Blood-Derived Plasma Protein Biomarkers for Alzheimer's Disease in Han Chinese

Subsequent correlated changes in complement component 3 and amyloid beta oligomers in the blood of patients with Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) involves the complement cascade, with complement component 3 (C3) playing a key role. However, the relationship between C3 and amyloid beta (Aβ) in blood is limited.

METHODS

Plasma C3 and Aβ oligomerization tendency (AβOt) were measured in 35 AD patients and 62 healthy controls. Correlations with cerebrospinal fluid (CSF) biomarkers, cognitive impairment, and amyloid positron emission tomography (PET) were analyzed. Differences between biomarkers were compared in groups classified by concordances of biomarkers.

RESULTS

Plasma C3 and AβOt were elevated in AD patients and in CSF or amyloid PET-positive groups. Weak positive correlation was found between C3 and AβOt, while both had strong negative correlations with CSF Aβ42 and cognitive performance. Abnormalities were observed for AβOt and CSF Aβ42 followed by C3 changes.

DISCUSSION

Increased plasma C3 in AD are associated with amyloid pathology, possibly reflecting a defense response for Aβ clearance. Further studies on Aβ-binding proteins will enhance understanding of Aβ mechanisms in blood.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Identification of Clinically Relevant Brain Endothelial Cell Biomarkers in Plasma

BACKGROUND

Proteins expressed by brain endothelial cells (BECs), the primary cell type of the blood-brain barrier, may serve as sensitive plasma biomarkers for neurological and neurovascular conditions, including cerebral small vessel disease.

METHODS

Using data from the BLSA (Baltimore Longitudinal Study of Aging; n=886; 2009-2020), BEC-enriched proteins were identified among 7268 plasma proteins (measured with SomaScanv4.1) using an automated annotation algorithm that filtered endothelial cell transcripts followed by cross-referencing with BEC-specific transcripts reported in single-cell RNA-sequencing studies. To identify BEC-enriched proteins in plasma most relevant to the maintenance of neurological and neurovascular health, we selected proteins significantly associated with 3T magnetic resonance imaging-defined white matter lesion volumes. We then examined how these candidate BEC biomarkers related to white matter lesion volumes, cerebral microhemorrhages, and lacunar infarcts in the ARIC study (Atherosclerosis Risk in Communities; US multisite; 1990-2017). Finally, we determined whether these candidate BEC biomarkers, when measured during midlife, were related to dementia risk over a 25-year follow-up period.

RESULTS

Of the 28 proteins identified as BEC-enriched, 4 were significantly associated with white matter lesion volumes (CDH5 [cadherin 5], CD93 [cluster of differentiation 93], ICAM2 [intracellular adhesion molecule 2], GP1BB [glycoprotein 1b platelet subunit beta]), while another approached significance (RSPO3 [R-Spondin 3]). A composite score based on 3 of these BEC proteins accounted for 11% of variation in white matter lesion volumes in BLSA participants. We replicated the associations between the BEC composite score, CDH5, and RSPO3 with white matter lesion volumes in ARIC, and further demonstrated that the BEC composite score and RSPO3 were associated with the presence of ≥1 cerebral microhemorrhages. We also showed that the BEC composite score, CDH5, and RSPO3 were associated with 25-year dementia risk.

CONCLUSIONS

In addition to identifying BEC proteins in plasma that relate to cerebral small vessel disease and dementia risk, we developed a composite score of plasma BEC proteins that may be used to estimate blood-brain barrier integrity and risk for adverse neurovascular outcomes.

