Urinary Metabolomic Markers of Protein Glycation, Oxidation, and Nitration in Early-Stage Decline in Metabolic, Vascular, and Renal Health

CKD Urine Metabolomics: Modern Concepts and Approaches

One of the primary challenges regarding chronic kidney disease (CKD) diagnosis is the absence of reliable methods to detect early-stage kidney damage. A metabolomic approach is expected to broaden the current diagnostic modalities by enabling timely detection and making the prognosis more accurate. Analysis performed on urine has several advantages, such as the ease of collection using noninvasive methods and its lower protein and lipid content compared with other bodily fluids. This review highlights current trends in applied analytical methods, major discoveries concerning pathways, and investigated populations in the context of urine metabolomic research for CKD over the past five years. Also, we are presenting approaches, instrument upgrades, and sample preparation modifications that have improved the analytical parameters of methods. The onset of CKD leads to alterations in metabolism that are apparent in the molecular composition of urine. Recent works highlight the prevalence of alterations in the metabolic pathways related to the tricarboxylic acid cycle and amino acids. Including diverse patient cohorts, using numerous analytical techniques with modifications and the appropriate annotation and explanation of the discovered biomarkers will help develop effective diagnostic models for different subtypes of renal injury with clinical applications.

Development and validation of a liquid chromatography-triple quadrupole mass spectrometry method for the determination of isopeptide ε-(γ-glutamyl) lysine in human urine as biomarker for transglutaminase 2 cross-linked proteins

Determination of the levels of protein cross-linking catalysed by the activity of transglutaminase 2 in various disease states has remained a significant challenge. The ability to quantify the isopeptide ε-(γ-glutamyl) lysine, which can form as a heterogeneous bond within or between proteins has significant analytical and clinical potential as a biomarker in biofluids such as human urine. Increased transglutaminase 2 activity is associated with a number of diseases, such as fibrosis. Previously published methods have been based on classical amino acid analysis, however they require a complex multi-enzyme digestion in order to achieve complete protein digestion, whilst leaving the isopeptide cross link intact. These methods require high levels of enzymes, which contaminate the analysis and alter the dynamics of digestion. The amino acid analysis detection also lacked selectivity, especially where the levels of crosslink are expected to be low relative to the background protein levels. We have systematically addressed these challenges, by optimising the precipitation of the protein in urine, the use of innovative immobilised enzyme technology, which allows for efficient digestion without enzyme contamination and LC-MS/MS detection based on multiple reaction monitoring. This method was validated for its analytical performance characteristics, showing the method has a sensitivity of 0.1 ng/mL of ε-(γ-glutamyl) lysine in human urine with precision of less than 20% CV, and is selective as no interferences were observed that may adversely affect the analysis. As such this approach represents a significant advance in the ability to detect and quantify ε-(γ-glutamyl) lysine.

The Maillard reaction end product Nε-carboxymethyllysine is metabolized in humans and the urinary levels of the microbial metabolites are associated with individual diet

During food processing most of the thermally-driven chemical reactions start off on the side chain amino group of lysine generating structurally modified compounds with specific metabolic routes. Upon human digestion, dietary N^ε-carboxymethyllysine (CML) may enter the colon and undergo gut microbial metabolism. However, little is known about the in vivo metabolic fate of dietary CML and its relationship with the habitual diet. We explored by hydrophilic interaction liquid chromatography tandem mass spectrometry the metabolites of CML in urine samples collected from 46 healthy subjects and studied the associations with diet. Mean concentration of N-carboxymethylcadaverine (CM-CAD), N-carboxymethylaminopentanoic acid (CM-APA), N-carboxymethylaminopentanol (CM-APO), and the N-carboxymethyl-Δ1-piperideinium ion were 0.49 nmol mg^-1 creatinine, 1.45 nmol mg^-1 creatinine, 4.43 nmol mg^-1 creatinine and 4.79 nmol mg^-1 creatinine, respectively. The urinary concentration of CML, its metabolites and lysine were positively correlated. Dietary intake of meat products negatively correlated with urinary excretion of CML and CM-APA; conversely dietary plant-to-animal proteins ratio positively correlated with urinary CML and its metabolites. The identification and quantification of CML metabolites in urine and the associations with diet corroborate the hypothesis that CML, an advanced glycation end-product, can undergo further biochemical transformations in vivo. The gut microbiome may have a major role in human metabolism of dietary CML.

