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Calibrating longitudinal cognition in Alzheimer's disease across diverse test batteries and datasets.

ABSTRACT: BACKGROUND:We sought to identify optimal approaches by calibrating longitudinal cognitive performance across studies with different neuropsychological batteries. METHODS:We examined four approaches to calibrate cognitive performance in nine longitudinal studies of Alzheimer's disease (AD) (n = 10,875): (1) common test, (2) standardize and average available tests, (3) confirmatory factor analysis (CFA) with continuous indicators, and (4) CFA with categorical indicators. To compare precision, we determined the minimum sample sizes needed to detect 25% cognitive decline with 80% power. To compare criterion validity, we correlated cognitive change from each approach with 6-year changes in average cortical thickness and hippocampal volume using available MRI data from the AD Neuroimaging Initiative. RESULTS:CFA with categorical indicators required the smallest sample size to detect 25% cognitive decline with 80% power (n = 232) compared to common test (n = 277), standardize-and-average (n = 291), and CFA with continuous indicators (n = 315) approaches. Associations with changes in biomarkers changes were the strongest for CFA with categorical indicators. CONCLUSIONS:CFA with categorical indicators demonstrated greater power to detect change and superior criterion validity compared to other approaches. It has wide applicability to directly compare cognitive performance across studies, making it a good way to obtain operational phenotypes for genetic analyses of cognitive decline among people with AD.

SUBMITTER: Gross AL

PROVIDER: S-EPMC4297570 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Calibrating longitudinal cognition in Alzheimer's disease across diverse test batteries and datasets.

Gross Alden L AL Sherva Richard R Mukherjee Shubhabrata S Newhouse Stephen S Kauwe John S K JS Munsie Leanne M LM Waterston Leo B LB Bennett David A DA Jones Richard N RN Green Robert C RC Crane Paul K PK

Neuroepidemiology 20141113 3-4

<h4>Background</h4>We sought to identify optimal approaches by calibrating longitudinal cognitive performance across studies with different neuropsychological batteries.<h4>Methods</h4>We examined four approaches to calibrate cognitive performance in nine longitudinal studies of Alzheimer's disease (AD) (n = 10,875): (1) common test, (2) standardize and average available tests, (3) confirmatory factor analysis (CFA) with continuous indicators, and (4) CFA with categorical indicators. To compare ...[more]

PMID: 25402421

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Project description:Background: National Institute on Aging-Alzheimer's Association (NIA-AA) proposed the AT(N) system based on β-amyloid deposition, pathologic tau, and neurodegeneration, which considered the definition of Alzheimer's disease (AD) as a biological construct. However, the associations between different AT(N) combinations and cognitive progression have been poorly explored systematically. The aim of this study is to compare different AT(N) combinations using recognized biomarkers within the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Methods: A total of 341 participants were classified into cognitively unimpaired (CU; n = 200) and cognitively impaired (CI; n = 141) groups according to the clinical manifestations and neuropsychological tests. Cerebrospinal fluid (CSF) Aβ42 and amyloid-PET ([18F]flutemetamol) were used as biomarkers for A; CSF phosphorylated tau (p-tau) and tau-PET ([18F]flortaucipir) were used as biomarkers for T; CSF total tau (t-tau), hippocampal volume, temporal cortical thickness, [18F]fluorodeoxyglucose (FDG) PET, and plasma neurofilament light (NfL) were used as biomarkers for (N). Binary biomarkers were obtained from the Youden index and publicly available cutoffs. Prevalence of AT(N) categories was compared between different biomarkers within the group using related independent sample non-parametric test. The relationship between AT(N) combinations and 12-year longitudinal cognition was assessed using linear mixed-effects modeling. Results: Among the CU participants, A-T-(N)- was most common. More T+ were detected using p-tau than tau PET (p < 0.05), and more (N)+ were observed using fluid biomarkers (p < 0.001). A+T+(N)+ was more common in the CI group. Tau PET combined with cortical thickness best predicted cognitive changes in the CI group and MRI predicted changes in the CU group. Conclusions: These findings suggest that optimal AT(N) combinations to determine longitudinal cognition differ by cognitive status. Different biomarkers within a specific component for defining AT(N) cannot be used identically. Furthermore, different strategies for discontinuous biomarkers will be an important area for future studies.

Project description:Alzheimer's disease (AD) is characterized by an accumulation of ?-amyloid (A?42) accompanied by brain atrophy and cognitive decline. Several recent studies have shown that A?42 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 A?42, computed both over continuous and categorical values of A?42, 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/A?42 ratio. Correlation analyses on the whole sample showed a dependence of GM atrophy rates on A?42 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/A?42 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.

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Calibrating longitudinal cognition in Alzheimer's disease across diverse test batteries and datasets.

Publications

Calibrating longitudinal cognition in Alzheimer's disease across diverse test batteries and datasets.

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