Exploring Serum Bile Acids as Potential Noninvasive Biomarkers for Nonalcoholic Fatty Liver Disease

doi:10.21203/rs.3.rs-4896620/v1

Background: Bile acids are vital regulators of liver metabolism, and their dysregulation is closely linked with the progression of nonalcoholic fatty liver disease (NAFLD). Profiling these bile acids may provide valuable diagnostic and prognostic markers for these conditions. This study aimed to evaluate bile acid profiles in NAFLD patients and assess their potential as biomarkers for diagnosing and predicting disease progression. Serum levels of 14 bile acids were measured in 25 normal healthy controls (NHC), 35patients with nonalcoholic steatosis (NAST), and 40 patients with NASH, categorized by the NAFLD Activity Score (NAS). Quantification was performed using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS).

Results: Primary unconjugated bile acids, CA and CDCA, along with conjugated acids GCA, GCDCA, TCA, and TCDCA, were significantly elevated in both NAST and NASH compared to NHC (all p < 0.05). While levels increased progressively from NHC to NAST to NASH, no significant differences were observed between NAST and NASH except for GCA and TCA (P< 0.05). Similarly, secondary bile acids LCA, TLCA, GUDCA, and TUDCA were higher in NAST and NASH compared to NHC (all p < 0.05).

Logistic regression identified CA (odds ratio = 2.05, p = 0.02), CDCA (odds ratio = 1.58, p = 0.04), GCA (odds ratio = 1.92, p = 0.03) and DCA (odds ratio = 2.06, p = 0.04) as significant predictors of fibrosis. For active inflammation, GCA (odds ratio = 2.04, p = 0.04), and TCA (odds ratio = 1.94, p = 0.04) were significant predictors. In steatosis, CA, CDCA, GCA, DCA, TDCA, TLCA, and UDCA were notable predictors, with high odds ratios.

Conclusion: The study highlights significant alterations in bile acid profiles associated with NAFLD progression. Specific bile acids, such as CA, GCA, TCA, and TCDCA are strong predictors of disease severity, indicating their potential as biomarkers for NAFLD treatment and prognosis.

Bile acids

NAFLD

Nonalcoholic fatty liver disease

NASH

Nonalcoholic steatohepatitis

Liquid chromatography-mass spectrometry

Nonalcoholic fatty liver disease (NAFLD) includes a spectrum of liver disorders, ranging from simple steatosis to nonalcoholic steatohepatitis (NASH). The mildest form, nonalcoholic fatty liver (NAFL), is characterized by lipid accumulation in hepatocytes, also known as hepatic steatosis. However, 20%–30% of NAFL cases may progress to NASH, marked by significant lobular inflammation and hepatocyte ballooning, potentially leading to fibrosis and cirrhosis[1]. NAFLD has emerged as the leading cause of chronic liver disease worldwide, with a prevalence estimated at 25% [2-4]. NASH, a severe form of NAFLD, affects about 1.5% to 6.45% of the population and can lead to serious complications such as cirrhosis, hepatocellular carcinoma, and liver-related mortality. The prevalence of NASH is projected to increase by 63% between 2015 and 2030, posing significant challenges to global healthcare [4-6].

The pathogenesis of NASH is complex and involves multiple mechanisms, including abnormal lipid accumulation and inflammation within hepatocytes or extrahepatic tissues, leading to hepatotoxic injuries[7]. NAFLD is strongly associated with metabolic dysfunctions, such as insulin resistance, obesity, and type 2 diabetes, particularly in Western populations. To better describe the metabolic basis of NAFLD, the term metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed [8, 9].

Bile acids are increasingly recognized as critical signaling molecules in NASH pathogenesis, facilitating communication between the liver, intestine, and other organs. These molecules, synthesized from cholesterol in the liver, play a vital role in emulsifying fats and in the digestion and absorption of lipids and fat-soluble vitamins. Primary bile acids, such as cholic acid and chenodeoxycholic acid, are transformed by intestinal bacteria into secondary bile acids, including lithocholic acid and deoxycholic acid[10, 11]. Besides their traditional roles, bile acids act as signaling molecules that regulate metabolic homeostasis and immune responses, primarily through receptors such as FXR and G protein-coupled bile acid receptor 1 (TGR5)[12]. Dysregulation of bile acid homeostasis is implicated in several metabolic diseases, including NASH, making bile acids and their receptors potential therapeutic targets [12, 13].

Despite advances in understanding NAFLD, predicting which patients are at risk for disease progression and complications remains challenging [14]. Liver biopsy is the gold standard for assessing inflammation and fibrosis in NAFLD but is invasive and carries risks such as bleeding and infection. Efforts to identify noninvasive biomarkers, particularly for inflammation and fibrosis, have produced mixed results, limiting their clinical utility [15-17]. Bile acids have emerged as promising biomarkers due to their roles in lipid absorption and regulation of hepatic glucose and lipid metabolism. High serum insulin levels can inhibit bile acid synthesis by suppressing CYP7A1, a key enzyme in bile acid biosynthesis, while elevated bile acids can reduce insulin secretion via glucagon-like peptide 1. This complex interplay highlights the connections between NAFLD, metabolic syndrome, and gut health[18-21].

The aim of this study is to comprehensively evaluate bile acid profiles as noninvasive biomarkers in NAFLD, with the goal of establishing these profiles as reliable diagnostic tools for assessing liver disease severity and predicting progression to NASH.

The study was conducted at the Department of Clinical Biochemistry and Molecular Diagnostics and the Department of Hepatobiliary and Gastroenterology from October 2022 to August 2024. The cohort included 75 biopsy-proven NAFLD patients, and a corresponding control group of 25 individuals, free from any liver impairment. The study received approval from the Ethics Committee of the National Liver Institute (IRB 00570/2024), and written consent was obtained from all participants. NAFLD diagnosis was established through abdominal ultrasound and liver biopsy but healthy controls were not subjected to liver biopsies[5]. The liver biopsy specimens were histologically assessed for steatosis, inflammation, and fibrosis according to the criteria established by the NAFLD Clinical Research Network [22].

The findings are illustrated in Figure 1. Patients with NAFLD were divided into two subgroups based on specific histological criteria into nonalcoholic steatosis (NAST, n=35) and nonalcoholic steatohepatitis (NASH, n=40). NAST patients included those with minimal or no fibrosis (F0-F1), no evidence of inflammation (A0-A1), but with varying degrees of steatosis; G0 (<5%,), G1 (up to 33%,), G2 (33% to 66%,), and G3 (>66%) of hepatocytes. NASH patients, besides having evidence of steatosis and or fibrosis, also showed evidence of inflammation greater than grade ≥ A2 The NAS was used to evaluate the severity of liver disease, ranging from 0 to 8. This score is calculated by summing the scores of steatoses (0-3), lobular inflammation (0-3), and hepatocyte ballooning (0-2). A NAS score of ≥ 5 strongly indicated NASH, while a score of ≤ 3 was associated with NAST [22].

Exclusion criteria encompassed patients with viral or autoimmune liver diseases, hepatotoxic drug use, iron overload, Wilson's disease, chronic cholestasis, and extrahepatic obstructive gall bladder diseases. Additionally, individuals presenting with liver diseases associated with severe renal or systemic conditions were excluded from the study.

