Alzheimer's Disease Biomarkers Research Articles

Novel diagnostic and prognostic approach for rapidly progressive dementias: Indicators based on amyloid/tau/neurodegeneration (ATN) framework.

Apply established cerebrospinal fluid (CSF) and serum biomarkers and novel combined indicators based on the amyloid/tau/neurodegeneration (ATN) framework to improve diagnostic and prognostic power in patients with rapidly progressive dementias (RPDs). CSF and serum biomarkers of Alzheimer's disease (AD) common neuropathology including Aβ42, Aβ40, p-Tau, and t-Tau were measured in cognitively normal (CN) controls (n = 33) and three RPD groups with rapidly progressive AD (rpAD, n = 23), autoimmune encephalitis (AE, n = 25), and Creutzfeldt-Jakob disease (CJD, n = 28). Logistic regression and multiple linear regression were used for producing combined indicators and prognostic assessment, respectively, including A&T, A&N, T&N, A&T&N, etc. RESULTS: Combined diagnostic indicator with A&T&N had the potential for differentiating AE from other types of RPDs, identifying 62.51% and 75% of AE subjects based on CSF and serum samples, respectively, compared to 39.13% and 37.5% when using autoantibodies. CSF t-Tau was associated with survival in the CJD group (adjusted R-Square = 0.16, p = 0.02), and its prognosis value improved when using combined predictors based on the ATN framework (adjusted R-Square = 0.273, p = 0.014). Combined indicators based on the ATN framework provide a novel perspective for establishing biomarkers for early recognition of RPDs due to treatment-responsive causes.

Associations between IL-1β, IL-6, and TNFα polymorphisms and longitudinal trajectories of cognitive function in non-demented older adults

Inflammation is implicated in Alzheimer's disease (AD), and specific single nucleotide polymorphisms (SNPs) in inflammatory cytokine genes are associated with increased AD risk. Whether the same polymorphisms also predict domain-specific cognitive change in cognitively healthy older adults is unclear. Specific SNPs in three cytokine genes, IL-1β (rs16944), IL-6 (rs1800795), and TNFα (rs1800629) were assessed for association with longitudinal trajectories spanning up to 16 years of global cognitive function, episodic memory, attention and working memory, and executive function in a sample of 324 non-demented older adults. Only rs1800629 (TNFα) was associated with significant change in global cognitive function over time [γ = 5.22; 95% CI: 0.61, 9.83; p = 0.027]. Despite an association with AD risk, rs16944 and rs1800795 may not predict cognitive decline in cognitively healthy older adults. The presence of an A at rs1800629 (TNFα) may have broad, protective effects on cognitive function, over time. More validation studies are needed to determine whether specific cytokine SNPs are associated with respective serum levels to further understanding of AD biomarkers that may also serve as markers of cognitive decline.

Association of glial fibrillary acid protein, Alzheimer's disease pathology and cognitive decline.

Increasing evidence shows that neuroinflammation is a possible modulator of tau spread effects on cognitive impairment in Alzheimer's disease. In this context, plasma levels of the glial fibrillary acidic protein (GFAP) have been suggested to have a robust association with Alzheimer's disease pathophysiology. This study aims to assess the correlation between plasma GFAP and Alzheimer's disease pathology, and their synergistic effect on cognitive performance and decline. A cohort of 122 memory clinic subjects with amyloid and tau positron emission tomography, MRI scans, plasma GFAP, and Mini-Mental State Examination (MMSE) was included in the study. A subsample of 94 subjects had a follow-up MMSE score at least one year after baseline. Regional and voxel-based correlations between Alzheimer's disease biomarkers and plasma GFAP were assessed. Mediation analyses were performed to evaluate the effects of plasma GFAP on the association between amyloid and tau PET, and tau PET and cognitive impairment and decline. GFAP was associated with increased tau PET ligand uptake in the lateral temporal and inferior temporal lobes in a strong left-sided pattern independently of age, gender, education, amyloid, and APOE status (β=0.001, p < 0.01). The annual rate of MMSE change was significantly and independently correlated with both GFAP (β=0.006, p < 0.01) and global tau SUVR (β=4.33, p < 0.01), but not with amyloid burden. Partial mediation effects of GFAP were found on the association between amyloid and tau pathology (13.7%), and between tau pathology and cognitive decline (17.4%), but not on global cognition at baseline. Neuroinflammation measured by circulating GFAP is independently associated with tau Alzheimer's disease pathology and with cognitive decline, suggesting neuroinflammation as a potential target for future disease-modifying trials targeting tau pathology. Peretti et al. show that a circulatory marker of neuroinflammation-glial fibrillary acidic protein-is associated with tau pathology in lateral temporal and frontal regions in patients with Alzheimer's disease, independent of amyloid load. Neuroinflammation appears to modulate the association between amyloid and tau biomarkers.

