A Decade of Blood Biomarkers for Alzheimer's Disease Research: An Evolving Field, Improving Study Designs, and the Challenge of Replication

Psychoneuroimmunoendocrinological and neuroanatomical basis of suicidal behavior: potential therapeutic strategies with a focus on transcranial magnetic stimulation (TMS)

Suicidal behavior is a complex phenomenon influenced by psychological, environmental, and biological factors. It affects a significant portion of the global population, with more than 720,000 deaths annually and millions of individuals experiencing suicidal ideation. Among those who attempt suicide, only a fraction progresses to a fatal outcome, emphasizing the importance of understanding individual vulnerabilities. This review explores the neuroanatomical basis of suicidal behavior, focusing on key brain regions and potential pathways for neuromodulation therapies, particularly Transcranial Magnetic Stimulation (TMS). The dorsolateral prefrontal cortex (DLPFC) plays a central role in cognitive control and emotional regulation, with extensive connections to the anterior cingulate cortex, amygdala, orbitofrontal cortex, hippocampus, and thalamus. Dysfunctions in these circuits contribute to heightened impulsivity, impaired decision-making, and emotional dysregulation in individuals with suicidal behavior. Structural and functional abnormalities in the DLPFC, coupled with altered neurotransmitter systems and inflammatory markers, have been consistently linked to suicidality. TMS, targeting the left DLPFC, has shown promise in reducing suicidal ideation by modulating frontostriatal connectivity, enhancing neuroplasticity, and improving cortical excitability. High-frequency TMS and accelerated theta-burst stimulation protocols demonstrate rapid therapeutic effects, though further research is needed to establish standardized treatment guidelines. Understanding the anatomical circuits implicated in suicidal behavior provides valuable insights for early risk assessment and the development of targeted neuromodulation interventions aimed at reducing the burden of suicide across diverse psychiatric populations.

The polygenic hazard score mediates the association between plasma neurofilament light chain and brain morphometry in dementia spectrum

INTRODUCTION

Blood-based biomarkers such as plasma neurofilament light chain (pNfL) are crucial biomarkers for Alzheimer's disease (AD). Additionally, neuroimaging techniques such as tensor-based morphometry (TBM), which identify structural changes in the brain, can provide valuable insights into AD pathophysiology. However, the role of genetics in linking the blood based biomarkers and imaging findings has not been well understood. Therefore, we aimed to investigate whether the polygenic hazard score (PHS), affects the association between neurofibrillary tangles and neuritis plaques and brain imaging findings.

METHODS

Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we enrolled all participants for whom a complete dataset of pNfL, PHS, and TBM was available. Using Python, we analyzed the associations between pNfL levels and the TBM data of 567 participants incluidng 152 cognitively normal individuals, 309 participants with mild cognitive impairment (MCI), and 106 patients with AD. We used a mediation analysis to identify the effect of PHS in how pNfL is associated with TBM measures.

RESULTS

We found a negative correlation between the accelerated TBM measure and NfL levels in both the MCI and AD groups. The pNfL concentration predicted both accelerated statistical and anatomical TMB measures in patients with MCI. Furthermore, PHS mediatedthe association between statistical TBM measures and NfL levels in AD patients, to the extent that the significant association between NfL and TBM measures disappeared after accounting for PHS.

CONCLUSION

We showed that although pNfL can predict the cognitiee decline and imaging findings in AD, this effect is mediated by the PHS. Therefore, PHS should be considered when investigating AD biomarkers and their corresponding imaging findings.

Blood-Based Biomarkers in Frontotemporal Dementia: A Narrative Review

This narrative review explores the current landscape of blood biomarkers in Frontotemporal dementia (FTD). Neurofilament light chain (NfL) may be useful in the differentiation of behavioral variant FTD from primary psychiatric disorders (PPDs) or dementia with Lewy bodies (DLB). In prodromal FTD and presymptomatic mutation carriers (GRN, MAPT, C9orf72), elevated NfL may herald pheno-conversion to full-blown dementia. Baseline NfL correlates with steeper neuroanatomical changes and cognitive, behavioral and functional decline, making NfL promising in monitoring disease progression. Phosphorylated neurofilament heavy chain (pNfH) levels have a potential limited role in the demarcation of the conversion stage to full-blown FTD. Combined NfL and pNfH measurements may allow a wider stage stratification. Total tau levels lack applicability in the framework of FTD. p-tau, on the other hand, is of potential value in the discrimination of FTD from Alzheimer's dementia. Progranulin concentrations could serve the identification of GRN mutation carriers. Glial fibrillary acidic protein (GFAP) may assist in the differentiation of PPDs from behavioral variant FTD and the detection of GRN mutation carriers (additional research is warranted). Finally, TAR DNA-binding protein-43 (TDP-43) appears to be a promising diagnostic biomarker for FTD. Its potential in distinguishing TDP-43 pathology from other FTD-related pathologies requires further research.

Alterations of human CSF and serum-based mitophagy biomarkers in the continuum of Alzheimer disease

Defective mitophagy is consistently found in postmortem brain and iPSC-derived neurons from Alzheimer disease (AD) patients. However, there is a lack of extensive examination of mitophagy status in serum or cerebrospinal fluid (CSF), and the clinical potential of mitophagy biomarkers has not been tested. We quantified biomarkers of mitophagy/autophagy and lysosomal degradation (PINK1, BNIP3L and TFEB) in CSF and serum from 246 individuals, covering mild cognitive impairment due to AD (MCI-AD, n = 100), dementia due to AD (AD-dementia, n = 100), and cognitively unimpaired individuals (CU, n = 46), recruited from the Czech Brain Aging Study. Cognitive function and brain atrophy were also assessed. Our data show that serum and CSF PINK1 and serum BNIP3L were higher, and serum TFEB was lower in individuals with AD than in corresponding CU individuals. Additionally, the magnitude of mitophagy impairment correlated with the severity of clinical indicators in AD patients. Specifically, levels of PINK1 positively correlated with phosphorylated (p)-MAPT/tau (181), total (t)-MAPT/tau, NEFL (neurofilament light chain), and NRGN (neurogranin) levels in CSF and negatively with memory, executive function, and language domain. Serum TFEB levels negatively correlated with NEFL and positively with executive function and language. This study reveals mitophagy impairment reflected in biofluid biomarkers of individuals with AD and associated with more advanced AD pathology.Abbreviation: Aβ: amyloid beta; AD: Alzheimer disease; AVs: autophagic vacuoles; BNIP3L: BCL2 interacting protein 3 like; CU: cognitively unimpaired; CSF: cerebrospinal fluid; LAMP1: lysosomal-associated membrane protein 1; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MCI: mild cognitive impairment; NRGN: neurogranin; NEFL: neurofilament light chain; p-MAPT/tau: phosphorylated microtubule associated protein tau; PINK1: PTEN induced kinase 1; t-MAPT/tau: total microtubule associated protein tau; TFEB: transcription factor EB; TMT: Trail Making Test.

Alzheimer's disease diagnostic accuracy by fluid and neuroimaging ATN framework

OBJECTIVES

The ATN's different modalities (fluids and neuroimaging) for each of the Aβ (A), tau (T), and neurodegeneration (N) elements are used for the biological diagnosis of Alzheimer's disease (AD). We aim to identify which ATN category achieves the highest potential for diagnosis and predictive accuracy of longitudinal cognitive decline.

METHODS

Based on the availability of plasma ATN biomarkers (plasma-derived Aβ42/40 , p-tau181, NFL, respectively), CSF ATN biomarkers (CSF-derived Aβ42 /Aβ40 , p-tau181, NFL), and neuroimaging ATN biomarkers (18F-florbetapir (FBP) amyloid-PET, 18F-flortaucipir (FTP) tau-PET, and fluorodeoxyglucose (FDG)-PET), a total of 2340 participants were selected from ADNI.

