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Urinary cell-free mitochondrial and nuclear deoxyribonucleic acid correlates with the prognosis of chronic kidney diseases

Urinary cell-free mitochondrial and nuclear deoxyribonucleic acid correlates with the prognosis... Introduction: Cell-free deoxyribonucleic acid DNA (cf-DNA) in urine is promising due to the advantage of urine as an easily obtained and non-invasive sample source over tissue and blood. In clinical practice, it is important to identify non-invasive biomarkers of chronic kidney disease (CKD) in monitoring and surveillance of disease progression. Information is limited, however, regarding the relationship between urine and plasma cf-DNA and the renal outcome in CKD patients. Methods: One hundred and thirty-one CKD patients were enrolled between January 2016 and September 2018. Baseline urine and plasma cell-free mitochondrial DNA (cf-mtDNA) and cell-free nuclear DNA (cf-nDNA) were isolated using quantitative real-time PCR. Estimated glomerular filtration rate (eGFR) measurement was performed at baseline and 6-month follow-up. Favorable renal outcome was defined as eGFR at 6 months minus baseline eGFR> = 0. Receiver operator characteristics (ROC) curve analysis was performed to assess different samples of cf- DNA to predict favorable renal outcomes at 6 months. A multivariate linear regression model was used to evaluate independent associations between possible predictors and different samples of cf-DNA. Results: Patients with an advanced stage of CKD has significantly low plasma cf-nDNA and high plasma neutrophil gelatinase-associated lipocalin (NGAL) levels. Low urine cf-mtDNA, cf-nDNA levels and low plasma NGAL were significantly correlated with favorable renal outcomes at 6 months. The urine albumin-creatinine ratio (ACR) or urine protein-creatinine ratio (PCR) level is a robust predictor of cf-mtDNA and cf-nDNA in CKD patients. Baseline urine levels of cf-mtDNA and cf- nDNA could predict renal outcomes at 6 months. Conclusions: Urinary cf-mtDNA and cf-nDNA may provide novel prognostic biomarkers for renal outcome in CKD patients. Thelevels ofplasmacf-nDNA andplasmaNGAL are significantlycorrelatedwiththe severity of CKD. Keywords: Cell-free mitochondrial deoxyribonucleic acid, Cf-mtDNA, Cell-free nuclear deoxyribonucleic acid, Cf-nDNA, Neutrophil gelatinase-associated lipocalin, NGAL, Chronic kidney disease Background CKD and timely detection of progression are truly global Chronic kidney disease (CKD) is a global public health prob- challenges [3, 4]. It is important to recognize the risk factors lem affecting up to 10% of the population worldwide [1], al- of CKD, and better approaches for the prevention, early de- though guidelines for the clinical staging of CKD have been tection, and treatment of CKD [5]. established [2]. The natural history of the earlier phases of The kidney is a highly energetic organ and rich in mito- CKD are highly unpredictable and the early identification of chondria and numerous studies have shown that mitochon- drial dysfunction contributestodifferent typesofkidney * Correspondence: 28071@cch.org.tw diseases, including diabetic and nondiabetic nephropathy [6]. Chin-San Liu and Ching-Hui Huang contributed equally to this work. Proteinuria, caused by a primary insult to the kidney, induces Vascular & Genomic Research Center, Changhua Christian Hospital, oxidative stress in renal tubular cells and causes mitochon- Changhua, Taiwan Department of Cardiology, Changhua Christian Hospital, Changhua, Taiwan drial dysfunction [7, 8], which leads to cellular damage by Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Chang et al. BMC Nephrology (2019) 20:391 Page 2 of 10 reactive oxygen species generation as well as epithelial–mes- Since the majority of urine cf-DNA originates from apop- enchymal transition (EMT) [9, 10]. To date, CKD is charac- tosis or necrosis of cells exfoliated from urogenital system terized by mitochondrial dysfunction, oxidative stress, and [30]. And the minority are originating from blood circula- aberrant autophagy [11, 12] in addition to significant changes tion, which contains important genomic information from in the activation of transforming growth factor-β,p53,hyp- various positions all over the body [33, 34]. We postulate oxia-inducible factor, chronic inflammation, and traditional that urine cf-DNA might be regarded as a marker which vascular dysfunction [11]. By the experimental models of combined genetic information from urogenital system and CKD, preventing mitochondrial dysfunction inhibits renal systemic. We hypothesis that urinary cf-DNA might be a tubular cell EMT and renal fibrosis [13]. However, only a better novel biomarker than circulating cf-DNA in pre- relatively small number of translational studies have shown dicting renal outcome in CKD patients. To clarify the clin- the clinical relevance of these mechanisms between renal dis- ical application of cf-mtDNA and cf-nDNA in CKD, we eases and mitochondrial dysfunction in humans [6, 14, 15]. studied the correlation between cf-mtDNA and cf-nDNA, Free circulating nucleic acids, cell-free deoxyribonucleic both urine and plasma, and the stage of CKD or prognosis acid (cf-DNA), were discovered in human plasma in 1948 of renal outcomes. by Mandel and Metais [16]. Some studies showed the damaged mitochondria release their DNA content into Methods the systemic circulation [17, 18]. Thus, cell-free mitochon- The Institutional Review Board of Changhua Christian drial deoxyribonucleic acid (cf-mtDNA) is easily detected Hospital approved the experimental protocols (approval in plasma, and has been explored as a biomarker of vari- number 140306) and all the participants provided written ous diseases [19–21]. Recently, increased plasma levels of informed consent to participate the study. All patients of cf-mtDNA have been reported to correlate with the sever- the study joined our nationwide preventive multidisciplin- ity of injury in patients sustaining polytrauma [22] and the ary program, also regulated by the Clinical Care Program severity of stroke [23], be a prognostic marker of acute Certification and Joint Commission International, for early myocardial infarction [24] and intensive care unit patients CKD or pre-ESRD (end stage renal disease). We investi- [25, 26]. Alterations of cf-mtDNA in the blood also might be gated patients who were enrolled in our CKD care pro- associated with several systemic diseases, including primary gram between January 2016 and September 2018.The mitochondrial disorders, carcinogenesis, and hematologic dis- goals for patients’ blood pressure, glucose and lipid con- eases [27, 28]. In a community-based population cohort, trol were based on the KDOGI guidelines. higher plasma cf-mtDNA was associated with a lower inci- Overall, of 131 patients with CKD, 7 patients dropped-out dence of CKD independent of traditional risk factors [20]and for the duration of follow-up less than 6 months, and 52 vol- was associated with a lower prevalence of microalbuminuria unteers were recruited from the Nephrology Clinic at Chan- [29]. Apart from blood, cf-DNA could also be detected in ghua Christian Hospital, a tertiary referral hospital in Taiwan. urine. Urine cf-DNA originates either from cells shedding into The duration of follow-up for CKD was more than 6 months urine from genitourinary tract, or from cell free DNA in circu- in all patients. The patients with following criteria were ex- lation passing through glomerular filtration [30]. The presence cluded: infection, acute fever, hepatic or cardiac disease, endo- of genetic information in urine has been observed in some crinopathy, glomerulonephritis proved by biopsy or treatment clinical studies. For examples, the urinary cf-mtDNA level had with steroids or immunosuppressants, surgery, trauma, miss- statistically significant correlations with the peak serum cre- ing data at baseline, prior kidney transplant, acute kidney in- atinine level and the duration of hospitalization in a study of jury and a history of RRT or hospitalization for any cause in acutekidneyinjury(AKI) [30]. Patients who required tempor- the past 3 months. The amount of proteinuria was calculated ary dialysis also tended to have higher urinary cf-mtDNA by urinary protein-creatinine ratio (PCR, mg/g) or albumin- levels than those without dialysis [31], but no relationship be- creatinine ratio (ACR, mg/g). Microalbuminuria was estab- tween the urinary cf-mtDNA level and renal outcomes has lished when two out of three ACR determinations were found been reported. A recent study showed that urinary cf-mtDNA to be within the range of 30–300 mg/g in a 6-month period. level was increased in mice after 10–15 min of ischemia, and We calculated the glomerular filtration rate (eGFR) of the pa- that the level correlated with the duration of ischemia [32]. tients according