Metabolic phenotyping reveals an emerging role of ammonia abnormality in Alzheimer's disease.

The metabolic implications in Alzheimer's disease (AD) remain poorly understood. Here, we conducted a metabolomics study on a moderately aging Chinese Han cohort (n = 1397; mean age 66 years). Conjugated bile acids, branch-chain amino acids (BCAAs), and glutamate-related features exhibited strong correlations with cognitive impairment, clinical stage, and brain amyloid-ß deposition (n = 421). These features demonstrated synergistic performances across clinical stages and subpopulations and enhanced the differentiation of AD stages beyond demographics and Apolipoprotein E ε4 allele (APOE-ε4). We validated their performances in eight data sets (total n = 7685) obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Memory and Aging Project (ROSMAP). Importantly, identified features are linked to blood ammonia homeostasis. We further confirmed the elevated ammonia level through AD development (n = 1060). Our findings highlight AD as a metabolic disease and emphasize the metabolite-mediated ammonia disturbance in AD and its potential as a signature and therapeutic target for AD.

Associations of Plasma and Fecal Metabolites with Body Mass Index and Body Fat Distribution in Children.

CONTEXT: Childhood obesity continues to be a critical public health concern with far-reaching implications for the well-being. OBJECTIVE: This study aimed to investigate the association between metabolites in plasma and feces and indicators including body mass index (BMI), BMI for age Z score (BMIZ), and body fat distribution among children aged 6-9 years in China. METHODS: This cross-sectional study enrolled 424 healthy children, including 186 girls and 238 boys. Dual-energy X-ray absorptiometry (DXA) was used to determine the body fat content and regional fat distribution. Plasma and fecal metabolites were analyzed using targeted metabolomic technologies. RESULTS: A total of 200 plasma metabolites and 212 fecal metabolites were accurately quantified via ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). By using Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) and random forest model, we discovered that 9 plasma metabolites and 11 fecal metabolites were associated with different weight statuses. After adjusting for potential covariates and false discovery rate (FDR) correction, multiple linear regression analyses revealed that plasma metabolites (fumaric acid, glycine, l-glutamine, methylmalonic acid, and succinic acid) and fecal metabolites (protocatechuic acid) were negatively associated (ß: -1.373--0.016, pFDR: <0.001-0.031; ß: -1.008--0.071, pFDR: 0.005-0.033), while plasma metabolites (isovaleric acid, isovalerylcarnitine, l-glutamic acid, and pyroglutamic acid) and fecal metabolites (3-aminoisobutanoic acid, butyric acid, N-acetylneuraminic acid, octanoylcarnitine, oleoylcarnitine, palmitoylcarnitine, stearoylcarnitine, taurochenodesoxycholic acid, and taurodeoxycholic acid) exhibited positive associations with BMI, BMIZ, and body fat distribution (ß: 0.023-2.396, pFDR: <0.001; ß: 0.014-1.736, pFDR: <0.001-0.049). CONCLUSION: Plasma and fecal metabolites such as glutamine may serve as a potential therapeutic target for the development of obesity.

Quartet metabolite reference materials for inter-laboratory proficiency test and data integration of metabolomics profiling.

BACKGROUND: Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets. RESULTS: As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC-MS-based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. The Quartet multi-sample-based signal-to-noise ratio enables objective assessment of the reliability of intra-batch and cross-batch metabolomics profiling in detecting intrinsic biological differences among the four groups of samples. Significant variations in the reliability of the metabolomics profiling are identified across laboratories. Importantly, ratio-based metabolomics profiling, by scaling the absolute values of a study sample relative to those of a common reference sample, enables cross-laboratory quantitative data integration. Thus, we construct the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory accuracy assessment, which enables objective evaluation of quantitative metabolomics profiling using various instruments and protocols. CONCLUSIONS: Our study provides the community with rich resources and best practices for inter-laboratory proficiency tests and data integration, ensuring reliability of large-scale and longitudinal metabolomic studies.

LiveBoost: A GB-based prediction system for liver fibrosis in chronic hepatitis B patients in China - A multi-center retrospective study.

