Study populations
Cohort 1
Patient data were obtained from a cross-sectional study in the US, as described elsewhere14. 106 patients aged ≥ 18 years, were enrolled from four outpatient dialysis centres located in Connecticut, USA, between April and September 2016. All participants provided written informed consent and received either thrice weekly HD for three to five hours per treatment session or daily home PD. Patients had to be medically stable with no infections or hospitalizations for a minimum of three months. Patients with a diagnosis of primary or secondary hyperoxaluria were excluded from the study. In the HD group, blood samples were collected prior to initiation of dialysis at the first appointment after a long interval. In the PD group, blood samples were collected at the monthly clinic appointment. To evaluate the validity of one-time sampling, we collected repeat blood samples from 20 patients at 3–4 subsequent treatment sessions, weekly after the long interval in HD patients and monthly at clinical appointments in PD patients. For patients with repeated measurements the first measurement was used for the analysis. The study was approved by the local authorities (Western Institutional Review Board Study No. 1162867). Data was extracted from the Yale-New Haven Hospital’s information system Epic (Epic; Verona, USA) and collected using SPSS (IBM, New York, USA). BMI was calculated by dividing a person’s weight in kilograms by the square of their height in meters. All types of diabetes were included in this study as indicated by each patient’s individual file.
Cohort 2 (4D cohort)
Design and methods of the 4D Study have been reported several times before14,51. In brief, the 4D Study was a prospective randomized controlled trial including 1255 HD patients with type 2 diabetes mellitus, who were 18–80 years old and had begun renal replacement therapy within the previous 2 years. Between March 1998 and October 2002, patients were recruited in 178 dialysis centers in Europe and randomly assigned to double-blind treatment with 20 mg atorvastatin (n = 619) or placebo (n = 636) once daily. The study was approved by the Universities of Würzburg and Heidelberg and by all Review Boards responsible for participating centres in the study52.
Statement on experiments with human participants
The studies with humans were approved by appropriate committees/local authorities mentioned above (Western Institutional Review Board, Ethics Committee of Charité, University of Würzburg, Heidelberg and responsible Review Boards for study centres of the 4D study). All patients/participants of the three cohorts gave their written informed consent before inclusion. The research was performed in accordance with all relevant guidelines and regulations following the Declaration of Helsinki.
Data collection
In cohort 1, clinical and supplementary laboratory, data were collected from electronic health records and complemented by reports from the treating clinician. Follow-up was thrice weekly for HD and once a month for PD patients, according to standard clinical routines.
In cohort 2 (4D), demographic and clinical information was obtained through patient interviews and reports from the treating nephrologists. Coronary artery disease was defined by a history of myocardial infarction, coronary artery bypass grafting surgery, percutaneous coronary intervention, or the presence of typical vascular findings by coronary angiography51.
Outcome assessment (4D Study)
In the 4D Study, the primary endpoint was a composite of cardiac death, nonfatal myocardial infarction, and fatal or nonfatal stroke, whichever occurred first (composite cardiovascular endpoint). Death from cardiac causes comprised death due to congestive heart failure, sudden cardiac death, fatal myocardial infarction, death due to coronary disease during or within 28 days after an intervention, and all other deaths that might be attributed to coronary artery disease. Sudden cardiac death was defined as: death verified by terminal rhythm disorders in an electrocardiogram, death observed by witnesses within one hour after the onset of cardiac symptoms, sudden cardiac death confirmed by autopsy, or unexpected death presumably or possibly of cardiac origin and in absence of a potassium level ≥ 7.5 mmol/L before the start of the three most recent HD sessions. Myocardial infarction was diagnosed when two of the following three criteria were met: typical symptoms, increased levels of cardiac enzymes (i.e., a level of creatine kinase MB > 5% of the total level of creatine kinase, a level of lactic dehydrogenase 1.5 times the upper limit of normal, or a level of troponin T > 2 ng/mL), or characteristic changes on the electrocardiogram. Stroke was defined as a neurologic deficit lasting > 24 h. Computed tomographic or magnetic resonance imaging was available in all but 16 cases51.
Oxalate measurement
Plasma oxalate (pOx) concentrations were measured as described previously53. In brief, blood samples of the patients and healthy participants were immediately put on wet ice and further processed: after centrifugation, the supernatant was filtered through a Vivaspin® 500 30,999 MWCO PES filter (Sartorius, Göttingen, Germany), acidified, and measured enzymatically with oxalate oxidase (Trinity Biontech, Bray, Co. Wicklow, Ireland). The lower limit of detection of our assay was 2 µM.
In the 4D Study, oxalate concentrations were measured in baseline serum samples taken 1 week prior to randomization, and stored at − 80 °C. Frozen serum samples were slowly thawed, vigorously vortexed, and then processed as described above.
