Probable Alzheimer Research Articles

Effects of an individual cognitive stimulation intervention on global cognition, memory, and executive function in older adults with mild to moderate Alzheimer's disease.

To determine the efficacy of a 12-week individual cognitive stimulation (iCS) intervention on global cognition, memory, and executive function of older adults with mild to moderate Alzheimer's disease (AD). Protocolized analysis using data from a multicenter, single-blind, randomized, parallel two-arm RCT of iCS for older adults with probable AD. A sample of 142 people with probable Alzheimer's disease attending 13 Portuguese institutions providing care and support services for older adults were selected. Intervention group (n = 72) received 24 iCS sessions, twice a week for 12 weeks. Control group (n = 70) maintained their activities as usual. Outcomes included global cognitive function (Mini-Mental State Examination, and Alzheimer's Disease Assessment Scale-Cognitive Subscale), memory (Memory Alteration Test, and Free and Cued Selective Reminding Test), and executive functioning (Frontal Assessment Battery). All participants were assessed at baseline (T0), after the intervention (T1), and 12 weeks follow-up (T2). The results showed significant improvements in memory performance at follow-up for the intervention group and greater stability in global cognition in the intervention relative to the control group. The current iCS protocol shows effectiveness in cognitive functioning in older adults with probable AD, particularly for memory upon completion of the intervention and at follow-up, adding further support to previous iCS studies showing similar results and to the effectiveness of the current intervention.

Associations between Sleep Duration and Autonomic Nervous System Regulation in Patients with Probable Alzheimer's Disease: A Cross-Sectional Pilot Study.

In this study, we aimed to investigate the relationships between sleep duration and autonomic nervous system (ANS) regulation. This cross-sectional pilot study included 27 older patients with probable Alzheimer's disease who were hospitalized at a psychiatric center. We measured heart rate variability to assess ANS regulation at night, evaluated dementia severity via the Clinical Dementia Rating scale, and obtained sleep duration data from sleep diaries maintained by psychiatric nurses. The data were analyzed using repeated-measures generalized linear models with age, sex, dementia severity, hypertension status, and medication use (antipsychotics) as covariates. A sleep duration of 6-9 h per night compared to shorter than 6 h was associated with a greater increase in parasympathetic nervous system activity (p = 0.03), and a sleep duration longer than 9 h was associated with a decrease sympathovagal balance (p = 0.02). In addition, we observed an inverted U-shaped association between sleep duration and ANS regulation. In this pilot study, we demonstrated that a sleep duration of 6-9 h per night may be beneficial for ANS regulation; however, the present study involved only a few participants and had some limitations. Additional research with a larger cohort is needed to confirm these findings.

Investigating patient eligibility for anti-amyloid monoclonal antibody treatment of Alzheimer's disease: real-world data from an Austrian psychiatric memory clinic population.

Pharmacological treatment options for patients with dementia owing to Alzheimer's disease are limited to symptomatic therapy. Recently, the US Food and Drug Administration approved the monoclonal antibody lecanemab for the treatment of amyloid-positive patients with mild cognitive impairment (MCI) and early Alzheimer´s dementia. European approval is expected in 2024. Data on the applicability and eligibility for treatment with anti-amyloid monoclonal antibodies outside of a study population are lacking. This study examined eligibility criteria for lecanemab in a real-world memory clinic population between 1 January 2022 and 31 July 2023. We conducted a retrospective, single-centre study applying the clinical trial eligibility criteria for lecanemab to out-patients of a specialised psychiatric memory clinic. Eligibility for anti-amyloid treatment was assessed following the phase 3 inclusion and exclusion criteria and the published recommendations for lecanemab. The study population consisted of 587 out-patients. Two-thirds were diagnosed with Alzheimer's disease (probable or possible Alzheimer's disease dementia in 43.6% of cases, n = 256) or MCI (23%, n = 135), and 33.4% (n = 196) were diagnosed with dementia or neurocognitive disorder owing to another aetiology. Applying all lecanemab eligibility criteria, 11 (4.3%) patients with dementia and two (1.5%) patients with MCI would have been eligible for treatment with this compound, whereas 13 dementia (5.1%) and 14 (10.4%) MCI patients met clinical inclusion criteria, but had no available amyloid status. Even in a memory clinic with a good infrastructure and sufficient facilities for dementia diagnostics, most patients do not meet the eligibility criteria for treatment with lecanemab.

