P: 1 Genetic Fingerprint of Hepatic Encephalopathy Risk in Liver Cirrhosis

Abstract

BACKGROUND: To determine the impact of genetic factors on the development of hepatic encephalopathy (HE) in patients with liver cirrhosis. METHODS: Patients suffering from compensated liver cirrhosis [n = 434; estimation cohort (n = 294) and validation cohort (n = 140)] were included. Patients were followed up for five years until HE bouts, liver transplant, or death. Methods: Patients were genotyped for 62 candidate SNPs (genes involved in the pathophysiology of HE: inflammation, ammonia and glutamine metabolism, intestinal barrier integrity and oxidative stress) by using OpenArray custom plates. Likewise, a haplotype formed by four SNPs within GLS plus the length of a microsatellite in the promoter region of GLS were determined (Romero-Gómez et al. Ann Intern Med 2010). Statistical analysis was performed by Cox regression and Kaplan-Meier for continuous and categorical data. Significant variables, and those known as weighted prognostic indicators, were entered into multivariable models by competing risks, according to Fine and Gray's method. RESULTS: In the estimation cohort, competing risks analysis showed GLS mutations, FUT2-(rs601338), TLR9-(rs5743836), SLC1A3-(rs2562582) and SLC1A5-(rs313853), together with MELD, albumin, sodium and previous episodes of HE as variables independently associated to HE development. Those genes encode for proteins involved in maintenance of intestinal barrier integrity by host-microbial interactions (FUT2), pro-inflammatory response triggered by pathogens (TLR-9) and glutamine transport (SLC1A3 and SLC1A5). Combining these genetic factors according to number of alleles at risk, three levels of risk patients were defined: low, mid or high risk [sHR: 1; 6.5 (1.8–22.9) P = 0.004; 27.1 (7.5–96.8) P < 0.001, respectively] (C-index = 0.82). This regression model performed in a similar manner in the validation cohort [sHR: 1; 4.2 (1.2–14.3) P = 0.024; 10.0 (2.7–36.7) P < 0.001] (C-index = 0.78). Cumulative survival free of HE after 5 years was also influenced by this genetic fingerprint: 95.3%, 77.0% and 42.5% for the low, mid and high-risk groups (log-Rank 53.1; P < 0.001) in the estimation, and 85.2%, 56.0% and 40.0% (log-Rank 14.1; P < 0.001) in the validation cohort, respectively (Figure 1). CONCLUSIONS: Combination of unfavorable variants could predict HE. This genetic fingerprint could be implemented in clinical practice for decision making in the management of cirrhotic patients. Besides, this work emphasizes the role of these pathways in the pathophysiology of HE and brings out novel genes as potential therapeutic targets.