Measurement of glycated albumin in serum and plasma by LC-MS/MS

Blood proteomics and multimodal risk profiling of human volunteers after incision injury: A translational study for advancing personalized pain management after surgery

A significant number of patients develop chronic pain after surgery, but prediction of those who are at risk is currently not possible. Thus, prognostic prediction models that include bio-psycho-social and physiological factors in line with the complex nature of chronic pain would be urgently required. Here, we performed a translational study in male volunteers before and after an experimental incision injury. We determined multi-modal features ranging from pain characteristics and psychological questionnaires to blood plasma proteomics. Outcome measures included pain intensity ratings and the extent of the area of hyperalgesia to mechanical stimuli surrounding the incision, as a proxy of central sensitization. A multi-step logistic regression analysis was performed to predict outcome measures based on feature combinations using data-driven cross-validation and prognostic model development. Phenotype-based stratification resulted in the identification of low and high responders for both outcome measures. Regression analysis revealed prognostic proteomic, specific psychophysical, and psychological features. A combinatorial set of distinct features enabled us to predict outcome measures with increased accuracy compared to using single features. Remarkably, in high responders, protein network analysis suggested a protein signature characteristic of low-grade inflammation. Alongside, in silico drug repurposing highlighted potential treatment options employing antidiabetic and anti-inflammatory drugs. Taken together, we present here an integrated pipeline that harnesses bio-psycho-physiological data for prognostic prediction in a translational approach. This pipeline opens new avenues for clinical application with the goal of stratifying patients and identifying potential new targets, as well as mechanistic correlates, for postsurgical pain.

Glycated albumin in pregnancy correlates negatively with body mass index and contributes to the risk of gestational diabetes mellitus

Objectives

The aims of our study were to establish a reference interval for glycated albumin (GA) in gestational week 30, to investigate whether GA can replace or reduce the need for oral glucose tolerance test (OGTT) in pregnancy, and to reassess the usefulness of body mass-index (BMI), age and fasting glucose in detection of gestational diabetes (GDM).

Design

and methods: We measured GA in 486 healthy pregnant women. Reference interval was calculated using the central 95 % of the results. ROC curves were created to assess the ability of GA, fasting glucose and BMI separately to detect GDM, and logistic regression analysis was used to estimate risk of developing GDM given the level of the same markers. Finally, multiple logistic regression analysis based on GA, fasting glucose and BMI was used to find a strategy of predicting a patient's risk of GDM.

Results

The reference interval for GA at week 30 of gestation is 6.8-10.3 %. The analysis has a low AUC (0.53) with respect to detecting GDM. It increases slightly to 0.64 when corrected for BMI, as GA is inversely correlated to BMI. Combining GA with fasting glucose and BMI at gestational weeks 16-20 could raise the AUC to 0.80.

Conclusion

GA cannot be recommended to replace OGTT for the diagnosis of GDM. Nor can it be used to identify women at risk of developing GDM. GA combined with fasting glucose and BMI in early pregnancy could be a useful model to estimate risk of GDM.

Synthesis of Silver Nanoparticles and Gold Nanoparticles Used as Biosensors for the Detection of Human Serum Albumin-Diagnosed Kidney Disease

Background/Objectives: This study aims to develop a screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) for the detection of human serum albumin (HSA). The objectives include utilizing green synthesis methods for nanoparticle production and evaluating the electrochemical performance of the modified electrodes. Methods: AgNPs and AuNPs were synthesized using Phulae pineapple peel extract (PPA) as a reducing agent. The nanoparticles were characterized using UV-visible spectrophotometry (UV-vis), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and transmission electron microscopy (TEM). The electrochemical performance of AgNP/SPCE and AuNP/SPCE was assessed by cyclic voltammetry (CV) studies, and the electrodes were functionalized with anti-HSA antibodies for HSA detection. Results: Characterization revealed spherical nanoparticles ranging from 10 to 30 nm. Both AgNP/SPCE and AuNP/SPCE demonstrated improved electrochemical performance compared to bare SPCEs. The modified sensors could detect serum albumin concentrations from 10 to 400 μg/mL, with high correlation values of 0.97 and 0.99 for AgNPs and AuNPs, respectively. Conclusions: This research demonstrates the potential of using agricultural waste for green synthesis of nanoparticles and highlights the application of AgNPs and AuNPs in developing sensitive biosensing platforms for the detection of human serum albumin.

