Glycolytic lactate in diabetic kidney disease.

Lactate elevation is a well-characterized biomarker of mitochondrial dysfunction, but its role in diabetic kidney disease (DKD) is not well defined. Urine lactate was measured in patients with type 2 diabetes (T2D) in 3 cohorts (HUNT3, SMART2D, CRIC). Urine and plasma lactate were measured during euglycemic and hyperglycemic clamps in participants with type 1 diabetes (T1D). Patients in the HUNT3 cohort with DKD had elevated urine lactate levels compared with age- and sex-matched controls. In patients in the SMART2D and CRIC cohorts, the third tertile of urine lactate/creatinine was associated with more rapid estimated glomerular filtration rate decline, relative to first tertile. Patients with T1D demonstrated a strong association between glucose and lactate in both plasma and urine. Glucose-stimulated lactate likely derives in part from proximal tubular cells, since lactate production was attenuated with sodium-glucose cotransporter-2 (SGLT2) inhibition in kidney sections and in SGLT2-deficient mice. Several glycolytic genes were elevated in human diabetic proximal tubules. Lactate levels above 2.5 mM potently inhibited mitochondrial oxidative phosphorylation in human proximal tubule (HK2) cells. We conclude that increased lactate production under diabetic conditions can contribute to mitochondrial dysfunction and become a feed-forward component to DKD pathogenesis.

Serum and Urine Metabolites and Kidney Function.

BACKGROUND: Metabolites represent a read-out of cellular processes underlying states of health and disease. METHODS: We evaluated cross-sectional and longitudinal associations between 1255 serum and 1398 urine known and unknown (denoted with "X" in name) metabolites (Metabolon HD4, 721 detected in both biofluids) and kidney function in 1612 participants of the Atherosclerosis Risk in Communities (ARIC) Study. All analyses were adjusted for clinical and demographic covariates, including for baseline eGFR and UACR in longitudinal analyses. RESULTS: At visit 5 of the ARIC study, the mean age of participants was 76 years (SD 6), 56% were women, mean eGFR was 62 ml/min/1.73m2 (SD 20), and median urine albumin-to-creatinine level (UACR) was 13 mg/g (IQR 25). In cross-sectional analysis, 675 serum and 542 urine metabolites were associated with eGFR (Bonferroni-corrected p < 4.0E-5 for serum analyses and p < 3.6E-5 for urine analyses), including 248 metabolites shared across biofluids. Fewer metabolites (75 serum and 91 urine metabolites, including 7 shared across biofluids) were cross-sectionally associated with albuminuria. Guanidinosuccinate, N2,N2-dimethylguanosine, hydroxy-N6,N6,N6-trimethyllysine, X-13844, and X-25422 were significantly associated with both eGFR and albuminuria. Over a mean follow-up of 6.6 years, serum mannose (HR 2.3 [1.6,3.2], p = 2.7E-5) and urine X-12117 (HR 1.7 [1.3,2.2], p = 1.9E-5) were risk factors for UACR doubling, whereas urine sebacate (HR 0.86 [0.80,0.92], p = 1.9E-5) was inversely associated. Compared to clinical characteristics alone, including the top 5 endogenous metabolites in serum and urine associated with longitudinal outcomes improved the outcome prediction (AUCs for eGFR decline: clinical model = 0.79, clinical + metabolites model = 0.87, p = 8.1E-6; for UACR doubling: clinical model = 0.66, clinical + metabolites model = 0.73, p = 2.9E-5). CONCLUSIONS: Metabolomic profiling in different biofluids provided distinct and potentially complementary insights into the biology and prognosis of kidney diseases.

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.

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.

Fibroblast Growth Factor 23 and Risk of Heart Failure Subtype: The CRIC (Chronic Renal Insufficiency Cohort) Study.

Rationale & Objective: Heart failure (HF) is an important cause of morbidity and mortality among individuals with chronic kidney disease (CKD). A large body of evidence from preclinical and clinical studies implicates excess levels of fibroblast growth factor 23 (FGF23) in HF pathogenesis in CKD. It remains unclear whether the relationship between elevated FGF23 levels and HF risk among individuals with CKD varies by HF subtype. Study Design: Prospective cohort study. Settings & Participants: A total of 3,502 participants were selected in the Chronic Renal Insufficiency Cohort study. Exposure: Baseline plasma FGF23. Outcomes: Incident HF by subtype and total rate of HF hospitalization. HF was categorized as HF with preserved ejection fraction (HFpEF, ejection fraction [EF] ≥ 50%), HF with reduced EF (HFrEF, EF < 50%) and HF with unknown EF (HFuEF). Analytical Approach: Multivariable-adjusted cause-specific Cox proportional hazards models were used to investigate associations between FGF23 and incident hospitalizations for HF by subtype. The Lunn-McNeil method was used to compare hazard ratios across HF subtypes. Poisson regression models were used to evaluate the total rate of HF. Results: During a median follow-up time of 10.8 years, 295 HFpEF, 242 HFrEF, and 156 HFuEF hospitalizations occurred. In multivariable-adjusted cause-specific Cox proportional hazards models, FGF23 was significantly associated with the incidence of HFpEF (HR, 1.41; 95% CI, 1.21-1.64), HFrEF (HR, 1.27; 95% CI, 1.05-1.53), and HFuEF (HR, 1.40; 95% CI, 1.13-1.73) per 1 standard deviation (SD) increase in the natural log of FGF23. The Lunn-McNeil method determined that the risk association was consistent across all subtypes. The rate ratio of total HF events increased with FGF23 quartile. In multivariable-adjusted models, compared with quartile 1, FGF23 quartile 4 had a rate ratio of 1.81 (95% CI, 1.28-2.57) for total HF events. Limitations: Self-report of HF hospitalizations and possible lack of an echocardiogram at time of hospitalization. Conclusions: In this large multicenter prospective cohort study, elevated FGF23 levels were associated with increased risks for all HF subtypes. Plain-Language Summary: Heart failure (HF) is a prominent cause of morbidity and mortality in individuals with chronic kidney disease (CKD). Identifying potential pathways in the development of HF is essential in developing therapies to prevent and treat HF. In a large cohort of individuals with CKD, the Chronic Renal Insufficiency Cohort (N = 3,502), baseline fibroblast growth factor-23 (FGF23), a hormone that regulates phosphorous, was evaluated in relation to the development of incident and recurrent HF with reduced, preserved, and unknown ejection fraction. In this large multicenter prospective cohort study, elevated FGF23 levels were associated with increased risk of all HF subtypes. These findings demonstrate the need for further research into FGF23 as a target in preventing the development of HF in individuals with CKD.

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.

Regional Variation in Hemoglobin Distribution Among Individuals With CKD: the ISN International Network of CKD Cohorts.

Introduction: Despite recognized geographic and sex-based differences in hemoglobin in the general population, these factors are typically ignored in patients with chronic kidney disease (CKD) in whom a single therapeutic range for hemoglobin is recommended. We sought to compare the distribution of hemoglobin across international nondialysis CKD populations and evaluate predictors of hemoglobin. Methods: In this cross-sectional study, hemoglobin distribution was evaluated in each cohort overall and stratified by sex and estimated glomerular filtration rate (eGFR). Relationships between candidate predictors and hemoglobin were assessed from linear regression models in each cohort. Estimates were subsequently pooled in a random effects model. Results: A total of 58,613 participants from 21 adult cohorts (median eGFR range of 17-49 ml/min) and 3 pediatric cohorts (median eGFR range of 26-45 ml/min) were included with broad geographic representation. Hemoglobin values varied substantially among the cohorts, overall and within eGFR categories, with particularly low mean hemoglobin observed in women from Asian and African cohorts. Across the eGFR range, women had a lower hemoglobin compared to men, even at an eGFR of 15 ml/min (mean difference 5.3 g/l, 95% confidence interval [CI] 3.7-6.9). Lower eGFR, female sex, older age, lower body mass index, and diabetic kidney disease were all independent predictors of a lower hemoglobin value; however, this only explained a minority of variance (R2 7%-44% across cohorts). Conclusion: There are substantial regional differences in hemoglobin distribution among individuals with CKD, and the majority of variance is unexplained by demographics, eGFR, or comorbidities. These findings call for a renewed interest in improving our understanding of hemoglobin determinants in specific CKD populations.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Role of endogenous adenine in kidney failure and mortality with diabetes.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Vitamin D Metabolites and Risk of Cardiovascular Disease in Chronic Kidney Disease: The CRIC Study.

Background The ratio of 24,25-dihydroxyvitamin D3/25-hydroxyvitamin D3 (vitamin D metabolite ratio [VDMR]) may reflect functional vitamin D activity. We examined associations of the VDMR, 25-hydroxyvitamin D (25[OH]D), and 1,25-dihydroxyvitamin D (1,25[OH]2D) with cardiovascular disease (CVD) in patients with chronic kidney disease. Methods and Results This study included longitudinal and cross-sectional analyses of 1786 participants from the CRIC (Chronic Renal Insufficiency Cohort) Study. Serum 24,25-dihydroxyvitamin D3, 25(OH)D, and 1,25(OH)2D were measured by liquid chromatography-tandem mass spectrometry 1 year after enrollment. The primary outcome was composite CVD (heart failure, myocardial infarction, stroke, and peripheral arterial disease). We used Cox regression with regression-calibrated weights to test associations of the VDMR, 25(OH)D, and 1,25(OH)2D with incident CVD. We examined cross-sectional associations of these metabolites with left ventricular mass index using linear regression. Analytic models adjusted for demographics, comorbidity, medications, estimated glomerular filtration rate, and proteinuria. The cohort was 42% non-Hispanic White race and ethnicity, 42% non-Hispanic Black race and ethnicity, and 12% Hispanic ethnicity. Mean age was 59 years, and 43% were women. Among 1066 participants without prevalent CVD, there were 298 composite first CVD events over a mean follow-up of 8.6 years. Lower VDMR and 1,25(OH)2D were associated with incident CVD before, but not after, adjustment for estimated glomerular filtration rate and proteinuria (hazard ratio, 1.11 per 1 SD lower VDMR [95% CI, 0.95-1.31]). Only 25(OH)D was associated with left ventricular mass index after full covariate adjustment (0.6 g/m2.7 per 10 ng/mL lower [95% CI, 0.0-1.3]). Conclusions Despite modest associations of 25(OH)D with left ventricular mass index, 25(OH)D, the VDMR, and 1,25(OH)2D were not associated with incident CVD in chronic kidney disease.

Association of Vitamin K Status with Arterial Calcification and Stiffness in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort.

Background: Arterial calcification and stiffness are common in people with chronic kidney disease (CKD). Higher vitamin K status has been associated with less arterial calcification and stiffness in CKD in cross-sectional studies. Objectives: To determine the association of vitamin K status with coronary artery calcium (CAC) and arterial stiffness [pulse wave velocity (PWV)] at baseline and over 2-4 follow-up years in adults with mild-to-moderate CKD. Methods: Participants (n = 2722) were drawn from the well-characterized Chronic Renal Insufficiency Cohort. Two vitamin K status biomarkers, plasma phylloquinone and plasma dephospho-uncarboxylated matrix gla protein [(dp)ucMGP], were measured at baseline. CAC and PWV were measured at baseline and over 2-4 y of follow-up. Differences across vitamin K status categories in CAC prevalence, incidence, and progression (defined as ≥100 Agatston units/y increase) and PWV at baseline and over follow-up were evaluated using multivariable-adjusted generalized linear models. Results: CAC prevalence, incidence, and progression did not differ across plasma phylloquinone categories. Moreover, CAC prevalence and incidence did not differ according to plasma (dp)ucMGP concentration. Compared with participants with the highest (dp)ucMGP (≥450 pmol/L), those in the middle category (300-449 pmol/L) had a 49% lower rate of CAC progression (incidence rate ratio: 0.51; 95% CI: 0.33, 0.78). However, CAC progression did not differ between those with the lowest (<300 pmol/L) and those with the highest plasma (dp)ucMGP concentration (incidence rate ratio: 0.82; 95% CI: 0.56, 1.19). Neither vitamin K status biomarker was associated with PWV at baseline or longitudinally. Conclusions: Vitamin K status was not consistently associated with CAC or PWV in adults with mild-to-moderate CKD.

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.

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.

Low concentrations of medium-sized HDL particles predict incident CVD in chronic kidney disease patients.

Patients with chronic kidney disease (CKD) are at high risk for CVD. However, traditional CVD risk factors cannot completely explain the increased risk. Altered HDL proteome is linked with incident CVD in CKD patients, but it is unclear whether other HDL metrics are associated with incident CVD in this population. In the current study, we analyzed samples from two independent prospective case-control cohorts of CKD patients, the Clinical Phenotyping and Resource Biobank Core (CPROBE) and the Chronic Renal Insufficiency Cohort (CRIC). We measured HDL particle sizes and concentrations (HDL-P) by calibrated ion mobility analysis and HDL cholesterol efflux capacity (CEC) by cAMP-stimulated J774 macrophages in 92 subjects from the CPROBE cohort (46 CVD and 46 controls) and in 91 subjects from the CRIC cohort (34 CVD and 57 controls). We tested associations of HDL metrics with incident CVD using logistic regression analysis. No significant associations were found for HDL-C or HDL-CEC in either cohort. Total HDL-P was only negatively associated with incident CVD in the CRIC cohort in unadjusted analysis. Among the six sized HDL subspecies, only medium-sized HDL-P was significantly and negatively associated with incident CVD in both cohorts after adjusting for clinical confounders and lipid risk factors with odds ratios (per 1-SD) of 0.45 (0.22-0.93, P = 0.032) and 0.42 (0.20-0.87, P = 0.019) for CPROBE and CRIC cohorts, respectively. Our observations indicate that medium-sized HDL-P-but not other-sized HDL-P or total HDL-P, HDL-C, or HDL-CEC-may be a prognostic cardiovascular risk marker in CKD.

Excess risk of cardiovascular events in patients in the United States vs. Japan with chronic kidney disease is mediated mainly by left ventricular structure and function.

While patients receiving dialysis therapy in the United States are more likely to develop cardiovascular disease (CVD) than those in Japan, direct comparisons of patients with predialysis chronic kidney disease (CKD) are rare. To study this, we compared various outcomes in patients with predialysis CKD using data from the Chronic Renal Insufficiency Cohort (CRIC) and CKD Japan Cohort (CKD-JAC) studies and determined mediators of any differences. Candidate mediators included left ventricular (LV) indices assessed by echocardiography. Among 3125 CRIC and 1097 CKD-JAC participants, the mean LV mass index (LVMI) and ejection fraction (EF) were 55.7 and 46.6 g/m2 and 54% and 65%, respectively (both significant). The difference in body mass index (32 and 24 kg/m2, respectively) largely accounted for the differences in LVMI and C-reactive protein levels across cohorts. Low EF and high LVMI were significantly associated with subsequent CVD in both cohorts. During a median follow-up of five years, CRIC participants were at higher risk for CVD (adjusted hazard ratio [95% confidence interval]: 3.66 [2.74-4.89]) and death (4.69 [3.05-7.19]). A three-fold higher C-reactive protein concentration and higher phosphate levels in the United States cohort were moderately strong mediators of the differences in CVD. However, echocardiographic parameters were stronger mediators than these laboratory measures. LVMI, EF and their combination mediated the observed difference in CVD (27%, 50%, and 57%, respectively) and congestive heart failure (33%, 62%, and 70%, respectively). Thus, higher LV mass and lower EF, even in the normal range, were found to be predictive of CVD in CKD.

Analytical and Biological Variability of a Commercial Modified Aptamer Assay in Plasma Samples of Patients with Chronic Kidney Disease.

BACKGROUND: We carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD). METHODS: Plasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic. We also measured correlations of aptamer measurements with traditional biomarker assays. RESULTS: A total of 4656 unique proteins (4849 total aptamer measures) were analyzed in all samples. Median (interquartile range [IQR] intra-assay CV) was 3.7% (2.8-5.3) in CRIC and 5.0% (3.8-7.0) in Brigham samples. Median (IQR) biological CV among Brigham samples drawn from one individual on 2 occasions separated by median (IQR) 7 (4-14) days was 8.7% (6.2-14). CVs were independent of CKD stage, diabetes, or albuminuria but were higher in patients with systemic lupus erythematosus. Rho correlations between aptamer and traditional assays for biomarkers of interest were cystatin C = 0.942, kidney injury model-1 = 0.905, fibroblast growth factor-23 = 0.541, tumor necrosis factor receptors 1 = 0.781 and 2 = 0.843, P < 10-100 for all. CONCLUSIONS: Intra-assay and within-subject variability for SomaScan in the CKD setting was low and similar to assay variability reported from individuals without CKD. Intra-assay precision was excellent whether samples were collected in an optimal research protocol, as were CRIC samples, or in the clinical setting, as were the Brigham samples.