Immunologic Predictors of Liver Transplantation Outcomes in HIV-HCV Co-Infected Persons

Ashwin Balagopal1, Burc Barin2, Jeffrey Quinn1

  • 1Department of Medicine, Johns Hopkins University, Baltimore, MD, 21205, United States of America.

Plos One
|August 28, 2015
PubMed

Insights

Predicting liver transplant outcomes in HIV-HCV co-infected patients is crucial. Pre-transplant monocyte activation markers like sCD14 and IL-10 may predict graft loss and rejection, respectively, in these high-risk individuals.

Area of Science:

  • Immunology
  • Hepatology
  • Infectious Diseases

Background:

  • Liver disease is a major cause of death in HIV-infected individuals, even with treatment.
  • Hepatitis C Virus (HCV) co-infection is common in HIV patients and leads to poorer outcomes, often necessitating liver transplantation (LT).
  • Post-LT outcomes remain suboptimal for patients with HIV-HCV co-infection.

Purpose of the Study:

  • To identify pre-transplant immunologic biomarkers that predict outcomes after liver transplantation in HIV-HCV co-infected individuals.
  • To investigate the association between immune activation, microbial translocation, and Th1/Th2 skewing with graft loss, rejection, and recurrent HCV post-LT.

Main Methods:

  • A cohort of 69 HIV-HCV co-infected patients undergoing LT was studied.
  • Pre-transplant immunologic biomarkers (sCD14, IL-10) were measured.
  • Cox-proportional hazards models were used to analyze predictors of post-LT outcomes, including graft loss, rejection, and recurrent HCV.

Main Results:

  • Lower pre-LT sCD14 levels were associated with increased risk of graft loss (HR 0.10).
  • Higher pre-LT IL-10 levels were linked to a greater risk of acute rejection (HR 2.10).
  • No specific biomarkers predicted severe recurrent HCV post-LT.

Conclusions:

  • Pre-transplant monocyte activation, indicated by sCD14 and IL-10 levels, may be mechanistically linked to graft health and rejection risk in HIV-HCV co-infected patients undergoing liver transplantation.
  • These biomarkers could potentially aid in risk stratification and management strategies for this vulnerable patient population.