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

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

The dysfunctionality of hippocampal synapses may be directly related to PM-induced impairments in spatial learning and memory in juvenile rats

Epidemiological studies have demonstrated that exposure to air particulate matter (PM) increases the incidence of cardiovascular and respiratory diseases and exerts a significant neurotoxic effect on the nervous system, especially on the immature nervous system. Here, we selected PND28 rats to simulate the immature nervous system of young children and used neurobehavioral methods to examine how exposure to PM affected spatial learning and memory, as well as electrophysiology, molecular biology, and bioinformatics to study the morphology of hippocampus and the function of hippocampal synapses. We discovered that spatial learning and memory were impaired in rats exposed to PM. The morphology and structure of the hippocampus were altered in the PM group. In addition, after exposure to PM, the relative expression of synaptophysin (SYP) and postsynaptic density 95 (PSD95) proteins decreased dramatically in rats. Furthermore, PM exposure impaired long-term potentiation (LTP) in the hippocampal Schaffer-CA1 pathway. Interestingly, RNA sequencing and bioinformatics analysis revealed that the differentially expressed genes (DEGs) were rich in terms associated with synaptic function. Five hub genes (Agt, Camk2a, Grin2a, Snca, and Syngap1) that may play a significant role in the dysfunctionality of hippocampal synapses were identified. Our findings implied that exposure to PM impaired spatial learning and memory via exerting impacts on the dysfunctionality of hippocampal synapses in juvenile rats and that Agt, Camk2a, Grin2a, Snca, and Syngap1 may drive PM-caused synaptic dysfunction.

Free complement and complement containing extracellular vesicles as potential biomarkers for neuroinflammatory and neurodegenerative disorders

The complement system is implicated in a broad range of neuroinflammatory disorders such as Alzheimer's disease (AD) and multiple sclerosis (MS). Consequently, measuring complement levels in biofluids could serve as a potential biomarker for these diseases. Indeed, complement levels are shown to be altered in patients compared to controls, and some studies reported a correlation between the level of free complement in biofluids and disease progression, severity or the response to therapeutics. Overall, they are not (yet) suitable as a diagnostic tool due to heterogeneity of reported results. Moreover, measurement of free complement proteins has the disadvantage that information on their origin is lost, which might be of value in a multi-parameter approach for disease prediction and stratification. In light of this, extracellular vesicles (EVs) could provide a platform to improve the diagnostic power of complement proteins. EVs are nanosized double membrane particles that are secreted by essentially every cell type and resemble the (status of the) cell of origin. Interestingly, EVs can contain complement proteins, while the cellular origin can still be determined by the presence of EV surface markers. In this review, we summarize the current knowledge and future opportunities on the use of free and EV-associated complement proteins as biomarkers for neuroinflammatory and neurodegenerative disorders.

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.

Cerebrospinal fluid YKL-40 level evolution is associated with autoimmune encephalitis remission

Objective

Because of its heterogeneity in clinical presentation and course, predicting autoimmune encephalitis (AIE) evolution remains challenging. Hence, our aim was to explore the correlation of several biomarkers with the clinical course of disease.

Methods

Thirty-seven cases of AIE were selected retrospectively and divided into active (N = 9), improved (N = 12) and remission (N = 16) AIE according to their disease evolution. Nine proteins were tested in both serum and cerebrospinal fluid (CSF) at diagnosis (T0) and during the follow-up (T1), in particular activated MMP-9 (MMP-9A) and YKL-40 (or chitinase 3-like 1).

Results

From diagnosis to revaluation, AIE remission was associated with decreased YKL-40 and MMP-9A levels in the CSF, and with decreased NfL and NfH levels in the serum. The changes in YKL-40 concentrations in the CSF were associated with (1) still active AIE when increasing >10% (P-value = 0.0093); (2) partial improvement or remission when the changes were between +9% and -20% (P-value = 0.0173); and remission with a reduction > -20% (P-value = 0.0072; overall difference between the three groups: P-value = 0.0088). At T1, the CSF YKL-40 levels were significantly decreased between active and improved as well as improved and remission AIE groups but with no calculable threshold because of patient heterogeneity.

Conclusion

The concentration of YKL-40, a cytokine-like proinflammatory protein produced by glial cells, is correlated in the CSF with the clinical course of AIE. Its introduction as a biomarker may assist in following disease activity and in evaluating therapeutic response.

