Poly-hydroxylated bile acids and their prognostic roles in Alagille syndrome

doi:10.21203/rs.3.rs-1605055/v1

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Poly-hydroxylated bile acids and their prognostic roles in Alagille syndrome

https://doi.org/10.21203/rs.3.rs-1605055/v1

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The liver manifestations of Alagille syndrome (ALGS) are highly variable, and factors affecting its prognosis are poorly understood. We asked whether or not the composition of bile acids in ALGS patients with good clinical outcomes differs from those with poor outcomes, and whether bile acids could be used as prognostic biomarkers. Blood for bile acid profiling were collected from genetically confirmed JAG1-associated ALGS patients before one year of age. Good prognosis was defined as survival with native liver and total bilirubin (TB) < 85.5 µmol/L, while poor prognosis as either liver transplanted, died of liver failure, or TB ≥ 85.5 µmol/L at last follow-up. We found that the concentrations of two poly-hydroxylated bile acids, tauro-2β,3α,7α,12α-tetrahydroxylated bile acid (THBA), and glyco-hyocholic acid (GHCA), were significantly increased in patients with good prognosis compared to those with poor prognosis (AUC = 0.836 and 0.782, respectively) in the discovery cohort. The same trend was also observed in the molar ratios of GHCA to GCDCA and THCA to TCDCA (both AUC = 0.836). A validation cohort confirmed these findings. Notably, tauro‐2β,3α,7α,12α-THBA achieved the highest prediction accuracy of 88.00% (92.31% sensitivity and 83.33% specificity); GHCA at > 607.69 nmol/L was associated with native liver survival (hazard ratio: 6.456, 95% CI: 1.173–35.545, P = 0.032). We identified two poly-hydroxylated bile acids as the liver prognostic biomarkers of ALGS patients. Enhanced hydroxylation of bile acids may result in better clinical outcomes.

bile acid profile

Alagille syndrome

prognostic biomarkers

poly-hydroxylated bile acids

Alagille syndrome (ALGS, OMIM 118450) is a multisystem autosomal dominant developmental disorder that is caused by pathogenic variants in either Jagged 1 (JAG1) or NOTCH2, with the JAG1 variants accounting for about 95% of the diagnosed cases[1–5]. It potentially leads to end-stage liver diseases requiring liver transplantation[6]. The poor prognosis of ALGS poses a substantial burden on clinical management, as well as on the families and society economically and emotionally.

With highly variable clinical manifestations and outcomes, and the lack of obvious correlation between genotype and phenotype[2], potential biomarkers indicating the liver prognosis of ALGS are urgently needed[7]. Previously, Kamath et al reported that in some cases of ALGS, total bilirubin levels fell rapidly between 12–24 months of age and the decrease may be associated with better outcomes[8]. However, to our knowledge, no early (before one-year-old age) prognostic biomarkers for ALGS have been reported to date.

Bile acids are amphipathic molecules essential for multiple physiological functions such as lipids and energy homeostasis[9, 10]. However, hydrophobic bile acids at high physiological concentrations are inherently cytotoxic which could induce inflammatory stress in the liver or intestines[11–13]. Hydroxylation and conjugation through amidation with glycine and taurine or esterification with sulfuric acids and glucuronic acids increase their hydrophilicity, representing two efficient mechanisms of bile acid detoxification[14, 15]. The compositions and relative hydrophobicity of different bile acids in biological materials are usually analyzed by ultrahigh performance liquid chromatography coupled to multiple-reaction monitoring-mass spectrometry (UPLC-MRM-MS)[16].

Tetrahydroxy bile acids (THBAs) are highly hydrophilic bile acids bearing four hydroxyl groups in their nuclear steroid rings. THBAs are usually not detectable or only present in trace amounts in healthy humans but they are often detected in the serum and urine of cholestatic patients and mouse models. It has been speculated that THBA may act as hepatoprotective agents in alleviating cholestatic stress[17–21]. In 2001, Wang et al reported the presence of a large amount of THBAs in Bsep^−/− mice, which displayed only very mild cholestasis in contrast to human BSEP (ABCB11) deficiency that results in fatal childhood disease, i.e., progressive familial intrahepatic cholestasis type 2 (PFIC 2). It was proposed that THBAs might protect the mutant mice from severe cholestatic damage[22]. A follow-up study of Mdr2^−/− and Bsep^−/− double knockout mice showed that increased hydrophilic bile acids such as muricholic acids (MCA, triply-hydroxylated bile acids) and THBAs, and reduced cholic acid prevented liver damage caused by the Mdr2^−/− genotype, which typically presented with progressive liver damages due to severe cholangitis[23]. In a preliminary study in infants with intrahepatic cholestasis of mixed etiologies, a high level of THBAs in urine was observed to be associated with good clinical outcomes[19]. In a more focused study of 17 PFIC 2 (ABCB11 deficiency) patients and 12 patients with genetically undiagnosed cholestasis, in comparison with 35 healthy controls, some THBAs and tauro-THBAs were found elevated along with significantly reduced hydrophobicity of the bile acid pools in plasma of PFIC 2 and genetically undiagnosed cholestasis patients[18]. In a follow-up study of a subset of PFIC 2 patients who underwent partial internal biliary diversion, Liu et al observed that changes in the level of THBAs were well-correlated with disease relief and recurrence, which implies a potential use for THBAs as prognostic indicators[24].

Since bile acids play a key role in cholestatic diseases, we asked in the present study whether THBA or other bile acids could be potential liver prognostic biomarkers of ALGS outcomes.

Study design

Blood serum or plasma for bile acid profiling were clinical specimens collected from genetically confirmed JAG1-associated ALGS patients before one year of age. These specimens were the leftover samples from clinical tests, which were deposited in biobanks in Jinshan Hospital (Shanghai, China) and Children's Hospital of Fudan University (Shanghai, China according to ethics approvals (No.2014-13-01 in Jinshan Hospital and No.2015-178 in Children's Hospital of Fudan University). The study was approved by the Ethics Committee of Children’s Hospital of Fudan University (Shanghai, China) (No. 2017-99). The selection of patients and samples was outlined in Fig. 1. If one patient had more than one specimen collected before the age of one year, the earliest one was used. Samples collected from 01 January 2015 to 30 December 2017 were enrolled as the discovery cohort and those collected from 01 January 2018 to 31 October 2020 as the validation cohort.

