|Year : 2020 | Volume
| Issue : 3 | Page : 91-98
A Systematic Review on Urinary Biomarkers for Early Diagnosis of Alzheimer’s Disease (AD)
P. Rani, S. Vivek, S. Maheswar Ram
Department of Biotechnology, PSG College of Technology, Coimbatore, Tamil Nadu, India
|Date of Submission||04-Feb-2020|
|Date of Decision||08-Mar-2020|
|Date of Acceptance||31-Mar-2020|
|Date of Web Publication||20-Aug-2020|
Professor P. Rani
Department of Biotechnology, PSG College of Technology, Coimbatore, 641004
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Alzheimer’s disease (AD) is a neurodegenerative disease that commonly affects the older population whose symptoms are only visible during the later stage which renders the available treatment ineffective. Our study attempts to provide a solution to this problem by identifying urinary biomarkers that could be used in the first-line screening of a larger population for AD before analysing with more sophisticated blood and CSF based biomarkers, which provide high sensitivity on comparison. A systematic review was performed using the keywords “Alzheimer”, “urine”, “biomarkers” and “metabolomics” following the PRISMA criteria, to identify urinary biomarkers for the early diagnosis of Alzheimer’s disease. From the performed study, three metabolites were identified namely 5-hydroxy indole acetic acid, L-arginine and allantoin as biomarkers whose level was altered in AD samples compared to controls. In AD, 5-hydroxy indole acetic acid level was downregulated in urine probably because of the extensive serotonergic denervation that has been observed in the AD brain. Increased levels of L-arginine in the brain which act as a precursor to nitric oxide due to the action of NO synthase might potentially lead to neurotoxicity when present in excess, and is also known to be in synergy with ROS. Increased levels of allantoin in urine is due to the action of increased ROS in the system reacting with uric acid. Here, we provide an overview of all the reported metabolites obtained from the search, by discussing their influence in AD pathology. This study identified three metabolites in urine that could function as potential biomarkers for AD based on significant changes observed between disease and control samples, along with its recurrence and commonality in different models namely mice and human. However, longitudinal and cross-sectional follow-up studies are required for the validation of these biomarkers.
Keywords: Alzheimer’s disease, early diagnosis, metabolomics, urinary biomarkers
|How to cite this article:|
Rani P, Vivek S, Ram SM. A Systematic Review on Urinary Biomarkers for Early Diagnosis of Alzheimer’s Disease (AD). Int J Nutr Pharmacol Neurol Dis 2020;10:91-8
|How to cite this URL:|
Rani P, Vivek S, Ram SM. A Systematic Review on Urinary Biomarkers for Early Diagnosis of Alzheimer’s Disease (AD). Int J Nutr Pharmacol Neurol Dis [serial online] 2020 [cited 2020 Sep 28];10:91-8. Available from: http://www.ijnpnd.com/text.asp?2020/10/3/91/292679
| Introduction|| |
Dementia refers to the severe changes occurring in the brain that causes memory loss. Globally, around 50 million people are affected by dementia and about 10 million new cases are being reported annually. In India, nearly 4 million people are affected by some form of dementia. The prevalence of Alzheimer’s disease (AD) is high among the aging population with dementia. In the United States, about 5.8 million Americans are affected by Alzheimer’s dementia. AD is a chronic neurodegenerative disease that affects cognitive ability such as memory, thinking and reasoning.
Several factors are involved in the disease etiology which include amyloid β(Aβ) accumulation, oxidative stress, tau phosphorylation, lipid dysregulation, mitochondrial dysfunction, and inflammation. In the case of Aβ accumulation, the β-amyloid proteins get adsorbed to the receptors of neuronal cells and get internalized to form amyloid fibrils which result in senile plaque formation.
