Metabolic Characterization of Advanced Liver Fibrosis in HCV Patients as Studied by Serum 1H-NMR Spectroscopy

The Metabolomic Footprint of Liver Fibrosis

Both experimental and clinical liver fibrosis leave a metabolic footprint that can be uncovered and defined using metabolomic approaches. Metabolomics combines pattern recognition algorithms with analytical chemistry, in particular, 1H and 13C nuclear magnetic resonance spectroscopy (NMR), gas chromatography-mass spectrometry (GC-MS) and various liquid chromatography-mass spectrometry (LC-MS) platforms. The analysis of liver fibrosis by each of these methodologies is reviewed separately. Surprisingly, there was little general agreement between studies within each of these three groups and also between groups. The metabolomic footprint determined by NMR (two or more hits between studies) comprised elevated lactate, acetate, choline, 3-hydroxybutyrate, glucose, histidine, methionine, glutamine, phenylalanine, tyrosine and citrate. For GC-MS, succinate, fumarate, malate, ascorbate, glutamate, glycine, serine and, in agreement with NMR, glutamine, phenylalanine, tyrosine and citrate were delineated. For LC-MS, only β-muricholic acid, tryptophan, acylcarnitine, p-cresol, valine and, in agreement with NMR, phosphocholine were identified. The metabolomic footprint of liver fibrosis was upregulated as regards glutamine, phenylalanine, tyrosine, citrate and phosphocholine. Several investigators employed traditional Chinese medicine (TCM) treatments to reverse experimental liver fibrosis, and a commentary is given on the chemical constituents that may possess fibrolytic activity. It is proposed that molecular docking procedures using these TCM constituents may lead to novel therapies for liver fibrosis affecting at least one-in-twenty persons globally, for which there is currently no pharmaceutical cure. This in-depth review summarizes the relevant literature on metabolomics and its implications in addressing the clinical problem of liver fibrosis, cirrhosis and its sequelae.

Exploration of TCM syndrome types of the material basis and risk prediction of Wilson disease liver fibrosis based on 1H NMR metabolomics

Wilson disease (WD) is an autosomal recessive disorder characterized by abnormal copper metabolism. The accumulation of copper in the liver can progress to liver fibrosis and, ultimately, cirrhosis, which is a primary cause of death in WD patients. Metabonomic technology offers an effective approach to investigate the traditional Chinese medicine (TCM) syndrome types of WD-related liver fibrosis by monitoring the alterations in small molecule metabolites within the body. In this study, we employed 1H-Nuclear Magnetic Resonance (1H NMR) metabonomics to assess the metabolic profiles associated with five TCM syndrome types of WD-related liver fibrosis and analyzed the diagnostic and predictive capabilities of various metabolites. The study found a variety of metabolites, each with varying levels of diagnostic and predictive capabilities. Furthermore, the discerned differential metabolic pathways were primarily associated with various pathways involving carbohydrate metabolism, amino acid metabolism, and lipid metabolism. This study has identified various characteristic metabolic markers and pathways associated with different TCM syndromes of liver fibrosis in WD, providing a substantial foundation for investigating the mechanisms underlying these TCM syndromes.

Network pharmacology combined with metabolomics to reveal the anti-fibrotic mechanism of Polygoni Orientalis Fructus in CCl4-induced hepatic fibrosis rats

Polygoni Orientalis Fructus (POF), a dried ripe fruit of Polygonum orientale L., is commonly used in China for liver disease treatment. However, its therapeutic mechanism remains unclear. The aim of this study was to elucidate the effects of POF on the regulation of endogenous metabolites and identify its key therapeutic targets in hepatic fibrosis (HF) rats by integrating network pharmacology and metabolomics approaches. First, serum liver indices and histopathological analyses were used to evaluate the therapeutic effects of POF on carbon tetrachloride (CCl4)-induced HF. Subsequently, differential metabolites and potential therapeutic targets of POF were screened using plasma metabolomics and network pharmacology, respectively. The key targets of POF were identified by overlapping differential metabolite-associated targets with the potential targets and validated by molecular docking and ELISA experiments. The results showed that POF effectively alleviated HF in rats. A total of 51 metabolites related to HF were screened, and 24 were associated with POF. 232 potential therapeutic targets were identified by network pharmacology analysis. Finally, six key targets were identified through a combined analysis. Furthermore, molecular docking and ELISA validation revealed that AGXT, PAH, and NOS3 are targets of POF action, while CBS, ALDH2, and ARG1 were identified as potential targets. SIGNIFICANCE: POF is now commonly used in the treatment of liver disease, but its mechanism of action remains unclear. Current studies on metabolomics of liver disease primarily focuse on the interpretation of differential metabolites and related metabolic pathways. This research delves into the intricate details of metabolomics findings via network pharmacology to uncover the targets and pathways of drug action.

Baicalin and N-acetylcysteine regulate choline metabolism via TFAM to attenuate cadmium-induced liver fibrosis

(Background): Cadmium is an environmental pollutant associated with several liver diseases. Baicalin and N-Acetylcysteine have antioxidant and hepatoprotective effects. (Purpose): However, it is unclear whether baicalin and N-Acetylcysteine can alleviate Cadmium -induced liver fibrosis by regulating metabolism, or whether they exert a synergistic effect. (Study design): We treated Cadmium-poisoned mice with baicalin, N-Acetylcysteine, or baicalin+ N-Acetylcysteine. We studied the effects of baicalin and N-Acetylcysteine on Cadmium-induced liver fibers and their specific mechanisms. (Methods): We used C57BL/6 J mice, and AML12, and HSC-6T cells to establish in vitro assays and in vivo models. (Results): Metabolomics was used to detect the effect of baicalin and N-Acetylcysteine on liver metabolism, which showed that compared with the control group, the Cadmium group had increased fatty acid and amino acid levels, with significantly reduced choline and acetylcholine contents. Baicalin and N-Acetylcysteine alleviated these Cadmium-induced metabolic changes. We further showed that choline alleviated Cadmium -induced liver inflammation and fibrosis. In addition, cadmium significantly promoted extracellular leakage of lactic acid, while choline alleviated the cadmium -induced destruction of the cell membrane structure and lactic acid leakage. Western blotting showed that cadmium significantly reduced mitochondrial transcription factor A (TFAM) and Choline Kinase α(CHKα2) levels, and baicalin and N-Acetylcysteine reversed this effect. Overexpression of Tfam in mouse liver and AML12 cells increased the expression of CHKα2 and the choline content, alleviating and cadmium-induced lactic acid leakage, liver inflammation, and fibrosis. (Conclusion): Overall, baicalin and N-Acetylcysteine alleviated cadmium-induced liver damage, inflammation, and fibrosis to a greater extent than either drug alone. TFAM represents a target for baicalin and N-Acetylcysteine, and alleviated cadmium-induced liver inflammation and fibrosis by regulating hepatic choline metabolism.

