Autoantibodies against PIP4K2B and AKT3 Are Associated with Skin and Lung Fibrosis in Patients with Systemic Sclerosis
Dataset from Geroldinger-Simic, M.; Bayati, S.; Pohjanen, E.; et al. Autoantibodies against PIP4K2B and AKT3 Are Associated with Skin and Lung Fibrosis in Patients with Systemic Sclerosis. Int J Mol Sci. Accepted on March 2023 Abstract: Systemic sclerosis (SSc) is a rare autoimmune systemic disease that leads to decreased survival and quality of life due to fibrosis, inflammation, and vascular damage in the skin and/or vital organs. Early diagnosis is crucial for clinical benefit in SSc patients. Our study aimed to identify autoantibodies in the plasma of SSc patients that are associated with fibrosis in SSc. Initially, we performed a proteome-wide screening on sample pools from SSc patients by untargeted autoantibody screening on a planar antigen array (including 42,000 antigens representing 18,000 unique proteins). The selection was complemented with proteins reported in the literature in the context of SSc. A targeted antigen bead array was then generated with protein fragments representing the selected proteins and used to screen 55 SSc plasma samples and 52 matched controls. We found eleven autoantibodies with a higher prevalence in SSc patients than in controls, eight of which were associated with fibrosis. Combining these autoantibodies in a panel could lead to the subgrouping of SSc patients with fibrosis. Anti-Phosphatidylinositol-5-phosphate 4-kinase type 2 beta (PIP4K2B)- and anti-AKT Serine/Threonine Kinase 3 (AKT3)-antibodies should be further explored to confirm their association with skin and lung fibrosis in SSc patients. This dataset contains relative continuous as well as binarized autoantibody data, with associated clinical data on the presence of currently clinically available autoantibody biomarkers (e.g. anti-Scl70 and anti-centromere antibodies) and symptomes (e.g. mRSS score, lung fibrosis, digital ulcers, Raynauds, reflux, sicca). Data Access Statement These data constitute sensitive personal information that fall under the GDPR. Therefore, access to data and related code is restricted. The data can be made available for validation purposes, upon reasonable request and in accordance with GDPR. A reasonable request should contain: 1) Name of PI and host organisation 2) Contact details 3) Scientific purpose of data access request 4) Commitment to inform when the data has been used in a publication 5) Commitment not to host or share the data outside the requesting organisation 6) Statement of non-commercial use of data
HEalth data LInkage for ClinicAL benefit