Background: The aim of this study was to evaluate the accuracy of LiveBoost™, a gradient boosting (GB)-based prediction system based on standard biochemical values (AST, ALT, platelet count) and age, in Chinese patients with chronic hepatitis B (CHB) and compare its performance with FIB-4 (fibrosis-4 score) and APRI (the aspartate transaminase to platelet ratio index). Methods: This retrospective trial enrolled 454 participants, including 279 CHB patients who underwent liver biopsy and 175 normal controls from 3 centers in China. All participants underwent laboratory blood testing. LiveBoost was constructed using GB and FIB-4 and APRI were calculated from laboratory data. Results: LiveBoost outperformed APRI and FIB-4 in predicting hepatic fibrosis and cirrhosis. The GB model had an AUROC of 0.977 for CHB diagnosis, 0.804 for early and advanced fibrosis, and 0.836 for non-cirrhosis and cirrhosis, compared to AUROC of 0.554, 0.673 and 0.720 for FIB-4, AUROC of 0.977, 0.652 and 0.654 for APRI. Conclusions: LiveBoost is a more reliable and cost-effective method than APRI and FIB-4 for assessing liver fibrosis in Chinese patients with CHB.

Association of gut microbiota, plasma and fecal metabolite profiles with intellectual development in school-age children.

Background: Little is known about how the gut microbiota and metabolic profiles are related to cognitive outcomes in young children until now. It was hypothesized that the gut microbiota, the plasma and fecal metabolites significantly correlated with intelligence quotient (IQ) in school-age children in current study. Methods: This cross-sectional study enrolled 452 children aged 6-9 years old. IQ was measured using the Wechsler Intelligence Scale for Children-Fourth Edition. Fecal microbiota, plasma and fecal metabolites were analyzed using 16S rRNA amplicon sequencing and targeted metabolomic technologies, respectively. Results: Restricted maximum likelihood (REML) analyses showed that microbiota composition and fecal metabolites were associated with neither subscale nor full-scale IQ (P: 0.059-0.500). However, plasma metabolites were significantly correlated with the processing speed (P=0.008). In multiple regression analysis after adjusting for confounders and multiple test correction, benzoic acid, azelaic acid, adipic acid, suberic acid and malonic acid selected by the multivariate methods with unbiased variable selection were positively associated with processing speed index (PSI) [Pfalse discovery rate (FDR): 0.006-0.024], whereas pyruvic acid was negatively associated with the PSI and full-scale IQ (PFDR: 0.014-0.030). Conclusions: In normal school-age children, certain plasma metabolites concentrations but not the gut microbiota composition nor fecal metabolites are correlated with intelligence.

Novel Deep Learning Network for Gait Recognition Using Multimodal Inertial Sensors.

Some recent studies use a convolutional neural network (CNN) or long short-term memory (LSTM) to extract gait features, but the methods based on the CNN and LSTM have a high loss rate of time-series and spatial information, respectively. Since gait has obvious time-series characteristics, while CNN only collects waveform characteristics, and only uses CNN for gait recognition, this leads to a certain lack of time-series characteristics. LSTM can collect time-series characteristics, but LSTM results in performance degradation when processing long sequences. However, using CNN can compress the length of feature vectors. In this paper, a sequential convolution LSTM network for gait recognition using multimodal wearable inertial sensors is proposed, which is called SConvLSTM. Based on 1D-CNN and a bidirectional LSTM network, the method can automatically extract features from the raw acceleration and gyroscope signals without a manual feature design. 1D-CNN is first used to extract the high-dimensional features of the inertial sensor signals. While retaining the time-series features of the data, the dimension of the features is expanded, and the length of the feature vectors is compressed. Then, the bidirectional LSTM network is used to extract the time-series features of the data. The proposed method uses fixed-length data frames as the input and does not require gait cycle detection, which avoids the impact of cycle detection errors on the recognition accuracy. We performed experiments on three public benchmark datasets: UCI-HAR, HuGaDB, and WISDM. The results show that SConvLSTM performs better than most of those reporting the best performance methods, at present, on the three datasets.

Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality rate due to its poor diagnosis in the early stage. Here, we report a urinary metabolomic study on a cohort of CRC patients (n =67) and healthy controls (n =21) using ultraperformance liquid chromatography triple quadrupole mass spectrometry. Pathway analysis showed that a series of pathways that belong to amino acid metabolism, carbohydrate metabolism, and lipid metabolism were dysregulated, for instance the glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, glycolysis, and TCA cycle. A total of 48 differential metabolites were identified in CRC compared to controls. A panel of 12 biomarkers composed of chenodeoxycholic acid, vanillic acid, adenosine monophosphate, glycolic acid, histidine, azelaic acid, hydroxypropionic acid, glycine, 3,4-dihydroxymandelic acid, 4-hydroxybenzoic acid, oxoglutaric acid, and homocitrulline were identified by Random Forest (RF), Support Vector Machine (SVM), and Boruta analysis classification model and validated by Gradient Boosting (GB), Logistic Regression (LR), and Random Forest diagnostic model, which were able to discriminate CRC subjects from healthy controls. These urinary metabolic biomarkers provided a novel and promising molecular approach for the early diagnosis of CRC.

Targeted Metabolomics Reveals Birth Screening Biomarkers for Biliary Atresia in Dried Blood Spots.

Early diagnosis and timely surgical Kasai portoenterostomy greatly improve the survival of patients with biliary atresia (BA), a neonatal cholestatic disease, which has encouraged investigators to develop newborn screening for BA. In this study, we used ultraperformance liquid chromatography-triple quadrupole mass spectrometry-based targeted metabolomics profiling to identify potential BA biomarkers in dried blood spots (DBS) collected from BA patients (n = 21) and healthy controls (n = 100). A distinctive metabolic profile comprising eight significantly differentially expressed metabolites, taurohyocholic acid (THCA), glutamic acid, 2-hydroxyglutaric acid, ketoleucine, indoleacetic acid, alpha-ketoisovaleric acid, glycocholic acid, and taurocholic acid (TCA), clearly distinguished BA infants from control neonates. Three metabolites, THCA, 2-hydroxyglutaric acid, and indoleacetic acid, were selected using linear regression and receiver operating characteristic (ROC) curve analysis and model construction. The area under the ROC curve for this model to discriminate between BA and comparison infants was 0.938 (95% confidence interval, CI: 0.874-1.000). A cutoff value of -0.336 produced a sensitivity of 90.48% (95% CI: 69.62% - 98.83%) and specificity of 92% (95% CI: 84.84% - 96.48%). In conclusion, the results suggest that metabolic markers in DBS obtained from newborns have a great potential for BA screening.

FoxM1 Regulates Proliferation and Apoptosis of Human Neuroblastoma Cell through PI3K/AKT Pathway.

Aim: This study investigated the effect of FoxM1 on the biological behavior of neuroblastoma (NB) cells in vitro and the association between FoxM1 and PI3K/AKT pathways in NB cell lines. Materials and methods: Recombinant plasmid pcDNA3.1 (+)-FoxM1 and FoxM1-specific small interfering RNA (siRNA) were transfected into IMR-32 cells by liposome transfection. The expression of FoxM1, AKT and PI3K were determined by qRT-PCR and western blotting. The effect of FoxM1 and PI3K/AKT pathways on the cell cycles and apoptosis were analyzed by flow cytometry. Cell viability and proliferation ability were assessed by CCK8 and colony formation assay. Results: Knockdown of FoxM1 promoted NB cell apoptosis and G1-phase cell cycle arrest significantly, increased the expression of apoptosis-related proteins, and suppressed the phospho-activation of PI3K and AKT. Over-expression of FoxM1 had the opposite effects. Conclusion: FoxM1 knockdown inhibited NB cell proliferation and induced apoptosis through inhibiting activation of PI3K and AKT.

Altered bile acid glycine : taurine ratio in the progression of chronic liver disease.

