Urinary Biomarkers of Brain Diseases

Urine Proteomic Signatures of Mild Hypothermia Treatment in Cerebral Ischemia-Reperfusion Injury in Rats

Mild hypothermia (MH) is an effective measure to alleviate cerebral ischemia-reperfusion (I/R) injury. However, the underlying biological mechanisms remain unclear. This study set out to investigate dynamic changes in urinary proteome due to MH in rats with cerebral I/R injury and explore the neuroprotective mechanisms of MH. A Pulsinelli's four-vessel occlusion (4-VO) rat model was used to mimic global cerebral I/R injury. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to profile the urinary proteome of rats with/without MH (32 °C) treatment after I/R injury. Representative differentially expressed proteins (DEPs) associated with MH were validated by western blotting in hippocampus. A total of 597 urinary proteins were identified, among which 119 demonstrated significant changes associated with MH. Gene Ontology (GO) annotation of the DEPs revealed that MH significantly enriched in endopeptidase activity, inflammatory response, aging, response to oxidative stress and reactive oxygen species, blood coagulation, and cell adhesion. Notably, changes in 12 DEPs were significantly reversed by MH treatment. Among them, 8 differential urinary proteins were previously reported to be closely associated with brain disease, including NP, FZD1, B2M, EPCR, ATRN, MB, CA1and VPS4A. Two representative proteins (FZD1, B2M) were further validated by western blotting in the hippocampus and the results were shown to be consistent with urinary proteomic analysis. Overall, this study strengthens the idea that urinary proteome can sensitively reflect pathophysiological changes in the brain, and appears to be the first study to explore the neuroprotective effects of MH by urinary proteomic analysis. FZD1 and B2M may be involved in the most fundamental molecular biological mechanisms of MH neuroprotection.

Chitosan lecithin nanocomposite based electrochemical biosensor for glycine detection in biological matrices

Increased glycine concentrations are associated with altered metabolism of cancer cells and is reflected in the bodily fluids of the brain cancer patients. Various studies have been conducted in past to detect glycine as an imaging biomarker via NMR Spectroscopy tools. However, the use is limited because of the low concentration and different in vivo detection due to overlapping of peaks with myo-inositol in same spectral position. Alongside, little is known about the electrochemical potential of Glycine as a biomarker for brain cancer. The prime impetus of this study was to check the feasibility of glycine as non-invasive biomarker for brain cancer. A divergent approach to detect glycine "non-enzymatically" via unique chitosan lecithin nanocomposite has been utilised during this study. The electrochemical inactivity at provided potential that prevented glycine to get oxidized or reduced without mediator was compensated utilising the chitosan-lecithin nanocomposite. Thus, a redox mediator (Prussian blue) was used for high sensitivity and indirect detection of glycine. The chitosan nanoparticles-lecithin nanocomposite is used as a matrix. The electrochemical analysis of the onco-metabolomic biomarker (glycine) utilizing cyclic voltammetry in glycine spiked multi-Purpose artificial urine was performed to check distribution of glycine over physiological range of glycine. A wide linear range of response varying over the physiological range from 7 to 240 μM with a LOD 8.5 μM was obtained, showing potential of detection in biological samples. We have further evaluated our results via simulating the interaction of mediator and matrix with Glycine by HOMO-LUMO band fluctuations.

Mendelian randomization study of the relationship between blood and urine biomarkers and schizophrenia in the UK Biobank cohort

BACKGROUND

The identification of suitable biomarkers is of crucial clinical importance for the early diagnosis of treatment-resistant schizophrenia (TRS). This study aims to comprehensively analyze the association between TRS and blood and urine biomarkers.

METHODS

Candidate TRS-related single nucleotide polymorphisms (SNPs) were obtained from a recent genome-wide association study. The UK Biobank cohort, comprising 376,807 subjects with blood and urine biomarker testing data, was used to calculate the polygenic risk score (PRS) for TRS. Pearson correlation analyses were performed to evaluate the correlation between TRS PRS and each of the biomarkers, using calculated TRS PRS as the instrumental variables. Bidirectional two-sample Mendelian randomization (MR) was used to assess potential causal associations between candidate biomarkers with TRS.

RESULTS

Here we identify a significant association between TRS PRS and phosphate (r = 0.007, P = 1.96 × 10-4). Sex subgroup analyses identify seven and three candidate biomarkers associated with TRS PRS in male and female participants, respectively. For example, total protein and phosphate for males, creatinine and phosphate for females. Bidirectional two-sample MR analyses indicate that TRS is negatively associated with cholesterol (estimate = -0.363, P  = 0.008). Conversely, TRS is positively associated with total protein (estimate = 0.137, P  = 0.027), mean corpuscular volume (estimate = 0.032, P  = 2.25 × 10-5), and mean corpuscular hemoglobin (estimate = 0.018, P  = 0.007).

CONCLUSIONS

Our findings provide insights into the roles of blood and urine biomarkers in the early detection and treatment of TRS.

Quantitative comparison of the renal pelvic urine and bladder urine to examine modifications of the urine proteome by the lower urinary tract

PURPOSE

Urine proteome is a valuable reservoir of biomarkers for disease diagnosis and monitoring. Following formation as the plasma filtrate in the kidney, urine is progressively modified by the active reabsorption and secretion of the urinary tract. However, little is known about how the urine proteome changes as it passes along the urinary tract.

EXPERIMENTAL DESIGN

To investigate this, we compared the proteome composition of the renal pelvis urine (RPU) and individually self-voided bladder urine (BU) collected from seven unilateral urinary tract obstruction male patients by LC-MS/MS screening. To our knowledge, this is the first proteomic comparison of RPU and BU samples from the same individual.

RESULTS

Overall, RPU and BU proteomes did not exhibit proteins that were exclusively present in all samples of one urine type while in none of the other type. Nonetheless, BU had more overrepresented proteins that were observed at a higher frequency than RPU. Label-free quantitative analyses revealed BU-RPU differential proteins that are enriched in exosomes and extracellular proteins. However, the differences were not significant after corrections for multiple testing. Interestingly, we observed a significant increase of collagen peptides with hydroxyproline modifications in the BU samples, suggesting differences in protein modifications.

CONCLUSIONS AND CLINICAL RELEVANCE

Our study revealed no substantial differences at the protein level between the BU and RPU samples. Future investigations with expanded cohorts would provide more insights about the urothelial-urinary interactions.

Portable and Recyclable Luminescent Lanthanide Coordination Polymer Film Sensors for Adenosine Triphosphate in Urine

Adenosine triphosphate (ATP) is a small molecule that is released to the urine from bladder urothelial cells and the bladder mucosal band of the human body. In certain cases, ATP can serve as a biomarker in bladder disease. For the practical applicability of luminescent sensors for ATP in urine, it is significant to find a new strategy for making the detection progress simple and available for in-field urine analysis. Here, a novel luminescent lanthanide coordination polymer (Tb-BPA) was designed and synthesized for quick and sensitive detection of ATP through luminescence quenching with a quenching constant of 4.90 × 103 M-1 and a detection limit of 0.55 × 10-6 M. Besides, Tb-BPA has excellent anti-interference ability and can detect ATP in simulated urine with a small relative standard deviation (<4%). Moreover, the luminescent polyacrylonitrile nanofiber films modified by Tb-BPA were prepared by electrospinning and were used for ATP visual detection. Notably, this film is easy to recover and reuse, and maintains good detection performance after at least 7 cycles.

LC-MS-based urine metabolomics analysis of chronic subdural hematoma for biomarker discovery

BACKGROUND

Chronic subdural hematoma (CSDH) is one of the most common neurosurgical diseases with atypical manifestations. The aim of this study was to utilize urine metabolomics to explore potential biomarkers for the diagnosis and prognosis of CSDH.

METHODS

Seventy-seven healthy controls and ninety-two patients with CSDH were enrolled in our study. In total, 261 urine samples divided into the discovery group and validation group were analyzed by LC-MS. The statistical analysis and functional annotation were applied to discover potential biomarker panels and altered metabolic pathways.

RESULTS

A total of 53 differential metabolites were identified in this study. And the urinary metabolic profiles showed apparent separation between patients and controls. Further functional annotation showed that the differential metabolites were associated with lipid metabolism, fatty acid metabolism, amino acid metabolism, biotin metabolism, steroid hormone biosynthesis, and pentose and glucuronate interconversions. Moreover, one panel of Capryloylglycine, cis-5-Octenoic acid, Ethisterone, and 5,6-DiHETE showed good predictive performance in the diagnosis of CSDH, with an AUC of 0.89 in discovery group and an AUC of 0.822 in validation group. Another five metabolites (Trilobinol, 3'-Hydroxyropivacaine, Ethisterone, Arginyl-Proline, 5-alpha-Dihydrotestosterone glucuronide) showed the levels of them returned to a healthy state after surgery, showing good possibility to monitor the recovery of CSDH patients.

CONCLUSION AND CLINICAL RELEVANCE

The findings of the study revealed urine metabolomic differences between CSDH and controls. The potentially diagnostic and prognostic biomarker panels of urine metabolites were established, and functional analysis demonstrated deeper metabolic disorders of CSDH, which might conduce to improve early diagnose of CSDH clinically.

Effect of electroacupuncture on global cerebral ischemia-reperfusion injury in rats: A urine proteome analysis

BACKGROUND

This study aimed to investigate dynamic urinary proteome changes of electroacupuncture (EP) on cerebral ischemia-reperfusion (CI/R) injured rats and to explore the therapeutic biological mechanisms of EP.

METHODS

First, changed urinary proteins were found in EP stimulation in healthy rats. Then, we used a CI/R injury rat model induced by Pulsinelli's four-vessel occlusion (4-VO) method to explore the function of EP on urinary proteome in CI/R injury. Urine samples were collected for proteome analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analysis.

RESULTS

In total, 384 proteins were identified, among which 47 proteins (23 upregulated, 24 downregulated) were differentially expressed with 0.6-log FC and p < .05. Gene ontology analysis revealed that the cell redox homeostasis, acute-phase response, response to lipopolysaccharide, and cellular response to glucocorticoid stimulus were significantly enriched. The partially biologically connected differential proteins were found by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis in the EP group. With the CI/R rat model, 80 proteins (27 upregulated, 53 downregulated) were significantly changed in the CI/R rats compared to the controls. Among these differentially expressed proteins (DEPs), 23 proteins (17 upregulated, six downregulated) showed significant changes after EP treatment (0.6-log FC change, p < .05). The main related biological processes were aging, immune response, acute-phase response, liver regeneration, protein catabolic process, and response to oxidative stress. Many metabolic pathways were enriched by KEGG analysis.

CONCLUSION

Our results indicate that the EP could alleviate cerebral damage induced by ischemia-reperfusion through an anti-inflammatory and metabolism regulation mechanism. The urinary proteome might reflect the pathophysiological changes in EP pretreatment in the treatment and prevention of CI/R injury.

Metabolites and Cognitive Decline in a Puerto Rican Cohort

Background

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans.

Objective

This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population.

Methods

We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory.

Results

We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory.

Conclusions

The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

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.

The Latest Developments in Using Proteomic Biomarkers from Urine and Serum for Non-Invasive Disease Diagnosis and Prognosis

Due to diagnostic improvements, medical diagnostics is demanding non-invasive or minimally invasive methods. Non-invasively obtained body fluids (eg., Urine, serum) can replace cerebral fluid, amniotic fluid, synovial fluid, bronchoalveolar lavage fluid, and others for diagnostic reasons. Many illnesses are induced by perturbations of cellular signaling pathways and associated pathway networks as a result of genetic abnormalities. These disturbances are represented by a shift in the protein composition of the fluids surrounding the tissues and organs that is, tissue interstitial fluid (TIF). These variant proteins may serve as diagnostic "signatures" for a variety of disorders. This review provides a concise summary of urine and serum biomarkers that may be used for the diagnosis and prognosis of a variety of disorders, including cancer, brain diseases, kidney diseases, and other system diseases. The studies reviewed in this article suggest that serum and urine biomarkers of various illnesses may be therapeutically useful for future diagnostics. Correct illness management is crucial for disease prognosis, hence non-invasive serum and urine biomarkers have been extensively studied for diagnosis, subclassification, monitoring disease activity, and predicting treatment results and consequences.

Phage Interactions with the Nervous System in Health and Disease

The central nervous system manages all of our activities (e.g., direct thinking and decision-making processes). It receives information from the environment and responds to environmental stimuli. Bacterial viruses (bacteriophages, phages) are the most numerous structures occurring in the biosphere and are also found in the human organism. Therefore, understanding how phages may influence this system is of great importance and is the purpose of this review. We have focused on the effect of natural bacteriophages in the central nervous system, linking them to those present in the gut microbiota, creating the gut-brain axis network, as well as their interdependence. Importantly, based on the current knowledge in the field of phage application (e.g., intranasal) in the treatment of bacterial diseases associated with the brain and nervous system, bacteriophages may have significant therapeutic potential. Moreover, it was indicated that bacteriophages may influence cognitive processing. In addition, phages (via phage display technology) appear promising as a targeted therapeutic tool in the treatment of, among other things, brain cancers. The information collected and reviewed in this work indicates that phages and their impact on the nervous system is a fascinating and, so far, underexplored field. Therefore, the aim of this review is not only to summarize currently available information on the association of phages with the nervous system, but also to stimulate future studies that could pave the way for novel therapeutic approaches potentially useful in treating bacterial and non-bacterial neural diseases.

Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson's disease

BACKGROUND

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson's disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.

METHODS

Utilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).

RESULTS

After efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.

CONCLUSIONS

These findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.

Repeated Low-Level Blast Exposure Alters Urinary and Serum Metabolites

Repeated exposure to low-level blast overpressures can produce biological changes and clinical sequelae that resemble mild traumatic brain injury (TBI). While recent efforts have revealed several protein biomarkers for axonal injury during repetitive blast exposure, this study aims to explore potential small molecule biomarkers of brain injury during repeated blast exposure. This study evaluated a panel of ten small molecule metabolites involved in neurotransmission, oxidative stress, and energy metabolism in the urine and serum of military personnel (n = 27) conducting breacher training with repeated exposure to low-level blasts. The metabolites were analyzed using HPLC-tandem mass spectrometry, and the Wilcoxon signed-rank test was used for statistical analysis to compare the levels of pre-blast and post-blast exposures. Urinary levels of homovanillic acid (p < 0.0001), linoleic acid (p = 0.0030), glutamate (p = 0.0027), and serum N-acetylaspartic acid (p = 0.0006) were found to be significantly altered following repeated blast exposure. Homovanillic acid concentration decreased continuously with subsequent repeat exposure. These results suggest that repeated low-level blast exposures can produce measurable changes in urine and serum metabolites that may aid in identifying individuals at increased risk of sustaining a TBI. Larger clinical studies are needed to extend the generalizability of these findings.

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.

