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Progress in Neuro-Psychopharmacology and Biological Psychiatry 2019-06

Schizophrenia, cannabis use and Catechol-O-Methyltransferase (COMT): Modeling the interplay on cognition.

يمكن للمستخدمين المسجلين فقط ترجمة المقالات
الدخول التسجيل فى الموقع
يتم حفظ الارتباط في الحافظة
Marta Bosia
Mariachiara Buonocore
Margherita Bechi
Liliana-Mihaela Stere
Maria Silvestri
Emanuela Inguscio
Marco Spangaro
Federica Cocchi
Laura Bianchi
Carmelo Guglielmino

الكلمات الدالة

نبذة مختصرة

Cognitive impairments are considered core features of schizophrenia and are recognized as the most important predictors of functional outcome and quality of life. A better study of the mechanisms underlying the cognition is of extreme relevance. Literature has shown that several genetic and environmental factors affect cognitive performance. In particular, the interaction between Catechol-O-Methyltransferase (COMT) gene and cannabis use has gained increasing attention in the past years. Based on these premises, the present study, aimed to analyze the interplay between cannabis use and COMT polymorphism on cognitive performance in a sample of 135 patients with chronic schizophrenia. Patients were assessed for neurocognitive measures with a broad battery, genotyped for COMT Val158Met polymorphism from peripheral blood sample, and evaluated with a semi-structured interview in order to establish the history of cannabis abuse. Results showed a significant interaction effect between COMT polymorphism and cannabis use on verbal fluency and speed of processing. The analysis revealed significant differences between subjects COMT Val/Val homozygous and Met carriers with history of cannabis use, with a better performance on both tasks among the Met carriers group. These data are in line with literature on healthy subjects that suggests a more detrimental effect of cannabis among subjects with Val/Val genotype. In conclusions, results highlight the need to better disentangle the biological pathways in which cannabis use and COMT are converging, as possible treatment targets, as well as the importance to assess these factors in clinical to optimize individualized interventions.

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