Expression and function of Toll‑like receptors in peripheral blood mononuclear cells in patients with ankylosing spondylitis

An in vitro study elucidating the synergistic effects of aqueous cinnamon extract and an anti-TNF-α biotherapeutic: implications for a complementary and alternative therapy for non-responders

BACKGROUND

Tumor necrosis factor-alpha (TNF-α) is a critical pro-inflammatory cytokine, and its abnormal production is associated with several immune mediated inflammatory diseases (IMID). Biological anti-TNF-α therapy includes treatment with monoclonal antibodies such as infliximab which have proven successful and are well-tolerated in most patients. Unfortunately, some patients may not respond to therapy (primary non-responders) or may lose sensitivity to the biological agent over time (early and late secondary non-responders). Natural products can reduce inflammation and act synergistically with small molecules or biologics, although evidence remains limited. This study aimed to investigate whether complementary and alternative medicine (CAM) could play a role in infliximab non-responders. Reportedly, cinnamon can help manage chronic inflammatory conditions owing to its anti-inflammatory properties.

METHODS

We studied the synergistic effects of cinnamon and infliximab in vitro using a two-step approach. First, we investigated whether cinnamon and infliximab act synergistically. Second, we selected conditions that supported statistically significant synergy with infliximab and studied the mRNA expression of several genes involved in non-response to infliximab. We used aqueous cinnamon extract (aCE) from Cinnamomum cassia, Cinnamomum zeylanicum, and Cinnamomum loureiroi and bioactive trans-cinnamaldehyde (TCA), cinnamic acid (CA), and eugenol to study the synergy between infliximab and aCE/bioactive compounds using bioassays in fibroblast (L929) and monocytic (U937) cell lines, followed by qPCR for molecular-level insights. TCA, C. cassia aCE, and C. zeylanicum aCE demonstrated a dose-dependent synergistic effect with infliximab. Moreover, we saw differential gene expression for adhesion molecules, apoptotic factors, signaling molecules, and matrix remodelers in presence and absence of aCE/bioactives.

RESULTS

CAM supplementation was most effective with C. cassia aCE, where a synergistic effect was observed for all the tested genes specifically for MMP-1, BcL-xL, Bax and JAK2, followed by TCA, which affected most of the tested genes except TLR-2, MMP1, MMP3, TIMP-1, and BAX, and C. zeylanicum aCE, which did not affect ICAM-1, VCAM-1, TLR-2, TLR-4, MMP1, MMP3, TIMP-1, and STAT3.

CONCLUSION

In conclusion, cinnamon acted synergistically with infliximab to mitigate inflammation when used as an extract. Purified bioactive TCA also showed synergistic activity. Thus, aCE, or cinnamon bioactive may be used as a CAM to improve patients' quality of life.

Network pharmacology combined with molecular docking and experimental validation to explore the potential mechanism of Cinnamomi ramulus against ankylosing spondylitis

BACKGROUND

Cinnamomi ramulus (C. ramulus) is frequently employed in the treatment of ankylosing spondylitis (AS). However, the primary constituents, drug targets, and mechanisms of action remain unidentified.

METHODS

In this study, various public databases and online tools were employed to gather information on the compounds of C. ramulus, drug targets, and disease targets associated with ankylosing spondylitis. The intersection of drug targets and disease targets was then determined to identify the common targets, which were subsequently used to construct a protein-protein interaction (PPI) network using the STRING database. Network analysis and the analysis of hub genes and major compounds were conducted using Cytoscape software. Furthermore, the Metascape platform was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Molecular docking studies and immunohistochemical experiments were performed to validate the core targets.

RESULTS

The network analysis identified 2-Methoxycinnamaldehyde, cinnamaldehyde, and 2-Hydroxycinnamaldehyde as the major effective compounds present in C. ramulus. The PPI network analysis revealed PTGS2, MMP9, and TLR4 as the most highly correlated targets. GO and KEGG analyses indicated that C. ramulus exerts its therapeutic effects in ankylosing spondylitis through various biological processes, including the response to hormones and peptides, oxidative stress response, and inflammatory response. The main signaling pathways involved were IL-17, TNF, NF-kappa B, and Toll-like receptor pathways. Molecular docking analysis confirmed the strong affinity between the key compounds and the core targets. Additionally, immunohistochemical analysis demonstrated an up-regulation of PTGS2, MMP9, and TLR4 levels in ankylosing spondylitis.

CONCLUSIONS

This study provides insights into the effective compounds, core targets, and potential mechanisms of action of C. ramulus in the treatment of ankylosing spondylitis. These findings establish a solid groundwork for future fundamental research in this field.

