Genetic Risk for Schizophrenia and Depression Was Linked to Cannabis and Cocaine Involvement

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.

Carey, Caitlin E et al.·Frontiers in genetics·2016·Moderate EvidenceCross-Sectional
RTHC-01121Cross SectionalModerate Evidence2016RETHINKTHC RESEARCH DATABASErethinkthc.com/research

Quick Facts

Study Type
Cross-Sectional
Evidence
Moderate Evidence
Sample
N=2,573

What This Study 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.

Key Numbers

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 They Did This

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.

Why This Research 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 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.

What This Study Doesn't 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.

Questions This Raises

  • ?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?

Trust & Context

Key Stat:
Schizophrenia genetic risk was associated with both cannabis use and severe cannabis dependence
Evidence Grade:
This is a genetic epidemiology study using validated polygenic risk scores and correcting for multiple comparisons, providing moderate evidence for shared genetic architecture.
Study Age:
Published in 2016. Psychiatric genetics and polygenic risk scoring methods have advanced substantially since then.
Original Title:
Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement.
Published In:
Frontiers in genetics, 7, 149 (2016)
Database ID:
RTHC-01121

Evidence Hierarchy

Meta-Analysis / Systematic Review
Randomized Controlled Trial
Cohort / Case-Control
Cross-Sectional / ObservationalSnapshot without intervening
This study
Case Report / Animal Study

A snapshot of a population at one point in time.

What do these levels mean? →

Frequently Asked Questions

Does this mean cannabis causes schizophrenia?

Not exactly. The study found shared genetic risk factors that predispose to both schizophrenia and cannabis involvement. This suggests that part of the observed association between cannabis and psychosis may reflect common genetic vulnerability rather than a purely causal relationship from cannabis to psychosis.

How much does genetics explain about substance use?

The genetic psychiatric risk scores explained about 1% of substance involvement in this study, which is statistically significant but small. This means that environmental factors, personal experiences, and many other genetic factors account for the vast majority of substance use risk.

Read More on RethinkTHC

Cite This Study

RTHC-01121·https://rethinkthc.com/research/RTHC-01121

APA

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

MLA

Carey, Caitlin E, et al. "Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement.." Frontiers in genetics, 2016. https://doi.org/10.3389/fgene.2016.00149

RethinkTHC

RethinkTHC Research Database. "Associations between Polygenic Risk for Psychiatric Disorder..." RTHC-01121. Retrieved from https://rethinkthc.com/research/carey-2016-associations-between-polygenic-risk

Access the Original Study

Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.

This study breakdown was produced by the RethinkTHC research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.