Integrative analysis of alternative splicing in Alzheimer's disease

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ABSTRACT Genome-wide association studies (GWAS) have significantly contributed to our knowledge of genetic variants linked to human complex diseases by identifying several thousand frequently occurring susceptibility loci. The risk loci predicted by GWAS represent weak effects and require further functional analysis to identify actionable loci. GWAS has the ability to analyze the entire genome agnostically for genetic variants associated with a disease, but there are the lack of a priori biological hypothesis to guide inquiry from association to underlying functional variants and the inability to take into account non-genetic biological variation. These points can be addressed by focusing on alternative splicing as a biological mechanism regulating gene expression and influencing phenotypic variation. Transcriptional changes accompany the onset and progression of Alzheimer diseases (AD) and anomalous gene expression by alternative splicing is implicated in AD. In addition, genetic (i.e., single nucleotide polymorphism (SNP)) and epigenetic (i.e., DNA methylation status) variation influences splicing regulation. However, splicing mechanisms have not been well investigated yet to identify genetic and epigenetic factors underlying AD biomarkers. Our central hypothesis is that functional genetic and methylation status variants within the splicing regulatory elements (SREs) are associated with exon skipping events and the emergent NIA- Alzheimer’s Association Research Framework (“A/T/N”) for AD biomarkers (i.e., Amyloid, Tau, and Neurodegeneration). With genomics, transcriptomics, epigenomics, and multimodal endophenotype data from large consortia including AMP-AD, ADNI, and M2OVE-AD, our specific aims are (1) to develop a splicing decision model to identify functional genetic and epigenetic factors by scanning the whole genome for the regions with putative SREs; (2) to apply the splicing decision model to identify the aberrant splicing events and their regulatory factors using RNA-Seq and methylation data in AD; and (3) to perform an association analysis of regulatory factors (SNPs, methylation signatures) with AD-related biomarkers. The proposed comprehensive and translational study targeting alternative splicing by integrating multi-omics and AD-related endophenotype data will enable us to gain deeper mechanistic insights into the molecular mechanisms of AD and help to identify new therapeutic targets and diagnostic/biomarker strategies.