Impending Cognitive Decline Research Articles

Latent change-on-change between amyloid accumulation and cognitive decline.

While the influence of cross-sectional β-amyloid (Aβ) on longitudinal changes in cognition is well established, longitudinal change-on-change between Aβ and cognition is less explored. A series of bivariate latent change score models (LCSM) examined the relationship between changes in 11C-Pittsburgh Compound-B (PiB) positron emission tomography (PET) and the Preclinical Alzheimer's Cognitive Composite-5 (PACC-5) while adjusting for covariates, including cross-sectional medial temporal lobe (MTL) tau-PET burden. We selected 352 clinically normal older participants with up to 9 years of PiB-PET and PACC-5 data from the Harvard Aging Brain Study (HABS). Aβ accumulation was associated with subsequent cognitive decline beyond the effects of cross-sectional Aβ burden. Within this model including covariates such as age, sex, and apolipoprotein ε4 (APOEε4) status, we found no evidence supporting previously published associations between cross-sectional tau-PET and cognitive intercept/slope. Short-term Aβ changes are significantly associated with cognitive decline in clinically normal older adults and may eclipse the effect of cross-sectional Aβ and MTL tau. Aβ accumulation is associated with subsequent cognitive decline. High Aβ burden is not the sole metric signaling impending cognitive decline. Contrary to prior work, MTL tau-PET and cognition were not associated in our models. Models of bivariate latent Aβ and cognitive change may eclipse theeffects of MTL tau.

Genetic Risk for Alzheimer's Disease Alters Perceived Executive Dysfunction in Cognitively Healthy Middle-Aged and Older Adults.

Subjective cognitive complaints (SCC) may be an early indicator of future cognitive decline. However, findings comparing SCC and objective cognitive performance have varied, particularly in the memory domain. Even less well established is the relationship between subjective and objective complaints in non-amnestic domains, such as in executive functioning, despite evidence indicating very early changes in these domains. Moreover, particularly early changes in both amnestic and non-amnestic domains are apparent in those carrying the Apolipoprotein-E ɛ4 allele, a primary genetic risk for Alzheimer's disease (AD). This study investigated the role of the ɛ4 allele in the consistency between subjective and objective executive functioning in 54 healthy, cognitively intact, middle-aged and older adults. Participants (Mage = 64.07, SD = 9.27, range = 48-84; ɛ4+ = 18) completed the Frontal Systems Behavior Scale (FrSBe) Executive Dysfunction Scale (EXECDYS) to measure subjective executive functioning (SEF) and multiple executive functioning tasks, which were condensed into a single factor. After accounting for age, depression, and anxiety, objective executive functioning performance significantly predicted SEF. Importantly, ɛ4 moderated this effect. Specifically, those carrying the ɛ4 allele had significantly less accurate self-awareness of their executive functioning compared to ɛ4 non-carriers. Utilizing an approach that integrates self-evaluation of executive functioning with objective neurocognitive assessment may help identify the earliest signs of impending cognitive decline, particularly in those with genetic risk for AD. Such an approach could sensitively determine those most prone to future cognitive decline prior to symptom onset, when interventions could be most effective.

A Traitlike Dimension of Subjective Memory Concern Over 30 Years Among Adult Male Twins

