| Title: | To explore the multi-level biomarkers and mechanisms of neurodevelopmental disorders |
| Lead Institution: | Xinhua Hospital |
| Principal investigator: |
Application 94522
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About
1. What is the primary change of the brain (including functional connectivity, gray matter volume and fiber integrity) for neurodevelopmental disorders? 2. Are these changes caused by genetic variants, or environmental factors, or both? Are there interactions between them? 3. What are the associations of other physical and mental disorders with neurodevelopmental disorders? 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 and precise intervention for neurodevelopmental disorders. 2. The association between neuroimaging changes, genetic variants and various phenotypes may help target neurotransmitters crucial for drug development and treatment of neurodevelopmental disorders. Timetable: 1.data preprocessing : 3 months. Including neuroimaging and genetic data processing. 2. Whole-brain association analysis: including voxel- and region-wise analysis of functional brain networks, gray matter and white matter of the brain. 4 months 3. Nonlinear GWAS analysis: including voxel- and region-wise analysis of functional brain networks, gray matter and white matter of the brain. 2 months 4. Correlation with various behavior phenotypes and environmental factors: 3 month First we will look for changes in 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 neurodevelopmental disorders being investigated. 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.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 15356 | Disease and mortality trajectories of cognitively able autistic individuals in mid- and later adulthood | Yiwei Pu (+9) | 2025 | BMC Medicine |
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