Decreased methylglyoxal-mediated protein glycation in the healthy aging mouse model of ectopic expression of UCP1 in skeletal muscle

Mice with ectopic expression of uncoupling protein-1 (UCP1) in skeletal muscle exhibit a healthy aging phenotype with increased longevity and resistance to impaired metabolic health. This may be achieved by decreasing protein glycation by the reactive metabolite, methylglyoxal (MG). We investigated protein glycation and oxidative damage in skeletal muscle of mice with UCP1 expression under control of the human skeletal actin promoter (HSA-mUCP1) at age 12 weeks (young) and 70 weeks (aged). We found both young and aged HSA-mUCP1 mice had decreased advanced glycation endproducts (AGEs) formed from MG, lysine-derived Nε(1-carboxyethyl)lysine (CEL) and arginine-derived hydroimidazolone, MG-H1, whereas protein glycation by glucose forming Nε-fructosyl-lysine (FL) was increased ca. 2-fold, compared to wildtype controls. There were related increases in FL-linked AGEs, Nε-carboxymethyl-lysine (CML) and 3-deoxylglucosone-derived hydroimidazolone 3DG-H, and minor changes in protein oxidative and nitration adducts. In aged HSA-mUCP1 mice, urinary MG-derived AGEs/FL ratio was decreased ca. 60% whereas there was no change in CML/FL ratio - a marker of oxidative damage. This suggests that, normalized for glycemic status, aged HSA-mUCP1 mice had a lower flux of whole body MG-derived AGE exposure compared to wildtype controls. Proteomics analysis of skeletal muscle revealed a shift to increased heat shock proteins and mechanoprotection and repair in HSA-mUCP1 mice. Decreased MG-derived AGE protein content in skeletal muscle of aged HSA-mUCP1 mice is therefore likely produced by increased proteolysis of MG-modified proteins and increased proteostasis surveillance of the skeletal muscle proteome. From this and previous transcriptomic studies, signaling involved in enhanced removal of MG-modified protein is likely increased HSPB1-directed HUWE1 ubiquitination through eIF2α-mediated, ATF5-induced increased expression of HSPB1. Decreased whole body exposure to MG-derived AGEs may be linked to increased weight specific physical activity of HSA-mUCP1 mice. Decreased formation and increased clearance of MG-derived AGEs may be associated with healthy aging in the HSA-mUCP1 mouse.

Analysis of Serum Advanced Glycation Endproducts Reveals Methylglyoxal-Derived Advanced Glycation MG-H1 Free Adduct Is a Risk Marker in Non-Diabetic and Diabetic Chronic Kidney Disease

Accumulation of advanced glycation endproducts (AGEs) is linked to decline in renal function, particularly in patients with diabetes. Major forms of AGEs in serum are protein-bound AGEs and AGE free adducts. In this study, we assessed levels of AGEs in subjects with and without diabetes, with normal renal function and stages 2 to 4 chronic kidney disease (CKD), to identify which AGE has the greatest progressive change with decline in renal function and change in diabetes. We performed a cross-sectional study of patients with stages 2-4 CKD, with and without diabetes, and healthy controls (n = 135). Nine protein-bound and free adduct AGEs were quantified in serum. Most protein-bound AGEs increased moderately through stages 2-4 CKD whereas AGE free adducts increased markedly. Methylglyoxal-derived hydroimidazolone MG-H1 free adduct was the AGE most responsive to CKD status, increasing 8-fold and 30-fold in stage 4 CKD in patients without and with diabetes, respectively. MG-H1 Glomerular filtration flux was increased 5-fold in diabetes, likely reflecting increased methylglyoxal glycation status. We conclude that serum MG-H1 free adduct concentration was strongly related to stage of CKD and increased in diabetes status. Serum MG-H1 free adduct is a candidate AGE risk marker of non-diabetic and diabetic CKD.

AGEomics Biomarkers and Machine Learning-Realizing the Potential of Protein Glycation in Clinical Diagnostics

Protein damage by glycation, oxidation and nitration is a continuous process in the physiological system caused by reactive metabolites associated with dicarbonyl stress, oxidative stress and nitrative stress, respectively. The term AGEomics is defined as multiplexed quantitation of spontaneous modification of proteins damage and other usually low-level modifications associated with a change of structure and function—for example, citrullination and transglutamination. The method of quantitation is stable isotopic dilution analysis liquid chromatography—tandem mass spectrometry (LC-MS/MS). This provides robust quantitation of normal and damaged or modified amino acids concurrently. AGEomics biomarkers have been used in diagnostic algorithms using machine learning methods. In this review, I describe the utility of AGEomics biomarkers and provide evidence why these are close to the phenotype of a condition or disease compared to other metabolites and metabolomic approaches and how to train and test algorithms for clinical diagnostic and screening applications with high accuracy, sensitivity and specificity using machine learning approaches.

