Potential Value of Plasma Amyloid-β, Total Tau, and Neurofilament Light for Identification of Early Alzheimer's Disease

Combined use of Donepezil and Memantine increases the probability of five-year survival of Alzheimer's disease patients

BACKGROUND

Alzheimer's disease (AD) is the most common neurodegenerative disease. Studying the effects of drug treatments on multiple health outcomes related to AD could be beneficial in demonstrating which drugs reduce the disease burden and increase survival.

METHODS

We conducted a comprehensive causal inference study implementing doubly robust estimators and using one of the largest high-quality medical databases, the Oracle Electronic Health Records (EHR) Real-World Data. Our work was focused on the estimation of the effects of the two common Alzheimer's disease drugs, Donepezil and Memantine, and their combined use on the five-year survival since initial diagnosis of AD patients. Also, we formally tested for the presence of interaction between these drugs.

RESULTS

Here, we show that the combined use of Donepezil and Memantine significantly elevates the probability of five-year survival. In particular, their combined use increases the probability of five-year survival by 0.050 (0.021, 0.078) (6.4%), 0.049 (0.012, 0.085), (6.3%), 0.065 (0.035, 0.095) (8.3%) compared to no drug treatment, the Memantine monotherapy, and the Donepezil monotherapy respectively. We also identify a significant beneficial additive drug-drug interaction effect between Donepezil and Memantine of 0.064 (0.030, 0.098).

CONCLUSIONS

Based on our findings, adopting combined treatment of Memantine and Donepezil could extend the lives of approximately 303,000 people with AD living in the USA to be beyond five-years from diagnosis. If these patients instead have no drug treatment, Memantine monotherapy or Donepezil monotherapy they would be expected to die within five years.

Serum neurofilament light chain and inflammatory cytokines as biomarkers for early detection of mild cognitive impairment

To investigate the association between serum neurofilament light chain (NfL) levels, inflammatory cytokines, and cognitive function to assess their utility in the early detection of mild cognitive impairment (MCI). We conducted a cross-sectional study involving 157 community-dwelling individuals aged 55 years and above, categorized into healthy controls, MCI, and probable Alzheimer's disease (AD). Serum levels of NfL, inflammatory cytokines, and AD pathology markers were measured using enzyme-linked immunosorbent assay (ELISA). Correlations between these biomarkers and cognitive function were analyzed, and the diagnostic performance of the cognitive assessment scales and serum biomarker concentrations was evaluated using receiver operating characteristic (ROC) curve analysis. Serum NfL levels were significantly elevated in MCI and probable AD groups compared to healthy controls. Positive correlations were found between serum NfL and inflammatory cytokines IL-1β, IL-6, and Aβ40. Combining serum NfL with p-tau217 and the Boston Naming Test significantly enhanced the predictive accuracy for MCI. However, combining serum NfL with inflammatory markers did not improve MCI prediction accuracy. Elevated serum NfL is associated with cognitive impairment and inflammatory markers, suggesting its potential as a peripheral serum biomarker for MCI detection. The combination of serum NfL with p-tau217 and cognitive tests could offer a more accurate prediction of MCI, providing new insights for AD treatment strategies.

Macrophage Migration Inhibitory Factor as a Potential Plasma Biomarker of Cognitive Impairment in Cerebral Small Vessel Disease

As the pathogenesis of cerebral small vessel disease with cognitive impairment (CSVD-CI) remains unclear, identifying effective biomarkers can contribute to the clinical management of CSVD-CI. This study recruited 54 healthy controls (HCs), 60 CSVD-CI patients, and 57 CSVD cognitively normal (CSVD-CN) patients. All participants underwent neuropsychological assessments and multimodal magnetic resonance imaging. Macrophage migration inhibitory factors (MIFs) were assessed in plasma. The least absolute shrinkage and selection operator model was used to determine a composite marker. Compared with HCs or CSVD-CN patients, CSVD-CI patients had significantly increased plasma MIF levels. In CSVD-CI patients, plasma MIF levels were significantly correlated with multiple cognitive assessment scores, plasma levels of blood-brain barrier (BBB)-related indices, white matter hyperintensity Fazekas scores, and the mean amplitude of low-frequency fluctuation in the right superior temporal gyrus. Higher plasma MIF levels were significantly associated with worse global cognition and information processing speed in CSVD-CI patients. The composite marker (including plasma MIF) distinguished CSVD-CI patients from CSVD-CN and HCs with >80% accuracy. Meta-analysis indicated that blood MIF levels were significantly increased in CSVD-CI patients. In conclusion, plasma MIF is a potential biomarker for early identification of CSVD-CI. Plasma MIF may play a role in cognitive decline in CSVD through BBB dysfunction and changes in white matter hyperintensity and brain activity.

Correlations between cognitive reserve, gray matter, and cerebrospinal fluid volume in healthy elders and mild cognitive impairment patients

Objective

To explore the effect of cognitive reserve (CR) on brain volume and cerebrospinal fluid (CSF) in patients with mild cognitive impairment (MCI) and healthy elders (HE).

Methods

31 HE and 50 MCI patients were collected in this study to obtain structural MRI, cognitive function, and composite CR scores. Educational attainment, leisure time, and working activity ratings from two groups were used to generate cognitive reserve index questionnaire (CRIq) scores. The different volumes of brain regions and CSF were obtained using uAI research portal in both groups, which were taken as the regions of interest (ROI), the correlation analysis between ROIs and CRIq scores were conducted.

Results

The scores of CRIq, CRIq-leisure time, and CRIq-education in HE group were significantly higher than patients in MCI group, and the montreal cognitive assessment (MoCA) and minimum mental state examination (MMSE) scores were positively correlated with the CRIq, CRIq-education in both groups, and were positively correlated with CRIq-leisure time in MCI group. The scores of auditory verbal learning test (AVLT) and verbal fluency test (VFT) were also positively correlated with CRIq, CRIq-leisure time, and CRIq-education in MCI group, but the score of AVLT was only positively correlated with CRIq in HE group. Moreover, in MCI group, the volume of the right middle cingulate cortex and the right parahippocampal gyrus were negatively correlated with the CRIq, and the volume of CSF, peripheral CSF, and third ventricle were positively correlated with the CRIq-leisure time score. The result of mediation analysis suggested that right parahippocampal gryus mediated the main effect of the relationship between CRIq and MoCA score in MCI group.

Conclusion

People with higher CR show better levels of cognitive function, and MCI patients with higher CR showed more severe volume atrophy of the right middle cingulate cortex and the right parahippocampal gyrus, but more CSF at a given level of global cognition.

The potential of blood neurofilament light as a marker of neurodegeneration for Alzheimer's disease

Over the past several years, there has been a surge in blood biomarker studies examining the value of plasma or serum neurofilament light (NfL) as a biomarker of neurodegeneration for Alzheimer's disease. However, there have been limited efforts to combine existing findings to assess the utility of blood NfL as a biomarker of neurodegeneration for Alzheimer's disease. In addition, we still need better insight into the specific aspects of neurodegeneration that are reflected by the elevated plasma or serum concentration of NfL. In this review, we survey the literature on the cross-sectional and longitudinal relationships between blood-based NfL levels and other, neuroimaging-based, indices of neurodegeneration in individuals on the Alzheimer's continuum. Then, based on the biomarker classification established by the FDA-NIH Biomarker Working group, we determine the utility of blood-based NfL as a marker for monitoring the disease status (i.e. monitoring biomarker) and predicting the severity of neurodegeneration in older adults with and without cognitive decline (i.e. a prognostic or a risk/susceptibility biomarker). The current findings suggest that blood NfL exhibits great promise as a monitoring biomarker because an increased NfL level in plasma or serum appears to reflect the current severity of atrophy, hypometabolism and the decline of white matter integrity, particularly in the brain regions typically affected by Alzheimer's disease. Longitudinal evidence indicates that blood NfL can be useful not only as a prognostic biomarker for predicting the progression of neurodegeneration in patients with Alzheimer's disease but also as a susceptibility/risk biomarker predicting the likelihood of abnormal alterations in brain structure and function in cognitively unimpaired individuals with a higher risk of developing Alzheimer's disease (e.g. those with a higher amyloid-β). There are still limitations to current research, as discussed in this review. Nevertheless, the extant literature strongly suggests that blood NfL can serve as a valuable prognostic and susceptibility biomarker for Alzheimer's disease-related neurodegeneration in clinical settings, as well as in research settings.

