Current state of Alzheimer's fluid biomarkers

Tau- and α-synuclein-targeted gold nanoparticles: applications, opportunities, and future outlooks in the diagnosis and therapy of neurodegenerative diseases

The use of nanomaterials in medicine offers multiple opportunities to address neurodegenerative disorders such as Alzheimer's and Parkinson's disease. These diseases are a significant burden for society and the health system, affecting millions of people worldwide without sensitive and selective diagnostic methodologies or effective treatments to stop their progression. In this sense, the use of gold nanoparticles is a promising tool due to their unique properties at the nanometric level. They can be functionalized with specific molecules to selectively target pathological proteins such as Tau and α-synuclein for Alzheimer's and Parkinson's disease, respectively. Additionally, these proteins are used as diagnostic biomarkers, wherein gold nanoparticles play a key role in enhancing their signal, even at the low concentrations present in biological samples such as blood or cerebrospinal fluid, thus enabling an early and accurate diagnosis. On the other hand, gold nanoparticles act as drug delivery platforms, bringing therapeutic agents directly into the brain, improving treatment efficiency and precision, and reducing side effects in healthy tissues. However, despite the exciting potential of gold nanoparticles, it is crucial to address the challenges and issues associated with their use in the medical field before they can be widely applied in clinical settings. It is critical to ensure the safety and biocompatibility of these nanomaterials in the context of the central nervous system. Therefore, rigorous preclinical and clinical studies are needed to assess the efficacy and feasibility of these strategies in patients. Since there is scarce and sometimes contradictory literature about their use in this context, the main aim of this review is to discuss and analyze the current state-of-the-art of gold nanoparticles in relation to delivery, diagnosis, and therapy for Alzheimer's and Parkinson's disease, as well as recent research about their use in preclinical, clinical, and emerging research areas.

Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics

The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aβ), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.

Lipid nanoparticle mediated small interfering RNA delivery as a potential therapy for Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative condition that exhibits a gradual decline in cognitive function and is prevalent among a significant number of individuals globally. The use of small interfering RNA (siRNA) molecules in RNA interference (RNAi) presents a promising therapeutic strategy for AD. Lipid nanoparticles (LNPs) have been developed as a delivery vehicle for siRNA, which can selectively suppress target genes, by enhancing cellular uptake and safeguarding siRNA from degradation. Numerous research studies have exhibited the effectiveness of LNP-mediated siRNA delivery in reducing amyloid beta (Aβ) levels and enhancing cognitive function in animal models of AD. The feasibility of employing LNP-mediated siRNA delivery as a therapeutic approach for AD is emphasized by the encouraging outcomes reported in clinical studies for other medical conditions. The use of LNP-mediated siRNA delivery has emerged as a promising strategy to slow down or even reverse the progression of AD by targeting the synthesis of tau phosphorylation and other genes linked to the condition. Improvement of the delivery mechanism and determination of the most suitable siRNA targets are crucial for the efficacious management of AD. This review focuses on the delivery of siRNA through LNPs as a promising therapeutic strategy for AD, based on the available literature.

Serum NFL and tau, but not serum UCHL-1 and GFAP or CSF SNAP-25, NPTX2, or sTREM2, correlate with delirium in a 3-year retrospective analysis

Delirium represents a common terminal pathway of heterogeneous neurological conditions characterized by disturbances in consciousness and attention. Contemporary theories highlight the acute impairment of synaptic function and network connectivity, driven by neuroinflammation, oxidative stress, and neurotransmitter imbalances. However, established biomarkers are still missing. Innovative diagnostic techniques, such as single-molecule array analysis, enable the detection of biomarkers in blood at picomolar concentrations. This approach paves the way for deeper insights into delirium and potentially therapeutic targets for tailored medical treatments. In a retrospective 3-year study, we investigated seven biomarkers indicative of neuroaxonal damage [neurofilament light chain (NFL), ubiquitin carboxyl-terminal hydrolase (UCHL-1), and tau protein], microglial activation [glial fibrillary acidic protein (GFAP) and soluble triggering receptor expressed on myeloid cells 2 (sTREM2)], and synaptic dysfunction [synaptosomal-associated protein 25 (SNAP-25) and neuronal pentraxin 2 (NPTX2)]. The analysis of 71 patients with delirium, Alzheimer's disease (AD), and non-AD controls revealed that serum NFL levels are higher in delirium cases compared to both AD and non-AD. This suggests that elevated NFL levels in delirium are not exclusively the result of dementia-related damage. Serum tau levels were also elevated in delirium cases compared to controls. Conversely, cerebrospinal fluid (CSF) SNAP-25 showed higher levels in AD patients compared to controls only. These findings add to the increasing body of evidence suggesting that serum NFL could be a valuable biomarker of neuroaxonal damage in delirium research. Although SNAP-25 and NPTX2 did not exhibit significant differences in delirium, the exploration of synaptic biomarkers remains promising for enhancing our understanding of this condition.

Predicting mild cognitive impairment in older adults: A machine learning analysis of the Alzheimer's Disease Neuroimaging Initiative

AIM

Mild cognitive impairment (MCI) in older adults is potentially devastating, but an accurate prediction model is still lacking. We hypothesized that neuropsychological tests and MRI-related markers could predict the onset of MCI early.

METHODS

We analyzed data from 306 older adults who were cognitive normal (CN) attending the Alzheimer's Disease Neuroimaging Initiative sequentially (474 pairs of visits) within 3 years. There were 231 pairs of MCI conversion (CN to MCI), and 242 pairs of CN maintenance (CN to CN). Variables on demographic, neuropsychological tests, genetic, and MRI-related markers were collected. Machine learning was used to construct MCI prediction models, comparing the area under the receiver operating characteristic curve (AUC) as the primary metric of performance. Important predictors were ranked for the optimal model.

RESULTS

The baseline age of the study sample was 74.8 years old. The best-performing model (gradient boosting decision tree) with 13 variables predicted MCI with an AUC of 0.819, and the rank of variable importance showed that intracranial volume, hippocampal volume, and score from task 4 (word recognition) of the Alzheimer's Disease Assessment Scale were important predictors of MCI.

CONCLUSIONS

With the help of machine learning, fewer neuropsychological tests and MRI-related markers are required to accurately predict MCI within 3 years, thereby facilitating targeted intervention. Geriatr Gerontol Int 2024; 24: 96-101.

Biomarker Changes during 20 Years Preceding Alzheimer's Disease

BACKGROUND

Biomarker changes that occur in the period between normal cognition and the diagnosis of sporadic Alzheimer's disease have not been extensively investigated in longitudinal studies.

METHODS

We conducted a multicenter, nested case-control study of Alzheimer's disease biomarkers in cognitively normal participants who were enrolled in the China Cognition and Aging Study from January 2000 through December 2020. A subgroup of these participants underwent testing of cerebrospinal fluid (CSF), cognitive assessments, and brain imaging at 2-year-to-3-year intervals. A total of 648 participants in whom Alzheimer's disease developed were matched with 648 participants who had normal cognition, and the temporal trajectories of CSF biochemical marker concentrations, cognitive testing, and imaging were analyzed in the two groups.

RESULTS

The median follow-up was 19.9 years (interquartile range, 19.5 to 20.2). CSF and imaging biomarkers in the Alzheimer's disease group diverged from those in the cognitively normal group at the following estimated number of years before diagnosis: amyloid-beta (Aβ)42, 18 years; the ratio of Aβ42 to Aβ40, 14 years; phosphorylated tau 181, 11 years; total tau, 10 years; neurofilament light chain, 9 years; hippocampal volume, 8 years; and cognitive decline, 6 years. As cognitive impairment progressed, the changes in CSF biomarker levels in the Alzheimer's disease group initially accelerated and then slowed.

CONCLUSIONS

In this study involving Chinese participants during the 20 years preceding clinical diagnosis of sporadic Alzheimer's disease, we observed the time courses of CSF biomarkers, the times before diagnosis at which they diverged from the biomarkers from a matched group of participants who remained cognitively normal, and the temporal order in which the biomarkers became abnormal. (Funded by the Key Project of the National Natural Science Foundation of China and others; ClinicalTrials.gov number, NCT03653156.).

Salivary Biomarkers for Parkinson's Disease: A Systematic Review with Meta-Analysis

Parkinson's Disease (PD) is a common neurodegenerative disease which manifests with motor features, such as bradykinesia, resting tremor, rigidity, and postural instability. Using the non-invasive technique of saliva collection, we designed a systematic review to answer the question "Are salivary biomarkers reliable for the diagnosis of Parkinson's Disease?". Following inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Mostly proteins were reported as potential biomarkers in saliva. Based on meta-analysis, in PD patients, salivary levels of total alpha-synuclein were significantly decreased, and those of oligomeric alpha-synuclein were significantly increased. Also, according to pooled AUC, heme oxygenase-1 demonstrated significant predictive value for saliva-based PD diagnosis. In conclusion, some potential biomarkers, especially alpha-synuclein, can be altered in the saliva of PD patients, which could be reliably useful for early diagnosis of this neurodegenerative disease differentiating other synucleopathies.

