Diagnostic and Prognostic Accuracy of the Cogstate Brief Battery and Auditory Verbal Learning Test in Preclinical Alzheimer's Disease and Incident Mild Cognitive Impairment: Implications for Defining Subtle Objective Cognitive Impairment

LAM Test: A New Cognitive Marker for Early Detection in Preclinical Alzheimer's Disease

Background

With the arrival of disease-modifying treatments, it is mandatory to find new cognitive markers that are sensitive to Alzheimer's disease (AD) pathology in preclinical stages.

Objective

To determine the utility of a newly developed Learning and Associative Memory face test: LAM test. This study examined the relationship between AD cerebrospinal fluid (CSF) biomarkers and performance on LAM test, and assessed its potential clinical applicability to detect subtle changes in cognitively healthy subjects at risk for AD.

Methods

We studied eighty cognitively healthy volunteers from the Valdecilla cohort. 61% were women and the mean age was 67.34 years (±6.416). All participants underwent a lumbar puncture for determination of CSF biomarkers and an extensive neuropsychological assessment, including performance on learning and associative memory indices of the LAM-test after 30 min and after 1 week, and two classic word lists to assess verbal episodic memory: the Rey Auditory Verbal Learning Test (RAVLT) and the Free and Cued Selective Reminding Test (FCSRT). We analyzed cognitive performance according to amyloid status (A+ versus A-) and to ATN model (A-T-N-; A+T-N-; A+T+N-/A+T+N+).

Results

Performance on the LAM-test was significantly correlated with CSF Aβ ratio. A+ participants performed worse on both learning (mean difference = 2.19, p = 0.002) and memory LAM measures than A- (mean difference = 2.19, p = 0.004). A decline in performance was observed along the Alzheimer's continuum, with significant differences between ATN groups.

Conclusions

Our findings suggest that LAM test could be a useful tool for the early detection of subjects within the AD continuum, outperforming classical memory tests.

Detection of cerebrospinal fluid biomarkers changes of Alzheimer's disease using a cognitive stress test in persons with subjective cognitive decline and mild cognitive impairment

Introduction

Timely and accurate diagnosis of the earliest manifestations of Alzheimer's disease (AD) is critically important. Cognitive challenge tests such as the Loewenstein Acevedo Scales for Semantic Interference and Learning (LASSI-L) have shown favorable diagnostic properties in a number of previous investigations using amyloid or FDG PET. However, no studies have examined LASSI-L performance against cerebrospinal fluid biomarkers of AD, which can be affected before the distribution of fibrillar amyloid and other changes that can be observed in brain neuroimaging. Therefore, we aimed to evaluate the relationship between LASSI-L scores and CSF biomarkers and the capacity of the cognitive challenge test to detect the presence of amyloid and tau deposition in patients with subjective cognitive decline and amnestic mild cognitive impairment (MCI).

Methods

One hundred and seventy-nine patients consulting for memory loss without functional impairment were enrolled. Patients were examined using comprehensive neuropsychological assessment, the LASSI-L, and cerebrospinal fluid (CSF) biomarkers (Aβ1-42/Aβ1-40 and ptau181). Means comparisons, correlations, effect sizes, and ROC curves were calculated.

Results

LASSI-L scores were significantly associated with CSF biomarkers Aβ1-42/Aβ1-40 in patients diagnosed with MCI and subjective cognitive decline, especially those scores evaluating the capacity to recover from proactive semantic interference effects and delayed recall. A logistic regression model for the entire sample including LASSI-L and age showed an accuracy of 0.749 and an area under the curve of 0.785 to detect abnormal amyloid deposition.

Conclusion

Our study supports the biological validity of the LASSI-L and its semantic interference paradigm in the context of the early stages of AD. These findings emphasize the utility and the convenience of including sensitive cognitive challenge tests in the assessment of patients with suspicion of early stages of AD.

Sex differences in functional connectivity and the predictive role of the connectome-based predictive model in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline. Sex differences in the progression of AD exist, but the neural mechanisms are not well understood. The purpose of the current study was to explore sex differences in brain functional connectivity (FC) at different stages of AD and their predictive ability on Montreal Cognitive Assessment (MoCA) scores using connectome-based predictive modeling (CPM). Resting-state functional magnetic resonance imaging was collected from 81 AD patients (44 females), 78 amnestic mild cognitive impairment patients (44 females), and 92 healthy controls (50 females). The FC analysis was conducted and the interaction effect between sex and group was investigated using two-factor variance analysis. The CPM was used to predict MoCA scores. There were sex-by-group interaction effects on FC between the left dorsolateral superior frontal gyrus and left middle temporal gyrus, left precuneus and right calcarine fissure surrounding cortex, left precuneus and left middle occipital gyrus, left middle temporal gyrus and left precentral gyrus, and between the left middle temporal gyrus and right cuneus. In the CPM, the positive network predictive model significantly predicted MoCA scores in both males and females. There were significant sex-by-group interaction effects on FC between the left precuneus and left middle occipital gyrus, and between the left middle temporal gyrus and right cuneus could predict MoCA scores in female patients. Our results suggest that there are sex differences in FC at different stages of AD. The sex-specific FC can further predict MoCA scores at individual level.

Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test

OBJECTIVE

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT).

METHOD

Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only.

RESULTS

The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.

CONCLUSIONS

Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Effects of adding adjuvants to propofol on the post-anesthesia cognitive function in patients undergoing gastroscopy/colonoscopy: a systematic review and meta-analysis

OBJECTIVES

This study aimed to elucidate the effects of propofol plus adjuvants on postoperative cognitive dysfunction (POCD) and patient satisfaction.

METHODS

Studies published up to September 2023 on the Chinese National Knowledge Infrastructure (CNKI), Wanfang Data, Sinomed, PubMed, Embase, Cochrane Library, Web of Science, and Clinictrials.gov websites were searched. Binary summary of results was used for meta-analyses.

RESULTS

We included 18 studies (2691 patients). The combined sedation did not affect the processing speed (ES = 0.02, 95%CI: -0.01, 0.04; I2 = 79.3%, p < 0.001), attention (ES = 0.02, 95%CI: -0.02, 0.05; I2 = 95.0%, p < 0.001), nor working memory (ES = 0.02, 95%CI: -0.03, 0.06; I2 = 94.4%, p < 0.001) in CogState brief battery tool. A significant effect of combined sedation was observed in the domain of visual learning in CogState tool (ES = -0.03, 95%CI: -0.04, -0.02; I2 = 15.8%, p = 0.306). The TDT (ES = 4.96, 95%CI: 2.92, 7.00) indicates that combined sedation would increase error rates in the tests of cognitive function. The DSST (ES = 0.16, 95% CI: -0.44, 0.75) shown that combined sedation does not affect cognitive function. In addition, an insignificant difference in patient satisfaction between combined sedation and propofol alone was observed (ES = -0.03, 95%CI: -0.09, 0.02).

CONCLUSION

The available evidence suggests that propofol combined with adjuvants may affect POCD but not patient satisfaction.

REGISTRATION NUMBER

INPLASY2023110092.

Unsupervised Online Paired Associates Learning Task from the Cambridge Neuropsychological Test Automated Battery (CANTAB®) in the Brain Health Registry

BACKGROUND

Unsupervised online cognitive assessments have demonstrated promise as an efficient and scalable approach for evaluating cognition in aging, and Alzheimer's disease and related dementias.

OBJECTIVES

The aim of this study was to evaluate the feasibility, usability, and construct validity of the Paired Associates Learning task from the Cambridge Neuropsychological Test Automated Battery® in adults enrolled in the Brain Health Registry.

DESIGN, SETTING, PARTICIPANTS, MEASUREMENTS

The Paired Associates Learning task was administered to Brain Health Registry participants in a remote, unsupervised, online setting. In this cross-sectional analysis, we 1) evaluated construct validity by analyzing associations between Paired Associates Learning performance and additional participant registry data, including demographics, self- and study partner-reported subjective cognitive change (Everyday Cognition scale), self-reported memory concern, and depressive symptom severity (Patient Health Questionnaire-9) using multivariable linear regression models; 2) determined the predictive value of Paired Associates Learning and other registry variables for identifying participants who self-report Mild Cognitive Impairment by employing multivariable binomial logistic regressions and calculating the area under the receiver operator curve; 3) investigated feasibility by looking at task completion rates and statistically comparing characteristics of task completers and non-completers; and 4) evaluated usability in terms of participant requests for support from BHR related to the assessment.

RESULTS

In terms of construct validity, in participants who took the Paired Associates Learning for the first time (N=14,528), worse performance was associated with being older, being male, lower educational attainment, higher levels of self- and study partner-reported decline, more self-reported memory concerns, greater depressive symptom severity, and self-report of Mild Cognitive Impairment. Paired Associates Learning performance and Brain Health Registry variables together identified those with self-reported Mild Cognitive Impairment with moderate accuracy (areas under the curve: 0.66-0.68). In terms of feasibility, in a sub-sample of 29,176 participants who had the opportunity to complete Paired Associates Learning for the first time in the registry, 14,417 started the task. 11,647 (80.9% of those who started) completed the task. Compared to those who did not complete the task at their first opportunity, those who completed were older, had more years of education, more likely to self-identify as White, less likely to self-identify as Latino, less likely to have a subjective memory concern, and more likely to report a family history of Alzheimer's disease. In terms of usability, out of 8,395 received requests for support from BHR staff via email, 4.4% (n=374) were related to PAL. Of those, 82% were related to technical difficulties.

CONCLUSIONS

Our findings support moderate feasibility, good usability, and construct validity of cross-sectional Paired Associates Learning in an unsupervised online registry, but also highlight the need to make the assessment more inclusive and accessible to individuals from ethnoculturally and socioeconomically diverse communities. A future, improved version could be a scalable, efficient method to assess cognition in many different settings, including clinical trials, observational studies, healthcare, and public health.

Symptomatic Clusters Related to Amyloid Positivity in Cognitively Unimpaired Individuals

Background

The NIA-AA Research Framework on Alzheimer's disease (AD) proposes a transitional stage (stage 2) characterized by subtle cognitive decline, subjective cognitive decline (SCD) and mild neurobehavioral symptoms (NPS).

