Metabolic profile of liver damage in non-cirrhotic virus C and autoimmune hepatitis: A proton decoupled 31P-MRS study

Phospholipids and their metabolites as diagnostic biomarkers of human diseases

Phospholipids that occur predominantly in the plasma membrane of mammalian cells are phosphatidylcholine (PC), phosphatidylserine (PS), phosphatidylethanolamine (PE), sphingomyelin (SM), and phosphatidylinositol (or phosphoinositide; PI). These membrane phospholipids are a promising source of disease-related biomarkers. Phospholipids and their metabolites are altered by the type of disease or disease progression. Metabolomics has shown that increased or decreased levels of altered phospholipids and their metabolites can be useful indicators for the diagnosis of various human diseases. In this review, we discuss the utility of the five major membrane phospholipids (PC, PS, PE, and SM, and PI) and their metabolites as diagnostic biomarkers of human diseases.

TLR3\TLR7 as Differentially Expressed Markers Among Viral, Nonviral, and Autoimmune Diseases in Egyptian Patients

Toll-like receptors (TLRs) represent the immune link between the innate and the adaptive immune signals against various pathogens. This study aimed to evaluate the TLRs3 and 7 as immune-markers in differentiating between hepatitis C virus (HCV)-infected and -uninfected patients. Also, the use of the TLR3 and TLR7 as immune markers was compared with the prevalent bio and immune markers for autoimmune diseases in HCV-infected or -uninfected patients. The levels of GPT, GOT, B cell activated factors, tumor necrosis factor-alpha (TNF-α), and interleukin (IL)-10 were measured in plasma, while the levels of TLR3 and TLR7 were quantified in lysates of peripheral blood mononuclear cells from healthy donors, HCV-infected patients, nonalcoholic fatty liver (NAFL) patients without autoimmune diseases and with autoimmune diseases (HCV-infected patients with autoimmune diseases [HCV+auto], nonalcoholic fatty liver patients with autoimmune diseases [NAFL+auto]), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE) patients. The relative expression of TLR3, TLR7, TNF, and IL-10 in cell lysates was assessed against glyceraldehyde 3-phosphate dehydrogenase (GAPDH) by quantitative real time-polymerase chain reaction (qRT-PCR). Results showed that TLRs 3 and 7 levels were significantly higher in SLE, RA, HCV, HCV+auto, and the NAFL patients compared to the normal control. The cell lysates from SLE patients expressed TLR3 at relatively significantly higher mRNA levels compared to normal subjects or other patient groups. The NAFL+auto patients expressed TLR7 at relatively significantly high mRNA levels compared to normal subjects or other patients. The RA patients expressed TLR7 at relatively significantly higher mRNA levels when compared to HCV, HCV+auto, and NAFL+auto patients. Conclusions: At the protein level, TLR7 can differentiate between HCV and NAFL patients. In addition, both TLRs3 and 7 can serve as potent markers in differentiating between NAFL and NAFL+auto.

Metabolomic profiles of breath odor compounds for prognostic prediction in patients with acute-on-chronic liver failure: A pilot study

AIM

The aim of this study was to use a metabonomics approach to identify potential biomarkers of exhaled breath condensate (EBC) for predicting the prognosis of acute-on-chronic liver failure (ACLF).

METHODS

Using liquid chromatography mass spectrometry, EBC metabolites of ACLF patients surviving without liver transplantation (n = 57) and those with worse outcomes (n = 45), and controls (n = 15) were profiled from a specialized liver disease center in Beijing. The metabolites were used to identify candidate biomarkers, and the predicted performance of potential biomarkers was tested.

RESULTS

Forty-one metabolites, involving glycerophospholipid metabolism, sphingolipid metabolism, arachidonic acid metabolism, and amino acid metabolism, as candidate biomarkers for discriminating the different outcomes of ACLF were selected. A prognostic model was constructed by a panel of four metabolites including phosphatidylinositol [20:4(5Z,8Z,11Z,14Z)/13:0], phosphatidyl ethanolamine (12:0/22:0), L-metanephrine and ethylbenzene, which could predict the worse prognosis in ACLF patients with sensitivity (84.4%) and specificity (89.5%) (area under the receiver operating characteristic curve [AUC] = 0.859, 95% confidence interval [CI] = 0.787-0.931). Compared with Model for End-Stage Liver Disease (MELD) score (AUC = 0.639, 95% CI = 0.526-0.753) and MELD-sodium (MELD-Na) score (AUC = 0.692, 95% CI = 0.582-0.803), EBC-associated metabolite signature model could better predict worse outcomes in patients with ACLF (p < 0.05). Using the MELD-Na score and EBC metabolite signatures, a decision tree model was built for predicting the prognosis of ACLF identified on logistic regression analyses (AUC = 0.906, 95% CI = 0.846-0.965).

CONCLUSION

EBC metabolic signatures show promise as potential biomarkers for predicting worse prognosis of ACLF.