A Two-Year Observational Study to Evaluate Conversion Rates from High- and Low-Risk Patients with Amnestic Mild Cognitive Impairment to Probable Alzheimer's Disease in a Real-World Setting.

Predicting conversion to probable Alzheimer&s disease (AD) from amnestic mild cognitive impairment (aMCI) is difficult but important. A nomogram was developed previously for determining the risk of 3-year probable AD conversion in aMCI. To compare the probable AD conversion rates with cognitive and neurodegenerative changes for 2 years from high- and low risk aMCI groups classified using the nomogram. This prospective, multicenter, observational study was conducted in Korea. A total of patients were classified as high- or low-risk aMCI according to the nomogram and followed-up for 2 years to compare the annual conversion rate to probable AD and brain structure changes between the two groups. In total, 176 (high-risk, 85; low-risk, 91) and 160 (high-risk, 77; low-risk, 83) patients completed the 1-year and 2-year follow-up, respectively. The probable AD conversion rate was significantly higher in the high-risk (Year 1, 28.9%; Year 2, 46.1%) versus low-risk group (Year 1, 0.0%; Year 2, 4.9%, both p < 0.0001). Mean changes from baseline in Seoul Neuropsychological Screening Battery-Dementia Version, Clinical Dementia Rating-Sum of Box, and Korean version of the Instrumental Activities of Daily Living scores and cortical atrophy index at Years 1 and 2 were significantly greater in the high-risk group (p < 0.0001). The high-risk aMCI group, as determined by the nomogram, had a higher conversion rate to probable AD and faster cognitive decline and neurodegeneration change than the low-risk group. These real-world results have clinical implications that help clinicians in accurately predicting patient outcomes and facilitating early decision-making.Trial Registration: ClinicalTrials.gov (NCT03448445).

Combining neuropsychological assessment and structural neuroimaging to identify early Alzheimer's disease in a memory clinic cohort.

The current study examined the contributions of comprehensive neuropsychological assessment and volumetric assessment of selected mesial temporal subregions on structural magnetic resonance imaging (MRI) to identify patients with amnestic mild cognitive impairment (aMCI) and mild probable Alzheimer's disease (AD) dementia in a memory clinic cohort. Comprehensive neuropsychological assessment and automated entorhinal, transentorhinal, and hippocampal volume measurements were conducted in 40 healthy controls, 38 patients with subjective memory symptoms, 16 patients with aMCI, 16 patients with mild probable AD dementia. Multinomial logistic regression was used to compare the neuropsychological and MRI measures. Combining the neuropsychological and MRI measures improved group membership prediction over the MRI measures alone but did not improve group membership prediction over the neuropsychological measures alone. Comprehensive neuropsychological assessment was an important tool to evaluate cognitive impairment. The mesial temporal volumetric MRI measures contributed no diagnostic value over and above the determinations made through neuropsychological assessment.

Serum neurofilament light chain and inflammatory cytokines as biomarkers for early detection of mild cognitive impairment

To investigate the association between serum neurofilament light chain (NfL) levels, inflammatory cytokines, and cognitive function to assess their utility in the early detection of mild cognitive impairment (MCI). We conducted a cross-sectional study involving 157 community-dwelling individuals aged 55 years and above, categorized into healthy controls, MCI, and probable Alzheimer's disease (AD). Serum levels of NfL, inflammatory cytokines, and AD pathology markers were measured using enzyme-linked immunosorbent assay (ELISA). Correlations between these biomarkers and cognitive function were analyzed, and the diagnostic performance of the cognitive assessment scales and serum biomarker concentrations was evaluated using receiver operating characteristic (ROC) curve analysis. Serum NfL levels were significantly elevated in MCI and probable AD groups compared to healthy controls. Positive correlations were found between serum NfL and inflammatory cytokines IL-1β, IL-6, and Aβ40. Combining serum NfL with p-tau217 and the Boston Naming Test significantly enhanced the predictive accuracy for MCI. However, combining serum NfL with inflammatory markers did not improve MCI prediction accuracy. Elevated serum NfL is associated with cognitive impairment and inflammatory markers, suggesting its potential as a peripheral serum biomarker for MCI detection. The combination of serum NfL with p-tau217 and cognitive tests could offer a more accurate prediction of MCI, providing new insights for AD treatment strategies.

