Isocitrate dehydrogenase 1 upregulation in urinary extracellular vesicles from proximal tubules of type 2 diabetic rats.

Diabetic nephropathy (DN) is a major cause of chronic kidney disease. Microalbuminuria is currently the most common non-invasive biomarker for the early diagnosis of DN. However, renal structural damage may have advanced when albuminuria is detected. In this study, we sought biomarkers for early DN diagnosis through proteomic analysis of urinary extracellular vesicles (uEVs) from type 2 diabetic model rats and normal controls. Isocitrate dehydrogenase 1 (IDH1) was significantly increased in uEVs from diabetic model rats at the early stage despite minimal differences in albuminuria between the groups. Calorie restriction significantly suppressed the increase in IDH1 in uEVs and 24-hour urinary albumin excretion, suggesting that the increase in IDH1 in uEVs was associated with the progression of DN. Additionally, we investigated the origin of IDH1-containing uEVs based on their surface sugar chains. Lectin affinity enrichment and immunohistochemical staining showed that IDH1-containing uEVs were derived from proximal tubules. These findings suggest that the increase in IDH1 in uEVs reflects pathophysiological alterations in the proximal tubules and that IDH1 in uEVs may serve as a potential biomarker of DN in the proximal tubules.

Urinary CD4 + T Cells Predict Renal Relapse in ANCA-Associated Vasculitis.

SIGNIFICANCE STATEMENT: Early identification of patients at risk of renal flares in ANCA vasculitis is crucial. However, current clinical parameters have limitations in predicting renal relapse accurately. This study investigated the use of urinary CD4 + T lymphocytes as a predictive biomarker for renal flares in ANCA vasculitis. This study, including urine samples from 102 patients, found that the presence of urinary CD4 + T cells was a robust predictor of renal relapse within a 6-month time frame, with a sensitivity of 60% and a specificity of 97.8%. The diagnostic accuracy of urinary CD4 + T cells exceeded that of ANCA titers, proteinuria, and hematuria. Monitoring urinary CD4 + T lymphocytes could help assess the risk of future renal relapse, enabling early preventive measures and tailored treatment strategies. BACKGROUND: In ANCA-associated vasculitis, there is a lack of biomarkers for predicting renal relapse. Urinary T cells have been shown to differentiate active GN from remission in ANCA-associated vasculitis, but their predictive value for renal flares remains unknown. METHODS: The PRE-FLARED study was a prospective multicenter biomarker study including 102 individuals with ANCA-associated vasculitis in remission aimed to predict renal relapse by quantifying urinary CD4 + T-cell subsets using flow cytometry at baseline and monitoring clinical outcomes over a 6-month follow-up. RESULTS: Among the participants, ten experienced renal relapses, two had non-renal flares, and 90 remained in stable remission. The median baseline urinary CD4 + T-cell count was significantly higher in patients who relapsed compared with those in remission. Receiver operating characteristic curve analysis of urinary CD4 + T-cell counts showed an area under the curve value of 0.88 for predicting renal flares, outperforming ANCA titers, hematuria, and proteinuria. Using a cutoff of 490 CD4 + T cells per 100 ml urine, the sensitivity and specificity in identifying patients with future renal flares were 60% and 97.8%, respectively. In a post hoc analysis, combining urinary CD4 + T-cell counts with proteinase-3 ANCA levels suggested improved predictive performance in the PR3 + subgroup. In addition, the number of urinary CD4 + T cells showed a limited correlation with a decline in GFR and an increase in proteinuria over the follow-up period. CONCLUSIONS: This study concluded that urinary CD4 + T-cell counts could identify patients with ANCA-associated vasculitis at a substantial risk of renal relapse within 6 months. Combining these counts with ANCA levels further improved the prediction of relapse. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Urinary T Lymphocytes Predict Renal Flares in Patients With Inactive ANCA-associated Glomerulonephritis (PRE-FLARED), NCT04428398 .

Ultrasensitive CCL2 Detection in Urine for Diabetic Nephropathy Diagnosis Using a WS2-Based Plasmonic Biosensor.

The accurate diagnosis of diabetic nephropathy relies on achieving ultrasensitive biosensing for biomarker detection. However, existing biosensors face challenges such as poor sensitivity, complexity, time-consuming procedures, and high assay costs. To address these limitations, we report a WS2-based plasmonic biosensor for the ultrasensitive detection of biomarker candidates in clinical human urine samples associated with diabetic nephropathy. Leveraging plasmonic-based electrochemical impedance microscopy (P-EIM) imaging, we observed a remarkable charge sensitivity in monolayer WS2 single crystals. Our biosensor exhibits an exceptionally low detection limit (0.201 ag/mL) and remarkable selectivity in detecting CC chemokine ligand 2 (CCL2) protein biomarkers, outperforming conventional techniques such as ELISA. This work represents a breakthrough in traditional protein sensors, providing a direction and materials foundation for developing ultrasensitive sensors tailored to clinical applications for biomarker sensing.