Changes of development from childhood to late adulthood in rats tracked by urinary proteome

To date, studies of development have mainly focused on the embryonic stage and a short time thereafter. There has been little research on the whole life of an individual from childhood to aging and death. For the first time, we used non-invasive urinary proteome technology to track changes in several important developmental timepoints in a group of rats, covering 10 timepoints from childhood, adolescence, young adulthood, middle adulthood, and near death in old age. Similar to previous studies on puberty, proteins were detected involved in sexual or reproductive maturation, mature spermatozoa in seminiferous tubules (first seen), gonadal hormones, decline of oestradiol, brain growth, and central nervous system myelination, and our differential protein enrichment pathways also included reproductive system development, tube development, response to hormone, response to oestradiol, brain development, and neuron development. Similar to previous studies in young adults, proteins were detected involved in musculoskeletal maturity, peak bone mass, development of the immune system, and growth and physical development, and our differential protein enrichment pathways also included skeletal system development, bone regeneration, system development, immune system processes, myeloid leukocyte differentiation, growth, and developmental growth. Studies on aging-related changes in neurons and neurogenesis have been reported, and we also found relevant pathways in aged rats, such as regulation of neuronal synaptic plasticity and positive regulation of long-term neuronal synaptic plasticity. However, at all timepoints throughout life, there were many biological pathways revealed by differential urinary protein enrichment involving multiple organs, tissues, systems, etc., that have not been mentioned in existing studies. This study shows comprehensive and detailed changes in rat lifetime development through the urinary proteome, helping to fill the gap in development research. Moreover, it provides a new approach to monitoring changes in human health and diseases of aging using the urinary proteome.

Relevance of Biochemical Deep Phenotyping for a Personalised Approach to Parkinson's Disease

Parkinson's disease (PD) is a multifactorial neurodegenerative disorder characterised by the progressive loss of dopaminergic neurons in the nigrostriatal tract. The identification of disease-modifying therapies is the Holy Grail of PD research, but to date no drug has been approved as such a therapy. A possible reason is the remarkable phenotypic heterogeneity of PD patients, which can generate confusion in the interpretation of results or even mask the efficacy of a therapeutic intervention. This heterogeneity should be taken into account in clinical trials, stratifying patients by their expected response to drugs designed to engage selected molecular targets. In this setting, stratification methods (clinical and genetic) should be supported by biochemical phenotyping of PD patients, in line with the deep phenotyping concept. Collection, from single patients, of a range of biological samples would streamline the generation of these profiles. Several studies have proposed biochemical characterisations of patient cohorts based on analysis of blood, cerebrospinal fluid, urine, stool, saliva and skin biopsy samples, with extracellular vesicles attracting increasing interest as a source of biomarkers. In this review we report and critically discuss major studies that used a biochemical approach to stratify their PD cohorts. The analyte most studied is α-synuclein, while other studies have focused on neurofilament light chain, lysosomal proteins, inflammasome-related proteins, LRRK2 and the urinary proteome. At present, stratification of PD patients, while promising, is still a nascent approach. Deep phenotyping of patients will allow clinical researchers to identify homogeneous subgroups for the investigation of tailored disease-modifying therapies, enhancing the chances of therapeutic success.

Changes in the urinary proteome before and after quadrivalent influenza vaccine and COVID-19 vaccination

The proteome of urine samples from quadrivalent influenza vaccine cohort were analyzed with self-contrasted method. Significantly changed urine protein at 24 hours after vaccination was enriched in immune-related pathways, although each person’s specific pathways varied. We speculate that this may be because different people have different immunological backgrounds associated with influenza. Then, urine samples were collected from several uninfected SARS-CoV-2 young people before and after the first, second, and third doses of the COVID-19 vaccine. The differential proteins compared between after the second dose (24h) and before the second dose were enriched in pathways involving in multicellular organismal process, regulated exocytosis and immune-related pathways, indicating no first exposure to antigen. Surprisingly, the pathways enriched by the differential urinary protein before and after the first dose were similar to those before and after the second dose. It is inferred that although the volunteers were not infected with SARS-CoV-2, they might have been exposed to other coimmunogenic coronaviruses. Two to four hours after the third vaccination, the differentially expressed protein were also enriched in multicellular organismal process, regulated exocytosis and immune-related pathways, indicating that the immune response has been triggered in a short time after vaccination. Multicellular organismal process and regulated exocytosis after vaccination may be a new indicator to evaluate the immune effect of vaccines. Urinary proteome is a terrific window to monitor the changes in human immune function.

Urinary Proteome Analysis of Global Cerebral Ischemia-Reperfusion Injury Rat Model via Data-Independent Acquisition and Parallel Reaction Monitoring Proteomics

Cerebral ischemia–reperfusion (I/R) injury is the leading cause of death in severe hypotension caused by cardiac arrest, drowning, and excessive blood loss. Urine can sensitively reflect pathophysiological changes in the brain even at an early stage. In this study, a rat model of global cerebral I/R injury was established via Pulsinelli’s four-vessel occlusion (4-VO) method. Overall, 164 urinary proteins significantly changed in the 4-VO rat urine samples compared to the control samples by data-independent acquisition (DIA) proteomics technique (1.5-fold change, p < 0.05). Gene Ontology annotation showed that the acute-phase response, the ERK1 and ERK2 cascade, endopeptidase activity, blood coagulation, and angiogenesis were overrepresented. After parallel reaction monitoring (PRM) validation, 15 differential proteins having human orthologs were verified as the potential urinary markers associated with cerebral I/R injury. Of these potential biomarkers, 8 proteins were reported to be closely associated with cerebral I/R injury. Nine differential proteins changed even when there were no clinical manifestations or histopathological cerebral damage, including FGG, COMP, TFF2, HG2A, KNG1, CATZ, PTGDS, PRVA, and HEPC. These 9 proteins are potential biomarkers for early screening of cerebral I/R injury to prevent the development of cerebral injury. KNG1, CATZ, PTGDS, PRVA, and HEPC showed an overall trend of upregulation or downregulation at 12 and 48 h after I/R injury, reflecting the progression of cerebral I/R injury. These 5 proteins may serve as potential biomarkers for prognostic evaluation of cerebral I/R injury. These findings provide important clues to inform the monitoring of cerebral I/R injury and further the current understanding of its molecular biological mechanisms.

Molecular species of oxidized phospholipids in brain differentiate between learning- and memory impaired and unimpaired aged rats

Loss of cognitive function is a typical consequence of aging in humans and rodents. The extent of decline in spatial memory performance of rats, assessed by a hole-board test, reaches from unimpaired and comparable to young individuals to severely memory impaired. Recently, proteomics identified peroxiredoxin 6, an enzyme important for detoxification of oxidized phospholipids, as one of several synaptosomal proteins discriminating between aged impaired and aged unimpaired rats. In this study, we investigated several components of the epilipidome (modifications of phospholipids) of the prefrontal cortex of young, aged memory impaired (AI) and aged unimpaired (AU) rats. We observed an age-related increase in phospholipid hydroperoxides and products of phospholipid peroxidation, including reactive aldehydophospholipids. This increase went in hand with cortical lipofuscin autofluorescence. The memory impairment, however, was paralleled by additional specific changes in the aged rat brain epilipidome. There was a profound increase in phosphocholine hydroxides, and a significant decrease in phosphocholine-esterified azelaic acid. As phospholipid-esterified fatty acid hydroxides, and especially those deriving from arachidonic acid are both markers and effectors of inflammation, the findings suggest that in addition to age-related reactive oxygen species (ROS) accumulation, age-related impairment of spatial memory performance has an additional and distinct (neuro-) inflammatory component.

