Acute Kidney Injury, Systemic Inflammation and Long-term Cognitive Function: ASSESS-AKI.

BACKGROUND: Cognitive dysfunction is a well-known complication of chronic kidney disease, but it is less known whether cognitive decline occurs in survivors after acute kidney injury (AKI). We hypothesized that an episode of AKI is associated with poorer cognitive function, mediated, at least in part, by persistent systemic inflammation. METHODS: ASSESS-AKI enrolled patients surviving three months after hospitalization with and without AKI matched based on demographics, comorbidities, and baseline kidney function. A subset underwent cognitive testing using the modified mini-mental status examination (3MS) at 3, 12, and 36 months. We examined the association of AKI with 3MS scores using mixed linear models and assessed the proportion of risk mediated by systemic inflammatory biomarkers. RESULTS: Among 1538 participants in ASSESS-AKI, 1420 (92%) completed the 3MS assessment at 3 months and had a corresponding matched participant. Participants with AKI had lower 3MS scores at three years (difference -1.1 (95% CI: -2.0, -0.3) P=0.009) compared to participants without AKI. A higher proportion of AKI participants had a clinically meaningful (≥ 5 point) reduction in 3MS scores at three years compared to participants without AKI (14% vs. 10%, P=0.04). In mediation analyses, plasma soluble tumor necrosis factor receptor-1 (sTNFR-1) at three months after AKI mediated 35% (P=0.02) of the AKI related risk for 3MS scores at three years. CONCLUSIONS: AKI was associated with lower 3MS scores and sTNFR-1 concentrations appeared to mediate a significant proportion of the risk of long-term cognitive impairment. Further work is needed to determine if AKI is causal or a marker for cognitive impairment.

Longitudinal plasma metabolome patterns and relation to kidney function and proteinuria in pediatric chronic kidney disease.

INTRODUCTION: Understanding plasma metabolome patterns in relation to changing kidney function in pediatric chronic kidney disease (CKD) is important for continued research for identifying novel biomarkers, characterizing biochemical pathophysiology, and developing targeted interventions. There is a limited number of studies of longitudinal metabolomics, and virtually none in pediatric CKD. METHODS: The Chronic Kidney Disease in Children (CKiD) study is a multi-institutional, prospective cohort that enrolled children aged six-months to 16-years with estimated glomerular filtration rate (eGFR) 30-90ml/min/1.73m2. Untargeted metabolomics profiling was performed on plasma samples from the baseline, two-, and four-year study visits. There were technologic updates in the metabolomic profiling platform used between the baseline and follow-up assays. Statistical approaches were adopted to avoid direct comparison of baseline and follow-up measurements.To identify metabolite associations with eGFR or urine protein:creatinine (UPCR) among all three timepoints, we applied linear mixed effects (LME) models. To identify metabolites associated with time, we applied LME models to the two- and four-year follow-up data. We applied linear regression analysis to examine associations between change in metabolite level over time (∆level) and change in eGFR (∆eGFR) and UPCR (∆UPCR). We reported significance based on both the False Discovery Rate (FDR) <0.05 and p<0.05. RESULTS: There were 1156 person-visits (N: baseline=626, 2-year=254, 4-year=276) included. There were 622 metabolites with standardized measurements at all three timepoints. In LME modeling, 406 and 343 metabolites associated with eGFR and UPCR at FDR<0.05 respectively. Among 530 follow-up person-visits, 158 metabolites showed differences over time at FDR<0.05. For participants with complete data at both follow-up visits (N=123), we report 35 metabolites with ∆level∼∆eGFR associations significant at FDR<0.05. There were no metabolites with significant ∆level∼∆UPCR associations at FDR<0.05. We report 16 metabolites with ∆level∼∆UPCR associations at p<0.05 and associations with UPCR in LME modeling at FDR<0.05. CONCLUSION: We characterized longitudinal plasma metabolomic patterns associated with eGFR and UPCR in a large pediatric CKD population. Many of these metabolite signals have been associated with CKD progression, etiology, and proteinuria in previous CKD Biomarkers Consortium studies. There were also novel metabolite associations with eGFR and proteinuria detected.