The characteristic patterns of individual brain susceptibility networks underlie Alzheimer’s disease and white matter hyperintensity-related cognitive impairment

Excessive iron accumulation in the brain cortex increases the risk of cognitive deterioration. However, interregional relationships (defined as susceptibility connectivity) of local brain iron have not been explored, which could provide new insights into the underlying mechanisms of cognitive decline. Seventy-six healthy controls (HC), 58 participants with mild cognitive impairment due to probable Alzheimer’s disease (MCI-AD) and 66 participants with white matter hyperintensity (WMH) were included. We proposed a novel approach to construct a brain susceptibility network by using Kullback‒Leibler divergence similarity estimation from quantitative susceptibility mapping and further evaluated its topological organization. Moreover, sparse logistic regression (SLR) was applied to classify MCI-AD from HC and WMH with normal cognition (WMH-NC) from WMH with MCI (WMH-MCI).The altered susceptibility connectivity in the MCI-AD patients indicated that relatively more connectivity was involved in the default mode network (DMN)-related and visual network (VN)-related connectivity, while more altered DMN-related and subcortical network (SN)-related connectivity was found in the WMH-MCI patients. For the HC vs. MCI-AD classification, the features selected by the SLR were primarily distributed throughout the DMN-related and VN-related connectivity (accuracy = 76.12%). For the WMH-NC vs. WMH-MCI classification, the features with high appearance frequency were involved in SN-related and DMN-related connectivity (accuracy = 84.85%). The shared and specific patterns of the susceptibility network identified in both MCI-AD and WMH-MCI may provide a potential diagnostic biomarker for cognitive impairment, which could enhance the understanding of the relationships between brain iron burden and cognitive decline from a network perspective.

A Hypermutable Region in the DISP2 Gene Links to Natural Selection and Late-Onset Neurocognitive Disorders in Humans.

(CCG) short tandem repeats (STRs) are predominantly enriched in genic regions, mutation hotspots for C to T truncating substitutions, and involved in various neurological and neurodevelopmental disorders. However, intact blocks of this class of STRs are widely overlooked with respect to their link with natural selection. The human neuron-specific gene, DISP2 (dispatched RND transporter family member 2), contains a (CCG) repeat in its 5' untranslated region. Here, we sequenced this STR in a sample of 448 Iranian individuals, consisting of late-onset neurocognitive disorder (NCD) (N = 203) and controls (N = 245). We found that the region spanning the (CCG) repeat was highly mutated, resulting in several flanking (CCG) residues. However, an 8-repeat of the (CCG) repeat was predominantly abundant (frequency = 0.92) across the two groups. While the overall distribution of genotypes was not different between the two groups (p > 0.05), we detected four genotypes in the NCD group only (2% of the NCD genotypes, Mid-p = 0.02), consisting of extreme short alleles, 5- and 6-repeats, that were not detected in the control group. The patients harboring those genotypes received the diagnoses of probable Alzheimer's disease and vascular dementia. We also found six genotypes in the control group only (2.5% of the control genotypes, Mid-p = 0.01) that consisted of the 8-repeat and extreme long alleles, 9- and 10-repeats, of which the 10-repeat was not detected in the NCD group. The (CCG) repeat specifically expanded in primates. In conclusion, we report an indication of natural selection at a novel hypermutable region in the human genome and divergent alleles and genotypes in late-onset NhCDs and controls. These findings reinforce the hypothesis that a collection of rare alleles and genotypes in a number of genes may unambiguously contribute to the cognition impairment component of late-onset NCDs.

Diagnosis Framework for Probable Alzheimer's Disease and Mild Cognitive Impairment Based on Multi-Dimensional Emotion Features.

Emotion and cognition are intercorrelated. Impaired emotion is common in populations with Alzheimer's disease (AD) and mild cognitive impairment (MCI), showing promises as an early detection approach. We aim to develop a novel automatic classification tool based on emotion features and machine learning. Older adults aged 60 years or over were recruited among residents in the long-term care facilities and the community. Participants included healthy control participants with normal cognition (HC, n = 26), patients with MCI (n = 23), and patients with probable AD (n = 30). Participants watched emotional film clips while multi-dimensional emotion data were collected, including mental features of Self-Assessment Manikin (SAM), physiological features of electrodermal activity (EDA), and facial expressions. Emotional features of EDA and facial expression were abstracted by using continuous decomposition analysis and EomNet, respectively. Bidirectional long short-term memory (Bi-LSTM) was used to train classification model. Hybrid fusion was used, including early feature fusion and late decision fusion. Data from 79 participants were utilized into deep machine learning analysis and hybrid fusion method. By combining multiple emotion features, the model's performance of AUC value was highest in classification between HC and probable AD (AUC = 0.92), intermediate between MCI and probable AD (AUC = 0.88), and lowest between HC and MCI (AUC = 0.82). Our method demonstrated an excellent predictive power to differentiate HC/MCI/AD by fusion of multiple emotion features. The proposed model provides a cost-effective and automated method that can assist in detecting probable AD and MCI from normal aging.