Objective

To identify participant clusters based on stage 2 features and assess their association with amyloid positivity in cognitively unimpaired individuals.

Methods

We included baseline data of N = 338 cognitively unimpaired participants from the DELCODE cohort with data on cerebrospinal fluid biomarkers for AD. Classification into the AD continuum (i.e., amyloid positivity, A+) was based on Aβ42/40 status. Neuropsychological test data were used to assess subtle objective cognitive dysfunction (OBJ), the subjective cognitive decline interview (SCD-I) was used to detect SCD, and the Neuropsychiatric Inventory Questionnaire (NPI-Q) was used to assess NPS. A two-step cluster analysis was carried out and differences in AD biomarkers between clusters were analyzed.

Results

We identified three distinct participant clusters based on presented symptoms. The highest rate of A+ participants (47.6%) was found in a cluster characterized by both OBJ and SCD. A cluster of participants that presented with SCD and NPS (A+:26.6%) and a cluster of participants with overall few symptoms (A+:19.7%) showed amyloid positivity in a range that was not higher than the expected A+ rate for the age group. Across the full sample, participants with a combination of SCD and OBJ in the memory domain showed a lower Aβ42/ptau181 ratio compared to those with neither SCD nor OBJ.

Conclusions

The cluster characterized by participants with OBJ and concomitant SCD was enriched for amyloid pathology.

Stress and Right Prefrontal Transcranial Direct Current Stimulation (tDCS) Interactive Effects on Visual Working Memory and Learning

Stress impacts prefrontal cortex (PFC) activity and modulates working memory performance. In a recent study, stimulating the dorsolateral PFC (dlPFC) using transcranial direct current stimulation (tDCS) interacted with social stress in modulating participants' working memory. More specifically, stress disrupted the enhancing effects of dlPFC tDCS on working memory performance. The current study aimed to further explore these initial findings by randomizing healthy females to four experimental conditions (N = 130); stimulation (right dlPFC tDCS vs. sham) and stress manipulation (social stress vs. control). Participants performed cognitive tasks (i.e., visual working memory task and a visual declarative memory task) at baseline and post-stimulation. They also completed self-report measures of stress and anxiety. A significant stimulation × stress interaction was evident in the declarative memory (One-Card Learning, OCL) task, while working memory performance was unaffected. Though tDCS stimulation and stress did not interact to affect working memory, further research is warranted as these initial findings suggest that immediate visual-memory learning may be affected by these factors. The limited number of earlier studies, as well as the variability in their designs, provides additional impetus for studying the interactive effects of stress and tDCS on human visual learning.

Relevance of Minor Neuropsychological Deficits in Patients With Subjective Cognitive Decline

BACKGROUND AND OBJECTIVES

To determine the relevance of minor neuropsychological deficits (MNPD) in patients with subjective cognitive decline (SCD) with regard to CSF levels of Alzheimer disease (AD) biomarkers, cognitive decline, and clinical progression to mild cognitive impairment (MCI).

METHODS

This study included patients with clinical SCD and SCD-free, healthy control (HC) participants with available baseline CSF and/or longitudinal cognitive data from the observational DZNE Longitudinal Cognitive Impairment and Dementia study. We defined MNPD as a performance of at least 0.5SD below the mean on a demographically adjusted total score derived from the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological assessment battery. We compared SCD patients with MNPD and those without MNPD with regard to CSF amyloid-β (Aβ)42/Aβ40, phosphorylated tau (p-tau181), total tau and Aβ42/p-tau181 levels, longitudinal cognitive composite trajectories, and risk of clinical progression to incident MCI (follow-up M ± SD: 40.6 ± 23.7 months). In addition, we explored group differences between SCD and HC in those without MNPD.

RESULTS

In our sample (N = 672, mean age: 70.7 ± 5.9 years, 50% female), SCD patients with MNPD (n = 55, 12.5% of SCD group) showed significantly more abnormal CSF biomarker levels, increased cognitive decline, and a higher risk of progression to incident MCI (HR: 4.07, 95% CI 2.46-6.74) compared with SCD patients without MNPD (n = 384). MNPD had a positive predictive value of 57.0% (95% CI 38.5-75.4) and a negative predictive value of 86.0% (95% CI 81.9-90.1) for the progression of SCD to MCI within 3 years. SCD patients without MNPD showed increased cognitive decline and a higher risk of incident MCI compared with HC participants without MNPD (n = 215; HR: 4.09, 95% CI 2.07-8.09), while AD biomarker levels did not differ significantly between these groups.

DISCUSSION

Our results suggest that MNPD are a risk factor for AD-related clinical progression in cognitively normal patients seeking medical counseling because of SCD. As such, the assessment of MNPD could be useful for individual clinical prediction and for AD risk stratification in clinical trials. However, SCD remains a risk factor for future cognitive decline even in the absence of MNPD.

