Your browser doesn't support javascript.
loading
Whole blood RNA sequencing identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis.
Wacker, Eike Matthias; Uellendahl-Werth, Florian; Bej, Saptarshi; Wolkenhauer, Olaf; Vesterhus, Mette; Lieb, Wolfgang; Franke, Andre; Karlsen, Tom Hemming; Folseraas, Trine; Ellinghaus, David.
Afiliación
  • Wacker EM; Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.
  • Uellendahl-Werth F; Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.
  • Bej S; Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.
  • Wolkenhauer O; Indian Institute of Science Education and Research, Thiruvananthapuram, India.
  • Vesterhus M; Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.
  • Lieb W; Leibniz-Institute for Food Systems Biology at the Technical University Munich, Munich, Germany.
  • Franke A; Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa.
  • Karlsen TH; Norwegian PSC Research Center, Department of Transplantation Medicine, Division of Surgery, Inflammatory Diseases and Transplantation, Oslo University Hospital Rikshospitalet and University of Oslo, Oslo, Norway.
  • Folseraas T; Department of Medicine, Haraldsplass Deaconess Hospital, Bergen, Norway.
  • Ellinghaus D; Department of Clinical Science, University of Bergen, Bergen, Norway.
JHEP Rep ; 6(2): 100988, 2024 Feb.
Article en En | MEDLINE | ID: mdl-38304234
ABSTRACT
Background &

Aims:

Genetic and microbiome studies across patients with primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) have indicated that UC in PSC is a separate disease entity to primary UC, but expression studies for PSC are lacking.

Methods:

We conducted whole blood RNA sequencing experiments for 495 patients with UC, 220 patients with PSC (including 177 with UC), and 320 healthy controls from Germany and Norway. Differential expression analyses, gene ontology and coexpression analyses and random forest machine learning were performed to identify genes, ontologies and transcriptional features that discriminate diagnoses.

Results:

The blood transcriptome in UC and PSC is dominated by neutrophil activation genes (e.g. S100A12). In UC, but not in PSC (neither PSC alone nor patients with an additional diagnosis of UC [PSC/UC]), ribosomal, mitochondrial, and energy metabolism genes are upregulated in conjunction with antibody transcript expression (MZB1, IGJ). In PSC, there is an increase in modules related to apoptosis and expression of genes of interferon-I-related ontologies. Random forest analysis could poorly discriminate PSC alone from PSC/UC (AUROC 0.56), but could discriminate PSC, UC, and controls with high accuracy (AUROC UC vs. controls 0.95, PSC vs. controls 0.88, UC vs. PSC 0.986). The main coexpression modules relevant for distinguishing PSC, UC, and controls are enriched in neutrophil degranulation and antibody production genes.

Conclusions:

Supported by machine learning results, PSC and UC appear to be separate entities on a molecular level, while PSC/UC and PSC are indistinguishable. Impact and implications Clinical and genetic studies suggest that the colitis-like symptoms in primary sclerosing cholangitis (PSC) represent a different disease entity from primary ulcerative colitis (UC). The present study supports this assumption with transcriptomic data from whole blood and describes notable differences in gene expression between primary UC and PSC, providing insights into the still unclear pathophysiology of both diseases. These findings are of interest to scientists seeking to decipher the molecular pathophysiology of both diseases and provide evidence that a redefinition of the PSC-UC phenotype should be considered. The study practically supports future molecular research by providing a large transcriptomic whole blood reference cohort.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JHEP Rep Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JHEP Rep Año: 2024 Tipo del documento: Article