Probable chronic pain, brain structure, and Alzheimer’s plasma biomarkers in older men

Chronic pain leads to tau accumulation and hippocampal atrophy in mice. In this study, we provide one of the first assessments in humans, examining the associations of probable chronic pain with hippocampal volume, integrity of the locus coeruleus (LC)—an upstream site of tau deposition—and Alzheimer’s Disease-related plasma biomarkers. Participants were mostly cognitively unimpaired men. Probable chronic pain was defined as moderate-to-severe pain in 2+ study waves at average ages 56, 62, and 68. At age 68, 424 participants underwent structural magnestic resonance imaging (MRI) of hippocampal volume and LC-sensitive MRI providing an index of LC integrity (LC contrast-to-noise ratio). Analyses adjusted for confounders including major health conditions, depressive symptoms, and opioid use. Models showed that men with probable chronic pain had smaller hippocampal volume and lower rostral-middle—but not caudal—LC contrast-to-noise ratio compared to men without probable chronic pain. Men with probable chronic pain also had higher levels of plasma total tau, beta-amyloid-42, and beta-amyloid-40 compared to men without probable chronic pain. These findings suggest that probable chronic pain is associated with tau accumulation and reduced structural brain integrity in regions affected early in the development of Alzheimer’s Disease. PerspectiveProbable chronic pain was associated with plasma biomarkers and brain regions that are affected early in Alzheimer’s disease (AD). Reducing pain in midlife and elucidating biological mechanisms may help to reduce the risk of AD in older adults.

Digital Clock and Recall is superior to the Mini-Mental State Examination for the detection of mild cognitive impairment and mild dementia

BackgroundDisease-modifying treatments for Alzheimer’s disease highlight the need for early detection of cognitive decline. However, at present, most primary care providers do not perform routine cognitive testing, in part due to a lack of access to practical cognitive assessments, as well as time and resources to administer and interpret the tests. Brief and sensitive digital cognitive assessments, such as the Digital Clock and Recall (DCR™), have the potential to address this need. Here, we examine the advantages of DCR over the Mini-Mental State Examination (MMSE) in detecting mild cognitive impairment (MCI) and mild dementia.MethodsWe studied 706 participants from the multisite Bio-Hermes study (age mean ± SD = 71.5 ± 6.7; 58.9% female; years of education mean ± SD = 15.4 ± 2.7; primary language English), classified as cognitively unimpaired (CU; n = 360), mild cognitive impairment (MCI; n = 234), or probable mild Alzheimer’s dementia (pAD; n = 111) based on a review of medical history with selected cognitive and imaging tests. We evaluated cognitive classifications (MCI and early dementia) based on the DCR and the MMSE against cohorts based on the results of the Rey Auditory Verbal Learning Test (RAVLT), the Trail Making Test-Part B (TMT-B), and the Functional Activities Questionnaire (FAQ). We also compared the influence of demographic variables such as race (White vs. Non-White), ethnicity (Hispanic vs. Non-Hispanic), and level of education (≥ 15 years vs. < 15 years) on the DCR and MMSE scores.ResultsThe DCR was superior on average to the MMSE in classifying mild cognitive impairment and early dementia, AUC = 0.70 for the DCR vs. 0.63 for the MMSE. DCR administration was also significantly faster (completed in less than 3 min regardless of cognitive status and age). Among 104 individuals who were labeled as “cognitively unimpaired” by the MMSE (score ≥ 28) but actually had verbal memory impairment as confirmed by the RAVLT, the DCR identified 84 (80.7%) as impaired. Moreover, the DCR score was significantly less biased by ethnicity than the MMSE, with no significant difference in the DCR score between Hispanic and non-Hispanic individuals.ConclusionsDCR outperforms the MMSE in detecting and classifying cognitive impairment—in a fraction of the time—while being not influenced by a patient’s ethnicity. The results support the utility of DCR as a sensitive and efficient cognitive assessment in primary care settings.Trial registrationClinicalTrials.gov identifier NCT04733989.