Alzheimer's Disease Biomarker Analysis Using Targeted Mass Spectrometry

Alzheimer's disease (AD) is characterized by several neuropathological changes, mainly extracellular amyloid aggregates (plaques), intraneuronal inclusions of phosphorylated tau (tangles), as well as neuronal and synaptic degeneration, accompanied by tissue reactions to these processes (astrocytosis and microglial activation) that precede neuronal network disturbances in the symptomatic phase of the disease. A number of biomarkers for these brain tissue changes have been developed, mainly using immunoassays. In this review, we discuss how targeted mass spectrometry (TMS) can be used to validate and further characterize classes of biomarkers reflecting different AD pathologies, such as tau- and amyloid-beta pathologies, synaptic dysfunction, lysosomal dysregulation, and axonal damage, and the prospect of using TMS to measure these proteins in clinical research and diagnosis. TMS advantages and disadvantages in relation to immunoassays are discussed, and complementary aspects of the technologies are discussed.

Small RNA Changes in Plasma Have Potential for Early Diagnosis of Alzheimer's Disease before Symptom Onset

Alzheimer's disease (AD), due to its multifactorial nature and complex etiology, poses challenges for research, diagnosis, and treatment, and impacts millions worldwide. To address the need for minimally invasive, repeatable measures that aid in AD diagnosis and progression monitoring, studies leveraging RNAs associated with extracellular vesicles (EVs) in human biofluids have revealed AD-associated changes. However, the validation of AD biomarkers has suffered from the collection of samples from differing points in the disease time course or a lack of confirmed AD diagnoses. Here, we integrate clinical diagnosis and postmortem pathology data to form more accurate experimental groups and use small RNA sequencing to show that EVs from plasma can serve as a potential source of RNAs that reflect disease-related changes. Importantly, we demonstrated that these changes are identifiable in the EVs of preclinical patients, years before symptom manifestation, and that machine learning models based on differentially expressed RNAs can help predict disease conversion or progression. This research offers critical insight into early disease biomarkers and underscores the significance of accounting for disease progression and pathology in human AD studies.

Improving Regression Analysis with Imputation in a Longitudinal Study of Alzheimer's Disease

Background

Missing data is prevalent in the Alzheimer's Disease Neuroimaging Initiative (ADNI). It is common to deal with missingness by removing subjects with missing entries prior to statistical analysis; however, this can lead to significant efficiency loss and sometimes bias. It has yet to be demonstrated that the imputation approach to handling this issue can be valuable in some longitudinal regression settings.

Objective

The purpose of this study is to demonstrate the importance of imputation and how imputation is correctly done in ADNI by analyzing longitudinal Alzheimer's Disease Assessment Scale -Cognitive Subscale 13 (ADAS-Cog 13) scores and their association with baseline patient characteristics.

Methods

We studied 1,063 subjects in ADNI with mild cognitive impairment. Longitudinal ADAS-Cog 13 scores were modeled with a linear mixed-effects model with baseline clinical and demographic characteristics as predictors. The model estimates obtained without imputation were compared with those obtained after imputation with Multiple Imputation by Chained Equations (MICE). We justify application of MICE by investigating the missing data mechanism and model assumptions. We also assess robustness of the results to the choice of imputation method.

Results

The fixed-effects estimates of the linear mixed-effects model after imputation with MICE yield valid, tighter confidence intervals, thus improving the efficiency of the analysis when compared to the analysis done without imputation.

Conclusions

Our study demonstrates the importance of accounting for missing data in ADNI. When deciding to perform imputation, care should be taken in choosing the approach, as an invalid one can compromise the statistical analyses.

An activatable small-molecule fluorogenic probe for detection and quantification of beta-amyloid aggregates

Extracellular accumulation of β amyloid (Aβ) peptides in the brain is thought to be a pathological hallmark and initial event before the symptom starts of Alzheimer's patients. Herein, we developed two series of benzo[d]thiazole-based small-molecule compounds (BM1-BM4, BPM1-BPM4) with a donor-acceptor (D-A) or donor-π-acceptor (D-π-A) architecture, respectively, based on structure-activity relationship. Among them, the optimized BPM1 not only displayed the highest binding affinity to Aβ aggregates over other proteins or Aβ monomers, but was readily activated its fluorescence with 10-fold fluorescence enhancement, allowing for specifically and sensitively detecting Aβ aggregates. BPM1 also exhibits several other advantages including low molecular weight, low cytotoxicity and excellent biological stability. Besides, cell staining results confirmed that SK-N-BE(2) cells can be fluorescently lighted up as well as cell permeability and damage when treated with BPM1-bound Aβ1-42 aggregates.

Cerebrospinal and Blood Biomarkers in Alzheimer's Disease: Did Mild Cognitive Impairment Definition Affect Their Clinical Usefulness?

Despite Alzheimer's Disease (AD) being known from the times of Alois Alzheimer, who lived more than one century ago, many aspects of the disease are still obscure, including the pathogenesis, the clinical spectrum definition, and the therapeutic approach. Well-established biomarkers for AD come from the histopathological hallmarks of the disease, which are Aβ and phosphorylated Tau protein aggregates. Consistently, cerebrospinal fluid (CSF) Amyloid β (Aβ) and phosphorylated Tau level measurements are currently used to detect AD presence. However, two central biases affect these biomarkers. Firstly, incomplete knowledge of the pathogenesis of diseases legitimates the search for novel molecules that, reasonably, could be expressed by neurons and microglia and could be detected in blood simpler and earlier than the classical markers and in a higher amount. Further, studies have been performed to evaluate whether CSF biomarkers can predict AD onset in Mild Cognitive Impairment (MCI) patients. However, the MCI definition has changed over time. Hence, the studies on MCI patients seem to be biased at the beginning due to the imprecise enrollment and heterogeneous composition of the miscellaneous MCI subgroup. Plasma biomarkers and novel candidate molecules, such as microglia biomarkers, have been tentatively investigated and could represent valuable targets for diagnosing and monitoring AD. Also, novel AD markers are urgently needed to identify molecular targets for treatment strategies. This review article summarizes the main CSF and blood AD biomarkers, underpins their advantages and flaws, and mentions novel molecules that can be used as potential biomarkers for AD.

Understanding the Episodic Memory and Executive Functioning Axis Impairment in MCI Patients: A Multicenter Study in Comparison with CSF Biomarkers

BACKGROUND

This study aimed to explore the association between a verbal learning task that evaluates the potential mutual dependency between memory and executive functions (i.e., the Test of Memory Strategies, TMS) and cerebrospinal fluid (CSF) Alzheimer's Disease (AD) biomarkers.

METHODS

A sample of 47 mild cognitive impairment (MCI) participants from Poland and Spain were classified according to the Erlangen Score Diagnostic Algorithm (ESA) into CSF- (n = 16) and CSF+ (n = 31) groups. Correlation analyses between TMS word-list conditions and CSF biomarkers were conducted. Additionally, an analysis of covariance was performed to define the effect on ESA classification in the sample, using as a covariable the country of origin of the participants.

RESULTS

Significant associations between the TMS-3 condition and Aβ42, t-tau, and p-tau were observed for the whole sample. In addition, the CSF- participants obtained higher cognitive performance in TMS-3 compared to the CSF+ group. This outcome persisted if the groups were based on Aβ42 scores, but not t-tau or p-tau values.

CONCLUSIONS

These findings could indicate that poor performance on verbal learning tests may be affected by executive dysfunctions. Therefore, future intervention plans focused on training executive functions would be of interest to improve the ability of MCI patients to encode and organize information.

