GENETIC MECHANISMS OF COMORBIDITY IN SCHIZOPHRENIA AND MAJOR DEPRESSIVE DISORDER: CURRENT STATE OF THE PROBLEM
DOI:
https://doi.org/10.4238/5ya3sv71Keywords:
schizophrenia; major depressive disorder; comorbidity; genetic predisposition; polygenic architecture; genetic correlation; polygenic risk scores.Abstract
The comorbid course of schizophrenia and major depressive disorder has been associated with marked clinical heterogeneity, complicating the identification of the mechanisms underlying their co-occurrence. This study aimed to analyze current concepts regarding the genetic mechanisms of comorbidity between schizophrenia and major depressive disorder and to systematize data on shared genetic factors, polygenic predisposition, and molecular pathways. The study was conducted as a systematic critical review of contemporary domestic and international literature. The analysis revealed that the genetic overlap between the two disorders manifests at multiple levels— ranging from common and rare variants and copy number variations to shared loci, genes, biological pathways, and polygenic effects. Research into pleiotropy, genetic correlation, functional genomics, and polygenic risk scores was identified as particularly significant. However, the observed genetic similarity did not constitute evidence of a single, specific mechanism of comorbidity. Interpretation of the results was limited by the heterogeneity of clinical phenotypes, variations in diagnostic criteria and sample ethnic composition, and the underrepresentation of patients with the co-occurrence of schizophrenia and major depressive disorder in large-scale genetic studies. It was concluded that comorbidity should be viewed as the result of an interplay between shared polygenic vulnerability, disorder-specific genetic factors, and additional clinical and environmental modifiers. To validate this model, the study highlights the need for direct investigation of the comorbid phenotype and the integration of GWAS, rare variant and CNV analysis, polygenic risk scores, and functional genomics.
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