Integrated Proteomic and Metabolomic Modules associated with Risk of Kidney Disease Progression.

BACKGROUND: Proteins and metabolites play crucial roles in various biological functions and are frequently interconnected through enzymatic or transport processes. METHODS: We present an integrated analysis of 4,091 proteins and 630 metabolites in the Chronic Renal Insufficiency Cohort Study (N=1,708; average follow-up for kidney failure [KF], 9.5 years, with 537 events). Proteins and metabolites were integrated using an unsupervised clustering method and we assessed associations between clusters and CKD progression and kidney failure using Cox proportional hazards models. Analyses were adjusted for demographics and risk factors including the estimated glomerular filtration rate (eGFR) and urine protein-creatinine ratio. Associations were identified in a discovery sample (random two-thirds, N=1139) and then evaluated in a replication sample (one-third, N=569). RESULTS: We identified 139 modules of correlated proteins and metabolites, which were represented by their principal components (PC). Modules and PC loadings were projected onto the replication sample which demonstrated a consistent network structure. Two modules, representing a total of 236 proteins and 82 metabolites, were robustly associated with both CKD progression and kidney failure in both discovery and validation samples. Using gene set enrichment, several transmembrane related terms were identified as over-represented in these modules. Transmembrane-ephrin receptor activity displayed the largest odds (OR = 13.2, P-value = 5.5×10 -5 ). A module containing CRIM1 and NPNT expressed in podocytes demonstrated particularly strong associations with kidney failure (P-value = 2.6×10 -5 ). CONCLUSIONS: This study demonstrates that integration of the proteome and metabolome can identify functions of pathophysiologic importance in kidney disease.

Metabolites Associated With Uremic Symptoms in Patients With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: The toxins that contribute to uremic symptoms in patients with chronic kidney disease (CKD) are unknown. We sought to apply complementary statistical modeling approaches to data from untargeted plasma metabolomic profiling to identify solutes associated with uremic symptoms in patients with CKD. STUDY DESIGN: Cross-sectional. SETTING & PARTICIPANTS: 1,761 Chronic Renal Insufficiency Cohort (CRIC) participants with CKD not treated with dialysis. PREDICTORS: Measurement of 448 known plasma metabolites. OUTCOMES: The uremic symptoms of fatigue, anorexia, pruritus, nausea, paresthesia, and pain were assessed by single items on the Kidney Disease Quality of Life-36 instrument. ANALYTICAL APPROACH: Multivariable adjusted linear regression, least absolute shrinkage and selection operator linear regression, and random forest models were used to identify metabolites associated with symptom severity. After adjustment for multiple comparisons, metabolites selected in at least 2 of the 3 modeling approaches were deemed "overall significant." RESULTS: Participant mean estimated glomerular filtration rate was 43mL/min/1.73m2, with 44% self-identifying as female and 41% as non-Hispanic Black. The prevalence of uremic symptoms ranged from 22% to 55%. We identified 17 metabolites for which a higher level was associated with greater severity of at least one uremic symptom and 9 metabolites inversely associated with uremic symptom severity. Many of these metabolites exhibited at least a moderate correlation with estimated glomerular filtration rate (Pearson's r≥0.5), and some were also associated with the risk of developing kidney failure or death in multivariable adjusted Cox regression models. LIMITATIONS: Lack of a second independent cohort for external validation of our findings. CONCLUSIONS: Metabolomic profiling was used to identify multiple solutes associated with uremic symptoms in adults with CKD, but future validation and mechanistic studies are needed. PLAIN-LANGUAGE SUMMARY: Individuals living with chronic kidney disease (CKD) often experience symptoms related to CKD, traditionally called uremic symptoms. It is likely that CKD results in alterations in the levels of numerous circulating substances that, in turn, cause uremic symptoms; however, the identity of these solutes is not known. In this study, we used metabolomic profiling in patients with CKD to gain insights into the pathophysiology of uremic symptoms. We identified 26 metabolites whose levels were significantly associated with at least one of the symptoms of fatigue, anorexia, itchiness, nausea, paresthesia, and pain. The results of this study lay the groundwork for future research into the biological causes of symptoms in patients with CKD.

