ToxSci Advance Access published October 24, 2014

Urinary Bile Acids as Biomarkers for Liver Diseases II. Signature Profiles in Patients Sai Praneeth R Bathena*, Rhishikesh Thakare*, Nagsen Gautam*, Sandeep Mukherjee†, Marco Olivera†, Jane Meza‡, Yazen Alnouti*§



Department of Internal Medicine, College of Medicine, University of Nebraska Medical Center, Omaha, NE, 68198, United States



§

Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE, 68198, United States

Correspondence to: Yazen Alnouti, Ph.D., Department of Pharmaceutical

Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198-6025, United States Phone: 402-559-2407 Fax: 402-559-9543 E-mail: [email protected]

Running title: Bile acids profile in liver patients

 

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*Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, United States

Abstract Hepatobiliary diseases result in the accumulation of bile acids (BAs) in the liver, systemic blood, and other tissues leading to an unfavorable prognosis. The BA profile was characterized by the calculation of indices that describe the composition, sulfation, and amidation of total and individual BAs. Comparison of the urinary BA profiles between healthy subjects and patients with hepatobiliary

and total BAs in patients. The % sulfation of some individual BAs were different between the two groups. The % amidation of overall and most individual BAs was higher in patients than controls. The % of primary BAs (CDCA and CA) was higher in patients, whereas, the % of secondary BAs (DCA and LCA) was lower in patients. BA indices belonging to % amidation and % composition were better associated with the severity of the liver disease as determined by the model for end-stage liver disease (MELD) score and disease compensation status compared to the absolute concentrations of individual and total BAs. In addition, BA indices corresponding to % amidation and % composition of certain BAs demonstrated the highest area under the receiver operating characteristic (ROC) curve suggesting their utility as diagnostic biomarkers in clinic. Furthermore, significant increase in the risk of having liver diseases was associated with changes in BA indices.

Keywords: hepatobiliary diseases, bile acids, bile acid sulfation, bile acid amidation, biomarker

 

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diseases demonstrated significantly higher absolute concentrations of individual

INTRODUCTION Several studies in animal models including cats and dogs indicated that bile acids (BAs) are elevated in liver diseases (Center et al., 1991; Balkman et al., 2003; Trainor et al., 2003). In addition, total BAs correlated well with the progression of liver and bile duct damage in bile-duct ligated and thiocitamideinduced cholestatic rats (Dueland et al., 1991; Kawai et al., 2009). The role of

been

investigated

extensively

in

intrahepatic

cholestasis

of

pregnancy

(Heikkinen, 1983; Ambros-Rudolph et al., 2007; Lucangioli et al., 2009; Sinakos and Lindor, 2010; Tribe et al., 2010), biliary atresia (Matsui et al., 1996; Shinohara et al., 2005) (Muraji et al., 2003), primary biliary cirrhosis (Trottier et al., 2012), primary sclerosing cholangitis (Trottier et al., 2012), alcoholic liver diseases (Stiehl et al., 1985; Simko et al., 1987; Mendenhall et al., 1993), nonalcoholic fatty liver disease (Dasarathy et al., 2011), and in viral hepatitis (Makino et al., 1969; Takikawa et al., 1986; Sherlock and Dusheiko, 1991; Ruiz et al., 1992; Liang et al., 1993; Simko and Michael, 1998). Currently, serum BAs are clinically used as biomarkers for the diagnosis of intrahepatic cholestasis of pregnancy (Huang et al., 2007).

BAs are also involved in the regulation of

glucose homeostasis and energy expenditure and their role as biomarkers for diabetes/metabolic syndrome is being investigated. Lower postprandial levels of BAs were observed in obese and diabetic subjects compared to healthy subjects possibly due to impaired bile flow, which attenuates the secretion of incretins including glucagon-like peptide 1 (GLP-1), gastric inhibitory peptide (GIP), and

 

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bile acids (BAs) as biomarkers for hepatobiliary diseases in humans has also

peptide YY (PYY) (Nakatani et al., 2009; Patti et al., 2009; Brufau et al., 2010; Glicksman et al., 2010; Roberts et al., 2011; Pournaras et al., 2012; Haeusler et al., 2013; Valentini et al., 2013). Serum BAs rise after food ingestion due to the release of cholecystokinin, which stimulates gallbladder contraction resulting in increasing bile flow into the intestine. Therefore, feeding status should be controlled before serum BAs can

this series, we observed that urinary BAs are affected to a lesser extent by food intake, and thus, in contrast to serum BAs, do not have to be obtained at fasting state (stability paper). Previous studies by other groups also support this notion (Simko et al., 1987; Simko and Michael, 1998).

BAs vary markedly in their

physiological roles and more importantly in their toxicities.

