A recent analysis has uncovered in-depth insights into genetic differences in brain cells, offering potential new opportunities for specific treatment of conditions such as schizophrenia and Alzheimer’s disease. The findings, which were reported on May 23 in the journal Science, stemmed from a joint effort known as PsychENCODE, established in 2015 by the National Institutes of Health.A new study was published in Science, Science Advances, and Science Translational Medicine, seeking to gain new insights into how genomic factors influence neuropsychiatric diseases. According to Mark Gerstein, the Albert L. Williams Professor of Biomedical Informatics at Yale School of Medicine and senior author of the study, previous research has already established a strong connection between an individual’s genetics and their likelihood of developing neuropsychiatric diseases. Gerstein also noted that the correlations between genetics and susceptibility to disease are significantly greater for brain disorders than for cancer or heart disease.Gerstein mentioned that having parents with schizophrenia makes it far more likely for a person to develop the condition compared to getting heart disease if their parents have it. He also noted that brain-related conditions have a high heritability. However, the exact process of how this genetic variation causes the disease is not fully understood. Gerstein expressed the need to comprehend the mechanism behind the gene variant’s impact on the brain. In the new study, researchers aimed to gain a deeper understanding of genetic variation in different cell types within the brain. They conducted various single-cell experiments on over 2.8 million cells.n the study, 388 people’s brain cells were examined, including those with various mental disorders such as schizophrenia, bipolar disorder, autism spectrum disorder, post-traumatic stress disorder, and Alzheimer’s disease. The researchers identified 28 different types of cells from this group and then studied the gene expression and regulation within those cell types.
One interesting finding was the ability to connect gene expression to variations in “upstream” regulatory regions, which are bits of genetic code located before the gene and can impact the gene’s expression. This discovery is valuable because it provides insights into the regulation of gene expression.According to Gerstein, if you have a different version of a gene, you can now associate it with a specific gene. This is extremely useful because it helps in the interpretation of the different versions and understanding their impact on the brain. The research also allowed for connecting these versions to specific cell types and their functions.
The scientists also examined the variations in specific genes, like those related to neurotransmitters, among individuals and cell types. They found that the variability was generally higher across cell types than across individuals. This difference was even more pronounced for genes that encode proteins targeted for The use of this data in analysis enabled the researchers to create genetic regulatory and communication networks within specific cell types. These networks were then inputted into a machine learning model. This model could then use a person’s genetic information to predict the presence of a brain disease. This approach, according to Gerstein, is beneficial for drug treatment. He explained that drugs targeting specific cell types without affecting the entire brain or body are generally effective and less impacted by genetic variations, making them more likely to work for many people.
“The model had these networks hard coded, so when it made a prediction, we could analyze which parts of the network played a role in it,” Gerstein explained. “This allowed us to pinpoint the genes and cell types that were crucial for the prediction, which in turn could lead to potential drug targets.”
For instance, the model predicted that an individual with a specific genetic variation might develop bipolar disorder, and the researchers found that this prediction was based on two genes in three different cell types. In another case, the researchers discovered that six genes in six different cell types contributed to a prediction of schizophrenia.”</ rnrn
The researchers were able to use the model in both directions. They could manipulate genetics and observe how it impacted the network and an individual’s health. This helps in drug design and predicting the effectiveness of drug treatments. The findings could aid in precision-medicine approaches for neuropsychiatric disease. The consortium has also made their results and model accessible to other researchers to further this research.
“Our hope is that other researchers can utilize our resources to study a specific gene or variant,” explained the researchers.Gerstein stated, “This will allow us to better understand its effects on the brain or to possibly discover new potential drug targets for further investigation.”