Proteome Network Analysis Identifies Potential Biomarkers for Brain Aging

BACKGROUND

Alzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults.

OBJECTIVE

To identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome.

METHODS

Weighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up).

RESULTS

Two proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities.

CONCLUSIONS

Proteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.

Early Diagnosis of Alzheimer's Disease with Blood Test; Tempting but Challenging

The increasing prevalence of Alzheimer's disease (AD) has led to a health crisis. According to official statistics, more than 55 million people globally have AD or other types of dementia, making it the sixth leading cause of death. It is still difficult to diagnose AD and there is no definitive diagnosis yet; post-mortem autopsy is still the only definite method. Moreover, clinical manifestations occur very late in the course of disease progression; therefore, profound irreversible changes have already occurred when the disease manifests. Studies have shown that in the preclinical stage of AD, changes in some biomarkers are measurable prior to any neurological damage or other symptoms. Hence, creating a reliable, fast, and affordable method capable of detecting AD in early stage has attracted the most attention. Seeking clinically applicable, inexpensive, less invasive, and much more easily accessible biomarkers for early diagnosis of AD, blood-based biomarkers (BBBs) seem to be an ideal option. This review is an inclusive report of BBBs that have been shown to be altered in the course of AD progression. The aim of this report is to provide comprehensive insight into the research status of early detection of AD based on BBBs.

Association of plasma brain-derived neurotrophic factor with Alzheimer's disease and its influencing factors in Chinese elderly population

OBJECTIVE

To explore the association of plasma brain-derived neurotrophic factor (BDNF) levels with Alzheimer's disease and its influencing factors.

MATERIALS AND METHODS

A total of 1,615 participants were included in the present study. Among all subjects, 660 were cognitive normal controls (CNCs), 571 were mild cognitive impairment (MCI) patients, and 384 were dementia with Alzheimer's type (DAT) patients. BDNF in blood samples collected from these subjects was analyzed via the Luminex assay. Additionally, DNA extraction and APOE4 genotyping were performed on leukocytes using a blood genotyping DNA extraction kit. All data were processed with SPSS 20.0 software. Analysis of variance (ANOVA) or analysis of covariance (ANCOVA) was used to compare differences among groups on plasma BDNF. Pearson and Spearman correlation analysis examined the correlation between BDNF and cognitive impairment, and linear regression analysis examined the comprehensive effects of diagnosis, gender, age, education, and sample source on BDNF.

RESULTS

BDNF levels in DAT patients were higher than those in CNC and MCI patients (P < 0.01). BDNF levels were significantly correlated with CDR, MMSE, and clinical diagnosis (P < 0.001). Age, education, occupation, and sample source had significant effects on BDNF differences among the CNC, MCI, and DAT groups (P < 0.001). BDNF first decreased and then increased with cognitive impairment in the ApoE4-negative group (P < 0.05).

CONCLUSION

Plasma BDNF levels decreased in the MCI stage and increased in the dementia stage and were affected by age, education, occupation, and sample source. Unless the effects of sample heterogeneity and methodological differences can be excluded, plasma BDNF is difficult to become a biomarker for the early screening and diagnosis of AD.

Phosphorylated Tau 181 Serum Levels Predict Alzheimer’s Disease in the Preclinical Stage

Background

There is an urgent need for cost-effective, easy-to-measure biomarkers to identify subjects who will develop Alzheimer’s disease (AD), especially at the pre-symptomatic stage. This stage can be determined in autosomal dominant AD (ADAD) which offers the opportunity to observe the dynamic biomarker changes during the life-course of AD stages. This study aimed to investigate serum biomarkers during different AD stages and potential novel protein biomarkers of presymptomatic AD.

