(159) Cross-disease single-cell surface protein atlas reveals shared and disease-specific immune phenotypes across 2,000 donors and 40+ immune conditions

Introduction/Rationale: Large-scale single-cell RNA sequencing has revealed blood cell diversity and disease-related changes, but these insights rarely translate into clinical biomarkers. Surface protein expression, by contrast, is easily measured and clinically applied, bridging transcripts and functional phenotypes. By mapping the surface proteome across diverse pathologies, we aim to identify disease-associated cell populations, enable their functional study, and support the development of clinically relevant diagnostic tools.

Methods: We generated combined scRNAseq and CITEseq from analyzed XX million peripheral blood mononuclear cells and combined this with external datasets to generate a combined dataset from 40 conditions including ,immune phenotypes in health, infection, autoimmunity, and checkpoint-related toxicity.

Results: Cross-disease integration revealed both conserved and context-specific remodeling of the immune proteome. Canonical lineage markers (CD4, CD8, CD19, CD14, CD56) remained stable, while activation and regulatory markers showed condition-specific modulation. Autoimmune and checkpoint-related conditions converged on shared signatures of peripheral activation and exhaustion, whereas infectious diseases showed transient effector upregulation. Protein–transcript decoupling highlighted post-transcriptional regulation as a key source of immune heterogeneity.

Conclusion: Large-scale CITE-seq integration reveals conserved immune phenotypes and distinct protein remodeling across disease contexts. These data establish a cross-disease immune reference linking surface markers to transcriptional states and support biomarker discovery and therapeutic stratification across immune-mediated disorders.