Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

Serum angiopoietin-2: a promising biomarker for early diabetic kidney disease in children and adolescents with type 1 diabetes

Albuminuria has been considered the golden standard biomarker for diabetic kidney disease (DKD), but appears once significant kidney damage has already occurred. Angiopoietin-2 (Angpt-2) has been implicated in the development and progression of DKD in adults. We aimed to explore the association of serum Angpt-2 levels with DKD in children and adolescents with type 1 diabetes mellitus (T1DM) of short duration (3-5 years) and to evaluate the predictive power of serum Angpt-2 in the early detection of DKD prior to the microalbuminuric phase. The current cross-sectional study included 90 children divided into three age and sex-matched groups based on urinary albumin-to-creatinine ratio (UACR): microalbuminuric diabetic group (n = 30), non-albuminuric diabetic group (n = 30), and control group (n = 30). All participants were subjected to anthropometric measurements, serum Angpt-2 and fasting lipid profile (total cholesterol, triglycerides, LDL-C, HDL-C, and Non-HDL-C) assessment. Glomerular filtration rate was estimated based on serum creatinine (eGFR-Cr). Higher serum Angpt-2 levels were detected in both diabetic groups compared to controls and in microalbuminuric compared to non-albuminuric diabetic group. There was no detected significant difference in eGFR-Cr values across the study groups. Serum Angpt-2 was positively correlated with triglycerides, LDL, Non-HDL-C, HbA1c, and UACR, while UACR, HbA1c, and Non-HDL-C were independent predictors for serum Angpt-2. Serum Angpt-2 at level of 137.4 ng/L could discriminate between microalbuminuric and non-albuminuric diabetic groups with AUC = 0.960 and at level of 115.95 ng/L could discriminate between the non-albuminuric diabetic group and controls with AUC = 0.976.Conclusion: Serum Angpt-2 is a promising potent biomarker for the detection of early stage of DKD in childhood T1DM before albuminuria emerges. What is Known? • Urine albumin-to-creatinine ratio (UACR) and glomerular filtration rate (GFR) are the golden standard but late biomarkers for DKD. • Angiopoietin-2 has been implicated in the development and progression of DKD in adults with diabetes, but has not been explored in T1DM children with DKD. What is New? • Higher serum angiopoietin-2 was detected in diabetic groups compared to controls and in microalbuminuric compared to non-albuminuric group. • Angiopoietin-2 correlated positively with triglycerides, LDL, Non-HDL-C, HbA1c, and UACR. • Serum angiopoietin-2 is a promising early diagnostic biomarker for DKD in children with T1DM.

Biomarkers and signaling pathways of diabetic nephropathy and peripheral neuropathy: possible therapeutic intervention of rutin and quercetin

Diabetic nephropathy and peripheral neuropathy are the two main complications of chronic diabetes that contribute to high morbidity and mortality. These conditions are characterized by the dysregulation of multiple molecular signaling pathways and the presence of specific biomarkers such as inflammatory cytokines, indicators of oxidative stress, and components of the renin-angiotensin system. In this review, we systematically collected and collated the relevant information from MEDLINE, EMBASE, ELSEVIER, PUBMED, GOOGLE, WEB OF SCIENCE, and SCOPUS databases. This review was conceived with primary objective of revealing the functions of these biomarkers and signaling pathways in the initiation and progression of diabetic nephropathy and peripheral neuropathy. We also highlighted the potential therapeutic effectiveness of rutin and quercetin, two plant-derived flavonoids known for their antioxidant and anti-inflammatory properties. The findings of our study demonstrated that both flavonoids can regulate important disease-promoting systems, such as inflammation, oxidative stress, and dysregulation of the renin-angiotensin system. Importantly, rutin and quercetin have shown protective benefits against nephropathy and neuropathy in diabetic animal models, suggesting them as potential therapeutic agents. These findings provide a solid foundation for further comprehensive investigations and clinical trials to evaluate the potential of rutin and quercetin in the management of diabetic nephropathy and peripheral neuropathy. This may contribute to the development of more efficient and comprehensive treatment approaches for diabetes-associated complications.

Urine Peptidome Analysis Identifies Common and Stage-Specific Markers in Early Versus Advanced CKD

Given the pathophysiological continuum of chronic kidney disease (CKD), different molecular determinants affecting progression may be associated with distinct disease phases; thus, identification of these players are crucial for guiding therapeutic decisions, ideally in a non-invasive, repeatable setting. Analyzing the urinary peptidome has been proven an efficient method for biomarker determination in CKD, among other diseases. In this work, after applying several selection criteria, urine samples from 317 early (stage 2) and advanced (stage 3b-5) CKD patients were analyzed using capillary electrophoresis coupled to mass spectrometry (CE-MS). The entire two groups were initially compared to highlight the respective pathophysiology between initial and late disease phases. Subsequently, slow and fast progressors were compared within each group in an attempt to distinguish phase-specific disease progression molecules. The early vs. late-stage CKD comparison revealed 929 significantly different peptides, most of which were downregulated and 268 with collagen origins. When comparing slow vs. fast progressors in early stage CKD, 42 peptides were significantly altered, 30 of which were collagen peptide fragments. This association suggests the development of structural changes may be reversible at an early stage. The study confirms previous findings, based on its multivariable-matched progression groups derived from a large initial cohort. However, only four peptide fragments differed between slow vs. fast progressors in late-stage CKD, indicating different pathogenic processes occur in fast and slow progressors in different stages of CKD. The defined peptides associated with CKD progression at early stage might potentially constitute a non-invasive approach to improve patient management by guiding (personalized) intervention.

