Liver transplantation (LTx) is now well-established as a means of restoring health in patients with end-stage liver disease (ESLD), the 10th leading cause of death in the US. With a long-term goal of optimizing the outcome of patients undergoing LTx, we have developed state-of-the-art statistical models applicable to daily care of LTx patients. One such example is the model for end stage liver disease (MELD), which has been adopted as an indicator of disease serverity with which to determine organ allocation priority for LTx in US. The focus of investigation in this application is renal insufficiency (Rl), a common and important problem in the setting of LTx. Rl prior to LTx is an important predictor of death;in some patients, it also necessitates combined liver-kidney transplantation. After LTx, some recovery of renal function occurs, but in more than a third of patients, Rl fails to resolve. Immunosuppressive drugs after LTx tend to be nephrotoxic, further decreasing the renal function of our patients. In this application, we address these issues by accomplishing the following aims. Aim1: We will investigate the best ways to estimate renal function in patients waiting for LTx and determine whether incorporating measures of renal function enhances the accuracy of survival prediction by MELD. Aim 2: We will identify predictors of reversibility of renal damage in patients with ESLD to inform the decision whether to perform combined liver-kidney transplantation. Predictive factors to be studied include renal histology (from biopsies obtained at the time of LTx surgery), a profile of serial GFR estimates, and urinary protein markers (microalbumin, a1-microglobulin and retinol-binding protein) prior to LTx. Aim 3: We will determine whether single nucleotide polymorphisms on the endothelial nitric oxide synthase gene determinine susceptibility to Rl before and after LTx. The results of Aim 1 will help allocate livers to patients at the highest risk of mortality. Aim 2 will yield information with which to reduce morbidity and mortality from Rl among LTx patients. The results of Aim 3 will help clinicians better assess patients at risk of Rl in order to optimize pre- and post-LTx management. Taken altogether, our projects will advance knowledge about the renal insufficiency that occurs in patients undergoing liver transplantation and will help achieve optimal outcomes by providing clinical tools with which to identify for patients at risk of poor outcome and to facilitate timely interventions.