Computational analysis of severe mental illness
Psychiatric disorders are recognized as leading causes of morbidity globally and are among the most expensive disorders to affect humans. Identifying the underlying pathophysiology is imperative and can lead to major health benefits, through better treatment and prevention strategies. The heritability is high, but most of the genetic factors and the interplay with the environment are unknown and the underlying brain mechanisms.
It is becoming increasingly clear that multiple factors influence most mental disorders. Each gene has a tiny effect in such a scenario with a very high number of risk genes. This makes it difficult to determine an individual’s risk and identify disease mechanisms that can be used to develop new effective treatments. Further, studies of the complex interplay with environmental stressors further complicates the analyses. It is increasingly clear that many small brain abnormalities seem to contribute to disease characteristics, not a single brain structure.
With help from the national e-infrastructure resources provided by Sigma2, the researchers from NORMENT aims to extend these approaches and develop new tools that can leverage the rapidly growing amount of genetic and brain imaging data and rich collections of various clinical measurements which they have access to.