Altered levels of blood proteins in Alzheimer's disease longitudinal study: Results from Australian Imaging Biomarkers Lifestyle Study of Ageing cohort

Targeting the chemokine-microglia nexus: A novel strategy for modulating neuroinflammation in Alzheimer's disease

An increasing body of evidence suggests neuroinflammation has a prominent role in the pathogenesis of Alzheimer's disease (AD). The amyloid-β-tau-neurodegeneration (ATN) classification system is now being expanded toward an amyloid-β-tau neurodegeneration-neuroinflammation (ATN(I)) system. Activated microglia and reactive astrocytes are the key hubs for neuroinflammation in AD, and chemokines are recognized as pivotal modulators of microglial innate immune functions. In this review, based on the chemokine-microglia regulatory axis, we elucidate the mechanisms through which chemokines influence microglial function, potentially modulating neurotoxicity or neuroprotection in AD. The key chemokines that significantly affect microglial polarization, such as CCL2, CCL3, and CXCL1, are summarized, and their role in disease progression are elaborated. Additionally, we explore prospective therapeutic interventions centered on the chemokine-microglia regulatory axis, offering valuable perspectives on pathobiology of AD and avenues for pharmacological advancements.

Blood and CSF chemokines in Alzheimer's disease and mild cognitive impairment: a systematic review and meta-analysis

OBJECTIVE

Chemokines, which are chemotactic inflammatory mediators involved in controlling the migration and residence of all immune cells, are closely associated with brain inflammation, recognized as one of the potential processes/mechanisms associated with cognitive impairment. We aim to determine the chemokines which are significantly altered in Alzheimer's disease (AD) and mild cognitive impairment (MCI), as well as the respective effect sizes, by performing a meta-analysis of chemokines in cerebrospinal fluid (CSF) and blood (plasma or serum).

METHODS

We searched three databases (Pubmed, EMBASE and Cochrane library) for studies regarding chemokines. The three pairwise comparisons were as follows: AD vs HC, MCI vs healthy controls (HC), and AD vs MCI. The fold-change was calculated using the ratio of mean (RoM) chemokine concentration for every study. Subgroup analyses were performed for exploring the source of heterogeneity.

RESULTS

Of 2338 records identified from the databases, 61 articles comprising a total of 3937 patients with AD, 1459 with MCI, and 4434 healthy controls were included. The following chemokines were strongly associated with AD compared with HC: blood CXCL10 (RoM, 1.92, p = 0.039), blood CXCL9 (RoM, 1.78, p < 0.001), blood CCL27 (RoM, 1.34, p < 0.001), blood CCL15 (RoM, 1.29, p = 0.003), as well as CSF CCL2 (RoM, 1.19, p < 0.001). In the comparison of AD with MCI, there was significance for blood CXCL9 (RoM, 2.29, p < 0.001), blood CX3CL1 (RoM, 0.77, p = 0.017), and blood CCL1 (RoM, 1.37, p < 0.001). Of the chemokines tested, blood CX3CL1 (RoM, 2.02, p < 0.001) and CSF CCL2 (RoM, 1.16, p = 0.004) were significant for the comparison of MCI with healthy controls.

CONCLUSIONS

Chemokines CCL1, CCL2, CCL15, CCL27, CXCL9, CXCL10, and CX3CL1 might be most promising to serve as key molecular markers of cognitive impairment, although more cohort studies with larger populations are needed.

An Update on Peripheral Blood Extracellular Vesicles as Biomarkers for Parkinson's Disease Diagnosis

Parkinson's disease (PD) is the world's second primary neurodegenerative disease, and the diagnosis and treatment of PD have become mainstream research. Over the past decades, several studies have identified potential biomarkers for diagnosing PD. Among them, extracellular vesicles (EVs) can carry specific biomarkers reflecting the physiological and pathological state of the body. Due to the blood-brain barrier (BBB) limitation, peripheral blood is limited in diagnosing neurodegenerative diseases. With the increasing research on EVs, their ability to pass through BBB indicated that peripheral blood could depict disease status like cerebrospinal fluid (CSF). Peripheral blood is a clinically available sample and has recently been widely used by researchers in various studies. In this review, we summarized previous studies on PD diagnosis biomarkers in peripheral blood EVs and evaluated their diagnostic value. Some EV surface markers were also described, which can extract EVs from specific cell origins. In addition, the combination of several biomarkers demonstrated good diagnostic performance in PD diagnosis compared with a single biomarker, suggesting the focus of future research.