Diagnosis and monitoring of hepatocellular carcinoma in Hepatitis C virus patients using attenuated total reflection Fourier transform infrared spectroscopy

BACKGROUND

Current diagnostic methods for assessment of hepatitis C virus related hepatocellular carcinoma and subsequent categorization of hepatocellular carcinoma into non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma, to establish appropriate treatment strategies, are costly, invasive and requires multiple screening steps. This demands alternative diagnostic approaches that are cost-effective, time-efficient, and minimally invasive, while maintaining their efficacy for screening of hepatitis c virus related hepatocellular carcinoma. In this study, we propose that attenuated total reflection Fourier transform infrared in conjunction with principal component analysis - linear discriminant analysis and support vector machine multivariate algorithms holds a potential as a sensitive tool for the detection of hepatitis C virus-related hepatocellular carcinoma and the subsequent categorization of hepatocellular carcinoma into non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma.

METHODS

Freeze-dried sera samples collected from 31 hepatitis c virus related hepatocellular carcinoma patients and 30 healthy individuals, were used to acquire mid-infrared absorbance spectra (3500-900 cm-1) using attenuated total reflection Fourier transform infrared. Chemometric machine learning techniques were utilized to build principal component analysis - linear discriminant analysis and support vector machine discriminant models for the spectral data of hepatocellular carcinoma patients and healthy individuals. Sensitivity, specificity, and external validation on blind samples were calculated.

RESULTS

Major variations were observed in the two spectral regions i.e., 3500-2800 and 1800-900 cm-1. IR spectral signatures of hepatocellular carcinoma were reliably different from healthy individuals. Principal component analysis - linear discriminant analysis and support vector machine models computed 100% accuracy for diagnosing hepatocellular carcinoma. To classify the non-angio-invasive hepatocellular carcinoma/ angio-invasive hepatocellular carcinoma status, diagnostic accuracy of 86.21% was achieved for principal component analysis - linear discriminant analysis. While the support vector machine showed a training accuracy of 98.28% and a cross-validation accuracy of 82.75%. External validation for support vector machine based classification observed 100% sensitivity and specificity for accurately classifying the freeze-dried sera samples for all categories.

CONCLUSIONS

We present the specific spectral signatures for non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma, which were prominently differentiated from healthy individuals. This study provides an initial insight into the potential of attenuated total reflection Fourier transform infrared to diagnose hepatitis C virus related hepatocellular carcinoma but also to further categorize into non-angio-invasive and angio-invasive hepatocellular carcinoma.

Blood Metabolite Profiling of Antarctic Expedition Members: An 1H NMR Spectroscopy-Based Study

Serum samples from eight participants during the XV winter-over at Concordia base (Antarctic expedition) collected at defined time points, including predeparture, constituted the key substrates for a specific metabolomics study. To ascertain acute changes and chronic adaptation to hypoxia, the metabolic profiles of the serum samples were analyzed using NMR spectroscopy, with principal components analysis (PCA) followed by partial least squares and orthogonal partial least squares discriminant analyses (PLS-DA and OPLS-DA) used as supervised classification methods. Multivariate data analyses clearly highlighted an adaptation period characterized by an increase in the levels of circulating glutamine and lipids, mobilized to supply the body energy needs. At the same time, a reduction in the circulating levels of glutamate and N-acetyl glycoproteins, stress condition indicators, and proinflammatory markers were also found in the NMR data investigation. Subsequent pathway analysis showed possible perturbations in metabolic processes, potentially related to the physiological adaptation, predominantly found by comparing the baseline (at sea level, before mission onset), the base arrival, and the mission ending collected values.

A multimodal pipeline using NMR spectroscopy and MALDI-TOF mass spectrometry imaging from the same tissue sample

NMR spectroscopy and matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) are both commonly used to detect large numbers of metabolites and lipids in metabolomic and lipidomic studies. We have demonstrated a new workflow, highlighting the benefits of both techniques to obtain metabolomic and lipidomic data, which has realized for the first time the combination of these two complementary and powerful technologies. NMR spectroscopy is frequently used to obtain quantitative metabolite information from cells and tissues. Lipid detection is also possible with NMR spectroscopy, with changes being visible across entire classes of molecules. Meanwhile, MALDI MSI provides relative measures of metabolite and lipid concentrations, mapping spatial information of many specific metabolite and lipid molecules across cells or tissues. We have used these two complementary techniques in combination to obtain metabolomic and lipidomic measurements from triple-negative human breast cancer cells and tumor xenograft models. We have emphasized critical experimental procedures that ensured the success of achieving NMR spectroscopy and MALDI MSI in a combined workflow from the same sample. Our data show that several phospholipid metabolite species were differentially distributed in viable and necrotic regions of breast tumor xenografts. This study emphasizes the power of combined NMR spectroscopy-MALDI imaging to advance metabolomic and lipidomic studies.

Serum nuclear magnetic resonance metabolomics analysis of human metastatic colorectal cancer: Biomarkers and pathway analysis

We describe the use of nuclear magnetic resonance metabolomics to analyze blood serum samples from healthy individuals (n = 26) and those with metastatic colorectal cancer (CRC; n = 57). The assessment, employing both linear and nonlinear multivariate data analysis techniques, revealed specific metabolite changes associated with metastatic CRC, including increased levels of lactate, glutamate, and pyruvate, and decreased levels of certain amino acids and total fatty acids. Biomarker ratios such as glutamate-to-glutamine and pyruvate-to-alanine were also found to be related to CRC. The study also found that glutamate was linked to progression-free survival and that both glutamate and 3-hydroxybutyrate were risk factors for metastatic CRC. Additionally, gas chromatography coupled to flame-ionization detection was utilized to analyze the fatty acid profile and pathway analysis was performed on the profiled metabolites to understand the metabolic processes involved in CRC. A correlation was also found between the presence of certain metabolites in the blood of CRC patients and certain clinical features.

