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Neuropathology and Cognitive Scores Workgroup The role of vascular and Alzheimer’s Disease pathology in differential cognitive impairment among older adults.

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Presentation on theme: "Neuropathology and Cognitive Scores Workgroup The role of vascular and Alzheimer’s Disease pathology in differential cognitive impairment among older adults."— Presentation transcript:

1 Neuropathology and Cognitive Scores Workgroup The role of vascular and Alzheimer’s Disease pathology in differential cognitive impairment among older adults Bennett, Crane, Gavett, Farias, Jones, Mungas, & Yang March 27, 2009

2 Background Differentiating between AD and vascular pathologies pre-mortem is challenging. Several studies have suggested the two pathologies can be associated with different cognitive impairment profiles. Studies linking neuropsychological performance to dementia diagnosis that lack a gold-standard, such as neuropathological data, have limitations in making accurate predictions in live patients.

3 Purpose of the Study The study intends to examine the effects of specific neuropathology (AD and vascular pathology) on the global domain of cognitive impairment and on specific cognitive indicators by using the MIMIC model to: 1)determine whether the relationship between vascular- and AD-related cognitive impairment is unique, competitive, or synergistic; 2)determine the amount and type of vascular- and AD-related neuropathology in individual and overall cognitive measures.

4 Methods

5 Sample This study makes use of the data collected in the Religious Order Study (ROS), which began enrollment in 1994. There were 1,123 older nuns, priests, and brothers without known dementia at baseline from 40 groups across the US. The ROS investigators have achieved greater than 95% follow-up of survivors and greater than 95% autopsy rate among those eligible, with 450 brain autopsies. Analyses for this study used baseline measures of cognition derived from neuropsychological data further described below.

6 Measures Cognition. This study will include the following 17 separate cognitive functioning tests: Story A Immediate and Delayed, 48 East Boston Story Immediate and Delayed, 49 Word List Learning Trials, 50 Boston Naming Test, 51 Verbal Fluency, 52 Digit Forwards and Backwards, 48 Digit Ordering, 52- 55 Alphabetical Span, 56 Judgment of Line Orientation, 57 Number Comparison, 58 Standard Progressive Matrices, 59 and Symbol Digit Modalities Test. 60

7 Measures Episodic Memory. There were seven episodic memory tests included in this study. The first two tests were the Story A Immediate and Delayed Recall derived from the Logical Memory Test of the Weschler Memory Scales-Revised. Similar to the Story A test, the next two tests were the East Boston Story 49 Immediate and Delayed. The last three tests were the Word List Memory, World List Recall, and the Word List Recognition.

8 Measures Semantic Memory. In this study, we use the following two tests as semantic memory measures: the Boston Naming Test 51 and the Verbal Fluency test. 52 The Working Memory. The Digit Span Forwards (6 pairs of items) and the Digit Span Backward (6 pairs of items) that were administered and scored according to the Wechsler Memory Scale-Revised procedures. 48 The Digit Ordering 52 test was a variation of the Cooper and colleagues’ original version 53-55 of the test. Similar to the Digit Ordering directions, the Alphabetical Span 56 was a task in which the participant were given two to eight words to sort in alphabetical order.

9 Measures Perceptual Speed. We included a timed and oral form of the Symbol Digit Modalities Test. 60 For the Number Comparison test, participants were asked to determine whether pairs of three to ten digit sequences were the same or different. 58 Visuospatial Abilities. For non-verbal intelligence visuospatial abilities, the Standard Progressive Matrices 59 were used that included 17 abstract visual display items that was lacking one element. The Judgment of Line Orientation 57 consisted of 15 different angles in a match-to-sample format that participants were asked to estimate.

10 Measures Brain autopsies were performed at predetermined sites using standard techniques. Vascular pathology. For these analyses, the vascular measures that we included were the following: all chronic macroscopic infarctions, ischemic lesions with small amounts of hemorrhage, the number of infarctions were coded as present (one or more infarctions) or absent, the location of infarctions as cortical or subcortical, frontal and non-frontal, and right and left. We also included lipohyalinosis 26 and amyloid angiopathy. AD pathology. The global measure of AD pathology

11 Statistical Analyses We used baseline data with continuous factor indicators and neuropathology scores. The multiple indicator, multiple causes (MIMIC) model, an extension of the confirmatory factor analytic model for dichotomous dependent variables with covariates was used at baseline, mid-wave follow-up, and the last neuropsychological assessment. We used the MIMIC model to determine differences in neuropsychological test performance on specific cognitive measures and composites, whole controlling for differing levels of global cognitive impairment.

12 MIMIC Model

13 Unidimensionality There were four residual correlations included in this initial model: the word list learning trials, the 3 minute delayed recall of words from the word list learning trials, and the multiple choice recognition task from the word list learning trials; logical memory immediate and delayed (Story A and East Boston Story); digit forward with digit backward. The fit of the model was  2= 809.21, df= 113, p<.001, CFI= 0.925, and an RMSEA= 0.074. We then took the largest modification indices and correlated each pair of tests, until we derived the best fit model number: number comparisons with digit symbol timed test; digit forward with digit backward with alphabetical span; and line orientation with rate of progressive matrices (nonverbal intelligence visuospatial abilities). A sufficiently unidimensional model (  2 =455.47, df=109, p<.001, CFI=0.963, and an RMSEA=0.053) allowing a small number of residual correlations to account for some local dependencies (e.g., among word list learning trials).

14 Summary of Results

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