Many kinds of oxidized proteins are present more in the urine of the elderly

Background

Many studies have shown an association between aging and oxidation. To our knowledge, there have been no studies exploring aging-related urine proteome modifications. The purpose of this study was to explore differences in global chemical modifications of urinary protein at different ages.

Methods

Discovery (n=38) cohort MS data including children, young and old groups were downloaded from three published studies, and this data was analyzed using open-pFind for identifying modifications. Verification cohort human samples (n=28) including young, middle-aged, and old groups, rat samples (n=7) at three-time points after birth, adulthood, and old age were collected and processed in the laboratory simultaneously based on label-free quantification combined with pFind.

Results

Discovery cohort: there were 28 kinds of differential oxidations in the old group that were higher than those in the young or children group in. Verification cohort: there were 17 kinds of differential oxidations of 49 oxidized proteins in the middle and old groups, which were significantly higher than those in the young group. Both oxidations and oxidized proteins distinguished different age groups well. There were also 15 kinds of differential oxidations in old age higher than others in the rat cohort. The results showed that the validation experiment was basically consistent with the results of the discovery experiment, showing that the level of oxidized proteins in urine increased significantly with age.

Conclusions

Our study is the first to show that oxidative proteins occur in urine and that oxidations are higher in older than younger ages. Perhaps improving the degree of excretion of oxidative protein in vivo through the kidney is helpful for maintaining the homeostasis of the body’s internal environment, delaying aging and the occurrence of senile diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09360-2.

Development of iPSC-based clinical trial selection platform for patients with ultrarare diseases

A "Leap-of-Faith" approach is used to treat patients with previously unknown ultrarare pathogenic mutations, often based on evidence from patients having dissimilar but more prevalent mutations. This uncertainty reflects the need to develop personalized prescreening platforms for these patients to assess drug efficacy before considering clinical trial enrollment. In this study, we report an 18-year-old patient with ultrarare Leigh-like syndrome. This patient had previously participated in two clinical trials with unfavorable responses. We established an induced pluripotent stem cell (iPSC)-based platform for this patient, and assessed the efficacy of a panel of drugs. The iPSC platform validated the safety and efficacy of the screened drugs. The efficacy of three of the screened drugs was also investigated in the patient. After 3 years of treatment, the drugs were effective in shifting the metabolic profile of this patient toward healthy control. Therefore, this personalized iPSC-based platform can act as a prescreening tool to help in decision-making with respect to patient's participation in future clinical trials.

Correlation Between Urine Formaldehyde and Cognitive Abilities in the Clinical Spectrum of Alzheimer’s Disease

Urine-based formaldehyde has been reported to be a potential biomarker for Alzheimer’s disease (AD). However, there is a lack of research about the correlation between urine formaldehyde and cognitive abilities in the clinical spectrum of AD, especially the preclinical period. The relationship of urine formaldehyde with APOE genotype, brain Aβ status and plasma pathological markers in AD are also not clear. This study intends to explore the correlation between urine formaldehyde and cognitive abilities throughout the AD continuum, to evaluate the role of APOE genotype and Aβ accumulation on urine formaldehyde, and further to clarify the relationship between urine formaldehyde level and AD plasma pathological markers. We recruited 72 cognitively normal controls (NC), 110 subjective cognitive decline (SCD), 140 objectively defined subtle cognitive decline (Obj-SCD), 171 mild cognitive impairment (MCI) and 136 AD dementia participants. Next, we collected the data of clinical materials, neuropsychological examination, APOE genotyping, urine formaldehyde concentration, 18F-florbetapir PET imaging and plasma biomarkers. Compared with NC, Obj-SCD and MCI groups, the level of urine formaldehyde was found to be significantly upregulated in SCD group. In addition, the level of urine formaldehyde was significantly higher in AD group compared to both NC and MCI groups. Further subgroup analysis showed that, the level of urine formaldehyde was higher in APOE ε4+ subgroup compared to APOE ε4– subgroup in both NC and AD groups. There was no difference in urine formaldehyde level between the brain Aβ+ subgroup and Aβ– subgroup in each group. In addition, regression analysis showed urine formaldehyde level was correlated with gender, plasma Aβ42 and p-Tau181/T-tau. The dynamic change of urine formaldehyde in the AD continuum could be used as a potential biomarker, and combined with comprehensive cognitive evaluation could become a useful method to distinguish SCD from NC and Obj-SCD, and to distinguish MCI from AD.

1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy

Background

5q spinal muscular atrophy (SMA) is a disabling and life-limiting neuromuscular disease. In recent years, novel therapies have shown to improve clinical outcomes. Yet, the absence of reliable biomarkers renders clinical assessment and prognosis of possibly already affected newborns with a positive newborn screening result for SMA imprecise and difficult. Therapeutic decisions and stratification of individualized therapies remain challenging, especially in symptomatic children. The aim of this proof-of-concept and feasibility study was to explore the value of ¹H-nuclear magnetic resonance (NMR)-based metabolic profiling in identifying non-invasive diagnostic and prognostic urinary fingerprints in children and adolescents with SMA.

Results

Urine samples were collected from 29 treatment-naïve SMA patients (5 pre-symptomatic, 9 SMA 1, 8 SMA 2, 7 SMA 3), 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. Using machine-learning algorithms, we propose a set of prediction models built on urinary fingerprints that showed potential diagnostic value in discriminating SMA patients from controls and DMD, as well as predictive properties in separating between SMA types, allowing predictions about phenotypic severity. Interestingly, preliminary results of the prediction models suggest additional value in determining biochemical onset of disease in pre-symptomatic infants with SMA identified by genetic newborn screening and furthermore as potential therapeutic monitoring tool.

Conclusions

This study provides preliminary evidence for the use of ¹H-NMR-based urinary metabolic profiling as diagnostic and prognostic biomarker in spinal muscular atrophy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-02075-x.

Alterations in Urine Metabolomics Following Sport-Related Concussion: A 1H NMR-Based Analysis

Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury.

Setting: Outpatient sports medicine clinic.

Participants: Twenty-six male youth sport participants.

Methods: Urine was analyzed pre-injury and after SRC by ¹H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome.

Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036).

Conclusion: We found that ¹H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.

Detection of Blood Cell Surface Biomarkers in Septic Mice

Sepsis arises when an infection induces a dysregulated immune response, resulting in organ damage. New methods are urgently needed to diagnose patients in the early stages of sepsis, and identify patients with a poor disease prognosis. One promising approach is to identify the rapid changes in cell surface antigens (biomarkers) that occur during sepsis, as a consequence of leukocyte mobilization and activation. This chapter describes the method for staining whole blood with fluorescently conjugated antibodies that detect cell surface biomarkers, and performing flow cytometry analysis to quantify biomarker-positive cells. Our protocol is designed to detect blood cell surface biomarkers in septic mice, but could also be applied to study potential biomarkers in blood obtained from human patients with sepsis and other medical conditions.

Plasma nontargeted peptidomics discovers potential biomarkers for major depressive disorder

PURPOSE

There are great demands for identifying biomarkers of major depressive disorder (MDD), a common mental illness with a prevalence of approximately 6%. Finding potential biomarkers to aid MDD diagnosis is in high demand.

EXPERIMENTAL DESIGN

In this study, a combination of pretreatment methods named salt-out assisted liquid-liquid extraction (SALLE) and nontargeted peptidomics based on nano-LC-Orbitrap/MS was primarily employed to discover the candidate peptide markers from the plasma of 238 subjects.