Exploring glycated sites in human serum albumin: impact of sample processing techniques on detection and analysis

Glycation and the subsequent formation of advanced glycation end products (AGEs) disrupt and impair the physiological functions of proteins. This study presents a comprehensive glycation site mapping of human serum albumin (HSA) utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS). Both in vitro glycation experiments and patient samples were investigated, exploring various enzymes, processing techniques, and their impacts on glycation site detection. A pilot study was conducted, analyzing sixteen serum samples, which spanned from healthy individuals to severe diabetic patients (with HbA1c values ranging from 5.7% to 18.1%). The aim was to comprehend the progression of glycation on various sites of HSA with increasing levels of glycation. Their glycated albumin levels (GA) spanned from 19.7% to 62.3%. Trypsin-mediated proteolytic digestion unveiled 12 glycation sites through direct in-solution digestion of whole serum. However, isolating albumin from serum enabled the identification of a higher number of glycation sites in each sample compared to direct serum digestion. Boronate affinity chromatography facilitated the segregation of less glycated albumin (LGA) from the more glycated albumin (MGA) fraction. Subsequent proteolytic digestion of both LGA and MGA samples revealed similar glycation sites. The MGA fraction exhibited a greater number of identified glycation sites, thereby elucidating which sites are particularly prone to glycation in highly glycated albumin samples. Changes in relative glycation levels were noted in the tryptic digests of albumin samples following the sample enrichment steps, as opposed to direct in-solution digestion of whole serum. Two enzymes, trypsin and Glu-C, were evaluated for efficacy in sequence coverage and glycation site analysis of HSA, with trypsin demonstrating superior efficiency over Glu-C.

Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies.

METHODS

We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN.

RESULTS

Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care.

CONCLUSION

Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.

Simultaneous electrochemical detection of glycated and human serum albumin for diabetes management

Developing highly selective and sensitive biosensors for diabetes management blood glucose monitoring is essential to reduce the health risks associated with diabetes. Assessing the glycation (GA) of human serum albumin (HSA) serves as an indicator for medium-term glycemic control, making it suitable for assessing the efficacy of blood glucose management protocols. However, most biosensors are not capable of simultaneous detection of the relative fraction of GA to HSA in a clinically relevant range. Here, we report an effective miniaturised biosensor architecture for simultaneous electrochemical detection of HSA and GA across relevant concentration ranges. We immobilise DNA aptamers specific for the detection of HSA and GA on gold nanoislands (Au NIs) decorated screen-printed carbon electrodes (SPCEs), and effectively passivate the residual surface sites. We achieve a dynamic detection range between 20 and 60 mg/mL for HSA and 1-40 mg/mL for GA in buffer solutions. The analytical utility of our HSA and GA biosensor architectures are validated in mice serum indicating immediate potential for clinical applications. Since HSA and GA have similar structures, we extensively assess our sensor specificity, observing high selectivity of the HSA and GA sensors against each other and other commonly present interfering molecules in blood such as glucose, glycine, ampicillin, and insulin. Additionally, we determine the glycation ratio, which is a crucial metric for assessing blood glucose management efficacy, in an extensive range representing healthy and poor blood glucose management profiles. These findings provide strong evidence for the clinical potential of our biosensor architecture for point-of-care and self-assessment of diabetes management protocols.