Subjects and grouping

The clinical diagnosis of ALGS was made by standard clinical criteria[3]: the presence of bile duct paucity and at least three major clinical features, or at least four of six major clinical features (chronic cholestasis, cardiac murmur, skeletal abnormalities, ocular abnormalities, a characteristic face, and renal abnormalities) in the absence of paucity of bile ducts. Only patients with confirmed JAG1 pathogenic/likely pathogenic variants were enrolled in this study. The exclusion criteria were as follows: (1) received Kasai procedure; (2) less than one year old in the last follow-up or lost to follow-up before the age of one year; (3) samples that were not available in the biobank.

The patients’ prognosis was assessed according to both clinical data and liver function tests at the last follow-up, which were collected from the medical electronic record system or parents of the patients. A good prognosis was defined as patients satisfying both of the following criteria: 1) survival with their native liver; 2) TB ＜85.5 μmol/L. Poor prognosis was defined if either of the following events occurs: 1) received liver transplantation; 2) died of liver failure; 3) TB ≥ 85.5 μmol/L.

According to the above criteria, 21 ALGS patients with JAG1 mutations were enrolled in the discovery cohort. Among them, 11 were grouped as good prognosis, including six patients without jaundice and five with mild jaundice at the last follow-up. They were sampled at a median age of 7.8 months with an interquartile of 6.1 m to 10.7 m. The last follow-up was at a median age of 3y4m (interquartile 1y10m to 5y5m). Ten were grouped as poor prognosis, including two who died before 1-year-old, five received liver transplantation at ages of 1y5m to 2y7m, and three lived with severe jaundice with the last follow-up at ages 4y5m, 3y10m, and 6y2m respectively. They were sampled at a median age of 7.9 months (interquartile 5.8m to 11.25m).

25 ALGS patients were enrolled in the validation cohort. Among them, 12 were grouped as good prognosis with a median sampling age of 4.5 months (interquartile 3.8m to 4.6m). Among them, nine patients lived without jaundice and three lived with mild jaundice at the last follow-up with a median age of 2y7m and interquartile of 2y3m to 4y. Thirteen were grouped as poor prognosis with a median sampling age at 6.4 months (interquartile 5.2m to 9.5m) among which 10 lived with severe jaundice after followed up to median age of 3y and interquartile 2y to 4y9m, one received liver transplantation at 6m old, and two died at the age of 9m and 2y10m. The demographic data and follow-up details of these patients were presented in Table S1.

Sample collection and specimen preparation

Plasma from AGLS patients in the discovery cohort was separated from EDTA‐treated peripheral blood by centrifugation and serum was collected. The samples were aliquoted, lyophilized, and stored at −80 °C until bile acid analysis. The samples of the validation cohort were from frozen plasma or serum deposited in the biobanks.

Bile acid analysis

Bile acid analysis was performed by ultrahigh-performance liquid chromatography coupled to multiple-monitoring reaction mass spectrometry (UPLC/MRM‐MS) according to the procedures as well as LC and MS operating parameters as previously described. [16] Briefly, bile acids in plasma or serum were extracted with a mixture of methanol/acetonitrile (1:1, v/v), followed by cleanup and enrichment by reversed-phase solid-phase extraction with the use of polymeric Strata-X cartridges (33 µm, 60 mg/1 mL, Phenomenx Inc. CA). Reversed-phase (C18) UPLC/MRM‐MS with negative ion detection was used to separate and quantitate bile acids in the samples of the discovery cohort, which was carried out in the University of Victoria‐Genome British Columbia Proteomics Centre. Quantitation of bile acids in the samples of the validation cohort was performed in the Institutes of Biomedical Sciences of Fudan University. In total, 83 bile acids including primary BAs (cholic acid, CA; chenodeoxycholic acid, CDCA) and secondary BAs (deoxycholic acid, DCA; lithocholic acid, LCA; ursodeoxycholic acid, UDCA), and their metabolites in the classes of unconjugated, glycine conjugated (glyco-), taurine conjugated (tauro-), sulfated and glucuronidated BAs, together with a few keto-/diketo- BAs, unconjugated and taurine conjugated THBAs, were quantified, with the use of their standard substances for the preparation of linearly regressed, internal-standard calibration curves. 14 deuterium-labeling bile acids were used as the internal standards for accurate quantitation. For the BAs, for which none of their isotope-labeling internal standards were available, glyco-CDCA-d4 was used as a common internal standard.

Total bile acids (TBA) are the sum of all detected bile acids. The total of sulfated, glyco- and tauro-bile acids were respectively calculated by adding the concentrations of the corresponding conjugated forms in each category. For example, concentrations of CA 3-sulfate, DCA 3-sulfate, CDCA 3-sulfate, and LCA 3-sulfate were summed as the total of bile acid sulfates. The concentrations of unconjugated and conjugated CA and CDCA, and that of unconjugated and conjugated DCA and LCA, were summed as the total of primary and secondary bile acids, respectively. The percentages of individual BAs among the total of its category, the molar ratio of secondary BAs to primary BAs, and the molar ratio of total tauro-BAs to total glyco-BAs were also calculated. The molar ratios of conjugated to corresponding unconjugated BAs were used to reflect the specific metabolism processes, including hydroxylation (GHCA: GCDCA and THCA: TCDCA), glyco-conjugation (GCA: CA, GCDCA: CDCA, GUDCA: UDCA, etc.), tauro-conjugation (TCA: CA, TCDCA: CDCA, TUDCA: UDCA, etc.), sulfonation (CAS: CA, CDCAS: CDCA, LCAS: LCA, etc.), glucuronidation (CDCA-glu: CDCA), carbon shortening from C24 to C23 BAs (nor-CA: CA, nor-UDCA: UDCA, nor-THBA: THBA) and oxide reduction (7-keto-LCA: LCA)[18].

Statistical analysis

Median and interquartile range (IQR) for quantitative indexes were presented. Mann-Whitney U test was used to determine the difference in the indexes between the two groups. Prognostic biomarkers were selected via receiver operating characteristic (ROC) curve analysis. Youden's index was used to define the optimal cut-off value. Fisher’s exact test was used to test the predicted efficacy of biomarkers in the validation cohort. Multivariate Cox regression analysis was conducted to determine whether the bile acids were independently associated with native liver survival. Kaplan-Meier curves were used to display survival curves. Graphs were generated using GraphPad Prism (version 8.0, GraphPad Software Inc.). Statistical significance was considered at P < 0.05 bilateral.

