Nature Communications (Jun 2024)

Identification and validation of a blood- based diagnostic lipidomic signature of pediatric inflammatory bowel disease

  • Samira Salihovic,
  • Niklas Nyström,
  • Charlotte Bache-Wiig Mathisen,
  • Robert Kruse,
  • Christine Olbjørn,
  • Svend Andersen,
  • Alexandra J. Noble,
  • Maria Dorn-Rasmussen,
  • Igor Bazov,
  • Gøri Perminow,
  • Randi Opheim,
  • Trond Espen Detlie,
  • Gert Huppertz-Hauss,
  • Charlotte R. H. Hedin,
  • Marie Carlson,
  • Lena Öhman,
  • Maria K. Magnusson,
  • Åsa V. Keita,
  • Johan D. Söderholm,
  • Mauro D’Amato,
  • Matej Orešič,
  • Vibeke Wewer,
  • Jack Satsangi,
  • Carl Mårten Lindqvist,
  • Johan Burisch,
  • Holm H. Uhlig,
  • Dirk Repsilber,
  • Tuulia Hyötyläinen,
  • Marte Lie Høivik,
  • Jonas Halfvarson

DOI
https://doi.org/10.1038/s41467-024-48763-7
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 15

Abstract

Read online

Abstract Improved biomarkers are needed for pediatric inflammatory bowel disease. Here we identify a diagnostic lipidomic signature for pediatric inflammatory bowel disease by analyzing blood samples from a discovery cohort of incident treatment-naïve pediatric patients and validating findings in an independent inception cohort. The lipidomic signature comprising of only lactosyl ceramide (d18:1/16:0) and phosphatidylcholine (18:0p/22:6) improves the diagnostic prediction compared with high-sensitivity C-reactive protein. Adding high-sensitivity C-reactive protein to the signature does not improve its performance. In patients providing a stool sample, the diagnostic performance of the lipidomic signature and fecal calprotectin, a marker of gastrointestinal inflammation, does not substantially differ. Upon investigation in a third pediatric cohort, the findings of increased lactosyl ceramide (d18:1/16:0) and decreased phosphatidylcholine (18:0p/22:6) absolute concentrations are confirmed. Translation of the lipidomic signature into a scalable diagnostic blood test for pediatric inflammatory bowel disease has the potential to support clinical decision making.