CSF 14-3-3β is associated with progressive cognitive decline in Alzheimer's disease

Alzheimer's disease is a neurodegenerative disorder characterized pathologically by amyloid-beta plaques, tau tangles and neuronal loss. In clinical practice, the 14-3-3 isoform beta (β) is a biomarker that aids in the diagnosis of sporadic Creutzfeldt-Jakob disease. Recently, a proteomics study found increased CSF 14-3-3β levels in Alzheimer's disease patients, suggesting a potential link between CSF 14-3-3β and Alzheimer's disease. Our present study aimed to further investigate the role of CSF 14-3-3β in Alzheimer's disease by analysing the data of 719 participants with available CSF 14-3-3β measurements from the Alzheimer's Disease Neuroimaging Initiative. Higher CSF 14-3-3β levels were observed in the mild cognitive impairment group compared to the cognitively normal group, with the highest CSF 14-3-3β levels in the Alzheimer's disease dementia group. This study also found significant associations between CSF 14-3-3β levels and CSF biomarkers of p-tau, t-tau, pTau/Aβ42 ratios and GAP-43, as well as other Alzheimer's disease biomarkers such as Aβ-PET. An early increase in CSF 14-3-3β levels was observed prior to Aβ-PET-positive status, and CSF 14-3-3β levels continued to rise after crossing the Aβ-PET positivity threshold before reaching a plateau. The diagnostic accuracy of CSF 14-3-3β (area under the receiver operating characteristic curve = 0.819) was moderate compared to other established Alzheimer's disease biomarkers in distinguishing cognitively normal Aβ pathology-negative individuals from Alzheimer's disease Aβ pathology-positive individuals. Higher baseline CSF 14-3-3β levels were associated with accelerated cognitive decline, reduced hippocampus volumes and declining fluorodeoxyglucose-PET values over a 4-year follow-up period. Patients with mild cognitive impairment and high CSF 14-3-3β levels at baseline had a significantly increased risk [hazard ratio = 2.894 (1.599-5.238), P < 0.001] of progression to Alzheimer's disease dementia during follow-up. These findings indicate that CSF 14-3-3β may be a potential biomarker for Alzheimer's disease and could provide a more comprehensive understanding of the underlying pathological changes of Alzheimer's disease, as well as aid in the diagnosis and monitoring of disease progression.

CSF biomarker analysis of ABCA7 mutation carriers suggests altered APP processing and reduced inflammatory response

BACKGROUND

The Alzheimer's disease (AD) risk gene ABCA7 has suggested functions in lipid metabolism and the immune system. Rare premature termination codon (PTC) mutations and an expansion of a variable number of tandem repeats (VNTR) polymorphism in the gene, both likely cause a lower ABCA7 expression and hereby increased risk for AD. However, the exact mechanism of action remains unclear. By studying CSF biomarkers reflecting different types of AD-related pathological processes, we aim to get a better insight in those processes and establish a biomarker profile of mutation carriers.

METHODS

The study population consisted of 229 AD patients for whom CSF was available and ABCA7 sequencing and VNTR genotyping had been performed. This included 28 PTC mutation and 16 pathogenic expansion carriers. CSF levels of Aβ1-42, Aβ1-40, P-tau181, T-tau, sAPPα, sAPPβ, YKL-40, and hFABP were determined using ELISA and Meso Scale Discovery assays. We compared differences in levels of these biomarkers and the Aβ ratio between AD patients with or without an ABCA7 PTC mutation or expansion using linear regression on INT-transformed data with APOE-status, age and sex as covariates.

RESULTS

Carriers of ABCA7 expansion mutations had significantly lower Aβ1-42 levels (P = 0.022) compared with non-carrier patients. The effect of the presence of ABCA7 mutations on CSF levels was especially pronounced in APOE ε4-negative carriers. In addition, VNTR expansion carriers had reduced Aβ1-40 (P = 0.023), sAPPα (P = 0.047), sAPPβ (P = 0.016), and YKL-40 (P = 0.0036) levels.

CONCLUSIONS

Our results are suggestive for an effect on APP processing by repeat expansions given the changes in the amyloid-related CSF biomarkers that were found in carriers. The decrease in YKL-40 levels in expansion carriers moreover suggests that these patients potentially have a reduced inflammatory response to AD damage. Moreover, our findings suggest the existence of a mechanism, independent of lowered expression, affecting neuropathology in expansion carriers.

Computational saturation mutagenesis to explore the effect of pathogenic mutations on extra-cellular domains of TREM2 associated with Alzheimer's and Nasu-Hakola disease

CONTEXT

The specialised family of triggering receptors expressed on myeloid cells (TREMs) plays a pivotal role in causing neurodegenerative disorders and activating microglial anti-inflammatory responses. Nasu-Hakola disease (NHD), a rare autosomal recessive disorder, has been associated with mutations in TREM2, which is also responsible for raising the risk of Alzheimer's disease (AD). Herein, we have made an endeavour to differentiate the confirmed pathogenic variants in TREM2 extra-cellular domain (ECD) linked with NHD and AD using mutation-induced fold stability change (∆∆G), with the computation of 12distinct structure-based methods through saturation mutagenesis. Correlation analysis between relative solvent accessibility (RSA) and ∆∆G expresses the discrete distributive behaviour of mutants associated with TREM2 in AD (R2 = 0.061) and NHD (R2 = 0.601). Our findings put an emphasis on W50 and V126 as major players in maintaining V-like domain in TREM2. Interestingly, we discern that both of them interact with a common residue Y108, which is dissolved upon mutation. This Y108 could have structural or functional role for TREM2 which can be an ideal candidate for further study. Furthermore, the residual interaction network highlights the importance of R47 and R62 in maintaining the CDR loops that are crucial for ligand binding. Future studies using biophysical characterisation of ligand interactions in TREM2-ECD would be helpful for the development of novel therapeutics for AD and NHD.

METHODS

ConSurf algorithm and ENDscript were used to determine the position and conservation of each residue in the wild-type ECD of TREM2. The mutation-induced fold stability change (∆∆G) of confirmed pathogenic mutants associated with NHD and AD was estimated using 12 state-of-the-art structure-based protein stability tools. Furthermore, we also computed the effect of random mutation on these sites using computational saturation mutagenesis. Linear regression analysis was performed using mutants ∆∆G and RSA through GraphPad software. In addition, a comprehensive non-bonded residual interaction network (RIN) of wild type and its mutants of TREM2-ECD was enumerated using RING3.0.

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.

Magneto-assisted enzymatic DNA walkers for simultaneous electrochemical detection of amyloid-beta oligomers and Tau

DNA walkers have been widely explored and applied as biosensor elements to detect disease-related biomarkers. Traditional interface-anchored DNA walkers typically have a fixed swing arm range and an orientation of the preset track, which might complicate the design of a sensor system and limit its application in more scenes. We propose a simple electrochemical aptasensor to accurately detect Alzheimer's disease (AD) based on a nicking enzyme-powered DNA walker. In this method, bifunctional magnetic nanoparticles are used to identify and capture Aβ oligomers (AβO) and Tau and release the DNA walker. As the DNA walker moves freely on the surface of the electrode, the nicking enzymes circularly cleave and release the two signal substrate chains, significantly amplifying the signal. It has been demonstrated that the constructed sensor can sensitively detect AβO and Tau, and the combined analysis of dual markers improves the accuracy of AD diagnosis. Furthermore, this method can distinguish normal individuals from AD patients in real cerebrospinal fluid samples. The excellent performance of this biosensor makes it promising for clinical applications in diagnosing AD patients and prognosis assessment.

Plasma biomarkers predict Alzheimer's disease before clinical onset in Chinese cohorts

Plasma amyloid-β (Aβ)42, phosphorylated tau (p-tau)181, and neurofilament light chain (NfL) are promising biomarkers of Alzheimer's disease (AD). However, whether these biomarkers can predict AD in Chinese populations is yet to be fully explored. We therefore tested the performance of these plasma biomarkers in 126 participants with preclinical AD and 123 controls with 8-10 years of follow-up from the China Cognition and Aging Study. Plasma Aβ42, p-tau181, and NfL were significantly correlated with cerebrospinal fluid counterparts and significantly altered in participants with preclinical AD. Combining plasma Aβ42, p-tau181, and NfL successfully discriminated preclinical AD from controls. These findings were validated in a replication cohort including 51 familial AD mutation carriers and 52 non-carriers from the Chinese Familial Alzheimer's Disease Network. Here we show that plasma Aβ42, p-tau181, and NfL may be useful for predicting AD 8 years before clinical onset in Chinese populations.

Cognitive impact of multidomain intervention and omega 3 according to blood Aβ42/40 ratio: a subgroup analysis from the randomized MAPT trial

BACKGROUND

In MAPT (Multidomain Alzheimer Preventive Trial), a cognitive effect of multidomain intervention (MI) was showed in non-demented subjects with positive amyloid PET. However, screening eligible patients for multidomain intervention by PET is difficult to generalize in real-world settings.

METHODS

MAPT study was a 3-year, randomized, placebo-controlled trial followed by a 2-year observational and optional extension. All participants were non-demented and randomly assigned (1:1:1:1) to the MI plus omega 3, MI plus placebo, omega 3 alone, or placebo alone group. The objectives were to assess the cognitive effect of MAPT interventions (omega 3 supplementation, MI, combined intervention) in non-demented subjects according to amyloid blood status at 12, 36, and 60 months. In this subgroup analysis (n = 483), amyloid status was defined by plasma Aβ42/40 ratio (cutoff ≤ 0.0107). The primary outcome measure was the change in cognitive composite score after a 1, 3, and 5-year clinical follow-up.

