| Title: | Unraveling Mechanisms of Neurodegenerative Diseases and Their Comorbidities via Multi-omics Integration |
| Lead Institution: | The First Affiliated Hospital of Nanchang University |
| Principal investigator: |
Application 1029284
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About
Research Question and Objectives Neurodegenerative diseases (NDDs), including Alzheimer's and Parkinson's diseases, affect over 65 million people globally and are projected to rise with aging populations. Despite their high burden, no disease-modifying therapies or effective preventive strategies exist. A major challenge is the frequent co-occurrence of NDDs with systemic comorbidities-such as metabolic, cardiovascular, renal, and immune disorders-that worsen prognosis and accelerate neurodegeneration. However, the mechanisms linking these systemic conditions to brain pathology remain poorly understood. To address this gap, we propose an integrative multi-omics approach combining genomics, proteomics, metabolomics, and imaging omics, leveraging large-scale cohorts . Our aims are threefold: (1) characterize molecular and neuroimaging changes in neurodegenerative diseases with metabolic and other comorbidities; (2) identify shared biological pathways and integrative biomarkers that link systemic dysfunction to brain health, pointing to potential therapeutic targets; and (3) develop and validate predictive models for early detection and risk assessment to support timely intervention. While prior studies have identified key features of neurodegenerative diseases (NDDs)-such as protein aggregation, metabolic dysregulation, and genetic risk-most rely on single-omics or observational data, limiting causal insight and understanding of systemic influences. Circulating proteins and metabolites reflect genetic, molecular, and environmental factors, while neuroimaging links these to brain structure and function. By integrating multi-omics data within robust epidemiological frameworks, this study will uncover novel biomarkers, clarify how systemic conditions influence NDD progression, and develop predictive models-advancing early detection and intervention through a comprehensive, systems-level approach.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 18042 | Joint associations of grip strength, lipid levels, and lipid-related genetic risk with atrial fibrillation | Zihao Zhang (+15) | 2026 | Lipids in Health and Disease |
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