Under physiological conditions, lower levels of ROS is regarded as a mode of signal transduction which allows for any adaptation to occur in the system, based on the changes occurring in the surrounding oxidative environment. However, under oxidative stress, excess production of reactive oxygen species (ROS) occurs which causes denaturation of all biomolecules due to pathological redox reactions. The abnormal hyperphosphorylation of normal tau proteins, which is also a consequence of increased ROS, polymerizes the paired helical filaments (PHF) with straight filaments (SF) resulting in the formation of neurofibrillary tangles in AD.
Mitochondrial dysfunction and lipid dysregulation are constantly associated with Aβ plaque formation of AD. Amyloid Beta (Aβ) monomers are generated through the cleavage of Aβ precursor protein by α‐, β‐, and γ‐secretases. Mitochondrial dysfunction occurs also in oxidative stress resulting in the production of lipid peroxidation product 4‐hydroxynonenal, which covalently modifies the γ‐secretase complex and contribute to amplified secretase activity. This results in accelerated Aβ accumulation, thereby resulting in neurodegeneration.
AD can be progressively categorized into three stages namely preclinical, mild cognitive impairment (MCI) and dementia. Currently, there are no effective drugs/treatments available to reverse or halt the progression of AD. The early and predictive diagnosis of AD is the paramount importance which could be made possible using biomarkers.
Biomarkers are measurable changes associated with the disease. The most common biomarkers associated with the diagnosis of AD are cerebral spinal fluid (CSF) and blood-based biomarkers. The identification of these biomarkers in AD patients involves invasive, expensive and time-consuming methods. An alternative biomarker for diagnosing AD could be obtained from the urine.
Unlike blood, which is stable because of homeostasis mechanisms, urine can accumulate many kinds of changes that could be exploited as a potential biomarker, particularly in the earlier stages of most diseases. Also, urine is a preferred resource for biomarker discovery since it can be non-invasively collected. The collection, storage, and post-treatment processes of plasma samples can adversely affect proteomics analysis and biomarker studies. In addition, the high abundance of plasma proteins provides a major constraint to plasma proteomics and subsequent biomarker screening.
Urinary biomarkers can help in providing first-line screening of diseases for larger population, which can be confirmed through sophisticated and more-sensitive CSF and blood-based biomarker analyses with high reliability. Due to the lack of any homeostasis mechanism, urine might reflect pathological changes, especially in the early stages of the neurodegenerative diseases which was studied in transgenic mouse models. This paper aims to systematically review the scientific literature and identify the potential urinary biomarkers for early diagnosis of AD.
| Materials and Methods|| |
In the study, a comprehensive electronic search was performed in PubMed and Alzforum databases using the Boolean expression (Alzheimer) AND (urine) AND (biomarker) AND (metabolomics). We searched for scientific papers without any time limit, as this area of study is relatively new. Those studies that were not based on diagnostic biomarkers were filtered. This procedure was repeated till December 2019, before the finalization of the manuscript, to include papers published on this subject until the submission of the present work. We also performed hand-searches of references cited in the associated studies to identify additional contributions.
No restrictions were imposed regarding language or country of publication. Assessment of eligibility was preliminary based on the analysis of the title and abstract of selected papers, followed by full-text screening. Biomarkers were grouped according to three major types namely oxidative stress associated, amyloid plaque formation associated and energy metabolism associated biomarkers. PRISMA criteria were followed for the systematic review [Figure 1].
|Figure 1 PRISMA flowchart − inclusion and exclusion criteria application in the systematic study.|
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The inclusion and exclusion criteria of the studies are described as:
- Inclusion: All articles on urinary biomarkers and the associated metabolomic profiling linked to the early diagnosis of Alzheimer’s disease were included in the study.
- Exclusion: All results and articles associated with therapy primarily, those studies focussed on only the analytical techniques, review articles and ones that do not focus on the early diagnosis (i.e. preclinical and mild cognitive impairment cases) were excluded from the systematic study.
| Results|| |
As depicted in [Figure 1], 30 records were identified from the electronic searches performed across PubMed (under “Best Match” conditions) and Alzforum databases. The duplicate entries were then removed and 19 unique records were identified. From the obtained entries, five listings based on webinars and seminars were removed. On reviewing the full-text articles of 14 records, and performing an assessment on their eligibility, the exclusion criteria were applied to filter off the review articles, studies based on analytical techniques, studies focused on treatments and those articles that do not involve the early diagnosis of dementia, AD or MCI. As a result, the data for this study were extracted from a total of six articles.
