Journal of Alzheimer's Disease

BackgroundAlzheimers disease involves brain pathologies such as amyloid plaque depositions and hyperphosphorylated tau tangles and is accompanied by cognitive decline. Identifying the biological mechanisms underlying disease onset and progression based on quantifiable phenotypes will help understand the disease etiology and devise therapies. ObjectiveOur objective was to identify molecular pathways associated with AD biomarkers (Amyloid-{beta} and tau) and cognitive status (MMSE) accounting for variables such as age, sex, education, and APOE genotype. MethodsWe introduce a novel pathway-based statistical approach, extending the gene set likelihood ratio test to continuous phenotypes. We first analyzed independently each of the three phenotypes (Amyloid-{beta}, tau, cognition), using continuous gene set likelihood ratio tests to account for covariates, including age, sex, education, and APOE genotype. The analysis involved a large sample size with data available for all three phenotypes, allowing for the identification of common pathways. ResultsWe identified 14 pathways significantly associated with Amyloid-{beta}, 5 associated with tau, and 174 associated with MMSE. Surprisingly, the MMSE outcome showed a larger number of significant pathways compared to biomarkers. A single pathway, vascular endothelial growth factor receptor binding (VEGF-RB), exhibited significant associations with all three phenotypes. ConclusionsThe studys findings highlight the importance of the VEGF signaling pathway in aging in AD. The complex interactions within the VEGF signaling family offer valuable insights for future therapeutic interventions.

INTRODUCTIONAlzheimers disease (AD) biomarkers can help differentiate cognitively unimpaired (CU) individuals from mild cognitive impairment (MCI) and dementia. The role of AD biomarkers in predicting cognitive impairment and AD needs examination. METHODSIn 628 CU individuals from a multi-ethnic cohort, A{beta}42, A{beta}40, phosphorylated tau-181 (P-tau181), glial fibrillary acid protein (GFAP), and neurofilament light chain (NfL) were measured in plasma. RESULTSHigher baseline levels of P-tau181/A{beta}42 ratio were associated with increased risk of incident dementia. A biomarker pattern (with elevated A{beta}42/A{beta}40 but low P-tau181/A{beta}42) was associated with decreased dementia risk. Compared to CU, participants who developed MCI or dementia had a rapid decrease in the biomarker pattern reflecting AD-specific pathological change. DISCUSSIONElevated levels of AD biomarker P-tau181/A{beta}42, by itself or combined with a low A{beta}42/A{beta}40 level, predicts clinically diagnosed AD. Individuals with a rapid change in these biomarkers may need close monitoring for the potential downward trajectory of cognition. Research in ContextO_LISystematic Review: Few studies have evaluated the clinical application of AD blood-based biomarkers longitudinally as antecedent risk predictors. Data from multiethnic populations are even more limited. How preclinical trajectories of blood-based biomarkers are related with the risk of developing clinically diagnosed MCI or AD is largely unknown. C_LIO_LIInterpretation: High circulating level of P-tau181/A{beta}42, by itself or combined with a low level of A{beta}42/A{beta}40, may predict development of incident clinical AD. Biomarkers levels of P-tau181, P-tau181/A{beta}42, and NfL increase with age even among individuals who remain cognitively healthy. A rapid change in biomarkers may indicate the individuals in the active trajectory to develop clinically diagnosed MCI or AD. C_LIO_LIFuture Directions: Larger studies or meta-analyses are needed to examine whether the predictive utility of blood-based biomarkers for AD differs across racial/ethnic groups. Well-designed studies are needed to evaluate the optimal duration between repeated measures of biomarkers. C_LI

INTRODUCTIONAlzheimers Disease (AD) is a major public health challenge. An AD-specific unfolded form of the p53 protein was identified (U-p53AZ) and data from animal studies suggests it colocalizes with pTau, in neurofibrillary tangles (NFT) METHODSBrain samples of patients with AD, cognitively unimpaired non-AD, and with fronto-temporal dementia (FTD) are being tested, comparing the pattern of U-p53AZ accumulation (using the antibody 2D3A8, developed by Diadem SpA) with accumulation of pTau, beta-amyloid, and TDP-43. RESULTSU-p53AZ accumulates in brain samples from AD, colocalizes with pTau in the NFT, with a small degree of accumulation in neuritic plaques (NP). The intensity of staining correlates with the pTau staining and Braak staging. No staining is observed in samples from cognitively unimpaired non-AD and FTD. DISCUSSIONThis study provides further support to the hypothesis that U-p53AZ is a player in AD pathology, in link with pTau accumulation and Braak staging.

Resting-state EEG records brain activity when awake but not engaged in tasks, analyzing frequency bands linked to cognitive states. Recent studies on Alzheimers disease (AD) and frontotemporal dementia (FTD) have found a link between EEG activity, MMSE scores, and age, though some findings are conflicting. This study aimed to explore EEG regional differences among AD and FTD, thereby improving diagnostic strategies. We analyzed EEG recordings from 88 participants in OpenNeuro Dataset ds004504, collected at AHEPA General Hospital using a Nihon Kohden 2100 EEG device. The study used preprocessed recordings, classification algorithms, and cognitive function assessments (MMSE) to identify significant predictors and correlations between EEG measures and cognitive variables. The study revealed that cognitive function, age, and brain activity show distinct relationships in AD and FTD. In AD, MMSE scores significantly predicted brain activity in regions like C3, C4, T4, and Fz, with better cognitive performance linked to higher EEG power in frontal and temporal areas. Conversely, age had a major influence on brain activity in FTD, particularly in regions like C3, P3, O1, and O2, while MMSE scores did not significantly predict brain activity. In FTD, higher EEG power in regions like P3, P4, Cz, and Pz correlated with lower cognitive function. Thus, the findings suggest that EEG biomarkers can enhance diagnostic strategies by highlighting different patterns of brain activity related to cognitive function and age in AD and FTD.

BackgroundDelaying the transition from minimal cognitive impairment to Alzheimers dementia is a major concern in Alzheimers disease (AD) therapeutics. Pathological signs of AD occur years before the onset of clinical dementia. Thus, long-term therapeutic approaches, with safe, minimally invasive, and yet effective substances are recommended. There is a need to develop new drugs to delay Alzheimers dementia. We have taken a nutritional supplement approach with genistein, a chemically defined polyphenol that acts by multimodal specific mechanisms. Our group previously showed that genistein supplementation is effective to treat the double transgenic (APP/PS1) AD animal model. MethodsIn this double-blind, placebo-controlled, bicentric clinical trial we evaluated the effect of daily oral supplementation with 120 mg of genistein for 12 months on 24 early symptomatic Alzheimers patients. We used a battery of validated neurocognitive tests: Mini-Mental State Exam (MMSE), Memory Alteration Test (M@T) Clock-drawing test, Complutense Verbal Learning Test (TAVEC), Barcelona Test-Revised (TBR), and Rey Complex Figure Test. ResultsWe report that genistein treatment results in a significant improvement in two of the tests used (dichotomized direct TAVEC, p=0.031; dichotomized delayed centil REY copy p=0.002 and a tendency to improve in all the rest of them. The amyloid-beta deposition was analyzed using 18F-flutemetamol uptake which showed that genistein-treated patients did not increase their uptake in the anterior cingulate gyrus after treatment (p = 0.878) while placebo-treated did increase it (p=0.036) We did not observe significant changes in other brain areas studied ConclusionsThis study shows that genistein may have a role in therapeutics to delay the onset of Alzheimers dementia in patients with mild cognitive impairment. These encouraging results indicate that this should be followed up by a new study with more patients to further validate the conclusion that arises from this study. Trial registrationNCT01982578

