Different apoptotic responses of RA synoviocytes depending on different genotypes of the mdm2 SNP T309G

Polymorphisms in the TP53-MDM2-MDM4-axis in patients with rheumatoid arthritis

BACKGROUND

In addition to being a tumour suppressor, TP53 is a suppressor of inflammation, and dysfunction of this gene has been related to autoimmune diseases. Patients with autoimmunity, such as rheumatoid arthritis (RA) have an increased risk of certain cancers, like lymphomas, indicating that some underlying mechanisms may modulate risk of both cancers and autoimmunity.

METHODS

We genotyped 5 common genetic variants in TP53 and its main regulators MDM2 and MDM4 in a sample of 942 RA patients and 3,747 healthy controls, and mined previously published GWAS-data, to assess the potential impact of these variants on risk of RA.

RESULTS

For the TP53 Arg72Pro polymorphism (rs1042522), MDM4 SNP34091 (rs4245739) and MDM2 SNP285C (rs117039649), we found no association to risk of RA. For MDM2 SNP309 (rs2279744), the minor G-allele was associated with a reduced risk of RA (OR: 0.87; CI: 0.79-0.97). This association was also seen in genotype models (OR: 0.86; CI: 0.74-0.99 and OR: 0.79; CI 0.63-0.99; dominant and recessive model, respectively), but was not validated in a large GWAS data set. For MDM2 del1518 (rs3730485), the minor del-allele was associated with an increased risk of RA in the dominant model (OR: 1.18; CI: 1.02-1.38). Stratifying RA cases and controls into phylogenetic subgroups according to the combined genotypes of all three MDM2 polymorphism, we found individuals with the del158-285-309 genotype del/ins-G/G-T/T to have an increased risk of RA as compared to those with the ins/ins-G/G-G/G genotype (OR: 1.56; CI: 1.18-2.06) indicating opposite effects of the del1518 del-allele and the SNP309 G-allele.

CONCLUSION

We find a potential association between the MDM2 del1518 variant and RA, and indications that combinatorial genotypes and haplotypes in the MDM2 locus may be related to RA.

Screening of differentially expressed genes associated with non-union skeletal fractures and analysis with a DNA microarray

The purpose of this study was to identify the feature genes that are associated with non-union skeletal fractures using samples of normal union and non-union skeletal fracture microarray data. The gene expression profile GSE494 was downloaded from the Gene Expression Omnibus database and included 12 samples based on three different platforms (GPL92, GPL93 and GPL8300). Each of the platforms had four sets of expression data, two from normal union skeletal fracture samples and two from non-union skeletal fracture samples. The differentially expressed genes within the three platforms of expression data were identified using packages in R language and the differentially expressed genes common to the three platforms were selected. The selected common differentially expressed genes were further analyzed using bioinformatic methods. The software HitPredict was used to search interactions of the common differentially expressed genes and then FuncAssociate was used to conduct a functional analysis of the genes in the interaction network. Further, the associated pathways were identified using the software WebGestalt. Under the three different platforms, GPL92, GPL93 and GPL8300, the numbers of differentially expressed genes identified were 531, 418 and 914, respectively. The common gene CLU and its interacting genes were most significantly associated with the regulation of sterol transport and the osteoclast differentiation pathway. Upregulation of the gene CLU was identified by comparing data for normal union and non-union skeletal fracture samples. According to the function of CLU and its interacting genes, it was concluded that they inhibit the normal healing process following a fracture, and result in non-union skeletal fractures through the regulation of sterol transport and the pathways of differentiation in osteoclasts.