# Dissecting the Multivariate Genetic Architecture of Psychiatric Diseases

> **NIH NIH R01** · UNIVERSITY OF TEXAS AT AUSTIN · 2022 · $643,750

## Abstract

PROJECT SUMMARY
Psychiatric disorders are highly polygenic, exhibit a complex pattern of genetic correlations across the full
spectrum of diagnostic categories. Genetic risk for psychiatric disorders acts via a poorly understood set of
intermediate mechanisms. With substantial investments in large consortia, registry-based efforts, and national
biobanks, genome-wide association studies (GWAS) of psychiatric disorders and related quantitative
phenotypes have made substantial strides in attaining the power needed to detect reproducible genetic
associations, estimate genome-wide chip heritabilities, and estimate genetic correlations between traits.
Combined with bioinformatic approaches, GWAS efforts have produced insights into tissues and cell types
relevant to psychiatric disease, and atlases of genetic correlations have rapidly expanded the ontological
network of descriptive knowledge of shared genetic architecture across psychiatric diseases and social,
behavioral, and biological traits. In order to more fully capitalize on this growing corpus of GWAS research
output, we have recently introduced Genomic Structural Equating Modeling (Genomic SEM; Grotzinger et al.,
2019; Nature Human Behaviour), an analytic framework and associated software for multivariate modelling of
genetic architecture using GWAS summary data from samples of varying or unknown degrees of overlap. The
primary goal of this R01 proposal is to capitalize on and further develop Genomic SEM to formally
investigate genetic risk sharing across psychiatric disorders and- equally importantly- genetic
differentiation between them. We will (1) identify transdiagnostic dimensions of genetic sharing across
psychiatric disorders, and test for commonalities and divergence in genetic associations with biological and
psychosocial dimensions of potentially cross-cutting genetic risk; (2) Identify gene sets and categories that
contribute disproportionately to risk sharing across disorders and/or to disorder-specific genetic variation; (3)
Formally distinguish disorder-general from disorder-specific Loci; and (4) Considerably expand the suite of
methods currently available in Genomic SEM software to meet increasing demand by the genetics community.
The availability of sex-stratified GWAS summary data will allow us to examine convergent and divergent
patterns of association and multivariate genetic architecture across males and females. Moreover, we will
incorporate cutting edge methods for modeling trans-ethnic data, which will be of increasing value as more
diverse GWAS samples become available. This project will constitute the most comprehensive interrogation of
the shared and disorder-specific genetic architecture of major psychiatric disorders and their relationships to
biological and psychosocial dimensions of potentially cross-cutting genetic risk, and will provide an expanded
suite of novel, user friendly, free, open-source tools that serve the entire genetics community.

## Key facts

- **NIH application ID:** 10401847
- **Project number:** 5R01MH120219-03
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Michel Guillaume Nivard
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $643,750
- **Award type:** 5
- **Project period:** 2020-07-17 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10401847

## Citation

> US National Institutes of Health, RePORTER application 10401847, Dissecting the Multivariate Genetic Architecture of Psychiatric Diseases (5R01MH120219-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10401847. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*