Serum Sample Collection and Bile Acid Measurement: Blood samples were obtained from both patients and controls following an overnight fast (8-12h). Three milliliters of blood were collected using sterile venipuncture techniques, and the extracted serum was stored at -80°C until analysis. Laboratory measurements, encompassing fasting blood glucose, HbA1c, lipid profile including total cholesterol, high density lipoprotein (HDL)-cholesterol, low density lipoprotein (LDL)-cholesterol, triglycerides; liver function tests AST, ALT, gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), direct and total bilirubin, albumin, and total proteins, AFP; kidney function tests as BUN, creatinine were conducted through standardized laboratory methods (Cobas 8000, Roche Diagnostics GmbH, Mannheim, Germany). Serum bile acids concentrations were measured in serum using high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS), employing a reversed-phase (C18) column (1.7 µm, 100 mm × 2.1 mm internal dimensions) (Waters ACQUITY, Milford, MA) and a methanol/water gradient. The assay included a total of 14 bile acids, categorized into six primary and eight secondary bile acids. The primary bile acids consisted of unconjugated forms, including CA (cholic acid) and CDCA (chenodeoxycholic acid), and conjugated forms, including GCA (glycocholic acid), GCDCA (glycochenodeoxycholic acid), TCA (taurocholic acid), and TCDCA (taurochenodeoxycholic acid). The secondary bile acids included unconjugated forms, including DCA (deoxycholic acid) and LCA (lithocholic acid), and conjugated forms, including GDCA (glycodeoxycholic acid), TDCA (taurodeoxycholic acid), TLCA (taurolithocholic acid), UDCA (ursodeoxycholic acid), GUDCA (glycoursodeoxycholic acid), and TUDCA (tauroursodeoxycholic acid).

Serum Sample Preparation and Bile Acid Detection: Serum bile acids underwent preparation for UPLC/MS/MS as previously described [13, 14]. Briefly, 100 µl of serum samples were treated with 400 µl of ice-cold 100% methanol, followed by centrifugation at 12,000 rpm for 20 min. Fifty microliters of the supernatant were mixed with 100 µl formic acid (1:1000), and 5 µl were injected into a C18 column at 50°C. Bile acids were eluted by gradient at a flow rate of 0.5 ml/min, with the mass spectrometer operating in the negative ion mode via Multiple Reactions Monitoring (MRM). UPLC-MS data were analyzed using MassLynx software version 4.1 (Waters Corp., Milford, MA, USA) to generate calibration equations and calculate the quantitative concentration of each bile acid in the sample. The UPLC-MS/MS analysis demonstrated robust performance including precision and accuracy at concentrations of 0.02 µMol/L, 0.2 µMol/L, and 2 µMol/L, exhibiting low relative standard deviation (RSD%) values for excellent precision. Relative error (RE%) values approximating 100% underscored the accuracy of quantitation. All the individual 14 bile acids were effectively resolved and quantified. The assay's linearity extended from 0.012 to 5x10³ µMol/L for all bile acids, emphasizing its suitability across a wide concentration range. With a lower quantitation limit of 2 ng/mL, the UPLC-MS/MS assay demonstrated sensitivity, making it reliable for quantitative assessments in biomedical research.

Statistical analysis

Data were analyzed using SPSS 23 (SPSS Inc., CA, USA). The Kolmogorov-Smirnov test was employed to verify the normality of distribution. Numerical variables were presented as mean ± standard deviation or as medians and interquartile ranges (IQR), while categorical variables were expressed as numbers (percentages). Differences between groups were analyzed using the Kruskal-Wallis H test and the Mann-Whitney U test as appropriate. A P-value of < 0.05 was considered statistically significant for all analyses. Non-parametric Spearman correlation was used to assess the relationships between bile acids and other numerical variables, such as lipid profiles and blood chemistry parameters. Principal Component Analysis (PCA) was conducted to explore patterns in bile acid concentrations among the study cohort, which included individuals with NAFLD and control subjects. The receiver operating characteristic (ROC) curve was used to evaluate the discriminatory power of bile acids in distinguishing controls from NAFLD cases. Binary logistic regression was applied to assess the predictive value of bile acids for fibrosis, lobular inflammation, and steatosis in NAFLD patients.

Demographic and Clinical Characteristics in Normal and NAFLD Groups

The data presented in Table 1 summarize the clinical characteristics of the study population, divided into three groups: Control, NASH, and NAST. NASH and NAST groups had a significantly higher proportion of hyperlipidemic patients compared to the control group (χ² = 14.23, p = 0.001). The NASH and NAST groups demonstrated higher mean body mass index (BMI) values compared to the control group (p < 0.001), indicating a greater prevalence of obesity among patients with NASH and NAST. Furthermore, the presence of diabetes mellitus was more common in the NASH and NAST groups, with a higher percentage of patients being diagnosed with DM (χ² = 5.42, p = 0.067).

Age differences across the groups were not statistically significant (t = 1.02, p = 0.313), suggesting that age is not a primary differentiating factor in the progression of NAFLD. Similarly, gender distribution did not differ significantly between the groups (χ² = 0.73, p = 0.695).

Hypertension prevalence was assessed across the groups, but no significant differences were observed (χ² = 1.44, p = 0.487). However, the trend indicated a higher occurrence of hypertension in the NASH group compared to the control and NAST groups.

There were significant differences in fibrosis and inflammation activity scores between the groups, with NASH patients having more advanced fibrosis (F2-F3) and higher activity (A2-A3) compared to the control group (p < 0.001). The distribution of steatosis grades and ultrasound findings also differed significantly among the groups, with the NASH and NAST groups showing more severe liver changes. These results highlight the progressive nature of liver disease in NAFLD and underscore the importance of early diagnosis and management.

Biochemical and Hematological Parameters Across Control, NASH, and NAST Groups

Table 2 details the biochemical and hematological parameters, showing significantly higher median FBS levels in NASH and NAST groups, indicating a tendency towards hyperglycemia. Direct bilirubin and GGT levels were elevated in NASH and NAST groups, suggesting liver dysfunction. Lipid profile analysis revealed higher total cholesterol levels in NASH and NAST groups, reflecting dyslipidemia. Hematological markers such as hemoglobin and platelet count remained stable across groups.

Alterations in Bile Acid Across NAFLD Groups

Table 3 summarizes the bile acid profiles among NHC, NAST, and nonalcoholic steatohepatitis (NASH). Primary unconjugated bile acids, CA and CDCA, were significantly elevated in both NAST and NASH compared to NHC (all p < 0.05), with no significant differences between NAST and NASH (all p > 0.05). Similarly, primary conjugated bile acids, including GCA, GCDCA, TCA, and TCDCA, were significantly higher in NASH and NAST compared to NHC (all p < 0.05). GCA and TCA levels were notably higher in NASH compared to NAST (all p < 0.05), whereas GCDCA and TCDCA did not differ significantly between NAST and NASH (all p > 0.05).

Secondary bile acids, LCA, TLCA, GUDCA, and TUDCA, were significantly elevated in NASH and NAST compared to NHC (all p < 0.05), with no significant differences between NAST and NASH (all p > 0.05). DCA, GDCA, TDCA, and UDCA did not show significant differences between either NAST or NASH and NHC (all p > 0.05).

