Biliary epithelium and liver B cells exposed to bacteria activate intrahepatic MAIT cells through MR1.

BACKGROUND & AIMS: Mucosal-Associated Invariant T (MAIT) cells are innate-like T cells characterised by the invariant TCR-chain, Vα7.2-Jα33, and are restricted by MR1, which presents bacterial vitamin B metabolites. They are important for antibacterial immunity at mucosal sites; however, detailed characteristics of liver-infiltrating MAIT (LI-MAIT) and their role in biliary immune surveillance remain unexplored. METHODS: The phenotype and intrahepatic localisation of human LI-MAIT cells was examined in diseased and normal livers. MAIT cell activation in response to E. coli-exposed macrophages, biliary epithelial cells (BEC) and liver B cells was assessed with/without anti-MR1. RESULTS: Intrahepatic MAIT cells predominantly localised to bile ducts in the portal tracts. Consistent with this distribution, they expressed biliary tropic chemokine receptors CCR6, CXCR6, and integrin αEß7. LI-MAIT cells were also present in the hepatic sinusoids and possessed tissue-homing chemokine receptor CXCR3 and integrins LFA-1 and VLA-4, suggesting their recruitment via hepatic sinusoids. LI-MAIT cells were enriched in the parenchyma of acute liver failure livers compared to chronic diseased livers. LI-MAIT cells had an activated, effector memory phenotype, expressed α4ß7 and receptors for IL-12, IL-18, and IL-23. Importantly, in response to E. coli-exposed macrophages, liver B cells and BEC, MAIT cells upregulated IFN-γ and CD40 Ligand and degranulated in an MR1-dependent, cytokine-independent manner. In addition, diseased liver MAIT cells expressed T-bet and RORγt and the cytokines IFN-γ, TNF-α, and IL-17. CONCLUSIONS: Our findings provide the first evidence of an immune surveillance effector response for MAIT cells towards BEC in human liver; thus they could be manipulated for treatment of biliary disease in the future.

Comparison of COVID-19 Hospitalization and Death Between Solid Organ Transplant Recipients and the General Population in Canada, 2020-2022.

Background: Solid organ transplant recipients have a high risk of severe outcomes from SARS-CoV-2 infection. A comprehensive understanding of the impact of the COVID-19 pandemic across multiple waves in the solid organ transplant population and how this compares to the general population is limited. We conducted a population-based cohort study using linked administrative healthcare databases from Ontario, Canada to answer this question. Methods: We included 15 306 solid organ transplant recipients and 12 160 904 individuals from the general population. Our primary outcome was the rate (per 100 person-years) of severe COVID-19 (ie, hospitalization or death with a positive SARS-CoV-2 test) occurring between January 25, 2020, and November 30, 2022. Results: Compared with the general population, solid organ transplant recipients had almost a 6 times higher rate of severe COVID-19 (20.39 versus 3.44 per 100 person-years), with almost 5.5 times as high a rate of death alone (4.19 versus 0.77 per 100 person-years). Transplant recipients with severe COVID-19 were substantially younger (60.1 versus 66.5 y) and had more comorbidities. The rate of severe COVID-19 declined over time in the solid organ transplant population, with an incidence rate of 41.25 per 100 person-years in the first wave (January 25, 2020, to August 31, 2020) and 18.41 in the seventh wave (June 19, 2022, to November 30, 2022, Omicron era). Conclusions: Solid organ transplant recipients remain at high risk of severe outcomes when they are infected with SARS-CoV-2. Resources and strategies to mitigate the impact of SARS-CoV-2 exposure are needed in this vulnerable patient population.

Predicting Real-world Hypoglycemia Risk in American Adults With Type 1 or 2 Diabetes Mellitus Prescribed Insulin and/or Secretagogues: Protocol for a Prospective, 12-Wave Internet-Based Panel Survey With Email Support (the iNPHORM [Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-world Models] Study).

BACKGROUND: Hypoglycemia prognostic models contingent on prospective, self-reported survey data offer a powerful avenue for determining real-world event susceptibility and interventional targets. OBJECTIVE: This protocol describes the design and implementation of the 1-year iNPHORM (Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-world Models) study, which aims to measure real-world self-reported severe and nonsevere hypoglycemia incidence (daytime and nocturnal) in American adults with type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues, and develop and internally validate prognostic models for severe, nonsevere daytime, and nonsevere nocturnal hypoglycemia. As a secondary objective, iNPHORM aims to quantify the effects of different antihyperglycemics on hypoglycemia rates. METHODS: iNPHORM is a prospective, 12-wave internet-based panel survey that was conducted across the United States. Americans (aged 18-90 years) with self-reported type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues were conveniently sampled via the web from a pre-existing, closed, probability-based internet panel (sample frame). A sample size of 521 baseline responders was calculated for this study. Prospective data on hypoglycemia and potential prognostic factors were self-assessed across 14 closed, fully automated questionnaires (screening, baseline, and 12 monthly follow-ups) that were piloted using semistructured interviews (n=3) before fielding; no face-to-face contact was required as part of the data collection. Participant responses will be analyzed using multivariable count regression and machine learning techniques to develop and internally validate prognostic models for 1-year severe and 30-day nonsevere daytime and nocturnal hypoglycemia. The causal effects of different antihyperglycemics on hypoglycemia rates will also be investigated. RESULTS: Recruitment and data collection occurred between February 2020 and March 2021 (ethics approval was obtained on December 17, 2019). A total of 1694 participants completed the baseline questionnaire, of whom 1206 (71.19%) were followed up for 12 months. Most follow-up waves (10,470/14,472, 72.35%) were completed, translating to a participation rate of 179% relative to our target sample size. Over 70.98% (856/1206) completed wave 12. Analyses of sample characteristics, quality metrics, and hypoglycemia incidence and prognostication are currently underway with published results anticipated by fall 2022. CONCLUSIONS: iNPHORM is the first hypoglycemia prognostic study in the United States to leverage prospective, longitudinal self-reports. The results will contribute to improved real-world hypoglycemia risk estimation and potentially safer, more effective clinical diabetes management. TRIAL REGISTRATION: ClinicalTrials.gov NCT04219514; https://clinicaltrials.gov/ct2/show/NCT04219514. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33726.