INTRODUCTIONRelationships between core Alzheimers disease (AD) biomarker accumulation and cognitive decline are well-established and the literature generally suggests a favorable relationship of cardiorespiratory fitness (CRF) on AD biomarker accumulation and cognition. Differences in risk of biomarker status conversion or accumulation rates by CRF, or their potential interactive relationships with cognitive decline remain largely unknown. METHODSParticipants (N=533; MeanAGE=65, 70% female) from the Wisconsin Alzheimers Disease Research Center and the Wisconsin Registry for Alzheimers Prevention underwent serial blood draws, and cognitive and imaging assessments (MeanFollow-up=6.0 years). PET imaging of amyloid-{beta} (A{beta}) and tau (T) and plasma phosphorylated tau-217 (pTau-217) were used to determine biomarker status (+/-). Sex-specific estimated CRF (eCRF) tertiles were created using a validated equation. Kaplan-Meier survival curves and Cox-proportional hazards models characterized the risk of becoming biomarker-positive. Linear mixed effects models estimated associations between baseline eCRF and core AD biomarker accumulation and whether eCRF modified relationships between biomarker accumulation and cognitive decline. Analyses were stratified by biomarker +/- status. RESULTSNo significant relationships were observed between eCRF and biomarker trajectories. However, those in the high eCRF group who were also A{beta}-(HR[95%CI]=0.42[0.20, 0.88]) and pTau-217-(HR[95%CI]=0.45[0.21, 0.97]) at baseline had a significantly lower risk of becoming biomarker-positive. There was a significant attenuation of the detrimental relationship between A{beta} accumulation and cognitive decline for those with high eCRF and A{beta}+/T+. DISCUSSIONWhile CRF did not influence core AD biomarker accumulation trajectories, high CRF did seem to protect against becoming biomarker-positive and attenuate the known deleterious relationship between biomarker accumulation and cognitive decline in A{beta}+/T+.

INTRODUCTIONThe association of blood-based biomarkers of neuropathology with cognition, dementia, and mortality and how these association potentially differ by race/ethnicity, has not been examined in large, diverse, nationally-representative samples of adults. METHODSThe sample included Health and Retirement Study (HRS) respondents over age 50 with blood-based neuropathology biomarker, demographic, and cognitive data (n=4,214). A{beta}-40, A{beta}-42, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured in plasma (Quanterix Neurology 4-Plex E kit), and phosphorylated tau (pTau-181) was measured in serum (Quanterix Advantage V2.0 kit). Cognitive tests included immediate and delayed word recall, serial 7s, and backward counting (total score 0-27). Dementia classification relied on a diagnostic algorithm previously validated in the HRS. RESULTSWhen each biomarker was analyzed individually, higher A{beta}-42/A{beta}-40 ratio was associated with better cognitive function among non-Hispanic (NH) whites. Higher NfL was associated with worse cognitive function in the total sample and in each race/ethnic group (NH white, NH black, and Hispanic). Higher pTau-181 was associated with worse cognitive function in the total and NH white sample. Higher GFAP was related to worse cognitive function in the total sample only. In a model that included all four biomarkers, NfL remained significantly related to cognitive performance in the total sample and in each race/ethnic group, and irrespective of APOE status. NfL was predictive of 6-year incident dementia in our sample (OR=1.33). All four markers significantly predicted 6-year mortality. DISCUSSIONIn a large nationally-representative sample of US adults, we found that NfL was the most consistent predictor of cross-sectional and incident dementia 6 years post blood collection. NfL was also the most consistent predictor across race/ethnic groups examined in our study. HighlightsThere are currently limited data on blood-based biomarkers of neuropathology as predictors of cognitive performance and incident dementia in diverse, population-based cohort studies. We used data from the Health and Retirement Study (n-=4,214) to examine the association between blood-based biomarkers of neuropathology and cognitive function, as well as their association with incident dementia and mortality 4 years after measurement. Mean levels of A{beta}-42/A{beta}-40 were similar across race/ethnic groups and age groups in this US population-representative sample where selection effects have been minimized. Average NfL was higher among non-Hispanic blacks and Hispanics; GFAP was higher among non-Hispanic blacks as compared to non-Hispanic whites. In a model that included all four biomarkers, NfL remained significantly related to cognitive performance in the total sample and in each race/ethnic group. NfL was associated with incident dementia 6 years after measurement in the total sample. A{beta}-42/A{beta}-40 ratio was predictive of 6-year incident dementia among those with at least one APOE e4 allele.