Subjective memory concern has long been considered a state-related indicator of impending cognitive decline or dementia. The possibility that subjective memory concern may itself be a heritable trait is largely ignored, yet such an association would substantially confound its use in clinical or research settings. To assess the heritability and traitlike dimensions of subjective memory concern and its clinical correlates. This longitudinal twin cohort study was conducted from 1967 to 2019 among male adults with a mean (SD) age of 37.75 (2.52) years to follow-up at mean ages of 56.15 (2.72), 61.50 (2.43), and 67.35 (2.57) years (hereafter, 38, 56, 62, and 67 years, respectively) in the Vietnam Era Twin Study of Aging. The study included a national community-dwelling sample with health, education, and lifestyle characteristics comparable to a general sample of US men in this age cohort. Participants were monozygotic and dizygotic twins randomly recruited from the Vietnam Era Twin Registry. Data were analyzed from May 2021 to December 2022. Measures included subjective memory concern at 4 time points; objective memory, depressive symptoms, and anxiety at the last 3 time points; negative emotionality (trait neuroticism) at age 56 years; polygenic risk scores (PRSs) for neuroticism, depression, and Alzheimer disease; APOE genotype; and parental history of dementia. Primary outcomes were heritability and correlations between subjective memory concern and other measures. The sample included 1555 male adults examined at age 38 years, 520 at age 56 years (due to late introduction of subjective memory concern questions), 1199 at age 62 years, and 1192 at age 67 years. Phenotypically, subjective memory concerns were relatively stable over time. At age 56 years, subjective memory concern had larger correlations with depressive symptoms (r, 0.32; 95% CI, 0.21 to 0.42), anxiety (r, 0.36; 95% CI, 0.18 to 0.51), and neuroticism (r, 0.34; 95% CI, 0.26 to 0.41) than with objective memory (r, -0.24; 95% CI, -0.33 to -0.13). Phenotypic results were similar at ages 62 and 67 years. A best-fitting autoregressive twin model indicated that genetic influences on subjective memory concern accumulated and persisted over time (h2 = 0.26-0.34 from age 38-67 years). At age 56 years, genetic influences for subjective memory concern were moderately correlated with genetic influences for anxiety (r, 0.36; 95% CI, 0.18 to 0.51), negative emotionality (r, 0.51; 95% CI, 0.44-0.57), and depressive symptoms (r, 0.20; 95% CI, 0.10 to 0.29) as well as objective memory (r, -0.22; 95% CI, -0.30 to -0.14). Similar genetic correlations were seen at ages 62 and 67 years. The neuroticism PRS was associated with subjective memory concern at age 38 years (r, 0.10; 95% CI, 0.03. to 0.18) and age 67 years (r, 0.09; 95% CI, 0.01 to 0.16). Subjective memory concern was not associated with any Alzheimer disease risk measures. This cohort study found stable genetic influences underlying subjective memory concern dating back to age 38 years. Subjective memory concern had larger correlations with affect-related measures than with memory-related measures. Improving the utility of subjective memory concern as an indicator of impending cognitive decline and dementia may depend on isolating its statelike component from its traitlike component.

Specific olfactory deficit patterns observed in seniors and associated with cognitive decline

Olfactory dysfunction is a common symptom in neurodegenerative disorders and is regarded as a potential early predictor of impending cognitive decline. This study was undertaken in order to determine if olfactory dysfunction observed in the elderly is due to a general loss of smell or the inability to detect specific odours, and if misidentification of odours correlates with cognitive scores. Seniors for the Olfactory Response and Cognition in Aging (ORCA) sub-study were recruited from the Quebec Nutrition and Successful Aging (NuAge) cohort. The University of Pennsylvania smell identification test (UPSIT) was performed to measure olfactory function and the telephone Mini Mental State Examination (t-MMSE) and the French version of the Telephone Interview for Cognitive Status Modified (F-TICS-m) for cognitive status. The results demonstrate that seniors exhibit specific olfactory loss and had severe difficulty in particular in identifying lemon, pizza, fruit punch, cheddar cheese and lime. Furthermore, there was a significant difference in the ability to detect certain odours between the sexes. Results also showed that misidentification of certain scents was associated with cognitive scores, and when the sexes were assessed separately sex-specific misidentification of cognitive-associated odours was observed. The relationship between the cognitive scores and scent misidentification suggests that impending cognitive decline may be highlighted by the inability to smell specific odours. Our study provides additional support for the testing of olfactory function in the elderly and suggests that loss of smell for particular scents may become a useful diagnostic tool.

