Accepted_test

Reconstruction and statistical estimates of gene networks of complex diseases based on online bioinformatics tools
by Maiia Bratchikova | Aylin Minasazova | Orlov Yuriy | Sechenov University | Sechenov University | First Moscow State Medical University named after. I.M. Sechenov Ministry of Health of Russia (Sechenov University), Institute of Cytology and Genetics SB RAS
Abstract ID: 748
Event: BGRS-abstracts
Sections: [Sym 2] Section “Reconstruction computational analysis and modeling of gene networks and metabolic pathways”

Using bioinformatics tools, the functions of the mentioned genes are described as follows:

1. COMT (Catechol-O-methyltransferase): Catalyzes the transfer of a methyl group from S-adenosylmethionine to catecholamines, including dopamine, epinephrine, and norepinephrine. This O-methylation process is a major degradation pathway for catecholamine transmitters.

2. DISC1 (Disrupted in schizophrenia 1): Involved in regulating various aspects of embryonic and adult neurogenesis. Required for the proliferation of neural precursors in specific brain regions during development and adulthood. Participates in Wnt-mediated proliferation of neural progenitors and modulates the AKT-mTOR signaling pathway, influencing neuronal integration, positioning, dendrite development, and synapse formation.

3. HTR2A (5-Hydroxytryptamine Receptor 2A): Encodes a serotonin receptor. Mutations in this gene are linked to susceptibility to schizophrenia and obsessive-compulsive disorder, as well as the response to the antidepressant citalopram in patients with major depressive disorder (MDD). Mutations in intron 2 of this gene can reduce the response to citalopram due to decreased gene expression.

4. NRXN1 (Neurexin 1): Encodes a cell surface receptor belonging to the neurexin family, which binds neuroligins and forms complexes at synapses in the central nervous system. This interaction is essential for efficient neurotransmission and synaptic contact formation. Mutations in NRXN1 are associated with Pitt-Hopkins syndrome-2 and may contribute to schizophrenia predisposition.

In conclusion, bioinformatics analysis of gene networks related to mental disorders, such as schizophrenia, can identify key genes, their interrelationships, and potential as drug targets. Despite the complexity of schizophrenia, understanding the genetic basis through bioinformatics offers insights for targeted interventions.