Literature DB >> 35363774

The role of CDH2 and MCP-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy.

Hojat Dehghanbanadaki1,2, Katayoon Forouzanfar3, Ardeshir Kakaei2, Samaneh Zeidi1,4, Negar Salehi1,4, Babak Arjmand3,5, Farideh Razi1,6, Ehsan Hashemi1,4.   

Abstract

BACKGROUND: Extracellular vesicles (EVs), including exosomes and microvesicles, are involved in intercellular communication by transferring biomolecules such as mRNA, which has been shown to be as essential biomarkers for many physiological and pathological conditions such as diabetic nephropathy (DN). This study aimed to investigate the expression of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in blood EVs of DN patients and to determine their accuracy in predicting early-stage DN.
METHODS: We recruited 196 participants, including 35 overt DN patients, 53 incipient DN patients, 62 diabetic patients (DM), and 46 healthy individuals. Quantification of the mRNA profile of blood EVs was performed using the qRT-PCR method. The diagnostic performance of mRNA was evaluated using receiver operating characteristic analysis.
RESULTS: The mRNA expression of CDH2 and MCP-1 was downregulated in overt DN group (0.22-fold change and 0.15-fold change, respectively) and incipient DN group (0.60-fold change and 0.43-fold change, respectively) compared to DM group (1.72-fold change and 2.77-fold change, respectively), while PAI-1 mRNA expression decreased in incipient DN group (0.70-fold change) and DM group (0.58-fold change) compared to control. However, the expression level of CDH1 mRNA was not significantly different among the four groups (p = 0.408). Moreover, CDH2 and MCP-1 mRNAs inversely correlated with creatinine (r = -0.370 and r = -0.361, p<0.001) and Alb/Cr ratio (r = -0.355 and r = -0.297, p<0.001). 1/CDH2 mRNA also predicted overt DN with an accuracy of 0.75 (95%CI: 0.65-0.85) and incipient DN with an accuracy of 0.61 (95%CI: 0.50-0.71) while 1/MCP-1 mRNA had an accuracy of 0.66 (95%CI: 0.55-0.77) for overt DN prediction and an accuracy of 0.61 (95%CI: 0.51-0.71) for incipient DN prediction.
CONCLUSION: CDH2 and MCP-1 mRNAs expression in blood EVs was decreased with the development of DN, suggesting the renoprotective effect of these mRNAs in diabetic individuals. Moreover, their quantifications could serve as diagnostic biomarkers for early-stage DN.

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Year:  2022        PMID: 35363774      PMCID: PMC8975111          DOI: 10.1371/journal.pone.0265619

