Unveiling the Cellular and Molecular Insights into Ulcerative ColitisPathogenesis through Integrative Multi-omics and Functional Experiments

Introduction: Single-cell RNA sequencing (scRNA-seq) enables the detection of cellular heterogeneity in ulcerative colitis (UC). But there is still inadequate evidence to unravel the causal relationship between differentially expressed genes (DEGs) and UC pathogenesis. This study aimed to comprehensively explore genomic, transcriptomic, proteomic, and scRNA-seq data to provide valuable insights into the molecular basis of UC and identify potential candidate biomarkers Materials and Methods: The GSE125527 single-cell RNA sequencing (scRNA-seq) dataset was subjected to quality control, dimension reduction, and cell identification using the Seurat package. DEGs specific to different cell types were identified. Mendelian randomization (MR) analysis was used to explore the causal relationship between feature DEGs and UC based on data derived from genome-wide association studies (GWAS) (ieu-a-32, 20,464 normal controls and 6968 UC patients), including expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL). Multi-omics data were integrated to verify the genetic regulatory relationships. Further validation of the final hub gene was performed in vitro and in vivo. Results: By analyzing the scRNA-seq dataset, we obtained 48,576 cells that were annotated into 5 different subtypes. A total of 1,905 DEGs were identified in different single-cell subsets. With these DEGs as exposure factors and the GWAS data of UC as outcomes, along with eQTL and pQTL analysis, FCN1 and ING4 were determined to be causally associated with UC. Both genes were effective in differentiating between UC patients and healthy controls. Furthermore, ING4 was lowly expressed in UC intestinal tissues and in LPS-treated intestinal epithelial cells, and it was involved in inflammatory responses. An in vitro functional experiment demonstrated that the knockdown or overexpression of ING4 could regulate the phosphorylation-induced activation of the NF-κB pathway and affect the release of the inflammatory factor iNOS, thereby triggering the occurrence and development of UC. Discussion: From a genetic causality perspective, ING4 emerges as a candidate gene with genetically supported relationship to UC, linking immune-related regulatory variation to epithelial inflammatory responses, while its precise tissue- and cell-type specific mechanisms remain to be clarified. Conclusion: This study emphasizes the importance of integrating multi-omics data in the exploration of UC pathogenesis. These findings position ING4 as a promising candidate biomarker and a potential molecule of therapeutic interest for UC.

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Publication Details

Journal
Combinatorial Chemistry & High Throughput Screening
Published
2026-07-01
DOI
https://doi.org/10.2174/0113862073448366260529224117
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Unveiling the Cellular and Molecular Insights into Ulcerative ColitisPathogenesis through Integrative Multi-omics and Functional Experiments

Yi Han, Junbo Xiao, Jun Yi
Combinatorial Chemistry & High Throughput Screening
Single-cell and spatial transcriptomics
article

Unveiling the Cellular and Molecular Insights into Ulcerative ColitisPathogenesis through Integrative Multi-omics and Functional Experiments

Yi Han, Junbo Xiao, Jun Yi
article en

Abstract

Introduction: Single-cell RNA sequencing (scRNA-seq) enables the detection of cellular heterogeneity in ulcerative colitis (UC). But there is still inadequate evidence to unravel the causal relationship between differentially expressed genes (DEGs) and UC pathogenesis. This study aimed to comprehensively explore genomic, transcriptomic, proteomic, and scRNA-seq data to provide valuable insights into the molecular basis of UC and identify potential candidate biomarkers Materials and Methods: The GSE125527 single-cell RNA sequencing (scRNA-seq) dataset was subjected to quality control, dimension reduction, and cell identification using the Seurat package. DEGs specific to different cell types were identified. Mendelian randomization (MR) analysis was used to explore the causal relationship between feature DEGs and UC based on data derived from genome-wide association studies (GWAS) (ieu-a-32, 20,464 normal controls and 6968 UC patients), including expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL). Multi-omics data were integrated to verify the genetic regulatory relationships. Further validation of the final hub gene was performed in vitro and in vivo. Results: By analyzing the scRNA-seq dataset, we obtained 48,576 cells that were annotated into 5 different subtypes. A total of 1,905 DEGs were identified in different single-cell subsets. With these DEGs as exposure factors and the GWAS data of UC as outcomes, along with eQTL and pQTL analysis, FCN1 and ING4 were determined to be causally associated with UC. Both genes were effective in differentiating between UC patients and healthy controls. Furthermore, ING4 was lowly expressed in UC intestinal tissues and in LPS-treated intestinal epithelial cells, and it was involved in inflammatory responses. An in vitro functional experiment demonstrated that the knockdown or overexpression of ING4 could regulate the phosphorylation-induced activation of the NF-κB pathway and affect the release of the inflammatory factor iNOS, thereby triggering the occurrence and development of UC. Discussion: From a genetic causality perspective, ING4 emerges as a candidate gene with genetically supported relationship to UC, linking immune-related regulatory variation to epithelial inflammatory responses, while its precise tissue- and cell-type specific mechanisms remain to be clarified. Conclusion: This study emphasizes the importance of integrating multi-omics data in the exploration of UC pathogenesis. These findings position ING4 as a promising candidate biomarker and a potential molecule of therapeutic interest for UC.

Combinatorial Chemistry & High Throughput ScreeningVol. 29
Central South University (CN), Hunan Mawangdui Hospital (CN), National Clinical Research (US), Xiangya Hospital Central South University (CN)
Openalex Percentile: Top 11%
Single-cell and spatial transcriptomics
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