Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group

Molecular probes for super-resolution imaging of drug dynamics

Super-resolution molecular probes (SRMPs) are essential tools for visualizing drug dynamics within cells, transcending the resolution limits of conventional microscopy. In this review, we provide an overview of the principles and design strategies of SRMPs, emphasizing their role in accurately tracking drug molecules. By illuminating the intricate processes of drug distribution, diffusion, uptake, and metabolism at a subcellular and molecular level, SRMPs offer crucial insights into therapeutic interventions. Additionally, we explore the practical applications of super-resolution imaging in disease treatment, highlighting the significance of SRMPs in advancing our understanding of drug action. Finally, we discuss future perspectives, envisioning potential advancements and innovations in this field. Overall, this review serves to inform and practitioners about the utility of SRMPs in driving innovation and progress in pharmacology, providing valuable insights for drug development and optimization.

Studying the Alzheimer's disease continuum using EEG and fMRI in single-modality and multi-modality settings

Alzheimer's disease (AD) is a biological, clinical continuum that covers the preclinical, prodromal, and clinical phases of the disease. Early diagnosis and identification of the stages of Alzheimer's disease (AD) are crucial in clinical practice. Ideally, biomarkers should reflect the underlying process (pathological or otherwise), be reproducible and non-invasive, and allow repeated measurements over time. However, the currently known biomarkers for AD are not suitable for differentiating the stages and predicting the trajectory of disease progression. Some objective parameters extracted using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are widely applied to diagnose the stages of the AD continuum. While electroencephalography (EEG) has a high temporal resolution, fMRI has a high spatial resolution. Combined EEG and fMRI (EEG-fMRI) can overcome single-modality drawbacks and obtain multi-dimensional information simultaneously, and it can help explore the hemodynamic changes associated with the neural oscillations that occur during information processing. This technique has been used in the cognitive field in recent years. This review focuses on the different techniques available for studying the AD continuum, including EEG and fMRI in single-modality and multi-modality settings, and the possible future directions of AD diagnosis using EEG-fMRI.

Distinct biological property of tau in tau-first cognitive proteinopathy: Evidence by longitudinal clinical neuroimaging profiles and compared with late-onset Alzheimer disease

BACKGROUND

Tau-first cognitive proteinopathy (TCP) denotes a clinical phenotype of Alzheimer disease (AD) showing Florzolotau(18F) positron emission tomography (PET) positivity but a negative amyloid status.

AIM

We explored the biological property of tau using longitudinal cognitive and neuroimaging data in TCP and compared with late-onset AD (LOAD).

METHOD

We enrolled 56 patients with LOAD, 34 patients with TCP, and 26 cognitive unimpaired controls. All of the participants had historical data of 2 to 4 three-dimensional T1 images and 2 to 6 annual cognitive evaluations over a follow-up period of 7 years. Tau topography was measured using Florzolotau(18F) PET. In the LOAD and TCP groups, we constructed tau or gray matter clusters covarying with the cognitive measurements. We used mediator analysis to explore the regional tau load as predictor, gray matter partitions as mediators, and significant cognitive test scores as outcomes. Longitudinal cognitive decline and cortical thickness degeneration pattern were analyzed using a linear mixed-effects model.

RESULTS

The TCP group had longitudinal declines in nonexecutive domains. The deterministic factor predicting the short-term memory score in TCP was the hippocampal volume and not directly via the medial and lateral temporal tau load. These features formed the conceptual differences with LOAD.

DISCUSSION

The biological properties of tau and the longitudinal cognitive-imaging trajectory support the conceptual distinction between TCP and LOAD. TCP represents one specific entity featuring salient short-term memory impairment, declines in nonexecutive domains, a slower gray matter degenerative pattern, and a restricted impact of tau.

Carbon dots as dual inhibitors of tau and amyloid-beta aggregation for the treatment of Alzheimer's disease

Alzheimer's disease (AD) is the most common form of senile dementia, presenting a significant challenge for the development of effective treatments. AD is characterized by extracellular amyloid plaques and intraneuronal neurofibrillary tangles. Therefore, targeting both hallmarks through inhibition of amyloid beta (Aβ) and tau aggregation presents a promising approach for drug development. Carbon dots (CD), with their high biocompatibility, minimal cytotoxicity, and blood-brain barrier (BBB) permeability, have emerged as promising drug nanocarriers. Congo red, an azo dye, has gathered significant attention for inhibiting amyloid-beta and tau aggregation. However, Congo red's inability to cross the BBB limits its potential to be used as a drug candidate for central nervous system (CNS) diseases. Furthermore, current studies only focus on using Congo red to target single disease hallmarks, without investigating dual inhibition capabilities. In this study, we synthesized Congo red-derived CD (CRCD) by using Congo red and citric acid as precursors, resulting in three variants, CRCD1, CRCD2 and CRCD3, based on different mass ratios of precursors. CRCD2 and CRCD3 exhibited sustained low cytotoxicity, and CRCD3 demonstrated the ability to traverse the BBB in a zebrafish model. Moreover, thioflavin T (ThT) aggregation assays and AFM imaging revealed CRCD as potent inhibitors against both tau and Aβ aggregation. Notably, CRCD1 emerged as the most robust inhibitor, displaying IC50 values of 0.2 ± 0.1 and 2.1 ± 0.5 µg/mL against tau and Aβ aggregation, respectively. Our findings underscore the dual inhibitory role of CRCD against tau and Aβ aggregation, showcasing effective BBB penetration and positioning CRCD as potential nanodrugs and nanocarriers for the CNS. Hence, CRCD-based compounds represent a promising candidate in the realm of multi-functional AD therapeutics, offering an innovative formulation component for future developments in this area. STATEMENT OF SIGNIFICANCE: This article reports Congo red-derived carbon dots (CRCD) as dual inhibitors of tau and amyloid-beta (Aβ) aggregation for the treatment of Alzheimer's disease (AD). The CRCD are biocompatible and show strong fluorescence, high stability, the ability to cross the blood-brain barrier, and the function of addressing two major pathological features of AD.

Dementia Ideal Care: Ecosystem Map of Best Practices and Care Pathways Enhanced by Technology and Community

Background

Globally, much work has been done by nonprofit, private, and academic groups to develop best practices for the care of people living with dementia (PLWD), including Alzheimer's disease. However, these best practices reside in disparate repositories and tend to focus on one phase of the patient journey or one relevant group.

Objective

To fill this gap, we developed a Dementia Ideal Care Map that everyone in the dementia ecosystem can use as an actionable tool for awareness, policy development, funding, research, training, service delivery, and technology design. The intended audience includes (and not limited to) policymakers, academia, industry, technology developers, health system leaders, clinicians, social service providers, patient advocates, PLWD, their families, and communities at large.

Methods

A search was conducted for published dementia care best practices and quality measures, which were then summarized in a visual diagram. The draft diagram was analyzed to identify barriers to ideal care. Then, additional processes, services, technologies, and quality measures to overcome those challenges were brainstormed. Feedback was then obtained from experts.

Results

The Dementia Ideal Care Map summarizes the ecosystem of over 200 best practices, nearly 100 technology enablers, other infrastructure, and enhanced care pathways in one comprehensive diagram. It includes psychosocial interventions, care partner support, community-based organizations; awareness, risk reduction; initial detection, diagnosis, ongoing medical care; governments, payers, health systems, businesses, data, research, and training.

Conclusions

Dementia Ideal Care Map is a practical tool for planning and coordinating dementia care. This visualized ecosystem approach can be applied to other conditions.

Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer's Disease: A Pragmatic Review for Clinicians

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer's disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

Comparing neuropsychological, typical, and ADNI criteria for the diagnosis of mild cognitive impairment in Vietnam-era veterans

OBJECTIVE

Neuropsychological criteria for mild cognitive impairment (MCI) more accurately predict progression to Alzheimer's disease (AD) and are more strongly associated with AD biomarkers and neuroimaging profiles than ADNI criteria. However, research to date has been conducted in relatively healthy samples with few comorbidities. Given that history of traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) are risk factors for AD and common in Veterans, we compared neuropsychological, typical (Petersen/Winblad), and ADNI criteria for MCI in Vietnam-era Veterans with histories of TBI or PTSD.