to the CKD Epidemiology Collaboration Otherwise, platelet and leukocyte counts in samples are im- equation (eGFR )[35]. The stages of CKD were defined CKD-EPI portant sources of variation when cf-DNA is measured in as follows: stage 1, eGFR > 90 ml/min/1.73 m ;stage 2, eGFR DNA extracted from whole blood [27, 28]. Emerging data 60–89 ml/min/1.73 m ;stage 3a, eGFR45–59 ml/min/1.73 2 2 showed that measuring cf-DNA extracted from whole blood m ;stage 3b,eGFR30–44 ml/min/1.73 m ;stage 4, eGFR 15– 2 2 (nuclear deoxyribonucleic acid, cf-nDNA) could yield different 29 ml/min/1.73 m and stage 5, eGFR < 15 ml/min/1.73 m or results from peripheral blood mononuclear cells or buffy coat maintenance on RRT. We divided the population to early (cf-mtDNA), because of the presence of mitochondrial DNA CKD (stages 1–3a) and advanced CKD (stages 3b–5) in the in platelets [27, 28]. study, based on our national CKD care program. Chang et al. BMC Nephrology (2019) 20:391 Page 3 of 10 Table 1 Demographic characteristics of varying stages of chronic kidney disease a b c d Variables Stage 1,2 Stage 3A Stage 3B Stage 4,5 p value Post hoc n =23 n =28 n =31 n =42 Age (year) 47.1 ± 12.7 53.6 ± 9.4 54.9 ± 10.5 58.7 ± 6.1 0.002* a < c,d Gender (M/F) 3/20 8/20 22/9 29/13 0.212 Hypertension (%) 42% 37% 59% 54% 0.191 Diabetes mellitus (%) 12% 11% 23% 54% 0.160 Systolic blood pressure (mm Hg) 138 ± 18 144 ± 28 138 ± 24 142 ± 15 0.943 Diastolic blood pressure (mm Hg) 90 ± 15 91 ± 4 84 ± 18 84 ± 12 0.784 BMI (kg/m ) 27.8 ± 5.4 28.2 ± 6.1 26.2 ± 6.1 24.8 ± 4.3 0.172 BUN (mg/dL) 14.3 ± 4.4 17.7 ± 3.8 31.4 ± 13.0 64.5 ± 27.1 <0.001** a,b < c < d eGFR (ml/min/1.73 m^2) 84.4 ± 20.2 52.1 ± 4.4 31 ± 9.6 11.5 ± 7.3 <0.001** a > b > c > d Phosphate (mg/dL) 3.5 ± 0.4 3.5 ± 0.6 4.0 ± 0.7 5.0 ± 1.1 <0.001** a,b,c < d Cholesterol (mg/dL) 198.3 ± 50.4 171.5 ± 31.8 196.6 ± 47.3 153.3 ± 44.5 0.001** a,c > d HDL-C (mg/dL) 47.8 ± 14.3 43.3 ± 9.8 46.1 ± 12.6 46.7 ± 21.2 0.677 LDL-C (mg/dL) 118.2 ± 45.3 104.6 ± 31.4 114.9 ± 41.3 80.8 ± 26.7 0.040* c > d Fasting Glucose (mg/dL) 118.3 ± 46.1 106 ± 21.8 112.6 ± 43.5 94.9 ± 24.6 0.263 HbA1C (%) 6.3 ± 1.4 6.0 ± 0.6 6.2 ± 1.1 6.1 ± 0.9 0.778 Urine A/C ratio (mg/g) 438.0 ± 826.4 535.7 ± 1018.4 2121.3 ± 2540.7 1548.0 ± 2377.2 0.058 WBC (×10 /μL) 7.1 ± 2.4 6.2 ± 1.9 6.4 ± 2.1 6.8 ± 2.0 0.323 Uric Acid (mg/dL) 7.1 ± 1.2 7.0 ± 1.4 7.5 ± 2.6 7.0 ± 1.2 0.629 Platelet(×10 /μL) 230.2 ± 72.6 209.2 ± 59.5 201.9 ± 51.1 195.1 ± 58.2 0.159 P-value by One-Way ANOVA follow with Bonferroni multiple comparisons at type I error of 0.05 level *P <0.05, **P <0.01. Gender (M/F), female/male; BMI, body mass index; BUN, blood urea nitrogen; HDL, high-density lipoprotein; LDL, low-density lipoprotein; HbA1C, glycated hemoglobin; WBC, white blood count; eGFR, estimated glomerular filtration rate; urine A/C ratio, urine albumin-creatinine ratio a b c d Post hoc: indicates group stage 1,2; indicates group stage 3a; indicates group stage 3b; indicates group stage 4,5 Studies in CKD always address primary outcomes of death, 6 months minus baseline eGFR> = 0; unfavorable renal out- ESRD, or doubling of baseline serum creatinine. Coresh et al. come indicated eGFR at 6 months minus baseline eGFR <0. extended use of percentage reduction in eGFR as a surrogate for hard outcomes and they reported that longer–term fol- Blood, plasma and urine sampling low-up, more than 1 year, was strongly predictive of ESRD Participants’ venous blood samples, following 8-h overnight and death [36]. We, therefore, examined the change of eGFR fasting, were obtained and first morning urine samples were as a surrogate for hard outcomes within 6 months. For study collected. Aliquots of urine were immediately frozen simplicity, favorable renal outcome was defined as eGFR at at − 80 °C until further analysis, but specimen reserved for Table 2 The levels of different parameters in varying stages of CKD a b c d Stage 1,2 Stage 3 Stage 3 Stage 4,5 P value Post hoc tests Plasma cf-mtDNA (GE/mL) 523 ± 710 373 ± 360 420 ± 664 112 ± 134 0.209 Plasma cf-nDNA (GE/mL) 1269 ± 1195 698 ± 527 439 ± 569 104 ± 70.01 <0.001** a > b,c,d Urine cf-mtDNA (GE/mL) 0.43 ± 0.69 0.98 ± 3.10 2.78 ± 10.12 6.49 ± 17.85 0.220 Urine cf-nDNA (GE/mL) 2.83 ± 4.60 4.49 ± 12.09 15.39 ± 44.01 8.01 ± 12.08 0.351 Plasma NGAL (ng/mL) 394 ± 175 489.6 ± 174.9 744.2 ± 272.1 1096 ± 488.7 <0.001** a,b,<c,d MCN (per cell) 90.7 ± 66.9 94.9 ± 77.01 92.9 ± 89.9 110.5 ± 112.7 0.901 Urine 8-OH dG/Cr 3.73 ± 1.81 3.78 ± 2.93 4.15 ± 2.65 2.99 ± 1.53 0.416 P-value by One-Way ANOVA follow with Bonferroni multiple comparisons at type I error of 0.05 level *P <0.05, **P <0.01 a b c d Post hoc indicates group stage 1,2; indicates group stage 3a; indicates group stage 3b; indicates group stage 4,5 MCN mitochondrial copy number, NGAL neutrophil gelatinase-associated lipocalin; 8-OH dG 8-hydroxy-2-deoxyguanosine, cf-mtDNA cell-free mitochondrial DNA, cf-nDNA cell-free nuclear DNA, GE/mL genome equivalents/mL Chang et al. BMC Nephrology (2019) 20:391 Page 4 of 10 Table 3 The difference of baseline parameters between favorable and unfavorable renal outcome at 6 months Favorable renal outcome Unfavorable renal outcome P value (n = 53) (n = 70) Plasma cf-mtDNA (GE/mL) 441.1 ± 525.6 370.6 ± 641.9 0.538 Plasma cf-nDNA (GE/mL) 760.9 ± 732.9 554.1 ± 850.9 0.184 Urine cf-mtDNA (GE/mL) 0.489 ± 0.751 3.745 ± 12.197 0.027* Urine cf-nDNA (GE/mL) 1.764 ± 2.388 15.119 ± 40.791 0.009* MCN (per cell) 87.21 ± 69.40 101.55 ± 95.75 0.356 Urine 8-OH dG/Cr 3.62 ± 2.44 4.03 ± 2.44 0.346 NGAL (ng/mL) 585.24 ± 251.62 780.85 ± 391.39 0.032* *P < 0.05, Student’s test MCN, mitochondrial copy number; NGAL, neutrophil gelatinase-associated lipocalin; 8-OH dG, 8-hydroxy-2-deoxyguanosine; cf-mtDNA, cell-free mitochondrial DNA; cf-nDNA, cell-free nuclear DNA; GE/mL, genome equivalents /mL Favorable renal outcome indicated eGFR at 6 months minus baseline eGFR> = 0; unfavorable renal outcome indicated eGFR at 6 months minus baseline eGFR <0 no longer than 1 month. All assays were undertaken in Leukocyte mitochondrial DNA copy number duplicate with intra-assay variation coefficient less than We used a LightCycler® 480 Instrument (Roche, Mannheim, 5%. Urinary albumin concentration was measured by an Germany) to measure mitochondrial copy number (MCN) immunoturbidimetric method (Roche Diagnostics GmbH, in leukocytes. Briefly, we extracted total DNA using the Mannheim, Germany). Gentra Puregene DNA kit (Qiagen, Hilden, Germany). Real- time polymerase chain reaction (PCR) was used to amplify DNA isolation and qPCR the ND1 gene of mtDNA and β-globin of nuclear DNA, re- The baseline data of urine and plasma cell-free mitochondrial spectively. The relative MCN of mtDNA was normalized to DNA (cf-mtDNA) and cell-free nuclear DNA (cf-nDNA) the β-globin gene. were isolated from 131 patients with CKD in our study. Blood collection were drawn from each subject in the morning after Quantification of urine and plasma cell-free DNA by real- overnight fasting 8 h. For each subject, 5 ml of whole blood time PCR was withdrawn from an antecubital vein and quickly delivered Baseline urine and plasma cf-mtDNA and cf-nDNA were into an EDTA-K3-containing plastic tube. Plasma was col- quantified by real-time PCR using the LightCycler® 480 In- lected by centrifugation of blood at 2500 rpm for 10 min, di- strument (Roche, Mannheim, Germany) using specific vided into several aliquots, and stored in − 80 °C until analysis. primers to amplify the β-globin (forward: 5′-GTG CAC Urine samples were placed on 4 °C, centrifuged at 12000 rpm CTG ACT CCT GAG GAG A-3′,reverse: 5′-CCT TGA for 15 min within 8 h of collection, and the urine supernatants TAC CAA CCT GCC CAG-3′) and MT-ND1 (forward: were separated and stored at − 80 °C until extraction DNA. AACATACCCATGGCCAACCT, reverse: AGCGAA Plasma and Urine cfDNA was extracted urine the Viral DNA GGGTTGTAGTAGCCC) genes from urine and plasma mini Kit (AccuBioMed, Co, Ltd., Taiwan), following the proto- DNA, and standard regression analyses were used to de- col of manufacturer. rive the amount of urine and plasma nuclear DNA and Table 4 Univariate correlation between urinary cf-nDNA and Table 5 Univariate correlation between urinary cf-mtDNA and variables variables Variable Rho correlation coefficient P value Variable Rho correlation coefficient P value Urine A/C ratio (mg/g) 0.408 0.005* Urine A/C ratio (mg/g) 0.375 0.008* Urine P/C ratio (mg/g) 0.314 0.007* Urine P/C ratio (mg/g) 0.349 0.002** Urine cf-mtDNA (GE/mL) 0.448 <0.001** Urine cf-nDNA (GE/mL) 0.448 <0.001** Urine protein (mg/dL) 0.246 0.029* Urine protein (mg/dL) 0.167 0.125 NGAL (ng/mL) 0.322 0.001** NGAL (ng/mL) 0.168 0.066 *P < 0.05, **P <0.01; Spearman's rho correlation *P < 0.05, **P < 0.01; Spearman’s rho correlation NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-mtDNA, cell-free NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-nDNA, cell-free mitochondrial DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, nuclear DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, urine urine albumin-creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine albumin-creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine ratio (mg/g) ratio (mg/g) Chang et al. BMC Nephrology (2019) 20:391 Page 5 of 10 Table 6 Multivariate Predictors of urinary cf- nDNA Predictors Unstandardized Coefficients Standardized Coefficients p value B Std. Error Beta (Constant) −14.839 24.831 0.576 NGAL −0.017 0.024 −0.071 0.502 Urine protein −0.144 0.150 −0.463 0.380 Urine A/C ratio −0.074 0.019 −2.214 0.013* Urine P/C ratio 0.085 0.014 3.526 0.002** R = 0.960; *P <0.05, **P <0.01 NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-nDNA, cell-free nuclear DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, urine albumin- creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine ratio (mg/g) mitochondrial DNA. The DNA concentrations were number of patient and control samples required to ensure expressed as genome equivalents (GE)/mL of urine and meaningful and statistically significant data (with a power of plasma, where 1 GE was equivalent to 6.6 ng DNA [37]. 