Transcriptomic profiling of blood from autoimmune hepatitis patients reveals potential mechanisms with implications for management

Abstract

Autoimmune hepatitis (AIH) is a poorly understood, chronic disease, for which corticosteroids are still the mainstay of therapy and most patients undergo liver biopsy to obtain a diagnosis. We aimed to determine if there was a transcriptomic signature of AIH in the peripheral blood and investigate underlying biologic pathways revealed by gene expression analysis. Whole blood RNA from 75 AIH patients and 25 healthy volunteers was extracted and sequenced. Differential gene expression analysis revealed 249 genes that were significantly differentially expressed in AIH patients compared to controls. Using a random forest algorithm, we determined that less than 10 genes were sufficient to differentiate the two groups in our cohort. Interferon signaling was more active in AIH samples compared to controls, regardless of treatment status. Pegivirus sequences were detected in five AIH samples and 1 healthy sample. The gene expression data and clinical metadata were used to determine 12 genes that were significantly associated with advanced fibrosis in AIH. AIH patients with a partial response to therapy demonstrated decreased evidence of a CD8+ T cell gene expression signal. These findings represent progress in understanding a disease in need of better tests, therapies, and biomarkers.

Early monocyte response following local ablation in hepatocellular carcinoma

“…Nevertheless, in IFN-alpha-mediated inflammation, CD200R can amplify the immune response ( 51 ). Type I interferon activation is also described for AIH ( 52 ), and it is likely that IBT triggers the induction of IFN-alpha. With regard to immunotherapies and their increasing use in combination with local ablative therapies, the CD200–CD200R axis is of major importance and additional investigations are needed to identify targets harmonizing combinations of both therapy types.…”

Artificial intelligence for precision medicine in autoimmune liver disease

“…Gene expression, proteomic, and metabolomic data come mainly from peripheral blood and single cohorts. More specifically, a recent study has shown that ML can discriminate between AIH and healthy controls based on gene expression profiles (92). A similar situation exists for microbiota, despite the growing interest on this side (93,94).…”