An empirical theory of the formation of emotional and volitional deficits in schizophrenia with a predominance of negative disorders, developed as a result of analysis of the relationship between clinical and genetic data with the JSM method for automated research support
https://doi.org/10.25881/18110193_2024_2_82
Abstract
The study attempted to test experts' assumptions about the difference in the genetic mechanisms of the formation of emotional and volitional deficits in schizophrenia with predominance of negative disorders. The aim of the study is to create empirical theory of these two phenomena using an approach based on JSM-method for automated research support (JSM-method ARS). Polymorphisms of four genes associated with schizophrenia (BDNF, 5HTR2A, HTTLPR, ZNF804A) and clinical data presented as PANSS score were used as empirical data.
The use of generalized JSM-method ARS, which generates ternary relationships “cause-blocker-effect”, allows us considering in detail the interaction of specific gene variants for emotional and volitional deficits in negative schizophrenia.
The result of the study is confirmation of the experts' hypothesis about the difference in the mechanisms of these clinical manifestations. This conclusion was based on a comparison of knowledge fragments for two phenomena.
The utilized approach can be extrapolated to a larger number of genes. We suggest that the use of the generalized JSM-method ARS is a promising approach to studying gene interactions in schizophrenia
About the Authors
O. P. ShesternikovaRussian Federation
E. F. Fabrikantova
Russian Federation
PhD
V. Ye. Golimbet
Russian Federation
DSc
T. V. Lezheiko
Russian Federation
PhD
D. V. Romanov
Russian Federation
DSc
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Review
For citations:
Shesternikova O.P., Fabrikantova E.F., Golimbet V.Ye., Lezheiko T.V., Romanov D.V. An empirical theory of the formation of emotional and volitional deficits in schizophrenia with a predominance of negative disorders, developed as a result of analysis of the relationship between clinical and genetic data with the JSM method for automated research support. Medical Doctor and Information Technologies. 2024;(2):82-90. (In Russ.) https://doi.org/10.25881/18110193_2024_2_82