Proteomics of urinary small extracellular vesicles in early diagnosis of kidney diseases in children-expectations and limitations.

The primary function of the kidneys is to maintain systemic homeostasis (disruption of renal structure and function results in multilevel impairment of body function). Kidney diseases are characterized by a chronic, progressive course and may result in the development of chronic kidney disease (CKD). Evaluation of the composition of the proteome of urinary small extracellular vesicles (sEVs) as a so-called liquid biopsy is a promising new research direction. Knowing the composition of sEV could allow localization of cellular changes in specific sections of the nephron or the interstitial tissue before fixed changes, detectable only at an advanced stage of the disease, occur. Research is currently underway on the role of sEVs in the diagnosis and monitoring of many disease entities. Reports in the literature on the subject include: diabetic nephropathy, focal glomerulosclerosis in the course of glomerulopathies, renal fibrosis of various etiologies. Studies on pediatric patients are still few, involving piloting if small groups of patients without validation studies. Here, we review the literature addressing the use of sEV for diagnosis of the most common urinary disorders in children. We evaluate the clinical utility and define limitations of markers present in sEV as potential liquid biopsy.

Comparative Analysis of Protein Quantification by the SomaScan Assay versus Orthogonal Methods in Urine from People with Diabetic Kidney Disease.

To our knowledge, calibration curves or other validations for thousands of SomaScan aptamers are not publicly available. Moreover, the abundance of urine proteins obtained from these assays is not routinely validated with orthogonal methods (OMs). We report an in-depth comparison of SomaScan readout for 23 proteins in urine samples from patients with diabetic kidney disease (n = 118) vs OMs, including liquid chromatography-targeted mass spectrometry (LC-MS), ELISA, and nephelometry. Pearson correlation between urine abundance of the 23 proteins from SomaScan 3.2 vs OMs ranged from -0.58 to 0.86, with a median (interquartile ratio, [IQR]) of 0.49 (0.18, 0.53). In multivariable linear regression, the SomaScan readout for 6 of the 23 examined proteins (26%) was most strongly associated with the OM-derived abundance of the same (target) protein. For 3 of 23 (13%), the SomaScan and OM-derived abundance of each protein were significantly associated, but the SomaScan readout was more strongly associated with OM-derived abundance of one or more "off-target" proteins. For the remaining 14 proteins (61%), the SomaScan readouts were not significantly associated with the OM-derived abundance of the targeted proteins. In 6 of the latest group, the SomaScan readout was not associated with urine abundance of any of the 23 quantified proteins. To sum, over half of the SomaScan results could not be confirmed by independent orthogonal methods.

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, this study collected urine from 87 patients with type 2 diabetes mellitus (which will be classified into normal albuminuria, microalbuminuria, and macroalbuminuria groups) and 38 healthy subjects. Twelve individuals from each group were then randomly selected as the screening cohort for proteomics analysis and the rest as the validation cohort. The results showed that humoral immune response, complement activation, complement and coagulation cascades, renin-angiotensin system, and cell adhesion molecules were closely related to the progression of DN. Five overlapping proteins (KLK1, CSPG4, PLAU, SERPINA3, and ALB) were identified as potential biomarkers by machine learning methods. Among them, KLK1 and CSPG4 were positively correlated with the urinary albumin to creatinine ratio (UACR), and SERPINA3 was negatively correlated with the UACR, which were validated by enzyme-linked immunosorbent assay (ELISA). This study provides new insights into disease mechanisms and biomarkers for early diagnosis of DN.

Acute high-dose MitoQ does not increase urinary kidney injury markers in healthy adults: a randomized crossover trial.

