0.05) but represented a protective factor of T2DM in European population (OR = 0.66, 95% CI = 0.45-0.98) under a heterozygous genetic model. With regard to the PON1 L55M polymorphism, significant protective effects of the 55M allele on T2DM under the heterozygous (OR = 0.77, 95% CI = 0.61-0.97) and dominant (OR = 0.80, 95% CI = 0.65-0.99) genetic models were found in the European population, while no significant associations in the Asian populations under all genetic models (P > 0.05). In summary, by a comprehensive meta-analysis, our results firmly indicated that distinct effects of PON1 genetic polymorphisms existed in the risk of T2DM across different ethnic backgrounds.

Corrigendum: Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients.

This corrects the article DOI: 10.1038/srep42192.

Vitamin Pharmacogenomics: New Insight into Individual Differences in Diseases and Drug Responses.

Vitamins are vital to sustain normal physiological function, metabolism, and growth for all living organisms. Being an integral component of coenzyme, vitamins can affect the catalytic activities of many enzymes and the expression of drug transporters. Genetic variations in metabolism and/or transporter genes of drugs can influence the exposure of the human body to drugs and/or their active metabolites, thus contributing to the variations in drug responses and toxicities. Nonetheless, pharmacogenomics studies on nutrients have been rarely summarized. In this article, we reviewed recent progress on vitamin pharmacogenomics, for a better understanding on the influence of vitamin-related gene polymorphisms on inter-individual differences in diseases and drug efficacy and safety.

Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients.

Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the "derivation cohort" to develop dose-prediction algorithm, while the remaining 20% constituted the "validation cohort" to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67-0.76)] and validation cohorts [0.73 (0.63-0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

IL-3 and CTLA4 gene polymorphisms may influence the tacrolimus dose requirement in Chinese kidney transplant recipients.

The highly variable pharmacokinetics and narrow therapeutic window of tacrolimus (TAC) has hampered its clinical use. Genetic polymorphisms may contribute to the variable response, but the evidence is not compelling, and the explanation is unclear. In this study we attempted to find previously unknown genetic factors that may influence the TAC dose requirements. The association of 105 pathway-related single nucleotide polymorphisms (SNPs) with TAC dose-adjusted concentrations (C0/D) was examined at 7, 30 and 90 d post-operation in 382 Chinese kidney transplant recipients. In CYP3A5 non-expressers, the patients carrying the IL-3 rs181781 AA genotype showed a significantly higher TAC logC0/D than those with the AG genotype at 30 and 90 d post-operation (AA vs AG, 2.21±0.06 vs 2.01±0.03, P=0.004; and 2.17±0.06 vs 2.03±0.03, P=0.033, respectively), and than those with the GG genotype at 30 d (AA vs GG, 2.21±0.06 vs 2.04±0.03, P =0.011). At 30 d, the TAC logC0/D in the grouped AG+GG genotypes of CTLA4 rs4553808 was significantly lower than that in the AA genotype (P =0.041) in CYP3A5 expressers, but it was higher (P=0.008) in the non-expressers. We further validated the influence of CYP3A5 rs776746, CYP3A4 rs2242480 and rs4646437 on the TAC C0/D; other candidate SNPs were not associated with the differences in TAC C0/D. In conclusion, genetic polymorphisms in the immune genes IL-3 rs181781 and CTLA4 rs4553808 may influence the TAC C0/D. They may, together with CYP3A5 rs776746, CYP3A4 rs2242480 and rs4646437, contribute to the variation in TAC dose requirements. When conducting individualized therapy with tacrolimus, these genetic factors should be taken into account.

The Associations between Apolipoprotein E Gene Epsilon2/Epsilon3/Epsilon4 Polymorphisms and the Risk of Coronary Artery Disease in Patients with Type 2 Diabetes Mellitus.

Background and Objective: Apolipoprotein E (APOE) plays important roles in lipoprotein metabolism and cardiovascular disease. Evidence suggests the APOE gene epsilon2/epsilon3/epsilon4 (ε2/ε3/ε4) polymorphisms might be associated with the susceptibility of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM). However, no clear consensus has yet been established. Therefore, the aim of this meta-analysis is to provide a precise conclusion on the potential association between APOE ε2/ε3/ε4 polymorphisms and the risk of CAD in patients with T2DM based on case-control studies. Methods: Pubmed, Embase, Chinese National Knowledge Infrastructure (CNKI), and Wanfang databases were searched for all relevant studies prior to August 2017 in English and Chinese language. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were used to assess the strength of the relationships. The between-study heterogeneity was evaluated by Cochran's Q-test and the I2 index to adopt fixed- or random- effect models. Results: A total of 13 studies were eligible for inclusion. There was evidence for significant associations between APOE ε4 mutation and the risk of CAD in patients with T2DM (for ε3/ε4 vs. ε3/ε3: OR = 1.69, 95% CI = 1.38-2.08, P < 0.001; for ε4/ε4 vs. ε3/ε3: OR = 2.72, 95% CI = 1.61-4.60, P < 0.001; for ε4/ε4+ε3/ε4 vs. ε3/ε3: OR = 1.83, 95% CI = 1.52-2.22, P < 0.001; for ε4 allele vs. ε3 allele: OR = 1.64, 95% CI = 1.40-1.94, P < 0.001). In contrast, no significant associations were found in genetic model of APOE ε2 mutation (for ε2/ε2 vs. ε3/ε3: OR = 1.67, 95% CI = 0.90-3.09, P = 0.104; for ε2/ε3 vs. ε3/ε3: OR = 1.18, 95% CI = 0.93-1.51, P = 0.175; for ε2/ε2+ε2/ε3 vs. ε3/ε3: OR = 1.26, 95% CI = 0.88-1.82, P = 0.212; for ε2 allele vs. ε3 allele: OR = 1.34, 95% CI = 0.98-1.84, P = 0.07). Conclusions: The APOE gene ε4 mutation is associated with an increased risk of CAD in patients with T2DM, while the ε2 variation has null association with this disease.

