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A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment.

ABSTRACT: The Alzheimer's Disease Neuroimaging Initiative (ADNI) measures abilities broadly related to executive function (EF), including WAIS-R Digit Symbol Substitution, Digit Span Backwards, Trails A and B, Category Fluency, and Clock Drawing. This study investigates whether a composite executive function measure based on these multiple indicators has better psychometric characteristics than the widely used individual components. We applied item response theory methods to 800 ADNI participants to derive an EF composite score (ADNI-EF) from the above measures. We then compared ADNI-EF with component measures in 390 longitudinally-followed participants with mild cognitive impairment (MCI) with respect to: (1) Ability to detect change over time; (2) Ability to predict conversion to dementia; (3) Strength of cross-sectional association with MRI-derived measures of structures involved in frontal systems, and (4) Strength of baseline association with cerebrospinal fluid (CSF) levels of amyloid ?????, total tau, and phosphorylated tau(181P). ADNI-EF showed the greatest change over time, followed closely by Category Fluency. ADNI-EF needed a 40 % smaller sample size to detect change. ADNI-EF was the strongest predictor of AD conversion. ADNI-EF was the only measure significantly associated with all the MRI regions, though other measures were more strongly associated in a few of the regions. ADNI-EF was associated with all the CSF measures. ADNI-EF appears to be a useful composite measure of EF in MCI, as good as or better than any of its composite parts. This study demonstrates an approach to developing a psychometrically sophisticated composite score from commonly-used tests.

SUBMITTER: Gibbons LE

PROVIDER: S-EPMC3684181 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment.

Gibbons Laura E LE Carle Adam C AC Mackin R Scott RS Harvey Danielle D Mukherjee Shubhabrata S Insel Philip P Curtis S McKay SM Mungas Dan D Crane Paul K PK

Brain imaging and behavior 20121201 4

The Alzheimer's Disease Neuroimaging Initiative (ADNI) measures abilities broadly related to executive function (EF), including WAIS-R Digit Symbol Substitution, Digit Span Backwards, Trails A and B, Category Fluency, and Clock Drawing. This study investigates whether a composite executive function measure based on these multiple indicators has better psychometric characteristics than the widely used individual components. We applied item response theory methods to 800 ADNI participants to deriv ...[more]

PMID: 22644789

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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.

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Dataset Information

A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment.

Publications

A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment.

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