Mild Cognitive Impairment Subtype Performance in Comparison to Healthy Older Controls on the NIH Toolbox and Cogstate

BACKGROUND

Early detection is necessary for the treatment of dementia. Computerized testing has become more widely used in clinical trials; however, it is unclear how sensitive these measures are to early signs of neurodegeneration. We investigated the use of the NIH Toolbox-Cognition (NIHTB-CB) and Cogstate-Brief computerized neuropsychological batteries in the identification of mild cognitive impairment (MCI) versus healthy older adults [healthy control (HC)] and amnestic (aMCI) versus nonamnestic MCI (naMCI). Exploratory analyses include investigating potential racial differences.

METHODS

Two hundred six older adults were diagnosed as aMCI (n = 58), naMCI (n = 15), or cognitively healthy (HC; n = 133).

RESULTS

The NIH Toolbox-CB subtests of Flanker, Picture Sequence Memory, and Picture Vocabulary significantly differentiated MCI from HC. Further, subtests from both computerized batteries differentiated patients with aMCI from those with naMCI. Although the main effect of race differences was noted on tests and in diagnostic groups was significant, there were no significant race-by-test interactions.

CONCLUSIONS

Computer-based subtests vary in their ability to help distinguish MCI subtypes, though these tests provide less expensive and easier-to-administer clinical screeners to help identify patients early who may qualify for more comprehensive evaluations. Further work is needed, however, to refine computerized tests to achieve better precision in distinguishing impairment subtypes.

Neural network process simulations support a distributed memory system and aid design of a novel computer adaptive digital memory test for preclinical and prodromal Alzheimer's disease

OBJECTIVE

Growing evidence supports the importance of learning as a central deficit in preclinical/prodromal Alzheimer's disease. The aims of this study were to conduct a series of neural network simulations to develop a functional understanding of a distributed, nonmodular memory system that can learn efficiently without interference. This understanding is applied to the development of a novel digital memory test.

METHOD

Simulations using traditional feed forward neural network architectures to learn simple logic problems are presented. The simulations demonstrate three limitations: (a) inefficiency, (b) an inability to learn problems consistently, and (c) catastrophic interference when given multiple problems. A new mirrored cascaded architecture is introduced to address these limitations, with support provided by a series of simulations.

RESULTS

The mirrored cascaded architecture demonstrates efficient and consistent learning relative to feed forward networks but also suffers from catastrophic interference. Addition of context values to add the capability of distinguishing features as part of learning eliminates the problem of interference in the mirrored cascaded, but not the feed forward, architectures.

CONCLUSIONS

A mirrored cascaded architecture addresses the limitations of traditional feed forward neural networks, provides support for a distributed memory system, and emphasizes the importance of context to avoid interference. These process models contributed to the design of a digital computer-adaptive word list learning test that places maximum stress on the capability to distinguish specific episodes of learning. Process simulations provide a useful method of testing models of brain function and contribute to new approaches to neuropsychological assessment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Current Diagnostic Pathways for Alzheimer's Disease: A Cross-Sectional Real-World Study Across Six Countries

Background

Diagnostic pathways for patients presenting with cognitive complaints may vary across geographies.

Objective

To describe diagnostic pathways of patients presenting with cognitive complaints across 6 countries.

Methods

This real-world, cross-sectional study analyzed chart-extracted data from healthcare providers (HCPs) for 6,744 patients across China, France, Germany, Spain, UK, and the US.

Results

Most common symptoms at presentation were cognitive (memory/amnestic; 89.86%), followed by physical/behavioral (87.13%). Clinical/cognitive tests were used in > 95%, with Mini-Mental State Examination being the most common cognitive test (79.0%). Blood tests for APOE ɛ4/other mutations, or to rule out treatable causes, were used in half of the patients. Clinical and cognitive tests were used at higher frequency at earlier visits, and amyloid PET/CSF biomarker testing at higher frequency at later visits. The latter were ordered at low rates even by specialists (across countries, 5.7% to 28.7% for amyloid PET and 5.0% to 27.3% for CSF testing). Approximately half the patients received a diagnosis (52.1% of which were Alzheimer's disease [AD]). Factors that influenced risk of not receiving a diagnosis were HCP type (higher for primary care physicians versus specialists) and region (highest in China and Germany).

Conclusion

These data highlight variability in AD diagnostic pathways across countries and provider types. About 45% of patients are referred/told to 'watch and wait'. Improvements can be made in the use of amyloid PET and CSF testing. Efforts should focus on further defining biomarkers for those at risk for AD, and on dismantling barriers such low testing capacity and reimbursement challenges.

Sex Difference in General Cognition Associated with Coupling of Whole-brain Functional Connectivity Strength to Cerebral Blood Flow Changes During Alzheimer's Disease Progression

Alzheimer's disease (AD) is a progressive age-related neurodegenerative disorder that results in irreversible cognitive impairments. Nonetheless, there are numerous sex-dependent differences in clinical course. We examined potential contributions of neurovascular coupling deficits to sex differences in AD progression. T1-weighted three-dimensional structural magnetic resonance images, functional blood oxygen level dependent and arterial spin labeling images were acquired from 50 AD patients (28 females), 52 amnesic mild cognitive impairment patients (31 females), and 59 healthy controls (36 females). Short- and long-range functional connectivity strength (FCS) and cerebral blood flow (CBF) values were calculated for all participants. Then, the CBF/FCS coupling ratio, which represented the amount of blood supply per unit of connectivity strength, was calculated for each voxel. Two-way ANOVA was performed to identify group × sex interactions and main effects of group. Correlation analysis was used to assess associations between CBF/FCS ratios and Mini-Mental State Examination (MMSE). There were significant group × sex interaction effects on short-range coupling ratios of right middle temporal gyrus, left angular gyrus, left inferior orbital frontal gyrus, and left superior frontal gyrus as well as on the long-range coupling ratios of right middle temporal gyrus, left precuneus, left posterior cingulate cortex, and left angular gyrus. There were significant negative correlations between MMSE scores and CBF/FCS ratios for all regions with significant group × sex interactions among female patients, while positive correlations were found among male patients. Our results demonstrate significant sex differences in neurovascular coupling mechanisms associated with cognitive function during the course of AD.

Sensitivity of Individual and Composite Test Scores from the Cogstate Brief Battery to Mild Cognitive Impairment and Dementia Due to Alzheimer's Disease

BACKGROUND

The Cogstate Brief Battery (CBB) is a computerized cognitive test battery used commonly to identify cognitive deficits related to Alzheimer's disease (AD). However, AD and normative samples used to understand the sensitivity of the CBB to AD in the clinic have been limited, as have the outcome measures studied.

OBJECTIVE

This study investigated the sensitivity of CBB outcomes, including potential composite scores, to cognitive impairment in mild cognitive impairment (MCI) and dementia due to AD, in carefully selected samples.

METHODS

Samples consisted of 4,871 cognitively unimpaired adults and 184 adults who met clinical criteria for MCI (Clinical Dementia Rating (CDR) = 0.5) or dementia (CDR > 0.5) due to AD and CBB naive. Speed and accuracy measures from each test were examined, and theoretically- and statistically-derived composites were created. Sensitivity and specificity of classification of cognitive impairment were compared between outcomes.

RESULTS

Individual CBB measures of learning and working memory showed high discriminability for AD-related cognitive impairment for CDR 0.5 (AUCs ∼ 0.79-0.88), and CDR > 0.5 (AUCs ∼ 0.89-0.96) groups. Discrimination ability for theoretically derived CBB composite measures was high, particularly for the Learning and Working Memory (LWM) composite (CDR 0.5 AUC = 0.90, CDR > 0.5 AUC = 0.97). As expected, statistically optimized linear composite measures showed strong discrimination abilities albeit similar to the LWM composite.

CONCLUSIONS

In older adults, the CBB is effective for discriminating cognitive impairment due to MCI or AD-dementia from unimpaired cognition with the LWM composite providing the strongest sensitivity.

Correlation between serum lipid profiles and cognitive impairment in old age: a cross-sectional study

Background

The correlation between cognitive function and lipid profiles, including total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides, is inconsistent.

Aims

This cross-sectional study investigated the association between serum lipid levels and the prevalence of cognitive impairment among community-dwelling older adults and explored this difference in association by gender and urban-rural residency.

Methods

Participants aged 65 and above in urban and rural areas were recruited between 2018 and 2020, selected from the Hubei Memory and Aging Cohort Study. Detailed neuropsychological evaluations, clinical examinations and laboratory tests were conducted in community health service centres. Multivariate logistic regression was used to analyse the correlation between serum lipid profiles and the prevalence of cognitive impairment.

Results

We identified 1 336 cognitively impaired adults (≥65 years)-1 066 with mild cognitive impairment and 270 with dementia-from 4 746 participants. Triglycerides level was correlated with cognitive impairment in the total sample (χ²=6.420, p=0.011). In gender-stratified multivariate analysis, high triglycerides in males reduced the risk of cognitive impairment (OR: 0.785, 95% CI: 0.623 to 0.989, p=0.040), and high LDL-C in females increased the risk of cognitive impairment (OR: 1.282, 95% CI: 1.040 to 1.581, p=0.020). In both gender-stratified and urban-rural stratified multivariate analyses, high triglycerides reduced the risk of cognitive impairment in older urban men (OR: 0.734, 95% CI: 0.551 to 0.977, p=0.034), and high LDL-C increased the risk of cognitive impairment in older rural women (OR: 1.830, 95% CI: 1.119 to 2.991, p=0.016).

Conclusions

There are gender and urban-rural differences in the correlation of serum lipids with cognitive impairment. High triglycerides levels may be a protective factor for cognitive function in older urban men, while high LDL-C levels may be a risk factor for cognitive function in older rural women.

Alpha3/alpha2 power ratios relate to performance on a virtual reality shopping task in ageing adults

Background

Aspects of cognitive function decline with age. This phenomenon is referred to as age-related cognitive decline (ARCD). Improving the understanding of these changes that occur as part of the ageing process can serve to enhance the detection of the more incapacitating neurodegenerative disorders such as Alzheimer’s disease (AD). In this study, we employ novel methods to assess ARCD by exploring the utility of the alpha3/alpha2 electroencephalogram (EEG) power ratio – a marker of AD, and a novel virtual reality (VR) functional cognition task – VStore, in discriminating between young and ageing healthy adults.

