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Abstract

Interferons (IFNs) orchestrate diverse immune responses, but distinguishing individual IFN contributions in human transcriptomic data is challenging due to overlapping interferon-stimulated gene (ISG) signatures and limited cell-type-specific datasets. To address this, we generated a single-cell transcriptomic atlas of IFN responses by stimulating primary human T, B, NK, and CD14 monocytes with IFN-I, IFN-II, and IFN-III. This revealed core and cell-type-specific ISG programs across 13 subsets, highlighting distinct functions of IFNs. We developed an algorithm to separate IFN-I and IFN-II activity in transcriptomic data. Applied to multiple myeloma samples, it showed elevated IFN-I and IFN-II responses, with induction therapy reducing only IFN-I. Extending to multiple disease datasets provided a cross-disease overview of IFN-I and IFN-II activities and revealed increased IFN-II activities in T cells during lupus flares. This resource and the accompanying analytical framework enable dissection of IFN-driven transcriptional programs in a cell-type specific manner in human disease.

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02 /Specification & Classification

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