Correlation studies of Hippocampal Morphometry and Plasma NFL Levels in Cognitively Unimpaired Subjects

Alzheimer's disease(AD) is being the burden of society and family. Applying computing-aided strategies to reveal its pathology is one of the research highlights. Plasma neurofilament light (NFL) is an emerging noninvasive and economic biomarker for AD molecular pathology. It is valuable to reveal the correlations between the plasma NFL levels and neurodegeneration, especially hippcampal deformations at the preclinical stage. The negative correlation between plasma NFL levels and hippocampal volumes has been documented. However, the relationship between the plasma NFL levels and the hippocampal morphometry details at the preclinical stage is still elusive. This study seeks to demonstrate the capacity of our proposed surface-based hippocampal morphometry system to discern the plasma NFL positive (NFL+>41.9 pg/L) level and plasma NFL negative (NFL-<41.9pg/L) level and illustrate its superiority to the hippocampal volume measurement by drawing the cohort of 154 CU middle aged and elderly adults. We also apply this morphometry measure and a proposed sparse coding based classification algorithm to classify CU individuals with NFL+ and NFL- levels. Experimental results show that the proposed hippocampal morphometry system offers stronger statistical power to discriminate CU subjects with NFL+ and NFL- levels, comparing with the hippocampal volume measure. Furthermore, this system can discriminate plasma NFL levels in CU individuals (Accuracy=0.86). Both the group level and individual level analysis results indicate that the association between plasma NFL levels and the hippocampal shapes can be mapped at the preclinical stage.

SIMOA-based analysis of plasma NFL levels in MCI and AD patients: a systematic review and meta-analysis

BACKGROUND

The single-molecule array assay (SIMOA)-based detection of neurofilament light (NFL) chain could be useful in diagnosing mild cognitive impairment (MCI) and Alzheimer's disease (AD). This meta-analysis aimed to evaluate the circulating concentration of NFL in AD and MCI patients compared with healthy controls using the SIMOA technique.

METHODS

To this end, Google Scholar, PubMed, Scopus, Web of Science, and the reference lists of relevant articles were systematically searched for studies reporting serum NFL chain levels in healthy controls, MCI, and AD patients. Appropriate statistical methods were employed to achieve the study purpose.

RESULTS

Fifteen eligible studies including 3086 patients were pooled out of a total of 347 publications. Fixed effect model analysis showed that NFL chain level was significantly higher in the serum of patients with MCI (0.361 SMD, 95% CI, 0.286-0.435, p = 0.000, I2 = 49.179) and AD (0.808 SMD, 95% CI, 0.727-0.888, p = 0.000, I2 = 39.433) compared with healthy individuals. The analysis also showed that the NFL chain levels in plasma were significantly different between patients with MCI and AD (0.436 SMD, 95% CI, 0.359-0.513, p = 0.000, I2 = 37.44). The overall heterogeneity of the studies was modest.

CONCLUSIONS

This study highlights the potential of serum NFL chain detected using SIMOA in differentiating MCI, AD, and healthy controls.

A causal inference study: The impact of the combined administration of Donepezil and Memantine on decreasing hospital and emergency department visits of Alzheimer's disease patients

Alzheimer's disease is the most common type of dementia that currently affects over 6.5 million people in the U.S. Currently there is no cure and the existing drug therapies attempt to delay the mental decline and improve cognitive abilities. Two of the most commonly prescribed such drugs are Donepezil and Memantine. We formally tested and confirmed the presence of a beneficial drug-drug interaction of Donepezil and Memantine using a causal inference analysis. We applied doubly robust estimators to one of the largest and high-quality medical databases to estimate the effect of two commonly prescribed Alzheimer's disease (AD) medications, Donepezil and Memantine, on the average number of hospital or emergency department visits per year among patients diagnosed with AD. Our results show that, compared to the absence of medication scenario, the Memantine monotherapy, and the Donepezil monotherapy, the combined use of Donepezil and Memantine treatment significantly reduces the average number of hospital or emergency department visits per year by 0.078 (13.8%), 0.144 (25.5%), and 0.132 days (23.4%), respectively. The assessed decline in the average number of hospital or emergency department visits per year is consequently associated with a substantial reduction in medical costs. As of 2022, according to the Alzheimer's Disease Association, there were over 6.5 million individuals aged 65 and older living with AD in the US alone. If patients who are currently on no drug treatment or using either Donepezil or Memantine alone were switched to the combined used of Donepezil and Memantine therapy, the average number of hospital or emergency department visits could decrease by over 613 thousand visits per year. This, in turn, would lead to a remarkable reduction in medical expenses associated with hospitalization of AD patients in the US, totaling over 940 million dollars per year.

Precise profiling of exosomal biomarkers via programmable curved plasmonic nanoarchitecture-based biosensor for clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease of complex pathogenesis, with overt symptoms following disease progression. Early AD diagnosis is challenging due to the lack of robust biomarkers and limited patient access to diagnostics via neuroimaging and cerebrospinal fluid (CSF) tests. Exosomes present in body fluids are attracting attention as diagnostic biomarkers that directly reflect neuropathological features within the brain. In particular, exosomal miRNAs (exomiRs) signatures are involved in AD pathogenesis, showing a different expression between patients and the healthy controls (HCs). However, low yield and high homologous nature impede the accuracy and reproducibility of exosome blood-based AD diagnostics. Here, we developed a programmable curved plasmonic nanoarchitecture-based biosensor to analyze exomiRs in clinical serum samples for accurate AD diagnosis. To allow the detection of exomiRs in serum at attomolar levels, nanospaces (e.g., nanocrevice and nanocavity) were introduced into the nanostructures to dramatically increase the spectral sensitivity by adjusting the bending angle of the plasmonic nanostructure through sodium chloride concentration control. The developed biosensor classifies individuals into AD, mild cognitive impairment (MCI) patients, and HCs through profiling and quantifying exomiRs. Furthermore, integrating analysis expression patterns of multiple exosomal biomarkers improved serum-based diagnostic performance (average accuracy of 98.22%). Therefore, precise, highly sensitive serum-derived exosomal biomarker detection-based plasmonic biosensor has a robust capacity to predict the molecular pathologic of neurodegenerative disease, progression of cognitive decline, MCI/AD conversion, as well as early diagnosis and treatment.

Episodic Memory-Related Imaging Features as Valuable Biomarkers for the Diagnosis of Alzheimer's Disease: A Multicenter Study Based on Machine Learning

BACKGROUND

Individualized and reliable biomarkers are crucial for diagnosing Alzheimer's disease (AD). However, lack of accessibility and neurobiological correlation are the main obstacles to their clinical application. Machine learning algorithms can effectively identify personalized biomarkers based on the prominent symptoms of AD.

METHODS

Episodic memory-related magnetic resonance imaging (MRI) features of 143 patients with amnesic mild cognitive impairment (MCI) were identified using a multivariate relevance vector regression algorithm. The support vector machine classification model was constructed using these MRI features and verified in 2 independent datasets (N = 994). The neurobiological basis was also investigated based on cognitive assessments, neuropathologic biomarkers of cerebrospinal fluid, and positron emission tomography images of amyloid-β plaques.

