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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. [ABSTRACT FROM AUTHOR]

In this review, we explore systemization of knowledge about the triggering effects of non-genetic factors in pathogenic mechanisms that contribute to the development of rheumatoid arthritis (RA). Possible mechanisms involving environmental and individual factors in RA pathogenesis were analyzed, namely, infections, mental stress, sleep deprivation ecology, age, perinatal and gender factors, eating habits, obesity and smoking. The non-genetic factors modulate basic processes in the body with the impact of these factors being non-specific, but these common challenges may be decisive for advancement of the disease in the predisposed body at risk for RA. The provocation of this particular disease is associated with the presence of congenital loci minoris resistentia. The more frequent non-genetic factors form tangles of interdependent relationships and, thereby, several interdependent external factors hit one vulnerable basic process at once, either provoking or reinforcing each other. Understanding the specific mechanisms by which environmental and individual factors impact an individual under RA risk in the preclinical stages can contribute to early disease diagnosis and, if the factor is modifiable, might be useful for the prevention or delay of its development. [ABSTRACT FROM AUTHOR]

The effective treatment of autoimmune disorders can greatly benefit from disease-specific biomarkers that are functionally involved in immune system regulation and can be collected through minimally invasive procedures. In this regard, human serum IgG N-glycans are promising for uncovering disease predisposition and monitoring progression, and for the identification of specific molecular targets for advanced therapies. In particular, the IgG N-glycome in diseased tissues is considered to be disease-dependent; thus, specific glycan structures may be involved in the pathophysiology of autoimmune diseases. This study provides a critical overview of the literature on human IgG N-glycomics, with a focus on the identification of disease-specific glycan alterations. In order to expedite the establishment of clinically-relevant N-glycan biomarkers, the employment of advanced computational tools for the interpretation of clinical data and their relationship with the underlying molecular mechanisms may be critical. Glycoinformatics tools, including artificial intelligence and systems glycobiology approaches, are reviewed for their potential to provide insight into patient stratification and disease etiology. Challenges in the integration of such glycoinformatics approaches in N-glycan biomarker research are critically discussed. [ABSTRACT FROM AUTHOR]