Pleconaril and ribavirin in new-onset type 1 diabetes: a phase 2 randomized trial

Previous studies showed a low-grade enterovirus infection in the pancreatic islets of patients with newly diagnosed type 1 diabetes (T1D). In the Diabetes Virus Detection (DiViD) Intervention, a phase 2, placebo-controlled, randomized, parallel group, double-blind trial, 96 children and adolescents (aged 6-15 years) with new-onset T1D received antiviral treatment with pleconaril and ribavirin (n = 47) or placebo (n = 49) for 6 months, with the aim of preserving β cell function. The primary endpoint was the mean stimulated C-peptide area under the curve (AUC) 12 months after the initiation of treatment (less than 3 weeks after diagnosis) using a mixed linear model. The model used longitudinal log-transformed serum C-peptide AUCs at baseline, at 3 months, 6 months and 1 year. The primary endpoint was met with the serum C-peptide AUC being higher in the pleconaril and ribavirin treatment group compared to the placebo group at 12 months (average marginal effect = 0.057 in the linear mixed model; 95% confidence interval = 0.004-0.11, P = 0.037). The treatment was well tolerated. The results show that antiviral treatment may preserve residual insulin production in children and adolescent with new-onset T1D. This provides a rationale for further evaluating antiviral strategies in the prevention and treatment of T1D. European Union Drug Regulating Authorities Clinical Trials identifier: 2015-003350-41 .

In Vitro and In Vivo Synergistic Antitumor Activity of Albumin-Coated Oleic Acid-Loaded Liposomes toward Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal and prevalent cancers, closely associated with cirrhosis and fibrosis. This study aimed to assess the antitumor activity of oleic acid-liposomes (uncoated liposomes) upon coating with albumin against HCC. The in vitro studies revealed the high safety of the prepared uncoated and albumin-coated liposomes to normal HFB-4 cells (EC100 of 35.57 ± 0.17 and 79.133 ± 2.92 µM, respectively) with significant anticancer activity against HepG-2 cells with IC50 of 56.29 ± 0.91 and 26.74 ± 0.64 µM, respectively. The albumin-coated liposomes revealed superior apoptosis induction potential (80.7%) with significant upregulation of p53 gene expression (> 7.0-fold), compared to OA. The in vivo study revealed that the administration of uncoated or albumin-coated liposomes (100 mg/kg) for six weeks markedly retarded the DENA-induced HCC in Wistar albino rates through regulating the liver enzymes, total bilirubin level, pro-inflammatory cytokines, and oxidative stress. Accordingly, the current study supports the in vitro and in vivo chemo-preventive feature of albumin-coated liposomes against HCC through modulation of apoptosis, improvement of the immune response, reduction of inflammation, and restoration of impaired oxidative stress, which is the first reported to the best of our knowledge.

Elevated Level of Glycated KQTALVELVK Peptide of Albumin Is Associated with the Risk of Diabetic Nephropathy

Diabetic nephropathy is a leading cause of end-stage renal disease. Hence, early detection of diabetic nephropathy is essential to mitigate the disease burden. Microalbuminuria, the currently used diagnostic marker of diabetic nephropathy, is not efficient in detecting it at an early stage. Therefore, we explored the utility of glycated human serum albumin (HSA) peptides for risk prediction of diabetic nephropathy. Three glycation-sensitive HSA peptides, namely, FKDLGEENFK, KQTALVELVK, and KVPQVSTPTLVEVSR, with deoxyfructosyllysine (DFL) modification were quantified by targeted mass spectrometry (MS) in a study population comprising healthy and type II diabetes subjects with and without nephropathy. Mass spectrometry, receiver operating characteristic (ROC) curve, and correlation analysis revealed that the DFL-modified KQTALVELVK peptide was better than other glycated HSA peptides and HbA_1c for identifying diabetic nephropathy. DFL-modified KQTALVELVK could be a potential marker for risk prediction of diabetic nephropathy.

Evaluation of glycated albumin levels in tears and saliva as a marker in patients with diabetes mellitus

AIMS

Glycated albumin (GA) is a biomarker, whose level reflects glycemic control status over the previous 2 weeks. To develop a non-invasive method for evaluating glycemic control in people with diabetes mellitus, we investigated the measurement of GA levels in tears and saliva, which could be collected noninvasively.