In general,

hepatotoxicity caused by monohydroxy BA (LCA) is the highest, followed by dihydroxy BA (CDCA and DCA), and then trihydroxy BA (CA) (Thomas et al., 2008; Song et al., 2011). Therefore, the damage inflicted on hepatocytes and cholangiocytes by accumulated BAs in liver diseases may be better correlated with the levels of the more toxic individual BAs rather than the levels of total BAs. Sulfation by the enzyme sulfotransferase 2A1 (SULT2A1) increases the solubility of BAs, enhances the urinary and fecal excretion of BAs, and more importantly, reduces their toxicity (Alnouti, 2009). In humans, urinary BAs are primarily sulfated. It was reported that total urinary BA-sulfates better correlated with the degree of liver damage than total serum BAs or serum enzymes in cats and dogs (Balkman et al., 2003; Trainor et al., 2003). Urinary BA-sulfates were  

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be used as a reliable biomarker. However, as demonstrated in the first paper of

shown to be highly sensitive for the early diagnosis of biliary atresia in children with normal serum transaminase enzymes (Muraji et al., 2003).

In addition,

urinary BA-sulfates were suggested to better predict intrahepatic cholestasis of pregnancy with better selectivity and specificity than serum or urine total BAs (Huang et al., 2007). These studies collectively suggest that urinary BA-sulfates can be more selective biomarkers of hepatobiliary diseases than serum liver

Although sulfation decreases the overall toxicity of BAs, the extent to which sulfation decreases toxicity of individual BAs, varies among different BAs. In addition, there are marked differences in the affinity of individual BAs for sulfation by SULT2A1 (Huang et al., 2010). BAs with high affinity to sulfation are the most toxic and are present in very low concentrations (LCA and DCA), while BAs with low affinity to sulfation are less toxic and comprise the major proportion of the total BA pool (CA and CDCA). Consequently, BA sulfation can be up-or down-regulated during hepatobiliary diseases without affecting the levels of total BA-sulfates significantly. Therefore, the extent to which the more toxic BAs such as LCA and DCA are present in the sulfated form rather than total BA-sulfates is more likely to reflect sulfation activity in vivo. Similar to sulfation, amidation with glycine and taurine amino acids plays a major role in increasing the solubility, enhancing the urinary excretion, and decreasing the toxicity of BAs (Heuman et al., 1991; Hofmann and Hagey, 2008; Bathena et al., 2013).

Therefore, the

extent to which BAs are amidated could also determine the toxicity of the BA profile.

 

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enzymes or total BAs in humans and in animal models.  

This study consists of two papers, which aim to investigate the use of the BA profile in urine as a biomarker for the diagnosis and prognosis of liver diseases. In the first paper, we characterized the stability of the baseline urinary BA profile in healthy controls without liver diseases. In this paper, we studied the differences between the urinary BA profiles in healthy subjects and patients with a variety of liver diseases. We quantified the BA profile via “BA indices” that

with amino acids and sulfation) of total and individual BAs. The performance of potential biomarkers from the urinary BA profile were also compared with that of existing markers of liver function including aspartate transaminase (AST), alanine transaminase (ALT), albumin, serum creatinine, protime, international normalized ratio (INR), and bilirubin. MATERIALS AND METHODS Study participants For controls, ninety healthy subjects, without liver diseases, (63 female and 27 male) between the ages of 19-65 were recruited by the Clinical Research Center in the University of Nebraska Medical Center as described previously (Bathena et al., 2013). Thirty mL of urine was collected from these subjects at fasting conditions over multiple visits. New and existing patients of the UNMC hepatology clinic, who were diagnosed with hepatobiliary conditions due to chronic hepatitis C (n=30), hepatitis B (n=6), alcoholic liver disease (n=23), primary biliary cirrhosis (n=6),

 

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describe the composition, hydrophilicity, and metabolism (including amidation

primary sclerosing cholangitis (n=6), autoimmune hepatitis (n=13), α1-antitrypsin deficiency (n=3), nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (n=36), and unknown etiology (n=7) were enrolled in this study. A total of 121 patients (57 female and 64 male; age range: 21-83 years) were recruited into the study after signing informed consents.

Thirty ml urine samples were collected

from patients on every visit to the hepatology clinic. Samples from all visits were

profile and the severity of the liver disease, patients were divided into three groups based on their MELD score: low MELD (6-15 score), medium MELD (1625), and high MELD (26-40). As there were only two subjects who had a high MELD score in the current study, this group was not included in the statistical analysis. In addition, patients were divided according to the compensation status as diagnosed by the hepatologists. Patients with decompensated liver diseases have severe complications including ascites, bleeding varices, encephalopathy, or jaundice. Compensated patients did not have any of these complications. Non-BA parameters The following non-BA parameters were measured in healthy subjects and patients with liver diseases.