Bile acid profiles in the discovery cohort

The concentrations of individual bile acids in the good prognosis versus poor prognosis patients in the discovery cohort were presented in Table 1. Eighty-three bile acids were analyzed for each patient (see Materials and Methods). Glyco-hyocholic acid (GHCA) in the good prognosis group showed higher concentrations than that in the poor prognosis group (median and inter-quartile range (IQR): 1168.03 nmol/L, 692.83 ~ 1863.72 nmol/L vs. 557.90 nmol/L, 339.18 ~ 1002.53 nmol/L, P = 0.036), a similar trend was found in tauro‐2β,3α,7α,12α-THBA (91.73 nmol/L, IQR: 52.07 ~ 298.87 nmol/L vs. 51.60 nmol/L, IQR: 34.72 ~ 69.77 nmol/L, P = 0.013). Some other poly-hydroxylated bile acids such as tauro-hyocholic acid (THCA) (P = 0.099), tauro-3α,6α,7α,12α-THBA (P = 0.061), and tauro-3α,6β,7α,12α-THBA (P = 0.099) also showed trends similar to GHCA and tauro‐2β,3α,7α,12α-THBA, with borderline significance. No statistical difference was observed in the concentrations of other bile acids except 3-oxo-CA.

To explore the overall metabolic process of bile acids, concentrations of individual bile acids were summed according to their different categories (Table S2). It was found that the concentration of total tauro-THBAs in the good prognosis group (3607.11 nmol/L, 1851.66 ~ 4506.49 nmol/L) was significantly higher than that in the poor prognosis group (1022.25 nmol/L, 749.59 ~ 1629.08 nmol/L; P = 0.001). No significant differences were observed in other categories, as well the molar ratios of tauro-BAs to glyco-BAs, and the secondary BAs to the primary BAs between these two patient groups.

To analyze in more detail the role of bile acid modification in these two groups of patients, the respective molar ratios of individual bile acids, conjugated versus unconjugated bile acids and some atypical modifications versus unmodified forms were examined (Table 2). The process of hydroxylation (GHCA: GCDCA, THCA: TCDCA) was significantly enhanced in patients with good prognosis compared to the patients with poor prognosis (P = 0.013 and 0.010 respectively). No significant differences were observed in the processes of sulfonation, taurine or glycine conjugation, glucuronidation, or oxide reduction between the two groups.

Bile acid profiles in the validation cohort

To determine whether the results observed in the discovery cohort could be reproduced, the same set of bile acids was profiled in a validation cohort of another 25 JAG1-variant confirmed patients. The difference in the poly-hydroxylated bile acids including GHCA, THCA, three tauro-THBAs (tauro-3α,6α,7α,12α-THBA, tauro-3α,6β,7α,12α-THBA and tauro-2β,3α,7α,12α-THBA) between the two different prognostic groups was confirmed and even more pronounced in the validation cohort (Table 3). Also, the molar ratios of GHCA to GCDCA and THCA to TCDCA as indicators of the bile acids metabolism process via hydroxylation were significantly higher in the good prognosis group than in the poor prognosis group. However, no significant difference was observed for 3-oxo-CA between the two prognosis groups in the validation cohort.

Selection and validation of ALGS prognostic biomarkers

We then focused on the poly-hydroxylated bile acids to determine if they could be used as biomarkers to predict the outcomes of young (one-year-old or less) ALGS patients. The variables with P-value < 0.05 and AUC > 0.7, both in the discovery and validation cohorts, were included as the candidates. Poly-hydroxylated bile acids, GHCA and tauro-2β,3α,7α,12α-THBA, and the molar ratios of GHCA to GCDCA and THCA to TCDCA were initially enrolled.

Optimal cutoffs (GHCA: 607.69 nmol/L, tauro-2β,3α,7α,12α-THBA: 79.88 nmol/L, GHCA: GCDCA: 0.0220, and THCA: TCDCA: 0.0762) were determined using the Youden index in the discovery cohort (Table 4) and these values were applied to predict prognostic outcomes in the validation cohort. The results are seen in Table 5, where, tauro‐2β,3α,7α,12α-THBA achieved an accuracy of 88.00% (92.31% sensitivity and 83.33% specificity), and the molar ratio of THCA to TCDCA achieved a prediction accuracy of 84.00% (100% sensitivity and 67.67% specificity) in the validation cohort.

Univariate and multivariate Cox proportional hazard model

Next, statistical tests of the poly-hydroxylated bile acids (GHCA, THCA, three tauro-THBAs) by Cox proportional hazard model analysis were used to assess their associations with the native liver survivability in the two cohorts using the optimal cutoff values determined in Table 4. Univariate analysis showed that the concentrations of GHCA, THCA, tauro‐3α,6β,7α,12α-THBA, and tauro-2β,3α,7α,12α-THBA affected the native liver survival (Fig. 2), while multivariate analysis indicated that the GHCA concentration was the single independent factor influencing native liver survival (hazard ratio: 6.456, 95%CI: 1.173 - 35.545, P=0.032) (Table 6). The ALGS patients with blood GHCA concentrations of lower than 607.69 nmol/L had a significantly higher death and/or transplantation rate (7/13 died or received liver transplantation at a median age of one year) compared with patients with GHCA concentrations higher than 607.69 nmol/L (2/33 received liver transplantation at 1 year 5 months old and 2 year 2 months old, respectively).

To our knowledge, no in-depth bile acid profiling in ALGS patients has been reported previously. The present study was focused on analyzing the profiles of bile acids, especially the poly-hydroxylated ones, in ALGS patients with different clinical outcomes to explore the potential liver prognostic indicators of the disease. We took advantage of a relatively large cohort of patients with follow-up data, and a comprehensive panel of different bile acids including multiple bile acids in the classes of unconjugated THBAs and tauro-THBAs, and used a well-developed bile acid profiling method[16]. We discovered that some poly-hydroxylated bile acids could serve as excellent prognostic biomarkers, and the enhanced bile acid poly-hydroxylation may have the ability to predict a good prognosis of ALGS.

