The Variant at TGFBRAP1 but Not TGFBR2 Is Associated with Antituberculosis Drug-Induced Liver Injury

Combined electronic medical records and gene polymorphism characteristics to establish an anti-tuberculosis drug-induced hepatic injury (ATDH) prediction model and evaluate the prediction value

BACKGROUND

Anti-tuberculosis drug-induced hepatic injury (ATDH) lacks specific diagnostic markers. The characteristics of gene polymorphisms have been preliminarily used for the risk classification of ATDH, and the activation of Pregnane X receptor/aminole-vulinic synthase-1/forkhead box O1 (PXR/ALAS1/FOXO1) axis is closely related to ATDH. Therefore, we consider combining general clinical features of the electronic medical record, laboratory indications, and genetic features of key genes in this axis for predictive model construction to help early clinical diagnosis and treatment.

METHODS

The general characteristics derived from the Hospital Information System (HIS) medical record system, the biochemical tests and hematology tests were detected by Roche automatic biochemical immunoassay analyzer cobas8000 and Sysmex automatic hemocytometer XE2100. The single nucleotide polymorphisms (SNPs) genotyping work was conducted with a custom-designed 48-plex SNP scan® TM Kit. A total of 746 cases were included which were divided into training set and validation set according to the ratio of 3:2 randomly. Taking the occurrence of confirmed ATDH as the outcome variable, lasso regression and logistic regression were used to identify the predictors preliminarily. alanine aminotransferase, aspartate aminotransferase, monocyte, uric acid, albumin, fever, the polymorphisms of rs4435111 (FOXO1) and rs3814055 (PXR) were chosen from all variables to combine the predictive model. The goodness of fit, predictive efficacy, discrimination, and consistency, and clinical decision curve analysis was used to assess the clinical applicability of the models.

RESULTS

The best model had a discriminant efficacy C-index of 0.8164, a sensitivity of 34.25%, specificity of 97.99%, a positive predictive value of 78.13% and negative predictive value of 87.69%, the two-tailed value of Spiegelhalter Z test of consistency test S:P =0.896, maximum absolute difference Emax =0.147, and average absolute difference Eave =0.017. In the validation set, performance was close. The clinical decision curve showed the clinical applicability of the prediction model when the prediction risk threshold was between 0.1 and 0.8.

CONCLUSIONS

The ATDH prediction model was constructed using a machine learning approach, combining general characteristics of the study population, laboratory indications, and SNP features of PXR and FOXO1 genes with good fit and certain predictive value, and has potential and value for clinical application.

Identification of key biomarkers and signaling pathways and analysis of their association with immune cells in immunoglobulin A nephropathy

Introduction

Immunoglobulin A nephropathy (IgAN) is the most common glomerular disease worldwide, with a poor prognosis. The aim of our study was to identify key biomarkers and their associations with immune cells to aid in the study of IgAN pathology and immunotherapy.

Material and methods

The data of IgAN were downloaded from a public database. The metaMA package and limma package were used to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs), respectively. Biological functions of the DEmRNAs were analyzed. Machine learning was used to screen the mRNA biomarkers of IgAN. Pearson's correlation coefficient was used to analyze the correlation between mRNA biomarkers, immune cells and signaling pathways. Moreover, we constructed a miRNAs-mRNAs targeted regulatory network. Finally, we performed in vitro validation of the identified miRNAs and mRNAs.

Results

1205 DEmRNAs and 125 DEmiRNAs were identified. In gene set enrichment analysis (GSEA), tumor necrosis factor α (TNF-α) signaling via nuclear factor κB (NF-κB), apoptosis and MTORC-1 signaling were inhibited in IgAN. 8 mRNA biomarkers were screened by machine learning. In addition, the distribution of 8 immune cell types was found to be significantly different between normal controls and IgAN by difference analysis. Pearson correlation coefficient analysis demonstrated that AKAP8L was significantly negatively correlated with CD4⁺ memory T-cells. AKAP8L was also significantly negatively correlated with TNF-α signaling via NF-κB, apoptosis, and MTORC-1 signaling. Subsequently, 5 mRNA biomarkers predicted corresponding negative regulatory miRNAs.

