The OMERACT core domain set for outcome measures for clinical trials in polymyalgia rheumatica

Objective. To inform development of a core domain set for outcome measures for clinical trials in polymyalgia rheumatica (PMR), we conducted patient consultations, a systematic review, a Delphi study, and 2 qualitative studies. Methods. Domains identified by 70% or more of physicians and/or patients in the Delphi study were selected. The conceptual framework derived from the 2 qualitative research studies helped inform the meaning of each domain and its relationship to the others. The draft core domain set was refined by further discussion with patients and physicians who had participated in the Delphi study. At the Outcome Measures in Rheumatology (OMERACT) 2016, the domains were discussed and prioritized by 8 breakout groups. Formal voting took place at the end of the workshop and in the final plenary. Results. Ninety-three percent of voters in the final plenary agreed that the inner core of domains considered mandatory for clinical trials of PMR should consist the following: laboratory markers of systemic inflammation, pain, stiffness, and physical function. Patient’s global and fatigue were considered important but not mandatory (outer core). The research agenda included psychological impact, weakness, physical activity, participation, sleep, imaging, and health-related quality of life. Conclusion. This core domain set was considered sufficiently well-defined that the next step will be to apply the OMERACT Filter 2.0 Instrument Selection Algorithm to select candidate instruments for a subsequent “deeper dive” into the data. This will allow instruments to be mapped onto each of our core domains to derive a core outcome set for PMR

Serum Neurotrophin Profile in Systemic Sclerosis

International audienceBACKGROUND: Neurotrophins (NTs) are able to activate lymphocytes and fibroblasts; they can modulate angiogenesis and sympathic vascular function. Thus, they can be implicated in the three pathogenic processes of systemic sclerosis (SSc). The aims of this study are to determine blood levels of Nerve Growth Factor (NGF), Brain-Derived Neurotrophic Factor (BDNF) and Neurotrophin-3 (NT-3) in SSc and to correlate them with clinical and biological data.METHODS: Serum samples were obtained from 55 SSc patients and 32 control subjects to measure NTs levels by ELISA and to determine their relationships with SSc profiles. FINDINGS: Serum NGF levels were higher in SSc patients (288.26 ± 170.34 pg/mL) than in control subjects (170.34 ± 50.8 pg/mL, p<0.001) and correlated with gammaglobulins levels and the presence of both anti-cardiolipin and anti-Scl-70 antibodies (p<0.05). In contrast, BDNF levels were lower in SSc patients than in controls (1121.9 ± 158.1 vs 1372.9 ± 190.9 pg/mL, p<0.0001), especially in pulmonary arterial hypertension and diffuse SSc as compared to limited forms (all p<0.05). NT-3 levels were similar in SSc and in the control group (2657.2 ± 2296 vs 2959.3 ± 2555 pg/mL, NS). BDNF levels correlated negatively with increased NGF levels in the SSc group (and not in controls). CONCLUSION: Low BDNF serum levels were not previously documented in SSc, particularly in the diffuse SSc subset and in patients with pulmonary hypertension or anti-Scl-70 antibodies. The negative correlation between NGF and BDNF levels observed in SSc and not in healthy controls could be implicated in sympathic vascular dysfunction in SSc

Association of HLA-DRB1 amino acid residues with giant cell arteritis: genetic association study, meta-analysis and geo-epidemiological investigation

Introduction: Giant cell arteritis (GCA) is an autoimmune disease commonest in Northern Europe and Scandinavia. Previous studies report various associations with HLA-DRB1*04 and HLA-DRB1*01; HLA-DRB1 alleles show a gradient in population prevalence within Europe. Our aims were (1) to determine which amino acid residues within HLA-DRB1 best explained HLA-DRB1 allele susceptibility and protective effects in GCA, seen in UK data combined in meta-analysis with previously published data, and (2) to determine whether the incidence of GCA in different countries is associated with the population prevalence of the HLA-DRB1 alleles that we identified in our meta-analysis. Methods: GCA patients from the UK GCA Consortium were genotyped by using single-strand oligonucleotide polymerization, allele-specific polymerase chain reaction, and direct sequencing. Meta-analysis was used to compare and combine our results with published data, and public databases were used to identify amino acid residues that may explain observed susceptibility/protective effects. Finally, we determined the relationship of HLA-DRB1*04 population carrier frequency and latitude to GCA incidence reported in different countries. Results: In our UK data (225 cases and 1378 controls), HLA-DRB1*04 carriage was associated with GCA susceptibility (odds ratio (OR) = 2.69, P = 1.5×10 −11 ), but HLA-DRB1*01 was protective (adjusted OR = 0.55, P = 0.0046). In meta-analysis combined with 14 published studies (an additional 691 cases and 4038 controls), protective effects were seen from HLA-DR2, which comprises HLA-DRB1*15 and HLA-DRB1*16 (OR = 0.65, P = 8.2×10 −6 ) and possibly from HLA-DRB1*01 (OR = 0.73, P = 0.037). GCA incidence (n = 17 countries) was associated with population HLA-DRB1*04 allele frequency (P = 0.008; adjusted R 2 = 0.51 on univariable analysis, adjusted R 2 = 0.62 after also including latitude); latitude also made an independent contribution. Conclusions: We confirm that HLA-DRB1*04 is a GCA susceptibility allele. The susceptibility data are best explained by amino acid risk residues V, H, and H at positions 11, 13, and 33, contrary to previous suggestions of amino acids in the second hypervariable region. Worldwide, GCA incidence was independently associated both with population frequency of HLA-DRB1*04 and with latitude itself. We conclude that variation in population HLA-DRB1*04 frequency may partly explain variations in GCA incidence and that HLA-DRB1*04 may warrant investigation as a potential prognostic or predictive biomarker