Alterations of Urinary Microbial Metabolites and Immune Indexes Linked With COVID-19 Infection and Prognosis

Coronavirus disease 2019 (COVID-19) has evolved into an established global pandemic. Metabolomic studies in COVID-19 patients is worth exploring for further available screening methods. In our study, we recruited a study cohort of 350 subjects comprising 248 COVID-19 patients (161 non-severe cases, 60 asymptomatic cases, and 27 severe cases) and 102 healthy controls (HCs), and herein present data with respect to their demographic features, urinary metabolome, immunological indices, and follow-up health status. We found that COVID-19 resulted in alterations of 39 urinary, mainly microbial, metabolites. Using random forest analysis, a simplified marker panel including three microbial metabolites (oxoglutaric acid, indoxyl, and phenylacetamide) was constructed (AUC=0.963, 95% CI, 0.930-0.983), which exhibited higher diagnostic performance than immune feature-based panels between COVID-19 and HC groups (P<0.0001). Meanwhile, we observed that urine metabolic markers enabled discriminating asymptomatic patients (ASY) from HCs (AUC = 0.981, 95% CI, 0.946-0.996), and predicting the incidence of high-risk sequalae in COVID-19 individuals (AUC=0.931, 95% CI, 0.877-0.966). Co-expression network analysis showed that 13 urinary microbial metabolites (e.g., oxoglutaric acid) were significantly correlated with alterations of CD4⁺, CD3⁺, and CD8⁺ T-cells, as well as IFN-γ, IL-2 and IL-4 levels, suggesting close interactions between microbial metabolites and host immune dysregulation in COVID-19. Taken together, our findings indicate that urinary metabolites may have promising potential for screening of COVID-19 in different application scenarios, and provide a new entry point to understand the microbial metabolites and related immune dysfunction in COVID-19.

Organelle Stress and Metabolic Derangement in Kidney Disease

Advanced multiomics analysis has revealed novel pathophysiological mechanisms in kidney disease. In particular, proteomic and metabolomic analysis shed light on mitochondrial dysfunction (mitochondrial stress) by glycation in diabetic or age-related kidney disease. Further, metabolic damage often results from organelle stress, such as mitochondrial stress and endoplasmic reticulum (ER) stress, as well as interorganelle communication, or "organelle crosstalk", in various kidney cells. These contribute to progression of the disease phenotype. Aberrant tubular mitochondrial lipid metabolism leads to tubular inflammation and fibrosis. This review article summarizes updated evidence regarding organelle stress, organelle crosstalk, and metabolic derangement in kidney disease.

Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes

AIMS/HYPOTHESIS

Large-scale prediabetes screening is still a challenge since fasting blood glucose and HbA_1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites.

METHODS

Non-targeted, modification group-assisted metabolomics by liquid chromatography-mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA_1c, and fasting insulin.

RESULTS

Female- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA_1c, insulin, or a combination of FPG and HbA_1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA_1c. In comparison, the AUCs of FPG, HbA_1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA_1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide).

CONCLUSIONS/INTERPRETATION

Our results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.

Methods to assess advanced glycation end-products

PURPOSE OF REVIEW

Advanced glycation end-products (AGEs) resulting from protein glycoxidation constitute biomarkers of interest in different pathological situations. Several methods for quantifying AGEs in biological fluids or tissues have been developed without any real consensus on a gold standard method. The aim of this review is to provide an overview of recent publications in the field helping to decide if these markers could find their place as diagnostic tools in clinical practice.

RECENT FINDINGS

This update shows that new AGEs are regularly discovered and new analytical methods (especially mass spectrometry-based methods) regularly described. Skin autofluorescence measurement is increasingly performed due to the practicability of the dedicated devices, in spite of its questionable specificity. In biological fluids, carboxymethyllysine remains the most frequently measured AGE. However, to date, it is still difficult to compare results obtained from different studies because measured AGEs and modes of expression are different and because no method standardization has been initiated.

SUMMARY

Despite their potential interest as biomarkers and the availability of unfortunately non-standardized assay methods, AGEs remain confined to clinical research studies without really being used in daily clinical practice. These challenges must be addressed in order to allow their implementation.

