Autoimmune hepatitis: Current and future therapies.

Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease that can lead to cirrhosis and liver failure. AIH can present in all ages, races, and ethnicities, but it predominantly affects women. As a heterogeneous disease, AIH presents variably in different patients, making diagnosis and treatment a challenge. Currently, the standard treatment for AIH comprises immunosuppressants; however, their long-term use is associated with adverse effects. The pathogenesis of AIH is complex, involving T cells, macrophages, and plasma cells that invade the periportal parenchyma and lead to an inflammatory cascade that can result in liver damage. Due to the complexity of AIH pathogenesis, treatment targets several inflammatory pathways. However, unlike other autoimmune diseases in which targeted treatments have been approved, there has been little progress made in advancing the treatment paradigm for AIH. Major obstacles to progress include challenges in conducting clinical trials, particularly patient recruitment and ensuring a diverse range of backgrounds; poorly defined outcomes to assess treatment response and improved quality of life; and a lack of study designs that account for the stage of disease and variations in treatment. A focus on individualized and steroid-free treatment approaches is needed to improve AIH prognosis and minimize steroid-associated adverse effects.

A polygenic risk score for alcohol-associated cirrhosis among heavy drinkers with European ancestry.

BACKGROUND: Polygenic Risk Scores (PRS) based on results from genome-wide association studies offer the prospect of risk stratification for many common and complex diseases. We developed a PRS for alcohol-associated cirrhosis by comparing single-nucleotide polymorphisms among patients with alcohol-associated cirrhosis (ALC) versus drinkers who did not have evidence of liver fibrosis/cirrhosis. METHODS: Using a data-driven approach, a PRS for ALC was generated using a meta-genome-wide association study of ALC (N=4305) and an independent cohort of heavy drinkers with ALC and without significant liver disease (N=3037). It was validated in 2 additional independent cohorts from the UK Biobank with diagnosed ALC (N=467) and high-risk drinking controls (N=8981) and participants in the Indiana Biobank Liver cohort with alcohol-associated liver disease (N=121) and controls without liver disease (N=3239). RESULTS: A 20-single-nucleotide polymorphisms PRS for ALC (PRSALC) was generated that stratified risk for ALC comparing the top and bottom deciles of PRS in the 2 validation cohorts (ORs: 2.83 [95% CI: 1.82 -4.39] in UK Biobank; 4.40 [1.56 -12.44] in Indiana Biobank Liver cohort). Furthermore, PRSALC improved the prediction of ALC risk when added to the models of clinically known predictors of ALC risk. It also stratified the risk for metabolic dysfunction -associated steatotic liver disease -cirrhosis (3.94 [2.23 -6.95]) in the Indiana Biobank Liver cohort -based exploratory analysis. CONCLUSIONS: PRSALC incorporates 20 single-nucleotide polymorphisms, predicts increased risk for ALC, and improves risk stratification for ALC compared with the models that only include clinical risk factors. This new score has the potential for early detection of heavy drinking patients who are at high risk for ALC.

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

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.