Materials and methods

Twenty young individuals aged 20–30, and 20 older adults aged 60–70 took part in the study. Participants underwent resting-state EEG and completed VStore and the Cogstate Computerised Cognitive Battery. The difference in alpha3/alpha2 power ratios between the age groups was tested using t-test. In addition, the discriminatory accuracy of VStore and Cogstate were compared using logistic regression and overlying receiver operating characteristic (ROC) curves. Youden’s J statistic was used to establish the optimal threshold for sensitivity and specificity and model performance was evaluated with the DeLong’s test. Finally, alpha3/alpha2 power ratios were correlated with VStote and Cogstate performance.

Results

The difference in alpha3/alpha2 power ratios between age cohorts was not statistically significant. On the other hand, VStore discriminated between age groups with high sensitivity (94%) and specificity (95%) The Cogstate Pre-clinical Alzheimer’s Battery achieved a sensitivity of 89% and specificity of 60%, and Cogstate Composite Score achieved a sensitivity of 83% and specificity of 85%. The differences between the discriminatory accuracy of VStore and Cogstate models were statistically significant. Finally, high alpha3/alpha2 power ratios correlated strongly with VStore (r = 0.73), the Cogstate Pre-clinical Alzheimer’s Battery (r = -0.67), and Cogstate Composite Score (r = -0.76).

Conclusion

While we did not find evidence that the alpha3/alpha2 power ratio is elevated in healthy ageing individuals compared to young individuals, we demonstrated that VStore can classify age cohorts with high accuracy, supporting its utility in the assessment of ARCD. In addition, we found preliminary evidence that elevated alpha3/alpha2 power ratio may be linked to lower cognitive performance.

Chinese version of the auditory verbal learning test: normative study and clinical applications in Chinese-speaking population in Shijiazhuang city

OBJECTIVE

The purposes were to establish standardized values for the Auditory Verbal Learning Test (AVLT) in the communities of Shijiazhuang city (China), with particular focus on the influences of age, education and sex, and to detect the discriminant validity data of the AVLT in patients with acute ischemic stroke (AIS).

METHODS

406 Chinese-speaking subjects (age: 50-84 years old) from Shijiazhuang city, were brought into this study. Using linear regression analyses, standardized values were developed for three variables of interest, including scores on short-term memory (sum of AVLT trials 1-3), delayed recall (AVLT trial 4), and an index representing recognition memory corrected for false-positive identifications (AVLT trial 5). 177 patients with AIS were included to probe the discriminant validity of the AVLT.

RESULTS

The linear regression analysis showed statistically significant effect of age and sex on all trials of the AVLT. Years of education contributed significantly to trial 1-3 and trial 4 but not trial 5. Based on the results obtained, trail 1-3 and trail 4 of AVLT norms were stratified by age (3 strata), education (2 strata), and sex (2 strata). Trail 5 norms were stratified by age (3 strata) and sex (2 strata). Moreover, AIS groups performed significantly worse on most AVLT trials than matched cognitively healthy controls.

CONCLUSIONS

Normative data stratified by age, education and sex for the Chinese-speaking community-residents in Shijiazhuang was presented for use in research and clinical settings. The AVLT measures adequately differentiated between the cognitive performance (especially memory decline) of healthy adults and patients with AIS.

Computerized paired associate learning performance and imaging biomarkers in older adults without dementia

This cross-sectional study examined whether performance on the computerized Paired Associate Learning (PAL) task from the Cambridge Neuropsychological Test Automated Battery is associated with amyloid positivity as measured by Positron Emission Tomography, regional volume composites as measured by Magnetic Resonance Imaging, and cognitive impairment. Participants from the BIOCARD Study (N = 73, including 62 cognitively normal and 11 with mild cognitive impairment; M age = 70 years) completed the PAL task, a comprehensive clinical and neuropsychological assessment, and neuroimaging as part of their annual study visit. In linear regressions covarying age, sex, years of education and diagnosis, higher PAL error scores were associated with amyloid positivity but not with medial temporal or cortical volume composites. By comparison, standard neuropsychological measures of episodic memory and global cognition were unrelated to amyloid positivity, but better performance on the verbal episodic memory measures was associated with larger cortical volume composites. Participants with mild cognitive impairment demonstrated worse cognitive performance on all of the cognitive measures, including the PAL task. These findings suggest that this computerized visual paired associate learning task may be more sensitive to amyloid positivity than standard neuropsychological tests, and may therefore be a promising tool for detecting amyloid positivity in non-demented participants.

Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage

Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.

