Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0015695 (fatty liver)
 13,941 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Emerging scientific evidence suggests that increases in body iron represent a risk factor for the development of metabolic syndrome and diabetes. The aim of our study was to determine the body iron stores in patients with metabolic syndrome, and to evaluate the potential relationship of iron overload with specific features of the metabolic syndrome, such as fatty liver. A total of 490 individuals were enrolled. The diagnosis of metabolic syndrome was based on National Cholesterol Education Program-Adult Treatment Panel III (ATPIII) criteria. The metabolic syndrome group was consisted of 185 patients having three or more criteria, whereas individuals with less than three criteria constituted the control group. Metabolic syndrome patients displayed higher ferritin concentration as compared to control individuals. Ferritin levels were positively correlated with insulin concentration, as well as with Homeostasis Model Assessment (HOMA) index values. Multiple regression analysis revealed that ferritin was the most important independent determinant of insulin resistance indices. Patients with metabolic syndrome also exhibited increased concentrations of alanine aminotransferase and gamma-glutamyltranspeptidase compared to controls. Multiple regression analysis revealed that ferritin concentration was the most important determinant of gamma-glutamyltranspeptidase levels. Patients with the metabolic syndrome exhibit an increase in body iron stores as well as elevated concentrations of liver enzymes compared to the individuals who do not fulfill the criteria for the diagnosis of this syndrome. Our data support a direct role of increased body iron in the pathogenesis of insulin resistance, whereas iron overload may also contribute to the development of specific features of the metabolic syndrome, such as fatty liver.
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PMID:Increased serum ferritin concentrations and liver enzyme activities in patients with metabolic syndrome. 1837 Jul 38

Investigating persistent hyperferritinaemia without apparent iron overload is challenging. Even when inflammation, cirrhosis, Still's disease, fatty liver and malignancy are excluded, there remains a group of patients with unexplained hyperferritinaemia for whom rare forms of haemochromatosis (ferroportin disease) are a consideration. Preliminary results suggest that abnormal percentage glycosylation of serum ferritin is seen in some cases of genetically determined hyperferritinaemia. Serum ferritin is normally 50-81% glycosylated, but low glycosylation (20-42%) prevails in hereditary hyperferritinaemia cataract syndrome. This contrasts with hyperglycosylation (>90%) associated with the benign hyperferritinaemia related to missense L ferritin (p.Thr30Ile) mutation. Here, we describe two novel missense L ferritin variants also associated with hyperglycosylation, p.Gln26Ile and p.Ala27Val. Ferritin glycosylation, a comparatively simple measurement, can identify patients for DNA sequencing as hyperglycosylation (>90%) is associated with benign hyperferritinaemia and mutant L ferritin chain.
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PMID:Two novel mutations in the L ferritin coding sequence associated with benign hyperferritinaemia unmasked by glycosylated ferritin assay. 2255 Mar 25

Insulin resistance, oxidative stress, and proinflammatory cytokines play a key role in pathogenesis of nonalcoholic fatty liver disease (NAFLD). The aim of our study was to investigate the dynamics of oxidative/nitrosative stress in methionine-choline-deficient (MCD) diet -induced NAFLD in mice. Male C57BL/6 mice were divided into following groups: group 1: control group on standard diet; group 2: MCD diet for 2, 4, and 6 weeks (MCD2, MCD4, and MCD6, respectively). After treatment, liver and blood samples were taken for histopathology, alanine- and aspartate aminotransferase, acute phase reactants, and oxidative/nitrosative stress parameters. Liver malondialdehyde level was higher in all MCD-fed groups versus control group (p < 0.01), while nitrites + nitrates level showed a progressive increase. The activity of total superoxide dismutase and its isoenzymes was significantly lower in all MCD-fed groups (p < 0.01). Although catalase activity was significantly lower in MCD-fed animals at all intervals (p < 0.01), the lowest activity of this enzyme was evident in MCD4 group. Liver content of glutathione was lower in MCD4 (p < 0.05) and MCD6 group (p < 0.01) versus control. : Ferritin and C-reactive protein serum concentration were significantly higher only in MCD6 group. Our study suggests that MCD diet induces a progressive rise in nitrosative stress in the liver. Additionally, the most prominent decrease in liver antioxidative capacity is in the fourth week, which implies that application of antioxidants would be most suitable in this period, in order to prevent nonalcoholic steatohepatitis but not the initial NAFLD phase.
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PMID:Dynamics of oxidative/nitrosative stress in mice with methionine-choline-deficient diet-induced nonalcoholic fatty liver disease. 2413 Feb 12

Aim: We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibrosis, cirrhosis, and the need for liver transplant. Methods: We analyzed data from 2239 hypertensive patients using descriptive statistics and supervised machine learning algorithms, including the least absolute shrinkage and selection operator and random forest classifier, to select the most relevant features of NASH. Results: The prevalence of NASH among our hypertensive patients was 11.3%. In univariate analyses, it was associated with metabolic syndrome, type 2 diabetes, insulin resistance, and dyslipidemia. Ferritin and serum insulin were the most relevant features in the final model, with a sensitivity of 70%, specificity of 79%, and area under the curve of 0.79. Conclusion: Ferritin and insulin are significant predictors of NASH. Clinicians may use these to better assess cardiovascular risk and provide better management to hypertensive patients with NASH. Machine-learning algorithms may help health care providers make decisions.
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PMID:Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection. 3167 74