Alzheimer's disease (AD) as a complex disease currently has limited pathogenic understanding and no cure. However, Genome Wide Association Studies (GWAS) have identified ~203 AD-associated loci based on National Human Genome Research Institute (NHGRI) catalog of published GWAS. These loci include ~3738 single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with r2>0.8. In theory, there is only one functional SNP (fSNP) in each LD that is responsible for the pathogenesis of AD; however, GWAS cannot tell which one is the fSNP in each LD, a challenge in the post-GWAS era. To meet this challenge, we developed two novel techniques: functional Single Nucleotide Polymorphism-next generation sequencing (fSNP-seq) and DNA competition pull-down-Mass spectrometry (DCP-MS). fSNP-seq is a high throughput screen to identify fSNPs with the SNPs in LD on the risk loci revealed by GWAS. DCP-MS uses fSNP sequences as ?bait? to identify their regulatory proteins in a semi-high throughput way with minimum background. We have demonstrated the feasibility of these fSNP-seq and FREP-MS, a prototype of DCP-MS, in our pilot screening on the CD40 locus as well as in a HTP screen on a library that contain 608 juvenile idiopathic arthritis (JIA)- associated SNPs. In this application, we propose two aims to apply our new methods to the GWAS data on AD risk loci.
Aim 1. We will use fSNP-seq to identify fSNPs by screening 3738 SNPs on the ~203 AD risk loci and validate the positive hits by allele-imbalanced electrophoretic mobility shift assay (EMSA) and/or CRISPR/Cas9.
Aim 2. We will employ DCP-MS to identify the AD risk gene regulators by screening on the validated fSNPs and characterize these proteins by shRNA knockdown and/or CRISPR/Cas9. We will focus our study on the fSNPs on the HLA-DRB5/HLA-DRB1, INPP5D and MEF2C loci that are involved in the inflammation/immune response pathway in AD. The goal of this proposal is to build a foundation for us to study cell type specific AD- associated signal transduction and allele specific transcription network for drug development.
Alzheimer's disease (AD), as a complex disease, is associated with the effects of multiple genes in combination with lifestyle and environmental factors. Genome-wide association study (GWAS) has opened a new path for us to understand the pathogenesis of AD by identifying numerous genetic variants that are associated with it. We have developed two new techniques to more efficiently translate GWAS data to pathogenic mechanisms in a high-throughput approach, with the goal of building an AD-associated signal transduction and allele specific transcription network for drug development.