Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol. 2010;6:131-144. [PMID: 20157306 DOI: 10.1038/nrneurol.2010.4]

Development of a robust parallel and multi-composite machine learning model for improved diagnosis of Alzheimer's disease: correlation with dementia-associated drug usage and AT(N) protein biomarkers

Introduction

Machine learning (ML) algorithms and statistical modeling offer a potential solution to offset the challenge of diagnosing early Alzheimer's disease (AD) by leveraging multiple data sources and combining information on neuropsychological, genetic, and biomarker indicators. Among others, statistical models are a promising tool to enhance the clinical detection of early AD. In the present study, early AD was diagnosed by taking into account characteristics related to whether or not a patient was taking specific drugs and a significant protein as a predictor of Amyloid-Beta (Aβ), tau, and ptau [AT(N)] levels among participants.

Methods

In this study, the optimization of predictive models for the diagnosis of AD pathologies was carried out using a set of baseline features. The model performance was improved by incorporating additional variables associated with patient drugs and protein biomarkers into the model. The diagnostic group consisted of five categories (cognitively normal, significant subjective memory concern, early mildly cognitively impaired, late mildly cognitively impaired, and AD), resulting in a multinomial classification challenge. In particular, we examined the relationship between AD diagnosis and the use of various drugs (calcium and vitamin D supplements, blood-thinning drugs, cholesterol-lowering drugs, and cognitive drugs). We propose a hybrid-clinical model that runs multiple ML models in parallel and then takes the majority's votes, enhancing the accuracy. We also assessed the significance of three cerebrospinal fluid biomarkers, Aβ, tau, and ptau in the diagnosis of AD. We proposed that a hybrid-clinical model be used to simulate the MRI-based data, with five diagnostic groups of individuals, with further refinement that includes preclinical characteristics of the disorder. The proposed design builds a Meta-Model for four different sets of criteria. The set criteria are as follows: to diagnose from baseline features, baseline and drug features, baseline and protein features, and baseline, drug and protein features.

Results

We were able to attain a maximum accuracy of 97.60% for baseline and protein data. We observed that the constructed model functioned effectively when all five drugs were included and when any single drug was used to diagnose the response variable. Interestingly, the constructed Meta-Model worked well when all three protein biomarkers were included, as well as when a single protein biomarker was utilized to diagnose the response variable.

Discussion

It is noteworthy that we aimed to construct a pipeline design that incorporates comprehensive methodologies to detect Alzheimer's over wide-ranging input values and variables in the current study. Thus, the model that we developed could be used by clinicians and medical experts to advance Alzheimer's diagnosis and as a starting point for future research into AD and other neurodegenerative syndromes.

Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction?

There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ1-42 and Aβ1-40 (used as Aβ42/Aβ40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants' brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors (APOE, single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65-80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance (R² = 0.15) to MRI (R² = 0.18) and cardiovascular measures (R² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction (R² = 0.26 and 0.27). For amyloid positive individuals Aβ42/Aβ40, glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ42/Aβ40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population's socio-demographics, brain and cardiovascular health.

Immunotherapy in Alzheimer's disease: focusing on the efficacy of gantenerumab on amyloid-β clearance and cognitive decline

Gantenerumab, a human monoclonal antibody (mAb), has been thought of as a potential agent to treat Alzheimer's disease (AD) by specifically targeting regions of the amyloid-β (Aβ) peptide sequence. Aβ protein accumulation in the brain leads to amyloid plaques, causing neuroinflammation, oxidative stress, neuronal damage, and neurotransmitter dysfunction, thereby causing cognitive decline in AD. Gantenerumab involves disrupting Aβ aggregation and promoting the breakdown of larger Aβ aggregates into smaller fragments, which facilitates the action of Aβ-degrading enzymes in the brain, thus slowing down the progression of AD. Moreover, Gantenerumab acts as an opsonin, coating Aβ plaques and enhancing their recognition by immune cells, which, combined with its ability to improve the activity of microglia, makes it an intriguing candidate for promoting Aβ plaque clearance. Indeed, the multifaceted effects of Gantenerumab, including Aβ disaggregation, enhanced immune recognition, and improved microglia activity, may position it as a promising therapeutic approach for AD. Of note, reports suggest that Gantenerumab, albeit its capacity to reduce or eliminate Aβ, has not demonstrated effectiveness in reducing cognitive decline. This review, after providing an overview of immunotherapy approaches that target Aβ in AD, explores the efficacy of Gantenerumab in reducing Aβ levels and cognitive decline.

The amyloid beta 42/38 ratio as a plasma biomarker of early memory deficits in cognitively unimpaired older adults

The amyloid beta (Aβ) 42/40 ratio has been widely studied as a biomarker in Alzheimer's disease (AD); however, other Aβ peptides could also represent relevant biomarkers. We measured levels of Aβ38/40/42 in plasma samples from cognitively-unimpaired older adults and determined the relationships between Aβ levels and amyloid positron-emission-tomography (PET) and performance on a learning and memory task. We found that all Aβ peptides individually and the Aβ42/40 ratio, but not the Aβ42/38 ratio, were significantly correlated with brain amyloid (Aβ-PET). Multiple linear modeling, adjusting for age, sex, education, APOE4 and Aβ-PET showed significant associations between the Aβ42/38 ratio and memory. Further, associations between the Aβ42/38 ratio and learning scores were stronger in males and in Aβ-PET-negative individuals. In contrast, no significant associations were detected between the Aβ42/40 ratio and any learning measure. These studies implicate the Aβ42/38 ratio as a biomarker to assess early memory deficits and underscore the utility of the Aβ38 fragment as an important biomarker in the AD field.

Navigating the intersection: Diabetes and Alzheimer's intertwined relationship

Alzheimer's disease (AD) and Diabetes mellitus (DM) exhibit comparable pathophysiological pathways. Genetic abnormalities in APP, PS-1, and PS-2 are linked to AD, with diagnostic aid from CSF and blood biomarkers. Insulin dysfunction, termed "type 3 diabetes mellitus" in AD, involves altered insulin signalling and neuronal shrinkage. Insulin influences beta-amyloid metabolism, exacerbating neurotoxicity in AD and amyloid production in DM. Both disorders display impaired glucose transporter expression, hastening cognitive decline. Mitochondrial dysfunction and Toll-like receptor 4-mediated inflammation worsen neurodegeneration in both diseases. ApoE4 raises disease risk, especially when coupled with dyslipidemia common in DM. Targeting shared pathways like insulin-degrading enzyme activation and HSP60 holds promise for therapeutic intervention. Recognizing these interconnected mechanisms underscores the imperative for developing tailored treatments addressing the overlapping pathophysiology of AD and DM, offering potential avenues for more effective management of both conditions.

Photophysics of Molecular Probes for Amyloid-β Detection: Computational Insights into the Roles of Probe Linker and Functional Groups

In this computational study, density functional theory (DFT) and time-dependent DFT methods (TD-DFT) were employed to study the optical properties of six families of molecules with donor (D), bridge (B), and acceptor (A) fragments that have potential for use as fluorescent molecular probes for the early detection of Alzheimer's disease. After validating our computational method against experimental data, using X-ray and absorption data, the equilibrium geometries and wave functions of the ground and first singlet excited states were systematically studied. Our simulations demonstrate that the S1 states of these rod-like D-B-A fluorescent probes are twisted intramolecular charge transfer states with a predominant highest occupied molecular orbital-least unoccupied molecular orbital (HOMO-LUMO) character, the former localized primarily at the donor, whereas the latter at the acceptor site. Moreover, the influence of the bridge, donor, and acceptor fragments on molecules' absorption energies is explored, highlighting the influence of double and triple bonds and some specific modifications on the acceptor side, including the addition of electronegative atoms, pyranone derivatives, and their functionalization. By having the absorption energies of 324 probes in hand, machine learning models were trained to predict the absorption energies of molecules. The models were found to be predictive, which suggests a potential that predictive models for other crucial properties, such as emission and quantum yield, can also be trained if suitable training data sets are made available.

The genetic association between bipolar disorder and dementia: a qualitative review

Bipolar disorder is a chronic disorder characterized by fluctuations in mood state and energy and recurrent episodes of mania/hypomania and depression. Bipolar disorder may be regarded as a neuro-progressive disorder in which repeated mood episodes may lead to cognitive decline and dementia development. In the current review, we employed genome-wide association studies to comprehensively investigate the genetic variants associated with bipolar disorder and dementia. Thirty-nine published manuscripts were identified: 20 on bipolar disorder and 19 on dementia. The results showed that the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A were overlapping between patients with bipolar disorder and dementia. In conclusion, the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A may be associated with the neuro-progression of bipolar disorder to dementia. Further genetic studies are needed to comprehensively clarify the role of genes in cognitive decline and the development of dementia in patients with bipolar disorder.

