Salvianolic acid B ameliorates retinal deficits in an early-stage Alzheimer's disease mouse model through downregulating BACE1 and Aβ generation

Alzheimer's disease (AD) is a neurodegenerative disease with subtle onset, early diagnosis remains challenging. Accumulating evidence suggests that the emergence of retinal damage in AD precedes cognitive impairment, and may serve as a critical indicator for early diagnosis and disease progression. Salvianolic acid B (Sal B), a bioactive compound isolated from the traditional Chinese medicinal herb Salvia miltiorrhiza, has been shown promise in treating neurodegenerative diseases, such as AD and Parkinson's disease. In this study we investigated the therapeutic effects of Sal B on retinopathy in early-stage AD. One-month-old transgenic mice carrying five familial AD mutations (5×FAD) were treated with Sal B (20 mg·kg-1·d-1, i.g.) for 3 months. At the end of treatment, retinal function and structure were assessed, cognitive function was evaluated in Morris water maze test. We showed that 4-month-old 5×FAD mice displayed distinct structural and functional deficits in the retinas, which were significantly ameliorated by Sal B treatment. In contrast, untreated, 4-month-old 5×FAD mice did not exhibit cognitive impairment compared to wild-type mice. In SH-SY5Y-APP751 cells, we demonstrated that Sal B (10 μM) significantly decreased BACE1 expression and sorting into the Golgi apparatus, thereby reducing Aβ generation by inhibiting the β-cleavage of APP. Moreover, we found that Sal B effectively attenuated microglial activation and the associated inflammatory cytokine release induced by Aβ plaque deposition in the retinas of 5×FAD mice. Taken together, our results demonstrate that functional impairments in the retina occur before cognitive decline, suggesting that the retina is a valuable reference for early diagnosis of AD. Sal B ameliorates retinal deficits by regulating APP processing and Aβ generation in early AD, which is a potential therapeutic intervention for early AD treatment.

Lecanemab Clarity AD: Quality-of-Life Results from a Randomized, Double-Blind Phase 3 Trial in Early Alzheimer's Disease

BACKGROUND

Lecanemab is a humanized IgG1 monoclonal antibody binding with high affinity to amyloid-beta protein protofibrils. In phase 3 development, lecanemab has been shown to reduce markers of amyloid in early Alzheimer's disease and reduce decline on clinical endpoints of cognition and function at 18 months.

OBJECTIVES

To describe the health-related quality-of-life (HRQoL) results from Clarity AD which were exploratory outcomes in this trial.

DESIGN

Clarity AD was an 18-month, multi-center, double-blind, phase 3 trial.

SETTING

Early Alzheimer's disease.

PARTICIPANTS

Individuals 50-90 years of age with a diagnosis of mild cognitive impairment or mild dementia due to Alzheimer's disease and positron emission tomography or cerebrospinal fluid evidence of cerebral amyloid accumulation.

INTERVENTION

Placebo or lecanemab 10-mg/kg IV biweekly.

MEASUREMENTS

HRQoL was measured at baseline and every 6 months using the European Quality of Life-5 Dimensions (EQ-5D-5L; by subject) and Quality of Life in AD (QOL-AD; by subject and proxy). Study partner burden was measured using the Zarit Burden Interview (ZBI).

RESULTS

A total of 1795 participants were enrolled (lecanemab:898; placebo:897). At month 18, adjusted mean change from baseline in EQ-5D-5L and QOL-AD by subject showed 49% and 56% less decline, respectively. QOL-AD rated by study partner as proxy resulted in 23% less decline. ZBI adjusted mean change from baseline at 18 months resulted in 38% less increase of care partner burden. Individual HRQoL test items and dimensions also showed lecanemab benefit.

CONCLUSIONS

Lecanemab was associated with a relative preservation of HRQoL and less increase in caregiver burden, with consistent benefits seen across different quality of life scales and within scale subdomains. These benefits provide valuable patient reported outcomes which, together with previously reported benefits of lecanemab across multiple measures of cognition, function, disease progression, and biomarkers, demonstrate that lecanemab treatment may offer meaningful benefits to patients, care partners, and society.

BMNet: A New Region-Based Metric Learning Method for Early Alzheimer's Disease Identification With FDG-PET Images