Bile Acids in Discriminating NAFLD Patients and Control

ROC curves (Figure2) and Principal Component Analysis (PCA) (Figure3) were used to examine the capacity of bile acids in discriminating healthy from NAFLD subgroups NAST and NAST. Figure 2a-b summarize the ROC curve analysis for primary and secondary bile acids in differentiating healthy controls from NAFLD patients (NAST+NASH). The primary unconjugated bile acid CDCA showed high diagnostic potential with an AUC of 0.937, 100% specificity, and 74.7% sensitivity at a cutoff of 0.002. The primary conjugated bile acid GCDCA achieved an AUC of 0.877, 100% specificity, and 80% sensitivity at a cutoff of 2.48.

The secondary bile acids collectively demonstrated moderate diagnostic performance. LCA had an AUC of 0.864, with 96% specificity and 74.7% sensitivity at a cutoff of 0.002, while TLCA had an AUC of 0.840, with 12% specificity and 80% sensitivity at a cutoff of 0.002. Other secondary bile acids, including TUDCA and GDCA, displayed varying degrees of diagnostic accuracy, with AUCs ranging from 0.784 to 0.420, reflecting different levels of specificity and sensitivity.

Overall, primary bile acids exhibited superior diagnostic accuracy compared to secondary bile acids, underscoring their potential utility as biomarkers for distinguishing NAFLD patients from healthy controls. In the subsequent analysis comparing NAST and NASH, the ROC curves for both primary and secondary bile acids showed limited diagnostic utility, with AUC values generally indicating weak discrimination. Primary bile acids like CDCA and CA had AUCs of 0.596 and 0.575, respectively, demonstrating moderate accuracy. Sensitivity and specificity were inconsistent, with significant variability. Secondary bile acids exhibited similarly low AUC values, ranging from 0.466 for LCA to 0.571 for TLCA, indicating limited differentiation between the conditions (Figure 2c-d). These findings, suggest that the bile acids assessed are not robust biomarkers for distinguishing NAST from NASH. PCA of these bile acids across the studied groups. PCA demonstrated that the first two principal components (PC1 and PC2) accounted for 55.82% of the total variance, with eigenvalues of 5.27 and 2.54, respectively. Key bile acids, including GCDCA, CA, and CDCA, emerged as significant contributors, underscoring their potential as biomarkers for differentiating NAFLD from the control group (Figure 3).

Impact of Gender, Diabetes Status, and Lipid Profile on Bile Acid Levels in NAST and NASH Patients

Table 4 presents the analysis of bile acid levels in NAFLD (NAST and NASH) patients across gender, diabetes status, and lipid profile, highlighting several key differences. Significant differences were observed in TDCA and TUDCA levels between genders, with females showing higher levels (p = 0.033 and p = 0.037, respectively). For diabetes status, CA, CDCA, GCA, and TCDCA levels were significantly different, with the highest levels found in the DM group (p < 0.05 for all). Hyperlipidemic patients exhibit higher significant differences in bile acids CA, LCA, GCA and GUDCA than normolipidemic with p < 0.05 for all these bile acids, suggesting that lipid profile substantially impact bile acid metabolism in NAFLD. Further correlation analysis between bile acids and lipid profile in NAST and NASH revealed several significant associations between some bile acids and lipid profile parameters (Table5).

In the NAST group, CA and CDCA had strong negative correlations with LDL (CA: r=-0.57**, p<0.01; CDCA: r=-0.53**, p<0.01) and positive correlations with HDL (CA: r=0.57**, p<0.01; CDCA: r=0.56**, p<0.01). LCA and GDCA were also negatively correlated with LDL (LCA: r=-0.69**, p<0.01; GDCA: r=-0.41*, p<0.05) and positively correlated with HDL (LCA: r=0.70**, p<0.01); GDCA: r= 0.39*, p<0.05). Conversely, other bile acids did not show significant correlations with lipid components.

In the NASH group, unconjugated bile acids, CA was positively correlated with HDL (CA: r=0.42**, p<0.01) and negatively correlated with LDL (CA: r=-0.31*, p<0.05). Primary conjugated bile acids GCA, GCDCA and TCDCA were positively correlated with cholesterol (GCA: r=0.49**, p<0.01; GCDCA: r=0.38*, p<0.05; TCDCA: r=0.31*, p<0.05). Secondary bile acids, GDCA, and GDUCA were positively correlated with cholesterol (GDCA: r=0.39*, p<0.01; GDUCA: r=0.38*, p<0.05) and HDL (GDCA: r=0.46**, p<0.01; GUDCA: r=0.50**, p<0.01) and negatively correlated with LDL (GDCA: r=-0.44**, p<0.01; GDUCA: r=-0.41*, p<0.05). TUDCA positively correlated with cholesterol (r=0.37*, p<0.05) and HDL (r= 0.38*, p<0.05). Other bile acids did not show significant correlations with any lipid components.

Bile Acid Levels Across Fibrosis, Inflammation, and Steatosis Grades in NAFLD Patients

Table 6 presents a detailed comparison of bile acid levels across various stages of fibrosis, inflammation, and steatosis in patients with either NAST or NASH.

In the context of fibrosis: CA, CDCA and GCA levels were significantly higher in the F2-F3 group compared to the F0-F1 group (all p < 0.05). No significant differences were found for, in the primary conjugated GCDCA, TCA, TCDCA, and all the secondaries uncogitated and conjugated bile acid DCA, LCA, GDCA, TDCA, TLCA, UDCA, GUDCA, and TUDCA (all p > 0.05).

In the context of inflammation GCA, TCA and TLCA levels were significantly higher in the A2-A3 group compared to A0-A1 (p < 0.05). In contrast, LCA levels were notably higher in A0-A1 compared to A2-A3 but did not reach the level of significant (p > 0.05). No significant differences were found for CDCA, GCDCA, TCDCA, DCA, GDCA, TDCA, UDCA, GUDCA, and TUDCA (all p > 0.05).

In the context of steatosis, CA, GCA, TCA, TCDCA, and TLCA levels were significantly elevated in the G2-G3 group compared to G0-G1 (CA: p = 0.003; GCA: p = 0.032). DCA levels were significantly higher in G0-G1 compared to G2-G3 (p < 0.05). No significant differences were observed for CDCA, GCDCA, LCA, GDCA, TDCA, UDCA, GUDCA, and TUDCA (all p > 0.05).

Predictive Value of Bile Acids for Fibrosis, Inflammation, and Steatosis in NAFLD: Logistic Regression Analysis

Table 7 reveals the logistic regression analysis results for bile acids as predictors of fibrosis, active inflammation, and steatosis in NAFLD patients (NAST and NASH). For fibrosis the analysis identified several bile acids with significant associations with fibrosis, CA, CDCA and DCA were notable predictors, with CA showing an odds ratio of 2.05 (p = 0.02); CDCA had an odds ratio of (Exp(B) = 1.58, p = 0.04) and DCA an odds ratio of 2.06 (p = 0.04).