80%, a sample size of 38 was sufficient to detect an observed Serially diluted human genomic DNA solution were used difference). All statistical analyses were performed using IBM for preparing a six-point calibration curve [38]. SPSS 20 (SPSS, Inc., Chicago, IL, USA) and a qualified statis- tician was employed to determine which tests should be used Plasma neutrophil gelatinase-associated lipocalin (NGAL) and whether they performed the analysis. In all analyses, P- Plasma NGAL concentrations were measured using a values of < 0.05 were considered statistically significant. commercially available assay kit (Immunology Consul- tants Laboratory, Inc., Oregon, USA). Results The demographic and clinical characteristics of the Statistical analysis varying stages of chronic kidney diseases Results are presented as the median (interquartile range) or Table 1 shows significant differences in age, renal func- number (proportion, %). All data were analyzed by the tions, phosphate and low-density lipoprotein levels among ANOVA test, if p with significant will receive further post varying stages of chronic kidney diseases and the further hoc test analysis. A multivariate linear regression model was post hoc test analysis showed CKD stage related. High in- used to evaluate independent associations between possible cidence, 37 to 59%, of hypertension encounters in varying predictors and cf-mtDNA or cf-nDNA. Receiver operator stage CKD patients. Concerning DM, the incidence is in- characteristics (ROC) curve analysis was performed to assess creasing comparable to CKD stage worsen, 12% DM in different samples of cf-DNA and NGAL to predict renal dis- early stage CKD and 54% in stage 5 CKD. ease related outcomes. Youden’s index is the sum of sensitiv- ity and specificity minus one, which is the most commonly The levels of cell-free mitochondrial (cf-mtDNA) and used criterion for cut-off point selection in the context of nuclear deoxyribonucleic acid (cf-nDNA), both urine and ROC curve analysis. The maximum value of the index may plasma, in varying stages of CKD patients be used as a criterion for selecting the optimum cut-off The plasma levels of neutrophil gelatinase-associated lipoca- point. We used logistic regression to analyze the significant lin (NGAL) significantly increase among the advanced stages predictors of dissimilar renal outcome at 6 months. Statistical of CKD (Table 2, Additional file 1:Fig.S1A). Theplasma methods were employed to determine the appropriate levels of cf-nDNA decrease as the renal function Table 7 Multivariate Predictors of urinary cf- mtDNA Predictors Unstandardized Coefficients Standardized Coefficients p value B Std. Error Beta (Constant) −1.790 2.295 0.471 NGAL −0.001 0.002 −0.049 0.597 Urine protein −0.018 0.014 −0.537 0.261 Urine A/C ratio −0.007 0.002 −1.867 0.015* Urine P/C ratio 0.008 0.001 3.277 0.002** R = 0.969; *P < 0.05, **P < 0.01 NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-mtDNA, cell-free mitochondrial DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, urine albumin-creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine ratio (mg/g) Chang et al. BMC Nephrology (2019) 20:391 Page 6 of 10 Fig. 1 Evaluation of urinary cf-nDNA and urine cf-mtDNA as predictors of CKD patient outcomes after 6 months. The areas under the curves (AUC) were as follows: urine cf-mtDNA: 0.685 (0.586–0.784, P = 0.001*), and urine cf-nDNA: 0.730 (0.637–0.823, P < 0.001*) deterioration (Additional file 1: Figure S1B), in contrast to cf- mtDNA and mitochondrial copy number (MCN), which is not significantly changed among varying stages of CKD patients. There was no significant changes in urinary cf-mtDNA and cf-nDNA levels for varying stages of CKD. Urinary 8-hydroxy- 2-deoxyguanosine (8-OHdG), a symbolic marker of oxidative stress, is also not signifi- Table 8 Logistic regression analysis of predictors of favorable cantly changed in our study. In post hoc analysis, the renal outcome at 6 months data reveals that base plasma cf-nDNA is significant B S.E. P value Odds ratio 95% C.I. higher in early CKD (stage 1 and 2) than other stages Module 1 and base plasma NGAL level is higher in advanced CKD (stage 3b, 4 and 5) than early CKD. Baseline eGFR .010 .011 .377 1.010 .988 1.031 Gender (male) .044 .494 .929 1.045 .396 2.753 The difference of baseline parameters between different Age .023 .020 .249 1.023 0.984 1.063 (favorable vs. unfavorable) renal outcome at 6 months NGAL .001 .001 .152 1.001 1.000 1.003 (Table 3) Urine cf-mtDNA .596 .266 .025* 1.815 1.076 3.059 There are significantly lesser levels of urinary cf-mtDNA, Constant −2.543 1.632 .119 .079 cf-nDNA and plasma NGAL in the favorable renal out- come group. The levels of urinary 8-hydroxy-2-deoxy- Module 2 guanosine (8-OHdG), plasma cf-mtDNA and plasma cf- Baseline eGFR .027 .014 .061 1.027 .999 1.056 nDNA are not significantly different between favorable Gender (male) .278 .587 .636 1.320 .417 4.175 and unfavorable renal outcome groups. Age .054 .024 .027* 1.056 1.006 1.107 NGAL .002 .001 .110 1.002 1.000 1.004 The correlation between urinary cf-nDNA, cf-mtDNA and Urine cf-nDNA .255 .102 .012* 1.290 1.057 1.575 variables As univariate analysis for the correlation between urinary cf- Constant −5.688 2.182 .009 .003 nDNA, cf-mtDNA and variables (Tables 4 and 5, Add- *P < 0.05. Module 1: test urine cf-mtDNA as a covariate; Module 2: test urine cf-nDNA as a covariate itional file 2: Figure S2 and Additional file 3:FigureS3),the NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-mtDNA, cell-free urinary cf-nDNA is significant correlation with urine PCR, mitochondrial DNA (GE/mL); cf-nDNA, cell-free nuclear DNA (GE/mL); GE/mL, genome equivalents/mL urine ACR, urine protein, cf-mtDNA and plasma NGAL. Chang et al. BMC Nephrology (2019) 20:391 Page 7 of 10 Concurrently, the urinary cf-mtDNA is significant correl- cell death by multifactorial mechanisms. As well-known, the ation with urine PCR, urine ACR, urine protein and cf- process of autophagy is generally assumed to be a mechanism mtDNA. In the multivariate analysis of predictors, we of survival or a cytoprotective mechanism that removes dam- demonstrate that both urine P/C ratio and A/C ratio are aged organelles, proteins, and other macromolecules [42, 43]. the significant predictors for urinary cf-mtDNA and cf- An animal study showed that kidney epithelium and podo- nDNA levels (Tables 6 and 7). cytes were sufficient to trigger a degenerative disease of the kidney with many of the manifestations of human focal seg- Evaluation of urine cf-mtDNA, and urine cf-nDNA levels as mental glomerulosclerosis, following the prevention of au- predictors of CKD patient outcomes after 6 months tophagic flux [11]. Figure 1 shows the urinary cf-mtDNA and cf-nDNA According to the results of a number of studies, cell levels as predictors of CKD patient outcomes after 6 death accompanied by the release of cf-DNA fragments months. The areas under the curves (AUC) were as fol- into the blood and urine can occur through autophagy as lows: urine cf-mtDNA: 0.685 (0.586–0.784, P =0.001*), well as mechanisms of apoptosis and necrosis [42, 43]. A and urine cf-nDNA: 0.730 (0.637–0.823, P <0.001*). Both variety of stress stimuli can induce autophagy process, such are better than plasma NGAL (data not shown). The opti- as infection, oxidative stress, starvation, hypoxia etc. The mal Youden’s index-based cut-off point was estimated. stimulation of autophagy by these stimuli produced cellular Urine cf-mtDNA cut-off value was 0.893 GE/mL, with sen- energy stress and activated 50-adenosine monophosphate sitivity 0.860, 1 – specificity 0.545, and Youden’sindex was activated protein