ADDGAP: Alzheimer’s Disease Database for Genetic Association Studies and Phosphorylation States
ADDGAP is a resource developed after Genetic association studies performed on the genotype data available for Alzheimer's related genes. It consists of of genetic parameters estimated for SNPs, haplotype blocks, linakge disequilibrium, phosphorylation sites and other related information.It serves not only as central information but also a comparative analysis platform. ADDGAP is equipped with intuitive and flexible query interface facilities for better comparative genomic analysis. It helps user to analyze, utilize, and understand the data more effectively.
ADDGAP:
It is first of its kind model where the users could easily retrieve and explore the quantitative genetic parameters and the phosphorylation states for Alzheimer's related genes. We applied supple approach for the design of our ADDGAP model to expand and update it on regular basis to provide state-of-the-art information to the scientific community.
Alzheimer's Disease:
"The pathogenesis of Alzheimer's disease is still a mystery however, genetic variants play a significant role in the pathogenesis of the disease and several target genes contributing to its etiology. A number of mutations in the genes APP, PSEN1 and PSEN2 are described as the cause of up to half cases of the rare and early onset form of AD.More and more genes are identified which increase the risk of developing Alzheimer's disease. All these prime genes point to potential new biomarkers for specific disease processes and the number of possible new points of attack for future disease modifying treatment."
Findings:
Here we performed statistics based in-silico analysis on genotype data of the prime genes. Various markers were found and Linkage disequilibrium plots were also generated. We have predicted the possible impact of amino acid substitutions on the structure and function of proteins using biophysical and evolutionary comparisons and found mutations that might be damaging. Phosphorylation states were also predicted for all the genes under study.
Generated information would be of utmost use to all the researchers working in the area of genomics and molecular genetics of the Alzheimer's disease.