Clinical and Translational Research
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. May 27, 2021; 13(5): 543-556
Published online May 27, 2021. doi: 10.4254/wjh.v13.i5.543
Bile acid indices as biomarkers for liver diseases II: The bile acid score survival prognostic model
Jawaher Abdullah Alamoudi, Wenkuan Li, Nagsen Gautam, Marco Olivera, Jane Meza, Sandeep Mukherjee, Yazen Alnouti
Jawaher Abdullah Alamoudi, Wenkuan Li, Nagsen Gautam, Yazen Alnouti, Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, NE 68198-6025, United States
Jawaher Abdullah Alamoudi, Department of Pharmaceutical Sciences, Princess Nourah Bint Abdulrahman University, Riyadh 11564, Saudi Arabia
Marco Olivera, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE 68105, United States
Jane Meza, Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE 68198-4375, United States
Sandeep Mukherjee, Department of Internal Medicine, Creighton University Medical Center, Omaha, NE 68124, United States
Author contributions: Alamoudi JA is the primary researcher, collected and analyzed data, wrote the manuscript, prepared figures and formatted manuscript for publication; Li WK and Gautam N helped in the LC-MS/MS sample analysis; Meza J supervised, reviewed, and approved all statistical analysis and provided intellectual input and feedback on manuscript; Olivera M and Mukherjee S helped in recruiting and consenting patients and sample collection as well as experimental design; Alnouti Y is the primary investigator who was responsible for the experimental design and supervising all aspects of this project and manuscript preparation.
Supported by the University of Nebraska Medical Center-Clinical Research Center and Great Plains Health Research Consortium, No. NR98-134.
Institutional review board statement: The study was reviewed and approved by the University of Nebraska Medical Center Institutional Review Board (Approval No. 487-10-EP).
Clinical trial registration statement: This study is registered at https://www.clinicaltrials.gov/ct2/show/NCT01200082?term=alnouti&draw=2&rank=1. The registration identification number is [NCT01200082].
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: The authors declare that there is no conflict of interests in this study.
Data sharing statement: Technical appendix, statistical code, and data set available from the corresponding author at [yalnouti@unmc.edu]. Participants gave informed consent for data sharing.
CONSORT 2010 statement: The authors have read the CONSORT 2010, and the manuscript was prepared and revised according to the CONSORT 2010.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yazen Alnouti, PhD, Professor, Department of Pharmaceutical Sciences, University of Nebraska Medical Center, 42nd and Emile, Omaha, NE 68198-6025, United States. yalnouti@unmc.edu
Received: January 5, 2021
Peer-review started: January 5, 2021
First decision: February 13, 2021
Revised: February 21, 2021
Accepted: March 31, 2021
Article in press: March 31, 2021
Published online: May 27, 2021
Abstract
BACKGROUND

Cholestatic liver diseases are characterized by an accumulation of toxic bile acids (BA) in the liver, blood and other tissues which lead to progressive liver injury and poor prognosis in patients.

AIM

To discover and validate prognostic biomarkers of cholestatic liver diseases based on the urinary BA profile.

METHODS

We analyzed urine samples by liquid chromatography-tandem mass spectrometry and investigated the use of the urinary BA profile to develop survival models that can predict the prognosis of hepatobiliary diseases. The urinary BA profile, a set of non-BA parameters, and the adverse events of liver transplant and/or death were monitored in 257 patients with cholestatic liver diseases for up to 7 years. The BA profile was characterized by calculating BA indices, which quantify the composition, metabolism, hydrophilicity, formation of secondary BA, and toxicity of the BA profile. We have developed and validated the bile-acid score (BAS) model (a survival model based on BA indices) to predict the prognosis of cholestatic liver diseases.

RESULTS

We have developed and validated a survival model based on BA (the BAS model) indices to predict the prognosis of cholestatic liver diseases. Our results demonstrate that the BAS model is more accurate and results in higher true-positive and true-negative prediction of death compared to both non-BAS and model for end-stage liver disease (MELD) models. Both 5- and 3-year survival probabilities markedly decreased as a function of BAS. Moreover, patients with high BAS had a 4-fold higher rate of death and lived for an average of 11 mo shorter than subjects with low BAS. The increased risk of death with high vs low BAS was also 2-4-fold higher and the shortening of lifespan was 6-7-mo lower compared to MELD or non-BAS. Similarly, we have shown the use of BAS to predict the survival of patients with and without liver transplant (LT). Therefore, BAS could be used to define the most seriously ill patients, who need earlier intervention such as LT. This will help provide guidance for timely care for liver patients.

CONCLUSION

The BAS model is more accurate than MELD and non-BAS models in predicting the prognosis of cholestatic liver diseases.

Keywords: Hepatobiliary diseases, Bile acid indices, Death, Liver transplant, Survival model, Prognosis

Core Tip: We have developed survival models based on bile acid (BA) indices to predict the prognosis of hepatobiliary diseases. Our BA models outperformed the model for end-stage liver disease and non-BA models in predicting the occurrence of the adverse events of death and/or liver transplant.