Age- and Race-Specific Changes in ESKD Incidence over Four Decades.

SIGNIFICANCE STATEMENT: ESKD incidence has changed substantially in the past four decades, but differences by age and race have been unexplored. Using data from the United States Renal Data System, we found that ESKD incidence rose for Black and White teenagers, adults, and older adults for two decades beginning in 1980. Growth in incidence slowed for most groups by 1993, and by 2006, the annual percent change (APC) in ESKD incidence had declined for all groups, except White adults, for whom rates continued to rise. By 2019, ESKD incidence among Black and White adolescents nearly returned to 1980 levels, but no other group achieved that degree of improvement. Nonetheless, the ESKD incidence rate among Black American patients exceeds that of White patients in every age group. Distinct patterns in ESKD incidence among patients of different age, sex, and racial groups are shown. These findings could reflect changes in dialysis acceptance rates, access to preventive health care, incidence of diabetes mellitus, implementation of evidence-based guidelines for treatment of CKD, or other unrecognized factors. There may be population-specific opportunities to change the growth of the US ESKD population and address current racial disparities. BACKGROUND: Substantial changes in ESKD incidence over four decades among Black and White Americans of different ages have been incompletely explored. METHODS: We analyzed United States Renal Data System data from 1980 to 2019 to determine ESKD incidence trends among Black and White adolescent (13-17 years), adult (18-64 years), and older adult (≥65) populations. We used the National Cancer Institute Joinpoint Regression Program to estimate annual percent change (APC) in ESKD incidence and to define points in time where a statistically significant change in APC slope occurred for each group. RESULTS: ESKD incidence rose after 1980 for all groups, although the trends differed ( P < 0.001). Growth in incidence slowed for most by 1993, and by 2006, the APC in ESKD incidence had declined for all groups, except White adults, for whom rates continued to rise ( P < 0.05). By 2019, ESKD incidence among Black and White adolescents nearly returned to 1980 levels, but no other group achieved that degree of improvement. Nonetheless, the ESKD incidence among Black American patients exceeds that of White patients in every age group. CONCLUSIONS: Distinct patterns in ESKD incidence among patients of different age, sex, and racial groups are shown. These findings could reflect changes in dialysis acceptance rates, access to preventive health care, incidence of diabetes mellitus, implementation of evidence-based guidelines for treatment of CKD, or other unrecognized factors. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/JASN/2024_03_13_ASN0000000000000310.mp3.

The design and baseline characteristics for the HOPE Consortium Trial to reduce pain and opioid use in hemodialysis.

The HOPE Consortium Trial to Reduce Pain and Opioid Use in Hemodialysis (HOPE Trial) is a multicenter randomized trial addressing chronic pain among patients receiving maintenance hemodialysis for end-stage kidney disease. The trial uses a sequential, multiple assignment design with a randomized component for all participants (Phase 1) and a non-randomized component for a subset of participants (Phase 2). During Phase 1, participants are randomized to Pain Coping Skills Training (PCST), an intervention designed to increase self-efficacy for managing pain, or Usual Care. PCST consists of weekly, live, coach-led cognitive behavioral therapy sessions delivered by video- or tele-conferencing for 12 weeks followed by daily interactive voice response sessions delivered by telephone for an additional 12 weeks. At 24 weeks (Phase 2), participants in both the PCST and Usual Care groups taking prescription opioid medications at an average dose of ≥20 morphine milligram equivalents per day are offered buprenorphine, a partial opioid agonist with a more favorable safety profile than full-agonist opioids. All participants are followed for 36 weeks. The primary outcome is pain interference ascertained, for the primary analysis, at 12 weeks. Secondary outcomes include additional patient-reported measures and clinical outcomes including falls, hospitalizations, and death. Exploratory outcomes include acceptability, tolerability, and efficacy of buprenorphine. The enrollment target of 640 participants was met 27 months after trial initiation. The findings of the trial will inform the management of chronic pain, a common and challenging issue for patients treated with maintenance hemodialysis. NCT04571619.

Plasma Metabolomics of Dietary Intake of Protein-Rich Foods and Kidney Disease Progression in Children.

