Simultaneous Distinction of Monospecific and Mixed DFS70 Patterns During ANA Screening with a Novel HEp-2 ELITE/DFS70 Knockout Substrate

2018 
Systemic autoimmune connective tissue disorders are characterized by circulating antinuclear antibodies (ANA). Although there are several technologies available for ANA screening, indirect immunofluorescence (IIF) using Human epithelial cells-2 (HEp-2) substrate remains the primary and recommended method because of its superior sensitivity. HEp-2 substrates can detect a multitude of patterns resulting from autoantibody binding to various protein and nucleic acid autoantigens distributed throughout the nucleus and cytoplasm of the cells. The great diversity of monospecific and mixed patterns resulting from positive reactions on HEp-2 substrate also complicate the interpretation and accuracy of reporting. One specific example which received utmost attention recently is the dense fine speckled 70 (DFS70) pattern resulting from autoantibodies that specifically bind to a protein called lens epithelium derived growth factor (LEDGF). Lack of clear association with a specific systemic autoimmune disease and high prevalence in healthy populations have made accurate interpretation of DFS70 pattern important. Accurate distinction of DFS70 pattern from disease-associated patterns using conventional HEp-2 substrate is challenging. Moreover, frequent co-occurrence of DFS70 pattern along with disease-associated patterns such as homogeneous, speckled, and mixed homogeneous-speckled patterns complicate the IIF interpretation. The goal of this paper is to demonstrate the utility of a novel engineered HEp-2 IIF substrate that retains all advantages of conventional HEp-2 substrate while simultaneously providing the ability to distinguish DFS70 pattern with high confidence in both monospecific and mixed ANA positive examples. The new substrate is further able to unmask disease-associated ANA patterns previously concealed by DFS70 pattern.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    3
    Citations
    NaN
    KQI
    []