RESULTS

The combination of gray matter volume and amplitude of low-frequency fluctuation MRI features accurately predicted episodic memory impairment in individual patients with amnesic MCI (r = 0.638) when measured using an episodic memory assessment panel. The MRI features that contributed to episodic memory prediction were primarily distributed across the default mode network and limbic network. The classification model based on these features distinguished patients with AD from normal control subjects with more than 86% accuracy. Furthermore, most identified episodic memory-related regions showed significantly different amyloid-β positron emission tomography measurements among the AD, MCI, and normal control groups. Moreover, the classification outputs significantly correlated with cognitive assessment scores and cerebrospinal fluid pathological biomarkers' levels in the MCI and AD groups.

CONCLUSIONS

Neuroimaging features can reflect individual episodic memory function and serve as potential diagnostic biomarkers of AD.

Blood Neurofilament Light Chain in Different Types of Dementia

AIMS

The study aimed to evaluate diagnostic values of circulating neurofilament light chain (NFL) levels in different types of dementia.

BACKGROUND

Previous studies reported inconsistent change of blood NFL for different types of dementia, including Alzheimer's disease (AD), frontotemporal dementia (FTD), Parkinson's disease dementia (PDD) and Creutzfeldt-Jakob disease (CJD) and Lewy body dementia (LBD).

OBJECTIVE

Meta-analysis was conducted to summarize the results of studies evaluating diagnostic values of circulating NFL levels in different types of dementia to enhance the strength of evidence.

METHODS

Articles evaluating change in blood NFL levels in dementia and published before July 2022 were searched on the following databases (PubMed, Web of Science, EMBASE, Medline and Google Scholar). The computed results were obtained by using STATA 12.0 software.

RESULTS

AD patients showed increased NFL concentrations in serum and plasma, compared to healthy controls (HC) (standard mean difference (SMD) = 1.09, 95% confidence interval (CI): 0.48, 1.70, I2 = 97.4%, p < 0.001). In AD patients, higher NFL concentrations in serum and plasma were associated with reduced cerebrospinal fluid (CSF) Aβ1-42, increased CSF t-tau, increased CSF p-tau, reduced Mini-Mental State Examination (MMSE) and decreased memory. Additionally, mild cognitive impairment (MCI) showed elevated NFL concentrations in serum and plasma, compared to HC (SMD = 0.53, 95% CI: 0.18, 0.87, I2 = 93.8%, p < 0.001). However, in MCI, no significant association was found between NFL concentrations in serum, plasma and memory or visuospatial function. No significant difference was found between preclinical AD and HC (SMD = 0.18, 95% CI: -0.10, 0.47, I2 = 0.0%, p = 0.438). FTD patients showed increased NFL concentrations in serum and plasma, compared to HC (SMD = 1.08, 95% CI: 0.72, 1.43, I2 = 83.3%, p < 0.001). Higher NFL concentrations in serum and plasma were associated with increased CSF NFL in FTD. Additionally, the pooled parameters calculated were as follows: sensitivity, 0.82 (95% CI: 0.72, 0.90); specificity, 0.91 (95% CI: 0.83, 0.96). CJD patients showed increased NFL concentrations in serum and plasma, compared to HC. No significant difference in NFL level in serum and plasma was shown between AD and FTD (SMD = -0.03, 95% CI: -0.77, 0.72, I2 = 83.3%, p = 0.003).

CONCLUSION

In conclusion, the study suggested abnormal blood NFL level in AD and MCI, but not in preclinical AD. FTD and CJD showed abnormal blood NFL levels.

Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks

BACKGROUND AND OBJECTIVE

Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.

METHODS

We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid β (Aβ) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with Aβ, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis.

RESULTS

Age and APOE alone predicted Aβ, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway.

CONCLUSION

Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.

Potential of brain age in identifying early cognitive impairment in subcortical small-vessel disease patients

Background

Reliable and individualized biomarkers are crucial for identifying early cognitive impairment in subcortical small-vessel disease (SSVD) patients. Personalized brain age prediction can effectively reflect cognitive impairment. Thus, the present study aimed to investigate the association of brain age with cognitive function in SSVD patients and assess the potential value of brain age in clinical assessment of SSVD.

Materials and methods

A prediction model for brain age using the relevance vector regression algorithm was developed using 35 healthy controls. Subsequently, the prediction model was tested using 51 SSVD patients [24 subjective cognitive impairment (SCI) patients and 27 mild cognitive impairment (MCI) patients] to identify brain age-related imaging features. A support vector machine (SVM)-based classification model was constructed to differentiate MCI from SCI patients. The neurobiological basis of brain age-related imaging features was also investigated based on cognitive assessments and oxidative stress biomarkers.

Results

The gray matter volume (GMV) imaging features accurately predicted brain age in individual patients with SSVD (R² = 0.535, p < 0.001). The GMV features were primarily distributed across the subcortical system (e.g., thalamus) and dorsal attention network. SSVD patients with age acceleration showed significantly poorer Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores. The classification model based on GMV features could accurately distinguish MCI patients from SCI patients (area under the curve = 0.883). The classification outputs of the classification model exhibited significant associations with MoCA scores, Trail Making Tests A and B scores, Stroop Color and Word Test C scores, information processing speed total scores, and plasma levels of total antioxidant capacity in SSVD patients.

Conclusion

Brain age can be accurately quantified using GMV imaging data and shows potential clinical value for identifying early cognitive impairment in SSVD patients.

Characterizing Plasma Biomarkers of Alzheimer's in a Diverse Community-Based Cohort: A Cross-Sectional Study of the HAB-HD Cohort

Background

Due to their low cost, less invasive nature, and ready availability, plasma biomarkers of Alzheimer's disease have been proposed as one-time screening tools for clinical trials and research. The impact of ethnoracial factors on these biomarkers has received little attention. The current cross-sectional study investigated the levels of Aβ₄₀, Aβ₄₂, total tau (t tau), and neurofilament light (NfL) across diagnoses for each of the three major ethnoracial groups in the United States in a community-based cohort of older adults.

Methods

A total of 1,862 participants (852 Mexican Americans (MAs); 775 non-Hispanic Whites (NHWs), and 235 African Americans (AAs)) drawn from The Health & Aging Brain Study—Health Disparities (HABS-HD) study were included. Diagnoses were assigned using an algorithm (decision tree) verified by consensus review. Plasma samples were assayed using Simoa technology. Levels of each biomarker were compared for the three ethnoracial groups across cognitive diagnoses using ANOVA covarying sex and age.

Results

Significant differences were found across the groups at each level of cognitive impairment. Cognitively unimpaired (CU) AA had significantly lower levels of each of the biomarkers than cognitively unimpaired MA or NHW and NHW had higher levels of Aβ₄₀, and NfL than the other two groups. MA had higher t tau than AA or NHW. Mild cognitive impairment (MCI) group NHW had the highest levels on all the biomarkers and AA had the lowest. NHW and MA have higher levels of Aβ₄₀, Aβ₄₂, and t tau there was no difference between the groups for Aβ₄₂. NHW had significantly higher levels of Aβ₄₀, t tau, and NfL than AA. AA had a higher Aβ₄₂/Aβ₄₀ ratio than either NHW or MA for CU MCI.

Conclusions

The use of plasma biomarkers of cognitive decline is promising given their advantages over other biomarkers such as CSF and imaging but as the current research shows, ethnoracial differences must be considered to enhance accuracy and utility. Developing ethnoracial-specific cut points and establishing normative ranges by assay platform for each of the biomarkers are needed. Longitudinal research to assess changes in biomarkers during a cognitive decline is ongoing.

