Polygenic risk scores for psychiatric disorders explained about 1% of variance in substance involvement, with schizophrenia genetic risk linked to cannabis and cocaine involvement, and depression risk linked to cannabis use and severe cocaine dependence.
Readers interested in the genetic links between psychiatric disorders and substance use.
Schizophrenia genetic risk was associated with both cannabis use and severe cannabis dependence
What the researchers found
Researchers tested whether genetic risk for five psychiatric disorders (ADHD, autism, bipolar disorder, depression, and schizophrenia) predicted involvement with five substances (alcohol, cannabis, cocaine, nicotine, and opioids) in 2,573 European-American participants.
A combined cross-disorder psychiatric risk score significantly predicted general substance involvement, explaining about 1.1% of variance. When broken down by specific disorders and substances, the strongest associations were:
- Schizophrenia genetic risk linked to non-problem cannabis use, severe cannabis dependence, and severe cocaine dependence
- Depression genetic risk linked to non-problem cannabis use and severe cocaine dependence
These associations survived correction for multiple testing, suggesting shared genetic architecture between psychiatric disorders and substance involvement.
Why it matters
This study provides genetic evidence for the commonly observed clinical co-occurrence of psychiatric disorders and substance use. The finding that schizophrenia genetic risk is associated with cannabis involvement has implications for understanding the cannabis-psychosis relationship.
The numbers in context
2,573 participants. Cross-disorder psychiatric risk explained 1.10% of variance in substance involvement (p<0.001). Schizophrenia risk: associated with cannabis use, severe cannabis dependence, and severe cocaine dependence. Depression risk: associated with cannabis use and severe cocaine dependence.
How the study worked
Polygenic risk scores were calculated from Psychiatric Genomics Consortium data for each of five disorders. These were tested against substance involvement measures ranging from ever-use to severe dependence in 2,573 participants from the Study of Addiction: Genetics and Environment.
What this study cannot tell us
The study was limited to non-Hispanic European-American participants and may not generalize to other populations. Polygenic risk scores explain only a small fraction of total risk. The cross-sectional design cannot determine temporal relationships. Environmental factors likely account for far more variance than genetic factors alone.
How to read the evidence
This is a genetic epidemiology study using validated polygenic risk scores and correcting for multiple comparisons, providing moderate evidence for shared genetic architecture.
When this study was published
Published in 2016. Psychiatric genetics and polygenic risk scoring methods have advanced substantially since then.
The bigger picture
The genetic overlap between psychiatric disorders and substance use is important for understanding why these conditions so frequently co-occur. Rather than one causing the other, shared genetic factors may predispose individuals to both, which has implications for treatment approaches that address both conditions simultaneously.
Questions still open
- Does the genetic overlap between schizophrenia and cannabis use reflect shared risk, or does genetic predisposition to cannabis use increase psychosis risk? Would these findings replicate in more diverse populations?
Common questions
Does this mean cannabis causes schizophrenia?
How much does genetics explain about substance use?
Read the original research
Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement.
Frontiers in genetics, 7, 149
Citation
Carey, Caitlin E; Agrawal, Arpana; Bucholz, Kathleen K; Hartz, Sarah M; Lynskey, Michael T; Nelson, Elliot C; Bierut, Laura J; Bogdan, Ryan. (2016). Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement.. Frontiers in genetics, 7, 149. https://doi.org/10.3389/fgene.2016.00149
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