P-glycoprotein gene MDR1 polymorphisms and susceptibility to systemic lupus erythematosus in Guangxi population: a case-control study

Pharmacogenetic Approach for the Prevention of Rivaroxaban's ADRs: A Systematic Review and Meta-Analysis

Introduction

Pharmacogenetics is a potential approach that can be applied to decline the burden of rivaroxaban's ADRs. The current systematic review and meta-analysis aim to identify genetic variants correlated with rivaroxaban exposure and evaluate their importance.

Methods

We systematically searched PubMed, Web of Science, and Scopus databases for all observational and interventional studies. The fixed effect method was used to pool the data when the Q-test's p value was higher than 0.1. We used random models when the p value was less than 0.1.

Results

Data from ten studies (4721 participants) were analyzed in the current review. Qualitative synthesis from included studies found that two variants of ABCB1 (rs1045642 and rs2032582) and one variant of APOB (rs13306198) are potential contributors to rivaroxaban concentrations. Both wild homozygotes (AA) and heterozygotes (AC) of rs1045642 have significantly lower rivaroxaban concentrations compared to mutated homozygotes (CC) (SMD = 0.516, 95% CI: 0.115 to 0.917; SMD = 0.772, 95% CI: 0.088 to 1.455, respectively). Nevertheless, pooling unadjusted odds ratios did not yield a statistically significant correlation between rivaroxaban ADRs and genetic mutations.

Conclusion

This study revealed that being an AC or CC for rs1045642 is attributed to a considerably higher rivaroxaban level in participants using rivaroxaban. That is to say, rs1045642 is a remarkable predictor of rivaroxaban metabolism. We concluded that identifying rs1045642 before drug administration might decrease ADRs although further studies adjusted for potential confounders are strongly suggested.

Research advances in the role and pharmaceuticals of ATP-binding cassette transporters in autoimmune diseases

Autoimmune diseases are caused by the immune response of the body to its antigens, resulting in tissue damage. The pathogenesis of these diseases has not yet been elucidated. Most autoimmune diseases cannot be cured by effective drugs. The treatment strategy is to relieve the symptoms of the disease and balance the body's autoimmune function. The abnormal expression of ATP-binding cassette (ABC) transporters is directly related to the pathogenesis of autoimmune diseases and drug therapy resistance, which poses a great challenge for the drug therapy of autoimmune diseases. Therefore, this paper reviews the interplay between ABC transporters and the pathogenesis of autoimmune diseases to provide research progress and new ideas for the development of drugs in autoimmune diseases.

Impact of IL-10 gene polymorphisms and its interaction with environment on susceptibility to systemic lupus erythematosus

This study aims to explore the impact of interleukin (IL)-10 single nucleotide polymorphisms (SNPs) and its interaction with environment on the risk of systemic lupus erythematosus (SLE). Chi-square testing method was used to investigate whether the distributions for genotype of four SNPs were differed from Hardy-Weinberg equilibrium (HWE). Logistic regression was used to test the association between IL-10 SNPs and SLE risk. The best interaction combinations between IL-10 SNPs and environmental factors were assessed by generalized multifactor dimensionality reduction (GMDR). Both rs1800896-G and rs1800871-T alleles were associated with increased risk of SLE, the odds ratios (ORs) (95% confidence interval (CI)) for the two SNPs were 1.68 (1.25-2.09) and 1.47 (1.12-1.94), respectively. Then, we used the GMDR method to analyze the high-order interactions of four SNPs within IL-10 gene and environmental factors on SLE risk. We found a significant interaction combination (two-locus model with P = 0.001) between rs1800896 and smoking, after adjusting for gender, age, body mass index (BMI), and alcohol drinking. We also used two-variable stratified analysis by logistic regression to analyze the synergistic effect between two variables (rs1800896 and smoking), which had significant significance in GMDR model. We found that current smokers with rs1800896-AG or GG genotype have the highest SLE risk, compared with never smokers with the rs1800896-AA genotype, OR (95% CI) = 2.24 (1.52-3.58). The rs1800896-G and rs1800871-T alleles and interaction between rs1800896 and current smoking were all associated with increased risk of SLE.