Olfactory Dysfunction Associated with Cognitive Decline in an Elderly Population

ABSTRACT Background In many neurological disorders, including Alzheimer disease, early olfactory dysfunction is observed. Objective In order to determine if deficits in olfactory memory are present in the elderly and if olfactory dysfunction correlates with cognitive impairment in the aging population, olfactory testing has been done on seniors from the NuAge cohort accepting to participate in the Olfactory Response Cognition and Aging (ORCA) secondary sub-study. The t-Mini Mental Statement Examination and the Telephone Interview for Cognitive Status tests were done to assess cognition levels. Results Overall, 94% of the ORCA cohort displayed olfactory dysfunction. Deficits in olfactory memory were also present. A correlation was observed between olfactory function and cognitive test scores. Moreover, in women who smoked, there was an association between olfactory memory and cognitive scores. Conclusion Our results suggest that olfactory dysfunction may predict impending cognitive decline and highlights the need for olfactory training in seniors to improve olfaction and overall well-being.

Self- and Partner-Reported Subjective Memory Complaints: Association with Objective Cognitive Impairment and Risk of Decline.

Background:Episodic memory decline is a hallmark of Alzheimer’s disease (AD). Subjective memory complaints (SMCs) may represent one of the earliest signs of impending cognitive decline. The degree to which self- or partner-reported SMCs predict cognitive change remains unclear.Objective:We aimed to evaluate the relationship between self- and partner-reported SMCs, objective cognitive performance, AD biomarkers, and risk of future decline in a well-characterized longitudinal memory center cohort. We also evaluated whether study partner characteristics influence reports of SMCs.Methods:758 participants and 690 study partners were recruited from the Penn Alzheimer’s Disease Research Center Clinical Core. Participants included those with Normal Cognition, Mild Cognitive Impairment, and AD. SMCs were measured using the Prospective and Retrospective Memory Questionnaire (PRMQ), and were evaluated for their association with cognition, genetic, plasma, and neuroimaging biomarkers of AD, cognitive and functional decline, and diagnostic progression over an average of four years.Results:We found that partner-reported SMCs were more consistent with cognitive test performance and increasing symptom severity than self-reported SMCs. Partner-reported SMCs showed stronger correlations with AD-associated brain atrophy, plasma biomarkers of neurodegeneration, and longitudinal cognitive and functional decline. A 10-point increase on baseline PRMQ increased the annual risk of diagnostic progression by approximately 70%. Study partner demographics and relationship to participants influenced reports of SMCs in AD participants only.Conclusion:Partner-reported SMCs, using the PRMQ, have a stronger relationship with the neuroanatomic and cognitive changes associated with AD than patient-reported SMCs. Further work is needed to evaluate whether SMCs could be used to screen for future decline.

Validating digital cognitive biomarkers for Alzheimer’s disease

AbstractBackgroundThis study sought to validate a pragmatic method to predict impending cognitive decline in Alzheimer’s disease (AD) patients, prior to the development of hallmark symptoms. The method, a Hierarchical Bayesian Cognitive Process (HBCP) model, uses item responses to a wordlist memory (WLM) test to generate digital cognitive biomarkers (Table 1). We replicated our earlier study, performed on AVLT item response data from Mayo Clinic, by applying the HBCP model to distinguish non‐decliner and decliner groups of normal subjects at baseline from a novel dataset, the Alzheimer’s Disease Neuroimaging Initiative (ADNI), with a distinct WLM test, ADAS‐Cog.MethodFrom the ADNI dataset, we classified non‐decliner subjects (n = 442) as those whose diagnosis remained normal for 3 or more years after normal baseline assessment and decliner subjects (n = 61) as those who developed amnestic MCI or AD within 3 years of normal baseline assessment. Three analytic approaches were compared: 1) Traditional summary scores per ADAS‐Cog task were assessed for group differences with a commonly‐used statistical approach, logistic regression; 2) summary scores were assessed with a Bayesian modeling approach; and 3) item response data were assessed with our HBCP model, generating digital cognitive biomarkers.ResultLogistic regression of summary scores generated β coefficients (Table 2) that did not significantly discriminate between groups. Bayes Factor assessment of fitted Gaussian distributions to the per‐task group recall by summary score measurement provided moderate evidence that the groups were measurably the same (BF sd = 3.4, 3.1, 2.9, and 1.4, respectively). The HBCP model produced posterior distributions of group differences. Bayes Factor assessment identified three with notable group differences: Immediate Retrieval from Durable Storage, L1 (BF ds = 11.8, strong evidence), One‐shot Learning, r (BF ds = 4.5, moderate), and Partial Learning, a (BF ds = 2.9, weak; Figure).ConclusionThe obtained strong evidence for L1 group differences represents successful replication of previous work with our HBCP model on this novel dataset. The ability to identify differences in subjects diagnosed cognitively normal at time of assessment demonstrates the HBCP model’s advantage over summary score assessment and its applicability for detection of impending cognitive decline in asymptomatic AD patients.

Application of Digital Cognitive Biomarkers for Alzheimer\u2019s Disease: Identifying Cognitive Process Changes and Impending Cognitive Decline

BackgroundRecent Alzheimer’s disease (AD) trials have faced significant challenges to enroll pre-symptomatic or early stage AD subjects with biomarker positivity, minimal or no cognitive impairment, and likelihood to decline cognitively during a short trial period. Our previous study showed that digital cognitive biomarkers (DCB), generated by a hierarchical Bayesian cognitive process (HBCP) model, were able to distinguish groups of cognitively normal individuals with impending cognitive decline from those without. We generated DCBs using only baseline Auditory Verbal Learning Test’s wordlist memory (WLM) item response data from the Mayo Clinic Alzheimer’s Disease Patient Registry.ObjectivesTo replicate our previous findings, using baseline ADAS-Cog WLM item response data from the Alzheimer’s Disease Neuroimaging Initiative, and compare DCBs to traditional approaches for scoring word-list memory tests. DESIGN: Classified decliner subjects (n = 61) as those who developed amnestic MCI or AD dementia within 3 years of normal baseline assessment and non-decliner (n = 442) as those who did not.MeasuresEvaluated the relative value of DCBs compared to traditional measures, using three analytic approaches to group differences: 1) logistic regression of summary scores per ADAS-Cog WLM task; 2) Bayesian modeling of summary scores; and 3) HBCP modeling to generate DCBs from item-level responses. RESULTS: The HBCP model produced posterior distributions of group differences, of which Bayes factor assessment identified three DCBs with notable group differences: Immediate Retrieval from Durable Storage, (BFds = 11.8, strong evidence); One-Shot Learning, (BFds = 4.5, moderate evidence); and Partial Learning (BFds = 2.9, weak evidence). In contrast, logistic regression of summary scores did not significantly discriminate between groups, and the Bayes factor assessment of modeled summary scores provided moderate evidence that the groups were equivalent (BFsd = 3.4, 3.1, 2.9, and 1.4, respectively).ConclusionsThis study demonstrated DCBs’ ability to distinguish, at baseline, between impending cognitive decline and non-decline groups where individuals in both groups were classified as cognitively normal. This validated findings from our previous study, demonstrating DCBs’ advantages over traditional approaches. This study warrants further refinement of the HBCP DCBs to predict impending cognitive decline in individuals and other factors associated with AD, such as physical biomarker load.

Increasing Inaccuracy of Self-Reported Subjective Cognitive Complaints Over 24 Months in Empirically Derived Subtypes of Mild Cognitive Impairment.