Differential gene expression of blood-based ABCA9, CNOT8, SESN1, UCP3, MAP2K1 and DDIT4 in Alzheimer’s disease

This study uncovered differential gene expression in blood to distinguish subjects with probable Alzheimer’s disease (AD) from normal elderly participants (non-demented controls, NDC). The participants were recruited via training (Phase 1) and validation cohorts (Phase 2). The changes of gene expression in blood samples from the training cohort (92 AD vs 92 NDC) were assessed using the microarray technology. The Partial Least Square Discrimination Analysis (PLSDA) was then used to develop a disease classifier algorithm (accuracy = 88.3%). Six differentially expressed genes were validated through RT-qPCR using blood samples from the validation cohort [(25 AD, 25 NDC, 12 mild cognitive impairment (MCI) and 12 vascular dementia (VaD) subjects] . The PLSDA model indicated a good separation between AD and NDC [area under the receiver operating characteristic curve (ROC AUC) = 0.88]. ABCA9, CNOT8, SESN1, UCP3, MAP2K1 and DDIT4 were found to be differentially expressed between the two groups. Validation of the panel of six genes gave an overall accuracy of 82.0% (AUC=0.86). The ABCA9 mRNA level, which was significantly (p &lt; 0.05) lower in the AD group, correctly classified 90.9% of all subjects (AUC=0.94). This group of genes may be responsible for dysregulation of pathways related to inflammation, mitochondrial dysfunction, oxidative injury, DNA damage, apoptosis and lipid metabolism. The disease classifier algorithm discriminated probable AD from MCI and VaD at specificity of 83.3% and 75.0%, respectively. These findings warrant further validation of potential blood-based biomarkers in larger samples of clinical AD.

Hyperbaric oxygen therapy—a new hope for Alzheimer’s patients: a case report and literature review

The currently available pharmacological anti-dementia treatments provide only temporary and limited benefits. Not surprisingly, patients and professionals increasingly explore non-pharmacological interventions that may alleviate dementia symptoms. Among these interventions is hyperbaric oxygen therapy (HBOT). A brief review is presented on HBOT use in medicine, with its mode of action in dementia, specifically Alzheimer’s disease, as well as a case report of self-initiated HBOT in a 63-year-old man with a clinical diagnosis of probable Alzheimer’s disease. He had over 400 HBOT sessions [2–3 times weekly, with a duration of 30–50 min, in a multi-place hyperbaric chamber at 2 atmospheres absolute (ATA)] over 7 years and use of donepezil (10 mg daily) for the last 3 years when formally diagnosed by the National Health Service (NHS) Memory Service. The patient’s longitudinal neurocognitive and neuroradiological evidence over 7 years of follow-up remained stable (with no major cognitive decline and no behavioral changes) when compared to his initial presentation when diagnosed by the private health provider. His driving remains unimpaired, and he continues to be independent. This highlights the potential HBOT benefits including those on visuospatial ability and activities of daily living in people with Alzheimer’s disease. This case report argues for more extensive research into the clinical effects of HBOT in Alzheimer’s disease. Discussion of HBOT use is along with the latest advances in anti-amyloid immunotherapy for Alzheimer’s disease, as well as HBOT augmentation of current and novel dementia drug delivery via nanotechnology.

Accelerated brain ageing in participants with higher cerebrovascular lesion load across aging, cognitive impairment, and mixed presentation

