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.

Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification.

BACKGROUND AND AIMS: Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed. METHODS: In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score. RESULTS: Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787). CONCLUSIONS: Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.

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.

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.

Comparative CKD risk prediction using homocitrulline and carbamylated albumin: two circulating markers of protein carbamylation.

BACKGROUND: Protein carbamylation, a post-translational protein modification primarily driven by urea, independently associates with adverse clinical outcomes in patients with CKD. Biomarkers used to quantify carbamylation burden have mainly included carbamylated albumin (C-Alb) and homocitrulline (HCit, carbamylated lysine). In this study, we aimed to compare the prognostic utility of these two markers in order to facilitate comparisons of existing studies employing either marker alone, and to inform future carbamylation studies. METHODS: Both serum C-Alb and free HCit levels were assayed from the same timepoint in 1632 individuals with CKD stages 2-4 enrolled in the prospective Chronic Renal Insufficiency Cohort (CRIC) study. Adjusted Cox proportional hazard models were used to assess risks for the outcomes of death (primary) and end stage kidney disease (ESKD) using each marker. C-statistics, net reclassification improvement, and integrated discrimination improvement were used to compare the prognostic value of each marker. RESULTS: Participant demographics included mean (SD) age 59 (11) years; 702 (43%) females; 700 (43%) white. C-Alb and HCit levels were positively correlated with one another (Pearson correlation coefficient 0.64). Higher C-Alb and HCit levels showed similar increased risk of death (e.g., the adjusted hazard ratio [HR] for death in the 4th carbamylation quartile compared to the 1st was 1.90 (95% confidence interval [CI] 1.35-2.66) for C-Alb, and 1.89 [1.27-2.81] for HCit; and on a continuous scale, the adjusted HR for death using C-Alb was 1.24 [1.11 to 1.39] per standard deviation increase, and 1.27 [1.10-1.46] using HCit). Both biomarkers also had similar HRs for ESKD. The C-statistics were similar when adding each carbamylation biomarker to base models (e.g., for mortality models, the C-statistic was 0.725 [0.707-0.743] with C-Alb and 0.725 [0.707-0.743] with HCit, both compared to a base model 0.723). Similarities were also observed for the net reclassification improvement and integrated discrimination improvement metrics. CONCLUSIONS: C-Alb and HCit had similar performance across multiple prognostic assessments. The markers appear readily comparable in CKD epidemiological studies.

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.

Testican-2 Is Associated with Reduced Risk of Incident ESKD.

BACKGROUND: Testican-2 was recently identified as a podocyte-derived protein that is released into circulation by the kidneys and is positively correlated with eGFR and eGFR slope. However, whether higher testican-2 levels are associated with lower risk of ESKD is unknown. METHODS: Aptamer-based proteomics assessed blood testican-2 levels among participants in the African American Study of Kidney Disease and Hypertension (AASK, n =703), the Chronic Renal Insufficiency Cohort (CRIC) study ( n =3196), and the Atherosclerosis Risk in Communities (ARIC) study ( n =4378). We compared baseline characteristics by testican-2 tertile and used Cox proportional hazards models to study the association of testican-2 with incident ESKD. RESULTS: Higher testican-2 levels were associated with higher measured GFR (mGFR) in AASK, higher eGFR in the CRIC and ARIC studies, and lower albuminuria in all cohorts. Baseline testican-2 levels were significantly associated with incident ESKD in Cox proportional hazards models adjusted for age, sex, and race (model 1) and model 1+mGFR or eGFR+comorbidities (model 2). In model 3 (model 2+proteinuria), the associations between testican-2 (per SD increase) and incident ESKD were AASK (hazard ratio [HR]=0.84 [0.72 to 0.98], P =0.023), CRIC (HR=0.95 [0.89 to 1.02], P =0.14), ARIC (HR=0.54 [0.36 to 0.83], P =0.0044), and meta-analysis (HR=0.92 [0.86 to 0.98], P =0.0073). CONCLUSIONS: Across three cohorts spanning >8000 individuals, testican-2 is associated with kidney health and prognosis, with higher levels associated with reduced risk of ESKD.

Proteomic cardiovascular risk assessment in chronic kidney disease.

