Diagnosis of Alzheimer's disease utilizing amyloid and tau as fluid biomarkers

Fluorescence-Based Monitoring of Early-Stage Aggregation of Amyloid-β, Amylin Peptide, Tau, and α-Synuclein Proteins

Early-stage aggregates of amyloid-forming proteins, specifically soluble oligomers, are implicated in neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and Huntington's disease. Protein aggregation is typically monitored by fluorescence using the amyloid-binding fluorophore thioflavin T (ThT). Thioflavin T interacts, however, preferentially with fibrillar amyloid structures rather than with soluble, early-stage aggregates. In contrast, the two fluorophores, aminonaphthalene 2-cyanoacrylate-spiropyran (AN-SP) and triazole-containing boron-dipyrromethene (taBODIPY), were reported to bind preferentially to early-stage aggregates of amyloidogenic proteins. The present study compares ThT with AN-SP and taBODIPY with regard to their ability to monitor early stages of aggregation of four different amyloid-forming proteins, including amyloid-β (Aβ), tau protein, amylin, and α-synuclein. The results show that the three fluorophores vary in their suitability to monitor the early aggregation of different amyloid-forming proteins. For instance, in the presence of Aβ and amylin, the fluorescence intensity of AN-SP increased at an earlier stage of aggregation than the fluorescence of ThT, albeit with only a small fluorescence increase in the case of AN-SP. In contrast, in the presence of tau and amylin, the fluorescence intensity of taBODIPY increased at an earlier stage of aggregation than the fluorescence of ThT. Finally, α-synuclein aggregation could only be monitored by ThT fluorescence; neither AN-SP nor taBODIPY showed a significant increase in fluorescence over the course of aggregation of α-synuclein. These results demonstrate the ability of AN-SP and taBODIPY to monitor the formation of early-stage aggregates from specific amyloid-forming proteins at an early stage of aggregation, although moderate increases in fluorescence intensity, relatively large uncertainties in fluorescence values, and limited solubility of both fluorophores limit their usefulness for some amyloid proteins. The capability to monitor early aggregation of some amyloid proteins, such as amylin, might accelerate the discovery of aggregation inhibitors to minimize the formation of toxic oligomeric species for potential therapeutic use.

Leptin bioavailability and markers of brain atrophy and vascular injury in the middle age

INTRODUCTION

We investigated the associations of leptin markers with cognitive function and magnetic resonance imaging (MRI) measures of brain atrophy and vascular injury in healthy middle-aged adults.

METHODS

We included 2262 cognitively healthy participants from the Framingham Heart Study with neuropsychological evaluation; of these, 2028 also had available brain MRI. Concentrations of leptin, soluble leptin receptor (sOB-R), and their ratio (free leptin index [FLI]), indicating leptin bioavailability, were measured using enzyme-linked immunosorbent assays. Cognitive and MRI measures were derived using standardized protocols.

RESULTS

Higher sOB-R was associated with lower fractional anisotropy (FA, β = -0.114 ± 0.02, p < 0.001), and higher free water (FW, β = 0.091 ± 0.022, p < 0.001) and peak-width skeletonized mean diffusivity (PSMD, β = 0.078 ± 0.021, p < 0.001). Correspondingly, higher FLI was associated with higher FA (β = 0.115 ± 0.027, p < 0.001) and lower FW (β = -0.096 ± 0.029, p = 0.001) and PSMD (β = -0.085 ± 0.028, p = 0.002).

DISCUSSION

Higher leptin bioavailability was associated with better white matter (WM) integrity in healthy middle-aged adults, supporting the putative neuroprotective role of leptin in late-life dementia risk.

HIGHLIGHTS

Higher leptin bioavailability was related to better preservation of white matter microstructure. Higher leptin bioavailability during midlife might confer protection against dementia. Potential benefits might be even stronger for individuals with visceral obesity. DTI measures might be sensitive surrogate markers of subclinical neuropathology.

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

BACKGROUND

Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI).

OBJECTIVE

This study aimed to use data collected from fitness trackers to predict MCI status.

METHODS

In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status.

RESULTS

Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time.

CONCLUSIONS

Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

Radionuclide Imaging of the Neuroanatomical and Neurochemical Substrate of Cognitive Decline in Parkinson's Disease

Cognitive impairment is a frequent manifestation of Parkinson's disease (PD), resulting in decrease in patients' quality of life and increased societal and economic burden. However, cognitive decline in PD is highly heterogenous and the mechanisms are poorly understood. Radionuclide imaging techniques like positron emission tomography (PET) and single photon emission computed tomography (SPECT) have been used to investigate the neurochemical and neuroanatomical substrate of cognitive decline in PD. These techniques allow the assessment of different neurotransmitter systems, changes in brain glucose metabolism, proteinopathy, and neuroinflammation in vivo in PD patients. Here, we review current radionuclide imaging research on cognitive deficit in PD with a focus on predicting accelerating cognitive decline. This research could assist in the development of prognostic biomarkers for patient stratification and have utility in the development of ameliorative or disease-modifying therapies targeting cognitive deficit in PD.

Alzheimer's disease and its treatment-yesterday, today, and tomorrow

Alois Alzheimer described the first patient with Alzheimer's disease (AD) in 1907 and today AD is the most frequently diagnosed of dementias. AD is a multi-factorial neurodegenerative disorder with familial, life style and comorbidity influences impacting a global population of more than 47 million with a projected escalation by 2050 to exceed 130 million. In the USA the AD demographic encompasses approximately six million individuals, expected to increase to surpass 13 million by 2050, and the antecedent phase of AD, recognized as mild cognitive impairment (MCI), involves nearly 12 million individuals. The economic outlay for the management of AD and AD-related cognitive decline is estimated at approximately 355 billion USD. In addition, the intensifying prevalence of AD cases in countries with modest to intermediate income countries further enhances the urgency for more therapeutically and cost-effective treatments and for improving the quality of life for patients and their families. This narrative review evaluates the pathophysiological basis of AD with an initial focus on the therapeutic efficacy and limitations of the existing drugs that provide symptomatic relief: acetylcholinesterase inhibitors (AChEI) donepezil, galantamine, rivastigmine, and the N-methyl-D-aspartate receptor (NMDA) receptor allosteric modulator, memantine. The hypothesis that amyloid-β (Aβ) and tau are appropriate targets for drugs and have the potential to halt the progress of AD is critically analyzed with a particular focus on clinical trial data with anti-Aβ monoclonal antibodies (MABs), namely, aducanumab, lecanemab and donanemab. This review challenges the dogma that targeting Aβ will benefit the majority of subjects with AD that the anti-Aβ MABs are unlikely to be the "magic bullet". A comparison of the benefits and disadvantages of the different classes of drugs forms the basis for determining new directions for research and alternative drug targets that are undergoing pre-clinical and clinical assessments. In addition, we discuss and stress the importance of the treatment of the co-morbidities, including hypertension, diabetes, obesity and depression that are known to increase the risk of developing AD.

Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease

Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) analysis of blood-based biomarkers is a convenient alternative to rapidly obtain spectral information from biofluids. However, despite the rapid acquisition of spectral information from biofluids, it is challenging to distinguish spectral features of biomarkers due to interference from biofluidic components. Here, we introduce a deep learning-assisted, SERS-based platform for separate analysis of blood-based amyloid β (1-42) and metabolites, enabling the diagnosis of Alzheimer's disease. SERS substrates consisting of Au nanowire arrays are fabricated and functionalized in two characteristic ways to compare the validity of different Alzheimer's disease biomarkers measured on our SERS system. The 6E10 antibody is immobilized for the capture of amyloid β (1-42) and analysis of its oligomerization process, while various self-assembled monolayers are attached for different dipole interactions with blood-based metabolites. Ultimately, SERS spectra of blood plasma of Alzheimer's disease patients and human controls are measured on the substrates and classified via advanced deep learning techniques that automatically extract informative features to learn generalizable representations. Accuracies up to 99.5% are achieved for metabolite-based analyses, which are verified with an explainable artificial intelligence technique that identifies key spectral features used for classification and for deducing significant biomarkers.