RESULTS

The intention-to-treat (ITT) population included 483 subjects (161 positive and 322 negative amyloid participants based on plasma Aβ42/40 ratio). In the positive amyloid ITT population, we showed a positive effect of MI plus omega 3 on the change in composite cognitive score in 12 (raw p = .0350, 0.01917, 95% CI = [0.0136 to 0.3699]) and 36 months (raw p = .0357, 0.2818, 95% CI = [0.0190 to 0.5446]). After correction of multiple comparisons and adjustments, these differences were not significant (adjusted p = .1144 and .0690). In the per-protocol positive amyloid group (n = 154), we observed a significant difference between the combined intervention and placebo groups at 12 (p = .0313, 0.2424, 0.0571 to 0.4276) and 36 months (p = .0195, 0.3747, 0.1055 to 0.6439) persisting after adjustment. In the ITT and per-protocol analyses, no cognitive effect was observed in the positive and negative amyloid group at 60-month visit.

CONCLUSIONS

These findings suggest a benefit of MI plus omega 3 in positive blood amyloid subjects. This promising trend needs to be confirmed before using blood biomarkers for screening in preventive trials.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01513252 .

Plasma biomarkers identify older adults at risk of Alzheimer's disease and related dementias in a real-world population-based cohort

INTRODUCTION

Plasma biomarkers-cost effective, non-invasive indicators of Alzheimer's disease (AD) and related disorders (ADRD)-have largely been studied in clinical research settings. Here, we examined plasma biomarker profiles and their associated factors in a population-based cohort to determine whether they could identify an at-risk group, independently of brain and cerebrospinal fluid biomarkers.

METHODS

We measured plasma phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid beta (Aβ)42/40 ratio in 847 participants from a population-based cohort in southwestern Pennsylvania.

RESULTS

K-medoids clustering identified two distinct plasma Aβ42/40 modes, further categorizable into three biomarker profile groups: normal, uncertain, and abnormal. In different groups, plasma p-tau181, NfL, and GFAP were inversely correlated with Aβ42/40, Clinical Dementia Rating, and memory composite score, with the strongest associations in the abnormal group.

DISCUSSION

Abnormal plasma Aβ42/40 ratio identified older adult groups with lower memory scores, higher dementia risks, and higher ADRD biomarker levels, with potential implications for population screening.

HIGHLIGHTS

Population-based plasma biomarker studies are lacking, particularly in cohorts without cerebrospinal fluid or neuroimaging data. In the Monongahela-Youghiogheny Healthy Aging Team study (n = 847), plasma biomarkers associated with worse memory and Clinical Dementia Rating (CDR), apolipoprotein E ε4, and greater age. Plasma amyloid beta (Aβ)42/40 ratio levels allowed clustering participants into abnormal, uncertain, and normal groups. Plasma Aβ42/40 correlated differently with neurofilament light chain, glial fibrillary acidic protein, phosphorylated tau181, memory composite, and CDR in each group. Plasma biomarkers can enable relatively affordable and non-invasive community screening for evidence of Alzheimer's disease and related disorders pathophysiology.

Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology

Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.

Plasma p-tau231 and p-tau217 inform on tau tangles aggregation in cognitively impaired individuals

INTRODUCTION

Phosphorylated tau (p-tau) biomarkers have been recently proposed to represent brain amyloid-β (Aβ) pathology. Here, we evaluated the plasma biomarkers' contribution beyond the information provided by demographics (age and sex) to identify Aβ and tau pathologies in individuals segregated as cognitively unimpaired (CU) and impaired (CI).

METHODS

We assessed 138 CU and 87 CI with available plasma p-tau231, 217+ , and 181, Aβ42/40, GFAP and Aβ- and tau-PET.

RESULTS

In CU, only plasma p-tau231 and p-tau217+ significantly improved the performance of the demographics in detecting Aβ-PET positivity, while no plasma biomarker provided additional information to identify tau-PET positivity. In CI, p-tau217+ and GFAP significantly contributed to demographics to identify both Aβ-PET and tau-PET positivity, while p-tau231 only provided additional information to identify tau-PET positivity.

DISCUSSION

Our results support plasma p-tau231 and p-tau217+ as state markers of early Aβ deposition, but in later disease stages they inform on tau tangle accumulation.

HIGHLIGHTS

It is still unclear how much plasma biomarkers contribute to identification of AD pathology across the AD spectrum beyond the information already provided by demographics (age + sex). Plasma p-tau231 and p-tau217+ contribute to demographic information to identify brain Aβ pathology in preclinical AD. In CI individuals, plasma p-tau231 contributes to age and sex to inform on the accumulation of tau tangles, while p-tau217+ and GFAP inform on both Aβ deposition and tau pathology.

A blood-based, metabolite and demographic characteristic markers panel for the diagnosis of Alzheimer's disease

Aims: This work was designed to provide early diagnosis strategies for Alzheimer's disease (AD) based on the identification of blood metabolic biomarkers. Patients & methods: A total of 90 subjects aged 60 years or older were included in this study; 45 patients were assigned to the case group and control group, respectively. A total of 31 target metabolites were quantitatively analyzed by parallel reaction monitoring between the two groups. Results & conclusion: Three metabolites were screened out, including cystine, serine and alanine/sarcosine. Logistic regression and random forest analysis were used to establish AD diagnosis models, and the model combining metabolic biomarkers and demographic variables had higher detection efficiency (area under the curve = 0.869). A combination diagnostic model to provide a scientific reference for early screening and diagnosis of AD was constructed.

Unraveling the Potential of EphA4: A Breakthrough Target and Beacon of Hope for Neurological Diseases

Erythropoietin-producing hepatocellular carcinoma A4 (EphA4) is a transmembrane receptor protein which is a part of the most prominent family of receptor tyrosine kinases (RTKs). It serves a crucial role in both physiological, biological, and functional states binding with their ligand like Ephrins. Its abundance in the majority of the body's systems has been reported. Moreover, it draws much attention in the CNS since it influences axonal and vascular guidance. Also, it has a widespread role at the pathological state of various CNS disorders. Reports suggest it obstructs axonal regeneration in various neurodegenerative diseases and neurological disorders. Although, neuro-regeneration is still an open challenge to the modern drug discovery community.  Hence, in this review, we will provide information about the role of EphA4 in neurological diseases by which it may emerge as a therapeutic target for CNS disease. We will also provide a glance at numerous signaling pathways that activate or inhibit the EphA4-associated biological processes contributing to the course of neurodegenerative diseases. Thus, this work might serve as a basis for futuristic studies that are related to the target-based drug discovery in the field of neuro-regeneration. Pathological and physiological events associated with EphA4 and Ephrin upregulation and interaction.

Harnessing acoustic speech parameters to decipher amyloid status in individuals with mild cognitive impairment

Alzheimer's disease (AD) is a neurodegenerative condition characterized by a gradual decline in cognitive functions. Currently, there are no effective treatments for AD, underscoring the importance of identifying individuals in the preclinical stages of mild cognitive impairment (MCI) to enable early interventions. Among the neuropathological events associated with the onset of the disease is the accumulation of amyloid protein in the brain, which correlates with decreased levels of Aβ42 peptide in the cerebrospinal fluid (CSF). Consequently, the development of non-invasive, low-cost, and easy-to-administer proxies for detecting Aβ42 positivity in CSF becomes particularly valuable. A promising approach to achieve this is spontaneous speech analysis, which combined with machine learning (ML) techniques, has proven highly useful in AD. In this study, we examined the relationship between amyloid status in CSF and acoustic features derived from the description of the Cookie Theft picture in MCI patients from a memory clinic. The cohort consisted of fifty-two patients with MCI (mean age 73 years, 65% female, and 57% positive amyloid status). Eighty-eight acoustic parameters were extracted from voice recordings using the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), and several ML models were used to classify the amyloid status. Furthermore, interpretability techniques were employed to examine the influence of input variables on the determination of amyloid-positive status. The best model, based on acoustic variables, achieved an accuracy of 75% with an area under the curve (AUC) of 0.79 in the prediction of amyloid status evaluated by bootstrapping and Leave-One-Out Cross Validation (LOOCV), outperforming conventional neuropsychological tests (AUC = 0.66). Our results showed that the automated analysis of voice recordings derived from spontaneous speech tests offers valuable insights into AD biomarkers during the preclinical stages. These findings introduce novel possibilities for the use of digital biomarkers to identify subjects at high risk of developing AD.

Navigating Early Alzheimer's Diagnosis: A Comprehensive Review of Diagnostic Innovations

The hunt for early Alzheimer's disease detection has created cutting-edge diagnostic instruments with enormous promise. This article examines the many facets of these developments, focusing on how they have revolutionised diagnosis and patient outcomes. These tools make it possible to detect tiny brain changes even before they give birth to clinical symptoms by combining cutting-edge biomarkers, neuroimaging methods, and machine-learning algorithms. A significant opportunity for therapies that can slow the course of the disease exists during this early detection stage. Additionally, these cutting-edge techniques improve diagnostic precision, objectivity, and accessibility. Liquid biopsies and blood-based biomarkers provide non-invasive alternatives, filling accessibility gaps in diagnosis. While issues with standardisation, ethics, and data integration continue, collaboration within research, clinical practice, and policy realms fuels positive developments. As technology advances, the way towards better Alzheimer's diagnosis becomes more evident, giving patients and families dealing with this difficult illness fresh hope. The synergy between scientific advancement and compassionate treatment is crucial for improving Alzheimer's disease diagnosis, as this paper emphasises.