Increased hydroxylation makes the bile acids pool more hydrophilic which is believed to be a common compensatory response observed in animals, and patients, experiencing cholestatic stress[17]. THBAs, the bile acids with four hydroxyl groups, and MCA, bile acids with three hydroxyl groups, in their molecular structures, had been found greatly elevated in Bsep^−/− mice, and expression of high levels of such bile acids prevented the progressive liver pathology associated with the Mdr2^−/− mutation[23]. Taurine conjugates are the major form of bile acid conjugation in mice [16, 25] and were often found elevated in cholestatic human patients[18, 24, 26, 27]. We have successfully quantified six new synthetic tauro-THBAs in this study. Consistent with the previous findings of Liu et al[18] that the levels of tauro-THBAs, THCA, GHCA were much higher in patients with ABCB11 deficiency and patients with undiagnosed cholestasis, we found that the levels of tauro- or glyco-conjugated polyhydroxylated bile acids in ALGS patients in this study were also much higher than those in healthy controls. The poly-hydroxylated bile acids in ALGS were mainly in tauro- or glyco- conjugated forms rather than unconjugated forms (Table S1). More importantly, we observed and verified that higher blood levels of tauro-2β,3α,7α,12α-THBA, and GHCA are associated with a better liver and overall prognosis of the patients.

Both conjugation and hydroxylation were the common pathways of bile acids metabolism for increased hydrophilicity and cellular detoxification of hydrophobic bile acids[15]. In this study, we found no difference in the molar ratios of bile acid conjugation, such as glyco- to tauro- conjugation, or sulfonation, in the ALGS patients associated with outcomes. This suggests that the processes of glyco-, tauro- conjugation, and sulfonation may not be involved in the differentiation of cholestatic responses in ALGS, as often seen in other forms of cholestasis in humans[18, 24, 26]. However, we observed and verified that the molar ratios GHCA to GCDCA and THCA to TCDCA were associated with different prognosis outcomes in this study, indicating that the enhanced bile acid poly-hydroxylation in ALGS patients may contribute to better clinical outcomes and survivability. It is therefore to assume that the high concentration of bile acids in ALGS patients due to cholestasis induces bile acid detoxification by producing poly-hydroxylated bile acids, which are more hydrophilic and less cytotoxic than the usual bile acids found in the control population[17].

One limitation of this study is that we were not able to compare the mRNA expression profiles of hydroxylases in the liver tissue of ALGS patients with different outcomes, as we did not have liver tissues from patients with a good prognosis. In Mdr2^−/− and Bsep^−/− mice, it was observed that the process of hydroxylation is enhanced by the up-regulation of hydroxylases[23]. Meanwhile, more studies are warranted to explore whether the poly-hydroxylated bile acids can be used as prognostic biomarkers for other forms of cholestasis or cholestatic liver diseases.

The current study has clinical relevance. It is known that the presentations and survivability of ALGS patients vary widely. [1] Some severely affected patients require liver transplantation, while others survive and even thrive with the native liver[6]. Unavoidably, some patients die while waiting for a suitable donor. An accurate prognostic biomarker(s) could help to triage patients to more appropriate treatments. The finding that lower levels of blood poly-hydroxylated bile acids indicated poor prognosis with high rates of mortality or liver transplantation, implied that more aggressive treatment and more comprehensive management could be clinically applied. The current findings provide some leads for future medical therapeutic development of ALGS. They raise the possibility that enhancing poly-hydroxylation of bile acids might be an effective therapeutic target for patients with cholestasis.

The findings from this study indicate that the blood level of tauro-2β,3α,7α,12α-THBA in ALGS patients before 1-year of age could be an excellent prognostic biomarker and that GHCA can predict native liver survival of such patients. The increased poly-hydroxylated bile acids and enhanced hydroxylation process associated with good clinical outcomes may point to a potential therapeutic target.

Author contributions:

Conceptualization: JSW, TL, MXW

Methodology: MXW, JH, JCY, LZ

Investigation: MXW, LTL, ZDL, LLL, SYL

Visualization: YL, XBX, JYG, JSW

Funding acquisition: JSW, TL

Project administration: JSW

Supervision: JSW

Writing – original draft: MXW, JSW

Writing – review & editing: JSW, JH, RXW, VL

Acknowledgments:

The authors are grateful for the support of the families we have studied, and would also like to thank the referring physicians, nurses, and technical staff. We thank Prof. Ying-Jie Zheng ([email protected]) as an independent statistician for his statistical guidance. This research was supported by the National Key Research and Development Program of China (Grant No. 2021YFC 2700800), the National Natural Science Foundation of China (81741056, 81873543), and the Natural Science Foundation of Shanghai (20YF1402900).

Competing interests: Authors declare that they have no competing interests.

Contributor Information:

Meng-Xuan Wang:[email protected]

Jun Han: [email protected]

Teng Liu: [email protected]

Ren-Xue Wang: [email protected]

Li-Ting Li: [email protected]

Zhong-Die Li: [email protected]

Jun-Cong Yang: [email protected]

Lang-Li Liu: [email protected]

Yi Lu: [email protected]

Xin-Bao Xie: [email protected]

Jing-Yu Gong: [email protected]

Shi-Yu Li2: [email protected]

Lei Zhang: [email protected]

Victor Ling: [email protected]

Jian-She Wang: [email protected]