AIMS: Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models. METHODS AND RESULTS: Elastic net regression was used to derive a proteomic risk model for incident cardiovascular risk in 2182 participants from the Chronic Renal Insufficiency Cohort. The model was then validated in 485 participants from the Atherosclerosis Risk in Communities cohort. All participants had CKD and no history of cardiovascular disease at study baseline when ∼5000 proteins were measured. The proteomic risk model, which consisted of 32 proteins, was superior to both the 2013 ACC/AHA Pooled Cohort Equation and a modified Pooled Cohort Equation that included estimated glomerular filtrate rate. The Chronic Renal Insufficiency Cohort internal validation set demonstrated annualized receiver operating characteristic area under the curve values from 1 to 10 years ranging between 0.84 and 0.89 for the protein and 0.70 and 0.73 for the clinical models. Similar findings were observed in the Atherosclerosis Risk in Communities validation cohort. For nearly half of the individual proteins independently associated with cardiovascular risk, Mendelian randomization suggested a causal link to cardiovascular events or risk factors. Pathway analyses revealed enrichment of proteins involved in immunologic function, vascular and neuronal development, and hepatic fibrosis. CONCLUSION: In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate. New biological insights may prioritize the development of therapeutic strategies for cardiovascular risk reduction in the CKD population.

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.

Readmission and Mortality After Hospitalization With Acute Kidney Injury.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) carries high rates of morbidity and mortality. This study quantified various short- and long-term outcomes after hospitalization with AKI. STUDY DESIGN: Retrospective propensity score (PS)-matched cohort study. SETTING & PARTICIPANTS: Optum Clinformatics, a national claims database, was used to identify patients hospitalized with and without an AKI discharge diagnosis between January 2007 and September 2020. EXPOSURE: Among patients with prior continuous enrollment for at least 2years without AKI hospitalization, 471,176 patients hospitalized with AKI were identified and PS-matched to 471,176 patients hospitalized without AKI. OUTCOME(S): All-cause and selected-cause rehospitalizations and mortality 90 and 365 days after index hospitalization. ANALYTICAL APPROACH: After PS matching, rehospitalization and death incidences were estimated using the cumulative incidence function method and compared using Gray's test. The association of AKI hospitalization with each outcome was tested using Cox models for all-cause mortality and, with mortality as competing risk, cause-specific hazard modeling for all-cause and selected-cause rehospitalization. Overall and stratified analyses were performed to evaluate for interaction between an AKI hospitalization and preexisting chronic kidney disease (CKD). RESULTS: After PS matching, AKI was associated with higher rates of rehospitalization for any cause (hazard ratio [HR], 1.62; 95% CI, 1.60-1.65), end-stage renal disease (HR, 6.21; 95% CI, 1.04-36.92), heart failure (HR, 2.81; 95% CI, 2.66, 2.97), sepsis (HR, 2.62; 95% CI, 2.49-2.75), pneumonia (HR, 1.47; 95% CI, 1.37-1.57), myocardial infarction (HR, 1.48; 95% CI, 1.33-1.65), and volume depletion (HR, 1.64; 95% CI, 1.37-1.96) at 90 days after discharge compared with the group without AKI, with similar findings at 365 days. Mortality rate was higher in the group with AKI than in the group without AKI at 90 (HR, 2.66; 95% CI, 2.61-2.72) and 365 days (HR, 2.11; 95% CI, 2.08-2.14). The higher risk of outcomes persisted when participants were stratified by CKD status (P<0.01). LIMITATIONS: Causal associations between AKI and the reported outcomes cannot be inferred. CONCLUSIONS: AKI during hospitalization in patients with and without CKD is associated with increased risk of 90- and 365-day all-cause/selected-cause rehospitalization and death.

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.

Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.

RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.

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.

Biomarkers of eGFR decline after cardiac surgery in children: findings from the ASSESS-AKI study.

BACKGROUND: Children who require surgery for congenital heart disease have increased risk for long-term chronic kidney disease (CKD). Clinical factors as well as urine biomarkers of tubular health and injury may help improve the prognostication of estimated glomerular filtration rate (eGFR) decline. METHODS: We enrolled children from 1 month to 18 years old undergoing cardiac surgery in the ASSESS-AKI cohort. We used mixed-effect models to assess the association between urinary biomarkers (log2-transformed uromodulin, NGAL, KIM-1, IL-18, L-FABP) measured 3 months after cardiac surgery and cyanotic heart disease with the rate of eGFR decline at annual in-person visits over 4 years. RESULTS: Of the 117 children enrolled, 30 (24%) had cyanotic heart disease. During 48 months of follow-up, the median eGFR in the subgroup of children with cyanotic heart disease was lower at all study visits as compared with children with acyanotic heart disease (p = 0.01). In the overall cohort, lower levels of both urine uromodulin and IL-18 after discharge were associated with eGFR decline. After adjustment for age, RACHS-1 surgical complexity score, proteinuria, and eGFR at the 3-month study visit, lower concentrations of urine uromodulin and IL-18 were associated with a monthly decline in eGFR (uromodulin ß = 0.04 (95% CI: 0.00-0.09; p = 0.07) IL-18 ß = 0.07 (95% CI: 0.01-0.13; p = 0.04), ml/min/1.73 m2 per month). CONCLUSIONS: At 3 months after cardiac surgery, children with lower urine uromodulin and IL-18 concentrations experienced a significantly faster decline in eGFR. Children with cyanotic heart disease had a lower median eGFR at all time points but did not experience faster eGFR decline. A higher-resolution version of the Graphical abstract is available as Supplementary information.

Transplantation Mediates Much of the Racial Disparity in Survival from Childhood-Onset Kidney Failure.

BACKGROUND: The role of kidney transplantation in differential survival in Black and White patients with childhood-onset kidney failure is unexplored. METHODS: We analyzed 30-year cohort data of children beginning RRT before 18 years of age between January 1980 and December 2017 (n=28,337) in the US Renal Data System. Cox regression identified transplant factors associated with survival by race. The survival mediational g-formula estimated the excess mortality among Black patients that could be eliminated if an intervention equalized their time with a transplant to that of White patients. RESULTS: Black children comprised 24% of the cohort and their crude 30-year survival was 39% compared with 57% for White children (log rank P<0.001). Black children had 45% higher risk of death (adjusted hazard ratio [aHR], 1.45; 95% confidence interval [95% CI], 1.36 to 1.54), 31% lower incidence of first transplant (aHR, 0.69; 95% CI, 0.67 to 0.72), and 39% lower incidence of second transplant (aHR, 0.61; 95% CI, 0.57 to 0.65). Children and young adults are likely to require multiple transplants, yet even after their first transplant, Black patients had 11% fewer total transplants (adjusted incidence rate ratio [aIRR], 0.89; 95% CI, 0.86 to 0.92). In Black patients, grafts failed earlier after first and second transplants. Overall, Black patients spent 24% less of their RRT time with a transplant than did White patients (aIRR, 0.76; 95% CI, 0.74 to 0.78). Transplantation compared with dialysis strongly protected against death (aHR, 0.28; 95% CI, 0.16 to 0.48) by time-varying analysis. Mediation analyses estimated that equalizing transplant duration could prevent 35% (P<0.001) of excess deaths in Black patients. CONCLUSIONS: Equalizing time with a functioning transplant for Black patients may equalize survival of childhood-onset ESKD with White patients.

Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology.

BACKGROUND: Untargeted plasma metabolomic profiling combined with machine learning (ML) may lead to discovery of metabolic profiles that inform our understanding of pediatric CKD causes. We sought to identify metabolomic signatures in pediatric CKD based on diagnosis: FSGS, obstructive uropathy (OU), aplasia/dysplasia/hypoplasia (A/D/H), and reflux nephropathy (RN). METHODS: Untargeted metabolomic quantification (GC-MS/LC-MS, Metabolon) was performed on plasma from 702 Chronic Kidney Disease in Children study participants (n: FSGS=63, OU=122, A/D/H=109, and RN=86). Lasso regression was used for feature selection, adjusting for clinical covariates. Four methods were then applied to stratify significance: logistic regression, support vector machine, random forest, and extreme gradient boosting. ML training was performed on 80% total cohort subsets and validated on 20% holdout subsets. Important features were selected based on being significant in at least two of the four modeling approaches. We additionally performed pathway enrichment analysis to identify metabolic subpathways associated with CKD cause. RESULTS: ML models were evaluated on holdout subsets with receiver-operator and precision-recall area-under-the-curve, F1 score, and Matthews correlation coefficient. ML models outperformed no-skill prediction. Metabolomic profiles were identified based on cause. FSGS was associated with the sphingomyelin-ceramide axis. FSGS was also associated with individual plasmalogen metabolites and the subpathway. OU was associated with gut microbiome-derived histidine metabolites. CONCLUSION: ML models identified metabolomic signatures based on CKD cause. Using ML techniques in conjunction with traditional biostatistics, we demonstrated that sphingomyelin-ceramide and plasmalogen dysmetabolism are associated with FSGS and that gut microbiome-derived histidine metabolites are associated with OU.

Longitudinal TNFR1 and TNFR2 and Kidney Outcomes: Results from AASK and VA NEPHRON-D.

