Urine Reflection of Changes in Blood. In: Gao Y, editor. Urine Proteomics in Kidney Disease Biomarker Discovery. Dordrecht: Springer Netherlands; 2015. pp. 13-9. [DOI: 10.1007/978-94-017-9523-4_2]

Effects of Hepatorenal Function on Urinary Alzheimer-Associated Neuronal Thread Protein: A Laboratory-Based Cross-Sectional Study Among the Older Chinese Population

Background

Urinary Alzheimer-associated neuronal thread protein (AD7c-NTP) is a biomarker for the early diagnosis of Alzheimer's disease (AD). It remains unclear whether hepatorenal function affects the urinary AD7c-NTP level.

Objective

To evaluate the effects of hepatorenal function on urinary AD7c-NTP level.

Methods

We enrolled 453 participants aged 60-100 years. An automated chemistry analyzer was used to determine the indicators of serum hepatorenal function. Enzyme-linked immunosorbent assay was used to measure the urinary AD7c-NTP level.

Results

Spearman's correlation analysis showed a negative correlation between urinary AD7c-NTP levels and indicators of hepatorenal function, including albumin (r = -0.181, p < 0.001), albumin/globulin ratio (r = -0.224, p < 0.001), cholinesterase (r = -0.094, p = 0.046), total carbon dioxide (r = -0.102, p = 0.030), and glomerular filtration rate (r = -0.260, p < 0.001), as well as a positive correlation with globulin (r = 0.141, p = 0.003), aspartate transaminase (r = 0.186, p < 0.001), blood urine nitrogen (r = 0.210, p < 0.001), creatinine (r = 0.202, p < 0.001), uric acid (r = 0.229, p < 0.001), and cystatin C (r = 0.265, p < 0.001). The least absolute shrinkage and selection operator (LASSO) regression analysis and multiple linear regression model analyses showed that the statistically significant hepatorenal indicators for predicting AD7c-NTP were A/G (p = 0.007), AST (p = 0.002), BUN (p = 0.019), and UA (p = 0.003).

Conclusions

The effects of hepatorenal indicators should be considered when using urinary AD7c-NTP levels in clinical settings.

Integrated Metabolomics and Proteomics Analysis of Urine in a Mouse Model of Posttraumatic Stress Disorder

Posttraumatic stress disorder (PTSD) is a serious stress disorder that occurs in individuals who have experienced major traumatic events. The underlying pathological mechanisms of PTSD are complex, and the related predisposing factors are still not fully understood. In this study, label-free quantitative proteomics and untargeted metabolomics were used to comprehensively characterize changes in a PTSD mice model. Differential expression analysis showed that 12 metabolites and 27 proteins were significantly differentially expressed between the two groups. Bioinformatics analysis revealed that the differentiated proteins were mostly enriched in: small molecule binding, transporter activity, extracellular region, extracellular space, endopeptidase activity, zymogen activation, hydrolase activity, proteolysis, peptidase activity, sodium channel regulator activity. The differentially expressed metabolites were mainly enriched in Pyrimidine metabolism, D-Glutamine and D-glutamate metabolism, Alanine, aspartate and glutamate metabolism, Arginine biosynthesis, Glutathione metabolism, Arginine, and proline metabolism. These results expand the existing understanding of the molecular basis of the pathogenesis and progression of PTSD, and also suggest a new direction for potential therapeutic targets of PTSD. Therefore, the combination of urine proteomics and metabolomics explores a new approach for the study of the underlying pathological mechanisms of PTSD.

Mass spectrometry-based proteomic exploration of the small urinary extracellular vesicles in ANCA-associated vasculitis in comparison with total urine

ANCA-associated vasculitis (AAV) is a rare, but potentially severe autoimmune disease, even nowadays displaying increased mortality and morbidity. Finding early biomarkers of activity and prognosis is thus very important. Small extracellular vesicles (EVs) isolated from urine can be considered as a non-invasive source of biomarkers. We evaluated several protocols for urinary EV isolation. To eliminate contaminating non-vesicular proteins due to AAV associated proteinuria we used proteinase K treatment. We investigated the differences in proteomes of small EVs of patients with AAV compared to healthy controls by label-free LC-MS/MS. In parallel, we performed an analogous proteomic analysis of urine samples from identical patients. The study results showed significant differences and similarities in both EV and urine proteome, the latter one being highly affected by proteinuria. Using bioinformatics tools we explored differentially changed proteins and their related pathways with a focus on the pathophysiology of AAV. Our findings indicate significant regulation of Golgi enzymes, such as MAN1A1, which can be involved in T cell activation by N-glycans glycosylation and may thus play a key role in pathogenesis and diagnosis of AAV. SIGNIFICANCE: The present study explores for the first time the changes in proteomes of small extracellular vesicles and urine of patients with renal ANCA-associated vasculitis compared to healthy controls by label-free LC-MS/MS. Isolation of vesicles from proteinuric urine samples has been modified to minimize contamination by plasma proteins and to reduce co-isolation of extraluminal proteins. Differentially changed proteins and their related pathways with a role in the pathophysiology of AAV were described and discussed. The results could be helpful for the research of potential biomarkers in renal vasculitis associated with ANCA.

