Blood-Based Biomarker Candidates of Cerebral Amyloid Using PiB PET in Non-Demented Elderly

Exercise to Counteract Alzheimer's Disease: What Do Fluid Biomarkers Say?

Neurodegenerative diseases (NDs) represent an unsolved problem to date with an ever-increasing population incidence. Particularly, Alzheimer's disease (AD) is the most widespread ND characterized by an accumulation of amyloid aggregates of beta-amyloid (Aβ) and Tau proteins that lead to neuronal death and subsequent cognitive decline. Although neuroimaging techniques are needed to diagnose AD, the investigation of biomarkers within body fluids could provide important information on neurodegeneration. Indeed, as there is no definitive solution for AD, the monitoring of these biomarkers is of strategic importance as they are useful for both diagnosing AD and assessing the progression of the neurodegenerative state. In this context, exercise is known to be an effective non-pharmacological management strategy for AD that can counteract cognitive decline and neurodegeneration. However, investigation of the concentration of fluid biomarkers in AD patients undergoing exercise protocols has led to unclear and often conflicting results, suggesting the need to clarify the role of exercise in modulating fluid biomarkers in AD. Therefore, this critical literature review aims to gather evidence on the main fluid biomarkers of AD and the modulatory effects of exercise to clarify the efficacy and usefulness of this non-pharmacological strategy in counteracting neurodegeneration in AD.

Serum Proteomic Signatures of Common Health Outcomes among Older Adults

INTRODUCTION

In aging populations, the coexistence of multiple health comorbidities represents a significant challenge for clinicians and researchers. Leveraging advances in omics techniques to characterize these health conditions may provide insight into disease pathogenesis as well as reveal biomarkers for monitoring, prognostication, and diagnosis. Researchers have previously established the utility of big data approaches with respect to comprehensive health outcome measurements in younger populations, identifying protein markers that may provide significant health information with a single blood sample.

METHODS

Here, we employed a similar approach in two cohorts of older adults, the Baltimore Longitudinal Study of Aging (mean age = 76.12 years) and InCHIANTI Study (mean age = 66.05 years), examining the relationship between levels of serum proteins and 5 key health outcomes: kidney function, fasting glucose, physical activity, lean body mass, and percent body fat.

RESULTS

Correlations between proteins and health outcomes were primarily shared across both older adult cohorts. We further identified that most proteins associated with health outcomes in the older adult cohorts were not associated with the same outcomes in a prior study of a younger population. A subset of proteins, adiponectin, MIC-1, and NCAM-120, were associated with at least three health outcomes in both older adult cohorts but not in the previously published younger cohort, suggesting that they may represent plausible markers of general health in older adult populations.

CONCLUSION

Taken together, these findings suggest that comprehensive protein health markers have utility in aging populations and are distinct from those identified in younger adults, indicating unique mechanisms of disease with aging.

Phenomic Imaging

Human phenomics is defined as the comprehensive collection of observable phenotypes and characteristics influenced by a complex interplay among factors at multiple scales. These factors include genes, epigenetics at the microscopic level, organs, microbiome at the mesoscopic level, and diet and environmental exposures at the macroscopic level. "Phenomic imaging" utilizes various imaging techniques to visualize and measure anatomical structures, biological functions, metabolic processes, and biochemical activities across different scales, both in vivo and ex vivo. Unlike conventional medical imaging focused on disease diagnosis, phenomic imaging captures both normal and abnormal traits, facilitating detailed correlations between macro- and micro-phenotypes. This approach plays a crucial role in deciphering phenomes. This review provides an overview of different phenomic imaging modalities and their applications in human phenomics. Additionally, it explores the associations between phenomic imaging and other omics disciplines, including genomics, transcriptomics, proteomics, immunomics, and metabolomics. By integrating phenomic imaging with other omics data, such as genomics and metabolomics, a comprehensive understanding of biological systems can be achieved. This integration paves the way for the development of new therapeutic approaches and diagnostic tools.

Serum IL-6, sAXL, and YKL-40 as systemic correlates of reduced brain structure and function in Alzheimer's disease: results from the DELCODE study

BACKGROUND

Neuroinflammation constitutes a pathological hallmark of Alzheimer's disease (AD). Still, it remains unresolved if peripheral inflammatory markers can be utilized for research purposes similar to blood-based beta-amyloid and neurodegeneration measures. We investigated experimental inflammation markers in serum and analyzed interrelations towards AD pathology features in a cohort with a focus on at-risk stages of AD.