RESULTS

Our data analysis indicates that the area under curves (AUCs) of CSF-A, neuroimaging-T, and neuroimaging-N were ranked the top three ATN candidates for accurate diagnosis of AD. Moreover, neuroimaging ATN biomarkers display the best predictive ability for longitudinal cognitive decline among the three categories. To note, neuroimaging-T correlates well with cognitive performances in a negative correlation manner. Meanwhile, participants in the "N" element positive group, especially the CSF-N positive group, experience the fastest cognitive decline compared with other groups defined by ATN biomarkers. In addition, the voxel-wise analysis showed that CSF-A related to tau accumulation and FDG-PET indexes more strongly in subjects with MCI stage. According to our analysis of the data, the best three ATN candidates for a precise diagnosis of AD are CSF-A, neuroimaging-T, and neuroimaging-N.

CONCLUSIONS

Collectively, our findings suggest that plasma, CSF, and neuroimaging biomarkers differ considerably within the ATN framework; the most accurate target biomarkers for diagnosing AD were the CSF-A, neuroimaging-T, and neuroimaging-N within each ATN modality. Moreover, neuroimaging-T and CSF-N both show excellent ability in the prediction of cognitive decline in two different dimensions.

Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer's disease pathology

Modifiable factors can influence the risk for Alzheimer's disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer's prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologies for AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.

Feasibility of detecting snake envenomation biomarkers from dried blood spots

Biofluid proteomics is a sensitive and high throughput technique that provides vast amounts of molecular data for biomarker discovery. More recently, dried blood spots (DBS) have gained traction as a stable, noninvasive, and relatively cheap source of proteomic data for biomarker identification in disease and injury. Snake envenomation is responsible for significant morbidity and mortality worldwide; however, much remains unknown about the systemic molecular response to envenomation and acquiring biological samples for analysis is a major hurdle. In this study, we utilized DBS acquired from a case of lethal rattlesnake envenomation to determine the feasibility of discovering biomarkers associated with human envenomation. We identified proteins that were either unique or upregulated in envenomated blood compared to non-envenomated blood and evaluated if physiological response pathways and protein markers that correspond to the observed syndromes triggered by envenomation could be detected. We demonstrate that DBS provide useful proteomic information on the systemic processes that resulted from envenomation in this case and find evidence for a massive and systemic inflammatory cascade, combined with coagulation dysregulation, complement system activation, hypoxia response activation, and apoptosis. We also detected potential markers indicative of lethal anaphylaxis, cardiac arrest, and brain death. Ultimately, DBS proteomics has the potential to provide stable and sensitive molecular data on envenomation syndromes and response pathways, which is particularly relevant in low-resource areas which may lack the materials for biofluid processing and storage.

Perfusion Imaging and Inflammation Biomarkers Provide Complementary Information in Alzheimer's Disease

BACKGROUND

Single photon emission tomography (SPECT) can detect early changes in brain perfusion to support the diagnosis of dementia. Inflammation is a driver for dementia progression and measures of inflammation may further support dementia diagnosis.

OBJECTIVE

In this study, we assessed whether combining imaging with markers of inflammation improves prediction of the likelihood of Alzheimer's disease (AD).

METHODS

We analyzed 91 participants datasets (Institutional Ethics Approval 20/NW/0222). AD biomarkers and markers of inflammation were measured in cerebrospinal fluid. Statistical parametric mapping was used to quantify brain perfusion differences in perfusion SPECT images. Logistic regression models were trained to evaluate the ability of imaging and inflammation markers, both individually and combined, to predict AD.

RESULTS

Regional perfusion reduction in the precuneus and medial temporal regions predicted Aβ42 status. Increase in inflammation markers predicted tau and neurodegeneration. Matrix metalloproteneinase-10, a marker of blood-brain barrier regulation, was associated with perfusion reduction in the right temporal lobe. Adenosine deaminase, an enzyme involved in sleep homeostasis and inflammation, was the strongest predictor of neurodegeneration with an odds ratio of 10.3. The area under the receiver operator characteristic curve for the logistic regression model was 0.76 for imaging and 0.76 for inflammation. Combining inflammation and imaging markers yielded an area under the curve of 0.85.

CONCLUSIONS

Study results showed that markers of brain perfusion imaging and markers of inflammation provide complementary information in AD evaluation. Inflammation markers better predict tau status while perfusion imaging measures represent amyloid status. Combining imaging and inflammation improves AD prediction.

Preclinical Alzheimer's dementia: a useful concept or another dead end?

The term, preclinical dementia, was introduced in 2011 when new guidelines for the diagnosis of Alzheimer's dementia (AD) were published. In the intervening 11 years, many studies have appeared in the literature focusing on this early stage. A search conducted in English on Google Scholar on 06.23.2022 using the term "preclinical (Alzheimer's) dementia" produced 121, 000 results. However, the label is arguably more relevant for research purposes, and it is possible that the knowledge gained may lead to a cure for AD. The term has not been widely adopted by clinical practitioners. Furthermore, it is still not possible to predict who, after a diagnosis of preclinical dementia, will go on to develop AD, and if so, what the risk factors (modifiable and non-modifiable) might be. This Review/Theoretical article will focus on preclinical Alzheimer's dementia (hereafter called preclinical AD). We outline how preclinical AD is currently defined, explain how it is diagnosed and explore why this is problematic at a number of different levels. We also ask the question: Is the concept 'preclinical AD' useful in clinical practice or is it just another dead end in the Holy Grail to find a treatment for AD? Specific recommendations for research and clinical practice are provided.

Early detection of Alzheimer's disease using neuropsychological tests: a predict-diagnose approach using neural networks

Alzheimer’s disease (AD) is a slowly progressing disease for which there is no known therapeutic cure at present. Ongoing research around the world is actively engaged in the quest for identifying markers that can help predict the future cognitive state of individuals so that measures can be taken to prevent the onset or arrest the progression of the disease. Researchers are interested in both biological and neuropsychological markers that can serve as good predictors of the future cognitive state of individuals. The goal of this study is to identify non-invasive, inexpensive markers and develop neural network models that learn the relationship between those markers and the future cognitive state. To that end, we use the renowned Alzheimer’s Disease Neuroimaging Initiative (ADNI) data for a handful of neuropsychological tests to train Recurrent Neural Network (RNN) models to predict future neuropsychological test results and Multi-Level Perceptron (MLP) models to diagnose the future cognitive states of trial participants based on those predicted results. The results demonstrate that the predicted cognitive states match the actual cognitive states of ADNI test subjects with a high level of accuracy. Therefore, this novel two-step technique can serve as an effective tool for the prediction of Alzheimer’s disease progression. The reliance of the results on inexpensive, non-invasive tests implies that this technique can be used in countries around the world including those with limited financial resources.

A Review of Application of Aβ42/40 Ratio in Diagnosis and Prognosis of Alzheimer’s Disease

The number of patients with Alzheimer’s disease (AD) and non-Alzheimer’s disease (non-AD) has drastically increased over recent decades. The amyloid cascade hypothesis attributes a vital role to amyloid-β protein (Aβ) in the pathogenesis of AD. As the main pathological hallmark of AD, amyloid plaques consist of merely the 42 and 40 amino acid variants of Aβ (Aβ 42 and Aβ 40). The cerebrospinal fluid (CSF) biomarker Aβ 42/40 has been extensively investigated and eventually integrated into important diagnostic tools to support the clinical diagnosis of AD. With the development of highly sensitive assays and technologies, blood-based Aβ 42/40, which was obtained using a minimally invasive and cost-effective method, has been proven to be abnormal in synchrony with CSF biomarker values. This paper presents the recent progress of the CSF Aβ 42/40 ratio and plasma Aβ 42/40 for AD as well as their potential clinical application as diagnostic markers or screening tools for dementia.

