# Genetics of Severe Mental Illness

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $1,100,859

## Abstract

PROJECT SUMMARY/ABSTRACT
This proposed project aims to use genetics to help develop an approach for classifying severe mental illness
(SMI) that has a stronger scientific foundation than the systems currently used in both research and clinical
practice. These classification systems have, for more than a century, divided the bulk of SMI into dichotomous
diagnostic categories: psychotic disorders (including schizophrenia [SCZ]) and mood disorders (including
bipolar disorder [BP] and major depressive disorder [MDD]). However the overlap of symptomatology across
mood and psychotic disorders, and growing evidence for the genetic correlation between these categories,
demonstrate that they imprecisely represent the biological underpinning of SMI. It has been proposed that
frameworks based on symptom-level and dimensional (quantitative) information, such as the NIMH Research
Domain Criteria (RDoC), would better reflect the genetic contribution to SMI and would therefore provide a
more useful framework for their classification. However the evidence supporting this hypothesis remains
sparse, in large part because we lack the right datasets to test it.
In this project we will generate a unique SMI dataset, using electronic health records to ascertain individuals
who have received inpatient treatment at a single psychiatric hospital that serves the entire 1 million
inhabitants of the state of Caldas, Colombia. All of the individuals whom we will investigate are members of the
“Paisa”, a genetically and culturally homogeneous population that comprises the majority in this region of
Colombia. By recruiting 8,000 participants across the full range of severe mood and psychotic disorders (as
well as 2,000 demographically-matched controls); performing uniform phenotyping of these 10,000 individuals
using diagnostic and quantitative assessments; and genome wide genotyping, we will establish dimensional
phenotypes that index core deficits of SMI and that reference multiple RDoC domains. We will then conduct
genetic analyses of symptom-level and quantitative phenotypes, evaluating their relationship to known SMI loci
and to polygenic risk scores (PRS) that represent the overall contribution of common genetic variation to these
disorders; the SCZ, BP, and MDD workgroups of the Psychiatric Genomics Consortium (PGC) will provide us
with up-to-date genetic data for each diagnosis. Additionally, we will conduct genome wide association
analyses of the quantitative traits, including meta-analyses for traits that have been assessed in other study
populations. We will also contribute our data (including genotypes available to us for an additional 6,000 Paisa
controls) to the case-control meta-analyses of the PGC workgroups, contributing to the diversity of their
datasets by adding a substantial number of samples from a previously underrepresented (Hispanic) population.
.

## Key facts

- **NIH application ID:** 9892048
- **Project number:** 5R01MH113078-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** CARRIE E BEARDEN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,100,859
- **Award type:** 5
- **Project period:** 2017-05-15 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9892048

## Citation

> US National Institutes of Health, RePORTER application 9892048, Genetics of Severe Mental Illness (5R01MH113078-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9892048. Licensed CC0.

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