| Title: | Neuroimaging based phenome-wide association study (PheWAS) |
| Lead Institution: | University of Southern California |
| Principal investigator: | Dr Lu Zhao |
Application 25641
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About
We aim to develop a new, big data discovery framework for neuroimaging based phenome-wide association study (PheWAS). This big data discovery approach will be applied to systematically explore relationships between SNPs of interest and a wide variety of neuroimaging phenotypes using a unified genotype-to-phenotype strategy, so as to achieve a broad survey for true system-level genetic influences on the brain. The extensive resource of neuroimaging and genomic data provided by Biobank will allow us to evaluate the performance of the developed tools and software in big, complex data management and its processing and analysis. And the biobank resource will allow us to conduct true PheWAS to validate existing GWAS or single-phenotype studies' findings, and more importantly to discover novel gene-brain associations. The expected finding will improve our understanding of the genetic pathways shaping the function, anatomy and connectivity of the brain in healthy populations, and further the pathology of diseased brains. Some advanced software and tools will be developed to manage and structure the complex, heterogenous, big-volume neuroimaging genomic data archives, and to implement sophisticated image processing and statistical analyses. The biobank data will be applied to evaluate the performance of these tools. Scientific researches will then be conduced using the developed tools and approaches for mining the biobank database for true system-level associations of SNPs of interest with diverse brain phenotypes. Full cohort.4 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 11264 | Different effects of cardiometabolic syndrome on brain age in relation to gender and ethnicity | Sung Hoon Kang (+18) | 2023 | Alzheimer's Research & Therapy |
| 11662 | Ethnic differences in the effects of apolipoprotein E ɛ4 and vascular risk factors on accelerated brain aging | Yanghee Im (+15) | 2024 | Brain Communications |
| 7245 | Mapping Complex Brain Torque Components and Their Genetic Architecture and Phenomic Associations in 24,112 Individuals | Lu Zhao (+4) | 2021 | Biological Psychiatry |
| 7328 | Predictive Big Data Analytics using the UK Biobank Data | Yiwang Zhou (+8) | 2019 | Scientific Reports |
Enabling scientific discoveries that improve human health