Reversal of Insulin Resistance in Overweight and Obese Subjects by trans-Resveratrol and Hesperetin Combination-Link to Dysglycemia, Blood Pressure, Dyslipidemia, and Low-Grade Inflammation

The dietary supplement, trans-resveratrol and hesperetin combination (tRES-HESP), induces expression of glyoxalase 1, countering the accumulation of reactive dicarbonyl glycating agent, methylglyoxal (MG), in overweight and obese subjects. tRES-HESP produced reversal of insulin resistance, improving dysglycemia and low-grade inflammation in a randomized, double-blind, placebo-controlled crossover study. Herein, we report further analysis of study variables. MG metabolism-related variables correlated with BMI, dysglycemia, vascular inflammation, blood pressure, and dyslipidemia. With tRES-HESP treatment, plasma MG correlated negatively with endothelial independent arterial dilatation (r = -0.48, p < 0.05) and negatively with peripheral blood mononuclear cell (PBMC) quinone reductase activity (r = -0.68, p < 0.05)-a marker of the activation status of transcription factor Nrf2. For change from baseline of PBMC gene expression with tRES-HESP treatment, Glo1 expression correlated negatively with change in the oral glucose tolerance test area-under-the-curve plasma glucose (ΔAUGg) (r = -0.56, p < 0.05) and thioredoxin interacting protein (TXNIP) correlated positively with ΔAUGg (r = 0.59, p < 0.05). Tumor necrosis factor-α (TNFα) correlated positively with change in fasting plasma glucose (r = 0.70, p < 0.001) and negatively with change in insulin sensitivity (r = -0.68, p < 0.01). These correlations were not present with placebo. tRES-HESP decreased low-grade inflammation, characterized by decreased expression of CCL2, COX-2, IL-8, and RAGE. Changes in CCL2, IL-8, and RAGE were intercorrelated and all correlated positively with changes in MLXIP, MAFF, MAFG, NCF1, and FTH1, and negatively with changes in HMOX1 and TKT; changes in IL-8 also correlated positively with change in COX-2. Total urinary excretion of tRES and HESP metabolites were strongly correlated. These findings suggest tRES-HESP counters MG accumulation and protein glycation, decreasing activation of the unfolded protein response and expression of TXNIP and TNFα, producing reversal of insulin resistance. tRES-HESP is suitable for further evaluation for treatment of insulin resistance and related disorders.

Protein glycation - biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine

Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established diabetes. A1C is an early-stage glycation adduct of hemoglobin with glucose; a fructosamine derivative. Glucose is an amino group-directed glycating agent, modifying N-terminal and lysine sidechain amino groups. A similar fructosamine derivative of serum albumin, glycated albumin (GA), finds use as a biomarker of glycemic control, particularly where there is interference in use of A1C. Later stage adducts, advanced glycation endproducts (AGEs), are formed by the degradation of fructosamines and by the reaction of reactive dicarbonyl metabolites, such as methylglyoxal. Dicarbonyls are arginine-directed glycating agents forming mainly hydroimidazolone AGEs. Glucosepane and pentosidine, an intense fluorophore, are AGE covalent crosslinks. Cellular proteolysis of glycated proteins forms glycated amino acids, which are released into plasma and excreted in urine. Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. Investigational glycation biomarkers are in development for: (i) healthy aging; (ii) risk prediction of vascular complications of diabetes; (iii) diagnosis of autism; and (iv) diagnosis and classification of early-stage arthritis. Protein glycation biomarkers are influenced by heritability, aging, decline in metabolic, vascular, renal and skeletal health, and other factors. They are applicable to populations of differing ethnicities, bridging the gap between genotype and phenotype. They are thereby likely to find continued and expanding clinical use, including in the current era of developing precision medicine, reporting on multiple pathogenic processes and supporting a precision medicine approach.

Metabolomics Signatures of Aging: Recent Advances

Metabolomics is the latest state-of-the-art omics technology that provides a comprehensive quantitative profile of metabolites. The metabolites are the cellular end products of metabolic reactions that explain the ultimate response to genomic, transcriptomic, proteomic, or environmental changes. Aging is a natural inevitable process characterized by a time-dependent decline of various physiological and metabolic functions and are dominated collectively by genetics, proteomics, metabolomics, environmental factors, diet, and lifestyle. The precise mechanism of the aging process is unclear, but the metabolomics has the potential to add significant insight by providing a detailed metabolite profile and altered metabolomic functions with age. Although the application of metabolomics to aging research is still relatively new, extensive attempts have been made to understand the biology of aging through a quantitative metabolite profile. This review summarises recent developments and up-to-date information on metabolomics studies in aging research with a major emphasis on aging biomarkers in less invasive biofluids. The importance of an integrative approach that combines multi-omics data to understand the complex aging process is discussed. Despite various innovations in metabolomics and metabolite associated with redox homeostasis, central energy pathways, lipid metabolism, and amino acid, a major challenge remains to provide conclusive aging biomarkers.