METHODS

Tear and saliva samples were collected from 48 participants with diabetes mellitus. The GA levels in the tear and saliva specimens were measured by Liquid Chromatography-Mass Spectrometry (LC-MS/MS).

RESULTS

GA levels in both tear and saliva samples were significantly correlated with the GA levels in the blood (P<0.001). Multiple regression analysis revealed that these correlations were maintained even after adjustments for the BMI, age, and nephropathy stage (P<0.001).

CONCLUSION

GA levels in tear and saliva specimens, as diabetes-related biomarkers, can be measured non-invasively. Since this measurement can be performed noninvasively and not as frequently as compared with the more invasive finger prick method, it is expected to reduce the burden on people with diabetes in terms of both the invasiveness and cost-effectiveness. In the future, we would like to verify the effect of regular GA measurement on the glycemic control while considering the clinical cost-effectiveness.

Protein glycation in diabetes mellitus

Diabetes mellitus is the ninth leading cause of mortality worldwide. It is a complex disease that manifests as chronic hyperglycemia. Glucose exposure causes biochemical changes at the proteome level as reflected in accumulation of glycated proteins. A prominent example is hemoglobin A1c (HbA1c), a glycated protein widely accepted as a diabetic indicator. Another emerging biomarker is glycated albumin which has demonstrated utility in situations where HbA1c cannot be used. Other proteins undergo glycation as well thus impacting cellular function, transport and immune response. Accordingly, these glycated counterparts may serve as predictors for diabetic complications and thus warrant further inquiry. Fortunately, modern proteomics has provided unique analytic capability to enable improved and more comprehensive exploration of glycating agents and glycated proteins. This review broadly covers topics from epidemiology of diabetes to modern analytical tools such as mass spectrometry to facilitate a better understanding of diabetes pathophysiology. This serves as an attempt to connect clinically relevant questions with findings of recent proteomic studies to suggest future avenues of diabetes research.

Glycated albumin and post-transplant diabetes mellitus in kidney transplant recipients

BACKGROUND

Post-transplant diabetes mellitus is one of the most important cardiovascular risk factors after solid organ transplantation. Factors other than hyperglycaemia found in patients post-transplant, affect the level of haemoglobin A_1c (HbA_1c), and new markers of hyperglycaemia are needed. Our aim was to establish a 95% reference interval for glycated albumin in kidney transplant recipients, and to compare glycated albumin concentrations to the diagnostic criteria for diabetes mellitus post-transplant using oral glucose tolerance test and HbA_1c.

METHODS

A total of 341 non-diabetic kidney transplant recipients aged ≥18 years who underwent an oral glucose tolerance test at 8 weeks and 1 year after transplantation were included. Glycated albumin was determined by liquid chromatography coupled with tandem mass spectrometry.

RESULTS

The 95% reference interval for glycated albumin was 8.2 (90% CI: 7.2-8.5) to 12.8% (90% CI: 12.2-13.5) which is not significantly different from our laboratory's 95% reference interval for persons without diabetes. At both 8 weeks and 1 year after transplantation, 35 patients (10.3%) fulfilled one, two or all three diagnostic criteria for diabetes mellitus. One year after transplantation, eight additional patients had glycated albumin concentration >12.8%.

CONCLUSION

Our findings are in accordance with the notion that kidney transplant recipients form glycation end products like normal controls as estimated by glycated albumin and HbA_1c. Further studies should address glycated albumin as a supplemental tool for the diagnosis of post-transplant diabetes mellitus in kidney transplant recipients.

Glycated albumin and continuous glucose monitoring metrics across pregnancy in women with pre-gestational diabetes

INTRODUCTION

Glycated albumin (GA), a biomarker reflecting short-term glycaemia, may be useful to assess glycaemic control in pregnancy. We examined the association between GA and continuous glucose monitoring (CGM) metrics across gestation.

