Autoimmune diseases are chronic conditions characterized by dysregulation of the immune system resulting in inflammation and multi-tissue damage. They are a poorly understood group of diseases, including rheumatoid arthritis (RA), Sjögren's syndrome (SS), systemic lupus erythematosus (SLE) and type I diabetes, among others. The effective management of patients with autoimmune diseases has been hampered by delays in diagnosis (often for years) combined with a lack of effective treatments. Accordingly, identification of early diagnostic biomarkers and therapeutic targets are important challenges facing the autoimmune disease research community.
Autoantibodies have a proven role as diagnostic biomarkers in autoimmune diseases and continue to be an important entry point for basic and clinical research into human autoimmunity. The pathogenic role of these autoantibodies is suggested by animal experiments and clinical observations. Despite being discovered several decades ago, little is known about the nature and pathogenic role of the autoreactive B cell and secreted autoantibody repertoires in autoimmune disease. Investigations have been hampered by a number of factors. First, autoimmune diseases evolve slowly in time from an at risk situation to chronic inflammation and finally full-blown clinical disease and its’ complications. This cannot be easily recapitulated in animal models, resulting in dependence on investigations using patient materials. Second, autoreactive responses are polyclonal and autoantigens and autoepitopes vary between individuals and in time within individuals. Third, the assays used to deduct B cell pathogenicity capture mostly single aspects of biological function and have inherent technical limitations. For example, autoantibody protein sequences and molecular composition cannot be resolved by conventional detection methods such as ELISA, immunoblotting and nephelometry. In light of these factors, there is a growing need for more advanced tools in order to study human autoantibodies and autoreactive B cells.
Omics have emerged as powerful tools in molecular research, smoothing the path towards biomarker discovery, new diagnostic and intervention strategies. In autoreactive repertoire research, single-cell sorting and high throughput RNA and DNA sequencing methods have provided information on Ig molecular composition at the B cell level. Mass spectrometry-based proteomics is a powerful tool to characterize secreted (serum) autoantibodies by identifying their immunoglobulin variable region (IgV) subfamily usage and mutational profiles at the level of the autoantibody proteome. However, each technology has its’ limitations. For example, peripheral blood BCR transcriptomes correlate poorly with the actual secreted antibody repertoire at a given time, and a limitation of isolated proteomic workflows is that clonality is difficult to establish due to the lack of reference databases for rearranged V-D-J segments. Therefore, integrated omics are generally required to provide different layers of information on autoreactive repertoires in the blood and tissues.
The current Research Topic aims to collect recent work on the application of omics strategies to characterize pathogenic autoantibodies and the autoreactive B cell repertoire in autoimmune diseases, thereby facilitating diagnosis and therapeutic intervention.
We invite contributions to this article collection addressing these specific aspects in the form of Original Research, Review, Perspective, and Methods articles. We welcome manuscripts related to, but not limited to:
• Omics approaches to reveal the molecular and pathological characteristics of autoantibody repertoires in tissue, serum and or other body fluid
• Omics analysis to investigate the role of autoreactive B cells in the pathogenesis of autoimmune diseases
• Advanced machine learning providing increasing power and capacities of omics data acquisition and analysis
• Autoantibodies as biomarkers in the diagnosis, treatment, and prognosis of autoimmune diseases utilizing different omics technologies
• Current challenges and future of omics approaches in autoreactive repertoire profiling
Autoimmune diseases are chronic conditions characterized by dysregulation of the immune system resulting in inflammation and multi-tissue damage. They are a poorly understood group of diseases, including rheumatoid arthritis (RA), Sjögren's syndrome (SS), systemic lupus erythematosus (SLE) and type I diabetes, among others. The effective management of patients with autoimmune diseases has been hampered by delays in diagnosis (often for years) combined with a lack of effective treatments. Accordingly, identification of early diagnostic biomarkers and therapeutic targets are important challenges facing the autoimmune disease research community.
Autoantibodies have a proven role as diagnostic biomarkers in autoimmune diseases and continue to be an important entry point for basic and clinical research into human autoimmunity. The pathogenic role of these autoantibodies is suggested by animal experiments and clinical observations. Despite being discovered several decades ago, little is known about the nature and pathogenic role of the autoreactive B cell and secreted autoantibody repertoires in autoimmune disease. Investigations have been hampered by a number of factors. First, autoimmune diseases evolve slowly in time from an at risk situation to chronic inflammation and finally full-blown clinical disease and its’ complications. This cannot be easily recapitulated in animal models, resulting in dependence on investigations using patient materials. Second, autoreactive responses are polyclonal and autoantigens and autoepitopes vary between individuals and in time within individuals. Third, the assays used to deduct B cell pathogenicity capture mostly single aspects of biological function and have inherent technical limitations. For example, autoantibody protein sequences and molecular composition cannot be resolved by conventional detection methods such as ELISA, immunoblotting and nephelometry. In light of these factors, there is a growing need for more advanced tools in order to study human autoantibodies and autoreactive B cells.
Omics have emerged as powerful tools in molecular research, smoothing the path towards biomarker discovery, new diagnostic and intervention strategies. In autoreactive repertoire research, single-cell sorting and high throughput RNA and DNA sequencing methods have provided information on Ig molecular composition at the B cell level. Mass spectrometry-based proteomics is a powerful tool to characterize secreted (serum) autoantibodies by identifying their immunoglobulin variable region (IgV) subfamily usage and mutational profiles at the level of the autoantibody proteome. However, each technology has its’ limitations. For example, peripheral blood BCR transcriptomes correlate poorly with the actual secreted antibody repertoire at a given time, and a limitation of isolated proteomic workflows is that clonality is difficult to establish due to the lack of reference databases for rearranged V-D-J segments. Therefore, integrated omics are generally required to provide different layers of information on autoreactive repertoires in the blood and tissues.
The current Research Topic aims to collect recent work on the application of omics strategies to characterize pathogenic autoantibodies and the autoreactive B cell repertoire in autoimmune diseases, thereby facilitating diagnosis and therapeutic intervention.
We invite contributions to this article collection addressing these specific aspects in the form of Original Research, Review, Perspective, and Methods articles. We welcome manuscripts related to, but not limited to:
• Omics approaches to reveal the molecular and pathological characteristics of autoantibody repertoires in tissue, serum and or other body fluid
• Omics analysis to investigate the role of autoreactive B cells in the pathogenesis of autoimmune diseases
• Advanced machine learning providing increasing power and capacities of omics data acquisition and analysis
• Autoantibodies as biomarkers in the diagnosis, treatment, and prognosis of autoimmune diseases utilizing different omics technologies
• Current challenges and future of omics approaches in autoreactive repertoire profiling