Several human studies have used the mitochondrial antioxidant MitoQ. Recent in vitro data indicating that MitoQ may induce nephrotoxicity caused concern regarding the safety of MitoQ on the kidneys, but the doses were supraphysiological. Therefore, we sought to determine whether acute MitoQ elicits changes in urinary biomarkers associated with tubular injury in healthy adults with our hypothesis being there would be no changes. Using a randomized crossover design, 32 healthy adults (16 females and 16 males, 29 ± 11 yr old) consumed MitoQ (100-160 mg based on body mass) or placebo capsules. We obtained serum samples and a 4- to 6-h postcapsule consumption urine sample. We assessed creatinine clearance and urine kidney injury biomarkers including the chitinase 3-like-1 gene product YKL-40, kidney-injury marker-1, monocyte chemoattractant protein-1, epidermal growth factor, neutrophil gelatinase-associated lipocalin, interleukin-18, and uromodulin using multiplex assays. We used t tests, Wilcoxon tests, and Hotelling's T2 to assess global differences in urinary kidney injury markers between conditions. Acute MitoQ supplementation did not influence urine flow rate (P = 0.086, rrb = 0.39), creatinine clearance (P = 0.085, rrb = 0.42), or urinary kidney injury markers (T22,8 = 30.6, P = 0.121, univariate ps > 0.064). Using exploratory univariate analysis, MitoQ did not alter individual injury markers compared with placebo (e.g., placebo vs. MitoQ: YKL-40, 507 ± 241 vs. 442 ± 236 pg/min, P = 0.241; kidney injury molecule-1, 84.1 ± 43.2 vs. 76.2 ± 51.2 pg/min, P = 0.890; and neutrophil gelatinase-associated lipocalin, 10.8 ± 10.1 vs. 9.83 ± 8.06 ng/min, P = 0.609). In conclusion, although longer-term surveillance and data are needed in clinical populations, our findings suggest that acute high-dose MitoQ had no effect on urinary kidney injury markers in healthy adults.NEW & NOTEWORTHY We found acute high-dose mitochondria-targeted antioxidant (MitoQ) supplementation was not nephrotoxic and had no effect on markers of acute kidney injury in healthy adults. These findings can help bolster further confidence in the safety of MitoQ, particularly for future investigations seeking to examine the role of mitochondrial oxidative stress, via acute MitoQ supplementation, on various physiological outcomes.

Sex-disaggregated analysis of acute kidney injury in hospitalized children with sickle cell anemia in Uganda.

A growing body of research is categorizing sex differences in both sickle cell anemia (SCA) and acute kidney injury (AKI); however, most of this work is being conducted in high-resource settings. Here, we evaluated risk factors and clinical parameters associated with AKI and AKI severity, stratified by sex, in a cohort of children hospitalized with SCA and vaso-occlusive pain crisis (VOC). The purpose of this study was to explore sex disparities in a high-risk, vulnerable population. This study was a secondary analysis of data collected from a cohort of Ugandan children between 2 and 18 yr of age prospectively enrolled. A total of 185 children were enrolled in the primary study; 41.6% were female and 58.4% were male, with a median age of 8.9 yr. Incident or worsening AKI (P = 0.026) occurred more frequently in female compared with male children, despite no differences in AKI on admission. Female children also had altered markers of renal function including higher creatinine levels at admission (P = 0.03), higher peak creatinine (P = 0.006), and higher urine neutrophil gelatinase-associated lipocalin (NGAL) at admission (P = 0.003) compared with male children. Female children had elevated total (P = 0.045) and conjugated bilirubin at admission (P = 0.02) compared with male children and higher rates of hematuria at admission (P = 0.004). Here, we report sex differences in AKI in children with SCA and VOC, including increased incidence and worsening of AKI in female pediatric patients, in association with an increase in biological indicators of poor renal function including creatinine, estimated glomerular filtration rate, and NGAL.NEW & NOTEWORTHY In this study, we report an increased risk of developing acute kidney injury (AKI) during hospitalization, worsening AKI, and death among females with sickle cell anemia (SCA) hospitalized with an acute pain crisis compared with males. The sex differences in AKI were not explained by socioeconomic differences, severity of pain, or disease severity among females compared with males. Together, these data suggest that female children with SCA may be at increased risk of AKI.

Prognostic implications of unbiased molecular categorization in kidney disease.

In this commentary, a novel approach to the reclassification of chronic kidney disease is reviewed. In the revisited study, the investigators identify 4 distinct subtypes of kidney disease derived from an unbiased self-organizing map of transcriptomic data from kidney biopsy samples. These molecular subtypes then are characterized by biologic cell processes, clinical and histopathologic features, urinary proteomics, and disease progression. The strengths and limitations of the self-organizing map approach are assessed; the prognostic, diagnostic, and therapeutic implications are considered briefly.

Development and Evaluation of a Noninvasive Microfluidic-Based Paper Analytical Device for Leptospirosis Diagnosis.