BACKGROUND AND AIM: The onset and progression of chronic liver disease (CLD) is a multistage process spanning years or several decades. Some bile acid (BA) features are identified as indicators for CLD progression. However, BAs are highly influenced by various factors and are stage and/or population specific. Emerging evidences demonstrated the association of structure of conjugated BAs and CLD progression. Here, we aimed to investigate the alteration of conjugated BAs and identify new features for CLD progression. METHODS: Based on liquid chromatography-mass spectrometry platform, 15 BAs were quantified in 1883 participants including healthy controls and CLD patients (non-alcoholic fatty liver [NAFL], non-alcoholic steatohepatitis [NASH], fibrosis, cirrhosis, and three types of liver cancer). Logistic regression was used to construct diagnostic models. Model performances were evaluated in discovery and test sets by area under the receiver operating characteristic curve, sensitivity, specificity, accuracy, and kappa index. RESULTS: Five BA glycine : taurine ratios were calculated, and glycocholic acid/taurocholic acid, glycodeoxycholic acid/taurodeoxycholic acid, and glycochenodeoxycholic acid/taurochenocholic acid were identified as candidates. Three diagnostic models were constructed for the differentiation of healthy control and early CLD (NAFL + NASH), early and advanced CLD (fibrosis + cirrhosis + liver cancer), and NAFL and NASH, respectively. The areas under the receiver operating characteristic curve of the models ranged from 0.91 to 0.97. The addition of age and gender improved model performances further. The alterations of the candidates and the performances of the diagnostic models were successfully validated by independent test sets (n = 291). CONCLUSIONS: Our findings revealed stage-specific BA perturbation patterns and provided new biomarkers and tools for the monitoring of liver disease progression.

Dimethyl fumarate ameliorates endotoxin-induced acute kidney injury against macrophage oxidative stress.

BACKGROUND: Characterized by macrophage infiltration, renal inflammation during septic acute kidney injury (AKI) reveals a ubiquitous human health problem. Unfortunately, effective therapies with limited side effects are still lacking. This study is aiming to elucidate the role of Dimethyl fumarate (DMF) in macrophages against oxidative stress of septic AKI. METHODS: Balb/c mice were gavaged by 50 mg/kg DMF then injected with 10 mg/kg LPS by i.p. We examined LPS-induced renal dysfunction and histological features in murine kidneys. Raw264.7 macrophage cells were also treated with DMF and then induced by LPS. The mitotracker staining was used to follow mitochondria integrity by confocal microscopy. Flow cytometry measured the production of ROS by DCF-HDA and the expression of iNOS. Western blot detected the expression of Nrf-2 and Sirt1. Co-IP measured the interaction between Sirt1 and Nrf-2. Confocal microscopy observed the colocalization of Sirt1 and Nrf-2 in LPS-treated Raw264.7 macrophage cells. RESULTS: DMF ameliorated murine LPS nephritis with reduced blood urea nitrogen and serum creatinine, as well as decreased the histological alterations compared to the normal control. DMF significantly inhibited the expression of iNOS and reduced the production of nitrite in Raw264.7 cells following LPS treatment. Our study also revealed the role of DMF in protecting against intracellular ROS accumulation and mitochondria dysfunction in LPS-induced nephritis. DMF facilitated colocalization and interaction between Sirt1 and Nrf-2 in LPS-treated cells. CONCLUSIONS: This study showed that DMF alleviated LPS-induced nephritis, indicating protective effects of DMF on macrophage against oxidative stress induced by LPS potentially involving Nrf-2-mediated pathway.

A Metabolite Array Technology for Precision Medicine.

The application of metabolomics in translational research suffers from several technological bottlenecks, such as data reproducibility issues and the lack of standardization of sample profiling procedures. Here, we report an automated high-throughput metabolite array technology that can rapidly and quantitatively determine 324 metabolites including fatty acids, amino acids, organic acids, carbohydrates, and bile acids. Metabolite identification and quantification is achieved using the Targeted Metabolome Batch Quantification (TMBQ) software, the first cross-vendor data processing pipeline. A test of this metabolite array was performed by analyzing serum samples from patients with chronic liver disease (N = 1234). With high detection efficiency and sensitivity in serum, urine, feces, cell lysates, and liver tissue samples and suitable for different mass spectrometry systems, this metabolite array technology holds great potential for biomarker discovery and high throughput clinical testing. Additionally, data generated from such standardized procedures can be used to generate a clinical metabolomics database suitable for precision medicine in next-generation healthcare.

Bile Acid Profiles Are Distinct among Patients with Different Etiologies of Chronic Liver Disease.

