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Multi-omics analysis reveals diagnostic and therapeutic biomarkers for aging phenotypes in ulcerative colitis

by Lei Guo, Jun Ge, Li Cheng, Xinyi Zhang, Zhengzheng Wu, Meili Liu, Hanmei Jiang, Wei Gong, Yi Liu

Background

The incidence of ulcerative colitis (UC) remains high, with an increasing prevalence among elderly patients. Cellular senescence has been widely recognized as a contributor to UC susceptibility; however, the underlying molecular mechanisms remain incompletely understood. This study aimed to identify senescence-associated biomarkers in UC to provide new insight for diagnosis and treatment.

Methods

By integrating transcriptomic data from UC patients with established aging-related databases, we identified aging-associated differentially expressed genes (DEGs). Using weighted gene co-expression network analysis (WGCNA) and Cytoscape, we pinpointed the core genes involved. A diagnostic model for UC was then developed based on these core genes, and their expression patterns were characterized at single-cell resolution. The roles of these genes were ultimately validated through in vitro and animal experiments.

Results

We identified 24 aging-related DEGs in UC, which were primarily implicated in inflammatory responses and cytokine-receptor interactions. Further analyses pinpointed three core genes (CXCL1, MMP9, and STAT1) that were predominantly expressed in macrophages. A diagnostic model constructed using these genes exhibited robust predictive performance. Experimental validation confirmed that the expression levels of all three core genes were significantly upregulated in both a UC mouse model and in macrophages compared to controls. Additionally, pathway analyses revealed elevated levels of CXCL12 and VEGFA in the enriched pathways.

Discussion

Our findings underscore the pivotal roles of CXCL1, MMP9, and STAT1 in UC-associated cellular senescence. The analysis positions these molecules as promising macrophage-mediated diagnostic biomarkers and therapeutic targets. Collectively, this work provides novel insights into UC pathogenesis and lays a foundation for developing precision medicine strategies that target senescence pathways.

Impact of Social Support on Health Literacy Among People With Diabetes: A Cross‐Sectional Study

ABSTRACT

Aim

In recent years, the critical role of health literacy in diabetes management has become increasingly prominent. The aim of this study was to investigate the impact of social support on health literacy among patients with diabetes, to test the mediating role of self-efficacy and empowerment between social support and health literacy, and the moderating role of eHealth literacy.

Design

A cross-sectional study conducted between August 2023 and June 2024.

Methods

This study adopted the cluster sampling method and conducted a questionnaire survey among 251 patients with diabetes in a tertiary hospital in Wuhu City, Anhui Province. The questionnaires included the Social Support Rating Scale, the Self-Efficacy for Diabetes scale, the Health Empowerment Scale, the eHealth Literacy Scale and the Diabetes Health Literacy Scale.

Results

Social support was positively associated with health literacy in patients with diabetes. Self-efficacy and empowerment mediated the relationship and formed chained mediation pathways respectively. eHealth literacy has a moderating role between self-efficacy and empowerment.

Conclusion

The results revealed that social support influences health literacy among patients with diabetes through the mediating pathways of self-efficacy and empowerment, and that this process is moderated by eHealth literacy. These findings provide a theoretical basis and practical insights for improving health literacy among patients with diabetes.

Implications

Enhancing health literacy among people with diabetes by strengthening social support, self-efficacy and empowerment levels, while focusing on the technology-enabling role of eHealth literacy in this context.

Reporting Method

This study adheres to the relevant EQUATOR guidelines based on the STROBE cross-sectional reporting method.

Patient or Public Contribution

We thank all patients who participated in the study for their understanding and support.

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