# Integrative analysis of alternative splicing in Alzheimer's disease

> **NIH NIH R03** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $155,000

## Abstract

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.

## Key facts

- **NIH application ID:** 9924431
- **Project number:** 5R03AG063250-02
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Younghee Lee
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $155,000
- **Award type:** 5
- **Project period:** 2019-05-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9924431

## Citation

> US National Institutes of Health, RePORTER application 9924431, Integrative analysis of alternative splicing in Alzheimer's disease (5R03AG063250-02). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/9924431. Licensed CC0.

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