Methods

In the first stage, 32 individuals [20 mutation carriers including 10 with AD, and 10 with mild cognitive impairment (MCI), and 12 healthy controls] from ADAD families were analyzed. All subjects underwent a complete clinical evaluation and a comprehensive neuropsychological battery. Serum samples were collected from all subjects, and antibody arrays were used to analyze 170 proteins in these samples. The most promising biomarkers were identified during this screening and were then measured in serum samples of 12 subjects with pre-MCI and 20 controls.

Results

The serum levels of 13 proteins were significantly different in patients with AD or MCI compared to controls. Of the 13 proteins, cathepsin D, immunoglobulin E, epidermal growth factor receptor (EGFR), matrix metalloproteinase-9 (MMP-9), von Willebrand factor (vWF), haptoglobin, and phosphorylated Tau-181 (p-Tau181) correlated with all cognitive measures (R² = −0.69–0.76). The areas under the receiver operating characteristic curve of these seven proteins were 0.71–0.93 for the classification of AD and 0.57–0.95 for the classification of MCI. Higher levels of p-Tau181 were found in the serum of pre-MCI subjects than in the serum of controls. The p-Tau181 serum level might detect AD before symptoms occur (area under the curve 0.85, sensitivity 75%, specificity 81.67%).

Conclusions

A total of 13 serum proteins showed significant differences between subjects with AD and MCI and healthy controls. The p-Tau181 serum level might be a broadly available and cost-effective biomarker to identify individuals with preclinical AD and assess the severity of AD.

Increased Inflammatory Markers at AMPH-Addicts Are Related to Neurodegenerative Conditions: Alzheimer’s Disease

Amphetamine addiction is widespread worldwide despite causing severe physical and mental problems, including neurodegeneration. One of the most common neurodegenerative disorders is Alzheimer’s disease (AD). Several inflammatory markers have been linked to AD. Previous studies have also found these biomarkers in amphetamine-addicts (AMPH-add). This study thus seeks to understand how AD and AMPH-addiction are related. A case–control observational study was conducted. Seventeen AMPH-adds ranging in age from 23 to 40 were recruited from Al Amal Psychiatric Hospital. In addition, 19 healthy subjects matching their age and gender were also recruited. The Luminex technique was used to measure serum alpha 1 antichymotrypsin (ACT), pigment epithelium-derived factor (PEDF), and macrophage inflammatory protein-4 (MIP-4), after complying with ethical guidelines and obtaining informed consent. In addition, liver function enzymes were correlated to AD’s predictive biomarkers in AMPH-adds. AMPH-adds had significantly higher serum levels of ACT, PEDF, and MIP-4 when compared to healthy controls (p = 0.03, p = 0.001, and p = 0.012, respectively). Furthermore, there is a significant correlation between lower ALT levels and elevated AST to ALT ratios in AMPH-adds (r = 0.618, 0.651, and p = 0.0001). These changes in inflammatory biomarkers may be linked to the onset of AD at a young age in amphetamine-drug addicts.

Potential Protein Blood-Based Biomarkers in Different Types of Dementia: A Therapeutic Overview

Abstract:

Biomarkers capable of identifying and distinguishing types of dementia such as Alzheimer's disease (AD), Parkinson's disease dementia (PDD), Lewy body dementia (LBD), and frontotemporal dementia (FTD) have been become increasingly relentless. Studies of possible biomarker proteins in the blood that can help formulate new diagnostic proposals and therapeutic visions of different types of dementia are needed. However, due to several limitations of these biomarkers, especially in discerning dementia, their clinical applications are still undetermined. Thus, the updating of biomarker blood proteins that can help in the diagnosis and discrimination of these main dementia conditions is essential to enable new pharmacological and clinical management strategies, with specificities for each type of dementia. To review the literature concerning protein blood-based AD and non-AD biomarkers as new pharmacological targets and/or therapeutic strategies. Recent findings for protein-based AD, PDD, LBD, and FTD biomarkers are focused on in this review. Protein biomarkers were classified according to the pathophysiology of the dementia types. The diagnosis and distinction of dementia through protein biomarkers is still a challenge. The lack of exclusive biomarkers for each type of dementia highlights the need for further studies in this field. Only after this, blood biomarkers may have a valid use in clinical practice as they are promising to help in diagnosis and in the differentiation of diseases.

Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19

The host response to COVID-19 pathophysiology over the first few days of infection remains largely unclear, especially the mechanisms in the blood compartment. We report on a longitudinal proteomic analysis of acute-phase COVID-19 patients, for which we used blood plasma, multiple reaction monitoring with internal standards, and data-independent acquisition. We measured samples on admission for 49 patients, of which 21 had additional samples on days 2, 4, 7, and 14 after admission. We also measured 30 externally obtained samples from healthy individuals for comparison at baseline. The 31 proteins differentiated in abundance between acute COVID-19 patients and healthy controls belonged to acute inflammatory response, complement activation, regulation of inflammatory response, and regulation of protein activation cascade. The longitudinal analysis showed distinct profiles revealing increased levels of multiple lipid-associated functions, a rapid decrease followed by recovery for complement activation, humoral immune response, and acute inflammatory response-related proteins, and level fluctuation in the regulation of smooth muscle cell proliferation, secretory mechanisms, and platelet degranulation. Three proteins were differentiated between survivors and nonsurvivors. Finally, increased levels of fructose-bisphosphate aldolase B were determined in patients with exposure to angiotensin receptor blockers versus decreased levels in those exposed to angiotensin-converting enzyme inhibitors. Data are available via ProteomeXchange PXD029437.

Diagnostic Accuracy of Blood-Based Biomarker Panels: A Systematic Review

Background

Because of high prevalence of Alzheimer's disease (AD) in low- and middle-income countries (LMICs), there is an urgent need for inexpensive and minimally invasive diagnostic tests to detect biomarkers in the earliest and asymptomatic stages of the disease. Blood-based biomarkers are predicted to have the most impact for use as a screening tool and predict the onset of AD, especially in LMICs. Furthermore, it has been suggested that panels of markers may perform better than single protein candidates.

Methods

Medline/Pubmed was searched to identify current relevant studies published from January 2016 to December 2020. We included all full-text articles examining blood-based biomarkers as a set of protein markers or panels to aid in AD's early diagnosis, prognosis, and characterization.

Results

Seventy-six articles met the inclusion criteria for systematic review. Majority of the studies reported plasma and serum as the main source for biomarker determination in blood. Protein-based biomarker panels were reported to aid in AD diagnosis and prognosis with better accuracy than individual biomarkers. Conventional (amyloid-beta and tau) and neuroinflammatory biomarkers, such as amyloid beta-42, amyloid beta-40, total tau, phosphorylated tau-181, and other tau isoforms, were the most represented. We found the combination of amyloid beta-42/amyloid beta-40 ratio and APOEε4 status to be most represented with high accuracy for predicting amyloid beta-positron emission tomography status.

Conclusion

Assessment of Alzheimer's disease biomarkers in blood as a non-invasive and cost-effective alternative will potentially contribute to early diagnosis and improvement of therapeutic interventions. Given the heterogeneous nature of AD, combination of markers seems to perform better in the diagnosis and prognosis of the disease than individual biomarkers.

Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging

Introduction

Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high‐performance, blood‐based test for AD.

Methods

We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high‐throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD.

Results

We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve  = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage‐dependent dysregulation, which can delineate AD stages.

Discussion

This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high‐performance, blood‐based test for clinical AD screening and staging.

Change in the plasma proteome associated with canine cognitive dysfunction syndrome (CCDS) in Thailand

BACKGROUND

Canine cognitive dysfunction syndrome (CCDS) is a progressive neurodegenerative disorder found in senior dogs. Due to the lack of biological markers, CCDS is commonly underdiagnosed. The aim of this study was to identify potential plasma biomarkers using proteomics techniques and to increase our understanding of the pathogenic mechanism of the disease. Plasma amyloid beta 42 (Aβ₄₂) has been seen to be a controversial biomarker for CCDS. Proteomics analysis was performed for protein identification and quantification.

RESULTS

Within CCDS, ageing, and adult dogs, 87 proteins were identified specific to Canis spp. in the plasma samples. Of 87 proteins, 48 and 41 proteins were changed in the ageing and adult groups, respectively. Several distinctly expressed plasma proteins identified in CCDS were involved in complement and coagulation cascades and the apolipoprotein metabolism pathway. Plasma Aβ₄₂ levels considerably overlapped within the CCDS and ageing groups. In the adult group, the Aβ₄₂ level was low compared with that in the other groups. Nevertheless, plasma Aβ₄₂ did not show a correlation with the Canine Cognitive Dysfunction Rating scale (CCDR) score in the CCDS group (p = 0.131, R² = 0.261).

CONCLUSIONS

Our present findings suggest that plasma Aβ₄₂ does not show potential for use as a diagnostic biomarker in CCDS. The nano-LC-MS/MS data revealed that the predictive underlying mechanism of CCDS was the co-occurrence of inflammation-mediated acute phase response proteins and complement and coagulation cascades that partly functioned by apolipoproteins and lipid metabolism. Some of the differentially expressed proteins may serve as potential predictor biomarkers along with Aβ₄₂ in plasma for improved CCDS diagnosis. Further study in larger population-based cohort study is required in validation to define the correlation between protein expression and the pathogenesis of CCDS.

Connection between the Altered HDL Antioxidant and Anti-Inflammatory Properties and the Risk to Develop Alzheimer's Disease: A Narrative Review

The protein composition of high-density lipoprotein (HDL) is extremely fluid. The quantity and quality of protein constituents drive the multiple biological functions of these lipoproteins, which include the ability to contrast atherogenesis, sustained inflammation, and toxic effects of reactive species. Several diseases where inflammation and oxidative stress participate in the pathogenetic process are characterized by perturbation in the HDL proteome. This change inevitably affects the functionality of the lipoprotein. An enlightening example in this frame comes from the literature on Alzheimer's disease (AD). Growing lines of epidemiological evidence suggest that loss of HDL-associated proteins, such as lipoprotein phospholipase A2 (Lp-PLA2), glutathione peroxidase-3 (GPx-3), and paraoxonase-1 and paraoxonase-3 (PON1, PON3), may be a feature of AD, even at the early stage. Moreover, the decrease in these enzymes with antioxidant/defensive action appears to be accompanied by a parallel increase of prooxidant and proinflammatory mediators, in particular myeloperoxidase (MPO) and serum amyloid A (SAA). This type of derangement of balance between two opposite forces makes HDL dysfunctional, i.e., unable to exert its “natural” vasculoprotective property. In this review, we summarized and critically analyzed the most significant findings linking HDL accessory proteins and AD. We also discuss the most convincing hypothesis explaining the mechanism by which an observed systemic occurrence may have repercussions in the brain.

Blood-based Biomarkers of Alzheimer's Disease: The Long and Winding Road

BACKGROUND

Blood-based biomarkers can be very useful in formulating new diagnostic and treatment proposals in the field of dementia, especially in Alzheimer's disease (AD). However, due to the influence of several factors on the reproducibility and reliability of these markers, their clinical use is still very uncertain. Thus, up-to-date knowledge about the main blood biomarkers that are currently being studied is extremely important in order to discover clinically useful and applicable tools, which could also be used as novel pharmacological strategies for the AD treatment.

METHODS

A narrative review was performed based on the current candidates of blood-based biomarkers for AD to show the main results from different studies, focusing on their clinical applicability and association with AD pathogenesis.

OBJECTIVE

The aim of this paper was to carry out a literature review on the major blood-based biomarkers for AD, connecting them with the pathophysiology of the disease.

