A novel single domain bispecific antibody targeting VEGF and TNF-α ameliorates rheumatoid arthritis

Anti-TNF-α therapy fails in 30% of patients, where TNF-α may not be the key causative factor in these patients. We developed a bispecific single-domain antibody block TNF-α and VEGF (V5-3).The experiments showed that V5-3 effectively activated proliferation and migration of RA-FLS and HUVEC, tube-forming role of HUVEC, and expression of inflammatory factors in vitro. Besides, the experiments indicated that the anti-RA activity of V5-3 was superior to Anbainuo in vivo. Application of V5-3 reduced the expression of inflammatory factors, extent of synovial inflammation and angiogenesis and attenuated the severity of autoimmune arthritis in collagen-induced arthritis (CIA) mice. Mechanistically, V5-3 suppressed p65, AKT and VEGFR2 phosphorylation, as well as production of TNF-α and VEGF in joint tissues. These results demonstrated that V5-3 displayed a superior effect of anti-RA, may be a new therapy to overcome the limitations of anti-TNF-α monoclonal antibody.

Candidate Genetic and Molecular Drivers of Dysregulated Adaptive Immune Responses After Traumatic Brain Injury

Abstract Neuroinflammation is a significant and modifiable cause of secondary injury after traumatic brain injury (TBI), driven by both central and peripheral immune responses. A substantial proportion of outcome after TBI is genetically mediated, with an estimated heritability effect of around 26%, but because of the comparatively small datasets currently available, the individual drivers of this genetic effect have not been well delineated. A hypothesis-driven approach to analyzing genome-wide association study (GWAS) datasets reduces the burden of multiplicity testing and allows variants with a high prior biological probability of effect to be identified where sample size is insufficient to withstand data-driven approaches. Adaptive immune responses show substantial genetically mediated heterogeneity and are well established as a genetic source of risk for numerous disease states; importantly, HLA class II has been specifically identified as a locus of interest in the largest TBI GWAS study to date, highlighting the importance of genetic variance in adaptive immune responses after TBI. In this review article we identify and discuss adaptive immune system genes that are known to confer strong risk effects for human disease, with the dual intentions of drawing attention to this area of immunobiology, which, despite its importance to the field, remains under-investigated in TBI and presenting high-yield testable hypotheses for application to TBI GWAS datasets.

Gaultheria leucocarpa var. yunnanensis for Treating Rheumatoid Arthritis-An Assessment Combining Machine Learning-Guided ADME Properties Prediction, Network Pharmacology, and Pharmacological Assessment

Background: Dianbaizhu (Gaultheria leucocarpa var. yunnanensis), a traditional Chinese/ethnic medicine (TC/EM), has been used to treat rheumatoid arthritis (RA) for a long time. The anti-rheumatic arthritis fraction (ARF) of G. yunnanensis has significant anti-inflammatory and analgesic activities and is mainly composed of methyl salicylate glycosides, flavonoids, organic acids, and others. The effective ingredients and rudimentary mechanism of ARF remedying RA have not been elucidated to date. Purpose: The aim of the present study is to give an insight into the effective components and mechanisms of Dianbaizhu in ameliorating RA, based on the estimation of the absorption, distribution, metabolism, and excretion (ADME) properties, analysis of network pharmacology, and in vivo and in vitro validations. Study design and methods: The IL-1β-induced human fibroblast-like synoviocytes of RA (HFLS-RA) model and adjuvant-induced arthritis in the rat model were adopted to assess the anti-RA effect of ARF. The components in ARF were identified by using UHPLC-LTQ-Orbitrap-MSⁿ. The quantitative structure-activity relationship (QSAR) models were developed by using five machine learning algorithms, alone or in combination with genetic algorithms for predicting the ADME properties of ARF. The molecular networks and pathways presumably referring to the therapy of ARF on RA were yielded by using common databases and visible software, and the experimental validations of the key targets conducted in vitro. Results: ARF effectively relieved RA in vivo and in vitro. The five optimized QSAR models that were developed showed robustness and predictive ability. The characterized 48 components in ARF had good biological potency. Four key signaling pathways were obtained, which were related to both cytokine signaling and cell immune response. ARF suppressed IL-1β-induced expression of EGFR, MMP 9, IL2, MAPK14, and KDR in the HFLS-RA . Conclusions: ARF has good druggability and high exploitation potential. Methyl salicylate glycosides and flavonoids play essential roles in attuning RA. ARF may partially attenuate RA by regulating the expression of multi-targets in the inflammation-immune system. These provide valuable information to rationalize ARF and other TC/EMs in the treatment of RA.

Assessment of the anti-rheumatoid arthritis activity of Gastrodia elata (tian-ma) and Radix aconitic lateralis preparata (fu-zi) via network pharmacology and untargeted metabolomics analyses

AIM

Gastrodia elata and Radix aconiti lateralis preparrata are respectively named as Tian-Ma and Fu-Zi (TF) in Chinese. We explored the active components against rheumatoid arthritis (RA) from an extensively used couplet of Chinese herbs, Gastrodia elata and Radix aconiti lateralis preparata (TF) via untargeted metabolomics and network pharmacological approaches.

METHODS

Water extracts of TF were mixed at ratios 1:1, 3:2 and 2:3 (w/w). Ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) was then utilized as metabolomics screening. Human Metabolome (http://www.hmdb.ca/) and Lipidmaps (http://www.lipidmaps.org/) databases were used to annotate detected compounds. Further identification of vital genes and important pathways associated with the anti-RA properties of the TF preparations was done via network pharmacology, and verified by real-time quantitative polymerase chain reaction (RT-qPCR).

RESULTS

Four key compounds involved in unsaturated fatty acid biosynthesis and isoflavonoid biosynthesis were identified through metabolomics analyses. Three key components of TF associated with anti-RA activity were linoleic acid, daidzein, and daidzin. Results of RT-qPCR revealed that all 3 tested TF couplets (1:1, 3:2, and 2:3) markedly suppressed the transcription of PTGS2. These results were consistent with our network pharmacological predictions.

CONCLUSIONS

The anti-RA properties of Tian-Ma and Fu-Zi are associated with the inhibition of arachidonic acid metabolism pathway.