RESULTS

Many peptides were enriched and identified from the plasma, 42 of which showed significant differences between MDD patients and controls by univariate statistical analysis. A binary logistic regression (BLR) model combined four peptide markers (P1, P9, P17, P29) was established, yielding an overall prediction accuracy of 91.7% and 82.2% in the discovery and validation sets, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

In conclusion, the excellent performance of the BLR model in both discovery and validation sets demonstrates the robustness of the four peptide markers panel. It is very valuable for quantification of the absolute content of four peptides and further verification.

[Large-scale enrichment and identification of human urinary N-glycoproteins/N-glycopeptides]

N-Glycosylation of proteins, an important post-translational modification in eukaryotic cells, plays an essential role in the regulation of cell adhesion, migration, signal transduction, and apoptosis. Abnormal changes in protein glycosylation are closely related to the occurrence of many critical diseases, including diabetes, tumors, and neurological, kidney, and inflammatory diseases. A non-invasive type of liquid biopsy, urine sampling has the advantage of reducing the complexity of proteomic analysis. This facilitates the design of large-scale and continuous or multi-time point sampling strategies. However, the dynamic range of urinary protein abundance is relatively large, owing to individual differences and physiological conditions. Currently, there is a lack of specialized research on individual differences, physiological fluctuations, and physiological abundance ranges of urinary N-glycoproteins in large healthy populations. Therefore, it is difficult to accurately distinguish individual differences and normal physiological fluctuations from changes caused by disease; this poses a great challenge in disease marker research. Liquid chromatography-mass spectrometry (LC-MS) is an analytical technique widely used for the large-scale profiling of proteomes in biological systems, and the enrichment of N-glycopeptides is a prerequisite for their detection by MS.In this study, we established an approach based on hydrophilic interaction chromatography (HILIC) by optimizing the activation, cleaning, and elution processes of the enrichment method, for instance through the optimization of particle size and solvent composition, and investigated the identification number, selectivity, and stability of N-glycoprotein/N-glycopeptide enrichment under different experimental conditions. We found that N-glycoproteins and N-glycopeptides were highly enriched in a trifluoroacetic acid system with 5-μm filling particles in the HILIC column. On this basis, we analyzed the levels of N-glycoproteins/N-glycopeptides in urine samples. The consistency of N-glycoprotein/N-glycopeptide levels in urine samples taken from the same healthy person for five consecutive days was investigated by correlation analysis. This analysis revealed that the urinary N-glycoproteome of the same healthy person was relatively stable over a short period of time. Next, urinary samples from 20 healthy male volunteers and 20 healthy female volunteers were enriched for N-glycoproteins/N-glycopeptides, which were profiled by MS through qualitative and quantitative analyses. Screening and functional analysis of differential proteins were then carried out. A total of 1016 N-glycoproteins and 2192 N-glycopeptides were identified in the mid-morning urine samples of the 40 healthy volunteers. A label-free quantitation strategy was used to investigate the fluctuation range of the physiologically abundant urinary N-glycopeptides. The abundance of urinary N-glycopeptides spanned across approximately five orders of magnitude. Subsequently, gender differences in the N-glycosylation levels of urinary proteins were also explored in healthy people. Functional analysis of the N-glycoproteins that exhibited gender differences in abundance was performed. Based on multivariate statistical analysis, 206 differentially expressed proteins (p<0.05, fold change (FC)> 4) were identified. In females, we found 175 significantly down-regulated N-glycoproteins and 31 significantly up-regulated N-glycoproteins with respect to males. The expression levels of N-glycopeptides between the two groups suggested a clear gender difference. To investigate the biological processes and functions of these proteins, gene ontology (GO) analysis was performed on the N-glycoproteins/N-glycopeptides differentially expressed between males and females. Metabolic pathway analysis was also carried out based on the kyoto encyclopedia of genes and genomes (KEGG). Differentially expressed N-glycoproteins were mostly associated with platelet degranulation, extracellular region, and ossification. The top three relevant pathways were glycan biosynthesis and metabolism, metabolism of cofactors and vitamins, and lipid metabolism. Overall, sex may be an important factor for urinary N-glycoproteome differences among normal individuals and should be considered in clinical applications. This study provides relevant information regarding the function and mechanisms of the urinary glycoproteome and the screening of clinical biomarkers.

Innate immunity impacts social-cognitive functioning in people with multiple sclerosis and healthy individuals: Implications for IL-1ra and urinary immune markers

Social-cognitive difficulties can negatively impact interpersonal communication, shared social experience, and meaningful relationships. This pilot investigation examined the relationship between social-cognitive functioning and inflammatory markers in people with multiple sclerosis (MS) and demographically-matched healthy individuals. Additionally, we compared the immune marker profile in serum and urine-matched samples. Social cognitive functioning was objectively assessed using The Awareness of Social Inference Test - Short (TASIT-S) and subjectively assessed using self-reports of abilities in emotion recognition, emotional empathy, and cognitive theory of mind. In people with MS and healthy individuals, there were moderate-to-large negative relationships between pro-inflammatory biomarkers (serum IL-1β, IL-17, TNF-α, IP-10, MIP-1α, and urine IP-10, MIP-1β) of the innate immune system and social-cognitive functioning. In MS, a higher serum concentration of the anti-inflammatory marker IL-1ra was associated with better social-cognitive functioning (i.e., self-reported emotional empathy and TASIT-S sarcasm detection performance). However, there were mixed findings for anti-inflammatory serum markers IL-4 and IL-10. Overall, our findings indicate a relationship between pro-inflammatory cytokines and social-cognitive abilities. Future studies may provide greater insight into biologically-derived inflammatory processes, sickness behaviour, and their connection with social cognition.

Are Mannan-binding Lectine Serin Protease-2 and Alpha-1-microglobulin and Bukinin Precursor the Potential Biomarkers of Manic Episode? A Study via Urinary Proetomic Analysis

Objective

Investigating the molecular basis of bipolar disorder (BD) is crucial in terms of developing effective treatment strategies as well as objective laboratory-based diagnostic tools for the disease.

Methods

We examined the urine samples of BD patients both in manic episode and after remission and compared their urinary protein profiles with the controls. Twelve patients and twelve controls (C group) included to the study. Urinary samples of patients were first collected during manic episode (M group) and then after remission (R group). Two-dimensional gel electrophoresis (2-DE) coupled to MALDI-TOF/TOF massspectrometry approach and Western blot analysis were used.

Results

Alphα-1-microglobulin and bukinin precursor (AMBP), Mannan-binding lectine serin protease-2 (MASP-2), and Ig gamma-1-chain displayed significant increases in their abundance in the urine protein pool of M group in comparison to the C and R groups. Alpha-1B glycoprotein and prostaglandin-H2 D-isomerase (PGD2) levels were significantly higher in the urine protein pool of the M and R groups in comparison to the C group. Annexin A1 was downregulated significantly in the urine protein pool of the M group in comparison to the C group.

Conclusion

Intensities of MASP-2 and AMBP proteins discriminated manic episode from remission period and healthy controls indicating that these proteins may be candidate biomarkers for manic episode. The decrease in Annexin A1 and increase in Ig gamma-1 chain levels appeared to be associated with “Manic Episode” while the increase in PGD2 and alpha-1B glycoprotein levels appeared to be associated with “Bipolar Disorder”.