Leptospirosis is a re-emerging infectious disease that presents a diagnostic enigma for clinicians with frequent misdiagnosis due to lack of rapid and accurate diagnostic tests, as the current methods are encumbered by inherent limitations. The development of a diagnostic sensor with a sample-in-result-out capability is pivotal for prompt diagnosis. Herein, we developed a microfluidic paper-based analytical device (spin-µPAD) featuring a sample-in-result-out fashion for the detection of Leptospira specific urinary biomarker, sph2 sphingomyelinase, crucial for noninvasive point-of-care testing. Fabrication of paper devices involved precise photolithography techniques, ensuring a high degree of reproducibility and replicability. By optimizing the device's configuration and protein components, a remarkable sensitivity and specificity was achieved for detecting leptospiral sph2 in urine, even at low concentrations down to 1.5 fg/mL, with an assay time of 15 min. Further, the spin-µPAD was validated with 20 clinical samples, suspected of leptospirosis including other febrile illnesses, and compared with gold standard microscopic agglutination test, culture, Lepto IgM ELISA, darkfield microscopy, and Leptocheck WB spot test. In contrast to commercial diagnostic tools, the spin-µPAD was noninvasive, rapid, easy to use, specific, sensitive, and cost-effective. The results highlight the potential of this innovative spin-µPAD for an efficient and dependable approach to noninvasive leptospirosis diagnosis, addressing critical needs in the realms of public health and clinical settings.

Upconversion Nanoparticle-Based Dot-Blot Immunoassay for Quantitative Biomarker Detection.

Dot-blot immunoassays are widely used for the user-friendly detection of clinical biomarkers. However, the majority of dot-blot assays have only limited sensitivity and are only used for qualitative or semiquantitative analysis. To overcome this limitation, we have employed labels based on photon-upconversion nanoparticles (UCNPs) that exhibit anti-Stokes luminescence and can be detected without optical background interference. First, the dot-blot immunoassay on a nitrocellulose membrane was optimized for the quantitative analysis of human serum albumin (HSA), resulting in a limit of detection (LOD) of 0.19 ng/mL and a signal-to-background ratio (S/B) of 722. Commercial quantum dots were used as a reference label, reaching the LOD of 4.32 ng/mL and the S/B of 3, clearly indicating the advantages of UCNPs. In addition, the potential of UCNP-based dot-blot for real sample analysis was confirmed by analyzing spiked urine samples, reaching the LOD of 0.24 ng/mL and recovery rates from 79 to 123%. Furthermore, we demonstrated the versatility and robustness of the assay by adapting it to the detection of two other clinically relevant biomarkers, prostate-specific antigen (PSA) and cardiac troponin (cTn), reaching the LODs in spiked serum of 9.4 pg/mL and 0.62 ng/mL for PSA and cTn, respectively. Finally, clinical samples of patients examined for prostate cancer were analyzed, achieving a strong correlation with the reference electrochemiluminescence immunoassay (recovery rates from 89 to 117%). The achieved results demonstrate that UCNPs are highly sensitive labels that enable the development of dot-blot immunoassays for quantitative analysis of low-abundance biomarkers.

Proteomics approach to discovering non-invasive diagnostic biomarkers and understanding the pathogenesis of endometriosis: a systematic review and meta-analysis.

BACKGROUND: Endometriosis is one of the most common gynaecological diseases, yet it lacks efficient biomarkers for early detection and unravels disease mechanisms. Proteomic profiling has revealed diverse patterns of protein changes in various clinical samples. Integrating and systematically analysing proteomics data can facilitate the development of biomarkers, expediting diagnosis and providing insights for potential clinical and therapeutic applications. Hence, this systematic review and meta-analysis aimed to explore potential non-invasive diagnostic biomarkers in various biological samples and therapeutic targets for endometriosis. METHODS: Online databases, including Scopus, PubMed, Web of Science, MEDLINE, Embase via Ovid, and Google Scholar, were searched using MeSH terms. Two independent authors screened the articles, extracted the data, and assessed the methodological quality of the included studies. GO and KEGG analyses were performed to identify the pathways that were significantly enriched. Protein­protein interaction and hub gene selection analyses were also conducted to identify biomarker networks for endometriosis. RESULTS: Twenty-six observational studies with a total of 2,486 participants were included. A total of 644 differentially expressed proteins (180 upregulated and 464 downregulated) were identified from 9 studies. Proteins in peripheral blood exhibited a sensitivity and specificity of 38-100% and 59-99%, respectively, for detecting endometriosis, while proteins in urine had a sensitivity of 58-91% and specificity of 76-93%. Alpha-1-antitrypsin, albumin, and vitamin D binding proteins were significantly DEPs in both serum and urine. Complement C3 is commonly expressed in serum, menstrual blood, and cervical mucus. Additionally, S100-A8 is commonly expressed in both menstrual blood and cervical mucus. Haptoglobin is commonly detected in both serum and plasma, whereas cathepsin G is found in urine, serum, and plasma. GO and KEGG enrichment analyses revealed that proteoglycans in cancer pathways, which regulate cell-to-cell interactions, modulate the extracellular matrix, and promote the proliferation and invasion of endometrial cells, are commonly enriched in serum and urine. CONCLUSION: This comprehensive study revealed potential proteomes that were significantly differentially expressed in women with endometriosis utilizing various non-invasive clinical samples. Exploring common differentially expressed proteins in various biological samples provides insights into the diagnosis and pathophysiology of endometriosis, as well as potential clinical and therapeutic applications.

Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry Analysis of Urinary Oligosaccharides and Glycoamino Acids for the Diagnosis of Mucopolysaccharidosis and Glycoproteinosis.

BACKGROUND: Mucopolysaccharidosis (MPS) and glycoproteinosis are 2 groups of heterogenous lysosomal storage disorders (LSDs) caused by defective degradation of glycosaminoglycans (GAGs) and glycoproteins, respectively. Oligosaccharides and glycoamino acids have been recognized as biomarkers for MPS and glycoproteinosis. Given that both groups of LSDs have overlapping clinical features, a multiplexed assay capable of unambiguous subtyping is desired for accurate diagnosis, and potentially for severity stratification and treatment monitoring. METHODS: Urinary oligosaccharides were derivatized with 3-methyl-1-phenyl-2-pyrazoline-5-one (PMP) and analyzed by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) together with the underivatized glycoamino acids. Novel biomarkers were identified with a semi-targeted approach with precursor mass scanning, the fragmentation pattern (if applicable), and the biochemical basis of the condition. RESULTS: A UPLC-MS/MS analysis with improved chromatographic separation was developed. Novel biomarkers for MPS-IIIA, IIIB, IIIC, and VII were identified and validated. A total of 28 oligosaccharides, 2 glycoamino acids, and 2 ratios were selected as key diagnostic biomarkers. Validation studies including linearity, lower limit of quantitation (LLOQ), and precision were carried out with the assay performance meeting the required criteria. Age-specific reference ranges were collected. In the 76 untreated patients, unambiguous diagnosis was achieved with 100% sensitivity and specificity. Additionally, the levels of disease-specific biomarkers were substantially reduced in the treated patients. CONCLUSIONS: A multiplexed UPLC-MS/MS assay for urinary oligosaccharides and glycoamino acids measurement was developed and validated. The assay is suitable for the accurate diagnosis and subtyping of MPS and glycoproteinosis, and potentially for severity stratification and monitoring response to treatment.

Automated Urinary Chemokine Assays for Noninvasive Detection of Kidney Transplant Rejection: A Prospective Cohort Study.

RATIONALE & OBJECTIVE: Prior studies have demonstrated the diagnostic potential of urinary chemokines C-X-C motif ligand 9 (CXCL9) and CXCL10 for kidney transplant rejection. However, their benefit in addition to clinical information has not been demonstrated. We evaluated the diagnostic performance for detecting acute rejection of urinary CXCL9 and CXCL10 when integrated with clinical information. STUDY DESIGN: Single-center prospective cohort study. SETTING & PARTICIPANTS: We analyzed 1,559 biopsy-paired urinary samples from 622 kidney transplants performed between April 2013 and July 2019 at a single transplant center in Belgium. External validation was performed in 986 biopsy-paired urinary samples. TESTS COMPARED: We quantified urinary CXCL9 (uCXCL9) and CXCL10 (uCXCL10) using an automated immunoassay platform and normalized the values to urinary creatinine. Urinary chemokines were incorporated into a multivariable model with routine clinical markers (estimated glomerular filtration rate, donor-specific antibodies, and polyoma viremia) (integrated model). This model was then compared with the tissue diagnosis according to the Banff classification for acute rejection. OUTCOME: Acute rejection detected on kidney biopsy using the Banff classification. RESULTS: Chemokines integrated with routine clinical markers had high diagnostic value for detection of acute rejection (n=150) (receiver operating characteristic area under the curve 81.3% [95% CI, 77.6-85.0]). The integrated model would help avoid 59 protocol biopsies per 100 patients when the risk for rejection is predicted to be below 10%. The performance of the integrated model was similar in the external validation cohort. LIMITATIONS: The cross-sectional nature obviates investigating the evolution over time and prediction of future rejection. CONCLUSIONS: The use of an integrated model of urinary chemokines and clinical markers for noninvasive monitoring of rejection could enable a reduction in the number of biopsies. Urinary chemokines may be useful noninvasive biomarkers whose use should be further studied in prospective randomized trials to clarify their role in guiding clinical care and the use of biopsies to detect rejection after kidney transplantation. PLAIN-LANGUAGE SUMMARY: Urinary chemokines CXCL9 and CXCL10 have been suggested to be good noninvasive biomarkers of kidney transplant rejection. However, defining a context of use and integration with clinical information is necessary before clinical implementation can begin. In this study, we demonstrated that urinary chemokines CXCL9 and CXCL10, together with clinical information, have substantial diagnostic accuracy for the detection of acute kidney transplant rejection. Application of urinary chemokines together with clinical information may guide biopsy practices following kidney transplantation and potentially reduce the need for kidney transplant biopsies.