kinase (AMPK) by sensing increases in 0.315. Meanwhile, urinary cf-nDNA cut-off value was 3.116 AMP:ATP and ADP:ATP ratios [43, 44]. In a DN study, GE/mL, with sensitivity 0.907 and 1 – Specificity 0.530, and Dr. Wei found a statistically significant inverse correlation Youden’s index was 0.377. Via logistic regression analysis, between urinary supernatant and intra-renal mtDNA levels we confirmed that both urine cf-mtDNA and urine cf- [39]. These findings were inter-related to our results where nDNA could be the significant predictors for dissimilar renal high urinary cfDNA levels might be a marker to predict outcome (favorable vs. unfavorable) at 6 months (Table 8). kidney tissue injury in CKD patients and a worse renal out- come. According multivariate analysis, we suggested that Discussion urine P/C ratio and A/C ratio are both the significant pre- To the best of our knowledge, this study is the first to dictors for urinary cf-nDNA and cf-mtDNA levels. How- show the clinical significant correlation between urine ever, we did not find a statistically significant correlation cf-mtDNA, urine cf-nDNA and divergent renal outcome between urinary cfDNA and CKD staging, possibly because at 6 months. We also propose that both urine PCR and of the relatively small population enrolled. ACR could significantly predict urinary cf-nDNA and cf- The detection of microalbuminuria is a standard method mtDNA levels. to diagnose the early stages of DKD; however, some patients Our study showed greater amounts of cf-nDNA in with microalbuminuria have advanced renal disease [45]. earlier stage CKD, but no correlation between urinary Microalbuminuria is not as sensitive as invasive renal biopsy. nuclear and mitochondria cf-DNA and CKD staging. There is an unmet need to identify non-invasive biomarkers Otherwise, there were greater quantities of urinary cf- of DKD in its early stages [45–49]. Our AUC analysis nDNA and cf-mtDNA in the unfavorable renal outcome showed that urinary cf-nDNA and cf-mtDNA levels were re- group. Our findings were consistent with the results liable to predict renal function outcomes within 6 months. from a diabetes population study that showed mtDNA Our findings were consistent with the positive cor- was readily detectable in urinary supernatant and kidney relation between NGAL levels and CKD staging. The tissue, and that its levels correlated with renal function NGAL gene product is a protein (23–26 kDa) induced and scarring in DN [39]. However, their study did not by triggers of acutekidneyinjury[50, 51]. NGAL is measure plasma cf-DNA levels or a correlation between rapidly released from renal tubular cells in response urinary nuclear cf-DNA levels and DN prognosis. to various insults to the kidney. In contrast, NGAL The death of cells in the tissues is an active process was recently shown to be useful in the quantitation that supports the homeostasis of tissues [40] and in- and prediction of CKD [52, 53]. Bolignano et al. re- crease of cf-DNA in plasma might occur due to the en- ported that NGAL closely reflected the entity of renal im- hancement of programmed cell death [41]. In AKI pairment and represented an independent risk marker for models, the activation of autophagy provided a signifi- the progression of CKD [52]. Liuetal.,however,demon- cant contribution to the elimination of damaged cells strated that urine NGAL levels did not predict progressive from tissues [41]. Our CKD cohort findings of more CKD [54]. NGAL is a member of the lipocalin family of pro- plasma cf-DNA in earlier stage CKD suggested that low teins that has been extensively studied in acute kidney injury plasma cf-DNA in later stages, even stages 4–5, indi- (AKI). NGAL is a robustly expressed protein in the kidney cated the deregulation or decompensation of programmed following ischemic or nephrotoxic injury in animals [55]and Chang et al. BMC Nephrology (2019) 20:391 Page 8 of 10 humans [56]. Via AUC analysis, we demonstrated that Funding This study was supported by 104-CCH-ICO-002 and 103-CCH-IRP-009 from cfDNA might be more sensitive than well-known CKD bio- Changhua Christian Hospital, Changhua, Taiwan. This funding body had no markerssuch asNGAL(data notshown). role in the design of this study and will not have any role during its collec- There are several potential limitations to this study. tion, analyses, interpretation of the data, or decision to submit results. First, a relatively low number of patients were investi- Availability of data and materials gated. Secondary, we conducted a cohort study for our All data and materials are availability in the draft. clinical analysis of less than 12 months duration. Third, Ethics approval and consent to participate there was subject-to-selection bias and information All experimental protocols were approved by the Institutional Review Board on exposure was subject to observation bias from of Changhua Christian Hospital (approval number 140306) and all the the statistic model. Only large-scale collaborative participants provided written informed consent to participate in the study. multicenter or international studies will identify im- Consent for publication portant risk factors. Finally, other hard outcomes in Not applicable. more than 6 months, beside eGFR surrogate, could be conducted in future study. Competing interests The authors declare that they have no competing interests. Conclusions Author details Department of Internal Medicine, Kuang Tien General Hospital, Taichung, In conclusion, both urinary cf-mtDNA and cf-nDNA should Taiwan. Department of Nutrition, Hungkuang University, Taichung, Taiwan. be novel biomarkers to predict the prognosis of chronic renal School of Medicine, Chung Shan Medical University, Taichung, Taiwan. diseases. The levels of plasma cf-nDNA and NGAL were sig- Nephrology Division, Department of Internal Medicine, Changhua Christian Hospital, Changhua, Taiwan. Vascular & Genomic Research Center, nificantly correlated with the severity of CKD. Changhua Christian Hospital, Changhua, Taiwan. Center of General Education Tunghai University, Taichung, Taiwan. Internal Medicine Research Center, Changhua Christian Hospital, Changhua, Taiwan. Department of Supplementary information Neurology, Changhua Christian Hospital, Changhua, Taiwan. Department of The online version of this article (https://doi.org/10.1186/s12882-019-1549-x) Cardiology, Changhua Christian Hospital, Changhua, Taiwan. Institute of contains supplementary material, which is available to authorized users. Statistics and Information Science, National Changhua University of Education, Changhua, Taiwan. School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. Department of Beauty Additional file 1. Figure S1. Box-whisker plots for plasma NGAL (Figure Science and Graduate Institute of Beauty Science Technology, Chienkuo S1A) and plasma cf-nDNA (Figure S1B) levels in varying stages of CKD. Technology University, Changhua, Taiwan. Additional file 2. Figure S2. Scatter-plots for correlation analysis between urinary cf-nDNA and different variables. Figure S2A Correlation Received: 25 February 2019 Accepted: 4 September 2019 between urine cf-nDNA and urine protein/creatinine ratio. Figure S2B Correlation between urine cf-nDNA and urine albumin/creatinine ratio. Figure S2C Correlation between urine cf-nDNA and urine protein ratio. References Figure S2D Correlation between urine cf-nDNA and plasma NGAL. Figure 1. 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Abbreviations Lancet. 2005;365:331–40. https://doi.org/10.1016/S0140-6736(05)17789-7. 8-OH dG: 8-hydroxy-2-deoxyguanosine; ACR: albumin-creatinine ratio; 4. Bello AK, Nwankwo E, El Nahas AM. Prevention of chronic kidney disease: a global AKI: acute kidney injury; cf-DNA: cell-free DNA; cf-mtDNA: cell-free challenge. Kidney Int Suppl. 2005;98:S11–7. https://doi.org/10.1111/j.1523-1755.2005.09802.x. mitochondrial DNA; cf-nDNA: cell-free nuclear DNA; CKD: chronic kidney 5. Gansevoort RT, Correa-Rotter R, Hemmelgarn BR, Jafar TH, Heerspink HJ, disease; DNA: deoxyribonucleic acid; eGFR: estimated glomerular filtration Mann JF, et al. Chronic kidney disease and cardiovascular risk: rate; eGFR : CKD- Epidemiology Collaboration equation; EMT: epithelial– CKD-EPI epidemiology, mechanisms, and prevention. Lancet. 2013;382:339–52. mesenchymal transition; ESRD: end stage renal disease; GE: genome https://doi.org/10.1016/S0140-6736(13)60595-4. equivalents; KDIGO: Kidney Disease Improving Global Outcomes; 6. Che R, Yuan Y, Huang S, Zhang A. Mitochondrial dysfunction in the NGAL: neutrophil gelatinase-associated lipocalin; PCR: protein-creatinine ratio; pathophysiology of renal diseases. Am J Phys Renal Phys. 2013;306:F367–78. ROC: Receiver operator characteristics https://doi.org/10.1152/ajprenal.00571.2013. 7. Yuan Y, Chen Y, Zhang P, Huang S, Zhu C, Ding G, et al. Mitochondrial dysfunction accounts for aldosterone-induced epithelial-to-mesenchymal Acknowledgements transition of renal proximal tubular epithelial cells. Free Radic Biol Med. This project was supported by the Changhua Christian Hospital, Changhua, 2012;53:30–43. https://doi.org/10.1016/j.freeradbiomed.2012.03.015. Taiwan. We thank Edanz Group (www.edanzediting.com/ac) for editing a 8. Zhang A, Jia Z, Guo X, Yang T. 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Urinary cell-free mitochondrial and nuclear deoxyribonucleic acid correlates with the prognosis of chronic kidney diseases