Biomarkers used in Alzheimer's disease diagnosis, treatment, and prevention

Alzheimer's disease (AD), being the number one in terms of dementia burden, is an insidious age-related neurodegenerative disease and is presently considered a global public health threat. Its main histological hallmarks are the Aβ senile plaques and the P-tau neurofibrillary tangles, while clinically it is marked by a progressive cognitive decline that reflects the underlying synaptic loss and neurodegeneration. Many of the drug therapies targeting the two pathological hallmarks namely Aβ and P-tau have been proven futile. This is probably attributed to the initiation of therapy at a stage where cognitive alterations are already obvious. In other words, the underlying neuropathological changes are at a stage where these drugs lack any therapeutic value in reversing the damage. Therefore, there is an urgent need to start treatment in the very early stage where these changes can be reversed, and hence, early diagnosis is of primordial importance. To this aim, the use of robust and informative biomarkers that could provide accurate diagnosis preferably at an earlier phase of the disease is of the essence. To date, several biomarkers have been established that, to a different extent, allow researchers and clinicians to evaluate, diagnose, and more specially exclude other related pathologies. In this study, we extensively reviewed data on the currently explored biomarkers in terms of AD pathology-specific and non-specific biomarkers and highlighted the recent developments in the diagnostic and theragnostic domains. In the end, we have presented a separate elaboration on aspects of future perspectives and concluding remarks.

Comparative metabolomic study of high-flux hemodialysis and high volume online hemodiafiltration in the removal of uremic toxins using 1H NMR spectroscopy

Uremic toxins (UTs) accumulate in the circulation of patients with chronic kidney disease (CKD). High volume hemodiafiltration (HDF) improves clearance of low and medium molecular weight UTs compared to HD. The present study is a post-hoc analysis comparing the metabolomic profile in serum from patients under high flux HD (hf-HD) and HDF in HDFIT, a multicentric randomized controlled trial (RCTs). Per protocol, serum samples were collected pre- and post- dialysis treatments at randomization (baseline) and at the end of the follow up (6 months) and stored in a biorepository. Random (pre- and post-dialysis) samples from nine patients in study arm were selected at baseline and at the end of the follow up. To compare the samples, 26 possibly matching metabolites were identified by a t-test among the four groups using ¹H nuclear magnetic resonance (NMR). To evaluate the comparison between the modalities is a single treatment session, the clearance rates (CRs) of each metabolite were calculated based on pre-dialysis and post-dialysis samples. In addition, to evaluate to effect of UT removal during the trial follow up period, the pre-dialysis metabolite concentrations at the baseline and at 6 months were compared among the two arms of the study. There was no significant difference between in the single session CRs of metabolites when hf-HD and HDF were compared. On the other hand, the comparison between baseline and 6-month (long-term evolution) led to the identification of 16 metabolites that differentiated the hf-HD and the HDF evolutions. Most of these 16 metabolites are involved in several important metabolic pathways, such as metabolism of phenylalanine and biosynthesis of phenylalanine, tyrosine, and tryptophan, which are related to UTs and cardiovascular disease development. Although no difference was observed between hf-HD and HDF samples before and after a single session, concentrations of CKD-relevant metabolites and associated pathologies were stable in the HDF samples, but not in the hf-HD samples, over the six-month period, suggesting that HDF enhances long-term stability.

Urinary metabolomics of HCV patients with severe liver fibrosis before and during the sustained virologic response achieved by direct acting antiviral treatment

Hepatitis C virus (HCV) infection induces a long-term inflammatory response and oxidative-stress in the liver microenvironment, leading to hepatic fibrosis and metabolic alterations. Direct-acting-antiviral-agents (DAAs) induce HCV-clearance, even though liver damage is only partially restored. In this context, understanding the impact of viral-eradication on liver metabolic activities could allow optimizing the metabolic care of the patient. The present prospective longitudinal study aims at characterizing the urinary metabolic profile of HCV-induced severe liver fibrosis and the metabolic changes induced by DAAs and HCV-clearance by nuclear magnetic resonance-based metabolomics. The urinary metabolic profile of 23 HCV males with severe liver fibrosis and 20 age-matched healthy-controls was analyzed by NMR-based-metabolomics before starting DAAs, at the end-of-therapy, after one and three months of follow-up. The urinary metabolic profile of patients with severe liver fibrosis was associated to pseudouridine, hypoxanthine, methylguanidine and dimethylamine, highlighting a profile related to oxidative damage, and to tyrosine and glutamine, related to a decreased breakdown of aromatic aminoacids and ammonia detoxification, respectively. 1-methylnicotinamide, a catabolic intermediate of nicotinamide-adenine-dinucleotide, was significantly increased in HCV-patients and restored after HCV-clearance, probably due to the reduced hepatic inflammation. 3-hydroxy-3-methylbutyrate, an intermediate of leucine-catabolism which was permanently restored after HCV-clearance, suggested an improvement of skeletal muscle protein synthesis. Finally, 3-hydroxyisobutyrate and 2,3-dihydroxy-2-methylbutyrate, intermediates of valine-catabolism, glycine and choline increased temporarily during therapy, resulting as potential biomarkers of DAAs systemic effects.

Investigation of the therapeutic effect of Yinchen Wuling Powder on CCl4-induced hepatic fibrosis in rats by 1H NMR and MS-based metabolomics analysis

Hepatic fibrosis (HF) is a typical consequence of various chronic liver diseases, and there is still no ideal drug for its treatment. Yinchen Wuling Powder (YCWLP), a famous traditional Chinese medicine prescription, is effective for the treatment of icteric hepatitis, hepatic fibrosis, non-alcoholic fatty liver disease and other liver diseases in clinical practices, however, the underlying mechanisms of YCWLP on HF is still unclear. In this study, ¹H NMR and MS-based metabolomics analysis along with body weight change, serum liver function indexes, serum liver fibrosis index and histopathological observations of liver were applied to evaluate the therapeutic effect of YCWLP on hepatic fibrosis and the mechanism associated with this. The results of the pharmacodynamics study show that YCWLP has a significant therapeutic effect on hepatic fibrosis. As for the metabolomics research, 7 metabolites in the plasma samples, 28 in the urine samples and 6 in the liver samples were significantly altered due to the protective effect of YCWLP on CCl₄-induced hepatic fibrosis. These endogenous metabolites are involved in amino acid metabolism, carbohydrate metabolism, glycerophospholipid metabolism and gut bacteria metabolism. These findings suggest that YCWLP could treat hepatic fibrosis by promoting urea circulation and reducing blood ammonia accumulation, improving carbohydrate metabolism and reducing oxidative stress, improving glycerophospholipid metabolism and protecting cell membrane, and regulating intestinal flora metabolism.