Association Between Urinary Biomarkers and CKD in Extremely Low Gestational Age Neonates.

RATIONALE & OBJECTIVE: Children born before 28 weeks' gestation are at increased risk of chronic kidney disease (CKD). Urine biomarkers may shed light on mechanistic pathways and improve the ability to forecast CKD. We evaluated whether urinary biomarkers in neonates of low gestational age (GA) are associated with a reduced estimated glomerular filtration rate (eGFR) over time. STUDY DESIGN: A cohort study of neonates with an exploratory case-control study of a subset of the cohort. SETTING & PARTICIPANTS: 327 neonates born at 24-27 weeks' gestation with 2-year eGFR data from the PENUT (Preterm Erythropoietin Neuroprotection Trial) and the REPaIReD (Recombinant Erythropoietin for Prevention of Infant Renal Disease) study. EXPOSURES: 11 urinary biomarkers measured at 27, 30, and 34 weeks' postmenstrual age for the primary cohort study and 10 additional biomarkers for the exploratory case-control study. OUTCOMES: eGFR<90mL/min/1.73m2 at 2 years corrected for GA. ANALYTICAL APPROACH: Linear mixed models to assess differences in biomarker values between neonates in whom CKD did and did not develop, accounting for multiple comparisons using Bonferroni-Holm correction in the cohort study only. Cohort analyses were adjusted for sex, GA, and body mass index. Cases were matched to controls on these variables in the case-control study. RESULTS: After adjusting for weeks of GA, urinary levels of α-glutathione-S-transferase (log difference, 0.27; 95% CI, 0.12-0.43), albumin (log difference, 0.13; 95% CI, 0.02-0.25), and cystatin C (log difference, 0.19; 95% CI, 0.04-0.34) were higher in those in whom CKD developed than in those in whom it did not. Urinary albumin and cystatin C levels did not remain significantly different after Bonferroni-Holm correction. In the exploratory case-control analysis, there were no differences in any biomarkers between cases and controls. LIMITATIONS: Early deaths and a high number of subjects without eGFR at 2 years corrected for GA. CONCLUSIONS: Measurement of urinary biomarkers may assist in monitoring neonates who are at risk for CKD. Additional studies are needed to confirm these findings. FUNDING: Grants from government (National Institutes of Health). TRIAL REGISTRATION: Registered at ClinicalTrials.gov with study number NCT01378273. PLAIN-LANGUAGE SUMMARY: Approximately 15 million neonates worldwide are born prematurely, and 2 million are born before 28 weeks' gestation. Many of these children go on to experience chronic kidney disease. Urine biomarkers may allow for early recognition of those at risk for the development of kidney disease. In this study of more than 300 children born before 28 weeks' gestational age, we found higher mean urinary levels of α-glutathione-S-transferase at 27, 30, and 34 weeks in children whose estimated glomerular filtration rate was<90mL/min/1.73m2 at 2 years compared with children whose estimated glomerular filtration rate was>90mL/min/1.73m2 at 2 years. Measurement of urinary biomarkers may assist in monitoring neonates who are at risk for chronic kidney disease. Additional studies are needed to confirm our findings.

Urinary Biomarkers and Kidney Injury in VA NEPHRON-D: Phenotyping Acute Kidney Injury in Clinical Trials.

