Identification and validation of a multivariable prediction model based on blood plasma and serum metabolomics for the distinction of chronic pancreatitis subjects from non-pancreas disease control subjects

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • M. Gordian Adam - , Metanomics-Health GmbH (Author)
  • Georg Beyer - , Ludwig Maximilian University of Munich (Author)
  • Nicole Christiansen - , trinamiX GmbH (Author)
  • Beate Kamlage - , Metanomics-Health GmbH (Author)
  • Christian Pilarsky - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Marius Distler - , Department of Visceral, Thoracic and Vascular Surgery, National Center for Tumor Diseases (Partners: UKD, MFD, HZDR, DKFZ), University Hospital Carl Gustav Carus Dresden (Author)
  • Tim Fahlbusch - , Ruhr University Bochum (Author)
  • Ansgar Chromik - , Asklepios Hospital Hamburg-Harburg (Author)
  • Fritz Klein - , Charité – Universitätsmedizin Berlin (Author)
  • Marcus Bahra - , Charité – Universitätsmedizin Berlin (Author)
  • Waldemar Uhl - , Ruhr University Bochum (Author)
  • Robert Grützmann - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Ujjwal M. Mahajan - , Ludwig Maximilian University of Munich (Author)
  • Frank U. Weiss - , University of Greifswald (Author)
  • Julia Mayerle - , Ludwig Maximilian University of Munich (Author)
  • Markus M. Lerch - , University of Greifswald (Author)

Abstract

Objective Chronic pancreatitis (CP) is a fibroinflammatory syndrome leading to organ dysfunction, chronic pain, an increased risk for pancreatic cancer and considerable morbidity. Due to a lack of specific biomarkers, diagnosis is based on symptoms and specific but insensitive imaging features, preventing an early diagnosis and appropriate management. Design We conducted a type 3 study for multivariable prediction for individual prognosis according to the TRIPOD guidelines. A signature to distinguish CP from controls (n=160) was identified using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry on ethylenediaminetetraacetic acid (EDTA)-plasma and validated in independent cohorts. Results A Naive Bayes algorithm identified eight metabolites of six ontology classes. After algorithm training and computation of optimal cut-offs, classification according to the metabolic signature detected CP with an area under the curve (AUC) of 0.85 ((95% CI 0.79 to 0.91). External validation in two independent cohorts (total n=502) resulted in similar accuracy for detection of CP compared with non-pancreatic controls in EDTA-plasma (AUC 0.85 (95% CI 0.81 to 0.89)) and serum (AUC 0.87 (95% CI 0.81 to 0.95)). Conclusions This is the first study that identifies and independently validates a metabolomic signature in plasma and serum for the diagnosis of CP in large, prospective cohorts. The results could provide the basis for the development of the first routine laboratory test for CP.

Details

Original languageEnglish
Pages (from-to)2150-2158
Number of pages9
JournalGut
Volume70
Issue number11
Publication statusPublished - 1 Nov 2021
Peer-reviewedYes

External IDs

PubMed 33541865

Keywords

Sustainable Development Goals

ASJC Scopus subject areas

Keywords

  • Chronic pancreatitis, Lipid metabolism, Liver cirrhosis, Liver metabolism, Pancreatic disorders