RESULTS

Recent advances in the search of blood-based AD biomarkers were summarized in this review. The biomarkers were classified according to the topics related to the main hallmarks of the disease such as inflammation, amyloid, and tau deposition, synaptic degeneration and oxidative stress. Moreover, molecules involved in the regulation of proteins related to these hallmarks were described, such as non-coding RNAs, neurotrophins, growth factors and metabolites. Cells or cellular components with the potential to be considered as blood-based AD biomarkers were described in a separate topic.

CONCLUSION

A series of limitations undermine new discoveries on blood-based AD biomarkers. The lack of reproducibility of findings due to the small size and heterogeneity of the study population, different analytical methods and other assay conditions make longitudinal studies necessary in this field to validate these structures, especially when considering a clinical evaluation that includes a broad panel of these potential and promising blood-based biomarkers.

Blood-based protein mediators of senility with replications across biofluids and cohorts

Dementia severity can be quantitatively described by the latent dementia phenotype 'δ' and its various composite 'homologues'. We have explored δ's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium. However, it would be convenient to replicate them in the Alzheimer's Disease Neuroimaging Initiative. To that end, we have engineered a δ homologue from the observed cognitive performance measures common to both projects [i.e. 'd:Texas Alzheimer's Research and Care Consortium to Alzheimer's Disease Neuroimaging Initiative' (dT2A)]. In this analysis, we confirm 13/22 serum proteins as partial mediators of age's effect on dementia severity as measured by dT2A in the Texas Alzheimer's Research and Care Consortium and then replicate 4/13 in the Alzheimer's Disease Neuroimaging Initiative's plasma data. The replicated mediators of age-specific effects on dementia severity are adiponectin, follicle-stimulating hormone, pancreatic polypeptide and resistin. In their aggregate, the 13 confirmed age-specific mediators suggest that 'cognitive frailty' pays a role in dementia severity as measured by δ. We provide both discriminant and concordant support for that hypothesis. Weight, calculated low-density lipoprotein and body mass index are partial mediators of age's effect in the Texas Alzheimer's Research and Care Consortium. Biomarkers related to other disease processes (e.g. cerebrospinal fluid Alzheimer's disease-specific biomarkers in the Alzheimer's Disease Neuroimaging Initiative) are not. It now appears that dementia severity is the sum of multiple independent processes impacting δ. Each may have a unique set of mediating biomarkers. Age's unique effect appears to be at least partially mediated through proteins related to frailty. Age-specific mediation effects can be replicated across cohorts and biofluids. These proteins may offer targets for the remediation of age-specific cognitive decline (aka 'senility'), help distinguish it from other determinants of dementia severity and/or provide clues to the biology of Aging Proper.

Identification of Hub Genes and Key Pathways Associated With Bipolar Disorder Based on Weighted Gene Co-expression Network Analysis

Bipolar disorder (BD) is a complex mental disorder with high mortality and disability rates worldwide; however, research on its pathogenesis and diagnostic methods remains limited. This study aimed to elucidate potential candidate hub genes and key pathways related to BD in a pre-frontal cortex sample. Raw gene expression profile files of GSE53987, including 36 samples, were obtained from the gene expression omnibus (GEO) database. After data pre-processing, 10,094 genes were selected for weighted gene co-expression network analysis (WGCNA). After dividing highly related genes into 19 modules, we found that the pink, midnight blue, and brown modules were highly correlated with BD. Functional annotation and pathway enrichment analysis for modules, which indicated some key pathways, were conducted based on the Enrichr database. One of the most remarkable significant pathways is the Hippo signaling pathway and its positive transcriptional regulation. Finally, 30 hub genes were identified in three modules. Hub genes with a high degree of connectivity in the PPI network are significantly enriched in positive regulation of transcription. In addition, the hub genes were validated based on another dataset (GSE12649). Taken together, the identification of these 30 hub genes and enrichment pathways might have important clinical implications for BD treatment and diagnosis.