Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification

INTRODUCTION

Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells.

METHODS

Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models.

RESULTS

WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis.

DISCUSSION

This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies.

HIGHLIGHTS

We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.

The role of visual rating and automated brain volumetry in early detection and differential diagnosis of Alzheimer's disease

BACKGROUND

Medial temporal lobe atrophy (MTA) is a diagnostic marker for mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the accuracy of quantitative MTA (QMTA) in diagnosing early AD is unclear. This study aimed to investigate the accuracy of QMTA and its related components (inferior lateral ventricle [ILV] and hippocampus) with MTA in the early diagnosis of MCI and AD.

METHODS

This study included four groups: normal (NC), MCI stable (MCIs), MCI converted to AD (MCIs), and mild AD (M-AD) groups. Magnetic resonance image analysis software was used to quantify the hippocampus, ILV, and QMTA. MTA was rated by two experienced neurologists. Receiver operating characteristic area under the curve (AUC) analysis was performed to compare their capability in differentiating AD from NC and MCI, and optimal thresholds were determined using the Youden index.

RESULTS

QMTA distinguished M-AD from NC and MCI with higher diagnostic accuracy than MTA, hippocampus, and ILV (AUCNC = 0.976, AUCMCI = 0.836, AUCMCIs = 0.894, AUCMCIc = 0.730). The diagnostic accuracy of QMTA was superior to that of MTA, the hippocampus, and ILV in differentiating MCI from AD. The diagnostic accuracy of QMTA was found to remain the best across age, sex, and pathological subgroups analyzed. The sensitivity (92.45%) and specificity (90.64%) were higher in this study when a cutoff value of 0.635 was chosen for QMTA.

CONCLUSIONS

QMTA may be a better choice than the MTA scale or the associated quantitative components alone in identifying AD patients and MCI individuals with higher progression risk.

Case Report: Taxifolin for neurosurgery-associated early-onset cerebral amyloid angiopathy

Cases of iatrogenic cerebral amyloid angiopathy (CAA) have been increasingly reported recently, particularly those associated with neurosurgery. Preclinical studies have shown taxifolin to be promising for treating CAA. We describe a young 42-year-old man with a history of childhood traumatic brain injury that required a craniotomy for hematoma evacuation. He later presented with recurrent lobar intracerebral hemorrhage (ICH) decades later, which was histologically confirmed to be CAA. Serial 11C-Pittsburgh compound B positron emission tomography (11C-PiB-PET) imaging showed a 24% decrease in global standardized uptake value ratio (SUVR) at 10 months after taxifolin use. During this period, the patient experienced clinical improvement with improved consciousness and reduced recurrent ICH frequency, which may be partly attributable to the potential amyloid-β (Aβ) clearing the effect of taxifolin. However, this effect seemed to have diminished at 15 months, CAA should be considered in young patients presenting with recurrent lobar ICH with a history of childhood neurosurgery, and serial 11C-PiB-PET scans warrant further validation as a strategy for monitoring treatment response in CAA for candidate Aβ-clearing therapeutic agents such as taxifolin.

A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups

INTRODUCTION

Existing blood-based biomarkers for Alzheimer's disease (AD) mainly focus on its pathological features. However, studies on blood-based biomarkers associated with other biological processes for a comprehensive evaluation of AD status are limited.

METHODS

We developed a blood-based, multiplex biomarker assay for AD that measures the levels of 21 proteins involved in multiple biological pathways. We evaluated the assay's performance for classifying AD and indicating AD-related endophenotypes in three independent cohorts from Chinese or European-descent populations.

RESULTS

The 21-protein assay accurately classified AD (area under the receiver operating characteristic curve [AUC] = 0.9407 to 0.9867) and mild cognitive impairment (MCI; AUC = 0.8434 to 0.8945) while also indicating brain amyloid pathology. Moreover, the assay simultaneously evaluated the changes of five biological processes in individuals and revealed the ethnic-specific dysregulations of biological processes upon AD progression.

DISCUSSION

This study demonstrated the utility of a blood-based, multi-pathway biomarker assay for early screening and staging of AD, providing insights for patient stratification and precision medicine.

HIGHLIGHTS

The authors developed a blood-based biomarker assay for Alzheimer's disease. The 21-protein assay classifies AD/MCI and indicates brain amyloid pathology. The 21-protein assay can simultaneously assess activities of five biological processes. Ethnic-specific dysregulations of biological processes in AD were revealed.

High-resolution omics of vascular ageing and inflammatory pathways in neurodegeneration

High-resolution omics, particularly single-cell and spatial transcriptomic profiling, are rapidly enhancing our comprehension of the normal molecular diversity of gliovascular cells, as well as their age-related changes that contribute to neurodegeneration. With more omic profiling studies being conducted, it is becoming increasingly essential to synthesise valuable information from the rapidly accumulating findings. In this review, we present an overview of the molecular features of neurovascular and glial cells that have been recently discovered through omic profiling, with a focus on those that have potentially significant functional implications and/or show cross-species differences between human and mouse, and that are linked to vascular deficits and inflammatory pathways in ageing and neurodegenerative disorders. Additionally, we highlight the translational applications of omic profiling, and discuss omic-based strategies to accelerate biomarker discovery and facilitate disease course-modifying therapeutics development for neurodegenerative conditions.

Familial α-synucleinopathy spectrum features in patients with psychiatric REM sleep behaviour disorder

BACKGROUND

Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the earliest and most specific prodromes of the α-synucleinopathies including Parkinson's disease (PD). It remains uncertain whether RBD occurring in the context of psychiatric disorders (psy-RBD), although very common, is merely a benign epiphenomenon of antidepressant treatment, or whether it harbours an underlying α-synucleinopathy. We hypothesised that patients with psy-RBD demonstrate a familial predisposition to an α-synucleinopathy.

METHODS

In this case-control-family study, a combination of family history and family study method was used to measure the α-synucleinopathy spectrum features, which included RBD, neurodegenerative prodromal markers and clinical diagnoses of neurodegenerative disorders. We compared the risk of α-synucleinopathy spectrum features in the first-degree relatives (FDRs) of patients with psy-RBD, psychiatric controls and healthy controls.

RESULTS

There was an increase of α-synucleinopathy spectrum features in the psy-RBD-FDRs, including possible and provisional RBD (adjusted HR (aHR)=2.02 and 6.05, respectively), definite RBD (adjusted OR=11.53) and REM-related phasic electromyographic activities, prodromal markers including depression (aHR=4.74) and probable subtle parkinsonism, risk of prodromal PD and clinical diagnosis of PD/dementia (aHR=5.50), as compared with healthy-control-FDRs. When compared with psychiatric-control-FDRs, psy-RBD-FDRs consistently presented with a higher risk for the diagnosis and electromyographic features of RBD, diagnosis of PD/dementia (aHR=3.91) and risk of prodromal PD. In contrast, psychiatric controls only presented with a familial aggregation of depression.

CONCLUSION

Patients with psy-RBD are familially predisposed to α-synucleinopathy. The occurrence of RBD with major depression may signify a subtype of major depressive disorders with underlying α-synucleinopathy neurodegeneration.

