The analysis of <i>GSTA1</i> promoter genetic and functional diversity of human populations

GSTA1 encodes a member of a family of enzymes that function to add glutathione to target electrophilic compounds, including carcinogens, therapeutic drugs, environmental toxins, and products of oxidative stress. GSTA1 has several functional SNPs within its promoter region that are responsible for a change in its expression by altering promoter function. This study aims to investigate distributions of GSTA1 promoter haplotypes across different human populations and to assess their impact on the expression of GSTA1. PHASE 2.1.1 was used to infer haplotypes and diplotypes of six GSTA1 promoter SNPs on 2501 individuals from 26 populations classified by the 1000 Genomes Project into five super-populations that included Africa (N = 660), America (N = 347), East Asia (N = 504), Europe (N = 502), and South Asia (N = 488). We used pairwise FST analysis to compare sub-populations and luciferase reporter assay (LRA) to evaluate the impact of each SNP on activation of transcription and interaction with other SNPs. The distributions of GSTA1 promoter haplotypes and diplotypes were significantly different among the different human populations. Three new promoter haplotypes were found in the African super-population. LRA demonstrated that SNPs at -52 and -69 has the most impact on GSTA1 expression, however other SNPs have a significant impact on transcriptional activity. Based on LRA, a new model of cis-elements interaction is presented. Due to the significant differences in GSTA1 diplotype population frequencies, future pharmacogenomics or disease-related studies would benefit from the inclusion of the complete GSTA1 promoter haplotype based on the newly proposed metabolic grouping derived from the LRA results

Precision dosing of intravenous busulfan in pediatric hematopoietic stem cell transplantation: Results from a multicenter population pharmacokinetic study

Busulfan (Bu) is a common component of conditioning regimens before hematopoietic stem cell transplantation (HSCT) and is known for high interpatient pharmacokinetic (PK) variability. This study aimed to develop and externally validate a multicentric, population PK (PopPK) model for intravenous Bu in pediatric patients before HSCT to first study the influence of glutathione-s-transferase A1 (GSTA1) polymorphisms on Bu's PK in a large multicentric pediatric population while accounting for fludarabine (Flu) coadministration and, second, to establish an individualized, model-based, first-dose recommendation for intravenous Bu that can be widely used in pediatric patients. The model was built using data from 302 patients from five transplantation centers who received a Bu-based conditioning regimen. External model validation used data from 100 patients. The relationship between body weight and Bu clearance (CL) was best described by an age-dependent allometric scaling of a body weight model. A stepwise covariate analysis identified Day 1 of Bu conditioning, GSTA1 metabolic groups based on GSTA1 polymorphisms, and Flu coadministration as significant covariates influencing Bu CL. The final model adequately predicted Bu first-dose CL in the external cohort, with 81% of predicted area under the curves within the therapeutic window. The final model showed minimal bias (mean prediction error, -0.5%; 95% confidence interval [CI], -3.1% to 2.0%) and acceptable precision (mean absolute prediction error percentage, 18.7%; 95% CI, 17.0%-20.5%) in Bu CL prediction for dosing. This multicentric PopPK study confirmed the influence of GSTA1 polymorphisms and Flu coadministration on Bu CL. The developed model accurately predicted Bu CL and first doses in an external cohort of pediatric patients

Using Cell Membranes as Recognition Layers to Construct Ultrasensitive and Selective Bioelectronic Affinity Sensors

Conventional sandwich immunosensors rely on antibody recognition layers to selectively capture and detect target antigen analytes. However, the fabrication of these traditional affinity sensors is typically associated with lengthy and multistep surface modifications of electrodes and faces the challenge of nonspecific adsorption from complex sample matrices. Here, we report on a unique design of bioelectronic affinity sensors by using natural cell membranes as recognition layers for protein detection and prevention of biofouling. Specifically, we employ the human macrophage (MΦ) membrane together with the human red blood cell (RBC) membrane to coat electrochemical transducers through a one-step process. The natural protein receptors on the MΦ membrane are used to capture target antigens, while the RBC membrane effectively prevents nonspecific surface binding. In an attempt to detect tumor necrosis factor alpha (TNF-α) cytokine using the bioelectronic affinity sensor, it demonstrates a remarkable limit of detection of 150 pM. This new sensor design integrates natural cell membranes and electronic transduction, which offers synergistic functionalities toward a broad range of biosensing applications