In terms of active inflammation, GCA was a significant predictor (Exp(B) = 1.92, p = 0.03), along with TCA (Exp(B) = 1.94, p = 0.02, and TLCA (Exp(B) = 15.95, p = 0.03). CDCA did not show a significant association with inflammation (Exp(B) = 0.49, p = 0.66).

In the context of steatosis, 1ry bile acids CA, CDCA, and GCA, were significant predictors (CA: Exp(B) = 2.62, p = 0.048; CDCA: Exp(B) = 1.25, p = 0.017; GCA: Exp(B) = 2.92, p = 0.041. Additionally,2ry Bile acid, DCA, TDCA, TLCA, UDCA showed a significant association and predictor of steatosis DCA: Exp(B) = 3.24, p = 0.042; TDCA: Exp(B) = 4.35, p = 0.04; TLCA: Exp(B) = 20, p = 0.03); and UDCA (Exp(B) = 20, p = 0.02).

These results highlight the role of specific bile acids, such as CA, CDCA and GCA, in predicting NAFLD severity, with implications for both fibrosis and steatosis. The significant associations of DCA, TDCA, and TLCA with steatosis suggest their potential importance in hepatic fat accumulation. Additionally, the significant correlations of GCA, TCA, and TLCA with inflammation suggest their potential utility in predicting liver inflammation activity.

This study provides a comprehensive analysis of bile acid profiles across the spectrum of NAFLD, from simple NAST to the more advanced hepatic inflammation in nonalcoholic steatohepatitis (NASH) and fibrosis. The findings underscore the critical role of bile acids as potential biomarkers in the progression of NAFLD, offering insights into the metabolic disturbances underlying the disease. Significant differences in clinical parameters, such as BMI, gender, and the prevalence of dyslipidemia and diabetes mellitus, were observed between the NASH and NAST groups compared to the NHC group. These differences align with existing literature that links metabolic disturbances, including obesity, dyslipidemia, and diabetes mellitus, to the severity of NAFLD, further emphasizing the role of these factors in NAFLD progression [3, 5].

The main finding of the current study is that bile acid profiles are significantly altered in NAFLD compared to healthy controls, with specific bile acids potentially serving as biomarkers for distinguishing between healthy individuals and NAFLD patients. Additionally, these bile acids may have predictive value for the progression of the disease, particularly in relation to fibrosis, inflammation, and steatosis.

Both primary unconjugated and conjugated bile acids were significantly elevated in NAST and NASH compared to healthy controls, with a particular increase in CA, CDCA, GCA, and TCA levels. The minimal differences between NAST and NASH in many bile acids suggest that these metabolic alterations may occur early in the disease process and persist as NAFLD progresses. These results are in line with previous research indicating that bile acid metabolism is disrupted in NAFLD, likely due to impaired hepatic bile acid synthesis and secretion, as well as altered gut microbiota[23-27].

Secondary bile acids also showed significant changes across NAFLD groups. Elevated levels of secondary bile acids such as LCA, TLCA, GUDCA, and TUDCA were observed in both NASH and NAST compared to NHC, reflecting the disruption in bile acid metabolism. However, no significant differences were found between NAST and NASH, indicating that secondary bile acids might not provide robust differentiation between these subtypes. These findings align with Cassey et al., who reported higher total primary bile acids and lower secondary bile acids in NAFLD patients compared to controls [28]. Gillard et al. also noted variability in bile acid levels across NAFLD studies, with some reports showing elevated levels and others unchanged [28, 29]. Chen et al. (2020) emphasized the role of gut microbiota in altering bile acid profiles, which is consistent with the observed increase in primary bile acids and decrease in secondary bile acids in NASH[25].

Diagnostic assessments of the discriminative power of bile acids through ROC curve analysis and PCA further highlight the potential of certain bile acids, especially primary bile acid CA, CDCA, GCDCA, and TCDCA and secondary bile acids LCA and TLCA in distinguishing NAFLD patients from healthy individuals with moderate sensitivity and high specificity, however, the limited ability of these bile acids to differentiate between NAST and NASH, for both primary and secondary bile acids, suggests that while bile acids are useful in identifying the presence of NAFLD, they may not be as effective in distinguishing its subtypes. PCA also identified significant contributors, including GCDCA, CA, and CDCA, indicating their relevance in distinguishing NAFLD from healthy states. These results mirror findings from other studies that emphasize the metabolic alterations in bile acids during NAFLD progression[30]. Notably, both ROC analysis and PCA demonstrated limited effectiveness in differentiating between NAST and NASH, suggesting these bile acids alone are insufficient for precise NAFLD subtyping. This limitation is consistent with broader challenges in the field, where a need for more specific biomarkers has been frequently noted[31, 32].

The study demonstrated significant bile acid dysregulation in diabetic and pre-diabetic patients, particularly elevated levels of CA, CDCA, GCA, and TCDCA, with the highest levels observed in diabetic patients. These elevations suggest a progressive impairment in bile acid metabolism linked to worsening glucose regulation. Additionally, hyperlipidemic patients exhibited higher levels of CA, LCA, GCA, and GUDCA, highlighting the interplay between lipid metabolism and bile acid profiles in NAFLD. The presence of elevated bile acids in pre-diabetic individuals indicates early metabolic changes, underscoring their potential as early biomarkers for disease progression. These findings align with previous research, which has reported similar increases in unconjugated bile acids, particularly CA, in diabetic and pre-diabetic patients, and suggest a compensatory increase in conjugated bile acids as an adaptive response [33, 34] [26, 27, 35, 36].

The study also observed gender differences, with female patients exhibiting higher levels of TDCA and TUDCA. These findings align with the findings of Puri et al., who suggested that sex hormones significantly influence bile acid metabolism by impacting the enzymes involved in bile acid synthesis and clearance. These results underscore the complexity of bile acid metabolism and highlight the importance of considering factors such as diabetes status, lipid profile, and gender when interpreting bile acid levels in clinical practice [37].

Exploring the relationship between bile acid levels and the severity of steatosis, inflammation, and fibrosis in NAFLD patients revealed that high levels of CA, GCA, TCA, TCDCA, DCA and TLCA, were found to be significantly associated with of steatosis. Higher levels of GCA, TCA, and TLCA were associated with liver inflammation, however, CA, CDCA, and GCA were significantly elevated in patients with advanced fibrosis. The logistic regression analysis also identified several bile acids as significant predictors of either steatosis, inflammation or fibrosis. Elevated CA, CDCA, GCA, TDCA, DCA TLCA, and UDCA were found to be significant predictors of steatosis. GCA, TCA and TLCA were identified as significant predictors of inflammation. Similarly, CA, CDCA, GCA and DCA were identified as significant predictors of fibrosis, emphasizing their potential utility in monitoring disease progression and severity.

Previous research partially or fully supports such associations[37-39]. For instance, Aranha et al. (2008) observed that elevated levels of CA, CDCA, and DCA in liver tissue correlated with steatosis and fibrosis in NASH patients[40]. Similarly, Puri et al. (2018) reported that increased serum levels of these bile acids were associated with steatosis and fibrosis in NAFLD patients, suggesting a role for these bile acids in the early detection and progression of the disease[37]. Furthermore, the elevated levels of GCA and DCA observed in this study align with earlier findings, indicating that these bile acids are involved in the pathogenesis of NAFLD and may reflect alterations in bile acid metabolism and liver function[25, 41, 42].

