Abstract
Alzheimer’s disease (AD), the most common form of dementia, shares many aspects of abnormal brain aging. We present a novel magnetic resonance imaging (MRI)-based biomarker that predicts the individual progression of mild cognitive impairment (MCI) to AD on the basis of pathological brain aging patterns. By employing kernel regression methods, the expression of normal brain-aging patterns forms the basis to estimate the brain age of a given new subject. If the estimated age is higher than the chronological age, a positive brain age gap estimation (BrainAGE) score indicates accelerated atrophy and is considered a risk factor for conversion to AD. Here, the BrainAGE framework was applied to predict the individual brain ages of 195 subjects with MCI at baseline, of which a total of 133 developed AD during 36 months of follow-up (corresponding to a pre-test probability of 68%). The ability of the BrainAGE framework to correctly identify MCI-converters was compared with the performance of commonly used cognitive scales, hippocampus volume, and state-of-the-art biomarkers derived from cerebrospinal fluid (CSF). With accuracy rates of up to 81%, BrainAGE outperformed all cognitive scales and CSF biomarkers in predicting conversion of MCI to AD within 3 years of follow-up. Each additional year in the BrainAGE score was associated with a 10% greater risk of developing AD (hazard rate: 1.10 [CI: 1.07–1.13]). Furthermore, the post-test probability was increased to 90% when using baseline BrainAGE scores to predict conversion to AD. The presented framework allows an accurate prediction even with multicenter data. Its fast and fully automated nature facilitates the integration into the clinical workflow. It can be exploited as a tool for screening as well as for monitoring treatment options.
Highlights
The global prevalence of dementia is projected to rise sharply over the coming decades
The baseline BrainAGE scores significantly differed between the diagnostic groups (F = 26.04; p,0.001), resulting in the following means: pMCI_early = 8.73 years, pMCI_late = 5.62 years, and sMCI = 0.75 years
Cognitive abilities substantially declined during the follow-up intervals in both pMCI groups but remained stable in those who did not convert to Alzheimer’s disease (AD) (Figure 3A-C)
Summary
The global prevalence of dementia is projected to rise sharply over the coming decades. Manifold pathological changes begin to develop years or decades before the onset of cognitive decline [2], including premature changes in gene expression [3,4], accelerated age-associated changes of the default mode network [5], and most obviously, abnormal changes in brain structures already at the mild cognitive impairment (MCI) stage [6,7]. The best validated biomarkers for an early detection include markers of brain b-amyloid-plaque (Ab) deposition, i.e. decreased CSF Ab42 and positive Pittsburgh compound B (PiB) amyloid imaging, as well as markers of neurodegeneration, i.e. increased CSF tau, decreased fluorodeoxyglucose uptake on PET (FDGPET), and structural magnetic resonance imaging (MRI) measures of cerebral atrophy [2]. Brain atrophy in general is not specific for AD, MRI-detected atrophy was found to retain the closest relationship with cognitive decline [2,22,23] suggesting a crucial role for structural MRI in predicting future conversion to AD [2,24]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