Although subjective cognitive complaints (SCC) are an integral component of the diagnostic criteria for mild cognitive impairment (MCI), previous findings indicate they may not accurately reflect cognitive ability. Within the Alzheimer's Disease Neuroimaging Initiative, we investigated longitudinal change in the discrepancy between self- and informant-reported SCC across empirically derived subtypes of MCI and normal control (NC) participants. Data were obtained for 353 MCI participants and 122 "robust" NC participants. Participants were classified into three subtypes at baseline via cluster analysis: amnestic MCI, mixed MCI, and cluster-derived normal (CDN), a presumptive false-positive group who performed within normal limits on neuropsychological testing. SCC at baseline and two annual follow-up visits were assessed via the Everyday Cognition Questionnaire (ECog), and discrepancy scores between self- and informant-report were calculated. Analysis of change was conducted using analysis of covariance. The amnestic and mixed MCI subtypes demonstrated increasing ECog discrepancy scores over time. This was driven by an increase in informant-reported SCC, which corresponded to participants' objective cognitive decline, despite stable self-reported SCC. Increasing unawareness was associated with cerebrospinal fluid Alzheimer's disease biomarker positivity and progression to Alzheimer's disease. In contrast, CDN and NC groups over-reported cognitive difficulty and demonstrated normal cognition at all time points. MCI participants' discrepancy scores indicate progressive underappreciation of their evolving cognitive deficits. Consistent over-reporting in the CDN and NC groups despite normal objective cognition suggests that self-reported SCC do not predict impending cognitive decline. Results demonstrate that self-reported SCC become increasingly misleading as objective cognitive impairment becomes more pronounced. (JINS, 2018, 24, 842-853).

Interactive Associations of Vascular Risk and β-Amyloid Burden With Cognitive Decline in Clinically Normal Elderly Individuals

Identifying asymptomatic individuals at high risk of impending cognitive decline because of Alzheimer disease is crucial for successful prevention of dementia. Vascular risk and β-amyloid (Aβ) pathology commonly co-occur in older adults and are significant causes of cognitive impairment. To determine whether vascular risk and Aβ burden act additively or synergistically to promote cognitive decline in clinically normal older adults; and, secondarily, to evaluate the unique influence of vascular risk on prospective cognitive decline beyond that of commonly used imaging biomarkers, including Aβ burden, hippocampal volume, fludeoxyglucose F18-labeled (FDG) positron emission tomography (PET), and white matter hyperintensities, a marker of cerebrovascular disease. In this longitudinal observational study, we examined clinically normal older adults from the Harvard Aging Brain Study. Participants were required to have baseline imaging data (FDG-PET, Aβ-PET, and magnetic resonance imaging), baseline medical data to quantify vascular risk, and at least 1 follow-up neuropsychological visit. Data collection began in 2010 and is ongoing. Data analysis was performed on data collected between 2010 and 2017. Vascular risk was quantified using the Framingham Heart Study general cardiovascular disease (FHS-CVD) risk score. We measured Aβ burden with Pittsburgh Compound-B PET. Cognition was measured annually with the Preclinical Alzheimer Cognitive Composite. Models were corrected for baseline age, sex, years of education, and apolipoprotein E ε4 status. Of the 223 participants, 130 (58.3%) were women. The mean (SD) age was 73.7 (6.0) years, and the mean (SD) follow-up time was 3.7 (1.2) years. Faster cognitive decline was associated with both a higher FHS-CVD risk score (β = -0.064; 95% CI, -0.094 to -0.033; P < .001) and higher Aβ burden (β = -0.058; 95% CI, -0.079 to -0.037; P < .001). The interaction of the FHS-CVD risk score and Aβ burden with time was significant (β = -0.040, 95% CI, -0.062 to -0.018; P < .001), suggesting a synergistic effect. The FHS-CVD risk score remained robustly associated with prospective cognitive decline (β = -0.055; 95% CI, -0.086 to -0.024; P < .001), even after adjustment for Aβ burden, hippocampal volume, FDG-PET uptake, and white matter hyperintensities. In this study, vascular risk was associated with prospective cognitive decline in clinically normal older adults, both alone and synergistically with Aβ burden. Vascular risk may complement imaging biomarkers in assessing risk of prospective cognitive decline in preclinical Alzheimer disease.

