# Identifying genetic sources of comorbidity between cannabis and schizophrenia using genome-wide and integrative omics data

> **NIH NIH K01** · WASHINGTON UNIVERSITY · 2024 · $157,281

## Abstract

Project Summary
Recreational cannabis use is becoming increasingly common in the United States, even within vulnerable
populations. Amidst growing concerns surrounding the possible adverse consequences of chronic cannabis use,
there is evidence that cannabis use disorder (CUD) is genetically correlated with susceptibility to several
behavioral (e.g., lower educational achievement) and psychiatric (e.g., schizophrenia) outcomes, thus bringing
into question prior causal claims. The most aggressively contested discussion surrounds the role of cannabis
use and CUD in the etiology of schizophrenia (SCZ) and psychotic illness. While there is now an abundance of
evidence supporting shared genetic influences, studies also outline the psychotomimetic effects of especially
high potency forms of tetrahydrocannabinol (THC). A systematic search for pleiotropic variants that undergird
this comorbidity between CUD and SCZ can not only provide insights into shared biology, but also outline
avenues for identifying subgroups of individuals at greatest risk. This Mentored Research Scientist Development
Award (K01) proposes a research plan that leverages some of the largest currently available genome-wide
association study (GWAS) datasets to (a) conduct a cross-disorder GWAS of CUD with SCZ, and to contrast it
with findings from a similar cross-disorder analysis of cannabis use with SCZ, to identify loci of convergent and
divergent effect; (b) to test for a causal relationship using a genetically-informed approach and harness curated
`omics data from human and rodent models of cannabis exposure and SCZ, to fine-map significant loci and
further prioritize causal variants for biological plausibility; and (c) to utilize polygenic risk scores derived from
these cross-disorder analyses to identify associations with first-episode psychosis, cannabis-induced psychosis,
and childhood psychosis-proneness in independent samples. These research aims are founded on four key
training objectives that will enhance the applicant's career goal of becoming an NIH-funded independent
investigator who works at the interface of addictions and psychiatric illness. These training objectives include (a)
a deep understanding of the clinical effects of acute and chronic exposure to cannabis, (b) integrative
bioinformatics approaches for post-GWAS annotation, including cross-species data (c) an appreciation of the
neurobiology underlying the comorbidity between cannabis and SCZ, and (d) career development towards
leadership and mentorship positions. The applicant builds upon her current funding and training directed at
advanced statistical genetics to addressing comorbidity by adding on novel facets relating more broadly to multi-
omics data integration and more specifically to the unique yet ubiquitous comorbidity between cannabis and
SCZ. Together, this training and research plan will produce some of the first insights into the shared genetic
etiology underlying CUD and SCZ and provide oppor...

## Key facts

- **NIH application ID:** 10811710
- **Project number:** 5K01DA051759-04
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Emma Covey Johnson
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $157,281
- **Award type:** 5
- **Project period:** 2021-04-01 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10811710

## Citation

> US National Institutes of Health, RePORTER application 10811710, Identifying genetic sources of comorbidity between cannabis and schizophrenia using genome-wide and integrative omics data (5K01DA051759-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10811710. Licensed CC0.

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