METHOD

267 Veterans (mean age = 69.8) from the DOD-ADNI study were evaluated for MCI using neuropsychological, typical, and ADNI criteria. Linear regressions adjusting for age and education assessed associations between MCI status and AD biomarker levels (cerebrospinal fluid [CSF] p-tau181, t-tau, and Aβ42) by diagnostic criteria. Logistic regressions adjusting for age and education assessed the effects of TBI severity and PTSD symptom severity simultaneously on MCI classification by each criteria.

RESULTS

Agreement between criteria was poor. Neuropsychological criteria identified more Veterans with MCI than typical or ADNI criteria, and were associated with higher CSF p-tau181 and t-tau. Typical and ADNI criteria were not associated with CSF biomarkers. PTSD symptom severity predicted MCI diagnosis by neuropsychological and ADNI criteria. History of moderate/severe TBI predicted MCI by typical and ADNI criteria.

CONCLUSIONS

MCI diagnosis using sensitive neuropsychological criteria is more strongly associated with AD biomarkers than conventional diagnostic methods. MCI diagnostics in Veterans would benefit from incorporation of comprehensive neuropsychological methods and consideration of the impact of PTSD.

Is blood pTau a reliable indicator of the CSF status? A narrative review

BACKGROUND

The identification of biomarkers for the early diagnosis of Alzheimer's disease (AD) is a crucial goal of the current research. Blood biomarkers are less invasive, easier to obtain and achievable by a cheaper means than those on cerebrospinal fluid (CSF) and significantly more economic than functional neuroimaging investigations; thus, a great interest is focused on blood isoforms of the phosphorylated Tau protein (pTau), indicators of ongoing tau pathology (i.e. neurofibrillary tangles, NFTs, an AD neuropathological hallmark) in the central nervous system (CNS). However, current data often highlight discordant results about the ability of blood pTau to predict CSF status.

OBJECTIVE

We aim to synthesise the studies that compared pTau levels on CSF and blood to assess their correlation in AD continuum.

METHODS

We performed a narrative literature review using, first, MEDLINE (via PubMed) by means of MeSH terms, and then, we expanded the reults by means of Scopus and Web of Sciences to be as inclusive as possible. Finally, we added work following an expert opinion. Only papers presenting original data on pTau values on both blood and CSF were included.

RESULTS

The 33 included studies show an extreme heterogeneity in terms of pTau isoform (pTau181, 217 and 231), laboratory methods, diagnostic criteria and choice of comparison groups. Most studies evaluated plasma pTau181, while data on other isoforms and serum are scarcer.

DISCUSSION

Most papers identify a correlation between CSF and blood measurements. Furthermore, even when not specified, it is often possible to show an increase in blood pTau values as AD-related damage progresses in the AD continuum and higher values in AD than in other neurodegenerative diseases. Notably, plasma pTau231 seems the first biomarker to look for in the earliest and pre-clinical stages, quickly followed by pTau217 and, finally, by pTau181.

CONCLUSIONS

Our results encourage the use of blood pTau for the early identification of patients with AD continuum.

Catatonia in patients with dementia: A descriptive study of clinical profiles and treatment response

BACKGROUND

Catatonia is a highly prevalent syndrome in patients presenting with major neurocognitive disorders (dementia). In this study, we aim to provide a comprehensive description of the clinical and therapeutic aspects of catatonia in patients with dementia.

METHOD

This descriptive study, conducted between September 2015 and June 2022, collected data from 25 patients diagnosed with dementia, out of 143 patients treated for catatonia in our specialized psychiatry department. We collected sociodemographic, clinical and treatment data for each patient.

RESULTS

Dementia patients constituted 17% of the catatonic cases. Predominantly female, the cohort had a mean age of 65. Diagnoses included Alzheimer's (4 patients, 17%) and Parkinson's (1 patient, 4%) diseases, Lewy body dementia (5 patients, 21%), vascular dementia (4 patients, 17%) and frontotemporal lobar degeneration (10 patients, 41%). The mean Bush-Francis Catatonia Rating Scale score upon admission was 20/69. Overall, complete remission of catatonia was achieved in 75% of patients (n=18), with only 13% (n=3) responding to lorazepam alone, while others required additional interventions such as electroconvulsive therapy (ECT) and/or amantadine. Vascular dementia was predominantly observed in cases resistant to treatment.

CONCLUSION

The findings indicate a frequent co-occurrence of catatonia and dementia, highlighting treatability yet suggesting a potential for resistance to lorazepam, which varies by dementia diagnosis. Investigating the mechanisms underlying this resistance and the variability in treatment response is crucial for developing more precise therapeutic strategies.

Genes related to neurotransmitter receptors as potential biomarkers for Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is a leading cause of dementia and is rapidly emerging as one of the costliest and most burdensome diseases. Neurotransmitter receptors play a vital role in many neuronal processes, primarily regulating signal inhibition within the brain to facilitate cell communication.

OBJECTIVES

Our research aims to identify potential biomarkers associated with AD and how these biomarkers impact immune infiltration.

METHODS

We extracted mRNA expression data from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were employed to identify hub genes as biomarkers in AD. The Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Variation Analysis (GSVA) were used for functional enrichment. Furthermore, we examined 22 immune cell types infiltration using "CIBERSORT".

RESULTS

In this study, we identified 70 neurotransmitter receptor genes showing differential expression in AD: 22 were up-regulated, and 48 were down-regulated. Functional analyses indicated these genes were involved in essential biochemical pathways, including G protein-coupled receptors, neurotransmitter receptor activity, and ion channel interactions. WGCNA generated three co-expression modules, with one demonstrating the strongest association with AD. Five key NRGs (HTR3C, HTR3E, ADRA2A, HTR3A, and ADRA1D) were identified using a combination of differential genes. These genes have better diagnostic value by ROC analysis. Immune infiltration analysis showed that these genes were closely associated with the levels of resting mast cells, activated natural killer (NK) cells, and plasma cells in AD compared to controls.

CONCLUSION

Our study identified five NRGs (ADRA1D, ADRA2A, HTR3A, HTR3C, and HTR3E) with significant associations with AD. These findings may offer promising sights for further studies.

Amyloid-β Deposition Predicts Grocery Shopping Performance in Older Adults Without Cognitive Impairment

Background

A screening tool sensitive to Alzheimer's disease (AD) risk factors, such as amyloid-β (Aβ) deposition, and subtle cognitive changes, best elicited by complex everyday tasks, is needed.

Objective

To determine if grocery shopping performance could differentiate older adults at elevated risk of developing AD (OAer), older adults at low risk of developing AD (OAlr), and young adults (YA), and if amount of Aβ deposition could predict grocery shopping performance in older adults (OA).

Methods

Twenty-one OAer (78±5 years), 33 OAlr (78±5 years), and 28 YA (31±3 years) performed four grocery shopping trials, with the best and worst performances analyzed. Measures included trial time, number of correct items, number of grocery note fixations, and number of fixations and percentage of time fixating on the correct shelving unit, correct brand, and correct shelf. Linear mixed effects models compared measures by performance rank (best, worst) and group (OAer, OAlr, YA), and estimated the effect of Aβ deposition on measures in OA.

Results

Relative to their best performance, OAer and OAlr exhibited more correct shelving unit fixations and correct brand fixations during their worst performance, while YA did not. Within OA's worst performance, greater Aβ deposition was associated with a smaller percentage of time fixating on the correct shelving unit, correct shelf, and correct brand. Within OA, greater Aβ deposition was associated with more grocery note fixations.

Conclusions

OA with elevated Aβ deposition may exhibit subtle working memory impairments and less efficient visual search strategies while performing a cognitively demanding everyday task.

The associations between nutritional status and physical frailty and Alzheimer's disease plasma biomarkers in older cognitively unimpaired adults with positive of amyloid-β PET

BACKGROUND & AIMS

It has been revealed good nutritional status and no physical frailty, which are modifiable lifestyle factors, are linked to less cognitive decline and a lower risk of Alzheimer's disease (AD). We aimed to investigate the associations between nutritional status and physical frailty and plasma AD biomarkers, especially the Tau-associated biomarkers in older cognitively unimpaired (CU) adults with higher β-amyloid (Aβ) burden.

