Julich-Brain bridges the gap between research approaches to rare diseases

Among other things, the scientists were able to show that correlations between gene expression and brain anatomy found in animal models are also relevant for humans. The findings could contribute to a better understanding of so-called rare diseases, a very high percentage of which have genetic causes. The study focused on developmental disorders that can permanently impair a person's sensory, motor, emotional, learning and memory abilities. According to the Orphanet database, 36 million people are affected in the European Union alone. The study has been published in the journal Mammalian Genome.

In their work, the researchers combined computer-assisted analyses of comprehensive phenotype data from genetic animal models with atlas-based approaches. The scientists compared the gene expression data in the brains of mice and humans in comparable brain areas. The latter were identified using the Julich Brain Atlas. The aim was to find overlaps in gene expression in relevant brain regions of both species and thus gain a better understanding of the genetic background of changes in the neurodevelopment of the species studied.

Various digital tools are available for Julich-Brain, such as JuGEx, which was used here. It was developed at Jülich to link cytoarchitectonic areas with transcriptome data of the tissue, which are accessible via the Allen Brain Atlas. These digital tools are available via the European research platform EBRAINS.

The scientists at Helmholtz Zentrum München identified 29 genes in the mouse brain that are discussed in connection with schizophrenia. Subsequently, brain regions associated with schizophrenia in humans were identified using the Julich Brain Atlas. These selected brain regions were then used to filter three-dimensionally anchored data from tissue samples from the Allen Brain Microarray dataset. Finally, the researchers at Jülich used JuGEx to statistically compare the gene expression levels of the region-specific tissue samples with the expression levels of all cerebral cortex tissue samples from the Allen Brain database.

One key finding: the researchers found increased expression of the 29 genes associated with schizophrenia in the human hippocampus. In addition, they were able to map the findings more precisely within the hippocampus using the Julich Brain Atlas maps.

In summary, the scientists came to three conclusions: Firstly, according to the study, the results showed that the gene-phenotype-driven investigation of certain disease-relevant neuroanatomical patterns in the mouse brain can provide clues that are also relevant for humans, despite differences in development. They conclude that further research is needed to determine which other gene and protein functions are suitable for this purpose. As a third result, the researchers emphasize that differences in the microstructure of the brain are linked to the genetic patterns specific to the respective area.

The scientists see their study as an important first step in using large-scale genotype-phenotype data from mice together with the high-resolution data from the Julich Brain Atlas with the aim of identifying genetic variants that influence brain development and function. Further studies using digital tools and FAIR data will advance research into the causes of brain diseases.

Original publication:
Hölter, S.M., Garrett, L., Bludau, S., Amunts, K. Digital tools of analysis and data integration facilitate synergy between mouse and human brain research and enable translation. Mamm Genome 35, 544–550 (2024). https://doi.org/10.1007/s00335-024-10072-1

JuGEx publication:
Bludau S, Mühleisen TW, Eickhoff SB, Hawrylycz MJ, Cichon S, Amunts K. Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network. Brain Struct Funct. 2018 Jun;223(5):2335-2342. doi: 10.1007/s00429-018-1620-6.