Association between TGFB1 genetic polymorphisms and chronic allograft dysfunction: a systematic review and meta-analysis

Bioinformatics analysis and experimental validation of key genes associated with lumbar disc degeneration and biomechanics

Background

Lumbar disc degeneration (LDD) is an important pathological basis for the development of degenerative diseases of the lumbar spine. Most clinical patients have low back pain as their main symptom. The deterioration of the biomechanical environment is an important cause of LDD. Although there is a large amount of basic research on LDD, there are fewer reports that correlate biomechanical mechanisms with basic research. Our research aims to identify 304 key genes involved in LDD due to biomechanical deterioration, using a bioinformatics approach. We focus on SMAD3, CAV1, SMAD7, TGFB1 as hub genes, and screen for 30 potential target drugs, offering novel insights into LDD pathology and treatment options.

Methods

The Gene Cards, GenCLip3, OMIM and Drugbank databases were explored to obtain genes associated with biomechanics and LDD, followed by making veen plots to obtain both co-expressed genes. GO enrichment analysis and KEGG pathway analysis of the co-expressed genes were obtained using the DAVID online platform and visualised via a free online website. Protein interaction networks (PPI) were obtained through the STRING platform and visualised through Cytoscape 3.9.0. These genes were predicted for downstream interaction networks using the STITCH platform. Then, the GSE56081 dataset was used to validate the key genes. RT-PCR was used to detect mRNA expression of core genes in the degenerated nucleus pulposus (NP) samples and western bolt was used for protein expression. Lastly, the obtained hub genes were searched in the drug database (DGIdb) to find relevant drug candidates.

Results

From the perspective of biomechanics-induced LDD, we obtained a total of 304 genes, the GO functional enrichment and KEGG pathway enrichment analysis showed that the functions of these genes are mostly related to inflammation and apoptosis. The PPI network was constructed and four Hub genes were obtained through the plug-in of Cytoscape software, namely SMAD3, CAV1, SMAD7 and TGFB1. The analysis of key genes revealed that biomechanical involvement in LDD may be related to the TGF-β signaling pathway. Validation of the GSE56081 dataset revealed that SMAD3 and TGFB1 were highly expressed in degenerating NP samples. RT-PCR results showed that the mRNA expression of SMAD3 and TGFB1 was significantly increased in the severe degeneration group; Western blot results also showed that the protein expression of TGFB1 and P-SMAD3 was significantly increased. In addition, we identified 30 potential drugs.

Conclusion

This study presented a new approach to investigate the correlation between biomechanical mechanisms and LDD. The deterioration of the biomechanical environment may cause LDD through the TGF-β signaling pathway. TGFB1 and SMAD3 are important core targets. The important genes, pathways and drugs obtained in this study provided a new basis and direction for the study, diagnosis and treatment of LDD.

Analysis of the Association between the Tgfb1 Gene Haplotype and Liver Diseases in Children

Transforming growth factor-β1 (TGF-β1), a cytokine with immunosuppressive and pro-fibrogenic activity, is a potential marker of infection, liver transplant rejection, and fibrosis. Its levels in the blood and tissues depend on many factors; however, the role of gene polymorphism is still unclear. In this work, the distribution frequency of three single nucleotide polymorphism (SNP) variants of the Tgfb1 gene, namely rs1800469, rs1800470, and rs1800471, was studied in children with end-stage liver disease (ESLD). The study included 225 pediatric liver recipients aged 1 month to 16 years (median, 8 months), including 100 boys and 125 girls, and 198 healthy individuals aged 32.7 ± 9.6 years, including 78 men and 120 women. The indication for liver transplantation in children was ESLD, which was mostly caused by congenital and inherited liver diseases. SNPs were detected by real-time polymerase chain reaction using TaqMan probes and DNA isolated from peripheral blood. SNP frequency distribution was in Hardy-Weinberg equilibrium and did not differ between children with liver diseases and the healthy ones. Analysis of the SNPs frequency based on allelic interaction models did not reveal any differences between patients and the healthy individuals. Evaluation of linkage disequilibrium for Tgfb1 polymorphic variant pairs revealed a statistically significant linkage between all studied variants. Seven haplotypes, which are variants of SNP combinations, were observed in the studied groups of patients and healthy individuals. A total of 80% of the group had three haplotypes, whose frequencies did not differ between patients and the healthy individuals. Significant differences were found in the frequency of the haplotypes A-A-C, G-G-C, and G-A-G (at rs1800469, rs1800470, and rs1800471, respectively), which were observed up to 11 times more often in recipients compared to the healthy individuals. It is possible that these haplotypes are ESLD-predisposing variants, which may also contribute to the development of complications after liver transplantation in children.

The rs1800470 Polymorphism of the TGFB1 Gene Is Associated with Myocardial Fibrosis in Heart Transplant Recipients

The transforming growth factor β1 (TGFβ1), whose level may depend on the polymorphism of the TGFB1 gene, is involved in the formation of myocardial fibrosis. Myocardial fibrosis in a cardiac allograft may lead to a heart's structural and functional remodeling and subsequent dysfunction. The frequency of occurrence of alleles and genotypes of the TGFB1 gene polymorphic regions rs1800469, rs1800470, and rs1800471 in heart transplant recipients and their association with graft myocardial fibrosis were analyzed. Carriers of the CC genotype (p = 0.023, OR = 0.12, 95% CI: 0.017-1.0), and more often the G allele of rs1800471 (p = 0.023, OR = 7.76, 95% CI: 1.0-60.20), were found among heart transplant recipients less frequently than among healthy individuals. In patients with ischemic heart disease (IHD), the GG genotype was less common (p = 0.035, OR = 2.68, 95% CI: 1.061-6.793), while the A allele of rs1800469 was found more frequently (p = 0.035, OR = 0.37 95% CI: 0.148-0.942) than in patients with dilated cardiomyopathy (DCM). In heart transplant recipients with the AA genotype of rs1800470, myocardial fibrosis, verified by endomyocardial biopsy, was detected more often than in carriers of the G allele (OR = 10.4, 95% CI: 1.152-94.538, p = 0.013). The revealed differences suggest a relationship between TGFB1 gene polymorphism and graft myocardial fibrosis. Studies on a larger group of patients would make it possible to characterize the influence of genetic factors on the formation of myocardial fibrosis in heart transplant recipients.

Genetic Polymorphism in Cytokines and Costimulatory Molecules in Stem Cell and Solid Organ Transplantation

There is growing evidence supporting the genetic variability outside of HLA system that is contributing to the variation in transplant outcomes. Determining novel predictors could help to identify patients at risk and tailor their immunosuppressive regimens. This article discusses the various single nucleotide polymorphisms in costimulatory molecules and cytokines that have been evaluated for their effect on transplantation. An overview of how gene polymorphism studies are conducted and factors to consider in the experimental design to ensure meaningful data can be concluded are discussed.

Biomarkers and Pharmacogenomics in Kidney Transplantation

This review is focused on present and future biomarkers, along with pharmacogenomics used in clinical practice for kidney transplantation. It aims to highlight biomarkers that could potentially be used to improve kidney transplant early and long-term graft survival, but also potentially patient co-morbidity. Future directions for improving outcomes are discussed, which include immune tolerance and personalising immunosuppression regimens.