METHODS

The nutritional status and physical frailty were assessed via Mini-Nutritional Assessment Short-Form (MNA-SF) and Fried frailty index. The participants underwent the examination of plasma AD biomarkers and 18F-florbetapir PET scan as well as 18F-MK6240 PET in the validation cohort. Correlation and multiple linear regression analyses were used to investigate the associations between nutritional status and frailty and AD biomarkers.

RESULTS

Two cohorts were included in our study. A total of 129 participants with Aβ-PET positive were enrolled in the development cohort. Multiple linear regression analysis showed MNA-SF scores, normal nutritional status, Fried frailty index scores, frailty and some domains of frailty including weight loss, maximal grip strength and exhaustion were associated with plasma p-Tau-181. Furthermore, weight loss, Fried frailty index scores and frailty were associated with higher Aβ-PET standard uptake value ratio. We further performed subgroup analyses stratified by age, sex and apolipoprotein E ε4 genotype to investigate the beneficial characteristics of nutrition and frailty in the special subgroups. Validation cohort contained 38 Aβ-PET positive participants. MNA-SF scores, normal nutritional status, Fried frailty index scores and frailty were associated with Tau burden evaluated by 18F-MK6240 PET Braak-like stages.

CONCLUSIONS

Our data indicates that normal nutritional status and no physical frailty may be associated with expected trend of plasma AD biomarkers, especially less Tau pathology in older CU adults with Aβ deposition. Adjusting to these characteristics of nutrition and physical frailty may help reduce the risk of AD development.

Peripheral GFAP and NfL as early biomarkers for dementia: longitudinal insights from the UK Biobank

BACKGROUND

Peripheral glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are sensitive markers of neuroinflammation and neuronal damage. Previous studies with highly selected participants have shown that peripheral GFAP and NfL levels are elevated in the pre-clinical phase of Alzheimer's disease (AD) and dementia. However, the predictive value of GFAP and NfL for dementia requires more evidence from population-based cohorts.

METHODS

This was a prospective cohort study to evaluate UK Biobank participants enrolled from 2006 to 2010 using plasma GFAP and NfL measurements measured by Olink Target Platform and prospectively followed up for dementia diagnosis. Primary outcome was the risk of clinical diagnosed dementia. Secondary outcomes were cognition. Linear regression was used to assess the associations between peripheral GFAP and NfL with cognition. Cox proportional hazard models with cross-validations were used to estimate associations between elevated GFAP and NfL with risk of dementia. All models were adjusted for covariates.

RESULTS

A subsample of 48,542 participants in the UK Biobank with peripheral GFAP and NfL measurements were evaluated. With an average follow-up of 13.18 ± 2.42 years, 1312 new all-cause dementia cases were identified. Peripheral GFAP and NfL increased up to 15 years before dementia diagnosis was made. After strictly adjusting for confounders, increment in NfL was found to be associated with decreased numeric memory and prolonged reaction time. A greater annualized rate of change in GFAP was significantly associated with faster global cognitive decline. Elevation of GFAP (hazard ratio (HR) ranges from 2.25 to 3.15) and NfL (HR ranges from 1.98 to 4.23) increased the risk for several types of dementia. GFAP and NfL significantly improved the predictive values for dementia using previous models (area under the curve (AUC) ranges from 0.80 to 0.89, C-index ranges from 0.86 to 0.91). The AD genetic risk score and number of APOE*E4 alleles strongly correlated with GFAP and NfL levels.

CONCLUSIONS

These results suggest that peripheral GFAP and NfL are potential biomarkers for the early diagnosis of dementia. In addition, anti-inflammatory therapies in the initial stages of dementia may have potential benefits.

Updated safety results from phase 3 lecanemab study in early Alzheimer's disease

BACKGROUND

Alzheimer disease (AD) is a major health problem of aging, with tremendous burden on healthcare systems, patients, and families globally. Lecanemab, an FDA-approved amyloid beta (Aβ)-directed antibody indicated for the treatment of early AD, binds with high affinity to soluble Aβ protofibrils, which have been shown to be more toxic to neurons than monomers or insoluble fibrils. Lecanemab has been shown to be well tolerated in multiple clinical trials, although risks include an increased rate of amyloid-related imaging abnormalities (ARIA) and infusion reactions relative to placebo.

METHODS

Clarity AD was an 18-month treatment (Core study), multicenter, double-blind, placebo-controlled, parallel-group study with open-label extension (OLE) in participants with early AD. Eligible participants were randomized 1:1 across 2 treatment groups (placebo and lecanemab 10 mg/kg biweekly). Safety evaluations included monitoring of vital signs, physical examinations, adverse events, clinical laboratory parameters, and 12-lead electrocardiograms. ARIA occurrence was monitored throughout the study by magnetic resonance imaging, read both locally and centrally.

RESULTS

Overall, 1795 participants from Core and 1612 participants with at least one dose of lecanemab (Core + OLE) were included. Lecanemab was generally well-tolerated in Clarity AD, with no deaths related to lecanemab in the Core study. There were 9 deaths during the OLE, with 4 deemed possibly related to study treatment. Of the 24 deaths in Core + OLE, 3 were due to intracerebral hemorrhage (ICH): 1 placebo in the Core due to ICH, and 2 lecanemab in OLE with concurrent ICH (1 on tissue plasminogen activator and 1 on anticoagulant therapy). In the Core + OLE, the most common adverse events in the lecanemab group (> 10%) were infusion-related reactions (24.5%), ARIA with hemosiderin deposits (ARIA-H) microhemorrhages (16.0%), COVID-19 (14.7%), ARIA with edema (ARIA-E; 13.6%), and headache (10.3%). ARIA-E and ARIA-H were largely radiographically mild-to-moderate. ARIA-E generally occurred within 3-6 months of treatment, was more common in ApoE e4 carriers (16.8%) and most common in ApoE ε4 homozygous participants (34.5%).

CONCLUSIONS

Lecanemab was generally well-tolerated, with the most common adverse events being infusion-related reactions, ARIA-H, ARIA-E. Clinicians, participants, and caregivers should understand the incidence, monitoring, and management of these events for optimal patient care.

TRIAL REGISTRATION

ClinicalTrials.gov numbers: Clarity AD NCT03887455).

Exploring the genetic heterogeneity of Alzheimer's disease: Evidence for genetic subtypes

Background

Alzheimer's disease (AD) exhibits considerable phenotypic heterogeneity, suggesting the potential existence of subtypes. AD is under substantial genetic influence, thus identifying systematic variation in genetic risk may provide insights into disease origins.

Objective

We investigated genetic heterogeneity in AD risk through a multi-step analysis.

Methods

We performed principal component analysis (PCA) on AD-associated variants in the UK Biobank (AD cases=2,739, controls=5,478) to assess structured genetic heterogeneity. Subsequently, a biclustering algorithm searched for distinct disease-specific genetic signatures among subsets of cases. Replication tests were conducted using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (AD cases=500, controls=470). We categorized a separate set of ADNI individuals with mild cognitive impairment (MCI; n=399) into genetic subtypes and examined cognitive, amyloid, and tau trajectories.

Results

PCA revealed three distinct clusters ("constellations") driven primarily by different correlation patterns in a region of strong LD surrounding the MAPT locus. Constellations contained a mixture of cases and controls, reflecting disease-relevant but not disease-specific structure. We found two disease-specific biclusters among AD cases. Pathway analysis linked bicluster-associated variants to neuron morphogenesis and outgrowth. Disease-relevant and disease-specific structure replicated in ADNI, and bicluster 2 exhibited increased CSF p-tau and cognitive decline over time.

Conclusions

This study unveils a hierarchical structure of AD genetic risk. Disease-relevant constellations may represent haplotype structure that does not increase risk directly but may alter the relative importance of other genetic risk factors. Biclusters may represent distinct AD genetic subtypes. This structure is replicable and relates to differential pathological accumulation and cognitive decline over time.

