Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation.

Genomic research to understand the pathology and development of AD has evolved from meta-GWAS studies to isolated variant effects at a molecular level. With this evolution, we focus on using the top significant IGAP variants that are related to AD and observe their chromatin feature functional changes. In addition to focusing significant known AD variants, we observed the changes when neighboring variants are also considered in combination to decode if functional effects are only dependent on the lead variant in each LD block. Using the Expecto deep learning model, we were able to conclusively isolate 8 variants with allele-specific effect without genomic context and 3 significant variants with genomic context. We also established the neuroprotective effect of rs584007 variant with the ADNI genotype for validation.

Article

Varathan P, Xie L, He B, et al. Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation. Medrxiv : the Preprint Server for Health Sciences. 2023 Oct:2023.10.23.23297399. DOI: 10.1101/2023.10.23.23297399. PMID: 37961458.

Variants from GWAS studies are the preliminary step for most genetic targeted studies of disease pathology including studies such as polygenic risk score, TWAS and discovery of drug target. With pruning and clumping of the cluster of SNPs in the same LD region, we obtain a singular lead SNP that is further processed downstream and sometimes varies in between GWAS studies. In this aim, our main innovation is to understand if high AD risk variants can produce any chromatin feature effects and if the neighboring variants of the lead variants produce a different chromatin effect in combination. There have been very rare studies to understanding if the combination of variants has influence in the chromatin features of the region and this aim tries to provide insight on such combinations to value the information from the neighboring variants. The most important novelty in this aim is that it explores the genetic context of functional annotation of top GWAS variants for the first time in one-of-a-kind study.