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Diabetic nephropathy (DN) is one of the most common microvascular complications of diabetes mellitus (DM), occuring in almost one-third of diabetic patients [1] and is also a leading cause of renal failure worldwide, affecting 40% of patients with end-stage renal disease (ESRD) [2, 3]. Because diabetic patients suffering from DN are at higher risk of cardiovascular morbidity and mortality, the diagnosis and treatment of DN in the early stage has become a global public health issue [4, 5]. Currently, the clinical diagnosis of DN is based on the presence of albuminuria which lacks sufficient sensitivity and specificity for predicting early-stage DN and its progression. In addition, a number of studies suggest that renal dysfunction can occur even in the absence of microalbuminuria [6-9]. The gold standard for DN diagnosis is based on the histopathological findings of a renal biopsy, an invasive procedure with serious complications such as infection and bleeding. In addition, DN patients cannot be followed up with serial renal biopsy to monitor disease progression [10]. Therefore, accurate noninvasive surrogates that can be used to predict early-stage DN and monitor disease progression are currently needed. In this case, new sensitive laboratory biomarkers, especially in combination with conventional biomarkers, can accurately detect DN patients in its early-stage, stratify them into different stages for individualized management, and monitor their response to therapy [11]. To this end, extracellular vesicles (EVs) have emerged as promising candidates, and their alterations in abundance and composition are associated with various conditions, including DM and DN [12-15]. EVs are lipidic, spherical, nanosized vesicles that are actively produced by almost all cell types and released into various body fluids such as serum, plasma, amniotic fluid, saliva, and urine [16]. Exosomes and microvesicles are two major subtypes of EVs that differ in size, biogenesis, and expressed biomarkers from the cell of origin. Exosomes are 30–100 nm in diameter and originate from the endosomal pathway and fusion of multivesicular bodies with plasma membranes, whereas microvesicles, with a diameter of 100–1,000 nm, originate from budding and evagination of plasma membranes [17]. EVs were initially proposed to be debris of cells [18]. Nowadays, we know that EVs transport various biomolecular components such as metabolites, lipids, proteins, RNA, and DNA from the cells of origin to the target cells, contribute to intercellular communications and play an important role in homeostasis in physiological condition and disease development under pathological conditions [19]. Previous studies have shown that EVs may be good candidates for early detection and monitoring of DN [13, 14, 20–24]. In this case, exosomal Wilm’s tumor-1 (WT1) mRNA from urine sediment of DN patients is inversely associated with estimated glomerular filtration rate (eGFR), indicating glomeruli damage and early renal failure. Moreover, this biomarker was found to predict DN with an accuracy of 0.705 [24]. In addition, a trial with 9 participants showed that mRNA expression of cadherin 1 (CDH1), cadherin 2 (CDH2), monocyte chemoattractant protein-1 (MCP-1), plasminogen activator inhibitor-1 (PAI-1), and angiotensin I-converting enzyme (ACE) genes in the urine pellet was significantly increased in DN patients compared with healthy controls, and of these biomarkers, CDH2 mRNA was increased 15-fold [25]. CDH1, CDH2, MCP-1, and PAI-1 are protein-coding genes that are transcribed into their corresponding mRNAs for protein synthesis. In this case, CDH1 and CDH2 mRNAs produce calcium-dependent adhesion proteins (E-cadherin and N-cadherin), which play a fundamental role in intercellular adhesion, and abnormal expression of these genes causes various diseases such as DN, diabetic retinopathy, and epithelial-derived solid tumors [25-27]. The MCP-1 gene produces chemokines that play a pivotal role in regulating monocyte/macrophage trafficking in the inflammatory process. Abnormal expression of this gene leads to DN, diabetic retinopathy, insulin resistance, atherosclerosis, and other inflammatory conditions [28-30]. The PAI-1 gene, also known as serpin family E member 1 (SERPINE1), produces plasminogen activator inhibitor 1 that plays a major role in hemostasis by inhibiting plasminogen activators mediated fibrinolysis and in cell motility and adhesion by inhibiting cell migration-mediated by vitronectin and integrin. Abnormal PAI-1 gene expression leads to various diseases such as DN and cardiovascular disease due to DM [31-34]. Previous studies have shown that CDH1, CDH2, MCP-1, and PAI-1 mRNAs can act as potential predictors of renal fibrosis due to chronic kidney disease [35], obstructive nephropathy [36], and DN [37-39]. In this study, we aimed to investigate the expression levels of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in blood EVs of overt DN patients, incipient DN patients, DM patients, and healthy controls and determine their diagnostic potential as novel biomarkers for predicting early-stage DN.

Materials and methods

Subjects and ethical considerations

A total of 196 participants, including 35 overt DN patients, 53 incipient DN patients, 62 DM patients, and 46 age- and sex-matched healthy controls, were recruited at an outpatient diabetes clinic between November 2018 and December 2019. All diabetic patients had type 2 diabetes mellitus and were divided into 3 subgroups according to the amount of albuminuria in three spot urine samples within 6 months. These included 62 diabetic patients with normoalbuminuria defined as urinary albumin excretion (UAE) < 30mg/gr creatinine in at least two samples (presented as DM group), 53 diabetic patients with microalbuminuria defined as UAE ≥ 30 and < 300 mg/gr creatinine in at least two samples (presented as incipient DN group), and 35 diabetic patients with macroalbuminuria defined as UAE ≥ 300 mg/ creatinine in at least two samples (presented as overt DN group). Participants who were younger than 30 years, older than 75 years, pregnant, or with comorbidities other than DM and DN such as cardiovascular disease, severe liver failure, urinary tract infection, and chronic inflammation were excluded. Besides, we included only participants with an eGFR ≥ 60 mL/min/1.73 m2 because our research question concerned early-stage DN. This study complied with all ethical guidelines for human experimentation in Helsinki Declaration and was approved by the Ethics Committee of Endocrine & Metabolism Research Institute and Tehran University of Medical Sciences (approval ID: IR.TUMS.EMRI.REC.1399.015). Written informed consent was obtained from all participants before participation.