The studies analyzed were compiled and represented in [Table 1]. The table contains various information such as authors (with the year of publication), sample number, country, platforms used, list of reported metabolites and our classification of the reported biomarkers based on the pathological involvement. All six studies with 26 potential biomarkers have been analyzed to arrive at the link between the brain and the urine. From the analysis, we could arrive at the possible involvement of these metabolites in their corresponding metabolic pathways which could influence AD pathogenesis.
|Table 1 Summary of studies identified from the systematic review of literature|
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| Discussion|| |
The development of reliable biomarkers that measures the risk, presence, and progression of the disease is one of the main goals and challenges in the research of neurodegenerative diseases, especially in AD. The existence of neuroimaging possibilities, CSF and blood-based biomarkers have helped in monitoring brain changes associated with its structures and inflammatory processes, but do not promote easily obtainable results from a larger population or with any inexpensive testing procedures. , Therefore, the need for biomarkers which not only provides an opportunity for in-depth investigation of the changes related to the early diagnosis of AD pathology but also serve as non-invasive alternatives with easier sample collection and processing procedures are required. This study attempts to aid in achieving that goal by identifying potential urinary biomarkers that could help in the large-scale screening of AD and attempt to establish a relationship between the metabolites and the associated metabolic pathways through the available literature.
Methodologies involved in biomarker metabolite analysis in this review include various techniques such as 1H-NMR, LC-MS, LC-MS/MS, UHPLC, UPLC and GC-MS which renders the data pooling more complex for quantitative comparisons and further analysis. However, the relative changes observed in the metabolite status in AD samples with respect to control samples, have been considered as criteria for metabolite selection. The major metabolites identified were relevant to the metabolism of tryptophan, arginine, tyrosine, cysteine and choline metabolisms [Figure 2]. The metabolites were grouped into the following AD pathological processes namely, oxidative stress, amyloid plaque formation, and energy metabolism associated biomarkers [Figure 3].
|Figure 2 Metabolic disturbances related to metabolites leading to neurodegeneration and AD pathology.|
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|Figure 3 Graphical representation of the framework used to identify urinary biomarkers for AD pathology − i) Study organisms; ii) analytical techniques; iii) mechanisms associated with AD pathology.|
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Biomarkers associated with oxidative stress
Fukuhara et al., have reported three metabolites namely 3-hydroxykynurenine, homogentisate and allantoin, which are relevant to oxidative stress, a major pathological process for AD.  3-hydroxy kynurenine is associated with the catabolic pathway of tryptophan metabolism.,, It acts as a potential glutamate receptor antagonist and also results in the accumulation of ROS  which could be due to the production of quinolinic acid. Quinolinic acid, under normal conditions, helps in the synthesis of NAD+ but under pathophysiological concentrations can lead to neurotoxicity and dysfunction, by various mechanisms. An increase in 3-hydroxy kynurenine in urine levels in AD samples, in turn, indicates decreased neurotransmitter activity in the brain, due to its antagonistic nature.
Homogentisate is an oxidative stress associated biomarker which is associated with alkaptonuria,, also an intermediate in the catabolism of tyrosine and phenylalanine pathways. It reacts with the ROS present in the system and forms benzoquinone acetate, under oxidative stress conditions. Increased levels of homogentisate in the urine of AD patients indicated decreased neurotransmitter production. It also reduces the amount of maleylacetoacetate, which is involved in the energy metabolism process of the brain.
