Dataset Information

Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: The PACC5.

ABSTRACT:

Introduction

Amyloid-related decline in semantic memory was recently shown to be observable in the preclinical period of Alzheimer's disease. Cognitive composites designed to be sensitive to cognitive change in preclinical Alzheimer's disease (e.g., preclinical Alzheimer's cognitive composite [PACC]) and currently used in secondary prevention trials do not currently integrate measures of semantic processing. Our objective was to determine whether a standard semantic measure (i.e., category fluency [CAT] to animals, fruits, and vegetables) adds independent information above and beyond A?-related decline captured by the PACC.

Methods

Clinically normal older adults from the Harvard Aging Brain Study were identified at baseline as A?+ (n = 70) or A?- (n = 209) using Pittsburgh compound B-positron emission tomography imaging and followed annually with neuropsychological testing for 3.87 ± 1.09 years. The relationships between PACC, CAT, and variations of the PACC including/excluding CAT were examined using linear mixed models controlling for age, sex, and education. We additionally examined decline on CAT by further grouping A?+ participants into preclinical stage 1 and stage 2 on the basis of neurodegeneration markers.

Results

CAT explained unique variance in amyloid-related decline, with A?+'s continuing to decline relative to A?-'s in CAT even after controlling for overall PACC decline. In addition, removal of CAT from the PACC resulted in a longitudinal A?+/- effect size reduction of 20% at 3-year follow-up and 12% at 5-year follow-up. Finally, both stage 1 and stage 2 participants declined on CAT in comparison with stage 0, suggesting CAT declines early within the preclinical trajectory.

Conclusion

Addition of CAT to the PACC provides unique information about early cognitive decline not currently captured by the episodic memory, executive function, and global cognition components and may therefore improve detection of early A?-related cognitive decline.

SUBMITTER: Papp KV

PROVIDER: S-EPMC5726754 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Publications

Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: The PACC5.

Papp Kathryn V KV Rentz Dorene M DM Orlovsky Irina I Sperling Reisa A RA Mormino Elizabeth C EC

Alzheimer's & dementia (New York, N. Y.) 20171110 4

<h4>Introduction</h4>Amyloid-related decline in semantic memory was recently shown to be observable in the preclinical period of Alzheimer's disease. Cognitive composites designed to be sensitive to cognitive change in preclinical Alzheimer's disease (e.g., preclinical Alzheimer's cognitive composite [PACC]) and currently used in secondary prevention trials do not currently integrate measures of semantic processing. Our objective was to determine whether a standard semantic measure (i.e., catego ...[more]

PMID: 29264389

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Project description:BACKGROUND:There is growing interest in identifying sensitive composite cognitive tests to serve as primary endpoints in preclinical Alzheimer's disease (AD) treatment trials. We reported previously a composite cognitive test score sensitive to tracking preclinical AD decline up to 5?years prior to clinical diagnosis. Here we expand upon and refine this work, empirically deriving a composite cognitive test score sensitive to tracking preclinical AD decline up to 11?years prior to diagnosis and suitable for use as a primary endpoint in a preclinical AD trial. METHODS:This study used a longitudinal approach to maximize sensitivity to tracking progressive cognitive decline in people who progressed to the clinical stages of AD (n =?868) compared to those who remained cognitively unimpaired during the same time period (n =?989), thereby correcting for normal aging and practice effects. Specifically, we developed the Alzheimer's Prevention Initiative Preclinical Composite Cognitive test (APCC) to measure very early longitudinal cognitive decline in older adults with preclinical AD. Data from three cohorts from Rush University were analyzed using a partial least squares (PLS) regression model to identify optimal composites within different time periods prior to diagnosis, up to 11?years prior to diagnosis. The mean-to-standard deviation ratio (MSDRs) is an indicator of sensitivity to change and was used to inform the final calculation of the composite score. RESULTS:The optimal composite, the APCC, is calculated: 0.26*Symbol Digit Modalities +?2.24*MMSE Orientation to Time?+?2.14*MMSE Orientation to Place +?0.53*Logical Memory Delayed Recall +?1.36* Word List-Delayed Recall +?0.68*Judgment of Line Orientation +?1.39*Raven's Progressive Matrices Matrices (subset of 9 items from A and B). The MSDR of the APCC in a population of preclinical AD individuals who eventually progress to cognitive impairment, compared to those who remained cognitively unimpaired during the same time period, was -?1.10 over 1 year. CONCLUSIONS:The APCC is an empirically derived composite cognitive test score with high face validity that is sensitive to preclinical AD decline up to 11?years prior to diagnosis of the clinical stages of AD. The components of the APCC are supported by theoretical understanding of cognitive decline that occurs during preclinical AD. The APCC was used as a primary outcome in the API Generation Program trials.

Project description:As Alzheimer disease (AD) research moves to intervene in presymptomatic phases of the disease, we must develop outcome measures sensitive to the earliest disease-related changes.To demonstrate the feasibility of a cognitive composite outcome for clinically normal elderly participants with evidence of AD pathology using the ADCS Preclinical Alzheimer Cognitive Composite (ADCS-PACC). The ADCS-PACC combines tests that assess episodic memory, timed executive function, and global cognition. The ADCS-PACC is the primary outcome measure for the first clinical trial in preclinical AD (ie, the Anti-Amyloid Treatment in Asymptomatic Alzheimer's study).With the ADCS-PACC, we derive pilot estimates of amyloid-related decline using data from 2 observational studies conducted in North America and another conducted in Australia. The participants analyzed had normal cognition and mean ages of 75.81, 71.37, and 79.42 years across the 3 studies.For the 2 studies that collected data on A? levels (ADNI and AIBL), we estimate decline in a preclinical AD "A?-positive" placebo group and compare them with an "A?-negative" group. For the study that did not include data on A? levels (the ADCS Prevention Instrument [ADCS-PI] study), we grouped participants by the presence of APOE-?4 and by clinical progression.In ADNI, A?-positive participants showed more decline than did A?-negative participants with regard to the ADCS-PACC score at 24 months (mean [SE] difference, -1.239 [0.522] [95% CI, -2.263 to -0.215]; P?=?.02). In AIBL, the mean (SE) difference is significant at both 18 months (-1.009 [0.406] [95% CI, -1.805 to -0.213]; P?=?.01) and 36 months (-1.404 [0.452] [95% CI, -2.290 to -0.519]; P?=?.002). In the ADCS-PI study, APOE-?4 allele carriers performed significantly worse on the ADCS-PACC at 24 months (mean [SE] score, -0.742 [0.294] [95% CI, -1.318 to -0.165]; P?=?.01) and 36 months (-1.531 [0.469] [95% CI, -2.450 to -0.612]; P?=?.001). In the ADCS-PI study, cognitively normal participants who progress from a global Clinical Dementia Rating score of 0 are significantly worse on the ADCS-PACC than cognitively normal participants who are stable with a global Clinical Dementia Rating score of 0 at months 12, 24, and 36 (mean [SE] ADCS-PACC score, -4.471 [0.702] [95% CI, -5.848 to -3.094]; P?<?.001). Using pilot estimates of variance and assuming 500 participants per group with 30% attrition and a 5% ? level, we project 80% power to detect effects in the range of ??=?0.467 to 0.733 on the ADCS-PACC.Analyses of at-risk cognitively normal populations suggest that we can reliably measure the first signs of cognitive decline with the ADCS-PACC. These analyses also suggest the feasibility of secondary prevention trials.

Dataset Information

Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: The PACC5.

Introduction

Methods

Results

Conclusion

Publications

Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: The PACC5.

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