Sample collection and clinical laboratory tests

After at least 10 hours of fasting, 15 ml of venous blood and random urine were sampled from each participant. 5 ml of the blood sample was analyzed for routine clinical laboratory tests, including urea, creatinine, fasting blood sugar (FBS), and HbA1c, while the remaining 10 ml was used for EVs extraction. The TOSOH G8 system was applied for HbA1c assessment, and a Roche commercial kit (Roche, Germany) was applied for the other laboratory tests. The Cockcroft–Gault equation was used to calculate eGFR [40] as follows:

Blood EVs extraction and assessment

The preparation and extraction process of blood EVs was described in a previous study [41]. Briefly, the plasma from 10 ml of blood was isolated (centrifugation, 290×g, 20 min, 4 °C) and centrifuged (12000×g, 20 min, 4 °C). Then, the supernatants were isolated and centrifuged (17000×g, 20 min, 4 °C). The obtained supernatants were picked up, and the pellets were suspended, centrifuged (10000×g,90 min, 4 °C), and resuspended in a phosphate-buffered sterile saline solution. The prepared pellets were stored at − 80 °C until RNA isolation. The morphology and size of the isolated EVs were assessed by scanning electron microscopy (SEM) and dynamic light scattering (DLS). For SEM assessment, we fixed the isolated EVs in PBS for 1 hour with 2.5% glutaraldehyde and then coated them with a gold layer to improve electrical conductivity and finally examined the samples with VEGA TESCAN. For DLS assessment, we carefully added EVs suspensions to a cuvette and examined the size and density of EVs (Malvern zetasizer, Worcestershire, UK).

mRNA isolation, cDNA preparation, and qRT-PCR analysis

According to the manufacturer’s instructions, we isolated total RNA from EVs using TRIzolTM reagent (Invitrogen, cat. no.: 15596026, USA) and stored at −70 °C. We evaluated the quality and quantity of isolated RNA using Nanodrop (Thermo Scientific 2000, USA). Besides, cDNA was synthesized from 100 ng of isolated RNA using the RevertAid First Strand cDNA Synthesis Kit (ThermoFisher Scientific, cat. no.: K1622, USA). Finally, we performed quantitative real‐time PCR (Applied Biosystems, USA) three times with cDNA replicates using SYBR Green PCR Master Mix (Applied Biosystems, USA). The utilized cycling conditions and thermal profile were as follows: 1 cycle at 95 °C for 10 min, 40 cycles at 95 °C for 10 s, 59–61 °C for 30 s (based on primers annealing), and melting curve analysis was performed ramping from 60 °C to 90 °C. In this instance, we utilized the following primers which were designed by Gene Runner software: CDH1 gene: forward: 5′GCTGTGTCATCCAACGGGAATG3′ and Reverse: 5′ GGGTGAATTCGGGCTTGTTGTC3′; CDH2 gene: forward: 5′ GATAGCCCGGTTTCATTTGAGG3′ and Reverse: 5′ TGTCCCATTCCAAACCTGGTG3′; MCP-1 gene: forward: 5′ GCATTGATTGCATCTGGCTG3′ and Reverse: 5′ TTCTCAAACTGAAGCTCGCAC3′; PAI-1 gene: forward: 5′ TGAATTCCTGCAGCTCAGC3′ and Reverse: 5′ ACAGCAGACCCTTCACCAAAG3′. The relative quantification of CDH1, CDH2, MCP-1, and PAI-1 mRNAs expression was calculated by using 2-ΔΔCt method [42]: Relative fold change of gene expression = 2-ΔΔCt

Statistical analysis

All statistical analyses were conducted in SPSS 19.0 software. To compare study groups, a one-way analysis of variance (ANOVA) with Bonferroni post hoc test was executed in case of continuous normally distributed variables, nonparametric Kruskal-Wallis and Mann-Whitney tests were performed in case of continuous non-normally distributed variables, and a chi-square test was executed in case of categorical variables. Correlation of mRNA expression level with demographic covariates and clinical laboratory tests was assessed with the Spearman’s correlation coefficient. Multivariable linear regression analysis using a stepwise method was performed to identify risk factors of mRNA expression. Receiver operating characteristic (ROC) analysis was used to explore the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of mRNA for predicting overt DN and incipient DN from DM. The best cutoff value for mRNA level was determined using Youden’s J statistic. In the case that overt DN and incipient DN groups had lower mRNA expression levels than the DM group, the reverse fold change of expression level was considered for the ROC analysis. Continuous normally distributed variables were reported with mean and standard deviation, continuous non-normally distributed variables were reported with median and interquartile range, and categorical variables were reported with absolute number and percentage. P-value < 0.05 was considered as a statistically significant level in all tests.