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Abstract

Introduction: Cell-free deoxyribonucleic acid DNA (cf-DNA) in urine is promising due to the advantage of urine as an easily obtained and non-invasive sample source over tissue and blood. In clinical practice, it is important to identify non-invasive biomarkers of chronic kidney disease (CKD) in monitoring and surveillance of disease progression. Information is limited, however, regarding the relationship between urine and plasma cf-DNA and the renal outcome in CKD patients. Methods: One hundred and thirty-one CKD patients were enrolled between January 2016 and September 2018. Baseline urine and plasma cell-free mitochondrial DNA (cf-mtDNA) and cell-free nuclear DNA (cf-nDNA) were isolated using quantitative real-time PCR. Estimated glomerular filtration rate (eGFR) measurement was performed at baseline and 6-month follow-up. Favorable renal outcome was defined as eGFR at 6 months minus baseline eGFR> = 0. Receiver operator characteristics (ROC) curve analysis was performed to assess different samples of cf- DNA to predict favorable renal outcomes at 6 months. A multivariate linear regression model was used to evaluate independent associations between possible predictors and different samples of cf-DNA. Results: Patients with an advanced stage of CKD has significantly low plasma cf-nDNA and high plasma neutrophil gelatinase-associated lipocalin (NGAL) levels. Low urine cf-mtDNA, cf-nDNA levels and low plasma NGAL were significantly correlated with favorable renal outcomes at 6 months. The urine albumin-creatinine ratio (ACR) or urine protein-creatinine ratio (PCR) level is a robust predictor of cf-mtDNA and cf-nDNA in CKD patients. Baseline urine levels of cf-mtDNA and cf- nDNA could predict renal outcomes at 6 months. Conclusions: Urinary cf-mtDNA and cf-nDNA may provide novel prognostic biomarkers for renal outcome in CKD patients. Thelevels ofplasmacf-nDNA andplasmaNGAL are significantlycorrelatedwiththe severity of CKD. Keywords: Cell-free mitochondrial deoxyribonucleic acid, Cf-mtDNA, Cell-free nuclear deoxyribonucleic acid, Cf-nDNA, Neutrophil gelatinase-associated lipocalin, NGAL, Chronic kidney disease Background CKD and timely detection of progression are truly global Chronic kidney disease (CKD) is a global public health prob- challenges [3, 4]. It is important to recognize the risk factors lem affecting up to 10% of the population worldwide [1], al- of CKD, and better approaches for the prevention, early de- though guidelines for the clinical staging of CKD have been tection, and treatment of CKD [5]. established [2]. The natural history of the earlier phases of The kidney is a highly energetic organ and rich in mito- CKD are highly unpredictable and the early identification of chondria and numerous studies have shown that mitochon- drial dysfunction contributestodifferent typesofkidney * Correspondence: 28071@cch.org.tw diseases, including diabetic and nondiabetic nephropathy [6]. Chin-San Liu and Ching-Hui Huang contributed equally to this work. Proteinuria, caused by a primary insult to the kidney, induces Vascular & Genomic Research Center, Changhua Christian Hospital, oxidative stress in renal tubular cells and causes mitochon- Changhua, Taiwan Department of Cardiology, Changhua Christian Hospital, Changhua, Taiwan drial dysfunction [7, 8], which leads to cellular damage by Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Chang et al. BMC Nephrology (2019) 20:391 Page 2 of 10 reactive oxygen species generation as well as epithelial–mes- Since the majority of urine cf-DNA originates from apop- enchymal transition (EMT) [9, 10]. To date, CKD is charac- tosis or necrosis of cells exfoliated from urogenital system terized by mitochondrial dysfunction, oxidative stress, and [30]. And the minority are originating from blood circula- aberrant autophagy [11, 12] in addition to significant changes tion, which contains important genomic information from in the activation of transforming growth factor-β,p53,hyp- various positions all over the body [33, 34]. We postulate oxia-inducible factor, chronic inflammation, and traditional that urine cf-DNA might be regarded as a marker which vascular dysfunction [11]. By the experimental models of combined genetic information from urogenital system and CKD, preventing mitochondrial dysfunction inhibits renal systemic. We hypothesis that urinary cf-DNA might be a tubular cell EMT and renal fibrosis [13]. However, only a better novel biomarker than circulating cf-DNA in pre- relatively small number of translational studies have shown dicting renal outcome in CKD patients. To clarify the clin- the clinical relevance of these mechanisms between renal dis- ical application of cf-mtDNA and cf-nDNA in CKD, we eases and mitochondrial dysfunction in humans [6, 14, 15]. studied the correlation between cf-mtDNA and cf-nDNA, Free circulating nucleic acids, cell-free deoxyribonucleic both urine and plasma, and the stage of CKD or prognosis acid (cf-DNA), were discovered in human plasma in 1948 of renal outcomes. by Mandel and Metais [16]. Some studies showed the damaged mitochondria release their DNA content into Methods the systemic circulation [17, 18]. Thus, cell-free mitochon- The Institutional Review Board of Changhua Christian drial deoxyribonucleic acid (cf-mtDNA) is easily detected Hospital approved the experimental protocols (approval in plasma, and has been explored as a biomarker of vari- number 140306) and all the participants provided written ous diseases [19–21]. Recently, increased plasma levels of informed consent to participate the study. All patients of cf-mtDNA have been reported to correlate with the sever- the study joined our nationwide preventive multidisciplin- ity of injury in patients sustaining polytrauma [22] and the ary program, also regulated by the Clinical Care Program severity of stroke [23], be a prognostic marker of acute Certification and Joint Commission International, for early myocardial infarction [24] and intensive care unit patients CKD or pre-ESRD (end stage renal disease). We investi- [25, 26]. Alterations of cf-mtDNA in the blood also might be gated patients who were enrolled in our CKD care pro- associated with several systemic diseases, including primary gram between January 2016 and September 2018.The mitochondrial disorders, carcinogenesis, and hematologic dis- goals for patients’ blood pressure, glucose and lipid con- eases [27, 28]. In a community-based population cohort, trol were based on the KDOGI guidelines. higher plasma cf-mtDNA was associated with a lower inci- Overall, of 131 patients with CKD, 7 patients dropped-out dence of CKD independent of traditional risk factors [20]and for the duration of follow-up less than 6 months, and 52 vol- was associated with a lower prevalence of microalbuminuria unteers were recruited from the Nephrology Clinic at Chan- [29]. Apart from blood, cf-DNA could also be detected in ghua Christian Hospital, a tertiary referral hospital in Taiwan. urine. Urine cf-DNA originates either from cells shedding into The duration of follow-up for CKD was more than 6 months urine from genitourinary tract, or from cell free DNA in circu- in all patients. The patients with following criteria were ex- lation passing through glomerular filtration [30]. The presence cluded: infection, acute fever, hepatic or cardiac disease, endo- of genetic information in urine has been observed in some crinopathy, glomerulonephritis proved by biopsy or treatment clinical studies. For examples, the urinary cf-mtDNA level had with steroids or immunosuppressants, surgery, trauma, miss- statistically significant correlations with the peak serum cre- ing data at baseline, prior kidney transplant, acute kidney in- atinine level and the duration of hospitalization in a study of jury and a history of RRT or hospitalization for any cause in acutekidneyinjury(AKI) [30]. Patients who required tempor- the past 3 months. The amount of proteinuria was calculated ary dialysis also tended to have higher urinary cf-mtDNA by urinary protein-creatinine ratio (PCR, mg/g) or albumin- levels than those without dialysis [31], but no relationship be- creatinine ratio (ACR, mg/g). Microalbuminuria was estab- tween the urinary cf-mtDNA level and renal outcomes has lished when two out of three