Dissecting type I and II interferon impacts on human immune cells in disease by a cell type-specific interferon response atlas
Nicholas MossiD, Catalina SakaiiD, N KauliD, Lucas T. GraybuckiD, Samir Rachid ZaimiD, Melinda L. Angus-HilliD, Yudong D. HeiD, Erik D. LaytoniD, Paige L. BouvatteiD, Peter J. WittigiD, Christian M. LaFranceiD, Tao PengiD, Marla C. GlassiD, Upaasana KrishnaniD, Aishwarya ChanderiD, Erin K. KaweloiD, Jessica GarberiD, Julian ReadingiD, Stephanie D. Anover-SombkeiD, Mary KwokiD, Damian J. GreeniD, Ananda W. GoldrathiD, Mikael SigvardssoniD, Peter J. SkeneiD, Xiaojun LiiD, , Emma Lo KuaniD
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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