Technical Performance Evaluation of Olink Proximity Extension Assay for Blood-Based Biomarker Discovery in Longitudinal Studies of Alzheimer's Disease

The core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers; amyloid-β (Aß), total tau (t-tau), and phosphorylated tau (p-tau181), are strong indicators of the presence of AD pathology, but do not correlate well with disease progression, and can be difficult to implement in longitudinal studies where repeat biofluid sampling is required. As a result, blood-based biomarkers are increasingly being sought as alternatives. In this study, we aimed to evaluate a promising blood biomarker discovery technology, Olink Proximity Extension Assays for technical reproducibility characteristics in order to highlight the advantages and disadvantages of using this technology in biomarker discovery in AD. We evaluated the performance of five Olink Proteomic multiplex proximity extension assays (PEA) in plasma samples. Three technical control samples included on each plate allowed calculation of technical variability. Biotemporal stability was measured in three sequential annual samples from 54 individuals with and without AD. Coefficients of variation (CVs), analysis of variance (ANOVA), and variance component analyses were used to quantify technical and individual variation over time. We show that overall, Olink assays are technically robust, with the largest experimental variation stemming from biological differences between individuals for most analytes. As a powerful illustration of one of the potential pitfalls of using a multi-plexed technology for discovery, we performed power calculations using the baseline samples to demonstrate the size of study required to overcome the need for multiple test correction with this technology. We show that the power of moderate effect size proteins was strongly reduced, and as a result investigators should strongly consider pooling resources to perform larger studies using this multiplexed technique where possible.

Alzheimer’s Disease Biomarkers Revisited From the Amyloid Cascade Hypothesis Standpoint

Alzheimer’s disease (AD) is the most common neurodegenerative disease worldwide. Amyloid beta (Aβ) is one of the proteins which aggregate in AD, and its key role in the disease pathogenesis is highlighted in the amyloid cascade hypothesis, which states that the deposition of Aβ in the brain parenchyma is a crucial initiating step in the future development of AD. The sensitivity of instruments used to measure proteins in blood and cerebrospinal fluid has significantly improved, such that Aβ can now successfully be measured in plasma. However, due to the peripheral production of Aβ, there is significant overlap between diagnostic groups. The presence of pathological Aβ within the AD brain has several effects on the cells and surrounding tissue. Therefore, there is a possibility that using markers of tissue responses to Aβ may reveal more information about Aβ pathology and pathogenesis than looking at plasma Aβ alone. In this manuscript, using the amyloid cascade hypothesis as a starting point, we will delve into how the effect of Aβ on the surrounding tissue can be monitored using biomarkers. In particular, we will consider whether glial fibrillary acidic protein, triggering receptor expressed on myeloid cells 2, phosphorylated tau, and neurofilament light chain could be used to phenotype and quantify the tissue response against Aβ pathology in AD.

Decreased Vessel Density in Retinal Capillary Plexus and Thinner Ganglion Cell Complex Associated With Cognitive Impairment

Background

To determine the association of the retinal capillary plexus (RCP) and ganglion cell complex (GCC) with cognitive impairment using optical coherence tomography angiography (OCTA).

Methods

A cross-sectional, community-based study utilizing data from the participants enrolled between August 2019 and January 2020 in the Jidong Eye Cohort Study. We assessed the vessel density in RCP and GCC thickness using OCTA, and cognitive testing using the Montreal Cognitive Assessment (MoCA). Cognitive impairment in this study was defined as MoCA score < 24. We used multivariable analysis to evaluate the association of RCP and GCC with cognitive impairment after adjusting for confounders.

Results

This study analyzed 1555 participants. The mean age of participants was 52.3 (8.4) years, and 861 (55.4%) were women. Cognitive impairment was observed in 268 (17.2%) participants. The adjusted odds ratio (OR) with 95% confidence interval (95% CI) for parafovea vessel density in the deep RCP with cognitive impairment was 1.20 (1.03–1.39). For vessel area and length density surrounding foveal avascular zone with cognitive impairment, the ORs with 95% CIs were 1.23 (1.07–1.41) and 1.30 (1.13–1.49), respectively. For thickness in the superior GCC with cognitive impairment, the OR with 95% CI was 1.16 (1.01–1.32).

Conclusion

Lower vessel density in the RCP and thinner GCC were associated with cognitive impairment. Our results suggest that alterations in the RCP and GCC could provide further evidence when assessing the cognitive function and may even be potentially useful biomarkers in the detection of cognitive impairment.

Therapeutic effects of crude extracts of Bacopa floribunda on beta-amyloid 1-42-induced Alzheimer's disease via suppression of dyslipidemia, systemic inflammation and oxidative stress in male Wistar Rats

Aims

Bacopa floribunda (BF), an African traditional plant and its species have been widely used as brain tonic for memory enhancement. It has also been reported to help relieve anxiety and some psychological disorders. This study aimed to investigate the mechanisms of action of BF on Amyloid beta (Aβ) 1-42 peptides induced cognitive deficit in male Wistar rats.

Main methods

A total of 48 healthy male wistar rats were used for this study. Some groups were pre-treated with 200 mg/kg of BF extracts before a single bilateral injection of Aβ 1-42 while some were post-treated with BF for 21 days after Aβ1-42 exposure. Cognitive performance was evaluated using Y-Maze and Novel Object recognition tests. After treatments, hippocampal homogenates were assayed for the levels of Acetylcholinesterase, Na-K/ATPase activities, glutamate and Aβ1-42 concentrations among others.

Key findings

It was observed that Aβ1-42 caused cognitive impairment and BF extracts especially the ethanol extract was able to significantly (p < 0.05) reverse almost all the perturbations including lipid imbalance caused by Aβ1-42 assault mainly at the post-treatment level.

Significance

Administration of ethanol and aqueous extracts of BF mitigated the hazardous effect of Aβ1-42 observed in the blood plasma and hippocampal homogenates. In this context, we conclude that BF is an efficient cognitive enhancer that can help alleviate some symptoms associated with Alzheimer's disease.

Neurodegenerative Disorders of Alzheimer, Parkinsonism, Amyotrophic Lateral Sclerosis and Multiple Sclerosis: An Early Diagnostic Approach for Precision Treatment

Neurodegenerative diseases (NDs) are characterised by progressive dysfunction of synapses, neurons, glial cells and their networks. Neurodegenerative diseases can be classified according to primary clinical features (e.g., dementia, parkinsonism, or motor neuron disease), anatomic distribution of neurodegeneration (e.g., frontotemporal degenerations, extrapyramidal disorders, or spinocerebellar degenerations), or principal molecular abnormalities. The most common neurodegenerative disorders are amyloidosis, tauopathies, a-synucleinopathy, and TAR DNA-binding protein 43 (TDP-43) proteopathy. The protein abnormalities in these disorders have abnormal conformational properties along with altered cellular mechanisms, and they exhibit motor deficit, mitochondrial malfunction, dysfunctions in autophagic-lysosomal pathways, synaptic toxicity, and more emerging mechanisms such as the roles of stress granule pathways and liquid-phase transitions. Finally, for each ND, microglial cells have been reported to be implicated in neurodegeneration, in particular, because the microglial responses can shift from neuroprotective to a deleterious role. Growing experimental evidence suggests that abnormal protein conformers act as seed material for oligomerization, spreading from cell to cell through anatomically connected neuronal pathways, which may in part explain the specific anatomical patterns observed in brain autopsy sample. In this review, we mention the human pathology of select neurodegenerative disorders, focusing on how neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis) represent a great healthcare problem worldwide and are becoming prevalent because of the increasing aged population. Despite many studies have focused on their etiopathology, the exact cause of these diseases is still largely unknown and until now with the only available option of symptomatic treatments. In this review, we aim to report the systematic and clinically correlated potential biomarker candidates. Although future studies are necessary for their use in early detection and progression in humans affected by NDs, the promising results obtained by several groups leads us to this idea that biomarkers could be used to design a potential therapeutic approach and preclinical clinical trials for the treatments of NDs.

Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry

Mass spectrometry (MS) has become a mainstream platform for comprehensive profiling of proteome, especially with the improvement of multiplexed tandem mass tag labeling coupled with two-dimensional liquid chromatography and tandem mass spectrometry (TMT-LC/LC-MS/MS). Recently, we have established a robust method for direct profiling of undepleted cerebrospinal fluid (CSF) proteome with the 16-plex TMTpro method, in which we optimized parameters in experimental steps of sample preparation, TMT labeling, LC/LC fractionation, tandem mass spectrometry, and computational data processing. The extensive LC fractionation not only enhances proteome coverage of the CSF but also alleviates ratio distortion of TMT quantification. The crucial quality control steps and improvements specific for the TMT16 analysis are highlighted. More than 3000 proteins can be quantified in a single experiment from 16 different CSF samples. This multiplexed method offers a powerful tool for profiling a variety of complex biofluids samples such as CSF, serum/plasma, and other clinical specimens.

Transitioning from cerebrospinal fluid to blood tests to facilitate diagnosis and disease monitoring in Alzheimer's disease

Alzheimer's disease (AD) is increasingly prevalent worldwide, and disease-modifying treatments may soon be at hand; hence, now, more than ever, there is a need to develop techniques that allow earlier and more secure diagnosis. Current biomarker-based guidelines for AD diagnosis, which have replaced the historical symptom-based guidelines, rely heavily on neuroimaging and cerebrospinal fluid (CSF) sampling. While these have greatly improved the diagnostic accuracy of AD pathophysiology, they are less practical for application in primary care, population-based and epidemiological settings, or where resources are limited. In contrast, blood is a more accessible and cost-effective source of biomarkers in AD. In this review paper, using the recently proposed amyloid, tau and neurodegeneration [AT(N)] criteria as a framework towards a biological definition of AD, we discuss recent advances in biofluid-based biomarkers, with a particular emphasis on those with potential to be translated into blood-based biomarkers. We provide an overview of the research conducted both in CSF and in blood to draw conclusions on biomarkers that show promise. Given the evidence collated in this review, plasma neurofilament light chain (N) and phosphorylated tau (p-tau; T) show particular potential for translation into clinical practice. However, p-tau requires more comparisons to be conducted between its various epitopes before conclusions can be made as to which one most robustly differentiates AD from non-AD dementias. Plasma amyloid beta (A) would prove invaluable as an early screening modality, but it requires very precise tests and robust pre-analytical protocols.

Transcriptomic profiling in canines and humans reveals cancer specific gene modules and biological mechanisms common to both species

Understanding relationships between spontaneous cancer in companion (pet) canines and humans can facilitate biomarker and drug development in both species. Towards this end we developed an experimental-bioinformatic protocol that analyzes canine transcriptomics data in the context of existing human data to evaluate comparative relevance of canine to human cancer. We used this protocol to characterize five canine cancers: melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, in 60 dogs. We applied an unsupervised, iterative clustering method that yielded five co-expression modules and found that each cancer exhibited a unique module expression profile. We constructed cancer models based on the co-expression modules and used the models to successfully classify the canine data. These canine-derived models also successfully classified human tumors representing the same cancers, indicating shared cancer biology between canines and humans. Annotation of the module genes identified cancer specific pathways relevant to cells-of-origin and tumor biology. For example, annotations associated with melanin production (PMEL, GPNMB, and BACE2), synthesis of bone material (COL5A2, COL6A3, and COL12A1), synthesis of pulmonary surfactant (CTSH, LPCAT1, and NAPSA), ribosomal proteins (RPL8, RPS7, and RPLP0), and epigenetic regulation (EDEM1, PTK2B, and JAK1) were unique to melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, respectively. In total, 152 biomarker candidates were selected from highly expressing modules for each cancer type. Many of these biomarker candidates are under-explored as drug discovery targets and warrant further study. The demonstrated transferability of classification models from canines to humans enforces the idea that tumor biology, biomarker targets, and associated therapeutics, discovered in canines, may translate to human medicine.

Plasma Proteomic Biomarkers Relating to Alzheimer's Disease: A Meta-Analysis Based on Our Own Studies

Background and Objective: Plasma biomarkers for the diagnosis and stratification of Alzheimer's disease (AD) are intensively sought. However, no plasma markers are well established so far for AD diagnosis. Our group has identified and validated various blood-based proteomic biomarkers relating to AD pathology in multiple cohorts. The study aims to conduct a meta-analysis based on our own studies to systematically assess the diagnostic performance of our previously identified blood biomarkers. Methods: To do this, we included seven studies that our group has conducted during the last decade. These studies used either Luminex xMAP or ELISA to measure proteomic biomarkers. As proteins measured in these studies differed, we selected protein based on the criteria that it must be measured in at least four studies. We then examined biomarker performance using random-effect meta-analyses based on the mean difference between biomarker concentrations in AD and controls (CTL), AD and mild cognitive impairment (MCI), MCI, and CTL as well as MCI converted to dementia (MCIc) and non-converted (MCInc) individuals. Results: An overall of 2,879 subjects were retrieved for meta-analysis including 1,053 CTL, 895 MCI, 882 AD, and 49 frontotemporal dementia (FTD) patients. Six proteins were measured in at least four studies and were chosen for meta-analyses for AD diagnosis. Of them, three proteins had significant difference between AD and controls, among which alpha-2-macroglobulin (A2M) and ficolin-2 (FCN2) increased in AD while fibrinogen gamma chain (FGG) decreased in AD compared to CTL. Furthermore, FGG significantly increased in FTD compared to AD. None of the proteins passed the significance between AD and MCI, or MCI and CTL, or MCIc and MCInc, although complement component 4 (CC4) tended to increase in MCIc individuals compared to MCInc. Conclusions: The results suggest that A2M, FCN2, and FGG are promising biomarkers to discriminate AD patients from controls, which are worthy of further validation.

Recent Advancements in Electrochemical Biosensors for Alzheimer's Disease Biomarkers Detection

Background

It is estimated that the average time between the diagnosis of Alzheimer’s disease (AD) and the patient’s death is 5-9 years. Therefore, both the initial phase of the disease and the preclinical state can be included in the critical period in disease diagnosis. Accordingly, huge progress has recently been observed in biomarker research to identify risk factors for dementia in older people with normal cognitive functions and mild cognitive impairments.

Methods

Electrochemical biosensors are excellent analytical tools that are used in the detection of AD biomarkers as they are easy to use, portable, and can do analysis in real time.

Results

This review presents the analytical techniques currently used to determine AD biomarkers in terms of their advantages and disadvantages; the most important clinical biomarkers of AD and their role in the disease. All recently used biorecognition molecules in electrochemical biosensor development, i.e., receptor protein, antibodies, aptamers and nucleic acids, are summarized for the first time. Novel electrochemical biosensors for AD biomarker detection, as ideal analytical platforms for point-of-care diagnostics, are also reviewed.

Conclusion

The article focuses on various strategies of biosensor chemical surface modifications to immobilize biorecognition molecules, enabling specific, quantitative AD biomarker detection in synthetic and clinical samples. In addition, this is the first review that presents innovative single-platform systems for simultaneous detection of multiple biomarkers and other important AD-associated biological species based on electrochemical techniques. The importance of these platforms in disease diagnosis is discussed.