Dual-Task Gait Testing Identifies MCI Patients Likely to Develop Dementia

Easy to administer, noninvasive, and low-cost, dual-task gait testing may capture some subtleties missed by global cognitive methods.

Early Signs of Pathological Cognitive Aging in Mice Lacking High-Affinity Nicotinic Receptors.

In order to address pathological cognitive decline effectively, it is critical to adopt early preventive measures in individuals considered at risk. It is therefore essential to develop approaches that identify such individuals before the onset of irreversible dementia. A deficient cholinergic system has been consistently implicated as one of the main factors associated with a heightened vulnerability to the aging process. In the present study we used mice lacking high affinity nicotinic receptors (β2-/-), which have been proposed as an animal model of accelerated/premature cognitive aging. Our aim was to identify behavioral signs that could serve as indicators or predictors of impending cognitive decline. We used test batteries in order to assess cognitive functions and additional tasks to investigate spontaneous behaviors, such as species-specific activities and exploration/locomotion in a novel environment. Our data confirm the hypothesis that β2-/- animals exhibit age-related cognitive impairments in spatial learning. In addition, they document age-related deficits in other areas, such as recognition memory, burrowing and nesting building, thereby extending the validity of this animal model for the study of pathological aging. Finally, our data reveal deficits in spontaneous behavior and habituation processes that precede the onset of cognitive decline and could therefore be useful as a non-invasive behavioral screen for identifying animals at risk. To our knowledge, this is the first study to perform an extensive behavioral assessment of an animal model of premature cognitive aging, and our results suggest that β2-nAChR dependent cognitive deterioration progressively evolves from initial subtle behavioral changes to global dementia due to the combined effect of the neuropathology and aging.

Editorial: "From brain to body: the impact of nervous system declines on muscle performance in aging".

Editorial: "From brain to body: the impact of nervous system declines on muscle performance in aging".

Task-Induced Brain Activity Patterns in Type 2 Diabetes: A Potential Biomarker for Cognitive Decline

Patients with type 2 diabetes demonstrate reduced functional connectivity within the resting state default mode network (DMN), which may signal heightened risk for cognitive decline. In other populations at risk for cognitive decline, additional magnetic resonance imaging abnormalities are evident during task performance, including impaired deactivation of the DMN and reduced activation of task-relevant regions. We investigated whether middle-aged type 2 diabetic patients show these brain activity patterns during encoding and recognition tasks. Compared with control participants, we observed both reduced 1) activation of the dorsolateral prefrontal cortex during encoding and 2) deactivation of the DMN during recognition in type 2 diabetic patients, despite normal cognition. During recognition, activation in several task-relevant regions, including the dorsolateral prefrontal cortex and DMN regions, was positively correlated with HbA1c and insulin resistance, suggesting that these important markers of glucose metabolism impact the brain’s response to a cognitive challenge. Plasma glucose ≥11 mmol/L was associated with impaired deactivation of the DMN, suggesting that acute hyperglycemia contributes to brain abnormalities. Since elderly type 2 diabetic patients often demonstrate cognitive impairments, it is possible that these task-induced brain activity patterns observed in middle age may signal impending cognitive decline.

Heterogeneous ability profiles may be a unique indicator of impending cognitive decline.

Prior research has found that within-person standard deviations across different neuropsychological domains are larger in various clinical groups than in healthy control groups, but little is known about the specificity of these measures to clinical conditions. Within-person standard deviations were computed across composite scores representing episodic memory, perceptual speed, inductive reasoning, and spatial visualization and compared in older adults differing in the amount of subsequent cognitive change, and as a function of age in a large sample of adults ranging from 18 to 89 years of age. The standard deviations at an initial occasion were significantly greater in older adults who experienced the most negative longitudinal change, but relations of the standard deviations with age were only evident in adults under 65 years of age, and they were negative rather than positive. These findings suggest that high values of within-person variability may have specificity in predicting late life cognitive decline.