Allantoin, a product of purine metabolism and is also known to play a role in the neuronal cell proliferation of the hippocampal region of the brain. An increase in allantoin levels in urine could indicate the increase in ROS in the system. Being the end product of the uric acid metabolism, significant changes from any non-enzymatic process could be detected using this biomarker with higher reliability in comparison to the other biomarkers.
A decrease in the concentration of N1-acetylspermidine in the urine from AD individuals was reported in the biochemical study. N1-acetylspermidine is an anti-oxidant belonging to the polyamine family, which plays an important role in stabilizing the cell membranes, cell growth, and differentiation and in the biosynthesis of several important molecules.
Acetyl-L-carnitine (ALC) is an antioxidant intrinsically containing unique neuro-modulatory and neurotrophic properties, which may play an important role in counteracting AD processes. Acetyl-L-carnitine is also neuroprotective when administered at supraphysiologic concentrations, and so their decreased concentration in urine could indicate an increased risk of AD. A study suggests that ALC might possess other important functions besides antioxidant activities such as neuroprotection in their involvement with the nervous system.
Arginosuccinic acid is a precursor for arginine in the urea cycle or citrulline-nitric oxide cycle. Arginine, being an excitatory amino acid, its increased levels in urine could indicate the arginine-excessive transshipment and conduction which could in turn damage nerve cells and result in AD.L-glutamine, the non-essential amino acid amide of glutamic acid, may act as a protectant in stress responses  and could affect the brain functioning under increased levels of the same. A study has reported that variations in glutamatergic signaling, including the fluctuations in the expression of glutamate transporters and its enzymes could lead to neuronal dysfunction of AD.
5-L-glutamyl glycine is an excitatory amino acid receptor antagonist with a structure similar to γ −aminobutyrate, which can reduce the release of glutamic acid by acting as a postsynaptic blocker and antagonizing glutamate toxicity thereby protecting the nerve cells from anoxic neuronal death. The low level of this inhibitory amino acid in the brain may cause memory disorders in AD patients. Increased level of 5-L-glutamyl glycine in the urine of AD patients might indicate decreased GABA in AD patients, leading to memory dysfunction.
Dimethyl arginine is involved in arginine metabolism. From arginine, nitrous oxide (NO) is produced by NO synthase which not only results in oxidative damage, but also causes neurotoxicity along with ROS in the system. When the level of arginine increases, the amount of NO produced would increase resulting in oxidative stress development, which would in-turn cause damages to the neuronal cell. This is usually prevented by dimethylarginine. There are two types of dimethylarginine namely symmetric dimethyl arginine (SDMA) and asymmetric dimethylarginine (ADMA) which act as nitrous oxide (NO) inhibitors. The ADMA inhibits NO production by inhibiting NO synthase enzyme. The SDMA inhibits NO production by competitively inhibiting the L-arginine uptake by the cell. When this metabolite is downregulated, the NO production increases and results in oxidative damage.
4-guanidinobutanoic acid is produced by the transfer of the guanidine group from arginine to gamma-aminobutyric acid through transamination., This metabolite causes neuronal damage due to the development of oxidative stress. 1-methyladenosine and 5’-deoxyadenosine are formed through purine metabolism. They are the modified nucleotides due to oxidative stress and hence can be used as a biomarker for detecting oxidative stress.
Biomarkers associated with amyloid plaque formation
Methionine, homocysteine and S-adenosyl methionine are the products of cysteine metabolism. Methionine rich diets could result in the production of higher amounts of homocysteine in the plasma, contributing towards hyperhomocysteinemia, which is often correlated with dementia, due to cysteine-rich-Aβ plaque formation.
S-adenosyl methionine (SAM) serves as a ubiquitous methyl group donor and is necessary for the synthesis of neurotransmitters, neuronal membrane stability, and DNA methylation. A decreased level of SAM in urine could indicate an increased risk of AD where a similar case was reported in CSF samples Taurine has many diverse biological functions serving as a neurotransmitter in the brain and as a facilitator in the transport of ions, whose imbalance could facilitate amyloid plaque formation. It helps in maintaining the structural integrity of the neuronal membrane, which is downregulated in AD urine samples.