Results

Demographic information and clinical laboratory characteristics

The demographic features and clinical laboratory test results of participants are depicted in Table 1. 196 participants with a mean age of 61.24 ± 7.91 years old were enrolled in this study. 119 (60.7%) of participants were male, and 47 had a positive family history of diabetes. Participants were divided into four groups, including 35 overt DN patients, 53 incipient DN patients, 62 DM patients, and 46 controls. These groups had no significant difference in age (p = 0.980), sex (p = 0.137), BMI (p = 0.052), and eGFR (p = 0.265). The study subjects had a mean BMI of 29.10 ± 4.86 kg/m2 and a mean eGFR of 91.82 ± 28.77 ml/min/1.73m2. The raw data of participants is available in S1 Data.
Table 1

Demographic and clinical laboratory characteristics.

VariablesTotal(n = 196)GroupP value
Overt DN(n = 35)Incipient DN(n = 53)DM(n = 62)Control(n = 46)
Age (years) 61.24 ± 7.9161.66 ± 8.8861.41 ± 9.8760.84 ± 6.8661.38 ± 6.860.980
Sex (M/F) 119/77 (60.7%)27/8 (77.1%)31/22 (58.5%)33/29 (53.2%)28/18 (60.9%)0.137
(Male, %)
Family History 47 (24%)4 (11.4%)13 (24.5%)23 (37.1%)7 (15.2%)0.013
(n, %)
Body Mass Index (kg/m 2 ) 29.10 ± 4.8626.92 ± 3.9331.19 ± 4.8629.72 ± 5.6027.56 ± 3.280.052
Fasting glucose (mg/dL) 147.47 ± 69.79186.26 ± 86.62165.25 ± 87.67146.50 ± 42.0998.58 ± 14.41<0.001
HbA1c (%) 7.86 ± 1.979.26 ± 2.348.36 ± 1.608.01 ± 1.615.85 ± 0.45<0.001
Urea (mg/dL) 35.26 ± 14.9044.56 ± 18.6639.06 ± 18.8532.65 ± 8.1127.38 ± 6.67<0.001
Creatinine (mg/dL) 1.10 ± 0.371.38 ± 0.501.18 ± 0.410.92 ± 0.241.02 ± 0.16<0.001
Urine Alb/Cr (mg/gr) 181.38 ± 370.42738.45 ± 587.66150.61 ± 110.7213.55 ± 12.148.13 ± 10.66<0.001
eGFR (ml/min/1.73m2) 91.82 ± 28.7791.10 ± 41.6894.74 ± 31.2497.00 ± 28.9083.47 ± 24.240.265

Continuous variables are reported with Mean ± SD and categorical variables are reported with number and percentage (n, %).

DN: diabetic nephropathy, DM: diabetes mellitus, HbA1c: glycated hemoglobin, Alb/Cr: albumin/ creatinine ratio, eGFR: estimated glomerular filtration rate