Concurrent validity of Dubois' five-word-test compared with CERAD memory subtests

Background: We have recently demonstrated the use of an innovative and sensitive behavioral assay, the Visual Paired Comparison (VPC) task, to successfully predict the transition from healthy aging to mild cognitive impairment (MCI), and fromMCI to Alzheimer’s disease (AD) (Zola, et al., 2013). For a subset of subjects, however, predictability is less clear (gray zone). We report here that the application of Machine Learning algorithms and eye movement characteristics can significantly improve the predictive ability of the task for this subset of individuals. Methods: The VPC task measures how individuals view side-by-side novel and familiar images. Normal individuals typically look at the novel image about two-thirds of the viewing time. Previous work has relied on a single parameter, i.e., percent time viewing the novel image (novelty preference, NP). In the present study we used a Machine Learning-based approach that uses additional variables, namely, distribution of NP across multiple trials, and latent factor decompositionbased analysis of eye movement trajectories, to develop amore accurate prediction algorithm. Results: For subjects in the gray zone, NP alone is not sufficient to distinguish between the subjects who will convert to MCI/AD and those who will not, resulting in ROC AUC of 0.70. Our new approach achieves AUC of 0.87, which represents a 24% relative improvement in predictive ability for the subjects in the gray zone. Conclusions: The VPC task can offer early detection of impending cognitive decline as much as 3 years prior to clinical diagnosis. To our knowledge, this is the first behavioral task that can identify healthy subjects who will soon develop MCI and possibly progress to AD within the next few years. For individuals in the gray zone, Machine Learning approaches can enhance still further the predictive capabilities of the VPC task. Finally, when combinedwith biomarker assays, this approachmay provide a newway of interrogating the underlying dynamics of AD, as well as other illnesses in which impaired cognition is a leading symptom.

Protective Role of S-Nitrosoglutathione (GSNO) Against Cognitive Impairment in Rat Model of Chronic Cerebral Hypoperfusion

Chronic cerebral hypoperfusion (CCH), featuring in most of the Alzheimer's disease spectrum, plays a detrimental role in brain amyloid-β (Aβ) homeostasis, cerebrovascular morbidity, and cognitive decline; therefore, early management of cerebrovascular pathology is considered to be important for intervention in the impending cognitive decline. S-nitrosoglutathione (GSNO) is an endogenous nitric oxide carrier modulating endothelial function, inflammation, and neurotransmission. Therefore, the effect of GSNO treatment on CCH-associated neurocognitive pathologies was determined in vivo by using rats with permanent bilateral common carotid artery occlusion (BCCAO), a rat model of chronic cerebral hypoperfusion. We observed that rats subjected to permanent BCCAO showed a significant decrease in learning/memory performance and increases in brain levels of Aβ and vascular inflammatory markers. GSNO treatment (50 μg/kg/day for 2 months) significantly improved learning and memory performance of BCCAO rats and reduced the Aβ levels and ICAM-1/VCAM-1 expression in the brain. Further, in in vitro cell culture studies, GSNO treatment also decreased the cytokine-induced proinflammatory responses, such as activations of NFκB and STAT3 and expression of ICAM-1 and VCAM-1 in endothelial cells. In addition, GSNO treatment increased the endothelial and microglial Aβ uptake. Additionally, GSNO treatment inhibited the β-secretase activity in primary rat neuron cell culture, thus reducing secretion of Aβ, suggesting GSNO mediated mechanisms in anti-inflammatory and anti-amyloidogenic activities. Taken together, these data document that systemic GSNO treatment is beneficial for improvement of cognitive decline under the conditions of chronic cerebral hypoperfusion and suggests a potential therapeutic use of GSNO for cerebral hypoperfusion associated mild cognitive impairment in Alzheimer's disease.