Endoplasmic reticulum stress in diabetic kidney disease: adaptation and apoptosis after three UPR pathways

Diabetes kidney disease (DKD) is one of the common chronic microvascular complications of diabetes, which has become the most important cause of modern chronic kidney disease beyond chronic glomerulonephritis. The endoplasmic reticulum is one of the largest organelles, and endoplasmic reticulum stress (ERS) is the basic mechanism of metabolic disorder in all organs and tissues. Under the stimulation of stress-induced factors, the endoplasmic reticulum, as a trophic receptor, regulates adaptive and apoptotic ERS through molecular chaperones and three unfolded protein reaction (UPR) pathways, thereby regulating diabetic renal damage. Therefore, three pathway factors have different expressions in different sections of renal tissues. This study deeply discussed the specific reagents, animals, cells, and clinical models related to ERS in DKD, and reviewed ERS-related three pathways on DKD with glomerular filtration membrane, renal tubular reabsorption, and other pathological lesions of different renal tissues, as well as the molecular biological mechanisms related to the balance of adaption and apoptosis by searching and sorting out MeSH subject words from PubMed database.

Alterations in the Circulating Proteome Associated with Albuminuria

SIGNIFICANCE STATEMENT

We describe circulating proteins associated with albuminuria in a population of African American Study of Kidney Disease and Hypertension with CKD (AASK) using the largest proteomic platform to date: nearly 7000 circulating proteins, representing approximately 2000 new targets. Findings were replicated in a subset of a general population cohort with kidney disease (ARIC) and a population with CKD Chronic Renal Insufficiency Cohort (CRIC). In cross-sectional analysis, 104 proteins were significantly associated with albuminuria in the Black group, of which 67 of 77 available proteins were replicated in ARIC and 68 of 71 available proteins in CRIC. LMAN2, TNFSFR1B, and members of the ephrin superfamily had the strongest associations. Pathway analysis also demonstrated enrichment of ephrin family proteins.

BACKGROUND

Proteomic techniques have facilitated understanding of pathways that mediate decline in GFR. Albuminuria is a key component of CKD diagnosis, staging, and prognosis but has been less studied than GFR. We sought to investigate circulating proteins associated with higher albuminuria.

METHODS

We evaluated the cross-sectional associations of the blood proteome with albuminuria and longitudinally with doubling of albuminuria in the African American Study of Kidney Disease and Hypertension (AASK; 38% female; mean GFR 46; median urine protein-to-creatinine ratio 81 mg/g; n =703) and replicated in two external cohorts: a subset of the Atherosclerosis Risk in Communities (ARIC) study with CKD and the Chronic Renal Insufficiency Cohort (CRIC).

RESULTS

In cross-sectional analysis, 104 proteins were significantly associated with albuminuria in AASK, of which 67 of 77 available proteins were replicated in ARIC and 68 of 71 available proteins in CRIC. Proteins with the strongest associations included LMAN2, TNFSFR1B, and members of the ephrin superfamily. Pathway analysis also demonstrated enrichment of ephrin family proteins. Five proteins were significantly associated with worsening albuminuria in AASK, including LMAN2 and EFNA4, which were replicated in ARIC and CRIC.

CONCLUSIONS

Among individuals with CKD, large-scale proteomic analysis identified known and novel proteins associated with albuminuria and suggested a role for ephrin signaling in albuminuria progression.

Novel Biomarkers of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a highly prevalent condition worldwide. It represents one of the most common complications arising from diabetes mellitus (DM) and is the leading cause of end-stage kidney disease (ESKD). Its development involves three fundamental components: the hemodynamic, metabolic, and inflammatory axes. Clinically, persistent albuminuria in association with a progressive decline in glomerular filtration rate (GFR) defines this disease. However, as these alterations are not specific to DKD, there is a need to discuss novel biomarkers arising from its pathogenesis which may aid in the diagnosis, follow-up, therapeutic response, and prognosis of the disease.

Antidiabetic effects of Andrographis paniculata supplementation on biochemical parameters, inflammatory responses, and oxidative stress in canine diabetes

Introduction: Diabetes mellitus is a common endocrine disorder that causes hyperglycemia in dogs. Persistent hyperglycemia can induce inflammation and oxidative stress. This study aimed to investigate the effects of A. paniculata (Burm.f.) Nees (Acanthaceae) (A. paniculata) on blood glucose, inflammation, and oxidative stress in canine diabetes. A total of 41 client-owned dogs (23 diabetic and 18 clinically healthy) were included in this double-blind, placebo-controlled trial. Methods: The diabetic dogs were further divided into two treatments protocols: group 1 received A. paniculata extract capsules (50 mg/kg/day; n = 6) or received placebo for 90 days (n = 7); and group 2 received A. paniculata extract capsules (100 mg/kg/day; n = 6) or received a placebo for 180 days (n = 4). Blood and urine samples were collected every month. No significant differences in fasting blood glucose, fructosamine, interleukin-6, tumor necrosis factor-alpha, superoxide dismutase, and malondialdehyde levels were observed between the treatment and placebo groups (p > 0.05). Results and Discussion: The levels of alanine aminotransferase, alkaline phosphatase, blood urea nitrogen, and creatinine were stable in the treatment groups. The blood glucose levels and concentrations of inflammatory and oxidative stress markers in the client-owned diabetic dogs were not altered by A. paniculata supplementation. Furthermore, treatment with this extract did not have any adverse effects on the animals. Non-etheless, the effects of A. paniculata on canine diabetes must be appropriately evaluated using a proteomic approach and involving a wider variety of protein markers.

Curcuminoid supplementation in canine diabetic mellitus and its complications using proteomic analysis

Introduction

Inflammation and oxidative stress contribute to diabetes pathogenesis and consequences. Therapeutic approaches for canine diabetes remain a challenge. Curcumin has anti-inflammatory and anti-oxidative effects and is beneficial for humans with diabetes mellitus (DM); however, data on its impact on canine diabetes is limited. This study aimed to evaluate the potential for causing adverse effects, anti-inflammatory effects, anti-oxidative effects and proteomic patterns of curcuminoid supplementation on canine DM.

Methods

Altogether, 18 dogs were divided into two groups: DM (n = 6) and healthy (n = 12). Curcuminoid 250 mg was given to the DM group orally daily for 180 days. Blood and urine sample collection for hematological parameters, blood biochemistry, urinalysis, oxidative stress parameters, inflammatory markers and proteomics were performed every 6 weeks.

Results and discussion

Curcuminoid supplementation with standard therapy significantly decreased oxidative stress with the increased glutathione/oxidized glutathione ratio, but cytokine levels were unaffected. According to the proteomic analysis, curcuminoid altered the expression of alpha-2-HS-glycoprotein, transthyretin, apolipoprotein A-I and apolipoprotein A-IV, suggesting that curcuminoid improves insulin sensitivity and reduces cardiovascular complications. No negative impact on clinical symptoms, kidneys or liver markers was identified. This study proposed that curcuminoids might be used as a targeted antioxidant strategy as an adjunctive treatment to minimize diabetes complications in dogs.

Multi-Scalar Data Integration Links Glomerular Angiopoietin-Tie Signaling Pathway Activation With Progression of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N = 58) in the Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this panel improved prediction of the composite outcome of ESKD or a 40% decline in glomerular filtration rate. The panel was validated in an independent group (N = 68), who also had kidney transcriptomic profiles. One marker, plasma angiopoietin 2 (ANGPT2), was significantly associated with outcomes in cohorts from the Cardiovascular Health Study (N = 3,183) and the Chinese Cohort Study of Chronic Kidney Disease (N = 210). Glomerular transcriptional angiopoietin/Tie (ANG-TIE) pathway scores, derived from the expression of 154 ANG-TIE signaling mediators, correlated positively with plasma ANGPT2 levels and kidney outcomes. Higher receptor expression in glomeruli and higher ANG-TIE pathway scores in endothelial cells corroborated potential functional effects in the kidney from elevated plasma ANGPT2 levels. Our work suggests that ANGPT2 is a promising prognostic endothelial biomarker with likely functional impact on glomerular pathogenesis in DKD.

Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers

Background

Osteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers.

Methods

Serum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography–tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis.

Results

In total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins from both OA groups, some of them alone would not be a suitable choice as specific OA biomarkers due to their rather non-specific role or their strong link to other pathological conditions. Altogether, data revealed that the protein CRTAC1 appears to be a strong OA biomarker candidate. Other potential new biomarker candidates are the proteins FBN1, VDBP, and possibly SERPINF1. Validation experiments revealed statistical differences between controls and OA for FBN1 (p=0.044) and VDPB (p=0.022), and a trend for SERPINF1 (p=0.064).

Conclusion

Our study suggests that 4 proteins, CRTAC1, FBN1, VDBP, and possibly SERPINF1, warrant further investigation as potential new biomarker candidates for the whole OA population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-022-02801-1.

Metabolomics as a tool for the early diagnosis and prognosis of diabetic kidney disease

Diabetic kidney disease (DKD) is one of the most prevalent comorbidities of diabetes mellitus and the leading cause of the end-stage renal disease (ESRD). DKD results from chronic exposure to hyperglycemia, leading to progressive alterations in kidney structure and function. The early development of DKD is clinically silent and when albuminuria is detected the lesions are often at advanced stages, leading to rapid kidney function decline towards ESRD. DKD progression can be arrested or substantially delayed if detected and addressed at early stages. A major limitation of current methods is the absence of albuminuria in non-albuminuric phenotypes of diabetic nephropathy, which becomes increasingly prevalent and lacks focused therapy. Metabolomics is an ever-evolving omics technology that enables the study of metabolites, downstream products of every biochemical event that occurs in an organism. Metabolomics disclosures complex metabolic networks and provide knowledge of the very foundation of several physiological or pathophysiological processes, ultimately leading to the identification of diseases' unique metabolic signatures. In this sense, metabolomics is a promising tool not only for the diagnosis but also for the identification of pre-disease states which would confer a rapid and personalized clinical practice. Herein, the use of metabolomics as a tool to identify the DKD metabolic signature of tubule interstitial lesions to diagnose or predict the time-course of DKD will be discussed. In addition, the proficiency and limitations of the currently available high-throughput metabolomic techniques will be discussed.

Stratification of diabetic kidney diseases via data-independent acquisition proteomics-based analysis of human kidney tissue specimens

AIM

The aims of this study were to analyze the proteomic differences in renal tissues from patients with diabetes mellitus (DM) and diabetic kidney disease (DKD) and to select sensitive biomarkers for early identification of DKD progression.

METHODS

Pressure cycling technology-pulse data-independent acquisition mass spectrometry was employed to investigate protein alterations in 36 formalin-fixed paraffin-embedded specimens. Then, bioinformatics analysis was performed to identify important signaling pathways and key molecules. Finally, the target proteins were validated in 60 blood and 30 urine samples.

RESULTS

A total of 52 up- and 311 down-regulated differential proteins were identified as differing among the advanced DKD samples, early DKD samples, and DM controls (adjusted p<0.05). These differentially expressed proteins were mainly involved in ion transport, apoptosis regulation, and the inflammatory response. UniProt database analysis showed that these proteins were mostly enriched in signaling pathways related to metabolism, apoptosis, and inflammation. NBR1 was significantly up-regulated in both early and advanced DKD, with fold changes (FCs) of 175 and 184, respectively (both p<0.01). In addition, VPS37A and ATG4B were significantly down-regulated with DKD progression, with FCs of 0.140 and 0.088, respectively, in advanced DKD and 0.533 and 0.192, respectively, in early DKD compared with the DM control group (both p<0.01). Bioinformatics analysis showed that NBR1, VPS37A, and ATG4B are closely related to autophagy. We also found that serum levels of the three proteins and urine levels of NBR1 decreased with disease progression. Moreover, there was a significant difference in serum VPS37A and ATG4B levels between patients with early and advanced DKD (both p<0.05). The immunohistochemistry assaay exhibited that the three proteins were expressed in renal tubular cells, and NBR1 was also expressed in the cystic wall of renal glomeruli.

CONCLUSION

The increase in NBR1 expression and the decrease in ATG4B and VPS37 expression in renal tissue are closely related to inhibition of the autophagy pathway, which may contribute to DKD development or progression. These three proteins may serve as sensitive serum biomarkers for early identification of DKD progression.

Protein discrimination using erythrosin B-based GUMBOS in combination with UV-Vis spectroscopy and chemometrics

GUMBOS (Group of Uniform Materials Based on Organic Salts) have recently emerged as interesting materials for protein analysis due to their unique features and high tunability. In this regard, four novel erythrosin B (EB)-based GUMBOS were synthesized and their potential to discriminate among proteins with distinct properties (e.g., size, charge, and hydrophobicity) was assessed. These solid-phase materials were prepared using a single-step metathesis reaction between EB and various phosphonium and ammonium cations, namely tetrabutylphosphonium (P₄₄₄₄⁺), tributylhexadecylphosphonium (P₄₄₄₁₆⁺), tetrabutylammonium (N₄₄₄₄⁺), and benzyldimethylhexadecylammonium (BDHA⁺). Subsequently, the effect of pH (3.0, 4.5, and 6.0) and reaction time (5, 10, and 15 min) on the discriminatory power of synthesized GUMBOS was evaluated. Absorption spectra resulting from the interaction between EB-based GUMBOS and proteins were analyzed using partial least squares discriminant analysis (PLSDA). Unlike time, the pH value was determined to have influence over GUMBOS discrimination potential. Correct protein assignments varied from 86.5% to 100.0%, and the best discriminatory results were observed for [P₄₄₄₄]₂[EB] and [N₄₄₄₄]₂[EB] at pH 6.0. Additionally, these two GUMBOS allowed discrimination of protein mixtures containing different ratios of albumin and myoglobin, which appeared as individualized clusters in the PLSDA scores plots. Overall, this study showcases EB-based GUMBOS as simple synthetic targets to provide a label-free, cost-effective, rapid, and successful approach for discrimination of single proteins and their mixtures.

Importance of Identifying Novel Biomarkers of Microvascular Damage in Type 1 Diabetes

Microvascular complications of type 1 diabetes, which primarily include diabetic kidney disease, retinopathy, and neuropathy, are characterized by damage to the microvasculature of the kidney, retina, and neurons. The pathogenesis of these complications is multifactorial, and several pathways are implicated. These complications are often silent during their early stages, and once symptoms develop, there might be little to be done to cure them. Thus, there is a strong need for novel biomarkers to identify individuals at risk of microvascular complications at an early stage and guide the implementation of new therapeutic options for preventing their development and progression. Recent advancements in proteomics, metabolomics, and other 'omics' have led to the identification of several potential biomarkers of microvascular complications. However, biomarker discovery has met several challenges and, up to now, there are no new biomarkers that have been implemented into clinical practice. This highlights the need for further work in this area to move towards better diagnostic and prognostic approaches.

Urinary proteomics for kidney dysfunction: insights and trends

Introduction: Kidney dysfunction poses a high burden on patients and health care systems. Early detection and accurate prediction of kidney disease progression remains a major challenge. Compared to existing clinical parameters, urinary proteomics has the potential to reveal molecular alterations within the kidney that may alter its function before the onset of clinical symptoms. Thus, urinary proteomics has greater prognostic potential for assessment of kidney dysfunction progression.Areas covered: Advances in urinary proteomics for major causes of kidney dysfunction are discussed. The application of urinary extracellular vesicles for studying kidney dysfunction are discussed. Technological advances in urinary proteomics are discussed. The literature was identified using a database search for titles containing 'proteom*' and 'urin*' and published within the past 5 years. Retrieved literature was manually filtered to retain kidney dysfunctions-related studies.Expert opinion: Despite major advances, diagnosis by urinary proteomics has not been fully applied in any clinical settings. This could be attributed to the complex nature of kidney diseases, in addition to the constraints on study power and feasibility of incorporating mass spectrometry techniques in daily routine analysis. Nevertheless, we are confident that advances in urinary proteomics will soon provide superior insights into kidney disease beyond existing clinical parameters.

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study

BACKGROUND

Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed.

METHODS

A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR.

RESULTS

In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR.

CONCLUSIONS

In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

A Phase IIb Randomized Controlled Trial Investigating the Effects of Tocotrienol-Rich Vitamin E on Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a debilitating complication of diabetes, which develops in 40% of the diabetic population and is responsible for up to 50% of end-stage renal disease (ESRD). Tocotrienols have shown to be a potent antioxidant, anti-inflammatory, and antifibrotic agent in animal and clinical studies. This study evaluated the effects of 400 mg tocotrienol-rich vitamin E supplementation daily on 59 DKD patients over a 12-month period. Patients with stage 3 chronic kidney disease (CKD) or positive urine microalbuminuria (urine to albumin creatinine ratio; UACR > 20–200 mg/mmol) were recruited into a randomized, double-blind, placebo-controlled trial. Patients were randomized into either intervention group (n = 31) which received tocotrienol-rich vitamin E (Tocovid SupraBio^TM; Hovid Berhad, Ipoh, Malaysia) 400 mg daily or a placebo group which received placebo capsules (n = 28) for 12 months. HbA1c, renal parameters (i.e., serum creatinine, eGFR, and UACR), and serum biomarkers were collected at intervals of two months. Tocovid supplementation significantly reduced serum creatinine levels (MD: −4.28 ± 14.92 vs. 9.18 ± 24.96), p = 0.029, and significantly improved eGFR (MD: 1.90 ± 5.76 vs. −3.29 ± 9.24), p = 0.011 after eight months. Subgroup analysis of 37 patients with stage 3 CKD demonstrated persistent renoprotective effects over 12 months; Tocovid improved eGFR (MD: 4.83 ± 6.78 vs. −1.45 ± 9.18), p = 0.022 and serum creatinine (MD: −7.85(20.75) vs. 0.84(26.03), p = 0.042) but not UACR. After six months post washout, there was no improvement in serum creatinine and eGFR. There were no significant changes in the serum biomarkers, TGF-β1 and VEGF-A. Our findings verified the results from the pilot phase study where tocotrienol-rich vitamin E supplementation at two and three months improved kidney function as assessed by serum creatinine and eGFR but not UACR.

Current updates on protein as biomarkers for diabetic kidney disease: a systematic review

BACKGROUND

In the past decade, researchers have been focused on discovering protein biomarkers for diabetic kidney disease. This paper aims to search for, analyze, and synthesize current updates regarding the development of these efforts.

METHODS

We systematically searched the ScienceDirect, SpringerLink, and PubMed databases for observational studies of protein biomarkers in patients with diabetes mellitus. We included studies published between January 2018 and April 2020, that were based on a population of patients with type-1 or type-2 diabetes mellitus aged ⩾18 years, with an observational design such as cross-sectional, case-control, or cohort studies. The dependent variable of the research results was in the form of protein biomarkers from urine, plasma, or serum.

RESULTS

Following the screening process, 20 research articles with available full text met the inclusion criteria. These could be categorized as glomerular biomarkers (ANGPTL4, beta-2 microglobulin, Smad1, and glypican-5); inflammatory biomarkers (MCP-1 and adiponectin); and tubular biomarkers (NGAL, VDBP, megalin, sKlotho, and KIM-1). The development of a panel of biomarkers showed more promising results than those for a single biomarker in diagnosing diabetic kidney disease.

CONCLUSION

All the biomarkers discussed in this review showed promising results for predicting diabetic kidney disease because they correlate with albuminuria, eGFR, or both. However, of the 11 protein biomarkers, none have prognostic value beyond albuminuria and eGFR.

Genomics, Proteomics and Metabolomics Approaches for Predicting Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients

BACKGROUND

There is a continuous rise in the prevalence of type 2 diabetes mellitus (T2DM) worldwide and most patients are unaware of the presence of this chronic disease at the early stages. T2DM is associated with complications related to long-term damage and failure of multiple organ systems caused by vascular changes associated with glycated end products, oxidative stress, mild inflammation, and neovascularization. Among the most frequent complications of T2DM observed in about 20-40% of T2DM patients is diabetes nephropathy (DN).

METHODS

A literature search was made in view of highlighting the novel applications of genomics, proteomics and metabolomics, as the new prospective strategy for predicting DN in T2DM patients.

RESULTS

The complexity of DN requires a comprehensive and unbiased approach to investigate the main causes of disease and identify the most important mechanisms underlying its development. With the help of evolving throughput technology, rapidly evolving information can now be applied to clinical practice.

DISCUSSION

DN is also the leading cause of end-stage renal disease and comorbidity independent of T2DM. In terms of the comorbidity level, DN has many phenotypes; therefore, timely diagnosis is required to prevent these complications. Currently, urine albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are gold standards for assessing glomerular damage and changes in renal function. However, GFR estimation based on creatinine is limited to hyperfiltration status; therefore, this makes albuminuria and eGFR indicators less reliable for early-stage diagnosis of DN.

CONCLUSION

The combination of genomics, proteomics, and metabolomics assays as suitable biological systems can provide new and deeper insights into the pathogenesis of diabetes, as well as discover prospects for developing suitable and targeted interventions.

Multiplexed MRM-based protein quantification of putative prognostic biomarkers for chronic kidney disease progression in plasma

Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. The disease complexity and heterogeneity underscore the need for multiplex quantification of different markers. The goal of this study was to determine the association of six previously reported CKD-associated plasma proteins [B2M (Beta-2-microglobulin), SERPINF1 (Pigment epithelium-derived factor), AMBP (Protein AMBP), LYZ (Lysozyme C), HBB (Hemoglobin subunit beta) and IGHA1 (Immunoglobulin heavy constant alpha 1)], as measured in a multiplex format, with kidney function, and outcome. Antibody-free, multiple reaction monitoring mass spectrometry (MRM) assays were developed, characterized for their analytical performance, and used for the analysis of 72 plasma samples from a patient cohort with longitudinal follow-up. The MRM significantly correlated (Rho = 0.5–0.9) with results from respective ELISA. Five proteins [AMBP, B2M, LYZ, HBB and SERPINF1] were significantly associated with eGFR, with the three former also associated with unfavorable outcome. The combination of these markers provided stronger associations with outcome (p < 0.0001) compared to individual markers. Collectively, our study describes a multiplex assay for absolute quantification and verification analysis of previously described putative CKD prognostic markers, laying the groundwork for further use in prospective validation studies.

Growth differentiation factor 15 (GDF-15) is a potential biomarker of both diabetic kidney disease and future cardiovascular events in cohorts of individuals with type 2 diabetes: a proteomics approach

