| Title: | Linking genetic and graph-theoretic phenotypes of psychiatric illness from WGS and effective connectivity. |
| Lead Institution: | Korea Advanced Institute of Science and Technology |
| Principal investigator: | Dr Sunghwan Kim |
Application 85156
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
Although many researchers have struggled to uncover the genetic background and understand the brain mechanism of psychiatric illness, they are still poorly understood. There are many hurdles to unveiling the relationship between gene and brain, and the lack of data that collected brain images and genetic information at the same time was also one of the major reasons. Thanks to the UK Biobank dataset, we can utilize invaluable data collected together and we can try to deepen our understanding of the characteristics of individuals' brains who suffer from psychiatric illness and find the causal role of genotypes that might contribute to the psychiatric symptoms. Firstly, we are going to try to discover the causal network of the brain from functional and structural brain images. There have been lots of methods to infer causal relationships between brain areas and gens from observed data, but these take too much time to calculate the causal relationships. Recently, deep learning-based causal inference has been gaining popularity, but data shortage was a major hurdle to train reliable and generally applicable models. If a certain deep learning model is well-trained, doctors can easily detect someone's disease state related to mental disorders, and it will be very helpful to early detect individuals who need some helps, or monitor the patients' status during treatment. Furthermore, our novel approach to the links between brain areas and genes can offer new tools to find individualized treatment targets for recent advanced therapies for psychiatric disorders known as electroceuticals or neuro-modulation. The complex interaction of genotypes related to brain disorders makes it hard to apply the knowledge about genetic networks to the clinical scene. If we can find the causal network of genotypes linked to the psychiatric disorder at the individual level, it would be possible to treat psychiatric illness by intervening target-gene-related transcriptome or gene regulatory networks. Lastly, the joint analysis of brain imaging data and genes can provide an integrated understanding of brain disorders. If we figure out the link between genetic and brain characteristics, we can more early and precisely diagnose the psychiatric illness and have a chance to offer more tailored treatment for the patients.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 13142 | The prognostic impact of psychiatric intervention on alcohol-associated liver disease : the UK Biobank cohort study | Keungmo Yang (+6) | 2024 | Clinical and Molecular Hepatology |
Enabling scientific discoveries that improve human health