Association of dietary inflammation with tooth loss and cognitive decline in older adults from cross-sectional data: The moderated role of albumin

OBJECTIVE

Growing evidence suggests a potential connection between tooth loss and cognitive function in recent years. Increasing studies have focused on their inter-relationship, however, the underlying mechanism has yet to be fully elucidated. Few studies have considered the role of dietary inflammation and serum albumin in the association between tooth loss and cognitive function. Therefore, the aim of this study was to explore the role of dietary inflammation and serum albumin in the association between tooth loss and cognitive impairment.

METHODS

A sample of 1,009 US adults from the National Health and Nutrition Examination Survey (NHANES) provided data on oral condition, cognitive function, dietary intake, and serum tests. The association between tooth loss (exposure variable) and cognitive function (outcome variable) was assessed by linear regression. Furthermore, a moderated mediation model was established to examine the influence of dietary inflammation on the association between tooth loss and cognitive tests, and the visualization of the moderating effect of serum albumin concentration was displayed through the Johnson-Neyman curve.

RESULTS

Participants with impaired dentition had worse cognitive function and a higher Dietary Inflammation Index (DII). DII was highly correlated with Immediate Recall Test (IR), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST), which mediated 16.46 %, 14.41 % and 11.28 % of the effect between tooth loss and cognitive functions. Additionally, the relationship between DII and DSST was moderated by serum albumin concentration.

CONCLUSION

Tooth loss was associated with cognitive function which was affected by pro-inflammatory dietary patterns and serum albumin level.

CLINICAL SIGNIFICANCE

This study presents evidence for dentists that dietary pattern change due to tooth loss plays a role in cognitive deterioration, which can also be moderated by serum albumin level. Therefore, the preservation of natural teeth is important for cognitive function, especially in an immunocompromised population with decreased serum albumin concentrations.

Immunotherapy: An emerging treatment option for neurodegenerative diseases

Accumulation of misfolded proteins and protein aggregates leading to degeneration of neurons is a hallmark of several neurodegenerative diseases. Therapy mostly relies on symptomatic relief. Immunotherapy offers a promising approach for the development of disease-modifying routes. Such strategies have shown remarkable results in oncology, and this promise is increasingly being realized for neurodegenerative diseases in advanced preclinical and clinical studies. This review highlights cases of passive and active immunotherapies in Parkinson's and Alzheimer's diseases. The reasons for success and failure, wherever available, and strategies to cross the blood-brain barrier, are discussed. The need for conditional modulation of the immune response is also reflected on.

Entropy-driven catalysis-based lateral flow assay for sensitive detection of Alzheimer 's-associated MicroRNA

Alzheimer's disease (AD) is a degenerative disease of the brain worldwide. Currently, there is no effective cure. But accurate and early diagnosis of AD is critical to the development of patient care and future treatments. MiRNA-16 has been considered as an effective diagnostic biomarker for AD because of its regulatory effect on key proteins of AD. Herein, a colorimetric lateral flow assay (LFA) was developed for sensitive detection of miRNA-16 based on entropy-driven catalysis (EDC) amplification strategy. MiRNA-16 triggered EDC and released more linker DNAs (LDNA) of sandwich structure. Thus, AuNPs were enriched at the T-line to enhance the colorimetric signal and improve the sensitivity of visual assay. It showed good specificity and sensitivity for detecting miRNA-16 with a detection limit of 1.01 pM. The practical detection of miRNA-16 in human serum obtained satisfactory result. Significantly, EDC achieved signal amplification in homogeneous solution without enzyme and DNA labeling, leading to a cheap and easy detection of miRNA-16. Therefore, it provided a portable and rapid assay for AD-related nucleic acid, which holds a potential for point-of-care testing (POCT) of AD.

Language switching and speaking a nondominant language challenge executive control: Preliminary data for novel behavioral markers of Alzheimer's risk in Spanish-English bilinguals

OBJECTIVE

The present study explored psycholinguistic analysis of spoken responses produced in a structured interview and cued linguistic and nonlinguistic task switching as possible novel markers of Alzheimer's disease (AD) risk in Spanish-English bilinguals.

METHOD

Nineteen Spanish-English bilinguals completed an Oral Proficiency Interview (OPI) in both languages, cued-switching tasks, and a battery of traditional neuropsychological tests (in a separate testing session). All were cognitively healthy at the time of testing, but eight decliners were later diagnosed with AD (on average 4.5 years after testing; SD = 2.3), while 11 controls remained cognitively healthy.

RESULTS

Past studies showed picture naming was more sensitive to AD in the dominant than in the nondominant language, but we found the opposite for a composite measure of spoken utterances produced in the OPI that included revisions, repetitions, and filled pauses (RRFPs), which were especially sensitive to AD risk in the nondominant language. Errors produced on language switch trials best discriminated decliners from controls (in receiver operating characteristic curves), and though the nonlinguistic switching task was also sensitive to AD risk, it elicited more errors overall and was also negatively affected by increased age and low education level.

CONCLUSIONS

Speaking a nondominant language and errors in cued language switching provided sensitive and specific markers of pending cognitive decline and AD risk in bilinguals. These measures may reflect early decline in executive control abilities that are needed to plan and monitor the production of connected speech and to manage competition for selection between languages. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Clinical variables contributing to the identification of biologically defined subgroups within cognitively unimpaired and mild cognitive impairment individuals

BACKGROUND

A lack of consensus exists in linking demographic, behavioral, and cognitive characteristics to biological stages of dementia, defined by the ATN (amyloid, tau, neurodegeneration) classification incorporating amyloid, tau, and neuronal injury biomarkers.

METHODS

Using a random forest classifier we investigated whether 27 demographic, behavioral, and cognitive characteristics allowed distinction between ATN-defined groups with the same cognitive profile. This was done separately for three cognitively unimpaired (CU) (112 A-T-N-; 46 A+T+N+/-; 65 A-T+/-N+/-) and three mild cognitive impairment (MCI) (128 A-T-N-; 223 A+T+N+/-; 94 A-T+/-N+/-) subgroups.

RESULTS

Classification-balanced accuracy reached 39% for the CU and 52% for the MCI subgroups. Logical Delayed Recall (explaining 16% of the variance), followed by the Alzheimer's Disease Assessment Scale 13 (14%) and Everyday Cognition Informant (10%), were the most relevant characteristics for classification of the MCI subgroups. Race and ethnicity, marital status, and Everyday Cognition Patient were not relevant (0%).

CONCLUSIONS

The demographic, behavioral, and cognitive measures used in our model were not informative in differentiating ATN-defined CU profiles. Measures of delayed memory, general cognition, and activities of daily living were the most informative in differentiating ATN-defined MCI profiles; however, these measures alone were not sufficient to reach high classification performance.

The mechanism of mitochondrial metabolic gene PMAIP1 involved in Alzheimer's disease process based on bioinformatics analysis and experimental validation

OBJECTIVES

This study explored novel biomarkers that can affect the diagnosis and treatment in Alzheimer's Disease (AD) related to mitochondrial metabolism.

METHODS

The authors obtained the brain tissue datasets for AD from the Gene Expression Omnibus (GEO) and downloaded the mitochondrial metabolism-related genes set from MitoCarta 3.0 for analysis. Differentially Expressed Genes (DEGs) were screened using the "limma" R package, and the biological functions and pathways were investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The LASSO algorithm was used to identify the candidate center genes and validated in the GSE97760 dataset. PMAIP1 with the highest diagnostic value was selected and its effect on the occurrence of AD by biological experiments.

RESULTS

A sum of 364 DEGs and 50 hub genes were ascertained. GO and KEGG enrichment analysis demonstrated that DEGs were preponderantly associated with cell metabolism and apoptosis. Five genes most associated with AD as candidate central genes by LASSO algorithm analysis. Then, the expression level and specificity of candidate central genes were verified by GSE97760 dataset, which confirmed that PMAIP1 had a high diagnostic value. Finally, the regulatory effects of PMAIP1 on apoptosis and mitochondrial function were detected by siRNA, flow cytometry and Western blot. siRNA-PMAIP1 can alleviate mitochondrial dysfunction and inhibit cell apoptosis.