Assessing amyloid PET positivity and cognitive function in Down syndrome to guide clinical trials targeting amyloid.

Trisomy 21, or Down syndrome (DS), predisposes individuals to early-onset Alzheimer's disease (AD). While monoclonal antibodies (mAbs) targeting amyloid are approved for older AD patients, their efficacy in DS remains unexplored. This study examines amyloid positron emission tomography (PET) positivity (A+), memory function, and clinical status across ages in DS to guide mAb trial designs. Cross-sectional data from the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) was analyzed. PET amyloid beta in Centiloids classified amyloid status using various cutoffs. Episodic memory was assessed using the modified Cued Recall Test, and clinical status was determined through consensus processes. Four hundred nine DS adults (mean age=44.83 years) were evaluated. A+ rates increased with age, with mean amyloid load rising significantly. Memory decline and cognitive impairment are also correlated with age. These findings emphasize the necessity of tailoring mAb trials for DS, considering age-related AD characteristics. There is rapid increase in prevalence of amyloid beta (Aβ) positron emission tomography (PET) positivity in Down syndrome (DS) after the age of 40 years. Aβ PET positivity thresholds have significant impact on prevalence rates in DS. There is a significant lag between Aβ PET positivity and clinical symptom onset in DS.

Integration of single-cell sequencing with machine learning and Mendelian randomization analysis identifies the NAP1L1 gene as a predictive biomarker for Alzheimer's disease.

The most effective approach to managing Alzheimer's disease (AD) lies in identifying reliable biomarkers for AD to forecast the disease in advance, followed by timely early intervention for patients. Transcriptomic data on peripheral blood mononuclear cells (PBMCs) from patients with AD and the control group were collected, and preliminary data processing was completed using standardized analytical methods. PBMCs were initially segmented into distinct subpopulations, and the divisions were progressively refined until the most significantly altered cell populations were identified. A combination of high-dimensional weighted gene co-expression analysis (hdWGCNA), cellular communication, pseudotime analysis, and single-cell regulatory network inference and clustering (SCENIC) analysis was used to conduct single-cell transcriptomics analysis and identify key gene modules from them. Genes were screened using machine learning (ML) in the key gene modules, and internal and external dataset validations were performed using multiple ML methods to test predictive performance. Finally, bidirectional Mendelian randomization (MR) analysis, regional linkage analysis, and the Steiger test were employed to analyze the key gene. A significant decrease in non-classical monocytes was detected in PMBC of AD patients. Subsequent analyses revealed the inherent connection of non-classical monocytes to AD, and the NAP1L1 gene identified within its gene module appeared to exhibit some association with AD as well. The NAP1L1 gene is a potential predictive biomarker for AD.

Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a lumbar puncture to be performed, making them impractical as screening tools. Considering the role of sleep disturbances in AD, recent research suggests quantitative sleep electroencephalography features as potential non-invasive biomarkers of AD pathology. However, quantitative analysis of comprehensive polysomnography (PSG) signals remains relatively understudied. PSG is a non-invasive test enabling qualitative and quantitative analysis of a wide range of parameters, offering additional insights alongside other biomarkers. Machine Learning (ML) gained interest for its ability to discern intricate patterns within complex datasets, offering promise in AD neuropathology detection. Therefore, this study aims to evaluate the effectiveness of a multimodal ML approach in predicting core AD CSF biomarkers. Mild-moderate AD patients were prospectively recruited for PSG, followed by testing of CSF and blood samples for biomarkers. PSG signals underwent preprocessing to extract non-linear, time domain and frequency domain statistics quantitative features. Multiple ML algorithms were trained using four subsets of input features: clinical variables (CLINVAR), conventional PSG parameters (SLEEPVAR), quantitative PSG signal features (PSGVAR) and a combination of all subsets (ALL). Cross-validation techniques were employed to evaluate model performance and ensure generalizability. Regression models were developed to determine the most effective variable combinations for explaining variance in the biomarkers. On 49 subjects, Gradient Boosting Regressors achieved the best results in estimating biomarkers levels, using different loss functions for each biomarker: least absolute deviation (LAD) for the Aβ42, least squares (LS) for p-tau and Huber for t-tau. The ALL subset demonstrated the lowest training errors for all three biomarkers, albeit with varying test performance. Specifically, the SLEEPVAR subset yielded the best test performance in predicting Aβ42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors. Multimodal ML can help predict the outcome of CSF biomarkers in early AD by utilizing non-invasive and economically feasible variables. The integration of computational models into medical practice offers a promising tool for the screening of patients at risk of AD, potentially guiding clinical decisions.