TRIAL REGISTRATION NUMBER

NCT03595475.

Neuroimaging standards for research into small vessel disease-advances since 2013

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

Impact of Cerebral Microbleeds in Stroke Patients with Atrial Fibrillation

OBJECTIVES

Cerebral microbleeds are associated with the risks of ischemic stroke and intracranial hemorrhage, causing clinical dilemmas for antithrombotic treatment decisions. We aimed to evaluate the risks of intracranial hemorrhage and ischemic stroke associated with microbleeds in patients with atrial fibrillation treated with vitamin K antagonists, direct oral anticoagulants, antiplatelets, and combination therapy (i.e. concurrent oral anticoagulant and antiplatelet).

METHODS

We included patients with documented atrial fibrillation from the pooled individual patient data analysis by the Microbleeds International Collaborative Network. Risks of subsequent intracranial hemorrhage and ischemic stroke were compared between patients with and without microbleeds, stratified by antithrombotic use.

RESULTS

A total of 7,839 patients were included. The presence of microbleeds was associated with an increased relative risk of intracranial hemorrhage (adjusted hazard ratio [aHR] = 2.74, 95% confidence interval = 1.76-4.26) and ischemic stroke (aHR = 1.29, 95% confidence interval = 1.04-1.59). For the entire cohort, the absolute incidence of ischemic stroke was higher than intracranial hemorrhage regardless of microbleed burden. However, for the subgroup of patients taking combination of anticoagulant and antiplatelet therapy, the absolute risk of intracranial hemorrhage exceeded that of ischemic stroke in those with 2 to 4 microbleeds (25 vs 12 per 1,000 patient-years) and ≥ 11 microbleeds (94 vs 48 per 1,000 patient-years).

INTERPRETATION

Patients with atrial fibrillation and high burden of microbleeds receiving combination therapy have a tendency of higher rate of intracranial hemorrhage than ischemic stroke, with potential for net harm. Further studies are needed to help optimize stroke preventive strategies in this high-risk group. ANN NEUROL 2023;94:61-74.

Gut microbiome dysbiosis across early Parkinson's disease, REM sleep behavior disorder and their first-degree relatives

The microbiota-gut-brain axis has been suggested to play an important role in Parkinson's disease (PD). Here we performed a cross-sectional study to profile gut microbiota across early PD, REM sleep behavior disorder (RBD), first-degree relatives of RBD (RBD-FDR), and healthy controls, which could reflect the gut-brain staging model of PD. We show gut microbiota compositions are significantly altered in early PD and RBD compared with control and RBD-FDR. Depletion of butyrate-producing bacteria and enrichment of pro-inflammatory Collinsella have already emerged in RBD and RBD-FDR after controlling potential confounders including antidepressants, osmotic laxatives, and bowel movement frequency. Random forest modelling identifies 12 microbial markers that are effective to distinguish RBD from control. These findings suggest that PD-like gut dysbiosis occurs at the prodromal stages of PD when RBD develops and starts to emerge in the younger RBD-FDR subjects. The study will have etiological and diagnostic implications.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction

BACKGROUND

The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk.

METHODS

We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model.

RESULTS

The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms.

CONCLUSION

Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Efficacy and safety of cilostazol in decreasing progression of cerebral white matter hyperintensities-A randomized controlled trial

Introduction

Cerebral small vessel disease (SVD) is an important cause of dementia that lacks effective treatment. We evaluated the efficacy and safety of cilostazol, an antiplatelet agent with potential neurovascular protective effects, in slowing the progression of white matter hyperintensities (WMHs) in stroke- and dementia-free subjects harboring confluent WMH on magnetic resonance imaging (MRI).

Methods

In this single-center, randomized, double-blind, placebo-controlled study, we randomized stroke- and dementia-free subjects with confluent WMHs to receive cilostazol or placebo for 2 years in a 1:1 ratio. The primary outcome was change in WMH volume over 2 years. Secondary outcomes were changes in brain volumes, lacunes, cerebral microbleeds, perivascular space, and alterations in white matter microstructural integrity, cognition, motor function, and mood.

Results

We recruited 120 subjects from October 27, 2014, to January 21, 2019. A total of 55 subjects in the cilostazol group and 54 subjects in the control group were included for intention-to-treat analysis. At 2-year follow-up, the changes in WMH volume were not statistically different between cilostazol treatment and placebo (0.3±1.0 mL vs -0.1±0.8 mL, p = 0.167). Secondary outcomes, bleeding and vascular events, were also not statistically different between the two groups.

Discussion

In this trial with stroke- and dementia-free subjects with confluent WMHs, cilostazol did not impact WMH progression but demonstrated an acceptable safety profile. Future studies should address the treatment effects of cilostazol on subjects at different clinical stages of SVD.

A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study

BACKGROUND

There is no simple model to screen for Alzheimer's disease, partly because the diagnosis of Alzheimer's disease itself is complex-typically involving expensive and sometimes invasive tests not commonly available outside highly specialised clinical settings. We aimed to develop a deep learning algorithm that could use retinal photographs alone, which is the most common method of non-invasive imaging the retina to detect Alzheimer's disease-dementia.

METHODS

In this retrospective, multicentre case-control study, we trained, validated, and tested a deep learning algorithm to detect Alzheimer's disease-dementia from retinal photographs using retrospectively collected data from 11 studies that recruited patients with Alzheimer's disease-dementia and people without disease from different countries. Our main aim was to develop a bilateral model to detect Alzheimer's disease-dementia from retinal photographs alone. We designed and internally validated the bilateral deep learning model using retinal photographs from six studies. We used the EfficientNet-b2 network as the backbone of the model to extract features from the images. Integrated features from four retinal photographs (optic nerve head-centred and macula-centred fields from both eyes) for each individual were used to develop supervised deep learning models and equip the network with unsupervised domain adaptation technique, to address dataset discrepancy between the different studies. We tested the trained model using five other studies, three of which used PET as a biomarker of significant amyloid β burden (testing the deep learning model between amyloid β positive vs amyloid β negative).

FINDINGS

12 949 retinal photographs from 648 patients with Alzheimer's disease and 3240 people without the disease were used to train, validate, and test the deep learning model. In the internal validation dataset, the deep learning model had 83·6% (SD 2·5) accuracy, 93·2% (SD 2·2) sensitivity, 82·0% (SD 3·1) specificity, and an area under the receiver operating characteristic curve (AUROC) of 0·93 (0·01) for detecting Alzheimer's disease-dementia. In the testing datasets, the bilateral deep learning model had accuracies ranging from 79·6% (SD 15·5) to 92·1% (11·4) and AUROCs ranging from 0·73 (SD 0·24) to 0·91 (0·10). In the datasets with data on PET, the model was able to differentiate between participants who were amyloid β positive and those who were amyloid β negative: accuracies ranged from 80·6 (SD 13·4%) to 89·3 (13·7%) and AUROC ranged from 0·68 (SD 0·24) to 0·86 (0·16). In subgroup analyses, the discriminative performance of the model was improved in patients with eye disease (accuracy 89·6% [SD 12·5%]) versus those without eye disease (71·7% [11·6%]) and patients with diabetes (81·9% [SD 20·3%]) versus those without the disease (72·4% [11·7%]).