Deciphering Protein Secretion from the Brain to Cerebrospinal Fluid for Biomarker Discovery

Cerebrospinal fluid (CSF) is an essential matrix for the discovery of neurological disease biomarkers. However, the high dynamic range of protein concentrations in CSF hinders the detection of the least abundant protein biomarkers by untargeted mass spectrometry. It is thus beneficial to gain a deeper understanding of the secretion processes within the brain. Here, we aim to explore if and how the secretion of brain proteins to the CSF can be predicted. By combining a curated CSF proteome and the brain elevated proteome of the Human Protein Atlas, brain proteins were classified as CSF or non-CSF secreted. A machine learning model was trained on a range of sequence-based features to differentiate between CSF and non-CSF groups and effectively predict the brain origin of proteins. The classification model achieves an area under the curve of 0.89 if using high confidence CSF proteins. The most important prediction features include the subcellular localization, signal peptides, and transmembrane regions. The classifier generalized well to the larger brain detected proteome and is able to correctly predict novel CSF proteins identified by affinity proteomics. In addition to elucidating the underlying mechanisms of protein secretion, the trained classification model can support biomarker candidate selection.

Blood-brain barrier integrity impacts the use of plasma amyloid-β as a proxy of brain amyloid-β pathology

INTRODUCTION

Amyloid-β (Aβ) and tau can be quantified in blood. However, biological factors can influence the levels of brain-derived proteins in the blood. The blood-brain barrier (BBB) regulates protein transport between cerebrospinal fluid (CSF) and blood. BBB altered permeability might affect the relationship between brain and blood biomarkers.

METHODS

We assessed 224 participants in research (TRIAD, n = 96) and clinical (BIODEGMAR, n = 128) cohorts with plasma and CSF/positron emission tomography Aβ, p-tau, and albumin measures.

RESULTS

Plasma Aβ42/40 better identified CSF Aβ42/40 and Aβ-PET positivity in individuals with high BBB permeability. An interaction between plasma Aβ42/40 and BBB permeability on CSF Aβ42/40 was observed. Voxel-wise models estimated that the association of positron emission tomography (PET), with plasma Aβ was most affected by BBB permeability in AD-related brain regions. BBB permeability did not significantly impact the relationship between brain and plasma p-tau levels.

DISCUSSION

These findings suggest that BBB integrity may influence the performance of plasma Aβ, but not p-tau, biomarkers in research and clinical settings.

HIGHLIGHTS

BBB permeability affects the association between brain and plasma Aβ levels. BBB integrity does not affect the association between brain and plasma p-tau levels. Plasma Aβ was most affected by BBB permeability in AD-related brain regions. BBB permeability increases with age but not according to cognitive status.

Blood levels of neurofilament light are associated with disease progression in a mouse model of spinocerebellar ataxia type 3

Increased neurofilament light (NfL; NEFL) protein in biofluids is reflective of neurodegeneration and has gained interest as a biomarker across neurodegenerative diseases. In spinocerebellar ataxia type 3 (SCA3), the most common dominantly inherited ataxia, patients exhibit progressive NfL increases in peripheral blood when becoming symptomatic, and NfL remains stably elevated throughout further disease course. However, progressive NfL changes are not yet validated in relevant preclinical SCA3 animal models, hindering its application as a biomarker during therapeutic development. We used ultra-sensitive single-molecule array (Simoa) to measure blood NfL over disease progression in YACQ84 mice, a model of SCA3, assessing relationships with measures of disease severity including age, CAG repeat size and magnetic resonance spectroscopy. YACQ84 mice exhibited plasma NfL increases that were concomitant with ataxia-related motor deficits as well as increased serum NfL, which correlated with previously established neurometabolite abnormalities, two relevant measures of disease in patients with SCA3. Our findings establish the progression of NfL increases in the preclinical YACQ84 mouse, further supporting the utility of blood NfL as a peripheral neurodegeneration biomarker and informing on coinciding timelines of different measures of SCA3 pathogenesis.

Mesenchymal Stem Cell-Derived Extracellular Vesicles: An Emerging Diagnostic and Therapeutic Biomolecules for Neurodegenerative Disabilities

Mesenchymal stem cells (MSCs) are a type of versatile adult stem cells present in various organs. These cells give rise to extracellular vesicles (EVs) containing a diverse array of biologically active elements, making them a promising approach for therapeutics and diagnostics. This article examines the potential therapeutic applications of MSC-derived EVs in addressing neurodegenerative disorders such as Alzheimer's disease (AD), multiple sclerosis (MS), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD). Furthermore, the present state-of-the-art for MSC-EV-based therapy in AD, HD, PD, ALS, and MS is discussed. Significant progress has been made in understanding the etiology and potential treatments for a range of neurodegenerative diseases (NDs) over the last few decades. The contents of EVs are carried across cells for intercellular contact, which often results in the control of the recipient cell's homeostasis. Since EVs represent the therapeutically beneficial cargo of parent cells and are devoid of many ethical problems connected with cell-based treatments, they offer a viable cell-free therapy alternative for tissue regeneration and repair. Developing innovative EV-dependent medicines has proven difficult due to the lack of standardized procedures in EV extraction processes as well as their pharmacological characteristics and mechanisms of action. However, recent biotechnology and engineering research has greatly enhanced the content and applicability of MSC-EVs.

Hypometabolism, Alzheimer's Disease, and Possible Therapeutic Targets: An Overview

The brain is a highly dynamic organ that requires a constant energy source to function normally. This energy is mostly supplied by glucose, a simple sugar that serves as the brain's principal fuel source. Glucose transport across the blood-brain barrier (BBB) is primarily controlled via sodium-independent facilitated glucose transport, such as by glucose transporter 1 (GLUT1) and 3 (GLUT3). However, other glucose transporters, including GLUT4 and the sodium-dependent transporters SGLT1 and SGLT6, have been reported in vitro and in vivo. When the BBB endothelial layer is crossed, neurons and astrocytes can absorb the glucose using their GLUT1 and GLUT3 transporters. Glucose then enters the glycolytic pathway and is metabolized into adenosine triphosphate (ATP), which supplies the energy to support cellular functions. The transport and metabolism of glucose in the brain are impacted by several medical conditions, which can cause neurological and neuropsychiatric symptoms. Alzheimer's disease (AD), Parkinson's disease (PD), epilepsy, traumatic brain injury (TBI), schizophrenia, etc., are a few of the most prevalent disorders, characterized by a decline in brain metabolism or hypometabolism early in the course of the disease. Indeed, AD is considered a metabolic disorder related to decreased brain glucose metabolism, involving brain insulin resistance and age-dependent mitochondrial dysfunction. Although the conventional view is that reduced cerebral metabolism is an effect of neuronal loss and consequent brain atrophy, a growing body of evidence points to the opposite, where hypometabolism is prodromal or at least precedes the onset of brain atrophy and the manifestation of clinical symptoms. The underlying processes responsible for these glucose transport and metabolic abnormalities are complicated and remain poorly understood. This review article provides a comprehensive overview of the current understanding of hypometabolism in AD and potential therapeutic targets.

Cerebrospinal fluid inflammatory biomarkers for disease progression in Alzheimer's disease and multiple sclerosis: a systematic review

Inflammatory processes are involved in the pathophysiology of both Alzheimer's disease (AD) and multiple sclerosis (MS) but their exact contribution to disease progression remains to be deciphered. Biomarkers are needed to define pathophysiological processes of these disorders, who may increasingly co-exist in the elderly generations of the future, due to the rising prevalence in both and ameliorated treatment options with improved life expectancy in MS. The purpose of this review was to provide a systematic overview of inflammatory biomarkers, as measured in the cerebrospinal fluid (CSF), that are associated with clinical disease progression. International peer-reviewed literature was screened using the PubMed and Web of Science databases. Disease progression had to be measured using clinically validated tests representing baseline functional and/or cognitive status, the evolution of such clinical scores over time and/or the transitioning from one disease stage to a more severe stage. The quality of included studies was systematically evaluated using a set of questions for clinical, neurochemical and statistical characteristics of the study. A total of 84 papers were included (twenty-five for AD and 59 for MS). Elevated CSF levels of chitinase-3-like protein 1 (YKL-40) were associated with disease progression in both AD and MS. Osteopontin and monocyte chemoattractant protein-1 were more specifically related to disease progression in AD, whereas the same was true for interleukin-1 beta, tumor necrosis factor alpha, C-X-C motif ligand 13, glial fibrillary acidic protein and IgG oligoclonal bands in MS. We observed a broad heterogeneity of studies with varying cohort characterization, non-disclosure of quality measures for neurochemical analyses and a lack of adequate longitudinal designs. Most of the retrieved biomarkers are related to innate immune system activity, which seems to be an important mediator of clinical disease progression in AD and MS. Overall study quality was limited and we have framed some recommendations for future biomarker research in this field.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42021264741.

