Literature DB >> 27259330

Transcriptomic Segregation of Human Autoantigens Useful for the Diagnosis of Autoimmune Diseases.

Peter D Burbelo1, Michael J Iadarola2, Ilias Alevizos3, Matthew R Sapio2.   

Abstract

The measurement of autoantibodies in the clinical care of autoimmune patients allows for diagnosis, monitoring, and even disease prediction. Despite their clinical utility, the functional significance of autoantibody target proteins in many autoimmune diseases remains unclear. Here we present a comprehensive review of 52 autoantigens commonly employed for the serological diagnosis of 24 autoimmune diseases. We discuss their function, whether they have extracellular-exposed epitopes, and whether antibodies to these proteins are known to be pathogenic. Transcriptomics (RNA-Seq) datasets were mined to display messenger RNA (mRNA) expression of the autoantigens across 32 tissues and organs. This analysis revealed that autoantigens cluster into one of three groups: expression in the tissue most strongly affected in the disease (Group I), ubiquitous expression with enrichment in immune tissues (Group II), or expression in other tissues not typically associated with the clinical presentation (Group III). Clustering demonstrated that the autoantigens within Group I were often proteins containing extracellular epitopes, many of which are targets of pathogenic autoantibodies. Group II autoantigens were targets for several rheumatological diseases, including Sjögren syndrome, systemic lupus erythematosus, myositis, and systemic sclerosis, and were ubiquitously expressed with enrichment in immune-rich tissues. This raises the possibility that immune cells in Group II disorders may be the source of autoimmunization and/or targets of immune cell responses. Since tissues showing enriched autoantigen gene expression may contribute to the development of autoantibodies and subsequent autoimmunity, the emergent patterns arising from the autoantigen transcriptomic profiles may provide a new heuristic framework to deconvolute these complex disorders.

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Year:  2016        PMID: 27259330      PMCID: PMC5023465          DOI: 10.1007/s40291-016-0211-6

Source DB:  PubMed          Journal:  Mol Diagn Ther        ISSN: 1177-1062            Impact factor:   4.074


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