Publications

Cognitive impairment is common among individuals with heart failure. The purpose of this study was to compare cognitive profiles of individuals with systolic and diastolic dysfunction. Eighty individuals with heart failure completed the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Mini-Mental State Examination, Trail Making Test, and letter fluency. Approximately 25% of individuals with systolic dysfunction were impaired on the RBANS Total Scale score, compared with only 3% in the diastolic group. Additionally, individuals with systolic dysfunction scored lower than those with diastolic dysfunction on tests of immediate and delayed memory. The groups did not differ on tests of visuospatial skills, but there were mixed results on the RBANS Attention and Language subtests. Overall, the results of this study suggest that individuals with different types of cardiac dysfunction (systolic and diastolic dysfunction) demonstrate differential patterns of performance on neuropsychological tests. These findings have important clinical implications.

The goal of the current study was to examine cognitive change in both healthy controls (n = 229) and individuals with mild cognitive impairment (MCI) (n = 397) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied latent growth modeling to examine baseline and longitudinal change over 36 months in five cognitive factors derived from the ADNI neuropsychological test battery (memory, executive function/processing speed, language, attention and visuospatial). At baseline, MCI patients demonstrated lower performance on all of the five cognitive factors when compared to controls. Both controls and MCI patients declined on memory over 36 months; however, the MCI patients declined at a significantly faster rate than controls. The MCI patients also declined over 36 months on the remaining four cognitive factors. In contrast, the controls did not exhibit significant change over 36 months on the non-memory cognitive factors. Within the MCI group, executive function declined faster than memory, while the other factor scores changed slower than memory over time. These findings suggest different patterns of cognitive change in healthy older adults and MCI patients. The findings also suggest that, when compared with memory, executive function declines faster than other cognitive factors in patients with MCI. Thus, decline in non-memory domains may be an important feature for distinguishing healthy older adults and persons with MCI.

Recent changes in diagnostic criteria for Alzheimer's disease (AD) state that biomarkers can enhance certainty in a diagnosis of AD. In the present study, we combined cognitive function and brain morphology, a potential imaging biomarker, to predict conversion from mild cognitive impairment to AD. We identified four biomarkers, or cortical signatures of cognition (CSC), from regressions of cortical thickness on neuropsychological factors representing memory, executive function/processing speed, language, and visuospatial function among participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Neuropsychological factor scores were created from a previously validated multidimensional factor structure of the neuropsychological battery in ADNI. Mean thickness of each CSC at the baseline study visit was used to evaluate risk of conversion to clinical AD among participants with mild cognitive impairment (MCI) and rate of decline on the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score. Of 307 MCI participants, 119 converted to AD. For all domain-specific CSC, a one standard deviation thinner cortical thickness was associated with an approximately 50% higher hazard of conversion and an increase of approximately 0.30 points annually on the CDR-SB. In combined models with a domain-specific CSC and neuropsychological factor score, both CSC and factor scores predicted conversion to AD and increasing clinical severity. The present study indicated that factor scores and CSCs for memory and language both significantly predicted risk of conversion to AD and accelerated deterioration in dementia severity. We conclude that predictive models are best when they utilize both neuropsychological measures and imaging biomarkers.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a large multi-center study designed to develop optimized methods for acquiring longitudinal neuroimaging, cognitive, and biomarker measures of AD progression in a large cohort of patients with Alzheimer's disease (AD), patients with Mild Cognitive Impairment, and healthy controls. Detailed neuropsychological testing was conducted on all participants. We examined the factor structure of the ADNI Neuropsychological Battery across older adults with differing levels of clinical AD severity based on the Clinical Dementia Rating Scale (CDR). Confirmatory factor analysis (CFA) of 23 variables from 10 neuropsychological tests resulted in five factors (memory, language, visuospatial functioning, attention, and executive function/processing speed) that were invariant across levels of cognitive impairment. Thus, these five factors can be used as indicators of cognitive function in older adults who are participants in ADNI.