METHODS

In this prospective cohort study including 40 women with pre-gestational diabetes, blood samples for analysis of GA and glycated haemoglobin A1c (HbA1c) were collected at pregnancy week 12, 20, 24, 28, 32 and 36. In the CGM-group (n = 19), CGM data were collected from first trimester until pregnancy week 36. Receiver operating characteristic (ROC) curves were used to assess the accuracy of GA and HbA1c to detect poor glycaemic control, using CGM metrics as the reference standard. This study was conducted at Stavanger University Hospital, Norway, in 2016-2018.

RESULTS

Glycaemic control improved across gestation with more time spent in target range, coinciding with decreased glycaemic variability and lower mean GA level. There was statistically significant correlation between GA and most CGM metrics. The area under the ROC curves (AUC) for detecting time in range <70% and time above range >25% for the pregnancy glucose target 63-140 mg/dl (3.5-7.8 mmol/L) were 0.78 and 0.82 for GA, whereas AUCs of 0.60 and 0.72 were found for HbA1c, respectively.

CONCLUSIONS

Higher GA levels were associated with less time spent in target range, more time spent in the above range area and increased glycaemic variability. GA was more accurate than HbA1c to detect time above range >25% and time in range <70%.

Glycated albumin in pregnancy: LC-MS/MS-based reference interval in healthy, nulliparous Scandinavian women and its diagnostic accuracy in gestational diabetes mellitus

Glycated albumin (GA) may be a useful biomarker of glycemia in pregnancy. The aim of this study was to establish the reference interval (RI) for GA, analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), in healthy, nulliparous pregnant women. In addition, we assessed the accuracy of GA and glycated hemoglobin A1c (HbA1c) in the diagnosis of gestational diabetes mellitus (GDM). Finally, we explored the prevalence of GDM in healthy nulliparas, comparing three diagnostic guidelines (WHO-1999, WHO-2013 and the Norwegian guideline). The study was carried out at Stavanger University Hospital, Norway, and included a study population of 147 pregnant nulliparous women. An oral glucose tolerance test (OGTT) was performed and used as the gold standard for GDM diagnosis. Blood samples for analysis of GA and HbA1c were collected at pregnancy week 24-28. A nonparametric approach was chosen for RI calculation, and receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of GA and HbA1c. The established RI for GA in 121 pregnant women was 7.1-11.6%. The area under the ROC curves (AUCs) were 0.531 (GA) and 0.627 (HbA1c). According to the WHO-1999, WHO-2013 and the Norwegian guideline, respectively, 24 (16%), 36 (24%) and 21 (14%) women were diagnosed with GDM. Only nine women (6%) fulfilled the GDM-criteria of all guidelines. In conclusion, we established the first LC-MS/MS-based RI for GA in pregnant women. At pregnancy weeks 24-28, neither GA nor HbA1c discriminated between those with and without GDM. Different women were diagnosed with GDM using the three guidelines.

Quantitation of glycated albumin by isotope dilution mass spectrometry

BACKGROUND

Glycated albumin is considered an alternative glycemic indicator in certain situations where HbA1c does not accurately reflect glycemic status. These patient cases are usually associated with decreased erythrocyte lifespan, gestational diabetes, or end-stage renal disease. The aim of our study was to develop an assay for absolute quantitation of glycated albumin based on isotope dilution liquid chromatography-mass spectrometry.

METHODS

The plasma samples were reduced/alkylated, spiked with isotope-labeled standards RQIKKQTALV(D₈)E and RQIKK(fructosyl)QTALV(D₈)E and enzymatically digested by Glu-C. The samples were analyzed on an LC-MS system. Two MRM transitions (M³⁺ → (b₉-3H₂O)²⁺ and M³⁺ → (b₁₀-3H₂O)²⁺ or M³⁺ → b₉²⁺ and M³⁺ → b₁₀²⁺) were used for each peptide, then the percentage of glycation (MS GA%) was calculated.