A significant increase of bile acid (BA) levels has been recognized as a general metabolic phenotype of diverse liver diseases. Monitoring of BA profiles has been proposed for etiology differentiation on liver injury. Here, we quantitatively profiled serum BAs of healthy controls and 719 patients with chronic liver disease of five etiologies, hepatitis B virus (HBV), hepatitis C virus (HCV), nonalcoholic steatohepatitis (NASH), alcohol-induced liver disease (ALD), and primary biliary cirrhosis (PBC), and investigated the generality and specificity of different etiologies. The raw data have been deposited into MetaboLights (ID: MTBLS2459). We found that patients with HBV, HCV, and NASH appeared to be more similar, and ALD and PBC patients clustered together. BA profiles, consisting of a total concentration of the 21 quantified BAs [total BAs (TBAs)], 21 BA proportions, and 24 BA relevant variables, were highly different among the etiologies. Specifically, the total BAs was higher in ALD and PBC patients compared with the other three groups. The proportion of conjugated deoxycholates was the highest in HBV-infected patients. The ratio of 12α-hydroxylated (12α-OH) to non-12α-OH BAs was the highest in NASH patients. The proportion of taurine-conjugated BAs was the highest in ALD patients. For PBC patients, the proportion of ursodeoxycholate species was the highest, and the ratio of primary to secondary BAs was the lowest. Comparatively, the difference of BA profiles among cirrhosis patients was consistent but weaker than that of all patients. The correlations between BA profiles and clinical indices were also quite different in different pathological groups, both in all patients and in patients with cirrhosis. Overall, our findings suggested that BA compositions are distinct among patients with different etiologies of chronic liver disease, and some BA-relevant variables are of clinical potentials for liver injury type differentiation, although further validations on more etiologies and populations are needed.

IP4M: an integrated platform for mass spectrometry-based metabolomics data mining.

BACKGROUND: Metabolomics data analyses rely on the use of bioinformatics tools. Many integrated multi-functional tools have been developed for untargeted metabolomics data processing and have been widely used. More alternative platforms are expected for both basic and advanced users. RESULTS: Integrated mass spectrometry-based untargeted metabolomics data mining (IP4M) software was designed and developed. The IP4M, has 62 functions categorized into 8 modules, covering all the steps of metabolomics data mining, including raw data preprocessing (alignment, peak de-convolution, peak picking, and isotope filtering), peak annotation, peak table preprocessing, basic statistical description, classification and biomarker detection, correlation analysis, cluster and sub-cluster analysis, regression analysis, ROC analysis, pathway and enrichment analysis, and sample size and power analysis. Additionally, a KEGG-derived metabolic reaction database was embedded and a series of ratio variables (product/substrate) can be generated with enlarged information on enzyme activity. A new method, GRaMM, for correlation analysis between metabolome and microbiome data was also provided. IP4M provides both a number of parameters for customized and refined analysis (for expert users), as well as 4 simplified workflows with few key parameters (for beginners who are unfamiliar with computational metabolomics). The performance of IP4M was evaluated and compared with existing computational platforms using 2 data sets derived from standards mixture and 2 data sets derived from serum samples, from GC-MS and LC-MS respectively. CONCLUSION: IP4M is powerful, modularized, customizable and easy-to-use. It is a good choice for metabolomics data processing and analysis. Free versions for Windows, MAC OS, and Linux systems are provided.

Development and validation of bile acid profile-based scoring system for identification of biliary atresia: a prospective study.

BACKGROUND: Early distinguishing biliary atresia from other causes of infantile cholestasis remains a major challenge. We aimed to develop and validate a scoring system based on bile acid for identification of biliary atresia. METHODS: In a prospective study, a total of 141 infants with cholestasis were enrolled in two sets (derivation cohort, n = 66; validation cohort, n = 75) from 2014 to 2018. Variables with significant difference between biliary atresia and non-biliary atresia infants were selected in the derivation cohort. Then, a scoring system including those variables was designed and validated. RESULTS: Among 66 patients in the derivation cohort, 34 (51.5%) had biliary atresia. A scoring system was proposed with the following variables: glycochenodeoxycholic acid/chenodeoxycholic acid, clay stool, and gamma-glutamyl transferase. The total score ranged from 0 to 41, and a cutoff value of 15 identified biliary atresia with an area under receiver operating characteristic curve of 0.87 (95% confidence interval, 0.77-0.94), sensitivity of 85.3%, and specificity of 81.3% in the derivation cohort; these values were also confirmed in a validation cohort with a sensitivity of 90.0% and specificity of 80.0%. CONCLUSIONS: The proposed simple scoring system had good diagnostic accuracy for estimating the risk of biliary atresia in infants with cholestasis.