AbstractBackgroundWe aimed to investigate the association between cortical brain age and white matter hyperintensities (WMH) in diverse forms of clinically‐defined vascular conditions. Our hypothesis was that a higher WMH burden would be associated with higher cortical brain age in all clinical subtypes.MethodWe used standardized MRI data obtained from participants in the COMPASS‐ND cohort of the CCNA. We used a standard linear support vector regression algorithm to estimate brain age, matching chronological age to cortical anatomical measurements obtained with the FreeSurfer toolbox on T1‐weighted MRI, sex, and intracranial volume. We calculated brain‐PAD (i.e., predicted brain age minus real age) and applied bias adjustment to remove age‐dependency in the estimates. A validated automated technique utilizing T2‐weighted and fluid attenuated inversion recovery MRIs was used to compute WMH loads.ResultParticipants included 107 CIE, 240 mild cognitive impairment (MCI), 115 vascular‐MCI (V‐MCI), 81 probable Alzheimer’s disease (AD), and 50 V‐AD. There was a significant difference in brain‐PAD [ F (4,599) = 56, P &lt; 0.001, ANCOVA test] among groups, whilst adjusting for sex and chronological age. All four categories of patients exhibited a significantly higher mean brain‐PAD than CIE (P &lt; 0.001), with the AD cohort having the highest brain‐PAD. There was a significant difference in WMH loads [ F (4,586) = 48, P &lt; 0.001, ANCOVA test] between groups, whilst adjusting for sex and age. All cohorts showed a positive correlation between brain‐PAD and WMH, indicating accelerated ageing in people with higher WMHs. We observed moderate and significant correlations between brain‐PAD and WMH loads for V‐MCI (r = 0.34, P &lt; 0.001) and V‐AD (r = 0.36, P = 0.001) but weaker, while significant correlations in CIE (r = 0.20, P = 0.035) and AD cohorts (r = 0.24, P = 0.025).ConclusionWe observed a positive and significant link between brain‐PAD and WMH in all categories. This finding indicates on the importance of treatment and prevention strategies for vascular risk factors, which might be able to slow down the progression of cerebrovascular lesions and delay the effect on cortical thickness.

A comparative study of Amyloid positive and negative individuals with “Alzheimer Syndrome”

AbstractBackgroundOutside academic centres, the diagnosis of probable Alzheimer’s Disease remains a clinical diagnosis supported by basic blood work and structural brain imaging. It has already been documented, approximately 1/3rd of individuals meeting clinical criteria for probable AD, do not show underlying amyloidopathy on PET or cerebrospinal fluid. Thus, the clinical “Alzheimer Syndrome” encompasses individuals with abnormal amyloid (Amyloid positive: A+), as well as “amyloid negative” individuals lacking amyloidopathy. Finding ways to distinguish these subgroups clinically will become increasingly important as anti‐amyloid therapies become more available. It is not yet clear if these two groups have any clinical or imaging features that might distinguish them. Our objective was to find out if there are any clinical or imaging pointers towards amyloid biomarker status.MethodsA retrospective chart review of 23 patients screened for anti‐amyloid clinical trials was performed, of whom 13 were (A+) and 10 were (A‐). The following information was collected from the chart review‐ demography, medical history, clinical presentation, course of disease and rate of progression, neuropsychological test scores, blood work, brain scans, and any other relevant investigations. Relevant data were subjected to appropriate statistical analysis.ResultsThis is an ongoing study and the results are derived from interim analysis. Comparison of the (A+) and (A‐) groups revealed no statistically significant difference in terms of age, sex, amnestic presentation and cognitive decline rate. We did not find evidence (in this small group) that (A‐) subjects had a greater vascular load ‐ no difference in Hachinski score or Fazekas score. The only statistically significant difference between the groups was found in their NPI scores, with the A+ group showing a higher score (2.92 versus 0.80, p = 0.008).ConclusionAmyloid positive individuals are more likely to have neuropsychiatric manifestations during the course of their cognitive decline than their Amyloid negative counterpart. Work is ongoing to delineate biological and biomarker differences that account for the cortical dementia (Alzheimer Syndrome) in Amyloid negative subjects. Delineating differences in clinical presentation may prove useful in specifying which of these individuals are actually Amyloid positive. Confirmation in a larger group of subjects will be necessary.