RATIONALE & OBJECTIVE: Urinary biomarkers of injury, inflammation, and repair may help phenotype acute kidney injury (AKI) observed in clinical trials. We evaluated the differences in biomarkers between participants randomized to monotherapy or to combination renin-angiotensin-aldosterone system (RAAS) blockade in VA NEPHRON-D, where an increased proportion of observed AKI was acknowledged in the combination arm. STUDY DESIGN: Longitudinal analysis. SETTING & PARTICIPANTS: A substudy of the VA NEPHRON-D trial. PREDICTOR: Primary exposure was the treatment arm (combination [RAAS inhibitor] vs monotherapy). AKI is used as a stratifying variable. OUTCOME: Urinary biomarkers, including albumin, EGF (epidermal growth factor), MCP-1 (monocyte chemoattractant protein-1), YKL-40 (chitinase 3-like protein 1), and KIM-1 (kidney injury molecule-1). ANALYTICAL APPROACH: Biomarkers measured at baseline and at 12 months in trial participants were compared between treatment groups and by AKI. AKI events occurring during hospitalization were predefined safety end points in the original trial. The results were included in a meta-analysis with other large chronic kidney disease trials to assess global trends in biomarker changes. RESULTS: In 707 participants followed for a median of 2.2 years, AKI incidence was higher in the combination (20.7%) versus the monotherapy group (12.7%; relative risk [RR], 1.64 [95% CI, 1.16-2.30]). Compared with the monotherapy arm, in the combination arm the urine biomarkers at 12 months were either unchanged (MCP-1: RR, -3% [95% CI, -13% to 9%], Padj=0.8; KIM-1: RR, -10% [95% CI, -20% to 1%], Padj=0.2; EGF, RR-7% [95% CI, -12% to-1%], Padj=0.08) or lower (albuminuria: RR, -24% [95% CI, -37% to-8%], Padj=0.02; YKL: RR, -40% to-44% [95% CI, -58% to-25%], Padj<0.001). Pooled meta-analysis demonstrated reduced albuminuria in the intervention arm across 3 trials and similar trajectories in other biomarkers. LIMITATIONS: Biomarker measurement was limited to 2 time points independent of AKI events. CONCLUSIONS: Despite the increased risk of serum creatinine-defined AKI, combination RAAS inhibitor therapy was associated with unchanged or decreased urinary biomarkers at 12 months. This suggests a possible role for kidney biomarkers to further characterize kidney injury in clinical trials. PLAIN-LANGUAGE SUMMARY: The VA NEPHRON-D trial investigated inhibition of the renin-angiotensin-aldosterone system (RAAS) hormonal axis on kidney outcomes in a large population of diabetic chronic kidney disease patients. The trial was stopped early due to increased events of serum creatinine-defined acute kidney injury in the combination therapy arm. Urine biomarkers can serve as an adjunct to serum creatinine in identifying kidney injury. We found that urinary biomarkers in the combination therapy group were not associated with a pattern of harm and damage to the kidney, despite the increased number of kidney injury events in that group. This suggests that serum creatinine alone may be insufficient for defining kidney injury and supports further exploration of how other biomarkers might improve identification of kidney injury in clinical trials.

Urinary Plasminogen as a Marker of Disease Progression in Human Glomerular Disease.

RATIONALE & OBJECTIVE: Glomerular disorders have a highly variable clinical course, and biomarkers that reflect the molecular mechanisms underlying their progression are needed. Based on our previous work identifying plasminogen as a direct cause of podocyte injury, we designed this study to test the association between urine plasmin(ogen) (ie, plasmin and its precursor plasminogen) and end-stage kidney disease (ESKD). STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 1,010 patients enrolled in the CureGN Cohort with biopsy-proven glomerular disease (focal segmental glomerulosclerosis, membranous nephropathy, and immunoglobulin A nephropathy). PREDICTORS: The main predictor was urine plasmin(ogen) at baseline. Levels were measured by an electrochemiluminescent immunoassay developed de novo. Traditional clinical and analytical characteristics were used for adjustment. The ratio of urine plasmin(ogen)/expected plasmin(ogen) was evaluated as a predictor in a separate model. OUTCOME: Progression to ESKD. ANALYTICAL APPROACH: Cox regression was used to examine the association between urinary plasmin(ogen) and time to ESKD. Urinary markers were log2 transformed to approximate normal distribution and normalized to urinary creatinine (Log2uPlasminogen/cr, Log2 urinary protein/cr [UPCR]). Expected plasmin(ogen) was calculated by multiple linear regression. RESULTS: Adjusted Log2uPlasminogen/cr was significantly associated with ESKD (HR per doubling Log2 uPlasminogen/cr 1.31 [95% CI, 1.22-1.40], P<0.001). Comparison of the predictive performance of the models including Log2 uPlasminogen/cr, Log2 UPCR, or both markers showed the plasmin(ogen) model superiority. The ratio of measured/expected urine plasmin(ogen) was independently associated with ESKD: HR, 0.41 (95% CI, 0.22-0.77) if ratio<0.8 and HR 2.42 (95% CI, 1.54-3.78) if ratio>1.1 (compared with ratio between 0.8 and 1.1). LIMITATIONS: Single plasmin(ogen) determination does not allow for the study of changes over time. The use of a cohort of mostly white patients and the restriction to patients with 3 glomerular disorders limits the external validity of our analysis. CONCLUSIONS: Urinary plasmin(ogen) and the ratio of measured/expected plasmin(ogen) are independently associated with ESKD in a cohort of patients with glomerular disease. Taken together with our previous experimental findings, urinary plasmin(ogen) could be a useful biomarker in prognostic decision making and a target for the development of novel therapies in patients with proteinuria and glomerular disease. PLAIN-LANGUAGE SUMMARY: Glomerular diseases are an important cause of morbidity and mortality in patients of all ages. Knowing the individual risk of progression to dialysis or transplantation would help to plan the follow-up and treatment of these patients. Our work studies the usefulness of urinary plasminogen as a marker of progression in this context, since previous studies indicate that plasminogen may be involved in the mechanisms responsible for the progression of these disorders. Our work in a sample of 1,010 patients with glomerular disease demonstrates that urinary plasminogen (as well as the ratio of measured to expected plasminogen) is associated with the risk of progression to end-stage kidney disease. Urine plasminogen exhibited good performance and, if further validated, could enable risk stratification for timely interventions in patients with proteinuria and glomerular disease.

