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

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • M. Gordian Adam - , Metanomics Health GmbH (Autor:in)
  • Georg Beyer - , Ludwig-Maximilians-Universität München (LMU) (Autor:in)
  • Nicole Christiansen - , trinamiX GmbH (Autor:in)
  • Beate Kamlage - , Metanomics Health GmbH (Autor:in)
  • Christian Pilarsky - , Friedrich-Alexander-Universität Erlangen-Nürnberg (Autor:in)
  • Marius Distler - , Klinik und Poliklinik für Viszeral-, Thorax- und Gefäßchirurgie, Nationales Centrum für Tumorerkrankungen (Partner: UKD, MFD, HZDR, DKFZ), Universitätsklinikum Carl Gustav Carus Dresden (Autor:in)
  • Tim Fahlbusch - , Ruhr-Universität Bochum (Autor:in)
  • Ansgar Chromik - , Asklepios Klinikum Hamburg-Harburg (Autor:in)
  • Fritz Klein - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Marcus Bahra - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Waldemar Uhl - , Ruhr-Universität Bochum (Autor:in)
  • Robert Grützmann - , Friedrich-Alexander-Universität Erlangen-Nürnberg (Autor:in)
  • Ujjwal M. Mahajan - , Ludwig-Maximilians-Universität München (LMU) (Autor:in)
  • Frank U. Weiss - , Ernst-Moritz-Arndt-Universität Greifswald (Autor:in)
  • Julia Mayerle - , Ludwig-Maximilians-Universität München (LMU) (Autor:in)
  • Markus M. Lerch - , Ernst-Moritz-Arndt-Universität Greifswald (Autor:in)

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

OriginalspracheEnglisch
Seiten (von - bis)2150-2158
Seitenumfang9
FachzeitschriftGut
Jahrgang70
Ausgabenummer11
PublikationsstatusVeröffentlicht - 1 Nov. 2021
Peer-Review-StatusJa

Externe IDs

PubMed 33541865

Schlagworte

Ziele für nachhaltige Entwicklung

ASJC Scopus Sachgebiete

Schlagwörter

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