Amyloid-β and Phosphorylated Tau are the Key Biomarkers and Predictors of Alzheimer's Disease

Alzheimer's disease (AD) is a age-related neurodegenerative disease and is a major public health concern both in Texas, US and Worldwide. This neurodegenerative disease is mainly characterized by amyloid-beta (Aβ) and phosphorylated Tau (p-Tau) accumulation in the brains of patients with AD and increasing evidence suggests that these are key biomarkers in AD. Both Aβ and p-tau can be detected through various imaging techniques (such as positron emission tomography, PET) and cerebrospinal fluid (CSF) analysis. The presence of these biomarkers in individuals, who are asymptomatic or have mild cognitive impairment can indicate an increased risk of developing AD in the future. Furthermore, the combination of Aβ and p-tau biomarkers is often used for more accurate diagnosis and prediction of AD progression. Along with AD being a neurodegenerative disease, it is associated with other chronic conditions such as cardiovascular disease, obesity, depression, and diabetes because studies have shown that these comorbid conditions make people more vulnerable to AD. In the first part of this review, we discuss that biofluid-based biomarkers such as Aβ, p-Tau in cerebrospinal fluid (CSF) and Aβ & p-Tau in plasma could be used as an alternative sensitive technique to diagnose AD. In the second part, we discuss the underlying molecular mechanisms of chronic conditions linked with AD and how they affect the patients in clinical care.

Salivary biomarkers: The early diagnosis of Alzheimer's disease

The precise identification of Alzheimer's disease and other prevalent neurodegenerative diseases remains a difficult issue that requires the development of early detection of the disease and inexpensive biomarkers that can replace the present cerebrospinal fluid and imaging biomarkers. Blood biomarkers, such as amyloid and neurofilament light, have been emphasized as an important and practical tool in a testing or examination procedure thanks to advancements in ultra-sensitive detection techniques. Although saliva is not currently being researched for neurodegenerative diseases, it is an important source of biomarkers that can be used for the identification of diseases and has some advantages over other biofluids. While this may be true for most people, getting saliva from elderly people presents some significant challenges. In this overview, we will first discuss how saliva is created and how aging-related illnesses may affect the amount and kind of saliva produced. The findings support the use of salivary amyloid protein, tau species, and novel biomarkers in the diagnosis of Alzheimer's disease.

"Cognitive" Criteria in Older Adults With Slow Gait Speed: Implications for Motoric Cognitive Risk Syndrome

BACKGROUND

Motoric cognitive risk syndrome (MCR) is a predementia condition that combines slow gait speed and subjective cognitive concerns (SCC). The SCC criterion is presently unstandardized, possibly limiting risk detection. We sought to (a) characterize SCC practices through MCR literature review; (b) investigate the ability of SCC in slow gait individuals in predicting the likelihood of cognitive impairment in a demographically diverse sample of community-dwelling, nondemented older adults.

METHODS

First, we comprehensively reviewed the MCR literature, extracting information regarding SCC measures, items, sources, and cognitive domain. Next, Einstein Aging Study (EAS) participants (N = 278, Mage = 77.22 ± 4.74, %female = 67, Meducation = 15 ± 3.61, %non-Hispanic White = 46.3) completed gait, Clinical Dementia Rating Scale (CDR), and SCC assessment at baseline and annual follow-up (Mfollow-up = 3.5). Forty-two participants met slow gait criteria at baseline. Generalized linear mixed-effects models examined baseline SCC to predict cognitive impairment on CDR over follow-up.

RESULTS

We reviewed all published MCR studies (N = 106) and documented ambiguity in SCC criteria, with a prevalent approach being use of a single self-reported memory item. In EAS, high SCC endorsement on a comprehensive, validated screen significantly affected the rate of cognitive impairment (CDR; βinteraction = 0.039, p = .018) in slow gait individuals.

CONCLUSIONS

An assessment approach that queries across numerous SCC domains was found to predict future decline in clinical dementia status in slow gait older adults. Current SCC practices in MCR, which tend to utilize a single-memory item, may not be the optimal approach. We discuss the implications of SCC criteria validation and standardization to enhance early dementia detection in MCR.

Circulating Biomarkers for Alzheimer's Disease: Unlocking the Diagnostic Potential in Low- and Middle-Income Countries, Focusing on Africa

BACKGROUND

Alzheimer's disease (AD) is emerging as a significant public health challenge in Africa, with predictions indicating a tripling in incidence by 2050. The diagnosis of AD on the African continent is notably difficult, leading to late detection that severely limits treatment options and significantly impacts the quality of life for patients and their families.

SUMMARY

This review focuses on the potential of high-sensitivity specific blood biomarkers as promising tools for improving AD diagnosis and management globally, particularly in Africa. These advances are particularly pertinent in the continent, where access to medical and technical resources is often limited.

KEY MESSAGES

Identifying precise, sensitive, and specific blood biomarkers could contribute to the biological characterization and management of AD in Africa. Such advances promise to improve patient care and pave the way for new regional opportunities in pharmaceutical research and drug trials on the continent for AD.

Advances in microfluidic chips targeting toxic aggregation proteins for neurodegenerative diseases

Neurodegenerative diseases (NDs) are characterized by nervous system damage, often influenced by genetic and aging factors. Pathological analysis frequently reveals the presence of aggregated toxic proteins. The intricate and poorly understood origins of these diseases have hindered progress in early diagnosis and drug development. The development of novel in-vitro and in-vivo models could enhance our comprehension of ND mechanisms and facilitate clinical treatment advancements. Microfluidic chips are employed to establish three-dimensional culture conditions, replicating the human ecological niche and creating a microenvironment conducive to neuronal cell survival. The incorporation of mechatronic controls unifies the chip, cells, and culture medium optimizing living conditions for the cells. This study provides a comprehensive overview of microfluidic chip applications in drug and biomarker screening for neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis. Our Lab-on-a-Chip system releases toxic proteins to simulate the pathological characteristics of neurodegenerative diseases, encompassing β-amyloid, α-synuclein, huntingtin, TAR DNA-binding protein 43, and Myelin Basic Protein. Investigating molecular and cellular interactions in vitro can enhance our understanding of disease mechanisms while minimizing harmful protein levels and can aid in screening potential therapeutic agents. We anticipate that our research will promote the utilization of microfluidic chips in both fundamental research and clinical applications for neurodegenerative diseases.

Automated Synthesis of [11C]PiB via [11CH3OTf]-as Methylating Agent for PET Imaging of β-Amyloid

AIM

Efficient synthesis of precursor from commercially available starting materials and automated radiosynthesis of [11C]PiB using commercially available dedicated [11C]- Chemistry module from the synthesized precursor.

BACKGROUND

[11C]PiB is a promising radiotracer for PET imaging of β-Amyloid, advancing Alzheimer's disease research. The availability of precursors and protocols for efficient radiolabelling foster the applications of any radiotracer. Efficient synthesis of PiB precursor was performed using anisidine and 4-nitrobenzoyl chloride as starting materials in 5 steps, having addition, substitutions, and cyclization chemical methodologies. This precursor was used for fully automated radiosynthesis of [11C]PiB in a commercially available synthesizer, MPS-100 (SHI, Japan). The synthesized [11C]PiB was purified via solid-phase methodology, and its quality control was performed by the quality and safety criteria required for clinical use.

METHODS

The synthesis of desired precursors and standard authentic compounds started with commercially available materials with 70-80% yields. The standard analytical methods were characterized all synthesized compounds. The fully automated [11C]-chemistry synthesizer (MPS-100) used for radiosynthesis of [11C]PiB with [11C]CH3OTf acts as a methylating agent. For radiolabelling, varied amounts of precursor and time of reaction were explored. The resulting crude product underwent purification through solid-phase cartridges. The synthesized radiotracer was analyzed using analytical tools such as radio TLC, HPLC, pH endo-toxicity, and half-life.