Total bilirubin in serum was analyzed using

QuantiChromTM assay kit (BioAssay Systems, Hayward, CA). Aspartate transaminase (AST), alanine transaminase (ALT), albumin, and serum creatinine were measured using the Beckman Coulter reagents (Beckman Coulter, Inc., Brea, CA). Protime and international normalized ratio (INR) was measured using

 

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included in the statistical analysis. To study the relationship between the BA

STA-Neoplastine “CI PLUS 10” reagent kit (Diagnostica Stago Inc., Parsippany, NJ). Measurement and calculation of BA Indices More than 45 BAs and their sulfate metabolites were quantified by LCMS/MS as described previously (Bathena et al., 2013).

The BA profile was

sulfation, and amidation of total and individual BAs as described in the first paper of this series. Statistical analysis BA profiles were not normally distributed according to the shapiro-wilk test. Therefore, nonparametric tests were used for all statistical analyses. For comparison of BA profiles between controls and patients, the Wilcoxon/MannWhitney rank-sum test was used. BA profiles were compared between control, low MELD (patients), and medium MELD (patients) groups using Kruskal-wallis ANOVA followed by post-hoc pairwise comparisons using Bonferroni’s adjustment if the p-value was 0.8,

comparisons were made between controls and specific liver disease group using the Wilcoxon/Mann-Whitney rank-sum test. A p-value of 0.05 was considered significant for all the statistical tests described above. All statistical analyses were performed using the Statistical Product and Service Solutions (SPSS) software, version 18 (IBM corporation, Armonk, NY). RESULTS Controls and Patients Table 1 shows the absolute concentrations of major urinary BAs in controls and patients.

Table 2 compares representative absolute BA concentrations and

indices between controls and overall patients as well as MELD and compensation patient groups. Supplementary Table 1 shows the results of all BA concentrations and indices that were determined in the current study. Total

 

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for a 10% change from the mean value of BA concentrations/indices.

BAs were 7.7-fold higher in patients compared to controls. The concentrations of primary BAs, CDCA (11.2 fold) and CA (8 fold) were also markedly higher in patients (Table 2). The % of CDCA, CA, and UDCA were 1.6 fold, 1.2 fold, and 1.3 fold higher in patients, whereas, the % of LCA and DCA were 2 fold lower in patients than controls (Table 2). There was not a significant difference in the % sulfation of overall BAs between controls and patients (Table 2). However, the %

and DCA being slightly lower (0.99 fold) and % sulfation of UDCA and CA being slightly higher (1.01-1.1 fold) in patients than controls (Table 2).

The %

amidation of overall BAs, UDCA, CA, and CDCA were higher in patients by 1.1 fold, 1.3 fold, 1.2 fold, and 1.03 fold respectively, whereas, the % amidation of LCA and DCA were lower in patients by 0.99 fold (Table 2). The % glycineamidation (G-amidation) of overall BAs, UDCA, and CA were higher in patients by 1.05 fold, 1.2 fold, and 1.6 fold, whereas, the % glycine-amidation of DCA was lower in patients by 0.9 fold (Supplementary Table 1). The % taurine-amidation (T-amidation) of overall BAs, UDCA, CDCA, and DCA were also higher in patients by 1.3 fold, 3.1 fold, 2.1 fold, and 1.9 fold respectively, whereas, the % taurine-amidation of CA was ~0.9 fold lower in patients (Supplementary Table 1). Low and Medium MELD groups Table 2 compares representative urinary BA concentrations and indices in controls and in patient MELD groups. The individual and total BA concentrations were higher in the medium MELD group (1.2 to 3.2 fold) than the low MELD group except for UDCA (~2 fold higher in the low MELD group). The % CDCA  

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sulfation of some individual BAs was statistically different with % sulfation of LCA

was 1.6-fold higher in the medium compared to the low MELD group, whereas the % of all other individual BAs were not significantly different. There were no significant differences in the % sulfation or % amidation of overall and individual BAs between low MELD and medium MELD groups. However, the % sulfation of UDCA and CA were slightly higher (1.01-1.1 fold) in low MELD than controls, whereas % sulfation of CDCA was slightly lower (~0.99 fold) in the medium

UDCA, CDCA, and CA were higher in both the low (1.03-1.3 fold) and the medium MELD (1.04-1.3 fold) groups compared to controls.