MetSCORE: a molecular metric to evaluate the risk of metabolic syndrome based on serum NMR metabolomics.

BACKGROUND: Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. METHODS: We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. RESULTS: We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920-0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients). CONCLUSIONS: We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.

Urine and serum metabolomic analysis of endometrial cancer diagnosis and classification based on ultra-performance liquid chromatography mass spectrometry.

OBJECTIVE: This study aimed to reveal the urinary and serum metabolic pattern of endometrial cancer (EC) and establish diagnostic models to identify EC from controls, high-risk from low-risk EC, and type II from type I EC. METHOD: This study included 146 EC patients (comprising 79 low-risk and 67 high-risk patients, including 124 type I and 22 type II) and 59 controls. The serum and urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry. Analysis was used to elucidate the distinct metabolites and altered metabolic pathways. Receiver operating characteristic (ROC) analyses were employed to discover and validate the potential biomarker models. RESULTS: Serum and urine metabolomes displayed significant differences between EC and controls, with metabolites related to amino acid and nicotinamide metabolisms. The serum and urine panels distinguished these two groups with Area Under the Curve (AUC) of 0.821 and 0.902, respectively. The panel consisting of serum and urine metabolites demonstrated the best predictive ability (AUC = 0.953 and 0.976 in discovering and validation group). In comparing high-risk and low risk EC, differential metabolites were enriched in purine and glutamine metabolism. The AUC values for serum and urine panels were 0.818, and 0.843, respectively. The combined panel exhibited better predictive accuracy (0.881 in discovering group and 0.936 in external validation). In the comparison between type I and type II group, altered folic acid metabolism was identified. The serum, urine and combined panels discriminated these two groups with the AUC of 0.829, 0.913 and 0.922, respectively. CONCLUSION: The combined urine and serum metabolome effectively revealed the metabolic patterns in EC patients, offering valuable diagnostic models for EC diagnosis and classification.

Biomarker panels for fruit intake assessment: a metabolomics analysis in the ELSA-Brasil study.

INTRODUCTION: Food intake biomarkers are used to estimate dietary exposure; however, selecting a single biomarker to evaluate a specific dietary component is difficult due to the overlap of diverse compounds from different foods. Therefore, combining two or more biomarkers can increase the sensitivity and specificity of food intake estimates. OBJECTIVE: This study aimed to evaluate the ability of metabolite panels to distinguish between self-reported fruit consumers and non-consumers among participants in the Longitudinal Study of Adult Health. MATERIALS AND METHODS: A total of 93 healthy adults of both sexes were selected from the Longitudinal Study of Adult Health. A 24-h dietary recall was obtained using the computer-assisted 24-h food recall GloboDiet software, and 24-h urine samples were collected from each participant. Metabolites were identified in urine using liquid chromatography coupled with high-resolution mass spectrometry by comparing their exact mass and fragmentation patterns using free-access databases. Multivariate receiver operating characteristic curve (ROC) analysis and partial least squares discriminant analysis were used to verify the ability of the metabolite combination to classify daily and non-daily fruit consumers. Fruit intake was identified using a 24 h dietary recall (24 h-DR). RESULTS: Bananas, grapes, and oranges are included in the summary. The panel of biomarkers exhibited an area under the curve (AUC) > 0.6 (Orange AUC = 0.665; Grape AUC = 0.622; Bananas AUC = 0.602; All fruits AUC = 0.679; Citrus AUC = 0.693) and variable importance projection score > 1.0, and these were useful for assessing the sensitivity and predictability of food intake in our population. CONCLUSION: A panel of metabolites was able to classify self-reported fruit consumers with strong predictive power and high specificity and sensitivity values except for banana and total fruit intake.