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        <identifier>oai:researchdata.se:doi-10-17044-scilifelab-26318929/0</identifier>
        <datestamp>2024-07-22</datestamp>
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        <setSpec>subject:ssif:10605</setSpec>
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        <setSpec>principal:slug:royal-institute-of-technology</setSpec>
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          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>http://purl.org/dc/dcmitype/Dataset</dc:type>
          <dc:identifier>https://doi.org/10.17044/SCILIFELAB.26318929</dc:identifier>
          <dc:title xml:lang="en">Prevalent and persistent new-onset autoantibodies in mild to severe COVID-19</dc:title>
          <dc:creator>https://orcid.org/0000-0002-7773-1851</dc:creator>
          <dc:creator>Lovisa Skoglund</dc:creator>
          <dc:creator>https://orcid.org/0000-0002-2158-2674</dc:creator>
          <dc:creator>Ronald Sjöberg</dc:creator>
          <dc:creator>Hanna Tegel</dc:creator>
          <dc:creator>Sophia Hober</dc:creator>
          <dc:creator>Elham Rostami</dc:creator>
          <dc:creator>Annica Rasmusson</dc:creator>
          <dc:creator>https://orcid.org/0000-0001-7876-7779</dc:creator>
          <dc:creator>https://orcid.org/0000-0003-1671-8183</dc:creator>
          <dc:creator>Charlotte Thålin</dc:creator>
          <dc:creator>https://orcid.org/0000-0002-0056-1313</dc:creator>
          <dc:creator>https://orcid.org/0000-0002-4657-8532</dc:creator>
          <dc:subject xml:lang="en">Medical and Health Sciences</dc:subject>
          <dc:subject xml:lang="sv">Medicin och hälsovetenskap</dc:subject>
          <dc:subject xml:lang="en">Autoimmunity and Inflammation</dc:subject>
          <dc:subject xml:lang="sv">Autoimmunitet och inflammation</dc:subject>
          <dc:subject xml:lang="en">Immunology</dc:subject>
          <dc:subject xml:lang="sv">Immunologi</dc:subject>
          <dc:description xml:lang="en">Note: The DOI of the related paper will be provided upon publication.

These datasets contain information on autoantibody and anti-SARS-CoV-2 IgG levels.

In this study, 478 healthcare workers and 48 patients were followed prospectively over 5 visits from May 2020 to Sept 2021. SARS-CoV-2 serology and autoantibodies were assessed using planar and bead-based arrays. Detected epitopes were validated in blood and cerebrospinal fluid from two independent cohorts of Neuro-COVID patients (n=25) and pre-pandemic healthy controls (n=29).

The datasets contain:

- SARS-CoV-2 serological profiles measured in all samples (above) using 3-plex bead arrays. The data is reported as raw and normalized MFI (AU) and compound serostatus.
- Proteome-wide autoantibody profiles measured in 12 sample pools using planar arrays. The data is reported as median fluorescent intensity, in raw and normalized arbitrary units (MFI [AU]), and reactivity classification.
- Targeted autoantibody profiles measured in 478 healthcare workers and 48 patients across 5 time points using 363-plex bead arrays. The data is reported as raw and normalized MFI (AU), fold change (FC) across infection, and new-onset classification.
- Peptide epitope mapping autoantibody profiles measured in a 142 healthcare workers and COVID-19 patients across 2 time points, and all Neuro-COVID patients (n=25) and pre-pandemic healthy controls (n=29), using 93-plex bead arrays. The data is reported as raw and normalized MFI (AU), and fold change (FC) across infection.
Source data is provided with the paper.

Access to this individual-level human data can be granted for non-commercial validation purposes and upon reasonable request to the provided contact. A reasonable request should contain the following:

- Name of PI and host organization
- Contact details
- The scientific purpose of the data access request
- Commitment to inform when the data has been used in a publication
- Commitment not to host or share the data outside the requesting organization
- Statement of non-commercial use of data</dc:description>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
          <dc:publisher xml:lang="en">Royal Institute of Technology</dc:publisher>
          <dc:publisher xml:lang="sv">Kungliga Tekniska högskolan</dc:publisher>
          <dc:date>2024-07-22T00:00:00Z</dc:date>
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