MSD Multiplex assays
In cohort 1, 21 cytokines including granulocyte–macrophage colony-stimulating factor (GM-CSF), interferon gamma (IFN-γ), IL-1α, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p40, IL-12p70, IL-13, IL-15, IL-16, IL-17, TNF-α, TNF-β and vascular endothelial growth factor (VEGF), were measured using a V-PLEX Proinflammatory Panel 1 Human and a V-PLEX Cytokine Panel 1 Human (both Meso Scale Diagnostics, Rockville, USA); and IL-33 using a Human IL-33 Quantikine enzyme-linked immunosorbent assay (ELISA, R&D Systems, Minneapolis, USA) following the company’s instruction. In brief, the samples were diluted twofold with Diluent 2 (V-PLEX Proinflammatory Panel 1 Human) or Diluent 43 (V-PLEX Cytokine Panel 1 Human) in the plate, the samples, calibrators, or controls were applied, and the plate incubated for 2 h at room temperature (RT) while shaking. Subsequently, the plate was washed, and pooled detection antibody was added, and the plates again incubated for 2 h on the shaker. After washing, 2X Read Buffer T was added to the plate and read on an MESO QuickPlex SQ 120 reader (Meso Scale Diagnostics). The analysis was performed using the MSD DISCOVERY WORKBENCH analysis software (Meso Scale Diagnostics).
In cohort 2 (4D Study), IL-16 was also measured using the V-PLEX Cytokine Panel 1 Human. Samples were diluted 1:5 with diluent 43. Instead of the pooled antibody mixture, only the IL-16 antibody was used. The protocol was performed as described before.
IL-33 ELISA
The IL-33 Quantikine ELISA was applied in cohort 1, and performed as per the manufacturer’s instructions. Samples were diluted twofold. A SpectraMax M3 microplate reader (Molecular Devices, San Jose, USA) was used to determine the optical density (OD) at 450 nm wavelength.
Statistical analysis
Cohort 1
The statistical analysis was performed using RStudio Version 1.2.5001 (Posit Software PBC, Boston, USA). P values of < 0.01 were considered statistically significant. For continuous variables, the median and IQR or mean and standard deviation (SD) were calculated. For categorical variables, frequency tables were calculated and the number (n) and the relative proportion (%) reported. Cohort 1: As not all analytes were normally distributed, the Spearman correlation rank test was used to analyse the association of pOx with the 21 cytokines. In addition, two linear regression models were calculated. For model 1, a univariate linear regression was calculated to test the association between pOx (independent variable) and the cytokines (dependent variables). Second, we fitted a model adjusting for the main confounding variables, i.e., age, gender, BMI, and diabetes (model 2). To identify clinical or laboratory characteristics associated with IL-16, the study group was stratified based on IL-16 concentrations into three subgroups. We compared the characteristics between those subgroups by analyses of variation (ANOVA, for continuous outcomes) or Pearson chi square statistic (for categorical outcomes). Differences between the groups were further assessed by testing the association of the clinical or laboratory parameters (independent variable) and IL-16 (dependent variable).
Cohort 2 (4D Study)
We calculated means (SDs) or medians (interquartile ranges [IQRs]) for continuous and frequency tables for categorical variables. We compared characteristics between groups by analyses of variation (ANOVA), or chi-square tests where appropriate. Patient characteristics are presented in subgroups defined by quartiles of IL-16 concentrations at baseline, with the following cut-points: ≤ 326 pg/mL, > 326 to ≤ 416 pg/mL, > 416 to ≤ 535 pg/mL, and > 535 pg/mL Bivariate correlations of IL-16, pOx and uremic toxins (creatinine, ADMA, SDMA, serum carbamylated albumin (C-Alb) und BUN/Urea) were analysed by calculating scatter plots and Pearson correlation coefficients. A multivariate prediction model was calculated to assess the impact of uremic toxins on IL-16. The risk of all-cause mortality, reaching the composite cardiovascular endpoint, death due to congestive heart failure, sudden cardiac death, myocardial infarction, stroke, and death due to infection, according to quartiles of IL16 levels (with quartile 1 being the reference group) were assessed by Cox regression models. First, we fitted a model including the main confounding variables i.e., age, sex, and two markers indicating progressive uremia, i.e. time on HD, and use of diuretics (model 1). Second, we fitted a model additionally adjusting for C-reactive protein, BMI, hemoglobin, albumin, and previous coronary artery disease (model 2—core model), which are known to be established risk factors for mortality in dialysis patients. All models were adjusted for treatment group (atorvastatin vs. placebo) and fit as complete case analyses (no missing value imputation)14,37. P-values are two-sided.
Statistical analyses were conducted using STATA (StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC) for the 4D Study.
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