SHR/NCrl rats as a model of ADHD can be discriminated from controls based on their brain, blood, or urine metabolomes

Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity. The neurobiological mechanisms underlying ADHD are still poorly understood, and its diagnosis remains difficult due to its heterogeneity. Metabolomics is a recent strategy for the holistic exploration of metabolism and is well suited for investigating the pathophysiology of diseases and finding molecular biomarkers. A few clinical metabolomic studies have been performed on peripheral samples from ADHD patients but are limited by their access to the brain. Here, we investigated the brain, blood, and urine metabolomes of SHR/NCrl vs WKY/NHsd rats to better understand the neurobiology and to find potential peripheral biomarkers underlying the ADHD-like phenotype of this animal model. We showed that SHR/NCrl rats can be differentiated from controls based on their brain, blood, and urine metabolomes. In the brain, SHR/NCrl rats displayed modifications in metabolic pathways related to energy metabolism and oxidative stress further supporting their importance in the pathophysiology of ADHD bringing news arguments in favor of the Neuroenergetic theory of ADHD. Besides, the peripheral metabolome of SHR/NCrl rats also shared more than half of these differences further supporting the importance of looking at multiple matrices to characterize a pathophysiological condition of an individual. This also stresses out the importance of investigating the peripheral energy and oxidative stress metabolic pathways in the search of biomarkers of ADHD.

An electrochemical method for detecting the biomarker 4-HPA by allosteric activation of Acinetobacterbaumannii reductase C1 subunit

The C1 (reductase) subunit of 4-hydroxy-phenylacetate (4-HPA) 3-hydroxylase (HPAH) from the soil-based bacterium Acinetobacterbaumannii catalyzes NADH oxidation by molecular oxygen, with hydrogen peroxide as a by-product. 4-HPA is a potent allosteric modulator of C1, but also a known urinary biomarker for intestinal bacterial imbalance and for some cancers and brain defects. We thus envisioned that C1 could be used to facilitate 4-HPA detection. The proposed test protocol is simple and in situ and involves addition of NADH to C1 in solution, with or without 4-HPA, and direct acquisition of the H₂O₂ current with an immersed Prussian Blue–coated screen-printed electrode (PB-SPE) assembly. We confirmed that cathodic H₂O₂ amperometry at PB-SPEs is a reliable electrochemical assay for intrinsic and allosterically modulated redox enzyme activity. We further validated this approach for quantitative NADH electroanalysis and used it to evaluate the activation of NADH oxidation of C1 by 4-HPA and four other phenols. Using 4-HPA, the most potent effector, allosteric activation of C1 was related to effector concentration by a simple saturation function. The use of C1 for cathodic biosensor analysis of 4-HPA is the basis of the development of a simple and affordable clinical routine for assaying 4-HPA in the urine of patients with a related disease risk. Extension of this principle to work with other allosteric redox enzymes and their effectors is feasible.

Label-Free Liquid Chromatography-Mass Spectrometry Proteomic Analysis of Urinary Identification in Diabetic Vascular Dementia in a Han Chinese Population

Objective: This study aimed to identify potential diagnostic biomarkers of diabetic vascular dementia (DVD) and unravel the underlying mechanisms using mass spectrometry (MS).

Methods: Label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis was applied to urine samples from four groups, including 14 patients with vascular dementia (VD), 22 patients with type 2 diabetes mellitus (T2DM), 12 patients with DVD, and 21 normal controls (NCs). Searching the MS data by Proteome Discoverer software (ThermoFisher Scientific; Waltham, MA, USA), protein abundances were analyzed qualitatively and quantitatively and compared between these groups. Combining bioinformatics analysis using Gene Ontology (GO), pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), protein–protein interaction (PPI) network analysis using STRING, and literature searching, the differentially expressed proteins (DEPs) of DVD can be comprehensively judged and were further quantified by receiver operating characteristic (ROC) curve methods.

Results: The proteomic findings showed quantitative changes in patients with DVD compared to patients with NC, T2DM, and VD groups; among 4,744 identified urine proteins, 1,222, 1,152, and 1,180 proteins displayed quantitative changes unique to DVD vs. NC, T2DM, and VD, respectively, including 481 overlapped common DEPs. Then, nine unique proteins [including HP, SERPIND, ATP5PB, VNN2, ALDH3A1, U2AF2, C6, A0A5C2GRG5 (no name), and A0A5C2FZ29 (no name)] and two composite markers (CM) (A0A5C2GRG5+U2AF2 and U2AF2+C6) were confirmed by a ROC curve method.

Conclusion: This study provided an insight into the potential pathogenesis of DVD and elucidated a method for early detection.

Urinary proteome profiling for stratifying patients with familial Parkinson's disease

The prevalence of Parkinson's disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive, and non‐invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)‐based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non‐carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone were sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP, and other PD‐associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD.

Diagnosis of Glioma Molecular Markers by Terahertz Technologies

This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed.

An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the nervous system that primarily affects young adults. Although the exact etiology of the disease remains obscure, it is clear that alterations in the metabolome contribute to this process. As such, defining a reliable and disease-specific metabolome has tremendous potential as a diagnostic and therapeutic strategy for MS. Here, we provide an overview of studies aimed at identifying the role of metabolomics in MS. These offer new insights into disease pathophysiology and the contributions of metabolic pathways to this process, identify unique markers indicative of treatment responses, and demonstrate the therapeutic effects of drug-like metabolites in cellular and animal models of MS. By and large, the commonly perturbed pathways in MS and its preclinical model include lipid metabolism involving alpha-linoleic acid pathway, nucleotide metabolism, amino acid metabolism, tricarboxylic acid cycle, d-ornithine and d-arginine pathways with collective role in signaling and energy supply. The metabolomics studies suggest that metabolic profiling of MS patient samples may uncover biomarkers that will advance our understanding of disease pathogenesis and progression, reduce delays and mistakes in diagnosis, monitor the course of disease, and detect better drug targets, all of which will improve early therapeutic interventions and improve evaluation of response to these treatments.

Label-Free Liquid Chromatography-Mass Spectrometry Proteomic Analysis of the Urinary Proteome for Measuring the Escitalopram Treatment Response From Major Depressive Disorder

Major depressive disorder (MDD) is a common mental disorder that can cause substantial impairments in quality of life. Clinical treatment is usually built on a trial-and-error method, which lasts ~12 weeks to evaluate whether the treatment is efficient, thereby leading to some inefficient treatment measures. Therefore, we intended to identify early candidate urine biomarkers to predict efficient treatment response in MDD patients. In this study, urine samples were collected twice from 19 respondent and 10 non-respondent MDD patients receiving 0-, 2-, and 12-week treatments with escitalopram. Differential urinary proteins were subsequently analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Our two pilot tests suggested that the urine proteome reflects changes associated with major depressive disorder at the early stage of treatment measures. On week 2, 20 differential proteins were identified in the response group compared with week 0, with 14 of these proteins being associated with the mechanisms of MDD. In the non-response group, 60 differential proteins were identified at week 2, with 28 of these proteins being associated with the mechanisms of MDD. In addition, differential urinary proteins at week 2 between the response and non-response groups can be clearly distinguished by using orthogonal projection on latent structure-discriminant analysis (OPLS-DA). Our small pilot tests indicated that the urine proteome can reflect early effects of escitalopram therapy between the response and non-response groups since at week 2, which may provide potential early candidate urine biomarkers to predict efficient treatment measures in MDD patients.

Secreted Peptides for Diagnostic Trajectory Assessments in Brain Injury Rehabilitation

BACKGROUND

Rehabilitation following traumatic brain injury (TBI) significantly improves outcomes; yet TBI heterogeneity raises the need for molecular evidence of brain recovery processes to better track patient progress, evaluate therapeutic efficacy, and provide prognostication.

