Recurrent disease in the liver transplant: window to identify and stop gut signals driving autoimmunity
Autoimmune disease is an increasing health concern. These diseases are strongly associated with altered gut microbiome. When immunosuppression fails there is little to offer in terms of therapy. In this project, I hypothesize that gut signals (microbial factors from the intestine) unaffected by immunosuppression are key drivers of autoimmune diseases. I propose to use recurrent autoimmune disease after organ transplantation as a human disease model to identify and stop these gut signals, providing a novel approach to close the gap between basic microbiome research and patient care in autoimmune diseases.

To identify autoimmunity-related gut signals, I will use patients with primary sclerosing cholangitis (PSC), an inflammatory disease of the bile ducts. PSC is a common indication for liver transplantation, but after transplantation there is high risk of recurrent PSC (rPSC). I recently showed that the PSC gut microbiome has low diversity and identified microbial metabolites associated with severe PSC. Preliminary data show that the post-transplant gut is even less diverse, suggesting that microbial factors drive autoimmunity. 

In this project I will identify gut signals by in-depth investigation of gut bacterial genes and circulating metabolites in the blood. The outcome will be diagnostic and prognostic markers overlapping in PSC and rPSC, defined by changes in gut bacterial genes and concentrations of bacterial metabolites in the blood. Next, I will investigate if common drugs or interventions influence the identified autoimmunity-related gut signals. By generating a library of interventions influencing the gut microbiome it will be possible to select promising candidates for pilot treatment trials after liver transplantation. 

The outcome of StopAutoimmunity will be gut signals useful as novel biomarkers and treatment targets. These may directly translate into improved patient care but also provide a foundation for understanding the mechanisms of autoimmunity.