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Unraveling the Mystery: How a New Discovery Sheds Light on Synaptic Dysfunction in Schizophrenia Patients

A recent study has identified genes associated with schizophrenia and revealed a mechanism that alters synaptic plasticity in those affected. Researchers pinpointed the involvement of three proteins in how synaptic plasticity is impaired in schizophrenia, which suggests potential pathways for new treatment options.
In a study led by researchers at Tampere University, genes linked to schizophrenia have been mapped, uncovering a mechanism that disturbs synaptic plasticity in individuals with this disorder. The team highlighted the contribution of three proteins to the dysfunction of synaptic plasticity in schizophrenia. These insights could pave the way for innovative treatment strategies.

While there has been significant advancement in uncovering the genetic links with schizophrenia, the underlying genetic mechanisms remain unclear. This uncertainty stems from the difficulty in examining how variations in each gene or their expression affect the symptoms or observable traits of schizophrenia in individual patients.

Recent developments in computational neuroscience enable researchers to investigate psychiatric disorders through simulations. In a collaborative effort, Tampere University teamed up with researchers in Norway and the USA to create a computational model aimed at assessing the influence of genetic and molecular changes on synaptic plasticity. Synaptic plasticity – the ability of synaptic connections between neurons to strengthen or weaken over time – is essential for learning and memory. Disruptions in this mechanism are thought to play a role in the emergence of schizophrenia.

“Our computational model indicates that certain changes in the expression of genes tied to schizophrenia can lead to deficiencies in synaptic plasticity. This conclusion is backed up by our analysis, where we modified polygenic risk scores from genome-wide association studies to evaluate the specific impact of plasticity-related genes on the risk of developing schizophrenia,” states Academy Research Fellow Tuomo Mäki-Marttunen, who is the lead author of the research article.

Genome-wide association studies (GWAS) are designed to find statistical connections between various genome regions and a specific phenotype. These studies are especially valuable for exploring polygenic conditions like schizophrenia, which stem from the interaction of numerous genetic variants.

“The adjusted polygenic risk factors were shown to correlate with a diminished response to visual stimuli, as indicated by the electroencephalograms (EEGs) conducted by our collaborators. This illustrates that certain genetic variants among plasticity-related genes can predict a weaker EEG response. Hence, our computational model has demonstrated its ability to predict disruptions in plasticity in schizophrenia more accurately,” explains Mäki-Marttunen.

Next Steps: Considering Environmental Factors

Mäki-Marttunen notes that the study represents a significant advancement in understanding the mechanisms linked to schizophrenia, as it offers a mechanistic polygenic model for analyzing the pathology at the single-cell level related to this condition. Currently, few computational models take into account the impact of multiple genes.

Animal studies have revealed how individual genetic mutations affect both cellular function and behavior. At the same time, new in vitro techniques have illuminated how the phenotypes of schizophrenia can be influenced by exchanging the complete genomes of patients with those of healthy individuals. However, observing how the interaction of numerous genes contributes to these phenotypes and pinpointing which genetic variants amid thousands are responsible for the changes presents considerable challenges.

“Our computational modeling method tackles this issue. It enables us to analyze each gene separately to see how variations in their expression levels affect schizophrenia’s phenotype. Additionally, we can readily explore the cumulative effects of changes in multiple gene expressions,” Mäki-Marttunen elaborates.

The study highlights three proteins related to plasticity that may play a crucial role in plasticity deficits associated with schizophrenia. Mäki-Marttunen is hopeful that these findings will motivate future animal and cell culture experiments to further clarify the significance of these proteins in schizophrenia, potentially leading to novel treatment avenues.

“However, our investigation does not yet clarify how the observed shifts in gene expression and the subsequent alterations in synaptic plasticity influence schizophrenia symptoms. To further this understanding, we require new computational models to delve into phenomena linked to symptoms of schizophrenia, such as working memory. Furthermore, we need to enhance our computational model to examine both genetic and environmental factors that may affect symptoms and phenotypes of schizophrenia,” Mäki-Marttunen concludes.

What is gene expression?

  • Gene expression is the process through which the information encoded in a gene is transformed into a functional gene product, like a protein or RNA molecule.
  • This process includes two main stages: transcription, where the genetic code in DNA is transcribed into RNA, followed by translation, where this RNA is used to produce proteins.
  • Gene expression functions as an on/off switch that determines when, where, and in what quantities proteins and RNA are produced.
  • Gene expression is tightly regulated, and any misregulation can result in various diseases.