The % glycine-

amidation of LCA was slightly lower in the medium MELD than low MELD group (~0.9 fold), whereas, the % taurine-amidation of LCA and CDCA was higher in medium MELD than low MELD group by 1.3 fold and 1.2 fold respectively (Supplementary Table 1). Compensated and Decompensated Patients Table 2 compares representative urinary BA concentrations and indices between compensated and decompensated patients. Urinary concentrations of individual and total BAs were higher in the decompensated patients than the compensated patients (1.5-3 fold), except for UDCA concentration, which was 0.6 fold lower in the decompensated patients. The % of LCA, UDCA, and DCA were 0.5-0.6 fold lower in decompensated patients, whereas the % of primary BAs (CDCA and CA) were 1.3-1.6 fold higher in decompensated compared to compensated patients. The % sulfation of overall BAs did not differentiate compensated from decompensated patients, whereas % sulfation of some individual BAs (UDCA  

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MELD group compared to controls. Similarly, the % amidation of overall BAs,

and CDCA) was slightly lower (~0.99 fold) in decompensated patients. The % amidation of overall BAs, CDCA, and DCA were slightly higher (1.01-1.02 fold) in decompensated compared to compensated patients. The % glycine-amidation of LCA and DCA were lower in decompensated patients by 0.8 fold and 0.9 fold respectively (Supplementary Table 1). The % taurine-amidation of overall BAs, LCA, UDCA, CDCA, and DCA were higher in decompensated patients by 1.4

Receiver operating characteristic (ROC) curve analysis Figure 1 shows ROC curves of representative BA indices concentrations. Table 3 lists BA concentrations and indices with area under the ROC curve (AUC) > 0.7. Absolute unsulfated glycine-amidated BAs, CDCA and CA (sulfated and total), % total DCA, % sulfated DCA of sulfated BA, and % amidated of unsulfated BA, % amidation of dihydroxy BAs, % glycine-amidation UDCA, and % amidation of UDCA demonstrated AUC > 0.8. Potential cut-off values selected based on the optimum sensitivity and selectivity for BA indices with AUC > 0.8 are listed in Table 4. Correlation analysis Correlation analyses were performed for BA concentrations and indices with ROC (AUC) > 0.8 to determine their association with non-BA parameters. The spearman correlation coefficients (ρ) for the correlation between BA indices and non-BA parameters are shown in Supplementary Table 2. Most BA concentrations/indices

 

demonstrated

significant

correlation

with

non-BA

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fold, 1.7 fold, 1.5 fold, and 1.7 fold respectively (Supplementary Table 1).

parameters including protime, INR, AST, ALT, serum creatinine, albumin, bilirubin, and MELD (p < 0.05). However, the correlation was generally weak except for AST, bilirubin, and MELD, where the spearman correlation coefficients (ρ) were usually > 0.35. Risk Analyses: Cochran-armitage trend test and Logistic regression analyses

analyses for BA concentrations/indices with ROC (AUC) > 0.8. Both logistic regression and cochran-armitage test detect if there is a risk of developing liver disease associated with changes in BA concentrations/indices. The risk of being diagnosed with a liver disease increased with changing levels of all BA concentrations/indices (p < 0.05) for both cochran-armitage trend test and logistic regression analysis. In addition, the odds ratio (OR) from logistic regression analysis quantifies the magnitude of the risk associated with certain changes (10%) in BA/BA indices. For example, for a 10 % increase in the % amidation of UDCA, the likelihood of having a liver disease increases 3.83 folds (Odds ratio (OR): 3.83; p 0.8 between controls and specific liver disease group.

The % amidation of

UDCA, %G-amidation of UDCA, % amidation of dihydroxy BA, and % amidated

 

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significantly higher in medium MELD than low MELD patients (1.3-3.2 fold).

to unsulfated BAs were higher (1.05-2 fold) in every disease group compared to controls. The % total DCA and % sulfated DCA to sulfated BA were lower (0.250.7 fold) in every liver disease group compared to controls. DISCUSSION Concentrations of all BAs were higher in the urine of patients with liver However, the increase in the absolute

concentrations of primary BAs was markedly higher (8.0-11.2 fold) compared to that of the secondary BAs (2.0-3.1 fold). As a result, the % of secondary BAs (LCA and DCA) in the overall BA pool decreased (~2 fold), while the % of primary BAs (CDCA and CA) increased (1.2 - 1.6 fold) in patients (Table 2). Patients are usually classified based on the severity their disease as estimated by the mayo model for end-stage liver disease (MELD) system. Patients with higher MELD score are considered to be at higher risk of developing severe hepatobiliary complications. MELD score is used to determine whether a person is eligibility for liver transplantation. MELD score was originally developed to predict the 90day survival rate of people with end-stage liver disease. These scores typically range between 6 and 40, and a score of 6 indicates the best likelihood of 90-day survival (Malinchoc et al., 2000; Kamath et al., 2001; Murray and Carithers, 2005). MELD score and compensation status are widely used in the clinic to assess the severity of liver diseases.

Remarkable increases in the absolute

levels and % of CDCA were observed with the increase in the severity of the liver disease (medium MELD > low MELD > controls), whereas the % of DCA decreased with the severity of the disease (controls > low MELD > medium  

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diseases compared to controls.

MELD) (Table 2). In addition, the % of secondary BAs (LCA and DCA) was lower while the % of primary BAs (CDCA and CA) was higher in decompensated compared to compensated patients.