CONCLUSION

This study identified biomarkers related to mitochondrial metabolism in AD and provided a theoretical basis for the diagnosis of AD. PMAIP1 was a potential candidate gene that may affect mitochondrial function in Hippocampal neuronal cells, and its mechanism deserves further study.

Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics

Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.

Incidence and Prevalence of Dementia: A 2015-2020 Population-Based Study in the Campania Region of Italy

OBJECTIVE

The aims of this study were to provide population-based estimates of prevalence and incidence of any dementia and Alzheimer's dementia (AD) in the Campania region (South Italy) and to validate towards a clinical registry.

METHODS

This was a population-based study, using routinely collected healthcare data of individuals living in the Campania region (South Italy) from 2015 to 2020. We included individuals aged ≥65 years alive at the prevalence day (January 1, 2021) who had at least one administrative record for dementia and/or AD from 2015 to 2020. Age-and sex-standardised prevalence rates were calculated using direct standardisation method (European population in 2020 as the reference population). To estimate the incidence, we tested three possible algorithms, which differed for the duration of the time interval between study baseline (January 1, 2015) and index date (first record for dementia and/or AD in administrative databases). We employed a clinical database for the validation of our algorithms towards neuropsychological test results.

RESULTS

Among individuals aged over 65 years, 80,392 had dementia, of which 35,748 had AD. The age- and sex-standardised prevalence rates per 1,000 individuals for any dementia and AD were 77.64 (95% confidence interval [CI] = 77.57; 77.68) and 34.05 (95% CI = 34.01; 34.09), respectively. There were 82.10 incident cases of any dementia per 100,000 per year (0.79 sensitivity and 0.62 specificity) and 59.89 incident cases of AD per 100,000 per year (0.80 sensitivity and 0.59 specificity). The capture-recapture method showed a very low number of undetected cases (1.7% for any dementia and 3.0% for AD). Our algorithms showed acceptable performance with the area under the curve ranging from 0.59 to 0.72 and a double likelihood ratio of correctly identifying individuals above and below mini-mental status examination (MMSE) standard cut-offs (24 and 26).

CONCLUSIONS

Prevalence and incidence of any dementia and AD in the Campania region (South Italy) from 2015 to 2020 are in line with previous estimates from other countries. Our algorithm, integrating administrative and clinical data, holds potential for assessing dementia's epidemiological burden, identifying risk factors, planning healthcare access, and developing prevention strategies.

Impaired lexical access for unique entities in individuals with subjective cognitive decline

Subjective cognitive decline (SCD) may serve as an early indicator of Alzheimer's disease (AD). However, accurately quantifying cognitive impairment in SCD is challenging, mainly because existing assessment tools lack sensitivity. This study examined how tasks specifically designed to assess knowledge of famous people, could potentially aid in identifying cognitive impairment in SCD. A total of 60 adults with SCD and 60 healthy controls (HCs) aged 50 to 82 years performed a famous people verbal fluency task and a famous people naming task. In the famous people fluency task, the results showed that the individuals with SCD produced significantly fewer famous names in the total time allowed than the HCs, and this difference was also found in the first and the second time interval. In the famous people naming task, the performance of the SCD group was significantly lower than that of the HC group only in the more recent period of fame. Overall, these results suggest that retrieving the names of famous people was more difficult for people with SCD than for people without cognitive complaints. They also suggest that famous people verbal fluency and naming tasks could be useful in detecting cognitive decline at the preclinical stage of AD.

Innovative Multivariable Model Combining MRI Radiomics and Plasma Indexes Predicts Alzheimer's Disease Conversion: Evidence from a 2-Cohort Longitudinal Study

To explore the complementary relationship between magnetic resonance imaging (MRI) radiomic and plasma biomarkers in the early diagnosis and conversion prediction of Alzheimer's disease (AD), our study aims to develop an innovative multivariable prediction model that integrates those two for predicting conversion results in AD. This longitudinal multicentric cohort study included 2 independent cohorts: the Sino Longitudinal Study on Cognitive Decline (SILCODE) project and the Alzheimer Disease Neuroimaging Initiative (ADNI). We collected comprehensive assessments, MRI, plasma samples, and amyloid positron emission tomography data. A multivariable logistic regression analysis was applied to combine plasma and MRI radiomics biomarkers and generate a new composite indicator. The optimal model's performance and generalizability were assessed across populations in 2 cross-racial cohorts. A total of 897 subjects were included, including 635 from the SILCODE cohort (mean [SD] age, 64.93 [6.78] years; 343 [63%] female) and 262 from the ADNI cohort (mean [SD] age, 73.96 [7.06] years; 140 [53%] female). The area under the receiver operating characteristic curve of the optimal model was 0.9414 and 0.8979 in the training and validation dataset, respectively. A calibration analysis displayed excellent consistency between the prognosis and actual observation. The findings of the present study provide a valuable diagnostic tool for identifying at-risk individuals for AD and highlight the pivotal role of the radiomic biomarker. Importantly, built upon data-driven analyses commonly seen in previous radiomics studies, our research delves into AD pathology to further elucidate the underlying reasons behind the robust predictive performance of the MRI radiomic predictor.

Multimodal Approach to Neurocognitive Function in People Living with HIV in the cART Era: A Comprehensive Review

Combination antiretroviral treatment (cART) has revolutionized the management of human immunodeficiency virus (HIV) and has markedly improved the disease burden and life expectancy of people living with HIV. HIV enters the central nervous system (CNS) early in the course of infection, establishes latency, and produces a pro-inflammatory milieu that may affect cognitive functions, even in the cART era. Whereas severe forms of neurocognitive impairment (NCI) such as HIV-associated dementia have declined over the last decades, milder forms have become more prevalent, are commonly multifactorial, and are associated with comorbidity burdens, mental health, cART neurotoxicity, and ageing. Since 2007, the Frascati criteria have been used to characterize and classify HIV-associated neurocognitive disorders (HAND) into three stages, namely asymptomatic neurocognitive impairment (ANI), mild neurocognitive disorder (MND), and HIV-associated dementia (HAD). These criteria are based on a comprehensive neuropsychological assessment that presupposes the availability of validated, demographically adjusted, and normative population data. Novel neuroimaging modalities and biomarkers have been proposed in order to complement NCI assessments, elucidate neuropathogenic mechanisms, and support HIV-associated NCI diagnosis, monitoring, and prognosis. By integrating neuropsychological assessments with biomarkers and neuroimaging into a holistic care approach, clinicians can enhance diagnostic accuracy, prognosis, and patient outcomes. This review interrogates the value of these modes of assessment and proposes a unified approach to NCI diagnosis.

What is Alzheimer's disease? An analysis of nosological perspectives from the 20th and 21st centuries

BACKGROUND

Recent US proposals suggest defining Alzheimer's disease (AD) based on β-amyloidosis alone. This sparked debates that echoed historical ones about the significance of brain lesions and clinical phenotype.

METHODS

This review covers debates on AD nosology through three key periods: AD's discovery in German-speaking countries in the early 20th century, its redefinition in Anglo-Saxon countries in the 1960s-1980s, and current debates on the biological or clinicobiological definitions of AD. Key players' opinions are focused on.

RESULTS

At the beginning of the 20th century, AD was defined as a clinicopathological entity. Debates arose around the pathological anchor, which included extended neurofibrillary tangles versus neuritic plaques (Alzheimer vs. Fischer) and its association with senile dementia (Kraepelin). In the 1960s-1980s, the debate shifted towards whether AD could be diagnosed using qualitative or quantitative neuropathological features and whether it was a unique process (Terry and Katzman) or had subtypes (Roth). The current definition proposed by the US Alzheimer's Association is based purely on biological β-amyloid abnormalities and represents a double break: from the historical clinicopathological definition of AD and from the historical emphasis on tau or combined tau and β-amyloid high levels of pathology. Conversely, the clinicobiological proposal of the International Working Group remains aligned with historical concepts of AD.

CONCLUSIONS

This historical perspective illustrates the unresolved questions surrounding AD pathogenesis, role of lesions, and the clinical phenotype, especially for sporadic cases. The intense nosological debates throughout the history of AD also illustrate the diversity of theoretical frameworks for defining disease in medicine.

