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Autoantibody profiling in autoimmune diseases

Time: Fri 2023-06-02 13.00

Location: Atrium, Nobels väg 12B, Solna

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Language: English

Subject area: Biotechnology

Doctoral student: Shaghayegh Bayati , Affinitets-proteomik, Science for Life Laboratory, SciLifeLab, SciLifeLab, Nilsson Lab

Opponent: Professor Peter Heeringa, University of Groningen

Supervisor: Professor Peter Nilsson, Affinitets-proteomik; Doktor Elisa Pin, Affinitets-proteomik

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QC 2023-05-11


Autoimmune disease diagnosis and definition of prognosis can be challenging. Patients with the same autoimmune disease could present with very heterogeneous symptoms. Therefore, there is a need to understand the disease better to improve patients’ diagnosis, and classification, and tailor the treatment. Autoantibodies are a hallmark of many autoimmune diseases. They are antibodies produced by B cells and targeting self-antigens. Autoantibodies could be useful as diagnostic and prognostic markers of autoimmune disease.

Protein arrays enable multiplex and high-throughput profiling of autoantibodies, therefore representing a good tool for autoantibody markers discovery and validation. This thesis presents the work performed to study autoantibodies in ANCA Associated Vasculitis (AAV) and Systemic Sclerosis (SSc) by employing planar and bead-based antigen arrays. Moreover, this thesis also includes the work done to optimize the application of a multiplex serology assay for the detection of anti-SARS-CoV-2 antibodies in saliva.

In paper 1, we aimed to perform a broad autoantibody profiling in serum samples of AAV patients to search for new autoantibodies associated with the disease or disease subgroups and activity. The main result is related to the identification of anti-KIF5C antibodies at high prevalence in anti-MPO-positive patients and patients with microscopic polyangiitis (MPA). Anti-KIF4A also showed a higher prevalence in anti-MPO positive and MPA patients.

In Paper 2 an in-depth autoantibody profiling was performed to identify autoantibodies as candidates for future relapse prediction in the plasma of AAV patients. We tested samples from patients classified as long-term remission-off-therapy (LTROT) and patients suffering future flares. Nine autoantibodies were found with higher reactivity in the relapse group. Among these, anti-ATF3 antibodies had increased reactivity in patients with kidney and ENT symptoms.

In paper 3, plasma samples from SSc patients and controls were tested to detect autoantibodies associated with fibrosis. We identified eleven autoantibodies with increased prevalence in patients with systemic sclerosis compared to the control group. Eight of these autoantibodies are new in the context of systemic sclerosis and all bind to proteins that are involved in fibrosis. Among these, the anti-AKT3 was shown to be more reactive in patients with skin and lung fibrosis and anti-PIP4K2B in patients that were negative for the available diagnostic marker.

Finally, in paper 4, a multiplex bead-based array serological assay was optimized to detect anti-SARS-CoV-2–specific IgG and IgA in saliva samples. This method was developed to measure antibodies, using SARS-CoV-2 spike and nucleocapsid proteins.

In conclusion, the described work shows the application of the protein array technology to identify (auto)antibodies in different body fluids and within autoimmune diseases and SARS-CoV-2 infection. Moreover, we have identified autoantibody targets that are worth further investigation for their usefulness in better understanding some autoimmune conditions.