OBJECTIVE

Here, we assessed whether the trajectory of TBI-responsive peptides secreted into urine can produce a predictive model of functional recovery during TBI rehabilitation.

METHODS

The multivariate urinary peptidome of 12 individuals with TBI was examined using quantitative peptidomics. Measures were assessed upon admission and discharge from inpatient rehabilitation. A combination of Pavlidis template matching and partial least-squares discriminant analysis was used to build models on Disability Rating Scale (DRS) and Functional Independence Measure (FIM) scores, with participants bifurcated into more or less functional improvement groups.

RESULTS

The produced models exhibited high sensitivity and specificity with the area under the receiver operator curve being 0.99 for DRS- and 0.95 for FIM-based models using the top 20 discriminant peptides. Predictive ability for each model was assessed using robust leave-one-out cross-validation with Q² statistics of 0.64 (P = .00012) and 0.62 (P = .011) for DRS- and FIM-based models, respectively, both with a high predictive accuracy of 0.875. Identified peptides that discriminated improved functional recovery reflected heightened neuroplasticity and synaptic refinement and diminished cell death and neuroinflammation, consistent with postacute TBI pathobiology.

CONCLUSIONS

Produced models of urine-based peptide measures reflective of ongoing recovery pathobiology can inform on rehabilitation progress after TBI, warranting further study to assess refined stratification across a larger population and efficacy in assessing therapeutic interventions.

Urinary metabolic phenotyping for Alzheimer's disease

Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.

Urinary Biomarkers for Neurodegenerative Diseases

Global incidence of neurodegenerative diseases (NDDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD) is rapidly increasing, but the diagnosis of these diseases at their early stage is challenging. Therefore, the availability of reproducible and reliable biomarkers to diagnose such diseases is more critical than ever. In addition, biomarkers could be used not only to diagnose diseases but also to monitor the development of disease therapeutics. Urine is an excellent biofluid that can be utilized as a source of biomarker to diagnose not only several renal diseases but also other diseases because of its abundance in invasive sampling. However, urine was conventionally regarded as inappropriate as a source of biomarker for neurodegenerative diseases because it is anatomically distant from the central nervous system (CNS), a major pathologic site of NDD, in comparison to other biofluids such as cerebrospinal fluid (CSF) and plasma. However, recent studies have suggested that urine could be utilized as a source of NDD biomarker if an appropriate marker is predetermined by metabolomic and proteomic approaches in urine and other samples. In this review, we summarize such studies related to NDD.

Host urine immunological biomarkers as potential candidates for the diagnosis of tuberculosis

OBJECTIVE

To investigate the potential of host urinary biomarkers as diagnostic candidates for tuberculosis (TB).

METHODS

Adults self-presenting with symptoms requiring further investigation for TB were enrolled in Cape Town, South Africa. Participants were later classified as having TB or other respiratory diseases (ORD) using results from TB confirmatory tests. The concentrations of 29 analytes were evaluated in urine samples from participants using the Luminex platform, and their diagnostic potential was assessed using standard statistical approaches.

RESULTS

Of the 151 study participants, 34 (22.5%) were diagnosed with TB and 26 (17.2%) were HIV-positive. Seven biomarkers showed potential as TB diagnostic candidates, with accuracy improving (in HIV-positives) when stratified according to HIV status (area under the receiver operating characteristics curve; AUC ≥0.80). In HIV-positive participants, a four-marker biosignature (sIL6R, MMP-9, IL-2Ra, IFN-γ) diagnosed TB with AUC of 0.96, sensitivity of 85.7% (95% confidence interval (CI) 42.1-99.6%), and specificity of 94.7% (95% CI 74.0-99.9%). In HIV-negatives, the most promising was a two-marker biosignature (sIL6R and sIL-2Ra), which diagnosed TB with AUC of 0.76, sensitivity of 53.9% (95% CI 33.4-73.4%), and specificity of 79.6% (95% CI 70.3-87.1%).

CONCLUSIONS

Urinary host inflammatory biomarkers possess TB diagnostic potential but may be influenced by HIV infection. The results of this study require validation in larger studies.

The relationship between urinary Alzheimer-associated neuronal thread protein and blood biochemical indicators in the general population

Urinary Alzheimer-associated neuronal thread protein (AD7c-NTP) is elevated in early Alzheimer's disease (AD) and mild cognitive impairment, and is considered a biomarker for the early diagnosis of AD. However, it has not yet been investigated whether urinary AD7c-NTP is elevated with increases in blood biochemical indicators related to AD risk factors. We recruited 2180 participants, aged 35-93 years, from communities of four districts in Beijing. Blood biochemical indicators, including blood glucose, blood lipids, renal function, and high-sensitivity C-reactive protein, were measured using routine methods. Urinary AD7c-NTP was detected using an enzyme-linked immunosorbent assay AD7c-NTP kit. In the general population, there were no significant differences in urinary AD7c-NTP levels in subjects with different Mini-Mental State Examination levels or C-reactive protein values. After adjusting for age and sex, there were significant differences in urinary AD7c-NTP levels between different education levels, marital statuses, blood glucose, blood lipids, and kidney function. There was a negative correlation between urinary AD7c-NTP levels and serum creatinine (r = -0.128). There was a positive correlation between urinary AD7c-NTP levels and HbA1c (r = 0.104), insulin (r = 0.101), and triglycerides (r = 0.093). Urinary AD7c-NTP might be useful as a potential indicator to predict AD risk.

Sensitive mass spectrometric analysis of carbonyl metabolites in human urine and fecal samples using chemoselective modification

Metabolites with ketone or aldehyde functionalities comprise a large proportion of the human metabolome, most notably in the form of sugars. However, these reactive molecules are also generated through oxidative stress or gut microbiota metabolism and have been linked to disease development. The discovery and structural validation of this class of metabolites over the large concentration range found in human samples is crucial to identify their links to pathogenesis. Herein, we have utilized an advanced chemoselective probe methodology alongside bioinformatic analysis to identify carbonyl-metabolites in urine and fecal samples. In total, 99 metabolites were identified in urine samples and the chemical structure for 40 metabolites were unambiguously validated using a co-injection procedure. We also describe the preparation of a metabolite-conjugate library of 94 compounds utilized to efficiently validate these ketones and aldehydes. This method was used to validate 33 metabolites in a pooled fecal sample extract to demonstrate the potential for rapid and efficient metabolite detection over a wide metabolite concentration range. This analysis revealed the presence of six metabolites that have not previously been detected in either sample type. The constructed library can be utilized for straightforward, large-scale, and expeditious analysis of carbonyls in any sample type.

Urinary protein biomarkers for pediatric medulloblastoma

OBJECTIVE

To identify candidate urinary protein biomarkers to distinguish medulloblastoma (MB) patients from healthy patients or benign brain disease control patients.

METHODS

The tandem mass tag (TMT)-labeled quantitative proteomics approach was used to identify differential proteins in the urinary proteome of 9 pre- and postsurgery MB patients and 9 healthy control patients, respectively. Ingenuity pathway analysis was used for functional annotation of differential proteins. The biomarker candidates were validated by the parallel reaction monitoring (PRM) method in 112 samples (29 pre- and postsurgery MB patients, 26 healthy control patients, and 28 benign brain disease control patients). Receiver operating characteristic (ROC) curves were developed to evaluate candidate biomarkers.

RESULTS

A total of 114 differential proteins were found. Bioinformatic analysis revealed that the urinary proteome could reflect changes in MB. Seventeen candidate biomarkers were validated by PRM. The combination of CADH1, FGFR4 and FIBB could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.973, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884.