Molecular Biomarkers of Neurodegenerative Disorders: A Practical Guide to Their Appropriate Use and Interpretation in Clinical Practice

Neurodegenerative disorders (NDs) represent a group of different diseases characterized by the progressive degeneration and death of the nervous system's cells. The diagnosis is challenging, especially in the early stages, due to no specific clinical signs and symptoms. In this context, laboratory medicine could support clinicians in detecting and differentiating NDs. Indeed, biomarkers could indicate the pathological mechanisms underpinning NDs. The ideal biofluid for detecting the biomarkers of NDs is cerebrospinal fluid (CSF), which has limitations, hampering its widespread use in clinical practice. However, intensive efforts are underway to introduce high-sensitivity analytical methods to detect ND biomarkers in alternative nonivasive biofluid, such as blood or saliva. This study presents an overview of the ND molecular biomarkers currently used in clinical practice. For some diseases, such as Alzheimer's disease or multiple sclerosis, biomarkers are well established and recommended by guidelines. However, for most NDs, intensive research is ongoing to identify reliable and specific biomarkers, and no consensus has yet been achieved.

Risk of conversion to mild cognitive impairment or dementia among subjects with amyloid and tau pathology: a systematic review and meta-analysis

BACKGROUND

Measurement of beta-amyloid (Aβ) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination.

METHODS

A systematic search of prospective and retrospective studies investigating the association of Aβ and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature.

RESULTS

A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled (n= 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aβ42 or Aβ42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aβ exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]).

CONCLUSIONS

Identifying Aβ-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aβ, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aβ decreases with age.

TRIAL REGISTRATION

The study was registered in PROSPERO (ID: CRD42021288100).

CSF biomarkers of immune activation and Alzheimer's disease for predicting cognitive impairment risk in the elderly

The immune system substantially influences age-related cognitive decline and Alzheimer's disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 (N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aβ42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aβ42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aβ42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.

Uncovering the distinct macro-scale anatomy of dysexecutive and behavioural degenerative diseases

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases.

Panax notoginseng saponins prevent dementia and oxidative stress in brains of SAMP8 mice by enhancing mitophagy

BACKGROUND

Mitochondrial dysfunction is one of the distinctive features of neurons in patients with Alzheimer's disease (AD). Intraneuronal autophagosomes selectively phagocytose and degrade the damaged mitochondria, mitigating neuronal damage in AD. Panax notoginseng saponins (PNS) can effectively reduce oxidative stress and mitochondrial damage in the brain of animals with AD, but their exact mechanism of action is unknown.

METHODS

Senescence-accelerated mouse prone 8 (SAMP8) mice with age-related AD were treated with PNS for 8 weeks. The effects of PNS on learning and memory abilities, cerebral oxidative stress status, and hippocampus ultrastructure of mice were observed. Moreover, changes of the PTEN-induced putative kinase 1 (PINK1)-Parkin, which regulates ubiquitin-dependent mitophagy, and the recruit of downstream autophagy receptors were investigated.

RESULTS

PNS attenuated cognitive dysfunction in SAMP8 mice in the Morris water maze test. PNS also enhanced glutathione peroxidase and superoxide dismutase activities, and increased glutathione levels by 25.92% and 45.55% while inhibiting 8-hydroxydeoxyguanosine by 27.74% and the malondialdehyde production by 34.02% in the brains of SAMP8 mice. Our observation revealed the promotion of mitophagy, which was accompanied by an increase in microtubule-associated protein 1 light chain 3 (LC3) mRNA and 70.00% increase of LC3-II/I protein ratio in the brain tissues of PNS-treated mice. PNS treatment increased Parkin mRNA and protein expression by 62.80% and 43.80%, while increasing the mRNA transcription and protein expression of mitophagic receptors such as optineurin, and nuclear dot protein 52.

CONCLUSION

PNS enhanced the PINK1/Parkin pathway and facilitated mitophagy in the hippocampus, thereby preventing cerebral oxidative stress in SAMP8 mice. This may be a mechanism contributing to the cognition-improvement effect of PNS.

Long-acting exenatide does not prevent cognitive decline in mild cognitive impairment: a proof-of-concept clinical trial

PURPOSE

According to preclinical evidence, GLP-1 receptor may be an actionable target in neurodegenerative disorders, including Alzheimer's disease (AD). Previous clinical trials of GLP-1 receptor agonists were conducted in patients with early AD, yielding mixed results. The aim was to assess in a proof-of-concept study whether slow-release exenatide, a long-acting GLP-1 agonist, can benefit the cognitive performance of people with mild cognitive impairment (MCI).

METHODS

Thirty-two (16 females) patients were randomized to either slow-release exenatide (n = 17; 2 mg s.c. once a week) or no treatment (n = 15) for 32 weeks. The primary endpoint was the change in ADAS-Cog11 cognitive test score at 32 weeks vs baseline. Secondary endpoints herein reported included additional cognitive tests and plasma readouts of GLP-1 receptor engagement. Statistical analysis was conducted by intention to treat.

RESULTS

No significant between-group effects of exenatide on ADAS-Cog11 score (p = 0.17) were detected. A gender interaction with treatment was observed (p = 0.04), due to worsening of the ADAS-Cog11 score in women randomized to exenatide (p = 0.018), after correction for age, scholar level, dysglycemia, and ADAS-Cog score baseline value. Fasting plasma glucose (p = 0.02) and body weight (p = 0.03) decreased in patients randomized to exenatide.

CONCLUSION

In patients with MCI, a 32-week trial with slow-release exenatide had no beneficial effect on cognitive performance.

TRIAL REGISTRATION NUMBER

NCT03881371, registered on 21 July, 2016.

Vascular risk burden is a key player in the early progression of Alzheimer's disease

Understanding whether vascular risk factors (VRFs) synergistically potentiate Alzheimer's disease (AD) progression is important in the context of emerging treatments for preclinical AD. In a group of 503 cognitively unimpaired individuals, we tested whether VRF burden interacts with AD pathophysiology to accelerate neurodegeneration and cognitive decline. Baseline VRF burden was calculated considering medical data and AD pathophysiology was assessed based on cerebrospinal fluid (CSF) amyloid-β1-42 (Aβ1-42) and tau phosphorylated at threonine 181 (p-tau181). Neurodegeneration was assessed with plasma neurofilament light (NfL) and global cognition with the modified version of the Preclinical Alzheimer's Cognitive Composite. The mean (SD) age of participants was 72.9 (6.1) years, and 220 (43.7%) were men. Linear mixed-effects models revealed that an elevated VRF burden synergistically interacted with AD pathophysiology to drive longitudinal plasma NfL increase and cognitive decline. Additionally, VRF burden was not associated with CSF Aβ1-42 or p-tau181 changes over time. Our results suggest that VRF burden and AD pathophysiology are independent processes; however, they synergistically lead to neurodegeneration and cognitive deterioration. In preclinical stages, the combination of therapies targeting VRFs and AD pathophysiology might potentiate treatment outcomes.

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.

A deeply supervised adaptable neural network for diagnosis and classification of Alzheimer's severity using multitask feature extraction

Alzheimer's disease is the most prevalent form of dementia, which is a gradual condition that begins with mild memory loss and progresses to difficulties communicating and responding to the environment. Recent advancements in neuroimaging techniques have resulted in large-scale multimodal neuroimaging data, leading to an increased interest in using deep learning for the early diagnosis and automated classification of Alzheimer's disease. This study uses machine learning (ML) methods to determine the severity level of Alzheimer's disease using MRI images, where the dataset consists of four levels of severity. A hybrid of 12 feature extraction methods is used to diagnose Alzheimer's disease severity, and six traditional machine learning methods are applied, including decision tree, K-nearest neighbor, linear discrimination analysis, Naïve Bayes, support vector machine, and ensemble learning methods. During training, optimization is performed to obtain the best solution for each classifier. Additionally, a CNN model is trained using a machine learning system algorithm to identify specific patterns. The accuracy of the Naïve Bayes, Support Vector Machines, K-nearest neighbor, Linear discrimination classifier, Decision tree, Ensembled learning, and presented CNN architecture are 67.5%, 72.3%, 74.5%, 65.6%, 62.4%, 73.8% and, 95.3%, respectively. Based on the results, the presented CNN approach outperforms other traditional machine learning methods to find Alzheimer severity.

