Background Gout is a common and complex form of immunoreactive arthritis based on hyperuricemia, while the symptoms would turn to remission or even got worse. So, it is hard to early identify whether an asymptomatic hyperuricemia (AHU) patient will be susceptible to get acute gout attack and it is also hard to predict the process of gout remission to flare. Here, we report that the plasma proteins profile can distinguish among acute gout (AG), remission of gout (RG), AHU patients, and healthy controls. Methods We established an isobaric tags for relative and absolute quantification (iTRAQ) and parallel reaction monitoring (PRM) based method to measure the plasma proteins for AG group (n = 8), RG group (n = 7), AHU group (n = 7) and healthy controls (n = 8). Results Eleven differentially expressed proteins such as Histone H2A, Histone H2B, Thrombospondin-1 (THBS1), Myeloperoxidase (MPO), Complement C2, Complement component C8 beta chain (C8B), Alpha-1-acid glycoprotein 1 (ORM1), Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Carbonic anhydrase 1 (CA1), Serum albumin (ALB) and Multimerin-1 (MMRN1) were identified. Histone H2A, Histone H2B and THBS1 might be the strongest influential regulator to maintain the balance and stability of the gout process. The complement and coagulation cascades is one of the main functional pathways in the mechanism of gout process. Conclusions Histone H2A, Histone H2B and THBS1 are potential candidate genes for novel biomarkers in discriminating gout attack from AHU or RG, providing new theoretical insights for the prognosis, treatment, and management of gout process. Trial registration This study is not a clinical trial.

Purpose This study aimed to explore the accuracy for joint application of inflammatory cytokines in diagnosis of gout flare by comparison with peripheral blood cells. Methods We collected the clinical data of 96 acute gout patients and 144 remission gout patients, and compared the levels of peripheral blood cells, inflammatory cytokines and blood biochemistry indexes between acute and remission gout. We respectively assessed the area under curves (AUCs) for single and multiple inflammatory cytokines including C-reactive protein (CRP), interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), and single and multiple peripheral blood cells including platelet (PLT), white blood cell (WBC), percentages of neutrophils (N%), lymphocytes (L%), eosinophils (E%), basophils (B%) in diagnosis of acute gout by receiver operating characteristic (ROC) curve analysis. Results By contrast with remission gout, the levels of PLT, WBC, N%, CRP, IL-1β, IL-6 and TNF-α increased, and the levels of L%, E% and B% decreased in acute gout. The AUCs of PLT, WBC, N%, L%, E% and B% in diagnosis of acute gout were respectively 0.591, 0.601, 0.581, 0.567, 0.608 and 0.635, while the AUC for joint application of these peripheral blood cells was 0.674. Moreover, the AUCs of CRP, IL-1β, IL-6 and TNF-α in diagnosis of acute gout were respectively 0.814, 0.683, 0.622 and 0.746, while the AUC for joint application of these inflammatory cytokines was 0.883, reflecting significantly higher levels than peripheral blood cells. Conclusion The joint application of multiple inflammatory cytokines can better distinguish acute gout from remission gout compared with peripheral blood cells.

BackgroundGout is a common and complex form of immunoreactive arthritis based on hyperuricemia, while the symptoms would turn to remission or even got worse. So, it is hard to early identify whether an asymptomatic hyperuricemia (AHU) patient will be susceptible to get acute gout attack and it is also hard to predict the process of gout remission to flare. Here, we report that the plasma proteins profile can distinguish among acute gout (AG), remission of gout (RG), AHU patients, and healthy controls.MethodsWe established an isobaric tags for relative and absolute quantification (iTRAQ) and parallel reaction monitoring (PRM) based method to measure the plasma proteins for AG group (n=8), RG group(n=7), AHU group(n=7) and healthy controls(n=8).Resultseleven differentially expressed proteins such as Histone H2A, Histone H2B, Thrombospondin-1 (THBS1), Myeloperoxidase (MPO), Complement C2, Complement component C8 beta chain (C8B), Alpha-1-acid glycoprotein 1 (ORM1), Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Carbonic anhydrase 1 (CA1), Serum albumin (ALB) and Multimerin-1 (MMRN1) were identified. Histone H2A, Histone H2B and THBS1 might be the strongest influential regulator to maintain the balance and stability of the gout process. The complement and coagulation cascades is one of the main functional pathways in the mechanism of gout process.ConclusionsHistone H2A, Histone H2B and THBS1 may be novel biomarkers in discriminating gout attack from AHU or RG, providing new theoretical insights for the prognosis, treatment, and management of gout process.Trial registrationThis study is not a clinical trial.

The oral microbiota is the direct precursor of dental caries and periodontitis, which are the most common microbial-induced diseases worldwide. The distinct microenvironment at the oral barrier breeds unique microbial communities, which are regulated by host factors (inflammation or dietary sugars)1. Increasing evidence indicates that dysbiosis of oral microbial communities is associated with many human diseases2-5. Our studies demonstrated that human disease could induce different alterations in salivary protein glycopatterns6. However, the relationship between salivary protein glycopatterns and oral microbial communities is unknown. Here, we report that altered salivary protein glycopatterns, namely, fucosylated or sialylated structures induced by gastric cancer (GC) or type 2 diabetes mellitus (T2DM), respectively, are also drivers of dysbiosis of oral microbial communities and ultimately dental caries and periodontitis. The fucosylated neoglycoproteins and sialic acid (SA) α2-3 galactose (Gal) structure can inhibit the growth or/and adhesion of Aggregatibacter segnis and Candida albicans from the oral cavity of patients with GC and T2DM, respectively. These findings provide a novel theory that dynamic communities of oral microbiota are regulated naturally by host salivary protein glycopatterns, having important implications for developing new carbohydrate drugs for oral and body health.