Continuous variables are reported with Mean ± SD and categorical variables are reported with number and percentage (n, %). DN: diabetic nephropathy, DM: diabetes mellitus, HbA1c: glycated hemoglobin, Alb/Cr: albumin/ creatinine ratio, eGFR: estimated glomerular filtration rate ANOVA analyses with multiple comparisons on clinical laboratory results (Table 2) showed that the overt DN group, incipient DN group, and DM group had higher FBS (p≤ 0.001) and HbA1c (p< 0.001) than controls. Also, overt DN group had higher FBS (p = 0.022) and HbA1c (p = 0.002) than DM group. Pairwise comparisons of overt DN group with incipient DN group and incipient DN group with DM group showed no significant difference for FBS (p = 0.799 and p = 0.695, respectively) and HbA1c (p = 0.065 and p = 1.000, respectively). Overt DN group had higher urea than DM group and control (p< 0.001 for both). Also, the incipient DN group had higher urea than the control (p< 0.001). However, no significant difference in urea was in pairwise comparisons of overt DN group with incipient DN group (p = 0.422), incipient DN group with DM group (p = 0.081), and DM group with control (p = 0.312). The concentration of creatinine in overt DN group was higher than in incipient DN patients (p = 0.044), DM patients (p< 0.001), and control (p< 0.001). Incipient DN group had a higher creatinine concentration than DM group (p = 0.001) while incipient DN group had no significant difference in creatinine concentration compared to control (p = 0.151). In addition, there was no significant difference in creatinine concentration between the DM group and the control. (p = 0.875) As expected, the overt DN group and incipient DN group had higher urine Alb/Cr ratio than the DM group and control (p≤ 0.040). Also, the overt DN group had higher urine Alb/Cr ratio than the incipient DN group (p< 0.001), and no significant difference was in the urine Alb/Cr ratio between the DM group and control (p = 1.000).
Table 2

Pairwise comparisons regarding clinical laboratory tests of overt DN group, incipient DN group, DM group, and control group versus each other.

VariablesOvert DN vs Incipient DNOvert DN vs DMOvert DN vs ControlIncipient DN vs DMIncipient DN vs ControlDM vs Control
FBS 0.799 0.022 <0.001 0.695 <0.001 0.001
HbA1c 0.065 0.002 <0.001 1.000 <0.001 <0.001
Urea 0.422 <0.001 <0.001 0.081 <0.001 0.312
Creatinine 0.044 <0.001 <0.001 0.001 0.1510.875
Alb/Cr <0.001 <0.001 <0.001 0.030 0.040 1.000

p values are calculated by the Bonferroni post hoc test. FBS: fasting blood sugar, Alb/Cr: urine albumin/ creatinine ratio

p values are calculated by the Bonferroni post hoc test. FBS: fasting blood sugar, Alb/Cr: urine albumin/ creatinine ratio

Characterization of blood EVs

Fig 1 shows the results of the size and morphology of isolated EVs analyzed by SEM and DLS. The results revealed that the size of isolated EVs was between 80–152 nm.
Fig 1

SEM (a) and DLS (b) images of isolated EVs show the morphology and size of EVs.

mRNA expression level in blood EVs

The relative fold changes of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in blood EVs of overt DN group, incipient DN group, and DM group compared to control are listed in Table 3. Kruskal–Wallis analyses showed no significant difference in CDH1 mRNA expression fold change between four study groups (p = 0.408) while CDH2, MCP-1, and PAI-1 mRNAs had different expression levels between groups. (p< 0.001, p< 0.001, and p = 0.017, respectively).
Table 3

Relative mRNA expression fold change in overt DN group, incipient DN group, and DM group compared to control.

mRNAsFold change*Total P value**
Overt DNIncipient DNDM
CDH1 0.79 (0.36, 1.35)0.87 (0.31, 1.59)0.71 (0.21, 1.98)0.408
CDH2 0.22 (0.10, 1.61)0.60 (0.19, 3.88)1.72 (0.35, 4.75)<0.001
MCP-1 0.15 (0.07, 3.21)0.43 (0.06, 4.40)2.77 (0.14, 16.28)<0.001
PAI-1 0.79 (0.41, 1.62)0.70 (0.34, 1.72)0.58 (0.23, 1.58)0.017

Data are expressed as median (IQR).

*Fold change was calculated by using 2−ΔΔCT method.

**Total p value is calculated by the Kruskal–Wallis test.

Data are expressed as median (IQR). *Fold change was calculated by using 2−ΔΔCT method. **Total p value is calculated by the Kruskal–Wallis test. The fold changes of CDH2 mRNA in different groups are depicted in Fig 2. CDH2 mRNA was expressed less in blood EVs of overt DN group than incipient DN group (p = 0.013), DM group (p< 0.001), and control (p< 0.001). Besides, the incipient DN group had lower CDH2 mRNA expression than the DM group (p = 0.042). However, there were no significant differences in CDH2 mRNA level in pairwise comparisons of incipient DN group with control (p = 0.061) and DM group with control (p = 0.234).
Fig 2

CDH2 mRNA expression level in blood extracellular vesicles.

p value is calculated by the Mann–Whitney U test.