Kamath BM, YeW, Goodrich NP, Loomes KM, Romero R, Heubi JE, et al. Outcomes of Childhood Cholestasis in Alagille Syndrome: Results of a Multicenter Observational Study. Hepatol Commun. 2020;4:387–98. 10.1002/hep4.1468: https://doi.org/10.1002/hep4.1468.
Gilbert MA, Bauer RC, Rajagopalan R, Grochowski CM, Chao G, McEldrew D, et al. Alagille syndrome mutation update: Comprehensive overview of JAG1 and NOTCH2 mutation frequencies and insight into missense variant classification. Hum Mutat. 2019;40:2197. 2220.10.1002/humu.23879: https://doi.org/10.1002/humu.23879.
Kamath BM, Piccoli DA. Liver Disease in Children. 3rd ed. New York: Cambridge University Press; 2007.
Kamath BM, Bason L, Piccoli DA, Krantz ID, Spinner NB. Consequences of JAG1 mutations. J Med Genet 2003;40:891-895.10.1136/jmg.40.12.891: https://doi.org/10.1136/jmg.40.12.891.
Spinner NB, Colliton RP, Crosnier C, Krantz ID, Hadchouel M, Meunier-Rotival M Jagged1 mutations in alagille syndrome. Hum Mutat. 2001;17:18-33.10.1002/1098 – 1004(2001)17:1 < 18::AID-HUMU3 > 3.0.CO;2-T: https://doi.org/10.1002/1098-1004(2001)17:1<18::AID-HUMU3>3.0.CO;2-T.
Kamath BM, Baker A, Houwen R, Todorova L, Kerkar N. Systematic Review: The Epidemiology, Natural History, and Burden of Alagille Syndrome. J Pediatr Gastroenterol Nutr 2018;67:148–56.10.1097/MPG.0000000000001958: https://doi.org/10.1097/MPG.0000000000001958.
Emerick KM, Rand EB, Goldmuntz E, Krantz ID, Spinner NB, Piccoli DA. Features of Alagille syndrome in 92 patients: frequency and relation to prognosis. Hepatology 1999;29:822–9.10.1002/hep.510290331: https://doi.org/10.1002/hep.510290331.
Mouzaki M, Bass LM, Sokol RJ, Piccoli DA, Quammie C, Loomes KM, et al. Early life predictive markers of liver disease outcome in an International, Multicentre Cohort of children with Alagille syndrome. Liver Int. 2016;36:755. 760.10.1111/liv.12920: https://doi.org/10.1111/liv.12920.
Chiang JYL. Bile acid metabolism and signaling in liver disease and therapy. Liver Res. 2017;1:3. 9.10.1016/j.livres.2017.05.001: https://doi.org/10.1016/j.livres.2017.05.001.
Monte MJ, Marin JJ, Antelo A, Vazquez-Tato J. Bile acids: chemistry, physiology, and pathophysiology. World J Gastroenterol. 2009;15:804. 816.10.3748/wjg.15.804: https://doi.org/10.3748/wjg.15.804.
Hofmann AF, Hagey LR. Key discoveries in bile acid chemistry and biology and their clinical applications: history of the last eight decades. J Lipid Res. 2014;55:1553–95. 10.1194/jlr.R049437: https://doi.org/10.1194/jlr.R049437.
Wang R, Sheps JA, Ling V. ABC transporters, bile acids, and inflammatory stress in liver cancer. Curr Pharm Biotechnol 2011;12:636–46.10.2174/138920111795163986: https://doi.org/10.2174/138920111795163986.
Fickert P, Wagner M. Biliary bile acids in hepatobiliary injury - What is the link? J Hepatol. 2017;67:619. 631.10.1016/j.jhep.2017.04.026: https://doi.org/10.1016/j.jhep.2017.04.026.
Alnouti Y. Bile Acid sulfation: a pathway of bile acid elimination and detoxification. Toxicol Sci. 2009;108:225. 246.10.1093/toxsci/kfn268: https://doi.org/10.1093/toxsci/kfn268.
Morita SY, Ikeda Y, Tsuji T, Terada T. Molecular Mechanisms for Protection of Hepatocytes against Bile Salt Cytotoxicity. Chem Pharm Bull (Tokyo). 2019;67:333. 340.10.1248/cpb.c18-01029: https://doi.org/10.1248/cpb.c18-01029.
Han J, Liu Y, Wang R, Yang J, Ling V, Borchers CH. Metabolic profiling of bile acids in human and mouse blood by LC-MS/MS in combination with phospholipid-depletion solid-phase extraction. Anal Chem 2015;87:1127–36.10.1021/ac503816u: https://doi.org/10.1021/ac503816u.
Sheps JA, Wang R, Wang J, Ling V. The protective role of hydrophilic tetrahydroxylated bile acids (THBA). Biochim Biophys Acta Mol Cell Biol Lipids 2021;1866:158925.10.1016/j.bbalip.2021.158925: https://doi.org/10.1016/j.bbalip.2021.158925.
Liu T, Wang RX, Han J, Hao CZ, Qiu YL, Yan YY, et al. Comprehensive bile acid profiling in hereditary intrahepatic cholestasis: Genetic and clinical correlations. Liver Int 2018;38:1676-1685.10.1111/liv.13714: https://doi.org/10.1111/liv.13714.
Lee CS, Kimura A, Wu JF, Ni YH, Hsu HY, Chang MH, et al. Prognostic roles of tetrahydroxy bile acids in infantile intrahepatic cholestasis. J Lipid Res. 2017;58:607–14. 10.1194/jlr.P070425: https://doi.org/10.1194/jlr.P070425.
Fuchs CD, Paumgartner G, Wahlstrom A, Schwabl P, Reiberger T, Leditznig N, et al. Metabolic preconditioning protects BSEP/ABCB11(-/-) mice against cholestatic liver injury. J Hepatol 2017;66:95-101.10.1016/j.jhep.2016.08.017: https://doi.org/10.1016/j.jhep.2016.08.017.
Megaraj V, Iida T, Jungsuwadee P, Hofmann AF, Vore M. Hepatobiliary disposition of 3alpha,6alpha,7alpha,12alpha-tetrahydroxy-cholanoyl taurine: a substrate for multiple canalicular transporters. Drug Metab Dispos 2010;38:1723-1730.10.1124/dmd.110.033480: https://doi.org/10.1124/dmd.110.033480.
Wang R, Salem M, Yousef IM, Tuchweber B, Lam P, Childs SJ, et al. Targeted inactivation of sister of P-glycoprotein gene (spgp) in mice results in nonprogressive but persistent intrahepatic cholestasis. Proc Natl Acad Sci U S A. 2001;98:2011–6. 10.1073/pnas.031465498: https://doi.org/10.1073/pnas.031465498.
Wang R, Sheps JA, Liu L, Han J, Chen PSK, Lamontagne J, et al. Hydrophilic bile acids prevent liver damage caused by lack of biliary phospholipid in Mdr2(-/-) mice. J Lipid Res. 2019;60:85. 97.10.1194/jlr.M088070: https://doi.org/10.1194/jlr.M088070.
Liu T, Wang RX, Han J, Qiu YL, Borchers CH, Ling V, et al. Changes in plasma bile acid profiles after partial internal biliary diversion in PFIC2 patients. Ann Transl Med 2020;8:185.10.21037/atm.2020.01.103: https://doi.org/10.21037/atm.2020.01.103.
Zheng J, Ye C, Hu B, Yang H, Yao Q, Ma J, et al. Bile acid profiles in bile and feces of obese mice by a high-performance liquid chromatography-tandem mass spectrometry. Biotechnol Appl Biochem. 2020. 10.1002/bab.2055: https://doi.org/10.1002/bab.2055.
Mao F, Liu T, Hou X, Zhao H, He W, Li C, et al. Increased sulfation of bile acids in mice and human subjects with sodium taurocholate cotransporting polypeptide deficiency. J Biol Chem. 2019;294:11853–62. 10.1074/jbc.RA118.007179: https://doi.org/10.1074/jbc.RA118.007179.
Bathena SP, Mukherjee S, Olivera M, Alnouti Y. The profile of bile acids and their sulfate metabolites in human urine and serum. J Chromatogr B Analyt Technol Biomed Life Sci 2013;942–943:53-62.10.1016/j.jchromb.2013.10.019: https://doi.org/10.1016/j.jchromb.2013.10.019.