ACR determinations were found been reported. A recent study showed that urinary cf-mtDNA to be within the range of 30–300 mg/g in a 6-month period. level was increased in mice after 10–15 min of ischemia, and We calculated the glomerular filtration rate (eGFR) of the pa- that the level correlated with the duration of ischemia [32]. tients according to the CKD Epidemiology Collaboration Otherwise, platelet and leukocyte counts in samples are im- equation (eGFR )[35]. The stages of CKD were defined CKD-EPI portant sources of variation when cf-DNA is measured in as follows: stage 1, eGFR > 90 ml/min/1.73 m ;stage 2, eGFR DNA extracted from whole blood [27, 28]. Emerging data 60–89 ml/min/1.73 m ;stage 3a, eGFR45–59 ml/min/1.73 2 2 showed that measuring cf-DNA extracted from whole blood m ;stage 3b,eGFR30–44 ml/min/1.73 m ;stage 4, eGFR 15– 2 2 (nuclear deoxyribonucleic acid, cf-nDNA) could yield different 29 ml/min/1.73 m and stage 5, eGFR < 15 ml/min/1.73 m or results from peripheral blood mononuclear cells or buffy coat maintenance on RRT. We divided the population to early (cf-mtDNA), because of the presence of mitochondrial DNA CKD (stages 1–3a) and advanced CKD (stages 3b–5) in the in platelets [27, 28]. study, based on our national CKD care program. Chang et al. BMC Nephrology (2019) 20:391 Page 3 of 10 Table 1 Demographic characteristics of varying stages of chronic kidney disease a b c d Variables Stage 1,2 Stage 3A Stage 3B Stage 4,5 p value Post hoc n =23 n =28 n =31 n =42 Age (year) 47.1 ± 12.7 53.6 ± 9.4 54.9 ± 10.5 58.7 ± 6.1 0.002* a < c,d Gender (M/F) 3/20 8/20 22/9 29/13 0.212 Hypertension (%) 42% 37% 59% 54% 0.191 Diabetes mellitus (%) 12% 11% 23% 54% 0.160 Systolic blood pressure (mm Hg) 138 ± 18 144 ± 28 138 ± 24 142 ± 15 0.943 Diastolic blood pressure (mm Hg) 90 ± 15 91 ± 4 84 ± 18 84 ± 12 0.784 BMI (kg/m ) 27.8 ± 5.4 28.2 ± 6.1 26.2 ± 6.1 24.8 ± 4.3 0.172 BUN (mg/dL) 14.3 ± 4.4 17.7 ± 3.8 31.4 ± 13.0 64.5 ± 27.1 <0.001** a,b < c < d eGFR (ml/min/1.73 m^2) 84.4 ± 20.2 52.1 ± 4.4 31 ± 9.6 11.5 ± 7.3 <0.001** a > b > c > d Phosphate (mg/dL) 3.5 ± 0.4 3.5 ± 0.6 4.0 ± 0.7 5.0 ± 1.1 <0.001** a,b,c < d Cholesterol (mg/dL) 198.3 ± 50.4 171.5 ± 31.8 196.6 ± 47.3 153.3 ± 44.5 0.001** a,c > d HDL-C (mg/dL) 47.8 ± 14.3 43.3 ± 9.8 46.1 ± 12.6 46.7 ± 21.2 0.677 LDL-C (mg/dL) 118.2 ± 45.3 104.6 ± 31.4 114.9 ± 41.3 80.8 ± 26.7 0.040* c > d Fasting Glucose (mg/dL) 118.3 ± 46.1 106 ± 21.8 112.6 ± 43.5 94.9 ± 24.6 0.263 HbA1C (%) 6.3 ± 1.4 6.0 ± 0.6 6.2 ± 1.1 6.1 ± 0.9 0.778 Urine A/C ratio (mg/g) 438.0 ± 826.4 535.7 ± 1018.4 2121.3 ± 2540.7 1548.0 ± 2377.2 0.058 WBC (×10 /μL) 7.1 ± 2.4 6.2 ± 1.9 6.4 ± 2.1 6.8 ± 2.0 0.323 Uric Acid (mg/dL) 7.1 ± 1.2 7.0 ± 1.4 7.5 ± 2.6 7.0 ± 1.2 0.629 Platelet(×10 /μL) 230.2 ± 72.6 209.2 ± 59.5 201.9 ± 51.1 195.1 ± 58.2 0.159 P-value by One-Way ANOVA follow with Bonferroni multiple comparisons at type I error of 0.05 level *P <0.05, **P <0.01. Gender (M/F), female/male; BMI, body mass index; BUN, blood urea nitrogen; HDL, high-density lipoprotein; LDL, low-density lipoprotein; HbA1C, glycated hemoglobin; WBC, white blood count; eGFR, estimated glomerular filtration rate; urine A/C ratio, urine albumin-creatinine ratio a b c d Post hoc: indicates group stage 1,2; indicates group stage 3a; indicates group stage 3b; indicates group stage 4,5 Studies in CKD always address primary outcomes of death, 6 months minus baseline eGFR> = 0; unfavorable renal out- ESRD, or doubling of baseline serum creatinine. Coresh et al. come indicated eGFR at 6 months minus baseline eGFR <0. extended use of percentage reduction in eGFR as a surrogate for hard outcomes and they reported that longer–term fol- Blood, plasma and urine sampling low-up, more than 1 year, was strongly predictive of ESRD Participants’ venous blood samples, following 8-h overnight and death [36]. We, therefore, examined the change of eGFR fasting, were obtained and first morning urine samples were as a surrogate for hard outcomes within 6 months. For study collected. Aliquots of urine were immediately frozen simplicity, favorable renal outcome was defined as eGFR at at − 80 °C until further analysis, but specimen reserved for Table 2 The levels of different parameters in varying stages of CKD a b c d Stage 1,2 Stage 3 Stage 3 Stage 4,5 P value Post hoc tests Plasma cf-mtDNA (GE/mL) 523 ± 710 373 ± 360 420 ± 664 112 ± 134 0.209 Plasma cf-nDNA (GE/mL) 1269 ± 1195 698 ± 527 439 ± 569 104 ± 70.01 <0.001** a > b,c,d Urine cf-mtDNA (GE/mL) 0.43 ± 0.69 0.98 ± 3.10 2.78 ± 10.12 6.49 ± 17.85 0.220 Urine cf-nDNA (GE/mL) 2.83 ± 4.60 4.49 ± 12.09 15.39 ± 44.01 8.01 ± 12.08 0.351 Plasma NGAL (ng/mL) 394 ± 175 489.6 ± 174.9 744.2 ± 272.1 1096 ± 488.7 <0.001** a,b,<c,d MCN (per cell) 90.7 ± 66.9 94.9 ± 77.01 92.9 ± 89.9 110.5 ± 112.7 0.901 Urine 8-OH dG/Cr 3.73 ± 1.81 3.78 ± 2.93 4.15 ± 2.65 2.99 ± 1.53 0.416 P-value by One-Way ANOVA follow with Bonferroni multiple comparisons at type I error of 0.05 level *P <0.05, **P <0.01 a b c d Post hoc indicates group stage 1,2; indicates group stage 3a; indicates group stage 3b; indicates group stage 4,5 MCN mitochondrial copy number, NGAL neutrophil gelatinase-associated lipocalin; 8-OH dG 8-hydroxy-2-deoxyguanosine, cf-mtDNA cell-free mitochondrial DNA, cf-nDNA cell-free nuclear DNA, GE/mL genome equivalents/mL Chang et al. BMC Nephrology (2019) 20:391 Page 4 of 10 Table 3 The difference of baseline parameters between favorable and unfavorable renal outcome at 6 months Favorable renal outcome Unfavorable renal outcome P value (n = 53) (n = 70) Plasma cf-mtDNA (GE/mL) 441.1 ± 525.6 370.6 ± 641.9 0.538 Plasma cf-nDNA (GE/mL) 760.9 ± 732.9 554.1 ± 850.9 0.184 Urine cf-mtDNA (GE/mL) 0.489 ± 0.751 3.745 ± 12.197 0.027* Urine cf-nDNA (GE/mL) 1.764 ± 2.388 15.119 ± 40.791 0.009* MCN (per cell) 87.21 ± 69.40 101.55 ± 95.75 0.356 Urine 8-OH dG/Cr 3.62 ± 2.44 4.03 ± 2.44 0.346 NGAL (ng/mL) 585.24 ± 251.62 780.85 ± 391.39 0.032* *P < 0.05, Student’s test MCN, mitochondrial copy number; NGAL, neutrophil gelatinase-associated lipocalin; 8-OH dG, 8-hydroxy-2-deoxyguanosine; cf-mtDNA, cell-free mitochondrial DNA; cf-nDNA, cell-free nuclear DNA; GE/mL, genome equivalents /mL Favorable renal outcome indicated eGFR at 6 months minus baseline eGFR> = 0; unfavorable renal outcome indicated eGFR at 6 months minus baseline eGFR <0 no longer than 1 month. All assays were undertaken in Leukocyte mitochondrial DNA copy number duplicate with intra-assay variation coefficient less than We used a LightCycler® 480 Instrument (Roche, Mannheim, 5%. Urinary albumin concentration was measured by an Germany) to measure mitochondrial copy number (MCN) immunoturbidimetric method (Roche Diagnostics GmbH, in leukocytes. Briefly, we extracted total DNA using the Mannheim, Germany). Gentra Puregene DNA kit (Qiagen, Hilden, Germany). Real- time polymerase chain reaction (PCR) was used to amplify DNA isolation and qPCR the ND1 gene of mtDNA and β-globin of nuclear DNA, re- The baseline data of urine and plasma cell-free mitochondrial spectively. The relative MCN of mtDNA was normalized to DNA (cf-mtDNA) and cell-free nuclear DNA (cf-nDNA) the β-globin gene. were isolated from 131 patients with CKD in our study. Blood collection were drawn from each subject in the morning after Quantification of urine and plasma cell-free DNA by real- overnight fasting 8 h. For each subject, 5 ml of whole blood time PCR was withdrawn from an antecubital vein and quickly delivered Baseline urine and plasma cf-mtDNA and cf-nDNA were into an EDTA-K3-containing plastic tube. Plasma was col- quantified by real-time PCR using the LightCycler® 480 In- lected by centrifugation of blood at 2500 rpm for 10 min, di- strument (Roche, Mannheim, Germany) using specific vided into several aliquots, and stored in − 80 °C until analysis. primers to amplify the β-globin (forward: 5′-GTG CAC Urine samples were placed on 4 °C, centrifuged at 12000 rpm CTG ACT CCT GAG GAG A-3′,reverse: 5′-CCT TGA for 15 min within 8 h of collection, and the urine supernatants TAC CAA CCT GCC CAG-3′) and MT-ND1 (forward: were separated and stored at − 80 °C until extraction DNA. AACATACCCATGGCCAACCT, reverse: AGCGAA Plasma and Urine cfDNA was extracted urine the Viral DNA GGGTTGTAGTAGCCC) genes from urine and plasma mini Kit (AccuBioMed, Co, Ltd., Taiwan), following the proto- DNA, and standard regression analyses were used to de- col of manufacturer. rive the amount of urine and plasma nuclear DNA and Table 4 Univariate correlation between urinary cf-nDNA and Table 5 Univariate correlation between urinary cf-mtDNA and variables variables Variable Rho correlation coefficient P value Variable Rho correlation coefficient P value Urine A/C ratio (mg/g) 0.408 0.005* Urine A/C ratio (mg/g) 0.375 0.008* Urine P/C ratio (mg/g) 0.314 0.007* Urine P/C ratio (mg/g) 0.349 0.002** Urine cf-mtDNA (GE/mL) 0.448 <0.001** Urine cf-nDNA (GE/mL) 0.448 <0.001** Urine protein (mg/dL) 0.246 0.029* Urine protein (mg/dL) 0.167 0.125 NGAL (ng/mL) 0.322 0.001** NGAL (ng/mL) 0.168 0.066 *P < 0.05, **P <0.01; Spearman's rho correlation *P < 0.05, **P < 0.01; Spearman’s rho correlation NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-mtDNA, cell-free NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-nDNA, cell-free mitochondrial DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, nuclear DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, urine urine albumin-creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine albumin-creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine ratio (mg/g) ratio (mg/g) Chang et al. BMC Nephrology (2019) 20:391 Page 5 of 10 Table 6 Multivariate Predictors of urinary cf- nDNA Predictors Unstandardized Coefficients Standardized Coefficients p value B Std. Error Beta (Constant) −14.839 24.831 0.576 NGAL −0.017 0.024 −0.071 0.502 Urine protein −0.144 0.150 −0.463 0.380 Urine A/C ratio −0.074 0.019 −2.214 0.013* Urine P/C ratio 0.085 0.014 3.526 0.002** R = 0.960; *P <0.05, **P <0.01 NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-nDNA, cell-free nuclear DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, urine albumin- creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine ratio (mg/g) mitochondrial DNA. The DNA concentrations were number of patient and control samples required to ensure expressed as genome equivalents (GE)/mL of urine and meaningful and statistically significant data (with a power of plasma, where 1 GE was equivalent to 6.6 ng DNA [37]. 80%, a sample size of 38 was sufficient to detect an observed Serially diluted human genomic DNA solution were used difference). All statistical analyses were performed using IBM for preparing a six-point calibration curve [38]. SPSS 20 (SPSS, Inc., Chicago, IL, USA) and a qualified statis- tician was employed to determine which tests should be used Plasma neutrophil gelatinase-associated lipocalin (NGAL) and whether they performed the analysis. In all analyses, P- Plasma NGAL concentrations were measured using a values of < 0.05 were considered statistically significant. commercially available assay kit (Immunology Consul- tants Laboratory, Inc., Oregon, USA). Results The demographic and clinical characteristics of the Statistical analysis varying stages of chronic kidney diseases Results are presented as the median (interquartile range) or Table 1 shows significant differences in age, renal func- number (proportion, %). All data were analyzed by the tions, phosphate and low-density lipoprotein levels among ANOVA test, if p with significant will receive further post varying stages of chronic kidney diseases and the further hoc test analysis. A multivariate linear regression model was post hoc test analysis showed CKD stage related. High in- used to evaluate independent associations between possible cidence, 37 to 59%, of hypertension encounters in varying predictors and cf-mtDNA or cf-nDNA. Receiver operator stage CKD patients. Concerning DM, the incidence is in- characteristics (ROC) curve analysis was performed to assess creasing comparable to CKD stage worsen, 12% DM in different samples of cf-DNA and NGAL to predict renal dis- early stage CKD and 54% in stage 5 CKD. ease related outcomes. Youden’s index is the sum of sensitiv- ity and specificity minus one, which is the most commonly The levels of cell-free mitochondrial (cf-mtDNA) and used criterion for cut-off point selection in the context of nuclear deoxyribonucleic acid (cf-nDNA), both urine and ROC curve analysis. The maximum value of the index may plasma, in varying stages of CKD patients be used as a criterion for selecting the optimum cut-off The plasma levels of neutrophil gelatinase-associated lipoca- point. We used logistic regression to analyze the significant lin (NGAL) significantly increase among the advanced stages predictors of dissimilar renal outcome at 6 months. Statistical of CKD (Table 2, Additional file 1:Fig.S1A). Theplasma methods were employed to determine the appropriate levels of cf-nDNA decrease as the renal function Table 7 Multivariate Predictors of urinary cf- mtDNA Predictors Unstandardized Coefficients Standardized Coefficients p value B Std. Error Beta (Constant) −1.790 2.295 0.471 NGAL −0.001 0.002 −0.049 0.597 Urine protein −0.018 0.014 −0.537 0.261 Urine A/C ratio −0.007 0.002 −1.867 0.015* Urine P/C ratio 0.008 0.001 3.277 0.002** R = 0.969; *P < 0.05, **P < 0.01 NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-mtDNA, cell-free mitochondrial DNA (GE/mL); GE/mL, genome equivalents/mL; urine A/C ratio, urine albumin-creatinine ratio (mg/g); urine P/C ratio, urine protein-creatinine ratio (mg/g) Chang et al. BMC Nephrology (2019) 20:391 Page 6 of 10 Fig. 1 Evaluation of urinary cf-nDNA and urine cf-mtDNA as predictors of CKD patient outcomes after 6 months. The areas under the curves (AUC) were as follows: urine cf-mtDNA: 0.685 (0.586–0.784, P = 0.001*), and urine cf-nDNA: 0.730 (0.637–0.823, P < 0.001*) deterioration (Additional file 1: Figure S1B), in contrast to cf- mtDNA and mitochondrial copy number (MCN), which is not significantly changed among varying stages of CKD patients. There was no significant changes in urinary cf-mtDNA and cf-nDNA levels for varying stages of CKD. Urinary 8-hydroxy- 2-deoxyguanosine (8-OHdG), a symbolic marker of oxidative stress, is also not signifi- Table 8 Logistic regression analysis of predictors of favorable cantly changed in our study. In post hoc analysis, the renal outcome at 6 months data reveals that base plasma cf-nDNA is significant B S.E. P value Odds ratio 95% C.I. higher in early CKD (stage 1 and 2) than other stages Module 1 and base plasma NGAL level is higher in advanced CKD (stage 3b, 4 and 5) than early CKD. Baseline eGFR .010 .011 .377 1.010 .988 1.031 Gender (male) .044 .494 .929 1.045 .396 2.753 The difference of baseline parameters between different Age .023 .020 .249 1.023 0.984 1.063 (favorable vs. unfavorable) renal outcome at 6 months NGAL .001 .001 .152 1.001 1.000 1.003 (Table 3) Urine cf-mtDNA .596 .266 .025* 1.815 1.076 3.059 There are significantly lesser levels of urinary cf-mtDNA, Constant −2.543 1.632 .119 .079 cf-nDNA and plasma NGAL in the favorable renal out- come group. The levels of urinary 8-hydroxy-2-deoxy- Module 2 guanosine (8-OHdG), plasma cf-mtDNA and plasma cf- Baseline eGFR .027 .014 .061 1.027 .999 1.056 nDNA are not significantly different between favorable Gender (male) .278 .587 .636 1.320 .417 4.175 and unfavorable renal outcome groups. Age .054 .024 .027* 1.056 1.006 1.107 NGAL .002 .001 .110 1.002 1.000 1.004 The correlation between urinary cf-nDNA, cf-mtDNA and Urine cf-nDNA .255 .102 .012* 1.290 1.057 1.575 variables As univariate analysis for the correlation between urinary cf- Constant −5.688 2.182 .009 .003 nDNA, cf-mtDNA and variables (Tables 4 and 5, Add- *P < 0.05. Module 1: test urine cf-mtDNA as a covariate; Module 2: test urine cf-nDNA as a covariate itional file 2: Figure S2 and Additional file 3:FigureS3),the NGAL, neutrophil gelatinase-associated lipocalin (ng/mL); cf-mtDNA, cell-free urinary cf-nDNA is significant correlation with urine PCR, mitochondrial DNA (GE/mL); cf-nDNA, cell-free nuclear DNA (GE/mL); GE/mL, genome equivalents/mL urine ACR, urine protein, cf-mtDNA and plasma NGAL. Chang et al. BMC Nephrology (2019) 20:391 Page 7 of 10 Concurrently, the urinary cf-mtDNA is significant correl- cell death by multifactorial mechanisms. As well-known, the ation with urine PCR, urine ACR, urine protein and cf- process of autophagy is generally assumed to be a mechanism mtDNA. In the multivariate analysis of predictors, we of survival or a cytoprotective mechanism that removes dam- demonstrate that both urine P/C ratio and A/C ratio are aged organelles, proteins, and other macromolecules [42, 43]. the significant predictors for urinary cf-mtDNA and cf- An animal study showed that kidney epithelium and podo- nDNA levels (Tables 6 and 7). cytes were sufficient to trigger a degenerative disease of the kidney with many of the manifestations of human focal seg- Evaluation of urine cf-mtDNA, and urine cf-nDNA levels as mental glomerulosclerosis, following the prevention of au- predictors of CKD patient outcomes after 6 months tophagic flux [11]. Figure 1 shows the urinary cf-mtDNA and cf-nDNA According to the results of a number of studies, cell levels as predictors of CKD patient outcomes after 6 death accompanied by the release of cf-DNA fragments months. The areas under the curves (AUC) were as fol- into the blood and urine can occur through autophagy as lows: urine cf-mtDNA: 0.685 (0.586–0.784, P =0.001*), well as mechanisms of apoptosis and necrosis [42, 43]. A and urine cf-nDNA: 0.730 (0.637–0.823, P <0.001*). Both variety of stress stimuli can induce autophagy process, such are better than plasma NGAL (data not shown). The opti- as infection, oxidative stress, starvation, hypoxia etc. The mal Youden’s index-based cut-off point was estimated. stimulation of autophagy by these stimuli produced cellular Urine cf-mtDNA cut-off value was 0.893 GE/mL, with sen- energy stress and activated 50-adenosine monophosphate sitivity 0.860, 1 – specificity 0.545, and Youden’sindex was activated protein kinase (AMPK) by sensing increases in 0.315. Meanwhile, urinary cf-nDNA cut-off value was 3.116 AMP:ATP and ADP:ATP ratios [43, 44]. In a DN study, GE/mL, with sensitivity 0.907 and 1 – Specificity 0.530, and Dr. Wei found a statistically significant inverse correlation Youden’s index was 0.377. Via logistic regression analysis, between urinary supernatant and intra-renal mtDNA levels we confirmed that both urine cf-mtDNA and urine cf- [39]. These findings were inter-related to our results where nDNA could be the significant predictors for dissimilar renal high urinary cfDNA levels might be a marker to predict outcome (favorable vs. unfavorable) at 6 months (Table 8). kidney tissue injury in CKD patients and a worse renal out- come. According multivariate analysis, we suggested that Discussion urine P/C ratio and A/C ratio are both the significant pre- To the best of our knowledge, this study is the first to dictors for urinary cf-nDNA and cf-mtDNA levels. How- show the clinical significant correlation between urine ever, we did not find a statistically significant correlation cf-mtDNA, urine cf-nDNA and divergent renal outcome between urinary cfDNA and CKD staging, possibly because at 6 months. We also propose that both urine PCR and of the relatively small population enrolled. ACR could significantly predict urinary cf-nDNA and cf- The detection of microalbuminuria is a standard method mtDNA levels. to diagnose the early stages of DKD; however, some patients Our study showed greater amounts of cf-nDNA in with microalbuminuria have advanced renal disease [45]. earlier stage CKD, but no correlation between urinary Microalbuminuria is not as sensitive as invasive renal biopsy. nuclear and mitochondria cf-DNA and CKD staging. There is an unmet need to identify non-invasive biomarkers Otherwise, there were greater quantities of urinary cf- of DKD in its early stages [45–49]. Our AUC analysis nDNA and cf-mtDNA in the unfavorable renal outcome showed that urinary cf-nDNA and cf-mtDNA levels were re- group. Our findings were consistent with the results liable to predict renal function outcomes within 6 months. from a diabetes population study that showed mtDNA Our findings were consistent with the positive cor- was readily detectable in urinary supernatant and kidney relation between NGAL levels and CKD staging. The tissue, and that its levels correlated with renal function NGAL gene product is a protein (23–26 kDa) induced and scarring in DN [39]. However, their study did not by triggers of acutekidneyinjury[50, 51]. NGAL is measure plasma cf-DNA levels or a correlation between rapidly released from renal tubular cells in response urinary nuclear cf-DNA levels and DN prognosis. to various insults to the kidney. In contrast, NGAL The death of cells in the tissues is an active process was recently shown to be useful in the quantitation that supports the homeostasis of tissues [40] and in- and prediction of CKD [52, 53]. Bolignano et al. re- crease of cf-DNA in plasma might occur due to the en- ported that NGAL closely reflected the entity of renal im- hancement of programmed cell death [41]. In AKI pairment and represented an independent risk marker for models, the activation of autophagy provided a signifi- the progression of CKD [52]. Liuetal.,however,demon- cant contribution to the elimination of damaged cells strated that urine NGAL levels did not predict progressive from tissues [41]. Our CKD cohort findings of more CKD [54]. NGAL is a member of the lipocalin family of pro- plasma cf-DNA in earlier stage CKD suggested that low teins that has been extensively studied in acute kidney injury plasma cf-DNA in later stages, even stages 4–5, indi- (AKI). NGAL is a robustly expressed protein in the kidney cated the deregulation or decompensation of programmed following ischemic or nephrotoxic injury in animals [55]and Chang et al. BMC Nephrology (2019) 20:391 Page 8 of 10 humans [56]. Via AUC analysis, we demonstrated that Funding This study was supported by 104-CCH-ICO-002 and 103-CCH-IRP-009 from cfDNA might be more sensitive than well-known CKD bio- Changhua Christian Hospital, Changhua, Taiwan. This funding body had no markerssuch asNGAL(data notshown). role in the design of this study and will not have any role during its collec- There are several potential limitations to this study. tion, analyses, interpretation of the data, or decision to submit results. First, a relatively low number of patients were investi- Availability of data and materials gated. Secondary, we conducted a cohort study for our All data and materials are availability in the draft. clinical analysis of less than 12 months duration. Third, Ethics approval and consent to participate there was subject-to-selection bias and information All experimental protocols were approved by the Institutional Review Board on exposure was subject to observation bias from of Changhua Christian Hospital (approval number 140306) and all the the statistic model. Only large-scale collaborative participants provided written informed consent to participate in the study. multicenter or international studies will identify im- Consent for publication portant risk factors. Finally, other hard outcomes in Not applicable. more than 6 months, beside eGFR surrogate, could be conducted in future study. Competing interests The authors declare that they have no competing interests. Conclusions Author details Department of Internal Medicine, Kuang Tien General Hospital, Taichung, In conclusion, both urinary cf-mtDNA and cf-nDNA should Taiwan. Department of Nutrition, Hungkuang University, Taichung, Taiwan. be novel biomarkers to predict the prognosis of chronic renal School of Medicine, Chung Shan Medical University, Taichung, Taiwan. diseases. The levels of plasma cf-nDNA and NGAL were sig- Nephrology Division, Department of Internal Medicine, Changhua Christian Hospital, Changhua, Taiwan. Vascular & Genomic Research Center, nificantly correlated with the severity of CKD. Changhua Christian Hospital, Changhua, Taiwan. Center of General Education Tunghai University, Taichung, Taiwan. Internal Medicine Research Center, Changhua Christian Hospital, Changhua, Taiwan. Department of Supplementary information Neurology, Changhua Christian Hospital, Changhua, Taiwan. Department of The online version of this article (https://doi.org/10.1186/s12882-019-1549-x) Cardiology, Changhua Christian Hospital, Changhua, Taiwan. Institute of contains supplementary material, which is available to authorized users. Statistics and Information Science, National Changhua University of Education, Changhua, Taiwan. School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. Department of Beauty Additional file 1. Figure S1. Box-whisker plots for plasma NGAL (Figure Science and Graduate Institute of Beauty Science Technology, Chienkuo S1A) and plasma cf-nDNA (Figure S1B) levels in varying stages of CKD. Technology University, Changhua, Taiwan. Additional file 2. Figure S2. Scatter-plots for correlation analysis between urinary cf-nDNA and different variables. Figure S2A Correlation Received: 25 February 2019 Accepted: 4 September 2019 between urine cf-nDNA and urine protein/creatinine ratio. Figure S2B Correlation between urine cf-nDNA and urine albumin/creatinine ratio. Figure S2C Correlation between urine cf-nDNA and urine protein ratio. References Figure S2D Correlation between urine cf-nDNA and plasma NGAL. Figure 1. Nallu A, Sharma S, Ramezani A, Muralidharan J, Raj D. Gut microbiome in S2E Correlation between urine cf-nDNA and urine cf-mtDNA. chronic kidney disease: challenges and opportunities. Transl Res. 2017;179: Additional file 3. Figure S3. Scatter-plots for correlation analysis 24–37. https://doi.org/10.1016/j.trsl.2016.04.007. between urinary cf-mtDNA and different variables. Figure S3A Correlation 2. Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. between urine cf-mtDNA and urine albumin/creatinine ratio. Figure S3B Definition and classification of chronic kidney disease: a position statement Correlation between urine cf-mtDNA and urine protein/creatinine ratio. from kidney disease: improving global outcomes (KDIGO). Kidney Int. 2005; 67:2089–100. https://doi.org/10.1111/j.1523-1755.2005.00365.x. 3. Meguid El Nahas A, Bello AK. Chronic kidney disease: the global challenge. 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Journal

BMC Nephrology – Springer Journals

Published: Dec 1, 2019

Keywords: nephrology; internal medicine

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