METHODS

Data of 74 healthy controls (HC), 99 subjective cognitive decline (SCD), 75 mild cognitive impairment (MCI), 23 AD relatives, and 38 AD subjects were obtained from the DELCODE cohort. A panel of 20 serum biomarkers was determined using immunoassays. Analyses were adjusted for age, sex, APOE status, and body mass index and included correlations between serum and CSF marker levels and AD biomarker levels. Group-wise comparisons were based on screening diagnosis and routine AD biomarker-based schematics. Structural imaging data were combined into composite scores representing Braak stage regions and related to serum biomarker levels. The Preclinical Alzheimer's Cognitive Composite (PACC5) score was used to test for associations between the biomarkers and cognitive performance.

RESULTS

Each experimental marker displayed an individual profile of interrelations to AD biomarkers, imaging, or cognition features. Serum-soluble AXL (sAXL), IL-6, and YKL-40 showed the most striking associations. Soluble AXL was significantly elevated in AD subjects with pathological CSF beta-amyloid/tau profile and negatively related to structural imaging and cognitive function. Serum IL-6 was negatively correlated to structural measures of Braak regions, without associations to corresponding IL-6 CSF levels or other AD features. Serum YKL-40 correlated most consistently to CSF AD biomarker profiles and showed the strongest negative relations to structure, but none to cognitive outcomes.

CONCLUSIONS

Serum sAXL, IL-6, and YKL-40 relate to different AD features, including the degree of neuropathology and cognitive functioning. This may suggest that peripheral blood signatures correspond to specific stages of the disease. As serum markers did not reflect the corresponding CSF protein levels, our data highlight the need to interpret serum inflammatory markers depending on the respective protein's specific biology and cellular origin. These marker-specific differences will have to be considered to further define and interpret blood-based inflammatory profiles for AD research.

Plasma proteome profiling identifies changes associated to AD but not to FTD

BACKGROUND

Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process.

METHODS

Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis.

RESULTS

Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified.

CONCLUSIONS

We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.

Biometal Dyshomeostasis in Olfactory Mucosa of Alzheimer's Disease Patients

Olfactory function, orchestrated by the cells of the olfactory mucosa at the rooftop of the nasal cavity, is disturbed early in the pathogenesis of Alzheimer's disease (AD). Biometals including zinc and calcium are known to be important for sense of smell and to be altered in the brains of AD patients. Little is known about elemental homeostasis in the AD patient olfactory mucosa. Here we aimed to assess whether the disease-related alterations to biometal homeostasis observed in the brain are also reflected in the olfactory mucosa. We applied RNA sequencing to discover gene expression changes related to metals in olfactory mucosal cells of cognitively healthy controls, individuals with mild cognitive impairment and AD patients, and performed analysis of the elemental content to determine metal levels. Results demonstrate that the levels of zinc, calcium and sodium are increased in the AD olfactory mucosa concomitantly with alterations to 17 genes related to metal-ion binding or metal-related function of the protein product. A significant elevation in alpha-2-macroglobulin, a known metal-binding biomarker correlated with brain disease burden, was observed on the gene and protein levels in the olfactory mucosa cells of AD patients. These data demonstrate that the olfactory mucosa cells derived from AD patients recapitulate certain impairments of biometal homeostasis observed in the brains of patients.

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.

Simulating the outcome of amyloid treatments in Alzheimer's disease from imaging and clinical data

In this study, we investigate SimulAD, a novel quantitative instrument for the development of intervention strategies for disease-modifying drugs in Alzheimer's disease. SimulAD is based on the modeling of the spatio-temporal dynamics governing the joint evolution of imaging and clinical biomarkers along the history of the disease, and allows the simulation of the effect of intervention time and drug dosage on the biomarkers' progression. When applied to multi-modal imaging and clinical data from the Alzheimer's Disease Neuroimaging Initiative the method enables to generate hypothetical scenarios of amyloid lowering interventions. The results quantify the crucial role of intervention time, and provide a theoretical justification for testing amyloid modifying drugs in the pre-clinical stage. Our experimental simulations are compatible with the outcomes observed in past clinical trials, and suggest that anti-amyloid treatments should be administered at least 7 years earlier than what is currently being done in order to obtain statistically powered improvement of clinical endpoints.

Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence

IMPORTANCE

Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies.

OBJECTIVE

To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020.

MAIN OUTCOMES AND MEASURES

In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models.

RESULTS

The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC, 0.99; PPV, 76.9%; and NPV, 100%) and test (AUC, 0.92; PPV, 81.8%; and NPV, 96.8%) data. The ALSPAC subsample (121 participants from the general population with plasma samples available at age 12 years (61 [50.4%] male) comprised 55 participants (45.5%) with PEs at age 18 years and 61 (50.4%) without PEs at age 18 years. A model using proteomic data at age 12 years predicted PEs at age 18 years, with an AUC of 0.74 (PPV, 67.8%; and NPV, 75.8%).

CONCLUSIONS AND RELEVANCE

In individuals at risk of psychosis, proteomic biomarkers may contribute to individualized prognosis and stratification strategies. These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes.

Association of serum Apolipoprotein B with cerebrospinal fluid biomarkers of Alzheimer's pathology

Objective

To examine whether apolipoprotein B (ApoB), apolipoprotein A‐1 (ApoA1), or their ratio (ApoB/A1) were associated with early changes in cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD) pathology in elderly adults with subjective cognitive decline (SCD).

Methods

This study included 507 objective cognitive normal participants from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) database including 288 cognitive normal participants (CN) and 219 SCD. Multiple linear regression models were used to examine the associations of apolipoproteins with CSF AD biomarkers.

Results

Compared with control group, SCD participants with significant AD biological characteristics had lower ApoB levels (P = 0.0461). In total participants, lower level of serum ApoB was associated with decreases in CSF Aβ42 (P = 0.0015) and Aβ42/40 (P = 0.0081) as well as increases in CSF p‐tau/Aβ42 (P < 0.0001) and t‐tau/Aβ42 (P = 0.0013), independent of APOEɛ4 status. In further subgroup analysis, these associations were more significant in SCD participants (ApoB × Diagnose: P < 0.05). In addition, lower levels of ApoB were also found associated with increases in p‐tau in the SCD subgroup (P = 0.0263). Furthermore, these protective associations were more significant in the overweight participants (ApoB × weight: P < 0.05). Results showed no association between ApoA1 and CSF biomarkers.

Interpretation

This study is the first to find protective associations of serum ApoB with CSF AD core biomarkers, especially in SCD individuals. It indicated that ApoB may be a potential biomarker for preclinical AD and may play different roles in different stages of AD.

Human CNS barrier-forming organoids with cerebrospinal fluid production

Cerebrospinal fluid (CSF) is a vital liquid, providing nutrients and signaling molecules and clearing out toxic by-products from the brain. The CSF is produced by the choroid plexus (ChP), a protective epithelial barrier that also prevents free entry of toxic molecules or drugs from the blood. Here, we establish human ChP organoids with a selective barrier and CSF-like fluid secretion in self-contained compartments. We show that this in vitro barrier exhibits the same selectivity to small molecules as the ChP in vivo and that ChP-CSF organoids can predict central nervous system (CNS) permeability of new compounds. The transcriptomic and proteomic signatures of ChP-CSF organoids reveal a high degree of similarity to the ChP in vivo. Finally, the intersection of single-cell transcriptomics and proteomic analysis uncovers key human CSF components produced by previously unidentified specialized epithelial subtypes.

Proteomics as a reliable approach for discovery of blood-based Alzheimer's disease biomarkers: A systematic review and meta-analysis