Potential Utility of Plasma P-Tau and Neurofilament Light Chain as Surrogate Biomarkers for Preventive Clinical Trials

OBJECTIVE

To test the utility of longitudinal changes in plasma phosphorylated tau 181 (p-tau181) and neurofilament light chain (NfL) as surrogate markers for clinical trials targeting cognitively unimpaired (CU) populations.

METHODS

We estimated the sample size needed to test a 25% drug effect with 80% of power at a 0.05 level on reducing changes in plasma markers in CU participants from Alzheimer's Disease Neuroimaging Initiative database.

RESULTS

We included 257 CU individuals (45.5% males; mean age = 73 [6] years; 32% β-amyloid [Aβ] positive). Changes in plasma NfL were associated with age, whereas changes in plasma p-tau181 with progression to amnestic mild cognitive impairment. Clinical trials using p-tau181 and NfL would require 85% and 63% smaller sample sizes, respectively, for a 24-month than a 12-month follow-up. A population enrichment strategy using intermediate levels of Aβ PET (Centiloid 20-40) further reduced the sample size of the 24-month clinical trial using p-tau181 (73%) and NfL (59%) as a surrogate.

DISCUSSION

Plasma p-tau181/NfL can potentially be used to monitor large-scale population interventions in CU individuals. The enrollment of CU with intermediate Aβ levels constitutes the alternative with the largest effect size and most cost-effective for trials testing drug effect on changes in plasma p-tau181 and NfL.

EVs-mediated delivery of CB2 receptor agonist for Alzheimer's disease therapy

Alzheimer's disease (AD) is a typical neurodegenerative disease that leads to irreversible neuronal degeneration, and effective treatment remains elusive due to the unclear mechanism. We utilized biocompatible mesenchymal stem cell-derived extracellular vesicles as carriers loaded with the CB2 target medicine AM1241 (EVs-AM1241) to protect against neurodegenerative progression and neuronal function in AD model mice. According to the results, EVs-AM1241 were successfully constructed and exhibited better bioavailability and therapeutic effects than bare AM1241. The Morris water maze (MWM) and fear conditioning tests revealed that the learning and memory of EVs-AM1241-treated model mice were significantly improved. In vivo electrophysiological recording of CA1 neurons indicated enhanced response to an auditory conditioned stimulus following fear learning. Immunostaining and Western blot analysis showed that amyloid plaque deposition and amyloid β (Aβ)-induced neuronal apoptosis were significantly suppressed by EVs-AM1241. Moreover, EVs-AM1241 increased the number of neurons and restored the neuronal cytoskeleton, indicating that they enhanced neuronal regeneration. RNA sequencing revealed that EVs-AM1241 facilitated Aβ phagocytosis, promoted neurogenesis and ultimately improved learning and memory through the calcium-Erk signaling pathway. Our study showed that EVs-AM1241 efficiently reversed neurodegenerative pathology and enhanced neurogenesis in model mice, indicating that they are very promising particles for treating AD.

The Role of Clinical Assessment in the Era of Biomarkers

Hippocratic Medicine revolved around the three main principles of patient, disease, and physician and promoted the systematic observation of patients, rational reasoning, and interpretation of collected information. Although these remain the cardinal features of clinical assessment today, Medicine has evolved from a more physician-centered to a more patient-centered approach. Clinical assessment allows physicians to encounter, observe, evaluate, and connect with patients. This establishes the patient-physician relationship and facilitates a better understanding of the patient-disease relationship, as the ultimate goal is to diagnose, prognosticate, and treat. Biomarkers are at the core of the more disease-centered approach that is currently revolutionizing Medicine as they provide insight into the underlying disease pathomechanisms and biological changes. Genetic, biochemical, radiographic, and clinical biomarkers are currently used. Here, we define a seven-level theoretical construct for the utility of biomarkers in neurodegenerative diseases. Level 1-3 biomarkers are considered supportive of clinical assessment, capable of detecting susceptibility or risk factors, non-specific neurodegeneration or dysfunction, and/or changes at the individual level which help increase clinical diagnostic accuracy and confidence. Level 4-7 biomarkers have the potential to surpass the utility of clinical assessment through detection of early disease stages and prediction of underlying pathology. In neurodegenerative diseases, biomarkers can potentiate, but cannot substitute, clinical assessment. In this current era, aside from adding to the discovery, evaluation/validation, and implementation of more biomarkers, clinical assessment remains crucial to maintaining the personal, humanistic, and sociocultural aspects of patient care. We would argue that clinical assessment is a custom that should never go obsolete.

Intersectionality in Alzheimer's Disease: The Role of Female Sex and Black American Race in the Development and Prevalence of Alzheimer's Disease

It is well known that vascular factors and specific social determinants of health contribute to dementia risk and that the prevalence of these risk factors differs according to race and sex. In this review, we discuss the intersection of sex and race, particularly female sex and Black American race. Women, particularly Black women, have been underrepresented in Alzheimer's disease clinical trials and research. However, in recent years, the number of women participating in clinical research has steadily increased. A greater prevalence of vascular risk factors such as hypertension and type 2 diabetes, coupled with unique social and environmental pressures, puts Black American women particularly at risk for the development of Alzheimer's disease and related dementias. Female sex hormones and the use of hormonal birth control may offer some protective benefits, but results are mixed, and studies do not consistently report the demographics of their samples. We argue that as a research community, greater efforts should be made to not only recruit this vulnerable population, but also report the demographic makeup of samples in research to better target those at greatest risk for the disease.

Impact of asthma on the brain: evidence from diffusion MRI, CSF biomarkers and cognitive decline

Chronic systemic inflammation increases the risk of neurodegeneration, but the mechanisms remain unclear. Part of the challenge in reaching a nuanced understanding is the presence of multiple risk factors that interact to potentiate adverse consequences. To address modifiable risk factors and mitigate downstream effects, it is necessary, although difficult, to tease apart the contribution of an individual risk factor by accounting for concurrent factors such as advanced age, cardiovascular risk, and genetic predisposition. Using a case-control design, we investigated the influence of asthma, a highly prevalent chronic inflammatory disease of the airways, on brain health in participants recruited to the Wisconsin Alzheimer's Disease Research Center (31 asthma patients, 186 non-asthma controls, aged 45-90 years, 62.2% female, 92.2% cognitively unimpaired), a sample enriched for parental history of Alzheimer's disease. Asthma status was determined using detailed prescription information. We employed multi-shell diffusion weighted imaging scans and the three-compartment neurite orientation dispersion and density imaging model to assess white and gray matter microstructure. We used cerebrospinal fluid biomarkers to examine evidence of Alzheimer's disease pathology, glial activation, neuroinflammation and neurodegeneration. We evaluated cognitive changes over time using a preclinical Alzheimer cognitive composite. Using permutation analysis of linear models, we examined the moderating influence of asthma on relationships between diffusion imaging metrics, CSF biomarkers, and cognitive decline, controlling for age, sex, and cognitive status. We ran additional models controlling for cardiovascular risk and genetic risk of Alzheimer's disease, defined as a carrier of at least one apolipoprotein E (APOE) ε4 allele. Relative to controls, greater Alzheimer's disease pathology (lower amyloid-β42/amyloid-β40, higher phosphorylated-tau-181) and synaptic degeneration (neurogranin) biomarker concentrations were associated with more adverse white matter metrics (e.g. lower neurite density, higher mean diffusivity) in patients with asthma. Higher concentrations of the pleiotropic cytokine IL-6 and the glial marker S100B were associated with more salubrious white matter metrics in asthma, but not in controls. The adverse effects of age on white matter integrity were accelerated in asthma. Finally, we found evidence that in asthma, relative to controls, deterioration in white and gray matter microstructure was associated with accelerated cognitive decline. Taken together, our findings suggest that asthma accelerates white and gray matter microstructural changes associated with aging and increasing neuropathology, that in turn, are associated with more rapid cognitive decline. Effective asthma control, on the other hand, may be protective and slow progression of cognitive symptoms.