The plasma neurofilament light chain (NfL), an axonal cytoskeleton protein, increases in Alzheimers disease and was therefore proposed as a blood-based biomarker of the disease. Tensor-based morphometry (TBM) is an MR based modality that identifies local volume changes in the brain. Herein, we aimed to investigate whether plasma NfL measures can predict TBM findings derived from temporal lobe of brain in a one-year follow-up and which biomarker can predict cognitive function. A total of 480 participants with Alzheimers disease (AD), mild cognitive impairment (MCI), and normal cognition (CN) were found eligible for inclusion from The Alzheimers Disease Neuroimaging Initiative (ADNI) database. There was a significant negative association between plasma NfL and TBM only when all subjects were pooled together at baseline ({beta} = -0.139, P= 0.004). After one-year follow-up, 30 subjects with MCI converted to AD (MCI-AD) and others remained unchanged (CN, MCI, AD). Plasma NfL levels elevated significantly only in MCI group after one year (P<0.001). We found a significant reduction in TBM measurements at first-year compared to baseline in all groups (P<0.001 for all groups). Additionally, TBM average change rate was significantly higher in MCI-AD and AD groups (P<0.001 for both); however, plasma NfL average change rate was not significantly different between groups. TBM was significantly correlated with MMSE, MoCA, ADAS-11 and ADAS-13 scores in both MCI and AD patients at baseline and after one year, whereas plasma NfL was not. Overall, our findings indicate that plasma NfL is not reliably associated with TBM, and is less effective and sensitive than TBM in predicting dementia progression and cognitive performance. Hence, TBM reduction is not reflected in plasma NfL increment after one year follow-up.

BackgroundAn early and accurate diagnosis is crucial to provide optimal patient care in neurodegenerative diseases. Although an EEG shows advantages in availability and cost compared to the current diagnostic tools, it is not routinely used in clinical practice. Previous reviews have either focused on single disease populations and/or solely on resting state EEG. To evaluate the utility of EEG for early diagnosis and differential diagnosis, we conducted a systematic review across Alzheimers disease (AD), Frontotemporal Dementia (FTD) and Lewy Body Dementia (DLB). MethodsWe searched databases Pubmed, Cochrane, Web of Science, and Scopus for articles published from 2000 to 2023 investigating resting-state and task-based EEG-markers in biomarker-proven AD, FTD and DLB. ResultsOur search yielded a total of 12010 studies, of which 71 papers were eligible: 34 on AD, 18 on DLB and 9 on FTD. Slowing of the frequency spectrum was a common observation across diseases, achieving excellent sensitivity in AD and DLB. Research on FTD was limited and with varying results in the discrimination from healthy controls, although connectivity analysis and microstates are promising avenues. In differential diagnosis, both spectral and connectivity metrics show encouraging results. Task-based EEG emerges as a promising tool in early AD. ConclusionEEG shows promise as a cost-effective, non-invasive tool for early detection and differential diagnosis. Future research should aim to collect standardized data from multicentric cohorts, across multiple diseases and stages, and explore the neural underpinnings of these diseases, to improve interpretability of the findings.

ObjectivesTo assess whether the burden of mortality attributable to Alzheimers dementia in the US for women and men. MethodsData came from 3,491 women and 1,160 men ages 65 and older (mean 76.5 for both sexes) with no dementia at baseline from five longitudinal cohort studies of aging with identical annual diagnostic assessments of dementia. Mortality hazard ratios (HR) after incident Alzheimers dementia were estimated per 10-year age strata from proportional hazard models. Population attributable risk percent (PAR%) was derived to estimate excess mortality after a diagnosis of incident Alzheimers dementia. Results were then stratified by self-reported sex, and separately with an interaction term for sex by incident Alzheimers dementia. The number of excess deaths attributable to Alzheimers dementia in the US for women and men by age group was then estimated. ResultsOver an average of 9 (SD=5.8) years, 954 (27.3%) women and 316 (27.2%) men without dementia at baseline developed Alzheimers dementia; 1,792 (51.3%) women and 726 (62.6%) men died. In a model with terms for sex, race, education, incident Alzheimers dementia, and interaction between male sex and Alzheimers dementia, we observed an interaction (HR = 1.24, 95% CI: 1.00, 1.53) in the age strata 85+, indicating a higher risk of mortality due to Alzheimers dementia for men; at lower ages the interaction was opposite (HR = 0.75, 95% CI: 0.52, 1.09 in age strata 75-84), indicating higher risk of mortality from Alzheimers dementia for females. After further adjusting for vascular risk factors and diseases, the interactions were similar. PAR% was similar for age 85+ for women and men (33.4% and 32.9% respectively) but higher for women than men in the age strata 75-84 (24.2% and 19.1%). In 2023, we estimate 465,400 deaths--271,700 in women and 193,700 in men--were attributable to Alzheimers dementia. Adjusted PAR%s that took account of differences in vascular risk factors and disease showed even larger gaps for women compared to men (41.3% vs 37.5% for age 85+ and 33.2% vs 16.3% for age 75-84), resulting in estimates of 349,409 deaths from AD for women and 198,724 for men. ConclusionsThe number of deaths attributable to Alzheimers dementia is estimated to be 270,000-350,000, making it one of the leading causes of death in women, on par with cancer. The number is about 200,000 in men which also makes it a leading cause of death, on a par with accidents but much lower than cancer.

