A pyroptosis-related gene signature for the diagnosis of acute pancreatitis

by Yuting Wang, Jun Li, Zhongsu Yu, Shuyuan Li, Yuxia Chen, Yun Pan, Liangping Cheng, Guangyuan Yu

Acute pancreatitis (AP) is a severe inflammatory disorder in which pyroptosis—a pro-inflammatory form of programmed cell death—may contribute to pathogenesis. However, the complete transcriptional profile of pyroptosis-related genes (PRGs) in AP and their potential as diagnostic biomarkers remain underexplored. This study aimed to systematically characterize pyroptosis-associated transcriptional signatures and identify the reliable biomarkers for diagnostic purposes. Three transcriptomic datasets from murine AP models were integrated to identify pyroptosis-related differentially expressed genes (PRDEGs). Functional enrichment and immune cell infiltration analyses were conducted to elucidate the biological pathways and immune microenvironment alterations associated with these genes. mRNA-transcription factor (TF) and mRNA-microRNA (miRNA) regulatory networks were constructed to investigate underlying molecular interactions. Machine learning techniques, including support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO), were applied for feature selection, leading to the identification of key diagnostic markers and the development of a logistic regression model. The regression model were then assessed using an independent cohort of human peripheral blood samples. Eleven PRDEGs were identified, with enrichment observed in processes such as cytoskeletal organization, cell-substrate adhesion, and critical inflammatory signaling pathways, including MAPK and NF-κB. Immune infiltration analysis revealed significant correlations between these PRDEGs and various immune cell subsets, particularly M1 macrophages, Treg cells, and monocytes. A four-gene diagnostic signature, comprising ANXA3, IQGAP1, RELA, and VTN, was established through SVM and LASSO analysis. In the independent human cohort, the fixed-coefficient four-gene model demonstrated reduced discrimination, which likely reflects interspecies and tissue-specific variations. However, after optimizing the model to exclude non-significant predictors, a refined two-gene signature (ANXA3 and IQGAP1) exhibited improved accuracy, with excellent calibration and clinical net benefit. This study offers a comprehensive transcriptomic analysis of the pyroptosis-mediated landscape and immune microenvironment in AP. An optimized two-gene signature, comprising ANXA3 and IQGAP1, was validated in a human cohort with superior accuracy, reflecting critical disruptions in inflammatory pathways and cytoskeletal organization. Notably, ANXA3 demonstrated potential for stratifying disease severity. Although these markers hold potential for molecular diagnosis, further prospective studies are essential to establish their clinical specificity and generalizability across diverse populations.

Trajectories and Co‐Occurrence of Perceived Control in Patients With Heart Failure and Self‐Efficacy in Their Caregivers: A Three‐Month Longitudinal Study of Dual Trajectories

ABSTRACT

Aim

This study aims to explore the trajectories and co-occurrence of perceived control and caregiver self-efficacy among patients with heart failure (HF) and their caregivers within 3 months post-discharge and identify associated risk factors.

Design

A prospective cohort design.

Methods

A prospective cohort study was conducted from March to June 2024 in Tianjin, China. Information on perceived control and caregiver self-efficacy was collected 24 h before discharge, 2 weeks, 1 month, and 3 months after discharge. Group-Based Dual Trajectory Modelling (GBDTM) and logistic regression were used for analysis.

Results

The study included 203 dyads of patients with HF and their caregivers (HF dyads). Perceived control identified three trajectories: low curve (15.3%), middle curve (57.1%) and high curve (27.6%). Caregiver self-efficacy demonstrated three trajectories: low curve (17.2%), middle curve (56.7%) and high stable (26.1%). GBDTM revealed nine co-occurrence patterns, with the highest proportion (36.7%) being ‘middle-curve group for perceived control and middle-curve group for caregiver self-efficacy’, and 16.7% being ‘high-curve group for perceived control and high-stable group for caregiver self-efficacy’. Age, gender, household income, NYHA class, symptom burden and psychological resilience were identified as risk factors for perceived control trajectories; marital status, regular exercise and psychological resilience were identified as risk factors for caregiver self-efficacy trajectories.

Conclusion

We identified distinct trajectories, co-occurrence patterns and risk factors of perceived control and caregiver self-efficacy among HF dyads. These findings help clinical nurses to better design and implement interventions, strengthening the comprehensive management and care outcomes for HF dyads.

Impact

These findings highlighted the interactive relationship between perceived control and caregiver self-efficacy trajectories, suggesting that interventions should boost both to improve personalised treatment plans and outcomes for HF dyads.

Reporting Method

This study adhered to the STROBE checklist.

Patient or Public Contribution

Patients and their caregivers contributed by participating in the study and completing the questionnaire.