Abstract
BACKGROUND: Cognitive impairment in schizophrenia patients is characterized by decreased functioning, reduced quality of life, and is a predictor of a more severe course of the disease. The rs4680 variant of the COMT gene (Val158Met), which encodes catechol-O-methyltransferase, affects dopamine metabolism in the prefrontal cortex and is a key genetic modifier of cognitive endophenotypes. However, the associations of the rs4680 alleles with the severity of cognitive impairment remain unclear. This review summarizes and critically re-evaluates the evidence on the role of rs4680 in the development of cognitive deficits in schizophrenia. AIM: To explore the associations of the rs4680 variant of the COMT gene with cognitive functions in schizophrenia. METHODS: A literature search of the PubMed database for the last 10 years (2014-2024) was performed with the search query "rs4680 schizophrenia cognition". The review included 11 studies. RESULTS: In the majority of studies (9 out of 11), carriers of the Met allele demonstrated better cognitive parameters, such as verbal and visual memory, information processing speed, and regulatory functions (especially in men). Individuals with the Val/Val genotype demonstrated worse attention. Women in the Russian population with Met allele had better conceptualization and inhibitory control results, and men in the Han population with Met allele had a better association with memory and attention. CONCLUSION: The results of this review confirm the association between the rs4680 variant of the COMT gene and cognitive function. Although the quality of the studies included in this review was low, the overall results indicate that further investigation of this association is promising. The identification of a stable association between the COMT genotype and the severity of cognitive deficit provides the basis for a personalized approach in the management of patients with schizophrenia. Further studies on the validation of genetic markers in independent cohorts and the development of algorithms for the integration of genetic data with complex neurocognitive assessments and clinical endophenotypes are needed to make the clinical implementation of this approach successful.