Using the ATN system as a guide for the neuropsychological assessment of Alzheimer's disease

INTRODUCTION

Many studies have attempted to determine whether Alzheimer's disease (AD) in-vivo biomarkers can predict neuropsychological performance since pathophysiological changes precede cognitive changes by several years. Nonetheless, neuropsychological measures can also detect cognitive deterioration in cognitively normal individuals with AD-positive biomarkers. Recent studies have investigated whether cognitive measures can be used as a proxy for biomarkers. This is a crucial issue since biomarker analysis is expensive, invasive, and not yet widespread in clinical practice. However, these studies have so far considered only one or two classes of AD biomarkers. Here, we aim at preliminarily evaluating whether and which neuropsychological measures can discriminate individuals that have been classified according to the full scheme of biomarkers known as ATN system. This scheme groups biomarkers as a function of the three main AD-related pathologic processes they measure (i.e., β-amyloidosis, tauopathy, and neurodegeneration) to provide an unbiased and descriptive definition of the Alzheimer's continuum.

METHOD

Biomarkers and neuropsychological data from 78 patients (70.01 ± 9.15 years; 38 females) with suspected cognitive decline were extracted from a medical database. Participants' biomarker profiles were classified into the following ATN categories: normal AD biomarkers; Alzheimer's continuum; non-AD pathologic change. Data were analyzed using a Bayesian approach, to guarantee reliable result interpretation of data stemming from small samples.

RESULTS

The discrimination ability of each neuropsychological measure varied depending on the pairs of ATN categories compared. The best-discriminating predictor in the Alzheimer's continuum vs. normal biomarkers comparison was the figure naming ability. In contrast, in the Alzheimer's continuum vs. non-AD pathologic change comparison the best predictor was the wordlist forgetting rate.

CONCLUSIONS

Although the study was exploratory in nature, the proposed methodological approach may have the potential to identify the best neuropsychological measures for estimating AD neuropathological changes, leading to a more biologically informed use of neuropsychological assessment.

A Paradox in Digital Memory Assessment: Increased Sensitivity With Reduced Difficulty

The One Card Learning Test (OCL80) from the Cogstate Brief Battery-a digital cognitive test used both in-person and remotely in clinical trials and in healthcare contexts to inform health decisions-has shown high sensitivity to changes in memory in early Alzheimer's disease (AD). However, recent studies suggest that OCL sensitivity to memory impairment in symptomatic AD is not as strong as that for other standardized assessments of memory. This study aimed to improve the sensitivity of the OCL80 to AD-related memory impairment by reducing the test difficultly (i.e., OCL48). Experiment 1 showed performance in healthy adults improved on the OCL48 while the pattern separation operations that constrain performance on the OCL80 were retained. Experiment 2 showed repeated administration of the OCL48 at short retest intervals did not induce ceiling or practice effects. Experiment 3 showed that the sensitivity of the OCL48 to AD-related memory impairment (Glass's Δ = 3.11) was much greater than the sensitivity of the OCL80 (Glass's Δ = 1.94). Experiment 4 used data from a large group of cognitively normal older adults to calibrate performance scores between the OCL80 and OCL48 using equipercentile equating. Together these results showed the OCL48 to be a valid and reliable test of learning with greater sensitivity to memory impairment in AD than the OCL80.

Urban-Rural Disparities in the Association Between Body Mass Index and Cognitive Impairment in Older Adults: A Cross-Sectional Study in Central China

BACKGROUND

Some studies have demonstrated an association between low and high body mass index (BMI) and an increased risk of dementia. However, only a few of these studies were performed in rural areas.

OBJECTIVE

This cross-sectional study investigated the associations between BMI and cognitive impairment among community-dwelling older adults from rural and urban areas.

METHODS

8,221 older persons enrolled in the Hubei Memory & Ageing Cohort Study (HMACS) were recruited. Sociodemographic and lifestyle data, comorbidities, physical measurements, and clinical diagnoses of cognitive impairment were analyzed. Logistic regression was performed to assess the associations of BMI categories with cognitive impairment. A series of sensitivity analyses were conducted to test whether reverse causality could influence our results.

RESULTS

Being underweight in the rural-dwelling participants increased the risk of cognitive impairment. Being overweight was a protective factor in rural-dwelling participants aged 65-69 years and 75-79 years, whereas being underweight was significantly associated with cognitive impairment (OR, 1.37; 95% CI: 1.03-1.83; p < 0.05). Sensitivity analyses support that underweight had an additive effect on the odds of cognitive impairment and was related to risk of dementia. Interaction test revealed that the differences between urban/rural in the relationship between BMI and cognitive impairment are statistically significant.

CONCLUSION

Associations between BMI and cognitive impairment differ among urban/rural groups. Older people with low BMI living in rural China are at a higher risk for dementia than those living in urban areas.

A Comparison of Cross-Sectional and Longitudinal Methods of Defining Objective Subtle Cognitive Decline in Preclinical Alzheimer's Disease Based on Cogstate One Card Learning Accuracy Performance

BACKGROUND

Longitudinal, but not cross-sectional, cognitive testing is one option proposed to define transitional cognitive decline for individuals on the Alzheimer's disease continuum.

OBJECTIVE

Compare diagnostic accuracy of cross-sectional subtle objective cognitive impairment (sOBJ) and longitudinal objective decline (ΔOBJ) over 30 months for identifying 1) cognitively unimpaired participants with preclinical Alzheimer's disease defined by elevated brain amyloid and tau (A+T+) and 2) incident mild cognitive impairment (MCI) based on Cogstate One Card Learning (OCL) accuracy performance.

