Research Questions
1. How do genetic predisposition, environmental exposure, lifestyle factors, and comorbidities interact to influence the onset and progression of neurological diseases?
2. What are the key biomarkers and molecular pathways that can be used for early detection, prognosis, and therapeutic intervention in neurological diseases?
Research objectives
1. Risk assessment model: Establish a multi-factor risk assessment framework by integrating genetic, environmental, lifestyle, and biomarker data to predict susceptibility to neurological diseases.
2. Mechanism elucidation: Study molecular mechanisms and key biomarkers associated with neurological diseases through advanced multi-omics analysis, including imaging, genomics, proteomics, and metabolomics.
3. Prognostic tools: Use machine learning techniques and statistical models to identify predictors of disease outcomes to provide accurate prognostic assessments for personalized treatment.
Scientific Rationale
1. Multifactorial complexity: neurological diseases are influenced by a complex network of genetic, environmental, and behavioral factors. A systematic analysis of these interactions can provide greater insight into the cause and progression of the disease.
2. Innovative analytical methods: Advanced methods such as genome-wide association studies (GWAS), Mendelian randomization, and machine learning provide new opportunities to identify causal factors and prognostic indicators.
3. Integration of multi-omics data: Use comprehensive data sets, including imaging, genetic, plasma metabolite and biomarker profiles, to help discover new molecular pathways and therapeutic targets.
4. Personalized medicine: By identifying key risk factors and molecular signatures, this study can guide the development of tailored prevention, diagnosis, and treatment interventions that can help improve clinical outcomes and public health strategies.