In order to gauge the impact of proteomics in discovery of Alzheimer's disease (AD) blood-based biomarkers, this study had systematically reviewed articles published between 1984-2019. Articles that fulfilled the inclusion criteria were assessed for risk of bias. A meta-analysis was performed for replicable candidate biomarkers (CB). Of the 1651 articles that were identified, 17 case-control and two cohort studies, as well as three combined case-control and longitudinal designs were shortlisted. A total of 207 AD and mild cognitive impairment (MCI) CB were discovered, with 48 reported in >2 studies. This review highlights six CB, namely alpha-2-macroglobulin (α2M)_ps, pancreatic polypeptide (PP)_ps, apolipoprotein A-1 (ApoA-1)_ps, afamin_p, insulin growth factor binding protein-2 (IGFBP-2)_ps and fibrinogen-γ-chain_p, all of which exhibited consistent pattern of regulation in >three independent cohorts. They are involved in AD pathogenesis via amyloid-beta (Aβ), neurofibrillary tangles, diabetes and cardiovascular diseases (CVD). Meta-analysis indicated that ApoA-1_ps was significantly downregulated in AD (SMD = -1.52, 95% CI: -1.89, -1.16, p < 0.00001), with low inter-study heterogeneity (I² = 0%, p = 0.59). α2M_ps was significantly upregulated in AD (SMD = 0.83, 95% CI: 0.05, 1.62, p = 0.04), with moderate inter-study heterogeneity (I² = 41%, p = 0.19). Both CB are involved in Aβ formation. These findings provide important insights into blood-based AD biomarkers discovery via proteomics.

Identifying Protein Biomarkers in Blood for Alzheimer's Disease

Background: At present, the main diagnostic methods for Alzheimer's disease (AD) are positron emission tomography (PET) scanning of the brain and analysis of cerebrospinal fluid (CSF) sample, but these methods are expensive and harmful to patients. Recently, more researchers focus on diagnosing AD by detecting biomarkers in blood, which is a cheaper and harmless way. Therefore, identifying AD-related proteins in blood can help treatment and diagnosis. Methods: We proposed a hypothesis that similar diseases share similar proteins. Diseases with similar symptoms are caused by abnormalities of similar proteins. Assuming that the similarities between AD and other diseases obey the normal distribution, we developed an iterative method based on disease similarity (IBDS). We combined Elastic Network (EN) with Minimum angle regression (MAR) to find the optimal solution. Finally, we used case studies and Summary data Mendelian Random (SMR) to verify our method. Results: We selected 39 diseases which are highly related to AD. They correspond 1,481 kinds of proteins. One hundred and eighty-four proteins are reported to be related to AD in Uniprot and the number would be 284 with our method. The AUC of our method by cross-validation is 0.9251 which is much higher than previous methods. Conclusion: In this paper, we presented a novel method for prioritizing AD-related proteins. Seven proteins have tissue specificity in blood among these 284 proteins, which could be used to diagnose AD in future. Case studies and SMR have been used to prove the relationship between these 7 proteins and AD. Availability and Implementation: https://github.com/zty2009/Identifying-Protein-Biomarkers-in-Blood-for-Alzheimer-s-Disease.

An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders

Cerebrospinal fluid analyses and neuroimaging can identify the underlying pathophysiology at the earliest stage of some neurodegenerative disorders, but do not have the scalability needed for population screening. Therefore, a blood-based marker for such pathophysiology would have greater utility in a primary care setting and in eligibility screening for clinical trials. Rapid advances in ultra-sensitive assays have enabled the levels of pathological proteins to be measured in blood samples, but research has been predominantly focused on Alzheimer disease (AD). Nonetheless, proteins that were identified as potential blood-based biomarkers for AD, for example, amyloid-β, tau, phosphorylated tau and neurofilament light chain, are likely to be relevant to other neurodegenerative disorders that involve similar pathological processes and could also be useful for the differential diagnosis of clinical symptoms. This Review outlines the neuropathological, clinical, molecular imaging and cerebrospinal fluid features of the most common neurodegenerative disorders outside the AD continuum and gives an overview of the current status of blood-based biomarkers for these disorders.

Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort

We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay

Introduction

Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins.

Methods

4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid.

Results

A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization.

Discussion

The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

Levels of α-2 Macroglobulin in cognitively normal Mexican- Americans with Subjective Cognitive Decline: A HABLE Study

BACKGROUND

The presence of Subjective Cognitive Decline (SCD) in the absence of objective change and the inflammatory biomarker Alpha 2 Macroglobulin (A2M) have both been implicated in preclinical Alzheimer's disease. Mexican Americans are population with high rates of cardiovascular and inflammatory disorders.

OBJECTIVES

The current study investigated the levels of A2M in cognitively normal Mexican Americans with and without complaints of cognitive decline.

METHOD

293 (243 females, 50 males) community-based cognitively normal older Mexican Americans from the ongoing Health and Aging Brain among Latino Elders (HABLE) study were grouped based on subjective cognitive decline and blood samples were assayed by electrochemiluminescence to determine levels of A2M.

