Exploration of immune phenotypes in self-sampling citizens

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Authors: Leo Dahl, Annika Bendes, Maria Bueno Alvez, Vincent Albrecht, Hooman Aghelpasand, Sofia Björkander, Simon Kebede Merid, Anja Mezger, Max Käller, Claudia Fredolini, Åsa Torinsson Naluai, Olof Beck
+5 more Erik Melén, Stefan Bauer, Magnus Gisslén, Niclas Roxhed, Jochen Schwenk
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Abstract

This dataset contains levels of circulating antibodies and proteins measured in dried blood spot (DBS) samples. Study participants from the general population in Stockholm and Gothenburg (Sweden) self-sampled blood using sampling kits (Capitainer AB) during the spring of 2021.Levels of circulating antibodies were determined by multi-analyte serology using the Luminex platform. The data has been processed and normalised using a mixed model, followed by a Z-score transformation.Levels of circulating proteins were determined by proximity extension assays using the Olink Explore Inflammation panel from the Olink platform and NULISA-Seq using the 250-plex inflammation panel from Alamar Biosciences. The raw data has been processed using ProtPQN, followed by a Z-score transformation.The files contain the following data and information:antigen_info.csv: Information about the antigens used in the serology assays.protein_data.csv: Proteomics measurements in wide format (each row a sample, each column a protein).protein_info.csv: Information about the proteins included in the proteomics assays.sample_info.csv: Information about the samples.serology_data.csv: Serological measurements in wide format.readme.txt: Additional details about the file contents.Access to this 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 organisationContact detailsThe scientific purpose of the data access requestCommitment to inform when the data has been used in a publicationCommitment not to host or share the data outside the requesting organisationStatement of non-commercial use of data

Publication details

Journal / source
SciLifeLab Data Repository
Publication date
1 January 2026
Document type
Dataset