CONCLUSION

This report describes the first application of a TMT-PRM workflow to identify and validate MB-specific biomarkers in urine. These findings might contribute to the application of urinary proteomics for detecting and monitoring MB.

BIOLOGICAL SIGNIFICANCE

Medulloblastoma (MB) is among the most common pediatric brain malignancies. This tumor has a highly aggressive clinical course with a high tendency for relapses. Magnetic resonance imaging (MRI) is the major means of diagnosis and for radiographic surveillance after surgery. In MRI, sedation is often required in young children, which could expose them to a series of risks, including airway obstruction and even death. Aside from MRI, there is no reliable biomarker for clinical screening or monitoring of the disease. These facts introduce the clinical need of noninvasive biomarkers for early screening or monitoring of MB. This study is focused on the investigation of a marker panel based on urinary proteome, as a tool for the detection of MB in selected patients at risk. Upon evaluation of the marker model in an independent blinded set of 112 samples, the panel (CADH1, FGFR4 and FIBB) could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.973, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884.

A Metabolomic Approach for Predicting Diurnal Changes in Cortisol

Introduction: The dysregulation of cortisol secretion has been associated with a number of mental health and mood disorders. However, diagnostics for mental health and mood disorders are behavioral and lack biological contexts. Objectives: The goal of this work is to identify volatile metabolites capable of predicting changes in total urinary cortisol across the diurnal cycle for long-term stress monitoring in psychological disorders. Methods: We applied comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry to sample the urinary volatile metabolome using an untargeted approach across three time points in a single day for 60 subjects. Results: The finalized multiple regression model includes 14 volatile metabolites and 7 interaction terms. A review of the selected metabolites suggests pyrrole, 6-methyl-5-hepten-2-one and 1-iodo-2-methylundecane may originate from endogenous metabolic mechanisms influenced by glucocorticoid signaling mechanisms. Conclusion: This analysis demonstrated the feasibility of using specific volatile metabolites for the prediction of secreted cortisol across time.

Overview of Brain-to-Gut Axis Exposed to Chronic CNS Bacterial Infection(s) and a Predictive Urinary Metabolic Profile of a Brain Infected by Mycobacterium tuberculosis

A new paradigm in neuroscience has recently emerged - the brain-gut axis (BGA). The contemporary focus in this paradigm has been gut → brain ("bottom-up"), in which the gut-microbiome, and its perturbations, affects one's psychological state-of-mind and behavior, and is pivotal in neurodegenerative disorders. The emerging brain → gut ("top-down") concept, the subject of this review, proposes that dysfunctional brain health can alter the gut-microbiome. Feedback of this alternative bidirectional highway subsequently aggravates the neurological pathology. This paradigm shift, however, focuses upon non-communicable neurological diseases (progressive neuroinflammation). What of infectious diseases, in which pathogenic bacteria penetrate the blood-brain barrier and interact with the brain, and what is this effect on the BGA in bacterial infection(s) that cause chronic neuroinflammation? Persistent immune activity in the CNS due to chronic neuroinflammation can lead to irreversible neurodegeneration and neuronal death. The properties of cerebrospinal fluid (CSF), such as immunological markers, are used to diagnose brain disorders. But what of metabolic markers for such purposes? If a BGA exists, then chronic CNS bacterial infection(s) should theoretically be reflected in the urine. The premise here is that chronic CNS bacterial infection(s) will affect the gut-microbiome and that perturbed metabolism in both the CNS and gut will release metabolites into the blood that are filtered (kidneys) and excreted in the urine. Here we assess the literature on the effects of chronic neuroinflammatory diseases on the gut-microbiome caused by bacterial infection(s) of the CNS, in the context of information attained via metabolomics-based studies of urine. Furthermore, we take a severe chronic neuroinflammatory infectious disease - tuberculous meningitis (TBM), caused by Mycobacterium tuberculosis, and examine three previously validated CSF immunological biomarkers - vascular endothelial growth factor, interferon-gamma and myeloperoxidase - in terms of the expected changes in normal brain metabolism. We then model the downstream metabolic effects expected, predicting pivotal altered metabolic pathways that would be reflected in the urinary profiles of TBM subjects. Our cascading metabolic model should be adjustable to account for other types of CNS bacterial infection(s) associated with chronic neuroinflammation, typically prevalent, and difficult to distinguish from TBM, in the resource-constrained settings of poor communities.

Urinary biomarker discovery in gliomas using mass spectrometry-based clinical proteomics

Background

Gliomas are the most common primary malignant brain tumors and have a poor prognosis. Early detection of gliomas is crucial to improve patient outcomes. Urine accumulates systematic body changes and thus serves as an excellent early biomarker source.

Methods

At the biomarker discovery phase, we performed a self-controlled proteomics analysis by comparing urine samples collected from five glioma patients at the time of tumor diagnosis and after surgical removal of the tumor. At the biomarker validation phase, we further validated some promising proteins using parallel reaction monitoring (PRM)-based targeted proteomics in another cohort, including glioma, meningioma, and moyamoya disease patients as well as healthy controls.

Results

Using label-free proteome quantitation (LFQ), we identified twenty-seven urinary proteins that were significantly changed after tumor resection, many of which have been previously associated with gliomas. The functions of these proteins were significantly enriched in the autophagy and angiogenesis, which are associated with glioma development. After targeted proteomics validation, we identified a biomarker panel (AACT, TSP4, MDHM, CALR, LEG1, and AHSG) with an area under the curve (AUC) value of 0.958 for the detection of gliomas. Interestingly, AACT, LEG1, and AHSG are also potential cerebrospinal fluid or blood biomarkers of gliomas.

Conclusions

Using LFQ and PRM proteome quantification, we identified candidate urinary protein biomarkers with the potential to detect gliomas. This study will also provide clues for future biomarker studies involving brain diseases.

Urinary Amine and Organic Acid Metabolites Evaluated as Markers for Childhood Aggression: The ACTION Biomarker Study

Biomarkers are of interest as potential diagnostic and predictive instruments in personalized medicine. We present the first urinary metabolomics biomarker study of childhood aggression. We aim to examine the association of urinary metabolites and neurotransmitter ratios involved in key metabolic and neurotransmitter pathways in a large cohort of twins (N = 1,347) and clinic-referred children (N = 183) with an average age of 9.7 years. This study is part of ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies), in which we developed a standardized protocol for large-scale collection of urine samples in children. Our analytical design consisted of three phases: a discovery phase in twins scoring low or high on aggression (N = 783); a replication phase in twin pairs discordant for aggression (N = 378); and a validation phase in clinical cases and matched twin controls (N = 367). In the discovery phase, 6 biomarkers were significantly associated with childhood aggression, of which the association of O-phosphoserine (β = 0.36; SE = 0.09; p = 0.004), and gamma-L-glutamyl-L-alanine (β = 0.32; SE = 0.09; p = 0.01) remained significant after multiple testing. Although non-significant, the directions of effect were congruent between the discovery and replication analyses for six biomarkers and two neurotransmitter ratios and the concentrations of 6 amines differed between low and high aggressive twins. In the validation analyses, the top biomarkers and neurotransmitter ratios, with congruent directions of effect, showed no significant associations with childhood aggression. We find suggestive evidence for associations of childhood aggression with metabolic dysregulation of neurotransmission, oxidative stress, and energy metabolism. Although replication is required, our findings provide starting points to investigate causal and pleiotropic effects of these dysregulations on childhood aggression.