Table 1. Blood concentrations of individual bile acids in the discovery cohort of ALGS patients with different prognosis

Compound name	RT	Median (IQR) nM^#		AUC	P^&
	(min)	Good prognosis (n=11)	Poor prognosis (n=10)		P^&
CA	14.80	51.48(22.52, 75.09)	34.92(29.30, 46.09)	0.550	0.705
TCA	9.60	21566(10197, 47081)	48097(10549, 65579)	0.627	0.349
GCA	11.90	40940(13059, 53168)	34798(24146, 72742)	0.582	0.557
CAS	7.4	35.06(12.75, 59.32)	19.29(10.38, 32.92)	0.659	0.223
GCAS	4.5	505.6(72.67, 700.4)	274.5(69.96, 564.8)	0.591	0.512
AlloCA	10.8	3.15(0.88, 8.94)	2.16(1.58, 3.55)	0.582	0.557
GalloCAS	4.4	12.37(7.67, 52.34)	13.53(5.20, 23.44)	0.600	0.468
THCA	5.4	1307(635.6, 4639)	743.6(556.9, 1372)	0.718	0.099
GHCA	6.3	1168(692.8, 1864)	557.9(339.2, 1003)	0.782	0.036
Nor-CA	9.0	95.04(42.65, 144.2)	61.02(38.30, 92.43)	0.536	1.000
3-oxo-CA	10.7	5.52(0.73, 9.22)	19.34(12.58, 28.68)	0.836	0.008
CDCA	18.60	64.54(49.54, 78.69)	72.13(52.54, 118.7)	0.577	0.557
TCDCA	13.00	30312(8026, 45238)	52417(22812, 68302)	0.655	0.251
GCDCA	10.3	65325(21265, 120317)	121154(42077, 137028)	0.636	0.314
CDCAG	8.8	286.4(210.8, 338.8)	114.4(41.34, 275.5)	0.745	0.061
CDCAS	9.5	26.88(18.78, 52.21)	39.69(19.31, 80.54)	0.568	0.605
TCDCAS	4.9	10148(4402, 16185)	13089(6698, 18386)	0.618	0.387
GCDCAS	6.3	8406(5013, 12897)	11668(6477, 17445)	0.627	0.349
DCA	19.10	102.9(95.62, 114. 8)	92.63(85.94, 108.2)	0.723	0.085
GDCAS	6.6	25.16(18.50, 58.33)	36.06(2.29, 61.25)	0.509	1.000
LCA	23.70	0.21(0.15, 0.41)	0.40(0.15, 0.79)	0.618	0.387
GLCA	19.60	6.98(2.04, 19.15)	10.10(3.88, 15.59)	0.532	0.809
LCAS	11.9	3.77(0.61, 7.33)	3.10(0.61, 10.69)	0.518	0.918
GLCAS	8.5	36.21(25.07, 67.16)	2.68(2.05, 105.40)	0.618	0.387
TLCAS	6.4	102.3(58.05, 244.4)	131.0(67.31, 294.8)	0.582	0.557
7-keto-LCA	12.6	4.91(2.82, 7.75)	4.39(3.90, 9.26)	0.523	0.863
UDCA	11.3	1584 (199.8, 5875)	538.9(109.4, 4090)	0.627	0.349
TUDCA	6.2	16330(6877, 41259)	24644 (2282, 51708)	0.536	0.809
GUDCA	7.2	34069(13804, 52817)	55195 (6483, 81022)	0.564	0.654
GUDCAS	4.1	112603 (71089, 137659)	79968 (26029, 148981)	0.582	0.557
Nor-UDCA	9.1	17.22(0.15, 33.60)	26.70(0.15, 31.90)	0.500	1.000
α-MCA	8.8	0.44(0.30, 7.68)	0.28(0.18, 0.95)	0.618	0.387
λ-MCA	10.1	10.19(0.15, 12.35)	0.15(0.15, 12.96)	0.605	0.426
ω-MCA	8.5	17.74(6.74, 43.66)	7.10(2.13, 34.69)	0.700	0.132
3α,4α,7β,12α-THBA	4.9	9.67(2.14, 51.63)	5.40(2.43, 23.71)	0.555	0.705
Nor-THBA	3.8	44.06(36.95, 57.24)	37.36(32.03, 62.58)	0.568	0.605
Tauro-3α,6α,7α,12α-THBA	3.6	262.6(31.70, 453.3)	44.09(19.93, 102.16)	0.745	0.061
Tauro-3α,6β,7α,12α-THBA	2.8	306.4(48.47, 651.2)	95.85(44.24, 180.5)	0.718	0.099
Tauro-2β,3α,7α,12α-THBA	4.0	91.73(52.07, 298.9)	53.42.60(33.94, 73.46)	0.836	0.013

RT: Retention time; IQR: Interquartile range; AUC: Area under the curve; CA: Cholic acid; TCA: Tauro-cholic acid; GCA: Glyco-cholic acid; CAS: Cholic acid-sulfate; GCAS: Glyco-cholic acid-sulfate; AlloCAS: Allo-cholic acid-sulfate; THCA: Tauro-hyocholic acid; GHCA: Glyco -hyocholic acid; CDCA: Chenodeoxycholic acid; TCDCA: Tauro-chenodeoxycholic acid; GCDCA: Glyco-chenodeoxycholic acid; CDCAG: Chenodeoxycholic acid-glucuronidation; CDCAS: Chenodeoxycholic acid-sulfate; TCDCAS: Tauro-chenodeoxycholic acid-sulfate; GCDCAS: Glyco-chenodeoxycholic acid-sulfate; DCA: Deoxycholic acid; GDCAS: Glyco-deoxycholic acid-sulfate; LCA: Lithocholic acid; GLCA: Glyco-lithocholic acid; LCAS: Lithocholic acid-sulfate; GLCAS: Glyco-lithocholic acid-sulfate; TLCAS: Tauro-lithocholic acid-sulfate; 7-keto-LCA: 7-ketonized lithocholic acid; UDCA: Ursodeoxycholic acid; TUDCA: Tauro-ursodeoxycholic acid; GUDCA: Glyco-ursodeoxycholic acid; GUDCAS: Glyco-ursodeoxycholic acid-sulfate; Nor-UDCA: 23C-ursodeoxycholic acid; MCA: Muricholic acid; THBA: Tetrahydroxylated bile acid; Nor-THBA : 23C-tetrahydroxylated bile acid;