Potential association of bone mineral density loss with cognitive impairment and central and peripheral amyloid-β changes: a cross-sectional study

BACKGROUND

There is some evidence in the literature that older adults with cognitive impairments have a higher risk for falls and osteoporotic hip fractures. Currently, the associations between bone health and cognitive health have not been extensively studied. Thus, the present cross-sectional study aims to investigate the relationship between markers of bone loss and cognitive performance in older adults with and without osteopenia as well as older adults with cognitive impairments (i.e., Alzheimer's disease [AD]).

METHODS

Sixty-two non-osteopenia participants and one hundred three osteopenia participants as the cohort 1 and 33 cognitively normal non-AD participants and 39 AD participants as the cohort 2 were recruited. To assess cognitive and bone health, hip bone mineral density (BMD) and cognitive performance (via Minimal Mental State Examination [MMSE] and/or Auditory Verbal Learning Test-delayed recall [AVLT-DR]) were assessed. Furthermore, in cohort 1, plasma amyloid-β (Aβ) levels, and in cohort 2, cerebrospinal fluid (CSF) Aβ levels were determined.

RESULTS

We observed that (1) compared with non-osteopenia participants, BMD values (t = - 22.806; 95%CI: - 1.801, - 1.484; p < 0.001), MMSE scores (t = - 5.392; 95%CI: - 3.260, - 1.698; p < 0.001), and AVLT-DR scores (t = - 4.142; 95%CI: - 2.181, - 0.804; p < 0.001), plasma Aβ42 levels (t = - 2.821; 95%CI: - 1.737, - 0.305; p = 0.01), and Aβ42/40 ratio (t = - 2.020; 95%CI: - 0.009, - 0.001; p = 0.04) were significantly lower in osteopenia participants; (2) plasma Aβ42/40 ratio showed a mediate effect for the association between BMD values and the performance of cognitive function in osteopenia participants by mediation analysis, adjusting age, sex, years of education, and body mass index (BMI); (3) BMD values (95%CI: - 1.085, 0.478; p < 0.001) were significantly reduced in AD participants as compared with cognitively normal non-AD participants; (4) in AD participants, the interactive effects of BMD and CSF Aβ42/40 ratio on MMSE scores was found by regression analysis, controlling age, sex, years of education, and BMI; (5) BMD can distinguish AD participants from cognitively normal non-AD participants with AUC of 0.816 and distinguish participants with the cognitive impairment from cognitively normal participants with AUC of 0.794.

CONCLUSION

Our findings suggest a relationship between bone health and cognitive health. Given the correlations between BMD and important markers of cognitive health (e.g., central and peripheral pathological change of Aβ), BMD might serve as a promising and easy-accessible biomarker. However, more research is needed to further substantiate our findings.

Increased Levels of Plasma Alzheimer’s Disease Biomarkers and Their Associations with Brain Structural Changes and Carotid Intima-Media Thickness in Cognitively Normal Obstructive Sleep Apnea Patients

Obstructive sleep apnea (OSA) has been linked to Alzheimer’s disease (AD) and amyloid deposition in the brain. OSA is further linked to the development of cardiovascular and cerebrovascular diseases. In this study, we analyzed the plasma levels of AD neuropathology biomarkers and their relationships with structural changes of the brain and atherosclerosis. Thirty OSA patients with normal cognition and 34 normal controls were enrolled. Cognitive functions were assessed by the Wechsler Adult Intelligence Scale third edition and Cognitive Ability Screening Instrument. Plasma Aβ-40, Aβ-42, and T-tau levels were assayed using immunomagnetic reduction. The carotid intima-media thickness was measured to assess the severity of atherosclerosis. Structural MR images of brain were acquired with voxel-based morphometric analysis of T1 structural images. The OSA patients exhibited significantly elevated plasma levels of Aβ-42 and T-tau, as well as increased gray matter volume in the right precuneus. Plasma T-tau level is associated with carotid intima-media thickness and gray matter volume of the precuneus. These findings may indicate early changes that precede clinically apparent cognitive impairment. The measurement of these biomarkers may aid in the early detection of OSA-associated morbidity and possible treatment planning for the prevention of irreversible neuronal damage and cognitive dysfunction.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ_1–42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Novel Ultrasensitive Detection Technologies for the Identification of Early and Minimally Invasive Alzheimer's Disease Blood Biomarkers

BACKGROUND

Single molecule array (SIMOA) and other ultrasensitive detection technologies have allowed the determination of blood-based biomarkers of Alzheimer's disease (AD) for diagnosis and monitoring, thereby opening up a promising field of research.

OBJECTIVE

To review the published bibliography on plasma biomarkers in AD using new ultrasensitive techniques.

METHODS

A systematic review of the PubMed database was carried out to identify reports on the use of blood-based ultrasensitive technology to identify biomarkers for AD.

RESULTS

Based on this search, 86 works were included and classified according to the biomarker determined. First, plasma amyloid-β showed satisfactory accuracy as an AD biomarker in patients with a high risk of developing dementia. Second, plasma t-Tau displayed good sensitivity in detecting different neurodegenerative diseases. Third, plasma p-Tau was highly specific for AD. Fourth, plasma NfL was highly sensitive for distinguishing between patients with neurodegenerative diseases and healthy controls. In general, the simultaneous determination of several biomarkers facilitated greater accuracy in diagnosing AD (Aβ42/Aβ40, p-Tau181/217).

CONCLUSION

The recent development of ultrasensitive technology allows the determination of blood-based biomarkers with high sensitivity, thus facilitating the early detection of AD through the analysis of easily obtained biological samples. In short, as a result of this knowledge, pre-symptomatic and early AD diagnosis may be possible, and the recruitment process for future clinical trials could be more precise. However, further studies are necessary to standardize levels of blood-based biomarkers in the general population and thus achieve reproducible results among different laboratories.

Tau proteins in blood as biomarkers of Alzheimer's disease and other proteinopathies

Alzheimer's disease (AD), the most common age-dependent neurodegenerative disorder, is characterized neuropathologically by extracellular Aβ plaques and intracellular tau neurofibrillary tangles. While in AD tau pathology probably follows early alterations in Aβ metabolism, it develops independently in the so-called primary tauopathies, the main form being frontotemporal lobar degeneration with tau pathology. Tau pathology in AD brain is reflected in the cerebrospinal fluid (CSF) by elevated levels of the two AD tau biomarkers total and phosphorylated tau, which are now used for routine diagnostic purposes. On the contrary, no established neurochemical biomarkers exist for tau pathology in primary tauopathies. Thanks to recent technological advances, total and phosphorylated tau can now be quantified also on peripheral blood, and accumulating evidence shows that measurement of plasma phosphorylated tau species (P-tau181, P-tau217, and P-tau231) has high performances in discriminating AD patients from cognitively unimpaired subjects but also from patients with other dementias. Moreover, plasma P-tau levels are associated with tracer uptake on tau- and amyloid-PET as well as with brain atrophy, cognitive measures and longitudinal changes of these parameters. These features, together with the low invasiveness, scalability, and ease of longitudinal sampling, which differentiate plasma P-tau species from their CSF counterparts, make these proteins promising peripheral biomarkers for AD in both research and clinical setting. This review discusses the recent developments in the field of plasma tau proteins as diagnostic, pathophysiological and prognostic biomarkers of Alzheimer's disease; additional findings from the fields of genetic forms of AD and of non-AD proteinopathies are also summarized.

