RESUMEN
The prevalence of nonalcoholic fatty liver disease (NAFLD) has increased with the incidence of obesity; however, the underlying mechanisms are unknown. In this study, high-resolution metabolomics (HRM) along with transcriptomics were applied on animal models to draw a mechanistic insight of NAFLD. Wild type (WT) and catalase knockout (CKO) mice were fed with normal fat diet (NFD) or high fat diet (HFD) to identify the changes in metabolic and transcriptomic profiles caused by catalase gene deletion in correspondence with HFD. Integrated omics analysis revealed that cholic acid and 3β, 7α-dihydroxy-5-cholestenoate along with cyp7b1 gene involved in primary bile acid biosynthesis were strongly affected by HFD. The analysis also showed that CKO significantly changed all-trans-5,6-epoxy-retinoic acid or all-trans-4-hydroxy-retinoic acid and all-trans-4-oxo-retinoic acid along with cyp3a41b gene in retinol metabolism, and α/γ-linolenic acid, eicosapentaenoic acid and thromboxane A2 along with ptgs1 and tbxas1 genes in linolenic acid metabolism. Our results suggest that dysregulated primary bile acid biosynthesis may contribute to liver steatohepatitis, while up-regulated retinol metabolism and linolenic acid metabolism may have contributed to oxidative stress and inflammatory phenomena in our NAFLD model created using CKO mice fed with HFD.
RESUMEN
Objective: This study attempted to identify altered metabolism and pathways related to non-Hodgkin's lymphoma [NHL] and myeloma patients
Materials and Methods: In this retrospective study, we collected plasma samples from 11 patients-6 healthy controls with no evidence of any blood cancers and 5 patients with either multiple myeloma [n=3] or NHL [n=2] during the preliminary study period. Samples were analyzed using quadrupole time-of-flight liquid chromatography mass spectrometry [LC-MS]. Significant features generated after statistical analyses were used for metabolomics and pathway analysis
Results: Data after false discovery rate [FDR] adjustment at q=0.05 of features showed 136 for positive and 350 significant features for negative ionization mode in NHL patients as well as 262 for positive and 98 features for negative ionization mode in myeloma patients. Kyoto Encyclopedia of Genes and Genomes [KEGG] pathway analysis determined that pathways such as steroid hormone biosynthesis, ABC transporters, and arginine and proline metabolism were affected in NHL patients. In myeloma patients, pyrimidine metabolism, carbon metabolism, and bile secretion pathways were potentially affected by the disease
Conclusion: The results have shown tremendous differences in the metabolites of healthy individuals compared to myeloma and lymphoma patients. Validation through quantitative metabolomics is encouraged, especially for the metabolites with significantly expression in blood cancer patients