RESULTS

The precursor for radiosynthesis of [11C]PiB was achieved in excellent yield using simple and feasible chemistry. A protocol for radiolabelling of precursor to synthesized [11C]PiB was developed using an automated synthesizer. The crude radiotracer was purified by solid-phase cartridge, with a decay-corrected radiochemical yield of 40±5% and radiochemical purity of more than 97% in approx 20 minutes (EOB). The specific activity was calculated and found in a 110-121 mCi/μmol range.

CONCLUSION

A reliable methodology was developed for preparing precursor followed by fully automated radiolabeling using [11C]MeOTf as a methylating agent to synthesize [11C]PiB. The final HPLC-free purification yielded more than 97% radiochemical purity tracer within one radionuclide half-life. The method was reproducible and efficient for any clinical center.

Natural Compounds as Inhibitors of Aβ Peptide and Tau Aggregation

Neurodegenerative conditions like Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) encompass disorders characterized by the degeneration of neurons in specific circumstances. The quest for novel agents to influence these diseases, particularly AD, has unearthed various natural compounds displaying multifaceted activities and diverse pharmacological mechanisms. Given the ongoing extensive study of pathways associated with the accumulation of neurofibrillary aggregates and amyloid plaques, this paper aims to comprehensively review around 130 studies exploring natural products. These studies focus on inhibiting the formation of amyloid plaques and tau protein tangles, with the objective of potentially alleviating or delaying AD.

Voxel-wise Fusion of Resting fMRI Networks and Gray Matter Volume for Alzheimer's Disease Classification using Deep Multimodal Learning

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder requiring accurate and early diagnosis for effective treatment. Resting-state functional magnetic resonance imaging (rs-fMRI) and gray matter volume analysis from structural MRI have emerged as valuable tools for investigating AD-related brain alterations. However, the potential benefits of integrating these modalities using deep learning techniques remain unexplored. In this study, we propose a novel framework that fuses composite images of multiple rs-fMRI networks (called voxelwise intensity projection) and gray matter segmentation images through a deep learning approach for improved AD classification. We demonstrate the superiority of fMRI networks over commonly used metrics such as amplitude of low-frequency fluctuations (ALFF) and fractional ALFF in capturing spatial maps critical for AD classification. We use a multi-channel convolutional neural network incorporating the AlexNet dropout architecture to effectively model spatial and temporal dependencies in the integrated data. Extensive experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset of AD patients and cognitively normal (CN) validate the efficacy of our approach, showcasing improved classification performance of 94.12% test accuracy and an area under the curve (AUC) score of 97.79 compared to existing methods. Our results show that the fusion results generally outperformed the unimodal results. The saliency visualizations also show significant differences in the hippocampus, amygdala, putamen, caudate nucleus, and regions of basal ganglia which are in line with the previous neurobiological literature. Our research offers a novel method to enhance our grasp of AD pathology. By integrating data from various functional networks with structural MRI insights, we significantly improve diagnostic accuracy. This accuracy is further boosted by the effective visualization of this combined information. This lays the groundwork for further studies focused on providing a more accurate and personalized approach to AD diagnosis. The proposed framework and insights gained from fMRI networks provide a promising avenue for future research in deep multimodal fusion and neuroimaging analysis.

The Major Hypotheses of Alzheimer's Disease: Related Nanotechnology-Based Approaches for Its Diagnosis and Treatment

Alzheimer's disease (AD) is a well-known chronic neurodegenerative disorder that leads to the progressive death of brain cells, resulting in memory loss and the loss of other critical body functions. In March 2019, one of the major pharmaceutical companies and its partners announced that currently, there is no drug to cure AD, and all clinical trials of the new ones have been cancelled, leaving many people without hope. However, despite the clear message and startling reality, the research continued. Finally, in the last two years, the Food and Drug Administration (FDA) approved the first-ever medications to treat Alzheimer's, aducanumab and lecanemab. Despite researchers' support of this decision, there are serious concerns about their effectiveness and safety. The validation of aducanumab by the Centers for Medicare and Medicaid Services is still pending, and lecanemab was authorized without considering data from the phase III trials. Furthermore, numerous reports suggest that patients have died when undergoing extended treatment. While there is evidence that aducanumab and lecanemab may provide some relief to those suffering from AD, their impact remains a topic of ongoing research and debate within the medical community. The fact is that even though there are considerable efforts regarding pharmacological treatment, no definitive cure for AD has been found yet. Nevertheless, it is strongly believed that modern nanotechnology holds promising solutions and effective clinical strategies for the development of diagnostic tools and treatments for AD. This review summarizes the major hallmarks of AD, its etiological mechanisms, and challenges. It explores existing diagnostic and therapeutic methods and the potential of nanotechnology-based approaches for recognizing and monitoring patients at risk of irreversible neuronal degeneration. Overall, it provides a broad overview for those interested in the evolving areas of clinical neuroscience, AD, and related nanotechnology. With further research and development, nanotechnology-based approaches may offer new solutions and hope for millions of people affected by this devastating disease.

Association between CSF biomarkers of Alzheimer's disease and neuropsychiatric symptoms: Mayo Clinic Study of Aging

INTRODUCTION

We examined the association between cerebrospinal fluid (CSF)-derived biomarkers of Alzheimer's disease and neuropsychiatric symptoms (NPS) in older non-demented adults.

METHODS

We included 784 persons (699 cognitively unimpaired, 85 with mild cognitive impairment) aged ≥ 50 years who underwent CSF amyloid beta (Aβ42), hyperphosphorylated tau 181 (p-tau), and total tau (t-tau) as well as NPS assessment using Beck Depression and Anxiety Inventories (BDI-II, BAI), and Neuropsychiatric Inventory Questionnaire (NPI-Q).

RESULTS

Lower CSF Aβ42, and higher t-tau/Aβ42 and p-tau/Aβ42 ratios were associated with BDI-II and BAI total scores, clinical depression (BDI-II ≥ 13), and clinical anxiety (BAI ≥ 10), as well as NPI-Q-assessed anxiety, apathy, and nighttime behavior.

DISCUSSION

CSF Aβ42, t-tau/Aβ42, and p-tau/Aβ42 ratios were associated with NPS in community-dwelling individuals free of dementia. If confirmed by a longitudinal cohort study, the findings have clinical relevance of taking into account the NPS status of individuals with abnormal CSF biomarkers.

Application of Pt@ZIF-8 nanocomposite-based electrochemical biosensor for sensitive diagnosis of tau protein in Alzheimer's disease patients

Alzheimer's disease (AD) is a progressive brain disorder characterized by the ongoing decline of brain functions. Studies have revealed the detrimental effects of hyperphosphorylated tau (p-tau) protein fibrils in AD pathogenesis, highlighting the importance of this factor in the early-stage detection of AD conditions. We designed an electrochemical immunosensor for quantitative detection of the cis conformation of the p-tau protein (cis-p-tau) employing platinum nanoparticles (Pt NPs) supported on zeolitic imidazolate frameworks (ZIF) for modifying the glassy carbon electrode (GCE) surface. Under optimum conditions, the immunosensor selectively and sensitively detected cis-p-tau within the broad linear range of 1 fg mL-1 to 10 ng mL-1 and the low limit of detection (LOD) of 1 fg mL-1 with desired reproducibility and stability. Furthermore, the fabricated immunosensor's performance was examined for the cis-p-tau analysis in the serum of AD patients, indicating its accuracy and feasibility for real-sample analysis. Notably, this is the first application of Pt@ZIF-8 nanocomposite in fabricating a valid immunosensor for selective cis-p-tau detection, even in the presence of trans-p-tau. It is worth mentioning that the enzyme-linked immunosorbent assay (ELISA) reference technique is not able to evaluate pico- or femtomolar concentrations of cis-p-tau, making the fabricated immunosensor superior for early-stage measurement and screening of AD.

