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INTRODUCTION:The aim of the study was to analyse genetic architecture of RA by utilizing multiparametric statistical methods such as linear discriminant analysis (LDA) and redundancy analysis (RDA). METHODS:A total of 1393 volunteers, 499 patients with RA and 894 healthy controls were included in the study. The presence of shared epitope (SE) in HLA-DRB1 and 11 SNPs (PTPN22 C/T (rs2476601), STAT4 G/T (rs7574865), CTLA4 A/G (rs3087243), TRAF1/C5 A/G (rs3761847), IRF5 T/C (rs10488631), TNFAIP3 C/T (rs5029937), AFF3 A/T (rs11676922), PADI4 C/T (rs2240340), CD28 T/C (rs1980422), CSK G/A (rs34933034) and FCGR3A A/C (rs396991), rheumatoid factor (RF), anti-citrullinated protein antibodies (ACPA) and clinical status was analysed using the LDA and RDA. RESULTS:HLA-DRB1, PTPN22, STAT4, IRF5 and PADI4 significantly discriminated between RA patients and healthy controls in LDA. The correlation between RA diagnosis and the explanatory variables in the model was 0.328 (Trace = 0.107; F = 13.715; P = 0.0002). The risk variants of IRF5 and CD28 genes were found to be common determinants for seropositivity in RDA, while positivity of RF alone was associated with the CTLA4 risk variant in heterozygous form. The correlation between serologic status and genetic determinants on the 1st ordinal axis was 0.468, and 0.145 on the 2nd one (Trace = 0.179; F = 6.135; P = 0.001). The risk alleles in AFF3 gene together with the presence of ACPA were associated with higher clinical severity of RA. CONCLUSIONS:The association among multiple risk variants related to T cell receptor signalling with seropositivity may play an important role in distinct clinical phenotypes of RA. Our study demonstrates that multiparametric analyses represent a powerful tool for investigation of mutual relationships of potential risk factors in complex diseases such as RA.

A glycolytic profile unifies a group of pheochromocytomas and paragangliomas (PHEOs/PGLs) with distinct underlying gene defects, including von Hippel-Lindau (VHL) and succinate dehydrogenase B (SDHB) mutations. Nevertheless, their tumor aggressiveness is distinct: PHEOs/PGLs metastasize rarely in VHL-, but frequently in SDHB-patients. To date, the molecular mechanisms causing the more aggressive phenotype in SDHB-PHEOs/PGLs remain largely unknown. Recently, however, an excellent model to study aggressive PHEOs (mouse tumor tissue (MTT) cells) has been developed from mouse PHEO cells (MPC). We employed this model for a proteomics based approach to identify changes characteristic for tumor aggressiveness, which we then explored in a homogeneous set of human SDHB- and VHL-PHEOs/PGLs. The increase of glucose transporter 1 in VHL, and of hexokinase 2 in VHL and SDHB, confirmed their glycolytic profile. In agreement with the cell model and in support of decoupling of glycolysis, the Krebs cycle and oxidative phosphorylation (OXPHOS), SDHB tumors showed increased lactate dehydrogenase levels. In SDHB-PGLs OXPHOS complex activity was increased at complex III and, as expected, decreased at complex II. Moreover, protein and mRNA expression of all tested OXPHOS-related genes were higher in SDHB- than in VHL-derived tumors. Although there was no direct evidence for increased reactive oxygen species production, elevated superoxide dismutase 2 expression may reflect elevated oxidative stress in SDHB-derived PHEOs/PGLs. For the first time, we show that despite dysfunction in complex II and evidence for a glycolytic phenotype, the Warburg effect does not seem to fully apply to SDHB-PHEOs/PGLs with respect to decreased OXPHOS. In addition, we present evidence for increased LDHA and SOD2 expression in SDHB-PHEOs/PGLs, proteins that have been proposed as promising therapeutic targets in other cancers. This study provides new insight into pathogenic mechanisms in aggressive human PHEOs/PGLs, which may lead to identifying new diagnostic and prognostic markers in the near future.