METHODS

Mayo Clinic Study of Aging cognitively unimpaired participants aged 50 + with amyloid and tau PET scans (n = 311) comprised the biomarker-defined sample. A case-control sample of participants aged 65 + remaining cognitively unimpaired for at least 30 months included 64 who subsequently developed MCI (incident MCI cases) and 184 controls, risk-set matched by age, sex, education, and visit number. sOBJ was assessed by OCL z-scores. ΔOBJ was assessed using within subjects' standard deviation and annualized change from linear regression or linear mixed effects (LME) models. Concordance measures Area Under the ROC Curve (AUC) or C-statistic and odds ratios (OR) from conditional logistic regression models were derived. sOBJ and ΔOBJ were modeled jointly to compare methods.

RESULTS

sOBJ and ΔOBJ-LME methods differentiated A+T+ from A-T- (AUC = 0.64, 0.69) and controls from incident MCI (C-statistic = 0.59, 0.69) better than chance; other ΔOBJ methods did not. ΔOBJ-LME improved prediction of future MCI over baseline sOBJ (p = 0.003) but not over 30-month sOBJ (p = 0.09).

CONCLUSION

Longitudinal decline did not offer substantial benefit over cross-sectional assessment in detecting preclinical Alzheimer's disease or incident MCI.

A cross-sectional study in healthy elderly subjects aimed at development of an algorithm to increase identification of Alzheimer pathology for the purpose of clinical trial participation

Background

In the current study, we aimed to develop an algorithm based on biomarkers obtained through non- or minimally invasive procedures to identify healthy elderly subjects who have an increased risk of abnormal cerebrospinal fluid (CSF) amyloid beta42 (Aβ) levels consistent with the presence of Alzheimer’s disease (AD) pathology. The use of the algorithm may help to identify subjects with preclinical AD who are eligible for potential participation in trials with disease modifying compounds being developed for AD. Due to this pre-selection, fewer lumbar punctures will be needed, decreasing overall burden for study subjects and costs.

Methods

Healthy elderly subjects (n = 200; age 65–70 (N = 100) and age > 70 (N = 100)) with an MMSE > 24 were recruited. An automated central nervous system test battery was used for cognitive profiling. CSF Aβ1-42 concentrations, plasma Aβ1-40, Aβ1-42, neurofilament light, and total Tau concentrations were measured. Aβ1-42/1-40 ratio was calculated for plasma. The neuroinflammation biomarker YKL-40 and APOE ε4 status were determined in plasma. Different mathematical models were evaluated on their sensitivity, specificity, and positive predictive value. A logistic regression algorithm described the data best. Data were analyzed using a 5-fold cross validation logistic regression classifier.

Results

Two hundred healthy elderly subjects were enrolled in this study. Data of 154 subjects were used for the per protocol analysis. The average age of the 154 subjects was 72.1 (65–86) years. Twenty-four (27.3%) were Aβ positive for AD (age 65–83). The results of the logistic regression classifier showed that predictive features for Aβ positivity/negativity in CSF consist of sex, 7 CNS tests, and 1 plasma-based assay. The model achieved a sensitivity of 70.82% (± 4.35) and a specificity of 89.25% (± 4.35) with respect to identifying abnormal CSF in healthy elderly subjects. The receiver operating characteristic curve showed an AUC of 65% (± 0.10).

Conclusion

This algorithm would allow for a 70% reduction of lumbar punctures needed to identify subjects with abnormal CSF Aβ levels consistent with AD. The use of this algorithm can be expected to lower overall subject burden and costs of identifying subjects with preclinical AD and therefore of total study costs.

Trial registration

ISRCTN.org identifier: ISRCTN79036545 (retrospectively registered).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00874-9.

Diagnostic accuracy of the Cogstate Brief Battery for prevalent MCI and prodromal AD (MCI A+ T+ ) in a population-based sample

INTRODUCTION

This study evaluated the diagnostic accuracy of the Cogstate Brief Battery (CBB) for mild cognitive impairment (MCI) and prodromal Alzheimer's disease (AD) in a population-based sample.

METHODS

Participants included adults ages 50+ classified as cognitively unimpaired (CU, n = 2866) or MCI (n = 226), and a subset with amyloid (A) and tau (T) positron emission tomography who were AD biomarker negative (A-T-) or had prodromal AD (A+T+).

RESULTS

Diagnostic accuracy of the Learning/Working Memory Composite (Lrn/WM) for discriminating all CU and MCI was moderate (area under the curve [AUC] = 0.75), but improved when discriminating CU A-T- and MCI A+T+ (AUC = 0.93) and when differentiating MCI participants without AD biomarkers from those with prodromal AD (AUC = 0.86). Conventional cut-offs yielded lower than expected sensitivity for both MCI (38%) and prodromal AD (73%).

DISCUSSION

Clinical utility of the CBB for detecting MCI in a population-based sample is lower than expected. Caution is needed when using currently available CBB normative data for clinical interpretation.