Long-lived SERS Matrix for Real-Time Biochemical Detection Using "Frozen" Transition State

For the long-time tracking of biological events, maintaining the bioactivity of the analytes during the detection process is essential. Here, we show a versatile surface-enhanced Raman Scattering (SERS) platform, termed a superwettable-omniphobic lubricous porous SERS (SOLP-SERS) substrate. The SOLP-SERS substrate could generate a three-dimensional liquid "hotspots" matrix with an ultra-long lifetime (tens of days) by confining tiny amounts of liquids within the gaps between nanoparticles. Then, the analytes are trapped in the uniform liquid "hotspots", whose bioactivity can be well maintained over a long period of time during SERS detection. Limits of detection down to femtomolar levels were achieved for various molecules. More importantly, SERS signals were uniform within the substrate and remained stable for more than 30 days. As a proof-of-concept experiment, the dynamic detection of the polymerization of Aβ peptides into amyloids was monitored by the SOLP-SERS substrate within 48 h. Moreover, the exosomes secreted by breast cancer cells, an important biomarker of cancer, were also measured. These results demonstrate that the SOLP-SERS platform will provide new insights into the development of real-time biochemical sensors with ultrahigh sensitivity.

Design of an electrochemical aptasensor in the presence of an array of gold nanostructure and a GO-MWCNTs nanocomposite: application in diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is considered one of the main progressive chronic diseases in elderly individuals. Early diagnosis using related biomarkers, specifically beta-amyloid peptide (Aβ), allows finding expected treatment routes. Here, we developed an electrochemical aptasensing platform for AD by employing a glassy carbon electrode (GCE) modified with a layer of jagged gold (JG) nanostructure (diameter: 60-185 nm) and graphene oxide-carboxylic acid functionalized multiwalled carbon nanotubes (GO-c-MWCNTs) nanocomposite. These surface modifications acted as the signal amplifier and provided an optimum nano-interface substrate for immobilizing aptamer strands. The measurements of Aβ were performed via differential pulse voltammetry (DPV), and the aptasensor detected the analyte in a linear range from 0.1 pg mL-1 to 1 ng mL-1, with an estimated limit of detection (LOD) of about 0.088 pg mL-1 (S/N = 3). The aptasensor showed sufficient stability (11 days), reversibility (three times), and reproducibility (five times re-fabrication with relative standard deviation (RSD): 1.27). The potential interfering agents showed negligible impact on the sensing performance. Finally, the application of the aptasensor was evaluated in the presence of 10 serum samples, and the recovery values were from 93 to 110.1%.

Novel Screening Tool Using Non-linguistic Voice Features Derived from Simple Phrases to Detect Mild Cognitive Impairment and Dementia

Appropriate intervention and care in detecting cognitive impairment early are essential to effectively prevent the progression of cognitive deterioration. Diagnostic voice analysis is a noninvasive and inexpensive screening method that could be useful for detecting cognitive deterioration at earlier stages such as mild cognitive impairment. We aimed to distinguish between patients with dementia or mild cognitive impairment and healthy controls by using purely acoustic features (i.e., nonlinguistic features) extracted from two simple phrases. Voice was analyzed on 195 recordings from 150 patients (age, 45-95 years). We applied a machine learning algorithm (LightGBM; Microsoft, Redmond, WA, USA) to test whether the healthy control, mild cognitive impairment, and dementia groups could be accurately classified, based on acoustic features. Our algorithm performed well: area under the curve was 0.81 and accuracy, 66.7% for the 3-class classification. Thus, our vocal biomarker is useful for automated assistance in diagnosing early cognitive deterioration.

Protein aggregation and neurodegenerative disease: Structural outlook for the novel therapeutics

Before the controversial approval of humanized monoclonal antibody lecanemab, which binds to the soluble amyloid-β protofibrils, all the treatments available earlier, for Alzheimer's disease (AD) were symptomatic. The researchers are still struggling to find a breakthrough in AD therapeutic medicine, which is partially attributable to lack in understanding of the structural information associated with the intrinsically disordered proteins and amyloids. One of the major challenges in this area of research is to understand the structural diversity of intrinsically disordered proteins under in vitro conditions. Therefore, in this review, we have summarized the in vitro applications of biophysical methods, which are aimed to shed some light on the heterogeneity, pathogenicity, structures and mechanisms of the intrinsically disordered protein aggregates associated with proteinopathies including AD. This review will also rationalize some of the strategies in modulating disease-relevant pathogenic protein entities by small molecules using structural biology approaches and biophysical characterization. We have also highlighted tools and techniques to simulate the in vivo conditions for native and cytotoxic tau/amyloids assemblies, urge new chemical approaches to replicate tau/amyloids assemblies similar to those in vivo conditions, in addition to designing novel potential drugs.

A structured evaluation of cryopreservation in generating single-cell transcriptomes from cerebrospinal fluid

Single-cell transcriptomics allows characterization of cerebrospinal fluid (CSF) cells at an unprecedented level. Here, we report a robust cryopreservation protocol adapted for the characterization of fragile CSF cells by single-cell RNA sequencing (RNA-seq) in moderate- to large-scale studies. Fresh CSF was collected from twenty-one participants at two independent sites. Each CSF sample was split into two fractions: one was processed fresh, while the second was cryopreserved for months and profiled after thawing. B and T cell receptor sequencing was also performed. Our comparison of fresh and cryopreserved data from the same individuals demonstrates highly efficient recovery of all known CSF cell types. We find no significant difference in cell type proportions and cellular transcriptomes between fresh and cryopreserved cells. Results were comparable at both sites and with different single-cell sequencing chemistries. Cryopreservation did not affect recovery of T and B cell clonotype diversity. Our CSF cell cryopreservation protocol provides an important alternative to fresh processing of fragile CSF cells.

Cerebrospinal fluid microRNAs as potential biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is the leading form of dementia worldwide, but its early detection and diagnosis remain a challenge. MicroRNAs (miRNAs) are a group of small endogenous RNA molecules that regulate mRNA expression. Recent evidence suggests miRNAs play an important role in the five major hallmarks of AD pathophysiology: amyloidogenesis, tauopathy, neuroinflammation, synaptic dysfunction, and neuronal death. Compared to traditional biomarkers of AD, miRNAs display a greater degree of stability in cerebrospinal fluid. Moreover, aberrant changes in miRNA expression can be measured over time to monitor and guide patient treatment. Specific miRNA profiles and combinations may also be used to distinguish AD subjects from normal controls and other causes of dementia. Because of these properties, miRNAs are now being considered as promising and potential biomarkers of AD. This review comprehensively summarizes the diagnostic potential and regulatory roles miRNAs play in AD.

Mass Spectrometry in Cerebrospinal Fluid Uncovers Association of Glycolysis Biomarkers with Alzheimer's Disease in a Large Clinical Sample

Background

Alzheimer's disease (AD) is a complex heterogenous neurodegenerative disorder, characterized by multiple pathophysiologies, including disruptions in brain metabolism. Defining markers for patient stratification across these pathophysiologies is an important step towards personalized treatment of AD. Efficient brain glucose metabolism is essential to sustain neuronal activity, but hypometabolism is consistently observed in AD. The molecular changes underlying these observations remain unclear. Recent studies have indicated dysregulation of several glycolysis markers in AD cerebrospinal fluid and tissue.

Methods

In this study, unbiased mass spectrometry was used to perform a deep proteomic survey of cerebrospinal fluid (CSF) from a large-scale clinically complex cohort to uncover changes related to impaired glucose metabolism.

Results

Two glycolytic enzymes, Pyruvate kinase (PKM) and Aldolase A (ALDOA) were found to be specifically upregulated in AD CSF compared to other non-AD groups. Presence of full-length protein of these enzymes in CSF was confirmed through immunoblotting. Levels of tryptic peptides of these enzymes correlated significantly with CSF glucose and CSF lactate in matching CSF samples.

Conclusions

The results presented here indicate a general dysregulation of glucose metabolism in the brain in AD. We highlight two markers ALDOA and PKM that may act as potential functionally-relevant biomarkers of glucose metabolism dysregulation in AD.