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.

Integration of metabolomics and proteomics to reveal the metabolic characteristics of high-intensity interval training

Metabolomics and proteomics were integrated to research the molecular characterization of high-intensity interval training, revealing changes in biological pathways.

Comparison of the Serum Metabolic Fingerprint of Different Exercise Modes in Men with and without Metabolic Syndrome

Exercise plays a beneficial role in the treatment of metabolic syndrome (MetS). Metabolomics can provide new insights and facilitate the optimization of exercise prescription. This study aimed to investigate whether the response of the human serum metabolic fingerprint to exercise depends on exercise mode or the presence of MetS. Twenty-three sedentary men (nine with MetS and fourteen healthy) completed four trials: Resting, high-intensity interval exercise (HIIE), continuous moderate-intensity exercise (CME), and resistance exercise (RE). Blood samples were collected pre-exercise, immediately after exercise, and 1 h post-exercise for targeted metabolomic analysis in serum by liquid chromatography–mass spectrometry. Time exerted the strongest differentiating effect, followed by exercise mode. The largest changes from baseline were found in the immediate post-exercise samples. RE caused the strongest responses overall, followed by HIIE, while CME had minimal effect. Unlike previous results in urine, no valid model could separate the two groups in serum. Exercise exerted a beneficial effect on prominent serum biomarkers of metabolic risks, such as branched-chain amino acids, alanine, acetylcarnitine, choline, and betaine. These findings contribute to the ongoing research efforts to map the molecular responses to exercise and to optimize exercise guidelines for individuals at cardiometabolic risk.

Proteomics of liquid biopsies: Depicting RCC infiltration into the renal vein by MS analysis of urine and plasma

Liquid biopsies, as blood and urine, could offer an invaluable, easily accessible source of biomarkers, and evidences for elucidating the pathological processes. Only few studies integrated the proteomes driven by more than one biofluid. Furthermore, it is not clear which biofluid better mirrors the alterations triggered by disease. Venous infiltrating RCC(Renal Cell Carcinoma) could represent an advantageous model for exploring this aspect. Herein, we investigate how blood and urine "proteomically" reflect the changes occurring during RCC infiltration into renal vein(RV) by label-free nLC-ESI-MS/MS. We found 574 and 58 differentially expressed proteins(DEPs) in response to vascular involvement. To the augment of vascular involvement, the abundance of only three proteins in urine(UROM,RALA,CNDP1) and two in plasma(APOA1,K2C1) diminished while increased for twenty-six urinary proteins. 80 proteins were found both in urine and plasma, among which twenty-eight were DEPs. A huge overlap between the two biofluids was highlighted, as expected, being urine the filtrate of blood. However, this consistency decreases when RV-occlusion occurs suggesting alternative protein releases, and a loss of kidney architecture. Moreover, several proteomic and functional signatures were biofluid-specific. In conclusion, the complementarity between the specimens allowed to achieve a deeper level of molecular complexity of the RCC venous infiltration. SIGNIFICANCE: Although plasma and urine are strongly interconnected, only few proteomic studies investigated the complementarity of these fluids as bio-sources of information. Moreover, none of them was focused to their analysis and comparison in the context of vascular infiltration of renal cancer. Herein, new insights were gained regarding the impact into urinary and plasma proteome of the changes triggered by the ccRCC invasion into vascular system and renal vein. Furthermore, the integration of the information driven by the two liquid biopsies permits to unravel biological processes otherwise lost.

Metabolomics in Human Acute-Exercise Trials: Study Design and Preparation

Metabolomics can be of great value in the study of exercise metabolism. However, because of the high intraindividual and interindividual biological variability of the human metabolome, special considerations should be taken into account when designing an acute-exercise metabolomic study. To study different exercise parameters, e.g., different exercise modes, intensities, etc., a crossover study design, where each participant acts as their own control, is preferable to a parallel design, one involving different groups of participants. Moreover, the study should include a no exercise, control trial. Before each trial, participants should follow carefully designed preparatory steps to control for possible confounding factors, i.e., maintain repeatable and constant conditions for all individual trials of the study to minimize variation due to factors other than the one(s) being studied. This chapter focuses on the design of human metabolomic studies, where the intervention is an acute metabolic challenge, such as an exercise bout or a test meal, and presents some basic steps for screening potential participants, performing preliminary tests, preparing for the trial day, and performing the trial.

Physiological conditions can be reflected in human urine proteome and metabolome

Biomarkers are the measurable changes associated with physiological or pathophysiological processes. Urine, unlike blood, lacks mechanisms for maintaining homeostasis: it is therefore an ideal source of biomarkers that can reflect systemic changes. Urinary proteome and metabolome have been studied for their diagnostic capabilities, ability to monitor disease and prognostic utility. In this review, the effects of common physiological conditions such as gender, age, diet, daily rhythms, exercise, hormone status, lifestyle and extreme environments on human urine are discussed. These effects should be considered when biomarker studies of diseases are conducted. More importantly, if physiological changes can be reflected in urine, we have reason to expect that urine will become widely used to detect small and early changes in pathological and/or pharmacological conditions.