No abstract

High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.

No abstract

No abstract

Background: Altered levels of serum glycated hemoglobin (HbA1c) and lipid profile are prevalent in patients having type 2 diabetic mellitus (T2DM). Aim of the study was to investigate the relationship between serum HbA1c and lipid profile in T2DM to predict diabetic dyslipidemia.Methods: A structured questionnaire was filled up by each study subject to collect data according to study protocol including age, gender, BMI, BP, residential status, socio-economic status, educational status, physical activity, dietary habit, smoking and duration of diabetes. We collected blood samples from 270 type-2 diabetes mellitus (T2DM) patients aged 30-65 years after overnight fasting (10-12 hours). Then blood samples collected from T2DM patients were used to measure serum levels of HbA1c, fasting blood glucose (FBG), total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL) and high-density lipoprotein (HDL) were estimated by standard laboratory methods.Results: In this study, increased levels of fasting blood glucose (8.61 mmo/l), HbA1c (7.86%), TC (226.15 mg/dl), TG (193.34 mg/dl) and LDL (147.37 mg/dl), and decreased levels of HDL (40.36 mg/dl) were observed in T2DM patients. Moreover, the strong positive correlation of HbA1c levels with FBG, TC, TG, and LDL levels were found in this study. Besides, a very strong and significant negative correlation (R2=0.1822) between the serum levels of HbA1c and HDL were noted in this study.Conclusions: This study revealed a strong correlation between dyslipidemia and serum levels of HbA1c in T2DM patients.