Cerebrospinal Fluid and Brain Proteoforms of the Granin Neuropeptide Family in Alzheimer's Disease

The granin neuropeptide family is composed of acidic secretory signaling molecules that act throughout the nervous system to help modulate synaptic signaling and neural activity. Granin neuropeptides have been shown to be dysregulated in different forms of dementia, including Alzheimer's disease (AD). Recent studies have suggested that the granin neuropeptides and their protease-cleaved bioactive peptides (proteoforms) may act as both powerful drivers of gene expression and as a biomarker of synaptic health in AD. The complexity of granin proteoforms in human cerebrospinal fluid (CSF) and brain tissue has not been directly addressed. We developed a reliable nontryptic mass spectrometry assay to comprehensively map and quantify endogenous neuropeptide proteoforms in the brain and CSF of individuals diagnosed with mild cognitive impairment and dementia due to AD compared to healthy controls, individuals with preserved cognition despite AD pathology ("Resilient"), and those with impaired cognition but no AD or other discernible pathology ("Frail"). We drew associations between neuropeptide proteoforms, cognitive status, and AD pathology values. Decreased levels of VGF proteoforms were observed in CSF and brain tissue from individuals with AD compared to controls, while select proteoforms from chromogranin A showed the opposite effect. To address mechanisms of neuropeptide proteoform regulation, we showed that the proteases Calpain-1 and Cathepsin S can cleave chromogranin A, secretogranin-1, and VGF into proteoforms found in both the brain and CSF. We were unable to demonstrate differences in protease abundance in protein extracts from matched brains, suggesting that regulation may occur at the level of transcription.

Advances in sample preparation and HPLC-MS/MS methods for determining amyloid-β peptide in biological samples: a review

Alzheimer's disease (AD), a neurological disorder, is a major public health concern and the most common form of dementia. Its typical symptoms include memory loss, confusion, changes in personality, and cognitive impairment, which result in patients gradually losing independence. Over the last decades, some studies have focused on searching for effective biomarkers as early diagnostic indicators of AD. Amyloid-β (Aβ) peptides have been consolidated as reliable AD biomarkers and have been incorporated into modern diagnostic research criteria. However, quantitative analysis of Aβ peptides in biological samples remains a challenge because both the sample and the physical-chemical properties of these peptides are complex. During clinical routine, Aβ peptides are measured in the cerebrospinal fluid by immunoassays, but the availability of a specific antibody is critical-in some cases, an antibody may not exist, or its specificity may be inadequate, leading to low sensitivity and false results. HPLC-MS/MS has been reported as a sensitive and selective method for determining different fragments of Aβ peptides in biological samples simultaneously. Developments in sample preparation techniques (preconcentration platforms) such as immunoprecipitation, 96-well plate SPME, online SPME, and fiber-in-tube SPME have enabled not only effective enrichment of Aβ peptides present at trace levels in biological samples, but also efficient exclusion of interferents from the sample matrix (sample cleanup). This high extraction efficiency has provided MS platforms with higher sensitivity. Recently, methods affording LLOQ values as low as 5 pg mL^-1 have been reported. Such low LLOQ values are adequate for quantifying Aβ peptides in complex matrixes including cerebrospinal fluid (CSF) and plasma samples. This review summarizes the advances in mass spectrometry (MS)-based methods for quantifying Aβ peptides and covers the period 1992-2022. Important considerations regarding the development of the HPLC-MS/MS method such as the sample preparation step, optimization of the HPLC-MS/MS parameters, and matrix effects are described. Clinical applications, difficulties related to analysis of plasma samples, and future trends of these MS/MS-based methods are also discussed.

Plasma-based diagnostic and screening platform using a combination of biosensing signals in Alzheimer's disease

Using biosensor to screen for Alzheimer's disease (AD) facilitates early detection of AD with high sensitivity and accuracy. This approach overcomes the limitations of conventional AD diagnostic methods, such as neuropsychological assessment and neuroimaging analysis. Here, we propose a simultaneous analysis of signal combinations generated by four crucial AD biomarkers (Amyloid beta 1-40 (Aβ₄₀), Aβ₄₂, total tau 441 (tTau₄₄₁), and phosphorylated tau 181 (pTau₁₈₁)) by inducing a dielectrophoretic (DEP) force on fabricated interdigitated microelectrode (IME) sensor. By applying an optimal DEP force, our biosensor selectively concentrates and filters the plasma-based AD biomarkers, exhibiting high sensitivity (limit of detection <100 fM) and selectivity in the plasma-based AD biomarkers detection (p < 0.0001). Consequently, it is demonstrated that a complex combined signal comprising four AD-specific biomarker signals (Aβ₄₀- Aβ₄₂+ tTau₄₄₁- pTau₁₈₁) can differentiate between patients with AD and healthy subjects with high accuracy (78.85%) and precision (80.95%) (p < 0.0001).

Beyond the classical amyloid hypothesis in Alzheimer's disease: Molecular insights into current concepts of pathogenesis, therapeutic targets, and study models

Alzheimer's disease (AD) is one of the progressive neurodegenerative disorders and the most common cause of dementia in the elderly worldwide causing difficulties in the daily life of the patient. AD is characterized by the aberrant accumulation of β-amyloid plaques and tau protein-containing neurofibrillary tangles (NFTs) in the brain giving rise to neuroinflammation, oxidative stress, synaptic failure, and eventual neuronal cell death. The total cost of care in AD treatment and related health care activities is enormous and pharmaceutical drugs approved by Food and Drug Administration have not manifested sufficient efficacy in protection and therapy. In recent years, there are growing studies that contribute a fundamental understanding to AD pathogenesis, AD-associated risk factors, and pharmacological intervention. However, greater molecular process-oriented research in company with suitable experimental models is still of the essence to enhance the prospects for AD therapy and cell lines as a disease model are still the major part of this milestone. In this review, we provide an insight into molecular mechanisms, particularly the recent concept in gut-brain axis, vascular dysfunction and autophagy, and current models used in the study of AD. Here, we emphasized the importance of therapeutic strategy targeting multiple mechanisms together with utilizing appropriate models for the discovery of novel effective AD therapy. This article is categorized under: Neurological Diseases > Molecular and Cellular Physiology.

Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer's Disease

The development of early non-invasive diagnosis methods and identification of novel biomarkers are necessary for managing Alzheimer's disease (AD) and facilitating effective prognosis and treatment. AD has multi-factorial nature and involves complex molecular mechanism, which causes neuronal degeneration. The primary challenges in early AD detection include patient heterogeneity and lack of precise diagnosis at the preclinical stage. Several cerebrospinal fluid (CSF) and blood biomarkers have been proposed to show excellent diagnosis ability by identifying tau pathology and cerebral amyloid beta (Aβ) for AD. Intense research endeavors are being made to develop ultrasensitive detection techniques and find potent biomarkers for early AD diagnosis. To mitigate AD worldwide, understanding various CSF biomarkers, blood biomarkers, and techniques that can be used for early diagnosis is imperative. This review attempts to provide information regarding AD pathophysiology, genetic and non-genetic factors associated with AD, several potential blood and CSF biomarkers, like neurofilament light, neurogranin, Aβ, and tau, along with biomarkers under development for AD detection. Besides, numerous techniques, such as neuroimaging, spectroscopic techniques, biosensors, and neuroproteomics, which are being explored to aid early AD detection, have been discussed. The insights thus gained would help in finding potential biomarkers and suitable techniques for the accurate diagnosis of early AD before cognitive dysfunction.

Alzheimer's disease as a fundamental disease of information processing systems: An information theory perspective

The human brain is a dynamic multiplex of information, both neural (neurotransmitter-to-neuron, involving 1.5×10¹⁵ action potentials per minute) and immunological (cytokine-to-microglia, providing continuous immune surveillance via 1.5×10¹⁰ immunocompetent cells). This conceptualization highlights the opportunity of exploiting "information" not only in the mechanistic understanding of brain pathology, but also as a potential therapeutic modality. Arising from its parallel yet interconnected proteopathic-immunopathic pathogeneses, Alzheimer's disease (AD) enables an exploration of the mechanistic and therapeutic contributions of information as a physical process central to brain disease progression. This review first considers the definition of information and its relevance to neurobiology and thermodynamics. Then we focus on the roles of information in AD using its two classical hallmarks. We assess the pathological contributions of β-amyloid peptides to synaptic dysfunction and reconsider this as a source of noise that disrupts information transfer between presynaptic and postsynaptic neurons. Also, we treat the triggers that activate cytokine-microglial brain processes as information-rich three-dimensional patterns, including pathogen-associated molecular patterns and damage-associated molecular patterns. There are structural and functional similarities between neural and immunological information with both fundamentally contributing to brain anatomy and pathology in health and disease. Finally, the role of information as a therapeutic for AD is introduced, particularly cognitive reserve as a prophylactic protective factor and cognitive therapy as a therapeutic contributor to the comprehensive management of ongoing dementia.

