Genetic-based classification of schizophrenia

Project Details

This project is assembling several SNP sets from which genetic classifiers with potential clinical utility will be developed in three distinct populations (European-American, African-American, and Han Chinese).  In the first study, a random forest algorithm will be employed to tests biological pathway-based SNP-sets for their ability to accurately classify schizophrenia.  In the second study, five evidence-based SNP sets based on previous experimental results will be assembled and then compared to each other as well as randomly derived SNP sets on their classification accuracy. In the third and final study, the traditional polygenic risk score approach will be compared to an evolutionary-informed polygenic risk score approach that replaces the traditional p-value based SNP selection strategy with an evolution-based strategy. As a whole, these studies will provide head-to-head comparisons of traditional and novel approaches to SNP-based diagnostic classification across three populations with distinct ancestry.

Funding

  • Brain & Behavior Research Foundation (NARSAD)

Research Group

Gene-Environment Neuropsychiatry (GENe)


Research Themes

Neuroscience

Areas of Excellence

Neuroscience and Psychiatry


Key Contact

For further information about this research, please contact the research group leader.

Department / Centre

Psychiatry