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Regulation of immune responses in primary biliary cholangitis: a transcriptomic analysis of peripheral immune cells

In patients with primary biliary cholangitis (PBC), the serum liver biochemistry measured during treatment with ursodeoxycholic acid—the UDCA response—accurately predicts long-term outcome. Molecular characterization of patients stratified by UDCA response can improve biological understanding of the...

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Detalles Bibliográficos
Autores principales: Mulcahy, Victoria, Liaskou, Evaggelia, Martin, Jose-Ezequiel, Kotagiri, Prasanti, Badrock, Jonathan, Jones, Rebecca L., Rushbrook, Simon M, Ryder, Stephen D., Thorburn, Douglas, Taylor-Robinson, Simon D., Clark, Graeme, Cordell, Heather J., Sandford, Richard N., Jones, David E., Hirschfield, Gideon M., Mells, George F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079354/
https://www.ncbi.nlm.nih.gov/pubmed/37026715
http://dx.doi.org/10.1097/HC9.0000000000000110
Descripción
Sumario:In patients with primary biliary cholangitis (PBC), the serum liver biochemistry measured during treatment with ursodeoxycholic acid—the UDCA response—accurately predicts long-term outcome. Molecular characterization of patients stratified by UDCA response can improve biological understanding of the high-risk disease, thereby helping to identify alternative approaches to disease-modifying therapy. In this study, we sought to characterize the immunobiology of the UDCA response using transcriptional profiling of peripheral blood mononuclear cell subsets. METHODS: We performed bulk RNA-sequencing of monocytes and T(H)1, T(H)17, T(REG), and B cells isolated from the peripheral blood of 15 PBC patients with adequate UDCA response (“responders”), 16 PBC patients with inadequate UDCA response (“nonresponders”), and 15 matched controls. We used the Weighted Gene Co-expression Network Analysis to identify networks of co-expressed genes (“modules”) associated with response status and the most highly connected genes (“hub genes”) within them. Finally, we performed a Multi-Omics Factor Analysis of the Weighted Gene Co-expression Network Analysis modules to identify the principal axes of biological variation (“latent factors”) across all peripheral blood mononuclear cell subsets. RESULTS: Using the Weighted Gene Co-expression Network Analysis, we identified modules associated with response and/or disease status (q<0.05) in each peripheral blood mononuclear cell subset. Hub genes and functional annotations suggested that monocytes are proinflammatory in nonresponders, but antiinflammatory in responders; T(H)1 and T(H)17 cells are activated in all PBC cases but better regulated in responders; and T(REG) cells are activated—but also kept in check—in responders. Using the Multi-Omics Factor Analysis, we found that antiinflammatory activity in monocytes, regulation of T(H)1 cells, and activation of T(REG) cells are interrelated and more prominent in responders. CONCLUSIONS: We provide evidence that adaptive immune responses are better regulated in patients with PBC with adequate UDCA response.