The role of 123-I-MIBG cardiac scintigraphy in the differential diagnosis between dementia with Lewy bodies and Alzheimer's disease

Although detailed diagnostic guidelines are available, differentiating dementia with Lewy bodies from Alzheimer's disease is often difficult. 123-I-MIBG cardiac scintigraphy is one of the tools which have been proposed for the diagnostic procedure. The present review is aimed at evaluating the available literature about this topic. Studies assessing the use of this technique to differentiate between the two diseases have been examined and reported. Overall, despite a certain study-to-study variability, the available literature suggests that 123-I-MIBG cardiac scintigraphy is an effective tool in differentiating between the two diseases, with high sensitivity and specificity values. Although the large-scale application of this technique is limited by possible interactions with specific medications and comorbidities, the reported studies are supportive for the usefulness of this technique in clinical practice.

The Role of Catecholamines in the Pathogenesis of Diseases and the Modified Electrodes for Electrochemical Detection of Catecholamines: A Review

Catecholamines (CAs), which include adrenaline, noradrenaline, and dopamine, are neurotransmitters and hormones that critically regulate the cardiovascular system, metabolism, and stress response in the human body. The abnormal levels of these molecules can lead to the development of various diseases, including pheochromocytoma and paragangliomas, Alzheimer's disease, and Takotsubo cardiomyopathy. Due to their low cost, high sensitivity, flexible detection strategies, ease of integration, and miniaturization, electrochemical techniques have been extensively employed in the detection of CAs, surpassing traditional analytical methods. Electrochemical detection of CAs in real samples is challenging due to the tendency of poisoning electrode. Chemically modified electrodes have been widely used to solve the problems of poor sensitivity and selectivity faced by bare electrodes. There are a few articles that provide an overview of electrochemical detection and efficient enrichment of CAs, but there is a dearth of updates on the role of CAs in the pathogenesis of diseases. Additionally, there is still a lack of systematic synthesis with a focus on modified electrodes for electrochemical detection. Thus, this review provides a summary of the recent clinical pathogenesis of CAs and the modified electrodes for electrochemical detection of CAs published between 2017 and 2022. Moreover, challenges and future perspectives are also highlighted. This work is expected to provide useful guidance to researchers entering this interdisciplinary field, promoting further development of CAs pathogenesis, and developing more novel chemically modified electrodes for the detection of CAs.

Viral Infections, Are They a Trigger and Risk Factor of Alzheimer's Disease?

Alzheimer's Disease (AD), a progressive and debilitating condition, is reported to be the most common type of dementia, with at least 55 million people believed to be currently affected. Many causation hypotheses of AD exist, yet the intriguing link between viral infection and its possible contribution to the known etiology of AD has become an attractive focal point of research for the field and a challenging study task. In this review, we will explore the historical perspective and milestones that led the field to investigate the viral connection to AD. Specifically, several viruses such as Herpes Simplex Virus 1 (HSV-1), Zika virus (ZIKV), and severe cute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with several others mentioned, include the various viruses presently considered within the field. We delve into the strong evidence implicating these viruses in the development of AD such as the lytic replication and axonal transport of HSV-1, the various mechanisms of ZIKV neurotropism through the human protein Musashi-1 (MSI1), and the spread of SARS-CoV-2 through the transfer of the virus through the BBB endothelial cells to glial cells and then to neurons via transsynaptic transfer. We will also explore beyond these mere associations by carefully analyzing the potential mechanisms by which these viruses may contribute to AD pathology. This includes but is not limited to direct neuronal infections, the dysregulation of immune responses, and the impact on protein processing (Aβ42 and hyperphosphorylated tau). Controversies and challenges of the virus-AD relationship emerge as we tease out these potential mechanisms. Looking forward, we emphasize future directions, such as distinct questions and proposed experimentations to explore, that the field should take to tackle the remaining unanswered questions and the glaring research gaps that persist. Overall, this review aims to provide a comprehensive survey of the past, present, and future of the potential link between viral infections and their association with AD development while encouraging further discussion.

Blood levels of glial fibrillary acidic protein for predicting clinical progression to Alzheimer's disease in adults without dementia: a systematic review and meta-analysis protocol

BACKGROUND

There is urgent clinical need to identify reliable prognostic biomarkers that predict the progression of dementia symptoms in individuals with early-phase Alzheimer's disease (AD) especially given the research on and predicted applications of amyloid-beta (Aβ)-directed immunotherapies to remove Aβ from the brain. Cross-sectional studies have reported higher levels of cerebrospinal fluid and blood glial fibrillary acidic protein (GFAP) in individuals with AD-associated dementia than in cognitively unimpaired individuals. Further, recent longitudinal studies have assessed the prognostic potential of baseline blood GFAP levels as a predictor of future cognitive decline in cognitively unimpaired individuals and in those with mild cognitive impairment (MCI) due to AD. In this systematic review and meta-analysis, we propose analyzing longitudinal studies on blood GFAP levels to predict future cognitive decline.

METHODS

This study will include prospective and retrospective cohort studies that assessed blood GFAP levels as a prognostic factor and any prediction models that incorporated blood GFAP levels in cognitively unimpaired individuals or those with MCI. The primary outcome will be conversion to MCI or AD in cognitively unimpaired individuals or conversion to AD in individuals with MCI. Articles from PubMed and Embase will be extracted up to December 31, 2023, without language restrictions. An independent dual screening of abstracts and potentially eligible full-text reports will be conducted. Data will be dual-extracted using the CHeck list for critical appraisal, data extraction for systematic Reviews of prediction Modeling Studies (CHARMS)-prognostic factor, and CHARMS checklists, and we will dual-rate the risk of bias and applicability using the Quality In Prognosis Studies and Prediction Study Risk-of-Bias Assessment tools. We will qualitatively synthesize the study data, participants, index biomarkers, predictive model characteristics, and clinical outcomes. If appropriate, random-effects meta-analyses will be performed to obtain summary estimates. Finally, we will assess the body of evidence using the Grading of Recommendation, Assessment, Development, and Evaluation Approach.

DISCUSSION

This systematic review and meta-analysis will comprehensively evaluate and synthesize existing evidence on blood GFAP levels for prognosticating presymptomatic individuals and those with MCI to help advance risk-stratified treatment strategies for early-phase AD.

TRIAL REGISTRATION

PROSPERO CRD42023481200.

Mitochondrial metabolism in neural stem cells and implications for neurodevelopmental and neurodegenerative diseases

Mitochondria are cytoplasmic organelles having a fundamental role in the regulation of neural stem cell (NSC) fate during neural development and maintenance.During embryonic and adult neurogenesis, NSCs undergo a metabolic switch from glycolytic to oxidative phosphorylation with a rise in mitochondrial DNA (mtDNA) content, changes in mitochondria shape and size, and a physiological augmentation of mitochondrial reactive oxygen species which together drive NSCs to proliferate and differentiate. Genetic and epigenetic modifications of proteins involved in cellular differentiation (Mechanistic Target of Rapamycin), proliferation (Wingless-type), and hypoxia (Mitogen-activated protein kinase)-and all connected by the common key regulatory factor Hypoxia Inducible Factor-1A-are deemed to be responsible for the metabolic shift and, consequently, NSC fate in physiological and pathological conditions.Both primary mitochondrial dysfunction due to mutations in nuclear DNA or mtDNA or secondary mitochondrial dysfunction in oxidative phosphorylation (OXPHOS) metabolism, mitochondrial dynamics, and organelle interplay pathways can contribute to the development of neurodevelopmental or progressive neurodegenerative disorders.This review analyses the physiology and pathology of neural development starting from the available in vitro and in vivo models and highlights the current knowledge concerning key mitochondrial pathways involved in this process.