Biosensor approaches on the diagnosis of neurodegenerative diseases: Sensing the past to the future

Early diagnosis of neurodegeneration-oriented diseases that develop with the aging world is essential for improving the patient's living conditions as well as the treatment of the disease. Alzheimer's and Parkinson's diseases are prominent examples of neurodegeneration characterized by dementia leading to the death of nerve cells. The clinical diagnosis of these diseases only after the symptoms appear, delays the treatment process. Detection of biomarkers, which are distinctive molecules in biological fluids, involved in neurodegeneration processes, has the potential to allow early diagnosis of neurodegenerative diseases. Studies on biosensors, whose main responsibility is to detect the target analyte with high specificity, has gained momentum in recent years with the aim of high detection of potential biomarkers of neurodegeneration process. This study aims to provide an overview of neuro-biosensors developed on the basis of biomarkers identified in biological fluids for the diagnosis of neurodegenerative diseases such as Alzheimer's disease (AD), and Parkinson's disease (PD), and to provide an overview of the urgent needs in this field, emphasizing the importance of early diagnosis in the general lines of the neurodegeneration pathway. In this review, biosensor systems developed for the detection of biomarkers of neurodegenerative diseases, especially in the last 5 years, are discussed.

Characterizing plasma NfL in a community-dwelling multi-ethnic cohort: Results from the HABLE study

INTRODUCTION

No large-scale characterizations of neurofilament light chain (NfL) have been conducted in diverse populations.

METHODS

Baseline data were analyzed among n = 890 Mexican Americans and n = 813 non-Hispanic Whites from the multi-ethnic Health & Aging Brain among Latino Elders (HABLE) study. Plasma NfL was measured on the Simoa platform.

RESULTS

In unadjusted models, NfL was significantly associated with age (P < .001), hypertension (P  < .001), dyslipidemia (P = .02), and diabetes (P  < .001). Covarying for age and sex, NfL was associated with neurodegeneration (P  < .001) and global amyloid burden levels (P = .02) in a subset with available data. NfL levels were significantly associated with diagnostic groups (Normal Cognition [NC], mild cognitive impairment [MCI], Dementia; P  < .001); however, there was no cut-score that yielded acceptable diagnostic accuracy. NfL levels produced a sensitivity of 0.60 and specificity of 0.78 with negative predictive value of 89% for detecting amyloid positivity.

DISCUSSION

Plasma NfL levels are significantly impacted by age and medical co-morbidities that are common among older adults, which complicate its utility as a diagnostic biomarker.

Risk of neurodegeneration among residents of electronic waste recycling areas

The abnormal disposal process of electronic waste (e-waste) always emits a variety of toxic substances that enter the human body through various environmental media and can have many adverse health effects. Metals are thought to be inextricably linked to neurodegeneration. In the present study, we tried to explore the neurodegenerative status of subjects exposed to e-waste and the association between metal intake and neurodegeneration. We recruited the residents near the e-waste recycling area (the exposed group) and the residents without any e-waste contact history (the reference group) for a comparative study with detection and analysis of metals, biomarkers associated with neurodegeneration or oxidative stress (OS). The results showed that the metals between the reference and exposed group were significantly different. The concentrations of Brain-derived neurotrophic factor (BDNF) and β-amyloid protein 42 (Aβ42) in the exposed groups were significantly lower, while the levels of Euchromatic Histone lysine Methyltransferase 1 (EHMT1), Bromodomain Adjacent to Zinc finger domain 2B (BAZ2B) and Malondialdehyde (MDA) were significantly higher than in the reference groups. Although the ratio of Aβ42/Aβ40 had no statistical significance in the two groups, the medians of the ratio in the exposed group was lower than in the reference group. The linear regression and mediating effect analysis showed that MDA (OS) might mediate the effects of metals on EHMT1(pAg-MDA <0.001, pMDA-EHMT1 <0.05, pAg-EHMT1 <0.001). It could be inferred from the results of the present investigation that e-waste exposure had a high risk of neurodegeneration, especially Sliver (Ag) and Nickel (Ni).

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

BACKGROUND

Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer's disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses.

OBJECTIVE

To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors/biomarkers.

METHODS

We used biomarker/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class.

RESULTS

For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma Aβ1-42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and Aβ1-40, higher depressive symptomology, and lower body mass index.

CONCLUSION

Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers/risk factors discriminating the higher and lower LHC/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers/risk factors from multiple modalities.

Sleep disturbance-related neuroimaging features as potential biomarkers for the diagnosis of major depressive disorder: A multicenter study based on machine learning

BACKGROUND

Objective biomarkers are crucial for overcoming the clinical dilemma in major depressive disorder (MDD), and the individualized diagnosis is essential to facilitate the precise medicine for MDD.

METHODS

Sleep disturbance-related magnetic resonance imaging (MRI) features was identified in the internal dataset (92 MDD patients) using the relevance vector regression algorithm, which was further verified in 460 MDD patients of an independent, multicenter dataset. Subsequently, using these MRI features, the eXtreme Gradient Boosting classification model was constructed in the current multicenter dataset (460 MDD patients and 470 normal controls). Meanwhile, the association between classification outputs and the severity of depressive symptoms was also investigated.

RESULTS

In MDD patients, the combination of gray matter density and fractional amplitude of low-frequency fluctuation can accurately predict individual sleep disturbance score that was calculated by the sum of item 4 score, item 5 score, and item 6 score of the 17-Item Hamilton Rating Scale for Depression (HAMD-17) (R² = 0.158 in the internal dataset; R² = 0.110 in multicenter dataset). Furthermore, the classification model based on these MRI features distinguished MDD patients from normal controls with 86.3% accuracy (area under the curve = 0.937). Importantly, the classification outputs significantly correlated with HAMD-17 scores in MDD patients.

LIMITATION

Lacking some specialized tools to assess the personal sleep quality, e.g. Pittsburgh Sleep Quality Index.

CONCLUSION

Neuroimaging features can reflect accurately individual sleep disturbance manifestation and serve as potential diagnostic biomarkers of MDD.

Performance of Plasma Amyloid β, Total Tau, and Neurofilament Light Chain in the Identification of Probable Alzheimer's Disease in South China

Background: Alzheimer's disease (AD) is the most common type of dementia and has no effective treatment to date. It is essential to develop a minimally invasive blood-based biomarker as a tool for screening the general population, but the efficacy remains controversial. This cross-sectional study aimed to evaluate the ability of plasma biomarkers, including amyloid β (Aβ), total tau (t-tau), and neurofilament light chain (NfL), to detect probable AD in the South Chinese population.

Methods: A total of 277 patients with a clinical diagnosis of probable AD and 153 healthy controls with normal cognitive function (CN) were enrolled in this study. The levels of plasma Aβ42, Aβ40, t-tau, and NfL were detected using ultra-sensitive immune-based assays (SIMOA). Lumbar puncture was conducted in 89 patients with AD to detect Aβ42, Aβ40, t-tau, and phosphorylated (p)-tau levels in the cerebrospinal fluid (CSF) and to evaluate the consistency between plasma and CSF biomarkers through correlation analysis. Finally, the diagnostic value of plasma biomarkers was further assessed by constructing a receiver operating characteristic (ROC) curve.

Results: After adjusting for age, sex, and the apolipoprotein E (APOE) alleles, compared to the CN group, the plasma t-tau, and NfL were significantly increased in the AD group (p < 0.01, Bonferroni correction). Correlation analysis showed that only the plasma t-tau level was positively correlated with the CSF t-tau levels (r = 0.319, p = 0.003). The diagnostic model combining plasma t-tau and NfL levels, and age, sex, and APOE alleles, showed the best performance for the identification of probable AD [area under the curve (AUC) = 0.89, sensitivity = 82.31%, specificity = 83.66%].

Conclusion: Blood biomarkers can effectively distinguish patients with probable AD from controls and may be a non-invasive and efficient method for AD pre-screening.

