There are limited data regarding glucose metabolism dysregulation in multiple sclerosis (MS). Present study investigates glucose and insulin response during oral glucose tolerance test (oGTT) in MS patients. We examined 19 MS patients and 19 age, sex and body mass index (BMI) matched healthy controls. MS patients were newly diagnosed, untreated and with low Expanded Disability Status Scale (EDSS) score (1.1 ± 0.7). Plasma glucose, lactate, insulin and GLP-1 during oGTT, and fasting adipokines, lipid and inflammatory parameters were analyzed. Insulin sensitivity indices (ISI) were calculated. MS patients had comparable fasting (5.2 ± 0.3 vs. 5.0 ± 0.4 mmol/l, p = 0.05) and post-load glucose concentrations as controls. Insulin response to oral glucose load in MS was increased (p = 0.022). Insulin sensitivity was lower in MS compared to controls [ISI(Matsuda) 6.95 ± 3.44 vs. 10.60 ± 4.81, p = 0.011 and ISI(Cederholm) 49.9 ± 15.3 vs. 61.3 ± 16.3, p = 0.032]. We did not find any difference in lactate, GLP-1, total, HDL and LDL cholesterol, triglycerides, interleukin 6, tumor necrosis factor, C-reactive protein, resistin, leptin, adiponectin levels between groups. We found decreased insulin sensitivity with postprandial hyperinsulinemia in MS patients, which seems not to be related to chronic inflammation or physical inactivity. The role of hyperinsulinemia in CNS function impairment should be further investigated.

Present study was aimed to investigate sympathetic responses to mental stress with hypothesis that the presence of obesity in patients with hypertension has a modifying effect. Young male subjects, 8 with hypertension grade I, with BMI25 kg/m2 (HT), 10 with hypertension grade I, and BMI30 kg/m2 (HT OB), 14 healthy controls with BMI30 kg/m2 (OB), and 13 healthy controls with BMI25 kg/m2 (C) underwent the Stroop test. ECG was recorded continuously to evaluate heart rate variability (HRV). Blood pressure (BP) and catecholamine concentrations were measured at baseline, at the end of mental stress test and 15 min thereafter. Patients with HT demonstrated increased adrenaline concentrations and enhanced stress-induced noradrenaline release compared to that in healthy controls. In obese subjects, stress-induced increase of systolicBP was lower compared to lean individuals. Stress exposure induced a significant rise in the low frequency power component of HRV, however the increase was lower in the HT OB group compared to C. Obesity in patients with hypertension did not lead to a different reaction in comparison with lean hypertensive subjects. The present data demonstrate higher sympathoadrenal activity in early-stage of hypertension. Obesity is connected with higher resting systolicBP and modifies the HRV response to mental stress.

IntroductionThe 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).MethodsA 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.ResultsHLA-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.ConclusionsThe 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.

Background Lower levels of dehydroepiandrosterone sulphate (DHEAS) were found in chronic inflammatory diseases such as rheumatoid arthritis (RA), however, mechanisms for this decrease remains unclear. Recently, several genes has been found to be associated with lower DHEAS levels [1]. Objectives The aim of our study was to analyze frequency of selected single nucleotide polymorphisms (SNPs) known to be associated with low DHEAS in RA patients and their impact on DHEAS levels during disease. Methods 1034 participants (438 RA, 596 controls) were analyzed for SNPs in genes ZKSCAN5 (rs11761528), SULT2A1 (rs2637125), HHEX (rs2497306) and ARPC1A (rs740160) by real-time PCR genotyping assay. Serum DHEAS concentration was measured in 156 RA patients and 102 healthy controls by ELISA. Results RA patients had significantly lower DHEAS than controls (age-adjusted), in female (p<0.001) as well as in male subgroup (p=0.013). The frequency of DHEAS-related SNPs were similar in RA and control groups. In RA female patients linear regression model adjusted for age and glucocorticoid treatment, showed significant effect of risk alleles in SULT2A1 (p<0.05) and HHEX (p<0.05) genes to lowering serum DHEAS levels. Conclusions Complex interactions exist between DHEAS-associated genotypes and adrenal androgen hypofunction in RA suggesting a significant contribution to adrenal androgen hypofunction in RA. References Zhai G et al. Eight common genetic variants associated with serum DHEAS levels suggest a key role in ageing mechanisms. PLoS Genet. 2011; 7(4):e1002025. Acknowledgements Study was supported by VEGA 2/0018/12 Disclosure of Interest : None declared DOI 10.1136/annrheumdis-2014-eular.5779