Association of Stages of Objective Memory Impairment With Incident Symptomatic Cognitive Impairment in Cognitively Normal Individuals

BACKGROUND AND OBJECTIVES

Increasing evidence indicates that a subset of cognitively normal individuals has subtle cognitive impairment at baseline. We sought to identify them using the Stages of Objective Memory Impairment (SOMI) system. Symptomatic cognitive impairment was operationalized by a Clinical Dementia Rating (CDR) ≥0.5. We hypothesized that incident impairment would be higher for participants with subtle retrieval impairment (SOMI-1), higher still for those with moderate retrieval impairment (SOMI-2), and highest for those with storage impairment (SOMI-3/4) after adjusting for demographics and APOE ε4 status. A secondary objective was to determine whether including biomarkers of β-amyloid, tau pathology, and neurodegeneration in the models affect prediction. We hypothesized that even after adjusting for in vivo biomarkers, SOMI would remain a significant predictor of time to incident symptomatic cognitive impairment.

METHODS

Among 969 cognitively normal participants, defined by a CDR = 0, from the Knight Alzheimer Disease Research Center, SOMI stage was determined from their baseline Free and Cued Selective Reminding Test scores, 555 had CSF and structural MRI measures and comprised the biomarker subgroup, and 144 of them were amyloid positive. Cox proportional hazards models tested associations of SOMI stages at baseline and biomarkers with time to incident cognitive impairment defined as the transition to CDR ≥0.5.

RESULTS

Among all participants, the mean age was 69.35 years, 59.6% were female, and mean follow-up was 6.36 years. Participants in SOMI-1-4 had elevated hazard ratios for the transition from normal to impaired cognition in comparison with those who were SOMI-0 (no memory impairment). Individuals in SOMI-1 (mildly impaired retrieval) and SOMI-2 (moderately impaired retrieval) were at nearly double the risk of clinical progression compared with persons with no memory problems. When memory storage impairment emerges (SOMI-3/4), the hazard ratio for clinical progression increased approximately 3 times. SOMI stage remained an independent predictor of incident cognitive impairment after adjusting for all biomarkers.

DISCUSSION

SOMI predicts the transition from normal cognition to incident symptomatic cognitive impairment (CDR ≥0.5). The results support the use of SOMI to identify those cognitively normal participants most likely to develop incident cognitive impairment who can then be referred for biomarker screening.

Validity of CSF alpha-synuclein to predict psychosis in prodromal Alzheimer's disease

Background

Alzheimer's disease (AD) accompanied by psychotic symptoms (PS) has a poor prognosis and may be associated with imbalances in key neural proteins such as alpha-synuclein (AS).

Aim

The aim of the study was to evaluate the diagnostic validity of AS levels in the cerebrospinal fluid (CSF) as a predictor of the emergence of PS in patients with prodromal AD.

Materials and methods

Patients with mild cognitive impairment were recruited between 2010 and 2018. Core AD biomarkers and AS levels were measured in CSF obtained during the prodromal phase of the illness. All patients who met the NIA-AA 2018 criteria for AD biomarkers received treatment with anticholinesterasic drugs. Follow-up evaluations were conducted to assess patients for the presence of psychosis using current criteria; the use of neuroleptic drugs was required for inclusion in the psychosis group. Several comparisons were made, taking into account the timing of the emergence of PS.

Results

A total of 130 patients with prodromal AD were included in this study. Of these, 50 (38.4%) met the criteria for PS within an 8-year follow-up period. AS was found to be a valuable CSF biomarker to differentiate between the psychotic and non-psychotic groups in every comparison made, depending on the onset of PS. Using an AS level of 1,257 pg/mL as the cutoff, this predictor achieved at least 80% sensitivity.

Conclusion

To our knowledge, this study represents the first time that a CSF biomarker has shown diagnostic validity for prediction of the emergence of PS in patients with prodromal AD.

A blood-based composite panel that screens Alzheimer's disease

BACKGROUND

Blood tests would be much easier to implement in the clinical diagnosis of Alzheimer's disease (AD) as minimally invasive measurements. Multiple inspection technologies promoted AD-associated blood biomarkers' exploration. However, there was a lack of further screening and validation for these explored blood-based biomarkers. We selected four potential biomarkers to explore their plasma levels in AD and amnestic mild cognitive impairment (aMCI) and developed a composite panel for AD and aMCI screening.

METHOD

The plasma concentrations of soluble low-density lipoprotein receptor-associated protein 1 (sLRP1), Gelsolin (GSN), Kallikrein 4 (KLK4) and Caspase 3 were measured in the discovery and validation cohort. The receiver operating characteristic (ROC) curve was generated to assess the classification panel with the area under the curve (AUC).

RESULTS

A total of 233 participants (26 CN, 27 aMCI, and 26 AD in the discovery cohort, and 51 CN, 50 aMCI, and 53 AD in the validation cohort) with complete data were included in the study. The plasma concentrations of sLRP1 and Caspase 3 were significantly decreased in AD and aMCI when compared with those in the CN group. Compared with the CN group, the concentrations of KLK4 and GSN were increased in AD, but not in MCI. Interestingly, one of four proteins, sLRP1 in plasma level was higher in Apolipoprotein E (APOE) ε4 non-carriers than that in APOE ε4 carriers, especially among CN and MCI. No significant difference was found between females and males in the plasma levels of four proteins. The composite panel is based on four blood biomarkers accurately classifying AD from CN (AUC = 0.903-0.928), and MCI from CN (AUC = 0.846-0.865). Moreover, dynamic changes in the plasma levels of four proteins exhibited a significant correlation with cognitive assessment.

CONCLUSIONS

Altogether, these findings indicate that the plasma levels of sLRP1, KLK4, GSN and Caspase 3 changed with the progression of AD. And their combination could be used to develop a panel for classifying AD and aMCI with high accuracy, which would provide an alternative approach for developing a blood-based test for AD and aMCI screening.

CSF Aβ40 Levels Do Not Correlate with the Clinical Manifestations of Alzheimer's Disease

INTRODUCTION

Cerebrospinal fluid (CSF) biomarker quantification provides physicians with a reliable diagnosis of Alzheimer's disease (AD). However, the relationship between their concentration and disease course has not been clearly elucidated. This work aimed to investigate the clinical and prognostic significance of Aβ40 CSF levels.

METHODS

A retrospective cohort of 76 patients diagnosed with AD using a decreased Aβ42/Aβ40 ratio was subclassified into hyposecretors (Aβ40 <7,755 pg/mL), normosecretors (Aβ40 7,755-16,715 pg/mL), and hypersecretors (Aβ40 >16,715 pg/mL). Potential differences in AD phenotype, Montreal Cognitive Assessment (MoCA) scores, and Global Deterioration Scale (GDS) stages were assessed. Correlation tests for biomarker concentrations were also performed.

RESULTS

Participants were classified as hyposecretors (n = 22, median Aβ40 5,870.500 pg/mL, interquartile range [IQR] 1,431), normosecretors (n = 47, median Aβ40 10,817 pg/mL, IQR 3,622), and hypersecretors (n = 7, 19,767 pg/mL, IQR 3,088). The distribution of positive phosphorylated Tau (p-Tau) varied significantly between subgroups and was more common in the normo- and hypersecretor categories (p = 0.003). Aβ40 and p-Tau concentrations correlated positively (ρ = 0.605, p < 0.001). No significant differences were found among subgroups regarding age, initial MoCA score, initial GDS stage, progression to the dementia stage, or changes in the MoCA score.

CONCLUSION

In this study, we found no significant differences in clinical symptoms or disease progression in AD patients according to their CSF Aβ40 concentration. Aβ40 was positively correlated with p-Tau and total Tau concentrations, supporting their potential interaction in AD pathophysiology.

Intrathecal administration of botulinum toxin type a antagonizes neuropathic pain by countering increased vesicular nucleotide transporter expression in the spinal cord of chronic constriction injury of the sciatic nerve rats

Botulinum toxin type A (BoNT/A) induces direct analgesic effects in neuropathic pain by inhibiting the release of substance P, calcitonin gene-related peptide (CGRP) and glutamate. Vesicular nucleotide transporter (VNUT) was responsible for the storage and release of ATP in vivo, and one of the mechanisms underlying neuropathic pain is VNUT-dependent release of extracellular ATP from dorsal horn neurons. However, the analgesic effect of BoNT/A by affecting the expression of VNUT remained largely unknown. Thus, in this study, we aimed to elucidate the antinociceptive potency and analgesic mechanism of BoNT/A in chronic constriction injury of the sciatic nerve (CCI) induced neuropathic pain. Our results showed that a single intrathecal injection of 0.1 U BoNT/A seven days after CCI surgery produced significant analgesic activity and decreased the expression of VNUT in the spinal cord of CCI rats. Similarly, BoNT/A inhibited the CCI-induced increase in ATP content in the rat spinal cord. Overexpression of VNUT in the spinal cord of CCI-induced rats markedly reversed the antinociceptive effect of BoNT/A. Furthermore, 33 U/mL BoNT/A dramatically reduced the expression of VNUT in pheochromocytoma (PC12) cells but overexpressing SNAP-25 increased VNUT expression in PC12 cells. Our current study is the first to demonstrate that BoNT/A is involved in neuropathic pain by regulating the expression of VNUT in the spinal cord in rats.

