Longitudinal structural cerebral changes related to core CSF biomarkers in preclinical Alzheimer's disease: A study of two independent datasets

Abstract

Alzheimer's disease (AD) is characterized by an accumulation of β-amyloid (Aβ₄₂) accompanied by brain atrophy and cognitive decline. Several recent studies have shown that Aβ₄₂ accumulation is associated with gray matter (GM) changes prior to the development of cognitive impairment, in the so-called preclinical stage of the AD (pre-AD). It also has been proved that the GM atrophy profile is not linear, both in normal ageing but, especially, on AD. However, several other factors may influence this association and may have an impact on the generalization of results from different samples. In this work, we estimate differences in rates of GM volume change in cognitively healthy elders in association with baseline core cerebrospinal fluid (CSF) AD biomarkers, and assess to what these differences are sample dependent. We report the dependence of atrophy rates, measured in a two-year interval, on Aβ₄₂, computed both over continuous and categorical values of Aβ₄₂, at voxel-level (p < 0.001; k < 100) and corrected for sex, age and education. Analyses were performed jointly and separately, on two samples. The first sample was formed of 31 individuals (22 Ctrl and 9 pre-AD), aged 60-80 and recruited at the Hospital Clinic of Barcelona. The second sample was a replica of the first one with subjects selected from the ADNI dataset. We also investigated the dependence of the GM atrophy rate on the basal levels of continuous p-tau and on the p-tau/Aβ₄₂ ratio. Correlation analyses on the whole sample showed a dependence of GM atrophy rates on Aβ₄₂ in medial and orbital frontal, precuneus, cingulate, medial temporal regions and cerebellum. Correlations with p-tau were located in the left hippocampus, parahippocampus and striatal nuclei whereas correlation with p-tau/Aβ₄₂ was mainly found in ventral and medial temporal areas. Regarding analyses performed separately, we found a substantial discrepancy of results between samples, illustrating the complexities of comparing two independent datasets even when using the same inclusion criteria. Such discrepancies may lead to significant differences in the sample size needed to detect a particular reduction on cerebral atrophy rates in prevention trials. Higher cognitive reserve and more advanced pathological progression in the ADNI sample could partially account for the observed discrepancies. Taken together, our findings in these two samples highlight the importance of comparing and merging independent datasets to draw more robust and generalizable conclusions on the structural changes in the preclinical stages of AD.

Keywords: AD, Alzheimer's disease; ADNI, Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Aβ42, amyloid beta; CDR, Clinical Dementia Rating; CSF biomarkers; CSF, Cerebro-Spinal Fluid; Ctrl, control; DI, divergences of the longitudinal deformations; ELISA, Enzyme-Linked ImmunoSorbent Assay; FWE, Family Wise Error; GM, gray matter; HCB, Hospital Clinic Barcelona; L, left; Longitudinal VBM; MMSE, Mini Mental State examination; PLR, pairwise longitudinal registration; Preclinical Alzheimer's disease; R, right; ROI, region of interest; TIV, total intracranial volume; VBM, voxel-based morphometry; WM, white matter; p-tau, phosphorylated tau; preAD, preclinical Alzheimer's disease; t-tau, total tau.

Fig. 1

Plots of p-tau/Aβ₄₂ and relative hippocampal volume distributions across groups at pre time point, corrected for age and gender.

Fig. 2

Comparison of correlation of longitudinal atrophy (atrophy-rates) with continuous Aβ₄₂ (yellow) with respect to Ctrl vs PreAD two-sample t-test, i.e. categorical Aβ₄₂ (red), on the HCB + ADNI merged sample. Orange areas denote overlap of statistical maps. Correlation with continuous Aβ₄₂ showed to be more sensitive than the two-sample t-test.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 3

Correlation of longitudinal atrophy (atrophy-rates) with CSF-biomarkers: comparison of results in different samples: a) shows correlations with Aβ₄₂. b) displays correlations with p-tau. c) shows correlation with p-tau/Aβ₄₂. Detailed enumeration of regions is provided in Table 2, Table 3, Table 4, Table 5.

Fig. 4

Correlation of longitudinal atrophy (atrophy-rates) with basal CSF biomarkers in (HCB + ADNI): continuous Aβ42 (yellow), continuous p-tau (blue) and p-tau/Aβ42 (red). Orange and violet areas shows overlap of p-tau/Aβ42 maps with Aβ42 and p-tau maps, respectively. No overlap was found between Aβ42 and p-tau maps at this significance level.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 5

Plots of mean GM atrophy rate (longitudinal) versus p-tau/Aβ₄₂ for two clusters. Bilateral precuneus ROI corresponds to the significant cluster in that area in the two-sample t-test analysis on the whole sample. R-parahipocampus ROI corresponds to the significant cluster in that region in the correlation of atrophy rates with p-tau/Aβ₄₂ on the whole sample analysis. It contains voxels from adjacent regions.

Fig. 6

a) Longitudinal atrophy rates versus Aβ₄₂ on a 4 mm-radius sphere at the peak on left hippocampus of p-tau/Aβ₄₂ correlation. Values corrected for age, sex, educational level and p-tau. b) Distribution of mean longitudinal atrophy rates (white without correction, gray with correction for age, gender and education years) on the same sphere across groups.