Quantitative proteomic screening uncovers candidate diagnostic and monitoring serum biomarkers of ankylosing spondylitis

BACKGROUND

We sought to discover serum biomarkers of ankylosing spondylitis (AS) for diagnosis and monitoring disease activity.

METHODS

We studied biologic-treatment-naïve AS and healthy control (HC) patients' sera. Eighty samples matched by age, gender, and race (1:1:1 ratio) for AS patients with active disease, inactive disease, and HC were analyzed with SOMAscan™, an aptamer-based discovery platform. T-tests tests were performed for high/low-disease activity AS patients versus HCs (diagnosis) and high versus low disease activity (Monitoring) in a 2:1 and 1:1 ratio, respectively, to identify differentially expressed proteins (DEPs). We used the Cytoscape Molecular Complex Detection (MCODE) plugin to find clusters in protein-protein interaction networks and Ingenuity Pathway Analysis (IPA) for upstream regulators. Lasso regression analysis was performed for diagnosis.

RESULTS

Of the 1317 proteins detected in our diagnosis and monitoring analyses, 367 and 167 (317 and 59, FDR-corrected q < .05) DEPs, respectively, were detected. MCODE identified complement, IL-10 signaling, and immune/interleukin signaling as the top 3 diagnosis PPI clusters. Complement, extracellular matrix organization/proteoglycans, and MAPK/RAS signaling were the top 3 monitoring PPI clusters. IPA showed interleukin 23/17 (interleukin 22, interleukin 23A), TNF (TNF receptor-associated factor 3), cGAS-STING (cyclic GMP-AMP synthase, Stimulator of Interferon Gene 1), and Jak/Stat (Signal transducer and activator of transcription 1), signaling in predicted upstream regulators. Lasso regression identified a Diagnostic 13-protein model predictive of AS. This model had a sensitivity of 0.75, specificity of 0.90, a kappa of 0.59, and overall accuracy of 0.80 (95% CI: 0.61-0.92). The AS vs HC ROC curve was 0.79 (95% CI: 0.61-0.96).

CONCLUSION

We identified multiple candidate AS diagnostic and disease activity monitoring serum biomarkers using a comprehensive proteomic screen. Enrichment analysis identified key pathways in AS diagnosis and monitoring. Lasso regression identified a multi-protein panel with modest predictive ability.

Emerging Roles of Long Non-Coding RNAs in Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a chronic systemic autoimmune disease characterized by inflammation, bone erosion, spur formation of the spine and the sacroiliac joints. However, the etiology and molecular pathogenesis of AS remain largely unclear. Recently, a growing number of studies showed that long non-coding RNAs (lncRNAs) played critical roles in the development and progression of autoimmune and orthopedic conditions, including AS. Studies demonstrated that a myriad of lncRNAs (e.g. H19, MEG3, LOC645166) pertinent to regulation of inflammatory signals were deregulated in AS. A number of lncRNAs might also serve as new biomarkers for the diagnosis and predicting the outcomes of AS. In this review, we summarize lncRNA profiling studies on AS and the functional roles and mechanism of key lncRNAs relevant to AS pathogenesis. We also discuss their potential values as biomarkers and druggable targets for this potentially disabling condition.

Andrographolide Against Lung Cancer-New Pharmacological Insights Based on High-Throughput Metabolomics Analysis Combined with Network Pharmacology

Andrographolide (Andro) has known to treat various illnesses such as colds, diarrhea, fever and infectious diseases. However, the effect mechanism of Andro is still unclear. Therefore, we used high-throughput metabolomics analysis to discover biomarkers, metabolic profiles and pathways to reveal the pharmacological action and effective mechanism of Andro against lung cancer. The metabolic effects of Andro on lung cancer animal was explored by ultra-performance liquid chromatography-triple-time of flight/mass spectrometry (UPLC-TOF/MS) analysis. Our results showed that Andro exhibited significant protective effects against lung cancer. Compared with control group, a total of 25 metabolites biomarkers was identified in urine of model animals, which 18 of them were regulated toward the normal direction after Andro treatment, and network pharmacology analysis showed that they were related with 570 proteins. Biological pathways analysis showed that the 11 metabolism pathways were regulated by Andro treatment in lung cancer mouse, and amino acid metabolism and arachidonic acid metabolism have great potential as target pathways for Andro against lung cancer. It revealed that high-throughput metabolomics combined with network pharmacology analysis provides deeply insight into the therapeutic mechanisms of natural product for promoting medicine development and disease treatment.