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Immune modules to guide diagnosis and personalized treatment of inflammatory skin diseases

  • Teofila Seremet
  • , Jeremy Di Domizio
  • , Antoine Girardin
  • , Ahmad Yatim
  • , Raphael Jenelten
  • , Francesco Messina
  • , Fanny Saidoune
  • , Christoph Schlapbach
  • , Sofia Bogiatzi
  • , Frederic Minisini
  • , Natalie Garzorz-Stark
  • , Matthieu Leuenberger
  • , Héloise Wüthrich
  • , Maxime Vernez
  • , Daniel Hohl
  • , Stefanie Eyerich
  • , Kilian Eyerich
  • , Emmanuella Guenova
  • , Carle Paul
  • , Raphael Gottardo
  • Curdin Conrad, Michel Gilliet*
*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

Abstract

Previous advances have identified immune pathways associated with inflammatory skin diseases, leading to the development of targeted therapies. However, there is a lack of molecular approaches that delineate these pathways at the individual patient level for personalized diagnostic and therapeutic guidance. Here, we conduct a cross-comparison of expression profiles from multiple inflammatory skin diseases to identify gene modules defining relevant immune pathways. Seven modules are identified, representing key immune pathways: Th17, Th2, Th1, Type I IFNs, neutrophilic, macrophagic, and eosinophilic. These modules allow the development of a molecular map with high diagnostic efficacy for inflammatory skin diseases and clinico-pathologically undetermined cases. Aligning dominant modules with treatment targets offers a rational framework for treatment selection, improving response rates in both treatment-naïve patients and non-responders to targeted therapies. Overall, our approach offers precision medicine for inflammatory skin diseases, utilizing transcriptional modules to support diagnosis and guide personalized treatment selection.

OriginalspracheEnglisch
Aufsatznummer10688
FachzeitschriftNature Communications
Volume15
Ausgabenummer1
DOIs
PublikationsstatusVeröffentlicht - 18 Dez. 2024
Extern publiziertJa

Wissenschaftszweige

  • 302 Klinische Medizin

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