Hepatocyte growth factor is a potential biomarker for osteoproliferation and osteoporosis in ankylosing spondylitis

Importance of Metalloproteinase Enzyme Group in Selected Skeletal System Diseases

Bone tissue is a dynamic structure that is involved in maintaining the homeostasis of the body due to its multidirectional functions, such as its protective, endocrine, or immunological role. Specialized cells and the extracellular matrix (ECM) are responsible for the remodeling of specific bone structures, which alters the biomechanical properties of the tissue. Imbalances in bone-forming elements lead to the formation and progression of bone diseases. The most important family of enzymes responsible for bone ECM remodeling are matrix metalloproteinases (MMPs)-enzymes physiologically present in the body's tissues and cells. The activity of MMPs is maintained in a state of balance; disruption of their activity is associated with the progression of many groups of diseases, including those of the skeletal system. This review summarizes the current understanding of the role of MMPs in bone physiology and the pathophysiology of bone tissue and describes their role in specific skeletal disorders. Additionally, this work collects data on the potential of MMPs as bio-markers for specific skeletal diseases.

Computational Drug Discovery in Ankylosing Spondylitis-Induced Osteoporosis Based on Data Mining and Bioinformatics Analysis

BACKGROUND

Ankylosing spondylitis (AS) and osteoporosis (OP) are both prevalent illnesses in spine surgery, with OP being a possible consequence of AS. However, the mechanism of AS-induced OP (AS-OP) remains unknown, limiting etiologic research and therapy of the illness. To mine targetable medicine for the prevention and treatment of AS-OP, this study analyzes public data sets using bioinformatics to identify genes and biological pathways relevant to AS-OP.

METHODS

First, text mining was used to identify common genes associated with AS and OP, after which functional analysis was carried out. The STRING database and Cytoscape software were used to create protein-protein interaction networks. Hub genes and potential drugs were discovered using drug-gene interaction analysis and transcription factors-gene interaction analysis.

RESULTS

The results of text mining showed 241 genes common to AS and OP, from which 115 key symbols were sorted out by functional analysis. As options for treating AS-OP, protein-protein interaction analysis yielded 20 genes, which may be targeted by 13 medications.

CONCLUSIONS

Carlumab, bermekimab, rilonacept, rilotumumab, and ficlatuzumab were first identified as the potential drugs for the treatment of AS-OP, proving the value of text mining and pathway analysis in drug discovery.

Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods

Long-term cigarette smoking causes various human diseases, including respiratory disease, cancer, and gastrointestinal (GI) disorders. Alterations in gene expression and variable splicing processes induced by smoking are associated with the development of diseases. This study applied advanced machine learning methods to identify the isoforms with important roles in distinguishing smokers from former smokers based on the expression profile of isoforms from current and former smokers collected in one previous study. These isoforms were deemed as features, which were first analyzed by the Boruta to select features highly correlated with the target variables. Then, the selected features were evaluated by four feature ranking algorithms, resulting in four feature lists. The incremental feature selection method was applied to each list for obtaining the optimal feature subsets and building high-performance classification models. Furthermore, a series of classification rules were accessed by decision tree with the highest performance. Eventually, the rationality of the mined isoforms (features) and classification rules was verified by reviewing previous research. Features such as isoforms ENST00000464835 (expressed by LRRN3), ENST00000622663 (expressed by SASH1), and ENST00000284311 (expressed by GPR15), and pathways (cytotoxicity mediated by natural killer cell and cytokine-cytokine receptor interaction) revealed by the enrichment analysis, were highly relevant to smoking response, suggesting the robustness of our analysis pipeline.

Matrix Metalloproteinases; A Biomarker of Disease Activity and Prognosis in Spondyloarthritis: A Narrative Review

BACKGROUND

Matrix metalloproteinases, as components of the proteolytic system, are deemed to be implicated in the pathogenesis and progression of several rheumatic diseases. Their role in spondyloarthritis has been investigated by several studies.

OBJECTIVE

This article aims to review and summarize the current knowledge related to metalloproteinases in patients with spondyloarthritis.

METHODS

To examine the association between matrix metalloproteinases and spondyloarthritis, we conducted a narrative review using a literature search in SCOPUS for English-language sources. The search included studies published from the database inception to December 2020.

