Functional Magnetic Resonance Imaging of Semantic Memory as a Presymptomatic Biomarker of Alzheimer’s Disease Risk

Extensive research efforts have been directed toward strategies for predicting risk of developing Alzheimer\u27s disease (AD) prior to the appearance of observable symptoms. Existing approaches for early detection of AD vary in terms of their efficacy, invasiveness, and ease of implementation. Several non-invasive magnetic resonance imaging strategies have been developed for predicting decline in cognitively healthy older adults. This review will survey a number of studies, beginning with the development of a famous name discrimination task used to identify neural regions that participate in semantic memory retrieval and to test predictions of several key theories of the role of the hippocampus in memory. This task has revealed medial temporal and neocortical contributions to recent and remote memory retrieval, and it has been used to demonstrate compensatory neural recruitment in older adults, apolipoprotein E ε4 carriers, and amnestic mild cognitive impairment patients. Recently, we have also found that the famous name discrimination task provides predictive value for forecasting episodic memory decline among asymptomatic older adults. Other studies investigating the predictive value of semantic memory tasks will also be presented. We suggest several advantages associated with the use of semantic processing tasks, particularly those based on person identification, in comparison to episodic memory tasks to study AD risk. Future directions for research and potential clinical uses of semantic memory paradigms are also discussed. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease

Dementia and Primary-Care Health Measures:Hearing, Gait, and Markers of Inflammation

Dementia is a syndrome associated with declining cognitive function that has a variety of types and causes, and is encountered frequently in general medical practice. Researchers are actively exploring possible risk factors for dementia. The St. Louis University Mental Status (SLUMS) exam is a dementia-screening exam used in primary care visits to detect cognitive impairment that may be a sign of dementia. This study compared scores on the SLUMS exam to other measures recorded in a typical primary care visit in 86 patients of age 65 and older to look for correlations between indicators of health, such as physical examination measures and complete blood count panels, and cognitive impairment, as measured by score on the SLUMS exam. Abnormal gait was associated with a lower score on the SLUMS exam compared to normal (p=.006), failure of the hearing test in both ears was associated with a lower score on the SLUMS exam compared to patients passing the hearing test in one or both ears (p=.046), red blood cell count was positively correlated with SLUMS exam score (p=.020), white blood cell count was negatively correlated with SLUMS exam score (p=.003), and serum albumin levels were negatively correlated with SLUMS exam score (p=.002). These data support the view that both physical impairments and markers of an inflammatory response are related to dementia

Lifestyle and Genetic Contributions to Cognitive Decline and Hippocampal Structure and Function in Healthy Aging

Background: Engagement in cognitively stimulating activities (CA) and leisure time physical activity (PA) have been associated with maintaining cognitive performance and reducing the likelihood of cognitive decline in older adults. However, neural mechanisms underlying protective effects of these lifestyle behaviors are largely unknown. In the current study, we investigated the effect of self-reported PA and CA on hippocampal volume and semantic processing activation during a fame discrimination task, as measured by functional magnetic resonance imaging (fMRI). We also examined whether possession of the apolipoprotein E (APOE) ?4 allele could moderate the effect of PA or CA on hippocampal structure or function. Methods: Seventy-eight healthy, cognitively intact older adults underwent baseline neuropsychological assessment, hippocampal volume measurement via manually-traced structural MRI, and task-activated fMRI. Results: After 18 months, 27 participants declined by one standard deviation or more on follow-up neuropsychological testing. Logistic regression analyses revealed that CA alone or in combination with baseline hippocampal structure or functional activity did not predict the probability of cognitive decline. In contrast, PA interacted with APOE 4 status such that engagement in PA reduced the risk of cognitive decline in APOE 4 carriers only. Furthermore, the benefits of PA appeared to diminish with reduced functional activity or volume in the hippocampus. Conclusions: Our findings suggest that increased leisure time PA is associated with reduced probability of cognitive decline in persons who are at high risk for AD. The beneficial effects of PA in this group may be related to enhancement of the functional and structural integrity of the hippocampus

Variables Influencing Help-Seeking Intentions For Early Symptoms Of Alzheimer’s Disease In An American Indian And Alaska Native Sample

Guided by the Sociocultural Health Belief Model (SHBM) of dementia care-seeking, this study aimed to evaluate the role of several factors, including health system barriers, cultural beliefs and knowledge of Alzheimer’s disease, in predicting help-seeking intentions for early symptoms of Alzheimer’s disease among American Indians/Alaska Natives (AI/ANs). Participant recruitment and study procedures took place online. Participants completed a series of online surveys designed to assessed predictor variables from the proposed model and help-seeking intentions from several care sources (i.e., informal, traditional, and biomedical). A total of 118 participants were included in the final sample. Three-step hierarchical regressions were conducted to evaluate the ability of the proposed model to predict help-seeking intentions for each type of care source. Results found the proposed model was significant in predicting help-seeking intentions for biomedical sources, but for predicting help-seeking intentions from informal or traditional sources. Alzheimer’s disease factual knowledge was found to be a significant predictor in biomedical help-seeking intentions. Results from this study contributed to our knowledge of how Alzheimer’s disease is understood by AI/ANs and may be useful for guiding future research and interventions related to timely recognition and care of Alzheimer’s disease in AI/ANs communities