RESULTS

The comparison study demonstrated a good linear correlation between our LC-MS/MS and Lucica method with r² = 0.95. The intra-day CV for the low HbA1c sample was 2.2%, while CV for the high HbA1c sample was 0.64%. Inter-day CV for low HbA1c sample was 5.6%, while the CV for the high HbA1c sample was 5.7%. We found the LLOQ to be 0.12 nmol/ml for the non-glycated and glycated peptide. No interference from hemoglobin was observed up to 500 mg/dL concentration.

CONCLUSIONS

This is the first implementation of isotope dilution LC-MS assay for glycated albumin with simultaneously quantitation of glycated and non-glycated peptides. The method includes a simple sample preparation and has demonstrated a good analytical performance.

Comprehensive overview of human serum albumin glycation in diabetes mellitus

The presence of excess glucose in blood is regarded as a sweet hurt for patients with diabetes. Human serum albumin (HSA) is the most abundant protein in human plasma, which undergoes severe non-enzymatic glycation with glucose in patients with diabetes; this modifies the structure and function of HSA. Furthermore, the advanced glycation end products produced by glycated HSA can cause pathological damage to the human body through various signaling pathways, eventually leading to complications of diabetes. Many potential glycation sites on HSA have different degrees of sensitivity to glucose concentration. This review provides a comprehensive assessment of the in vivo glycation sites of HSA; it also discusses the effects of glycation on the structure and function of HSA. Moreover, it addresses the relationship between HSA glycation and diabetes complications. Finally, it focuses on the value of non-enzymatic glycation of HSA in diabetes-related clinical applications.

Dual sensitive and rapid detection of glycated human serum albumin using a versatile lead/graphene nanocomposite probe as a fluorescence-electrochemical aptasensor

Monitoring of glycated human serum albumin (GHSA) as a glycemic marker for screening and monitoring of diabetes mellitus is widely practiced for patients with conditions that affect red blood cells. In this study, a complex comprising Pb ions adsorbed on graphene oxide (GO-Pb) was fabricated and utilized as a versatile probe in a fluorescence-electrochemical aptasensor for GHSA quantification. To simplify the aptasensor, the GO-Pb complex probe was prepared via an ion adsorption process. After modification with a fluorophore-labeled aptamer, the GO-Pb complex served as an excellent energy acceptor in fluorescence-based analysis, as well as generating a high current in the electrochemical transducer. Additionally, the proposed platform can detect GHSA via the dual technique from a single sample, allowing for precise and accurate results. Under optimal conditions, the fluorescence-electrochemical aptasensor exhibited a linear relationship with GHSA concentrations from 0.001 to 80 μg mL^-1 and from 0.005 to 10 μg mL^-1 for fluorescence and electrochemical detection, respectively. The corresponding detection limits were 8.80 ng mL^-1 and 0.77 ng mL^-1, respectively. The proposed aptasensor additionally displayed good selectivity and excellent stability. Moreover, its successful application in the analysis of clinical samples further demonstrated its utility. Therefore, the proposed platform has significant potential as a novel, facile, highly responsive, and low-cost monitoring method for the development of diabetes mellitus diagnostic devices intended for a clinical setting.

Glycation of glucose sensitive lysine residues K36, K438 and K549 of albumin is associated with prediabetes