18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) reveals altered brain metabolism in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Some biomarkers derived from FDG-PET by computer-aided-diagnosis (CAD) technologies have been proved that they can accurately diagnosis normal control (NC), MCI, and AD. However, existing FDG-PET-based researches are still insufficient for the identification of early MCI (EMCI) and late MCI (LMCI). Compared with methods based other modalities, current methods with FDG-PET are also inadequate in using the inter-region-based features for the diagnosis of early AD. Moreover, considering the variability in different individuals, some hard samples which are very similar with both two classes limit the classification performance. To tackle these problems, in this paper, we propose a novel bilinear pooling and metric learning network (BMNet), which can extract the inter-region representation features and distinguish hard samples by constructing the embedding space. To validate the proposed method, we collect 898 FDG-PET images from Alzheimer's disease neuroimaging initiative (ADNI) including 263 normal control (NC) patients, 290 EMCI patients, 147 LMCI patients, and 198 AD patients. Following the common preprocessing steps, 90 features are extracted from each FDG-PET image according to the automatic anatomical landmark (AAL) template and then sent into the proposed network. Extensive fivefold cross-validation experiments are performed for multiple two-class classifications. Experiments show that most metrics are improved after adding the bilinear pooling module and metric losses to the Baseline model respectively. Specifically, in the classification task between EMCI and LMCI, the specificity improves 6.38% after adding the triple metric loss, and the negative predictive value (NPV) improves 3.45% after using the bilinear pooling module. In addition, the accuracy of classification between EMCI and LMCI achieves 79.64% using imbalanced FDG-PET images, which illustrates that the proposed method yields a state-of-the-art result of the classification accuracy between EMCI and LMCI based on PET images.

Early Detection of Alzheimer's Disease Based on the Patient's Creative Drawing Process: First Results with a Novel Neuropsychological Testing Method

Based on the knowledge of art therapy, we developed a new neuropsychological drawing test in order to identify individuals with mild cognitive impairment (MCI) as well as dementia patients and healthy controls (HC). By observing a variety of drawing characteristics of 92 participants with a mean age of 67.7, art therapy and dementia experts discriminate HC from MCI, early dementia of the Alzheimer-type (eDAT), and moderate dementia of the Alzheimer-type (mDAT) by the process analysis of tree drawings on a digitizing tablet. The art therapist's average categorical rating of healthy and MCI or demented individuals matched the clinical diagnosis by 88%. In a first small study, we analyzed interrater reliability, sensitivity, specificity, negative and positive predicted values of our tree drawing test (TDT) in comparison with the clock drawing test (CDT). Similar values of moderate interrater reliability were found for the TDT (0.56) as well as for the CDT (0.54). A significant high sensitivity of 0.9 within this binary impairment scale (HC versus impaired or demented) can be demonstrated. Substantial values for the specificity (0.67) could be obtained that however remain under a perfect value of the CDT (1.0). Considering 31 individuals that received the clinical diagnosis "impaired or demented" the TDT shows a higher recognition rate for the MCI group than the CDT. Furthermore in 8 of 12 borderline cases of clinical diagnosis, the outcome of the TDT diagnosis was consistent with the final clinical result.

Diagnostic Value of a Tablet-Based Drawing Task for Discrimination of Patients in the Early Course of Alzheimer's Disease from Healthy Individuals

There is a considerable delay in the diagnosis of dementia, which may reduce the effectiveness of available treatments. Thus, it is of great interest to develop fast and easy to perform, non-invasive and non-expensive diagnostic measures for the early detection of cognitive impairment and dementia. Here we investigate movement kinematics between 20 patients with early dementia due to Alzheimer's disease (eDAT), 30 patients with amnestic mild cognitive impairment (aMCI), and 20 cognitively healthy control (HC) individuals while copying a three-dimensional house using a digitizing tablet. Receiver-operating characteristic (ROC) curves and logistic regression analyzes have been conducted to explore whether alterations in movement kinematics could be used to discriminate patients with aMCI and eDAT from healthy individuals. Time-in-air (i.e., transitioning from one stroke to the next without touching the surface) differed significantly between patients with aMCI, eDAT, and HCs demonstrating an excellent sensitivity and a moderate specificity to discriminate aMCI subjects from normal elderly and an excellent sensitivity and specificity to discriminate patients affected by mild Alzheimer's disease from healthy individuals. Time-on-surface (i.e., time while stylus is touching the surface) differed only between HCs and patients with eDAT but not between HCs and patients with aMCI. Furthermore, total-time (i.e., time-in-air plus time-on-surface) did not differ between patients with aMCI and early dementia due to AD. Modern digitizing devices offer the opportunity to measure a broad range of visuoconstructive abilities that may be used as a fast and easy to perform screening instrument for the early detection of cognitive impairment and dementia in primary care.

Hyperplanar Morphological Clustering of a Hippocampus by Using Volumetric Computerized Tomography in Early Alzheimer's Disease