The impaired bile flow to the intestine

during cholestatic diseases is expected to be associated with less conversion of primary BAs into secondary BAs by intestinal bacteria. Therefore, the decrease in the proportion of secondary bile acid with the severity of the disease may Similar results were observed in

previous studies, where a marked increase in the proportions of primary BAs and a decrease in the proportion of secondary BAs were observed in patients with cholestatic liver diseases (Trottier et al., 2011; Humbert et al., 2012; Trottier et al., 2012). The increase in the absolute concentration of taurine-amidated (T-BAs) (~11 fold) in patients was more profound than that of the glycine-amidated (GBAs) (8 fold) or the unamidated BAs (2.9 fold) (Table 2). Similarly, the increase in % taurine-amidation of BAs (1.3 fold) in patients was overall higher than that of % glycine-amidation of BAs (1.05 fold) (Supplementary Table 1). Amidation of BAs with glycine and taurine decreases their pKa, increases their solubility, enhances their urinary elimination, and decreases their toxicity (Heuman et al., 1991; Rolo et al., 2000; Hofmann and Hagey, 2008; Bathena et al., 2013). However, glycine-amidated BAs are generally more cytotoxic than the corresponding taurine-amidated BAs (Rust et al., 2000; Rust et al., 2005). Although the % amidation of BAs was not different between low and medium MELD groups, it was slightly higher in decompensated than compensated

 

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reflect the extent of bile flow impairment.

patients (~2%) (Table 2). This was primarily a result of changes in % taurineamidation (1.46 fold higher), whereas % taurine-amidation was generally not altered with severity of the liver disease (Supplementary table 1). Therefore, the marked accumulation of taurine-amidated BAs observed in the present study can be interpreted as an adaptive compensated response to enhance the elimination and detoxification of BAs. The increase in overall amidation of BAs in patients

completely amidated after their synthesis in the liver, but partial deamidation of BAs takes place in the intestine before they are reabsorbed into the systemic circulation (Mallory et al., 1973; Northfield and McColl, 1973). Therefore, it is expected that lower bile flow during cholestatic diseases may be associated with less deamidation in the intestine, which leads to higher amidated BAs in blood and urine. Overall, impairment of bile flow may be worsened in decompensated and/or patients with higher MELD scores, which results in both the increase in the % amidation of BAs and a decrease in the % of secondary BAs. Animal models with induced expression of Sult2a1 such as hyperactivePXR (Staudinger et al., 2001; Xie et al., 2001), hyperactive-CAR (Saini et al., 2004), and hyperactive-LXR (Uppal et al., 2007) are more resistant to liver toxicity resulting from BA accumulation.

This suggests that induction of BA

sulfation during liver diseases may serve as a compensatory pathway to detoxify and eliminate the accumulated BAs. Evidence exists to suggest that sulfation of BAs can be upregulated in patients with liver diseases as a compensatory mechanism to eliminate the accumulated toxic BAs (Makino et al., 1975; van

 

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may also be due to the impairment of bile flow to intestine. BAs are almost

Berge Henegouwen et al., 1976; Summerfield et al., 1977; Takikawa et al., 1984; Stiehl et al., 1985).

However, it is also possible that sulfation activity could

decrease in these patients due to the exhaustion or defects of such upregulation mechanisms. Therefore, it is possible that insults to the liver are handled by the upregulation of BA sulfation under normal conditions, but subjects who fail to upregulate this defensive mechanism are more likely to develop liver diseases.

sulfation of BAs between controls and patients in the current study. ROC analysis helps determine the potential use of a test as a diagnostic marker in the clinic. The higher the AUC value, the higher is the overall accuracy of a marker in discriminating between controls and patients. In general, AUC values of 0.6-0.7, 0.7-0.8, 0.8-0.9, and 0.9-1 are considered as poor, fair, good, and excellent markers, respectively (Pines and Everett, 2008).

Many BA

concentrations and indices demonstrated AUC >0.7 suggesting their utility as biomarkers for the diagnosis of liver diseases (Table 3). ROC curves are also used to determine cut-off values that quantify the normal ranges of biomarkers. The selection of optimum cut-off values is a tradeoff between selectivity and sensitivity, where higher cut-off values are associated with higher specificity but lower sensitivity, and vice versa. Three potential cut-off values for every one of the best BAs/BA indices were selected, which all achieved a good balance between sensitivity and specificity (Table 4). Logistic regression analysis and Cochran-armitage test help determine the increase in the risk of having a liver disease in association with a certain change  

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This could be the reason why significant differences were not observed in the %

in BA parameters. The unadjusted OR (univariate logistic regression) associated with a 10% change from the mean value for the absolute BA concentrations ranged from 1.06-1.09, whereas it was as high as 13.78 for BA indices (Table 5), suggesting that BA indices could be more useful markers than absolute BA concentrations in terms of predicting the risk of having a liver disease.