Prefrontal EEG slowing, synchronization, and ERP peak latency in association with predementia stages of Alzheimer's disease

Background

Early screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it.

Objective

We examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer's disease (AD).

Methods

One hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A-) and neurodegeneration status (N+ or N-): cognitively normal (CN; A-N-, n = 27), asymptomatic AD (aAD; A + N-, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(-); A-N+, n = 42). Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min. Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG slowing, temporal synchrony, and ERP latency, respectively.

Results

Decreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively.

Conclusion

Slow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD.

Significance

The EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals' early stages on the AD continuum as well as overall cognitive impairment.

Age-Dependent Increase in Tau Phosphorylation at Serine 396 in Huntington's Disease Prefrontal Cortex

BACKGROUND

To date, it is still controversial whether tau phosphorylation plays a role in Huntington's disease (HD), as previous studies demonstrated either no alterations or increases in phosphorylated tau (pTau) in HD postmortem brain and mouse models.

OBJECTIVE

The goal of this study was to determine whether total tau and pTau levels are altered in HD.

METHODS

Immunohistochemistry, cellular fractionations, and western blots were used to measure total tau and pTau levels in a large cohort of HD and control postmortem prefrontal cortex (PFC). Furthermore, western blots were performed to assess tau, and pTau levels in HD and control isogenic embryonic stem cell (ESC)-derived cortical neurons and neuronal stem cells (NSCs). Similarly, western blots were used to assess tau and pTau levels in HttQ111 and transgenic R6/2 mice. Lastly, total tau levels were assessed in HD and healthy control plasma using Quanterix Simoa assay.

RESULTS

Our results revealed that, while there was no difference in total tau or pTau levels in HD PFC compared to controls, the levels of tau phosphorylated at S396 were increased in PFC samples from HD patients 60 years or older at time of death. Additionally, tau and pTau levels were not changed in HD ESC-derived cortical neurons and NSCs. Similarly, total tau or pTau levels were not altered in HttQ111 and transgenic R6/2 mice compared to wild-type littermates. Lastly, tau levels were not changed in plasma from a small cohort of HD patients compared to controls.

CONCLUSIONS

Together these findings demonstrate that pTau-S396 levels increase significantly with age in HD PFC.

Early Diagnosis of Alzheimer's Disease with Blood Test; Tempting but Challenging

The increasing prevalence of Alzheimer's disease (AD) has led to a health crisis. According to official statistics, more than 55 million people globally have AD or other types of dementia, making it the sixth leading cause of death. It is still difficult to diagnose AD and there is no definitive diagnosis yet; post-mortem autopsy is still the only definite method. Moreover, clinical manifestations occur very late in the course of disease progression; therefore, profound irreversible changes have already occurred when the disease manifests. Studies have shown that in the preclinical stage of AD, changes in some biomarkers are measurable prior to any neurological damage or other symptoms. Hence, creating a reliable, fast, and affordable method capable of detecting AD in early stage has attracted the most attention. Seeking clinically applicable, inexpensive, less invasive, and much more easily accessible biomarkers for early diagnosis of AD, blood-based biomarkers (BBBs) seem to be an ideal option. This review is an inclusive report of BBBs that have been shown to be altered in the course of AD progression. The aim of this report is to provide comprehensive insight into the research status of early detection of AD based on BBBs.

Understanding the Intricate Role of Exosomes in Pathogenesis of Alzheimer's Disease

Alzheimer's disease causes loss of memory and deterioration of mental abilities is utmost predominant neurodegenerative disease accounting 70-80% cases of dementia. The appearance of plaques of amyloid-β and neurofibrillary tangles in the brain post-mortems of Alzheimer's patients established them as key participants in the etiology of Alzheimer's disease. Exosomes exist as extracellular vesicles of nano-size which are present throughout the body. Exosomes are known to spread toxic hyperphosphorylated tau and amyloid-β between the cells and are linked to the loss of neurons by inducing apoptosis. Exosomes have progressed from cell trashcans to multifunctional organelles which are involved in various functions like internalisation and transmission of macromolecules such as lipids, proteins, and nucleic acids. This review covers current findings on relationship of exosomes in biogenesis and angiogenesis of Alzheimer's disease and functions of exosomes in the etiology of AD. Furthermore, the roles of exosomes in development, diagnosis, treatment, and its importance as therapeutic targets and biomarkers for Alzheimer's disease have also been highlighted.

Stem Cell-based and Advanced Therapeutic Modalities for Parkinson's Disease: A Risk-effectiveness Patient-centered Analysis

Treatment of Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, is currently considered a challenging issue since it causes substantial disability, poor quality of life, and mortality. Despite remarkable progress in advanced conventional therapeutic interventions, the global burden of the disease has nearly doubled, prompting us to assess the riskeffectiveness of different treatment modalities. Each protocol could be considered as the best alternative treatment depending on the patient's situation. Prescription of levodopa, the most effective available medicine for this disorder, has been associated with many complications, i.e., multiple episodes of "off-time" and treatment resistance. Other medications, which are typically used in combination with levodopa, may have several adverse effects as well. As a result, the therapies that are more in line with human physiology and make the least interference with other pathways are worth investigating. On the other hand, remaining and persistent symptoms after therapy and the lack of effective response to the conventional approaches have raised expectations towards innovative alternative approaches, such as stem cell-based therapy. It is critical to not overlook the unexplored side effects of innovative approaches due to the limited number of research. In this review, we aimed to compare the efficacy and risk of advanced therapies with innovative cell-based and stemcell- based modalities in PD patients. This paper recapitulated the underlying factors/conditions, which could lead us to more practical and established therapeutic outcomes with more advantages and few complications. It could be an initial step to reconsider the therapeutic blueprint for patients with Parkinson's disease.

Evaluation of Salivary Biomarkers of Periodontal Disease Based on Smoking Status: A Systematic Review

Saliva is a useful biomarker for diagnosing oral health conditions, including periodontal disease (PD). Smoking is a risk factor for PD. The aim of this systematic review was to summarize the salivary biomarkers associated with PD based on smoking status. A comprehensive search of the MEDLINE (via PubMed), EMBASE, Cochrane, SCOPUS, and Web of Sciences databases was conducted up to 1 January 2021 using key terms relevant to the topic of our research and Cochrane methodology and improved with searching a gray literature resource. The methodological quality of all included studies was assessed with the revised Quality Assessment of Diagnostic Accuracy Studies-2. Seven studies were included. Smokers had increased levels of malondialdehyde, sialic acid, salivary cortisol, salivary interleukin 1β, albumin, tissue inhibitor of matrix metalloproteinase (TIMP), and the pyridinoline cross-linked carboxyterminal telopeptide of type I collagen (ICTP), as well as decreased levels of superoxide dismutase, activity of lactate dehydrogenase, activity of enzyme activity of β-glucuronidase, uric acid, matrix metalloproteinase-8 (MMP-8)/TIMP-1 ratio, and combinations of MMP-8 and ICTP. However, mixed results were observed some studies in detecting glutathione peroxidase, MMP-8, and MMP-14. The results were interpreted with caution because of limitations in the number of included studies and the study design. Some salivary biomarkers are potentially useful in combination or alone for diagnosing PD. Methodological and systematic studies are needed to develop more effective biomarkers.