INTERPRETATION

A retinal photograph-based deep learning algorithm can detect Alzheimer's disease with good accuracy, showing its potential for screening Alzheimer's disease in a community setting.

FUNDING

BrightFocus Foundation.

The Hong Kong Grocery Shopping Dialog Task (HK-GSDT): A Quick Screening Test for Neurocognitive Disorders

The Hong Kong Grocery Shopping Dialog Task (HK-GSDT) is a short and easy-to-administer cognitive test developed for quickly screening neurocognitive disorders (NCDs). In the test, participants are instructed to do a hypothetical instrumental activity of daily living task of purchasing ingredients for a dish from a grocery store and verbally describe the specific shopping procedures. The current study aimed to validate the test with a sample of 545 Hong Kong older adults (58.8% female; aged 73.4 ± 8.37 years), including 464 adults with normal cognitive function, 39 with mild NCD, and 42 with major NCD. Demographic characteristics (i.e., sex, age, education) and clinical diagnosis of cognitive states (i.e., major NCD, mild NCD, and normal aging) were collected. Cognitive functioning was measured using the HK-GSDT and several standardized NCD-screening tests. The results showed good reliability (i.e., internal consistency) and structural validity in the HK-GSDT. It discriminated among different cognitive conditions, particularly between major NCDs and the other conditions, as effectively as did the existing standardized neurocognitive tests (e.g., Montreal Cognitive Assessment, Hong Kong List Learning Test). Moreover, the HK-GSDT explained additional variance of cognitive condition on top of those standardized neurocognitive tests. These results indicate that the HK-GSDT can be used alone, or in combination with other tests, to screen for NCDs.

Antibody stabilization for thermally accelerated deep immunostaining

Antibodies have diverse applications due to their high reaction specificities but are sensitive to denaturation when a higher working temperature is required. We have developed a simple, highly scalable and generalizable chemical approach for stabilizing off-the-shelf antibodies against thermal and chemical denaturation. We demonstrate that the stabilized antibodies (termed SPEARs) can withstand up to 4 weeks of continuous heating at 55 °C and harsh denaturants, and apply our method to 33 tested antibodies. SPEARs enable flexible applications of thermocycling and denaturants to dynamically modulate their binding kinetics, reaction equilibrium, macromolecular diffusivity and aggregation propensity. In particular, we show that SPEARs permit the use of a thermally facilitated three-dimensional immunolabeling strategy (termed ThICK staining), achieving whole mouse brain immunolabeling within 72 h, as well as nearly fourfold deeper penetration with threefold less antibodies in human brain tissue. With faster deep-tissue immunolabeling and broad compatibility with tissue processing and clearing methods without the need for any specialized equipment, we anticipate the wide applicability of ThICK staining with SPEARs for deep immunostaining.

Thermostable antibodies called SPEARs enable rapid immunostaining with improved tissue penetration.

Validation of the Alzheimer's disease-resemblance atrophy index in classifying and predicting progression in Alzheimer's disease

Background

Automated tools for characterising dementia risk have the potential to aid in the diagnosis, prognosis, and treatment of Alzheimer's disease (AD). Here, we examined a novel machine learning-based brain atrophy marker, the AD-resemblance atrophy index (AD-RAI), to assess its test-retest reliability and further validate its use in disease classification and prediction.

Methods

Age- and sex-matched 44 probable AD (Age: 69.13 ± 7.13; MMSE: 27-30) and 22 non-demented control (Age: 69.38 ± 7.21; MMSE: 27-30) participants were obtained from the Minimal Interval Resonance Imaging in Alzheimer's Disease (MIRIAD) dataset. Serial T1-weighted images (n = 678) from up to nine time points over a 2-year period, including 179 pairs of back-to-back scans acquired on same participants on the same day and 40 pairs of scans acquired at 2-week intervals were included. All images were automatically processed with AccuBrain® to calculate the AD-RAI. Its same-day repeatability and 2-week reproducibility were first assessed. The discriminative performance of AD-RAI was evaluated using the receiver operating characteristic curve, where DeLong's test was used to evaluate its performance against quantitative medial temporal lobe atrophy (QMTA) and hippocampal volume adjusted by intracranial volume (ICV)-proportions and ICV-residuals methods, respectively (HVR and HRV). Linear mixed-effects modelling was used to investigate longitudinal trajectories of AD-RAI and baseline AD-RAI prediction of cognitive decline. Finally, the longitudinal associations between AD-RAI and MMSE scores were assessed.

Results

AD-RAI had excellent same-day repeatability and excellent 2-week reproducibility. AD-RAI's AUC (99.8%; 95%CI = [99.3%, 100%]) was equivalent to that of QMTA (96.8%; 95%CI = [92.9%, 100%]), and better than that of HVR (86.8%; 95%CI = [78.2%, 95.4%]) or HRV (90.3%; 95%CI = [83.0%, 97.6%]). While baseline AD-RAI was significantly higher in the AD group, it did not show detectable changes over 2 years. Baseline AD-RAI was negatively associated with MMSE scores and the rate of the change in MMSE scores over time. A negative longitudinal association was also found between AD-RAI values and the MMSE scores among AD patients.

Conclusions

The AD-RAI represents a potential biomarker that may support AD diagnosis and be used to predict the rate of future cognitive decline in AD patients.

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

High Fall Risk Associated With Memory Deficit and Brain Lobes Atrophy Among Elderly With Amnestic Mild Cognitive Impairment and Mild Alzheimer's Disease

Objectives

This study aimed to primarily examine the association between memory deficit and increased fall risk, second, explore the underlying neuroanatomical linkage of this association in the elderly with aMCI and mild AD.

Methods

In this cross-sectional study, a total of 103 older adults were included (55 cognitively normal, CN; 48 cognitive impairment, CI, elderly with aMCI, and mild AD). Memory was assessed by the Auditory Verbal Learning Test (AVLT). Fall risk was evaluated by the Timed Up and Go (TUG) Test, heel strike angles, and stride speed, which were collected by an inertial-sensor-based wearable instrument (the JiBuEn™ gait analysis system). Brain volumes were full-automatic segmented and quantified using AccuBrain^® v1.2 from three-dimensional T1-weighted (3D T1W) MR images. Multivariable regression analysis was used to examine the extent of the association between memory deficit and fall risk, the association of brain volumes with memory, and fall risk. Age, sex, education, BMI, and HAMD scores were adjusted. Sensitivity analysis was conducted.

Results

Compared to CN, participants with aMCI and mild AD had poorer cognitive performance (p < 0.001), longer TUG time (p = 0.018), and smaller hippocampus and medial temporal volumes (p = 0.037 and 0.029). In the CI group, compared to good short delayed memory (SDM) performance (AVLT > 5), the elderly with bad SDM performance (AVLT ≤ 3) had longer TUG time, smaller heel strike angles, and slower stride speed. Multivariable regression analysis showed that elderly with poor memory had higher fall risk than relative good memory performance among cognitive impairment elderly. The TUG time increased by 2.1 s, 95% CI, 0.54∼3.67; left heel strike angle reduced by 3.22°, 95% CI, −6.05 to −0.39; and stride speed reduced by 0.09 m/s, 95% CI, −0.19 to −0.00 for the poor memory elderly among the CI group, but not found the association in CN group. In addition, serious medial temporal atrophy (MTA), small volumes of the frontal lobe and occipital lobe were associated with long TUG time and small heel strike angles; small volumes of the temporal lobe, frontal lobe, and parietal lobe were associated with slow stride speed.

Conclusion

Our findings suggested that memory deficit was associated with increased fall risk in the elderly with aMCI and mild AD. The association might be mediated by the atrophy of medial temporal, frontal, and parietal lobes. Additionally, increased fall risk, tested by TUG time, heel stride angles, and stride speed, might be objective and convenient kinematics markers for dynamic monitoring of both memory function and fall risk.

The Correlation Between White Matter Hyperintensity Burden and Regional Brain Volumetry in Patients With Alzheimer's Disease

Background

White matter hyperintensities (WMHs) and regional brain lobe atrophy coexist in the brain of patients with Alzheimer's disease (AD), but the association between them in patients with AD still lacks comprehensive investigation and solid imaging data support.

Objective

We explored whether WMHs can promote the pathological process of AD by aggravating atrophy in specific brain regions and tried to explain the regional specificity of these relationships.

Methods

A sample of 240 adults including 180 normal controls (NCs) and 80 cases with AD were drawn from the ADNI database. T1-weighted magnetic resonance imaging (MRI) and T2-weighted fluid-attenuated MRI of the participants were downloaded and were analyzed using AccuBrain^® to generate the quantitative ratio of WMHs (WMHr, WMH volumes corrected by intracranial volume) and regional brain atrophy. We also divided WMHr into periventricular WMHr (PVWMHr) and deep WMHr (DWMHr) for the purpose of this study. The Cholinergic Pathways Hyperintensities Scale (CHIPS) scores were conducted by two evaluators. Independent t-test, Mann–Whitney U test, or χ² test were used to compare the demographic characteristics, and Spearman correlation coefficient values were used to determine the association between WMHs and different regions of brain atrophy.

Results

Positive association between WMHr and quantitative medial temporal lobe atrophy (QMTA) (r_s = 0.281, p = 0.011), temporal lobe atrophy (r_s = 0.285, p = 0.011), and insular atrophy (r_s = 0.406, p < 0.001) was found in the AD group before Bonferroni correction. PVWMHr contributed to these correlations. By separately analyzing the relationship between PVWMHr and brain atrophy, we found that there were still positive correlations after correction in QMTA (r_s = 0.325, p = 0.003), temporal lobe atrophy (r_s = 0.298, p = 0.007), and insular atrophy (r_s = 0.429, p < 0.001) in AD group.

Conclusion

WMH severity tends to be associated with regional brain atrophy in patients with AD, especially with medial temporal lobe, temporal lobe, and insular lobe atrophy. PVWMHs were devoted to these correlations.

Restoration of Autophagic Flux Improves Endothelial Function in Diabetes Through Lowering Mitochondrial ROS-Mediated eNOS Monomerization

Endothelial nitric oxide synthase (eNOS) monomerization and uncoupling play crucial roles in mediating vascular dysfunction in diabetes, although the underlying mechanisms are still incompletely understood. Increasing evidence indicates that autophagic dysregulation is involved in the pathogenesis of diabetic endothelial dysfunction; however, whether autophagy regulates eNOS activity through controlling eNOS monomerization or dimerization remains elusive. In this study, autophagic flux was impaired in the endothelium of diabetic db/db mice and in human endothelial cells exposed to advanced glycation end products or oxidized low-density lipoprotein. Inhibition of autophagic flux by chloroquine or bafilomycin A1 were sufficient to induce eNOS monomerization and lower nitric oxide bioavailability by increasing mitochondrial reactive oxygen species (mtROS). Restoration of autophagic flux by overexpressing transcription factor EB (TFEB), a master regulator of autophagy and lysosomal biogenesis, decreased endothelial cell oxidative stress, increased eNOS dimerization, and improved endothelium-dependent relaxations (EDRs) in db/db mouse aortas. Inhibition of mammalian target of rapamycin kinase (mTOR) increased TFEB nuclear localization, reduced mtROS accumulation, facilitated eNOS dimerization, and enhanced EDR in db/db mice. Moreover, calorie restriction also increased TFEB expression, improved autophagic flux, and restored EDR in the aortas of db/db mice. Taken together, the findings of this study reveal that mtROS-induced eNOS monomerization is closely associated with the impaired TFEB-autophagic flux axis leading to endothelial dysfunction in diabetic mice.

AD Resemblance Atrophy Index of Brain Magnetic Resonance Imaging in Predicting the Progression of Mild Cognitive Impairment Carrying Apolipoprotein E-ε4 Allele

Background and Objective

Early identification is important for timely Alzheimer’s disease (AD) treatment. Apolipoprotein E ε4 allele (APOE-ε4) is an important genetic risk factor for sporadic AD. The AD-Resemblance Atrophy Index (RAI)—a structural magnetic resonance imaging-derived composite index—was found to predict the risk of progression from mild cognitive impairment (MCI) to AD. Therefore, we investigated whether the AD-RAI can predict cognitive decline and progression to AD in patients with MCI carrying APOE ε4.

Methods

We included 733 participants with MCI from the Alzheimer’s Disease Neuroimaging Initiative Database (ADNI). Their APOE genotypes, cognitive performance, and levels of AD-RAI were assessed at baseline and follow-up. Linear regression models were used to test the correlations between the AD-RAI and baseline cognitive measures, and linear mixed models with random intercepts and slopes were applied to investigate whether AD-RAI and APOE-ε4 can predict the level of cognitive decline. Cox proportional risk regression models were used to test the association of AD-RAI and APOE status with the progression from MCI to AD.

Results

The baseline AD-RAI was higher in the MCI converted to AD group than in the MCI stable group (P < 0.001). The AD-RAI was significantly correlated with cognition, and had a synergistic effect with APOE-ε4 to predict the rate of cognitive decline. The AD-RAI predicted the risk and timing of MCI progression to AD. Based on the MCI population carrying APOE-ε4, the median time to progression from MCI to AD was 24 months if the AD-RAI > 0.5, while the median time to progression from MCI to AD was 96 months for patients with an AD-RAI ≤ 0.5.

Conclusion

The AD-RAI can predict the risk of progression to AD in people with MCI carrying APOE ε4, is strongly correlated with cognition, and can predict cognitive decline.

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke

BACKGROUND

Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction.

AIMS

To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline.

METHODS

We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI < 3 months post-stroke to no PSCI at follow-up, and cognitive decline as conversion from no PSCI to PSCI. The network impact score was related to serial measures of PSCI using Generalized Estimating Equations (GEE) models, and to PSCI stratified according to post-stroke interval (<3, 3-12, 12-24, >24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site.