Conclusions

The identification of 8 important biomarkers and their correlation with immune cells and biological signaling pathways provides new ideas for further study of IgAN.

Genetic and Functional Evaluation of the Role of FOXO1 in Antituberculosis Drug-Induced Hepatotoxicity

Background

The accumulation of the hepatotoxic substance protoporphyrin IX (PPIX) induced by aminolevulinate synthase 1 (ALAS1) activation is one of the important mechanisms of antituberculosis drug-induced hepatotoxicity (ATDH). Forkhead box protein O1 (FOXO1) may activate ALAS1 transcription. However, little is known about their roles in ATDH; we performed a study to determine the association between polymorphisms in the two genes and ATDH susceptibility. Then, we verified this possible association by cellular functional experiments.

Materials and Methods

Tag single-nucleotide polymorphisms (TagSNPs) in the two genes were genotyped in 746 tuberculosis patients. The frequencies of the alleles, genotypes, genetic models, and haplotype distribution of the variants were compared between the case and control groups. L-02 cells and HepG2 cells were incubated with the indicated concentration of isoniazid (INH) and rifampicin (RIF) for the desired times, and then the expression levels of ALAS1 and FOXO1 mRNAs and proteins were detected. HepG2 cells were transiently transfected with FOXO1 siRNA to observe the effect of changes in the FOXO1 expression on the cell survival rate and ALAS1 expression.

Results

The C allele at rs2755237 and the T allele at rs4435111 in the FOXO1 gene were associated with a decreased risk of ATDH. The expression of ALAS1 in both L-02 cells and HepG2 cells was increased by the coadministration of INH/RIF (600/200 μM) for 24 h. Although FOXO1 expression was reduced slightly by the same treatment, its content in the nucleus was significantly increased. However, the cell survival rate and ALAS1 expression level were not significantly altered by the downregulation of FOXO1 in HepG2 cells.

Conclusions

Variants of the rs4435111 and rs2755237 loci in the FOXO1 gene were associated with susceptibility to ATDH. Coadministration of INH/RIF promoted the transfer of FOXO1 from the cytoplasm to the nucleus, but the functional significance of its nuclear translocation requires further verification.

The effects of FAR1 and TGFBRAP1 on the proliferation and apoptosis of follicular granulosa cells in goose (Anser cygnoides)

The low laying performance of geese seriously damages the growth of the poultry industry, and is related to the development of pre- hierarchical follicles. Our previous studies have revealed that FAR1 and TGFBRAP1 were involved in follicular development, but the exact regulation mechanism still kept unclear. In recent studies, the expression of FAR1 and TGFBRAP1 mRNA were detected, and we found that their expression levels were relatively higher in hierarchical follicles than in pre-hierarchical follicles (P < 0.05). Moreover, generally the level of FAR1 and TGFBRAP1 mRNA gradually increased in hierarchical follicles. In addition, the proliferation and apoptosis of granulosa cells were assayed with overexpression or knockdown technology. The results showed that by the knockdown of FAR1 mRNA level, the proliferation rate of follicular granulosa cells increased significantly, the apoptosis rate decreased (P < 0.05), and the apoptosis rate also reduced obviously by transfecting TGFBRAP1-siRNA (P < 0.05). Finally, the overexpression of FAR1 or TGFBRAP1 resulted in the inhabitation to the secretion of E2 and P4 in granulosa cells, while the knockdown of FAR1 or TGFBRAP1 enhanced the secretion of E2 and P4. In conclusion, the results indicated that FAR1 and TGFBRAP1 regulated the apoptosis of follicular granulosa cells and cut the secretion of E2 and P4 in geese, which provided basic data for the understanding of the regulating process of goose reproduction.