Application of Metabolomics in Diagnosis and Treatment of Chronic Liver Diseases

Chronic liver disease represents stepwise destruction of the liver parenchyma after chronic liver injury, which is often difficult to be diagnosed accurately. Thus, the development of specific biomarkers of chronic liver disease is important. Metabolomics is a powerful tool for biomarker exploration, which enables the exploration of disease pathogenesis or drug action mechanisms at the global metabolic level. The metabolomics workflow generally includes collection, preparation, and analysis of samples, and data processing and bioinformatics. A metabolomics study can simultaneously detect the dysfunctions in the glucose, lipid, amino-acid, and nucleotide metabolisms. Hence, it facilitates the obtaining of a better understanding of the pathogenesis of chronic liver disease and its diagnosis. Many effective drugs could reverse the change of comprehensive biochemical phenotypes induced by chronic liver disease. They can even potentially restore the normal metabolic signatures of patients. Increasingly more researchers have begun to apply metabolomics technologies to diagnose chronic liver disease and investigate the mechanism of action of effective drugs or the variations in drug responses. We are convinced that deepening the understanding of the metabolic alterations could extend their use as powerful biomarkers, promoting the more effective clinical diagnosis and treatment of chronic liver disease in the future.

SARS-CoV-2 Infection Dysregulates the Metabolomic and Lipidomic Profiles of Serum

COVID-19 is a systemic infection that exerts significant impact on the metabolism. Yet, there is little information on how SARS-CoV-2 affects metabolism. Using NMR spectroscopy, we measured the metabolomic and lipidomic serum profile from 263 (training cohort) + 135 (validation cohort) symptomatic patients hospitalized after positive PCR testing for SARS-CoV-2 infection. We also established the profiles of 280 persons collected before the coronavirus pandemic started. Principal-component analysis discriminated both cohorts, highlighting the impact that the infection has on overall metabolism. The lipidomic analysis unraveled a pathogenic redistribution of the lipoprotein particle size and composition to increase the atherosclerotic risk. In turn, metabolomic analysis reveals abnormally high levels of ketone bodies (acetoacetic acid, 3-hydroxybutyric acid, and acetone) and 2-hydroxybutyric acid, a readout of hepatic glutathione synthesis and marker of oxidative stress. Our results are consistent with a model in which SARS-CoV-2 infection induces liver damage associated with dyslipidemia and oxidative stress.

Metabolic Variations between Low-Grade and High-Grade Gliomas-Profiling by 1H NMR Spectroscopy

Altered cellular metabolism is one of the crucial hallmarks of glioma that deserves exploration, as the metabolites act as direct indicators of protein function and genetic variations. The current study focused on the metabolomic profiling of patients from whom glioma specimens were obtained for the identification of specific metabolites that could distinguish the low grade and high grade. In the current study, ¹H NMR spectroscopy was carried out and the data were analyzed by partial least-squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). Pathway analysis was done to associate characteristic metabolites with the grades of sample using MetaboAnalyst 4.0 software based on the KEGG metabolic pathways database. Distinctive metabolic profiles among low- and high-grade gliomas with top 15 characteristic metabolites that could discriminate these grades were identified on the basis of their VIP scores from the OPLS-DA model. The major altered metabolic pathways include choline, taurine and hypotaurine, glutamate/glutamine, glutathione, and phenyl alanine/tyrosine, which were found to be consistent with the particular grade of a sample. Our study clearly demonstrated a characteristic metabolic profile of individual grades of glioma, suggesting that an altered metabolism is consistent with the specific grades of glioma appreciation and could lead to the development novel treatment strategies.

1H NMR-Based Urine Metabolomics Reveals Signs of Enhanced Carbon and Nitrogen Recycling in Prostate Cancer

Prostate cancer is the second most common tumor and the fifth cause of cancer-related death among men worldwide. PC cells exhibit profound signaling and metabolic reprogramming that account for the acquisition of aggressive features. Although the metabolic understanding of this disease has increased in recent years, the analysis of such alterations through noninvasive methodologies in biofluids remains limited. Here, we used NMR-based metabolomics on a large cohort of urine samples (more than 650) from PC and benign prostate hyperplasia (BPH) patients to investigate the molecular basis of this disease. Multivariate analysis failed to distinguish between the two classes, highlighting the modest impact of prostate alterations on urine composition and the multifactorial nature of PC. However, univariate analysis of urine metabolites unveiled significant changes, discriminating PC from BPH. Metabolites with altered abundance in urine from PC patients revealed changes in pathways related to cancer biology, including glycolysis and the urea cycle. We found out that metabolites from such pathways were diminished in the urine from PC individuals, strongly supporting the notion that PC reduces nitrogen and carbon waste in order to maximize their usage in anabolic processes that support cancer cell growth.

Metabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy

In recent years, there has been a plethora of attempts to discover biomarkers that are more reliable than α-fetoprotein for the early prediction and prognosis of hepatocellular carcinoma (HCC). Efforts have involved such fields as genomics, transcriptomics, epigenetics, microRNA, exosomes, proteomics, glycoproteomics, and metabolomics. HCC arises against a background of inflammation, steatosis, and cirrhosis, due mainly to hepatic insults caused by alcohol abuse, hepatitis B and C virus infection, adiposity, and diabetes. Metabolomics offers an opportunity, without recourse to liver biopsy, to discover biomarkers for premalignant liver disease, thereby alerting the potential of impending HCC. We have reviewed metabolomic studies in alcoholic liver disease (ALD), cholestasis, fibrosis, cirrhosis, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH). Specificity was our major criterion in proposing clinical evaluation of indole-3-lactic acid, phenyllactic acid, N-lauroylglycine, decatrienoate, N-acetyltaurine for ALD, urinary sulfated bile acids for cholestasis, cervonoyl ethanolamide for fibrosis, 16α-hydroxyestrone for cirrhosis, and the pattern of acyl carnitines for NAFL and NASH. These examples derive from a large body of published metabolomic observations in various liver diseases in adults, adolescents, and children, together with animal models. Many other options have been tabulated. Metabolomic biomarkers for premalignant liver disease may help reduce the incidence of HCC.