SLCO1B1 Variants and Angiotensin Converting Enzyme Inhibitor (Enalapril)-Induced Cough: a Pharmacogenetic Study.

Clinical observations suggest that incidence of cough in Chinese taking angiotensin converting enzyme inhibitors is much higher than other racial groups. Cough is the most common adverse reaction of enalapril. We investigate whether SLCO1B1 genetic polymorphisms, previously reported to be important determinants of inter-individual variability in enalapril pharmacokinetics, are associated with the enalapril-induced cough. A cohort of 450 patients with essential hypertension taking 10 mg enalapril maleate were genotyped for the functional SLCO1B1 variants, 388A > G (Asn130Asp, rs2306283) and 521T > C (Val174Ala, rs4149056). The primary endpoint was cough, which was recorded when participants were bothered by cough and respiratory symptoms during enalapril treatment without an identifiable cause. SLCO1B1 521C allele conferred a 2-fold relative risk of enalapril-induced cough (95% confidence interval [CI] = 1.34-3.04, P = 6.2 × 10(-4)), and haplotype analysis suggested the relative risk of cough was 6.94-fold (95% CI = 1.30-37.07, P = 0.020) in SLCO1B1*15/*15 carriers. Furthermore, there was strong evidence for a gene-dose effect (percent with cough in those with 0, 1, or 2 copy of the 521C allele: 28.2%, 42.5%, and 71.4%, trend P = 6.6 × 10(-4)). Our study highlights, for the first time, SLCO1B1 variants are strongly associated with an increased risk of enalapril-induced cough. The findings will be useful to provide pharmacogenetic markers for enalapril treatment.

Pharmacogenomics research: a potential strategy for drug development.

Adverse drug reactions (ADR) and drug ineffectiveness are the common in clinical practice. Recent studies have indicated their strong connection to the genetic feature of patients. To further illustrate this relationship, the discipline of Pharmacogenomics (PGx) was born. At present, in vitro cell models and in vivo transgenic animal models have a large potential to study the influence of human genetic mutations on drug response. Moreover, PGx guided clinical trials also provide benefits to drug development. With the drug targets introduced by PGx, great success has been achieved in targeted therapy (eg. gefitinib, cetuximab and ado-trastuzumab). Although the progress on PGx research is fascinating, the translation of PGx into drug development is unsatisfactory. To improve this situation, a rounded system that includes individuals, medical staff, academics associations, Government and Pharmaceutics-Biotechnology Industry should be established, as well as a connected pipeline consisting of policy guidance, PGx research, genotyping technology, preclinical and clinical studies.

Pharmacogenomics and herb-drug interactions: merge of future and tradition.

The worldwide using of herb products and the increasing potential herb-drug interaction issue has raised enthusiasm on discovering the underlying mechanisms. Previous review indicated that the interactions may be mediated by metabolism enzymes and transporters in pharmacokinetic pathways. On the other hand, an increasing number of studies found that genetic variations showed some influence on herb-drug interaction effects whereas these genetic factors did not draw much attention in history. We highlight that pharmacogenomics may involve the pharmacokinetic or pharmacodynamic pathways to affect herb-drug interaction. We are here to make an updated review focused on some common herb-drug interactions in association with genetic variations, with the aim to help safe use of herbal medicines in different individuals in the clinic.

Epigenetic perspectives on cancer chemotherapy response.

Epigenetic programs are now widely recognized as being critical to the biological processes of cancer genesis. However, it has not been comprehensively understood how and to what degree they can influence anticancer drugs responses. The development of drugs targeting epigenetic regulation has generated great enthusiasm, with a growing number in clinical development. We highlight here that epigenetic modifications can be involved in the regulation of genes responsible for the absorption, distribution, metabolism and excretion of drugs and for the pathological progression of cancer, thereby affecting anticancer drug responses. The major epigenetic regulatory mechanisms are reviewed, including DNA methylation, miRNA regulation and histone modification, with the aim of promoting rational use of anticancer drugs in the clinic and epigenetic drug development.

[Epigenetic research progress of anti-tumor drugs].

Epigenetic abnormalities not only associated with carcinogenesis, they may also influence the curative effect and prognosis of anticancer drugs through modifying pharmacokinetic genes related to drug absorption, distribution, metabolism, excretion and pharmacodynamic genes related to signaling pathways and targets. That drugs through regulating epigenetic factors pocessing anti-cancer effect is becoming a research hot spot. We summarized and analyzed the realtionship of DNA methylation, miRNA, and histone modification with antitumor drug effect, aiming at promoting rational use of antitumor drugs and providing new ideas on developing epi-drugs.