RESULTS

Participants with SCD had significantly higher levels of A2M than those without SCD. Females with SCD had a significantly higher level of A2M.

CONCLUSIONS

Results suggest that higher levels of A2M, a marker of neuronal injury, may be involved in subtle changes in cognitive functioning recognizable to persons reporting SCD but too subtle to be objectively measured. Longitudinal research is needed to assess the impact of SDC and A2M in progression to MCI and dementia in Mexican Americans.

A blood-based signature of cerebrospinal fluid Aβ1-42 status

It is increasingly recognized that Alzheimer's disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1-42 (Aβ1-42) may be an earlier indicator of Alzheimer's disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual's CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1-42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1-42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1-42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1-42 levels and that the resulting model also validates reasonably across PET Aβ1-42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1-42 status, the earliest risk indicator for AD, with high accuracy.

A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease

A blood-based assessment of preclinical disease would have huge potential in the enrichment of participants for Alzheimer's disease (AD) therapeutic trials. In this study, cognitively unimpaired individuals from the AIBL and KARVIAH cohorts were defined as Aβ negative or Aβ positive by positron emission tomography. Nontargeted proteomic analysis that incorporated peptide fractionation and high-resolution mass spectrometry quantified relative protein abundances in plasma samples from all participants. A protein classifier model was trained to predict Aβ-positive participants using feature selection and machine learning in AIBL and independently assessed in KARVIAH. A 12-feature model for predicting Aβ-positive participants was established and demonstrated high accuracy (testing area under the receiver operator characteristic curve = 0.891, sensitivity = 0.78, and specificity = 0.77). This extensive plasma proteomic study has unbiasedly highlighted putative and novel candidates for AD pathology that should be further validated with automated methodologies.

Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [18F]-Flutemetamol PET Scan Result

Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) Aβ and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/Aβ42 (n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures (n = 100), MCI participants enrolled in the GE067-005 study with [18F]-Flutemetamol PET amyloid measures (n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF Aβ42 measurements (n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/Aβ42 (P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen β chain confirmed by immunoassay (P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid (P < 0.05) replicating the association with CSF Tau/Aβ42. There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF Aβ42 (P ≈ 0.05), while both A1AT and clusterin were nominally significantly associated with CSF Aβ42 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important.

Advances in Multi-Functional Ligands and the Need for Metal-Related Pharmacology for the Management of Alzheimer Disease

Alzheimer’s disease (AD) is the age linked neurodegenerative disorder with no disease modifying therapy currently available. The available therapy only offers short term symptomatic relief. Several hypotheses have been suggested for the pathogenesis of the disease while the molecules developed as possible therapeutic agent in the last decade, largely failed in the clinical trials. Several factors like tau protein hyperphosphorylation, amyloid-β (Aβ) peptide aggregation, decline in acetyl cholinesterase and oxidative stress might be contributing toward the pathogenesis of AD. Additionally, biometals dyshomeostasis (Iron, Copper, and Zinc) in the brain are also reported to be involved in the pathogenesis of AD. Thus, targeting these metal ions may be an effective strategy for the development of a drug to treat AD. Chelation therapy is currently employed for the metal intoxication but we lack a safe and effective chelating agents with additional biological properties for their possible use as multi target directed ligands for a complex disease like AD. Chelating agents possess the ability to disaggregate Aβ aggregation, dissolve amyloid plaques, and delay the cognitive impairment. Thus there is an urgent need to develop disease modifying therapeutic molecules with multiple beneficial features like targeting more than one factor responsible of the disease. These molecules, as disease modifying therapeutic agents for AD, should possess the potential to inhibit Aβ-metal interactions, the formation of toxic Aβ aggregates; and the capacity to reinstate metal homeostasis.

