Approved Research

Prediction of progression of Alzheimer's disease (AD) in early stage using quantitative susceptibility mapping (QSM) image in UK Biobank brain imaging

Lay summary

Background/scientific rationale: Recently, emerging evidence shows that Alzheimer's disease (AD) has a long and protracted preclinical stage, and earlier treatments are desired since most available drugs can only slowdown the progression of the disease. As a result, detection of preclinical AD before symptoms presented becomes more important. Previous studies showed that iron is elevated in brains with AD and iron deposition appears before structural changes of magnetic resonance imaging (MRI) and positron emission tomography (PET) images. This implies that iron deposition image of brain obtained by MRI scan may be used as a predictive marker to detect preclinical AD.

Aims: We aim to investigate how effective the iron deposition image obtained by MRI scan are for detecting preclinical AD alone or combining with other biomarkers including Apolipoprotein E (ApoE) genotype, Amyloid !, phosphorylated protein tau (pTau), structural MRI images and cognitive test scores. To achieve it, we plan to build a predictive model using both images and non-image information to detect preclinical AD.

Project duration and plan of investigation: We propose this study as a three-year project from the date of data access. Participants with at least an iron deposition image obtained by MRI scan and a follow up period between 2 to 5 years from the date of the first scan will be included in this study. Demographical information, structural MRI Images, cognitive test scores, ApoE genotype and biomarkers such as cerebrospinal fluid and/or plasma amyloid ! and pTau within a period of ±6 months around the date of the first scan, will also be collected from UK Biobank. Preclinical AD which had normal cognitive scores at the time of the first scan but progressed to mild cognitive impairment (MCI) or AD in a follow up period of 2 to 5 years will be identified from the linkage to the National Health Service (NHS) records. Predictive models will be built to detect preclinical AD using iron deposition and structural images obtained by MRI scan and non-image information.

Public health impact: The project will establish quantitative evidence of the effectiveness of iron deposition images obtained by MRI scan for predicting disease progression in early stage of AD. A successful outcome of this study will lead to an improvement of the AD progression prediction and more opportunities to treat AD in preclinical stage. Main output of this study will be publications in peer-reviewed journals, conference papers in AD and related conferences.