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.

Background: The objective of this study was to investigate the correlation between prothrombin time‐international normalized ratio to albumin ratio (PTAR) and QTc prolongation and to evaluate the predictive value of PTAR for long‐term clinical outcomes in patients with liver cirrhosis. Methods: Data from participants with liver cirrhosis admitted to Southwest Hospital between April 2017 and April 2018 were included in this study. The association between PTAR and QTc prolongation was examined using univariate and multivariable logistic regression analyses. The restricted cubic spline (RCS) method was employed for curve fitting and to determine the optimal PTAR threshold for predicting QTc prolongation. The SHapley Additive exPlanations (SHAP) algorithm, based on multivariable logistic regression, was utilized to assess the feature importance of PTAR. Kaplan–Meier curves and Cox proportional hazards models were used to evaluate the prognostic value of PTAR for liver‐related decompensation and severe arrhythmia. Results: Among the 374 participants (mean age 56.7 years; 66.3% male), 41.4% (155/374) experienced QTc prolongation. The median QT interval was 402.9 ± 41.9 ms. An adverse L‐shaped curve association between PTAR and QTc prolongation was observed, with an inflection point at 37.40. The odds ratio (OR) for developing QTc prolongation was 1.17 (95% CI: 1.06–1.28, p = 0.001) as PTAR ranged from 0 to 37.40. Interestingly, a threshold of 37.40 was also identified for predicting QTc prolongation, with PTAR achieving an area under the receiver operating characteristic curve (AUC) of 0.66. According to the feature importance ranking based on the SHAP algorithm, PTAR emerged as the most significant predictor, followed by sex, TBIL, and the etiology of liver cirrhosis. During a median follow‐up of 502 days, patients in the high PTAR group had a significantly higher risk of liver‐related decompensation (HR 3.51, 95% CI 2.35–5.24) and severe arrhythmia (HR 2.34, 95% CI 1.57–3.48) compared to the low PTAR group. Conclusion: There is a significant correlation between PTAR and QTc prolongation in patients with liver cirrhosis. An inflection point at 37.40 was identified, at which PTAR showed strong predictive value for QTc prolongation. Furthermore, elevated PTAR serves as a robust independent predictor for long‐term liver‐related decompensation and severe arrhythmia.