3 Separating Memory Impairment from Other Neuropsychological Deficits on the CVLT-II

Objective:Learning curve patterns on list-learning tasks can help clinicians determine the nature of memory difficulties, as an “impaired” score may actually reflect attention and/or executive difficulties rather than a true memory impairment. Though such pattern analysis is often qualitative, there are quantitative methods to assess these concepts that have been generally underutilized. This study aimed to develop a model that decomposes learning over repeated trials into separate cognitive processes and then include other testing data to predict performance at each trial as a function of general cognitive functioning.Participants and Methods:Data for CVLT-II learning trials were obtained from an outpatient neuropsychology service within an academic medical center referred for clinical reasons. Participants with a cognitive diagnosis of non-demented (ND) or probable Alzheimer’s disease (AD) were included. The final sample consisted of 323 ND [Mage = 58.6 (14.8); Medu = 15.4 (2.7); 55.7% female] and 915 AD [Mage = 72.6 (9.0); Medu = 14.2 (3.1); 60.1% female cases. A Bayesian non-linear beta-binomial multilevel model was used, which uses three parameters to predict CVLT-II recall-by-trial: verbal attention span (VAS), maximal learning potential (MLP), and learning rate (LR). Briefly, VAS predicts expected first trial performance while MLP, conversely, predicts the expected best performance as trials are repeated, and LR weights the influence of VAS versus MLR over repeated trials. Predictors of these parameters included age, education, sex, race, and clinical diagnosis, in addition to raw scores on Trail Making Test Parts A and B, phonemic (FAS) fluency, animal fluency, Boston Naming Test, Wisconsin Card Sorting Test (WCST) Categories Completed, and then age-adjusted scaled scores from WAIS-IV Digit Span, Block Design, Vocabulary, and Coding. Random intercepts were included for each parameter and extracted for comparison of residual differences by diagnosis.Results:The model explained 84% of the variance in CVLT-II raw scores. VAS reduced with age and time-to-complete Trails B but improved with both verbal fluencies and confrontation naming. MLP increased as a function of WAIS Digit Span, animal fluency, confrontation naming, and WCST categories completed. Finally, LR was greater for females and WAIS-IV Coding and Vocabulary performances but reduced with age. Participants with AD had lower estimates of all three parameters: Cohen’s d = 2.49 (VAS) - 3.48 (LR), though including demographic and neuropsychological tests attenuated differences, Cohen’s d = 0.34 (LR) - 0.95 (MLP).Conclusions:The resulting model highlights how non-memory neuropsychological deficits affect list-learning test performance. At the same time, the model demonstrated that memory patterns on the CVLT-II can still be identified beyond other confounding deficits since having AD affected all parameters independent of other cognitive impairments. The modeling approach can generate conditional learning curves for individual patient data, and when multiple diagnoses are included in the model, a person-fit statistic can be computed to return the mostly likely diagnosis for an individual. The model can also be used in research to quantify or adjust for the effect of other patient data (e.g., neuroimaging, biomarkers, medications).

Association Between Hippocampal Volume and African Neuropsychology Memory Tests in Adult Individuals with Probable Alzheimer's Disease in Democratic Republic of Congo.

Western studies indicate potential associations between hippocampal volume and memory in the trajectory of Alzheimer's disease (AD). However, limited availability of neuroimaging technology and neuropsychological tests appropriate for sub-Saharan African (SSA) countries makes it difficult to establish neuroanatomical associations of hippocampus and memory in this locale. This study examined hippocampal volumes and memory in healthy control (HC) and probable AD groups in the Democratic Republic of Congo (DRC). Forty-six subjects with probable AD and 29 HC subjects were screened using the Community Instrument for Dementia and the Alzheimer Questionnaire. Participants underwent neuroimaging in Kinshasa, DRC, and memory was evaluated using the African Neuropsychology Battery (ANB). Multiple linear regression was used to determine associations between hippocampal volumes and memory. Patients with probable AD performed significantly worse than HCs on ANB memory measures, and exhibited greater cerebral atrophy, which was significantly pronounced in the medial temporal lobe region (hippocampus, entorhinal cortex). Both AD and HC subjects exhibited high rates of white matter hyperintensities compared to international base rate prevalence, which was significantly worse for probable AD. Both also exhibited elevated rates of microhemorrhages. Regression analysis demonstrated a significant association between hippocampal volume and ANB memory tests. Hippocampal atrophy discriminated probable AD from the HC group. This study establishes the feasibility of conducting neuroimaging research in the SSA, demonstrates many known neuroimaging findings in probable AD patients hold up using culturally appropriate memory tasks, and suggest cardiovascular problems are a greater issue in SSA than in Western countries.

A - 180 Anosognosia across the Spectrum of Alzheimer's Pathology and Validation of a New Measure.