IntroductionAlzheimers Disease (AD) is the leading cause of dementia, accounting for 80% of cases globally. With an aging population, AD poses a growing concern due to its increasing mortality rate and associated healthcare costs. Early diagnosis or prediction of AD is crucial for managing and potentially slowing its progression, particularly with the advent of disease-modifying therapies. MethodsThis study involved a total of 60 participants: 15 with mild AD, 23 with mild cognitive impairment (MCI), and 22 healthy controls, comprising both males and females aged 50-85 years. Data collection included blood samples, the Montreal Cognitive Assessment (MoCA), and the Integrated Cognitive Assessment (ICA). Serum phosphorylated tau181 (p-tau181) levels were measured using enzyme-linked immunosorbent assay (ELISA) kits. Linear regression models were applied to predict serum biomarker levels based on the ICA index, demographic data, and APOE {varepsilon}4 status. Aims and ObjectivesThe primary aim was to examine the association between ICA scores and blood-based p-tau181 levels in individual with MCI, mild AD, and elderly healthy controls. Additionally, the study compared the correlation of ICA and MoCA with APOE {varepsilon}4 status. FindingsThe study found that the ICA can significantly differentiate between diagnostic groups and that elevated serum p-tau181 levels are associated with cognitive decline, as measured by the ICA. Additionally, a significant correlation was observed between APOE {varepsilon}4 status and cognitive decline, but not between APOE {varepsilon}4 status and serum p-tau181 levels. Using a model that incorporates the ICA, demographic data, and APOE {varepsilon}4 status, we were able to modestly predict serum p-tau181 levels, indicating the potential of combining cognitive assessment with biological markers for AD prediction. DiscussionThe findings suggest that ICA is a valuable tool in detecting cognitive decline associated with AD and correlates with increased p-tau181 levels. The significant correlation between APOE {varepsilon}4 status and cognitive decline highlights its potential role in risk assessment, independent of p-tau181 levels. The study supports the use of a computerized, self-administered cognitive assessment in conjunction with blood-based biomarkers for early AD detection. Limitations include the small sample size and cross-sectional design, which restricts causal inference and longitudinal analysis. Future research should focus on larger, longitudinal studies to further validate these associations and their implications for early diagnosis and monitoring of AD progression.

INTRODUCTIONAlzheimers disease (AD) is a major public health concern in Korea, with a high prevalence among older adults. A community-based longitudinal study is essential for tracking disease progression, identifying biomarkers, and developing targeted prevention and treatment strategies. The Gwangju Alzheimers and Related Dementias (GARD) cohort was established to address these needs through a multimodal approach. METHODSParticipants aged [&ge;]60 undergo comprehensive clinical evaluations, neuroimaging, and biospecimen collection for multi-omics analyses (genomics, transcriptomics, proteomics, microbiome) at baseline and systematic follow-up visits. RESULTSFrom over 17,000 screened individuals, 12,877 were enrolled. Baseline diagnoses include 5,995 cognitively unimpaired (CU), 4,025 mild cognitive impairment (MCI), and 1,026 AD dementia. The resource includes MRI scans (n=10,843) and extensive multi-omics data: genomic (n=10,775), proteome (n=116), and microbiome (n=595). DISCUSSIONThe integrated GARD dataset provides a powerful and scalable resource for identifying novel biomarkers, understanding disease heterogeneity, and advancing precision medicine for AD.

