Glioblastoma is a fast and aggressively growing tumor in the brain and spinal cord. Mutation of amino acid residues in targets proteins, which are involved in glioblastoma, alters the structure and function and may lead to disease. In this study, we collected a set of 9386 disease-causing (drivers) mutations based on the recurrence in patient samples and experimentally annotated as pathogenic and 8728 as neutral (passenger) mutations. We observed that Arg is highly preferred at the mutant sites of drivers, whereas Met and Ile showed preferences in passengers. Inspecting neighboring residues at the mutant sites revealed that the motifs YP, CP and GRH, are preferred in drivers, whereas SI, IQ and TVI are dominant in neutral. In addition, we have computed other sequence-based features such as conservation scores, Position Specific Scoring Matrices (PSSM) and physicochemical properties, and developed a machine learning-based method, GBMDriver (GlioBlastoma Multiforme Drivers), for distinguishing between driver and passenger mutations. Our method showed an accuracy and AUC of 73.59% and 0.82, respectively, on 10-fold cross-validation and 81.99% and 0.87 in a blind set of 1809 mutants. The tool is available at https://web.iitm.ac.in/bioinfo2/GBMDriver/index.html. We envisage that the present method is helpful to prioritize driver mutations in glioblastoma and assist in identifying therapeutic targets.
Introduction: Non-alcoholic fatty liver disease (NAFLD) is one of the most prominent causes of chronic liver disease. It is known that dyslipidemia in NAFLD patients may have more severe atherogenic potential with high triglyceride and low density lipoprotein (LDL) as well as less high density lipoprotein (HDL) level.
Objective: To determine the atherogenic dyslipidemia and associated factors among patients with NAFLD, Visiting Tertiary Care Center
Methodology: Prospective cross-sectional study was conducted at Dhulikhel Hospital-Kathmandu University Hospital (DH-KUH) from January, 2016 to December, 2016. All the patients (n= 973) diagnosed to have fatty liver during this study period were initially enrolled in this study. Patients were further asked to fill up the questioner. Out of total 973 cases, 169 patients were identified as NAFLD. Fasting blood sample and anthropometric measurements (BMI, WHR) were taken. After adjusting exclusion criteria, refusal to participate and dropout from the study, 101 patients and 92 apparently healthy age sex matched control group was selected for the study. Blood sugar level and lipid profile were analyzed to assess the risk of athrogenicity among the NAFLD.
Result: High total cholesterol was found in 64.4 %, High LDL was found in 20.8 %, Low HDL is present in 72.2% and high triglyceride is present in 65.8 % patients with NAFLD. Non-HDL cholesterol was significantly higher in NAFLD compared to control group (116.75 ± 34.38 vs. 137.63 ± 39.76, p=0.00). Similarly, calculated cardiac risk ratio (TC/HDL) was significant higher (4.15 ± 1.18 vs. 5.25 ± 1.78, p=0.00) whereas atherogenic index of plasma (AIP) was higher (0.30 ± 0.13 vs. 0.33 ± 0.19, p=0.37).
Conclusion: NAFLD is significantly associated with atherogenic dyslipidemia. Calculated cardiac risk and AIP is higher in patients with NAFLD. Therefore it may be helpful to assess dyslipidemia among the patients with NAFLD to prevent cardiovascular events.
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