The validation status of blood biomarkers of amyloid and phospho-tau assessed with the 5-phase development framework for AD biomarkers

PURPOSE

The development of blood biomarkers that reflect Alzheimer's disease (AD) pathophysiology (phosphorylated tau and amyloid-β) has offered potential as scalable tests for dementia differential diagnosis and early detection. In 2019, the Geneva AD Biomarker Roadmap Initiative included blood biomarkers in the systematic validation of AD biomarkers.

METHODS

A panel of experts convened in November 2019 at a two-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of blood biomarkers was assessed based on the Biomarker Roadmap methodology and discussed fully during the workshop which also evaluated cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers.

RESULTS

Plasma p-tau has shown analytical validity (phase 2 primary aim 1) and first evidence of clinical validity (phase 3 primary aim 1), whereas the maturity level for Aβ remains to be partially achieved. Full and partial achievement has been assigned to p-tau and Aβ, respectively, in their associations to ante-mortem measures (phase 2 secondary aim 2). However, only preliminary evidence exists for the influence of covariates, assay comparison and cut-off criteria.

CONCLUSIONS

Despite the relative infancy of blood biomarkers, in comparison to CSF biomarkers, much has already been achieved for phases 1 through 3 - with p-tau having greater success in detecting AD and predicting disease progression. However, sufficient data about the effect of covariates on the biomarker measurement is lacking. No phase 4 (real-world performance) or phase 5 (assessment of impact/cost) aim has been tested, thus not achieved.

Machine learning compensates fold-change method and highlights oxidative phosphorylation in the brain transcriptome of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder causing 70% of dementia cases. However, the mechanism of disease development is still elusive. Despite the availability of a wide range of biological data, a comprehensive understanding of AD's mechanism from machine learning (ML) is so far unrealized, majorly due to the lack of needed data density. To harness the AD mechanism's knowledge from the expression profiles of postmortem prefrontal cortex samples of 310 AD and 157 controls, we used seven predictive operators or combinations of RapidMiner Studio operators to establish predictive models from the input matrix and to assign a weight to each attribute. Besides, conventional fold-change methods were also applied as controls. The identified genes were further submitted to enrichment analysis for KEGG pathways. The average accuracy of ML models ranges from 86.30% to 91.22%. The overlap ratio of the identified genes between ML and conventional methods ranges from 19.7% to 21.3%. ML exclusively identified oxidative phosphorylation genes in the AD pathway. Our results highlighted the deficiency of oxidative phosphorylation in AD and suggest that ML should be considered as complementary to the conventional fold-change methods in transcriptome studies.

Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk

The plasma proteomic changes that precede the onset of dementia could yield insights into disease biology and highlight new biomarkers and avenues for intervention. We quantified 4,877 plasma proteins in nondemented older adults in the Atherosclerosis Risk in Communities cohort and performed a proteome-wide association study of dementia risk over five years (n = 4,110; 428 incident cases). Thirty-eight proteins were associated with incident dementia after Bonferroni correction. Of these, 16 were also associated with late-life dementia risk when measured in plasma collected nearly 20 years earlier, during mid-life. Two-sample Mendelian randomization causally implicated two dementia-associated proteins (SVEP1 and angiostatin) in Alzheimer's disease. SVEP1, an immunologically relevant cellular adhesion protein, was found to be part of larger dementia-associated protein networks, and circulating levels were associated with atrophy in brain regions vulnerable to Alzheimer's pathology. Pathway analyses for the broader set of dementia-associated proteins implicated immune, lipid, metabolic signaling and hemostasis pathways in dementia pathogenesis.

A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease

BACKGROUND

Accurate diagnosis of Alzheimer disease (AD) involving less invasive molecular procedures and at reasonable cost is an unmet medical need. We identified a serum miRNA signature for AD that is less invasive than a measure in cerebrospinal fluid.

METHODS

From the Oxford Project to Investigate Memory and Aging (OPTIMA) study, 96 serum samples were profiled by a multiplex (>500 analytes) microRNA (miRNA) reverse transcription quantitative PCR analysis, including 51 controls, 32 samples from patients with AD, and 13 samples from patients with mild cognitive impairment (MCI). Clinical diagnosis of a subset of AD and the controls was confirmed by postmortem (PM) histologic examination of brain tissue. In a machine learning approach, the AD and control samples were split 70:30 as the training and test cohorts. A multivariate random forest statistical analysis was applied to construct and test a miRNA signature for AD identification. In addition, the MCI participants were included in the test cohort to assess whether the signature can identify early AD patients.

RESULTS

A 12-miRNA signature for AD identification was constructed in the training cohort, demonstrating 76.0% accuracy in the independent test cohort with 90.0% sensitivity and 66.7% specificity. The signature, however, was not able to identify MCI participants. With a subset of AD and control participants with PM-confirmed diagnosis status, a separate 12-miRNA signature was constructed. Although sample size was limited, the PM-confirmed signature demonstrated improved accuracy of 85.7%, largely owing to improved specificity of 80.0% with comparable sensitivity of 88.9%.

CONCLUSION

Although additional and more diverse cohorts are needed for further clinical validation of the robustness, the miRNA signature appears to be a promising blood test to diagnose AD.

Nanoparticle-Enabled Enrichment of Longitudinal Blood Proteomic Fingerprints in Alzheimer's Disease

Blood-circulating biomarkers have the potential to detect Alzheimer's disease (AD) pathology before clinical symptoms emerge and to improve the outcomes of clinical trials for disease-modifying therapies. Despite recent advances in understanding concomitant systemic abnormalities, there are currently no validated or clinically used blood-based biomarkers for AD. The extremely low concentration of neurodegeneration-associated proteins in blood necessitates the development of analytical platforms to address the "signal-to-noise" issue and to allow an in-depth analysis of the plasma proteome. Here, we aimed to discover and longitudinally track alterations of the blood proteome in a transgenic mouse model of AD, using a nanoparticle-based proteomics enrichment approach. We employed blood-circulating, lipid-based nanoparticles to extract, analyze and monitor AD-specific protein signatures and to systemically uncover molecular pathways associated with AD progression. Our data revealed the existence of multiple proteomic signals in blood, indicative of the asymptomatic stages of AD. Comprehensive analysis of the nanoparticle-recovered blood proteome by label-free liquid chromatography-tandem mass spectrometry resulted in the discovery of AD-monitoring signatures that could discriminate the asymptomatic phase from amyloidopathy and cognitive deterioration. While the majority of differentially abundant plasma proteins were found to be upregulated at the initial asymptomatic stages, the abundance of these molecules was significantly reduced as a result of amyloidosis, suggesting a disease-stage-dependent fluctuation of the AD-specific blood proteome. The potential use of the proposed nano-omics approach to uncover information in the blood that is directly associated with brain neurodegeneration was further exemplified by the recovery of focal adhesion cascade proteins. We herein propose the integration of nanotechnology with already existing proteomic analytical tools in order to enrich the identification of blood-circulating signals of neurodegeneration, reinvigorating the potential clinical utility of the blood proteome at predicting the onset and kinetics of the AD progression trajectory.

Replication study of plasma proteins relating to Alzheimer's pathology

INTRODUCTION

This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis.

METHODS

Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively.

RESULTS

Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis.

DISCUSSION

Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Early-Onset Alzheimer's Disease: What Is Missing in Research?

PURPOSE OF REVIEW

Early-onset Alzheimer's disease (EOAD), defined as Alzheimer's disease (AD) occurring before age 65, is significantly less well studied than the late-onset form (LOAD) despite EOAD often presenting with a more aggressive disease progression. The aim of this review is to summarize the current understanding of the etiology of EOAD, their translation into clinical practice, and to suggest steps to be taken to move our understanding forward.