Oral glucose tolerance test does not affect degree of hemoglobin glycation as measured by routine assay

BACKGROUND

Hemoglobin A1c (HbA1c) is an accurate index of fluctuation in glycemia over the 2-3 months prior to quantitative assessment. During this time, hemoglobin (Hb) slowly glycates until it shows the properties of advanced glycation end-products. Glycation kinetics is intensified by prolonged glucose exposure. In subjects undergoing oral glucose tolerance testing (OGTT), immediately after ingestion, glucose is ostensibly transported by the glucose transporter 1 (GLUT1) to erythrocyte corpuscular hemoglobin. The earliest significant measurable level of hemoglobin glycation associated with this transportation is still not clear.

SUBJECTS AND METHODS

We attempted to explore the early impact of short-term glucose load on HbA1c levels, because it is now known that transmembrane GLUT1-mediated glucose transport occurs immediately. A total of 88 participants (46 patients and 42 clinically healthy controls) underwent fasting plasma glucose quantitation during an OGTT. HbA1c, revealed by a monoclonal anti-glycation epitope antibody and adiponectin, was quantitated before (T0) and 2 hours (T120) after 80 g glucose ingestion.

RESULTS

Wilcoxon test revealed that the HbA1c values did not significantly vary (P=0.15) during the OGTT, whereas glucose concentration varied strongly between T0 and T120.

DISCUSSION

It is well known that quantitative estimation of HbA1c is informative for clinical care, independently of glucose level. The molecular mechanisms and dynamics by which glucose enters/exits red blood cells are incompletely known and may differ between individuals. We here show, for the first time, that HbA1c levels do not significantly increase during OGTT, supporting the view that non-enzymatic glycation of hemoglobin occurs slowly and that glycation during the 2 hours of an OGTT is insignificant.

Reading patterns of proteome damage by glycation, oxidation and nitration: quantitation by stable isotopic dilution analysis LC-MS/MS

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) provides a high sensitivity, high specificity multiplexed method for concurrent detection of adducts formed by protein glycation, oxidation and nitration, also called AGEomics. Combined with stable isotopic dilution analysis, it provides for robust quantitation of protein glycation, oxidation and nitration adduct analytes. It is the reference method for such measurements. LC-MS/MS has been used to measure glycated, oxidized and nitrated amino acids - also called glycation, oxidation and nitration free adducts, with a concurrent quantitation of the amino acid metabolome in physiological fluids. Similar adduct residues in proteins may be quantitated with prior exhaustive enzymatic hydrolysis. It has also been applied to quantitation of other post-translation modifications, such as citrullination and formation of Nε-(γ-glutamyl)lysine crosslink by transglutaminases. Application to cellular and extracellular proteins gives estimates of the steady-state levels of protein modification by glycation, oxidation and nitration, and measurement of the accumulation of glycation, oxidation and nitration adducts in cell culture medium and urinary excretion gives an indication of flux of adduct formation. Measurement of glycation, oxidation and nitration free adducts in plasma and urine provides for estimates of renal clearance of free adducts. Diagnostic potential in clinical studies has been enhanced by the combination of estimates of multiple adducts in optimized diagnostic algorithms by machine learning. Recent applications have been in early-stage detection of metabolic, vascular and renal disease, and arthritis, metabolic control and risk of developing vascular complication in diabetes, and a blood test for autism.

Deep learning meets metabolomics: a methodological perspective

Deep learning (DL), an emerging area of investigation in the fields of machine learning and artificial intelligence, has markedly advanced over the past years. DL techniques are being applied to assist medical professionals and researchers in improving clinical diagnosis, disease prediction and drug discovery. It is expected that DL will help to provide actionable knowledge from a variety of 'big data', including metabolomics data. In this review, we discuss the applicability of DL to metabolomics, while presenting and discussing several examples from recent research. We emphasize the use of DL in tackling bottlenecks in metabolomics data acquisition, processing, metabolite identification, as well as in metabolic phenotyping and biomarker discovery. Finally, we discuss how DL is used in genome-scale metabolic modelling and in interpretation of metabolomics data. The DL-based approaches discussed here may assist computational biologists with the integration, prediction and drawing of statistical inference about biological outcomes, based on metabolomics data.