Ultrasensitive detection of blood biomarkers of Alzheimer's and Parkinson's diseases: a systematic review

Purpose: Neurodegenerative disorders are a global health burden with costly and invasive diagnoses relying on brain imaging technology or CSF-based biomarkers. Therefore, considerable efforts to identify blood-biomarkers for Alzheimer's (AD) and Parkinson's diseases (PD) are ongoing. Objectives: This review evaluates the blood biomarkers for AD and PD for their diagnostic value. Methods: This study systematically reviewed articles published between July 1984 and February 2021. Among 1266 papers, we selected 42 studies for a systematic review and 23 studies for meta-analysis. Results & conclusion: Our analysis highlights P-tau181, T-tau and Nfl as promising blood biomarkers for AD diagnosis. Nfl levels were consistently raised in 16 AD and three PD cohorts. P-tau181 and T-tau were also significantly increased in 12 and eight AD cohorts, respectively.

Electroencephalography as a Non-Invasive Biomarker of Alzheimer's Disease: A Forgotten Candidate to Substitute CSF Molecules?

Biomarkers for disease diagnosis and prognosis are crucial in clinical practice. They should be objective and quantifiable and respond to specific therapeutic interventions. Optimal biomarkers should reflect the underlying process (pathological or not), be reproducible, widely available, and allow measurements repeatedly over time. Ideally, biomarkers should also be non-invasive and cost-effective. This review aims to focus on the usefulness and limitations of electroencephalography (EEG) in the search for Alzheimer's disease (AD) biomarkers. The main aim of this article is to review the evolution of the most used biomarkers in AD and the need for new peripheral and, ideally, non-invasive biomarkers. The characteristics of the EEG as a possible source for biomarkers will be revised, highlighting its advantages compared to the molecular markers available so far.

Identification of the Neural Circuit Underlying Episodic Memory Deficit in Amnestic Mild Cognitive Impairment via Machine Learning on Gray Matter Volume

Based on whole-brain gray matter volume (GMV), we used relevance vector regression to predict the Rey's Auditory Verbal Learning Test Delayed Recall (AVLT-DR) scores of individual amnestic mild cognitive impairment (aMCI) patient. The whole-brain GMV pattern could significantly predict the AVLT-DR scores (r = 0.54, p < 0.001). The most important GMV features mainly involved default-mode (e.g., posterior cingulate gyrus, angular gyrus, and middle temporal gyrus) and limbic systems (e.g., hippocampus and parahippocampal gyrus). Therefore, our results provide evidence supporting the idea that the episodic memory deficit in aMCI patients is associated with disruption of the default-mode and limbic systems.

Longitudinal Association of Total Tau Concentrations and Physical Activity With Cognitive Decline in a Population Sample

IMPORTANCE

Tau is a brain protein located in neurons and develops abnormally in individuals with Alzheimer disease. New technology is convenient for measuring blood total tau concentrations and provides a unique and increased opportunity for early intervention to slow cognitive decline.

OBJECTIVE

To evaluate the association of physical activity and total tau concentrations with cognitive decline at baseline and over time.

DESIGN, SETTING, AND PARTICIPANTS

The Chicago Health and Aging Project is a population-based cohort study conducted in 4 Chicago communities. Data collection occurred in 3-year cycles between 1993 and 2012. Participants completed in-home interviews. Clinical evaluations, which included blood samples, were performed with a stratified random sample of 1159 participants. Statistical analyses were conducted from October 30, 2020, to May 25, 2021.

EXPOSURES

Physical activity and total serum tau concentrations. Data on physical activity were obtained through self-report items, and a sum of minutes per week was calculated. Little physical activity was defined as no participation in a minimum of 4 of the items on the physical activity measure. Medium activity was defined as participating in less than 150 minutes of physical activity per week, and high activity was defined as participating in 150 minutes or more of physical activity per week.

MAIN OUTCOMES AND MEASURES

The main outcome for this study is global cognitive function, measured through a battery of cognitive tests. The study hypothesis was developed after data were collected.

RESULTS

Of the 1159 participants in the study, 728 were women (63%), and 696 were African American (60%); the mean (SD) age was 77.4 (6.0) years, and the mean (SD) educational level was 12.6 (3.5) years. Participants with high total tau concentrations with medium physical activity had a 58% slower rate of cognitive decline (estimate, -0.028 standard deviation unit [SDU] per year [95% CI, -0.057 to 0.002 SDU per year]; difference, 0.038 SDU per year [95% CI, 0.011-0.065 SDU per year]), and those with high physical activity had a 41% slower rate of cognitive decline (estimate, -0.038 SDU per year [95% CI, -0.068 to -0.009 SDU per year]; difference, 0.027 SDU per year [95% CI, -0.002 to 0.056 SDU per year]), compared with those with little physical activity. Among participants with low total tau concentrations, medium physical activity was associated with a 2% slower rate of cognitive decline (estimate, -0.050 SDU per year [95% CI, -0.069 to -0.031 SDU per year]; difference, 0.001 SDU per year [95% CI, -0.019 to 0.021 SDU per year]), and high physical activity was associated with a 27% slower rate of cognitive decline (estimate, -0.037 SDU per year [95% CI, -0.055 to -0.019 SDU per year]; difference, 0.014 SDU per year [95% CI, -0.007 to 0.034 SDU per year]), compared with little physical activity. Individual tests of cognitive function showed similar results.

CONCLUSIONS AND RELEVANCE

This study suggests that, among participants with both high and low total tau concentrations, physical activity was associated with slower cognitive decline. Results support the potential utility of blood biomarkers in measuring the benefits associated with health behaviors and may contribute to specifying target populations or informing interventions for trials that focus on improving physical activity behavior. Future work should examine the association of total tau concentrations with other health behaviors and physical activity types.

Plasma biomarker profiles and the correlation with cognitive function across the clinical spectrum of Alzheimer's disease

BACKGROUND

Plasma biomarkers showed a promising value in the disease diagnosis and management of Alzheimer's disease (AD). However, profiles of the biomarkers and the associations with cognition across a spectrum of cognitive stages have seldom been reported.

METHODS

We recruited 320 individuals with cognitive impairment and 131 cognitively normal participants from a memory clinic and a community cohort. Participants were classified into 6 groups based on their Clinical Dementia Rating (CDR) scores and clinical diagnosis, including AD, amnestic mild cognitive impairment (aMCI), and normal cognition (NC). A battery of neuropsychological tests was used to assess the global and domain-specific cognition. Plasma Aβ1-40, Aβ1-42, Aβ1-42/Aβ1-40, total tau (t-tau), neurofilament protein light chain (NfL), and phosphorylated tau at threonine 181 (p-tau181) were quantified using the single-molecule array (Simoa) platform.

RESULTS

All the plasma markers (Aβ1-40, Aβ1-42, Aβ1-42/Aβ1-40, t-tau, NfL, p-tau181) showed certain discrepancies among NC, aMCI, and AD groups. The p-tau181 level showed a continuous escalating trend as the CDR scores increased from 0 (NC group) to 3 (severe AD). Compared with other biomarkers, p-tau181 had correlations with broader cognitive domains, covering global cognition (r = -0.536, P < 0.0001), memory (r = -0.481, P < 0.0001), attention (r = -0.437, P < 0.0001), visuospatial function (r = -0.385, P < 0.0001), and language (r = -0.177, P = 0.0003). Among participants with CDR ≥ 1, higher p-tau181 was correlated with worse global cognition (r = -0.301, P < 0.001).

CONCLUSIONS

Plasma p-tau181 had correlations with broader cognitive domains, suggesting its potential as a promising clinical-relevant blood-based biomarker.

