P0336 From inflammation to depression: key biomarkers for Inflammatory Bowel Disease-related Major Depressive Disorder

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Abstract Background Inflammatory bowel disease (IBD) is a chronic, inflammatory, and autoimmune disorder[1], and its incidence of comorbid with major depressive disorder (MDD) is significantly higher than the general population[2]. However, many patients lack proper recognition and necessary psychological health treatments. We aimed to identify potential biomarkers and mechanisms involved in the development of IBD comorbid with MDD (IBD-MDD). Methods We utilized IBD and MDD-related datasets from the GEO database for differential gene expression analysis, protein-protein interaction (PPI) and pathway enrichment analysis, random forest algorithm, LASSO regression analysis, and construction of a disease prediction model. We assessed the accuracy of the model using ROC curve, explored potential mechanisms through immune infiltration analysis, and validated candidate biomarkers using peripheral blood samples from patients in our center’s cohort. Results We identified 484 IBD-related secreted proteins and 142 key module genes associated with MDD. PPI analysis revealed two crucial modules primarily involved in inflammation and immune regulation. We identified four diagnostic genes (HGF, SPARC, ADAM12, and MMP8) from the 21 shared genes between IBD-related secreted proteins and MDD key module genes, constructed a nomogram model and confirmed its accuracy using ROC curve from an external independent dataset. Immune infiltration analysis revealed significant associations between the four diagnostic genes, and cellular immune dysregulation in MDD. Finally, we validated the expression patterns of the four diagnostic genes in our cohort.The results showed that the serum levels of HGF and MMP8 were significantly elevated in IBD patients with comorbid MDD, SPARC and ADAM12 showed an increasing trend (Figure 1A). Meanwhile, we developed a predictive model for IBD-related MDD based on our cohort (Figure 1B). The calibration curve suggests that the predictive probability of the nomogram model is nearly the same as that of the ideal model (Figure 1C). ROC curve analysis of the efficacy of the joint predictive model based on the 4 diagnostic markers showed that the AUC value was 0.87, indicating that the nomogram have strong diagnostic value for IBD-related MDD (Figure 1D). Conclusion Our study discovered four candidate biomarkers for IBD-MDD, providing new insights for the diagnosis and therapeutic intervention of serum-based IBD comorbid with MDD.