# Prioritization of splicing-altering genetic variants in Alzheimer's disease

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $452,170

## Abstract

Project Summary
The goal of this project is to develop computational pipelines that allow in silico prediction of
functional genetic variants that disrupt pre-mRNA splicing and related pathways in Alzheimer's
disease (AD). Recently, tremendous success has been achieved in constructing a catalog of
genetic variants in AD genomes of various patient cohorts. The next great challenge is to
identify causal variants and elucidate their potential function relevant to disease processes. To
this end, research efforts have been directed to studying variants located in protein-coding,
promoter, and splice site regions due to their apparent impacts on gene expression. However,
many of the newly identified disease-associated variants reside in other non-coding regions,
such as introns, that may confer regulatory function to the related gene. The mechanisms of
these variants have been hard to decipher. It is expected that many of them may function at the
post-transcriptional level, thus affecting mRNA expression. In human, a myriad of processes
mediate RNA expression at the post-transcriptional stage, one of which being splicing. Splicing
is an essential step of mammalian gene expression and alternative splicing affects most human
genes. Recent literature reported that RNA splicing is a primary link between GVs and disease.
In general, it was estimated that 15-60% of point mutations that result in human genetic
diseases disrupt splicing, highlighting the importance of this regulatory step. In AD, aberrant
splicing has been detected in many functionally critical genes, some of which are modulated by
GVs. Despite the importance, how to accurately identify functional genetic variants in splicing
regulation remains a key question in the field. To address this question, the large collection of
RNA-Seq and genotyping data sets collected from AD and control subjects represent an
invaluable resource. We will develop and apply novel methodologies to make full use of these
data sets, complemented by further bioinformatic prediction and experimental validations. This
work will allow a previously unattained level of understanding of genetic variants in splicing
regulation and provide new means to tackle the imperative task of functional annotations of
genetic variants in AD.

## Key facts

- **NIH application ID:** 10152491
- **Project number:** 5R01AG056476-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Xinshu Grace Xiao
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $452,170
- **Award type:** 5
- **Project period:** 2017-08-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10152491

## Citation

> US National Institutes of Health, RePORTER application 10152491, Prioritization of splicing-altering genetic variants in Alzheimer's disease (5R01AG056476-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10152491. Licensed CC0.

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