A New Perspective on Alzheimer's Disease Biomarkers in the IVD Field

A New Perspective on Alzheimer's Disease Biomarkers in the IVD Field

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.

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). 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. 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. 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.

Leveraging Diverse Regulated Cell Death Patterns to Identify Diagnosis Biomarkers for Alzheimer’s Disease

BackgroundThe functions of regulated cell death (RCD) are closely related to Alzheimer’s disease (AD). However, very few studies have systematically investigated the diagnosis and immunologic role of RCD-related genes in AD patients.Methods8 multicenter AD cohorts were included in this study, and then were merged into a meta cohort. Then, an unsupervised clustering analysis was carried out to detect unique subtypes of AD based on RCD-related genes. Subsequently, differently expressed genes (DEGs) and weighted correlation network analysis (WGCNA) between subtypes were identified. Finally, to establish an optimal risk model, an RCD. score was constructed by using computational algorithm (10 machine-learning algorithms, 113 combinations).ResultsWe identified two distinct subtypes based on RCD-related genes, each exhibiting distinct hallmark pathway activity and immunologic landscape. Specifically, cluster.A patients had a higher immune infiltration, a higher immune modulators and poor AD progression. Utilizing the shared DEGs and WGCNA of these subtypes, we constructed an RCD. score that demonstrated excellent predictive ability in AD across multiple datasets. Furthermore, RCD.score was identified to exhibit the strongest association with poor AD progression. Mechanistically, we observed activation of signaling pathways and effective immune infiltration and immune modulators in the high RCD.score group, thus leading to a poor AD progression. Additionally, Mendelian randomization screening revealed four genes (CXCL1, ENTPD2, METTL7A, and SERPINB6) as feature genes for AD.ConclusionThe RCD model is a valuable tool in categorizing AD patients. This model can be of great assistance to clinicians in determining the most suitable personalized treatment plan for each individual AD patient.

Exercise to Counteract Alzheimer's Disease: What Do Fluid Biomarkers Say?

Neurodegenerative diseases (NDs) represent an unsolved problem to date with an ever-increasing population incidence. Particularly, Alzheimer's disease (AD) is the most widespread ND characterized by an accumulation of amyloid aggregates of beta-amyloid (Aβ) and Tau proteins that lead to neuronal death and subsequent cognitive decline. Although neuroimaging techniques are needed to diagnose AD, the investigation of biomarkers within body fluids could provide important information on neurodegeneration. Indeed, as there is no definitive solution for AD, the monitoring of these biomarkers is of strategic importance as they are useful for both diagnosing AD and assessing the progression of the neurodegenerative state. In this context, exercise is known to be an effective non-pharmacological management strategy for AD that can counteract cognitive decline and neurodegeneration. However, investigation of the concentration of fluid biomarkers in AD patients undergoing exercise protocols has led to unclear and often conflicting results, suggesting the need to clarify the role of exercise in modulating fluid biomarkers in AD. Therefore, this critical literature review aims to gather evidence on the main fluid biomarkers of AD and the modulatory effects of exercise to clarify the efficacy and usefulness of this non-pharmacological strategy in counteracting neurodegeneration in AD.

Late-onset temporal lobe epilepsy: insights from brain atrophy and Alzheimer's disease biomarkers.

Considering the growing age of the world population, the incidence of epilepsy in older adults is expected to increase significantly. It has been suggested that late-onset temporal lobe epilepsy (LO-TLE) may be neurodegenerative in origin and overlap with Alzheimer's Disease (AD). Herein, we aimed to characterize the pattern of cortical atrophy and cerebrospinal fluid (CSF) biomarkers of AD (total and phosphorylated tau, and β-amyloid) in a selected population of LO-TLE of unknown origin. We prospectively enrolled individuals with temporal lobe epilepsy onset after the age of 50 and no cognitive impairment. They underwent a structural MRI scan and CSF biomarkers measurement. Imaging and biomarkers data were compared to three retrospectively collected groups: (i) age-sex-matched healthy controls, (ii) patients with Mild Cognitive Impairment (MCI) and abnormal CSF AD biomarkers (MCI-AD), and (iii) patients with MCI and normal CSF AD biomarkers (MCI-noAD). From a pool of 52 patients, twenty consecutive eligible LO-TLE patients with a mean disease duration of 1.8 years were recruited. As control populations, 25 patients with MCI-AD, 25 patients with MCI-noAD, and 25 healthy controls were enrolled. CSF biomarkers returned normal values in LO-TLE, significantly different from patients with MCI due to AD. There were no differences in cortico-subcortical atrophy between epilepsy patients and healthy controls, while patients with MCI demonstrated widespread injuries of cortico-subcortical structures. Individuals with a late-onset form of temporal lobe epilepsy, characterized by short disease duration and normal CSF β-amyloid and tau protein levels, showed patterns of cortical thickness and subcortical volumes not significantly different from healthy controls, but highly different from patients with MCI, either due to Alzheimer's Disease or not.

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.

Predicting Driving Cessation Among Cognitively Normal Older Drivers: The Role of Alzheimer Disease Biomarkers and Clinical Assessments.

With the aging US population and increasing incidence of Alzheimer disease (AD), understanding factors contributing to driving cessation among older adults is crucial for clinicians. Driving is integral for maintaining independence and functional mobility, but the risk factors for driving cessation, particularly in the context of normal aging and preclinical AD, are not well understood. We studied a well-characterized community cohort to examine factors associated with driving cessation. This prospective, longitudinal observation study enrolled participants from the Knight Alzheimer Disease Research Center and The DRIVES Project. Participants were enrolled if they were aged 65 years or older, drove weekly, and were cognitively normal (Clinical Dementia Rating [CDR] = 0) at baseline. Participants underwent annual clinical, neurologic, and neuropsychological assessments, including β-amyloid PET imaging and CSF (Aβ42, total tau [t-Tau], and phosphorylated tau [p-Tau]) collection every 2-3 years. The primary outcome was time from baseline visit to driving cessation, accounting for death as a competing risk. The cumulative incidence function of driving cessation was estimated for each biomarker. The Fine and Gray subdistribution hazard model was used to examine the association between time to driving cessation and biomarkers adjusting for clinical and demographic covariates. Among the 283 participants included in this study, there was a mean follow-up of 5.62 years. Driving cessation (8%) was associated with older age, female sex, progression to symptomatic AD (CDR ≥0.5), and poorer performance on a preclinical Alzheimer cognitive composite (PACC) score. Aβ PET imaging did not independently predict driving cessation, whereas CSF biomarkers, specifically t-Tau/Aβ42 (hazard ratio [HR] 2.82, 95% CI 1.23-6.44, p = 0.014) and p-Tau/Aβ42 (HR 2.91, 95% CI 1.28-6.59, p = 0.012) ratios, were independent predictors in the simple model adjusting for age, education, and sex. However, in the full model, progression to cognitive impairment based on the CDR and PACC score across each model was associated with a higher risk of driving cessation, whereas AD biomarkers were not statistically significant. Female sex, CDR progression, and neuropsychological measures of cognitive functioning obtained in the clinic were strongly associated with future driving cessation. The results emphasize the need for early planning and conversations about driving retirement in the context of cognitive decline and the immense value of clinical measures in determining functional outcomes.

A Novel Peptidome Technology for the Diagnosis of Mild Cognitive Impairment and Alzheimer’s Disease by Selected Reaction Monitoring

Background: With the aging of populations worldwide, Alzheimer’s disease (AD) has become a concern due to its high prevalence and the continued lack of established treatments. Early diagnosis is required as a preventive intervention to modify the disease’s progression. In our previous study, we performed peptidomic analysis of serum samples obtained from AD patients and age-matched healthy subjects to seek peptide biomarker candidates for AD by using BLOTCHIP-MS analysis, and identified four peptides as AD biomarker candidates. Objective: The objective was to validate the serum biomarker peptides to distinguish mild cognitive impairment (MCI) and AD in comparison to cognitively healthy controls using a new peptidome technology, the Dementia Risk Test. Methods: We enrolled 195 subjects with normal cognitive function (NC; n = 70), MCI (n = 55), and AD (n = 70), The concentrations of cognitive impairment marker peptides (Fibrinogen α chain (FAC), Fibrinogen β chain (FBC), Plasma protease C1 inhibitor (PPC1I), α2-HS-glycoprotein (AHSG)) were quantified by using a selected reaction monitoring assay based on liquid chromatography-MS/MS. Results: The present study confirmed that three peptides, FAC, FBC, and PPC1I, were significantly upregulated during the onset of AD. This three-peptide set was both highly sensitive in determining AD (sensitivity: 85.7%, specificity: 95.7%, AUC: 0.900) and useful in distinguishing MCI (sensitivity: 61.8%, specificity: 98.6%, AUC: 0.824) from NC. Conclusions: In this validation study, we confirmed the high diagnostic potential of the three peptides identified in our previous study as candidate serum biomarkers for AD. The Dementia Risk Test may be a powerful tool for detecting AD-related pathological changes.

Association Between Carotid Plaque and Alzheimer’s Disease Cerebrospinal Fluid Biomarkers and Cognitive Function in Cognitively Intact Adults: The CABLE Study

Background: The association between carotid plaque and cognitive decline has recently been reported. However, the current research evidence is insufficient, and the possible causes of cognitive changes are unknown. Objective: This study aims to explore the relationships between carotid plaque and cognition functions, cerebrospinal fluid (CSF) Alzheimer’s disease (AD) biomarkers in cognitively intact adults, and try to study the underlying mechanisms. Methods: We enrolled 165 cognitively normal participants from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) study, who had CSF AD biomarker measurements and carotid ultrasound. Linear modeling was used to assess the association of carotid plaque with CSF biomarkers and cognition. Additionally, mediation analysis was conducted through 10,000 bootstrapped iterations to explore potential links between carotid plaque, AD pathology, and cognition. Results: We found that carotid plaque exhibited significant correlations with Aβ42 (β = –1.173, p = 0.022), Aβ42/Aβ40 (β = –0.092, p &lt; 0.001), P-tau/Aβ42 (β = 0.110, p = 0.045), and T-tau/Aβ42 (β = 0.451, p = 0.010). A significant correlation between carotid plaque and cognition decline was also found in men (β = –0.129, p = 0.021), and mediation analyses revealed that the effect of carotid plaque on cognitive function could be mediated by Aβ42/Aβ40 (proportion of mediation = 55.8%), P-tau/Aβ42 (proportion of mediation = 51.6%, p = 0.015) and T-tau/Aβ42 (proportion of mediation = 43.8%, p = 0.015) mediated. Conclusions: This study demonstrated the link between carotid plaque and CSF AD biomarkers in cognitively intact adults, and the important role that AD pathology may play in the correlation between carotid plaque and cognitive changes.

Lower Prevalence of Asymptomatic Alzheimer's Disease Among Healthy African Americans.

Alzheimer's disease (AD) is believed to be more common in African Americans (AA), but biomarker studies in AA populations are limited. This report represents the largest study to date examining cerebrospinal fluid AD biomarkers in AA individuals. We analyzed 3,006 cerebrospinal fluid samples from controls, AD cases, and non-AD cases, including 495 (16.5%) self-identified black/AA and 2,456 (81.7%) white/European individuals using cutoffs derived from the Alzheimer's Disease Neuroimaging Initiative, and using a data-driven multivariate Gaussian mixture of regressions. Distinct effects of race were found in different groups. Total Tauand phospho181-Tau were lower among AA individuals in all groups (p < 0.0001), and Aβ42 was markedly lower in AA controls compared with white controls (p < 0.0001). Gaussian mixture of regressions modeling of cerebrospinal fluid distributions incorporating adjustments for covariates revealed coefficient estimates for AA race comparable with 2-decade change in age. Using Alzheimer's Disease Neuroimaging Initiative cutoffs, fewer AA controls were classified as biomarker-positive asymptomatic AD (8.0% vs 13.4%). After adjusting for covariates, our Gaussian mixture of regressions model reduced this difference, but continued to predict lower prevalence of asymptomatic AD among AA controls (9.3% vs 13.5%). Although the risk of dementia is higher, data-driven modeling indicates lower frequency of asymptomatic AD in AA controls, suggesting that dementia among AA populations may not be driven by higher rates of AD. ANN NEUROL 2024;96:463-475.

Eye Adult Changes in Thought (Eye ACT) Study: Design and Report on the Inaugural Cohort.

Conflicting research on retinal biomarkers of Alzheimer's disease and related dementias (AD/ADRD) is likelyrelated to limited sample sizes, study design, and protocol differences. The prospective Eye Adult Changes in Thought (Eye ACT) seeks to address these gaps. Eye ACT participants are recruited from ACT, an ongoing cohort of dementia-free, older adults followed biennially until AD/ADRD, and undergo visual function and retinal imaging assessment either in clinic or at home. 330 participants were recruited as of 03/2023. Compared to ACT participants not in Eye ACT (N = 1868), Eye ACT participants (N = 330) are younger (mean age: 70.3 versus 71.2, p = 0.014), newer to ACT (median ACT visits since baseline: 3 versus 4, p < 0.001), have more years of education (17.7 versus 16.2, p < 0.001) and had lower rates of visual impairment (12% versus 22%, p < 0.001). Compared to those seen in clinic (N = 300), Eye ACT participants seen at home (N = 30) are older (77.2 versus 74.9, p = 0.015), more frequently female (60% versus 49%, p = 0.026), and have significantly worse visual acuity (71.1 versus 78.9 Early Treatment Diabetic Retinopathy Study letters, p < 0.001) and contrast sensitivity (-1.9 versus -2.1 mean log units at 3 cycles per degree, p = 0.002). Cognitive scores and retinal imaging measurements are similar between the two groups. Participants assessed at home had significantly worse visual function than those seen in clinic. By including these participants, Eye ACT provides a unique longitudinal cohort for evaluating potential retinal biomarkers of dementia.

Cholesterol profiling reveals 7β-hydroxycholesterol as a pathologically relevant peripheral biomarker of Alzheimer's disease.

Cholesterol homeostasis is associated with Alzheimer's disease (AD). Despite the multitude of cholesterol metabolites, little is known about which metabolites are directly involved in AD pathogenesis and can serve as its potential biomarkers. To identify "hit" metabolites, steroid profiling was conducted in mice with different age, diet, and genotype and also in humans with normal cognition, mild cognitive impairment, and AD using gas chromatography-mass spectrometry. Then, using one of the "hit" molecules (7β-hydroxycholesterol; OHC), molecular and histopathological experiment and behavioral testing were conducted in normal mice following its intracranial stereotaxic injection to see whether this molecule drives AD pathogenesis and causes cognitive impairment. The serum levels of several metabolites, including 7β-OHC, were increased by aging in the 3xTg-AD unlike normal mice. Consistently, the levels of 7β-OHC were increased in the hairs of patients with AD and were correlated with clinical severity. We found that 7β-OHC directly affects AD-related pathophysiology; intrahippocampal injection of 7β-OHC induced astrocyte and microglial cell activation, increased the levels of pro-inflammatory cytokines (TNF-alpha, IL-1β, IL-6), and enhanced amyloidogenic pathway. Mice treated with 7β-OHC also exhibited deficits in memory and frontal/executive functions assessed by object recognition and 5-choice serial reaction time task, respectively. Our results suggest that 7β-OHC could serve as a convenient, peripheral biomarker of AD. As directly involved in AD pathogenesis, 7β-OHC assay may help actualize personalized medicine in a way to identify an at-risk subgroup as a candidate population for statin-based AD treatment.

Effects of time of the day at sampling on CSF and plasma levels of Alzheimer’ disease biomarkers