RECENT FINDINGS

EOAD cases make up 5-10% of AD cases but only 10-15% of these cases show known mutations in the APP, PSEN1, and PSEN2, which are linked to EOAD. New data suggests that these unexplained cases following a non-Mendelian pattern of inheritance is potentially caused by a mix of common and newly discovered rare variants. However, only a fraction of this genetic variation has been identified to date leaving the molecular mechanisms underlying this type of AD and their association with clinical, biomarker, and neuropathological changes unclear. While great advancements have been made in characterizing EOAD, much work is needed to disentangle the molecular mechanisms underlying this type of AD and to identify putative targets for more precise disease screening, diagnosis, prevention, and treatment.

Identification of Cathepsin D as a Plasma Biomarker for Alzheimer's Disease

Although Alzheimer’s disease (AD) is the most common neurodegenerative disease, there are still no drugs available to treat or prevent AD effectively. Here, we examined changes in levels of selected proteins implicated in the pathogenesis of AD using plasma samples of control subjects and patients with cognition impairment. To precisely categorize the disease, fifty-six participants were examined with clinical cognitive tests, amyloid positron emission tomography (PET) scan, and white matter hyperintensities scored by magnetic resonance imaging. Plasma cathepsin D levels of the subjects were examined by immunoblotting and enzyme-linked immunosorbent assay (ELISA). Correlation of plasma cathepsin D levels with AD-related factors and clinical characteristics were examined by statistical analysis. By analyzing quantitative immunoblot and ELISA, we found that the plasma level of cathepsin D, a major lysosomal protease, was decreased in the group with amyloid plaque deposition at the brain compared to the control group. The level of plasma cathepsin D was negatively correlated with clinical dementia rating scale sum of boxes (CDR-SB) scores. In addition, our integrated multivariable logistic regression model suggests the high performance of plasma cathepsin D level for discriminating AD from non-AD. These results suggest that the plasma cathepsin D level could be developed as a diagnostic biomarker candidate for AD.

Why Inclusion Matters for Alzheimer's Disease Biomarker Discovery in Plasma

BACKGROUND

African American/Black adults have a disproportionate incidence of Alzheimer's disease (AD) and are underrepresented in biomarker discovery efforts.

OBJECTIVE

This study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults.

METHODS

We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates.

RESULTS

In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD.

CONCLUSION

These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.

Retinal imaging in Alzheimer's and neurodegenerative diseases

In the last 20 years, research focused on developing retinal imaging as a source of potential biomarkers for Alzheimer's disease and other neurodegenerative diseases, has increased significantly. The Alzheimer's Association and the Alzheimer's & Dementia: Diagnosis, Assessment, Disease Monitoring editorial team (companion journal to Alzheimer's & Dementia) convened an interdisciplinary discussion in 2019 to identify a path to expedite the development of retinal biomarkers capable of identifying biological changes associated with AD, and for tracking progression of disease severity over time. As different retinal imaging modalities provide different types of structural and/or functional information, the discussion reflected on these modalities and their respective strengths and weaknesses. Discussion further focused on the importance of defining the context of use to help guide the development of retinal biomarkers. Moving from research to context of use, and ultimately to clinical evaluation, this article outlines ongoing retinal imaging research today in Alzheimer's and other brain diseases, including a discussion of future directions for this area of study.

Late-onset vs nonmendelian early-onset Alzheimer disease: A distinction without a difference?

There is mounting evidence that only a small fraction of early-onset Alzheimer disease cases (onset <65 years) are explained by known mutations. Even multiplex families with early onset often also have late-onset cases, suggesting that the commonly applied categorization of Alzheimer disease into early- and late-onset forms may not reflect distinct underlying etiology. Nevertheless, this categorization continues to govern today's research and the design of clinical trials. The aim of this review is to evaluate this categorization by providing a comprehensive, critical review of reported clinical, neuropathologic, and genomic characteristics of both onset-based subtypes and explore potential overlap between both categories. The article will lay out the need to comprehensively assess the phenotypic, neuropathologic, and molecular variability in Alzheimer disease and identify factors explaining the observed significant variation in onset age in persons with and without known mutations. The article will critically review ongoing large-scale genomic efforts in Alzheimer disease research (e.g., Alzheimer Disease Sequencing Project, Dominantly Inherited Alzheimer Network, Alzheimer Disease Neuroimaging Initiative) and their shortcomings to disentangle the delineation of unexplained nonmendelian early-onset from late-onset and mendelian forms of Alzheimer disease. In addition, it will outline specific approaches including epigenetic research through which a comprehensive characterization of this delineation can be achieved.

Circulating asymmetric dimethylarginine and cognitive decline: A 4-year follow-up study of the 1936 Aberdeen Birth Cohort

BACKGROUND

The underlying mechanisms leading to dementia and Alzheimer's disease (AD) are unclear. Asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase, may be associated with cognitive decline, but population-based evidence is lacking.

METHODS

Change in cognitive performance was assessed in participants of the Aberdeen Birth Cohort of 1936 using longitudinal Raven's progressive matrices (RPM) between 2000 and 2004. Multiple linear regression was used to estimate the association between ADMA concentrations in 2000 and change in cognitive performance after adjustment for potential confounders.

RESULTS

A total of 93 participants had complete information on cognitive performance between 2000 and 2004. Mean plasma ADMA concentrations were approximately 0.4 μmol/L lower in those participants with stable or improved RPM scores over follow-up compared with participants whose cognitive performance worsened. In confounder-adjusted analysis, one SD (0.06 μmol/L) increase in ADMA at 63 years of age was associated with an average reduction in RPM of 1.26 points (95% CI 0.14-2.26) after 4 years.

CONCLUSION

Raised plasma ADMA concentrations predicted worsening cognitive performance after approximately 4 years in this cohort of adults in late-middle age. These findings have implications for future research, including presymptomatic diagnosis or novel therapeutic targets for dementia and AD.

Blood biomarkers indicate that the preclinical stages of Alzheimer's disease present overlapping molecular features

It is still debated whether non-specific preclinical symptoms of Alzheimer's disease (AD) can have diagnostic relevance. We followed the evolution from cognitively normal to AD by NMR-based metabolomics of blood sera. Multivariate statistical analysis of the NMR profiles yielded models that discriminated subjective memory decline (SMD), mild cognitive impairment (MCI) and AD. We validated a panel of six statistically significant metabolites that predicted SMD, MCI and AD in a blind cohort with sensitivity values ranging from 88 to 95% and receiver operating characteristic values from 0.88 to 0.99. However, lower values of specificity, accuracy and precision were observed for the models involving SMD and MCI, which is in line with the pathological heterogeneity indicated by clinical data. This excludes a "linear" molecular evolution of the pathology, pointing to the presence of overlapping "gray-zones" due to the reciprocal interference of the intermediate stages. Yet, the clear difference observed in the metabolic pathways of each model suggests that pathway dysregulations could be investigated for diagnostic purposes.

Integrated lipidomics and proteomics network analysis highlights lipid and immunity pathways associated with Alzheimer's disease

BACKGROUND

There is an urgent need to understand the pathways and processes underlying Alzheimer's disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer's dementia using an unsupervised lipid, protein and gene multi-omics integrative approach.

METHODS

A lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored.

RESULTS

Five of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype).

CONCLUSIONS

Modules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes.