Targeted Metabolomics Identifies Differential Serum and Liver Amino Acids Biomarkers in Rats with Alcoholic Liver Disease.

To investigate changes in serum and hepatic levels of amino acids in ALD and to provide novel evidence and approaches for the prevention and treatment of ALD. Twenty specific pathogen-free SD male rats were devided into two groups, ten for the control group, and ten for the model group. Serum biochemical markers, including alanine aminotransferase, aspartate aminotransferase, laminin and hyaluronidase were measured. Histological analysis of liver tissues was performed. Serum and liver amino acids levels were quantitatively determined by ultra-high-performance liquid chromatography-tandem quadrupole mass spectrometry (UPLC-TQMS)-based targeted metabolomics. Compared with the normal group, ALD rats showed an obvious increase in the levels of ß-alanine, alanine, serine, ornithine, tyrosine and the tyrosine ratio, while there was a decrease in arginine levels, the BTR ratio and Fischer's ratio in serum. Additionally, ALD rats exhibited a significant increase in the levels of cysteine and putrescine, while there was a decrease in sarcosine, ß-alanine, serine, proline, valine, threonine, ornithine, lysine, histidine, tyrosine, symmetric dimethylarginine, methionine, isoleucine and methionine-sulfoxide levels in liver tissues compared with the normal group. The serum and liver amino acids showed significant changes in ALD rats and can be considered as potential specific diagnostic biomarkers for ALD.

Retraction Note: Interactions between Th1 cells and Tregs affect regulation of hepatic fibrosis in biliary atresia through the IFN-γ/STAT1 pathway.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

FXR agonist GW4064 improves liver and intestinal pathology and alters bile acid metabolism in rats undergoing small intestinal resection.

Mortality associated with liver disease has been observed in patients with short bowel syndrome (SBS); however, its mechanism remains unclear, but bile acid (BA) dysmetabolism has been proposed as a possible cause. The farnesoid X receptor (FXR) is the key regulator of BA synthesis. Here, we showed that, in a rat model of short bowel resection associated with liver disease (SBR-ALD), the BA composition of hepatic tissues reflected a larger proportion of primary and secondary unconjugated BAs, whereas that of the colon contents and serum showed an increased ratio of secondary unconjugated BAs. Both hepatic and intestinal regulation of BA synthesis was characterized by a blunted hepatic FXR activation response. The mRNA expression levels of cholesterol 7a-hydroxylase (CYP7A1), sterol 12a-hydroxylase (CYP8B1), and sterol 27 hydroxylase (CYP27A1), the key enzymes in BA synthesis, were upregulated. After intervention with the FXR agonist GW4064, both the liver histology and serum transaminase activity were improved, which demonstrated the attenuation of SBR-ALD. The BA compositions of hepatic tissue, the colon contents, and serum recovered and were closer to those of the sham group. The expression levels of hepatic FXR increased, and its target genes were activated. Consistent with this, the expression levels of CYP7A1, CYP8B1, and CYP27A1 were downregulated. Ileum tissue FXR and its target genes were slightly elevated. This study showed that the FXR agonist GW4064 could correct BA dysmetabolism to alleviate hepatotoxicity in SBR animals. GW4064 intervention resulted in a decrease in fecal bile excretion and elevated plasma/hepatic conjugated BA levels. GW4064 increased the reabsorption of conjugated BAs by inducing apical sodium-dependent bile salt transporter expression in the ileum. Concomitantly, FXR activation in the presence of GW4064 decreased BA production by repressing the expression of key synthetases, including CYP7A1, CYP8B1, and CYP27A1. These findings provide a clinical research direction for the prevention of liver disease in patients with SBS.NEW & NOTEWORTHY This study assessed the impact of treatment with GW4064, a farnesoid X receptor agonist, on the development of short bowel resection (SBR) associated with liver disease in a rat model of SBR. GW4064 was able to correct bile acid dysmetabolism and alleviate hepatotoxicity in SBR animals.