Dataset Information

Serial MRI and CSF biomarkers in normal aging, MCI, and AD.

ABSTRACT:

Objective

To compare the annual change in MRI and CSF biomarkers in cognitively normal (CN), amnestic mild cognitive impairment (aMCI), and Alzheimer disease (AD). Comparisons were based on intergroup discrimination, correlation with concurrent cognitive/functional changes, relationships to APOE genotype, and sample sizes for clinical trials.

Methods

We used data from the Alzheimer's Disease Neuroimaging Initiative study consisting of CN, aMCI, and AD cohorts with both baseline and 12-month follow-up CSF and MRI. The annual change in CSF (total-tau [t-tau], Abeta(1-42)) and MRI (change in ventricular volume) was obtained in 312 subjects (92 CN, 149 aMCI, 71 AD).

Results

There was no significant average annual change in either CSF biomarker in any clinical group except t-tau in CN; moreover, the annual change did not differ by clinical group in pairwise comparisons. In contrast, annual increase in ventricular volume increased in the following order, AD > aMCI > CN, and differences were significant between all clinical groups in pairwise comparisons. Ventricular volume increase correlated with concurrent worsening on cognitive/functional indices in aMCI and AD whereas evidence of a similar correlation with change in CSF measures was unclear. The annual changes in MRI differed by APOE epsilon4 status overall and among aMCI while annual changes in CSF biomarkers did not. Estimated sample sizes for clinical trials are notably less for MRI than the CSF or clinical measures.

Conclusions

Unlike the CSF biomarkers evaluated, changes in serial structural MRI are correlated with concurrent change on general cognitive and functional indices in impaired subjects, track with clinical disease stage, and are influenced by APOE genotype.

SUBMITTER: Vemuri P

PROVIDER: S-EPMC2905929 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and 18F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the 18F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on 18F-FDG SUVR. CSF measures included Aβ1-42, Aβ1-40, T-tau, P-tau181, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = -0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or 18F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters.