Biomarkers Of Kidney Disease Research Articles

Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance.

As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patients. We conducted a targeted metabolomics study of 26 urinary metabolites in consecutive patients with DKD stage 1 to 5 (n = 208) and healthy controls (n = 26). The relationships between estimated glomerular filtration rate (eGFR) or urine protein-creatinine ratio (UPCR) and metabolites were evaluated. Multivariate Cox analysis was used to estimate relationships between urinary metabolites and the target outcome, end-stage renal disease (ESRD). C statistics and time-dependent receiver operating characteristics (ROC) were used to assess diagnostic validity. During a median 4.5 years of follow-up, 103 patients (44.0%) progressed to ESRD and 65 (27.8%) died. The median fold changes of nine metabolites belonged to monosaccharide and tricarboxylic acid (TCA) cycle metabolites tended to increase with DKD stage. Myo-inositol, choline, and citrates were correlated with eGFR and choline, while mannose and myo-inositol were correlated with UPCR. Elevated urinary monosaccharide and TCA cycle metabolites showed associations with increased morality and ESRD progression. The predictive power of ESRD progression was high, in the order of choline, myo-inositol, and citrate. Although urinary metabolites alone were less predictive than serum creatinine or UPCR, myo-inositol had additive effect with serum creatinine and UPCR. In time-dependent ROC, myo-inositol was more predictive than UPCR of 1-year ESRD progression prediction. Myo-inositol can be used as an additive biomarker of ESRD progression in DKD.

Function follows form: the quest for the best prognostic imaging biomarker in ADPKD

Total kidney volume represents the most solid prognostic biomarker for autosomal dominant polycystic kidney disease, because it mirrors cyst growth that precedes kidney function decline. Considerable variability of glomerular filtration rate trajectories, however, remains unexplained by total kidney volume, and its calculation is time-consuming. Using deep learning algorithms, Gregory etal. determined total kidney volume and other, novel, imaging-based biomarkers. They achieved automation and improved prognostic accuracy for long-term kidney function loss, yet the study leaves some open questions and room for further improvement.

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

Diabetic kidney disease (DKD) is one of the most debilitating complications of type 2 diabetes mellitus (T2DM), as it progresses silently to end-stage renal disease (ESRD). The discovery of novel biomarkers of early DKD becomes acute, as its incidence is reaching catastrophic proportions. Our study aimed to quantify previously identified metabolites from serum and urine through untargeted ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-ESI+-MS) techniques, such as the following: arginine, dimethylarginine, hippuric acid, indoxyl sulfate, p-cresyl sulfate, L-acetylcarnitine, butenoylcarnitine and sorbitol. The study concept was based on the targeted analysis of selected metabolites, using the serum and urine of 20 healthy subjects and 90 T2DM patients with DKD in different stages (normoalbuminuria-uACR < 30 mg/g; microalbuminuria-uACR 30-300 mg/g; macroalbuminuria-uACR > 300 mg/g). The quantitative evaluation of metabolites was performed with pure standards, followed by the validation methods such as the limit of detection (LOD) and the limit of quantification (LOQ). The following metabolites from this study resulted as possible biomarkers of early DKD: in serum-arginine, dimethylarginine, hippuric acid, indoxyl sulfate, butenoylcarnitine and sorbitol and in urine-p-cresyl sulfate.

Significance of Diabetic Kidney Disease Biomarkers in Predicting Metabolic-Associated Fatty Liver Disease.

Metabolic-associated fatty liver disease (MAFLD) and diabetic kidney disease (DKD) share various pathophysiological factors, and epidemiological evidence suggests that these two diseases are associated. Albuminuria and the estimated glomerular filtration rate, which are conventional biomarkers of DKD, are reportedly associated with the risk or severity of MAFLD. Recently, novel DKD biomarkers reflecting renal tubular injury have been introduced to complement conventional DKD markers. In this article, we looked at previous studies that showed an association between MAFLD and DKD, and also reviewed the significance of DKD biomarkers as predictive risk factors for MAFLD.

Microneedle coupled epidermal sensor for multiplexed electrochemical detection of kidney disease biomarkers

Early diagnosis of chronic kidney disease (CKD) and constant monitoring to guide optimal intervention is critical to prevent renal failure and other critical diseases. However, the conventional blood tests in hospital are time-consuming and have poor patient compliance. Herein, we demonstrate a real-time, minimally invasive, and self-administrable approach to detect kidney biomarkers in the skin interstitial fluid (ISF) using a polymeric microneedle coupled electrochemical sensor array (MNESA). Microneedles can readily penetrate stratum corneum and quickly extract ISF onto the sensors. Four biomarkers are simultaneously detected to avoid false positive and provide an accurate assessment of kidney functions. Using an artificial skin model, it is shown that MNSEA gives specific and sensitive responses to these kidney biomarkers in physiologically relevant ranges (phosphate: 0.3–1.8 mM, 3.62 μA/mM; uric acid: 50–550 μM, 4.19 nA/μM; creatinine: 50–550 μM, 12.58 nA/μM; urea: 1–16 mM, 44.6 mV/decade). Using a mouse model, we demonstrate that this approach is as reliable as the commercial assays and is feasible to readily monitor the progression of CDK.

Methyl functionalization of trimesic acid in copper-based metal-organic framework for ammonia colorimetric sensing at high relative humidity

Exhaled ammonia (NH3) can be used as a crucial biomarker of kidney and liver diseases. However, the high humidity in the detection conditions remains a challenge for accurate detection by gas sensors. Herein, a copper-based metal-organic framework (CH3-Cu-BTC) with methyl (CH3-) functionalization of trimesic acid was synthesized for NH3 colorimetric sensing. The CH3-Cu-BTC exhibited a strong response for 5 ppm NH3 with high selectivity under high relative humidity (75% RH). Density functional theory (DFT) simulations indicated that the NH3 molecules interacted more strongly with CH3-Cu-BTC than H2O molecules did, and the corresponding color switching was attributed to the lone-pair electron in NH3 changing the coordination environment of Cu2+ ions, leading to an obviously visible color switching response from ruby green to blue. Based on the tailor-made pore chemistry, the precise detection of trace amounts of NH3 in exhaled air was realized through functionalized MOF materials. The strategy used in this study not only offers a new pathway for the rapid detection of low concentration NH3 under humid conditions, but also shows a method for early respiration diagnosis of kidney and liver diseases.

Elevated serum trimethylamine oxide levels as potential biomarker for diabetic kidney disease

Diabetic kidney disease (DKD) has become a major cause of chronic kidney disease. However, early diagnosis of DKD is challenging. Trimethylamine oxide (TMAO) is an intestinal microbial metabolite which might be associated with diabetes complications. The aim of this study was to investigate the correlation between TMAO and DKD. A cross-sectional study was conducted. 108 T2DM patients and 33 healthy subjects were enrolled in this study. Multiple logistic regression analysis and area under receiver operating characteristic curve (AUROC) were performed to evaluate the correlation between serum TMAO and DKD. Serum TMAO levels were significantly higher in DKD patients than healthy control group and the NDKD (T2DM without combined DKD) group (P < 0.05). TMAO levels were negatively correlated with eGFR and positively correlated with urea nitrogen, ACR and DKD (P < 0.05). Logistic regression analysis indicated that serum TMAO was one of the independent risk factors for DKD patients (P < 0.05). In the diagnostic model, the AUROC of TMAO for the diagnosis of DKD was 0.691. Elevated levels of serum TMAO levels were positively associated with the risk of DKD in T2DM patients, which might be a potential biomarker for DKD.

In-depth urinary and exosome proteome profiling analysis identifies novel biomarkers for diabetic kidney disease.

Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics (n=144) and urinary exosome proteomics (n=44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

1092-P: sRAGE—A Biomarker of Kidney Disease in Youth-Onset Type 2 Diabetes (T2D)

The circulating soluble receptor for advanced glycation end products (sRAGE) has been proposed as a biomarker of diabetes complications in adults. In the TODAY study of youth with T2D, we measured sRAGE 3 times at: randomization (T1), glycemic failure (HbA1c≥8%) on randomized treatment or midpoint in study (T2), and end of follow-up (T3). Of TODAY subjects, 165 lost glycemic control with HbA1c ≥ 8% (G1) and 135 maintained HbA1c &amp;lt; 8% (G2)]. Controls [n=99, HbA1 5% (4.9, 5.2), with similar obesity, sex (60% female), race-ethnicity, median age 24 (21, 27) years as the TODAY cohort at T3] had sRAGE measured once. Multivariable models examined the relationship of sRAGE with nephropathy [urine albumin: creatinine (UACR) ≥30 mg/g, hyperfiltration (eGFR ≥135 ml/min/1.73m2)] and vascular measures [pulse wave velocity (PWV), augmentation index (AI)], adjusting for treatment, diabetes duration, HbA1c, BMI, age, sex, and race-ethnicity. At T1, the T2D youth groups had similar age (13.9 yrs), diabetes duration (0.7 yrs), and sex (60% female). sRAGE concentrations were lower in T2D vs. controls (752.8±308.3 vs. 954.4 ± 356.7 pg/ml, p&amp;lt;0.0001) at T3. By T3 (mean duration 7 yrs), sRAGE levels decreased compared with T1 and T2 in G1 vs. G2 (p&amp;lt;0.05). sRAGE concentrations were 711.9±294.1 vs. 802.7±318.9 pg/ml, p=0.0032 in G1 vs. G2 at T3, with no significant difference by treatment. HbA1c was inversely related with sRAGE. Higher sRAGE concentrations were associated with a lower risk of hyperfiltration (HR=0.93, 95% CI 0.86-0.99, p=0.03) and inversely related to eGFR (p&amp;lt;0.001); no relationships were observed with UACR, PWV, or AI. sRAGE levels decline overtime in youth with T2D, are inversely related to glycemia, and may serve as a biomarker of kidney function. Disclosure F.Bacha: Other Relationship; Takeda Pharmaceutical Co., Ltd., AstraZeneca. E.M.Urbina: Advisory Panel; Astellas Pharma Inc., Other Relationship; Targus Medical, Inc. S.Gidding: Consultant; ESPERION Therapeutics, Inc. V.M.Monnier: None. L.El ghormli: None. K.Drews: None. B.H.Braffett: None. Funding National Institutes of Health (5U01DK061230-16)

12-OR: Urine Lactate Is a Disease Biomarker for Diabetic Kidney Disease

As lactate (LA) elevation is associated with mitochondrial dysfunction, we examined the role of LA in diabetic kidney disease (DKD) progression. Urine LA (ULA) was measured in patients with type 2 diabetes (T2D) in three independent cohort studies (HUNT3, SMART2D, and CRIC). ULA and plasma LA (PLA) were also measured in patients with type 1 diabetes (T1D) following eu- or hyperglycemic clamp, in mouse kidney sections, and sodium-glucose cotransporter-2 (SGLT2)-deficient mice. Mitochondrial functional changes in human kidney proximal tubule (HK2) cells were assayed in response to exogenous LA. Subjects in HUNT3 with DKD (n=39) had elevated ULA levels compared to healthy controls (n=53, p=0.023) (Fig. 1). In subjects with T2D from SMART2D (n=230) and CRIC (n=889), the third tertile of ULA/creatinine ratio was associated with a greater estimated glomerular filtration rate (eGFR) decline [-1.63 mL/min/1.73m2/year, p=0.007, and -0.63 mL/min/1.73m2, p=0.042], relative to the first tertile. Acute hyperglycemia stimulated PLA (p&amp;lt;0.0001) and ULA (p=0.001) in patients with T1D (n=39), and in kidney sections incubated with high glucose. Compared to wild-type, SGLT2-deficient mice had lower ULA levels. LA above 2.5 mM inhibited oxygen consumption rate in HK2 cells. Elevated ULA/creatinine ratio inhibits mitochondrial function in diabetes and identifies subjects at risk of rapid renal decline independent of chronic glycemic control. Disclosure L.Kugathasan: None. L.Natarajan: None. S.Lim: None. S.Waikar: None. Y.M.Osman: None. J.He: None. V.Vallon: Research Support; NIH - National Institutes of Health, Gilead Sciences, Inc., Merck Sharp &amp; Dohme Corp., Novo Nordisk, Maze Therapeutics, Boehringer-Ingelheim, Speaker's Bureau; AstraZeneca. S.Hallan: None. D.Cherney: Other Relationship; Boehringer Ingelheim-Lilly, Merck, AstraZeneca, Sanofi, Mitsubishi-Tanabe, Abbvie, Janssen, Bayer, Prometic, BMS, Maze, Gilead, CSL-Behring, Otsuka, Novartis, Youngene, Lexicon and Novo-Nordisk, Research Support; Boehringer Ingelheim-Lilly, Merck, Janssen, Sanofi, AstraZeneca, CSL-Behring and Novo-Nordisk. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc. Cric study investigators: n/a. M.Darshi: Employee; Janssen Research &amp; Development, LLC. V.Srinivasan sridhar: Other Relationship; Merck &amp; Co., Inc. V.Drel: None. J.Tumova: None. J.Liu: None. J.Wang: None. B.A.Perkins: Advisory Panel; Dexcom, Inc., Insulet Corporation, Novo Nordisk, Sanofi, Vertex Pharmaceuticals Incorporated, Other Relationship; Abbott, Medtronic, Sanofi, Research Support; Novo Nordisk, Bank of Montreal (BMO). Y.Lytvyn: None.

Inverse association between caffeine intake and albuminuria in US adults: an analysis of NHANES 2005-2016

ABSTRACT Objectives Albuminuria is a significant biomarker of various kidney diseases and is associated with renal outcome. Recently, caffeine intake has shown potential renoprotective effects. However, the relationship between caffeine intake and albuminuria remains profoundly elusive. Methods We conducted a cross-sectional study aimed to explore the association between caffeine intake and albuminuria in the American adult population using the data acquired from the National Health and Nutrition Examination Survey (NHANES) 2005–2016. Caffeine intake was assessed by 24-h dietary recalls, and albuminuria was assessed by albumin-to-creatinine ratio. Multivariate logistic regression was performed to explore the independent association between caffeine intake and albuminuria. Subgroup analysis and interaction tests were also conducted. Results Among 23,060 participants, 11.8% of the individuals exhibited albuminuria, and the prevalence of albuminuria decreased with higher caffeine intake tertiles (Tertile 1: 13%; Tertile 2: 11.9%; Tertile 3: 10.5%; P < 0.001). After adjusted potential confounders, the results of logistic regression indicated that a higher caffeine intake was associated with a decreased risk of albuminuria (OR = 0.903; 95% CI: 0.84, 0.97; P = 0.007), especially in females and the participants aged <60 years and chronic kidney disease stage II. Conclusion The present study first indicated an inverse correlation between caffeine intake and albuminuria, which further confirmed the potentially protective effects of caffeine on the kidney.

Copeptin in autosomal dominant polycystic kidney disease: real-world experiences from a large prospective cohort study.

The identification of new biomarkers in autosomal-dominant polycystic kidney disease (ADPKD) is crucial to improve and simplify prognostic assessment as a basis for patient selection for targeted therapies. Post hoc analyses of the TEMPO 3:4 study indicated that copeptin could be one of those biomarkers. Copeptin was tested in serum samples from patients of the AD(H)PKD study. Serum copeptin levels were measured using a time-resolved amplified cryptate emission (TRACE)-based assay. In total, we collected 711 values from 389 patients without tolvaptan treatment and a total of 243 values (of which 64 were pre-tolvaptan) from 94 patients on tolvaptan. These were associated with rapid progression and disease-causing gene variants and their predictive capacity tested and compared with the Mayo Classification. As expected, copeptin levels showed a significant negative correlation with estimated glomerular filtration rate (eGFR). Measurements on tolvaptan showed significantly higher copeptin levels (9.871pmol/L vs 23.90pmol/L at 90/30mg; P<.0001) in all chronic kidney disease stages. Linear regression models (n=133) show that copeptin is an independent predictor of eGFR slope. A clinical model (including eGFR, age, gender, copeptin) was nearly as good (R2=0.1196) as our optimal model (including height-adjusted total kidney volume, eGFR, copeptin, R2=0.1256). Adding copeptin to the Mayo model improved future eGFR estimation. Copeptin levels are associated with kidney function and independently explained future eGFR slopes. As expected, treatment with tolvaptan strongly increases copeptin levels.

An Overview of Major Clinical Predictive Factors and Prognostic Biomarkers of Diabetic Kidney Disease in Children and Adolescents

The onset and progression of diabetic nephropathy represent a significant issue in diabetic management as it is the primary microvascular consequence of both type 1 and type 2 diabetes mellitus and a significant contributor to end stage renal disease-related mortality. Major risk factors for nephropathy in children and adolescents include hyperglycemia, HbA1c, diabetes duration, gender, blood pressure, dyslipidemia, uric acid, family history and genetic factors, smoking, puberty, and obesity. Metabolism and hemodynamic variables interact on a complex basis during disease development. A series of intricate molecular events take place in response to hyperglycemia, which disturbs the body's metabolic environment and causes glomerular enlargement, tubular inflammation, mesangial expansion, oxidative stress, and renal fibrosis. Fortunately, the main approaches for preventing the beginning and reducing the progression of diabetic kidney damage are rigorous glucose control and antihypertensive medications. As children and adolescents with T1D are at risk for developing early diabetic nephropathy, patients with T1D must have the best metabolic control, an early diagnosis, and timely treatment of dyslipidemia and hypertension. Prospects for better diabetic nephropathy outcomes are improving as novel approaches are developed. Novel biomarkers are increasingly proven to be more reliable instruments than the traditional microalbuminuria, which can forecast the development of disease. In addition to glomerular and tubular indicators, inflammation and oxidative stress markers have proven to be reliable diagnostic aids. In order to emphasize the methods being employed lately to enhance therapeutic approaches in diabetic nephropathy, certain emerging critical biomarkers are illustrated in this review.

Elevated baseline adiponectin level predicting an increased risk of disease activity in idiopathic nephrotic syndrome and chronic kidney disease in children

Adiponectin, an adipocyte-derived protein, is present abundantly in circulation and has anti-atherogenic and anti-inflammatory effects, so we aimed to assess the role of adiponectin in idiopathic nephrotic syndrome and chronic kidney disease in children. Overall of 290 children, 95 patients with the steroid-responsive idiopathic nephrotic syndrome (50 in remission and 45 in relapse). Another 95 patients with chronic kidney disease (50 on hemodialysis and 45 on conservative therapies) and 100 apparently healthy matched children were enrolled into the study. Serum adiponectin levels, blood chemistry (protein/albumin, serum creatinine, blood urea and electrolytes levels) and 24-hour proteinuria w studied as well. There was highly significant increasing differences in adiponectin level between the relapsed idiopathic nephrotic syndrome (26.93±6.79 µg/mL) compared to remission (10.96±3.33 µg/mL) and control group (4.89±1.01 µg/mL) and between remission in comparing to control group (P<0.001). Also there was significant negative correlation between adiponectin level and serum albumin level in the relapse group (r=-0.60, P≤0.05), and highly positive correlation between adiponectin level and 24-hour proteinuria in relapse (r=0.98, P≤0.001) and remission group (r=0.92, P≤0.001). Regarding children with chronic kidney disease, There were high significant increasing differences in adiponectin levels in conservative (13.88±4.27 µg/mL) and dialysis (15.09±6.14 µg/mL) groups compared to controls (6.05±5.83 µg/mL) with P<0.001. Furthermore, there was a significant positive correlation between adiponectin and serum creatinine and blood urea levels in both conservative and dialysis groups with P<0.05. Adiponectin can be considered as an important useful biomarker for chronic kidney diseases in children.

Urine Metabolomic Signature of People Diagnosed with Balkan Endemic Nephropathy and Other Types of Chronic Kidney Disease Compared with Healthy Subjects in Romania

Metabolomic analysis methods were employed to determine biomarkers for various chronic kidney diseases (CKDs). Modern analytical methods were developed and applied successfully to find a specific metabolomic profile in urine samples from CKD and Balkan endemic nephropathy (BEN) patients. The aim was to explore a specific metabolomic profile defined by feasible/easy-to-identify molecular markers. Urine samples were collected from patients with CKDs and BEN, and from healthy subjects from endemic and nonendemic areas in Romania. Metabolomic analysis of urine samples, extracted by the liquid-liquid extraction (LLE) method, was performed by gas chromatography-mass spectrometry (GC-MS). The statistical exploration of the results was performed through a principal component analysis (PCA) evaluation. Urine samples were statistically analyzed using a classification based on six types of metabolites. Most urinary metabolites are distributed in the center of a loading plot, meaning that these compounds do not represent significant markers for BEN. One of the most frequent and higher-concentration urinary metabolites in BEN patients was p-Cresol, a phenolic compound that implies a severe injury of the renal filtration function. The presence of p-Cresol was associated with protein-bound uremic toxins, which have specific functional groups such as indole and phenyl. In prospective studies for future investigation, prevention, and disease treatment, we suggest a larger sample size, sample extraction using other methods, and analysis using other chromatography techniques coupled with mass spectrometry, which can generate a more significant data set for statistical analysis.

Genome-wide mRNA profiling in urinary extracellular vesicles reveals stress gene signature for diabetic kidney disease

Urinary extracellular vesicles (uEV) are a largely unexplored source of kidney-derived mRNAs with potential to serve as a liquid kidney biopsy. We assessed ∼200 uEV mRNA samples from clinical studies by genome-wide sequencing to discover mechanisms and candidate biomarkers of diabetic kidney disease (DKD) in Type 1 diabetes (T1D) with replication in Type 1 and 2 diabetes. Sequencing reproducibly showed >10,000 mRNAs with similarity to kidney transcriptome. T1D DKD groups showed 13 upregulated genes prevalently expressed in proximal tubules, correlated with hyperglycemia and involved in cellular/oxidative stress homeostasis. We used six of them (GPX3, NOX4, MSRB, MSRA, HRSP12, and CRYAB) to construct a transcriptional "stress score" that reflected long-term decline of kidney function and could even identify normoalbuminuric individuals showing early decline. We thus provide workflow and web resource for studying uEV transcriptomes in clinical urine samples and stress-linked DKD markers as potential early non-invasive biomarkers or drug targets.

Electrodeposited copper nanoparticles for creatinine detection via the in situ formation of copper-creatinine complexes.

Creatinine is an important biomarker of kidney diseases. In this work, a fast and facile electrochemical sensor was developed for creatinine detection based on the use of copper nanoparticle-modified screen-printed electrodes. The copper electrodes were prepared by simple electrodeposition of Cu2+ (aq). The electrochemically inactive creatinine was detected reductively via the in situ formation of copper-creatinine complexes. Two linear detection ranges, 0.28-3.0mM and 3.0-20.0mM, were achieved using differential pulse voltammetry, with the sensitivities of 0.824 ± 0.053 μA mM-1 and 0.132 ± 0.003 μA mM-1, respectively. The limit of detection was determined to be 0.084mM. The sensor was validated in synthetic urine samples to yield 99.3% recovery (%RSD = 2.8), demonstrating high tolerance to possible interfering species. Finally, the stability of creatinine and its degradation kinetics at different temperatures were evaluated using our developed sensor. The loss of creatinine was found to be a first-order reaction with the activation energy of 64.7kJmol-1.

Unbiased Human Kidney Tissue Proteomics Identifies Matrix Metalloproteinase 7 as a Kidney Disease Biomarker.

Although gene expression changes have been characterized in human diabetic kidney disease (DKD), unbiased tissue proteomics information for this condition is lacking. The authors conducted an unbiased aptamer-based proteomic analysis of samples from patients with DKD and healthy controls, identifying proteins with levels that associate with kidney function (eGFR) or fibrosis, after adjusting for key covariates. Overall, tissue gene expression only modestly correlated with tissue protein levels. Kidney protein and RNA levels of matrix metalloproteinase 7 (MMP7) strongly correlated with fibrosis and with eGFR. Single-cell RNA sequencing indicated that kidney tubule cells are an important source of MMP7. Furthermore, plasma MMP7 levels predicted future kidney function decline. These findings identify kidney tissue MMP7 as a biomarker of fibrosis and blood MMP7 as a biomarker for future kidney function decline. Diabetic kidney disease (DKD) is responsible for close to half of all ESKD cases. Although unbiased gene expression changes have been extensively characterized in human kidney tissue samples, unbiased protein-level information is not available. We collected human kidney samples from 23 individuals with DKD and ten healthy controls, gathered associated clinical and demographics information, and implemented histologic analysis. We performed unbiased proteomics using the SomaScan platform and quantified the level of 1305 proteins and analyzed gene expression levels by bulk RNA and single-cell RNA sequencing (scRNA-seq). We validated protein levels in a separate cohort of kidney tissue samples as well as in 11,030 blood samples. Globally, human kidney transcript and protein levels showed only modest correlation. Our analysis identified 14 proteins with kidney tissue levels that correlated with eGFR and found that the levels of 152 proteins correlated with interstitial fibrosis. Of the identified proteins, matrix metalloprotease 7 (MMP7) showed the strongest association with both fibrosis and eGFR. The correlation between tissue MMP7 protein expression and kidney function was validated in external datasets. The levels of MMP7 RNA correlated with fibrosis in the primary and validation datasets. Findings from scRNA-seq pointed to proximal tubules, connecting tubules, and principal cells as likely cellular sources of increased tissue MMP7 expression. Furthermore, plasma MMP7 levels correlated not only with kidney function but also associated with prospective kidney function decline. Our findings, which underscore the value of human kidney tissue proteomics analysis, identify kidney tissue MMP7 as a diagnostic marker of kidney fibrosis and blood MMP7 as a biomarker for future kidney function decline.

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.

Bioenergetics: the evolutionary basis of progressive kidney disease.

Chronic kidney disease (CKD) affects >10% of the world population, with increasing prevalence in middle age. The risk for CKD is dependent on the number of functioning nephrons through the life cycle, and 50% of nephrons are lost through normal aging, revealing their vulnerability to internal and external stressors. Factors responsible for CKD remain poorly understood, with limited availability of biomarkers or effective therapy to slow progression. This review draws on the disciplines of evolutionary medicine and bioenergetics to account for the heterogeneous nephron injury that characterizes progressive CKD following episodes of acute kidney injury with incomplete recovery. The evolution of symbiosis in eukaryotes led to the efficiencies of oxidative phosphorylation and the rise of metazoa. Adaptations to ancestral environments are the products of natural selection that have shaped the mammalian nephron with its vulnerabilities to ischemic, hypoxic, and toxic injury. Reproductive fitness rather than longevity has served as the driver of evolution, constrained by available energy and its allocation to homeostatic responses through the life cycle. Metabolic plasticity has evolved in parallel with robustness necessary to preserve complex developmental programs, and adaptations that optimize survival through reproductive years can become maladaptive with aging, reflecting antagonistic pleiotropy. Consequently, environmental stresses promote trade-offs and mismatches that result in cell fate decisions that ultimately lead to nephron loss. Elucidation of the bioenergetic adaptations by the nephron to ancestral and contemporary environments may lead to the development of new biomarkers of kidney disease and new therapies to reduce the global burden of progressive CKD.