Machine and deep learning algorithms for classifying different types of dementia: A literature review

The cognitive impairment known as dementia affects millions of individuals throughout the globe. The use of machine learning (ML) and deep learning (DL) algorithms has shown great promise as a means of early identification and treatment of dementia. Dementias such as Alzheimer's Dementia, frontotemporal dementia, Lewy body dementia, and vascular dementia are all discussed in this article, along with a literature review on using ML algorithms in their diagnosis. Different ML algorithms, such as support vector machines, artificial neural networks, decision trees, and random forests, are compared and contrasted, along with their benefits and drawbacks. As discussed in this article, accurate ML models may be achieved by carefully considering feature selection and data preparation. We also discuss how ML algorithms can predict disease progression and patient responses to therapy. However, overreliance on ML and DL technologies should be avoided without further proof. It's important to note that these technologies are meant to assist in diagnosis but should not be used as the sole criteria for a final diagnosis. The research implies that ML algorithms may help increase the precision with which dementia is diagnosed, especially in its early stages. The efficacy of ML and DL algorithms in clinical contexts must be verified, and ethical issues around the use of personal data must be addressed, but this requires more study.

Cerebrospinal fluid p-tau181, 217, and 231 in definite Creutzfeldt-Jakob disease with and without concomitant pathologies

INTRODUCTION

The established cerebrospinal fluid (CSF) phosphorylated tau181 (p-tau181) may not reliably reflect concomitant Alzheimer's disease (AD) and primary age-related tauopathy (PART) found in Creutzfeldt-Jakob disease (CJD) at autopsy.

METHODS

We investigated CSF N-terminal p-tau181, p-tau217, and p-tau231 with in-house Simoa assays in definite CJD (n = 29), AD dementia (n = 75), mild cognitive impairment (MCI) due to AD (n = 65), and subjective cognitive decline (SCD, n = 28). Post-mortem examination performed in patients with CJD 1.3 (0.3-14.3) months after CSF collection revealed no co-pathology in 10, concomitant AD in 8, PART in 8, and other co-pathologies in 3 patients.

RESULTS

N-terminal p-tau was increased in CJD versus SCD (p < 0.0001) and correlated with total tau (t-tau) in the presence of AD and PART co-pathology (rho = 0.758-0.952, p ≤ 001). Concentrations in CJD+AD were indistinguishable from AD dementia, with the largest fold-change in p-tau217 (11.6), followed by p-tau231 and p-tau181 (3.2-4.5).

DISCUSSION

Variable fold-changes and correlation with t-tau suggest that p-tau closely associates with neurodegeneration and concomitant AD in CJD.

HIGHLIGHTS

N-terminal phosphorylated tau (p-tau) biomarkers are increased in Creutzfeldt-Jakob disease (CJD) with and without concomitant AD. P-tau217, p-tau231, and p-tau181 correlate with total tau (t-tau) and increase in the presence of amyloid beta (Aβ) co-pathology. N-terminal p-tau181 and p-tau231 in Aβ-negative CJD show variation among PRNP genotypes. Compared to mid-region-targeting p-tau181, cerebrospinal fluid (CSF) N-terminal p-tau has greater potential to reflect post-mortem neuropathology in the CJD brain.

An exploratory study of the damage markers NfL, GFAP, and t-Tau, in cerebrospinal fluid and other findings from a patient cohort enriched for suspected autoimmune psychiatric disease

There is growing evidence suggesting that immunological mechanisms play a significant role in the development of psychiatric symptoms in certain patient subgroups. However, the relationship between clinical red flags for suspected autoimmune psychiatric disease and signs of central nervous system (CNS) pathology (e.g., routine cerebrospinal fluid (CSF) alterations, CNS damage markers, neurophysiological or neuroimaging findings) has received limited attention. Here, we aimed to describe the prevalence and distribution of potential CNS pathologies in psychiatric patients in relation to clinical red flags for autoimmune psychiatric disease and psychiatric symptoms. CSF routine findings and CNS damage markers; neurofilament light chain protein (NfL), glial fibrillary acidic protein (GFAP) and total Tau (t-Tau), in CSF from 127 patients with psychiatric disease preselected for suspected immunological involvement were related to recently proposed clinical red flags, psychiatric features, and MRI and EEG findings. Twenty-one percent had abnormal routine CSF findings and 27% had elevated levels of CNS damage markers. Six percent had anti-neuronal antibodies in serum and 2% had these antibodies in the CSF. Sixty-six percent of patients examined with MRI (n = 88) had alterations, mostly atrophy or nonspecific white matter lesions. Twenty-seven percent of patients with EEG recordings (n = 70) had abnormal findings. Elevated NfL levels were associated with comorbid autoimmunity and affective dysregulation symptoms. Elevated t-Tau was associated with catatonia and higher ratings of agitation/hyperactivity. Elevated GFAP was associated with acute onset, atypical presentation, infectious prodrome, tics, depressive/anxiety symptom ratings and overall greater psychiatric symptom burden. In conclusion, preselection based on suspected autoimmune psychiatric disease identifies a population with a high prevalence of CSF alterations suggesting CNS pathology. Future studies should examine the value of these markers in predicting treatment responses.

A review of the application of exercise intervention on improving cognition in patients with Alzheimer's disease: mechanisms and clinical studies

Alzheimer's disease (AD) is the most common form of dementia, leading to sustained cognitive decline. An increasing number of studies suggest that exercise is an effective strategy to promote the improvement of cognition in AD. Mechanisms of the benefits of exercise intervention on cognitive function may include modulation of vascular factors by affecting cardiovascular risk factors, regulating cardiorespiratory health, and enhancing cerebral blood flow. Exercise also promotes neurogenesis by stimulating neurotrophic factors, affecting neuroplasticity in the brain. Additionally, regular exercise improves the neuropathological characteristics of AD by improving mitochondrial function, and the brain redox status. More and more attention has been paid to the effect of Aβ and tau pathology as well as sleep disorders on cognitive function in persons diagnosed with AD. Besides, there are various forms of exercise intervention in cognitive improvement in patients with AD, including aerobic exercise, resistance exercise, and multi-component exercise. Consequently, the purpose of this review is to summarize the findings of the mechanisms of exercise intervention on cognitive function in patients with AD, and also discuss the application of different exercise interventions in cognitive impairment in AD to provide a theoretical basis and reference for the selection of exercise intervention in cognitive rehabilitation in AD.

Deep Cascade of Convolutional Neural Networks for Quantification of Enlarged Perivascular Spaces in the Basal Ganglia in Magnetic Resonance Imaging

In this paper, we present a cascaded deep convolution neural network (CNN) for assessing enlarged perivascular space (ePVS) within the basal ganglia region using T2-weighted MRI. Enlarged perivascular spaces (ePVSs) are potential biomarkers for various neurodegenerative disorders, including dementia and Parkinson's disease. Accurate assessment of ePVS is crucial for early diagnosis and monitoring disease progression. Our approach first utilizes an ePVS enhancement CNN to improve ePVS visibility and then employs a quantification CNN to predict the number of ePVSs. The ePVS enhancement CNN selectively enhances the ePVS areas without the need for additional heuristic parameters, achieving a higher contrast-to-noise ratio (CNR) of 113.77 compared to Tophat, Clahe, and Laplacian-based enhancement algorithms. The subsequent ePVS quantification CNN was trained and validated using fourfold cross-validation on a dataset of 76 participants. The quantification CNN attained 88% accuracy at the image level and 94% accuracy at the subject level. These results demonstrate significant improvements over traditional algorithm-based methods, highlighting the robustness and reliability of our deep learning approach. The proposed cascaded deep CNN model not only enhances the visibility of ePVS but also provides accurate quantification, making it a promising tool for evaluating neurodegenerative disorders. This method offers a novel and significant advancement in the non-invasive assessment of ePVS, potentially aiding in early diagnosis and targeted treatment strategies.

A randomized, double-blind, placebo-controlled study of Cistanche tubulosa and Ginkgo biloba extracts for the improvement of cognitive function in middle-aged and elderly people

Mild cognitive impairment poses an increasing challenge to middle-aged and elderly populations. Traditional Chinese medicinal herbs like Cistanche tubulosa and Ginkgo biloba (CG) have been proposed as potential agents to improve cognitive and memory functions. A randomized controlled trial involving 100 Chinese middle-aged and elderly participants was conducted to investigate the potential synergistic effects of CG on cognitive function in individuals at risk of neurodegenerative diseases. Over 90 days, both CG group and placebo group received two tablets daily, with each pair of CG tablets containing 72 mg echinacoside and 27 mg flavonol glycosides. Cognitive functions were assessed using multiple scales and blood biomarkers were determined at baseline, Day 45, and Day 90. The CG group exhibited significant improvements in the scores of Mini-Mental State Examination (26.5 at baseline vs. 27.1 at Day 90, p < 0.001), Montreal Cognitive Assessment (23.4 at baseline vs. 25.3 at Day 90, p < 0.001), and World Health Organization Quality of Life (81.6 at baseline vs. 84.2 at Day 90, p < 0.001), all surpassing scores in placebo group. Notably, both the Cognitrax matrix test and the Wechsler Memory Scale-Revised demonstrated enhanced memory functions, including long-term and delayed memory, after CG intervention. Moreover, cognitive-related blood biomarkers, including total tau, pT181, pS199, pT231, pS396, and thyroid-stimulating hormone, significantly decreased, whereas triiodothyronine and free triiodothyronine significantly increased. No treatment-related adverse events were reported, and routine blood and urine tests remained stable. These findings indicated that CG supplementation could potentially serve as an effective supplementary solution for enhancing cognitive and memory functions.

