Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution.

Publication date: Jul 28, 2025

Current molecular quantitative trait locus catalogs are mostly at bulk resolution and centered on Europeans. Here, we constructed an immune cell atlas with single-cell transcriptomics of >1. 5 million peripheral blood mononuclear cells, host genetics, plasma proteomics and gut metagenomics from 235 Japanese persons, including patients with coronavirus disease 2019 (COVID-19) and healthy individuals. We mapped germline genetic effects on gene expression within immune cell types and across cell states. We elucidated cell type- and context-specific human leukocyte antigen (HLA) and genome-wide associations with T and B cell receptor repertoires. Colocalization using dynamic genetic regulation provided better understanding of genome-wide association signals. Differential gene and protein expression analyses depicted cell type- and context-specific effects of polygenic risks. Various somatic mutations including mosaic chromosomal alterations, loss of Y chromosome and mitochondrial DNA (mtDNA) heteroplasmy were projected into single-cell resolution. We identified immune features specific to somatically mutated cells. Overall, immune cells are dynamically regulated in a cell state-dependent manner characterized with multiomic profiles.

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Concepts Keywords
Atlas Cell
Coronavirus Cells
Japanese Context
Loss Dependent
Transcriptomics Expression
Genetic
Genome
Immune
Including
Resolution
Single
Specific
State
Type
Wide

Semantics

Type Source Name
disease IDO cell
disease IDO blood
disease IDO host
disease MESH coronavirus disease 2019
drug DRUGBANK Tropicamide
disease IDO protein

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