IntroductionCognitive impairment (CI) and its related risk factors (e.g., diabetes and stroke) are highly prevalent among Hispanic/Latinos (H/L); however, prior research in H/L focused on aging individuals ([&ge;]65 years of age). We conducted a prospective study in a younger cohort of H/L (majority <65 years old) from the Cameron County Hispanic Cohort (CCHC) to comprehensively assess the associations between a wide-range of cardiometabolic health indicators with CI. MethodsWe identified a total of 1240 CCHC subjects with complete Mini-mental status exam (MMSE) data at study baseline and at 5-year follow-up. The outcome (i.e., CI) was based on MMSE scores of less than 24. We conducted univariate associations for multiple cardiometabolic indicators with CI; and mixed logistic regression models to estimate odds ratios for the associations between cardiometabolic indicators and CI adjusted for age, education, prior stroke, and APOE gene. ResultsThe majority (89.9%) of the participants were <65 years old. A total of 117 subjects had CI at baseline (9.4%). Baseline study cohort showed that Individuals with CI were older with a lower education performance, and were more likely to be diabetic with lower mean levels of Low-density Lipoprotein, and a higher mean systolic blood pressure. Diabetes significantly increased the odds for CI (OR:2.11, 95%CI:1.26-3.52) from the adjusted multivariate mixed logistic models. ConclusionsThis analysis showed that diabetes was an important indicator for CI regardless of age, education, or APOE gene status. These findings highlight the higher burden of cardiometabolic risk factors on CI in the CCHC cohort.

The Ascertaining Dementia 8 (AD8) is a brief informant- or self-administered questionnaire designed to screen for cognitive impairment, offering several advantages over performance-based screening tests. We analyzed cross-sectional data from a non-probabilistic sample of English- and Spanish-speaking Latinos who were either cognitively unimpaired or had a research diagnosis of mild cognitive impairment or dementia. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, and the Youden Index was used to determine the optimal cutoff score. Internal consistency was tested with the Kuder-Richardson Formula 20, and concurrent validity with correlations to the Clinical Dementia Rating scale, Mini-Mental State Exam, and Montreal Cognitive Assessment scores. Among 46 participants, the optimal cutoff was 3 or higher for the total sample and in both language groups. At this threshold, the AD8 showed a sensitivity of 73.7% and specificity of 85.2%, with an area under the curve of 0.843. The AD8 achieved good internal consistency of 0.872 and demonstrated correlations in the expected directions with the cognitive impairment measures. The Spanish version generally outperformed the English version. The AD8 questionnaire has adequate psychometric properties and diagnostic performance among US Latinos. To our knowledge, this is the first manuscript to validate the AD8 among US Latinos. These findings support its use in healthcare settings and its applicability for multiple research purposes.

ObjectivesStage-sensitive markers can aid in early diagnosis of Alzheimers disease (AD) and can improve sensitivity, performance and interpretability. In this study, causal markers from longitudinal imaging data were extracted and integrated with risk factors to improve diagnostic models. Data DescriptionOASIS-3, a longitudinal dataset consisting of 613 controls and 214 cases with very mild to moderate Alzheimers disease is used for this study. A meta model was built using a predisposition model built from risk factors, a stage-sensitization model built from MRI markers at various stages of atrophy and a confirmatory model built using PET markers. The meta model achieved good diagnostic performance (accuracy = 93%, sensitivity = 80%, specificity = 95%). Exclusion of PET data achieved comparable performance (accuracy = 91%, sensitivity = 85%, specificity = 92%). The results demonstrate that integrating causal pathological markers with risk factors improves diagnosis and aids in elucidating stage-specific patterns of AD.

INTRODUCTIONGenome-wide association studies (GWAS) are fundamental for identifying loci associated with diseases. However, they require replication in other ethnicities. METHODSwe performed a GWAS on sporadic Alzheimers disease (AD) including 540 patients and 852 controls from Argentina and Chile. We explored the variants associated with AD in European GWAS from European Alzheimers and Dementia Biobank (EADB) and tested their genetic risk score (GRS) performance in this admixed population. RESULTSwe detected APOE4 as single genome-wide significant signal (OR=2.93[2.37-3.63], p=2.6x10-23), and fifteen additional suggestive signals previously undetected. Nine of the 83 variants reported by EADB in Europeans were replicated, and the AD-GRS presented similar performance in this Latin population, despite the score diminishes when the Native American ancestry rises. DISCUSSIONwe report the first GWAS on AD in a population from South America. It shows shared genetics that modulate AD risk between the European and the Latin American populations.