Chen et al. (2020) highlighted the importance of bile acids CA and CDCA in the progression from simple steatosis to more advanced stages of liver disease, emphasizing their role in the inflammatory and fibrotic processes[25]. TLCA, a secondary bile acid, has also been identified in previous studies as a marker of disease severity. Caussy et al. (2019) demonstrated significant changes in TLCA levels corresponding with advanced liver fibrosis, suggesting that TLCA could be a valuable marker for assessing the extent of liver damage [28]. Elevated levels of CA, CDCA, and TLCA in this study are consistent with observations from Khalil et al. (2022), who reported that elevated serum levels of these bile acids are associated with liver fibrosis and cirrhosis [43]. Additionally, Gottlieb and Canbay (2019) noted that increased conjugated bile acids such as TLCA are indicative of heightened inflammatory activity, which aligns with our findings that these bile acids are significant predictors of inflammation [41].

In summary, the study's findings that CA, CDCA, GCA, and DCA are predictors of steatosis, and CA, CDCA, TCA, and TLCA are predictors of fibrosis and inflammation, underscore the potential utility of these bile acids in monitoring the progression and severity of NAFLD. These observations are supported by existing literature, which highlights the role of these bile acids in the pathogenesis and progression of liver disease. The identification of these bile acids as significant predictors provides valuable insights into their potential use as biomarkers for early diagnosis, disease monitoring, and therapeutic targeting in NAFLD.

This study has several limitations. The cross-sectional design limits the ability to establish causality between bile acid alterations and NAFLD progression. Additionally, the sample size, while sufficient for detecting significant differences, may limit the generalizability of the findings. The study also did not account for dietary intake or genetic factors, which could influence bile acid metabolism[30, 44-46].

In conclusion, this study highlights the significant alterations in bile acid profiles in NAFLD and their potential utility as biomarkers for disease presence and progression. The associations identified between specific bile acids such as (CA, GCA, TCA, TCDCA, DCA and TLCA), and key pathological features like steatosis, fibrosis, and inflammation, underscore their relevance as indicators of disease severity. The predictive value of CA, CDCA, and TLCA for fibrosis and inflammation further emphasizes their potential role in monitoring NAFLD progression. These findings are consistent with existing literature, which underscores the involvement of these bile acids in the pathogenesis and advancement of liver disease [38, 44]. The identification of these bile acids as significant predictors offers valuable insights into their potential application in early diagnosis, disease monitoring, and therapeutic targeting in NAFLD. Future research should focus on longitudinal studies to track changes in bile acid profiles over time and assess their relationship with NAFLD progression, as well as evaluate the impact of therapeutic interventions on these biomarkers[47].

NHC: Normal healthy control, NAST: Nonalcoholic steatosis, NASH: Nonalcoholic steatohepatitis, NAFLD: Nonalcoholic fatty liver disease.

CA: Cholic acid, CDCA: Chenodeoxycholic acid, GCA: Glycholic acid, GCDCA: Glycochenodeoxycholic acid, TCA: Taurocholic acid, TCDCA: Taurochenodeoxycholic acid, DCA: Deoxycholic acid, LCA: Lithocholic acid, GDCA: Glycodeoxycholic acid, TDCA: Taurodeoxycholic acid, TLCA: Taurolithocholic acid, UDCA: Ursodeoxycholic acid, GUDCA: Glycoursodeoxycholic acid, TUDCA: Tauroursodeoxycholic acid. 1ryU: primary unconjugated, 1rygc: primary glycoconjugated, 1rytc: primary taurocongugated, 2ryU: secondary unconjugated, 2rygc: secondary glycoconjugated, 2rytc: secondary tauroconjugated.

AST: aspartate transaminase, ALT: alanine transaminase, GGT: Gamma-glutamyl transferase, ALP: alkaline phosphatase, TBil: total bilirubin, DBIL: direct bilirubin, TP: total protein, Alb: albumin, UA: uric acid, Chol: Cholesterol, LDL: low density lipoprotein, HDL: high density lipoprotein. TG: triglyceride. Hb: hemoglobin, WBCs: white blood cells. RBCs: red blood cells.

Ethics approval and consent to participate: The research ethics committees of the National Liver Institute (IRB005700 -2024), Menoufia University, approved the research proposal and the protocols to comply with national research guidelines. Patients provided informed written consent for the use of tissue for research purposes.

Consent for publication: obtained from all participants

Availability of data and material: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests: The authors declare they do not have any conflict of interest.

Funding: The authors declare they do not have any financial disclosure.

Authors' contributions: AAB: Conducted the UPLC/MS/MS analysis method. Contributed to the study concept and design, manuscript preparation. MFE: Patient recruitment and evaluation, collection of clinical data. DA: Conducted the pathological examination of the liver biopsy, staged and confirmed the diagnosis, and contributed to the concept and protocol development. AK: Corresponding author, study concept and design, analyzed the data, generated the result, wrote and edited the manuscript. All authors reviewed and approved the final version of the manuscript.

Acknowledgements: The authors would like to express their gratitude to Dr. Samah Elsheaty, Dr. Ghada Salah, Dr. Azza Elsheashaey, and Ms. Maryam Nagah for their dedicated efforts in patient care during sample collection and their outstanding work with HPLC at the National Liver Institute, Menoufia University.

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Table 1: Clinical Characteristics of the Studied Groups