CDH2 mRNA expression level in blood extracellular vesicles.

p value is calculated by the Mann–Whitney U test. Fig 3 shows MCP-1 mRNA expression fold change in different groups. As can be seen, the overt DN group had a lower MCP-1 mRNA level than the DM group and control (p = 0.002 for both), while there was no significant difference in MCP-1 mRNA between the overt DN group and incipient DN group (p = 0.262). Incipient DN group also expressed less MCP-1 mRNA compared to DM group (p = 0.008) and control (p = 0.001), and DM group expressed more MCP-1 mRNA than control (p = 0.017). The pairwise comparisons of CDH1, CDH2, MCP-1, PAI-1 mRNAs between each of two groups of overt DN group, incipient DN group, DM group, and control group are summarized in Table 4.
Fig 3

MCP-1 mRNA expression level in blood extracellular vesicles.

p value is calculated by the Mann–Whitney U test.

Table 4

Pairwise comparisons of overt DN group, incipient DN group, DM group, and control group versus each other.

mRNAsOvert DN vs Incipient DNOvert DN vs DMOvert DN vs ControlIncipient DN vs DMIncipient DN vs ControlDM vs Control
CDH1 0.6390.9880.0890.6410.1260.234
CDH2 0.013 <0.001 <0.001 0.042 0.0610.234
MCP-1 0.262 0.002 0.002 0.008 0.001 0.017
PAI-1 0.9630.1840.0890.219 0.011 0.003

p values are calculated by the Mann–Whitney U test.

MCP-1 mRNA expression level in blood extracellular vesicles.

p value is calculated by the Mann–Whitney U test. p values are calculated by the Mann–Whitney U test. Pairwise comparisons in PAI-1 mRNA level show lower expression of PAI-1 mRNA in incipient DN group (p = 0.011) and DM group (p = 0.003) compared to control, while there were no significant differences in PAI-1 mRNA expression level between overt DN group and incipient DN group (p = 0.963), overt DN group and DM group (p = 0.184), overt DN group and control (p = 0.089), and incipient DN group and DM group (p = 0.219).

Correlation between mRNA level and clinical laboratory tests

The correlations of CDH1, CDH2, MCP-1, and PAI-1 mRNAs with demographic features and clinical laboratory results are summarized in Table 5. Within all participants, CDH2 mRNA level inversely correlated with HbA1c (Spearman correlation coefficient = -0.183, p = 0.012), urea (Spearman correlation coefficient = -0.152, p = 0.035), creatinine (Spearman correlation coefficient = -0.370, p< 0.001), and urine Alb/Cr ratio (Spearman correlation coefficient = -0.355, p< 0.001). Besides, MCP-1 mRNA had negative correlations with creatinine (Spearman correlation coefficient = -0.361, p< 0.001) and urine Alb/Cr ratio (Spearman correlation coefficient = -0.297, p< 0.001).
Table 5

Correlations of CDH1, CDH2, MCP-1, and PAI-1 mRNAs with demographic data and clinical laboratory tests in all participants.

mRNAAgeBMIFBSHbA1cUreaCreGFRAlb/Cr
Total CDH1r-0.049-0.0690.000-0.096-0.0110.000-0.043-0.064
p0.5850.5200.9970.1870.8800.9960.6850.376
CDH2r-0.0080.050-0.093 -0.183 -0.152 -0.370 0.139 -0.355
p0.9300.6400.195 0.012 0.035 <0.001 0.189 <0.001
MCP-1r0.015-0.081-0.028-0.111-0.044 -0.361 0.025 -0.297
p0.8670.4450.6970.1290.541 <0.001 0.818 <0.001
PAI-1r-0.083-0.069-0.068-0.086-0.0110.038-0.0430.008
p0.3590.5180.3430.2360.8760.5960.6870.908

BMI: body mass index, FBS: fasting blood sugar, Cr: serum creatinine, eGFR: estimated glomerular filtration rate, Alb/Cr: urine albumin/ creatinine ratio, r = Spearman correlation coefficient, p = p-value.

