TOPLINE

A meta-analysis of longitudinal studies found that cannabis use more than doubled the risk for subsequent bipolar disorder (BD) and nearly doubled the risk for manic or hypomanic symptoms compared with non-use among individuals without BD or relevant manic or hypomanic symptoms at baseline.

METHODOLOGY

• Investigators conducted a systematic review and meta-analysis of longitudinal observational studies examining the association between cannabis exposure and subsequent bipolar-spectrum outcomes.
• The review included 19 studies from 11 countries (6,960,517 participants, including 67,992 cannabis users). The mean age of participants at baseline was 23.8 years among studies reporting age, and 51.3% of participants were females among studies reporting sex.
• Overall, 13 studies contributed to separate meta-analyses of incident BD (eight studies; 206,572 participants) and incident manic or hypomanic symptoms (six studies; 57,243 participants). One study contributed to both.
• Cannabis exposure was defined variably as any use, lifetime use, frequent use, or cannabis use disorder (CUD). Outcomes were assessed using diagnostic criteria or validated symptom scales.
• Random-effects meta-analyses calculated pooled unadjusted risk ratios (RRs) using the Mantel-Haenszel method; subgroup analyses were conducted by exposure definition, age group, and follow-up duration.

TAKEAWAY

• Eight studies showed that cannabis use was associated with an increased risk for incident BD compared with non-use (RR, 2.46; P < .0001), with substantial heterogeneity.
• Six studies reported an increased risk for incident manic or hypomanic symptoms among cannabis users vs non-users (RR, 2.11; P = .032), with high heterogeneity. The results were not significant when several individual studies were excluded.
• For BD, subgroup analyses showed no significant differences by exposure definition (CUD vs non-CUD) or age group (mean age ≤ 18 vs > 18 years). In an exploratory analysis, studies with a follow-up duration of 3 years or less showed stronger associations (RR, 3.34; 95% CI, 2.03-5.50) than those with a follow-up duration of more than 3 years (RR, 1.50; 95% CI, 0.95-2.37; P = .0206 for between-subgroup differences).
• Meta-regression for BD showed that more recent publication year was associated with smaller effect estimates (P = .0242). Older mean age and shorter follow-up showed trend-level associations with larger effects.

IN PRACTICE

"Cannabis use is associated with an increased risk of subsequent bipolar-spectrum outcomes in people without previous bipolar disorder. While these findings cannot be interpreted as proof of direct causality, they support considering cannabis exposure as a clinically relevant factor in the assessment of young people with emerging affective symptoms," the authors wrote.

"Routine evaluation of cannabis use and monitoring of bipolar disorder outcomes, together with prevention strategies focused on delaying initiation and reducing frequent use, is therefore be warranted," they added.

SOURCE

The study was led by Cecilia Sanjuan-Ortiz and Paula Querol, King's College London, London, UK. It was published online on October 06, 2026, in the Journal of Affective Disorders.

LIMITATIONS

The observational design precluded causal conclusions, and estimates were unadjusted for confounding factors such as tobacco and alcohol use. High heterogeneity likely reflected varied baseline risks and follow-up durations and inconsistent definitions of cannabis exposure and outcomes. Furthermore, cannabis use was often self-reported, lacking details on age at initiation, frequency, and potency, and secondary analyses were underpowered.

DISCLOSURES

No study-specific funding was reported. Several authors of the study received support from the Alicia Koplowitz Foundation and Instituto de Salud Carlos III. Several authors reported receiving personal fees, grants, or honoraria from pharmaceutical companies including Medice, Angelini, Janssen-Cilag, Lundbeck, Menarini, Neuraxpharm, Rovi, and Takeda, unrelated to this work.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.