ArticleiScience2026
Development, validation, and implementation of the antibody-secreting cell maturity index: Universal prediction of human plasma cell maturity.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
Defining the maturity of long-lived antibody-secreting cells (ASCs) is important for vaccine optimization and research into autoimmune diseases, but current assessment of plasma cell maturity is limited. We developed a universal, robust method to define plasma cell maturity using a meta-analysis of public, human cytometry data, with harmonized expression of ASC maturity markers across samples. Vaccination or infection samples were selected to train a random forest-based machine learning prediction model (performance of r = 0.866). After evaluation (performance of r = 0.616), the final model, named the antibody-secreting cell maturity index (ASC-ME), was applied to compartments with long-term ASC survival niches, namely bone marrow and gut. Both compartments showed increased ASC maturity, biologically validating the ASC-ME model. Example analyses highlight the broad spectrum for model application, e.g., in vaccine research, clinical trials or in ASC-related autoimmune diseases. Overall, our ASC-ME model, accessible via an online platform, offers a robust approach in evaluating ASC maturity.
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