The

adjusted ORs for BA concentrations/indices from the mulvariate logistic

indicating that BA concentrations/indices could be independent predictors of liver diseases. Compared to non-BA indices, the BA concentrations and indices showed a higher magnitude of change in patients than controls. For example, non-BA indices were 1.2-2.9 fold higher in patients than controls (Table 6), whereas the fold change for BA parameters was as high as 11.2 (Total CDCA) in patients than controls (Table 2).

Furthermore, even though most non BA-parameters

were significantly different within the MELD groups, the fold difference within these groups was in the range of 0.6-3.2 (Table 6). In contrast, the fold changes for BA concentrations/indices was as high as 6.2- fold and 3.2- fold higher in medium compared to mild MELD groups with unsulfated CDCA and total CDCA, respectively (Table 6 and Supplementary Table 1). Similarly, the magnitude of change was as high as 6.1 fold (unsulfated CDCA) for BA concentrations/indices in decompensated than compensated patients, whereas the fold change for nonBA indices were 0.8-2.4 fold higher (Table 6 and Supplementary Table 1).

 

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regression analysis were similar to the unadjusted OR from univariate analysis

In comparison to non-BA parameters, BA concentrations and indices demonstrated higher ROC (AUC), suggesting they could be more accurate diagnostic markers of liver disease.

Only AST, ALT, and bilirubin had ROC

(AUC) > 0.8, whereas 11 of the BA indices had AUC > 0.8 and one > 0.9. Previous studies reported the AUC of AST and ALT in the range of 0.64-0.72 and 0.58-0.793 (Feldstein et al., 2009; Franzini et al., 2012).

Most notably, BA

compared to non-BA parameters as determined by the logistic regression and Cochran-armitage analyses. For example, a 10% increase from the mean values of BA parameters was associated with as high as a 13.8 fold increase in the risk of having a liver disease (Table 5), whereas the same change in non-BA parameters was associated with only as high as a 1.8 fold increase in the same risk (Supplementary Table 3). The risk of developing liver diseases associated with changes in BA parameters was independent of other covariates including AST, ALT, bilirubin, INR, protime, serum creatinine, albumin, and MELD score. This is a preliminary study performed in order to identify the potential usefulness of BAs and BA indices as diagnostic markers of liver disease in clinic, in general, and identify signature differences between “normal” and “abnormal” urinary BA profiles. The limitations of the current study include: (i) We have relatively small number of subjects in most individual disease groups, (ii) unbalanced distribution of subjects between disease groups, (iii) there is overlap in disease diagnosis where the same patients can belong to different disease groups, (iv) patients in the same disease group can be further divided into

 

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parameters were better associated with the risk of having a liver disease

subgroups based on multiple factors such as the MELD score, disease history, co-existing diseases, etc. Therefore, eventhough the study has enough power to make conclusions about qualitative and quantitative disturbances of the BA profile in patients with hepatobiliary idiseases, conclusions about comparisons between different disease groups can not be made at this stage. However, as recruitment continues in this study, we will be able to address this issue.

individual disease groups were significantly different between control group and every liver disease group. In summary, this pilot study demonstrated the advantages of novel “BA indices” as diagnostic and prognostic biomarkers of hepatobiliary diseases over currently used liver enzymes and proteins. The magnitude of changes in BA indices associated with liver diseases was higher than that of liver enzymes. The % of secondary BAs (LCA and DCA) decreased while the % of primary BAs increased (CDCA and CA) in patients.

In addition the % of secondary BAs

decreased while the % of primary BAs increased with the severity of the disease as measured by MELD score and compensation status. The % amidation of BAs also increased with disease severity. These changes collectively, may indicate the extent of impairment of bile flow, which may be worsened in decompensated and/or patients with higher MELD scores.

BA indices demonstrated high

specificity and selectivity as biomarkers for liver diseases as demonstrated by ROC analyses, which resulted in AUCs as high as 0.9.

Finally, logistic

regression analysis suggested that changes in BA indices were associated with

 

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Preliminary analysis to compare the urinary BA profile between normal and

marked increase in the risk of having a liver disease. Overall, these results indicate that several BA indices have the potential to perform as well as the existing non-BA parameters in the diagnosis and prognosis of liver disease. Identification of the “best” BA prognostic and diagnostic biomarker(s) should take into account the various statistical and biological criteria.

Importantly, larger

scale studies are required to identify and validate such biomarkers in specific

FUNDING INFORMATION This clinical study was supported by University of Nebraska Medical CenterClinical Research Center (CRC) and Great Plains Health Research Consortium (GPHRC). ACKNOWLEDGEMENT The authors wish to thank the CRC nurses (Claire Haire, Mary Phillips, Carolyn Peterson, Mary Ann Martin, and Cindy Cowardin) and staff for their valuable contributions in managing the healthy controls arm of the study, recruiting subjects, and collecting samples.

References

Alnouti, Y. (2009). Bile Acid sulfation: a pathway of bile acid elimination and detoxification. Toxicol. Sci. 108, 225-246.  