Application of NMR metabolomics to search for human disease biomarkers in blood

Recently, nuclear magnetic resonance spectroscopy (NMR)-based metabolomics analysis and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The purpose of these efforts is to identify unique metabolite biomarkers in a specific human disease so as to (1) accurately predict and diagnose diseases, including separating distinct disease stages; (2) provide insights into underlying pathways in the pathogenesis and progression of the malady and (3) aid in disease treatment and evaluate the efficacy of drugs. In this review we discuss recent developments in the application of NMR-based metabolomics in searching disease biomarkers in human blood samples in the last 5 years.

Metabolic Signature of Hepatic Fibrosis: From Individual Pathways to Systems Biology

Hepatic fibrosis is a major cause of morbidity and mortality worldwide, as it ultimately leads to cirrhosis, which is estimated to affect up to 2% of the global population. Hepatic fibrosis is confirmed by liver biopsy, and the erroneous nature of this technique necessitates the search for noninvasive alternatives. However, current biomarker algorithms for hepatic fibrosis have many limitations. Given that the liver is the largest organ and a major metabolic hub in the body, probing the metabolic signature of hepatic fibrosis holds promise for the discovery of new markers and therapeutic targets. Regarding individual metabolic pathways, accumulating evidence shows that hepatic fibrosis leads to alterations in carbohydrate metabolism, as aerobic glycolysis is aggravated in activated hepatic stellate cells (HSCs) and the whole fibrotic liver; in amino acid metabolism, as Fischer’s ratio (branched-chain amino acids/aromatic amino acids) decreases in patients with hepatic fibrosis; and in lipid metabolism, as HSCs lose vitamin A-containing lipid droplets during transdifferentiation, and cirrhotic patients have decreased serum lipids. The current review also summarizes recent findings of metabolic alterations relevant to hepatic fibrosis based on systems biology approaches, including transcriptomics, proteomics, and metabolomics in vitro, in animal models and in humans.

NMR-based newborn urine screening for optimized detection of inherited errors of metabolism

Inborn errors of metabolism (IEMs) are rare diseases produced by the accumulation of abnormal amounts of metabolites, toxic to the newborn. When not detected on time, they can lead to irreversible physiological and psychological sequels or even demise. Metabolomics has emerged as an efficient and powerful tool for IEM detection in newborns, children, and adults with late onset. In here, we screened urine samples from a large set of neonates (470 individuals) from a homogeneous population (Basque Country), for the identification of congenital metabolic diseases using NMR spectroscopy. Absolute quantification allowed to derive a probability function for up to 66 metabolites that adequately describes their normal concentration ranges in newborns from the Basque Country. The absence of another 84 metabolites, considered abnormal, was routinely verified in the healthy newborn population and confirmed for all but 2 samples, of which one showed toxic concentrations of metabolites associated to ketosis and the other one a high trimethylamine concentration that strongly suggested an episode of trimethylaminuria. Thus, a non-invasive and readily accessible urine sample contains enough information to assess the potential existence of a substantial number (>70) of IEMs in newborns, using a single, automated and standardized ¹H- NMR-based analysis.

Metabolomic-Based Methods in Diagnosis and Monitoring Infection Progression

A robust biomarker screening and validation is crucial for overcoming the current limits in the clinical management of infectious diseases. In this chapter, a general workflow for metabolomics is summarized. Subsequently, an overview of the major contributions of this omics science to the field of biomarkers of infectious diseases is discussed. Different approaches using a variety of analytical platforms can be distinguished to unveil the key metabolites for the diagnosis, prognosis, response to treatment and susceptibility for infectious diseases. To allow the implementation of such biomarkers into the clinics, the performance of large-scale studies employing solid validation criteria becomes essential. Focusing on the etiological agents and after an extensive review of the field, we present a comprehensive revision of the main metabolic biomarkers of viral, bacterial, fungal, and parasitic diseases. Finally, we discussed several articles which show the strongest validation criteria. Following these research avenues, precious clinical resources will be revealed, allowing for reduced misdiagnosis, more efficient therapies, and affordable costs, ultimately leading to a better patient management.

The metabolic fingerprints of HCV and HBV infections studied by Nuclear Magnetic Resonance Spectroscopy

Few studies are available on metabolic changes in liver injuries and this is the first metabolomic study evaluating a group of HCV-positive patients, before and after viral eradication via DAA IFN-free regimens, using ¹H-NMR to characterize and compare their serum fingerprints to naïve HBV-patients and healthy donors. The investigation clearly shows differences in the metabolomic profile of HCV patients before and after effective DAA treatment. Significant changes in metabolites levels in patients undergoing therapy suggest alterations in several metabolic pathways. It has been shown that ¹H-NMR fingerprinting approach is an optimal technique in predicting the specific infection and the healthy status of studied subjects (Monte-Carlo cross validated accuracies: 86% in the HCV vs HBV model, 98.7% in the HCV vs HC model). Metabolite data collected support the hypothesis that the HCV virus induces glycolysis over oxidative phosphorylation in a similar manner to the Warburg effect in cancer, moreover our results have demonstrated a different action of the two viruses on cellular metabolism, corroborating the hypothesis that the metabolic perturbation on patients could be attributed to a direct role in viral infection. This metabolomic study has revealed some alteration in metabolites for the first time (2-oxoglutarate and 3-hydroxybutrate) concerning the HCV-infection model that could explain several extrahepatic manifestations associated with such an infection.

Metabolic Characterization of Peripheral Host Responses to Drainage-Resistant Klebsiella pneumoniae Liver Abscesses by Serum 1H-NMR Spectroscopy

Purpose: To explore the metabolic characterization of host responses to drainage-resistant Klebsiella pneumoniae liver abscesses (DRKPLAs) with serum 1H-nuclear magnetic resonance (NMR) spectroscopy.