Predicting progression from subjective cognitive decline to mild cognitive impairment or dementia based on brain atrophy patterns

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the 'severity index' generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI).

METHODS

We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk "disease-like" or low-risk "CN-like". Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data.

RESULTS

In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57).

CONCLUSION

When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.

Sleep disturbances, cognitive decline, and AD biomarkers alterations in early Parkinson's disease

OBJECTIVE

We aimed to investigate whether each type of sleep disturbances (i.e., pRBD, EDS, and insomnia) is specifically associated with faster decline in global cognition and different cognitive domains among de novo PD patients. We also assessed the influence of sleep disturbances on core AD CSF biomarkers alterations and conversion to dementia.

METHODS

Prospectively longitudinal data were obtained from the PPMI cohort. Sleep disturbances and cognition ability were assessed by questionnaires at baseline and follow-up visits. Generalized linear mixed models were utilized to assess the effect of sleep disturbances on cognitive decline and core AD CSF biomarkers change. The associations between sleep disturbances and conversion to dementia were analyzed using Cox regression analysis.

RESULTS

Baseline pRBD was associated with faster decline in global cognition and all cognitive domains, including verbal episodic memory, visuospatial ability, executive function, language, and processing speed. EDS was associated with faster decline in three cognitive domains, including verbal episodic memory, executive function/working memory, and processing speed. Insomnia was associated with faster decline in global cognition and verbal episodic memory. Meanwhile, pRBD and EDS were associated with longitudinal decrease of CSF Aβ42. Baseline pRBD increased the risk of conversion to dementia. The risk of dementia in PD patients with multiple sleep disturbances also increased compared with those without sleep disturbance.

INTERPRETATION

Sleep disturbances (i.e., pRBD, EDS, and insomnia) were associated with cognitive decline in early PD. EDS and pRBD were associated with decrease of CSF Aβ42. Moreover, pRBD was associated with conversion to dementia.

Amyloid and Tau as cerebrospinal fluid biomarkers in anti-N-Methyl-D-aspartate receptor encephalitis

INTRODUCTION

Neuroinfection is associated with the deposition of amyloid-beta (Aβ) peptides, and subsequent decrease in cerebrospinal fluid (CSF) amyloid levels. However, whether autoimmune encephalitis involves extracellular deposition of Aβ peptides in the brain is unreported.

METHODS

We examined CSF amyloid and tau values in adults with anti-N-methyl-D-aspartate receptor encephalitis (NMDAR-E). Forty-two patients with NMDAR-E, 35 patients with viral and bacterial neuroinfections, and 16 controls were included. We measured CSF Aβ1-42 (cAβ1-42), Aβ1-40 (cAβ1-40), t-Tau (ct-Tau), and p-Tau181 (cp-Tau181) levels and assessed their efficacies regarding differential diagnosis and predicting prognosis.

RESULTS

NMDAR-E patients had lower cAβ1-42 levels; however, they were higher than those of patients with bacterial meningitis. ct-Tau levels in NMDAR-E patients were lower than those in patients with neuroinfections. No changes were observed in controls. cAβ1-42 and ct-Tau were combined as an excellent marker to distinguish NMDAR-E from neuroinfections. cAβ1-42 levels in NMDAR-E patients were positively correlated with Montreal Cognitive Assessment scores. We observed an inverse relationship between cAβ1-42 levels and modified Rankin Scale scores. Patients with poor outcomes exhibited low cAβ1-42 levels and high levels of several blood parameters. cAβ1-42 was the highest quality biomarker for assessing NMDAR-E prognosis. Correlations were found between cAβ1-42 and some inflammatory indicators.

CONCLUSION

cAβ1-42 was decreased in NMDAR-E patients. cAβ1-42 levels indicated NMDAR-E severity and acted as a biomarker for its prognosis. Combining cAβ1-42 and ct-Tau levels could serve as a novel differential diagnostic marker for NMDAR-E.

Induced pluripotent stem cell models as a tool to investigate and test fluid biomarkers in Alzheimer's disease and frontotemporal dementia

Neurodegenerative diseases are increasing in prevalence and comprise a large socioeconomic burden on patients and their caretakers. The need for effective therapies and avenues for disease prevention and monitoring is of paramount importance. Fluid biomarkers for neurodegenerative diseases have gained a variety of uses, including informing participant selection for clinical trials, lending confidence to clinical diagnosis and disease staging, determining prognosis, and monitoring therapeutic response. Their role is expected to grow as disease-modifying therapies start to be available to a broader range of patients and as prevention strategies become established. Many of the underlying molecular mechanisms of currently used biomarkers are incompletely understood. Animal models and in vitro systems using cell lines have been extensively employed but face important translatability limitations. Induced pluripotent stem cell (iPSC) technology, where a theoretically unlimited range of cell types can be reprogrammed from peripheral cells sampled from patients or healthy individuals, has gained prominence over the last decade. It is a promising avenue to study physiological and pathological biomarker function and response to experimental therapeutics. Such systems are amenable to high-throughput drug screening or multiomics readouts such as transcriptomics, lipidomics, and proteomics for biomarker discovery, investigation, and validation. The present review describes the current state of biomarkers in the clinical context of neurodegenerative diseases, with a focus on Alzheimer's disease and frontotemporal dementia. We include a discussion of how iPSC models have been used to investigate and test biomarkers such as amyloid-β, phosphorylated tau, neurofilament light chain or complement proteins, and even nominate novel biomarkers. We discuss the limitations of current iPSC methods, mentioning alternatives such as coculture systems and three-dimensional organoids which address some of these concerns. Finally, we propose exciting prospects for stem cell transplantation paradigms using animal models as a preclinical tool to study biomarkers in the in vivo context.

Assessment of Preanalytical Cerebrospinal Fluid Handling and Storage Factors on Measurement of Aβ1-42, Aβ1-40, and pTau181 Using an Automated Chemiluminescent Platform

BACKGROUND

Standardizing cerebrospinal fluid (CSF) laboratory protocols will improve the reliability and availability of clinical biomarker testing required for prescription of novel Alzheimer disease (AD) therapies. This study evaluated several preanalytical handling and storage factors common to β-amyloid1-42 (Aβ1-42), β-amyloid1-40 (Aβ1-40), and phosphorylated tau (pTau181) concentrations including storage at different temperatures, extended cap contact, various mixing methods, and multiple freeze-thaw cycles.

METHODS

Aβ1-42, Aβ1-40, and pTau181 concentrations were measured using LUMIPULSE G1200 automated assays. Samples were collected in polypropylene tubes of various volumes. Sample cap-contact was evaluated by storing samples in upright and inverted positions at either 4°C for 1 week or -80°C for 1 month. To assess mixing methods, samples were freeze-thawed and mixed by inversion, vortex, horizontal roller, or unmixed prior to assay sampling. The impact of successive freeze-thaw cycles was assessed through freezing, thawing, and analyzing CSF samples.

RESULTS

Short-term storage at 4°C did not affect Aβ1-42, Aβ1-40, or pTau181 measurements in any tube type. Tube cap contact affected Aβ1-42 in 2.5 mL tubes and pTau181 levels in 10 mL tubes. No difference was observed between mixing methods. After 4 freeze-thaw cycles, Aβ1-42 significantly decreased but Aβ1-40 remained unchanged. Utilizing the Aβ1-42/Aβ1-40 ratio, Aβ1-42 values normalized, maintaining ratio values within ±5% of baseline measurements.

CONCLUSIONS

Storage of CSF at 4°C for 1 week or -80°C for 1 month did not significantly affect Aβ1-42, Aβ1-40, pTau181, or associated ratio measurements. Tube cap-contact impacted pTau181 and pTau181/Aβ1-42 values in larger tubes. Mixing methods are equivalent. The Aβ1-42/Aβ1-40 ratio compensates for freeze-thaw variability up to 4 cycles.

Effects of time of the day at sampling on CSF and plasma levels of Alzheimer' disease biomarkers

BACKGROUND

Studies suggest that cerebrospinal fluid (CSF) levels of amyloid-β (Aβ)42 and Aβ40 present a circadian rhythm. However sustained sampling of large volumes of CSF with indwelling intrathecal catheters used in most of these studies might have affected CSF dynamics and thereby confounded the observed fluctuations in the biomarker levels.

METHODS

We included 38 individuals with either normal (N = 20) or abnormal (N = 18) CSF Aβ42/Aβ40 levels at baseline. CSF and plasma were collected at two visits separated by an average of 53 days with lumbar punctures and venipunctures performed either in the morning or evening. At the first visit, sample collection was performed in the morning for 17 participants and the order was reversed for the remaining 21 participants. CSF and plasma samples were analyzed for Alzheimer' disease (AD) biomarkers, including Aβ42, Aβ40, GFAP, NfL p-tau181, p-tau217, p-tau231 and t-tau. CSF samples were also tested using mass spectrometry for 22 synaptic and endo-lysosomal proteins.

RESULTS

CSF Aβ42 (mean difference [MD], 0.21 ng/mL; p = 0.038), CSF Aβ40 (MD, 1.85 ng/mL; p < 0.001), plasma Aβ42 (MD, 1.65 pg/mL; p = 0.002) and plasma Aβ40 (MD, 0.01 ng/mL, p = 0.002) were increased by 4.2-17.0% in evening compared with morning samples. Further, CSF levels of 14 synaptic and endo-lysosomal proteins, including neurogranin and neuronal pentraxin-1, were increased by 4.5-13.3% in the evening samples (MDrange, 0.02-0.56 fmol/µl; p < 0.042). However, no significant differences were found between morning and evening levels for the Aβ42/Aβ40 ratio, different p-tau variants, GFAP and NfL. There were no significant interaction between sampling time and Aβ status for any of the biomarkers, except that CSF t-tau was increased (by 5.74%) in the evening samples compared to the morning samples in Aβ-positive (MD, 16.46 ng/ml; p = 0.009) but not Aβ-negative participants (MD, 1.89 ng/ml; p = 0.47). There were no significant interactions between sampling time and order in which samples were obtained.

DISCUSSION

Our findings provide evidence for diurnal fluctuations in Aβ peptide levels, both in CSF and plasma, while CSF and plasma p-tau, GFAP and NfL were unaffected. Importantly, Aβ42/Aβ40 ratio remained unaltered, suggesting that it is more suitable for implementation in clinical workup than individual Aβ peptides. Additionally, we show that CSF levels of many synaptic and endo-lysosomal proteins presented a diurnal rhythm, implying a build-up of neuronal activity markers during the day. These results will guide the development of unified sample collection procedures to avoid effects of diurnal variation for future implementation of AD biomarkers in clinical practice and drug trials.

Research Progress on the Pathogenesis, Diagnosis, and Drug Therapy of Alzheimer's Disease

As the population ages worldwide, Alzheimer's disease (AD), the most prevalent kind of neurodegenerative disorder among older people, has become a significant factor affecting quality of life, public health, and economies. However, the exact pathogenesis of Alzheimer's remains elusive, and existing highly recognized pathogenesis includes the amyloid cascade hypothesis, Tau neurofibrillary tangles hypothesis, and neuroinflammation hypothesis. The major diagnoses of Alzheimer's disease include neuroimaging positron emission computed tomography, magnetic resonance imaging, and cerebrospinal fluid molecular diagnosis. The therapy of Alzheimer's disease primarily relies on drugs, and the approved drugs on the market include acetylcholinesterase drugs, glutamate receptor antagonists, and amyloid-β monoclonal antibodies. Still, the existing drugs can only alleviate the symptoms of the disease and cannot completely reverse it. This review aims to summarize existing research results on Alzheimer's disease pathogenesis, diagnosis, and drug therapy, with the objective of facilitating future research in this area.

SIMOA Diagnostics on Alzheimer's Disease and Frontotemporal Dementia

BACKGROUND

Accurate diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 matching Control subjects in combination with demographic-clinical characteristics.

METHODS

136 subjects (AD: n = 43, FTD: n = 33, Controls: n = 60) participated. Single-molecule array (SIMOA), glial fibrillary acidic protein (GFAP), neurofilament light (NfL), TAU, and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) in CSF were analyzed with a multiplex neuro 4plex kit. Receiver operating characteristic (ROC) curve analysis compared area under the curve (AUC), while the principal of the sparse partial least squares discriminant analysis (sPLS-DA) was used with the intent to strengthen the identification of confident disease clusters.

RESULTS

CSF exhibited increased levels of all SIMOA biomarkers in AD compared to Controls (AUCs: 0.71, 0.86, 0.92, and 0.94, respectively). Similar patterns were observed in FTD with NfL, TAU, and UCH-L1 (AUCs: 0.85, 0.72, and 0.91). sPLS-DA revealed two components explaining 19% and 9% of dataset variation.

CONCLUSIONS

CSF data provide high diagnostic accuracy among AD, FTD, and Control discrimination. Subgroups of demographic-clinical characteristics and biomarker concentration highlighted the potential of combining different kinds of data for successful and more efficient cohort clustering.

Evaluation of the biodistribution and preliminary safety profile of a novel brain-targeted manganese dioxide-based nanotheranostic system for Alzheimer's disease

A novel brain-targeted and reactive oxygen species-activatable manganese dioxide containing nanoparticle system functionalized with anti-amyloid-β antibody (named aAβ-BTRA-NC) developed by our group has shown great promise as a highly selective magnetic resonance imaging (MRI) contrast agent for early detection and multitargeted disease-modifying treatment of Alzheimer's disease (AD). To further evaluate the suitability of the formulation for future clinical application, we investigated the safety, biodistribution, and pharmacokinetic profile of aAβ-BTRA-NC in a transgenic TgCRND8 mouse AD model, wild type (WT) littermate, and CD-1 mice. Dose-ascending studies demonstrated that aAβ-BTRA-NC was well-tolerated by the animals up to 300 μmol Mn/kg body weight [b.w.], 3 times the efficacious dose for early AD detection without apparent adverse effects; Histopathological, hematological, and biochemical analyses indicated that a single dose of aAβ-BTRA-NC did not cause any toxicity in major organs. Immunotoxicity data showed that aAβ-BTRA-NC was safer than commercially available gadolinium-based MRI contrast agents at an equivalent dose of 100 μmol/kg b.w. of metal ions. Intravenously administered aAβ-BTRA-NC was taken up by main organs with the order of liver, kidneys, intestines, spleen, followed by other organs, and cleared after one day to one week post injection. Pharmacokinetic analysis indicated that the plasma concentration profile of aAβ-BTRA-NC followed a 2-compartmental model with faster clearance in the AD mice than in the WT mice. The results suggest that aAβ-BTRA-NC exhibits a strong safety profile as a nanotheranostic agent which warrants more robust preclinical development for future clinical applications.

Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort

INTRODUCTION

We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities.

METHODS

We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]).

RESULTS

Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function.

DISCUSSION

eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers.

HIGHLIGHTS

Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.

The Taxonomy of Subjective Cognitive Decline: Proposal and First Clinical Evidence from the Geneva Memory Clinic Cohort

INTRODUCTION

Subjective cognitive decline (SCD) is characterized by subjective cognitive concerns without objective cognitive impairment and is considered a risk factor for cognitive decline and dementia. However, most SCD patients will not develop neurodegenerative disorders, yet they may suffer from minor psychiatric, neurological, or somatic comorbidities. The aim of the present study was to provide a taxonomy of the heterogeneous SCD entity and to conduct a preliminary validation using data from a memory clinic sample.

METHODS

Participants were fifty-five SCD individuals consecutively recruited at the Geneva Memory Center. Based on clinical reports, they were classified into three clinically pre-defined subgroups: (i) those with psychological or psychiatric comorbidities (Psy), (ii) those with somatic comorbidities (SomCom), (iii) and those with no apparent cause (NAC). Baseline demographics, clinical, cognitive, and biomarker differences among the SCD subgroups were assessed. Longitudinal cognitive changes (average 3 years follow-up) were modeled using a linear mixed model.

RESULTS

Out of the 55 SCD cases, 16 were SomCom, 18 Psy, and 21 NAC. 47% were female, mean age was 71 years. We observed higher frequency of APOE ε4 carriers in NAC (53%) compared to SomCom (14%) and Psy (0%, p = 0.023) and lower level of plasma Aβ42 in NAC (6.8 ± 1.0) compared to SomCom (8.4 ± 1.1; p = 0.031). SomCom subjects were older (74 years) than Psy (67 years, p = 0.011), and had greater medial temporal lobe atrophy (1.0 ± 1.0) than Psy (0.2 ± 0.6) and NAC (0.4 ± 0.5, p = 0.005). SomCom has worse episodic memory performances (14.5 ± 3.5) than Psy (15.8 ± 0.4) and NAC (15.8 ± 0.7, p = 0.032). We observed a slightly steeper, yet not statistically significant, cognitive decline in NAC (β = -0.48) compared to Psy (β = -0.28) and SomCom (β = -0.24).