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disease groups. Such studies are currently undergoing in our laboratory.

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Figure legends Fig.1 Receiver operating characteristics (ROC) curves of representative urinary absolute concentrations and BA indices; the area under the ROC curve for BA indices and concentrations for differentiating the patients from healthy subjects is shown. Downloaded from http://toxsci.oxfordjournals.org/ at University of Chicago on November 16, 2014

 

32

Table 1. Absolute Concentrations of major BAs in controls’ and patients’ urine Controls Unamidated (nM)

G-BAs (nM)

T-BAs (nM)

Total (nM)

Unsulfated BAs CA

69.8 ± 5.5

9.78 ± 0.8

273.8 ± 34.4

137.0 ± 13.9

-

-

137.0 ± 13.9

MCA

26.3 ± 2.2

-

37.3 ± 2.9

63.6 ± 3.8

MDCA

45.3 ± 2.9

-

-

45.3 ± 2.9

UDCA

3.46 ± 0.25

35.4 ± 3.8

2.15 ± 0.13

41.0 ± 3.9

DCA

20.1 ± 1.2

10.7 ± 0.6

1.88 ± 0.1

32.8 ± 1.2

HCA

9.19 ± 1.72

16.8 ± 1.1

1.45 ± 0.09

27.4 ± 1.7

CDCA

3.52 ± 0.25

7.73 ± 0.54

1.81 ± 0.29

13.1 ± 0.8

HDCA

5.73 ± 0.70

ND

ND

5.73 ± 0.70

LCA

0.15 ± 0.02

0.36 ± 0.03

0.32 ± 0.03

0.83 ± 0.07

Total

445 ± 41.2

140.8 ± 9.7

54.6 ± 3.7

640.5 ± 49.2

Atypical BAs

Downloaded from http://toxsci.oxfordjournals.org/ at University of Chicago on November 16, 2014

194.2 ± 30.2 *

Sulfated BAs DCA-S

2.42 ± 0.09

2991.1 ± 151.5

221.2 ± 17.4

3214.8 ± 165.5

CDCA-S

73.5 ± 5.8

2399.9 ± 126.2

57.3 ± 2.7

2530.7 ± 128.5

UDCA-S

459.3 ± 24.5

1116.3 ± 56.3

26.2 ± 1.5

1601.9 ± 73.2

LCA-S

7.19 ± 0.63

808.2 ± 46.1

222.9 ± 12.5

1038.3 ± 56.5

CA-S

4.32 ± 0.21

53.1 ± 2.5

141.5 ± 7.0

198.8 ± 8.1

Total

546.8 ± 28.0

7368.6 ± 285.0

669.1 ± 32.7

8584.5 ± 320.7

Overall Total

991.8 ± 54.2

7509.5 ± 285.0

723.7 ± 34.6

9225.0 ± 331.3

243.5 ± 72.8

1142.2 ± 166.7

Patients Unsulfated BAs CA

247.0 ± 45.6

UDCA

98.6 ± 71.5

676.9 ± 492.3

22.9 ± 13.7

798.4 ± 577.2

MCA

48.0 ± 10.4

-

504.2 ± 88.6

552.2 ± 93.6

HCA

1.53 ± 0.24

182.7 ± 42.4

78.5 ± 29.4

262.7 ± 65.4

22.9 ± 10.0

124.9 ± 26.1

103.8 ± 30.0

251.6 ± 57.3

CDCA Atypical BAs

*

651.7 ± 92.6

212.7 ± 30.4

-

-

212.7 ± 30.4

DCA

36.9 ± 8.4

40.8 ± 8.3

6.92 ± 1.25

84.6 ± 16.3

MDCA

67.5 ± 13.3

-

-

67.5 ± 13.3

HDCA

13.4 ± 4.0

ND

ND

13.4 ± 4.0

LCA

4.80 ± 2.13

0.68 ± 0.28

0.30 ± 0.23

5.77 ± 2.4

Total

753.4 ± 124.3

1677.6 ± 555.1

960.0 ± 168.1

3391.0 ± 747.8

CDCA-S

229.0 ± 72.7

25494.9 ± 3722.1

2598.6 ± 839.5

28322.5 ± 4290.9

UDCA-S

1855.4 ± 612.0

23480.0 ± 6439.8

1797.2 ± 722.2

27132.5 ± 7493.3

DCA-S

1.11 ± 0.23

6011.2 ± 1462.1

569.5 ± 117.8

6581.8 ± 1527.8

LCA-S

41.4 ± 14.6

2463.9 ± 462.6

748.9 ± 117.4

3254.2 ± 559.9

CA-S

25.7 ± 4.3

1262.4 ± 309.4

1376.7 ± 340.0

2664.8 ± 592.4

Total

2152.7 ± 629.5

58712.3 ± 9810.4

7090.7 ± 1602.0

67955.8 ± 11359.3

Sulfated BAs

Overall Total 2906.1 ± 734.6 60389.9 ± 10217.3 8050.8 ± 1734.7 71346.8 ± 11952.8 Atypical BAs include isoDCA, isoLCA, norDCA, 3-dehydroCA, 12-oxoCDCA, 7-oxoLCA, and 12-oxoLCA; ND: not detected; - not quantified *