RESULTS

We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) <3 months, 709/1640 (43%) at 3-12 months, 243/853 (28%) at 12-24 months, and 208/522 (40%) >24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline.

CONCLUSIONS

The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/.

Cost-Effectiveness of Monitoring Patients Post-Stroke With Mobile ECG During the Hospital Stay

Background

The effectiveness of a nurse‐led in‐hospital monitoring protocol with mobile ECG (iECG) was investigated for detecting atrial fibrillation in patients post‐ischemic stroke or post‐transient ischemic attack. The study aimed to assess the cost‐effectiveness of using iECG during the initial hospital stay compared with standard 24‐hour Holter monitoring.

Methods and Results

A Markov microsimulation model was constructed to simulate the lifetime health outcomes and costs. The rate of atrial fibrillation detection in iECG and Holter monitoring during the in‐hospital phase and characteristics of modeled population (ie, age, sex, CHA2DS2‐VASc) were informed by patient‐level data. Costs related to recurrent stroke, stroke management, medications (new oral anticoagulants), and rehabilitation were included. The cost‐effectiveness analysis outcome was calculated as an incremental cost per quality‐adjusted life‐year gained. As results, monitoring patients with iECG post‐stroke during the index hospitalization was associated with marginally higher costs (A$31 196) and greater benefits (6.70 quality‐adjusted life‐years) compared with 24‐hour Holter surveillance (A$31 095 and 6.66 quality‐adjusted life‐years) over a 20‐year time horizon, with an incremental cost‐effectiveness ratio of $3013/ quality‐adjusted life‐years. Monitoring patients with iECG also contributed to lower recurrence of stroke and stroke‐related deaths (140 recurrent strokes and 20 deaths avoided per 10 000 patients). The probabilistic sensitivity analyses suggested iECG is highly likely to be a cost‐effective intervention (100% probability).

Conclusions

A nurse‐led iECG monitoring protocol during the acute hospital stay was found to improve the rate of atrial fibrillation detection and contributed to slightly increased costs and improved health outcomes. Using iECG to monitor patients post‐stroke during initial hospitalization is recommended to complement routine care.

Evaluation of oropharyngeal deglutitive pressure dynamics in patients with Parkinson's disease

In Parkinson's disease (PD), oropharyngeal dysphagia is common and clinically relevant. The neurophysiology of dysphagia in PD is complex and incompletely understood. The aim of the study was to determine the changes in oropharyngeal deglutitive pressure dynamics in PD and to correlate these with clinical characteristics including dysphagia and PD severity. In prospective consecutive series of 64 patients with PD [mean age: 66.9 ± 8.3 (SD)], we evaluated dysphagia severity clinically as well as with Sydney Swallow Questionnaire (SSQ) and Swallow Quality-of-Life Questionnaire (SWAL-QOL). PD severity was assessed with Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). We used high-resolution pharyngeal impedance manometry (HRPIM) to objectively evaluate swallow function and compared data from 23 age-matched healthy controls [mean age 62.3 ± 9.1 (SD)]. Metrics assessed were upper esophageal sphincter (UES), integrated relaxation pressure (IRP), relaxation time (RT), maximum opening (MaxAdm), and pharyngeal intrabolus pressure (IBP) and pharyngeal contractility (PhCI). Mean MDS-UPDRS score was positively associated with dysphagia severity on SSQ and SWAL-QOL. HRPIM in PD compared with controls showed impaired UES relaxation parameters, with shorter RT, and elevated IRP and IBP. MaxAdm was not affected. The overall pharyngeal contractility was significantly higher in PD. Only the IBP and IRP were associated with PD severity and only IBP was significantly associated with dysphagia severity. UES dysfunction leading to increased flow resistance is common in patients with PD and correlates with dysphagia severity. Increased flow resistance may suggest impaired UES relaxation and/or impaired neuromodulation to bolus volume.NEW & NOTEWORTHY In Parkinson's disease, objective assessment of swallow function with high-resolution impedance manometry identifies upper esophageal sphincter dysfunction leading to increased flow resistance.

Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

IMPORTANCE

One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.

OBJECTIVE

To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.

EXPOSURES

Alzheimer disease biomarkers detected on PET or in CSF.

MAIN OUTCOMES AND MEASURES

Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.

RESULTS

Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).

CONCLUSIONS AND RELEVANCE

This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Effects of functional task exercise on everyday problem-solving ability and functional status in older adults with mild cognitive impairment-a randomised controlled trial

OBJECTIVE

To investigate the effect of functional task exercise on everyday problem-solving ability and functional status in older adults with mild cognitive impairment compared to single exercise or cognitive training and no treatment control.

DESIGN

A single-blind, four-arm randomised controlled trial.

SETTING

Out-patient clinic and community centre.

PARTICIPANTS

Older adults with mild cognitive impairment aged ≥60 living in community.

METHODS

Participants (N = 145) were randomised to 8-week functional task exercise (N = 34), cognitive training (N = 38), exercise training (N = 37), or wait-list control (N = 36) group. Outcomes measures: Neurobehavioral Cognitive Status Examination, Category Verbal Fluency Test, Trail Making Test, Problems in Everyday Living Test, Activities of Daily Living Questionnaire, Instrumental Activities of Daily Living Scale; Chair stand test, Berg Balance Scale, and Short Form-12 Health Survey were conducted at baseline, post-intervention and 5-months follow-up.

RESULTS

Post-intervention results of ANCOVA revealed cognitive training improved everyday problem-solving (P = 0.012) and exercise training improved functional status (P = 0.003) compared to wait-list control. Functional task exercise group demonstrated highest improvement compared to cognitive training, exercise training and wait-list control groups in executive function (P range = 0.003-0.018); everyday problem-solving (P < 0.001); functional status (P range = <.001-0.002); and physical performance (P = 0.008) at post-intervention, with all remained significant at 5-month follow-up, and further significant improvement in mental well-being (P = 0.043).

CONCLUSIONS

Functional task exercise could be an effective intervention to improve everyday problem-solving ability and functional status in older adults with mild cognitive impairment. The findings support combining cognitive and exercise intervention may give additive and even synergistic effects.

Systemic GLP-1R agonist treatment reverses mouse glial and neurovascular cell transcriptomic aging signatures in a genome-wide manner

Pharmacological reversal of brain aging is a long-sought yet challenging strategy for the prevention and treatment of age-related neurodegeneration, due to the diverse cell types and complex cellular pathways impacted by the aging process. Here, we report the genome-wide reversal of transcriptomic aging signatures in multiple major brain cell types, including glial and mural cells, by systemic glucagon-like peptide-1 receptor (GLP-1R) agonist (GLP-1RA) treatment. The age-related expression changes reversed by GLP-1RA encompass both shared and cell type-specific functional pathways that are implicated in aging and neurodegeneration. Concomitantly, Alzheimer's disease (AD)-associated transcriptomic signature in microglia that arises from aging is reduced. These results show the feasibility of reversing brain aging by pharmacological means, provide mechanistic insights into the neurological benefits of GLP-1RAs, and imply that GLP-1R agonism may be a generally applicable pharmacological intervention for patients at risk of age-related neurodegeneration.

Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts

BACKGROUND

Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model.

METHODS

In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa.

FINDINGS

In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high.

INTERPRETATION

To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI.

FUNDING

The Netherlands Organisation for Health Research and Development.

Simeprevir Potently Suppresses SARS-CoV-2 Replication and Synergizes with Remdesivir

The outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global threat to human health. Using a multidisciplinary approach, we identified and validated the hepatitis C virus (HCV) protease inhibitor simeprevir as an especially promising repurposable drug for treating COVID-19. Simeprevir potently reduces SARS-CoV-2 viral load by multiple orders of magnitude and synergizes with remdesivir in vitro. Mechanistically, we showed that simeprevir not only inhibits the main protease (Mpro) and unexpectedly the RNA-dependent RNA polymerase (RdRp) but also modulates host immune responses. Our results thus reveal the possible anti-SARS-CoV-2 mechanism of simeprevir and highlight the translational potential of optimizing simeprevir as a therapeutic agent for managing COVID-19 and future outbreaks of CoV.

Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging

Introduction

Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high‐performance, blood‐based test for AD.

Methods

We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high‐throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD.

Results

We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve  = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage‐dependent dysregulation, which can delineate AD stages.

Discussion

This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high‐performance, blood‐based test for clinical AD screening and staging.

Elevated Neutrophil to Lymphocyte Ratio Associated With Increased Risk of Recurrent Vascular Events in Older Minor Stroke or TIA Patients

Background

The risk of recurrent stroke following a minor stroke or transient ischemic attack (TIA) is high, when inflammation might play an important role. We aimed to evaluate the value of neutrophil to lymphocyte ratio (NLR) in predicting composite cardiovascular events in patients with minor stroke and TIA.

Methods

Consecutive patients with acute minor stroke or TIA admitted within 24 h of symptoms onset during a 5-year period in a prospective stroke registry were analyzed. We calculated the NLR dividing absolute neutrophil count by absolute lymphocyte count tested within 24 h of admission. NLR ≥4th quartile was defined as high NLR. A composite outcome was defined as stroke, acute coronary syndrome or vascular death within 1 year. We investigated associations between NLR and the composite outcome in univariate and multivariate analyses, among all patients and in those aged over 60 years (i.e., older patients).

Results

Overall, 841 patients (median age 68 years; 60.4% males) were recruited. No significant independent association was found between NLR and the composite outcome in multivariate analysis in the overall cohort. Among the 612 older patients (median age 73 years; 59.2% males), the median NLR was 2.76 (interquartile range 1.96-4.00) and 148 (24.2%) patients had high NLR. The composite outcome occurred in 77 (12.6%) older patients, who were more likely to have a high NLR (39.0% versus 22.1%; p = 0.001) than those without a composite outcome. In multivariate logistic regression, high NLR (adjusted odds ratio 2.00; 95% confidence interval 1.07-3.75; p = 0.031) was independently associated with the composite outcome in older patients.

Conclusion

In older (aged ≥60 years) patients with acute minor stroke or TIA, a higher NLR, a marker of systemic inflammation that can be easily obtained in routine blood tests, is an independent predictor of subsequent cardiovascular events.

AD Resemblance Atrophy Index as a Diagnostic Biomarker for Alzheimer's Disease: A Retrospective Clinical and Biological Validation

BACKGROUND

Magnetic resonance imaging (MRI) provides objective information about brain structural atrophy in patients with Alzheimer's disease (AD). This multi-structural atrophic information, when integrated as a single differential index, has the potential to further elevate the accuracy of AD identification from normal control (NC) compared to the conventional structure volumetric index.

OBJECTIVE

We herein investigated the performance of such an MRI-derived AD index, AD-Resemblance Atrophy Index (AD-RAI), as a neuroimaging biomarker in clinical scenario.

METHOD

Fifty AD patients (19 with the Amyloid, Tau, Neurodegeneration (ATN) results assessed in cerebrospinal fluid) and 50 age- and gender-matched NC (19 with ATN results assessed using positron emission tomography) were recruited in this study. MRI-based imaging biomarkers, i.e., AD-RAI, were quantified using AccuBrain®. The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of these MRI-based imaging biomarkers were evaluated with the diagnosis result according to clinical criteria for all subjects and ATN biological markers for the subgroup.

RESULTS

In the whole groups of AD and NC subjects, the accuracy of AD-RAI was 91%, sensitivity and specificity were 88% and 96%, respectively, and the AUC was 92%. In the subgroup of 19 AD and 19 NC with ATN results, AD-RAI results matched completely with ATN classification. AD-RAI outperforms the volume of any single brain structure measured.

CONCLUSION

The finding supports the hypothesis that MRI-derived composite AD-RAI is a more accurate imaging biomarker than individual brain structure volumetry in the identification of AD from NC in the clinical scenario.

Frontotemporal dementia and COVID-19: Hypothesis generation and roadmap for future research

The COVID-19 pandemic has caused tremendous suffering for patients with dementia and their caregivers. We conducted a survey to study the impact of the pandemic on patients with mild frontotemporal dementia (FTD). Our preliminary findings demonstrate that patients with FTD have significant worsening in behavior and social cognition, as well as suffer greater negative consequences from disruption to health-care services compared to patients with AD. The reduced ability to cope with sudden changes to social environments places patients with FTD at increased vulnerability to COVID-19 infection as well as to poorer clinical and social outcomes. Caregivers of FTD patients also demonstrate high burden during crisis situations. A proportion of patients with FTD benefitted from use of web-based interactive platforms. In this article, we outline the priority areas for research as well as a roadmap for future collaborative research to ensure greatest benefit for patients with FTD and their caregivers.

An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer's disease

BACKGROUND

The differential diagnosis of frontotemporal dementia (FTD) and Alzheimer's disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we aim at deriving a novel integrated index by leveraging the volumetric measures in brain regions with significant difference between AD and FTD and developing an MRI-based strategy for the differentiation of FTD and AD.

METHODS

In this study, the data were acquired from three different databases, including 47 subjects with FTD, 47 subjects with AD, and 47 normal controls in the NACC database; 50 subjects with AD in the ADNI database; and 50 subjects with FTD in the FTLDNI database. The MR images of all subjects were automatically segmented, and the brain atrophy, including the AD resemblance atrophy index (AD-RAI), was quantified using AccuBrain®. A novel MRI index, named the frontotemporal dementia index (FTDI), was derived as the ratio between the weighted sum of the volumetric indexes in "FTD dominant" structures over that obtained from "AD dominant" structures. The weights and the identification of "FTD/AD dominant" structures were acquired from the statistical analysis of NACC data. The differentiation performance of FTDI was validated using independent data from ADNI and FTLDNI databases.

RESULTS

AD-RAI is a proven imaging biomarker to identify AD and FTD from NC with significantly higher values (p < 0.001 and AUC = 0.88) as we reported before, while no significant difference was found between AD and FTD (p = 0.647). FTDI showed excellent accuracy in identifying FTD from AD (AUC = 0.90; SEN = 89%, SPE = 75% with threshold value = 1.08). The validation using independent data from ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC = 0.93; SEN = 96%, SPE = 70% with threshold value = 1.08).