Serum Levels of Clusterin, PKR, and RAGE Correlate with Amyloid Burden in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia and biomarkers are essential to help in the diagnosis of this disease. Image techniques and cerebrospinal fluid (CSF) biomarkers are limited in their use because they are expensive or invasive. Thus, the search for blood-borne biomarkers is becoming central to the medical community.

OBJECTIVE

The main objective of this study is the evaluation of three serum proteins as potential biomarkers in AD patients.

METHODS

We recruited 27 healthy controls, 19 mild cognitive impairment patients, and 17 AD patients. Using the recent A/T/N classification we split our population into two groups (AD and control). We used ELISA kits to determine Aβ42, tau, and p-tau in CSF and clusterin, PKR, and RAGE in serum.

RESULTS

The levels of serum clusterin, PKR, and RAGE were statistically different in the AD group compared to controls. These proteins showed a statistically significant correlation with CSF Aβ42. So, they were selected to generate an AD detection model showing an AUC-ROC of 0.971 (CI 95%, 0.931-0.998).

CONCLUSION

The developed model based on serum biomarkers and other co-variates could reflect the AD core pathology. So far, not one single blood-biomarker has been described, with effectiveness offering high sensitivity and specificity. We propose that the complexity of AD pathology could be reflected in a set of biomarkers also including clinical features of the patients.

Ultrasensitive assays for detection of plasma tau and phosphorylated tau 181 in Alzheimer's disease: a systematic review and meta-analysis

A lack of convenient and reliable biomarkers for diagnosis and prognosis is a common challenge for neurodegenerative diseases such as Alzheimer's disease (AD). Recent advancement in ultrasensitive protein assays has allowed the quantification of tau and phosphorylated tau proteins in peripheral plasma. Here we identified 66 eligible studies reporting quantification of plasma tau and phosphorylated tau 181 (ptau181) using four ultrasensitive methods. Meta-analysis of these studies confirmed that the AD patients had significantly higher plasma tau and ptau181 levels compared with controls, and that the plasma tau and ptau181 could predict AD with high-accuracy area under curve of the Receiver Operating Characteristic. Therefore, plasma tau and plasma ptau181 can be considered as biomarkers for AD diagnosis.

Relationship of Neurofilament Light (NfL) and Cognitive Performance in a Sample of Mexican Americans with Normal Cognition, Mild Cognitive Impairment and Dementia

INTRODUCTION

This study characterized the relationship between plasma NfL and cognition in a community-based sample of older Mexican Americans.

METHODS

544 participants completed a battery of neuropsychological tests and were diagnosed using clinical criteria. NfL was assayed using Simoa. NfL levels across groups and tests were analyzed.

RESULTS

Difference in NfL was found between normal and impaired groups and was related to global cognition, processing speed, executive functions and a list of learning tasks with a significant negative effect for all diagnostic groups. NfL had a negative impact on processing speed, attention, executive functions and delayed and recognition memory for both normal and MCI groups.

CONCLUSION

The research supports plasma NfL as a marker of cognitive impairment related to neurodegenerative processes in Mexican Americans and may be a marker of early changes in cognition in those with normal cognition and at risk for developing MCI.

Assessment of Plasma Amyloid-β42/40 and Cognitive Decline Among Community-Dwelling Older Adults

IMPORTANCE

Plasma measurement of amyloid-β (Aβ) peptides has been associated with cognitive function, but evidence of its ability to identify cognitive decline is still scarce.

OBJECTIVE

To investigate the associations between plasma Aβ42/40 and cognitive decline over time among community-dwelling older adults with subjective memory concerns.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter cohort study used data from volunteers in the 5-year study Multidomain Alzheimer Preventive Trial (MAPT). Participants were aged 70 years or older and observed for a median (interquartile range) of 3.9 (2.0-4.0) years. Recruitment of participants started in May 2008 and ended in February 2011. Follow-up ended in April 2016. Data analysis was conducted from April to October 2020.

EXPOSURE

Plasma Aβ42 and Aβ40 were measured at 12 months for 448 participants (92.8%) and at 24 months for the rest. The moment of Aβ assessment was defined as the baseline for this study.

MAIN OUTCOMES AND MEASURES

Cognitive function was assessed at 12, 24, 36, 48, and 60 months by a composite cognitive score based on 4 tests; Mini Mental State Examination (MMSE); Clinical Dementia Rating, sum of boxes; and Alzheimer Disease Cooperative Study-Activities of Daily Living. Mixed-effect linear regressions were performed.

RESULTS

A total of 483 participants (median [IQR] age, 76.0 [73.0-80.0]; 286 [59.2%] women) were analyzed. Of them, 161 (33.3%) were classified as low plasma Aβ42/40 (≤0.107). After adjusting for age, sex, education, body mass index, Geriatric Depression Scale score, apolipoprotein E ε4 genotype, and MAPT intervention groups, low plasma Aβ42/40 was associated with more pronounced decline in composite cognitive score (adjusted between-group mean difference: -0.20, 95% CI, -0.34 to -0.07; P = .004) and decline in MMSE score (adjusted between-group mean difference: -0.59; 95% CI, -1.07 to -0.11; P = .02) during the follow-up period compared with the group with an Aβ42/40 ratio greater than 0.107.

CONCLUSIONS AND RELEVANCE

In this study, low plasma Aβ42/40 was associated with more pronounced decline in cognitive function (measured by multiple outcomes) over time. Findings suggest that plasma Aβ42/40 may be used to identify people at risk of cognitive decline, being an alternative to more complex and expensive measures, such as positron emission tomography imaging or cerebrospinal fluid measurement.

Plasma N-terminal tau fragment levels predict future cognitive decline and neurodegeneration in healthy elderly individuals

The availability of blood-based assays detecting Alzheimer's disease (AD) pathology should greatly accelerate AD therapeutic development and improve clinical care. This is especially true for markers that capture the risk of decline in pre-symptomatic stages of AD, as this would allow one to focus interventions on participants maximally at risk and at a stage prior to widespread synapse loss and neurodegeneration. Here we quantify plasma concentrations of an N-terminal fragment of tau (NT1) in a large, well-characterized cohort of clinically normal elderly who were followed longitudinally. Plasma NT1 levels at study entry (when all participants were unimpaired) were highly predictive of future cognitive decline, pathological tau accumulation, neurodegeneration, and transition to a diagnosis of MCI/AD. These predictive effects were particularly strong in participants with even modestly elevated brain β-amyloid burden at study entry, suggesting plasma NT1 levels capture very early cognitive, pathologic and neurodegenerative changes along the AD trajectory.

Diagnostic Utility of Selected Serum Dementia Biomarkers: Amyloid β-40, Amyloid β-42, Tau Protein, and YKL-40: A Review

Introduction: Dementia is a group of disorders that causes dysfunctions in human cognitive and operating functions. Currently, it is not possible to conduct a fast, low-invasive dementia diagnostic process with the use of peripheral blood biomarkers, however, there is a great deal of research in progress covering this subject. Research on dementia biomarkers in serum validates anticipated health and economic benefits from early screening tests. Biomarkers are also essential for improving the process of developing new drugs. Methods: The result analysis, of current studies on selected biomarker concentrations (Aβ40, Aβ42, t-tau, and YKL-40) and their combination in the serum of patients with dementia and mild cognitive disorders, involved a search for papers available in Medline, PubMed, and Web of Science databases published from 2000 to 2020. Results: The results of conducted cross-sectional studies comparing Aβ40, Aβ42, and Aβ42/Aβ40 among people with cognitive disorders and a control group are incoherent. Most of the analyzed papers showed an increase in t-tau concentration in diagnosed Alzheimer’s disease (AD) patients’ serum, whereas results of mild cognitive impairment (MCI) groups did not differ from the control groups. In several papers on the concentration of YKL-40 and t-tau/Aβ42 ratio, the results were promising. To date, several studies have only covered the field of biomarker concentrations in dementia disorders other than AD. Conclusions: Insufficient amyloid marker test repeatability may result either from imperfection of the used laboratorial techniques or inadequate selection of control groups with their comorbidities. On the basis of current knowledge, t-tau, t-tau/Aβ42, and YKL-40 seem to be promising candidates as biomarkers of cognitive disorders in serum. YKL-40 seems to be a more useful biomarker in early MCI diagnostics, whereas t-tau can be used as a marker of progress of prodromal states in mild AD. Due to the insignificant number of studies conducted to date among patients with dementia disorders other than AD, it is not possible to make a sound assessment of their usefulness in dementia differential diagnostics.

