Urinary Biomarkers for Neurodegenerative Diseases

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

Delirium pathophysiology in cancer: neurofilament light chain biomarker - narrative review

Background Delirium is a debilitating disorder with high prevalence near the end of life, impacting quality of life of patients and their relatives. Timely recognition of delirium can lead to prevention and/or better treatment of delirium. According to current hypotheses delirium is thought to result from aberrant inflammation and neurotransmission, with a possible role for neuronal damage. Neurofilament light chain (NfL) is a protein biomarker in body fluids that is unique to neurons, with elevated levels when neurons are damaged, making NfL a viable biomarker for early detection of delirium. This narrative review summarises current research regarding the pathophysiology of delirium and the potential of NfL as a susceptibility biomarker for delirium and places this in the context of care for patients with advanced cancer.Results Six studies were conducted exclusively on NfL in patients with delirium. Three of these studies demonstrated that high plasma NfL levels preoperatively predict delirium in older adult patients postoperatively. Two studies demonstrated that high levels of NfL in intensive care unit (ICU) patients are correlated with delirium duration and severity. One study found that incident delirium in older adult patients was associated with increased median NfL levels during hospitalisation.Conclusions Targeted studies are required to understand if NfL is a susceptibility biomarker for delirium in patients with advanced cancer. In this palliative care context, better accessible matrices, such as saliva or urine, would be helpful for repetitive testing. Improvement of biological measures for delirium can lead to improved early recognition and lay the groundwork for novel therapeutic strategies.

Effects of Exercise on Urinary AD7c-NTP (Alzheimer-Associated Neuronal Thread Protein) Levels and Cognitive Function Among Active Korean Elderly: A Randomized Controlled Trial

Background

Alzheimer-associated neuronal thread protein (AD7c-NTP) has been demonstrated to have high diagnostic accuracy in differentiating Alzheimer's disease (AD) patients from healthy individuals. However, it is yet unclear whether exercise can lower the level of AD7c-NTP in urine among active Korean elderly.

Objective

To assess the effect of exercise on AD7c-ntp levels in urine and cognitive function among active Korean elderly.

Methods

In total, 40 Korean elderly (≥65 years) were divided into Active Control group (CG, n = 10), Aerobic exercise group (AG, n = 18), and combined Resistance/Aerobic exercise group (RAG, n = 12). A total of 12 weeks of exercise intervention was implemented. At week 0 and 12, cognitive performance (Korean Mini-Mental State Examination, Korean-Color Word Stroop test), grip strength, and body composition (muscle mass and body fat percentage) were measured. Also, a morning urine sample was obtained from each subject. The level of AD7c-NTP was measured using competitive enzyme-linked immunosorbent assay (ELISA).

Results

After 12 weeks of exercise intervention, there was a significant difference of AD7c-NTP levels between RAG and CG (p = 0.026), AG and CG (p = 0.032), respectively. Furthermore, the AD7c-NTP levels in urine showed negative correlation with K-MMSE scores (r = -0.390, p = 0.013) and grip strength (r = -0.376, p = 0.017), among all participants after exercise intervention.

Conclusions

This is the first study to investigate urine biomarker through exercise intervention. In future stuides, participants who have low cognitive function and low activity levels need to be recruited to observe more significant 'Exercise' effect.

Urine metabolomics phenotyping and urinary biomarker exploratory in mild cognitive impairment and Alzheimer's disease

Introduction

Alzheimer's disease is a prevalent disease with a heavy global burden and is suggested to be a metabolic disease in the brain in recent years. The metabolome is considered to be the most promising phenotype which reflects changes in genetic, transcript, and protein profiles as well as environmental effects. Aiming to obtain a comprehensive understanding and convenient diagnosis of MCI and AD from another perspective, researchers are working on AD metabolomics. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.

Methods

We first enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples and conducted an LC-MS/MS analysis. In parallel, clinical data were collected and clinical examinations were performed. After statistical and bioinformatics analyzes, significant risk factors and differential urinary metabolites were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.

Results

Fifty-seven AD patients, 43 MCI patients and 62 CN subjects were enrolled. A total of 2,140 metabolites were identified among which 125 significantly differed between the AD and CN groups, including 46 upregulated ones and 79 downregulated ones. In parallel, there were 93 significant differential metabolites between the MCI and CN groups, including 23 upregulated ones and 70 downregulated ones. AD diagnostic panel (30 metabolites+ age + APOE) achieved an AUC of 0.9575 in the test set while MCI diagnostic panel (45 metabolites+ age + APOE) achieved an AUC of 0.7333 in the test set. Atropine, S-Methyl-L-cysteine-S-oxide, D-Mannose 6-phosphate (M6P), Spiculisporic Acid, N-Acetyl-L-methionine, 13,14-dihydro-15-keto-tetranor Prostaglandin D2, Pyridoxal 5'-Phosphate (PLP) and 17(S)-HpDHA were considered valuable for both AD and MCI diagnosis and defined as hub metabolites. Besides, diagnostic metabolites were weakly correlated with cognitive functions.

Discussion

In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN. Atropine, M6P and PLP were evidence-based hub metabolites in AD.

Identification of novel diagnostic panel for mild cognitive impairment and Alzheimer's disease: findings based on urine proteomics and machine learning

BACKGROUND

Alzheimer's disease is a prevalent disease with a heavy global burden. Proteomics is the systematic study of proteins and peptides to provide comprehensive descriptions. Aiming to obtain a more accurate and convenient clinical diagnosis, researchers are working for better biomarkers. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.

METHODS

We firstly enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples, and conducted an LC-MS/MS analysis. In parallel, clinical data were collected, and clinical examinations were performed. After statistical and bioinformatics analyses, significant risk factors and differential urinary proteins were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.

RESULTS

Fifty-seven AD patients, 43 MCI patients, and 62 CN subjects were enrolled. A total of 3366 proteins were identified, and 608 urine proteins were finally included in the analysis. There were 33 significantly differential proteins between the AD and CN groups and 15 significantly differential proteins between the MCI and CN groups. AD diagnostic panel included DDC, CTSC, EHD4, GSTA3, SLC44A4, GNS, GSTA1, ANXA4, PLD3, CTSH, HP, RPS3, CPVL, age, and APOE ε4 with an AUC of 0.9989 in the training test and 0.8824 in the test set while MCI diagnostic panel included TUBB, SUCLG2, PROCR, TCP1, ACE, FLOT2, EHD4, PROZ, C9, SERPINA3, age, and APOE ε4 with an AUC of 0.9985 in the training test and 0.8143 in the test set. Besides, diagnostic proteins were weakly correlated with cognitive functions.

CONCLUSIONS

In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN.

Urine proteomic analysis of the rat e-cigarette model

Background

We were curious if the urinary proteome could reflect the effects of e-cigarettes on the organism.

Methods

Urine samples were collected from a rat e-cigarette model before, during, and after two weeks of e-cigarette smoking. Urine proteomes before and after smoking of each rat were compared individually, while the control group was set up to rule out differences caused by rat growth and development.

Results

Fetuin-B, a biomarker of chronic obstructive pulmonary disease (COPD), and annexin A2, which is recognized as a multiple tumour marker, were identified as differential proteins in five out of six smoking rats on day 3. To our surprise, odourant-binding proteins expressed in the olfactory epithelium were also found and were significantly upregulated. Pathways enriched by the differential proteins include the apelin signalling pathway, folate biosynthesis pathway, arachidonic acid metabolism, chemical carcinogenesis-DNA adducts and chemical carcinogenesis-reactive oxygen species. They have been reported to be associated with immune system, cardiovascular system, respiratory system, etc.

Conclusions

Urinary proteome could reflect the effects of e-cigarettes in rats.

Urinary Cytokines as Potential Biomarkers of Mild Cognitive Impairment and Alzheimer's Disease: A Pilot Study

Background

Alzheimer's disease (AD) is the most common form of dementia, accounting for 80% of all cases. Mild cognitive impairment (MCI) is a transitional state between normal aging and AD. Early detection is crucial, as irreversible brain damage occurs before symptoms manifest.

Objective

This study aimed to identify potential biomarkers for early detection of AD by analyzing urinary cytokine concentrations. We investigated 37 cytokines in AD, MCI, and cognitively normal individuals (NC), assessing their associations with AD development.

Methods

Urinary cytokine concentrations were measured in AD (n = 25), MCI (n = 25), and NC (n = 26) patients. IL6ST and MMP-2 levels were compared between AD and NC, while TNFRSF8, IL6ST, and IL-19 were assessed in AD versus MCI. Diagnostic models distinguished AD from NC, and in-silico analysis explored molecular mechanisms related to AD.

Results

Significant perturbations in IL6ST and MMP-2 concentrations were observed in AD urine compared to NC, suggesting their potential as biomarkers. TNFRSF8, IL6ST, and IL-19 differed significantly between AD and MCI, implicating them in disease progression. Diagnostic models exhibited promising performance (AUC: 0.59-0.79, sensitivity: 0.72-0.80, specificity: 0.56-0.78) in distinguishing AD from NC. In-silico analysis revealed molecular insights, including relevant non-coding RNAs, microRNAs, and transcription factors.

Conclusion

This study establishes significant associations between urinary cytokine concentrations and AD and MCI. IL6ST, MMP-2, TNFRSF8, IL6ST, and IL-19 emerge as potential biomarkers for early detection of AD. In-silico analysis enhances understanding of molecular mechanisms in AD. Further validation and exploration of these biomarkers in larger cohorts are warranted to assess their clinical utility.

Urinary Biomarkers and Point-of-Care Urinalysis Devices for Early Diagnosis and Management of Disease: A Review

Biosensing and microfluidics technologies are transforming diagnostic medicine by accurately detecting biomolecules in biological samples. Urine is a promising biological fluid for diagnostics due to its noninvasive collection and wide range of diagnostic biomarkers. Point-of-care urinalysis, which integrates biosensing and microfluidics, has the potential to bring affordable and rapid diagnostics into the home to continuing monitoring, but challenges still remain. As such, this review aims to provide an overview of biomarkers that are or could be used to diagnose and monitor diseases, including cancer, cardiovascular diseases, kidney diseases, and neurodegenerative disorders, such as Alzheimer’s disease. Additionally, the different materials and techniques for the fabrication of microfluidic structures along with the biosensing technologies often used to detect and quantify biological molecules and organisms are reviewed. Ultimately, this review discusses the current state of point-of-care urinalysis devices and highlights the potential of these technologies to improve patient outcomes. Traditional point-of-care urinalysis devices require the manual collection of urine, which may be unpleasant, cumbersome, or prone to errors. To overcome this issue, the toilet itself can be used as an alternative specimen collection and urinalysis device. This review then presents several smart toilet systems and incorporated sanitary devices for this purpose.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Brain-specific biomarkers in urine as a non-invasive approach to monitor neuronal and glial damage

BACKGROUND AND PURPOSE

This study evaluates the quantitative measurability of glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and total tau (t-tau) in urine of patients with acute cerebral damage.

METHODS

Serum and urine samples were prospectively collected from patients with an acute ischemic stroke or intracerebral hemorrhage (target group) and compared to healthy subjects (control group); samples were measured using ultrasensitive single-molecule arrays (Simoa®). Glomerular barrier function was assessed based on albumin-creatinine ratio (ACR); biomarker-creatinine ratios were calculated for correction of urine dilution.

RESULTS

Ninety-three urine-serum pairs in the target group and 10 urine-serum pairs in the control group were measured. The mean absolute concentration ± standard deviation in urine of the target and control groups were 184.7 ± 362.4 pg/ml and 27.3 ± 24.1 pg/ml for GFAP (r = 0.3 [Wilcoxon effect size], p = 0.007), 17.5 ± 38.6 pg/ml and 0.9 ± 0.3 pg/ml for NfL (r = 0.4, p < 0.005), 320.2 ± 443.3 pg/ml and 109.6 ± 116.8 pg/ml for UCH-L1 (r = 0.26, p = 0.014), and 219.5 ± 255.8 pg/ml and 21.1 ± 27.1 pg/ml for t-tau (r = 0.37, p < 0.005), respectively, whereas biomarker-creatinine ratio was significantly different only for NfL (r = 0.29, p = 0.015) and t-tau (r = 0.32, p < 0.01). In patients with intact glomerular barrier (ACR < 30 mg/g), only NfL in urine was significantly different between the target and control group and showed a significant correlation with the respective serum concentrations (r = 0.58 [Pearson's correlation-coefficient], p < 0.005).

CONCLUSION

All four investigated biomarkers could be measured in urine, with NfL and t-tau showing the strongest effect size after correction for urine dilution. NfL revealed the most accurate relation between serum and urine concentrations in patients with intact kidney function.

Employing nanoparticle tracking analysis of salivary neuronal exosomes for early detection of neurodegenerative diseases

Neurodegenerative diseases are a set of progressive and currently incurable diseases that are primarily caused by neuron degeneration. Neurodegenerative diseases often lead to cognitive impairment and dyskinesias. It is now well recognized that molecular events precede the onset of clinical symptoms by years. Over the past decade, intensive research attempts have been aimed at the early diagnosis of these diseases. Recently, exosomes have been shown to play a pivotal role in the occurrence and progression of many diseases including cancer and neurodegenerative diseases. Additionally, because exosomes can cross the blood-brain barrier, they may serve as a diagnostic tool for neural dysfunction. In this review, we detail the mechanisms and current challenges of these diseases, briefly review the role of exosomes in the progression of neurodegenerative diseases, and propose a novel strategy based on salivary neuronal exosomes and nanoparticle tracking analysis that could be employed for screening the early onset of neurodegenerative diseases.

From protein biomarkers to proteomics in dementia with Lewy Bodies

Dementia with Lewy Bodies (DLB) is the second most common neurodegenerative dementia. Despite considerable research progress, there remain gaps in our understanding of the pathophysiology and there is no disease-modifying treatment. Proteomics is a powerful tool to elucidate complex biological pathways across heterogenous conditions. This review summarizes the widely used proteomic methods and presents evidence for protein dysregulation in the brain and peripheral tissues in DLB. Proteomics of post-mortem brain tissue shows that DLB shares common features with other dementias, such as synaptic dysfunction, but retains a unique protein signature. Promising diagnostic biomarkers are being identified in cerebrospinal fluid (CSF), blood, and peripheral tissues, such as serum Heart-type fatty acid binding protein. Research is needed to track these changes from the prodromal stage to established dementia, with standardized workflows to ensure replicability. Identifying novel protein targets in causative biological pathways could lead to the development of new targeted therapeutics or the stratification of participants for clinical trials.

Prospective biomarkers of Alzheimer's disease: A systematic review and meta-analysis

OBJECTIVE

Alzheimer's disease (AD) involves a series of pathological changes and some biomarkers were reported to assist in monitoring and predicting disease progression before the emergence of clinical symptoms. We aimed to identify prospective biomarkers and quantify their effect on AD progression.

METHODS

PubMed, EMBASE and Web of Science databases were searched for prospective cohort studies published up to October 2021. Eligible studies were included, and the available data were extracted. Meta-analyses were conducted based on random-effect models. Relative risk (RR) with 95% confidence interval (CI) was adopted as the final effect size.

RESULTS

Totally 48,769 articles were identified, of which 84 studies with 20 prospective biomarkers were included in meta-analyses. In the present study, 15 biomarkers were associated with AD progression, comprising CSF Aβ42 (RR=2.49, 95%CI=1.68-3.69), t-tau (RR=1.88, 95%CI=1.49-2.37), p-tau (RR=1.74, 95%CI=1.37-2.21), tau/Aβ42 ratio (RR=5.11, 95%CI=2.01-13.00); peripheral blood Aβ42/Aβ40 (RR=1.26, 95%CI=1.05-1.51), t-tau (RR=1.33, 95%CI=1.08-1.64), NFL (RR=1.75, 95%CI=1.07-2.87); whole, left and right hippocampal volume (HV) (whole: RR=1.65, 95%CI=1.39-1.95; left: RR=2.60, 95%CI=1.02-6.64; right: RR=1.43, 95%CI=1.23-1.66), entorhinal cortex (EC) volume (RR=1.69, 95%CI=1.24-2.30), medial temporal lobe atrophy (MTA) (RR=1.52, 95%CI=1.33-1.74), 18 F-FDG PET (RR=2.24, 95%CI=1.29-3.89), 11 C-labeled Pittsburgh Compound B PET (11 C-PIB PET) (RR=3.91, 95%CI=1.06-14.41); APOE ε4 (RR=2.16, 1.83-2.55). A total of 70 articles were included in the qualitative review, in which 61 biomarkers were additionally associated with AD progression.

CONCLUSION

CSF Aβ42, t-tau, p-tau, tau/Aβ42; peripheral blood t-tau, Aβ42/Aβ40, NFL; whole, left and right HV, EC volume, MTA, 18 F-FDG PET, 11 C-PIB PET; APOE ε4 may be promising prospective biomarkers for AD progression.

Modular Assembly of MXene Frameworks for Noninvasive Disease Diagnosis via Urinary Volatiles

Volatile organic compounds (VOCs) in urine are valuable biomarkers for noninvasive disease diagnosis. Herein, a facile coordination-driven modular assembly strategy is used for developing a library of gas-sensing materials based on porous MXene frameworks (MFs). Taking advantage of modules with diverse composition and tunable structure, our MFs-based library can provide more choices to satisfy gas-sensing demands. Meanwhile, the laser-induced graphene interdigital electrodes array and microchamber are laser-engraved for the assembly of a microchamber-hosted MF (MHMF) e-nose. Our MHMF e-nose possesses high-discriminative pattern recognition for simultaneous sensing and distinguishing of complex VOCs. Furthermore, with the MHMF e-nose being a plug-and-play module, a point-of-care testing (POCT) platform is modularly assembled for wireless and real-time monitoring of urinary volatiles from clinical samples. By virtue of machine learning, our POCT platform achieves noninvasive diagnosis of multiple diseases with a high accuracy of 91.7%, providing a favorable opportunity for early disease diagnosis, disease course monitoring, and relevant research.

Is liquid biopsy mature enough for the diagnosis of Alzheimer’s disease?

The preclinical diagnosis and clinical practice for Alzheimer’s disease (AD) based on liquid biopsy have made great progress in recent years. As liquid biopsy is a fast, low-cost, and easy way to get the phase of AD, continual efforts from intense multidisciplinary studies have been made to move the research tools to routine clinical diagnostics. On one hand, technological breakthroughs have brought new detection methods to the outputs of liquid biopsy to stratify AD cases, resulting in higher accuracy and efficiency of diagnosis. On the other hand, diversiform biofluid biomarkers derived from cerebrospinal fluid (CSF), blood, urine, Saliva, and exosome were screened out and biologically verified. As a result, more detailed knowledge about the molecular pathogenesis of AD was discovered and elucidated. However, to date, how to weigh the reports derived from liquid biopsy for preclinical AD diagnosis is an ongoing question. In this review, we briefly introduce liquid biopsy and the role it plays in research and clinical practice. Then, we summarize the established fluid-based assays of the current state for AD diagnostic such as ELISA, single-molecule array (Simoa), Immunoprecipitation–Mass Spectrometry (IP–MS), liquid chromatography–MS, immunomagnetic reduction (IMR), multimer detection system (MDS). In addition, we give an updated list of fluid biomarkers in the AD research field. Lastly, the current outstanding challenges and the feasibility to use a stand-alone biomarker in the joint diagnostic strategy are discussed.

Emerging urinary alpha-synuclein and miRNA biomarkers in Parkinson's disease

Parkinson's disease (PD) is one of the most common neurodegenerative diseases after Alzheimer's disease (AD), afflicting adults above the age of sixty irrespective of gender, race, ethnicity, and social status. PD is characterized by motor dysfunctions, displaying resting tremor, rigidity, bradykinesia, and postural imbalance. Non-motor symptoms, including rapid eye movement (REM) behavior disorder, constipation, and loss of sense of smell, typically occur many years before the appearance of the PD motor symptoms that lead to a diagnosis. The loss of dopaminergic neurons in the substantia nigra, which leads to the motor symptoms seen in PD, is associated with the deposition of aggregated, misfolded α-Synuclein (α-Syn, SNCA) proteins forming Lewy Bodies. Additionally, dysregulation of miRNA (a short form of mRNA) may contribute to the developing pathophysiology in PD and other diseases such as cancer. Overexpression of α-Syn and miRNA in human samples has been found in PD, AD, and dementia. Therefore, evaluating these molecules in urine, present either in the free form or in association with extracellular vesicles of biological fluids, may lead to early biomarkers for clinical diagnosis. Collection of urine is non-invasive and thus beneficial, particularly in geriatric populations, for biomarker analysis. Considering the expression and function of α-Syn and miRNA, we predict that they can be used as early biomarkers in the diagnosis and prognosis of neurodegenerative diseases.

Non-Invasive Nasal Discharge Fluid and Other Body Fluid Biomarkers in Alzheimer’s Disease

The key to current Alzheimer’s disease (AD) therapy is the early diagnosis for prompt intervention, since available treatments only slow the disease progression. Therefore, this lack of promising therapies has called for diagnostic screening tests to identify those likely to develop full-blown AD. Recent AD diagnosis guidelines incorporated core biomarker analyses into criteria, including amyloid-β (Aβ), total-tau (T-tau), and phosphorylated tau (P-tau). Though effective, the accessibility of screening tests involving conventional cerebrospinal fluid (CSF)- and blood-based analyses is often hindered by the invasiveness and high cost. In an attempt to overcome these shortcomings, biomarker profiling research using non-invasive body fluid has shown the potential to capture the pathological changes in the patients’ bodies. These novel non-invasive body fluid biomarkers for AD have emerged as diagnostic and pathological targets. Here, we review the potential peripheral biomarkers, including non-invasive peripheral body fluids of nasal discharge, tear, saliva, and urine for AD.

Uncommon Noninvasive Biomarkers for the Evaluation and Monitoring of the Etiopathogenesis of Alzheimer's Disease

Background:

Alzheimer´s disease (AD) is the most widespread dementia in the world, followed by vascular dementia. Since AD is a heterogeneous disease that shows several varied phenotypes, it is not easy to make an accurate diagnosis, so it arises when the symptoms are clear and the disease is already very advanced. Therefore, it is important to find out biomarkers for AD early diagnosis that facilitate treatment or slow down the disease. Classic biomarkers are obtained from cerebrospinal fluid and plasma, along with brain imaging by positron emission tomography. Attempts have been made to discover uncommon biomarkers from other body fluids, which are addressed in this update.

Objective:

This update aims to describe recent biomarkers from minimally invasive body fluids for the patients, such as saliva, urine, eye fluid or tears.

Methods:

Biomarkers were determined in patients versus controls by single tandem mass spectrometry, and immunoassays. Metabolites were identified by nuclear magnetic resonance, and microRNAs with genome-wide high-throughput real-time polymerase chain reaction-based platforms.

Results:

Biomarkers from urine, saliva, and eye fluid were described, including peptides/proteins, metabolites, and some microRNAs. The association with AD neuroinflammation and neurodegeneration was analyzed, highlighting the contribution of matrix metalloproteinases, the immune system and microglia, as well as the vascular system.

Conclusion:

Unusual biomarkers have been developed, which distinguish each stage and progression of the disease, and are suitable for the early AD diagnosis. An outstanding relationship of biomarkers with neuroinflammation and neurodegeneration was assessed, clearing up concerns of the etiopathogenesis of AD.

Distance-based β-amyloid protein detection on PADs for the scanning and subsequent follow-up of Alzheimer's disease in human urine samples

We report on the first development of a simple distance-based β-amyloid (Aβ) protein quantification using a paper-based device (dPAD) to screen for Alzheimer's disease (AD) and to subsequently follow up on its influence, i.e., clinical dementia. This sensor method is based on the transformation of a free acid form and its binding with a basic form of bromocresol purple (BCP) through its electrostatic interaction with an Aβ protein. This sensor can measure the length of color change from yellow to blue-green on a paper strip, with this change proportional to the amount of Aβ protein level. We found that the linearity for Aβ protein monitoring was in the range from 0.50 to 10.0 ng mL^-1, and the subsequent naked-eye detection limit for Aβ was 0.20 ng mL^-1. This system also provided high reproducibility and with no apparent interference effect for Aβ protein analysis in human urine samples. Furthermore, our developed dPAD constituted an accurate and effective device to precisely determine an Aβ protein concentration in real samples, with percentage recoveries in the range of 97-103%, and with the highest relative standard deviation of 5.41%. Subsequently, the validation of our assay was assessed by comparison with a commercial ELISA approach, with favorable results. Finally, the proposed dPAD was successfully applied to the determination of an Aβ protein in human urine samples and showed more benefits for the unskilled user, such as cost-efficiency, simplicity, low reagent usage, and low time consumption. It is also suitable for point-of-care monitoring.

Plasma Metabolite Signature Classifies Male LRRK2 Parkinson’s Disease Patients

Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.

Opposite Roles of Co-enzyme Q10 and Formaldehyde in Neurodegenerative Diseases

Most of neurodegenerative diseases (NDD) have no cure. The common etiology of neurodegenerations is unclear. Air pollutant-gaseous formaldehyde is notoriously known to induce demyelination and cognitive impairments. Unexpectedly, an amount of formaldehyde has been detected in the brains. Multiple factors can induce the generation and accumulation of endogenous formaldehyde. Excessive formaldehyde can induce oxidative stress to generate H2O2; in turn, H2O2 promote formaldehyde production. Clinical investigations have shown that an abnormal high level of formaldehyde but low level of coenzyme Q10 (coQ10) was observed in patients with NDD. Further studies have proven that excessive formaldehyde directly inactivates coQ10, reduces the ATP generation, enhances oxidative stress, initiates inflammation storm, induces demyelination; subsequently, it results in neurodegeneration. Although the low water solubility of coQ10 limits its clinical application, nanomicellar water-soluble coQ10 exhibits positive therapeutical effects. Hence, nanopackage of coQ10 may be a promising strategy for treating NDD.

Microarray microRNA profiling of urinary exosomes in a 5XFAD mouse model of Alzheimer's disease

Background

Alzheimer's disease (AD) is an incurable and irreversible neurodegenerative disease, without a clear pathogenesis. Therefore, identification of candidates before amyloid-β plaque (Aβ) deposition proceeds is of major significance for earlier intervention in AD.

Methods

To explore the potential noninvasive earlier biomarkers of AD in a 5XFAD mouse model, microRNAs (miRNAs) from urinary exosomes in 1-month-old pre-Aβ accumulation 5XFAD mice models and their littermate controls were profiled by microarray analysis. The differentially expressed miRNAs were further analyzed via droplet digital PCR (ddPCR).

Results

Microarray analysis demonstrated that 48 differentially expressed miRNAs (18 upregulated and 30 downregulated), of which six miRNAs - miR-196b-5p, miR-339-3p, miR-34a-5p, miR-376b-3p, miR-677-5p, and miR-721 - were predicted to display gene targets and important signaling pathways closely associated with AD pathogenesis and verified by ddPCR.

Conclusions

Urinary exosomal miRNAs showing differences in expression prior to Aβ-plaque deposition were identified. These exosomal miRNAs represent potential noninvasive biomarkers that may be used to prevent AD in clinical applications.

Brain-Derived Exosomal Proteins as Effective Biomarkers for Alzheimer's Disease: A Systematic Review and Meta-Analysis

Alzheimer's disease (AD), a progressive neurodegenerative disease, affects approximately 50 million people worldwide, which warrants the search for reliable new biomarkers for early diagnosis of AD. Brain-derived exosomal (BDE) proteins, which are extracellular nanovesicles released by all cell lineages of the central nervous system, have been focused as biomarkers for diagnosis, screening, prognosis prediction, and monitoring in AD. This review focused on the possibility of BDE proteins as AD biomarkers. The articles published prior to 26 January 2021 were searched in PubMed, EMBASE, Web of Science, and Cochrane Library to identify all relevant studies that reported exosome biomarkers in blood samples of patients with AD. From 342 articles, 20 studies were selected for analysis. We conducted a meta-analysis of six BDE proteins and found that levels of amyloid-β42 (standardized mean difference (SMD) = 1.534, 95% confidence interval [CI]: 0.595-2.474), total-tau (SMD = 1.224, 95% CI: 0.534-1.915), tau phosphorylated at threonine 181 (SMD = 4.038, 95% CI: 2.312-5.764), and tau phosphorylated at serine 396 (SMD = 2.511, 95% CI: 0.795-4.227) were significantly different in patients with AD compared to those in control. Whereas, those of p-tyrosine-insulin receptor substrate-1 and heat shock protein 70 did not show significant differences. This review suggested that Aβ42, t-tau, p-T181-tau, and p-S396-tau could be effective in diagnosing AD as blood biomarkers, despite the limitation in the meta-analysis based on the availability of data. Therefore, certain BDE proteins could be used as effective biomarkers for AD.

Targeting for Success: Demonstrating Proof-of-Concept with Mechanistic Early Phase Clinical Pharmacology Studies for Disease-Modification in Neurodegenerative Disorders

The clinical failure rate for disease-modifying treatments (DMTs) that slow or stop disease progression has been nearly 100% for the major neurodegenerative disorders (NDDs), with many compounds failing in expensive and time-consuming phase 2 and 3 trials for lack of efficacy. Here, we critically review the use of pharmacological and mechanistic biomarkers in early phase clinical trials of DMTs in NDDs, and propose a roadmap for providing early proof-of-concept to increase R&D productivity in this field of high unmet medical need. A literature search was performed on published early phase clinical trials aimed at the evaluation of NDD DMT compounds using MESH terms in PubMed. Publications were selected that reported an early phase clinical trial with NDD DMT compounds between 2010 and November 2020. Attention was given to the reported use of pharmacodynamic (mechanistic and physiological response) biomarkers. A total of 121 early phase clinical trials were identified, of which 89 trials (74%) incorporated one or multiple pharmacodynamic biomarkers. However, only 65 trials (54%) used mechanistic (target occupancy or activation) biomarkers to demonstrate target engagement in humans. The most important categories of early phase mechanistic and response biomarkers are discussed and a roadmap for incorporation of a robust biomarker strategy for early phase NDD DMT clinical trials is proposed. As our understanding of NDDs is improving, there is a rise in potentially disease-modifying treatments being brought to the clinic. Further increasing the rational use of mechanistic biomarkers in early phase trials for these (targeted) therapies can increase R&D productivity with a quick win/fast fail approach in an area that has seen a nearly 100% failure rate to date.