CONCLUSIONS

NAC features a higher proportion of APOE ε4 carriers, lower plasma Aβ42 and a trend towards steeper cognitive decline than SomCom and Psy. Taken together, these findings suggest that NACs are at higher risk of cognitive decline due to AD. The proposed clinical taxonomy might be implemented in clinical practice to identify SCD at higher risk. However, such taxonomy should be tested on an independent cohort with a larger sample size.

Blood biomarkers of neurodegeneration associate differently with amyloid deposition, medial temporal atrophy, and cerebrovascular changes in APOE ε4-enriched cognitively unimpaired elderly

BACKGROUND

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β (Aβ) plaques, neurofibrillary tau tangles, and neurodegeneration in the brain parenchyma. Here, we aimed to (i) assess differences in blood and imaging biomarkers used to evaluate neurodegeneration among cognitively unimpaired APOE ε4 homozygotes, heterozygotes, and non-carriers with varying risk for sporadic AD, and (ii) to determine how different cerebral pathologies (i.e., Aβ deposition, medial temporal atrophy, and cerebrovascular pathology) contribute to blood biomarker concentrations in this sample.

METHODS

Sixty APOE ε4 homozygotes (n = 19), heterozygotes (n = 21), and non-carriers (n = 20) ranging from 60 to 75 years, were recruited in collaboration with Auria biobank (Turku, Finland). Participants underwent Aβ-PET ([11C]PiB), structural brain MRI including T1-weighted and T2-FLAIR sequences, and blood sampling for measuring serum neurofilament light chain (NfL), plasma total tau (t-tau), plasma N-terminal tau fragments (NTA-tau) and plasma glial fibrillary acidic protein (GFAP). [11C]PiB standardized uptake value ratio was calculated for regions typical for Aβ accumulation in AD. MRI images were analysed for regional volumes, atrophy scores, and volumes of white matter hyperintensities. Differences in biomarker levels and associations between blood and imaging biomarkers were tested using uni- and multivariable linear models (unadjusted and adjusted for age and sex).

RESULTS

Serum NfL concentration was increased in APOE ε4 homozygotes compared with non-carriers (mean 21.4 pg/ml (SD 9.5) vs. 15.5 pg/ml (3.8), p = 0.013), whereas other blood biomarkers did not differ between the groups (p > 0.077 for all). From imaging biomarkers, hippocampal volume was significantly decreased in APOE ε4 homozygotes compared with non-carriers (6.71 ml (0.86) vs. 7.2 ml (0.7), p = 0.029). In the whole sample, blood biomarker levels were differently predicted by the three measured cerebral pathologies; serum NfL concentration was associated with cerebrovascular pathology and medial temporal atrophy, while plasma NTA-tau associated with medial temporal atrophy. Plasma GFAP showed significant association with both medial temporal atrophy and Aβ pathology. Plasma t-tau concentration did not associate with any of the measured pathologies.

CONCLUSIONS

Only increased serum NfL concentrations and decreased hippocampal volume was observed in cognitively unimpaired APOEε4 homozygotes compared to non-carriers. In the whole population the concentrations of blood biomarkers were affected in distinct ways by different pathologies.

Novel Biomarkers for Alzheimer's Disease: Plasma Neurofilament Light and Cerebrospinal Fluid

Neurodegenerative disorders such as Alzheimer's disease (AD) represent an increasingly significant public health concern. As clinical diagnosis faces challenges, biomarkers are becoming increasingly important in research, trials, and patient assessments. While biomarkers like amyloid-β peptide, tau proteins, CSF levels (Aβ, tau, and p-tau), and neuroimaging techniques are commonly used in AD diagnosis, they are often limited and invasive in monitoring and diagnosis. For this reason, blood-based biomarkers are the optimal choice for detecting neurodegeneration in brain diseases due to their noninvasiveness, affordability, reliability, and consistency. This literature review focuses on plasma neurofilament light (NfL) and CSF NfL as blood-based biomarkers used in recent AD diagnosis. The findings revealed that the core CSF biomarkers of neurodegeneration (T-tau, P-tau, and Aβ42), CSF NFL, and plasma T-tau were strongly associated with Alzheimer's disease, and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer's disease. Elevated levels of plasma and cerebrospinal fluid NfL were linked to decreased [18F]FDG uptake in corresponding brain areas. In participants with Aβ positivity (Aβ+), NfL correlated with reduced metabolism in regions susceptible to Alzheimer's disease. In addition, CSF NfL levels correlate with brain atrophy and predict cognitive changes, while plasma total tau does not. Plasma P-tau, especially in combination with Aβ42/Aβ40, is promising for symptomatic AD stages. Though not AD-exclusive, blood NfL holds promise for neurodegeneration detection and assessing treatment efficacy. Given the consistent levels of T-tau, P-tau, Aβ42, and NFL in CSF, their incorporation into both clinical practice and research is highly recommended.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

A SERS nanocellulose-paper-based analytical device for ultrasensitive detection of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), one of the most prevalent neurodegenerative diseases, results in severe cognitive decline and irreversible memory loss. Early detection of AD is significant to patients for personalized intervention since effective cure and treatment methods for AD are still lacking. Despite the severity of the disease, existing highly sensitive AD detection methods, including neuroimaging and brain deposit-positive lesion tests, are not suitable for screening purposes due to their high cost and complicated operation. Therefore, these methods are unsuitable for early detection, especially in low-resource settings. Although regular paper-based microfluidics are cost-efficient for AD detection, they are restricted by a poor limit of detection (LOD).

RESULTS

To address the above limitations, we report the ultrasensitive and low-cost nanocellulose paper (nanopaper)-based analytical microfluidic devices (NanoPADs) for detecting one of the promising AD blood biomarkers (glial fibrillary acidic protein, GFAP) using Surface-enhanced Raman scattering (SERS) immunoassay. Nanopaper offers advantages as a SERS substrate, such as an ultrasmooth surface, high optical transparency, and tunable chemical properties. We detected the target GFAP in artificial serum, achieving a LOD of 150 fg mL-1.

SIGNIFICANCE

The developed NanoPADs are distinguished by their cost-efficiency and ease of implementation, presenting a promising avenue for effective early detection of AD's GFAP biomarker with ultrahigh sensitivity. More importantly, our work provides the experimental routes for SERS-based immunoassay of biomarkers on NanoPADs for various diseases in the future.

Diurnal cortisol, neuroinflammation, and neuroimaging visual rating scales in memory clinic patients

BACKGROUND

Neuroinflammation is a hallmark of the Alzheimer's disease (AD) pathogenic process. Cortisol dysregulation may increase AD risk and is related to brain atrophy. This cross-sectional study aims to examine interactions of cortisol patterns and neuroinflammation markers in their association with neuroimaging correlates.

METHOD

134 participants were recruited from the Karolinska University Hospital memory clinic (Stockholm, Sweden). Four visual rating scales were applied to magnetic resonance imaging or computed tomography scans: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), white matter lesions (WML), and posterior atrophy. Participants provided saliva samples for assessment of diurnal cortisol patterns, and underwent lumbar punctures for cerebrospinal fluid (CSF) sampling. Three cortisol measures were used: the cortisol awakening response, total daily output, and the ratio of awakening to bedtime levels. Nineteen CSF neuroinflammation markers were categorized into five composite scores: proinflammatory cytokines, other cytokines, angiogenesis markers, vascular injury markers, and glial activation markers. Ordinal logistic regressions were conducted to assess associations between cortisol patterns, neuroinflammation scores, and visual rating scales, and interactions between cortisol patterns and neuroinflammation scores in relation to visual rating scales.

RESULT

Higher levels of angiogenesis markers were associated with more severe WML. Some evidence was found for interactions between dysregulated diurnal cortisol patterns and greater neuroinflammation-related biomarkers in relation to more severe GCA and WML. No associations were found between cortisol patterns and visual rating scales.

CONCLUSION

This study suggests an interplay between diurnal cortisol patterns and neuroinflammation in relation to brain structure. While this cross-sectional study does not provide information on causality or temporality, these findings suggest that neuroinflammation may be involved in the relationship between HPA-axis functioning and AD.

Cerebrospinal fluid glial fibrillary acidic protein, in contrast to amyloid beta protein, is associated with disease symptoms in Huntington's disease

INTRODUCTION

Huntington's disease (HD) is a hereditary neurodegenerative disease, currently lacking disease-modifying treatments. Biomarkers are needed for objective assessment of disease progression. Evidence supports both complex protein aggregation and astrocyte activation in HD. This study assesses the 42 amino acid long amyloid beta (Aβ42) and glial fibrillary acidic protein (GFAP) as potential biomarkers in the cerebrospinal fluid (CSF) of HD mutation carriers.