Background: On diagnosing Alzheimer’s disease (AD), most existing imaging-based schemes have relied on analyzing the hippocampus and its peripheral structures. Recent studies have confirmed that volumetric variations are one of the primary indicators in differentiating symptomatic AD from healthy aging. In this study, we focused on deriving discriminative shape-based parameters that could effectively identify early AD from volumetric computerized tomography (VCT) delineation, which was previously almost intangible. Methods: Participants were 63 volunteers of Thai nationality, whose ages were between 40 and 90 years old. Thirty subjects (age 68.51 ± 5.5) were diagnosed with early AD, by using Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) criteria and the National Institute of Neurological and Communicative Disorders and the Stroke and the Alzheimer’s disease and Related Disorders Association (NINCDS-ADRDA) criteria, while the remaining 33 were in the healthy control group (age 67.93 ± 5.5). The structural imaging study was conducted by using VCT. Three uninformed readers were asked to draw left and right hippocampal outlines on a coronal section. The resultant shapes were aligned and then analyzed with statistical shape analysis to obtain the first few dominant variational parameters, residing in hyperplanes. A supervised machine learning, i.e., support vector machine (SVM) was then employed to elucidate the proposed scheme. Results: Provided trivial delineations, relatively as low as 5 to 7 implicit model parameters could be extracted and used as discriminants. Clinical verification showed that the model could differentiate early AD from aging, with high sensitivity, specificity, accuracy and F-measure of 0.970, 0.968, 0.983 and 0.983, respectively, with no apparent effect of left-right asymmetry. Thanks to a less laborious task required, yet high discriminating capability, the proposed scheme is expected to be applicable in a typical clinical setting, equipped with only a moderate-specs VCT.

Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer's disease patients from non-demented subjects

Alzheimer's disease (AD) is the most common age-related dementia. Among its major challenges is identifying molecular signatures characteristic for the early AD stage in patients with Mild Cognitive Impairment (MCI-AD), which could serve for deciphering the AD pathomechanism and also as non-invasive, easy-to-access biomarkers. Using qRT-PCR we compared the microRNA (miRNA) profiles in blood plasma of 15 MCI-AD patients, whose diagnoses were confirmed by cerebrospinal fluid (CSF) biomarkers, with 20 AD patients and 15 non-demented, age-matched individuals (CTR).To minimize methodological variability, we adhered to standardization of blood and CSF assays recommended by the international Joint Programming for Neurodegenerative Diseases (JPND) BIOMARKAPD consortium, and we employed commercially available Exiqon qRT-PCR-assays. In the first screening, we assessed 179 miRNAs of plasma. We confirmed 23 miRNAs reported earlier as AD biomarker candidates in blood and found 26 novel differential miRNAs between AD and control subjects. For representative 15 differential miRNAs, the TargetScan, MirTarBase and KEGG database analysis indicated putative protein targets among such AD hallmarks as MAPT (Tau), proteins involved in amyloidogenic proteolysis, and in apoptosis. These 15 miRNAs were verified in separate, subsequent subject groups. Finally, 6 miRNAs (3 not yet reported in AD context and 3 reported in AD blood) were selected as the most promising biomarker candidates differentiating early AD from controls with the highest fold changes (from 1.32 to 14.72), consistent significance, specificities from 0.78 to 1 and sensitivities from 0.75 to 1. (patent pending, PCT/IB2016/052440).

Increased Diagnostic Accuracy of Digital vs. Conventional Clock Drawing Test for Discrimination of Patients in the Early Course of Alzheimer's Disease from Cognitively Healthy Individuals

The conventional Clock Drawing Test (cCDT) is a rapid and inexpensive screening tool for detection of moderate and severe dementia. However, its usage is limited due to poor diagnostic accuracy especially in patients with mild cognitive impairment (MCI). The diagnostic value of a newly developed digital Clock Drawing Test (dCDT) was evaluated and compared with the cCDT in 20 patients with early dementia due to AD (eDAT), 30 patients with amnestic MCI (aMCI) and 20 cognitively healthy controls (HCs). Parameters assessed by dCDT were time while transitioning the stylus from one stroke to the next above the surface (i.e., time-in-air), time the stylus produced a visible stroke (i.e., time-on-surface) and total-time during clock drawing. Receiver-operating characteristic (ROC) curves were calculated and logistic regression analyses have been conducted for statistical analysis. Using dCDT, time-in-air was significantly increased in eDAT (70965.8 ms) compared to aMCI (54073.7 ms; p = 0.027) and HC (32315.6 ms; p < 0.001). In addition, time-in-air was significantly longer in patients with aMCI compared to HC (p = 0.003), even in the aMCI group with normal cCDT score (54141.8 ms; p < 0.001). Time-in-air using dCDT allowed discrimination of patients with aMCI from HCs with a sensitivity of 81.3% and a specificity of 72.2% while cCDT scoring revealed a sensitivity of 62.5% and a specificity of 83.3%. Most interestingly, time-in-air allowed even discrimination of aMCI patients with normal cCDT scores (80% from all aMCI patients) from HCs with a clinically relevant sensitivity of 80.8% and a specificity of 77.8%. A combination of dCDT variables and cCDT scores did not improve the discrimination of patients with aMCI from HC. In conclusion, assessment of time-in-air using dCDT yielded a higher diagnostic accuracy for discrimination of aMCI patients from HCs than the use of cCDT even in those aMCI patients with normal cCDT scores. Modern digitizing devices offer the opportunity to measure subtle changes of visuo-constructive demands and executive functions that may be used as a fast and easy to perform screening instrument for the early detection of cognitive impairment in primary care.