CONCLUSIONS

Brain atrophy in AD, FTD, and normal elderly shows distinct patterns. In addition to AD-RAI that is designed to detect abnormal brain atrophy in dementia, a novel index specific to FTD is proposed and validated. By combining AD-RAI and FTDI, an MRI-based decision strategy was further proposed as a promising solution for the differential diagnosis of AD and FTD in clinical practice.

Electronic Cognitive Screen Technology for Screening Older Adults With Dementia and Mild Cognitive Impairment in a Community Setting: Development and Validation Study

BACKGROUND

A digital cognitive test can be a useful and quick tool for the screening of cognitive impairment. Previous studies have shown that the diagnostic performance of digital cognitive tests is comparable with that of conventional paper-and-pencil tests. However, the use of commercially available digital cognitive tests is not common in Hong Kong, which may be due to the high cost of the tests and the language barrier. Thus, we developed a brief and user-friendly digital cognitive test called the Electronic Cognitive Screen (EC-Screen) for the detection of mild cognitive impairment (MCI) and dementia of older adults.

OBJECTIVE

The aim of this study was to evaluate the performance of the EC-Screen for the detection of MCI and dementia in older adults.

METHODS

The EC-Screen is a brief digital cognitive test that has been adapted from the Rapid Cognitive Screen test. The EC-Screen uses a cloud-based platform and runs on a tablet. Participants with MCI, dementia, and cognitively healthy controls were recruited from research clinics and the community. The outcomes were the performance of the EC-Screen in distinguishing participants with MCI and dementia from controls, and in distinguishing participants with dementia from those with MCI and controls. The cohort was randomly split into derivation and validation cohorts based on the participants' disease group. In the derivation cohort, the regression-derived score of the EC-Screen was calculated using binomial logistic regression. Two predictive models were produced. The first model was used to distinguish participants with MCI and dementia from controls, and the second model was used to distinguish participants with dementia from those with MCI and controls. Receiver operating characteristic curves were constructed and the areas under the curves (AUCs) were calculated. The performances of the two predictive models were tested using the validation cohorts. The relationship between the EC-Screen and paper-and-pencil Montreal Cognitive Assessment-Hong Kong version (HK-MoCA) was evaluated by the Pearson correlation coefficient.

RESULTS

A total of 126 controls, 54 participants with MCI, and 63 participants with dementia were included in the study. In differentiating participants with MCI and dementia from controls, the AUC of the EC-Screen in the derivation and validation cohorts was 0.87 and 0.84, respectively. The optimal sensitivity and specificity in the derivation cohorts were 0.81 and 0.80, respectively. In differentiating participants with dementia from those with MCI and controls, the AUC of the derivation and validation cohorts was 0.90 and 0.88, respectively. The optimal sensitivity and specificity in the derivation cohort were 0.83 and 0.83, respectively. There was a significant correlation between the EC-Screen and HK-MoCA (r=-0.67, P<.001).

CONCLUSIONS

The EC-Screen is suggested to be a promising tool for the detection of MCI and dementia. This test can be self-administered or assisted by a nonprofessional staff or family member. Therefore, the EC-Screen can be a useful tool for case finding in primary health care and community settings.

Nurse Led Smartphone Electrographic Monitoring for Atrial Fibrillation after Ischemic Stroke: SPOT-AF

BACKGROUND AND PURPOSE

Paroxysmal atrial fibrillation (PAF) underlying acute stroke frequently evades detection by standard practice, considered to be a combination of routine electrocardiogram (ECG) monitoring, and 24-hour Holter recordings. We hypothesized that nurse-led in-hospital intermittent monitoring approach would increase PAF detection rate.

METHODS

We recruited patients hospitalised for stroke/transient ischemic attack, without history of atrial fibrillation (AF), in a prospective multi-centre observational study. Patients were monitored using a smartphone-enabled handheld ECG (iECG) during routine nursing observations, and underwent 24-hour Holter monitoring according to local practice. The primary outcome was comparison of AF detection by nurse-led iECG versus Holter monitoring in patients who received both tests: secondary outcome was oral anticoagulant commencement at 3-month following PAF detection.

RESULTS

One thousand and seventy-nine patients underwent iECG monitoring: 294 had iECG and Holter monitoring. AF was detected in 25/294 (8.5%) by iECG, and 8/294 (2.8%) by 24-hour Holter recordings (P<0.001). Median duration from stroke onset to AF detection for iECG was 3 days (interquartile range [IQR], 2 to 6) compared with 7 days (IQR, 6 to 10) for Holter recordings (P=0.02). Of 25 patients with AF detected by iECG, 11 were commenced on oral anticoagulant, compared to 5/8 for Holter. AF was detected in 8.8% (69/785 patients) who underwent iECG recordings only (P=0.8 vs. those who had both iECG and 24-hour Holter).

CONCLUSIONS

Nurse-led in-hospital iECG surveillance after stroke is feasible and effective and detects more PAF earlier and more frequently than routine 24-hour Holter recordings. Screening with iECG could be incorporated into routine post-stroke nursing observations to increase diagnosis of PAF, and facilitate institution of guideline-recommended anticoagulation.

Tackling challenges in care of Alzheimer's disease and other dementias amid the COVID-19 pandemic, now and in the future

We have provided an overview on the profound impact of COVID‐19 upon older people with Alzheimer's disease and other dementias and the challenges encountered in our management of dementia in different health‐care settings, including hospital, out‐patient, care homes, and the community during the COVID‐19 pandemic. We have also proposed a conceptual framework and practical suggestions for health‐care providers in tackling these challenges, which can also apply to the care of older people in general, with or without other neurological diseases, such as stroke or parkinsonism. We believe this review will provide strategic directions and set standards for health‐care leaders in dementia, including governmental bodies around the world in coordinating emergency response plans for protecting and caring for older people with dementia amid the COIVD‐19 outbreak, which is likely to continue at varying severity in different regions around the world in the medium term.

Genetic and polygenic risk score analysis for Alzheimer's disease in the Chinese population

INTRODUCTION

Dozens of Alzheimer's disease (AD)-associated loci have been identified in European-descent populations, but their effects have not been thoroughly investigated in the Hong Kong Chinese population.

METHODS

TaqMan array genotyping was performed for known AD-associated variants in a Hong Kong Chinese cohort. Regression analysis was conducted to study the associations of variants with AD-associated traits and biomarkers. Lasso regression was applied to establish a polygenic risk score (PRS) model for AD risk prediction.

RESULTS

SORL1 is associated with AD in the Hong Kong Chinese population. Meta-analysis corroborates the AD-protective effect of the SORL1 rs11218343 C allele. The PRS is developed and associated with AD risk, cognitive status, and AD-related endophenotypes. TREM2 H157Y might influence the amyloid beta 42/40 ratio and levels of immune-associated proteins in plasma.

DISCUSSION

SORL1 is associated with AD in the Hong Kong Chinese population. The PRS model can predict AD risk and cognitive status in this population.