An Insight into Cellular and Molecular Mechanisms Underlying the Pathogenesis of Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is the most prominent neurodegenerative disorder in the aging population. It is characterized by cognitive decline, gradual neurodegeneration, and the development of amyloid-β (Aβ)-plaques and neurofibrillary tangles, which constitute hyperphosphorylated tau. The early stages of neurodegeneration in AD include the loss of neurons, followed by synaptic impairment. Since the discovery of AD, substantial factual research has surfaced that outlines the disease's causes, molecular mechanisms, and prospective therapeutics, but a successful cure for the disease has not yet been discovered. This may be attributed to the complicated pathogenesis of AD, the absence of a well-defined molecular mechanism, and the constrained diagnostic resources and treatment options. To address the aforementioned challenges, extensive disease modeling is essential to fully comprehend the underlying mechanisms of AD, making it easier to design and develop effective treatment strategies. Emerging evidence over the past few decades supports the critical role of Aβ and tau in AD pathogenesis and the participation of glial cells in different molecular and cellular pathways. This review extensively discusses the current understanding concerning Aβ- and tau-associated molecular mechanisms and glial dysfunction in AD. Moreover, the critical risk factors associated with AD including genetics, aging, environmental variables, lifestyle habits, medical conditions, viral/bacterial infections, and psychiatric factors have been summarized. The present study will entice researchers to more thoroughly comprehend and explore the current status of the molecular mechanism of AD, which may assist in AD drug development in the forthcoming era.

Advances and applications of fluids biomarkers in diagnosis and therapeutic targets of Alzheimer's disease

AIMS

Alzheimer's disease (AD) is a neurodegenerative disease with challenging early diagnosis and effective treatments due to its complex pathogenesis. AD patients are often diagnosed after the appearance of the typical symptoms, thereby delaying the best opportunity for effective measures. Biomarkers could be the key to resolving the challenge. This review aims to provide an overview of application and potential value of AD biomarkers in fluids, including cerebrospinal fluid, blood, and saliva, in diagnosis and treatment.

METHODS

A comprehensive search of the relevant literature was conducted to summarize potential biomarkers for AD in fluids. The paper further explored the biomarkers' utility in disease diagnosis and drug target development.

RESULTS

Research on biomarkers mainly focused on amyloid-β (Aβ) plaques, Tau protein abnormal phosphorylation, axon damage, synaptic dysfunction, inflammation, and related hypotheses associated with AD mechanisms. Aβ₄₂ , total Tau (t-Tau), and phosphorylated Tau (p-Tau), have been endorsed for their diagnostic and predictive capability. However, other biomarkers remain controversial. Drugs targeting Aβ have shown some efficacy and those that target BACE1 and Tau are still undergoing development.

CONCLUSION

Fluid biomarkers hold considerable potential in the diagnosis and drug development of AD. However, improvements in sensitivity and specificity, and approaches for managing sample impurities, need to be addressed for better diagnosis.

GFAP as a Potential Biomarker for Alzheimer's Disease: A Systematic Review and Meta-Analysis

Blood biomarkers have been considered tools for the diagnosis, prognosis, and monitoring of Alzheimer's disease (AD). Although amyloid-β peptide (Aβ) and tau are primarily blood biomarkers, recent studies have identified other reliable candidates that can serve as measurable indicators of pathological conditions. One such candidate is the glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein that can be detected in blood samples. Increasing evidence suggests that blood GFAP levels can be used to detect early-stage AD. In this systematic review and meta-analysis, we aimed to evaluate GFAP in peripheral blood as a biomarker for AD and provide an overview of the evidence regarding its utility. Our analysis revealed that the GFAP level in the blood was higher in the Aβ-positive group than in the negative groups, and in individuals with AD or mild cognitive impairment (MCI) compared to the healthy controls. Therefore, we believe that the clinical use of blood GFAP measurements has the potential to accelerate the diagnosis and improve the prognosis of AD.

Cell-free DNA-based liquid biopsies in neurology

This article reviews recent developments in the application of cell-free DNA-based liquid biopsies to neurological diseases. Over the past few decades, an explosion of interest in the use of accessible biofluids to identify and track molecular disease has revolutionized the fields of oncology, prenatal medicine and others. More recently, technological advances in signal detection have allowed for informative analysis of biofluids that are typically sparse in cells and other circulating components, such as CSF. In parallel, advancements in epigenetic profiling have allowed for novel applications of liquid biopsies to diseases without characteristic mutational profiles, including many degenerative, autoimmune, inflammatory, ischaemic and infectious disorders. These events have paved the way for a wide array of neurological conditions to benefit from enhanced diagnostic, prognostic, and treatment abilities through the use of liquid biomarkers: a 'liquid biopsy' approach. This review includes an overview of types of liquid biopsy targets with a focus on circulating cell-free DNA, methods used to identify and probe potential liquid biomarkers, and recent applications of such biomarkers to a variety of complex neurological conditions including CNS tumours, stroke, traumatic brain injury, Alzheimer's disease, epilepsy, multiple sclerosis and neuroinfectious disease. Finally, the challenges of translating liquid biopsies to use in clinical neurology settings-and the opportunities for improvement in disease management that such translation may provide-are discussed.

Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia

Dementia is a progressive and debilitating neurological disease that affects millions of people worldwide. Identifying the minimally invasive biomarkers associated with dementia that could provide insights into the disease pathogenesis, improve early diagnosis, and facilitate the development of effective treatments is pressing. Proteomic studies have emerged as a promising approach for identifying the protein biomarkers associated with dementia. This pilot study aimed to investigate the plasma proteome profile and identify a panel of various protein biomarkers for dementia. We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. There was also the dysregulation of 153 plasma proteins in individuals with dementia compared with those with MCI, and machine learning algorithms identified 8 biomarkers that classified dementia from MCI with an AUC of 0.87 ± 0.07. Moreover, multiple proteins selected in both diagnostic panels such as NEFL, IL17D, WNT9A, and PGF were negatively correlated with cognitive performance, with a correlation coefficient (r²) ≤ -0.47. Gene Ontology (GO) and pathway analysis of dementia-associated proteins implicated immune response, vascular injury, and extracellular matrix organization pathways in dementia pathogenesis. In conclusion, the combination of high-throughput proteomics and machine learning enabled us to identify a blood-based protein signature capable of potentially differentiating dementia from MCI and cognitively normal controls. Further research is required to validate these biomarkers and investigate the potential underlying mechanisms for the development of dementia.

Biomarkers for parkinsonian disorders in CNS-originating EVs: promise and challenges

Extracellular vesicles (EVs), including exosomes, microvesicles, and oncosomes, are nano-sized particles enclosed by a lipid bilayer. EVs are released by virtually all eukaryotic cells and have been shown to contribute to intercellular communication by transporting proteins, lipids, and nucleic acids. In the context of neurodegenerative diseases, EVs may carry toxic, misfolded forms of amyloidogenic proteins and facilitate their spread to recipient cells in the central nervous system (CNS). CNS-originating EVs can cross the blood-brain barrier into the bloodstream and may be found in other body fluids, including saliva, tears, and urine. EVs originating in the CNS represent an attractive source of biomarkers for neurodegenerative diseases, because they contain cell- and cell state-specific biological materials. In recent years, multiple papers have reported the use of this strategy for identification and quantitation of biomarkers for neurodegenerative diseases, including Parkinson's disease and atypical parkinsonian disorders. However, certain technical issues have yet to be standardized, such as the best surface markers for isolation of cell type-specific EVs and validating the cellular origin of the EVs. Here, we review recent research using CNS-originating EVs for biomarker studies, primarily in parkinsonian disorders, highlight technical challenges, and propose strategies for overcoming them.

Molecular Biomarkers of Neuronal Injury in Epilepsy Shared with Neurodegenerative Diseases

In neurodegenerative diseases, changes in neuronal proteins in the cerebrospinal fluid and blood are viewed as potential biomarkers of the primary pathology in the central nervous system (CNS). Recent reports suggest, however, that level of neuronal proteins in fluids also alters in several types of epilepsy in various age groups, including children. With increasing evidence supporting clinical and sub-clinical seizures in Alzheimer's disease, Lewy body dementia, Parkinson's disease, and in other less common neurodegenerative conditions, these findings call into question the specificity of neuronal protein response to neurodegenerative process and urge analysis of the effects of concomitant epilepsy and other comorbidities. In this article, we revisit the evidence for alterations in neuronal proteins in the blood and cerebrospinal fluid associated with epilepsy with and without neurodegenerative diseases. We discuss shared and distinctive characteristics of changes in neuronal markers, review their neurobiological mechanisms, and consider the emerging opportunities and challenges for their future research and diagnostic use.