Prediabetes is a risk factor for the development of diabetes. Early diagnosis of prediabetes may prevent the onset and progression of diabetes and its associated complications. Therefore, this study aimed at the identification of novel markers for efficient prediction of prediabetes. In this pursuit, we have evaluated the ability of glycated peptides of albumin in predicting prediabetes. Glycated peptides of in vitro glycated albumin were characterized by data dependent acquisition and parallel reaction monitoring using LC-HRMS. Amongst 14 glycated peptides characterized in vitro, four peptides, particularly, FK(CML)DLGEENFK, K(AML)VPQVSTPTLVEVSR, K(CML)VPQVSTPTLVEVSR, and K(AML)QTALVELVK, corresponding to 3 glucose sensitive lysine residues K36, K438, and K549, respectively showed significantly higher abundance in prediabetes than control. Additionally, the abundance of three of these peptides, namely K(AML)QTALVELVK, K(CML)VPQVSTPTLVEVSR and FK(CML)DLGEENFK was >1.8-fold in prediabetes, which was significantly higher than the differences observed for FBG, PPG, and HbA1c. Further, the four glycated peptides showed a significant correlation with FBG, PPG, HbA1c, triglycerides, VLDL, and HDL. This study supports that glycated peptides of glucose sensitive lysine residues K36, K438 and K549 of albumin could be potentially useful markers for prediction of prediabetes. SIGNIFICANCE: Undiagnosed prediabetes may lead to diabetes and associated complications. This study reports targeted quantification of four glycated peptides particulary FK(CML)DLGEENFK, K(AML)VPQVSTPTLVEVSR, K(CML)VPQVSTPTLVEVSR, and K(AML)QTALVELVK, corresponding to 3 glucose sensitive lysine residues K36, K438 and K549 respectively by parallel reaction monitoring in healthy and prediabetic subjects. These peptides showed significantly higher abundance in prediabetes than healthy subjects, and showed significant correlation with various clinical parameters including FBG, PPG, HbA1c, and altered lipid profile. Therefore, together these four peptides constitute a panel of markers that can be useful for prediction of prediabetes.

Update on biomarkers of glycemic control

Attaining and maintaining good glycemic control is a cornerstone of diabetes care. The monitoring of glycemic control is currently based on the self-monitoring of blood glucose (SMBG) and laboratory testing for hemoglobin A1c (HbA1c), which is a surrogate biochemical marker of the average glycemia level over the previous 2-3 mo period. Although hyperglycemia is a key biochemical feature of diabetes, both the level of and exposure to high glucose, as well as glycemic variability, contribute to the pathogenesis of diabetic complications and follow different patterns in type 1 and type 2 diabetes. HbA1c provides a valuable, standardized and evidence-based parameter that is relevant for clinical decision making, but several biological and analytical confounders limit its accuracy in reflecting true glycemia. It has become apparent in recent years that other glycated proteins such as fructosamine, glycated albumin, and the nutritional monosaccharide 1,5-anhydroglucitol, as well as integrated measures from direct glucose testing by an SMBG/continuous glucose monitoring system, may provide valuable complementary data, particularly in circumstances when HbA1c results may be unreliable or are insufficient to assess the risk of adverse outcomes. Long-term associations of these alternative biomarkers of glycemia with the risk of complications need to be investigated in order to provide clinically relevant cut-off values and to validate their utility in diverse populations of diabetes patients.

Nano liquid chromatography columns

Nano liquid chromatography (nanoLC), with columns having an inner diameter (ID) of ≤100 μm, can provide enhanced sensitivity and enable analysis of limited samples.

Maillard Proteomics: Opening New Pages

Protein glycation is a ubiquitous non-enzymatic post-translational modification, formed by reaction of protein amino and guanidino groups with carbonyl compounds, presumably reducing sugars and α-dicarbonyls. Resulting advanced glycation end products (AGEs) represent a highly heterogeneous group of compounds, deleterious in mammals due to their pro-inflammatory effect, and impact in pathogenesis of diabetes mellitus, Alzheimer's disease and ageing. The body of information on the mechanisms and pathways of AGE formation, acquired during the last decades, clearly indicates a certain site-specificity of glycation. It makes characterization of individual glycation sites a critical pre-requisite for understanding in vivo mechanisms of AGE formation and developing adequate nutritional and therapeutic approaches to reduce it in humans. In this context, proteomics is the methodology of choice to address site-specific molecular changes related to protein glycation. Therefore, here we summarize the methods of Maillard proteomics, specifically focusing on the techniques providing comprehensive structural and quantitative characterization of glycated proteome. Further, we address the novel break-through areas, recently established in the field of Maillard research, i.e., in vitro models based on synthetic peptides, site-based diagnostics of metabolism-related diseases (e.g., diabetes mellitus), proteomics of anti-glycative defense, and dynamics of plant glycated proteome during ageing and response to environmental stress.

