Searching the Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Liver-type fatty acid-binding protein (L-FABP) is a key regulator of fatty acid metabolism, but serum L-FABP levels are not well investigated in chronic liver diseases. We aimed to elucidate the prognostic ability of serum L-FABP in human chronic liver diseases and compare it with the albumin-bilirubin (ALBI) score. In 242 chronic liver disease patients, including chronic hepatitis (CH, n = 100), liver cirrhosis (LC, n = 142), and presence of hepatocellular carcinoma (HCC, n = 144), serum L-FABP levels were correlated with liver function (P < 0.0001), increased in LC compared with CH (P < 0.01), and correlated to ALBI score (P < 0.0001). Serum L-FABP levels were increased in the presence of HCC (P < 0.0001), correlating to des-gamma-carboxy prothrombin (P < 0.0001), alpha-fetoprotein (P = 0.009), and Barcelona-Clinic Liver Cancer stage. In the average follow-up period of 1,054 days, serum L-FABP levels were elevated (P < 0.0001) in patients who eventually died. The area under the curve (AUC) of serum L-FABP (0.764) was higher than that of ALB (0.709), and the patients with serum L-FABP ≤ 6.8 ng/mL had significantly longer rates of survival (P < 0.0001). Serum L-FABP (hazard ratio [HR] 4.0; P < 0.001), HCC (HR 3.7; P = 0.001), ALBI score (HR 2.7; P < 0.001), and age (HR 1.0; P = 0.049) were independent predictors of survival. In the subgroup who maintained liver function, the AUC of serum L-FABP (0.751) was higher than that of ALB (0.643). In this subgroup, serum L-FABP (HR 4.4; P = 0.002) and HCC (HR 13.9; P < 0.001) were independent predictors of survival. Conclusion: Serum L-FABP is a possible predictor of survival in chronic liver diseases from CH to LC and HCC, including any subgroup that maintains liver function.
Pubmed ID: 31168516
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentions