Alzheimer's Research & Therapy最新文献

Background: The potential diagnostic value of plasma amyloidogenic beta residue 42/40 ratio (Aβ42/Aβ40 ratio), neurofilament light (NfL), tau phosphorylated at threonine-181 (p-tau181), and threonine-217 (p-tau217) has been extensively discussed in the literature. We have also previously described the association between retinal biomarkers and preclinical Alzheimer's disease (AD). The goal of this study was to evaluate the association, and a multimodal model of, retinal and plasma biomarkers for detection of preclinical AD.

Methods: We included 82 cognitively unimpaired (CU) participants (141 eyes; mean age: 67 years; range: 56-80) from the Atlas of Retinal Imaging in Alzheimer's Study (ARIAS). Blood samples were assessed for concentrations of Aβ42/Aβ40 ratio, NfL, p-tau181, and p-tau217 (ALZpath, Inc.) using Single molecule array (SIMOA) technology. The Spectralis II system (Heidelberg Engineering) was used to acquire macular centered Spectral Domain Optical Coherence Tomography (SD-OCT) images for evaluation of putative retinal gliosis surface area and macular retinal nerve fiber layer (mRNFL) thickness. For all participants, correlations (adjusted for age and correlation between eyes) were assessed between retinal and blood-based biomarkers. A subgroup cohort of 57 eyes from 32 participants with recent Aβ positron emission tomography (PET) results, comprising 18 preclinical patients (Aβ PET + ve, 32 eyes) and 14 controls (Aβ PET -ve, 25 eyes) with a mean age of 69 vs. 66, p = 0.06, was included for the assessment of a multimodal model to distinguish between the two groups. For this subgroup cohort, receiver operating characteristic (ROC) analysis was performed to compare the multimodal model of retinal and plasma biomarkers vs. each biomarker alone to distinguish between the two groups.

Results: Significant correlation was found between putative retinal gliosis and p-tau217 in the univariate mixed model (β = 0.48, p = 0.007) but not for the other plasma biomarkers (p > 0.05). This positive correlation was also retained in the multivariate mixed model (β = 0.43, p = 0.022). The multimodal ROC model based on retinal (gliosis area, inner inferior RNFL thickness, inner superior RNFL thickness, and inner nasal RNFL thickness) and plasma biomarkers (p-tau217 and Aβ42/Aβ40 ratio) had an excellent AUC of 0.97 (95% CI = 0.93-1.01; p < 0.001) compared to unimodal models of retinal and plasma biomarkers.

Conclusions: Our analyses show the potential of integrating retinal and blood-based biomarkers for improved detection and screening of preclinical AD.

Background: Epidemiological and genetic studies have elucidated associations between antihypertensive medication and Alzheimer's disease (AD), with the directionality of these associations varying upon the specific class of antihypertensive agents.

Methods: Genetic instruments for the expression of antihypertensive drug target genes were identified using expression quantitative trait loci (eQTL) in blood, which are associated with systolic blood pressure (SBP). Exposure was derived from existing eQTL data in blood from the eQTLGen consortium and in the brain from the PsychENCODE and subsequently replicated in GTEx V8 and BrainMeta V2. We performed two-sample Mendelian randomization (MR) to estimate the potential effect of different antihypertensive drug classes on AD using summary statistics from a meta-analysis (111,326 cases and 677,663 controls) and further replicated in FinnGen cohorts (9301 cases and 367,976 controls). The reverse causality detection, assessing horizontal pleiotropy, Bayesian co-localization, phenotype scanning, and protein quantitative trait loci (pQTL) analysis were implemented to consolidate the MR findings further.

Results: A 1-standard deviation (SD) lower expression of the angiotensin-converting enzyme (ACE) gene in blood was associated with a lower SBP of 3.92 (95% confidence interval (CI), 2.69-5.15) mmHg but an increased risk of AD (odds ratio (OR), 2.46; 95% CI, 1.82-3.33). A similar direction of association was also observed between ACE expression in prefrontal cortex (OR, 1.19; 95% CI, 1.10-1.28), frontal cortex (OR, 1.19; 95% CI, 1.11-1.27), cerebellum (OR, 1.13; 95% CI, 1.09-1.17), cortex (OR, 1.59; 95% CI, 1.33-1.28) and ACE protein levels in plasma (OR, 1.13; 95% CI, 1.09-1.17) and AD risk. Colocalization supports these results. Similar results were found in external validation. We found no evidence for an association between genetically estimated blood pressure (BP) and AD risk.

Conclusions: There findings suggest an adverse association of lower ACE messenger RNA and protein levels with an elevated risk of AD, irrespective of its BP-lowering effects. These findings warrant greater pharmacovigilance and further investigation into the effect of ACE inhibitors, particularly those that are centrally acting, on neurodegenerative symptoms in patients with AD.

Background: Dementia patients commonly present multiple neuropathologies, worsening cognitive function, yet structural neuroimaging signatures of dementia have not been positioned in the context of combined pathology. In this study, we implemented an MRI voxel-based approach to explore combined and independent effects of dementia pathologies on grey and white matter structural changes.

Methods: In 91 amnestic dementia patients with post-mortem brain donation, grey matter density and white matter hyperintensity (WMH) burdens were obtained from pre-mortem MRI and analyzed in relation to Alzheimer's, vascular, Lewy body, TDP-43, and hippocampal sclerosis (HS) pathologies. After exploring co-occurrence profiles of these pathologies, voxel-based morphometry was implemented to determine their joint and independent effects on grey matter loss. The impact of these pathologies on WMH burden was then evaluated both in spatial and quantitative combined analyses, using voxel-based and generalized linear models respectively.

Results: 86.8% of patients in this cohort presented more than one pathology. The combined structural effect of these pathologies was a focal impact on hippocampal grey matter atrophy, primarily driven by HS and Alzheimer's pathology (family-wise error corrected, p < 0.05), which also exhibited the strongest individual effects (uncorrected, p < 0.001). WMHs, predominant in middle and anterior cerebral portions, were most strongly associated with vascular (T = 2.47, p = 0.017) and tau pathologies (T = 2.09, p = 0.041).

Conclusions: The mixed associations of these dementia neuroimaging hallmarks are relevant for the fine-tuning of diagnostic protocols and underscore the need for comprehensive pathology evaluations in the study of dementia phenotypes.

Background: Quantitative susceptibility mapping (QSM) can study the susceptibility values of brain tissue which allows for noninvasive examination of local brain iron levels in both normal and pathological conditions.

Purpose: Our study compares brain iron deposition in gray matter (GM) nuclei between cerebral small vessel disease (CSVD) patients and healthy controls (HCs), exploring factors that affect iron deposition and cognitive function.

Materials and methods: A total of 321 subjects were enrolled in this study. All subjects had cognitive examination including the Stroop color word test (SCWT) and MRI including multiecho gradient echo (mGRE) sequence. The patients with CSVD were divided into mild to moderate group (CSVD-M, total CSVD score ≤ 1) and severe group (CSVD-S, total CSVD score > 1). Morphology-enabled dipole inversion with an automated uniform cerebrospinal fluid zero reference algorithm (MEDI + 0) was used to generate brain QSM maps from mGRE data. Deep gray regional susceptibility values and cognitive function were compared among three groups (CSVD-S, CSVD-M, and HC) using multiple linear regression analysis and mediation effect analysis.

Results: There were significant differences in the SCWT scores and mean susceptibility values of the globus pallidus (GP), putamen (Put), and caudate nucleus (CN) among the three groups (P < 0.05, FDR correction). Age had a significant positive impact on the susceptibility values of GP (p = 0.018), Put (p < 0.001), and CN (p < 0.001). A history of diabetes had a significant positive influence on the susceptibility values of Put (p = 0.011) and CN (p < 0.001). A smoking history had a significant positive association with the susceptibility values of CN (p = 0.019). Mediation effect analysis demonstrated that iron deposition in the neostriatum partially mediated the relationship between hypertension and cognitive function. Age, diabetes, and smoking may increase iron deposition in the basal ganglia, associated with cognitive decline. The mean susceptibility values of the neostriatum played a mediating role in the association between hypertension and cognitive scores.

Conclusions: Age, diabetes, and smoking are associated with increased iron deposition in the basal ganglia and also linked to cognitive decline. This can help with understanding CSVD and its prevention and treatment.

Background: The safety data of lecanemab in the post-marketing period has yet to be fully investigated in the current literature. We aimed to identify and characterise the safety profile of lecanemab in the post-marketing period.

Methods: We searched and reviewed the reports submitted to the FDA's Adverse Event Reporting System (FAERS). We used a case/non-case approach to estimate the reporting odds ratio (ROR) and information component (IC) with 95% confidence intervals (CI) for lecanemab-related adverse events (AEs) reported at least four counts. We compared the difference between serious and non-serious reports using non-parametric tests.

Results: The FAERS recorded 1,986 lecanemab-related AEs affecting 868 patients. Two hundred and three patients experienced serious AEs, including 22 deaths. The most frequently reported AEs were headache (n = 193), chills (n = 100), fatigue (n = 93), and amyloid-related imaging abnormality-oedema/effusion (ARIA-E) (n = 91). Safety signals were detected, such as headache (ROR: 10.4, 95%CI: 8.97, 12.07; IC: 3.25, 95%CI: 2.97, 3.40), ARIA-E (ROR: 18,299.69, 95%CI: 14,001.27, 23,917.73; IC: 13.37, 95%CI: 6.15, 6.87), and infusion-related reaction (ROR: 35.25, 95CI 27.58, 45.07; IC: 5.09, 95CI 4.15, 4.87). We also identified several new AEs, such as migraine and pancreatic carcinoma. Patients with serious AEs were more likely to be on polypharmacy for Alzheimer's disease and use aspirin, acid-suppressing medications, statins, antidepressants, or benzodiazepines compared to those with non-serious AEs.

Conclusions: Lecanemab may have a significant potential for AEs. Our results provide evidence for healthcare professionals and patients to weigh the risks and benefits of lecanemab treatment. Further prospective studies are needed to explore rare and unexpected AEs.

Background: Disease-modifying therapies targeting the diverse pathophysiology of Alzheimer's disease (AD), including neuroinflammation, represent potentially important and novel approaches. The glucagon-like peptide-1 receptor agonist semaglutide is approved for the treatment of type 2 diabetes and obesity and has an established safety profile. Semaglutide may have a disease-modifying, neuroprotective effect in AD through multimodal mechanisms including neuroinflammatory, vascular, and other AD-related processes. Large randomized controlled trials are needed to assess the efficacy and safety of semaglutide in early-stage symptomatic AD.

Methods: evoke and evoke+ are randomized, double-blind, placebo-controlled phase 3 trials investigating the efficacy, safety, and tolerability of once-daily oral semaglutide versus placebo in early-stage symptomatic AD. Eligible participants were men or women aged 55-85 years with mild cognitive impairment or mild dementia due to AD with confirmed amyloid abnormalities (assessed by positron emission tomography or cerebrospinal fluid [CSF] analysis). After a maximum 12-week screening phase, an anticipated 1840 patients in each trial are randomized (1:1) to semaglutide or placebo for 156 weeks (104-week main treatment phase and 52-week extension). Randomized participants follow an 8-week dose escalation regimen (3 mg [weeks 0-4], 7 mg [weeks 4-8], and 14 mg [weeks 8-156]). The primary endpoint is the semaglutide-placebo difference on change from baseline to week 104 in the Clinical Dementia Rating - Sum of Boxes score. Analyses of plasma biomarkers, collected from all participants, and a CSF sub-study (planned n = 210) will explore semaglutide effects on AD biomarkers and neuroinflammation.

Results: Enrollment was undertaken between May 18, 2021, and September 8, 2023. Completion of the trials' main phase is expected in September 2025, and the 52-week extension (in which participants and investigators remain blinded to treatment assignment) will continue to October 2026.

Conclusion: evoke and evoke+ are the first large-scale trials to investigate the disease-modifying potential of semaglutide in participants with early-stage symptomatic AD, including exploration of effects on AD biomarkers and neuroinflammation. The trials will provide data on the potential disease-modifying effects of semaglutide and will be important in evaluating its utility in the treatment of early-stage symptomatic AD.

Trial registration: Clinicaltrials.gov, NCT04777396 and NCT04777409. Date: 02/03/2021.

Background: Alzheimer's disease (AD) is a complex neurodegenerative disorder with a largely unexplored epigenetic landscape.

Objective: This study employs an innovative approach that integrates multi-omics analysis and explainable machine learning to explore the epigenetic regulatory mechanisms underlying the epigenetic signature of PRRT1 implicated in AD.

Methods: Through comprehensive DNA methylation and transcriptomic profiling, we identified distinct epigenetic signatures associated with gene PRRT1 expression in AD patient samples compared to healthy controls. Utilizing interpretable machine learning models and ELMAR analysis, we dissected the complex relationships between these epigenetic signatures and gene expression patterns, revealing novel regulatory elements and pathways. Finally, the epigenetic mechanisms of these genes were investigated experimentally.

Results: This study identified ten epigenetic signatures, constructed an interpretable AD diagnostic model, and utilized various bioinformatics methods to create an epigenomic map. Subsequently, the ELMAR R package was used to integrate multi-omics data and identify the upstream transcription factor MAZ for PRRT1. Finally, experiments confirmed the interaction between MAZ and PRRT1, which mediated apoptosis and autophagy in AD.

Conclusion: This study adopts a strategy that integrates bioinformatics analysis with molecular experiments, providing new insights into the epigenetic regulatory mechanisms of PRRT1 in AD and demonstrating the importance of explainable machine learning in elucidating complex disease mechanisms.

Background: Evidence indicates that cognitive function is influenced by potential environmental factors. We aimed to determine the variables influencing cognitive function.

Methods: Our study included 164,463 non-demented adults (89,644 [54.51%] female; mean [SD] age, 56.69 [8.14] years) from the UK Biobank who completed four cognitive assessments at baseline. 364 variables were finally extracted for analysis through a rigorous screening process. We performed univariate analyses to identify variables significantly associated with each cognitive function in two equal-sized split discovery and replication datasets. Subsequently, the identified variables in univariate analyses were further assessed in a multivariable model. Additionally, for the variables identified in multivariable model, we explored the associations with longitudinal cognitive decline. Moreover, one- and two- sample Mendelian randomization (MR) analyses were conducted to confirm the genetic associations. Finally, the quality of the pooled evidence for the associations between variables and cognitive function was evaluated.

Results: 252 variables (69%) exhibited significant associations with at least one cognitive function in the discovery dataset. Of these, 231 (92%) were successfully replicated. Subsequently, our multivariable analyses identified 41 variables that were significantly associated with at least one cognitive function, spanning categories such as education, socioeconomic status, lifestyle factors, body measurements, mental health, medical conditions, early life factors, and household characteristics. Among these 41 variables, 12 were associated with more than one cognitive domain, and were further identified in all subgroup analyses. And LASSO, rigde, and principal component analysis indicated the robustness of the primary results. Moreover, among these 41 variables, 12 were significantly associated with a longitudinal cognitive decline. Furthermore, 22 were supported by one-sample MR analysis, and 5 were further confirmed by two-sample MR analysis. Additionally, the quality of the pooled evidence for the associations between 10 variables and cognitive function was rated as high. Based on these 10 identified variables, adopting a more favorable lifestyle was significantly associated with 38% and 34% decreased risks of dementia and Alzheimer's disease (AD).

Conclusion: Overall, our study constructed an evidence database of variables associated with cognitive function, which could contribute to the prevention of cognitive impairment and dementia.

We have previously demonstrated that the intracellular, non-GPI anchored CD59 isoforms IRIS-1 and IRIS-2 (Isoforms Rescuing Insulin Secretion 1 and 2) are necessary for insulin secretion from pancreatic β-cells. While investigating their expression across human tissues, we identified IRIS-1 and IRIS-2 mRNA in the human brain, though their protein expression and function remained unclear. This study shows the presence of both IRIS-1 and 2 proteins in the human brain, specifically in neurons and astrocytes. In the neuroblastoma cell line (SH-SY5Y), both isoforms are intracellular, and their expression increases upon differentiation into mature neurons. Silencing IRIS-1 and 2 in SH-SY5Y cells reduces the SNARE complex formation, essential for synaptic vesicle exocytosis, leading to a reduction in noradrenaline secretion. Notably, we observed diminished expression of neuronal IRIS-1 and 2 in patients with Alzheimer's disease (AD) and non-demented individuals with type 2 diabetes (T2D). In SH-SY5Y cells, knockdown of all isoforms of CD59 including IRIS-1 and 2 not only elevates phosphorylated tau but also increases cyclin-dependent kinase 5 (CDK5) expression, known promoter of hyperphosphorylation and accumulation of tau, a key pathological feature of AD. Additionally, we found that prolonged exposure to high glucose or cytokines markedly reduces the expression of IRIS-1 and 2 in SH-SY5Y cells, suggesting a link between AD pathology and metabolic stress through modulation of these isoforms.

Backgrounds: Digital, online assessments are efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subjective change measure, predicts longitudinal change in cognition in the Brain Health Registry (BHR), an online registry for neuroscience research.

Methods: This study included BHR participants aged 55 + who completed both the baseline ECog and repeated administrations of the CANTAB^® Paired Associates Learning (PAL) visual learning and memory test. Both self-reported ECog (Self-ECog) and study partner-reported ECog (SP-ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We estimated associations between multiple ECog scoring outputs (ECog positive [same or above cut-off score], ECog consistent [report of consistent decline in any item], and total score) and longitudinal change in PAL. Additionally we assessed the ability of ECog to identify 'decliners', who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below.

Results: Participants (n = 16,683) had an average age of 69.07 ± 7.34, 72.04% were female, and had an average of 16.66 ± 2.26 years of education. They were followed for an average of 2.52 ± 1.63 visits over a period of 11.49 ± 11.53 months. Both Self-ECog positive (estimate = -0.01, p < 0.001, R²m = 0.56) and Self-ECog consistent (estimate=-0.01, p = 0.002, R²m = 0.56) were associated with longitudinal change in PAL FAMS after adjusting demographics and clinical confounders. Those who were Self-ECog total (Odds ratio [95% confidence interval] = 1.390 [1.121-1.708]) and SP-ECog consistent (2.417 [1.591-3.655]) had higher probability of being decliners based on PAL FAMS.

Conclusion: In the BHR's unsupervised online setting, baseline subjective change was feasible in predicting longitudinal decline in neuropsychological tests. Online, self-administered measures of subjective cognitive change might have a potential to predict objective subjective change and identify individuals with cognitive impairments.