Manipulation of the diet-microbiota-brain axis in Alzheimer's disease

Several studies investigating the pathogenesis of Alzheimer's disease have identified various interdependent constituents contributing to the exacerbation of the disease, including Aβ plaque formation, tau protein hyperphosphorylation, neurofibrillary tangle accumulation, glial inflammation, and the eventual loss of proper neural plasticity. Recently, using various models and human patients, another key factor has been established as an influential determinant in brain homeostasis: the gut-brain axis. The implications of a rapidly aging population and the absence of a definitive cure for Alzheimer's disease have prompted a search for non-pharmaceutical tools, of which gut-modulatory therapies targeting the gut-brain axis have shown promise. Yet multiple recent studies examining changes in human gut flora in response to various probiotics and environmental factors are limited and difficult to generalize; whether the state of the gut microbiota in Alzheimer's disease is a cause of the disease, a result of the disease, or both through numerous feedback loops in the gut-brain axis, remains unclear. However, preliminary findings of longitudinal studies conducted over the past decades have highlighted dietary interventions, especially Mediterranean diets, as preventative measures for Alzheimer's disease by reversing neuroinflammation, modifying the intestinal and blood-brain barrier (BBB), and addressing gut dysbiosis. Conversely, the consumption of Western diets intensifies the progression of Alzheimer's disease through genetic alterations, impaired barrier function, and chronic inflammation. This review aims to support the growing body of experimental and clinical data highlighting specific probiotic strains and particular dietary components in preventing Alzheimer's disease via the gut-brain axis.

Altering Brain Amyloidosis by Intra-Lingual and Extra-Nasal Exposure of Aβ Aggregates

Extensive experimental and human-derived evidence suggest that misfolded Aβ particles spread similarly to infectious prions. Moreover, peripheral administration of Aβ seeds accelerates brain amyloidosis in both susceptible experimental animals and humans. The mechanisms and elements governing the transport of misfolded Aβ from the periphery to the brain are not fully understood, although circulation and retrograde axonal transport have been proposed. Here, we demonstrate that injection of Aβ seeds in the tongue, a highly innervated organ, substantially accelerates the appearance of plaques in Tg2576 mice. In addition, the extra-nasal exposure of Aβ aggregates increased amyloid pathology in the olfactory bulb. Our results show that exposing highly innervated tissues to Aβ seeds accelerates AD-like pathological features, and suggest that Aβ seeds can be transported from peripheral compartments to the brain by retrograde axonal transport. Research in this direction may be relevant on different fronts, including disease mechanisms, diagnosis, and risk-evaluation of potential iatrogenic transmission of Aβ misfolding.

Multi-task deep autoencoder to predict Alzheimer's disease progression using temporal DNA methylation data in peripheral blood

Traditional approaches for diagnosing Alzheimer's disease (AD) such as brain imaging and cerebrospinal fluid are invasive and expensive. It is desirable to develop a useful diagnostic tool by exploiting biomarkers obtained from peripheral tissues due to their noninvasive and easily accessible characteristics. However, the capacity of using DNA methylation data in peripheral blood for predicting AD progression is rarely known. It is also challenging to develop an efficient prediction model considering the complex and high-dimensional DNA methylation data in a longitudinal study. Here, we develop two multi-task deep autoencoders, which are based on the convolutional autoencoder and long short-term memory autoencoder to learn the compressed feature representation by jointly minimizing the reconstruction error and maximizing the prediction accuracy. By benchmarking on longitudinal DNA methylation data collected from the peripheral blood in Alzheimer's Disease Neuroimaging Initiative, we demonstrate that the proposed multi-task deep autoencoders outperform state-of-the-art machine learning approaches for both predicting AD progression and reconstructing the temporal DNA methylation profiles. In addition, the proposed multi-task deep autoencoders can predict AD progression accurately using only the historical DNA methylation data and the performance is further improved by including all temporal DNA methylation data. Availability:: https://github.com/lichen-lab/MTAE.

Earlier Detection of Alzheimer's Disease Based on a Novel Biomarker cis P-tau by a Label-Free Electrochemical Immunosensor

Early detection of cis phosphorylated tau (cis P-tau) may help as an effective treatment to control the progression of Alzheimer's disease (AD). Recently, we introduced for the first time a monoclonal antibody (mAb) with high affinity against cis P-tau. In this study, the cis P-tau mAb was utilized to develop a label-free immunosensor. The antibody was immobilized onto a gold electrode and the electrochemical responses to the analyte were acquired by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and differential pulse voltammetry (DPV). The immunosensor was capable of selective detection of cis P-tau among non-specific targets like trans P-tau and major plasma proteins. A wide concentration range (10 × 10^-14 M-3.0 × 10^-9 M) of cis P-tau was measured in PBS and human serum matrices with a limit of detection of 0.02 and 0.05 pM, respectively. Clinical applicability of the immunosensor was suggested by its long-term storage stability and successful detection of cis P-tau in real samples of cerebrospinal fluid (CSF) and blood serum collected from human patients at different stages of AD. These results suggest that this simple immunosensor may find great application in clinical settings for early detection of AD which is an unmet urgent need in today's healthcare services.

Experimental and Clinical Biomarkers for Progressive Evaluation of Neuropathology and Therapeutic Interventions for Acute and Chronic Neurological Disorders

This article describes commonly used experimental and clinical biomarkers of neuronal injury and neurodegeneration for the evaluation of neuropathology and monitoring of therapeutic interventions. Biomarkers are vital for diagnostics of brain disease and therapeutic monitoring. A biomarker can be objectively measured and evaluated as a proxy indicator for the pathophysiological process or response to therapeutic interventions. There are complex hurdles in understanding the molecular pathophysiology of neurological disorders and the ability to diagnose them at initial stages. Novel biomarkers for neurological diseases may surpass these issues, especially for early identification of disease risk. Validated biomarkers can measure the severity and progression of both acute neuronal injury and chronic neurological diseases such as epilepsy, migraine, Alzheimer's disease, Parkinson's disease, Huntington's disease, traumatic brain injury, amyotrophic lateral sclerosis, multiple sclerosis, and other brain diseases. Biomarkers are deployed to study progression and response to treatment, including noninvasive imaging tools for both acute and chronic brain conditions. Neuronal biomarkers are classified into four core subtypes: blood-based, immunohistochemical-based, neuroimaging-based, and electrophysiological biomarkers. Neuronal conditions have progressive stages, such as acute injury, inflammation, neurodegeneration, and neurogenesis, which can serve as indices of pathological status. Biomarkers are critical for the targeted identification of specific molecules, cells, tissues, or proteins that dramatically alter throughout the progression of brain conditions. There has been tremendous progress with biomarkers in acute conditions and chronic diseases affecting the central nervous system.

Anodal transcranial direct current stimulation alleviates cognitive impairment in an APP/PS1 model of Alzheimer's disease in the preclinical stage

Anodal transcranial direct current stimulation (AtDCS) has been shown to alleviate cognitive impairment in an APP/PS1 model of Alzheimer's disease in the preclinical stage. However, this enhancement was only observed immediately after AtDCS, and the long-term effect of AtDCS remains unknown. In this study, we treated 26-week-old mouse models of Alzheimer's disease in the preclinical stage with 10 AtDCS sessions or sham stimulation. The Morris water maze, novel object recognition task, and novel object location test were implemented to evaluate spatial learning memory and recognition memory of mice. Western blotting was used to detect the relevant protein content. Morphological changes were observed using immunohistochemistry and immunofluorescence staining. Six weeks after treatment, the mice subjected to AtDCS sessions had a shorter escape latency, a shorter path length, more platform area crossings, and spent more time in the target quadrant than sham-stimulated mice. The mice subjected to AtDCS sessions also performed better in the novel object recognition and novel object location tests than sham-stimulated mice. Furthermore, AtDCS reduced the levels of amyloid-β42 and glial fibrillary acidic protein, a marker of astrocyte activation, and increased the level of neuronal marker NeuN in hippocampal tissue. These findings suggest that AtDCS can improve the spatial learning and memory abilities and pathological state of an APP/PS1 mouse model of Alzheimer's disease in the preclinical stage, with improvements that last for at least 6 weeks.

