👤 Eda Ates

The study aimed to assess the effectiveness of three clinical diagnostic criteria [Simon Broome (SB), MEDPED (MP), and guideline-derived (GL-EAS)] in identifying children with familial hypercholesterolaemia (FH) compared with genetic testing. The evaluation involved 1337 children with elevated LDL cholesterol (LDL-C) levels, focusing on the sensitivity and specificity of these clinical scores in detecting genetically confirmed FH cases. Clinical data were gathered by a self-reporting questionnaire. Clinical FH was defined in accordance with the tested FH score. Genetically confirmed heterozygous FH (HeFH) was defined by a (likely) pathogenic variant. Of the 1337 children undergoing genetic analysis, 211 showed a pathogenic FH mutation. Applying SB, MP, and GL-EAS criteria resulted in 210/1337, 125/1337, and 112/835 children being categorized to have FH clinically. The sensitivity of the clinical scores ranged from 0.44 to 0.54 with a positive predictive value (PPV) of 0.51-0.79. The specificity was 0.91-0.97 with a negative predictive value (NPV) of 0.89-0.91. Similar results were observed for the three clinical scores regarding sensitivity, specificity, PPV, and NPV in subgroup analyses defined by gender, age (<10 years vs. ≥10 years), or weight [≥90th BMI (body mass index) percentile vs. <90th BMI percentile]. Clinical FH scores offer a high degree of specificity for FH diagnosis in children, but at the expense of low sensitivity. Specifically, half of the mutation-positive children in this study would have been missed for early diagnosis and preventive treatment. Given the widespread availability of affordable genetic testing, such analysis should be performed at a lower threshold than that indicated by these clinical scores. Show less

Nonalcoholic fatty liver disease is a hepatic condition characterized by excessive fat accumulation in the liver with advanced stage nonalcoholic steatohepatitis (NASH), potentially leading to liver fibrosis, cirrhosis, and cancer. Currently, the identification and classification of NASH require invasive liver biopsy, which has certain limitations. Mass spectrometry-based proteomics can detect crucial proteins and pathways implicated in NASH development and progression. We collected the liver and serum samples from choline-deficient, L-amino acid-defined high-fat diet fed NASH C57BL/6J mice and human serum samples to examine proteomic alterations and identify early biomarkers for NASH diagnosis. In-depth targeted multiple reaction monitoring scanning and immunoblotting assays were used to verify the biomarker candidates from mouse liver and serum samples, and enzyme-linked immunosorbent assay (ELISA) was employed to analyze human serum samples. The multiple reaction monitoring analysis of NASH liver revealed 50 proteins with altered expression (21 upregulated and 29 downregulated) that are involved in biological processes such as detoxification, fibrosis, inflammation, and fatty acid metabolism. Ingenuity pathway analysis identified impaired protein synthesis, cellular stress and defense, cellular processes and communication, and metabolism in NASH mouse liver. Immunoblotting analysis confirmed that the expression of proteins associated with fatty acid metabolism (Aldo B and Fasn) and urea cycle (Arg1, Cps1, and Otc) was altered in the mouse liver and serum. Further analysis on human serum samples using ELISA confirmed the increased expression of multiple proteins, including Aldo B, Asl, and Lgals3, demonstrating values of 0.917, 0.979, and 0.965 of area under the curve in NASH diagnosis. These findings offer valuable insights into the molecular mechanisms of NASH and possible diagnostic biomarkers for early detection. Show less

Stress is thought to be an important contributing factor for eating disorders; however, neural substrates underlying the complex relationship between stress and appetite are not fully understood. Using in vivo recordings from awake behaving mice, we show that various acute stressors activate catecholaminergic nucleus tractus solitarius (NTS Show less

Norepinephrine (NE) is a well-known appetite regulator, and the nor/adrenergic system is targeted by several anti-obesity drugs. To better understand the circuitry underlying adrenergic appetite control, here we investigated the paraventricular hypothalamic nucleus (PVN), a key brain region that integrates energy signals and receives dense nor/adrenergic input, using a mouse model. We found that PVN NE level increases with signals of energy deficit and decreases with food access. This pattern is recapitulated by the innervating catecholaminergic axon terminals originating from NTS Show less