Dysregulation of Signaling Pathways Due to Differentially Expressed Genes From the B-Cell Transcriptomes of Systemic Lupus Erythematosus Patients - A Bioinformatics Approach

Systemic lupus erythematosus (SLE) is an autoimmune inflammatory disorder that is clinically complex and has increased production of autoantibodies. Via emerging technologies, researchers have identified genetic variants, expression profiling of genes, animal models, and epigenetic findings that have paved the way for a better understanding of the molecular and genetic mechanisms of SLE. Our current study aimed to illustrate the essential genes and molecular pathways that are potentially involved in the pathogenesis of SLE. This study incorporates the gene expression profiling data of the microarray dataset GSE30153 from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) between the B-cell transcriptomes of SLE patients and healthy controls were screened using the GEO2R web tool. The identified DEGs were subjected to STRING analysis and Cytoscape to explore the protein-protein interaction (PPI) networks between them. The MCODE (Molecular Complex Detection) plugin of Cytoscape was used to screen the cluster subnetworks that are highly interlinked between the DEGs. Subsequently, the clustered DEGs were subjected to functional annotation with ClueGO/CluePedia to identify the significant pathways that were enriched. For integrative analysis, we used GeneGo MetacoreTM, a Cortellis Solution software, to exhibit the Gene Ontology (GO) and enriched pathways between the datasets. Our study identified 4 upregulated and 13 downregulated genes. Analysis of GO and functional enrichment using ClueGO revealed the pathways that were statistically significant, including pathways involving T-cell costimulation, lymphocyte costimulation, negative regulation of vascular permeability, and B-cell receptor signaling. The DEGs were mainly enriched in metabolic networks such as the phosphatidylinositol-3,4,5-triphosphate pathway and the carnitine pathway. Additionally, potentially enriched pathways, such as the signaling pathways induced by oxidative stress and reactive oxygen species (ROS), chemotaxis and lysophosphatidic acid signaling induced via G protein-coupled receptors (GPCRs), and the androgen receptor activation pathway, were identified from the DEGs that were mainly associated with the immune system. Four genes (EGR1, CD38, CAV1, and AKT1) were identified to be strongly associated with SLE. Our integrative analysis using a multitude of bioinformatics tools might promote an understanding of the dysregulated pathways that are associated with SLE development and progression. The four DEGs in SLE patients might shed light on the pathogenesis of SLE and might serve as potential biomarkers in early diagnosis and as therapeutic targets for SLE.

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus

DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein-protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG-I-like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll-like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2′-5′-oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin-like modifier, DExD/H-box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2′-5′-oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG-I-like receptor signaling, cytosolic DNA-sensing, toll-like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited significant co-expressed tendency in multi-experiment microarray datasets (P<0.01). In conclusion, these key genes and cellular pathways may improve the current understanding of the underlying mechanism of development of SLE. These key genes may be potential biomarkers of diagnosis, therapy and prognosis for SLE.

Genotype and haplotype analysis of ABCB1 at 1236, 2677 and 3435 among systemic sclerosis patients

Systemic sclerosis (SSc) belongs to the group of systemic diseases of the connective tissue, which are characterized by a chronic autoimmune inflammatory process. P-glycoprotein, initially associated with the drug resistance in patients with cancer, becomes more and more often a subject of considerations in terms of its significance in the development of illnesses, including autoimmune diseases. The aim of the study was an attempt to answer the question whether there was a relationship between ABCB1 polymorphisms and morbidity of systemic sclerosis in a Polish population. The study was carried out in 61 patients with SSc and 100 healthy volunteers. Determination of polymorphisms C1236T and C3435T in ABCB1 was carried out with the PCR-RFLP (polymerase chain reaction - restriction fragment length polymorphism) method. The G2677T/A ABCB1 polymorphism was analysed with the allele-specific PCR method. No statistically significant differences were observed in the frequencies of ABCB1 genotypes and alleles between SSc patients and the control group. It was observed that haplotype 1236 C-2677 G-3435 T occurred in the group of patients with SSc statistically more frequently than in the group of healthy volunteers (25% vs. 15%; p = .032). Carriers of the haplotype demonstrated almost a twofold greater risk of SSc (OR = 1.85; p = .032). No statistically significant correlations for the other nine haplotypes were found. Presented results concerning the relationship of ABCB1 polymorphisms with susceptibility to systemic sclerosis are the first ones that were obtained in a Polish population. They imply that single nucleotide polymorphisms do not affect the risk for SSc, but the 1236 C-2677 G-3435 T haplotype might increase this risk.