Background: Diabetic kidney disease (DKD) is a leading risk factor for end-stage renal disease and is one of the most important risk factors for cardiovascular disease in patients with diabetes. It is possible that novel markers portraying the pathophysiological underpinning processes may be useful.Aim: To investigate the associations between 80 circulating proteins, measured by a proximity extension assay, and prevalent DKD and major adverse cardiovascular events (MACE) in type 2 diabetes.Methods: We randomly divided individuals with type 2 diabetes from three cohorts into a two-thirds discovery and one-third replication set (total n = 813, of whom 231 had DKD defined by estimated glomerular filtration rate <60 mg/mL/1.73 m² and/or urinary albumin-creatinine ratio ≥3 g/mol). Proteins associated with DKD were also assessed as predictors for incident major adverse cardiovascular events (MACE) in persons with DKD at baseline.Results: Four proteins were positively associated with DKD in models adjusted for age, sex, cardiovascular risk factors, glucose control, and diabetes medication: kidney injury molecule-1 (KIM-1, odds ratio [OR] per standard deviation increment, 1.65, 95% confidence interval [CI] 1.27-2.14); growth differentiation factor 15 (GDF-15, OR 1.40, 95% CI 1.16-1.69); myoglobin (OR 1.57, 95% CI 1.30-1.91), and matrix metalloproteinase 10 (MMP-10, OR 1.43, 95% CI 1.17-1.74). In patients with DKD, GDF-15 was significantly associated with increased risk of MACE after adjustments for baseline age, sex, microalbuminuria, and kidney function and (59 MACE events during 7 years follow-up, hazard ratio per standard deviation increase 1.43 [95% CI 1.03-1.98]) but not after further adjustments for cardiovascular risk factors.Conclusion: Our proteomics approach confirms and extends previous associations of higher circulating levels of GDF-15 with both micro- and macrovascular disease in patients with type 2 diabetes. Our data encourage additional studies evaluating the clinical utility of our findings.

Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease

The aim of this study was to establish a peptidomic profile based on LC-MS/MS and random forest (RF) algorithm to distinguish the urinary peptidomic scenario of type 2 diabetes mellitus (T2DM) patients with different stages of diabetic kidney disease (DKD). Urine from 60 T2DM patients was collected: 22 normal (stage A1), 18 moderately increased (stage A2) and 20 severely increased (stage A3) albuminuria. A total of 1080 naturally occurring peptides were detected, which resulted in the identification of a total of 100 proteins, irrespective of the patients’ renal status. The classification accuracy showed that the most severe DKD (A3) presented a distinct urinary peptidomic pattern. Estimates for peptide importance assessed during RF model training included multiple fragments of collagen and alpha-1 antitrypsin, previously associated to DKD. Proteasix tool predicted 48 proteases potentially involved in the generation of the 60 most important peptides identified in the urine of DM patients, including metallopeptidases, cathepsins, and calpains. Collectively, our study lightened some biomarkers possibly involved in the pathogenic mechanisms of DKD, suggesting that peptidomics is a valuable tool for identifying the molecular mechanisms underpinning the disease and thus novel therapeutic targets.

Unraveling the Role of Inflammation in the Pathogenesis of Diabetic Kidney Disease

Diabetic kidney disease (DKD) remains the leading cause of end-stage renal disease (ESRD) and is therefore a major burden on the healthcare system. Patients with DKD are highly susceptible to developing cardiovascular disease, which contributes to increased morbidity and mortality rates. While progress has been made to inhibit the acceleration of DKD, current standards of care reduce but do not eliminate the risk of DKD. There is growing appreciation for the role of inflammation in modulating the process of DKD. The focus of this review is on providing an overview of the current status of knowledge regarding the pathologic roles of inflammation in the development of DKD. Finally, we summarize recent therapeutic advances to prevent DKD, with a focus on the anti-inflammatory effects of newly developed agents.

Metabolic and proteomic signatures of hypoglycaemia in type 2 diabetes

AIMS

To determine the biochemical changes that underlie hypoglycaemia in a healthy control group and in people with type 2 diabetes (T2D).

MATERIALS AND METHODS

We report a hypoglycaemic clamp study in seven healthy controls and 10 people with T2D. Blood was withdrawn at four time points: at baseline after an overnight fast; after clamping to euglycaemia at 5 mmol/L; after clamping to hypoglycaemia at 2.8 mmol/L; and 24 hours later, after overnight fast. Deep molecular phenotyping using non-targeted metabolomics and the SomaLogic aptamer-based proteomics platform was performed on collected samples.

RESULTS

A total of 955 metabolites and 1125 proteins were identified, with significant alterations in >90 molecules. A number of metabolites significantly increased during hypoglycaemia, but only cortisol, adenosine-3',5'-cyclic monophosphate (cyclic AMP), and pregnenolone sulphate, were independent of insulin. By contrast, identified protein changes were triggered by hypoglycaemia rather than insulin. The T2D group had significantly higher levels of fatty acids including 10-nonadecenoate, linolenate and dihomo-linoleate during hypoglycaemia compared with the control group. Molecules contributing to cardiovascular complications such as fatty-acid-binding protein-3 and pregnenolone sulphate were altered in the participants with T2D during hypoglycaemia. Almost all molecules returned to baseline at 24 hours.

CONCLUSIONS

The present study provides a comprehensive description of molecular events that are triggered by insulin-induced hypoglycaemia. We identified deregulated pathways in T2D that may play a role in the pathophysiology of hypoglycaemia-induced cardiovascular complications.