^&: Mann-Whitney U test; nM: nmol/L; ^#: Only integer parts were displayed in values >1000, values from 100 to 1000 were rounded to 1 decimal place and 2 decimal places in values<100

Table 2. Molar ratios of conjugated vs unconjugated bile acids, and atypical modifications versus unmodified forms in the discovery cohort

Molar ratio	Median (IQR)*		AUC	P^&
Molar ratio	Good prognosis(n=11)	Poor prognosis(n=10)	AUC	P^&
A	GHCA: GCDCA	0.0236 (0.0092, 0.0405)	0.0065 (0.0034, 0.0183)	0.836	0.013
	THCA: TCDCA	0.0792 (0.0382, 0.1295)	0.0213 (0.0113, 0.0420)	0.836	0.010
B	CAS: CA	0.5500 (0.4000, 1.030)	0.5213 (0.3204, 0.9313)	0.573	0.605
	CDCAS: CDCA	0.5009 (0.3712, 0.8506)	0.5812 (0.4509, 0.7205)	0.518	0.918
	LCAS: LCA	5.728 (4.001, 26.33)	8.591(3.253, 21.34)	0.536	0.809
	GCAS: GCA	0.0092 (0.0047, 0.0249)	0.0059 (0.0042, 0.0083)	0.718	0.099
	GalloCAS: GalloCA	0.0190 (0.0145, 0.1456)	0.0451 (0.0223, 0.0621)	0.590	0.512
	GCDCAS: GCDCA	0.1137 (0.0894, 0.2357)	0.1031 (0.0683, 0.1701)	0.609	0.426
	GLCAS: GLCA	6.252 (1.804, 17.58)	2.249 (0.1657, 17.32)	0.636	0.314
	GUDCAS: GUDCA	2.522 (1.726, 6.064)	1.073 (0.7374, 2.593)	0.709	0.114
	TCDCAS: TCDCA	0.3377 (0.2496, 0.5186)	0.2921 (0.1826, 0.4012)	0.627	0.349
C	TCA: CA	622.9 (268.5, 1411)	1329 (274.7, 1635)	0.618	0.387
	TCDCA: CDCA	595.5 (175.6, 637.0)	612.3 (271.0, 1017.0)	0.581	0.557
	TUDCA: UDCA	17.68 (3.790, 52.20)	20.47 (10.06, 139.5)	0.645	0.251
	TCDCAS: CDCAS	242.3 (110.03, 408.4)	292.1 (115.4, 411.6)	0.518	0.918
	TLCAS: LCAS	30.19 (16.37, 95.11)	27.92 (13.07, 99.63)	0.509	1.000
D	GCA: CA	781.8 (540.5, 989.4)	1036 (604.5, 1932)	0.663	0.223
	GCDCA: CDCA	1012 (503.1, 1175)	1528 (840.3, 1919)	0.645	0.282
	GalloCA: alloCA	88.26 (57.76, 1506)	103.5 (81.82, 192.5)	0.509	0.973
	GLCA: LCA	14.96 (9.347, 64.35)	18.77 (10.66, 52.42)	0.500	1.000
	GUDCA: UDCA	38.29 (3.156, 183.5)	65.29 (28.25, 199.6)	0.645	0.282
	GCAS: CAS	10.84 (5.863, 21.87)	8.371 (6.454, 20.46)	0.509	0.973
	GCDCAS: CDCAS	259.9 (156.4, 342.4)	220.5 (133.1, 420.5)	0.509	1.000
	GLCAS: LCAS	10.47 (1.434, 41.08)	4.210 (0.2201, 51.67)	0.590	0.512
E	CDCAG: CDCA	5.035 (1.428, 8.654)	1.7607 (0.5234, 3.2535)	0.745	0.061
F	Nor-CA: CA	1.772 (1.205, 3.580)	2.000 (1.004, 2.4403)	0.555	0.705
	Nor-UDCA: UDCA	0.0059 (0.0006, 0.0561)	0.0460 (0.0041, 0.3794)	0.727	0.143
	Nor-THBA: THBA	3.543 (0.7225, 16.60)	3.400 (0.9112, 7.3637)	0.536	0.809
G	7-keto-LCA: LCA	23.52 (8.275, 43.36)	15.20 (4.910, 37.54)	0.573	0.605

IQR: Interquartile range; AUC: Area under the curve; A, Hydroxylation; B, Sulfation; C, Taurine conjugation; D, Glycine conjugation; E, Glucuronidation; F, 23C bile acid; G, Oxidoreduction; GHCA: Glyco-hyocholic acid; GCDCA: Glyco-chenodeoxycholic acid; THCA: Tauro-hyocholic acid; TCDCA: Tauro-chenodeoxycholic acid; CAS: Cholic acid-sulfate; CA: Cholic acid; CDCDS: Chenodeoxycholic acid-sulfate; CDCA: Chenodeoxycholic acid; LCAS: Lithocholic acid-sulfate; LCA: Lithocholic acid; GCAS: Glyco-cholic acid-sulfate; GCA: Glyco-cholic acid; GalloCAS: Glyco-allocholic acid-sulfate; GalloCA: Glyco-allocholic acid; GCDCAS: Glyco-chenodeoxycholic acid-sulfate; GCDCA: Glyco-chenodeoxycholic acid; GLCAS: Glyco-lithocholic acid-sulfate; GLCA: Glyco-lithocholic acid; GUDCAS: Glyco-ursodeoxycholic acid-sulfate; GUDCA: Glyco-ursodeoxycholic acid; TCDCAS: Tauro-chenodeoxycholic acid-sulfate; TCDCA: Tauro-chenodeoxycholic acid; TCA: Tauro-cholic acid; TUDCA: Tauro-ursodeoxycholic acid ; UDCA: Ursodeoxycholic acid; TCDCAS: Tauro-chenodeoxycholic acid-sulfate; TLCAS: Tauro-lithocholic acid-sulfate; CDCAG: Chenodeoxycholic acid-glucuronidation; Nor-CA: 23C-cholic acid; Nor-UDCA: 23C-ursodeoxycholic acid; Nor-THBA: 23C-tetrahydroxylated bile acid; THBA: Tetrahydroxylated bile acid; 7-keto-LCA: 7-ketonized lithocholic acid; ^&: Mann-Whitney U test; *: Values displayed to 4 significant figures rounded up to 4 decimal places;

