A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease
Ana-Maria CujbaiD, Sergio Aguilar-FernándeziD, Adrien Antoinette, Wamia SaidiD, Michaela MülleriD, Kian Hong KockiD, Jacquelyn NestoriD, Radhika SonthaliaiD, Eliora Violain BuyaminiD, Pragya RawatiD, Alexander V. PredeusiD, Lorenz KretschmeriD, Lijiang FeiiD, Kamil SlowikowskiiD, Pritha SeniD, Christopher V. CosgriffiD, MGH COVID-19 Collection & Processing Team, Olli DufvaiD, Mohamad AskariiD, Kyle KimleriD, Mary FuteyiD, Ida ZucchiiD, Arsenios ChatzigeorgiouiD, Parisa NejadiD, Liying JiniD, , Gary ReynoldsiD
Abstract
Blood provides an accessible window into human health, yet the absence of a peripheral blood mononuclear cells (PBMCs) reference with standardized immune cell annotations has constrained comparisons between single-cell RNA sequencing (scRNAseq) studies. Here, we present HARP (Human Cell Atlas Reference for PBMCs), an integrated atlas of ~9 million PBMCs from >2,600 donors across 15 studies spanning four continents, encompassing diverse populations, neonates to 97 years, across health and diverse immune-related diseases. We developed optimized integration workflows, including novel label-free metrics to assess integration quality, and generated community-driven consensus annotations for 192 immune cell subsets, identifying rare populations representing as few as 0.004% of PBMCs. HARP reveals coordinated cellular modules associated with age, sex, and disease, identifies female-biased interferon and inflammatory gene programs and their perturbation by COVID-19, and uncovers a novel sexual dimorphism in prostaglandin signaling. Finally, we introduce scTiger, a hierarchical label-transfer framework that accurately projects these 192 cell annotations onto ~18 million additional PBMCs, providing a robust and transferable reference for harmonizing future PBMC studies. HARP provides a high-resolution community-driven reference atlas for PBMC annotation and analysis, as a basis for emerging clinical applications of single-cell genomics.
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