RESULTS

A total number of 74 articles were included. It was found that levels of matrix metalloproteinases 3 were higher in radiographic axial spondyloarthritis patients and seemed to play a role in the progression of joint damage. The levels of matrix metalloproteinases 1, 2, and 9 were upregulated in psoriatic arthritis patients compared to psoriasis and could identify psoriasis patients who would develop rheumatic manifestations. The levels of matrix metalloproteinases correlated significantly with disease activity in ankylosing spondylitis and decreased upon treatment with Tumor Necrosis Factor inhibitors (TNFi).

CONCLUSION

Excessive matrix metalloproteinases activity is associated with articular destruction. Their levels can reflect disease activity, structural damage, and response to TNFi in patients with spondyloarthritis. Nevertheless, further studies are needed to confirm these results.

Practical Significance of Biomarkers in Axial Spondyloarthritis: Updates on Diagnosis, Disease Activity, and Prognosis

Axial spondyloarthritis (axSpA) is a chronic inflammatory disease that can lead to ankylosis by secondary ossification of inflammatory lesions, with progressive disability and a significant impact on quality of life. It is also a risk factor for the occurrence of comorbidities, especially cardiovascular diseases (CVDs), mood disorders, osteoporosis, and malignancies. Early diagnosis and treatment are needed to prevent or decrease functional decline and to improve the patient's prognosis. In respect of axSpA, there is an unmet need for biomarkers that can help to diagnose the disease, define disease activity and prognosis, and establish personalized treatment approaches. The aim of this review was to summarize the available information regarding the most promising biomarkers for axSpA. We classified and identified six core categories of biomarkers: (i) systemic markers of inflammation; (ii) molecules involved in bone homeostasis; (iii) HLA-B27 and newer genetic biomarkers; (iv) antibody-based biomarkers; (v) microbiome biomarkers; and (vi) miscellaneous biomarkers. Unfortunately, despite efforts to validate new biomarkers, few of them are used in clinical practice; however, we believe that these studies provide useful data that could aid in better disease management.

Biomarkers in axial spondyloarthritis and low back pain: a comprehensive review

The spectrum of axial spondyloarthritis (AxSpA) (including both non-radiographic and radiographic AxSpA), also known as ankylosing spondylitis AS, has achieved growing recognition. With the development of treatments not only effective in controlling disease activity but also in slowing radiographic progression, and given the cost and risk profiles of these novel treatments and the limitations of current clinical criteria, imaging and peripheral blood biomarkers (C-reactive protein, HLA-B27 testing), the need for better biomarkers has never been greater. The purpose of this review is to present up-to-date information on the biomarkers for the diagnosis for assessing disease diagnosis, activity, treatment response, and radiographic progression of AxSpA, and entails multiple search strings used to identify articles of interest published in PubMed and the Cochrane database up to May 1, 2021. We present the current status of research in serologic biomarkers such as cytokines, adipokines, matrix metalloproteinases, calprotectin, CD74, antibodies, bone turnover markers, and circulating protein fragments of cartilage and connective tissue degradation and other biomarkers. Despite a great deal of work, most serologic results have been disappointing and to date none perform better than CRP. Recent promising preliminary data for some has been published, but require further confirmation. Transcriptomic biomarkers such as micro-RNAs and genetic biomarkers also show promise to assist in diagnosis and possibly for radiographic severity, including a recently developed panel of genetic risk markers used in a polygenic risk score instrument in AS diagnosis. These need further confirmation and application in AS as well as in nr-AxSpA.

Melatonin restores osteoporosis-impaired osteogenic potential of bone marrow mesenchymal stem cells and alleviates bone loss through the HGF/PTEN/Wnt/β-catenin axis

Background:

Previous studies reported that melatonin exerts its effect on mesenchymal stem cell (MSC) survival and differentiation into osteogenic and adipogenic lineage. In the current study we aimed to explore the effect of melatonin on osteoporosis and relevant mechanisms.

Methods:

Real-time qualitative polymerase chain reaction (RT-qPCR) and Western blot analysis were conducted to determine expression of HGF, PTEN, and osteoblast differentiation-related genes in ovariectomy (OVX)-induced osteoporosis mice and the isolated bone marrow MSCs (BMSCs). Pre-conditioning with melatonin (1 μmol/l, 10 μmol/l and 100 μmol/l) was carried out in OVX mice BMSCs. Bone microstructure was analyzed using micro-computed tomography and the contents of alkaline phosphatase (ALP) and tartrate-resistant acid phosphatase 5b (TRAP5b) were detected by enzyme-linked immunosorbent assay in serum. BMSC proliferation was measured by cell-counting kit (CCK)-8 assay. Alizarin red S (ARS) staining and ALP activity assay were performed to assess BMSC mineralization and calcification. The activity of the Wnt/β-catenin pathway was evaluated by dual-luciferase reporter assay.

