Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections.

Communications medicine(2024)

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摘要
BACKGROUND:Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored. METHODS:Our study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information. RESULTS:Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors. CONCLUSIONS:Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.
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