OBJECTIVE: Evidence regarding the efficacy of a low-protein diet for patients with CKD is inconsistent and recommending a low-protein diet for pediatric patients is controversial. There is also a lack of objective biomarkers of dietary intake. The purpose of this study was to identify plasma metabolites associated with dietary intake of protein and to assess whether protein-related metabolites are associated with CKD progression. METHODS: Nontargeted metabolomics was conducted in plasma samples from 484 Chronic Kidney Disease in Children (CKiD) participants. Multivariable linear regression estimated the cross-sectional association between 949 known, nondrug metabolites and dietary intake of total protein, animal protein, plant protein, chicken, dairy, nuts and beans, red and processed meat, fish, and eggs, adjusting for demographic, clinical, and dietary covariates. Cox proportional hazards models assessed the prospective association between protein-related metabolites and CKD progression defined as the initiation of kidney replacement therapy or 50% eGFR reduction, adjusting for demographic and clinical covariates. RESULTS: One hundred and twenty-seven (26%) children experienced CKD progression during 5 years of follow-up. Sixty metabolites were significantly associated with dietary protein intake. Among the 60 metabolites, 10 metabolites were significantly associated with CKD progression (animal protein: n = 1, dairy: n = 7, red and processed meat: n = 2, nuts and beans: n = 1), including one amino acid, one cofactor and vitamin, 4 lipids, 2 nucleotides, one peptide, and one xenobiotic. 1-(1-enyl-palmitoyl)-2-oleoyl-glycerophosphoethanolamine (GPE, P-16:0/18:1) was positively associated with dietary intake of red and processed meat, and a doubling of its abundance was associated with 88% higher risk of CKD progression. 3-ureidopropionate was inversely associated with dietary intake of red and processed meat, and a doubling of its abundance was associated with 48% lower risk of CKD progression. CONCLUSIONS: Untargeted plasma metabolomic profiling revealed metabolites associated with dietary intake of protein and CKD progression in a pediatric population.

Epidemiology of Infantile Ureteropelvic Junction Obstruction in the US.

OBJECTIVE: To describe sex- and diagnosis-specific comorbidities, outcomes, and secular trends associated with ureteropelvic junction obstruction (UPJO) in a large, real-world population diagnosed with hydronephrosis in infancy. MATERIALS AND METHODS: We identified all infants ≤1 year old with ≥1 claim in the Optum Clinformatics 2007-2020 nationwide population database and used univariable and multivariable Cox regression analyses to estimate associations of demographic and clinical characteristics of infants with a UPJO diagnosis with surgical status. RESULTS: Of 22,349 infants with hydronephrosis (1.1% of infants; males-1.4%, females-0.7%), 1722 (7.7%; 7.9%-males, 7.2%-females) had UPJO. Follow-up was ≥1 year in 1198 (70%) and ≥3 years in 555 (32%) cases, and UPJO repair was performed in 542 children (31.5%; 32.3%-males, 29.5%-females); 77.7% within 1 year and 97.3% within 3 years. UPJO repair was associated with prior urinary tract infection (UTI) (hazard ratio (HR) 1.41, 95% confidence interval (CI) 1.12-1.76) and South (HR 1.42, 95% CI 1.14-1.78) or Midwest (HR 1.60, 95% CI 1.26-2.04) geographic region but did not change over time. CONCLUSION: This population-based study provides a real-world view of postnatally diagnosed hydronephrosis, focusing on UPJO, for which 522 cases (∼1/3) had ≥3 years continuous coverage. UPJO-associated comorbidities were more common in females, and the frequencies of UPJO-associated surgery and comorbidities were higher than in other studies. Other than UTI, no other associated kidney or urinary tract diagnoses were associated with UPJO repair. We identified unique sex- and diagnosis-specific differences in associated comorbidities and interventions in children diagnosed with UPJO in the first year of life.

Association of Obesity, Metabolic Syndrome, and Diabetes With Urinary Incontinence and Chronic Kidney Disease: Analysis of the National Health and Nutrition Examination Survey, 2003-2020.

