Approved Research

Predicting the conversion of normal cognition to mild cognitive impairment and dementia using multimodal MRI and genetic biomarkers

Lay summary

Alzheimer's disease (AD) is a global concern. Due to the lack of effective therapeutic methods targeting late-stage AD patients, it is critical to investigate brain alterations in the preclinical stage to pave the way for early diagnosis and intervention. Structural and functional magnetic resonance imaging (MRI) has been proven to be an effective and non-invasive approach for exploring the neural mechanisms underlying neurological disorders. Genetic factors such as apolipoprotein E play an important role in AD development and progression. However, the interaction effects of risk genes and different biological pathways implicated in the pathogenesis of AD remain unclear. Furthermore, a prognostic model which could predict future cognitive decline or clinical progression based on objective features derived from baseline demographic, cognitive, multimodal MRI, and genetic data needs to be further explored.

We aim to investigate the neural basis underlying early cognitive deficits using structural and functional MRI data combined with novel analytical methods such as dynamic functional connectivity, surface-based morphometry, graph theory, multilayer network, functional-structural coupling, hidden Markov model, and connectome gradient mapping. Secondly, to explore the interaction effects of risk genes, which may help a better illustration of different biological pathways implicated in the pathogenesis of Alzheimer's disease. Thirdly, to investigate the divergent and dynamic abnormalities of multimodal imaging markers across different stages of Alzheimer's disease, which may enhance our understanding of the neuropathological mechanisms. Fourthly, to provide scientific evidence on the potential targets for early intervention of neurodegenerative diseases. Lastly, to establish a prognostic model which could help the preclinical identification of subjects at higher risk of clinical progression to mild cognitive impairment and dementia based on combined features of baseline multimodal MRI and genetic biomarkers. These studies may help a better understanding of the neural and biological basis underlying AD and pave the way for early diagnosis and intervention.

We propose to complete this project in 36 months.

Public health impact: the identification of these novel gene variants might provide valuable insights into the molecular mechanisms with important roles in AD pathogenesis. The study of imaging markers is helpful to the early diagnosis and pathogenesis of AD. On the whole, this study will help to promote the continuous refinement and concretization of various AD-related biological markers, and help clinicians and researchers understand pathogenesis deeper and more global.