Gender	NHC (n=25)	NAST (n=35)	NASH (n=40)	P-value
- Female	16 (64%)	23 (65.7%)	23 (57.5%)	χ² = 0.73, p = 0.695
- Male	9 (36%)	12 (34.3%)	17 (42.5%)
Age (years)	50.32 ± 9.45	50.31 ± 8.56	48.13 ± 8.77	t = 1.02, p = 0.313
Weight (kg)	72.92 ± 5.90	81.26 ± 10.27	77.00 ± 10.71	t = 3.34, p = 0.001
Height (cm)	169.20 ± 8.97	162.69 ± 8.39	163.25 ± 9.81	t = 2.49, p = 0.015
BMI (kg/m²)	25.73 ± 3.88	30.91 ± 4.77	29.22 ± 5.64	t = 4.50, p < 0.001
Diabetes Mellitus
- DM	4 (16%)	13 (37.1%)	12 (30%)	χ² = 5.42, p = 0.067
- No DM	14 (56%)	13 (37.1%)	17 (42.5%)
- Prediabetes (pDM)	7 (28%)	9 (25.7%)	11 (27.5%)
Hypertension
- Yes	7 (28%)	10 (28.6%)	16 (40%)	χ² = 1.44, p = 0.487
- No	18 (72%)	25 (71.4%)	24 (60%)
Lipid Status
- Hyperlipidemic	6 (24%)	20 (57.1%)	26 (65%)	χ² = 14.23, p = 0.001
- Normolipidemic	19 (76%)	15 (42.9%)	14 (35%)
Fibrosis Stage
- F0	25 (100%)	25 (71.4%)	0 (0%)	χ² = 58.75, p < 0.001
- F1	0 (0%)	10 (28.6%)	0 (0%)
- F2	0 (0%)	0 (0%)	16 (40%)
- F3	0 (0%)	0 (0%)	24 (60%)
Activity Grade
- A0	25 (100%)	22 (62.9%)	0 (0%)	χ² = 54.43, p < 0.001
- A1	0 (0%)	13 (37.1%)	0 (0%)
- A2	0 (0%)	0 (0%)	16 (40%)
- A3	0 (0%)	0 (0%)	24 (60%)
Steatosis Grade
- G0	25 (100%)	0 (0%)	0 (0%)	χ² = 75.00, p < 0.001
- G1	0 (0%)	18 (51.4%)	0 (0%)
- G2	0 (0%)	11 (31.4%)	16 (40%)
- G3	0 (0%)	6 (17.1%)	24 (60%)
Ultrasound Findings
- Normal homogenous liver	25 (100%)	0 (0%)	0 (0%)	χ² = 88.75, p < 0.001
- Fatty liver	0 (0%)	17 (48.6%)	0 (0%)
- Mildly enlarged fatty liver	0 (0%)	8 (22.9%)	9 (22.5%)
- Moderately enlarged fatty liver	0 (0%)	10 (28.6%)	31 (77.5%)
Clinical characteristics of NHC, NAST, and NASH groups with statistical significance for demographic, anthropometric, metabolic, and histological variables. NHC: Normal healthy control, NAST: Nonalcoholic steatosis, NASH, Nonalcoholic steatohepatitis, F0: No fibrosis F1: Mild fibrosis F2: Moderate fibrosis F3: Advanced fibrosis. Lobular inflammation Grade: A0: No lobular inflammation A1: Mild lobular inflammation A2: Moderate lobular inflammation, A3: Severe lobular inflammation. Steatosis Grade: G0: No steatosis (no fat accumulation in the liver), G1: Mild steatosis G2: Moderate steatosis G3: Severe steatosis. Ultrasound Findings: Normal homogeneous liver: Liver with normal echotexture. Fatty liver: Liver with increased echogenicity indicating fat accumulation. Mildly enlarged fatty liver: Slight increase in liver size with fatty infiltration. Moderately enlarged fatty liver: Moderate increase in liver size with more pronounced fatty infiltration.

Table 2: Descriptive Statistics and Kruskal-Wallis Test Results for Biochemical and Hematological Parameters Across NHC, NASH, and NAST Groups

Parameter	NHC (n=25)	NAST (n=35)	NASH (n=40)	P-value
Blood Glucose & Hemoglobin
FBS (mg/dL)	112 (21.5)	130 (71) (a)	143 (88.25) (b)	0.011
HA1C (%)	5.6 (0.35)	5.8 (0.9)	5.8 (1.475)	0.467
Renal Function
Creatinine (mg/dL)	0.77 (0.205)	0.78 (0.15)	0.77 (0.255)	0.358
Urea (mg/dL)	23 (6.5)	23 (11)	23.5 (12.75)	0.364
UA (mg/dL)	5.3 (2.0)	5.3 (0.8)	5.3 (2.0)	0.668
Liver Function
AST (U/L)	16 (8.5)	20 (31)	23 (41)	0.071
ALT (U/L)	21 (18.5)	24 (15)	30.5 (40.25)	0.136
TBIL (mg/dL)	0.9 (0.4)	0.98 (0.11)	0.9 (0.1)	0.215
DBIL (mg/dL)	0.11 (0.035)	0.13 (0.07) (a)	0.15(0.035) (b)	0.038
ALB (g/dL)	3.8 (0.5)	4.2 (1.1)	3.8 (0.775)	0.141
Glob (g/dL)	3.9 (0.9)	3.1 (1.3) (a)	3.7 (1.05)	0.016
TP (g/dL)	7.5 (0.45)	7.5 (0.7)	7.6 (0.55)	0.963
GGT (U/L)	12.4 (8.5)	23 (41) (a)	20 (12) (b)	0.002
Lipid Profile
Chol (mg/dL)	188 (47)	214 (62) (a)	207 (45.5) (b)	0.014
LDL (mg/dL)	105 (8.5)	99 (45)	102 (28)	0.269
HDL (mg/dL)	56 (14)	65 (31)	64 (28.5)	0.174
TG (mg/dL)	123 (25)	116 (27)	123 (35.75)	0.294
Hematological Parameters
Hb (g/dL)	11.7 (2.8)	12.0 (2.4)	12.8 (2.575)	0.489
RBC (10⁶/μL)	4.71 (1.125)	4.71 (0.83)	4.71 (0.98)	0.945
Platelets (10³/μL)	250 (40)	240 (41)	235 (53.75)	0.103
WBCs (10³/μL)	6.1 (2.7)	5.8 (2.7)	5.9 (4.15)	0.602
Comparative analysis of bile acid profiles using Kruskal-Wallis and Pairwise comparisons across NHC, NAST, and NASH Groups: IQR: Interquartile rang, K: Kruskal-Wallis test comparison among all groups, *P-value < 0.05 indicates significant. Mann-Whitney U test comparison between two groups. P-value < 0.05 indicates significant. a: comparing between NHC vs. NAST group. b: comparing between NHC vs. NASH group. c: comparing between NAST vs. NASH group. NHC: Normal healthy control, NAST: Nonalcoholic steatosis, NASH, Nonalcoholic steatohepatitis.

Table 3: Comparative Analysis of Bile Acid Profiles Across NHC, NAST, and NASH Groups

Bile Acid	Class	NHC Median (IQR)	NAST Median (IQR)	NASH Median (IQR)	K-Wallis P-value
CA	1ryU	0.130 (0.12)	0.230 (1.55) a	0.410 (1.41) b	0.000
CDCA	1ryU	0.001 (0.000)	0.050 (3.298) a	0.830 (3.29) b	0.000
GCA	1rygc	0.190 (0.165)	0.400 (1.76) a, c	1.770 (4.83) b, c	0.031
GCDCA	1rygc	2.120 (0.3)	3.730 (1.97) a	4.220 (9.14) a	0.000
TCA	1rytc	0.002 (0.015)	0.130 (0.028) ac	0.310 (0.019) b, c	0.004
TCDCA	1rytc	0.002 (0.059)	3.205 (4.32) a	4.390 (4.40) b	0.000
DCA	2ryU	0.160 (0.06)	0.280 (0.51)	0.335 (0.56)	0.588
LCA	2ryU	0.001 (0.000)	0.030 (0.218) a	0.006 (0.206) b	0.000
GDCA	2rygc	0.060 (0.13)	0.110 (0.168)	0.105 (0.143)	0.447
TDCA	2rytc	0.002 (0.001)	0.002 (0.049)	0.002 (0.002)	0.218
TLCA	2rytc	0.001 (0.000)	0.003 (0.008) a	0.010 (0.468) b	0.000
UDCA	2ryU	0.030 (0.034)	0.002 (0.009)	0.002 (0.059)	0.506
GUDCA	2rygc	0.003 (0.001)	1.200 (1.698) a	1.300 (1.698) b	0.025
TUDCA	2rytg	0.001 (0.001)	0.005 (0.259) a	0.005 (0.039) b	0.000
Comparative analysis of bile acid profiles using Kruskal-Wallis and Pairwise comparisons across NHC, NAST, and NASH Groups: IQR: Interquartile rang, K: Kruskal-Wallis test comparison among all groups, *P-value < 0.05 indicates significant. Mann-Whitney U test comparison between two groups. P-value < 0.05 indicates significant. a: comparing between NHC vs. NAST group. b: comparing between NHC vs. NASH group. c: comparing between NAST vs. NASH group. NHC: Normal healthy control, NAST: Nonalcoholic steatosis, NASH, Nonalcoholic steatohepatitis. 1ryU: primary unconjugated, 1rygc: primary glycoconjugated, 1rytc: primary tauroconjugated, 2ryU: secondary unconjugated, 2rygc: secondary glycoconjugated, 2rytc: secondary tauroconjugated.

