A Review on MS-Based Blood Biomarkers for Alzheimer's Disease

An integrated paper-based microfluidic platform for screening of early-stage Alzheimer's disease by detecting Aβ42

Alzheimer's disease (AD) is the leading cause of dementia worldwide, and the development of early screening methods can address its significant health and social consequences. In this paper, we present a rotary-valve assisted paper-based immunoassay device (RAPID) for early screening of AD, featuring a highly integrated on-chip rotary micro-valve that enables fully automated and efficient detection of the AD biomarker (amyloid beta 42, Aβ42) in artificial plasma. The microfluidic paper-based analytical device (μPAD) of the RAPID pre-stores the required assay reagents on a μPAD and automatically controls the liquid flow through a single valve. Once the test sample is added, the test reagents are sequentially transferred to the test area in the order set by the enzyme-linked immunosorbent assay (ELISA) protocol. In addition, the RAPID can remotely control the operation of the μPAD valve via a micro-servomotor, quantify the signals generated, display the results, and wirelessly transmit the data to a smartphone. To calibrate the RAPID, we performed a sandwich ELISA for Aβ42 in artificial plasma, and obtained a low limit of detection (LOD) of 9.6 pg mL-1, a coefficient of determination (COD) of 0.994, and an individual assay time of ∼30 minutes. In addition, we simulated 24 artificial samples to quantify Aβ42 protein concentrations in artificial plasma samples. The results show good consistency between the conventional ELISA and RAPID detection. The experimental results demonstrate that the RAPID is expected to promote further popularization of the screening of early-stage AD.

Soluble markers of viral rebound and post-treatment HIV control

PURPOSE OF REVIEW

We focus on the different classes of biological molecules measurable in easily accessible bodily fluids that have the potential to serve as biomarkers for the HIV post-treatment controller (PTC) phenotype and/or the timing of viral rebound after stopping antiretroviral therapy (ART).

RECENT FINDINGS

Various viral components and host factors measurable in body fluids can play crucial roles in understanding and predicting the PTC phenotype. We review recent findings linking viral components, the quantitative and qualitative features of antibodies (including autologous HIV-specific antibodies), markers of inflammation and tissue damage, other host proteins (including hormones such as sex hormones), as well as metabolites, extracellular vesicles, and cell-free DNA to HIV control post-ART interruption. Several of these molecules can or have the potential to predict the time and probability of viral rebound after stopping ART and are biologically active molecules that can directly or indirectly (by modulating immune pressures) impact the size and activity of HIV reservoirs during and post-ART interruption.

SUMMARY

A comprehensive model combining multiple markers is needed to predict the PTC phenotype. This model can be leveraged to predict and understand the PTC phenotype, which can guide novel curative interventions to replicate this phenotype in post-treatment non-controllers.

Effects of xylo-oligosaccharide on gut microbiota, brain protein expression, and lipid profile induced by high-fat diet

Midlife overweight and obesity are risk factors of cognitive decline and Alzheimer' s disease (AD) in late life. In addition to increasing risk of obesity and cognitive dysfunction, diets rich in fats also contributes to an imbalance of gut microbiota. Xylo-oligosaccharides (XOS) are a kind of prebiotic with several biological advantages, and can selectively promote the growth of beneficial microorganisms in the gut. To explore whether XOS can alleviate cognitive decline induced by high-fat diet (HFD) through improving gut microbiota composition, mice were fed with normal control or 60% HFD for 9 weeks to induce obesity. After that, mice were supplemented with XOS (30 g or 60 g/kg-diet) or without, respectively, for 12 weeks. The results showed that XOS inhibited weight gain, decreased epidydimal fat weight, and improved fasting blood sugar and blood lipids in mice. Additionally, XOS elevated spatial learning and memory function, decreased amyloid plaques accumulation, increased brain-derived neurotrophic factor levels, and improved neuroinflammation status in hippocampus. Changes in glycerolipids metabolism-associated lipid compounds caused by HFD in hippocampus were reversed after XOS intervention. On the other hand, after XOS intervention, increase in immune-mediated bacteria, Faecalibacterium was observed. In conclusion, XOS improved gut dysbiosis and ameliorated spatial learning and memory dysfunction caused by HFD by decreasing cognitive decline-associated biomarkers and changing lipid composition in hippocampus.

Dysregulation of Lipid Metabolism Serves as A Link Between Alzheimer's and Cardiovascular Disease, As Witnessed in A Cross-Sectional Study

Cardiovascular risk factors and established cardiovascular disease (CVD) increase the risk of suffering dementia of the Alzheimer's type (DAT). Here, we set out to define specific molecular profiles of CVD in patients with DAT to better understand its relationship, to unravel the mechanisms underlying the high risk of developing DAT in CVD patients and to define new markers of early disease. Plasma samples from patients with DAT, with and without CVD, were analyzed through a multiomics approach, with integration of metabolomics and proteomics datasets using the OmicsNet web-based tool. Metabolomics results showed an enrichment in lipids and lipid-like molecules. Similarly, the most significant cluster identified through proteomics was formed by 5 proteins related to lipoprotein and cholesterol metabolism. After integration and functional enrichment, glycerolipid metabolism, fatty acid degradation and sphingolipid metabolism were among the most significant functions. Finally, the differential expression of ABCA1 and APOH proteins was verified, in an independent cohort also including controls and patients with CVD alone. Both proteins positively correlated with phospho-Tau (181), a classical hallmark of DAT. Different molecular profiles exist in patients with DAT, with and without CVD, with exacerbated alterations in patients in which DAT and CVD co-exist. This information may help to define biomarkers like ABCA1 and APOH that identify patients with cardiovascular dysfunction that are at high risk of developing DAT. Such markers will allow more personalized interventions to be selected, a further step towards precision medicine for individuals whose molecular profiles indicate a distinct response to the same management strategies.

A critical appraisal of blood-based biomarkers for Alzheimer's disease

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

Association between Alzheimer's disease, MAPT gene mutation and some biochemical biomarkers

Alzheimer's Disease (AD) is a multifactorial neurodegenerative disease and there is still no definitive treatment today. Early diagnosis of the disease is important, but there are almost no biomarkers that can be used in early diagnosis. The cerebrospinal fluid used in the diagnosis of the disease is not sufficient and is very difficult to obtain. Therefore, blood biomarkers that are less costly, less invasive, easily accessible, and can be used in long-term studies would be a better alternative. The aim of this study is to determine the relationship between Alzheimer's Disease and P301L MAPT gene mutation, homocysteine, folate and uric acid. 101 Alzheimer's patients and 101 healthy individuals were included in this study. Mutation analysis was performed using the Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) method with blood samples taken from the subjects. There was no significant difference between the patient and control groups in terms of homocysteine (p = 0.771), folate (p = 0.366) and uric acid (p = 0.860). When the genotypes were compared between the patient and control groups in terms of MAPT gene mutation (P301L), no statistically significant difference was detected (p = 0.081). There are very few studies in the literature investigating the relationship between Alzheimer's disease and P301L MAPT gene mutation. Additionally, there is no study investigating the relationship between Alzheimer's disease and homocysteine, folate, uric acid and P301L MAPT mutation in the Turkish population. We believe that this study has shed light on future studies.

Targeted protein quantitation in human body fluids by mass spectrometry

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

The Role of Steroidomics in the Diagnosis of Alzheimer's Disease and Type 2 Diabetes Mellitus

Epidemiological studies suggest an association between Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM). This study aimed to investigate the pathophysiological markers of AD vs. T2DM for each sex separately and propose models that would distinguish control, AD, T2DM, and AD-T2DM comorbidity groups. AD and T2DM differed in levels of some circulating steroids (measured mostly by GC-MS) and in other observed characteristics, such as markers of obesity, glucose metabolism, and liver function tests. Regarding steroid metabolism, AD patients (both sexes) had significantly higher sex hormone binding globulin (SHBG), cortisol, and 17-hydroxy progesterone, and lower estradiol and 5α-androstane-3α,17β-diol, compared to T2DM patients. However, compared to healthy controls, changes in the steroid spectrum (especially increases in levels of steroids from the C21 group, including their 5α/β-reduced forms, androstenedione, etc.) were similar in patients with AD and patients with T2DM, though more expressed in diabetics. It can be assumed that many of these steroids are involved in counter-regulatory protective mechanisms that mitigate the development and progression of AD and T2DM. In conclusion, our results demonstrated the ability to effectively differentiate AD, T2DM, and controls in both men and women, distinguish the two pathologies from each other, and differentiate patients with AD and T2DM comorbidities.

Advances and applications of fluids biomarkers in diagnosis and therapeutic targets of Alzheimer's disease

AIMS

Alzheimer's disease (AD) is a neurodegenerative disease with challenging early diagnosis and effective treatments due to its complex pathogenesis. AD patients are often diagnosed after the appearance of the typical symptoms, thereby delaying the best opportunity for effective measures. Biomarkers could be the key to resolving the challenge. This review aims to provide an overview of application and potential value of AD biomarkers in fluids, including cerebrospinal fluid, blood, and saliva, in diagnosis and treatment.

METHODS

A comprehensive search of the relevant literature was conducted to summarize potential biomarkers for AD in fluids. The paper further explored the biomarkers' utility in disease diagnosis and drug target development.

RESULTS

Research on biomarkers mainly focused on amyloid-β (Aβ) plaques, Tau protein abnormal phosphorylation, axon damage, synaptic dysfunction, inflammation, and related hypotheses associated with AD mechanisms. Aβ₄₂ , total Tau (t-Tau), and phosphorylated Tau (p-Tau), have been endorsed for their diagnostic and predictive capability. However, other biomarkers remain controversial. Drugs targeting Aβ have shown some efficacy and those that target BACE1 and Tau are still undergoing development.

CONCLUSION

Fluid biomarkers hold considerable potential in the diagnosis and drug development of AD. However, improvements in sensitivity and specificity, and approaches for managing sample impurities, need to be addressed for better diagnosis.

Comparison of ultrasensitive and mass spectrometry quantification of blood-based amyloid biomarkers for Alzheimer's disease diagnosis in a memory clinic cohort

BACKGROUND

Alzheimer's disease (AD) is a complex neurodegenerative disorder with β-amyloid pathology as a key underlying process. The relevance of cerebrospinal fluid (CSF) and brain imaging biomarkers is validated in clinical practice for early diagnosis. Yet, their cost and perceived invasiveness are a limitation for large-scale implementation. Based on positive amyloid profiles, blood-based biomarkers should allow to detect people at risk for AD and to monitor patients under therapeutics strategies. Thanks to the recent development of innovative proteomic tools, the sensibility and specificity of blood biomarkers have been considerably improved. However, their diagnosis and prognosis relevance for daily clinical practice is still incomplete.

METHODS

The Plasmaboost study included 184 participants from the Montpellier's hospital NeuroCognition Biobank with AD (n = 73), mild cognitive impairments (MCI) (n = 32), subjective cognitive impairments (SCI) (n = 12), other neurodegenerative diseases (NDD) (n = 31), and other neurological disorders (OND) (n = 36). Dosage of β-amyloid biomarkers was performed on plasma samples using immunoprecipitation-mass spectrometry (IPMS) developed by Shimadzu (IPMS-Shim Aβ₄₂, Aβ₄₀, APP_669-711) and Simoa Human Neurology 3-PLEX A assay (Aβ₄₂, Aβ₄₀, t-tau). Links between those biomarkers and demographical and clinical data and CSF AD biomarkers were investigated. Performances of the two technologies to discriminate clinically or biologically based (using the AT(N) framework) diagnosis of AD were compared using receiver operating characteristic (ROC) analyses.

RESULTS

The amyloid IPMS-Shim composite biomarker (combining APP_669-711/Aβ₄₂ and Aβ₄₀/Aβ₄₂ ratios) discriminated AD from SCI (AUC: 0.91), OND (0.89), and NDD (0.81). The IPMS-Shim Aβ_42/40 ratio also discriminated AD from MCI (0.78). IPMS-Shim biomarkers have similar relevance to discriminate between amyloid-positive and amyloid-negative individuals (0.73 and 0.76 respectively) and A-T-N-/A+T+N+ profiles (0.83 and 0.85). Performances of the Simoa 3-PLEX Aβ_42/40 ratio were more modest. Pilot longitudinal analysis on the progression of plasma biomarkers indicates that IPMS-Shim can detect the decrease in plasma Aβ₄₂ that is specific to AD patients.

CONCLUSIONS

Our study confirms the potential usefulness of amyloid plasma biomarkers, especially the IPMS-Shim technology, as a screening tool for early AD patients.

Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine.

METHODS

Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort.

RESULTS

Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients.

DISCUSSION

These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.

Relevance of plasma biomarkers to pathologies in Alzheimer's disease, Parkinson's disease and frontotemporal dementia

Amyloid plaques and tau tangles are pathological hallmarks of Alzheimer's disease (AD). Parkinson's disease (PD) results from the accumulation of α-synuclein. TAR DNA-binding protein (TDP-43) and total tau protein (T-Tau) play roles in FTD pathology. All of the pathological evidence was found in the biopsy. However, it is impossible to perform stein examinations in clinical practice. Assays of biomarkers in plasma would be convenient. It would be better to investigate the combinations of various biomarkers in AD, PD and FTD. Ninety-one subjects without neurodegenerative diseases, 76 patients with amnesic mild cognitive impairment (aMCI) or AD dementia, combined as AD family, were enrolled. One hundred and nine PD patients with normal cognition (PD-NC) or dementia (PDD), combined as PD family, were enrolled. Twenty-five FTD patients were enrolled for assays of plasma amyloid β 1-40 (Aβ_1-40), Aβ_1-42, T-Tau, α-synuclein and TDP-43 using immunomagnetic reduction (IMR). The results show that Aβs and T-Tau are major domains in AD family. α-synuclein is highly dominant in PD family. FTD is closely associated with TDP-43 and T-Tau. The dominant plasma biomarkers in AD family, PD family and FTD are consistent with pathology. This implies that plasma biomarkers are promising for precise and differential assessments of AD, PD and FTD in clinical practice.

Quantitative NMR-Based Lipoprotein Analysis Identifies Elevated HDL-4 and Triglycerides in the Serum of Alzheimer’s Disease Patients

Alzheimer’s disease (AD) is the most common form of dementia in the elderly and has been associated with changes in lipoprotein metabolism. We performed quantitative lipoprotein analysis in a local cohort of cognitively impaired elderly and control subjects using standardized nuclear magnetic resonance (NMR) spectroscopy. A commercially available quantitative NMR-based assay covering 112 lipoprotein main and subtype variables was used to investigate blood serum samples from a moderate cohort size of 161 persons (71 female, 90 male), including measures of quality control. Additionally, clinical metadata and cerebrospinal fluid AD biomarkers were collected and used for analysis. High-density lipoprotein (HDL) HDL-4 subfraction levels were mostly high in female individuals with mild cognitive impairment (MCI), followed by AD. Low-density lipoprotein (LDL) LDL-2 cholesterol was slightly elevated in male AD patients. HDL-2 apolipoprotein Apo-A1, HDL-2 phospholipids, and HDL-3 triglycerides were highly abundant in AD and MCI women compared to men. When considering clinical biomarkers (Aβ, tau), very low-density lipoprotein (VLDL) VLDL-1 and intermediate-density lipoprotein (IDL) triglycerides were substantially higher in AD compared to MCI. In addition, triglyceride levels correlated positively with dementia. Different lipoprotein serum patterns were identified for AD, MCI, and control subjects. Interestingly, HDL-4 and LDL-2 cholesterol parameters revealed strong gender-specific changes in the context of AD-driven dementia. As gender-based comparisons were based on smaller sub-groups with a low n-number, several statistical findings did not meet the significance threshold for multiple comparisons testing. Still, our finding suggests that serum HDL-4 parameters and various triglycerides correlate positively with AD pathology which could be a read-out of extended lipids traveling through the blood-brain barrier, supporting amyloid plaque formation processes. Thereof, we see herein a proof of concept that this quantitative NMR-based lipoprotein assay can generate important and highly interesting data for refined AD diagnosis and patient stratification, especially when larger cohorts are available.

Viral and Host Biomarkers of HIV Remission Post Treatment Interruption

PURPOSE OF REVIEW

HIV rebound/remission after antiretroviral therapy (ART) interruption is likely influenced by (a) the size of the inducible replication-competent HIV reservoir and (b) factors in the host environment that influence immunological pressures on this reservoir. Identifying viral and/or host biomarkers of HIV rebound after ART cessation may improve the safety of treatment interruptions and our understanding of how the viral-host interplay results in post-treatment control. Here we review the predictive and functional significance of recently suggested viral and host biomarkers of time to viral rebound and post-treatment control following ART interruption.

RECENT FINDINGS

There are currently no validated viral or host biomarkers of viral rebound; however, several biomarkers have been recently suggested. A combination of viral and host factors will likely be needed to predict viral rebound and to better understand the mechanisms contributing to post-treatment control of HIV, critical steps to developing a cure for HIV infection.

Differential diagnostic performance of a panel of plasma biomarkers for different types of dementia

Introduction

We explored what combination of blood‐based biomarkers (amyloid beta [Aβ]_{1‐42/1‐40}, phosphorylated tau [p‐tau]181, neurofilament light [NfL], glial fibrillary acidic protein [GFAP]) differentiates Alzheimer's disease (AD) dementia, frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB).

Methods

We measured the biomarkers with Simoa in two separate cohorts (n = 160 and n = 152). In one cohort, Aβ_{1‐42/1‐40} was also measured with mass spectrometry (MS). We assessed the differential diagnostic value of the markers, by logistic regression with Wald's backward selection.

Results

MS and Simoa Aβ_{1‐42/1‐40} similarly differentiated AD from controls. The Simoa panel that optimally differentiated AD from FTD consisted of NfL and p‐tau181 (area under the curve [AUC] = 0.94; cohort 1) or NfL, GFAP, and p‐tau181 (AUC = 0.90; cohort 2). For AD from DLB, the panel consisted of NfL, p‐tau181, and GFAP (AUC = 0.88; cohort 1), and only p‐tau181 (AUC = 0.81; cohort 2).

Discussion

A combination of plasma p‐tau181, NfL, and GFAP, but not Aβ_{1‐42/1‐40}, might be useful to discriminate AD, FTD, and DLB.

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

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

Novel Exosome Biomarker Candidates for Alzheimer's Disease Unravelled Through Mass Spectrometry Analysis

Exosomes are small extracellular vesicles (EVs) present in human biofluids that can transport specific disease-associated molecules. Consequently blood-derived exosomes have emerged as important peripheral biomarker sources for a wide range of diseases, among them Alzheimer’s disease (AD). Although there is no effective cure for AD, an accurate diagnosis, relying on easily accessible peripheral biofluids, is still necessary to discriminate this disease from other dementias, test potential therapies and even monitor rate of disease progression. The ultimate goal is to produce a cost-effective and widely available alternative, which can also be employed as a first clinical screen. In this study, EVs with exosome-like characteristics were isolated from serum of Controls and AD cases through precipitation- and column-based methods, followed by mass spectrometry analysis. The resulting proteomes were characterized by Gene Ontology (GO) and multivariate analyses. Although GO terms were similar for exosomes’ proteomes of Controls and ADs, using both methodologies, a clear segregation of disease cases was obtained when using the precipitation-based method. Nine significantly different abundant proteins were identified between Controls and AD cases, representing putative biomarker candidate targets. Among them are AACT and C4BPα, two Aβ-binding proteins, whose exosome levels were further validated in individuals from independent cohorts using antibody-based approaches. The findings discussed represent an important contribution to the identification of novel exosomal biomarker candidates useful as potential blood-based tools for AD diagnosis.

Mass Spectrometry Based Protein Biomarkers and Drug Target Discovery and Clinical Diagnosis in Age-Related Progressing Neurodegenerative Diseases

Neurodegenerative diseases correspond to overly complex health disorders that are driven by intersecting pathophysiology that are often trapped in vicious cycles of degeneration and cognitive decline. The usual diagnostic route of these diseases is based on postmortem examination that involves identifying pathology that is specific to the disease in the brain. However, in such cases, accurate diagnosis of the specific disease is limited because clinical disease presentations are often complex that do not easily allow to discriminate patient's cognitive, behavioral, and functional impairment profiles. Additionally, an early identification and therapeutic intervention of these diseases is pivotal to slow the progression of neurodegeneration and extend healthy life span. Mass spectrometry-based techniques have proven to be hugely promising in biological sample analysis and discovery of biomarkers including protein and peptide biomarkers for potential drug target discovery. Recent studies on these biomarkers have demonstrated their potential for applications in early diagnostics and identifying therapeutic targets to battle against neurodegenerative diseases. In this review, we have presented principles of mass spectrometry (MS) and the associated workflows in analyzing and imaging biological samples for discovery of biomarkers. We have especially focused on age- related progressing neurodegenerative diseases such as Alzheimer's (AD) and Parkinson's disease (PD), Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal dementia (FTD) and the related MS-based biomarkers developments for these diseases. Finally, we present a future perspective discussing the potential research directions ahead.

Differential Expression of miR-381-3p in Alzheimer's Disease Patients and Its Role in Beta-Amyloid-Induced Neurotoxicity and Inflammation

INTRODUCTION

This study aimed to explore the diagnostic value and effect of miR-381-3p on Alzheimer's disease (AD).

METHODS

RT-qPCR was used for the measurement of miR-381-3p levels. Pearson correlation coefficient was used for the correlation analysis. Receiver operating characteristic (ROC) curve was constructed to assess the distinct ability of miR-381-3p for AD. SH-SY5Y cells were treated with Aβ25-35 to establish an AD cell model. The role of miR-381-3p on cell proliferation and apoptosis was detected. ELISA was applied to detect the protein levels of inflammatory cytokine expression. The target relationship of miR-381-3p with PTGS2 was verified by luciferase reporter gene assay.

RESULTS

Low expression of miR-381-3p was detected in the serum of AD patients and cell models. There was a negative association of serum miR-381-3p with the serum inflammatory cytokines. The ROC curve demonstrated the distinct ability of serum miR-381-3p for AD, with the AUC value of 0.898, with a sensitivity of 87.5%, and a specificity of 77.7%. Overexpression of miR-381-3p reversed the influence of Aβ25-35 on cell proliferation and apoptosis, but miR-381-3p downregulation exacerbated the influence. miR-381-3p overexpression inhibited the release of IL-6, IL-1β, and TNF-α induced by Aβ25-35 treatment, whereas miR-381-3p downregulation further promoted the release of inflammatory cytokines. PTGS2 was the target gene of miR-381-3p and was upregulated in AD cell models.

CONCLUSION

miR-381-3p is less expressed in the serum of AD patients and has potential diagnostic values for AD. Overexpression of miR-381-3p may attenuate Aβ25-35-induced neurotoxicity and inflammatory responses via targeting PTGS2 in SH-SY5Y cells.

Development of molecular tools for diagnosis of Alzheimer's disease that are based on detection of amyloidogenic proteins

Alzheimer's disease (AD) is the most common form of dementia that usually occurs among older people. AD results from neuronal degeneration that leads to the cognitive impairment and death. AD is incurable, typically develops over the course of many years and is accompanied by a loss of functional autonomy, making a patient completely dependent on family members and/or healthcare workers. Critical features of AD are pathological polymerization of Aβ peptide and microtubule-associated protein tau, accompanied by alterations of their conformations and resulting in accumulation of cross-β fibrils (amyloids) in human brains. AD apparently progresses asymptomatically for years or even decades before the appearance of symptoms. Therefore, development of the early AD diagnosis at a pre-symptomatic stage is essential for potential therapies. This review is focused on current and potential molecular tools (including non-invasive methods) that are based on detection of amyloidogenic proteins and can be applicable to early diagnosis of AD.Abbreviations: Aβ - amyloid-β peptide; AβO - amyloid-β oligomers; AD - Alzheimer's disease; ADRDA - Alzheimer's Disease and Related Disorders Association; APH1 - anterior pharynx defective 1; APP - amyloid precursor protein; BACE1 - β-site APP-cleaving enzyme 1; BBB - brain blood barrier; CJD - Creutzfeldt-Jakob disease; CRM - certified reference material; CSF - cerebrospinal fluid; ELISA - enzyme-linked immunosorbent assay; FGD - 18F-fluorodesoxyglucose (2-deoxy-2-[18F]fluoro-D-glucose); IP-MS - immunoprecipitation-mass spectrometry assay; MCI - mild cognitive impairment; MDS - multimer detection system; MRI - magnetic resonance imaging; NIA-AA - National Institute on Ageing and Alzheimer's Association; NINCDS - National Institute of Neurological and Communicative Disorders and Stroke; PEN2 - presenilin enhancer 2; PET - positron emission tomography; PiB - Pittsburgh Compound B; PiB-SUVR - PIB standardized uptake value ratio; PMCA - Protein Misfolding Cycling Amplification; PrP - Prion Protein; P-tau - hyperphosphorylated tau protein; RMP - reference measurement procedure; RT-QuIC - real-time quaking-induced conversion; SiMoA - single-molecule array; ThT - thioflavin T; TSEs - Transmissible Spongiform Encephslopathies; T-tau - total tau protein.

Alterations in Glycerolipid and Fatty Acid Metabolic Pathways in Alzheimer's Disease Identified by Urinary Metabolic Profiling: A Pilot Study

An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) is needed. Evidence suggests that metabolic dysfunction underlies the pathophysiology of AD. While urine is a non-invasively collectable biofluid and a good source for metabolomics analysis, it is not yet widely used for this purpose. This small-scale pilot study aimed to examine whether the metabolic profile of urine from AD patients reflects the metabolic dysfunction reported to underlie AD pathology, and to identify metabolites that could distinguish AD patients from cognitively healthy controls. Spot urine of 18 AD patients (AD group) and 18 age- and sex-matched, cognitively normal controls (control group) were analyzed by mass spectrometry (MS). Capillary electrophoresis time-of-flight MS and liquid chromatography–Fourier transform MS were used to cover a larger range of molecules with ionic as well as lipid characteristics. A total of 304 ionic molecules and 81 lipid compounds of 12 lipid classes were identified. Of these, 26 molecules showed significantly different relative concentrations between the AD and control groups (Wilcoxon's rank-sum test). Moreover, orthogonal partial least-squares discriminant analysis revealed significant discrimination between the two groups. Pathway searches using the KEGG database, and pathway enrichment and topology analysis using Metaboanalyst software, suggested alterations in molecules relevant to pathways of glycerolipid and glycerophospholipid metabolism, thermogenesis, and caffeine metabolism in AD patients. Further studies of urinary metabolites will contribute to the early detection of AD and understanding of its pathogenesis.

Association Between Plasma Amyloid-β and Neuropsychological Performance in Patients With Cognitive Decline

Objective: To investigate the association between plasma amyloid-β (Aβ) levels and neuropsychological performance in patients with cognitive decline using a highly sensitive nano-biosensing platform.

Methods: We prospectively recruited 44 patients with cognitive decline who underwent plasma Aβ analysis, amyloid positron emission tomography (PET) scanning, and detailed neuropsychological tests. Patients were classified into a normal control (NC, n = 25) or Alzheimer’s disease (AD, n = 19) group based on amyloid PET positivity. Multiple linear regression was performed to determine whether plasma Aβ (Aβ₄₀, Aβ₄₂, and Aβ_42/40) levels were associated with neuropsychological test results.

Results: The plasma levels of Aβ_42/40 were significantly different between the NC and AD groups and were the best predictor of amyloid PET positivity by receiver operating characteristic curve analysis [area under the curve of 0.952 (95% confidence interval, 0.892–1.000)]. Although there were significant differences in the neuropsychological performance of cognitive domains (language, visuospatial, verbal/visual memory, and frontal/executive functions) between the NC and AD groups, higher levels of plasma Aβ_42/40 were negatively correlated only with verbal and visual memory performance.

Conclusion: Our results demonstrated that plasma Aβ analysis using a nano-biosensing platform could be a useful tool for diagnosing AD and assessing memory performance in patients with cognitive decline.

Comparison of proteomic approaches used for the detection of potential biomarkers of Alzheimer's disease in blood plasma

At present, Alzheimer's disease is detected mainly using psychological tests, which can only confirm the disease in its more advanced phases. Therefore, bioanalytical possibilities for detecting this disease earlier are being investigated. To date, the results of analyses, which focus mainly on the study of lipids and proteins either in cerebrospinal fluid or much less often in blood plasma, do not provide satisfactory results. In addition, cerebrospinal fluid sampling is uncomfortable for the patients and involves many health risks. In this work, we deal with proteomic analysis using Matrix-Assisted Laser Desorption/Ionisation-Time of Flight and Liquid Chromatography coupled to tandem Mass Spectrometry of blood plasma with a focus on various ways of preanalytical sample treatments. This should lead to results improvement and facilitate the subsequent evaluation using principal component analysis and partial least squares discriminant analysis. The obtained results indicate the direction of further research, namely the study of interactions between proteins and lipids contained in blood plasma. These substances may be regarded as potential biomarkers allowing for the diagnosis of Alzheimer´s disease even in its early stages.

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

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

Non-invasive plasma glycomic and metabolic biomarkers of post-treatment control of HIV

Non-invasive biomarkers that predict HIV remission after antiretroviral therapy (ART) interruption are urgently needed. Such biomarkers can improve the safety of analytic treatment interruption (ATI) and provide mechanistic insights into the host pathways involved in post-ART HIV control. Here we report plasma glycomic and metabolic signatures of time-to-viral-rebound and probability-of-viral-remission using samples from two independent cohorts. These samples include a large number of post-treatment controllers, a rare population demonstrating sustained virologic suppression after ART-cessation. These signatures remain significant after adjusting for key demographic and clinical confounders. We also report mechanistic links between some of these biomarkers and HIV latency reactivation and/or myeloid inflammation in vitro. Finally, machine learning algorithms, based on selected sets of these biomarkers, predict time-to-viral-rebound with 74% capacity and probability-of-viral-remission with 97.5% capacity. In summary, we report non-invasive plasma biomarkers, with potential functional significance, that predict both the duration and probability of HIV remission after treatment interruption.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The NLRP3 inflammasome inhibitor OLT1177 rescues cognitive impairment in a mouse model of Alzheimer's disease

Numerous studies demonstrate that neuroinflammation is a key player in the progression of Alzheimer's disease (AD). Interleukin (IL)-1β is a main inducer of inflammation and therefore a prime target for therapeutic options. The inactive IL-1β precursor requires processing by the the nucleotide-binding oligomerization domain-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome into a mature and active form. Studies have shown that IL-1β is up-regulated in brains of patients with AD, and that genetic inactivation of the NLRP3 inflammasome improves behavioral tests and synaptic plasticity phenotypes in a murine model of the disease. In the present study, we analyzed the effect of pharmacological inhibition of the NLRP3 inflammasome using dapansutrile (OLT1177), an oral NLRP3-specific inhibitor that is safe in humans. Six-month-old WT and APP/PS1 mice were fed with standard mouse chow or OLT1177-enriched chow for 3 mo. The Morris water maze test revealed an impaired learning and memory ability of 9-mo-old APP/PS1 mice (P = 0.001), which was completely rescued by OLT1177 fed to mice (P = 0.008 to untreated APP/PS1). Furthermore, our findings revealed that 3 mo of OLT1177 diet can rescue synaptic plasticity in this mouse model of AD (P = 0.007 to untreated APP/PS1). In addition, microglia were less activated (P = 0.07) and the number of plaques was reduced in the cortex (P = 0.03) following NLRP3 inhibition with OLT1177 administration. We also observed an OLT1177 dose-dependent normalization of plasma metabolic markers of AD to those of WT mice. This study suggests the therapeutic potential of treating neuroinflammation with an oral inhibitor of the NLRP3 inflammasome.

Serum Metabolomics Profiling of Commercially Mixed Functional Foods—Effects in Beta-Amyloid Induced Rats Measured Using 1H NMR Spectroscopy

Functional foods such as pomegranate, dates and honey were shown by various previous studies to individually have a neuroprotective effect, especially in neurodegenerative disease such as Alzheimer’s disease (AD). In this novel and original study, an ¹H NMR spectroscopy tool was used to identify the metabolic neuroprotective mechanism of commercially mixed functional foods (MFF) consisting of pomegranate, dates and honey, in rats injected with amyloid-beta 1-42 (Aβ-42). Forty-five male albino Wistar rats were randomly divided into five groups: NC (0.9% normal saline treatment + phosphate buffer solution (PBS) solution injection), Abeta (0.9% normal saline treatment + 0.2 µg/µL Aβ-42 injection), MFF (4 mL/kg MFF treatment + PBS solution injection), Abeta–MFF (4 mL/kg MFF treatment + 0.2 µg/µL Aβ-42 injection) and Abeta–NAC (150 mg/kg N-acetylcysteine + 0.2 µg/µL Aβ-42 injection). Based on the results, the MFF and NAC treatment improved the spatial memory and learning using Y-maze. In the metabolic analysis, a total of 12 metabolites were identified, for which levels changed significantly among the treatment groups. Systematic metabolic pathway analysis found that the MFF and NAC treatments provided a neuroprotective effect in Aβ-42 injected rats by improving the acid amino and energy metabolisms. Overall, this finding showed that MFF might serve as a potential neuroprotective functional food for the prevention of AD.

A Community-Based Study Identifying Metabolic Biomarkers of Mild Cognitive Impairment and Alzheimer's Disease Using Artificial Intelligence and Machine Learning

BACKGROUND

Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess disease severity, and prognosticate course. Metabolomics is a promising tool for discovery of new, biologically, and clinically relevant biomarkers for AD detection and classification.

OBJECTIVE

Utilizing artificial intelligence and machine learning, we aim to assess whether a panel of metabolites as detected in plasma can be used as an objective and clinically feasible tool for the diagnosis of mild cognitive impairment (MCI) and AD.

METHODS

Using a community-based sample cohort acquired from different sites across the US, we adopted an approach combining Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR), Liquid Chromatography coupled with Mass Spectrometry (LC-MS) and various machine learning statistical approaches to identify a biomarker panel capable of identifying those patients with AD and MCI from healthy controls.

RESULTS

Of the 212 measured metabolites, 5 were identified as optimal to discriminate between controls, and individuals with MCI or AD. Our models performed with AUC values in the range of 0.72-0.76, with the sensitivity and specificity values ranging from 0.75-0.85 and 0.69-0.81, respectively. Univariate and pathway analysis identified lipid metabolism as the most perturbed biochemical pathway in MCI and AD.

CONCLUSION

A comprehensive method of acquiring metabolomics data, coupled with machine learning techniques, has identified a strong panel of diagnostic biomarkers capable of identifying individuals with MCI and AD. Further, our data confirm what other groups have reported, that lipid metabolism is significantly perturbed in those individuals suffering with dementia. This work may provide additional insight into AD pathogenesis and encourage more in-depth analysis of the AD lipidome.

Body Fluid Biomarkers for Alzheimer's Disease-An Up-To-Date Overview

Neurodegeneration is a highly complex process which is associated with a variety of molecular mechanisms related to ageing. Among neurodegenerative disorders, Alzheimer's disease (AD) is the most common, affecting more than 45 million individuals. The underlying mechanisms involve amyloid plaques and neurofibrillary tangles (NFTs) deposition, which will subsequently lead to oxidative stress, chronic neuroinflammation, neuron dysfunction, and neurodegeneration. The current diagnosis methods are still limited in regard to the possibility of the accurate and early detection of the diseases. Therefore, research has shifted towards the identification of novel biomarkers and matrices as biomarker sources, beyond amyloid-β and tau protein levels within the cerebrospinal fluid (CSF), that could improve AD diagnosis. In this context, the aim of this paper is to provide an overview of both conventional and novel biomarkers for AD found within body fluids, including CSF, blood, saliva, urine, tears, and olfactory fluids.

Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders

There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.

Plasma metabolites in treatment-requiring retinopathy of prematurity: Potential biomarkers identified by metabolomics

Retinopathy of prematurity (ROP) is a potentially blinding condition caused by disruption of retinal vascularization and metabolism. This study aims to identify altered metabolites from plasma in patients with treatment-requiring ROP (TR-ROP) compared with controls. An untargeted metabolomics analysis was performed to reveal the metabolomic profiles of the plasma between TR-ROP patients (n = 38) and age-matched infants (n = 23). The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore the potential signaling pathways of the changed metabolites. Under positive ion mode, a total of 29 metabolites were significantly altered in plasma between TR-ROP patients and controls, and 23 altered metabolites were identified under negative ion mode. KEGG analyses indicated that "protein digestion and absorption" and "aminoacyl-tRNA biosynthesis" were the most enriched pathways of the altered metabolites. These results demonstrated that metabolomic profiles changed in plasma of TR-ROP, and the altered metabolites could be served as potential biomarkers for the diagnosis and prognosis of TR-ROP patients. Besides, the metabolomic profiles might provide clues to discover novel therapeutic strategies in ROP treatment.

In slow pace towards the proteome of equine body fluids

Equine medicine represents a relevant field of veterinary science and the horse industry generates a significant economic impact. Horses can be involved in different sport disciplines, meat production, work and recreational purposes. Horses are also important for human health as they can be used as animal models for studying human diseases and in equine-assisted therapy. This review summarizes the data related to body fluids such as plasma/serum, urine, cerebrospinal fluid, synovial fluid, saliva, bronchoalveolar lavage fluid and peritoneal fluid obtained using proteomic analysis. Horse body fluid proteome analysis under various physiological and pathological conditions is a useful method for identifying new biomarkers for horse diseases which are still difficult to diagnose, but with serious consequences on equine health and welfare. The findings reported here reveal that further proteomic studies on equine body fluids collected from diseased animals are required. SIGNIFICANCE: Body fluids are sources of potential protein biomarkers for diagnosis and therapeutic target identification. Indeed, they contain proteins that play a crucial role in cell functions and whose presence or relative abundance are indicative of the health status of tissues/organs. The review reports the data on the equine body fluids obtained using proteomic analysis, including those which are commonly used to obtain a correct diagnosis and prognosis of horse diseases which still pose a significant challenge. For equine medicine, new biomarkers are needed to formulate early diagnosis and to distinguish among diseases with similar clinical signs.