Results:

Melatonin prevented bone loss in OVX mice. Melatonin increased ALP expression and reduced TRAP5b expression. HGF and β-catenin were downregulated, while PTEN was upregulated in the femur of OVX mice. Melatonin elevated HGF expression and then stimulated BMSC proliferation and osteogenic differentiation. Additionally, HGF diminished the expression of PTEN, resulting in activated Wnt/β-catenin pathway both in vitro and in vivo. Furthermore, melatonin was shown to ameliorate osteoporosis in OVX mice via the HGF/PTEN/Wnt/β-catenin axis.

Conclusion:

Melatonin could potentially enhance osteogenic differentiation of BMSCs and retard bone loss through the HGF/PTEN/Wnt/β-catenin axis.

Association of Circulating Vascular Endothelial Growth Factor Levels With Autoimmune Diseases: A Systematic Review and Meta-Analysis

Background

Autoimmune diseases (ADs) are characterized by immune-mediated tissue damage, in which angiogenesis is a prominent pathogenic mechanism. Vascular endothelial growth factor (VEGF), an angiogenesis modulator, is significantly elevated in several ADs including rheumatoid arthritis (RA), systemic sclerosis (SSc), and systemic lupus erythematosus (SLE). We determined whether circulating VEGF levels were associated with ADs based on pooled evidence.

Methods

The analyses included 165 studies from the PubMed, EMBASE, Cochrane Library, and Web of Science databases and fulfilled the study criteria. Comparisons of circulating VEGF levels between patients with ADs and healthy controls were performed by determining pooled standard mean differences (SMDs) with 95% confidence intervals (CIs) in a random-effect model using STATA 16.0. Subgroup, sensitivity, and meta-regression analyses were performed to determine heterogeneity and to test robustness.

Results

Compared with healthy subjects, circulating VEGF levels were significantly higher in patients with SLE (SMD 0.84, 95% CI 0.25-1.44, P = 0.0056), RA (SMD 1.48, 95% CI 0.82-2.15, P <0.0001), SSc (SMD 0.56, 95% CI 0.36-0.75, P <0.0001), Behcet's disease (SMD 1.65, 95% CI 0.88-2.41, P <0.0001), Kawasaki disease (SMD 2.41, 95% CI 0.10-4.72, P = 0.0406), ankylosing spondylitis (SMD 0.78, 95% CI 0.23-1.33, P = 0.0052), inflammatory bowel disease (SMD 0.57, 95% CI 0.43-0.71, P <0.0001), psoriasis (SMD 0.98, 95% CI 0.62-1.34, P <0.0001), and Graves' disease (SMD 0.69, 95% CI 0.20-1.19, P = 0.0056). Circulating VEGF levels correlated with disease activity and hematological parameters in ADs.

Conclusion

Circulating VEGF levels were associated with ADs and could predict disease manifestations, severity and activity in patients with ADs.

Systematic Review Registration

PROSPERO, identifier CRD42021227843.

Elevated serum level of hepatocyte growth factor predicts development of new syndesmophytes in men with ankylosing spondylitis

Objectives

To study baseline serum hepatocyte growth factor (s-HGF) as a predictor of spinal radiographic progression overall and by sex and to analyse factors correlated to changes in s-HGF in patients with AS.

Methods

At baseline and the 5-year follow-up, s-HGF was analysed with ELISA. Spinal radiographs were graded according to modified Stoke Ankylosing Spondylitis Spinal Score. Radiographic progression was defined as ≥2 modified Stoke Ankylosing Spondylitis Spinal Score units/5 years or development of ≥1 syndesmophyte. Logistic regression analyses were used.

Results

Of 204 baseline participants, 163 (80%) completed all examinations at the 5-year follow-up (54% men). Baseline s-HGF was significantly higher in men who developed ≥1 syndesmophyte compared with non-progressors, median (interquartile range) baseline s-HGF 1551 (1449–1898) vs 1436 (1200–1569) pg/ml, P = 0.003. The calculated optimal cut-off point for baseline s-HGF ≥1520 pg/ml showed a sensitivity of 70%, a specificity of 69% and univariate odds radio (95% CI) of 5.25 (1.69, 14.10) as predictor of development of ≥1 new syndesmophyte in men. Baseline s-HGF ≥1520 pg/ml remained significantly associated with development of ≥1 new syndesmophyte in men in an analysis adjusted for the baseline variables age, smoking, presence of syndesmophytes and CRP, odds radio 3.97 (1.36, 11.60). In women, no association with HGF and radiographic progression was found. Changes in s-HGF were positively correlated with changes in ESR and CRP.