Two studies were performed to validate a brief, new method for assessing informant-patient discrepancies to quantify cognitive insight, and to compare it to an empirically supported model - the Cognitive Awareness Model (CAM). Study 1 included 31 (52% male; Mage = 69.42) patients from an outpatient neuropsychological assessment clinic. Seven patients were diagnosed with probable Alzheimer's dementia (PAD), 15 mild cognitive impairment (MCI), and 9 no diagnosis (i.e., healthy controls; HC). The Cognitive Coding Form (CCF) was compared with several measures to assess convergent and discriminant validity. Study 2 entailed archival data extraction of 240 patients (80 HC, 80 MCI, and 80 PAD; 53.3% female; Mage = 72.8) to examine the ability of the CCF to predict various cognitive domains, including executive functioning (Trail-Making Test Form B). In study 1, the 8-item CCF demonstrated good convergent and discriminant validity with established measures. Study 2 identified that both patient-reported cognitive concerns and, to a greater degree, CCF informant-patient discrepancy scores, can distinguish HCs from those with MCI and PAD. Further, a regression indicated that depression (Geriatric Depression Scale; 5.5%; β= -0.38, p < 0.001) and TMT-B (13%; β= -0.43, p < 0.001), together accounted for 18.5% of the variance in insight (R2 = 0.19, F(2,219) = 26.10, p < 0.001), supporting the CAM. In addition to establishing an efficient measure of insight with high clinical utility (the CCF), these studies inform the literature on the role of insight in predicting performance in those with Alzheimer's pathology.

The efficacy and practicality of the Neurotrack Cognitive Battery assessment for utilization in clinical settings for the identification of cognitive decline in an older Japanese population.

Japan has the largest aging population with 33% of the population over the age of 60 years. The number of Japanese adults with dementia is estimated to be approximately 4.6 million, comprising nearly 15% of the older adult population. It is critical to administer cognitive assessments early in the disease state that have high reliability and low user burden to detect negative cognitive changes as early as possible; however, current preclinical AD detection methods are invasive, time-consuming, and expensive. A number of traditional and digital cognitive assessments are also available, but many of these tests are time-consuming, taxing to the user, and not widely scalable. The purpose of this study was to incorporate a digital cognitive assessment battery into a standard clinical assessment performed within a Japanese-based neuropsychology clinic to assess the diagnostic accuracy and the relationship between the digital Neurotrack Cognitive Assessment Battery (N-CAB) to traditional cognitive assessments. Healthy individuals and probable Alzheimer's patients completed the N-CAB, as well as two traditional cognitive assessments, the Mini Mental Status Exam (MMSE) and the Revised Hasegawa's Dementia Scale (HDS-R). Our results demonstrate the Image Pairs hand-response phase of the N-CAB had the highest diagnostic accuracy with 95% sensitivity and 89% specificity to probable Alzheimer's disease. This was closely followed by the Symbol Match assessment, with a 96% sensitivity and 74% specificity to probable Alzheimer's disease. Additionally, Symbol Match and Path Points used in combination resulted in a sensitivity of 94%, specificity of 90%; a model with all N-CAB assessments resulted in a sensitivity and specificity of 100%. All N-CAB assessments had moderate to strong and significant correlations with the MMSE and HDS-R. Together, this suggests that the N-CAB assessment battery may be an appropriate alternative for the clinical screening of cognition for earlier detection of Alzheimer's disease.

Comparison of cerebrospinal fluid space between probable normal pressure hydrocephalus and Alzheimer's disease.

Idiopathic normal pressure hydrocephalus (INPH) is a potentially reversible syndrome characterized by complex symptoms, difficulty in diagnosis and a lack of detailed clinical description, and it is difficult to distinguish from Alzheimer's disease (AD). The objective of this study was to design a method for measuring the actual amount of hydrocephalus in patients with INPH and to evaluate INPH. All subjects underwent a 3D T1-weighted MRI. Statistical parametric mapping 12 was used for preprocessing images, statistical analysis, and voxel-based morphometric gray matter (GM) volume, white matter (WM) volume, and cerebrospinal fluid (CSF) volume analysis. The demographic and clinical characteristics of the groups were compared using a t-test for continuous variables and a chi-square test for categorical variables. Pearson's correlation analysis and Bonferroni's statistic-corrected one-way ANOVA were used to determine the relationship among demographic variables. Receiver operating characteristic (ROC) curves were used to assess the accuracy of the callosal angle (CA), WM ratio, and CSF ratio in distinguishing probable INPH from AD. The study included 42 patients with INPH, 32 patients with AD, and 24 healthy control subjects (HCs). There were no differences among the three groups in basic characteristics except for Mini-Mental State Examination (MMSE). There was a correlation between the intracranial CSF ratio and CA. The WM ratio and CSF ratio in patients with INPH and AD were statistically different. Furthermore, the combination of CA, WM ratio, and CSF ratio had a greater differential diagnostic value between INPH and AD patients than CA alone. INPH can be accurately assessed by measuring intracranial CSF ratio, and the addition of WM ratio and CSF ratio significantly improved the differential diagnostic value of probable INPH from AD compared to CA alone.