Urinary Proteomics in Biomarker Discovery of Kidney-Related Disorders: Diabetic Nephropathy and Drug-Induced Nephrotoxicity in Chronic Headache

OBJECTIVE

Urinary proteomics is primarily applied to the study of renal and urogenital tract disorders. Here are reported two distinct successful examples of this approach for the discovery of early urinary biomarkers of kidney-related dysfunctions: diabetic nephropathy (DN), a well-known complication of diabetes frequently leading to dialysis, and drug-induced nephrotoxicity, a possible condition caused by medication-overuse headache (MOH). Early detection of kidney disorders based on selective biomarkers could permit to diagnose patients at the initial stage of the disease, where the therapy may be suspended or prevent disease advancement.

METHODS

Urine samples were first concentrated and desalted. Subsequently, they were subjected to two-dimensional gel electrophoresis (2-DE) coupled to mass spectrometry (MS) for protein identification. Furthermore, some proteins were verified by Western blot and ELISA test.

RESULTS

In diabetes-related study, 11 differentially expressed proteins were detected (8 up-regulated and 3 down-regulated) in type 2 diabetic (T2D) and T2DN patients compared to the healthy control subjects. In the MOH study, a total of 21 over-excreted proteins were revealed in urine of non-steroidal anti-inflammatory drugs (NSAIDs) and mixtures abusers vs controls. Particularly, 4 proteins were positively validated by immunob-lotting and EUSA.

CONCLUSION

Urinary proteomics allows non-invasive assessment of renal diseases at an early stage by the identification of characteristic protein pattern.

An integrative systems biology approach for precision medicine in diabetic kidney disease

Current therapeutic approaches are ineffective in many patients with established diabetic kidney disease (DKD), an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large-scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed show that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to first identify patients at high risk of progression, and second to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.

Biomarkers of diabetic kidney disease

Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.

Proteomics for Biomarker Identification and Clinical Application in Kidney Disease

Treatment effectiveness for kidney disease is limited by lack of accuracy, sensitivity, specificity of diagnostic, prognostic, and therapeutic biomarkers. The gold standard test renal biopsy along with serum creatinine and proteinuria is often necessary to establish a diagnosis, particularly in glomerular disease. Proteomics has become a powerful tool for novel biomarker discovery in kidney disease. Novel proteomics offer earlier and more accurate diagnosis of renal pathology than possible with traditional biomarkers such as serum creatinine and urine protein. In addition, proteomic biomarkers could also be useful to choose the most suitable therapeutic targets. This review focuses on the current status of proteomic biomarkers from animal models (5/6 nephrectomy, unilateral ureteral obstruction, and diabetic nephropathy) and human studies (chronic kidney disease, glomerular diseases, transplantation, dialysis, acute and drug-induced kidney injury) to assess relevant findings and clinical usefulness. Current issues and problems related to the discovery, validation, and clinical application of proteomic biomarkers are discussed. We also describe several proteomic strategies highlighting technologic advancements, specimen selection, data processing and analysis. This review might provide help in future proteomic studies to improve the diagnosis and management of kidney disease.

Pooled Analysis of Multiple Crossover Trials To Optimize Individual Therapy Response to Renin-Angiotensin-Aldosterone System Intervention

BACKGROUND AND OBJECTIVES

In the treatment of CKD, individual patients show a wide variation in their response to many drugs, including renin-angiotensin-aldosterone system inhibitors (RAASi). To investigate whether therapy resistance to RAASi can be overcome by uptitrating the dose of drug, changing the mode of intervention (with drugs from similar or different classes), or lowering dietary sodium intake, we meta-analyzed individual responses to different modes of interventions.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Randomized crossover trials were analyzed to assess correlation of individual responses to RAASi and nonsteroidal anti-inflammatory drugs (NSAIDs; n=395 patients). Included studies compared the antialbuminuric effect of uptitrating the dose of RAASi (n=10 studies) and NSAIDs (n=1), changing within the same class of RAASi (e.g., angiotensin-converting enzyme inhibition to angiotensin receptor blockers; n=5) or NSAIDs (n=1), changing from RAASi to NSAIDs (n=2), and changing from high to low sodium intake (n=5). A two-stage meta-analysis was conducted: Deming regression was conducted in each study to assess correlations in response, and individual study results were then meta-analyzed.

RESULTS

The albuminuria response to one dose of RAASi or NSAIDs positively correlated with the response to a higher dose of the same drug (r=0.72; 95% confidence interval [95% CI], 0.66 to 0.78), changes within the same class of RAASi or NSAIDs (r=0.54; 95% CI, 0.35 to 0.68), changes between RAASi and NSAIDs (r=0.44; 95% CI, 0.16 to 0.66), and changes from high to moderately low salt intake (r=0.36; 95% CI, 0.22 to 0.48). Results were similar when the individual systolic BP and potassium responses were analyzed, and were consistent in patients with and without diabetes.

CONCLUSIONS

Individuals who show a poor response to one dose or type of RAASi also show a poor response to higher doses, other types of RAASi or NSAIDs, or a reduction in dietary salt intake. Whether other drugs or drug combinations targeting pathways beyond the renin-angiotensin-aldosterone system and prostaglandins would improve the individual poor response requires further study.