Conclusion

In this prospective cohort study elevated s-HGF was shown to be associated with development of new syndesmophytes in men with AS.

Aptamers for Proteins Associated with Rheumatic Diseases: Progress, Challenges, and Prospects of Diagnostic and Therapeutic Applications

Nucleic acid aptamers capable of affine and specific binding to their molecular targets have now established themselves as a very promising alternative to monoclonal antibodies for diagnostic and therapeutic applications. Although the main focus in aptamers’ research and development for biomedicine is made on cardiovascular, infectious, and malignant diseases, the use of aptamers as therapeutic or diagnostic tools in the context of rheumatic diseases is no less important. In this review, we consider the main features of aptamers that make them valuable molecular tools for rheumatologists, and summarize the studies on the selection and application of aptamers for protein biomarkers associated with rheumatic diseases. We discuss the progress in the development of aptamer-based diagnostic assays and targeted therapeutics for rheumatic disorders, future prospects in the field, and issues that have yet to be addressed.

An update on serum biomarkers to assess axial spondyloarthritis and to guide treatment decision

Axial spondyloarthritis (axSpA) is a group of debilitating, chronic, rheumatic conditions characterized by inflammation and new bone formation, mainly involving the spine and the sacroiliac joints. The lack of biomarkers in axSpA is well known. Despite significant treatment advances in recent years thanks to the introduction of drugs with a new mode of action, such as new biologic and targeted synthetic disease-modifying antirheumatic drugs, no relevant improvement in the identification of disease biomarkers has been achieved. Common parameters, such as erythrocyte sedimentation rate and C-reactive protein, which are routinely used to measure systemic inflammation, are the sole markers available to date and are not adequate to assess disease activity in all patients. The aim of this study is to review the most promising serum biomarkers that may help treatment decision in axSpA via a proper assessment of disease activity and identification of negative prognostic factors.

Biomarkers for Diagnosis of Axial Spondyloarthritis, Disease Activity, Prognosis, and Prediction of Response to Therapy

There exists a major unmet need for biomarkers that can identify axial spondyloarthritis (axSpA) early after disease onset because of the availability of highly effective therapies. Several recent reports have examined the autoantibody response in patients with axSpA through the use of protein microarrays and protein-protein interactions although diagnostic performance of biomarkers identified to date has been inadequate. An example of such a biomarker is protein phosphatase magnesium-dependent 1A. Antibodies to the human leukocyte antigen class II-associated invariant chain peptide (anti-CD74) are candidate diagnostic biomarkers but sensitivity declines with increasing duration of disease. Metabolomic studies have employed nuclear magnetic resonance (NMR) spectrometry to identify disease-specific metabolites related to fat metabolism and intestinal microbial metabolism. A second major unmet need exists for biomarkers of disease activity that have superiority over standard C-reactive protein assessment and reflect MRI inflammation in the axial spine. Several biomarkers reflecting inflammation (calprotectin), angiogenesis (vasoactive endothelial growth factor), and connective tissue turnover (C2M, C3M, and citrullinated metalloproteinase degraded fragment of vimentin) have recently been shown to reflect disease activity when compared with clinical outcomes but comparisons with MRI inflammation are very limited. With increasing availability of highly effective but costly therapies, a third unmet need is biomarkers that can predict response to therapies with different mechanisms of action and are superior to C-reactive protein. Calprotectin is currently the only candidate. Although there are as yet no proven therapies for preventing progression of disease there is an unmet need for biomarkers of prognosis that are more responsive than radiography. Aside from CRP no consistent candidates have emerged. Future studies will need to be prospective, include consecutive patients presenting with undiagnosed back pain, and use more reliable and objective endpoints such as MRI inflammation. Moreover, it has become evident that targeted biomarker studies have not been successful in identifying clinically useful biomarkers and technologies that can simultaneously assess “multiomic” markers will need to be analyzed for future advances. These include more sophisticated metabolomic profiling and universal metabolome-standard (UMS) methodology, next generation RNA sequencing, and affinity-based quantitative proteomics based on the use of nucleic acid binders such as the aptamer-based SOMAscan assay.