METHODS

CSF from participants was obtained from three sites in Sweden. Clinical symptoms were graded with the composite Unified Huntington's disease rating scale (cUHDRS). Protein concentrations were measured using ELISA. Pearson correlations were calculated to assess disease progression association. Results were adjusted for age and collection site.

RESULTS

The study enrolled 28 manifest HD patients (ManHD), 13 premanifest HD gene-expansion carriers (PreHD) and 20 controls. Aβ42 levels did not differ between groups and there was no correlation with measures of disease progression. GFAP concentration was higher in ManHD (424 ng/l, SD 253) compared with both PreHD (266 ng/l, SD 92.4) and controls (208 ng/l, SD 83.7). GFAP correlated with both cUHDRS (r = -0.77, p < 0.001), and 5-year risk of disease onset (r = 0.70, p = 0.008).

CONCLUSION

We provide evidence that indicates CSF Aβ42 has limited potential as a biomarker for HD. GFAP is a potential biomarker of progression in HD. Validation in larger cohorts measuring GFAP in blood and CSF would be of interest.

Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort

Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10-8 and 4.3 × 10-7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.

The role of the Pin1-cis P-tau axis in the development and treatment of vascular contribution to cognitive impairment and dementia and preeclampsia

Tauopathies are neurodegenerative diseases characterized by deposits of abnormal Tau protein in the brain. Conventional tauopathies are often defined by a limited number of Tau epitopes, notably neurofibrillary tangles, but emerging evidence suggests structural heterogeneity among tauopathies. The prolyl isomerase Pin1 isomerizes cis P-tau to inhibit the development of oligomers, tangles and neurodegeneration in multiple neurodegenerative diseases such as Alzheimer's disease, traumatic brain injury, vascular contribution to cognitive impairment and dementia (VCID) and preeclampsia (PE). Thus, cis P-tau has emerged as an early etiological driver, blood marker and therapeutic target for multiple neurodegenerative diseases, with clinical trials ongoing. The discovery of cis P-tau and other tau pathologies in VCID and PE calls attention for simplistic classification of tauopathy in neurodegenerative diseases. These recent advances have revealed the exciting novel role of the Pin1-cis P-tau axis in the development and treatment of vascular contribution to cognitive impairment and dementia and preeclampsia.

Early-phase amyloid PET reproduces metabolic signatures of cognitive decline in Parkinson's disease

INTRODUCTION

Recent work suggests that amyloid beta (Aβ) positron emission tomography (PET) tracer uptake shortly after injection ("early phase") reflects brain metabolism and perfusion. We assessed this modality in a predominantly amyloid-negative neurodegenerative condition, Parkinson's disease (PD), and hypothesized that early-phase 18F-florbetaben (eFBB) uptake would reproduce characteristic hypometabolism and hypoperfusion patterns associated with cognitive decline in PD.

METHODS

One hundred fifteen PD patients across the spectrum of cognitive impairment underwent dual-phase Aβ PET, structural and arterial spin labeling (ASL) magnetic resonance imaging (MRI), and neuropsychological assessments. Multiple linear regression models compared eFBB uptake to cognitive performance and ASL MRI perfusion.

RESULTS

Reduced eFBB uptake was associated with cognitive performance in brain regions previously linked to hypometabolism-associated cognitive decline in PD, independent of amyloid status. Furthermore, eFBB uptake correlated with cerebral perfusion across widespread regions.

DISCUSSION

EFBB uptake is a potential surrogate measure for cerebral perfusion/metabolism. A dual-phase PET imaging approach may serve as a clinical tool for assessing cognitive impairment.

Highlights

Images taken at amyloid beta (Aβ) positron emission tomography tracer injection may reflect brain perfusion and metabolism.Parkinson's disease (PD) is a predominantly amyloid-negative condition.Early-phase florbetaben (eFBB) in PD was associated with cognitive performance.eFBB uptake reflects hypometabolism-related cognitive decline in PD.eFBB correlated with arterial spin labeling magnetic resonance imaging measured cerebral perfusion.eFBB distinguished dementia from normal cognition and mild cognitive impairment.Findings were independent of late-phase Aβ burden.Thus, eFBB may serve as a surrogate measure for brain metabolism/perfusion.

The potential diagnostic accuracy of circulating microRNAs for Alzheimer's disease: A meta-analysis

BACKGROUND & OBJECTIVE

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease that seriously affects cognitive ability and has become a key public health problem. Many studies have identified the possibility of peripheral blood microRNA as effective non-invasive biomarkers for AD diagnosis, but the results are inconsistent. Therefore, we carried out this meta-analysis to evaluate the diagnostic accuracy of circulating microRNAs in the diagnosis of AD patients.

METHODS

We performed a systematic literature search of the following databases: PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure, updated to March 15, 2021. A random effects model was used to pool the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve. Meta-regression and subgroup analysis were performed to explore the sources of heterogeneity, and Deeks' funnel plot was used to assess whether there was publication bias.

RESULTS

62 studies from 18 articles were included in this meta-analysis. The pooled sensitivity was 0.82 (95% CI: 0.78-0.85), specificity was 0.80 (95% CI: 0.76-0.83), PLR was 4. 1 (95% CI: 3.4-4.9), NLR was 0.23 (95% CI: 0.19-0.28), DOR was 18 (95% CI: 13-25) and AUC was 0.88 (95% CI: 0.84-0.90). Subgroup analysis shows that the microRNA clusters of plasma type performed a better diagnostic accuracy of AD patients. In addition, publication bias was not found.

CONCLUSIONS

Circulating microRNAs can be used as a promising non-invasive biomarker in AD diagnosis.

ReTimeML: a retention time predictor that supports the LC-MS/MS analysis of sphingolipids

The analysis of ceramide (Cer) and sphingomyelin (SM) lipid species using liquid chromatography-tandem mass spectrometry (LC-MS/MS) continues to present challenges as their precursor mass and fragmentation can correspond to multiple molecular arrangements. To address this constraint, we developed ReTimeML, a freeware that automates the expected retention times (RTs) for Cer and SM lipid profiles from complex chromatograms. ReTimeML works on the principle that LC-MS/MS experiments have pre-determined RTs from internal standards, calibrators or quality controls used throughout the analysis. Employed as reference RTs, ReTimeML subsequently extrapolates the RTs of unknowns using its machine-learned regression library of mass-to-charge (m/z) versus RT profiles, which does not require model retraining for adaptability on different LC-MS/MS pipelines. We validated ReTimeML RT estimations for various Cer and SM structures across different biologicals, tissues and LC-MS/MS setups, exhibiting a mean variance between 0.23 and 2.43% compared to user annotations. ReTimeML also aided the disambiguation of SM identities from isobar distributions in paired serum-cerebrospinal fluid from healthy volunteers, allowing us to identify a series of non-canonical SMs associated between the two biofluids comprised of a polyunsaturated structure that confers increased stability against catabolic clearance.

CSF 14-3-3 zeta(ζ) isoform is associated with tau pathology and cognitive decline in Alzheimer's disease

14-3-3 is a family of conserved proteins that consist of seven isoforms which are highly expressed in the brain, and 14-3-3 zeta(ζ) is one of the isoforms encoded by the YWHAZ gene. Previous studies demonstrated that 14-3-3ζ is deposited in the neurofibrillary tangles of Alzheimer's disease (AD) brains, and that 14-3-3ζ interacts with tau from the purified neurofibrillary tangles of AD brain extract. The present study examined the cerebrospinal fluid (CSF) 14-3-3ζ levels of 719 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including cognitively normal (CN) participants, patients with mild cognitive impairment (MCI) and patients with AD dementia, and aimed to identify whether CSF 14-3-3ζ is associated with tau pathology. CSF 14-3-3ζ levels were increased in AD, and particularly elevated among tau pathology positive individuals. CSF 14-3-3ζ levels were associated with CSF phosphorylated tau 181 (p-tau) (r = 0.741, P < 0.001) and plasma p-tau (r = 0.293, P < 0.001), which are fluid biomarkers of tau pathology, and could predict tau pathology positive status with high accuracy (area under the receiver operating characteristic curve [AUC], 0.891). CSF 14-3-3ζ levels were also correlated to synaptic biomarker CSF GAP-43 (r = 0.609, P < 0.001) and neuroinflammatory biomarker CSF sTREM-2 (r = 0.507, P < 0.001). High CSF 14-3-3ζ levels at baseline were associated with progressive decline of cognitive function and neuroimaging findings during follow up. In conclusion, this study suggests that CSF 14-3-3ζ is a potential biomarker of AD that may be useful in clinical practice.