Fluid-based proteomics targeted on pathophysiological processes and pathologies in neurodegenerative diseases

Neurodegenerative dementias constitute a broad group of diseases in which abnormally folded proteins accumulate in specific brain regions and result in tissue reactions that eventually cause neuronal dysfunction and degeneration. Depending on where in the brain this happens, symptoms appear which may be used to classify the disorders on clinical grounds. However, brain changes in neurodegenerative dementias start to accumulate many years prior to symptom onset and there is a poor correlation between the clinical picture and what pathology that is the most likely to cause it. Thus, novel drug candidates having disease-modifying effects that is targeting the underlying pathology and changes the course of the disease needs to be defined using objective biomarker-based measures since the clinical symptoms are often non-specific and overlap between different disorders. Furthermore, the treatment should ideally be initiated as soon as symptoms are evident or when biomarkers confirm an underlying pathology (pre-clinical phase of the disease) to reduce irreversible damage to, for example, neurons, synapses and axons. Clinical trials in the pre-clinical phase bring a greater importance to biomarkers since by definition the clinical effects are difficult or slow to discern in a population that is not yet clinically affected. Here, we discuss neuropathological changes that may underlie neurodegenerative dementias, including how they can be detected and quantified using currently available biofluid-based biomarkers and how more of them could be identified using targeted proteomics approaches. This article is part of the special issue "Proteomics".

Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias

Neurodegenerative dementias are highly complex disorders driven by vicious cycles of intersecting pathophysiologies. While most can be definitively diagnosed by the presence of disease-specific pathology in the brain at postmortem examination, clinical disease presentations often involve substantially overlapping cognitive, behavioral, and functional impairment profiles that hamper accurate diagnosis of the specific disease. As global demographics shift towards an aging population in developed countries, clinicians need more sensitive and specific diagnostic tools to appropriately diagnose, monitor, and treat neurodegenerative conditions. This review is intended as an overview of how modern proteomic techniques (liquid chromatography mass spectrometry (LC-MS/MS) and advanced capture-based technologies) may contribute to the discovery and establishment of better biofluid biomarkers for neurodegenerative disease, and the limitations of these techniques. The review highlights some of the more interesting technical innovations and common themes in the field but is not intended to be an exhaustive systematic review of studies to date. Finally, we discuss clear reporting principles that should be integrated into all studies going forward to ensure data is presented in sufficient detail to allow meaningful comparisons across studies.

Update on biomarkers for amyloid pathology in Alzheimer's disease

At the center of Alzheimer's disease pathogenesis is the aberrant aggregation of amyloid-β (Aβ) into oligomers, fibrils and plaques. Effective monitoring of Aβ deposition directly in patients is essential to assist anti-Aβ therapeutics in target engagement and participant selection. In the advent of approved anti-Aβ therapeutics, biomarkers will become of fundamental importance in initiating treatments having disease modifying effects at the earliest stage. Two well-established Aβ biomarkers are widely utilized: Aβ-binding ligands for positron emission tomography and immunoassays to measure Aβ42 in cerebrospinal fluid. In this review, we will discuss the current clinical, diagnostic and research state of biomarkers for Aβ pathology. Furthermore, we will explore the current application of blood-based markers to assess Aβ pathology.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Molecular biomarkers of Alzheimer's disease: progress and prospects

The neurodegenerative disorder Alzheimer's disease is characterised by the formation of β-amyloid plaques and neurofibrillary tangles in the brain parenchyma, which cause synapse and neuronal loss. This leads to clinical symptoms, such as progressive memory deficits. Clinically, these pathological changes can be detected in the cerebrospinal fluid and with brain imaging, although reliable blood tests for plaque and tangle pathologies remain to be developed. Plaques and tangles often co-exist with other brain pathologies, including aggregates of transactive response DNA-binding protein 43 and Lewy bodies, but the extent to which these contribute to the severity of Alzheimer's disease is currently unknown. In this 'At a glance' article and poster, we summarise the molecular biomarkers that are being developed to detect Alzheimer's disease and its related pathologies. We also highlight the biomarkers that are currently in clinical use and include a critical appraisal of the challenges associated with applying these biomarkers for diagnostic and prognostic purposes of Alzheimer's disease and related neurodegenerative disorders, also in their prodromal clinical phases.

Chronically raised C-reactive protein is inversely associated with cortical β-amyloid in older adults with subjective memory complaints

BACKGROUND

Inflammation promotes amyloidogenesis in animals and markers of inflammation are associated with β-amyloid (Aβ) in humans. Hence, we sought to examine the cross-sectional associations between chronically elevated plasma C reactive protein (CRP) and cortical Aβ in 259 non-demented elderly individuals reporting subjective memory complaints from the Multidomain Alzheimer Preventive Trial (MAPT).

METHODS

Cortical-to-cerebellar standard uptake value ratios were obtained using [¹⁸F] florbetapir positron emission tomography (PET). CRP was measured in plasma using immunoturbidity. Chronically raised CRP was defined as having 2 consecutively high CRP readings (>3 mg/l ≤ 10 mg/l) between study baseline and the 1 year visit (visits were performed at baseline, 6 months, 1 year and then annually). Associations were explored using adjusted multiple linear regression.

RESULTS

Chronically raised CRP was found to be inversely associated with cortical Aβ (B-coefficient: -0.054, SE: 0.026, p = 0.040) and this association seemed to be specific to apolipoprotein E (Apo E) ε4 carriers (B-coefficient: -0.130, SE: 0.058, p = 0.027). CRP as an isolated reading measured closest to PET scan was also inversely associated with cortical Aβ when CRP was treated as a dichotomized variable (high CRP > 3 mg/l ≤ 10 mg/l, B-coefficient: -0.048, SE: 0.023, p = 0.043).

CONCLUSIONS

Our preliminary findings suggest that inflammation might be beneficial in the early stages of Alzheimer's disease as the immune systems attempts to combat Aβ pathology particularly in ApoE ε4 carriers. Investigating the temporal relationships between cerebral Aβ and a panel of inflammatory markers would provide further evidence as to whether chronic inflammation might modulate amyloidogenesis in vivo.

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

Blood-based biomarkers represent a less invasive and potentially cheaper approach for aiding Alzheimer's disease (AD) detection compared with cerebrospinal fluid and some neuroimaging biomarkers. Acknowledging that many in the field have made great progress, here we review some of the work that our group has pursued to identify and validate blood-based proteomic biomarkers through both case control and AD pathology endophenotype-based approaches. Our focus is primarily to identify a minimally invasive and hopefully cost-effective blood-based biomarker to reduce screen failure in clinical trials where participants have prodromal or even pre-clinical disease. We summarize some of the key findings and approaches taken in these biomarker studies, while addressing the main challenges, including that of limited replication in the field, and discuss opportunities for biomarker development.

A Blood Test for Alzheimer's Disease: Progress, Challenges, and Recommendations

Ever since the discovery of APOEɛ4 around 25 years ago, researchers have been excited about the potential of a blood test for Alzheimer's disease (AD). Since then researchers have looked for genetic, protein, metabolite, and/or gene expression markers of AD and related phenotypes. However, no blood test for AD is yet being used in the clinical setting. We first review the trends and challenges in AD blood biomarker research, before giving our personal recommendations to help researchers overcome these challenges. While some degree of consistency and replication has been seen across independent studies, several high-profile studies have seemingly failed to replicate. Partly due to academic incentives, there is a reluctance in the field to report predictive ability, to publish negative findings, and to independently replicate the work of others. If this can be addressed, then we will know sooner whether a blood test for AD or related phenotypes with clinical utility can be developed.

Effect of apolipoprotein E phenotype on the association of plasma amyloid β and amyloid positron emission tomography imaging in Japan

INTRODUCTION

The plasma concentration of beta-amyloid (Aβ) has been considered another biomarker of Alzheimer's disease and was reportedly associated with cortical Aβ accumulation.

METHODS

We analyzed 28 subjects with apolipoprotein E4 (ApoE4; E4 group) and 89 subjects without ApoE4 (non-E4 group) to determine the association between cortical Aβ accumulation by standard uptake value ratio with [¹⁸F]florbetapir positron emission tomography and plasma Aβ_1-40 and Aβ_1-42.

RESULTS

Aβ_1-42/Aβ_1-40 correlated significantly with mean regional [¹⁸F]florbetapir standard uptake value ratio in the non-E4 group (R² = 0.06, P = .02) but not in the E4 group, and receiver operating characteristic curve analysis for Aβ_1-42/Aβ_1-40 in the non-E4 group showed sensitivity (92.9%) and specificity (45.9%) with a cutoff value of 0.150 for Aβ positivity.

DISCUSSION

We verified that the correlation between Aβ_1-42/Aβ_1-40 and Aβ accumulation differed according to ApoE phenotype. The high sensitivity of plasma Aβ_1-42/Aβ_1-40 for Aβ positivity in non-E4 subjects indicated a possible role of plasma Aβ_1-42/Aβ_1-40 as a screening biomarker before amyloid positron emission tomography in clinical settings.