PURPOSE: Diabetes and obesity, components of the metabolic syndrome (MetS), are risk factors for urinary incontinence (UI) and chronic kidney disease (CKD). We interrogated US population-based data to explore independent, sex-specific associations between nondiabetic MetS, with and without obesity, and UI and/or CKD. MATERIALS AND METHODS: We analyzed data from 8586 males and 8420 females ≥20 years from the National Health and Nutrition Examination Survey. Multivariable logistic regression models were used to examine associations of UI or CKD with diabetes and 4 nondiabetic obesity/metabolic phenotypes: non-MetS/nonobese, MetS/nonobese, non-MetS/obese, and MetS/obese. Multinominal logistic regression models were used to assess associations of co-occurring UI/CKD with obesity/metabolic phenotypes. RESULTS: Male MetS/obese participants had increased odds of any UI (1.25; 95% CI 1.00-1.57) and urgency UI (1.36; 1.03-1.80), compared with non-MetS/nonobese participants. Female MetS/obese participants had increased odds of any UI (2.16; 95% CI 1.76-2.66), stress UI (1.51; 1.21-1.87), and mixed UI (1.66; 1.31-2.11) compared with non-MetS/nonobese participants. The odds of co-occurring UI/CKD were increased relative to either condition alone in persons with diabetes, and in males with MetS/obese phenotypes and females with MetS phenotypes as compared to same sex participants with neither obesity nor MetS. CONCLUSIONS: We found novel associations between MetS/obese and urgency UI in males without diabetes, and between SUI and both MetS and obesity in females without diabetes. Odds estimates for UI/CKD were increased by existing obesity or MetS as compared to those for UI or CKD alone. Improved understanding of modifiable factors associated with UI will inform prevention and treatment opportunities.

Plasma Biomarkers and Incident CKD Among Individuals Without Diabetes.

Rationale & Objective: Biomarkers of kidney disease progression have been identified in individuals with diabetes and underlying chronic kidney disease (CKD). Whether or not these markers are associated with the development of CKD in a general population without diabetes or CKD is not well established. Study Design: Prospective observational cohort. Setting & Participants: In the Atherosclerosis Risk in Communities) study, 948 participants were studied. Exposures: The baseline plasma biomarkers of kidney injury molecule-1 (KIM-1), monocyte chemoattractant protein-1 (MCP-1), soluble urokinase plasminogen activator receptor (suPAR), tumor necrosis factor receptor 1 (TNFR-1), tumor necrosis factor receptor 2 (TNFR-2), and human cartilage glycoprotein-39 (YKL-40) measured in 1996-1998. Outcome: Incident CKD after 15 years of follow-up defined as ≥40% estimated glomerular filtration rate decline to <60 mL/min/1.73 m2 or dialysis dependence through United States Renal Data System linkage. Analytical Approach: Logistic regression and C statistics. Results: There were 523 cases of incident CKD. Compared with a random sample of 425 controls, there were greater odds of incident CKD per 2-fold higher concentration of KIM-1 (OR, 1.49; 95% CI, 1.25-1.78), suPAR (OR, 2.57; 95% CI, 1.74-3.84), TNFR-1 (OR, 2.20; 95% CI, 1.58-3.09), TNFR-2 (OR, 2.03; 95% CI, 1.37-3.04). After adjustment for all biomarkers, KIM-1 (OR, 1.42; 95% CI, 1.19-1.71), and suPAR (OR, 1.86; 95% CI, 1.18-2.92) remained associated with incident CKD. Compared with traditional risk factors, the addition of all 6 biomarkers improved the C statistic from 0.695-0.731 (P < 0.01) and using the observed risk of 12% for incident CKD, the predicted risk gradient changed from 5%-40% (for the 1st-5th quintile) to 4%-44%. Limitations: Biomarkers and creatinine were measured at one time point. Conclusions: Higher levels of KIM-1, suPAR, TNFR-1, and TNFR-2 were associated with higher odds of incident CKD among individuals without diabetes. Plain-Language Summary: For people with diabetes or kidney disease, several biomarkers have been shown to be associated with worsening kidney disease. Whether these biomarkers have prognostic significance in people without diabetes or kidney disease is less studied. Using the Atherosclerosis Risk in Communities study, we followed individuals without diabetes or kidney disease for an average of 15 years after biomarker measurement to see if these biomarkers were associated with the development of kidney disease. We found that elevated levels of KIM-1, suPAR, TNFR-1, and TNFR-2 were associated with the development of kidney disease. These biomarkers may help identify individuals who would benefit from interventions to prevent the development of kidney disease.

