Alzheimer's disease (AD) is a progressive neurodegenerative disorder with profound global impact. While Genome-wide Association Studies (GWAS) have revealed genomic variants linked to AD, their translational impact has been limited due to challenges in interpreting the identified genetic associations. To address this challenge, we have devised a novel approach termed Transcription Factor-Wide Association Studies (TF-WAS). By integrating the GWAS, eQTL and transcriptome analyses, we selected 30 AD SNPs in non-coding regions that are likely to be functional. Using human transcription factor (TF) microarrays, we have identified 90 allele-specific TF interactions with 53 unique TFs. We then focused on several interactions involving SMAD4, and further validated them using EMSA, luciferase, and ChIP on engineered genetic backgrounds (female cells). This approach holds promise for unraveling the intricacies of not just AD, but any complex disease with available GWAS data, providing insight into underlying molecular mechanisms and clues towards potential therapeutic targets.Signficance statement We introduce a powerful platform for better understanding the genetic contribution of Alzheimer's Disease (AD) and other complex diseases. Through Genome-Wide Association Studies (GWAS), many statistically significant Single Nucleotide Polymorphisms (SNPs) associated with AD have been identified, but their functionality remains unknown. By screening >85% of human proteome transcription factors and cofactors for allele-specific binding preferences with GWAS SNPs, we can comprehensively elucidate the functionality of these SNPs in disease etiology. Using this strategy, we have identified and validated several allele-specific interactions with AD-associated GWAS SNPs that have potential implications in processes relevant to AD. By leveraging available GWAS data, we can identify functional SNPs not just in AD, but in essentially all other complex diseases.
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