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Two-dimensional enrichment analysis for mining high-level imaging genetic associations.
Xiaohui Yao1,2, Jingwen Yan1, Sungeun Kim1
1Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street Suite 4100, Indianapolis, IN, USA.
Brain Informatics
|October 18, 2016
Summary
Imaging Genetic Enrichment Analysis (IGEA) extends pathway analysis to brain imaging genetics. This new framework links gene sets with brain circuits to uncover neurobiological insights for complex diseases.
Area of Science:
- Neuroscience
- Genetics
- Bioinformatics
Background:
- Enrichment analysis is crucial in genome-wide association studies for interpreting genetic associations with phenotypes.
- Brain imaging genetics, studying genetic influences on brain structure and function, presents challenges due to high-dimensional data.
Purpose of the Study:
- To introduce Imaging Genetic Enrichment Analysis (IGEA), a novel paradigm for brain imaging genetics.
- To jointly analyze gene sets (GS) and brain circuits (BC) for enriched gene-QT associations.
Main Methods:
- Developed the IGEA framework integrating gene expression data (Allen Human Brain Atlas) and imaging genetics data (Alzheimer's Disease Neuroimaging Initiative).
- Evaluated the framework through a proof-of-concept study to identify significant GS-BC pairs.
Main Results:
- Identified 25 significant high-level two-dimensional imaging genetics modules.
- Demonstrated relevance of identified modules to neurobiological pathways and neurodegenerative diseases.
Conclusions:
- The IGEA framework offers a promising approach for brain imaging genetics research.
- IGEA provides valuable insights into the mechanisms underlying complex diseases by linking genetic variations to brain imaging traits.
