ArticleClinical epigenetics2021
Accurate prediction of acute pancreatitis severity based on genome-wide cell free DNA methylation profiles.
Article in Clinical epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- MPCI: A novel metric for quantifying DNA methylation patterns in NGS data.PLoS computational biology · 2026Article
- Clinical and Biochemical Characteristics of Traditional Chinese Medicine Syndromes in Acute Pancreatitis: A Two-Center Retrospective Study.International journal of general medicine · 2026Article
- Cell-Free DNA Hypermethylation in Patients with Acute Pancreatitis.International journal of molecular sciences · 2025Article
- In-depth investigation of the mechanism in rats with alcoholic acute pancreatitis via DNA methylation, intestinal flora, and fecal metabolomics.Journal of inflammation (London, England) · 2025Article
- Biomarkers to predict the severity of acute pancreatitis.Frontiers in medicine · 2025Review
- Clinical significance of peripheral blood DDR1 and CtBP gene methylation detection in patients with acute pancreatitis.Epigenetics · 2024Article
- Article
- Methylomics and cancer: the current state of methylation profiling and marker development for clinical care.Cancer cell international · 2023Review
- Article
- Single-cell transcriptome analysis for cancer and biology of the pancreas: A review on recent progress.Frontiers in genetics · 2023Review
- Damage associated molecular patterns and neutrophil extracellular traps in acute pancreatitis.Frontiers in cellular and infection microbiology · 2022Review
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPatients with severe acute pancreatitis (SAP) have a high mortality, thus early diagnosis and interventions are critical for improving survival. However, conventional tests are limited in acute pancreatitis (AP) stratification. We aimed to assess AP severity by integrating the informative clinical measurements with cell free DNA (cfDNA) methylation markers.
methodsOne hundred and seventy-five blood samples were collected from 61 AP patients at multiple time points, plus 24 samples from healthy individuals. Genome-wide cfDNA methylation profiles of all samples were characterized with reduced representative bisulfite sequencing. Clinical blood tests covering 93 biomarkers were performed on AP patients within 24 h. SAP predication models were built based on cfDNA methylation and conventional blood biomarkers separately and in combination.
resultsWe identified 565 and 59 cfDNA methylation markers informative for acute pancreatitis and its severity. These markers were used to develop prediction models for AP and SAP with area under the receiver operating characteristic of 0.92 and 0.81, respectively. Twelve blood biomarkers were systematically screened for a predictor of SAP with a sensitivity of 87.5% for SAP, and a specificity of 100% in mild acute pancreatitis, significantly higher than existing blood tests. An expanded model integrating 12 conventional blood biomarkers with 59 cfDNA methylation markers further improved the SAP prediction sensitivity to 92.2%.
conclusionsThese findings have demonstrated that accurate prediction of SAP by the integration of conventional and novel blood molecular markers, paving the way for early and effective SAP intervention through a non-invasive rapid diagnostic test.
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