Table 3. The results of blood concentrations and molar ratios of selected bile acids in the validation cohort

Bile acids	Median (IQR)^#		AUC	P^&
Bile acids	Good prognosis (n=12)	Poor prognosis (n=13)		P^&
GHCA(nM)	2517.13(1256.22, 3553.13)	710.42(355.14, 1719.05)	0.814	0.008
THCA(nM)	3366.61(2552.91, 4689.99)	1227.12(687.99, 1496.65)	0.885	0.001
3-oxo-CA	0.86(0.32, 4.38)	1.36(0.33, 3.48)	0.506	1.000
Tauro-3α,6α,7α,12α-THBA(nM)	118.14(67.94, 437.30)	28.23(0.09, 48.70)	0.904	0.000
Tauro-3α,6β,7α,12α-THBA(nM)	424.33(184.88, 1227.66)	69.00(42.12, 104.11)	0.942	0.000
Tauro-2β,3α,7α,12α-THBA(nM)	267.87(132.75, 303.96)	0.09(0.09, 36.69)	0.907	0.000
GHCA: GCDCA	0.0177(0.0129, 0.0261)	0.0036(0.0020, 0.0110)	0.904	0.000
THCA: TCDCA	0.0843(0.0512, 0.1145)	0.0194(0.0112, 0.0594)	0.923	0.000

CA: Cholic acid; GHCA: Glyco-hyocholic acid; THCA: Tauro-hyocholic acid; THBA: Tetrahydroxylated bile acid; GCDCA: Glyco-chenodeoxycholic acid; THCA: Tauro-hyocholic acid; TCDCA: Tauro-chenodeoxycholic acid; nM: nmol/L; IQR: Interquartile range; AUC: Area under the curve; ^&: Mann-Whitney U test; ^#: Results are rounded to two decimal points.

Table 4. The receiver operating characteristic curve analysis and the optimal cut-off values of poly-hydroxylated bile acids in the discovery cohort

Bile acids	Cut-off value	AUC	95% CI		Sensi tivity	Speci ficity	+LR	-LR	P^&
Bile acids	Cut-off value	AUC	Lower limit	Upper limit	Sensi tivity	Speci ficity	+LR	-LR	P^&
GHCA	607.69(nM)	0.773	0.561	0.985	0.909	0.600	2.27	0.15	0.036
THCA	1033.96(nM)	0.718	0.495	0.941	0.727	0.700	2.42	0.39	0.099
Tauro‐ 3α,6α,7α,12α -THBA	102.84(nM)	0.745	0.520	0.971	0.727	0.800	3.64	0.34	0.061
Tauro‐ 3α,6β,7α,12α -THBA	187.80(nM)	0.718	0.485	0.951	0.727	0.800	3.64	0.34	0.099
Tauro‐2β,3α,7α,12α -THBA	79.88(nM)	0.818	0.634	1.000	0.727	0.900	7.27	0.30	0.013
GHCA: GCDCA	0.0220	0.818	0.638	0.999	0.545	1.000	0.54	0.00	0.013
THCA: TCDCA	0.0762	0.827	0.651	1.000	0.545	1.000	0.54	0.00	0.010

GHCA: Glyco-hyocholic acid; THCA: Tauro-hyocholic acid; THBA: Tetrahydroxylated bile acid; GCDCA: Glyco-chenodeoxycholic acid; TCDCA: Tauro-chenodeoxycholic acid; nM: nmol/L; AUC: Area under the curve; CI: Confidence interval; +LR: Positive likelihood ratio; -LR: Negative likelihood ratio; ^&: Mann-Whitney U test

Table 5. The prognostic efficiency of the candidate indices

Criterion	Good prognosis(n=12)	Poor prognosis(n=13)	P^$	χ2	Sensitivity (%)	Specificity (%)	Correct prediction rate (%)	+LR	-LR
GHCA<607.69(nM)	0/12	6/7	0.015	7.29	46.15%	100%	72%	0.00	0.54
Tauro‐2β,3α,7α,12α-THBA<79.88(nM)	2/10	12/1	0.000	14.49	92.31%	83.33%	88%	5.54	0.09
GHCA: GCDCA <0.0220	8/4	13/0	0.039	5.16	100%	33.33%	68%	1.49	0.00
THCA: TCDCA <0.0762	4/8	13/0	0.000	12.75	100%	67.67%	84%	3.03	0.00

GHCA: Glyco-hyocholic acid; THBA: Tetrahydroxylated bile acid; GCDCA: Glyco-chenodeoxycholic acid; THCA: Tauro-hyocholic acid; TCDCA: Tauro-chenodeoxycholic acid; nM: nmol/L; ^$: Fisher’s exact test; +LR: Positive likelihood ratio; -LR: Negative likelihood ratio.

Table 6. Univariate and multivariate Cox proportional analysis of the hydroxylated bile acids associated with a reduced native liver survival rate

Bile acids criterion	Univariate Analysis		Multivariate Analysis
Bile acids criterion	Hazard Ratio (95%CI)	P*	Hazard Ratio (95%CI)	P*
GHCA<607.69 (nM)	41.85(7.91-221.6)	<0.0001	7.63(1.412, 41.66)	0.018
THCA<1033.96 (nM)	4.66(1.253-17.33)	0.042	-	0.80
Tauro‐3α,6α,7α,12α-THBA <102.84 (nM)	3.51(0.96-12.78)	0.089	-	-
Tauro‐3α,6β,7α,12α-THBA <187.80 (nM)	4.72(1.34-16.68)	0.028	-	0.66
Tauro‐2β,3α,7α,12α-THBA <79.88 (nM)	7.04(1.99-24.84)	0.0035	-	0.95

GHCA: Glyco-hyocholic acid; THCA: Tauro-hyocholic acid; THBA: Tetrahydroxylated bile acids; nM: nmol/L; CI: Confidience interval; *: log-rank test

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Poly-hydroxylated bile acids and their prognostic roles in Alagille syndrome

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