Materials and Methods: The hospital records of all patients with a diagnosis of a liver abscess between June 2015 and December 2016 were retrieved from an electronic hospital database. Eighty-six patients with Klebsiella pneumoniae (K. pneumoniae) liver abscesses who underwent percutaneous drainage were identified. Twenty patients with confirmed DRKPLAs were studied. Moreover, we identified 20 consecutive patients with drainage-sensitive Klebsiella pneumoniae liver abscesses (DSKPLAs) as controls. Serum samples from the two groups were analyzed with 1H NMR spectroscopy. Partial least squares discriminant analysis (PLS-DA) was used to perform 1H NMR metabolic profiling. Metabolites were identified using the Human Metabolome Database, and pathway analysis was performed with MetaboAnalyst 3.0.

Results: The PLS-DA test was able to discriminate between the two groups. Five key metabolites that contributed to their discrimination were identified. Glucose, lactate, and 3-hydroxybutyrate were found to be upregulated in DRKPLAs, whereas glutamine and alanine were downregulated compared with the DSKPLAs. Pathway analysis indicated that amino acid metabolisms were significantly different between the DRKPLAs and the DSKPLAs. The D-glutamine and D-glutamate metabolisms exhibited the greatest influences.

Conclusions: The five key metabolites identified in our study may be potential targets for guiding novel therapeutics of DRKPLAs and are worthy of additional investigation.

Metabolomics: From liver chiromancy to personalized precision medicine in advanced chronic liver disease

Currently there is a lack of accurate biomarkers for diagnosis and prognosis in advanced liver diseases. Either the occurrence of first decompensation, or diagnosis of acute on chronic liver failure, severe alcoholic hepatitis, or hepatocellular carcinoma (HCC), none of the available biomarkers are satisfactory. Metabolomics is the newest of omics, being much closer than the others to the actual phenotype and pathologic changes that characterizes a certain condition. It deals with a much wider spectrum of low molecular weight bio-compounds providing a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication and therapy. Until now metabolomics was applied in a wide spectrum of liver conditions, but the findings were contradictory. This review proposes a synthesis of the existing evidences of metabolomics use in advanced chronic liver diseases, decompensated liver cirrhosis, severe alcoholic hepatitis and HCC.

Proton nuclear magnetic resonance-based metabonomic models for non-invasive diagnosis of liver fibrosis in chronic hepatitis C: Optimizing the classification of intermediate fibrosis

AIM

To develop metabonomic models (MMs), using ¹H nuclear magnetic resonance (NMR) spectra of serum, to predict significant liver fibrosis (SF: Metavir ≥ F2), advanced liver fibrosis (AF: METAVIR ≥ F3) and cirrhosis (C: METAVIR = F4 or clinical cirrhosis) in chronic hepatitis C (CHC) patients. Additionally, to compare the accuracy of the MMs with the aspartate aminotransferase to platelet ratio index (APRI) and fibrosis index based on four factors (FIB-4).

METHODS

Sixty-nine patients who had undergone biopsy in the previous 12 mo or had clinical cirrhosis were included. The presence of any other liver disease was a criterion for exclusion. The MMs, constructed using partial least squares discriminant analysis and linear discriminant analysis formalisms, were tested by cross-validation, considering SF, AF and C.

RESULTS

Results showed that forty-two patients (61%) presented SF, 28 (40%) AF and 18 (26%) C. The MMs showed sensitivity and specificity of 97.6% and 92.6% to predict SF; 96.4% and 95.1% to predict AF; and 100% and 98.0% to predict C. Besides that, the MMs correctly classified all 27 (39.7%) and 25 (38.8%) patients with intermediate values of APRI and FIB-4, respectively.

CONCLUSION

The metabonomic strategy performed excellently in predicting significant and advanced liver fibrosis in CHC patients, including those in the gray zone of APRI and FIB-4, which may contribute to reducing the need for these patients to undergo liver biopsy.

Robust Regression Analysis of GCMS Data Reveals Differential Rewiring of Metabolic Networks in Hepatitis B and C Patients

About one in 15 of the world’s population is chronically infected with either hepatitis virus B (HBV) or C (HCV), with enormous public health consequences. The metabolic alterations caused by these infections have never been directly compared and contrasted. We investigated groups of HBV-positive, HCV-positive, and uninfected healthy controls using gas chromatography-mass spectrometry analyses of their plasma and urine. A robust regression analysis of the metabolite data was conducted to reveal correlations between metabolite pairs. Ten metabolite correlations appeared for HBV plasma and urine, with 18 for HCV plasma and urine, none of which were present in the controls. Metabolic perturbation networks were constructed, which permitted a differential view of the HBV- and HCV-infected liver. HBV hepatitis was consistent with enhanced glucose uptake, glycolysis, and pentose phosphate pathway metabolism, the latter using xylitol and producing threonic acid, which may also be imported by glucose transporters. HCV hepatitis was consistent with impaired glucose uptake, glycolysis, and pentose phosphate pathway metabolism, with the tricarboxylic acid pathway fueled by branched-chain amino acids feeding gluconeogenesis and the hepatocellular loss of glucose, which most probably contributed to hyperglycemia. It is concluded that robust regression analyses can uncover metabolic rewiring in disease states.

Role of Gut Microbiota on Cardio-Metabolic Parameters and Immunity in Coronary Artery Disease Patients with and without Type-2 Diabetes Mellitus