Cortical folding correlates to aging and Alzheimer's Disease's cognitive and CSF biomarkers

This manuscript presents the quantification and correlation of three aspects of Alzheimer's Disease evolution, including structural, biochemical, and cognitive assessments. We aimed to test a novel structural biomarker for neurodegeneration based on a cortical folding model for mammals. Our central hypothesis is that the cortical folding variable, representative of axonal tension in white matter, is an optimal discriminator of pathological aging and correlates with altered loadings in Cerebrospinal Fluid samples and a decline in cognition and memory. We extracted morphological features from T1w 3T MRI acquisitions using FreeSurfer from 77 Healthy Controls (age = 66 ± 8.4, 69% females), 31 Mild Cognitive Impairment (age = 72 ± 4.8, 61% females), and 13 Alzheimer's Disease patients (age = 77 ± 6.1, 62% females) of recruited volunteers in Brazil to test its discriminative power using optimal cut-point analysis. Cortical folding distinguishes the groups with reasonable accuracy (Healthy Control-Alzheimer's Disease, accuracy = 0.82; Healthy Control-Mild Cognitive Impairment, accuracy = 0.56). Moreover, Cerebrospinal Fluid biomarkers (total Tau, A[Formula: see text]1-40, A[Formula: see text]1-42, and Lipoxin) and cognitive scores (Cognitive Index, Rey's Auditory Verbal Learning Test, Trail Making Test, Digit Span Backward) were correlated with the global neurodegeneration in MRI aiming to describe health, disease, and the transition between the two states using morphology.

Effects of certain pre-analytical factors on the performance of plasma phospho-tau217

INTRODUCTION

Pre-analytical factors can cause substantial variability in the measurements of cerebrospinal fluid (CSF) and plasma biomarkers of Alzheimer's disease (AD). However, their effects on the performance of one of the most promising plasma AD biomarkers, phosphorylated tau (p-tau)217, are not known.

METHODS

We included 50 amyloid-β positive (Aβ+) and 50 Aβ- participants from the Swedish BioFINDER-1 study. Plasma and CSF p-tau217 were measured using an immunoassay developed by Lilly Research Laboratories. We examined the effect of four plasma handling conditions, i.e., (1) thawing at room temperature (RT) with no centrifugation, (2) thawing at RT followed by centrifugation, (3) thawing on ice with no centrifugation, and (4) thawing on ice followed by centrifugation. In addition, we also tested the effects of up to 3 freeze-thaw cycles on the associations of plasma p-tau217 with AD-related pathologies measured with CSF p-tau217 and CSF Aβ42/Aβ40.

RESULTS

In the whole cohort (combining Aβ+ and Aβ- participants), we found significant correlations between plasma p-tau217 and both CSF p-tau217 (Rrange, 0.614-0.717, p < 0.001) and CSF Aβ42/Aβ40 (Spearman Rrange, - 0.515 to - 0.652, p < 0.001) for each of the four tested conditions. Correlations between plasma and CSF p-tau217 were also significant for all conditions in the Aβ+ group (Rrange, 0.506-0.579, p < 0.001). However, in this Aβ+ subgroup, correlations with CSF Aβ42/Aβ40 were only significant for centrifuged samples (thawed at RT, R =  - 0.394, p = 0.010; thawed on ice, R =  - 0.406; p = 0.007). In Aβ- participants, correlations between plasma and CSF p-tau217 were again significant only for centrifuged samples (thawed at RT, R = 0.394, p = 0.007; thawed on ice, R = 0.334; p = 0.022), with no correlations seen between plasma p-tau217 and CSF Aβ42/Aβ40 for any of the conditions. While the accuracy of plasma p-tau217 to identify individuals with abnormal CSF Aβ42/Aβ40 or CSF p-tau217 status was high, the AUCs for samples thawed at RT and analyzed without centrifugation were numerically lower than the AUCs of other conditions (CSF Aβ42/Aβ40 = 0.845 vs 0.872-0.884; CSF p-tau217 = 0.866 vs 0.908-0.924, pdiff > 0.11). P-tau217 concentration was consistently higher in non-centrifuged samples than in centrifuged samples (p ≤ 0.021). There were no differences between samples freeze-thawed once, twice, or three times.

CONCLUSION

Centrifugation improved the performance of plasma p-tau217, but thawing temperatures and up to three freeze-thaw cycles did not have a significant impact. These results may inform the future development of standardized sample-handling protocols for AD biomarkers.

Association of cigarette smoking with cerebrospinal fluid biomarkers of insulin sensitivity and neurodegeneration

INTRODUCTION

Cigarette smoking increases both the risk for insulin resistance and amyloid-β (Aβ) aggregation, and impaired brain insulin/insulin-like growth factor 1 (IGF1) signaling might increase risk factors for Alzheimer's disease (AD). We aimed to investigate the association among cerebrospinal fluid (CSF) insulin sensitivity/IGF1, glucose/lactate, and Aβ42 and further explore whether insulin sensitivity contributed to the risk for AD in active smokers.

METHODS

In this cross-sectional study, levels of insulin, IGF1, and lactate/glucose of 75 active smokers and 78 nonsmokers in CSF were measured. Three polymorphisms regulating IGF1 were genotyped. Analysis of variance was used to compare differences of variables between groups. Partial correlation was performed to test the relationship between CSF biomarkers and smoking status. General linear models were applied to test the interaction of the effect of single nucleotide polymorphisms and cigarette smoking on CSF IGF1 levels.

RESULTS

In the CSF from active smokers, IGF1 and lactate levels were significantly lower (p = .016 and p = .010, respectively), whereas Aβ42 (derived from our earlier research) and insulin levels were significantly higher (p < .001 and p = .022, respectively) as compared to the CSF from nonsmokers. The AG + GG genotype of rs6218 in active smokers had a significant effect on lower CSF IGF1 levels (p = .004) and lower CSF insulin levels in nonsmokers (p = .016).

CONCLUSIONS

Cigarette smoking as the "at-risk" factor for AD might be due to lower cerebral insulin sensitivity in CSF, and the subjects with rs6218G allele seem to be more susceptible to the neurodegenerative risks for cigarette smoking.

Akt activation ameliorates deficits in hippocampal-dependent memory and activity-dependent synaptic protein synthesis in an Alzheimer's disease mouse model

Protein kinase-B (Akt) and the mechanistic target of rapamycin (mTOR) signaling pathways are implicated in Alzheimer's disease (AD) pathology. Akt/mTOR signaling pathways, activated by external inputs, enable new protein synthesis at the synapse and synaptic plasticity. The molecular mechanisms impeding new protein synthesis at the synapse in AD pathogenesis remain elusive. Here, we aimed to understand the molecular mechanisms prior to the manifestation of histopathological hallmarks by characterizing Akt1/mTOR signaling cascades and new protein synthesis in the hippocampus of WT and amyloid precursor protein/presenilin-1 (APP/PS1) male mice. Intriguingly, compared to those in WT mice, we found significant decreases in pAkt1, pGSK3β, pmTOR, pS6 ribosomal protein, and p4E-BP1 levels in both post nuclear supernatant and synaptosomes isolated from the hippocampus of one-month-old (presymptomatic) APP/PS1 mice. In synaptoneurosomes prepared from the hippocampus of presymptomatic APP/PS1 mice, activity-dependent protein synthesis at the synapse was impaired and this deficit was sustained in young adults. In hippocampal neurons from C57BL/6 mice, downregulation of Akt1 precluded synaptic activity-dependent protein synthesis at the dendrites but not in the soma. In three-month-old APP/PS1 mice, Akt activator (SC79) administration restored deficits in memory recall and activity-dependent synaptic protein synthesis. C57BL/6 mice administered with an Akt inhibitor (MK2206) resulted in memory recall deficits compared to those treated with vehicle. We conclude that dysregulation of Akt1/mTOR and its downstream signaling molecules in the hippocampus contribute to memory recall deficits and loss of activity-dependent synaptic protein synthesis. In AD mice, however, Akt activation ameliorates deficits in memory recall and activity-dependent synaptic protein synthesis.

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.

CRISPR-Powered Aptasensor for Diagnostics of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia, characterized by the accumulation of amyloid beta (Aβ) peptides in the brain. Here, we present a simple, rapid, and affordable CRISPR-powered aptasensor for the quantitative detection of Aβ40 and Aβ42 biomarkers in cerebrospinal fluid (CSF) samples, enabling early and accurate diagnostics of AD patients. The aptasensor couples the high specificity of aptamers for Aβ biomarkers with CRISPR-Cas12a-based fluorescence detection. The CRISPR-powered aptasensor enables us to detect Aβ40 and Aβ42 in CSF samples within 60 min, achieving a detection sensitivity of 1 pg/mL and 0.1 pg/mL, respectively. To validate its clinical utility, we quantitatively detected Aβ40 and Aβ42 biomarkers in clinical CSF samples. Furthermore, by combining CSF Aβ42 levels with the c(Aβ42)/c(Aβ40) ratio, we achieved an accurate diagnostic classification of AD patients and healthy individuals, showing superior performance over the conventional ELISA method. We believe that our innovative aptasensor approach holds promise for the early diagnostic classification of AD patients.

