Integrative Genomics Reveals Causal Pleiotropy and Therapeutic Opportunities at the Interface of Acute Pancreatitis and Infection

ABSTRACT Background Understanding the genetic links between acute pancreatitis (AP) and its infectious comorbidities is crucial for prognosis and therapy, yet remains underexplored. Methods We conducted a comprehensive post‐GWAS analysis using large‐scale summary statistics for AP and 16 infectious diseases. To pinpoint pleiotropic genes, we integrated multi‐omics data via transcriptome‐wide and proteome‐wide association studies, and resolved cell‐type‐specific effects using single‐cell analysis. Extensive locus colocalization analyses were performed to validate our findings by estimating the probability of shared causal variants. Results This computational discovery phase prioritized 29 high‐confidence pleiotropic genes, including established loci ( SPINK1, CRP ) and novel candidates ( ERBB2, ALDH2, FLOT1 ). To functionally validate and contextualize these findings, we performed bulk transcriptomic analysis on peripheral blood from AP patients and employed gsMap, a spatial GWAS mapping algorithm, to integrate our genetic data with transcriptomics from a murine AP model, comparing pathological versus normal tissue. These analyses confirmed that the identified genes are dynamically regulated in a severity‐dependent manner in patients and are activated within specific pathological niches in pancreatic tissue. Conclusion In conclusion, this study provides a genetic map linking AP and its infectious comorbidities, offering insights into potential prevention strategies and highlighting novel therapeutic targets for further investigation and validation.