Gut microbiota composition has been reported as a factor linking host metabolism with the development of cardiovascular diseases (CVD) and intestinal immunity. Such gut microbiota has been shown to aggravate CVD by contributing to the production of trimethylamine N-oxide (TMAO), which is a pro-atherogenic compound. Treg cells expressing the transcription factor Forkhead box protein P3 (FoxP3) play an essential role in the regulation of immune responses to commensal microbiota and have an atheroprotective role. However, the aim of this study was to analyze the role of gut microbiota on cardio-metabolic parameters and immunity in coronary artery disease (CAD) patients with and without type-2 diabetes mellitus (DM2). The study included 16 coronary CAD-DM2 patients, and 16 age, sex, and BMI matched CAD patients without DM2 (CAD-NDM2). Fecal bacterial DNA was extracted and analyzed by sequencing in a GS Junior 454 platform followed by a bioinformatic analysis (QIIME and PICRUSt). The present study indicated that the diversity and composition of gut microbiota were different between the CAD-DM2 and CAD-NDM2 patients. The abundance of phylum Bacteroidetes was lower, whereas the phyla Firmicutes and Proteobacteria were higher in CAD-DM2 patients than those in the CAD-NDM2 group. CAD-DM2 patients had significantly less beneficial or commensal bacteria (such as Faecalibacterium prausnitzii and Bacteroides fragilis) and more opportunistic pathogens (such as Enterobacteriaceae, Streptococcus, and Desulfovibrio). Additionally, CAD-DM2 patients had significantly higher levels of plasma zonulin, TMAO, and IL-1B and significantly lower levels of IL-10 and FOXP3 mRNA expression than CAD-NDM2. Moreover, in the CAD-MD2 group, the increase in Enterobacteriaceae and the decrease in Faecalibacterium prausnitzii were significantly associated with the increase in serum TMAO levels, while the decrease in the abundance of Bacteroides fragilis was associated with the reduction in the FOXP3 mRNA expression, implicated in the development and function of Treg cells. These results suggest that the presence of DM2 is related to an impaired regulation of the immune system in CAD patients, mediated in part by the gut microbiota composition and functionality and the production and effects of their gut microbiota derived molecules.

Metabolic Biomarkers and Neurodegeneration: A Pathway Enrichment Analysis of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) lack robust diagnostics and prognostic biomarkers. Metabolomics is a postgenomics field that offers fresh insights for biomarkers of common complex as well as rare diseases. Using data on metabolite-disease associations published in the previous decade (2006-2016) in PubMed, ScienceDirect, Scopus, and Web of Science, we identified 101 metabolites as putative biomarkers for these three neurodegenerative diseases. Notably, uric acid, choline, creatine, L-glutamine, alanine, creatinine, and N-acetyl-L-aspartate were the shared metabolite signatures among the three diseases. The disease-metabolite-pathway associations pointed out the importance of membrane transport (through ATP binding cassette transporters), particularly of arginine and proline amino acids in all three neurodegenerative diseases. When disease-specific and common metabolic pathways were queried by using the pathway enrichment analyses, we found that alanine, aspartate, glutamate, and purine metabolism might act as alternative pathways to overcome inadequate glucose supply and energy crisis in neurodegeneration. These observations underscore the importance of metabolite-based biomarker research in deciphering the elusive pathophysiology of neurodegenerative diseases. Future research investments in metabolomics of complex diseases might provide new insights on AD, PD, and ALS that continue to place a significant burden on global health.

Poly-pharmacokinetic Study of a Multicomponent Herbal Medicine in Healthy Chinese Volunteers

The advent of mass spectrometry-based analytical technologies coupled with multivariate statistical methods offer tremendous new opportunities for understanding the pharmacokinetics (PKs) of multicomponent herbal medicines (HMs). We recently proposed a poly-PK strategy to characterize the concentration-time profile and the metabolic response profile of multicomponent HMs using an integrated phytochemical and metabolomics approach. Here, we provided the first example of the poly-PK strategy, in which we simultaneously characterized the PK as well as the metabolic response profiles of a Chinese HM, Huangqi decoction (HQD, consisting of Radix Astragali and Radix Glycyrrhizae), in healthy Chinese volunteers. Using the poly-PK approach, we identified 56 HQD-derived compounds and 292 biotransformed HQD metabolites in human plasma. Additionally, we acquired the concentration-time profiles of these plasma HQD metabolites and correlated them with a plasma metabolomics profile consisting of 166 human endogenous metabolites that were significantly altered in response to HQD intervention.

A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients

Liver fibrosis must be evaluated in patients with hepatitis C virus (HCV) after liver transplantation because its severity affects their prognosis and the recurrence of HCV. Since invasive biopsy is still the gold standard to identify patients at risk of graft loss from rapid fibrosis progression, it becomes crucial the development of new accurate, non-invasive methods that allow repetitive examination of the patients. Therefore, we have developed a non-invasive, accurate model to distinguish those patients with different liver fibrosis stages. Two hundred and three patients with HCV were histologically classified (METAVIR) into five categories of fibrosis one year after liver transplantation. In this cross-sectional study, patients at fibrosis stages F0-F1 (n = 134) were categorised as “slow fibrosers” and F2-F4 (n = 69) as “rapid fibrosers”. Chloroform/methanol serum extracts were analysed by reverse ultra-high performance liquid chromatography coupled to mass spectrometry. A diagnostic model was built through linear discriminant analyses. An algorithm consisting of two sphingomyelins and two phosphatidylcholines accurately classifies rapid and slow fibrosers after transplantation. The proposed model yielded an AUROC of 0.92, 71% sensitivity, 85% specificity, and 84% accuracy. Moreover, specific bile acids and sphingomyelins increased notably along with liver fibrosis severity, differentiating between rapid and slow fibrosers.

Diagnosis of coinfection by schistosomiasis and viral hepatitis B or C using 1H NMR-based metabonomics

BACKGROUND

Diagnosis of liver involvement due to schistosomiasis in asymptomatic patients from endemic areas previously diagnosed with chronic hepatitis B (HBV) or C (HCV) and periportal fibrosis is challenging. H-1 Nuclear Magnetic Resonance (NMR)-based metabonomics strategy is a powerful tool for providing a profile of endogenous metabolites of low molecular weight in biofluids in a non-invasive way. The aim of this study was to diagnose periportal fibrosis due to schistosomiasis mansoni in patients with chronic HBV or HCV infection through NMR-based metabonomics models.

METHODOLOGY/PRINCIPAL FINDINGS

The study included 40 patients divided into two groups: (i) 18 coinfected patients with schistosomiasis mansoni and HBV or HCV; and (ii) 22 HBV or HCV monoinfected patients. The serum samples were analyzed through H-1 NMR spectroscopy and the models were based on Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA). Ultrasonography examination was used to ascertain the diagnosis of periportal fibrosis. Exploratory analysis showed a clear separation between coinfected and monoinfected samples. The supervised model built from PLS-DA showed accuracy, R2 and Q2 values equal to 100%, 98.1% and 97.5%, respectively. According to the variable importance in the projection plot, lactate serum levels were higher in the coinfected group, while the signals attributed to HDL serum cholesterol were more intense in the monoinfected group.

CONCLUSIONS/SIGNIFICANCE

The metabonomics models constructed in this study are promising as an alternative tool for diagnosis of periportal fibrosis by schistosomiasis in patients with chronic HBV or HCV infection from endemic areas for Schistosoma mansoni.