Plasma Aβ42 as a Biomarker of Prodromal Alzheimer's Disease Progression in Patients with Amnestic Mild Cognitive Impairment: Evidence from the PharmaCog/E-ADNI Study

It is an open issue whether blood biomarkers serve to diagnose Alzheimer's disease (AD) or monitor its progression over time from prodromal stages. Here, we addressed this question starting from data of the European FP7 IMI-PharmaCog/E-ADNI longitudinal study in amnesic mild cognitive impairment (aMCI) patients including biological, clinical, neuropsychological (e.g., ADAS-Cog13), neuroimaging, and electroencephalographic measures. PharmaCog/E-ADNI patients were classified as "positive" (i.e., "prodromal AD" n = 76) or "negative" (n = 52) based on a diagnostic cut-off of Aβ42/P-tau in cerebrospinal fluid as well as APOE ε 4 genotype. Blood was sampled at baseline and at two follow-ups (12 and 18 months), when plasma amyloid peptide 42 and 40 (Aβ42, Aβ40) and apolipoprotein J (clusterin, CLU) were assessed. Linear Mixed Models found no significant differences in plasma molecules between the "positive" (i.e., prodromal AD) and "negative" groups at baseline. In contrast, plasma Aβ42 showed a greater reduction over time in the prodromal AD than the "negative" aMCI group (p = 0.048), while CLU and Aβ40 increased, but similarly in the two groups. Furthermore, plasma Aβ42 correlated with the ADAS-Cog13 score both in aMCI patients as a whole and the prodromal AD group alone. Finally, CLU correlated with the ADAS-Cog13 only in the whole aMCI group, and no association with ADAS-Cog13 was found for Aβ40. In conclusion, plasma Aβ42 showed disease progression-related features in aMCI patients with prodromal AD.

Further understanding the connection between Alzheimer's disease and Down syndrome

Improved medical care of individuals with Down syndrome (DS) has led to an increase in life expectancy to over the age of 60 years. In conjunction, there has been an increase in age-related co-occurring conditions including Alzheimer's disease (AD). Understanding the factors that underlie symptom and age of clinical presentation of dementia in people with DS may provide insights into the mechanisms of sporadic and DS-associated AD (DS-AD). In March 2019, the Alzheimer's Association, Global Down Syndrome Foundation and the LuMind IDSC Foundation partnered to convene a workshop to explore the state of the research on the intersection of AD and DS research; to identify research gaps and unmet needs; and to consider how best to advance the field. This article provides a summary of discussions, including noting areas of emerging science and discovery, considerations for future studies, and identifying open gaps in our understanding for future focus.

Changes in Plasma Amyloid and Tau in a Longitudinal Study of Normal Aging, Mild Cognitive Impairment, and Alzheimer's Disease

BACKGROUND

Changes in cerebrospinal fluid, neuroimaging, and cognitive functions have been used as diagnostic biomarkers of Alzheimer's disease (AD). This study aimed to investigate the temporal trajectories of plasma biomarkers in subjects with mild cognitive impairment (MCI) and patients with AD relative to healthy controls (HCs).

METHODS

In this longitudinal study, 82 participants (31 HCs, 33 MCI patients, and 18 AD patients) were enrolled. After 3 years, 7 HCs had transitioned to MCI and 10 subjects with MCI had converted to AD. We analyzed plasma amyloid beta (Aβ) and tau proteins at baseline and annually to correlate with biochemical data and neuropsychological scores.

RESULTS

Longitudinal data analysis showed an evolution of Aβ-related biomarkers over time within patients, whereas tau-related biomarkers differed primarily across diagnostic classifications. An initial steady increase in Aβ42 in the MCI stage was followed by a decrease just prior to clinical AD onset. Hyperphosphorylated tau protein levels correlated with cognitive decline in the MCI stage, but not in the AD stage.

CONCLUSION

Plasma Aβ and tau levels change in a dynamic, nonlinear, nonparallel manner over the AD continuum. Changes in plasma Aβ concentration are time-dependent, whereas changes in hyperphosphorylated tau protein levels paralleled the clinical progression of MCI. It remains to be clarified whether diagnostic efficiency can be improved by combining multiple plasma markers or combining plasma markers with other diagnostic biomarkers.

Disposable immunoplatforms for the simultaneous determination of biomarkers for neurodegenerative disorders using poly(amidoamine) dendrimer/gold nanoparticle nanocomposite

Early diagnosis in primary care settings can increase access to therapies and their efficiency as well as reduce health care costs. In this context, we report in this paper the development of a disposable immunoplatform for the rapid and simultaneous determination of two protein biomarkers recently reported to be involved in the pathological process of neurodegenerative disorders (NDD), tau protein (tau), and TAR DNA-binding protein 43 (TDP-43). The methodology involves implementation of a sandwich-type immunoassay on the surface of dual screen-printed carbon electrodes (dSPCEs) electrochemically grafted with p-aminobenzoic acid (p-ABA), which allows the covalent immobilization of a gold nanoparticle-poly(amidoamine) (PAMAM) dendrimer nanocomposite (3D-Au-PAMAM). This scaffold was employed for the immobilization of the capture antibodies (CAbs). Detector antibodies labeled with horseradish peroxidase (HRP) and amperometric detection at - 0.20 V (vs. Ag pseudo-reference electrode) using the H₂O₂/hydroquinone (HQ) system were used. The developed methodology exhibits high sensitivity and selectivity for determining the target proteins, with detection limits of 2.3 and 12.8 pg mL^-1 for tau and TDP-43, respectively. The simultaneous determination of tau and TDP-43 was accomplished in raw plasma samples and brain tissue extracts from healthy individuals and NDD-diagnosed patients. The analysis can be performed in just 1 h using a simple one-step assay protocol and small sample amounts (5 μL plasma and 2.5 μg brain tissue extracts). Graphical abstract.

Plasma proteomic signatures predict dementia and cognitive impairment

INTRODUCTION

Biomarker discovery of dementia and cognitive impairment is important to gather insight into mechanisms underlying the pathogenesis of these conditions.

METHODS

In 997 adults from the InCHIANTI study, we assessed the association of 1301 plasma proteins with dementia and cognitive impairment. Validation was conducted in two Alzheimer's disease (AD) case-control studies as well as endophenotypes of AD including cognitive decline, brain amyloid burden, and brain volume.

RESULTS

We identified four risk proteins that were significantly associated with increased odds (peptidase inhibitor 3 (PI3), trefoil factor 3 (TFF3), pregnancy associated plasma protein A (PAPPA), agouti-related peptide (AGRP)) and two protective proteins (myostatin (MSTN), integrin aVb5 (ITGAV/ITGB5)) with decreased odds of baseline cognitive impairment or dementia. Of these, four proteins (MSTN, PI3, TFF3, PAPPA) were associated cognitive decline in subjects that were cognitively normal at baseline. ITGAV/ITGB5 was associated with lower brain amyloid burden, MSTN and ITGAV/ITGB5 were associated with larger brain volume and slower brain atrophy, and PI3, PAPPA, and AGRP were associated with smaller brain volume and/or faster brain atrophy.

DISCUSSION

These proteins may be useful as non-invasive biomarkers of dementia and cognitive impairment.

Utility of Animal Models to Understand Human Alzheimer's Disease, Using the Mastermind Research Approach to Avoid Unnecessary Further Sacrifices of Animals

To diagnose and treat early-stage (preclinical) Alzheimer’s disease (AD) patients, we need body-fluid-based biomarkers that reflect the processes that occur in this stage, but current knowledge on associated processes is lacking. As human studies on (possible) onset and early-stage AD would be extremely expensive and time-consuming, we investigate the potential value of animal AD models to help to fill this knowledge gap. We provide a comprehensive overview of processes associated with AD pathogenesis and biomarkers, current knowledge on AD-related biomarkers derived from on human and animal brains and body fluids, comparisons of biomarkers obtained in human AD and frequently used animal AD models, and emerging body-fluid-based biomarkers. In human studies, amyloid beta (Aβ), hyperphosphorylated tau (P-tau), total tau (T-tau), neurogranin, SNAP-25, glial fibrillary acidic protein (GFAP), YKL-40, and especially neurofilament light (NfL) are frequently measured. In animal studies, the emphasis has been mostly on Aβ. Although a direct comparison between human (familial and sporadic) AD and (mostly genetic) animal AD models cannot be made, still, in brain, cerebrospinal fluid (CSF), and blood, a majority of similar trends are observed for human AD stage and animal AD model life stage. This indicates the potential value of animal AD models in understanding of the onset and early stage of AD. Moreover, animal studies can be smartly designed to provide mechanistic information on the interrelationships between the different AD processes in a longitudinal fashion and may also include the combinations of different conditions that may reflect comorbidities in human AD, according to the Mastermind Research approach.

