Principal Investigator: Professor Jianfeng Feng
Department: Computer ScienceTags: 19542, biomarkers, networks, Nonlinear GWAS, Wholebrain analysis
- Professor Gunter Schumann
- Professor Jie Zhang
- Professor Keith Kendrick
- Dr Lena Palaniyappan
Collaborating Institutions and Addresses:
- King’s College London, MRC Social Genetic and Developmental Psychiatry, Institute of Psychiatry, 16 De Crespigny Park, London SE5 8AF, United Kingdom.
- Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, 220 Handan Road, Shanghai 200433, China.
- University of Electronic Science and Technology of China, School of Life Science and Technology, 2006 Xiyuan Avenue, West Hi-Tech Zone, Chengdu 611731, China.
- University of Western Ontario, Department of Psychiatry, A2-636, LHSC-Victoria Hospital, 800 Commissioners Road East, London N6A 5W9, Canada.
Funding body: National Natural Science Foundation of China
1a: 1. What is the primary change of the brain (including functional connectivity, gray matter volume and fiber integrity) for major psychiatric disorders?
- Are these changes caused by genetic variants, or environmental factors, or both? Are there interactions between them?
- What are the main neurotransmitter dysfunctions for various mental disorders? What brain regions are influenced by these neurotransmitter dysfunctions?
1b: Our proposal meets the purpose of Biobank by two important goals raised: 1. Identification of sensitive neuro- and genetic biomarkers is expected to help early diagnosis of major mental disorders and 2. The association between neuroimaging changes, genetic variants and various phenotypes may help target neurotransmitters crucial for drug development and treatment of the mental disorders.
1c: First we will look for changes in multimodal neuroimaging data and identify brain regions with significant alteration. A GWAS analysis in then carried out to find SNPs that is potentially responsible for these changes. Both neuroimaging changes and genetic variants will be correlated with various behavior phenotypes so that a closed loop among neuroimaging alterations, genetic variants, and behavior phenotypes will be identified which may help understand the etiology of the mental disorders being investigated.
1d: As we are using whole brain association analysis and GWAS analysis with tens of thousands of variables, we would using the whole cohort data, including data now being available and future data when available.
Last updated on April 24th, 2017