# Rescuing SYNGAP1 haploinsufficiency by redirecting alternative splicing

> **NIH NIH R01** · UNIVERSITY OF CHICAGO · 2024 · $609,214

## Abstract

PROJECT SUMMARY
Synaptic transmission and plasticity are fundamental to neuronal functions, and dysregulations of synaptic
protein expression are direct causes of neurodevelopmental disorders such as autism. Over one hundred de
novo loss-of-function mutations in SYNGAP1 have been unambiguously associated with autism spectral
disorders and intellectual disability. Recent success in splice-switching oligonucleotides (SSOs) suggests that
redirecting splicing through genetic and SSO-mediated ablations is a promising approach to rescue
haploinsufficiency. We have identified an alternative splicing event in SYNGAP1 that leads to nonsense-
mediated mRNA decay (NMD) during mouse and human development. To determine whether the SYNGAP1
NMD exon is a viable therapeutic target, we investigate the regulatory mechanism and its functions using genetic
approaches, and determine whether genetic deletion and SSO suppression of the SYNGAP1 NMD exon can
rescue heterozygous knockout phenotypes in mouse mutants and patient-iPSC-derived neurons. Upon
completion, this project will provide genetic insights into the physiological functions of this SYNGAP1 NMD exon
and generate critical preclinical reagents to restore SYNGAP1 protein expression from haploinsufficiency.

## Key facts

- **NIH application ID:** 10805496
- **Project number:** 5R01MH130594-02
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Xiaochang Zhang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $609,214
- **Award type:** 5
- **Project period:** 2023-04-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10805496

## Citation

> US National Institutes of Health, RePORTER application 10805496, Rescuing SYNGAP1 haploinsufficiency by redirecting alternative splicing (5R01MH130594-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10805496. Licensed CC0.

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