Proteomics of CKD progression in the chronic renal insufficiency cohort.

Progression of chronic kidney disease (CKD) portends myriad complications, including kidney failure. In this study, we analyze associations of 4638 plasma proteins among 3235 participants of the Chronic Renal Insufficiency Cohort Study with the primary outcome of 50% decline in estimated glomerular filtration rate or kidney failure over 10 years. We validate key findings in the Atherosclerosis Risk in the Communities study. We identify 100 circulating proteins that are associated with the primary outcome after multivariable adjustment, using a Bonferroni statistical threshold of significance. Individual protein associations and biological pathway analyses highlight the roles of bone morphogenetic proteins, ephrin signaling, and prothrombin activation. A 65-protein risk model for the primary outcome has excellent discrimination (C-statistic[95%CI] 0.862 [0.835, 0.889]), and 14/65 proteins are druggable targets. Potentially causal associations for five proteins, to our knowledge not previously reported, are supported by Mendelian randomization: EGFL9, LRP-11, MXRA7, IL-1 sRII and ILT-2. Modifiable protein risk markers can guide therapeutic drug development aimed at slowing CKD progression.

Circulating Metabolomic Associations with Neurocognitive Outcomes in Pediatric CKD.

BACKGROUND: Children with CKD are at risk for impaired neurocognitive functioning. We investigated metabolomic associations with neurocognition in children with CKD. METHODS: We leveraged data from the Chronic Kidney Disease in Children (CKiD) study and the Neurocognitive Assessment and Magnetic Resonance Imaging Analysis of Children and Young Adults with Chronic Kidney Disease (NiCK) study. CKiD is a multi-institutional cohort that enrolled children aged 6 months to 16 years with eGFR 30-90 ml/min per 1.73 m 2 ( n =569). NiCK is a single-center cross-sectional study of participants aged 8-25 years with eGFR<90 ml/min per 1.73 m 2 ( n =60) and matched healthy controls ( n =67). Untargeted metabolomic quantification was performed on plasma (CKiD, 622 metabolites) and serum (NiCK, 825 metabolites) samples. Four neurocognitive domains were assessed: intelligence, attention regulation, working memory, and parent ratings of executive function. Repeat assessments were performed in CKiD at 2-year intervals. Linear regression and linear mixed-effects regression analyses adjusting for age, sex, delivery history, hypertension, proteinuria, CKD duration, and glomerular versus nonglomerular diagnosis were used to identify metabolites associated with neurocognitive z-scores. Analyses were performed with and without adjustment for eGFR. RESULTS: There were multiple metabolite associations with neurocognition observed in at least two of the analytic samples (CKiD baseline, CKiD follow-up, and NiCK CKD). Most of these metabolites were significantly elevated in children with CKD compared with healthy controls in NiCK. Notable signals included associations with parental ratings of executive function: phenylacetylglutamine, indoleacetylglutamine, and trimethylamine N-oxide-and with intelligence: γ -glutamyl amino acids and aconitate. CONCLUSIONS: Several metabolites were associated with neurocognitive dysfunction in pediatric CKD, implicating gut microbiome-derived substances, mitochondrial dysfunction, and altered energy metabolism, circulating toxins, and redox homeostasis.

The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events.

Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients.

Association of urine and plasma ADMA with atherosclerotic risk in DKD cardiovascular disease risk in diabetic kidney disease: findings from the Chronic Renal Insufficiency Cohort (CRIC) study.