Proximity extension assay-based proteomics studies in neurodegenerative disorders and multiple sclerosis

Neurodegenerative diseases impact the structure and operation of the nervous system, causing progressive and irreparable harm. Efforts for distinguishing neurodegenerative diseases in their early stages are continuing. Despite several biomarkers being identified, there is always search for more accurate and abundant ones. Additionally, it can be difficult to pinpoint the precise neurodegenerative disorder affecting a patient as the symptoms of these conditions frequently overlap. Numerous studies have shown that pathological changes occur years before clinical signs appear. Therefore, it is crucial to discover blood-based biomarkers for neurodegenerative diseases for easier and earlier diagnosis. Proximity extension assay is a unique proteomics method that uses antibodies linked to oligonucleotides for quantifying proteins with real-time PCR. Proximity extension assay can identify even low-quantity proteins using a small volume of specimens with increased sensitivity compared to conventional methods. In this article, we reviewed the employment of proximity extension assay technology to detect biomarkers or protein profiles for several neurodegenerative diseases.

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.

Rapid Discovery of Aβ42 Fibril Disintegrators from Ganoderma lucidum via Ligand Fishing and Their Neuroprotective Effects on Alzheimer's Disease

An amyloid-β (Aβ) fibril is a vital pathogenic factor of Alzheimer's disease (AD). Aβ fibril disintegrators possess great potential to be developed into novel anti-AD agents. Here, a ligand fishing method was employed to rapidly discover Aβ42 fibril disintegrators from Ganoderma lucidum using Aβ42 fibril-immobilized magnetic beads, which led to the isolation of six Aβ42 fibril disintegrators including ganodermanontriol, ganoderic acid DM, ganoderiol F, ganoderol B, ganodermenonol, and ergosterol. Neuroprotective evaluation in vitro exhibited that these Aβ42 fibril disintegrators could significantly mitigate Aβ42-induced neurotoxicity. Among these six disintegrators, ergosterol and ganoderic acid DM with stronger protecting activity were further selected to evaluate their neuroprotective effect on AD in vivo. Results showed that ergosterol and ganoderic acid DM could significantly alleviate Aβ42-induced cognitive dysfunction and hippocampus neuron loss in vivo. Moreover, ergosterol and ganoderic acid DM could significantly inhibit Aβ42-induced neuron apoptosis and Nrf2-mediated neuron oxidative stress in vitro and in vivo.

Prognostic and Predictive Factors in Early Alzheimer's Disease: A Systematic Review

Background

Alzheimer's disease (AD) causes progressive decline of cognition and function. There is a lack of systematic literature reviews on prognostic and predictive factors in its early clinical stages (eAD), i.e., mild cognitive impairment due to AD and mild AD dementia.

Objective

To identify prognostic factors affecting eAD progression and predictive factors for treatment efficacy and safety of approved and/or under late-stage development disease-modifying treatments.

Methods

Databases were searched (August 2022) for studies reporting prognostic factors associated with eAD progression and predictive factors for treatment response. The Quality in Prognostic Factor Studies tool or the Cochrane risk of bias tool were used to assess risk of bias. Two reviewers independently screened the records. A single reviewer performed data extraction and quality assessment. A second performed a 20% check. Content experts reviewed and interpreted the data collected.

Results

Sixty-one studies were included. Self-reporting, diagnosis definition, and missing data led to high risk of bias. Population size ranged from 110 to 11,451. Analyses found data indicating that older age was and depression may be associated with progression. Greater baseline cognitive impairment was associated with progression. APOE4 may be a prognostic factor, a predictive factor for treatment efficacy and predicts an adverse response (ARIA). Elevated biomarkers (CSF/plasma p-tau, CSF t-tau, and plasma neurofilament light) were associated with disease progression.

Conclusions

Age was the strongest risk factor for progression. Biomarkers were associated with progression, supporting their use in trial selection and aiding diagnosis. Baseline cognitive impairment was a prognostic factor. APOE4 predicted ARIA, aligning with emerging evidence and relevant to treatment initiation/monitoring.

A single-domain antibody for the detection of pathological Tau protein in the early stages of oligomerization

BACKGROUND

Soluble oligomeric forms of Tau protein have emerged as crucial players in the propagation of Tau pathology in Alzheimer's disease (AD). Our objective is to introduce a single-domain antibody (sdAb) named 2C5 as a novel radiotracer for the efficient detection and longitudinal monitoring of oligomeric Tau species in the human brain.

METHODS

The development and production of 2C5 involved llama immunization with the largest human Tau isoform oligomers of different maturation states. Subsequently, 2C5 underwent comprehensive in vitro characterization for affinity and specificity via Enzyme-Linked Immunosorbent Assay and immunohistochemistry on human brain slices. Technetium-99m was employed to radiolabel 2C5, followed by its administration to healthy mice for biodistribution analysis.

RESULTS

2C5 exhibited robust binding affinity towards Tau oligomers (Kd = 6.280 nM ± 0.557) and to Tau fibers (Kd = 5.024 nM ± 0.453), with relatively weaker binding observed for native Tau protein (Kd = 1791 nM ± 8.714) and amyloid peptide (Kd > 10,000 nM). Remarkably, this SdAb facilitated immuno-histological labeling of pathological forms of Tau in neurons and neuritic plaques, yielding a high-contrast outcome in AD patients, closely mirroring the performance of reference antibodies AT8 and T22. Furthermore, 2C5 SdAb was successfully radiolabeled with 99mTc, preserving stability for up to 6 h post-radiolabeling (radiochemical purity > 93%). However, following intravenous injection into healthy mice, the predominant uptake occurred in kidneys, amounting to 115.32 ± 3.67, 97.70 ± 43.14 and 168.20 ± 34.52% of injected dose per gram (% ID/g) at 5, 10 and 45 min respectively. Conversely, brain uptake remained minimal at all measured time points, registering at 0.17 ± 0.03, 0.12 ± 0.07 and 0.02 ± 0.01% ID/g at 5, 10 and 45 min post-injection respectively.

CONCLUSION

2C5 demonstrates excellent affinity and specificity for pathological Tau oligomers, particularly in their early stages of oligomerization. However, the current limitation of insufficient blood-brain barrier penetration necessitates further modifications before considering its application in nuclear medicine imaging for humans.

Designed Directional Growth of Ti-Metal-Organic Frameworks for Decoding Alzheimer's Disease-Specific Exosome Metabolites

Exosomes, a growing focus for liquid biopsies, contain diverse molecular cargos. In particular, exosome metabolites with valuable information have exhibited great potential for improving the efficiency of liquid biopsies for addressing complex medical conditions. In this work, we design the directional growth of Ti-metal-organic frameworks on polar-functionalized magnetic particles. This design facilitates the rapid synergistic capture of exosomes with the assistance of an external magnetic field and additionally synergistically enhances the ionization of their metabolites during mass spectrometry detection. Benefiting from this dual synergistic effect, we identified three high-performance exosome metabolites through the differential comparison of a large number of serum samples from individuals with Alzheimer's disease (AD) and normal cognition. Notably, the accuracy of AD identification ranges from 93.18 to 100% using a single exosome metabolite and reaches a flawless 100% with three metabolites. These findings emphasize the transformative potential of this work to enhance the precision and reliability of AD diagnosis, ushering in a new era of improved diagnostic accuracy.

Characterizing amyloid protein conformation with a multi-resonant metasurface based biosensor in the infrared window

Misfolding of amyloid protein will cause neurodegeneration and trigger conformational disease. The lack of an effective detection approach is a brake on unveiling the mechanism of protein misfolding. We theoretically proposed a novel metasurface-based biosensor for characterizing the protein's conformation. The coupling complementary split ring resonator (cSRR) was engineered to manipulate incident waves in the near-infrared (NIR) and mid-infrared (MIR) windows at the same sensing surface. The cSRRs had the advantages of intensifying the electric field and sharpening the resonance profile, resulting in a highly qualified biosensing performance. In the NIR window, the biolayer's refractive index and thickness change were detected by the dual-wavelength, which resolved into an optogeometrical parameter of the amyloid biolayer. In the MIR window, the resonant wave specifically triggered the rotation-vibration transition of amyloid protein molecules with different conformations, which was shown as the unique Amide I and II bands in the fingerprint spectrum. Thus, our proposed biosensor presented sensitive detection of biolayer and specific identification of constituent molecules. It is helpful to interpret the protein's misfolding behavior on the molecular level by associating the biolayer's structure and the constituent molecule's conformational change.