5-hydroxy indole acetic acid is a metabolite of serotonin, which is one of the important neurotransmitters in the brain, belonging to the tryptophan metabolism., Initially, tryptophan will get converted to serotonin by the action of two enzymes namely tryptophan hydrolase and aromatic L-amino acid decarboxylase and is then converted to 5-hydroxy indole acetic acid by monoamine oxidase, which was downregulated in the AD urine., Since serotonin is a neurotransmitter and is involved in the cognitive function of the brain, dysregulation of the above metabolite results in cognitive dysfunction.
Choline is an important metabolite since it is required for brain development, which serves as a precursor of acetylcholine and as a methyl donor in various metabolic processes., The levels of choline are decreased in urine samples of AD patients. 1-octen-3-ol, is upregulated in AD and is produced by the transformation of C18-polyunsaturated fatty acids mediated by lipoxygenase/hydroperoxide lyase. It is found that 1-octen-3-ol interferes in the dopamine packaging in cells and causes oxidation of dopamine into 3,4-dihydroxy phenylacetaldehyde. When this metabolite is upregulated, it results in the depletion of dopamine stored in the neurons resulting in cognitive decline.
3,4-dihydroxyphenyglycol is upregulated in AD urine and is produced from norepinephrine by the action of monoamine oxidase., Since norepinephrine is involved in the cognitive activities of the brain, its dysfunction could lead directly to a cognitive disorder. The relation between the mechanism involved in the Aβ plaque formation and 3,4-dihydroxyphenyglycol remains uncertain, despite several studies confirming the involvement of the metabolite in Aβ plaque formation.
Biomarkers associated with energy metabolism
Desaminotyrosine is upregulated in AD urine and is one of the phenolic acid metabolites of tyrosine by tyrosine aminotransferase,, which plays a role in neurotransmitter production and also has been proposed to be involved in Krebs cycle as a key intermediate in energy metabolism by undergoing iodination.
N-acryloyl glycine, a metabolite of fatty acids, is an acyl-glycine found in most human biofluids., Isobutyryl-L-carnitine is a product of the acyl-CoA dehydrogenases, which are a group of mitochondrial enzymes involved in fatty acid metabolism. Impaired energy metabolism, is well established in AD brains, indicating mitochondrial dysfunction., Therefore, the significant changes in these two metabolites seen in AD urine samples might indicate that AD is accompanied by, an underlying metabolic disorder affecting fatty acid oxidation and mitochondrial dysfunction. Their increased levels in urine can be used to diagnose AD associated with mitochondrial fatty acid β-oxidation.
1-(beta-D-ribofuranosyl)-1,4-dihydro-nicotinamide is a reduced form of nicotinamide riboside which is a precursor for NADH., NADH not only serves as an energy source but also helps in preventing Aβ plaque formation by activating peroxisome proliferator-activated receptor-γ coactivator-1α which helps in degrading beta-site amyloid precursor protein cleaving enzyme1 (BACE-1). Lower amounts of the aforementioned metabolite impaired energy metabolism along with accelerated Aβ plaque formation.
| Conclusion|| |
Three metabolites namely 5-hydroxy indole acetic acid, L-arginine and allantoin were found as putative urinary biomarkers since their alterations have been reported in both AD patients and AD mice. In AD, 5-hydroxy indole acetic acid level was downregulated and this indicates the reduced level of serotonin in the brain. The increased levels of L-arginine in AD urine implies enhanced levels of L-arginine in the brain which could be converted into nitric oxide due to the action of NO synthase leading to oxidative stress. Increase in the levels of allantoin could be due to the action of ROS on uric acid in the brain. Interestingly, these metabolites are also found to be elevated in the blood of MCI patients, which could have presumably arrived from brain through blood brain barrier. The predictive nature of these metabolites for AD diagnosis needs to be validated through longitudinal and cross-sectional studies.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]