Rodent models and metabolomics in non-alcoholic fatty liver disease: What can we learn?

Non-alcoholic fatty liver disease (NAFLD) prevalence has increased drastically in recent decades, affecting up to 25% of the world’s population. NAFLD is a spectrum of different diseases that starts with asymptomatic steatosis and continues with development of an inflammatory response called steatohepatitis, which can progress to fibrosis. Several molecular and metabolic changes are required for the hepatocyte to finally vary its function; hence a “multiple hit” hypothesis seems a more accurate proposal. Previous studies and current knowledge suggest that in most cases, NAFLD initiates and progresses through most of nine hallmarks of the disease, although the triggers and mechanisms for these can vary widely. The use of animal models remains crucial for understanding the disease and for developing tools based on biological knowledge. Among certain requirements to be met, a good model must imitate certain aspects of the human NAFLD disorder, be reliable and reproducible, have low mortality, and be compatible with a simple and feasible method. Metabolism studies in these models provides a direct reflection of the workings of the cell and may be a useful approach to better understand the initiation and progression of the disease. Metabolomics seems a valid tool for studying metabolic pathways and crosstalk between organs affected in animal models of NAFLD and for the discovery and validation of relevant biomarkers with biological understanding. In this review, we provide a brief introduction to NAFLD hallmarks, the five groups of animal models available for studying NAFLD and the potential role of metabolomics in the study of experimental NAFLD.

The Serum Metabolic Biomarkers in Early Diagnosis and Risk Stratification of Acute Coronary Syndrome

Despite advances in the treatment of coronary diseases, acute coronary syndrome (ACS) remains the leading cause of death worldwide. ACS is associated with metabolic abnormalities of lipid oxidation stress. In this study, based on liquid chromatograph mass spectrometry technique, we conducted the metabolic profiling analysis of serum samples from stable plaques (SPs) and vulnerable plaques (VPs) in ACS patients for exploring the potential biomarkers of plaque stability. The results showed that four differential metabolites were identified between the SPs and VPs, including betaine, acetylcarnitine, 1-heptadecanoyl-sn-glycero-3-phosphocholine, and isoundecylic acid. Meanwhile, the diagnostic model was identified using stepwise logistic regression and internally validated with 10-fold cross-validation. We analyzed the correlations between serum metabolic perturbations and plaque stability, and the serum betaine and ejection fraction-based model was established with a good diagnostic efficacy [area under the curve (AUC) = 0.808, sensitivity = 70.6%, and specificity = 80.0%]. In summary, we firstly illustrate the comprehensive serum metabolic profiles in ACS patients, suggesting that the combined model of serum betaine and ejection fraction seems to be used as the potential diagnostic biomarker for the vulnerability of plaque stability.

Serum Metabolomics Reveals Personalized Metabolic Patterns for Macular Neovascular Disease Patient Stratification

The macular neovascular disease is a group disorder with complex pathogenesis of neovascularization for vision impairment and irreversible blindness, posing great challenges to precise diagnosis and management. We prospectively recruited participants with age-related macular degeneration (AMD), polypoidal choroidal vasculopathy (PCV), and pathological myopia (PM) and compared with cataract patients without fundus diseases as a control group. The serum metabolome was profiled by gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS) analysis. Multivariate statistical methods as well as data mining were performed for interpretation of macular neovascularization. A total of 446 participants with macular neovascularization and 138 cataract subjects as the control group were enrolled in this study. By employing GC-TOFMS, 131 metabolites were identified and 33 differentiating metabolites were highlighted in patients with macular neovascularization. For differential diagnosis, three panels of specific metabolomics-based biomarkers provided areas under the curve of 0.967, 0.938, and 0.877 in the discovery phase (n = 328) and predictive values of 87.3%, 79%, and 85.7% in the test phase (n = 256). Personalized pathway dysregulation scores measurement using Lilikoi package in R language revealed the pentose phosphate pathway and mitochondrial electron transport chain as the most important pathways in AMD; purine metabolism and glycolysis were identified as the major disturbed pathways in PCV, while the altered thiamine metabolism and purine metabolism may contribute to PM phenotypes. Serum metabolomics are powerful for characterizing metabolic disturbances of the macular neovascular disease. Differences in metabolic pathways may reflect an underlying macular neovascular disease and serve as therapeutic targets for macular neovascular treatment.

Metabolomic profile of diabetic retinopathy: a GC-TOFMS-based approach using vitreous and aqueous humor

AIM

To identify the potential metabolite markers in diabetic retinopathy (DR) by using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS).

METHODS

GC-TOFMS spectra were acquired from vitreous and aqueous humor (AH) samples of patients with DR and non-diabetic participants. Comparative analysis was used to elucidate the distinct metabolites of DR. Metabolic pathway was employed to explicate the metabolic reprogramming pathways involved in DR. Logistic regression and receiver-operating characteristic analyses were carried out to select and validate the biomarker metabolites and establish a therapeutic model.

RESULTS

Comparative analysis showed a clear separation between disease and control groups. Eight differentiating metabolites from AH and 15 differentiating metabolites from vitreous were highlighted. Out of these 23 metabolites, 11 novel metabolites have not been detected previously. Pathway analysis identified nine pathways (three in AH and six in vitreous) as the major disturbed pathways associated with DR. The abnormal of gluconeogenesis, ascorbate-aldarate metabolism, valine-leucine-isoleucine biosynthesis, and arginine-proline metabolism might weigh the most in the development of DR. The AUC of the logistic regression model established by D-2,3-Dihydroxypropanoic acid, isocitric acid, fructose 6-phosphate, and L-Lactic acid in AH was 0.965. The AUC established by pyroglutamic acid and pyruvic acid in vitreous was 0.951.

CONCLUSIONS

These findings have expanded our understanding of identified metabolites and revealed for the first time some novel metabolites in DR. These results may provide useful information to explore the mechanism and may eventually allow the development of metabolic biomarkers for prognosis and novel therapeutic strategies for the management of DR.

Metabolomics study of the therapeutic mechanism of a Chinese herbal formula on collagen-induced arthritis mice

Wenjinghuoluo (WJHL) prescription, the typical rheumatoid arthritis (RA) treatment compound in traditional Chinese medicine, shows favorable efficacy. The precise mechanism of WJHL on RA therapy is yet to be elucidated. This study aimed to determine the metabolic biomarkers in the early onset of RA and evaluate the regulation effect of WJHL on metabolite levels. Multivariate statistical analysis identified 93 biomarkers by precise MS/MS. These biomarkers played an important role in the regulation of key metabolic pathways associated with collagen-induced arthritis (CIA). A total of 68 biomarkers were related to the treatment of CIA by WJHL therapy. In addition, pathway analysis results showed six and three significant related pathways according to corresponding differential metabolites before and after WJHL therapy. Finally, disease and function prediction of ingenuity pathway analysis indicated that lipid metabolism, small molecule biochemistry, and carbohydrate metabolism were associated functions of WJHL therapy on CIA. Furthermore, top analysis-ready molecules of up-regulated thiamine and down-regulated arachidonic acid maybe the most related metabolites of WJHL therapy on CIA. The present work indicates that a metabolomics platform provides a new insight into understanding the mechanisms of action of natural medicines, such as WJHL.

Wenjinghuoluo (WJHL) prescription, the typical rheumatoid arthritis (RA) treatment compound in traditional Chinese medicine, shows favorable efficacy.