Presenter of 1 Presentation
O024 - IDENTIFICATION OF AUTOANTIBODIES IN LONG-COVID PATIENTS BY ENGINE HEALTHY ALIGNMENT (ID 424)
Abstract
Background and Aims
Background and aims: Protein arrays are a powerful tool to identify autoreactive proteins in clinical samples for various disorders. But the achieved data must be validated by comparison with reference samples of healthy and self-reported healthy donors. Engine developed the ENGINE HEALTHY ALIGNMENT for search on potential autoantibodies. This new database can be applied for identification of autoantibodies in patients of various disorders. Here, samples of Long-Covid patients were used as clinical application model.
Methods
Methods: Human sera from healthy donors (20) and patients with previous SARS-CoV-2 infection and long term clinical symptoms were screened using engine array 1008 (15.000 human proteins; expression host: E.coli), to identify autoantibodies in healthy individuals in comparison to SARS-CoV-2-induced autoantibodies. After incubation of diluted sera, detection was performed using anti-human-IgG-AP-secondary antibody. Signals were declared positive if comparable signal intensities for duplicate clones were distinguishable from background.
Results
Results: ENGINE HEALTHY ALIGNMENT was successfully used to identify autoreactive proteins in Long-Covid patients. For healthy reference cohort positive and negative signal should be found in the majority of analyzed samples. For pathological samples, possible candidates of reactive autoantibodies were only considered if protein arrays showed positive signals for one target protein in at least 2 different donor serums.
Conclusions
Conclusion: The availability of a valid reference cohort is crucial for fast and reliable identification of pathological candidates. The inclusion of sufficient data of healthy controls and comparison of this data with different clinical projects will be the base for reliable identification of disease related autoantibodies.