Determination of Subset-Restricted Anti-neutrophil Cytoplasmic Antibodies (ANCA) by Immunofluorescence Cytochemistry

Antieosinophil Antibodies Alone or in Combination with Antineutrophil Cytoplasmic Antibodies (ANCA) Detected in Different Autoimmune Conditions

Circulating antieosinophil antibodies (AEOSA) have been associated with various autoimmune conditions affecting the liver, kidneys, lungs, and joints but are not part of routine clinical diagnostics. While analyzing human sera for antineutrophil cytoplasmic antibodies (ANCA) by indirect immunofluorescence (IIF) on granulocytes, 0.8% of analyzed samples were found to be reactive with eosinophils. Our aim was to determine the diagnostic relevance and antigenic specificity of AEOSA. AEOSA were seen either in combination with an myeloperoxidase (MPO)-positive p-ANCA (44%; AEOSA+/ANCA+) or on their own (56%; AEOSA+/ANCA-). AEOSA/ANCA positivity was seen in patients with thyroid disease (44%) or vasculitis (31%), while AEOSA+/ANCA- pattern was more common in patients with autoimmune disorders of the gastrointestinal tract and/or liver. Eosinophil peroxidase (EPX) was the main target recognized in 66% of the AEOSA+ sera by enzyme-linked immunosorbent assay (ELISA). Eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN) were also identified as target antigens but less frequently and only in combination with EPX. In conclusion, we confirmed that EPX is a major target of AEOSA, illustrating the high antigenic potential of EPX. Our results also demonstrate the presence of concomitant AEOSA/ANCA positivity in a defined patient group. Further research should aim to elucidate the association of AEOSA with autoimmunity.

Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome

Sepsis is defined as dysregulated host response caused by systemic infection, leading to organ failure. It is a life-threatening condition, often requiring admission to an intensive care unit (ICU). The causative agents and processes involved are multifactorial but are characterized by an overarching inflammatory response, sharing elements in common with severe inflammatory response syndrome (SIRS) of non-infectious origin. Sepsis presents with a range of pathophysiological and genetic features which make clinical differentiation from SIRS very challenging. This may reflect a poor understanding of the key gene inter-activities and/or pathway associations underlying these disease processes. Improved understanding is critical for early differential recognition of sepsis and SIRS and to improve patient management and clinical outcomes. Judicious selection of gene biomarkers suitable for development of diagnostic tests/testing could make differentiation of sepsis and SIRS feasible. Here we describe a methodologic framework for the identification and validation of biomarkers in SIRS, sepsis and septic shock patients, using a 2-tier gene screening, artificial neural network (ANN) data mining technique, using previously published gene expression datasets. Eight key hub markers have been identified which may delineate distinct, core disease processes and which show potential for informing underlying immunological and pathological processes and thus patient stratification and treatment. These do not show sufficient fold change differences between the different disease states to be useful as primary diagnostic biomarkers, but are instrumental in identifying candidate pathways and other associated biomarkers for further exploration.