# Isoform-level probabilistic transcriptome-wide association to undercover neurogenetic mechanisms underlying complex psychiatric traits

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $691,796

## Abstract

PROJECT SUMMARY/ABSTRACT
As large-scale genome-wide association studies (GWAS) rapidly identify associations with neurodevelopmental
and psychiatric traits, the major defining challenge of the post-GWAS era is to rigorously define the
neurobiological mechanisms underlying disease-associated genetic variation at scale. To this end, we and others
have recently developed methods to directly integrate GWAS results with large-scale tissue-specific expression
quantitative trait loci (eQTL) reference panels, enabling a transcriptome-wide association study (TWAS) – a
powerful approach to identify genes whose expression is associated with genetic risk for disease. In parallel,
emerging evidence has strongly implicated alternative splicing – a form of genetic regulation capable of
generating an exponential number of unique RNA transcript isoforms from a single gene – as an important
mechanism that exhibits dynamic patterns across development and is disrupted in the brains on individuals
affected by psychiatric diseases, including autism and schizophrenia. Yet, no studies have systematically
characterized the genetic regulation of isoform expression in human brain or its association with genetic risk for
psychiatric disorders. This proposal seeks to develop a novel, isoform-level TWAS approach (iso-TWAS) to
identify transcript-isoforms whose cis-regulated expression is associated with psychiatric disease risk. We will
compile a large-scale functional genomic reference panel incorporating genotype and isoform quantifications
from RNA-seq data of more than 3800 human brain samples, which we will leverage to perform iso-TWAS along
with traditional gene-level TWAS for a host of neuropsychiatric traits. We will directly integrate isoform
quantification uncertainties as well as probabilistic fine-mapping within our iso-TWAS framework, in order to
ensure the robustness of resulting associations. We hypothesize that isoform-level characterization will provide
substantially greater resolution to detect candidate biological mechanisms underlying psychiatric GWAS loci.
Finally, predicted SNP-isoform-disease associations will be experimentally validated using genome-engineering
in primary human neural progenitor cell (phNPC) lines followed by long-read RNA-sequencing and detailed
cellular phenotyping. Together, these studies will systematically characterize a critical, yet underexplored area
of genomic regulation in human brain, thereby providing novel insights into psychiatric disease mechanisms and
identifying potential neurobiological targets for therapeutic development and intervention.

## Key facts

- **NIH application ID:** 9867294
- **Project number:** 1R01MH121521-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Michael Gandal
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $691,796
- **Award type:** 1
- **Project period:** 2020-01-03 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9867294

## Citation

> US National Institutes of Health, RePORTER application 9867294, Isoform-level probabilistic transcriptome-wide association to undercover neurogenetic mechanisms underlying complex psychiatric traits (1R01MH121521-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/9867294. Licensed CC0.

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