Effects of Mindfulness Yoga vs Stretching and Resistance Training Exercises on Anxiety and Depression for People With Parkinson Disease: A Randomized Clinical Trial

Importance

Clinical practice guidelines support exercise for patients with Parkinson disease (PD), but to our knowledge, no randomized clinical trials have tested whether yoga is superior to conventional physical exercises for stress and symptom management.

Objective

To compare the effects of a mindfulness yoga program vs stretching and resistance training exercise (SRTE) on psychological distress, physical health, spiritual well-being, and health-related quality of life (HRQOL) in patients with mild-to-moderate PD.

Design, Setting, and Participants

An assessor-masked, randomized clinical trial using the intention-to-treat principle was conducted at 4 community rehabilitation centers in Hong Kong between December 1, 2016, and May 31, 2017. A total of 187 adults (aged ≥18 years) with a clinical diagnosis of idiopathic PD who were able to stand unaided and walk with or without an assistive device were enrolled via convenience sampling. Eligible participants were randomized 1:1 to mindfulness yoga or SRTE.

Interventions

Mindfulness yoga was delivered in 90-minute groups and SRTE were delivered in 60-minute groups for 8 weeks.

Main Outcomes and Measures

Primary outcomes included anxiety and depressive symptoms assessed using the Hospital Anxiety and Depression Scale. Secondary outcomes included severity of motor symptoms (Movement Disorder Society Unified Parkinson's Disease Rating Scale [MDS-UPDRS], Part III motor score), mobility, spiritual well-being in terms of perceived hardship and equanimity, and HRQOL. Assessments were done at baseline, 8 weeks (T1), and 20 weeks (T2).

Results

The 138 participants included 65 men (47.1%) with a mean (SD) age of 63.7 (8.7) years and a mean (SD) MDS-UPDRS score of 33.3 (15.3). Generalized estimating equation analyses revealed that the yoga group had significantly better improvement in outcomes than the SRTE group, particularly for anxiety (time-by-group interaction, T1: β, -1.79 [95% CI, -2.85 to -0.69; P = .001]; T2: β, -2.05 [95% CI, -3.02 to -1.08; P < .001]), depression (T1: β, -2.75 [95% CI, -3.17 to -1.35; P < .001]); T2: β, -2.75 [95% CI, -3.71 to -1.79; P < .001]), perceived hardship (T1: β, -0.92 [95% CI, -1.25 to -0.61; P < .001]; T2: β, -0.76 [95% CI, -1.12 to -0.40; P < .001]), perceived equanimity (T1: β, 1.11 [95% CI, 0.79-1.42; P < .001]; T2: β, 1.19 [95% CI, 0.82-1.56; P < .001]), and disease-specific HRQOL (T1: β, -7.77 [95% CI, -11.61 to -4.38; P < .001]; T2: β, -7.99 [95% CI, -11.61 to -4.38; P < .001]).

Conclusions and Relevance

Among patients with mild-to-moderate PD, the mindfulness yoga program was found to be as effective as SRTE in improving motor dysfunction and mobility, with the additional benefits of a reduction in anxiety and depressive symptoms and an increase in spiritual well-being and HRQOL.

Trial Registration

Centre for Clinical Research and Biostatistics identifier: CUHK_CCRB00522.

Impaired cognition is related to microstructural integrity in relapsing remitting multiple sclerosis

Background

Cognitive impairment is common in multiple sclerosis (MS). However, the relationship between cognitive deficits and microstructural abnormalities in Chinese MS patients remains unclear. We aimed to investigate the importance of microstructural abnormalities and the associations with cognitive impairment in Chinese MS patients.

Methods

Three‐dimensional T1‐weighted magnetic resonance imaging (MRI) scans were obtained from 36 relapsing remitting MS patients. Diffusion tensor imaging (DTI) scans were acquired for 29 (81%) patients. Cognitive impairment was assessed using a comprehensive neuropsychological battery. Patients were classified into cognitively impaired (CI) group and cognitively preserved (CP) group. Using volBrain and FSL software, we assessed white matter lesion burden, white matter (WM) and gray matter (GM) volumetric as well as microstructural diffusivity. MRI variables explaining cognitive impairment were analyzed.

Results

Fifteen (42%) patients were classified as CI. Verbal learning and memory was the most commonly impaired domain (n = 16, 44%). CI patients had lower mean skeleton fractional anisotropy (FA) value than CP patients (275.45 vs. 283.61 × 10⁻³, P = 0.023). The final predicting model including demographic variables and global skeleton mean diffusivity (MD) explained 43.6% of variance of the presence of cognitive impairment (β = 0.131, P = 0.041). CI patients showed a widespread change of microstructural integrity comparing to CP patients, which was rarely overlapping with lesion probability map. Microstructural abnormalities in corpus callosum were associated with performance in verbal learning and memory, processing speed and selective attention (P < 0.05).

Conclusion

Loss of microstructural integrity demonstrated by DTI helps explain cognitive dysfunction in Chinese MS patients.

Herb-drug interaction of gastrodiae rhizoma on carbamazepine: A pharmacokinetic study in rats

OBJECTIVE

Gastrodiae Rhizoma (GR), is a traditional Chinese Medicine that has been used for neurological disorders, including epilepsy. Epilepsy patients may be treated with adjunctive therapy of GR with antiepileptic drugs (AEDs). In particular, carbamazepine (CBZ) is of high potential to interact with concurrent treatment of Chinese Medicine. This study was to investigate the herb-drug interactions of GR and CBZ, an AED, through pharmacokinetic approach in rats.

METHODS

We adopted a high-performance liquid chromatography (HPLC) system to quantify the plasma level of CBZ and its metabolite (carbamazepine-10, 11-epoxide, CBZE). The method was validated as per instructions under United States Food and Drug Administration (USFDA) guidance. For the herb-drug interaction study, rats were randomly divided into four different treatment groups: single-dose CBZ treatment, single-dose CBZ/GR treatment, 2-week course of CBZ treatment and 2-week course of CBZ/GR treatment.

RESULTS

Our results demonstrated the auto-induction of CBZ metabolization when comparing single-dose with 2-week course of CBZ treatment. Pharmacokinetic interactions were noted in concomitant use of GR with CBZ by comparing two single-dose treatments (CBZ versus CBZ/GR). Our data showed that GR increased the mean residence time (MRT0-t) and the time taken to reach the maximum concentration (Tmax) of CBZ in single-dose of CBZ/GR treatment. The maximum drug concentration (Cmax) of CBZ was reduced in single-dose CBZ/GR treatment. When comparing the 2-week course of CBZ treatment with the 2-week course of CBZ/GR treatment, the MRT0-t and half-life of CBZ were increased. The AUC0-t, the Cmax and the half-life of CBZE were increased.

CONCLUSION

CBZ/GR treatment may reduce the auto-induction of CBZ over 2 weeks. While the reduction of auto-induction could enhance the therapeutic effects of CBZ, it could also lead to an increase in neurological side effects and non-neurological adverse effects. Our results provided preclinical evidence of herb-drug interaction, which may have implications for epilepsy patients treated with GR.