Project Summary
Substance use and other psychiatric disorders result in enormous personal, healthcare, and economic
costs. Substance use (e.g., tobacco use disorder) and psychiatric (e.g., schizophrenia) disorders are highly
comorbid. Three main theories have been proposed to explain the high comorbidity of tobacco use and
schizophrenia: 1) self-medication (e.g., schizophrenia promotes tobacco use due to nicotine’s effect on reducing
cognitive deficits and medication side effects), 2) tobacco use causes schizophrenia, and 3) a shared liability,
due to shared genetic and environmental factors. Tobacco use and schizophrenia are each highly heritable (~60-
80%) and we and others have shown that they share several common genetic risk factors. Two traits may share
genetic risk factors due pleiotropy (i.e., a gene variant influences both traits) or because one disorder causes
the other. Furthermore, shared genetic risk may be present in all individuals (i.e., whole-group pleiotropy) or may
be restricted to a subset of individuals (i.e., sub-group heterogeneity).
Using our expertise in tobacco use, biomarkers, schizophrenia, statistical genetics, and transcriptional
analyses, we will develop a comprehensive analytic pipeline to elucidate the shared genomic liability of tobacco
use and schizophrenia, and identify potential causal effects. Our study improves upon initial cross-disorder
analyses, and involves 1) obtaining data from the largest available genomics datasets of schizophrenia and
tobacco use, 2) examining genetic correlation between the traits, 3) identifying shared genetic variants, 4)
examining biological (i.e., mechanistic) pathways, 5) exploring functional effects of the shared genetic variants,
and 6) testing causal directions and effects of whole-group pleiotropy versus sub-group heterogeneity. In Aim 1,
we will become proficient in all 6 steps of the analytic pipeline by analyzing women and men together. In Aim 2,
we will conduct genome-wide sex-based analyses of tobacco use to determine the feasibility of using sex-based
genomic analyses in future investigations of concurrent psychiatric disorders. To develop the pipeline, we will
use nicotine intake biomarkers, which capture tobacco use more accurately than self-reported measures.
However, GWAS of self-reported traits or diagnostic criteria could be used when biomarkers are unavailable.
This grant will train the young investigator PI for a larger genomics program investigating the shared
genomic liability and causality between other pairs of heritable and concurrent psychiatric disorders. We will
apply this pipeline to diverse populations as the datasets become available. Through these efforts, we will better
understand the biological vulnerability to developing co-occurring substance use and psychiatric disorders. This
work may lead to improved prevention and treatment approaches, as well as reveal novel targets for drug
discovery.
