Frontiers in cell and developmental biology · 2026
Multi-omics mapping of PSC genetic risk to a high TWAS-active JAML+ lipid-associated macrophage program: bridging single-cell heterogeneity, spatial fibrotic niches, and machine learning selection.
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Du Zhongyan, Xu Zhihao, Yang Chenxiao, Zhang Yuanyuan, Jiang Quan, Wang Xiaolan
Аннотация
BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease with progressive peribiliary inflammation and fibrosis. Disease-modifying therapies are lacking, and the cell-type-specific mechanisms linking genetic susceptibility to pathogenic immune states remain incompletely understood.
METHODS: We performed a transcriptome-wide association study (TWAS) using PSC GWAS summary statistics and GTEx v8 liver eQTL weights. TWAS-prioritized genes were mapped onto a PSC liver single-cell RNA-seq atlas (GSE247128) using integrated gene set scoring (irGSEA). Monocyte/macrophage subsets were re-clustered and lipid-associated macrophages (LAMs) were stratified by TWAS activity. Core genes distinguishing high-versus low-activity LAMs were identified using seven machine-learning feature selection algorithms. JAML was validated in bulk transcriptomic cohorts (GSE119600, GSE177044), evaluated by immune infiltration analysis, examined by cell-cell communication inference (CellChat), assessed by virtual knockout (scTenifoldKnk), and spatially localized using Visium FFPE spatial transcriptomics (PSC: GSE245620; control: GSE240429), and validated at the protein level using Western blot and ELISA in an in vitro macrophage model.
RESULTS: TWAS activity was predominantly enriched in the monocyte/macrophage lineage. Within this lineage, LAMs (TREM2+ GPNMB+ APOC1+) showed the highest TWAS activity and occupied late pseudotime states. High-activity LAMs were enriched in fibrosis-related pathways (e.g., TGF-β, NOTCH, WNT/β-catenin) and innate immune pathways (e.g., TLR2/4-MAPK, NLRP3 inflammasome). Multi-algorithm feature selection identified JAML (AMICA1) as a core discriminator of high-versus low-activity LAMs. JAML was upregulated in PSC in bulk cohorts, associated with higher macrophage and lower activated CD8+ T-cell infiltration, showed enhanced cell-cell communication signatures, and spatially co-localized with LAM and fibrosis scores in PSC tissue sections. In vitro, JAML upregulation accompanied NF-κB p65 phosphorylation and PD-L1 expression in LPS/IL-6-stimulated macrophages, and JAML knockdown attenuated these responses.
CONCLUSION: Integrating TWAS with single-cell and spatial transcriptomics highlights a genetically linked, highly active LAM state in PSC and nominates JAML + LAMs as a testable effector population potentially connecting genetic susceptibility to peribiliary fibrosis, with in vitro evidence supporting a JAML/NF-κB/PD-L1 inflammatory axis.
METHODS: We performed a transcriptome-wide association study (TWAS) using PSC GWAS summary statistics and GTEx v8 liver eQTL weights. TWAS-prioritized genes were mapped onto a PSC liver single-cell RNA-seq atlas (GSE247128) using integrated gene set scoring (irGSEA). Monocyte/macrophage subsets were re-clustered and lipid-associated macrophages (LAMs) were stratified by TWAS activity. Core genes distinguishing high-versus low-activity LAMs were identified using seven machine-learning feature selection algorithms. JAML was validated in bulk transcriptomic cohorts (GSE119600, GSE177044), evaluated by immune infiltration analysis, examined by cell-cell communication inference (CellChat), assessed by virtual knockout (scTenifoldKnk), and spatially localized using Visium FFPE spatial transcriptomics (PSC: GSE245620; control: GSE240429), and validated at the protein level using Western blot and ELISA in an in vitro macrophage model.
RESULTS: TWAS activity was predominantly enriched in the monocyte/macrophage lineage. Within this lineage, LAMs (TREM2+ GPNMB+ APOC1+) showed the highest TWAS activity and occupied late pseudotime states. High-activity LAMs were enriched in fibrosis-related pathways (e.g., TGF-β, NOTCH, WNT/β-catenin) and innate immune pathways (e.g., TLR2/4-MAPK, NLRP3 inflammasome). Multi-algorithm feature selection identified JAML (AMICA1) as a core discriminator of high-versus low-activity LAMs. JAML was upregulated in PSC in bulk cohorts, associated with higher macrophage and lower activated CD8+ T-cell infiltration, showed enhanced cell-cell communication signatures, and spatially co-localized with LAM and fibrosis scores in PSC tissue sections. In vitro, JAML upregulation accompanied NF-κB p65 phosphorylation and PD-L1 expression in LPS/IL-6-stimulated macrophages, and JAML knockdown attenuated these responses.
CONCLUSION: Integrating TWAS with single-cell and spatial transcriptomics highlights a genetically linked, highly active LAM state in PSC and nominates JAML + LAMs as a testable effector population potentially connecting genetic susceptibility to peribiliary fibrosis, with in vitro evidence supporting a JAML/NF-κB/PD-L1 inflammatory axis.