An adjustable amyloid-β oligomers aptasensor based on the synergistic effect of self-enhanced metal-organic gel luminophore and triple-helix DNA system

Amyloid-β oligomers (AβOs) was the core-biomarker of Alzheimer's disease (AD), and the detection of AβOs is very important for the early diagnosis of AD. However, existing tests for AβOs are majorly suffering from complex process and poor sensitivity. Thus, an adjustable AβOs electrochemiluminescence (ECL) aptasensor based on the synergistic effect of self-enhanced metal-organic gel (AgCNS) and triple-helix DNA system (THS) was successfully constructed. AgCNS was prepared by an extremely simple one-pot method and was an innovative luminophore with excellent ECL performance. The AgCNS-labeled complementary sequence (AgCNS@CP) was interlaced with the unlabeled aptamer (Apt) carrying two short-arms fixed on the gold electrode (GE) to form the THS. Along with the specific-binding of AβOs and Apt, the THS was disrupted and adjusted flexibly between "on" and "off", resulting in significant changes in the ECL signals. Thus, ECL detection of AβOs was sensitively achieved with a detection limit as low as 0.23 fM and the different forms of Aβ can be specifically distinguished. The aptasensor also exhibited satisfactory selectivity, stability and reproducibility. Moreover, when proposed method and ELISA-kit were simultaneously applied to artificial cerebrospinal fluid (A-CSF) samples, the obtained results were completely consistent, reflecting the potential clinical application value of this work.

Beta amyloid deposition and cognitive decline in Parkinson's disease: a study of the PPMI cohort

The accumulation of beta amyloid in the brain has a complex and poorly understood impact on the progression of Parkinson's disease pathology and much controversy remains regarding its role, specifically in cognitive decline symptoms. Some studies have found increased beta amyloid burden is associated with worsening cognitive impairment in Parkinson's disease, especially in cases where dementia occurs, while other studies failed to replicate this finding. To better understand this relationship, we examined a cohort of 25 idiopathic Parkinson's disease patients and 30 healthy controls from the Parkinson's Progression Marker Initiative database. These participants underwent [¹⁸F]Florbetaben positron emission tomography scans to quantify beta amyloid deposition in 20 cortical regions. We then analyzed this beta amyloid data alongside the longitudinal Montreal Cognitive Assessment scores across 3 years to see how participant's baseline beta amyloid levels affected their cognitive scores prospectively. The first analysis we performed with these data was a hierarchical cluster analysis to help identify brain regions that shared similarity. We found that beta amyloid clusters differently in Parkinson's disease patients compared to healthy controls. In the Parkinson's disease group, increased beta amyloid burden in cluster 2 was associated with worse cognitive ability, compared to deposition in clusters 1 or 3. We also performed a stepwise linear regression where we found an adjusted R² of 0.495 (49.5%) in a model explaining the Parkinson's disease group's Montreal Cognitive Assessment score 1-year post-scan, encompassing the left gyrus rectus, the left anterior cingulate cortex, and the right parietal cortex. Taken together, these results suggest regional beta amyloid deposition alone has a moderate effect on predicting future cognitive decline in Parkinson's disease patients. The patchwork effect of beta amyloid deposition on cognitive ability may be part of what separates cognitive impairment from cognitive sparing in Parkinson's disease. Thus, we suggest it would be more useful to measure beta amyloid burden in specific brain regions rather than using a whole-brain global beta amyloid composite score and use this information as a tool for determining which Parkinson's disease patients are most at risk for future cognitive decline.

A classification for complex imbalanced data in disease screening and early diagnosis

Imbalanced classification has drawn considerable attention in the statistics and machine learning literature. Typically, traditional classification methods often perform poorly when a severely skewed class distribution is observed, not to mention under a high-dimensional longitudinal data structure. Given the ubiquity of big data in modern health research, it is expected that imbalanced classification in disease diagnosis may encounter an additional level of difficulty that is imposed by such a complex data structure. In this article, we propose a nonparametric classification approach for imbalanced data in longitudinal and high-dimensional settings. Technically, the functional principal component analysis is first applied for feature extraction under the longitudinal structure. The univariate exponential loss function coupled with group LASSO penalty is then adopted into the classification procedure in high-dimensional settings. Along with a good improvement in imbalanced classification, our approach provides a meaningful feature selection for interpretation while enjoying a remarkably lower computational complexity. The proposed method is illustrated on the real data application of Alzheimer's disease early detection and its empirical performance in finite sample size is extensively evaluated by simulations.

Promising protein biomarkers in the early diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is an insidious, multifactorial disease that involves the devastation of neurons leading to cognitive impairments. Alzheimer's have compounded pathologies of diverse nature, including proteins as one important factor along with mutated genes and enzymes. Although various review articles have proposed biomarkers, still, the statistical importance of proteins is missing. Proteins associated with AD include amyloid precursor protein, glial fibrillary acidic protein, calmodulin-like skin protein, hepatocyte growth factor, matrix Metalloproteinase-2. These proteins play a crucial role in the AD hypothesis which includes the tau hypothesis, amyloid-beta (Aβ) hypothesis, cholinergic neuron damage, etc. The present review highlights the role of major proteins and their physiological functions in the early diagnosis of AD. Altered protein expression results in cognitive impairment, synaptic dysfunction, neuronal degradation, and memory loss. On the medicinal ground, efforts of making anti-amyloid, anti-tau, anti-inflammatory treatments are on the peak, having these proteins as putative targets. Few proteins, e.g., Amyloid precursor protein results in the formation of non-soluble sticky Aβ₄₀ and Aβ₄₂ monomers that, over time, aggregate into plaques in the cortical and limbic brain areas and neurogranin is believed to regulate calcium-mediated signaling pathways and thus modulating synaptic plasticity are few putative and potential forthcoming targets for developing effective anti-AD therapies. These proteins may help to diagnose the disease early, bode well for the successful discovery and development of therapeutic and preventative regimens for this devasting public health problem.

Polymer–Metal Composite Healthcare Materials: From Nano to Device Scale

Metals have been investigated as biomaterials for a wide range of medical applications. At nanoscale, some metals, such as gold nanoparticles, exhibit plasmonics, which have motivated researchers’ focus on biosensor development. At the device level, some metals, such as titanium, exhibit good physical properties, which could allow them to act as biomedical implants for physical support. Despite these attractive features, the non-specific delivery of metallic nanoparticles and poor tissue–device compatibility have greatly limited their performance. This review aims to illustrate the interplay between polymers and metals, and to highlight the pivotal role of polymer–metal composite/nanocomposite healthcare materials in different biomedical applications. Here, we revisit the recent plasmonic engineered platforms for biomolecules detection in cell-free samples and highlight updated nanocomposite design for (1) intracellular RNA detection, (2) photothermal therapy, and (3) nanomedicine for neurodegenerative diseases, as selected significant live cell–interactive biomedical applications. At the device scale, the rational design of polymer–metallic medical devices is of importance for dental and cardiovascular implantation to overcome the poor physical load transfer between tissues and devices, as well as implant compatibility under a dynamic fluidic environment, respectively. Finally, we conclude the treatment of these innovative polymer–metal biomedical composite designs and provide a future perspective on the aforementioned research areas.

Non-Invasive Nasal Discharge Fluid and Other Body Fluid Biomarkers in Alzheimer’s Disease

The key to current Alzheimer’s disease (AD) therapy is the early diagnosis for prompt intervention, since available treatments only slow the disease progression. Therefore, this lack of promising therapies has called for diagnostic screening tests to identify those likely to develop full-blown AD. Recent AD diagnosis guidelines incorporated core biomarker analyses into criteria, including amyloid-β (Aβ), total-tau (T-tau), and phosphorylated tau (P-tau). Though effective, the accessibility of screening tests involving conventional cerebrospinal fluid (CSF)- and blood-based analyses is often hindered by the invasiveness and high cost. In an attempt to overcome these shortcomings, biomarker profiling research using non-invasive body fluid has shown the potential to capture the pathological changes in the patients’ bodies. These novel non-invasive body fluid biomarkers for AD have emerged as diagnostic and pathological targets. Here, we review the potential peripheral biomarkers, including non-invasive peripheral body fluids of nasal discharge, tear, saliva, and urine for AD.