Identifying genetic sources of comorbidity between cannabis and schizophrenia using genome-wide and integrative omics data
Project Number5K01DA051759-05
Former Number1K01DA051759-01
Contact PI/Project LeaderJOHNSON, EMMA COVEY
Awardee OrganizationWASHINGTON UNIVERSITY
Description
Abstract Text
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 opportunities for functionally targeted future studies, with the
ultimate objective of producing therapeutic alternatives that can partially mitigate the serious personal costs of
chronic cannabis use in SCZ patients.
Public Health Relevance Statement
Project Narrative
Cannabis involvement is heritable and is more common in those with psychosis-related behaviors and
schizophrenia, but the contributions to this co-occurrence remain unclear. This proposal aims to better
understand the specific variants, genes, and biological pathways that underlie these behaviors, test for a causal
relationship using a genetically-informed design, incorporate transcriptomic and epigenetic data from human and
rodent studies to prioritize genes and pathways for functional follow-up, and examine whether polygenic risk for
cannabis use disorder and schizophrenia predicts psychosis-related behaviors in population-based and/or high-
risk samples. This line of research will advance our understanding of the genetic etiology of these frequently-
comorbid behaviors, train the applicant in the use of multi-omic approaches particularly related to cannabis and
schizophrenia neurobiology, and ultimately produce translationally-relevant results informed by multiple lines of
evidence.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AccountingAcuteAddressAnimal ModelAntipsychotic AgentsBehaviorBehavioralBioinformaticsBiologicalBiologyCannabisCannabis policyChildChildhoodChronicClinicalDataData AnalysesData SetDevelopmentDiseaseEducational StatusEpigenetic ProcessEtiologyExposure toFoundationsFundingFutureGene ExpressionGeneral PopulationGenesGeneticGenetic Predisposition to DiseaseGoalsHeritabilityIncidenceIndividualInvestigationLeadershipMapsMediatingMental DepressionMental disordersMentored Research Scientist Development AwardMentorshipMotivationMultiomic DataNeurobiologyOutcomePathway interactionsPatientsPersonsPharmaceutical PreparationsPopulationPositioning AttributePredispositionPrefrontal CortexPsychosesPsychotic DisordersPublic HealthREM SleepRecording of previous eventsRecreationRelapseReportingResearchResearch PersonnelRiskRodentRodent ModelRoleSamplingSchizophreniaSourceSubgroupSuicideTestingTetrahydrocannabinolTherapeuticTimeTissue ModelTissuesTrainingUS StateUnited StatesUnited States National Institutes of HealthVariantVulnerable PopulationsWorkactionable mutationaddictionadverse outcomecareercareer developmentcausal variantclinical effectclinical translationcomorbiditycostdata integrationdesignexperimental studyfirst episode psychosisfollow-upgenetic architecturegenetic variantgenome wide association studygenome-widehigh riskhuman datahuman modelhuman tissueinsightlongitudinal coursemarijuana legalizationmarijuana usemarijuana use disordermarijuana usermultiple omicsnovelpleiotropismpolygenic risk scorepopulation basedpsychiatric comorbiditypsychosocialskill acquisitionsubstance use treatmenttranscriptomics
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