Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning.
Transl Psychiatry
; 12(1): 188, 2022 05 06.
Article
em En
| MEDLINE
| ID: mdl-35523763
ABSTRACT
While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naïve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Contexto em Saúde:
2_ODS3
/
8_ODS3_consumo_sustancias_psicoactivas
Problema de saúde:
2_sustancias_psicoativas
/
8_cannabis_related_disorders
/
8_cocaine_other_stimulant_related_disorders
/
8_hallucinogen_related_disorders
Assunto principal:
Cannabis
/
Transtornos Relacionados ao Uso de Substâncias
/
Alucinógenos
Tipo de estudo:
Prognostic_studies
Limite:
Adolescent
/
Humans
Idioma:
En
Revista:
Transl Psychiatry
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos