Visual Abstract
Keywords: endothelial dysfunction, chronic inflammation, oxidative stress, chronic kidney disease, sodium nitrite, isoquercetin
Abstract
Background and objectives
Endothelial dysfunction is common among patients with CKD. We tested the efficacy and safety of combination treatment with sodium nitrite and isoquercetin on biomarkers of endothelial dysfunction in patients with CKD.
Design, setting, participants, & measurements
This randomized, double-blind, placebo-controlled phase 2 pilot trial enrolled 70 patients with predialysis CKD. Thirty-five were randomly assigned to combination treatment with sodium nitrite (40 mg twice daily) and isoquercetin (225 mg once daily) for 12 weeks, and 35 were randomly assigned to placebo. The primary outcome was mean change in flow-mediated vasodilation over the 12-week intervention. Secondary and safety outcomes included biomarkers of endothelial dysfunction, inflammation, and oxidative stress as well as kidney function, methemoglobin, and adverse events. Intention-to-treat analysis was conducted.
Results
Baseline characteristics, including age, sex, race, cigarette smoking, history of hypertension and diabetes, use of renin-angiotensin system blockers, BP, fasting glucose, lipid profile, kidney function, urine albumin-creatinine ratio, and endothelial biomarkers, were comparable between groups. Over the 12-week intervention, flow-mediated vasodilation increased 1.1% (95% confidence interval, −0.1 to 2.3) in the treatment group and 0.3% (95% confidence interval, −0.9 to 1.5) in the placebo group, and net change was 0.8% (95% confidence interval, −0.9 to 2.5). In addition, changes in biomarkers of endothelial dysfunction (vascular adhesion molecule-1, intercellular adhesion molecule-1, E-selectin, vWf, endostatin, and asymmetric dimethylarginine), inflammation (TNF-α, IL-6, C-reactive protein, IL-1 receptor antagonist, and monocyte chemoattractant protein-1), and oxidative stress (oxidized LDL and nitrotyrosines) were not significantly different between the two groups. Furthermore, changes in eGFR, urine albumin-creatinine ratio, methemoglobin, and adverse events were not significantly different between groups.
Conclusions
This randomized phase 2 pilot trial suggests that combination treatment with sodium nitrite and isoquercetin did not significantly improve flow-mediated vasodilation or other endothelial function biomarkers but also did not increase adverse events compared with placebo among patients with CKD.
Clinical Trial registry name and registration number:
Nitrite, Isoquercetin, and Endothelial Dysfunction (NICE), NCT02552888
Introduction
CKD is highly prevalent in the United States and globally (1,2). Cardiovascular disease and kidney failure are major causes of premature death in patients with CKD (3–6). Endothelial dysfunction, inflammation, and oxidative stress are common among patients with CKD (7–11). Nitric oxide deficiency may be a key component of endothelial dysfunction in CKD and contribute to both CKD and cardiovascular disease progression (7,12–14). For instance, nitric oxide synthetase inhibitor (asymmetric dimethylarginine) was elevated in patients with CKD compared with patients without CKD (7), and every 0.1 μmol/L higher asymmetric dimethylarginine was associated with a 47% higher risk of CKD progression (13). Additionally, 0.25-μmol/L higher asymmetric dimethylarginine was associated with a 19% higher risk for cardiovascular disease mortality in patients with CKD (14). Moreover, endothelial dysfunction, inflammation, oxidative stress, CKD, and cardiovascular disease can form a vicious cycle (15,16). Previous studies suggest that sodium nitrite provides exogenous nitric oxide and may improve endothelial function (17,18). Intravenous administration of sodium nitrite (8.7 μmol/min) dilated the radial artery by 10.7% under normal oxygenated conditions in healthy men and dose-dependently increased cyclic guanosine monophosphate production (18). Dietary isoquercetin (a natural flavonoid) reduces inflammation and oxidative stress (19,20). A randomized trial reported that quercetin-3-glucoside (160 mg/d) significantly reduced E-selectin by 27.7 ng/ml and IL-1β by 20.2 pg/ml in 37 individuals who were hypertensive or prehypertensive (19). Quercetin reduced systolic BP and plasma oxidized LDL concentrations (LDL) in overweight subjects in a clinical trial (20). Given the potential for oxidative stress to rapidly inactivate nitric oxide (21,22), combination treatment with a nitric oxide donor and antioxidant may synergistically improve endothelial dysfunction. The overall objective of this trial was to test the efficacy and safety of combination treatment with sodium nitrite and isoquercetin on biomarkers of endothelial function, inflammation, and oxidative stress among patients with CKD.
Materials and Methods
Study Participants
The Nitrite, Isoquercetin, and Endothelial Dysfunction (NICE) trial enrolled 70 patients with stages 1–5 CKD in the greater New Orleans area, Louisiana (Figure 1). Recruitment started in March 2016, and follow-up finished in June 2017. Participants were identified through electronic medical record searches and provider referrals. Main eligibility criteria included men and women aged 21–74 years of any races/ethnicities with predialysis CKD defined as an eGFR<60 ml/min per 1.73 m2 or urine albumin-creatinine ratio (UACR) ≥30 mg/g or protein-creatinine ratio ≥150 mg/g with eGFR>60 ml/min per 1.73 m2. The detailed inclusion and exclusion criteria are presented in Supplemental Table 1. The NICE trial was approved by institutional review boards at participating institutions. Written informed consent was obtained from all participants. The study was registered on ClinicalTrials.gov (NCT02552888). An Investigational New Drug application (127397) was approved by the Food and Drug Administration (FDA).
Figure 1.
Study participant flow diagram.
Randomization and Blinding
Eligible participants were randomly assigned to treatment or placebo groups using a block randomization method with a random block size of two to six. Thirty-five were randomized to the treatment group, and 35 were randomized to the placebo group. The randomization allocation was prepared by a statistician using SAS statistical software and concealed in sealed envelopes that were opened only by the study pharmacist, who dispensed the study drugs per allocation assignment. Neither statistician nor pharmacist were involved in the trial’s clinical operations. Active medications, placebos, and drug accountability logs were kept in the research pharmacy at Tulane Health System.
Study participants, study staff, investigators, ultrasound technicians, and laboratory technicians were all blinded to treatment assignments.
Intervention
The participants in the intervention group took oral immediate-release sodium nitrite (40 mg twice daily) and isoquercetin (225 mg once daily) at least 30 minutes before eating, and the participants in the control group took identical placebos, each for 12 weeks. Previous studies showed that 40 mg sodium nitrite did not increase methemoglobin levels compared with placebo (23). The FDA approved isoquercetin as “Generally Recognized As Safe” with an acceptable daily intake of 293 mg. TheraVasc Inc. supplied the sodium nitrite and placebos. Quercegen Pharmaceuticals supplied isoquercetin and placebos.
Study Outcomes and Measurements
The primary outcome was the difference in mean change of endothelium-dependent flow-mediated vasodilation (FMD) between the two groups over a 12-week intervention. FMD was measured using high-resolution ultrasound of the brachial artery at baseline, 6 weeks, and 12 weeks using a standard protocol (24). In brief, participants were required to fast for 10 hours and rest for 15 minutes prior to examination. Digitized images of the right brachial artery diameter were captured continuously for 1 minute before application of the cuff and every 60 seconds after cuff deflation for 5 minutes. Images were analyzed at the University of Pennsylvania Vascular Center. An FDA-approved software (Vascular Tools 6; Medical Imaging Applications, LLC, Iowa City, IA) was used to analyze electrocardiogram-gated brachial artery diameters. FMD was expressed as percentage change of brachial artery diameter from baseline.
Secondary outcomes included net changes in biomarkers of endothelial dysfunction (vascular adhesion molecule-1, intercellular adhesion molecule-1, E-selectin, vWf, endothelin-1, endostatin, asymmetric dimethylarginine, and urine EGF), inflammation (serum C-reactive protein, TNF-α, IL-6, IL-10, IL-17, IL-1β, IL-18, IL-1 receptor antagonist, and monocyte chemoattractant protein-1), and oxidative stress (plasma oxidized LDL and serum nitrotyrosine). ELISAs were used to measure E-selectin R&D Systems, Minneapolis, MN), urine EGF (R&D Systems), vWf (RayBiotech, Peachtree Corners, GA), asymmetric dimethylarginine (DLD Diagnostika, Hamburg, Germany), oxidized LDL (LifeSpan Biosciences, Seattle, WA), and nitrotyrosine (LifeSpan Biosciences). All ELISA intra-assay coefficients of variation (CVs) were <10%. Intercellular adhesion molecule-1, vascular adhesion molecule-1, endothelin-1, endostatin, C-reactive protein, TNF-α, IL-6, IL-10, IL-17, IL-1β, IL-18, IL-1 receptor antagonist, and monocyte chemoattractant protein-1 were measured using Meso Scale Discovery (MSD) methods. MSD assays are multiplex sandwich immunoassays that utilize an electrochemiluminescence-based detection system. All assays were conducted per manufacturers’ specifications (MSD, Rockville, MD) with intra-assay CVs <10%.
Serum creatinine, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, complete blood cell count, whole-blood methemoglobin, plasma isoquercetin, and UACR were measured in the clinical laboratory of Tulane Health System. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation (25). Plasma nitrite and nitrate levels were measured by Griess reagent using the total nitric oxide and nitrate/nitrate assay. The intra-assay CVs were 2.3% for nitrate and 12.0% for nitrite. Quercetin levels were determined by high-performance liquid chromatography at Appalachian State University, North Carolina, with an intra-assay CV of 12.5% (26).
All biomarkers were measured at baseline, 6 weeks, and 12 weeks, except the lipid panel (measured at baseline and 12 weeks). BP was measured using the OMRON HEM-907 XL BP Monitor per standard protocol by trained and certified research staff.
Patient Safety
Safety parameters (medical history, concomitant medication use, side effects, BP, pulse, complete blood cell count, methemoglobin, adverse events [AEs], and serious AEs [SAEs]) were assessed using standard methods at baseline, 6-week, and 12-week visits. AEs and SAEs were assessed by questionnaires at each visit. Participants were advised to call the study nurse if they had any side effects, emergency room visits, or hospitalizations at any time. The medical records of SAEs were obtained and reviewed to determine if it was study related. Medical records of AEs were also obtained as needed when the etiology was unclear. SAEs and safety concerns were reported to the Data and Safety Monitoring Board. The site clinician reviewed the safety parameters and determined whether results should be sent to a participant’s physician for further evaluation or whether the intervention should be modified.
Drug Adherence
Nitrite, nitrate, and isoquercetin levels were also measured for the purpose of assessing adherence. Participants were instructed to return unused study medications at each study visit. Treatment adherence was calculated as the percentage of capsules/tablets taken by participants.
Statistical Analyses
The NICE trial was designed to have 80% statistical power to detect a net change of 2.8% FMD between treatment and placebo groups at a two-sided significance level of 0.05 (27,28). Net change in FMD was calculated as the mean difference (active treatment minus placebo) of the change from baseline to 12 weeks. The power calculation was on the basis of an average of three repeated measurements, a correlation between FMD measures over time of 0.55, and an SD of 4.6%. The estimates of SD and correlation between repeated measurement of FMD were from 201 patients with CKD in an observational study (7).
Baseline characteristics are reported as mean (SD) or median (interquartile range) for continuous variables and as percentage for categorical variables. Intention-to-treat analysis was conducted on all patients per their randomization allocation. Outcomes were defined as mean changes at 6 and 12 weeks from baseline values. For variables with skewed distribution, the log transformation was used, and mean changes in log-transformed values were calculated. Linear mixed effects models were used to assess treatment effects, where intercepts and slopes were assumed to be random effects and treatment group was assumed to be a fixed effect. A post hoc subgroup analysis by baseline eGFR was conducted and adjusted for imbalanced baseline outcome values. The level of significance was set at P<0.05 for a two-sided test. All analyses were performed using SAS software, version 9.4 (SAS Institute Inc., Cary, NC).
Results
Among 70 participants with eGFR ranging from 12 to 105 ml/min per 1.73 m2, 68 (97%) completed the trial (Figure 1). Baseline characteristics of study participants are presented in Table 1. Demographic and clinical characteristics were comparable between the two groups. Baseline FMD was lower, whereas nitrotyrosine levels were higher, in the treatment group compared with the placebo group.
Table 1.
Baseline characteristics of study participants by treatment allocation
| Characteristics | Treatment, n=35 | Placebo, n=35 |
|---|---|---|
| Age, mean (SD), yr | 61 (10) | 62 (10) |
| Women, no. (%) | 13 (37%) | 13 (37%) |
| Race, no. (%) | ||
| White | 16 (46%) | 20 (57%) |
| Black | 17 (49%) | 15 (43%) |
| Other | 2 (6%) | 0 (0%) |
| High school graduates, no. (%) | 33 (94%) | 33 (94%) |
| Physical activity, ≥3 times per week, no. (%) | 19 (54%) | 22 (63%) |
| Ever smoker, no. (%) | 12 (34%) | 11 (31%) |
| Current drinking, no. (%) | 11 (31%) | 9 (26%) |
| History of cardiovascular disease, no. (%) | 5 (14%) | 6 (17%) |
| History of hypertension, no. (%) | 32 (91%) | 34 (97%) |
| History of diabetes, no. (%) | 21 (60%) | 23 (66%) |
| Body mass index, mean (SD), kg/m2 | 30.5 (5.6) | 32.9 (5.7) |
| Systolic BP, mean (SD), mm Hg | 129 (15) | 129 (15) |
| Diastolic BP, mean (SD), mm Hg | 73 (7) | 75 (11) |
| Fasting plasma glucose, mean (SD), mg/dl | 119 (44) | 124 (70) |
| Total cholesterol, mean (SD), mg/dl | 178 (43) | 171 (50) |
| HDL cholesterol, mean (SD), mg/dl | 48 (13) | 47 (14) |
| LDL cholesterol, mean (SD), mg/dl | 107 (34) | 100 (37) |
| Triglycerides, median (IQR), mg/dl | 116 (84–161) | 118 (75–194) |
| Bicarbonate, mean (SD), mEq/L | 27 (3) | 28 (3) |
| Hemoglobin, mean (SD), g/dl | 13.0 (1.7) | 13.2 (2.0) |
| White blood cell count, mean (SD), 109/L | 6.3 (1.9) | 6.6 (1.7) |
| eGFR, mean (SD), ml/min per 1.73 m2 | 51 (22) | 45 (16) |
| Urine albumin-creatinine ratio, median (IQR), mg/g | 22 (9–456) | 52 (28–472) |
| Use of ACE inhibitor or ARB, no. (%) | 33 (94%) | 35 (100%) |
| Use of aspirin, no. (%) | 12 (34%) | 13 (37%) |
| Use of statin, no. (%) | 22 (63%) | 19 (54%) |
| Flow-mediated vasodilation, mean (SD), % | 4.1 (3.9) | 5.8 (3.3) |
| Vascular adhesion molecule-1, mean (SD), ng/ml | 560 (150) | 626 (221) |
| Intercellular adhesion molecule-1, median (IQR), ng/ml | 452 (410–540) | 482 (399–599) |
| E-selectin, mean (SD), ng/ml | 43.5 (15.9) | 49.1 (24.2) |
| vWf, median (IQR), ng/ml | 26,396 (18,320–37,531) | 23,662 (13,682–33,958) |
| Endothelin-1, mean (SD), pg/ml | 4.2 (1.7) | 5.1 (4.9) |
| Endostatin, median (IQR), ng/ml | 129 (101–210) | 161 (112–211) |
| Asymmetric dimethylarginine, mean (SD), μmol/L | 0.58 (0.13) | 0.60 (0.15) |
| Urine EGF-creatinine ratio, median (IQR), pg/g | 52 (30–113) | 39 (19–89) |
| TNF-α, mean (SD), pg/ml | 1.6 (0.8) | 1.9 (1.2) |
| IL-6, median (IQR), pg/ml | 0.54 (0.29–1.18) | 0.63 (0.39–1.06) |
| C-reactive protein, mean (SD), mg/L | 2.7 (0.2) | 2.9 (0.2) |
| IL-1β, mean (SD), pg/ml | 0.09 (0.03) | 0.09 (0.04) |
| IL-17, mean (SD), pg/ml | 2.1 (4.1) | 2.0 (2.0) |
| IL-18, median (IQR), pg/ml | 458 (353–684) | 514 (440–739) |
| IL-10, mean (SD), pg/ml | 1.1 (0.1) | 1.1 (0.2) |
| IL-1 receptor antagonist, median (IQR), pg/ml | 266 (186–353) | 256 (176–422) |
| Monocyte chemoattractant protein-1, mean (SD), pg/ml | 263 (95.1) | 264 (92.8) |
| Oxidized LDL, mean (SD), ng/ml | 31.0 (9.99) | 28.6 (6.2) |
| Nitrotyrosine, median (IQR), pg/ml | 2222 (1908–2703) | 2071 (1854–2212) |
IQR, interquartile range; ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker.
Efficacy of Treatment
Over the 12-week intervention, FMD increased 1.1% (95% confidence interval [95% CI], −0.1 to 2.3) in treatment and 0.3% (95% CI, −0.9 to 1.5) in placebo. The net change was 0.8% (95% CI, −0.9 to 2.5) (Table 2). Likewise, the differences in mean changes of biomarkers of endothelial dysfunction (vascular adhesion molecule-1, intercellular adhesion molecule-1, E-selectin, vWf, endothelin-1, endostatin, asymmetric dimethylarginine, and urine EGF-creatinine ratio), inflammation (TNF-α, C-reactive protein, IL-1β, IL-6, IL-10, IL-17, IL-18, IL-1 receptor antagonist, and monocyte chemoattractant protein-1), and oxidation (oxidized LDL and nitrotyrosine) were not statistically significantly different.
Table 2.
Mean changes of primary, secondary, and other outcomes over the 12-week intervention by treatment allocation
| Outcomes | Mean Changes over 12 wk (95% Confidence Interval) | Difference in Mean Changes (95% Confidence Interval) | |
|---|---|---|---|
| Treatment, n=35 | Placebo, n=35 | ||
| Primary outcomes | |||
| Flow-mediated vasodilation, % | 1.1 (−0.1 to 2.3) | 0.3 (−0.9 to 1.5) | 0.8 (−0.9 to 2.5) |
| Secondary outcomes | |||
| Endothelial dysfunction biomarkers | |||
| Vascular adhesion molecule-1, ng/ml | −22.2 (−49.3 to 5.0) | −10.8 (−37.5 to 15.9) | −11.3 (−49.3 to 26.6) |
| Intercellular adhesion molecule-1, ng/ml | −16.1 (−41.5 to 9.3) | −4.0 (−29.0 to 21.0) | −12.1 (−47.7 to 23.5) |
| E-selectin, ng/ml | −0.32 (−3.14 to 2.50) | 1.06 (−1.73 to 3.84) | −1.37 (−5.22 to 2.48) |
| vWf, ng/ml | −683 (−3784 to 2419) | 2744 (−328 to 5815) | −3426 (−6925 to 72) |
| Endothelin-1, pg/ml | 0.44 (−0.15 to 1.04) | −0.19 (−0.78 to 0.40) | 0.63 (−0.16 to 1.42) |
| Log-transformed endostatin, ng/ml | −0.02 (−0.08 to 0.05) | −0.01 (−0.08 to 0.05) | −0.00 (−0.10 to 0.09) |
| Asymmetric dimethylarginine, μmol/L | 0.03 (−0.02 to 0.08) | 0.02 (−0.03 to 0.07) | 0.01 (−0.05 to 0.08) |
| Log-transformed EGF-creatinine ratio, pg/g | −0.01 (−0.39 to 0.37) | 0.23 (−0.14 to 0.61) | −0.24 (−0.78 to 0.29) |
| Inflammatory biomarkers | |||
| TNF-α, pg/ml | −0.04 (−0.20 to 0.12) | −0.04 (−0.20 to 0.12) | 0.00 (−0.23 to 0.23) |
| Log-transformed IL-6, pg/ml | 0.07 (−0.06 to 0.20) | −0.17 (−0.30 to -0.04) | 0.24 (0.06 to 0.42) |
| C-reactive protein, mg/L | 0.05 (−0.31 to 0.42) | −0.02 (−0.38 to 0.33) | 0.08 (−0.43 to 0.58) |
| IL-1β, pg/ml | −0.00 (−0.01 to 0.01) | −0.01 (−0.02 to 0.00) | 0.01 (−0.01 to 0.02) |
| IL-17, pg/ml | −0.72 (−1.80 to 0.36) | 0.01 (−1.05 to 1.08) | −0.73 (−2.22 to 0.76) |
| IL-18, pg/ml | −6.3 (−42.7 to 30.0) | 33.4 (−2.2 to 69.1) | −39.8 (−90.2 to 10.6) |
| IL-10, pg/ml | −0.01 (−0.08 to 0.05) | −0.01 (−0.08 to 0.05) | 0.00 (−0.09 to 0.09) |
| IL-1 receptor antagonist, pg/ml | −17.1 (−77.5 to 43.4) | −30.5 (−90.0 to 29.0) | 13.5 (−71.2 to 98.2) |
| Monocyte chemoattractant protein-1, pg/ml | −6.0 (−25.0 to 13.0) | 0.6 (−18.0 to 19.3) | −6.6 (−33.3 to 20.0) |
| Oxidative biomarkers | |||
| Oxidized LDL, ng/ml | −1.7 (−3.9 to 0.5) | −0.3 (−2.4 to 1.9) | −1.4 (−4.5 to 1.6) |
| Nitrotyrosine, pg/ml | −10.9 (−96.9 to 75.2) | 62.2 (−22.6 to 147.0) | −73.1 (−192.3 to 46.1) |
| Other outcomes | |||
| eGFR, ml/min per 1.73 m2 | 0.1 (−2.3 to 2.5) | 0.2 (−2.2 to 2.6) | −0.1 (−3.4 to 3.1) |
| Log-transformed albumin-creatinine ratio, mg/g | 0.04 (−0.27 to 0.36) | 0.02 (−0.29 to 0.33) | 0.02 (−0.41 to 0.46) |
| Systolic BP, mm Hg | −2.2 (−6.8 to 2.4) | −0.7 (−5.3 to 3.8) | −1.5 (−7.7 to 4.8) |
| Diastolic BP, mm Hg | −2.5 (−5.0 to −0.1) | 0.1 (−2.3 to 2.6) | −2.7 (−6.1 to 0.8) |
| Total cholesterol, mg/dl | −1.6 (−10.5 to 7.2) | 3.9 (−4.9 to 12.8) | −5.6 (−18.1 to 6.9) |
| LDL cholesterol, mg/dl | −1.9 (−7.4 to 3.7) | 0.9 (−4.6 to 6.5) | −2.8 (−10.6 to 5.1) |
| HDL cholesterol, mg/dl | 0.9 (−1.7 to 3.4) | 2.2 (−0.4 to 4.7) | −1.3 (−4.9 to 2.4) |
| Log-transformed triglyceride, mg/dl | −0.09 (−0.21 to 0.04) | −0.01 (−0.14 to 0.11) | −0.08 (−0.25 to 0.10) |
Mean changes in eGFR, UACR, BP, and lipids were not significantly different between treatment and placebo groups (Table 2).
Post Hoc Subgroup Analysis by Baseline Estimated Glomerular Filtration Rate
Given that the dose of combination treatment may be more effective among patients with earlier-stage CKD who have less severe nitric oxide deficiency, we conducted a post hoc analysis stratified by baseline eGFR ≥30 ml/min per 1.73 m2 versus eGFR<30 ml/min per 1.73 m2. Only 14 participants (six in the active treatment group and eight in the placebo control group) had an eGFR<30 ml/min per 1.73 m2. Among those with eGFR≥30 ml/min per 1.73 m2, FMD increased 1.4% (95% CI, 0.2 to 2.5) in treatment and 0.7% (95% CI, −0.5 to 1.9) in placebo, with a net change of 0.6% (95% CI, −1.0 to 2.3) (Supplemental Table 2). Net changes were −34.6 ng/ml (95% CI, −66.1 to −3.1) for vascular adhesion molecule-1; −4517 ng/ml (95% CI, −8198 to −837) for vWf; −62.1 pg/ml (95% CI, −119 to −5.4) for IL-18; −4.6 mm Hg (95% CI, −8.0 to −1.1) for diastolic BP; and −12.1 mg/dl (95% CI, −23.6 to −0.7) for total cholesterol.
Participant Safety and Adherence Data
Safety measures are summarized in Table 3. There were no significant differences in methemoglobin, hemoglobin, nitrite, or pulse between groups. Nitrate and isoquercetin were significantly higher in treatment versus placebo. SAEs and AEs were similar between groups (Table 4), except that leg swelling was more common in the placebo group.
Table 3.
Safety measurements over the 12-week intervention by treatment allocation
| Safety Measures | Treatment, n=35 | Placebo, n=35 | Difference (95% CI) |
|---|---|---|---|
| Methemoglobin, % | |||
| Baseline, mean (SD) | 0.28 (0.12) | 0.29 (0.17) | −0.006 (−0.08 to 0.06) |
| 6 and 12 wk, mean (SD) | 0.23 (0.11) | 0.24 (0.10) | −0.007 (−0.06 to 0.05) |
| Change during intervention, mean (95% CI) | −0.06 (−0.11 to −0.01) | −0.05 (−0.11 to −0.01) | −0.005 (−0.08 to 0.07) |
| Nitrite, μmol/L | |||
| Baseline, mean (SD) | 0.48 (0.30) | 0.53 (0.39) | −0.05 (−0.22 to 0.12) |
| 6 and 12 wk, mean (SD) | 0.40 (0.28) | 0.42 (0.23) | −0.02 (−0.15 to 0.10) |
| Change during intervention, mean (95% CI) | −0.07 (−0.20 to 0.05) | −0.11 (−0.23 to 0.01) | 0.04 (−0.14 to 0.21) |
| Nitrate, μmol/L | |||
| Baseline, mean (SD) | 37.3 (27.7) | 40.4 (26.6) | −3.1 (−16.1 to 9.8) |
| 6 and 12 wk, mean (SD) | 52.1 (28.9) | 34.7 (18.1) | 17.4 (5.7 to 29.1) |
| Change during intervention, mean (95% CI) | 15.4 (5.9 to 25.0) | −6.3 (−15.7 to 3.1) | 21.7 (8.3 to 35.1) |
| Isoquercetin, μg/L | |||
| Baseline, mean (SD) | 56.5 (29.3) | 50.1 (22.1) | 6,5 (−5.9 to 18.9) |
| 6 and 12 wk, mean (SD) | 226 (261) | 59 (23) | 168 (78 to 258) |
| Change during intervention, mean (95% CI) | 166 (102 to 230) | 11.7 (−51.1 to 74.5) | 154 (66 to 242) |
| Hemoglobin, g/dl | |||
| Baseline, mean (SD) | 13.0 (1.7) | 13.2 (2.0) | −0.17 (−1.06 to 0.72) |
| 6 and 12 wk, mean (SD) | 12.8 (1.8) | 13.0 (1.9) | −0.19 (−1.11 to 0.73) |
| Change during intervention, mean (95% CI) | −0.25 (−0.46 to −0.04) | −0.13 (−0.34 to 0.07) | −0.12 (−0.41 to 0.17) |
| Pulse, beats per minute | |||
| Baseline, mean (SD) | 71 (11) | 69 (11) | 1 (−4 to 7) |
| 6 and 12 wk, mean (SD) | 71 (9) | 69 (11) | 3 (−2 to 7) |
| Change during intervention, mean (95% CI) | 0.6 (−1.7 to 2.3) | −0.5 (−2.8 to 1.9) | 1.1 (−2.2 to 4.4) |
95% CI, confidence interval.
Table 4.
Adverse events over the 12-week intervention by treatment allocation
| Adverse Events | Treatment, n=35 | Placebo, n=35 |
|---|---|---|
| Serious adverse events, no. | ||
| Hospitalization | 1a | 1 |
| Death | 0 | 0 |
| Adverse events, no. | ||
| Headache | 6 | 8 |
| Dizziness | 5 | 3 |
| Lightheadedness | 3 | 5 |
| Blurred vision | 6 | 1 |
| Leg swelling | 7 | 15 |
| Palpitation | 2 | 3 |
| Skin rash | 2 | 0 |
| Abdomen pain | 3 | 3 |
Not study related.
There was no significant difference in adherence between groups, with the exception of slightly lower isoquercetin pill counts in treatment versus placebo at 12 weeks (Supplemental Table 3).
Discussion
In this randomized, double-blinded, placebo-controlled trial, the combination treatment with sodium nitrite and isoquercetin did not significantly improve FMD or biomarkers of endothelial dysfunction, inflammation, and oxidative stress compared with placebo in patients with CKD. Additionally, combination treatment did not increase side effects or AEs compared with placebo. In a post hoc subgroup analysis by baseline eGFR, vascular adhesion molecule-1, vWf, IL-18, diastolic BP, and total cholesterol were nominally significantly reduced in combination treatment compared with placebo among patients with an eGFR≥30 ml/min per 1.73 m2.
This randomized phase 2 pilot trial was designed to test the efficacy and safety of combination treatment with sodium nitrite and isoquercetin on multiple biomarkers of endothelial dysfunction. It aimed to generate study hypotheses for future clinical trials rather than provide direct evidence for clinical practice. Endothelial dysfunction, inflammation, and oxidative stress are common among patients with CKD (7–11). Treatments specifically targeting endothelial dysfunction may slow or reverse vascular disease progression in kidney and cardiovascular systems. Our study showed that combination treatment increased FMD by 0.8%, although it was not statistically significant. In a meta-analysis, a 1% increase in FMD was associated with 10% lower cardiovascular disease events (29). Our study also suggested potential favorable effects of combination treatment on biomarkers of endothelial dysfunction and inflammation compared with placebo among patients with CKD and an eGFR≥30 ml/min per 1.73 m2. However, this study was underpowered to detect a clinically meaningful difference in FMD and other biomarkers.
Our study suggested that combination treatment with sodium nitrite and isoquercetin might reduce vascular adhesion molecule-1 and vWf among those with higher eGFR. Nitric oxide deficiency is significantly associated with higher vascular adhesion molecule-1, intercellular adhesion molecule-1, E-selectin, and vWf (7,30–32). The decrease in these biomarkers may reflect the effect of sodium nitrite and isoquercetin (19). Vascular adhesion molecule-1, intercellular adhesion molecule-1, and E-selectin induce inflammation and are associated with higher risk of cardiovascular disease and CKD (7,33). Elevated vWf causes thrombosis and is associated with CKD progression and cardiovascular disease risk (34,35). Future clinical trials are warranted to examine whether reduction in these biomarkers would improve kidney and cardiovascular outcomes.
One concern of nitrite treatment is that nitric oxide may be converted to oxidative by-products, like nitrotyrosine, that can cause side effects and nitrite tolerance (22,36). Our study indicated that the combination treatment with sodium nitrite and isoquercetin did not significantly increase AEs. Therefore, combination of isoquercetin with sodium nitrite may not only synergistically improve endothelial dysfunction but also reduce side effects of nitrite.
In patients with CKD and eGFR≥30 ml/min per 1.73 m2, IL-18 was reduced in combination treatment compared with placebo. IL-18 may be induced by oxidative stress (37,38). In an animal study, neutralizing IL-18 was protective against kidney dysfunction, tubular damage, and cellular infiltration in the kidney in AKI after ischemia reperfusion (39). High IL-18 level was associated with more frequent coronary artery disease events independent of traditional risk factors, C-reactive protein, and IL-6 (40). Further research should investigate the long-term effect of lowering IL-18 on CKD and cardiovascular disease progression.
The increase in net change of IL-6 in our study was mainly due to an unexpected reduction in IL-6 in the placebo group. IL-6 acts as both a proinflammatory cytokine and an anti-inflammatory cytokine, mediated through its stimulatory effects on TNF-α, IL-1, IL-10, IL-17, IL-1 receptor antagonist, vascular adhesion molecule-1, and intercellular adhesion molecule-1 (41). In our study, combination treatment did not increase these downstream biomarkers.
Nitrate levels were significantly higher in combination treatment compared with placebo during the 12-week intervention but fell within an acceptable range for safety (42). The nitrite level was low because most nitrite is converted to nitric oxide in the stomach and absorbed systematically, and nitrite in the blood converts to nitrate (with a 100-second t1/2) (43). These findings further suggest that the combination treatment is safe.
This study has several strengths. First, it utilized a randomized, double-blind, placebo-controlled design to reduce potential biases. Second, combination treatment targeted multiple pathways of vascular pathogeneses. Third, combination treatment did not increase AEs and was well tolerated. However, this study has a few limitations. First, the anticipated effect size of treatment on FMD was overestimated, so the sample size did not provide sufficient statistical power to detect the observed net changes in FMD. Second, more research is needed on FMD measurements in patients with CKD. For example, the vessel might not be dilated within 5 minutes postcuff among patients with CKD. Utilizing a longer postcuff time in FMD measurement may yield more accurate results. Third, the optimal dosage and long-term treatment effects were not examined in this study. Finally, the subgroup analysis was not predefined, and a very small sample size in the lower eGFR subgroup makes comparison difficult.
In conclusion, this randomized phase 2 pilot trial indicates that combination treatment with sodium nitrite and isoquercetin did not significantly improve FMD or other endothelial function biomarkers in patients with CKD. In addition, combination treatment did not increase AEs compared with placebo. However, this study generates hypotheses that combination treatment with sodium nitrite and isoquercetin might reduce vascular adhesion molecule-1, vWf, IL-18, diastolic BP, and total cholesterol levels in patients with CKD and eGFR≥30 ml/min per 1.73 m2. Therefore, future clinical trials of sodium nitrite and isoquercetin supplementation should target individuals with an eGFR≥30 ml/min per 1.73 m2. In addition, our study cannot exclude the potential beneficial effect of sodium nitrite and isoquercetin supplements among patients with CKD and an eGFR<30 ml/min per 1.73 m2 due to the small sample size in this subgroup.
Disclosures
All authors have nothing to disclose.
Funding
This study is supported in part by Louisiana Clinical and Translational Science Center National Institute of General Medical Sciences of the National Institutes of Health grant U54 GM104940; Tulane Centers of Biomedical Research Excellence for Clinical and Translational Research in Cardiometabolic Diseases National Institute of Health (NIH), National Institute of General Medical Sciences (NIGMS) grant P20 GM109036; and Tulane Translational Research in Hypertension and Renal Biology NIH, NIGMS grant P30-GM103337.
Supplementary Material
Acknowledgments
We thank our data and safety monitoring board members Dr. Vecihi Batuman (chair), Dr. Lydia Bazzano, and Dr. Wan Tang. We thank our research pharmacist Dr. Stephen Gotzkowsky for his efforts in dispensing the study drugs and managing the drug accountability logs, and we thank our ultrasound technician, Mr. Russell Pitre. We also thank all of the study staff involved in this trial, and we are grateful to all study participants who contributed to this clinical trial. The sodium nitrite and placebo were donated by TheraVasc Inc. Isoquercetin and placebo were donated by Quercegen Pharmaceuticals. We are also grateful to the University of Pennsylvania Vascular Research Center for reading FMD. We thank the Tulane Pulmonary Diseases, Critical Care & Environmental Medicine Lab for measuring the methemoglobin and the Tulane School of Medicine Clinical Trials Cooperative Core Laboratory for use of the MSD equipment.
Data Sharing Statement
The individual deidentified participant data, including demographic information, the primary study outcome (FMD), the secondary outcomes (endothelial dysfunction biomarkers: vascular adhesion molecule-1, intercellular adhesion molecule-1, E-selectin, vWf, endothelin-1, endostatin, asymmetrical dimethylarginine, and urine EGF; inflammatory biomarkers: TNF-α, IL-6, C-reactive protein, IL-1β, IL-17, IL-18, IL-10, IL-1 receptor antagonist, and monocyte chemoattractant protein-1; and oxidative biomarkers: oxidized LDL and nitrotyrosine), other outcomes (eGFR, UACR, systolic BP, diastolic BP, total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride), and other covariables, will be shared after the study results are published. The study protocol and study forms will become available as well. To access to these data, individuals should contact J. Chen. Data access must be approved by the Tulane University Biomedical Institution Review Board.
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
Supplemental Material
This article contains the following supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.02020220/-/DCSupplemental.
Supplemental Table 1. Inclusion and exclusion criteria.
Supplemental Table 2. Adjusted mean changes of primary, secondary, and other outcomes over the 12-week intervention by treatment allocation in 56 participants with eGFR≥30 ml/min per 1.73 m2 and 14 participants with eGFR<30 in a post hoc analysis.
Supplemental Table 3. Treatment adherence.
References
- 1.Snyder JJ, Foley RN, Collins AJ: Prevalence of CKD in the United States: A sensitivity analysis using the National Health and Nutrition Examination Survey (NHANES) 1999-2004. Am J Kidney Dis 53: 218–228, 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Mills KT, Xu Y, Zhang W, Bundy JD, Chen CS, Kelly TN, Chen J, He J: A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010. Kidney Int 88: 950–957, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Coresh J, Turin TC, Matsushita K, Sang Y, Ballew SH, Appel LJ, Arima H, Chadban SJ, Cirillo M, Djurdjev O, Green JA, Heine GH, Inker LA, Irie F, Ishani A, Ix JH, Kovesdy CP, Marks A, Ohkubo T, Shalev V, Shankar A, Wen CP, de Jong PE, Iseki K, Stengel B, Gansevoort RT, Levey AS; CKD Prognosis Consortium : Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality. JAMA 311: 2518–2531, 2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, de Jong PE, Coresh J, Gansevoort RT; Chronic Kidney Disease Prognosis Consortium : Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: A collaborative meta-analysis. Lancet 375: 2073–2081, 2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Manjunath G, Tighiouart H, Ibrahim H, MacLeod B, Salem DN, Griffith JL, Coresh J, Levey AS, Sarnak MJ: Level of kidney function as a risk factor for atherosclerotic cardiovascular outcomes in the community. J Am Coll Cardiol 41: 47–55, 2003. [DOI] [PubMed] [Google Scholar]
- 6.Saran R, Robinson B, Abbott KC, Bragg-Gresham J, Chen X, Gipson D, Gu H, Hirth RA, Hutton D, Jin Y, Kapke A, Kurtz V, Li Y, McCullough K, Modi Z, Morgenstern H, Mukhopadhyay P, Pearson J, Pisoni R, Repeck K, Schaubel DE, Shamraj R, Steffick D, Turf M, Woodside KJ, Xiang J, Yin M, Zhang X, Shahinian V: US Renal Data System 2018 Annual Data Report: Epidemiology of kidney disease in the United States. Am J Kidney Dis 73: Svii-Sxxii, 2019 [DOI] [PubMed] [Google Scholar]
- 7.Chen J, Hamm LL, Mohler ER, Hudaihed A, Arora R, Chen CS, Liu Y, Browne G, Mills KT, Kleinpeter MA, Simon EE, Rifai N, Klag MJ, He J: Interrelationship of multiple endothelial dysfunction biomarkers with chronic kidney disease. PLoS One 10: e0132047, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Stenvinkel P, Carrero JJ, Axelsson J, Lindholm B, Heimbürger O, Massy Z: Emerging biomarkers for evaluating cardiovascular risk in the chronic kidney disease patient: How do new pieces fit into the uremic puzzle? Clin J Am Soc Nephrol 3: 505–521, 2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Rebholz CM, Wu T, Hamm LL, Arora R, Khan IE, Liu Y, Chen CS, Mills KT, Rogers S, Kleinpeter MA, Simon EE, Chen J: The association of plasma fluorescent oxidation products and chronic kidney disease: A case-control study. Am J Nephrol 36: 297–304, 2012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Lee BT, Ahmed FA, Hamm LL, Teran FJ, Chen CS, Liu Y, Shah K, Rifai N, Batuman V, Simon EE, He J, Chen J: Association of C-reactive protein, tumor necrosis factor-alpha, and interleukin-6 with chronic kidney disease. BMC Nephrol 16: 77, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Shankar A, Sun L, Klein BE, Lee KE, Muntner P, Nieto FJ, Tsai MY, Cruickshanks KJ, Schubert CR, Brazy PC, Coresh J, Klein R: Markers of inflammation predict the long-term risk of developing chronic kidney disease: A population-based cohort study. Kidney Int 80: 1231–1238, 2011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Wever R, Boer P, Hijmering M, Stroes E, Verhaar M, Kastelein J, Versluis K, Lagerwerf F, van Rijn H, Koomans H, Rabelink T: Nitric oxide production is reduced in patients with chronic renal failure. Arterioscler Thromb Vasc Biol 19: 1168–1172, 1999. [DOI] [PubMed] [Google Scholar]
- 13.Fliser D, Kronenberg F, Kielstein JT, Morath C, Bode-Böger SM, Haller H, Ritz E: Asymmetric dimethylarginine and progression of chronic kidney disease: The mild to moderate kidney disease study. J Am Soc Nephrol 16: 2456–2461, 2005. [DOI] [PubMed] [Google Scholar]
- 14.Young JM, Terrin N, Wang X, Greene T, Beck GJ, Kusek JW, Collins AJ, Sarnak MJ, Menon V: Asymmetric dimethylarginine and mortality in stages 3 to 4 chronic kidney disease. Clin J Am Soc Nephrol 4: 1115–1120, 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Himmelfarb J, Stenvinkel P, Ikizler TA, Hakim RM: The elephant in uremia: Oxidant stress as a unifying concept of cardiovascular disease in uremia. Kidney Int 62: 1524–1538, 2002. [DOI] [PubMed] [Google Scholar]
- 16.Ravarotto V, Simioni F, Pagnin E, Davis PA, Calò LA: Oxidative stress—chronic kidney disease—cardiovascular disease: A vicious circle. Life Sci 210: 125–131, 2018. [DOI] [PubMed] [Google Scholar]
- 17.Ormerod JO, Arif S, Mukadam M, Evans JD, Beadle R, Fernandez BO, Bonser RS, Feelisch M, Madhani M, Frenneaux MP: Short-term intravenous sodium nitrite infusion improves cardiac and pulmonary hemodynamics in heart failure patients. Circ Heart Fail 8: 565–571, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Omar SA, Fok H, Tilgner KD, Nair A, Hunt J, Jiang B, Taylor P, Chowienczyk P, Webb AJ: Paradoxical normoxia-dependent selective actions of inorganic nitrite in human muscular conduit arteries and related selective actions on central blood pressures. Circulation 131: 381–389, 2015. [DOI] [PubMed] [Google Scholar]
- 19.Dower JI, Geleijnse JM, Gijsbers L, Schalkwijk C, Kromhout D, Hollman PC: Supplementation of the pure flavonoids epicatechin and quercetin affects some biomarkers of endothelial dysfunction and inflammation in (pre)hypertensive adults: A randomized double-blind, placebo-controlled, crossover trial. J Nutr 145: 1459–1463, 2015. [DOI] [PubMed] [Google Scholar]
- 20.Egert S, Bosy-Westphal A, Seiberl J, Kürbitz C, Settler U, Plachta-Danielzik S, Wagner AE, Frank J, Schrezenmeir J, Rimbach G, Wolffram S, Müller MJ: Quercetin reduces systolic blood pressure and plasma oxidised low-density lipoprotein concentrations in overweight subjects with a high-cardiovascular disease risk phenotype: A double-blinded, placebo-controlled cross-over study. Br J Nutr 102: 1065–1074, 2009. [DOI] [PubMed] [Google Scholar]
- 21.Yilmaz MI, Saglam M, Caglar K, Cakir E, Sonmez A, Ozgurtas T, Aydin A, Eyileten T, Ozcan O, Acikel C, Tasar M, Genctoy G, Erbil K, Vural A, Zoccali C: The determinants of endothelial dysfunction in CKD: Oxidative stress and asymmetric dimethylarginine. Am J Kidney Dis 47: 42–50, 2006. [DOI] [PubMed] [Google Scholar]
- 22.Cai H, Harrison DG: Endothelial dysfunction in cardiovascular diseases: The role of oxidant stress. Circ Res 87: 840–844, 2000. [DOI] [PubMed] [Google Scholar]
- 23.Mohler ER 3rd, Hiatt WR, Gornik HL, Kevil CG, Quyyumi A, Haynes WG, Annex BH: Sodium nitrite in patients with peripheral artery disease and diabetes mellitus: Safety, walking distance and endothelial function. Vasc Med 19: 9–17, 2014. [DOI] [PubMed] [Google Scholar]
- 24.Lekakis J, Abraham P, Balbarini A, Blann A, Boulanger CM, Cockcroft J, Cosentino F, Deanfield J, Gallino A, Ikonomidis I, Kremastinos D, Landmesser U, Protogerou A, Stefanadis C, Tousoulis D, Vassalli G, Vink H, Werner N, Wilkinson I, Vlachopoulos C: Methods for evaluating endothelial function: A position statement from the European Society of Cardiology Working Group on Peripheral Circulation. Eur J Cardiovasc Prev Rehabil 18: 775–789, 2011. [DOI] [PubMed] [Google Scholar]
- 25.Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) : A new equation to estimate glomerular filtration rate [published correction appears in Ann Intern Med 155: 408, 2011]. Ann Intern Med 150: 604–612, 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Jin F, Nieman DC, Shanely RA, Knab AM, Austin MD, Sha W: The variable plasma quercetin response to 12-week quercetin supplementation in humans. Eur J Clin Nutr 64: 692–697, 2010. [DOI] [PubMed] [Google Scholar]
- 27.DeVan AE, Johnson LC, Brooks FA, Evans TD, Justice JN, Cruickshank-Quinn C, Reisdorph N, Bryan NS, McQueen MB, Santos-Parker JR, Chonchol MB, Bassett CJ, Sindler AL, Giordano T, Seals DR: Effects of sodium nitrite supplementation on vascular function and related small metabolite signatures in middle-aged and older adults. J Appl Physiol (1985) 120: 416–425, 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Lee JS, Stebbins CL, Jung E, Nho H, Kim JK, Chang MJ, Choi HM: Effects of chronic dietary nitrate supplementation on the hemodynamic response to dynamic exercise. Am J Physiol Regul Integr Comp Physiol 309: R459–R466, 2015. [DOI] [PubMed] [Google Scholar]
- 29.Ras RT, Streppel MT, Draijer R, Zock PL: Flow-mediated dilation and cardiovascular risk prediction: A systematic review with meta-analysis. Int J Cardiol 168: 344–351, 2013. [DOI] [PubMed] [Google Scholar]
- 30.Khan BV, Harrison DG, Olbrych MT, Alexander RW, Medford RM: Nitric oxide regulates vascular cell adhesion molecule 1 gene expression and redox-sensitive transcriptional events in human vascular endothelial cells. Proc Natl Acad Sci U S A 93: 9114–9119, 1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Kosonen O, Kankaanranta H, Uotila J, Moilanen E: Inhibition by nitric oxide-releasing compounds of E-selectin expression in and neutrophil adhesion to human endothelial cells. Eur J Pharmacol 394: 149–156, 2000. [DOI] [PubMed] [Google Scholar]
- 32.Zarei S, Frieden M, Kaufmann JE, Vischer UM: The regulation of endothelial VWF secretion by nitric oxide: Is it physiological? J Thromb Haemost 4: 263–265, 2006. [DOI] [PubMed] [Google Scholar]
- 33.Blankenberg S, Rupprecht HJ, Bickel C, Peetz D, Hafner G, Tiret L, Meyer J: Circulating cell adhesion molecules and death in patients with coronary artery disease. Circulation 104: 1336–1342, 2001. [DOI] [PubMed] [Google Scholar]
- 34.Bash LD, Erlinger TP, Coresh J, Marsh-Manzi J, Folsom AR, Astor BC: Inflammation, hemostasis, and the risk of kidney function decline in the Atherosclerosis Risk in Communities (ARIC) Study. Am J Kidney Dis 53: 596–605, 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Frankel DS, Meigs JB, Massaro JM, Wilson PWF, O’Donnell CJ, D’Agostino RB, Tofler GH: Von Willebrand factor, type 2 diabetes mellitus, and risk of cardiovascular disease: The Framingham Offspring Study. Circulation 118: 2533–2539, 2008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Münzel T, Daiber A, Mülsch A: Explaining the phenomenon of nitrate tolerance. Circ Res 97: 618–628, 2005. [DOI] [PubMed] [Google Scholar]
- 37.Wenzel U, Turner JE, Krebs C, Kurts C, Harrison DG, Ehmke H: Immune mechanisms in arterial hypertension. J Am Soc Nephrol 27: 677–686, 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Arifa RD, Madeira MF, de Paula TP, Lima RL, Tavares LD, Menezes-Garcia Z, Fagundes CT, Rachid MA, Ryffel B, Zamboni DS, Teixeira MM, Souza DG: Inflammasome activation is reactive oxygen species dependent and mediates irinotecan-induced mucositis through IL-1β and IL-18 in mice. Am J Pathol 184: 2023–2034, 2014. [DOI] [PubMed] [Google Scholar]
- 39.Wu H, Craft ML, Wang P, Wyburn KR, Chen G, Ma J, Hambly B, Chadban SJ: IL-18 contributes to renal damage after ischemia-reperfusion. J Am Soc Nephrol 19: 2331–2341, 2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Jefferis BJ, Papacosta O, Owen CG, Wannamethee SG, Humphries SE, Woodward M, Lennon LT, Thomson A, Welsh P, Rumley A, Lowe GD, Whincup PH: Interleukin 18 and coronary heart disease: Prospective study and systematic review. Atherosclerosis 217: 227–233, 2011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Smith JK: IL-6 and the dysregulation of immune, bone, muscle, and metabolic homeostasis during spaceflight. NPJ Microgravity 4: 24, 2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Moshage H, Kok B, Huizenga JR, Jansen PL: Nitrite and nitrate determinations in plasma: A critical evaluation. Clin Chem 41: 892–896, 1995. [PubMed] [Google Scholar]
- 43.Ma L, Hu L, Feng X, Wang S: Nitrate and nitrite in health and disease. Aging Dis 9: 938–945, 2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.