Late-life depression, mild cognitive impairment and hippocampal functional network architecture.

Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are associated with medial temporal lobe structural abnormalities. However, the hippocampal functional connectivity (HFC) similarities and differences related to these syndromes when they occur alone or coexist are unclear. Resting-state functional connectivity MRI (R-fMRI) technique was used to measure left and right HFC in 72 elderly participants (LLD [n = 18], aMCI [n = 17], LLD with comorbid aMCI [n = 12], and healthy controls [n = 25]). The main and interactive relationships of LLD and aMCI on the HFC networks were determined, after controlling for age, gender, education and gray matter volumes. The effects of depressive symptoms and episodic memory deficits on the hippocampal functional connections also were assessed. While increased and decreased left and right HFC with several cortical and subcortical structures involved in mood regulation were related to LLD, aMCI was associated with globally diminished connectivity. Significant LLD–aMCI interactions on the right HFC networks were seen in the brain regions critical for emotion processing and higher-order cognitive functions. In the interactive brain regions, LLD and aMCI were associated with diminished hippocampal functional connections, whereas the comorbid group demonstrated enhanced connectivity. Main and interactive effects of depressive symptoms and episodic memory performance were also associated with bilateral HFC network abnormalities. In conclusion, these findings indicate that discrete hippocampal functional network abnormalities are associated with LLD and aMCI when they occur alone. However, when these conditions coexist, more pronounced vulnerabilities of the hippocampal networks occur, which may be a marker of disease severity and impending cognitive decline. By utilizing R-fMRI technique, this study provides novel insights into the neural mechanisms underlying LLD and aMCI in the functional network level.

A behavioral task predicts conversion to mild cognitive impairment and Alzheimer's disease.

Currently, we cannot reliably differentiate individuals at risk of cognitive decline, for example, mild cognitive impairment (MCI), Alzheimer's disease (AD), from those individuals who are not at risk. A total of 32 participants with MCI and 60 control (CON) participants were tested on an innovative, sensitive behavioral assay, the visual paired comparison (VPC) task using infrared eye tracking. The participants were followed for 3 years after testing. Scores on the VPC task predicted, up to 3 years prior to a change in clinical diagnosis, those patients with MCI who would and who would not progress to AD and CON participants who would and would not progress to MCI. The present findings show that the VPC task can predict impending cognitive decline. To our knowledge, this is the first behavioral task that can identify CON participants who will develop MCI or patients with MCI who will develop AD within the next few years.

Engagement in social activities and progression from mild to severe cognitive impairment: the MYHAT study

It is of considerable public health importance to prevent or delay the progression of mild cognitive impairment (MCI) to more severely impaired cognitive states. This study examines the risk of progression from mild to severe cognitive impairment in relation to engagement in social activities while mildly impaired and the concurrence of subsequent change in engagement with MCI progression. Participants were 816 older adults with cognitively defined MCI (mean age 78.0 (standard deviation or SD = 7.4) years) from the Monongahela-Youghiogheny Healthy Aging Team (MYHAT) Study--a prospective cohort study of MCI in the community. Over three years of follow-up, 78 individuals progressed from MCI to severe cognitive impairment, while 738 did not progress. Risk of progression was estimated using discrete time survival analyses. The main predictors were standardized composite measures of the variety and frequency of engagement in social activities. Lower risk of progression from mild to severe cognitive impairment was associated with both a greater level of frequency of engagement in social activities while mildly impaired (OR = 0.72, 95% CI: 0.55-0.93, p = 0.01) and also with a slower rate of decline in the variety of activities over time (OR = 0.01, 95% CI: <0.001-0.38, p = 0.02). Greater engagement in social activities may potentially be beneficial for preventing or delaying further cognitive decline among older adults with MCI. Alternatively, lesser engagement in social activities may be a marker of impending cognitive decline in MCI.