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Interpretable Inflammation Landscape of Circulating Immune cells (ILCIC_BRCA)

GSE248685 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/10/13 Platform GPL24676
Summary
Inflammation is a biological phenomenon beneficial for homeostasis, but unfavorable if dysregulated. Although major progress has been made in characterizing inflammation in specific diseases, a global, holistic understanding is still elusive. This is particularly intriguing, considering its function for human health and the potential for modern medicine if fully deciphered. Here, we leveraged advances in single-cell transcriptomics to delineate inflammatory processes of circulating immune cells during infection, immune-mediated inflammatory diseases and cancer. Our single-cell atlas of >6.5 million peripheral blood mononuclear cells from 1047 patients (56% female, 43% male) and 19 diseases allowed us to learn a comprehensive model of inflammation in circulating immune cells. The atlas expanded our current knowledge of the biology of inflammation of immune-mediated diseases, acute and chronic inflammatory diseases, infection and solid tumors, and laid the foundation to develop a disease classification framework using unsupervised as well as explainable machine learning. Beyond a disease-centered analysis, we charted altered activity of inflammatory molecules in peripheral blood cells, depicting discriminative inflammation-related genes to further understand mechanisms of inflammation. We present a rich resource for the community, and laid the groundwork for learning a classifier for inflammatory diseases, presenting cells in circulation as a potential tool for disease classification.
Published in
Interpretable inflammation landscape of circulating immune cells
Jiménez-Gracia L, Maspero D, Aguilar-Fernández S et al. · Nature medicine 2026 · PMID 41526507 · doi:10.1038/s41591-025-04126-3
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Direct links to NCBI, no account and no request form: the whole study as GSE248685_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1045593 and SRA study SRP474440. Searching any of these in the dataset finder brings you back here.

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