Abundance matters: role of albumin in diabetes, a proteomics perspective

INTRODUCTION

Human serum albumin (HSA) is a multifaceted protein with vital physiological functions. It is the most abundant plasma protein with inherent capability to bind to diverse ligands, and thus susceptible to various post-translational modifications (PTMs) which alter its structure and functions. One such PTM is glycation, a non-enzymatic reaction between reducing sugar and protein leading to formation of heterogeneous advanced glycation end products (AGEs). Glycated albumin (GA) concentration increases significantly in diabetes and is implicated in development of secondary complications. Areas covered: In this review, we discuss in depth, formation of GA and its consequences, approaches used for characterization and quantification of GA, milestones in GA proteomics, clinical relevance of GA as a biomarker, significance of maintaining abundant levels of albumin and future perspectives. Expert commentary: Elevated GA levels are associated with development of insulin resistance as well as secondary complications, in healthy and diabetic individuals respectively. Mass spectrometry (MS) based approaches aid in precise characterization and quantification of GA including early and advanced glycated peptides, which can be useful in prediction of the disease status. Thus GA has evolved to be one of the best candidates in the pursuit of diagnostic markers for prediction of prediabetes and diabetic complications.

Methods of albumin estimation in clinical biochemistry: Past, present, and future

Estimation of serum and urinary albumin is routinely performed in clinical biochemistry laboratories. In the past, precipitation-based methods were popular for estimation of human serum albumin (HSA). Currently, dye-binding or immunochemical methods are widely practiced. Each of these methods has its limitations. Research endeavors to overcome such limitations are on-going. The current trends in methodological aspects of albumin estimation guiding the field have not been reviewed. Therefore, it is the need of the hour to review several aspects of albumin estimation. The present review focuses on the modern trends of research from a conceptual point of view and gives an overview of recent developments to offer the readers a comprehensive understanding of the subject.

Mass spectrometric determination of early and advanced glycation in biology

Protein glycation in biological systems occurs predominantly on lysine, arginine and N-terminal residues of proteins. Major quantitative glycation adducts are found at mean extents of modification of 1-5 mol percent of proteins. These are glucose-derived fructosamine on lysine and N-terminal residues of proteins, methylglyoxal-derived hydroimidazolone on arginine residues and N(ε)-carboxymethyl-lysine residues mainly formed by the oxidative degradation of fructosamine. Total glycation adducts of different types are quantified by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring mode. Metabolism of glycated proteins is followed by LC-MS/MS of glycation free adducts as minor components of the amino acid metabolome. Glycated proteins and sites of modification within them - amino acid residues modified by the glycating agent moiety - are identified and quantified by label-free and stable isotope labelling with amino acids in cell culture (SILAC) high resolution mass spectrometry. Sites of glycation by glucose and methylglyoxal in selected proteins are listed. Key issues in applying proteomics techniques to analysis of glycated proteins are: (i) avoiding compromise of analysis by formation, loss and relocation of glycation adducts in pre-analytic processing; (ii) specificity of immunoaffinity enrichment procedures, (iii) maximizing protein sequence coverage in mass spectrometric analysis for detection of glycation sites, and (iv) development of bioinformatics tools for prediction of protein glycation sites. Protein glycation studies have important applications in biology, ageing and translational medicine - particularly on studies of obesity, diabetes, cardiovascular disease, renal failure, neurological disorders and cancer. Mass spectrometric analysis of glycated proteins has yet to find widespread use clinically. Future use in health screening, disease diagnosis and therapeutic monitoring, and drug and functional food development is expected. A protocol for high resolution mass spectrometry proteomics of glycated proteins is given.