# The genomic and synaptic basis of language disorder and learned sound association

> **NIH NIH F31** · COLUMBIA UNIV NEW YORK MORNINGSIDE · 2024 · $48,974

## Abstract

Project Summary/Abstract
Language disorder is a neurodevelopmental condition that occurs in ~7% of children starting school
(Tomblin et al., 1997; Norbury et al., 2016). It has high comorbidity with autism spectrum disorder
(ASD) (Ellis Weismer, 2013) and other impairments (Mueller and Tomblin, 2012; Snowling et al.,
2020), which makes it challenging to identify its unique genomic and synaptic mechanisms. The focus
of this proposal is to apply computational genomics and behavioral neuroscience to study language
disorder in the context of learned sound association, the process by which the auditory nervous
system associates a sound with a certain outcome (Stanley, 2023; Stanley et al., 2024). In Aim 1, I will
use genome-wide association studies (GWAS) and post-GWAS analysis methods to conduct a
large-scale analysis of the variants, genes, and pathways involved in language disorder and identify
shared and distinct genetic factors between language disorder and ASD using human genetic data
from the Genetics of Language (GenLang) consortium, the Simons Foundation Powering Autism
Research (SPARK) dataset, the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort,
and the United Kingdom (UK) Biobank. In Aim 2, I will conduct behavioral sound association
experiments with wildtype (WT) and mutant mouse models using an interactive virtual reality (VR)
environment, where mice will be trained to associate auditory cues with rewarding/aversive stimuli.
Neuronal activity will be measured using fiber photometry recordings in the tail of the striatum. The
comparison of human genetic data from Aim 1 with mouse physiology and behavioral data in Aim 2
will identify the timing and role for language disorder/ASD-linked genes in sound association learning
and its disruption in neurodevelopmental disease.

## Key facts

- **NIH application ID:** 11071726
- **Project number:** 1F31DC022183-01A1
- **Recipient organization:** COLUMBIA UNIV NEW YORK MORNINGSIDE
- **Principal Investigator:** Shashaank Narayanan
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $48,974
- **Award type:** 1
- **Project period:** 2024-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11071726

## Citation

> US National Institutes of Health, RePORTER application 11071726, The genomic and synaptic basis of language disorder and learned sound association (1F31DC022183-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11071726. Licensed CC0.

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