BACKGROUND: Chronic kidney disease (CKD) is associated with atherosclerotic cardiovascular disease (ASCVD) risk, especially among those with diabetes. Altered metabolism of solutes that accumulate in CKD [asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA) and trimethylamine N-oxide (TMAO)] may reflect pathways linking CKD with ASCVD. METHODS: This case-cohort study included Chronic Renal Insufficiency Cohort participants with baseline diabetes, estimated glomerular filtration rate <60 mL/min/1.73 m2, and without prior history for each outcome. The primary outcome was incident ASCVD (time to first myocardial infarction, stroke or peripheral artery disease event) and secondary outcome was incident heart failure. The subcohort comprised randomly selected participants meeting entry criteria. Plasma and urine ADMA, SDMA and TMAO concentrations were determined by liquid chromatography-tandem mass spectrometry. Associations of uremic solute plasma concentrations and urinary fractional excretions with outcomes were evaluated by weighted multivariable Cox regression models, adjusted for confounding covariables. RESULTS: Higher plasma ADMA concentrations (per standard deviation) were associated with ASCVD risk [hazard ratio (HR) 1.30, 95% confidence interval (CI) 1.01-1.68]. Lower fractional excretion of ADMA (per standard deviation) was associated with ASCVD risk (HR 1.42, 95% CI 1.07-1.89). The lowest quartile of ADMA fractional excretion was associated with greater ASCVD risk (HR 2.25, 95% CI 1.08-4.69) compared with the highest quartile. Plasma SDMA and TMAO concentration and fractional excretion were not associated with ASCVD. Neither plasma nor fractional excretion of ADMA, SDMA and TMAO were associated with incident heart failure. CONCLUSION: These data suggest that decreased kidney excretion of ADMA leads to increased plasma concentrations and ASCVD risk.

Integrated Analysis of Blood and Urine Biomarkers to Identify Acute Kidney Injury Subphenotypes and Associations With Long-term Outcomes.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is a heterogeneous clinical syndrome with varying causes, pathophysiology, and outcomes. We incorporated plasma and urine biomarker measurements to identify AKI subgroups (subphenotypes) more tightly linked to underlying pathophysiology and long-term clinical outcomes. STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 769 hospitalized adults with AKI matched with 769 without AKI, enrolled from December 2009 to February 2015 in the ASSESS-AKI Study. PREDICTORS: 29 clinical, plasma, and urinary biomarker parameters used to identify AKI subphenotypes. OUTCOME: Composite of major adverse kidney events (MAKE) with a median follow-up period of 4.7 years. ANALYTICAL APPROACH: Latent class analysis (LCA) and k-means clustering were applied to 29 clinical, plasma, and urinary biomarker parameters. Associations between AKI subphenotypes and MAKE were analyzed using Kaplan-Meier curves and Cox proportional hazard models. RESULTS: Among 769 AKI patients both LCA and k-means identified 2 distinct AKI subphenotypes (classes 1 and 2). The long-term risk for MAKE was higher with class 2 (adjusted HR, 1.41 [95% CI, 1.08-1.84]; P=0.01) compared with class 1, adjusting for demographics, hospital level factors, and KDIGO stage of AKI. The higher risk of MAKE among class 2 was explained by a higher risk of long-term chronic kidney disease progression and dialysis. The top variables that were different between classes 1 and 2 included plasma and urinary biomarkers of inflammation and epithelial cell injury; serum creatinine ranked 20th out of the 29 variables for differentiating classes. LIMITATIONS: A replication cohort with simultaneously collected blood and urine sampling in hospitalized adults with AKI and long-term outcomes was unavailable. CONCLUSIONS: We identify 2 molecularly distinct AKI subphenotypes with differing risk of long-term outcomes, independent of the current criteria to risk stratify AKI. Future identification of AKI subphenotypes may facilitate linking therapies to underlying pathophysiology to prevent long-term sequalae after AKI. PLAIN-LANGUAGE SUMMARY: Acute kidney injury (AKI) occurs commonly in hospitalized patients and is associated with high morbidity and mortality. The AKI definition lumps many different types of AKI together, but subgroups of AKI may be more tightly linked to the underlying biology and clinical outcomes. We used 29 different clinical, blood, and urinary biomarkers and applied 2 different statistical algorithms to identify AKI subtypes and their association with long-term outcomes. Both clustering algorithms identified 2 AKI subtypes with different risk of chronic kidney disease, independent of the serum creatinine concentrations (the current gold standard to determine severity of AKI). Identification of AKI subtypes may facilitate linking therapies to underlying biology to prevent long-term consequences after AKI.