Dataset Information

Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

ABSTRACT: We sought to develop and evaluate a composite memory score from the neuropsychological battery used in the Alzheimer's Disease (AD) Neuroimaging Initiative (ADNI). We used modern psychometric approaches to analyze longitudinal Rey Auditory Verbal Learning Test (RAVLT, 2 versions), AD Assessment Schedule - Cognition (ADAS-Cog, 3 versions), Mini-Mental State Examination (MMSE), and Logical Memory data to develop ADNI-Mem, a composite memory score. We compared RAVLT and ADAS-Cog versions, and compared ADNI-Mem to RAVLT recall sum scores, four ADAS-Cog-derived scores, the MMSE, and the Clinical Dementia Rating Sum of Boxes. We evaluated rates of decline in normal cognition, mild cognitive impairment (MCI), and AD, ability to predict conversion from MCI to AD, strength of association with selected imaging parameters, and ability to differentiate rates of decline between participants with and without AD cerebrospinal fluid (CSF) signatures. The second version of the RAVLT was harder than the first. The ADAS-Cog versions were of similar difficulty. ADNI-Mem was slightly better at detecting change than total RAVLT recall scores. It was as good as or better than all of the other scores at predicting conversion from MCI to AD. It was associated with all our selected imaging parameters for people with MCI and AD. Participants with MCI with an AD CSF signature had somewhat more rapid decline than did those without. This paper illustrates appropriate methods for addressing the different versions of word lists, and demonstrates the additional power to be gleaned with a psychometrically sound composite memory score.

SUBMITTER: Crane PK

PROVIDER: S-EPMC3806057 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Crane Paul K PK Carle Adam A Gibbons Laura E LE Insel Philip P Mackin R Scott RS Gross Alden A Jones Richard N RN Mukherjee Shubhabrata S Curtis S McKay SM Harvey Danielle D Weiner Michael M Mungas Dan D

Brain imaging and behavior 20121201 4

We sought to develop and evaluate a composite memory score from the neuropsychological battery used in the Alzheimer's Disease (AD) Neuroimaging Initiative (ADNI). We used modern psychometric approaches to analyze longitudinal Rey Auditory Verbal Learning Test (RAVLT, 2 versions), AD Assessment Schedule - Cognition (ADAS-Cog, 3 versions), Mini-Mental State Examination (MMSE), and Logical Memory data to develop ADNI-Mem, a composite memory score. We compared RAVLT and ADAS-Cog versions, and compa ...[more]

PMID: 22782295

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Project description:BackgroundRecent Alzheimer's disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD.Methods and findingsWe focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3 × 10(-13)). We applied a multivariate approach based on combinatorial optimization ((?,?)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering "meta-features," representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%.ConclusionsApplying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of plasma biomarkers for pre-clinical AD. While studies of independent test sets are required to validate the signatures, these analyses provide a starting point for developing a cost-effective and minimally invasive test capable of diagnosing AD in its pre-clinical stages.

Project description:BackgroundAlzheimer's disease (AD) is a chronic progressive neurodegenerative disease impacting an estimated 44 million adults worldwide. The causal pathology of AD (accumulation of amyloid-beta and tau), precedes hallmark symptoms of dementia by more than a decade, necessitating development of early diagnostic markers of disease onset, particularly for new drugs that aim to modify disease processes. To evaluate differentially methylated positions (DMPs) as novel blood-based biomarkers of AD, we used a subset of 653 individuals with peripheral blood (PB) samples in the Alzheimer's disease Neuroimaging Initiative (ADNI) consortium. The selected cohort of AD, mild cognitive impairment (MCI), and age-matched healthy controls (CN) all had imaging, genetics, transcriptomics, cerebrospinal protein markers, and comprehensive clinical records, providing a rich resource of concurrent multi-omics and phenotypic information on a well-phenotyped subset of ADNI participants.ResultsIn this manuscript, we report cross-diagnosis differential peripheral DNA methylation in a cohort of AD, MCI, and age-matched CN individuals with longitudinal DNA methylation measurements. Epigenome-wide association studies (EWAS) were performed using a mixed model with repeated measures over time with a P value cutoff of 1 × 10-5 to test contrasts of pairwise differential peripheral methylation in AD vs CN, AD vs MCI, and MCI vs CN. The most highly significant differentially methylated loci also tracked with Mini Mental State Examination (MMSE) scores. Differentially methylated loci were enriched near brain and neurodegeneration-related genes (e.g., BDNF, BIN1, APOC1) validated using the genotype tissue expression project portal (GTex).ConclusionsOur work shows that peripheral differential methylation between age-matched subjects with AD relative to healthy controls will provide opportunities to further investigate and validate differential methylation as a surrogate of disease. Given the inaccessibility of brain tissue, the PB-associated methylation marks may help identify the stage of disease and progression phenotype, information that would be central to bringing forward successful drugs for AD.

Dataset Information

Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Publications

Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

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