Specific protein biomarker patterns for Alzheimer's disease: improved diagnostics in progress

This short review looks at Alzheimer's disease (AD) diagnosis through my own point of view, going from imaging through cerebrospinal fluid to blood proteins. Over the last couple of years, we have published two papers targeted at Alzheimer's diagnosis. In one paper, we took an approach of selecting a specific target, namely, activity-dependent neuroprotective protein (ADNP), and our results tightened the association of ADNP blood expression with intelligence. In another paper, we took an unbiased approach of analysis of all genes expressed in lymphoblastoid cells lines and discovered changes in expression of the regulator of G-protein signaling 2 (RGS2) as a potential AD predictor. This review will assess our data in comparison to selected independent studies focusing on blood protein biomarkers as well as assessing saliva and urine samples with potential predictive value for AD. Furthermore, the review will provide directions for a combination of innovative markers, stratifying the population toward disease prevention and personalized medicine.

The influence of insulin resistance on cerebrospinal fluid and plasma biomarkers of Alzheimer's pathology

Background

Insulin resistance (IR) has previously been associated with an increased risk of developing Alzheimer’s disease (AD), although the relationship between IR and AD is not yet clear. Here, we examined the influence of IR on AD using plasma and cerebrospinal fluid (CSF) biomarkers related to IR and AD in cognitively healthy men. We also aimed to characterise the shared protein signatures between IR and AD.

Methods

Fifty-eight cognitively healthy men, 28 IR and 30 non-IR (age and APOE ε4 matched), were drawn from the Metabolic Syndrome in Men study in Kuopio, Finland. CSF AD biomarkers (amyloid β-peptide (Aβ), total tau and tau phosphorylated at the Thr181 epitope) were examined with respect to IR. Targeted proteomics using ELISA and Luminex xMAP assays were performed to assess the influence of IR on previously identified CSF and plasma protein biomarker candidates of AD pathology. Furthermore, CSF and plasma SOMAscan was performed to discover proteins that associate with IR and CSF AD biomarkers.

Results

CSF AD biomarkers did not differ between IR and non-IR groups, although plasma insulin correlated with CSF Aβ/tau across the whole cohort. In total, 200 CSF and 487 plasma proteins were differentially expressed between IR and non-IR subjects, and significantly enriched pathways, many of which have been previously implicated in AD, were identified. CSF and plasma proteins significantly associated with CSF AD biomarkers were also discovered, and those sensitive to both IR and AD were identified.

Conclusions

These data indicate that IR is not directly related to the level of CSF AD pathology in cognitively healthy men. Proteins that associated with both AD and IR are potential markers indicative of shared pathology.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-017-0258-6) contains supplementary material, which is available to authorized users.

Applying fluid biomarkers to Alzheimer's disease

Alzheimer's disease (AD) is a common neurodegenerative disease that starts with a clinically silent phase of a decade or more during which brain pathologies accumulate predominantly in the medial temporal lobe but also elsewhere in the brain. Network dysfunction and clinical symptoms typically appear when senile plaque (amyloid-β) and neurofibrillary tangle (tau) pathologies meet in the brain parenchyma, producing synapse and neuronal loss. For plaque and tangle pathologies, reliable fluid biomarkers have been developed. These require sampling of cerebrospinal fluid. Reliable blood tests for plaque and tangle pathologies are currently lacking, but blood tests for general neurodegeneration have recently been developed. In AD, plaques and tangles often coexist with other pathologies, including Lewy bodies, and to what extent these contribute to symptoms is currently unknown. There are also important differential diagnoses that may be possible to distinguish from AD with the aid of biomarkers. The scope of this review is fluid biomarkers for AD and related pathologies. The purpose is to provide the reader with an updated account of currently available fluid biomarkers for AD and clinically relevant differential diagnoses.

Blood-based biomarkers in Alzheimer disease: Current state of the science and a novel collaborative paradigm for advancing from discovery to clinic

The last decade has seen a substantial increase in research focused on the identification of blood-based biomarkers that have utility in Alzheimer's disease (AD). Blood-based biomarkers have significant advantages of being time- and cost-efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood-based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public-private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.