Researchers at the VRVis Zentrum für Virtual Reality und Visualisierung and the Institute of Molecular Pathology (IMP) have developed a method that bridges the gap between information about neural circuits and genomes. The brain and gene data used are publicly available and raise exciting questions about how large amounts of data are handled in biology and medicine.
A central goal in neuroscience and psychiatry is to understand how genetic variations influence our behaviour. Behavioural traits such as fear or pain sensation can depend on the interaction of several genes. The challenging question is through which neuronal circuits these genes interact to influence a particular behavioral trait. Until now, this could only be answered incompletely and with considerable effort.
The new method, published in the journal "Neuroimage", is based on a dynamic trend: For years, neuroscientists have been collecting large amounts of data on the architecture of the brain. Numerous research initiatives are mapping the connections in brains in more and more detail using the latest methods and creating so-called connectors. At the same time, knowledge is growing about genes that are associated with certain behaviours.
The joint research project of VRVis and IMP is now building a bridge between the two worlds: it combines maps of neural circuits with genetic information, enabling functional neuroanatomical maps to be calculated. This new method allows predictions to be made about which of these circuits influence certain genes in behavioral characteristics. The scientists tested the reliability of the method by predicting known neural circuits that underlie characteristic behavior in psychiatric diseases. In addition, this genetically weighted network analysis also enabled them to assign new nodes to certain behaviours, thereby refining the neuroanatomical maps known to date.
Wulf Haubensak, group leader at the IMP, is very pleased with the results and discusses possible applications: "In the future, our method could be used to achieve a better understanding of the relationship between genetic variations and altered behaviour in psychiatric diseases such as different forms of autism or anxiety disorders.
To create "neuroanatomical maps", the researchers used an algorithm that combines and accumulates gene expression data (i.e. information about genes and the time, place and intensity of their activity) with connectivity data (information about networks of neurons in the brain). Now synergy effects of genes in the network can be calculated and analysed. "The visualisation of neurobiological connections already starts with the raw data, which is why the focus of this project was on creating the mathematical method," said Florian Ganglberger, PhD student at VRVis and first author of the study.
"Our method allows the use of the currently available big data resources generated by large brain research initiatives worldwide. It enables neuroscientists to investigate relationships between genes, brain structure and function in silico and at high processing rates, enabling them to design and conduct complex and cost-intensive experiments in a much more targeted manner," says Katja Bühler, head of the Biomedical Image Informatics research group at VRVis.
Basic research can use such methods to create more detailed neuroanatomical maps with the help of computers. In addition, researchers could simulate experiments on the computer and carry out subsequent experiments in a more targeted manner. In medical research, the method could be combined with clinical studies to understand the connections between genome and brain in psychiatric diseases in a better way.
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