Table 4. Bile Acid Levels Across Gender, Diabetes Status, and Lipid Profile in NAFLD Patients

	Bile Acid	Female (Median [IQR])	Male (Median [IQR])	P-value	DM (Median (IQR)	Pre-DM (Median (IQR)	No DM Median (IQR)	P-value	Normolipidemic (Median [IQR])	Hyperlipidemic (Median [IQR])	Mann-Whitney U	P-value
CA	1ryU	0.900 (1.53)	0.320 (1.41)	0.952	1.06 (0.39) a	0.34 (0.44)	0.32 (0.66)	0.034	0.93 (1.38)	0.29 (1.59)	795.5	0.001
CDCA	1ryU	1.100 (3.32)	0.650 (3.33)	0.719	2.50 (0.75) a	1.98 (0.65) b	1.38 (3.32)	0.045	1.35 (3.53)	0.08 (3.25)	802.5	0.167
GCA	1rygc	1.765 (2.26)	0.280 (2.02)	0.116	2.80 (0.80) a	1.60 (0.59) b	1.09 (0.74)	0.039	1.23 (1.85)	1.78 (3.52)	582.5	0.016
GCDCA	1rygc	4.175 (4.21)	3.850 (1.94)	0.918	4.24 (9.36)	3.98 (3.43)	3.41 (2.04)	0.146	4.05 (1.75)	4.17 (6.73)	628.5	0.615
TCA	1rytc	0.006 (0.04)	0.002 (0.02)	0.991	0.002 (0.029)	0.01 (0.018)	0.002 (1.5)	0.892	0.00 (0.02)	0.01 (0.04)	541.0	0.139
TCDCA	1rytc	4.390 (4.36)	2.980 (4.39)	0.723	4.40 (4.16) a	3.65 (4.35) b	2.37 (4.32)	0.020*	4.06 (4.13)	4.22 (4.58)	667.5	0.935
DCA	2ryU	0.280 (0.50)	0.420 (0.61)	0.682	0.18 (0.495)	0.46 (0.495)	0.27 (0.54)	0.376	0.28 (0.52)	0.33 (0.55)	657.0	0.845
LCA	2ryU	0.030 (0.21)	0.002 (0.19)	0.235	0.002 (0.079)	0.007 (0.218)	0.11 (0.274)	0.616	0.04 (0.22)	0.08 (0.21)	713.5	0.023
GDCA	2rygc	0.110 (0.15)	0.110 (0.16)	0.934	0.01 (0.148)	0.12 (0.212)	0.11 (0.118)	0.115	0.11 (0.17)	0.11 (0.13)	753.5	0.392
TDCA	2rytc	0.004 (0.01)	0.002 (0.08)	0.033*	0.001 (0.001)	0.002 (0.079)	0.002 (0.001)	0.104	0.00 (0.00)	0.00 (0.04)	678.0	0.973
TLCA	2rytc	0.005 (0.18)	0.010 (0.01)	0.490	0.01 (0.008)	0.005 (0.177)	0.01 (0.458)	0.943	0.01 (0.02)	0.01 (0.01)	626.0	0.591
UDCA	2ryU	0.001 (0.01)	0.002 (0.06)	0.170	0.001 (0.030)	0.002 (0.059)	0.002 (0.009)	0.535	0.00 (0.04)	0.00 (0.05)	669.5	0.950
GUDCA	2rygc	0.245 (1.70)	1.200 (1.70)	0.755	0.10 (1.648)	1.20 (1.697)	1.20 (1.698)	0.439	0.77 (1.70)	1.20 (1.71)	644.0	0.036
TUDCA	2rytg	0.012 (0.24)	0.001 (0.17)	0.037*	0.003 (0.164)	0.005 (0.093)	0.006 (1.499)	0.871	0.01 (0.29)	0.01 (0.07)	683.5	0.926
Comparative analysis of bile acid profiles using Kruskal-Wallis and Pairwise comparisons across diabetic groups: IQR: Interquartile rang, *P-value < 0.05 indicates significant. Pairwise comparisons a: comparing between No DM vs. DM group. b: comparing between No DM vs. p-DM group, c: comparing between p-DM vs. DM group. Mann-Whitney U test comparison between two groups (gender, lipidemic state). P-value < 0.05 indicates significant. DM: diabetes mellitus, p-DM: pre-diabetic, No DM: no diabetes mellitus, 1ryU: primary unconjugated, 1rygc: primary glycoconjugated, 1rytc: primary taurocongugated, 2ryU: secondary unconjugated, 2rygc: secondary glycoconjugated, 2rytc: secondary tauroconjugated.

Table 5: Correlation Analysis Between Bile Acids and Lipid Profile in NAST and NASH

		NAST, n=35				NASH, n=40
Bile Acid	class	Chol	LDL	HDL	TG	Chol	LDL	HDL	TG
CA	1ryU	0.22	-0.57**	0.57**	-0.12	0.18	-0.31*	0.42**	-0.11
CDCA	1ryU	0.15	-0.53**	0.56**	-0.12	0.29	-0.29	0.25	0.01
GCA	1rygc	0.14	0.06	-0.07	-0.08	0.49**	-0.19	0.28	-0.03
GCDCA	1rygc	-0.08	0.00	-0.02	-0.07	0.38*	-0.11	0.20	0.15
TCA	1rytc	-0.18	0.21	-0.20	-0.29	0.16	-0.01	0.29	0.05
TCDCA	1rytc	-0.32	0.32	-0.14	-0.13	0.31*	-0.14	0.29	0.13
DCA	2ryU	-0.13	-0.24	-0.24	-0.14	0.30	-0.22	0.20	-0.04
LCA	2ryU	0.14	-0.69**	0.70**	-0.17	0.29	-0.14	0.32	0.11
GDCA	2rygc	-0.09	-0.41*	0.39*	-0.16	0.39*	-0.44**	0.46**	-0.13
TDCA	2rytc	0.27	-0.27	0.29	-0.05	-0.26	0.29	-0.18	-0.04
TLCA	2rytc	-0.15	-0.15	0.07	-0.23	0.09	-0.09	0.07	0.05
UDCA	2ryU	0.00	0.28	-0.12	0.03	-0.08	0.08	-0.04	0.03
GUDCA	2rygc	-0.13	-0.09	0.28	-0.11	0.38*	-0.41*	0.50**	-0.09
TUDCA	2rytg	0.15	-0.20	0.01	0.02	0.37*	-0.23	0.38*	0.01
Spearman Rank Correlation Coefficients (r) Among Variables Across NHC, NAST, and NASH Groups. ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). NHC: Normal healthy control, NAST: Nonalcoholic steatosis, NASH: Nonalcoholic steatohepatitis, 1ryU: primary unconjugated, 1rygc: primary glycoconjugated, 1rytc: primary tauroconjugated, 2ryU: secondary unconjugated, 2rygc: secondary glycoconjugated, 2rytc: secondary tauroconjugated.