BMI: body mass index, FBS: fasting blood sugar, Cr: serum creatinine, eGFR: estimated glomerular filtration rate, Alb/Cr: urine albumin/ creatinine ratio, r = Spearman correlation coefficient, p = p-value. Multivariate linear regression results on the parameters affecting CDH2 and MCP-1 mRNAs expression are depicted in Table 6. These analyses indicated that the expression level of CDH2 mRNA could be estimated from creatinine (unstandardized coefficient = -2.673, p< 0.001) and urea (unstandardized coefficient = 0.035, p = 0.019), and MCP-1 mRNA expression level could be estimated from creatinine level (unstandardized coefficient = -3.024, p = 0.010).
Table 6

Multivariable linear regression analysis on the parameters affecting CDH2 and MCP-1 mRNAs level.

Dependent variable: CDH2 mRNA
Predictors 1 Unstandardized coefficientsStandardized coefficientstP-value*
BSEBeta
Constant 3.5250.5096.926<0.001
Cr -2.6730.592-0.429-4.516<0.001
Urea 0.0350.0150.2252.3670.019
Dependent variable: MCP-1 mRNA
Predictors 2 Unstandardized coefficientsStandardized coefficientstP-value*
BSEBeta
Constant 6.8841.3475.110<0.001
Cr -3.0241.158-0.186-2.6110.010

1 HbA1c, urea, serum creatinine, and urine Alb/Cr ratio were adopted for stepwise multivariable linear regression analysis of CDH2 mRNA.

2 Serum creatinine and urine Alb/Cr ratio were adopted for stepwise multivariable linear regression analysis of MCP-1 mRNA.

* Statistically significance was set at p value < 0.05.

Cr: serum creatinine, SE: standard error.

1 HbA1c, urea, serum creatinine, and urine Alb/Cr ratio were adopted for stepwise multivariable linear regression analysis of CDH2 mRNA. 2 Serum creatinine and urine Alb/Cr ratio were adopted for stepwise multivariable linear regression analysis of MCP-1 mRNA. * Statistically significance was set at p value < 0.05. Cr: serum creatinine, SE: standard error.

Diagnostic ability of 1/CDH2 and 1/MCP-1 mRNAs in incipient DN detection

The expression levels of CDH2 and MCP-1 mRNAs in the incipient DN group and overt DN group were lower than those in the DM group; thus, as described previously, ROC analysis was performed using the inverse fold changes of mRNA. Fig 4 shows the ROC curves of 1/CDH2 and 1/MCP-1 mRNAs for discrimination of incipient DN patients from diabetic patients. In this case, 1/CDH2 mRNA had an accuracy of 0.61 (95%CI: 0.50–0.71, p = 0.038), sensitivity of 37.7%, specificity of 83.9%, PPV of 66.6%, and NPV of 61.1% at a cutoff of 3.47 for incipient DN detection. In addition, the accuracy, sensitivity, specificity, PPV, and NPV of 1/MCP-1 mRNA≥ 0.61 to detect incipient DN were 0.61 (95%CI: 0.51–0.71, p = 0.035), 69.8%, 61.3%, 60.6%, and 70.3%, respectively. Table 7 summarizes the diagnostic ability of 1/CDH2 and 1/MCP-1 mRNAs to distinguish incipient DN from DM.
Fig 4

The receiver operating characteristic (ROC) analyses of 1/CDH2 mRNA and 1/MCP-1 mRNA to differentiate incipient DN patients from DM patients.

Table 7

Diagnostic performance of 1/CDH2 mRNA and 1/MCP-1 mRNA for incipient DN detection.

ParametersCutoff valuesSensitivity (%)Specificity (%)PPV (%)NPV (%)AUC (95%CI)p value
1/CDH2 3.4737.783.966.661.10.61 (0.50, 0.71)0.038
1/MCP-1 0.6169.861.360.670.30.61 (0.51, 0.71)0.035

PPV: positive predictive value, NPV: negative predictive value, AUC: area under the curve

PPV: positive predictive value, NPV: negative predictive value, AUC: area under the curve