Structured AbstractO_ST_ABSBACKGROUNDC_ST_ABSPatient reports are the standard when examining subjective cognitive decline (SCD). Recent research suggests that informant and clinician reports may also be associated with cognition. This study examined differences between patient, informant, and clinician definitions of SCD and their relationship to cognition. METHODSData from 4290 older adults (n=1690 normal controls, NC; n=840 mild cognitive impairment, MCI; n=1760 Alzheimers disease, AD) were examined from the National Alzheimers Coordinating Center. Linear models examined the relationships between SCD status using the three definitions and cognition at baseline and over time. RESULTSIn NC, informant and clinician SCD were associated with worse cognition at baseline, with patient and clinician SCD associated with worse cognition over time. All definitions were associated with worse cognition at baseline and over time in MCI and AD. DISCUSSIONOur findings suggest the importance of examining different SCD definitions, especially the inclusion of clinician SCD.

BACKGROUND: Neuropsychiatric symptoms (NPS) are prevalent and debilitating in Alzheimer's disease (AD). Existing pharmacologic treatments are often ineffective and associated with serious adverse events. Identifying modifiable risk factors (MRFs) is critical for prevention and treatment. METHODS: Capitalizing on data from 14,497 individuals with AD from the National Alzheimer's Coordinating Center (NACC) database, we examined longitudinal associations between modifiable risk factors, APOE genotype and NPI-Q-assessed NPS using Cox proportional hazards models adjusted for demographics. RESULTS: Diabetes, alcohol consumption, smoking, and TBI were associated with an increased risk of specific NPS in AD. APOE{varepsilon}4 carrier status was linked to multiple NPS, showing a dose-response relationship. Education, LDL-C, and corrective lenses were protective; hypertension showed no associations. CONCLUSION: These findings strongly suggest that individual MRFs are associated with specific NPS in line with a complex etiology underlying these symptoms. Early detection and management of vascular, lifestyle and sensory factors could reduce NPS.

BackgroundVerbal speech-in-noise (SIN) measures are impaired in early Alzheimers disease (AD) but may be confounded by linguistic and cultural factors. We investigated whether non-verbal auditory memory could predict cognitive impairment in AD. MethodsWe evaluated 158 cognitively healthy individuals, 26 with mild cognitive impairment (MCI), and 28 with AD dementia using the Addenbrookes Cognitive Examination (ACE-III), pure-tone audiometry, verbal SIN tests, and non-verbal auditory memory tests for basic sound features. Group differences were assessed adjusting for age, sex, and education. Logistic regression and receiver operating characteristic (ROC) analyses compared model fit of verbal and non-verbal auditory variables. ResultsAll auditory cognition measures were significantly associated with cognition. Non-verbal measures provided a better fit to diagnosis than verbal measures (AIC difference >10), although ROC analyses showed no significant differences between models. ConclusionsNon-verbal auditory measures are effective measures in distinguishing between cognitively healthy, MCI, and AD dementia individuals.

A progressive reduction in synaptic connections between neurons is one neurophysiological indicator of brain ageing and was linked to the severity of dementia. In our study, we hypothesized that if synaptic disconnection as the neuropathology of Alzheimers disease (AD) is responsible for the brains inability to integrate diverse regions into efficient networks, then electroencephalographic data may be utilized to identify Alzheimers dementia. The study explored EEG coherence, reflecting connectivity between regions, as a potential AD indicator and identified four promising EEG coherence markers. As the pattern of degeneration follows the temporal-parietal-frontal axis, the temporal gamma marker was chosen for further evaluation. We utilize conventional analysis, producing paired results such as sensitivity and specificity and the receiver operating characteristic (ROC) curve to evaluate the accuracy of the temporal gamma marker. The optimal cut-off point of 0.950 was confirmed by both methods and provided 95% correct classification indicating an almost perfect differentiation between control and impaired cognitive status. This evaluation will be used in a blinded diagnostic test accuracy study to determine the TG_marker validity in detecting AD and excluding pseudo-dementias.