Metabolomics: Strategies to Define the Role of Metabolism in Virus Infection and Pathogenesis

Metabolomics is an analytical profiling technique for measuring and comparing large numbers of metabolites present in biological samples. Combining high-throughput analytical chemistry and multivariate data analysis, metabolomics offers a window on metabolic mechanisms. Because they intimately utilize and often rewire host metabolism, viruses are an excellent choice to study by metabolomics techniques. Studies of the effects of viruses on metabolism during replication in vitro and infection in animal models or human subjects have provided novel insights into these networks and provided new targets for therapy and biomarker development. Identifying the common metabolic pathways utilized by viruses has the potential to reveal those that can be targeted by broad-spectrum antiviral and vaccine approaches.

Nuclear magnetic resonance metabolomics and human liver diseases: The principles and evidence associated with protein and carbohydrate metabolism

During the last decade, metabolomics has become widely used in the field of human diseases. Numerous studies have demonstrated that this is a powerful technique for improving the understanding, diagnosis and management of various types of liver disease, such as acute and chronic liver diseases, and liver transplantation. Nuclear magnetic resonance (NMR) spectroscopy is one of the two most commonly applied methods for metabolomics. The aim of the present review was to investigate the results from recent key publications focusing on aspects of protein and carbohydrate metabolism. The review includes existing procedures, which are currently used for NMR data acquisition and statistical analysis. In addition, notable results obtained by these studies on protein and carbohydrate metabolism concerning human liver diseases are presented.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

Multi-dimensional Roles of Ketone Bodies in Fuel Metabolism, Signaling, and Therapeutics

Ketone body metabolism is a central node in physiological homeostasis. In this review, we discuss how ketones serve discrete fine-tuning metabolic roles that optimize organ and organism performance in varying nutrient states and protect from inflammation and injury in multiple organ systems. Traditionally viewed as metabolic substrates enlisted only in carbohydrate restriction, observations underscore the importance of ketone bodies as vital metabolic and signaling mediators when carbohydrates are abundant. Complementing a repertoire of known therapeutic options for diseases of the nervous system, prospective roles for ketone bodies in cancer have arisen, as have intriguing protective roles in heart and liver, opening therapeutic options in obesity-related and cardiovascular disease. Controversies in ketone metabolism and signaling are discussed to reconcile classical dogma with contemporary observations.

Metabonomics Research Progress on Liver Diseases

Metabolomics as the new omics technique develops after genomics, transcriptomics, and proteomics and has rapid development at present. Liver diseases are worldwide public health problems. In China, chronic hepatitis B and its secondary diseases are the common liver diseases. They can be diagnosed by the combination of history, virology, liver function, and medical imaging. However, some patients seldom have relevant physical examination, so the diagnosis may be delayed. Many other liver diseases, such as drug-induced liver injury (DILI), alcoholic liver disease (ALD) and nonalcoholic fatty liver disease (NAFLD), and autoimmune liver diseases, still do not have definite diagnostic markers; the diagnosis consists of history, medical imaging, and the relevant score. As a result, the clinical work becomes very complex. So it has broad prospects to explore the specific and sensitive biomarkers of liver diseases with metabolomics. In this paper, there are several summaries which are related to the current research progress and application of metabolomics on biomarkers of liver diseases.

Limiting the access to direct-acting antivirals against HCV: an ethical dilemma

Hepatitis C virus (HCV) infection affects about 200 million people worldwide and represents a leading cause of liver-related mortality. Eradication of HCV infection, achieved mainly through direct-acting antivirals (DAA), results in a decrease of mortality and an improvement of quality of life. These drugs have a maximal efficacy and an optimal tolerability. However, their high cost precludes a universal access even in wealthy countries. Areas covered: This article deals with the policies adopted for the use of the new anti-HCV drugs, especially in Europe and most of all in Italy, supposedly the developed country with the highest HCV prevalence. The literature search was performed using Pubmed and Web of Science. Moreover, national regulatory institutional websites were consulted. Expert commentary: The current policy of limitation to the access of the DAA presents a series of ethical issues that makes it non-applicable. A 'treat-all' strategy should resolve all ethical dilemmas, by virtue of the wide benefits of anti-HCV treatment not only for the advanced stage of infection, but also for the initial stages. A reduction in price of the drugs is the actual condition to achieve such a change.

1H NMR-based serum metabolomics reveals erythromycin-induced liver toxicity in albino Wistar rats

Introduction:

Erythromycin (ERY) is known to induce hepatic toxicity which mimics other liver diseases. Thus, ERY is often used to produce experimental models of drug-induced liver-toxicity. The serum metabolic profiles can be used to evaluate the liver-toxicity and to further improve the understanding of underlying mechanism.

Objective:

To establish the serum metabolic patterns of Erythromycin induced hepatotoxicity in albino wistar rats using ¹H NMR based serum metabolomics.

Experimental:

Fourteen male rats were randomly divided into two groups (n = 7 in each group): control and ERY treated. After 28 days of intervention, the metabolic profiles of sera obtained from ERY and control groups were analyzed using high-resolution 1D ¹H CPMG and diffusion-edited nuclear magnetic resonance (NMR) spectra. The histopathological and SEM examinations were employed to evaluate the liver toxicity in ERY treated group.

Results:

The serum metabolic profiles of control and ERY treated rats were compared using multivariate statistical analysis and the metabolic patterns specific to ERY-induced liver toxicity were established. The toxic response of ERY was characterized with: (a) increased serum levels of Glucose, glutamine, dimethylamine, malonate, choline, phosphocholine and phospholipids and (b) decreased levels of isoleucine, leucine, valine, alanine, glutamate, citrate, glycerol, lactate, threonine, circulating lipoproteins, N-acetyl glycoproteins, and poly-unsaturated lipids. These metabolic alterations were found to be associated with (a) decreased TCA cycle activity and enhanced fatty acid oxidation, (b) dysfunction of lipid and amino acid metabolism and (c) oxidative stress.

Conclusion and Recommendations:

Erythromycin is often used to produce experimental models of liver toxicity; therefore, the established NMR-based metabolic patterns will form the basis for future studies aiming to evaluate the efficacy of anti-hepatotoxic agents or the hepatotoxicity of new drug-formulations.