Understanding preclinical dementia : early detection of dementia through cognitive and biological markers

Dementia is becoming a growing healthcare crisis, therefore identifying individuals at risk or in the earliest stages of dementia is essential if prevention or disease modification is to be achieved. The objective of this thesis was to examine cognitive performance and decline during the preclinical phase and explore the ability of cognitive and biological markers to identify those at risk of future dementia. Data from a population-based longitudinal study, SNAC-K, were used to investigate this aim. Study I examined the ability of neuropsychological tests, genetics, and structural MRI volumes to predict dementia six years later. Models were systematically created to identify the best combinations for prediction. A model containing all three modalities: hippocampal volume, a task of category fluency, presence of an APOE ɛ4 allele, white-matter hyperintensities volume, and a task of general knowledge, displayed the most predictive value (AUC=.924; C.I=.883–.965). However, this model did not significantly improve predictive value over one containing only cognitive and genetic markers, suggesting that minor increases in predictivity should be weighed against the costs of additional tests. Study II investigated the benefit of DTI, alongside neuropsychological tests, genetics, and brain volume markers in predicting future dementia. MD values for tracts CHC, CS, FMAJ, and IFOF (AUC=.837– .862) and the FA IFOF latent factor (AUC=.839) were significantly associated with dementia at six years. A final model consisting of a measure of perceptual speed, hippocampal volume, and MD of the FMAJ tract was created with the highest predictive value (AUC=.911). Assessment of microstructural white matter integrity via DTI was associated with future dementia but the additional benefit when combined with other markers was relatively small. Study III narrowed its focus to the ability of cognitive markers alone and the effect of modifying factors (age, sex, education, the presence of an ɛ4 allele, AD–only dementia, and time to diagnosis) on identifying those at risk of dementia. The most predictive model, consisting of category fluency, word recall, and pattern comparison, achieved good prediction values (AUC=.913) for dementia six years later. Tests in the domains of category fluency, episodic memory, and perceptual speed were, in general, good predictors across all subgroups and up to 6 years before a dementia diagnosis. However, cognitive tests became increasingly unreliable at predicting dementia beyond that time. Study IV explored the trajectories of cognitive decline over a 12-year period during the preclinical stage of dementia, before examining the ability of early cognitive decline in identifying those with increased likelihood of future dementia. Persons in the preclinical phase showed increased rate of decline in all cognitive domains compared to those who did not develop dementia (β:-.07 to -.11), this difference was particularly noticeable closer to diagnosis. Those classified as fast decliners for 3 or more cognitive tests demonstrated the highest risk of dementia (HR: 3.38, CI: 1.91-6.01). Although, changes in early rates of decline were small and rates of decline may be more predictive closer to diagnosis. Collectively, these studies confirm a long preclinical period in dementia development, which allows for the use of a wide range of markers (cognitive, genetic, MRI, and DTI) capable of identifying those at high risk of dementia. The ability of these markers to predict future dementia is increased through combining within and between modalities

Environmental coping employed in the home environments of persons with Alzheimer's disease

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Cerebrospinal fluid markers including trefoil factor 3 are associated with neurodegeneration in amyloid-positive individuals.

We aimed to identify cerebrospinal fluid (CSF) biomarkers associated with neurodegeneration in individuals with and without CSF evidence of Alzheimer pathology. We investigated 287 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects (age=74.9±6.9; 22/48/30% with Alzheimer's disease/mild cognitive impairment/controls) with CSF multiplex analyte data and serial volumetric MRI. We calculated brain and hippocampal atrophy rates, ventricular expansion and Mini Mental State Examination decline. We used false discovery rate corrected regression analyses to assess associations between CSF variables and atrophy rates in individuals with and without amyloid pathology, adjusting in stages for tau, baseline volume, p-tau, age, sex, ApoE4 status and diagnosis. Analytes showing statistically significant independent relationships were entered into reverse stepwise analyses. Adjusting for tau, baseline volume, p-tau, age, sex and ApoE4, 4/83 analytes were significantly independently associated with brain atrophy rate, 1/83 with ventricular expansion and 2/83 with hippocampal atrophy. The strongest CSF predictor for the three atrophy measures was low trefoil factor 3 (TFF3). High cystatin C (CysC) was associated with higher whole brain atrophy and hippocampal atrophy rates. Lower levels of vascular endothelial growth factor and chromogranin A (CrA) were associated with higher whole brain atrophy. In exploratory reverse stepwise analyses, lower TFF3 was associated with higher rates of whole brain, hippocampal atrophy and ventricular expansion. Lower levels of CrA were associated with higher whole brain atrophy rate. The relationship between low TFF3 and increased hippocampal atrophy rate remained after adjustment for diagnosis. We identified a series of CSF markers that are independently associated with rate of neurodegeneration in amyloid-positive individuals. TFF3, a substrate for NOTCH processing may be an important biomarker of neurodegeneration across the Alzheimer spectrum