 

33

Table 2. Representative BA concentrations and indices in controls, overall, low MELD, medium MELD, compensated, and decompensated patients

BAs/BA indices

Controls

Patients

Mean

SEM

Mean

Total BA

9225.0

331.3

71346.8

Unsulfated BA

640.5

49.2

3391.0

8584.5

320.7

*

67955.8

*

Total LCA

1039.1

56.5

3260.0

Total UDCA

1642.9

74.5

27931.0

Total CDCA

2543.7

129.0

28574.1

Total DCA

3247.6

166.0

472.7

36.3

3806.9

89.1%

0.5%

88.6%

%Sulfation UDCA

97.0%

0.1% 0.2%

*

99.5%

*

97.9%

%Sulfation CDCA

99.4%

0.0%

99.1%

%Sulfation DCA

98.4%

0.1%

97.4%

%Sulfation CA

55.1%

1.3%

60.8%

* *

4057.8

1406.4

5389.4

11359.3

78790.4

19831.2



124385.7



SEM

Mean

SEM

Mean

36009.2

62240.9

13664.7

96957.1

1139.1

3063.4

969.7

4312.4

35160.1

59177.5

12849.8

#

92644.8

#

24352.2 831.4 23735.2

560.9

3429.6

833.6

8363.0

3158.4

2761.9

470.3

4660.7

1677.5

7951.2

39267.6

14568.6

19874.4

8466.8

31493.6

10589.3

17911.0

5595.5

4330.6

26984.3

6150.2

85300.2

22662.4

18525.2

3391.8

56836.4

1541.8

7316.0

2853.0



9045.5

2589.5

5145.4

635.3

10944.4

# #

#

12711.9 5597.2

736.5

4555.5

1349.3

5684.1

1182.4

3314.4

910.3

5192.1

0.7%

87.2%

1.4%

91.5%

1.5%

88.2%

0.8%

89.8%

1.3%

0.2%

99.6%

0.3%

99.0%

0.8%

99.5%

0.2%

99.5%

0.4%

0.3%

97.7%

0.5%

98.5%

0.2%

98.1%

0.4%

#

97.4%

#

1143.7

0.6%

0.1%

99.1%

0.2%

99.0%

0.2%

99.3%

0.1%

98.7%

0.2%

0.3%

97.2%

0.6%

97.4%

0.5%

97.5%

0.4%

97.3%

0.6%

1.5%

63.1%

2.0%

54.1%

4.3%

61.8%

1.8%

57.8%

2.7%

#

96.1%

98.1%

0.4%

98.8%

0.2%

97.3%

1.0%

98.0%

0.5%

98.4%

0.4%

0.5%

90.3%

0.6%

91.0%

1.7%

88.9%

0.6%

90.9%

1.0%

0.3%

98.3%

0.2%

98.6%

0.3%

99.1%

0.4%

98.0%

0.3%

99.2%

%Amidation CDCA

95.5%

0.1%

* * *

98.6%

*

%Amidation CA

71.6%

1.3%

86.1%

%Total LCA

11.8%

0.4%

6.3%

0.5% 0.7%

*

24.4% *

43.8%

*

%Total DCA

32.3%

0.8%

15.3%

%Total CA

5.8%

0.3%

7.2%

*

0.3%

98.4%

1.4% 0.4% 1.6% 1.6%

0.4%

96.2%

0.5%

98.8%

87.9%

1.5%

5.7%

0.5%

26.5% 39.8%

2.5% 2.2%

1.6%

93.8%

84.9%

1.7%

89.5%

2.3%

7.0%

0.5%

4.2%

5.1%

5.9%

1.2%

64.0%

3.4%

0.2% 0.3%

85.9%

2.1%

#

98.9%

98.5%



#

0.8%

0.3%

0.4%

12.3%

0.5%

27.7% 37.7%

2.0% 1.6%

# #

14.9%

#

61.2%

#

0.6% 2.2% 2.8%

1.0%

13.4%

1.2%

6.5%

1.4%

17.9%

1.2%

8.2%

1.7%

0.4%

7.0%

0.6%

6.9%

1.4%

6.6%

0.4%

8.8%

1.1%

*

significant difference between controls and patients (p

Urinary bile acids as biomarkers for liver diseases II. Signature profiles in patients.

Hepatobiliary diseases result in the accumulation of bile acids (BAs) in the liver, systemic blood, and other tissues leading to an unfavorable progno...
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