BackgroundStudies suggest that cerebrospinal fluid (CSF) levels of amyloid-β (Aβ)42 and Aβ40 present a circadian rhythm. However sustained sampling of large volumes of CSF with indwelling intrathecal catheters used in most of these studies might have affected CSF dynamics and thereby confounded the observed fluctuations in the biomarker levels.MethodsWe included 38 individuals with either normal (N = 20) or abnormal (N = 18) CSF Aβ42/Aβ40 levels at baseline. CSF and plasma were collected at two visits separated by an average of 53 days with lumbar punctures and venipunctures performed either in the morning or evening. At the first visit, sample collection was performed in the morning for 17 participants and the order was reversed for the remaining 21 participants. CSF and plasma samples were analyzed for Alzheimer’ disease (AD) biomarkers, including Aβ42, Aβ40, GFAP, NfL p-tau181, p-tau217, p-tau231 and t-tau. CSF samples were also tested using mass spectrometry for 22 synaptic and endo-lysosomal proteins.ResultsCSF Aβ42 (mean difference [MD], 0.21 ng/mL; p = 0.038), CSF Aβ40 (MD, 1.85 ng/mL; p < 0.001), plasma Aβ42 (MD, 1.65 pg/mL; p = 0.002) and plasma Aβ40 (MD, 0.01 ng/mL, p = 0.002) were increased by 4.2-17.0% in evening compared with morning samples. Further, CSF levels of 14 synaptic and endo-lysosomal proteins, including neurogranin and neuronal pentraxin-1, were increased by 4.5-13.3% in the evening samples (MDrange, 0.02-0.56 fmol/µl; p < 0.042). However, no significant differences were found between morning and evening levels for the Aβ42/Aβ40 ratio, different p-tau variants, GFAP and NfL. There were no significant interaction between sampling time and Aβ status for any of the biomarkers, except that CSF t-tau was increased (by 5.74%) in the evening samples compared to the morning samples in Aβ-positive (MD, 16.46 ng/ml; p = 0.009) but not Aβ-negative participants (MD, 1.89 ng/ml; p = 0.47). There were no significant interactions between sampling time and order in which samples were obtained.DiscussionOur findings provide evidence for diurnal fluctuations in Aβ peptide levels, both in CSF and plasma, while CSF and plasma p-tau, GFAP and NfL were unaffected. Importantly, Aβ42/Aβ40 ratio remained unaltered, suggesting that it is more suitable for implementation in clinical workup than individual Aβ peptides. Additionally, we show that CSF levels of many synaptic and endo-lysosomal proteins presented a diurnal rhythm, implying a build-up of neuronal activity markers during the day. These results will guide the development of unified sample collection procedures to avoid effects of diurnal variation for future implementation of AD biomarkers in clinical practice and drug trials.

An interim exploratory proteomics biomarker analysis of a phase 2 clinical trial to assess the impact of CT1812 in Alzheimer's disease

CT1812 is a novel, brain penetrant small molecule modulator of the sigma-2 receptor (S2R) that is currently in clinical development for the treatment of Alzheimer's disease (AD). Preclinical and early clinical data show that, through S2R, CT1812 selectively prevents and displaces binding of amyloid beta (Aβ) oligomers from neuronal synapses and improves cognitive function in animal models of AD. SHINE is an ongoing phase 2 randomized, double-blind, placebo-controlled clinical trial (COG0201) in participants with mild to moderate AD, designed to assess the safety and efficacy of 6 months of CT1812 treatment. To elucidate the mechanism of action in AD patients and pharmacodynamic biomarkers of CT1812, the present study reports exploratory cerebrospinal fluid (CSF) biomarker data from 18 participants in an interim analysis of the first set of patients in SHINE (part A). Untargeted mass spectrometry-based discovery proteomics detects >2000 proteins in patient CSF and has documented utility in accelerating the identification of novel AD biomarkers reflective of diverse pathophysiologies beyond amyloid and tau, and enabling identification of pharmacodynamic biomarkers in longitudinal interventional trials. We leveraged this technique to analyze CSF samples taken at baseline and after 6 months of CT1812 treatment. Proteome-wide protein levels were detected using tandem mass tag-mass spectrometry (TMT-MS), change from baseline was calculated for each participant, and differential abundance analysis by treatment group was performed. This analysis revealed a set of proteins significantly impacted by CT1812, including pathway engagement biomarkers (i.e., biomarkers tied to S2R biology) and disease modification biomarkers (i.e., biomarkers with altered levels in AD vs. healthy control CSF but normalized by CT1812, and biomarkers correlated with favorable trends in ADAS-Cog11 scores). Brain network mapping, Gene Ontology, and pathway analyses revealed an impact of CT1812 on synapses, lipoprotein and amyloid beta biology, and neuroinflammation. Collectively, the findings highlight the utility of this method in pharmacodynamic biomarker identification and providing mechanistic insights for CT1812, which may facilitate the clinical development of CT1812 and enable appropriate pre-specification of biomarkers in upcoming clinical trials of CT1812.