Identifying the healthy aging pattern of topological asymmetry of human brain networks and the underlying pathway between gene, brain asymmetry and cognitive
Principal Investigator: Dr Gaolang Gong
Approved Research ID: 31282
Approval date: July 1st 2017
Human brain is structurally and functionally asymmetrical. A number of asymmetries in brain phenotypes change dynamically during aging. From the perspective of brain network, abnormal topological asymmetries are found in age-related diseases while little is known about how topological asymmetries changes during healthy aging. Thus, we aim to explore how topological asymmetry of brain networks changes during healthy aging and to identify candidate genetic factors underlying these asymmetry changes and cognitive declines. This will help to uncover the neural and genetic mechanism of age-related asymmetry changes and to provide a whole picture of gene-brain-behavior pathway. Older adults face special physical challenges and deficits in a myriad of cognitive domains. As the world?s older population growing dramatically, mental and behavioral health are need to be taken seriously. Our research will explore the age-related changes in topological asymmetry of brain network to form a normal aging pattern of brain topological asymmetry. Furthermore, identification of genetic biomarkers for this aging pattern and establishment the association between genetic factors, brain topological asymmetry and cognitive performances during healthy aging are expected to help to better understand the age-related neural and cognitive changes and to facilitate early diagnosis. We will first construct the human functional and anatomical networks based on multi-modal brain imaging data and then apply graph theory approaches to calculate the topological properties at both regional and global levels. Statistical analyses will be conducted to test the age-related changing pattern of hemispheric asymmetries of the brain. A GWAS analysis is then performed to identify the SNPs that are associated with these changes. Finally, both imaging-derived topological asymmetry aging pattern and genetic variants will be correlated to various cognitive abilities to form the gene-brain-behavior pathway. We want all the data for the participants who have brain MRI data.