Table 6: Comparison of bile acid levels in NAFLD patients categorized by Fibrosis, Inflammation, and Steatosis Grades

			Fibrosis				Inflammation				Steatosis
Bile Acid	class	F0-F1		F2-F3	P-value	A0-A1		A2-A3	P-value	G0-G1		G2-G3	P-value
CA	1ryU	0.12 (1.05)		0.41 (1.40)	0.024	0.23 (1.55)		0.41 (1.40)	0.264	0.21 (0.54)		0.41 (0.42)	0.003
CDCA	1ryU	0.06 (3.30)		0.83 (0.29)	0.011	0.05 (3.30)		0.83 (3.29)	0.154	0.05 (3.14)		0.81 (3.32)	0.332
GCA	1rygc	1.57 (3.63)		0.40 (1.35)	0.041	1.77 (4.83)		0.40 (1.76)	0.048	1.27 (1.14)		2.76 (1.06)	0.032
GCDCA	1rygc	4.22 (9.14)		3.73 (1.97)	0.184	4.22 (9.14)		3.73 (1.97)	0.184	3.90 (3.20)		4.13 (3.20)	0.794
TCA	1rytc	0.01 (0.01)		0.00 (0.03)	0.803	0.01 (0.01)		0.04 (0.03)	0.033	0.02 (0.03)		0.04 (0.03)	0.025
TCDCA	1rytc	2.39 (4.11)		3.51 (4.32)	0.247	4.39 (4.30)		3.21 (4.32)	0.247	2.05 (4.35)		4.23 (4.38)	0.034
DCA	2ryU	0.21 (0.31)		0.24 (0.26)	0.890	0.28 (0.51)		0.34 (0.23)	0.890	0.40 (0.57)		0.28 (0.15)	0.047
LCA	2ryU	0.02 (0.29)		0.02 (0.23)	0.609	0.03 (0.19)		0.01 (0.20)	0.609	0.00 (0.19)		0.02 (0.20)	0.840
GDCA	2rygc	0.11 (0.04)		0.11 (0.05)	0.765	0.11 (0.06)		0.11 (0.04)	0.765	0.11 (0.15)		0.10 (0.15)	0.990
TDCA	2rytc	0.01 (0.00)		0.01 (0.00)	0.698	0.00 (0.00)		0.00 (0.00)	0.698	0.00 (0.08)		0.00 (0.00)	0.386
TLCA	2rytc	0.00 (0.42)		0.01 (0.46)	0.286	0.00 (0.02)		0.02 (0.46)	0.026	0.00 (0.01)		0.01 (0.60)	0.049
UDCA	2ryU	0.00 (0.04)		0.00 (0.06)	0.263	0.00 (0.01)		0.00 (0.06)	0.363	0.00 (0.06)		0.00 (0.02)	0.974
GUDCA	2rygc	1.28 (0.39)		1.34 (0.52)	0.673	1.20 (0.50)		1.30 (0.40)	0.673	1.20 (1.74)		0.34 (1.70)	0.950
TUDCA	2rytg	0.01 (0.37)		0.01 (0.14)	0.842	0.01 (0.26)		0.01 (0.04)	0.842	0.01 (0.13)		0.01 (0.24)	0.568
Comparison of bile acid levels in NAFLD patients categorized by fibrosis (F0-F1 vs. F2-F3), inflammation (A0-A1 vs. A2-A3), and steatosis (G0-G1 vs. G2-G3) grades. Mann-Whitney U test comparison between two groups. indicates significant, data are presented as median (IQR), with P-value < 0.05 indicates the statistical significance of differences between groups. 1ryU: primary unconjugated, 1rygc: primary glycoconjugated, 1rytc: primary tauroconjugated, 2ryU: secondary unconjugated, 2rygc: secondary glycoconjugated, 2rytc: secondary tauroconjugated.

Table 7: Binary Logistic Regression Analysis for Predicting Fibrosis, Lobular Inflammation, and Steatosis in NAFLD

		Fibrosis F0-1 vs F2-3				Active inflammation A0-1 vs A2-3				Steatosis G0-1 vs G2-3
	Variable	B	Wald	Sig.	Exp(B)	B	Wald	Sig.	Exp(B)	B	Wald	Sig.	Exp(B)
CA	1ryU	0.72	1.29	0.02	2.05	0.09	0.02	0.90	1.10	0.96	0.50	0.048	2.62
CDCA	1ryU	-0.55	0.93	0.04	1.58	-0.41	0.48	0.49	0.66	0.23	0.09	0.017	1.25
GCA	1rygc	-0.08	0.45	0.03	1.92	0.04	0.02	0.04	2.04	-0.09	0.47	0.041	2.92
GCDCA	1rygc	-0.20	1.67	0.20	0.82	-0.19	0.89	0.35	0.82	0.14	0.45	0.50	1.15
TCA	1rytc	0.18	1.11	0.29	1.20	-0.06	0.13	0.02	1.94	0.12	0.54	0.46	1.12
TCDCA	1rytc	0.12	0.54	0.47	1.12	0.16	0.98	0.32	1.17	-0.12	0.55	0.46	0.89
DCA	2ryU	0.72	0.31	0.04	2.06	0.37	0.16	0.69	1.45	-1.42	0.71	0.042	3.24
LCA	2ryU	-3.63	0.51	0.48	0.03	-0.67	0.40	0.53	0.51	-4.42	0.34	0.56	0.01
GDCA	2rygc	-1.66	0.63	0.43	0.19	-0.08	0.00	0.95	0.93	-4.11	3.81	0.05	0.02
TDCA	2rytc	-28.9	2.54	0.11	0.00	-1.03	1.24	0.27	0.36	1.47	1.21	0.04	4.35
TLCA	2rytc	2.91	2.70	0.10	18.39	2.77	1.76	0.03	15.95	14.45	2.45	0.03	20
UDCA	2ryU	19.17	0.93	0.34	20	16.48	1.12	0.03	20	17.13	1.19	0.02	20
GUDCA	2rygc	0.31	0.54	0.47	1.37	-0.02	0.00	0.96	0.98	-0.60	1.22	0.27	0.55
TUDCA	2rytg	0.59	1.16	0.28	1.80	0.16	0.14	0.71	1.18	0.85	0.96	0.33	2.34
The binary logistic regression analysis results are presented for three comparisons: fibrosis (F0-1 vs. F2-3), active inflammation (A0-1 vs. A2-3), and steatosis (G0-1 vs. G2-3) in NAFLD patients, using various bile acids as predictors. 1ryU: primary unconjugated, 1rygc: primary glycoconjugated, 1rytc: primary tauroconjugated, 2ryU: secondary unconjugated, 2rygc: secondary glycoconjugated, 2rytc: secondary tauroconjugated.

No competing interests reported.

Exploring Serum Bile Acids as Potential Noninvasive Biomarkers for Nonalcoholic Fatty Liver Disease

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