Genetic networks in Parkinson's and Alzheimer's disease

Parkinson’s disease (PD) and Alzheimer’s disease (AD) are the most common neurodegenerative diseases and there is increasing evidence that they share common physiological and pathological links. Here we have conducted the largest network analysis of PD and AD based on their gene expressions in blood to date. We identified modules that were not preserved between disease and healthy control (HC) networks, and important hub genes and transcription factors (TFs) in these modules. We highlighted that the PD module not preserved in HCs was associated with insulin resistance, and HDAC6 was identified as a hub gene in this module which may have the role of influencing tau phosphorylation and autophagic flux in neurodegenerative disease. The AD module associated with regulation of lipolysis in adipocytes and neuroactive ligand-receptor interaction was not preserved in healthy and mild cognitive impairment networks and the key hubs TRPC5 and BRAP identified as potential targets for therapeutic treatments of AD. Our study demonstrated that PD and AD share common disrupted genetics and identified novel pathways, hub genes and TFs that may be new areas for mechanistic study and important targets in both diseases.

Dielectric Constant and Conductivity of Blood Plasma: Possible Novel Biomarkers for Alzheimer's Disease

Alzheimer's disease is a complex debilitating neurodegenerative disease for which there is no cure. The lack of reliable biomarkers for Alzheimer's disease has made the evaluation of the efficacy of new treatments difficult and reliant on only clinical symptoms. In an aged population where cognitive function may be deteriorating for other reasons, the dependence on clinical symptoms is also unreliable. However, it is well established that infusion of β-amyloid into the dorsal hippocampus of rats leads to cognitive impairment in a rat model of Alzheimer's disease. Moreover, the blood plasma of β-amyloid-lesioned rats exhibits a distinct variation of the dielectric constant and conductivity when compared to that of normal rats in a time-dependent manner. These two electric parameters of blood plasma may therefore act as potential biomarkers for dementia due to Alzheimer's disease. This review is aimed at highlighting evidences that support blood plasma electrical properties, e.g., dielectric constant and conductivity as possible novel biomarkers for the early development and progression of dementia due to Alzheimer's disease.

Intranasal Administration of PACAP Is an Efficient Delivery Route to Reduce Infarct Volume and Promote Functional Recovery After Transient and Permanent Middle Cerebral Artery Occlusion

Intranasal (IN) administration appears to be a suitable route for clinical use as it allows direct delivery of bioactive molecules to the central nervous system, reducing systemic exposure and sides effects. Nevertheless, only some molecules can be transported to the brain from the nasal cavity. This led us to compare the efficiency of an IN, intravenous (IV), and intraperitoneal (IP) administration of pituitary adenylate cyclase-activating polypeptide (PACAP) after transient or permanent middle cerebral artery occlusion (MCAO) in C57BL/6 mice. The results show that the neuroprotective effect of PACAP is much more efficient after IN administration than IV injection while IP injection had no effect. IN administration of PACAP reduced the infarct volume when injected within 6 h after the reperfusion and improved functional recovery up to at least 1 week after the ischemia.

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology

BACKGROUND

Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown.

OBJECTIVE

We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes.

METHODS

We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677).

RESULTS

We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts.

CONCLUSIONS

Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.

Recent Advancements in Pathogenesis, Diagnostics and Treatment of Alzheimer's Disease

BACKGROUND

The only conclusive way to diagnose Alzheimer's is to carry out brain autopsy of the patient's brain tissue and ascertain whether the subject had Alzheimer's or any other form of dementia. However, due to the non-feasibility of such methods, to diagnose and conclude the conditions, medical practitioners use tests that examine a patient's mental ability.

OBJECTIVE

Accurate diagnosis at an early stage is the need of the hour for initiation of therapy. The cause for most Alzheimer's cases still remains unknown except where genetic distinctions have been observed. Thus, a standard drug regimen ensues in every Alzheimer's patient, irrespective of the cause, which may not always be beneficial in halting or reversing the disease progression. To provide a better life to such patients by suppressing existing symptoms, early diagnosis, curative therapy, site-specific delivery of drugs, and application of hyphenated methods like artificial intelligence need to be brought into the main field of Alzheimer's therapeutics.

METHODS

In this review, we have compiled existing hypotheses to explain the cause of the disease, and highlighted gene therapy, immunotherapy, peptidomimetics, metal chelators, probiotics and quantum dots as advancements in the existing strategies to manage Alzheimer's.

CONCLUSION

Biomarkers, brain-imaging, and theranostics, along with artificial intelligence, are understood to be the future of the management of Alzheimer's.

Elevation of plasma soluble amyloid precursor protein beta in Alzheimer's disease

INTRODUCTION

Beta-amyloid is considered to be a pathophysiological marker in Alzheimer's disease (AD). Soluble amyloid precursor proteins (sAPPs) -α (sAPPα) and -β (sAPPβ), which are the byproducts of non-amyloidogenic and amyloidogenic process of APP, respectively, have been repeatedly observed in the cerebrospinal fluids (CSF) of AD patients. The present study focused on the determination of sAPP levels in peripheral blood.

METHODS

The plasma protein levels of sAPPα and sAPPβ were measured with ELISA. Plasma from 52 AD patients, 98 amnestic mild cognitive impairment (MCI) patients, and 114 cognitively normal controls were compared.

RESULTS

The plasma level of sAPPβ was significantly increased in AD patients than in cognitively healthy controls. However, no significant change in plasma sAPPα was observed among the three groups. Furthermore, the plasma sAPPβ levels significantly correlated with cognitive assessment scales, such as clinical dementia rating (CDR), and mini-mental status examination (MMSE). Interestingly, sAPPα and sAPPβ had a positive correlation with each other in blood plasma, similar to previous studies on CSF sAPP. This correlation was stronger in the MCI and AD groups than in the cognitively healthy controls.

CONCLUSIONS

These results suggest that individuals with elevated plasma sAPPβ levels are at an increased risk of AD; elevation in these levels may reflect the progression of disease.

Latest advances in cerebrospinal fluid and blood biomarkers of Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease and its diagnosis has classically been based on clinical symptoms. Recently, a biological rather than a syndromic definition of the disease has been proposed that is based on biomarkers that reflect neuropathological changes. In AD, there are two main biomarker categories, namely neuroimaging and fluid biomarkers [cerebrospinal fluid (CSF) and blood]. As a complex and multifactorial disease, AD biomarkers are important for an accurate diagnosis and to stage the disease, assess the prognosis, test target engagement, and measure the response to treatment. In addition, biomarkers provide us with information that, even if it does not have a current clinical use, helps us to understand the mechanisms of the disease. In addition to the pathological hallmarks of AD, which include amyloid-β and tau deposition, there are multiple concomitant pathological events that play a key role in the disease. These include, but are not limited to, neurodegeneration, inflammation, vascular dysregulation or synaptic dysfunction. In addition, AD patients often have an accumulation of other proteins including α-synuclein and TDP-43, which may have a pathogenic effect on AD. In combination, there is a need to have biomarkers that reflect different aspects of AD pathogenesis and this will be important in the future to establish what are the most suitable applications for each of these AD-related biomarkers. It is unclear whether sex, gender, or both have an effect on the causes of AD. There may be differences in fluid biomarkers due to sex but this issue has often been neglected and warrants further research. In this review, we summarize the current state of the principal AD fluid biomarkers and discuss the effect of sex on these biomarkers.