BACKGROUND: Higher baseline levels of soluble TNF receptors (TNFR1 and TNFR2) have been associated with progressive CKD. Whether longitudinal changes in these biomarkers of inflammation are also associated with worse kidney outcomes has been less studied. METHODS: We evaluated associations of longitudinal changes in TNFR1 and TNFR2 with ESKD in the African American Study of Kidney Disease and Hypertension (AASK; 38% female; 0% diabetes) and kidney function decline (first occurrence of ≥30 ml/min per 1.73 m2 or ≥50% eGFR decline if randomization eGFR ≥60 or <60 ml/min per 1.73 m2, respectively; ESKD) in the Veterans Affairs Nephropathy in Diabetes trial (VA NEPHRON-D; 99% male; 100% diabetes) using Cox models. Biomarkers were measured from samples collected at 0-, 12-, and 24-month visits for AASK (serum) and 0- and 12-month visits for VA NEPHRON-D (plasma). Biomarker slopes (AASK) were estimated using linear mixed-effects models. Covariates included sociodemographic/clinical factors, baseline biomarker level, and kidney function. RESULTS: There were 129 ESKD events over a median of 7.0 years in AASK (n=418) and 118 kidney function decline events over a median of 1.5 years in VA NEPHRON-D (n=754). In AASK, each 1 SD increase in TNFR1 and TNFR2 slope was associated with 2.98- and 1.87-fold higher risks of ESKD, respectively. In VA NEPHRON-D, each 1 SD increase in TNFR1 and TNFR2 was associated with 3.20- and 1.43-fold higher risks of kidney function decline, respectively. CONCLUSIONS: Among individuals with and without diabetes, longitudinal increases in TNFR1 and TNFR2 were each associated with progressive CKD, independent of initial biomarker level and kidney function.

Angiopoietins as Prognostic Markers for Future Kidney Disease and Heart Failure Events after Acute Kidney Injury.

BACKGROUND: The mechanisms underlying long-term sequelae after AKI remain unclear. Vessel instability, an early response to endothelial injury, may reflect a shared mechanism and early trigger for CKD and heart failure. METHODS: To investigate whether plasma angiopoietins, markers of vessel homeostasis, are associated with CKD progression and heart failure admissions after hospitalization in patients with and without AKI, we conducted a prospective cohort study to analyze the balance between angiopoietin-1 (Angpt-1), which maintains vessel stability, and angiopoietin-2 (Angpt-2), which increases vessel destabilization. Three months after discharge, we evaluated the associations between angiopoietins and development of the primary outcomes of CKD progression and heart failure and the secondary outcome of all-cause mortality 3 months after discharge or later. RESULTS: Median age for the 1503 participants was 65.8 years; 746 (50%) had AKI. Compared with the lowest quartile, the highest quartile of the Angpt-1:Angpt-2 ratio was associated with 72% lower risk of CKD progression (adjusted hazard ratio [aHR], 0.28; 95% confidence interval [CI], 0.15 to 0.51), 94% lower risk of heart failure (aHR, 0.06; 95% CI, 0.02 to 0.15), and 82% lower risk of mortality (aHR, 0.18; 95% CI, 0.09 to 0.35) for those with AKI. Among those without AKI, the highest quartile of Angpt-1:Angpt-2 ratio was associated with 71% lower risk of heart failure (aHR, 0.29; 95% CI, 0.12 to 0.69) and 68% less mortality (aHR, 0.32; 95% CI, 0.15 to 0.68). There were no associations with CKD progression. CONCLUSIONS: A higher Angpt-1:Angpt-2 ratio was strongly associated with less CKD progression, heart failure, and mortality in the setting of AKI.

A randomized controlled pilot trial of anakinra for hemodialysis inflammation.

Chronic inflammation is highly prevalent among patients receiving maintenance hemodialysis and is associated with morbidity and mortality. Inhibiting inflammation with anti-cytokine therapy has been proposed but not well studied in this population. Therefore, we conducted the ACTION trial, a pilot, multicenter, randomized, placebo-controlled trial of an IL-1 receptor antagonist, anakinra, to evaluate safety, tolerability, and feasibility, and explore efficacy. Eighty hemodialysis patients with plasma concentrations of high sensitivity C-reactive protein (hsCRP) 2 mg/L and above were randomized 1:1 to placebo or anakinra 100 mg, three times per week via the hemodialysis circuit for 24 weeks, with an additional 24 weeks of post-treatment safety monitoring. Efficacy outcomes included changes in hsCRP (primary), cytokines, and patient-reported outcomes. Rates of serious adverse events and deaths were similar with anakinra and placebo (serious adverse events: 2.71 vs 2.74 events/patient-year; deaths: 0.12 vs 0.22 events/patient-year). The rate of adverse events of interest (including infections and cytopenias) was significantly lower with anakinra than placebo (0.48 vs 1.40 events/patient-year). Feasibility was demonstrated by attaining the enrollment target, a retention rate of 80%, and administration of 72% of doses. The median decrease in hsCRP from baseline to Week 24 was 41% in the anakinra group and 6% in the placebo group, a between-group difference that was not statistically significant. For IL-6, the median decreases were significant: 25% and 0% in the anakinra and placebo groups, respectively. An effect of anakinra on patient-reported outcomes was not evident. Thus, anakinra was well tolerated and did not increase infections or cytopenias. The promising safety data and potential efficacy on CRP and IL-6 provide support for conducting definitive trials of IL-1 inhibition to improve outcomes in hemodialysis patients.

Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study.

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.