Combination of plasma amyloid beta(1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology

BACKGROUND

Blood-based biomarkers for Alzheimer's disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta_(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity.

METHODS

We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET-), mild cognitive impairment (26 PET+, 24 PET-), or AD-dementia (132 PET+). Plasma Abeta_(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald's backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman's correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA).

RESULTS

Abeta_(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta_(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83-93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = - 0.40 to - 0.26; NfL: range sβ = - 0.35 to - 0.18; all: p < 0.002), whereas Abeta_(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 - 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman's rho> 0.33, p < 0.001). Abeta_(1-42/1-40) showed a moderate negative correlation with MTA (Spearman's rho = - 0.24, p = 0.001).

DISCUSSION AND CONCLUSIONS

Combination of plasma Abeta_(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.

Prevalence of mild cognitive impairment in type 2 diabetes mellitus is associated with serum galectin-3 level

AIMS/INTRODUCTION

Galectin-3 (Gal3) contributes to insulin resistance, inflammation and obesity, the three risk factors for mild cognitive impairment (MCI) in type 2 diabetes mellitus patients.

MATERIALS AND METHODS

A total of 134 hospitalized type 2 diabetes mellitus patients were assessed by the Montreal Cognitive Assessment method, and divided into 65 MCI and 69 controls. Levels of variables, Gal3 and Aβ42, were investigated in relation with cognitive function in both type 2 diabetes mellitus patients with MCI and high-fat diet/streptozotocin induced type 2 diabetes mellitus rats.

RESULTS

Significantly higher levels of serum Gal3 and lower levels of plasma Aβ42 (all P < 0.05) were found in the MCI type 2 diabetes mellitus group as compared with the non-MCI type 2 diabetes mellitus control. Partial correlation analysis showed that Gal3 is negatively correlated with both MMSE score (r = -0.51, P < 0.01) and Montreal Cognitive Assessment score (r = -0.47, P < 0.001) after adjustment for glycated hemoglobin, homoeostasis model assessment of insulin resistance and Aβ42 in all type 2 diabetes mellitus patients, with a stronger effect seen in the MCI type 2 diabetes mellitus group after further analysis with MCI strata. A simple logistic regression model showed that Gal3 and Aβ42 are significantly associated with MCI type 2 diabetes mellitus patients after adjustment with the covariates sex, age, body mass index, glycated hemoglobin, homoeostasis model assessment of insulin resistance and antidiabetic drugs. Serum and brain Gal3 levels were significantly increased in high-fat diet/streptozotocin diabetic rats, which correlate to the impairment of learning and memory ability. Gal3 inhibitor modified citrus pectin decreased serum and brain Gal3 levels in diabetic rats, accompanied by the amelioration of learning and memory impairment.

CONCLUSIONS

Gal3 might be associated with cognitive impairment in type 2 diabetes mellitus, and serum Gal3 level might be a new risk factor of MCI in type 2 diabetes mellitus patients.

Predicting conversion to Alzheimer's disease among individual high-risk patients using the Characterizing AD Risk Events index model

AIMS

Both amnestic mild cognitive impairment (aMCI) and remitted late-onset depression (rLOD) confer a high risk of developing Alzheimer's disease (AD). This study aims to determine whether the Characterizing AD Risk Events (CARE) index model can effectively predict conversion in individuals at high risk for AD development either in an independent aMCI population or in an rLOD population.

METHODS

The CARE index model was constructed based on the event-based probabilistic framework fusion of AD biomarkers to differentiate individuals progressing to AD from cognitively stable individuals in the aMCI population (27 stable subjects, 6 progressive subjects) and rLOD population (29 stable subjects, 10 progressive subjects) during the follow-up period.

RESULTS

AD diagnoses were predicted in the aMCI population with a balanced accuracy of 80.6%, a sensitivity of 83.3%, and a specificity of 77.8%. They were also predicted in the rLOD population with a balanced accuracy of 74.5%, a sensitivity of 80.0%, and a specificity of 69.0%. In addition, the CARE index scores were observed to be negatively correlated with the composite Z scores for episodic memory (R2  = .17, P < .001) at baseline in the combined high-risk population (N = 72).

CONCLUSIONS

The CARE index model can be used for the prediction of conversion to AD in both aMCI and rLOD populations effectively. Additionally, it can be used to monitor the disease severity of patients.

Plasma Neurofilament Light Chain May Be a Biomarker for the Inverse Association Between Cancers and Neurodegenerative Diseases

An inverse association may exist between cancers and neurodegenerative diseases, although convenient biomarkers for verifying this inverse association are lacking. Plasma neurofilament light chain (NfL) is a novel biomarker for neurodegenerative diseases, such as Alzheimer's disease (AD), but it has not been measured in patients with cancers, such as gastric cancer (GC). We aimed to explore whether plasma NfL could be a biomarker for GC and AD and whether an inverse association of NfL exists between GC and AD. In this study, plasma NfL levels of 60 normal controls (NC), 91 GC subjects, and 74 AD subjects were measured by a highly sensitive single-molecule array assay. We found that GC subjects expressed lower plasma NfL levels but AD subjects expressed higher plasma NfL levels than NCs. After controlling for confounding factors, plasma NfL levels in the GC group were associated with serum tumor marker levels, and plasma NfL levels in the AD group were associated with cognitive performance and cerebrospinal fluid (CSF) pathological marker levels. Across the entire cohort, plasma NfL levels were associated with cognitive performance, CSF pathological marker levels and serum tumor marker levels. These results suggest thatplasma NfL may be a potential biomarker for GC and AD and may be convenient for evaluating the inverse association between cancers and neurodegenerative diseases.

Plasma amyloid is associated with the rate of cognitive decline in cognitively normal elderly: the SCIENCe project

Plasma biomarkers are promising prognostic tools in individuals with subjective cognitive decline (SCD). We aimed to investigate the relationships of baseline plasma amyloid beta (Aβ)42/Aβ40 and total Tau (tTau) with rate of cognitive decline, in comparison to relationships of baseline cerebrospinal fluid (CSF) Aβ42, tTau, and phosphorylated tau181 (pTau181) with rate of cognitive decline. We included 241 subjects with SCD (age = 61 ± 9, 40% female, Mini-Mental State Examination = 28 ± 2) with follow-up (average: 2 ± 2 years, median visits: 3 [range: 1-11]) for re-evaluation of neuropsychological test performance (attention, memory, language, and executive functioning domains). Using age, gender and education-adjusted linear mixed models, we found that lower plasma Aβ42/Aβ40 was associated with steeper rate of decline on tests for attention, memory, and executive functioning, but not language. Lower CSF Aβ42 was associated with steeper decline on tests covering all domains. Associations for plasma amyloid and cognitive decline mirror those of CSF amyloid. Plasma tTau was not associated with rate of cognitive decline, whereas CSF tTau and pTau181 were on multiple tests covering all domains.