A conjoint analysis of bulk RNA-seq and single-nucleus RNA-seq for revealing the role of ferroptosis and iron metabolism in ALS

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive and selective degeneration of motor neurons in the motor cortex of brain and spinal cord. Ferroptosis is a newly discovered form of cell death and reported to mediate selective motor neuron death in the mouse model of ALS. The growing awareness of ferroptosis and iron metabolism dysfunction in ALS prompted us to investigate the expression pattern of ferroptosis and iron metabolism-related genes (FIRGs) in ALS. Here, we performed a conjoint analysis of bulk-RNA sequence and single-nucleus RNA sequence data using the datasets from Gene Expression Omnibus (GEO) to reveal the role of FIRGs in ALS, especially in selective motor neuron death of ALS. We first investigated the differentially expressed genes (DEGs) between ALS and non-neurological controls. Weighted gene co-expression network analysis constructed the gene co-expression network and identified three modules closely associated with ALS. Fifteen FIRGs was identified as target genes based on least absolute shrinkage and selection operator regression analysis as follows: ACSL4, ANO6, ATP6V0E1, B2M, CD44, CHMP5, CYBB, CYBRD1, HIF1A, MOSPD1, NCF2, SDCBP, STEAP2, TMEM14C, ULK1. These genes could differentiate ALS patients from non-neurological controls (p < 2.2e-16) and had a valid value in predicting and diagnosing ALS (AUC = 0.881 in primary dataset and AUC = 0.768 in validation dataset). Then we performed the functional enrichment analysis of DEGs between ALS cases, the most significantly influenced by target genes, and non-neurological controls. The result indicated that the most significantly influenced functions in ALS pathogenesis by these identified FIRGs are synapse pathways, calcium signaling pathway, cAMP signaling pathway, and phagosome and several immune pathways. At last, the analysis of single- nuclear seq found that CHMP5, one of the 15 FIRGs identified by bulk single-nucleus RNA-seq data, was expressed significantly higher in ALS than pathologically normal (PN), specifically in excitatory neuron populations with layer 2 and layer 3 markers (Ex L2_L3), layer 3 and layer 5 markers (Ex L3_L5). Taken together, our study indicates the positive correlation between FIRGs and ALS, presents potential markers for ALS diagnosis and provides new research directions of CHMP5 function in selective motor neuron death in ALS.

Cerebrospinal fluid levels of fatty acid-binding protein 3 are associated with likelihood of amyloidopathy in cognitively healthy individuals

Introduction

Fatty acid-binding protein 3 (FABP3) is a biomarker of neuronal membrane disruption, associated with lipid dyshomeostasis-a notable Alzheimer's disease (AD) pathophysiological change. We assessed the association of cerebrospinal fluid (CSF) FABP3 levels with brain amyloidosis and the likelihood/risk of developing amyloidopathy in cognitively healthy individuals.

Methods

FABP3 levels were measured in CSF samples of cognitively healthy participants, > 60 years of age (n = 142), from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL).

Results

FABP3 levels were positively associated with baseline brain amyloid beta (Aβ) load as measured by standardized uptake value ratio (SUVR, standardized β = 0.22, P = .009) and predicted the change in brain Aβ load (standardized β = 0.32, P = .004). Higher levels of CSF FABP3 (above median) were associated with a likelihood of amyloidopathy (odds ratio [OR] 2.28, 95% confidence interval [CI] 1.12 to 4.65, P = .023).

Discussion

These results support inclusion of CSF FABP3 as a biomarker in risk-prediction models of AD.

Plasma high-density lipoprotein cargo is altered in Alzheimer's disease and is associated with regional brain volume

Cholesterol levels have been repeatedly linked to Alzheimer's Disease (AD), suggesting that high levels could be detrimental, but this effect is likely attributed to Low-Density Lipoprotein (LDL) cholesterol. On the other hand, High-Density Lipoproteins (HDL) cholesterol levels have been associated with reduced brain amyloidosis and improved cognitive function. However, recent findings have suggested that HDL-functionality, which depends upon the HDL-cargo proteins associated with HDL, rather than HDL levels, appears to be the key factor, suggesting a quality over quantity status. In this report, we have assessed the HDL-cargo (Cholesterol, ApoA-I, ApoA-II, ApoC-I, ApoC-III, ApoD, ApoE, ApoH, ApoJ, CRP, and SAA) in stable healthy control (HC), healthy controls who will convert to MCI/AD (HC-Conv) and AD patients (AD). Compared to HC we observed an increased cholesterol/ApoA-I ratio in AD and HC-Conv, as well as an increased ApoD/ApoA-I ratio and a decreased ApoA-II/ApoA-I ratio in AD. Higher cholesterol/ApoA-I ratio was also associated with lower cortical grey matter volume and higher ventricular volume, while higher ApoA-II/ApoA-I and ApoJ/ApoA-I ratios were associated with greater cortical grey matter volume (and for ApoA-II also with greater hippocampal volume) and smaller ventricular volume. Additionally, in a clinical status-independent manner, the ApoE/ApoA-I ratio was significantly lower in APOE ε4 carriers and lowest in APOE ε4 homozygous. Together, these data indicate that in AD patients the composition of HDL is altered, which may affect HDL functionality, and such changes are associated with altered regional brain volumetric data.

Combination of Serum and Plasma Biomarkers Could Improve Prediction Performance for Alzheimer's Disease

Alzheimer's disease (AD) can be predicted either by serum or plasma biomarkers, and a combination may increase predictive power, but due to the high complexity of machine learning, it may also incur overfitting problems. In this paper, we investigated whether combining serum and plasma biomarkers with feature selection could improve prediction performance for AD. 150 D patients and 150 normal controls (NCs) were enrolled for a serum test, and 100 patients and 100 NCs were enrolled for the plasma test. Among these, 79 ADs and 65 NCs had serum and plasma samples in common. A 10 times repeated 5-fold cross-validation model and a feature selection method were used to overcome the overfitting problem when serum and plasma biomarkers were combined. First, we tested to see if simply adding serum and plasma biomarkers improved prediction performance but also caused overfitting. Then we employed a feature selection algorithm we developed to overcome the overfitting problem. Lastly, we tested the prediction performance in a 10 times repeated 5-fold cross validation model for training and testing sets. We found that the combined biomarkers improved AD prediction but also caused overfitting. A further feature selection based on the combination of serum and plasma biomarkers solved the problem and produced an even higher prediction performance than either serum or plasma biomarkers on their own. The combined feature-selected serum-plasma biomarkers may have critical implications for understanding the pathophysiology of AD and for developing preventative treatments.

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.

Blood biomarkers in Alzheimer's disease

INTRODUCTION

Early diagnosis of Alzheimer disease (AD) through the use of biomarkers could assist in the implementation and monitoring of early therapeutic interventions, and has the potential to significantly modify the course of the disease.

DEVELOPMENT

The classic cerebrospinal fluid and approved structural and functional neuroimaging biomarkers are of limited clinical application given their invasive nature and/or high cost. The identification of more accessible and less costly biomarkers, such as blood biomarkers, would increase their use in clinical practice. We review the available published evidence on the main blood biochemical biomarkers potentially useful for diagnosing AD.

CONCLUSIONS

Blood biomarkers are more cost- and time-effective than CSF biomarkers. However, immediate applicability in clinical practice is relatively unlikely. The main limitations come from the difficulty of measuring and standardising thresholds between different laboratories and the failure to replicate results. Of all the molecules studied, apoptosis and neurodegeneration biomarkers and the biomarker panels obtained through "omics" approaches, such as isolated or combined metabolomics, offer the most promising results.

Construction of Unified Human Antimicrobial and Immunomodulatory Peptide Database and Examination of Antimicrobial and Immunomodulatory Peptides in Alzheimer's Disease Using Network Analysis of Proteomics Datasets

The reanalysis of genomics and proteomics datasets by bioinformatics approaches is an appealing way to examine large amounts of reliable data. This can be especially true in cases such as Alzheimer's disease, where the access to biological samples, along with well-defined patient information can be challenging. Considering the inflammatory part of Alzheimer's disease, our aim was to examine the presence of antimicrobial and immunomodulatory peptides in human proteomic datasets deposited in the publicly available proteomics database ProteomeXchange (http://www.proteomexchange.org/). First, a unified, comprehensive human antimicrobial and immunomodulatory peptide database, containing all known human antimicrobial and immunomodulatory peptides was constructed and used along with the datasets containing high-quality proteomics data originating from the examination of Alzheimer's disease and control groups. A throughout network analysis was carried out, and the enriched GO functions were examined. Less than 1% of all identified proteins in the brain were antimicrobial and immunomodulatory peptides, but the alterations characteristic of Alzheimer's disease could be recapitulated with their analysis. Our data emphasize the key role of the innate immune system and blood clotting in the development of Alzheimer's disease. The central role of antimicrobial and immunomodulatory peptides suggests their utilization as potential targets for mechanistic studies and future therapies.

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

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

Peripheral Markers of Vascular Endothelial Dysfunction Show Independent but Additive Relationships with Brain-Based Biomarkers in Association with Functional Impairment in Alzheimer's Disease

BACKGROUND

Cerebrovascular dysfunction confers risk for functional decline in Alzheimer's disease (AD), yet the clinical interplay of these two pathogenic processes is not well understood.

OBJECTIVE

We utilized Alzheimer's Disease Neuroimaging Initiative (ADNI) data to examine associations between peripherally derived soluble cell adhesion molecules (CAMs) and clinical diagnostic indicators of AD.

METHODS

Using generalized linear regression models, we examined cross-sectional relationships of soluble plasma vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and E-Selectin to baseline diagnosis and functional impairment (clinical dementia rating sum-of-boxes, CDR-SB) in the ADNI cohort (n = 112 AD, n = 396 mild cognitive impairment (MCI), n = 58 cognitively normal). We further analyzed associations of these biomarkers with brain-based AD biomarkers in a subset with available cerebrospinal fluid (CSF) data (n = 351). p-values derived from main effects and interaction terms from the linear regressions were used to assess the relationship between independent and dependent variables for significance (significance level was set at 0.05 a priori for all analysis).

RESULTS

Higher mean VCAM-1 (p = 0.0026) and ICAM-1 (p = 0.0189) levels were found in AD versus MCI groups; however, not in MCI versus cognitively normal groups. Only VCAM-1 was linked with CDR-SB scores (p = 0.0157), and APOE ɛ4 genotype modified this effect. We observed independent, additive associations when VCAM-1 and CSF amyloid-β (Aβ42), total tau, phosphorylated tau (P-tau), or P-tau/Aβ42 (all < p = 0.01) were combined in a CDR-SB model; ICAM-1 showed a similar pattern, but to a lesser extent.

CONCLUSION

Our findings indicate independent associations of plasma-based vascular biomarkers and CSF biomarkers with AD-related clinical impairment.

Interdependence of metals and its binding proteins in Parkinson's disease for diagnosis

Metalloproteins utilizes cellular metals which plays a crucial function in brain that linked with neurodegenerative disorders. Parkinson's disease (PD) is a neurodegenerative disorder that affects geriatric population world-wide. Twenty-four metal-binding protein networks were investigated to identify key regulating protein hubs in PD blood and brain. Amongst, aluminum, calcium, copper, iron, and magnesium protein hubs are the key regulators showing the ability to classify PD from control based on thirty-four classification algorithms. Analysis of these five metal proteins hubs showed involvement in environmental information processing, immune, neuronal, endocrine, aging, and signal transduction pathways. Furthermore, gene expression of functional protein in each hub showed significant upregulation of EFEMP2, MMP9, B2M, MEAF2A, and TARDBP in PD. Dysregulating hub proteins imprint the metal availability in a biological system. Hence, metal concentration in serum and cerebrospinal fluid were tested, which were altered and showed significant contribution towards gene expression of metal hub proteins along with the previously reported PD markers. In conclusion, analyzing the levels of serum metals along with the gene expression in PD opens up an ideal and feasible diagnostic intervention for PD. Hence, this will be a cost effective and rapid method for the detection of Parkinson's disease.

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.

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

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

Plasma Clusterin as a Potential Link Between Diabetes and Alzheimer Disease

OBJECTIVE

Plasma clusterin, a promising biomarker of Alzheimer disease (AD), has been associated with diabetes mellitus (DM). However, clusterin has not been investigated considering a relationship with both DM and AD. In this study, we aimed to investigate the individual and interactive relationships of plasma clusterin levels with both diseases.

DESIGN

Cross-sectional observation study.

METHODS

We classified participants by the severity of cognitive (normal cognition, mild cognitive impairment [MCI], and AD) and metabolic (healthy control, prediabetes, and DM) impairments. We evaluated the cognitive and metabolic functions of the participants with neuropsychological assessments, brain magnetic resonance imaging, and various blood tests, to explore potential relationships with clusterin.

RESULTS

Plasma clusterin levels were higher in participants with AD and metabolic impairment (prediabetes and DM). A two-way ANCOVA revealed no synergistic, but an additive effect of AD and DM on clusterin. Clusterin was negatively correlated with cognitive scores. It was also associated with metabolic status indicated by glycated hemoglobin A1c (HbA1c), the Homeostatic Model Assessment for Insulin Resistance index, and fasting C-peptide. It showed correlations between medial temporal atrophy and periventricular white matter lesions, indicating neurodegeneration and microvascular insufficiency, respectively. Further mediation analysis to understand the triadic relationship between clusterin, AD, and DM revealed that the association between DM and AD was significant when clusterin is considered as a mediator of their relationship.

CONCLUSIONS

Clusterin is a promising biomarker of DM as well as of AD. Additionally, our data suggest that clusterin may have a role in linking DM with AD as a potential mediator.

Early Stage Glycosylation Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) is of great cause for concern in our ageing population, which currently lacks diagnostic tools to permit accurate and timely diagnosis for affected individuals. The development of such tools could enable therapeutic interventions earlier in the disease course and thus potentially reducing the debilitating effects of AD. Glycosylation is a common, and important, post translational modification of proteins implicated in a host of disease states resulting in a complex array of glycans being incorporated into biomolecules. Recent investigations of glycan profiles, in a wide range of conditions, has been made possible due to technological advances in the field enabling accurate glycoanalyses. Amyloid beta (Aβ) peptides, tau protein, and other important proteins involved in AD pathogenesis, have altered glycosylation profiles. Crucially, these abnormalities present early in the disease state, are present in the peripheral blood, and help to distinguish AD from other dementias. This review describes the aberrant glycome in AD, focusing on proteins implicated in development and progression, and elucidates the potential of glycome aberrations as early stage biomarkers of AD.

Blood biomarkers in Alzheimer's disease

INTRODUCTION

The early diagnosis of Alzheimer's disease (AD) via the use of biomarkers could facilitate the implementation and monitoring of early therapeutic interventions with the potential capacity to significantly modify the course of the disease.

DEVELOPMENT

Classic cerebrospinal fluid biomarkers and approved structural and functional neuroimaging have a limited clinical application given their invasive nature and/or high cost. The identification of more accessible and less costly biomarkers, such as blood biomarkers, would facilitate application in clinical practice. We present a literature review of the main blood biochemical biomarkers with potential use for diagnosing Alzheimer's disease.

CONCLUSIONS

Blood biomarkers are cost and time effective with regard to cerebrospinal fluid biomarkers. However, the immediate applicability of blood biochemical biomarkers in clinical practice is not very likely. The main limitations come from the difficulties in measuring and standardising thresholds between different laboratories and in failures to replicate results. Among all the molecules studied, apoptosis and neurodegeneration biomarkers and the biomarker panels obtained through omics approaches, such as isolated or combined metabolomics, offer the most promising results.

Blood DNA methylation as a potential biomarker of dementia: A systematic review

Dementia is a major public health issue with rising prevalence rates, but many individuals remain undiagnosed. Accurate and timely diagnosis is key for the optimal targeting of interventions. A noninvasive, easily measurable peripheral biomarker would have greatest utility in population-wide diagnostic screening. Epigenetics, including DNA methylation, is implicated in dementia; however, it is unclear whether epigenetic changes can be detected in peripheral tissue. This study aimed to systematically review the evidence for an association between dementia and peripheral DNA methylation. Forty-eight studies that measured DNA methylation in peripheral blood were identified, and 67% reported significant associations with dementia. However, most studies were underpowered and limited by their case-control design. We emphasize the need for future longitudinal studies on large well-characterized populations, measuring epigenetic patterns in asymptomatic individuals. A biomarker detectable in the preclinical stages of the disease would have the greatest utility in future intervention and treatment trials.

Study protocol of the Intense Physical Activity and Cognition study: The effect of high-intensity exercise training on cognitive function in older adults

Introduction

Inconsistent results from previous studies of exercise and cognitive function suggest that rigorously designed randomized controlled trials are urgently needed. Here, we describe the design of the Intense Physical Activity and Cognition (IPAC) study, which will assess the impact of a 6-month high-intensity exercise intervention on cognitive function and biomarkers of dementia risk, compared with a 6-month moderate-intensity exercise intervention and control group (no study-related exercise).

Methods

One-hundred and five cognitively healthy men and women aged between 60 and 80 years are randomized into a high-intensity exercise, moderate-intensity exercise, or control group. Individuals randomized to an exercise intervention undertake 6 months of cycle-based exercise twice a week, at 50 minutes per session. All participants undergo comprehensive neuropsychological testing, blood sampling, brain magnetic resonance imaging, fitness testing, and a body composition scan at baseline, 6 months (immediately after intervention), and 18 months (12 months after intervention).

Discussion

The IPAC study takes a multidisciplinary approach to investigating the role of exercise in maintaining a healthy brain throughout aging. Rigorous monitoring of exertion and adherence throughout the intervention, combined with repeated measures of fitness, is vital in ensuring an optimum exercise dose is reached. Results from the IPAC study will be used to inform a large-scale multicentre randomized controlled trial, with the ultimate aim of pinpointing the frequency, duration, and intensity of exercise that provides the most benefit to the brain, in terms of enhancing cognitive function and reducing dementia risk in older adults.