Detection of Femtomolar Amyloid-β Peptides for Early-Stage Identification of Alzheimer's Amyloid-β Aggregation with Functionalized Gold Nanoparticles

Progressive amyloid-β (Aβ) fibrillar aggregates have long been considered as the pathogenesis of Alzheimer's disease (AD). Biocompatible and stable cysteine-Aβ peptide-conjugated gold nanoparticles (Cys-Aβ@AuNP) are demonstrated as suitable materials for detecting subfemtomolar Aβ peptides in human plasma. Incubation with Aβ peptides causes the Cys-Aβ@AuNP to aggregate and changes its absorption spectra. The spectral change is especially apparent and noticeable when detecting subfemtomolar Aβ peptides, and the aggregates contain only two or three AuNPs. Cys-Aβ@AuNP can also be used to identify early-stage Aβ oligomerization, which is not possible using the conventional method, in which the fluorescence of thioflavin-T is measured. The ability to detect Aβ oligomerization can facilitate therapeutics for AD. In addition, the binding of Aβ peptides by Cys-Aβ@AuNP in combination with centrifugation redirects the conventional Aβ aggregation pathway and can effectively inhibit the formation of toxic Aβ oligomers or fibrils. Therefore, the proposed Cys-Aβ@AuNP can also be used to develop effective therapeutic agents to inhibit Aβ aggregation. The results obtained in this study are expected to open revolutionary ways to both detect and inhibit Aβ aggregation at an early stage.

Tau Protein Alterations Induced by Hypobaric Hypoxia Exposure

Tauopathies are a group of neurodegenerative diseases whose central feature is dysfunction of the microtubule-associated protein tau (MAPT). Although the exact etiology of tauopathies is still unknown, it has been hypothesized that their onset may occur up to twenty years before the clear emergence of symptoms, which has led to questions about whether the prognosis of these diseases can be improved by, for instance, targeting the factors that influence tauopathy development. One such factor is hypoxia, which is strongly linked to Alzheimer's disease because of its association with obstructive sleep apnea and has been reported to affect molecular pathways related to the dysfunction and aggregation of tau proteins and other biomarkers of neurological damage. In particular, hypobaric hypoxia exposure increases the activation of several kinases related to the hyperphosphorylation of tau in neuronal cells, such as ERK, GSK3β, and CDK5. In addition, hypoxia also increases the levels of inflammatory molecules (IL-β1, IL-6, and TNF-α), which are also associated with neurodegeneration. This review discusses the many remaining questions regarding the influence of hypoxia on tauopathies and the contribution of high-altitude exposure to the development of these diseases.

Secretome Analyses Identify FKBP4 as a GBA1-Associated Protein in CSF and iPS Cells from Parkinson's Disease Patients with GBA1 Mutations

Mutations in the GBA1 gene increase the risk of developing Parkinson's disease (PD). However, most carriers of GBA1 mutations do not develop PD throughout their lives. The mechanisms of how GBA1 mutations contribute to PD pathogenesis remain unclear. Cerebrospinal fluid (CSF) is used for detecting pathological conditions of diseases, providing insights into the molecular mechanisms underlying neurodegenerative disorders. In this study, we utilized the proximity extension assay to examine the levels of metabolism-linked protein in the CSF from 17 PD patients carrying GBA1 mutations (GBA1-PD) and 17 idiopathic PD (iPD). The analysis of CSF secretome in GBA1-PD identified 11 significantly altered proteins, namely FKBP4, THOP1, GLRX, TXNDC5, GAL, SEMA3F, CRKL, APLP1, LRP11, CD164, and NPTXR. To investigate GBA1-associated CSF changes attributed to specific neuronal subtypes responsible for PD, we analyzed the cell culture supernatant from GBA1-PD-induced pluripotent stem cell (iPSC)-derived midbrain dopaminergic (mDA) neurons. The secretome analysis of GBA1-PD iPSC-derived mDA neurons revealed that five differently regulated proteins overlapped with those identified in the CSF analysis: FKBP4, THOP1, GLRX, GAL, and CRKL. Reduced intracellular level of the top hit, FKPB4, was confirmed via Western Blot. In conclusion, our findings identify significantly altered CSF GBA1-PD-associated proteins with FKPB4 being firmly attributed to mDA neurons.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status

BACKGROUND

Although cerebrospinal fluid (CSF) amyloid-β42 peptide (Aβ42) and phosphorylated tau (p-tau) and blood p-tau are valuable for differential diagnosis of Alzheimer's disease (AD) from cognitively normal (CN) there is a lack of validated biomarkers for mild cognitive impairment (MCI).

OBJECTIVE

This study sought to determine how plasma and CSF protein markers compared in the characterization of MCI and AD status.

METHODS

This cohort study included Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 75 proteins measured commonly in plasma and CSF (257 total, 46 CN, 143 MCI, and 68 AD). Logistic regression, least absolute shrinkage and selection operator (LASSO) and Random Forest (RF) methods were used to identify the protein candidates for the disease classification.

RESULTS

We observed that six plasma proteins panel (APOE, AMBP, C3, IL16, IGFBP2, APOD) outperformed the seven CSF proteins panel (VEGFA, HGF, PRL, FABP3, FGF4, CD40, RETN) as well as AD markers (CSF p-tau and Aβ42) to distinguish the MCI from AD [area under the curve (AUC) = 0.75 (plasma proteins), AUC = 0.60 (CSF proteins) and AUC = 0.56 (CSF p-tau and Aβ42)]. Also, these six plasma proteins performed better than the CSF proteins and were in line with CSF p-tau and Aβ42 in differentiating CN versus MCI subjects [AUC = 0.89 (plasma proteins), AUC = 0.85 (CSF proteins) and AUC = 0.89 (CSF p-tau and Aβ42)]. These results were adjusted for age, sex, education, and APOEϵ4 genotype.

CONCLUSIONS

This study suggests that the combination of 6 plasma proteins can serve as an effective marker for differentiating MCI from AD and CN.

Assessing the Linguistic Capacity Across Alzheimer's Disease and Its Preclinical Stages: Evidence from Narrative Macrostructure in Elderly Speakers of Greek

Background

The assessment of language deficits can be valuable in the early clinical diagnosis of neurodegenerative disorders, including Alzheimer's disease (AD).

Objective

The present study aims to explore whether language markers at the macrostructural level could assist with the placement of an individual across the dementia continuum employing production data from structured narratives.

Methods

We administered a Picture Sequence Narrative Discourse Task to 170 speakers of Greek: young healthy controls (yHC), cognitively intact healthy elders (eHC), elder participants with subjective cognitive impairment (SCI), with mild cognitive impairment (MCI), and with AD dementia at the mild/moderate stages. Structural MRIs, medical history, neurological examination, and neuropsychological/cognitive screening determined the status of each speaker to appropriately groupthem.

Results

The data analysis revealed that the Macrostructure Index, Irrelevant Info, and Narration Density markers can track cognitive decline and AD (p < 0.001; Macrostructural Index: eHC versus AD Sensitivity 93.8%, Specificity 74.4%, MCI versus AD Sensitivity 93.8%, Specificity 66.7%; Narration Density: eHC versus AD Sensitivity 90.6%, Specificity 71.8%, MCI versus AD Sensitivity 93.8%, Specificity 66.7%). Moreover, Narrative Complexity was significantly affected for subjects with AD, Irrelevant Info increased in the narrations of speakers with MCI and AD, while Narration Length did not appear to indubitably differentiate between the cognitively intact groups and the clinical ones.

Conclusions

Narrative Macrostructure Indices provide valuable information on the language profile of speakers with(out) intact cognition revealing subtle early signs of cognitive decline and AD suggesting that the inclusion of language-based assessment tools would facilitate the clinical process.

Preventing cognitive decline via digital inclusion and virtual game management: an intervention study with older adults in the community

OBJECTIVE

To evaluate the impact of cognitive stimulation via digital inclusion and the practice of video games on the cognition of the older population.

METHOD

This is a randomized controlled intervention study, nested in a population cohort study. Based on the application of the Clinical Dementia Rating (CDR) test, individuals aged 60 years or older with scores 0 and 0.5 were included and randomly allocated in the Intervention Group (IG) or Control Group (CG). Initially, 160 participants met the selection criteria and underwent neuropsychological evaluation via the Montreal Cognitive Assessment (MoCA), applied before and after intervention. The IG (n = 62) participated in computer-based intervention once a week for one-and-a-half hours, for 4 months. The CG (n = 47) participated in the mindfulness workshops held in the same period.

RESULTS

The digital literacy intervention group averaged 2.6 points more in the MoCA after 4 months. The change in the final MoCA decreased in 0.46 points at each unit in the basal MoCA. Individuals with average schooling had an increase of 0.93 points in the change of the MoCA in relation to individuals with low or high schooling.

CONCLUSION

Digital inclusion combined with the practice of video games has the potential to improve the cognition of the older population.