Diagnostic ability of 1/CDH2 and 1/MCP-1 mRNAs in overt DN detection

ROC curves of 1/CDH2 and 1/MCP-1 mRNAs for discrimination of overt DN from DM are depicted in Fig 5. 1/CDH2 mRNA showed good diagnostic accuracy with an AUC of 0.75 (95%CI: 0.65–0.85, p< 0.001). Based on Youden’s J statistic, 1/CDH2 mRNA had optimal diagnostic performance at 2.14-fold change. At this threshold, 1/CDH2 mRNA had a sensitivity of 74.3%, specificity of 69.4%, PPV of 57.8%, and NPV of 82.7% for overt DN detection. Besides,the accuracy 1/MCP-1 mRNA for overt DN detection was 0.66 (95%CI: 0.55–0.77, p = 0.007), and 1/MCP-1 mRNA level ≥ 5.89 as the best cutoff value resulted in 57.1% as sensitivity, 74.2% as specificity, 55.5% as PPV, and 75.3% as NPV for discrimination of overt DN from DM. The diagnostic ability of 1/CDH2 and 1/MCP-1 mRNAs to distinguish overt DN from DM is summarized in Table 8.
Fig 5

The receiver operating characteristic (ROC) analyses of 1/CDH2 mRNA and 1/MCP-1 mRNA to differentiate overt DN patients from DM patients.

Table 8

Diagnostic performance of 1/CDH2 mRNA and 1/MCP-1 mRNA for overt DN detection.

ParametersCutoff valuesSensitivity (%)Specificity (%)PPV (%)NPV (%)AUC (95%CI)p value
1/CDH2 2.1474.369.457.882.70.75 (0.65, 0.85)<0.001
1/MCP-1 5.8957.174.255.575.30.66 (0.55, 0.77)0.007

PPV: positive predictive value, NPV: negative predictive value, AUC: area under the curve

PPV: positive predictive value, NPV: negative predictive value, AUC: area under the curve

Discussion

In this study, we assessed the expression levels of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in blood EVs of overt DN, incipient DN, and DM patients compared to healthy controls and investigated whether or not these mRNAs could serve as diagnostic biomarkers for early-stage DN. The results showed that CDH2 and MCP-1 mRNAs were downregulated in DN groups compared to the DM group, whereas the expression levels of CDH1 and PAI-1 mRNAs did not significantly differ between DN groups and the DM group. Moreover, CDH2 and MCP-1 mRNAs inversely correlated with the severity of albuminuria and showed excellent diagnostic ability to discriminate DN from DM. In this case, CDH2 and MCP-1 mRNAs from blood EVs not only have diagnostic potential for early-stage DN, but also could be promising target points to understand underlying mechanisms of DN progression and develop an alternative approach for the prevention, prognosis, and treatment of DN. To date, several studies have been conducted to investigate the level of miRNAs and mRNAs derived from circulating EVs [43, 44] and urine EVs in DN [21, 22, 24, 45–48]. However, to the best of our knowledge, this study is the first assessment of these specific mRNAs derived from blood EVs of DN patients. Previously, a nine patients-trial by Zheng M et al. [25] characterized the expression profile of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in the urinary sediment of DN patients and reported significantly increased expression levels of these mRNAs in the DN group compared to healthy controls. They also found that CDH2 mRNA in the DN group had a 15-fold higher expression level than in control. Although this trial indicated upregulation of CDH1 and PAI-1 mRNAs of urinary pellet in DN, our study showed no significant change in CDH1 and PAI-1 mRNA expression in blood EVs of DN patients compared to DM patients and controls; meanwhile, PAI-1 mRNA was downregulated in DM patients compared to controls. A multiple microarray analysis by Zhang Y et al. [39] revealed a positive correlation between CDH2 mRNA expression and eGFR in DN, suggesting a protective role of CDH2 mRNA expression in DN patients. Our analysis revealed no significant correlation between eGFR and CDH2 and MCP-1 mRNA expression. One reason for this finding is that four groups in our study had no significant difference in eGFR, and all participants had normal eGFR despite the different degrees of albuminuria. Thus, this result needs to be confirmed in a future study in which the participants have different levels of eGFR. In addition, because DN patients had normal eGFR, indicating good renal function, they were considered to be in the early stages of diabetic nephropathy. Therefore, we interpreted that the downregulation of CDH2 and MCP-1 mRNAs could be good predictors of early-stage DN. In addition, several studies indicated the overexpression of urinary MCP-1 mRNA and protein in DN [28, 49–51] and showed that the expression of glomerular MCP-1 mRNA positively correlated with urinary protein excretion rate and kidney injuries [52]. Our analysis showed that CDH2 and MCP-1 mRNA expression had an inverse correlation with urine Alb/Cr ratio and serum creatinine, reflecting their renoprotective effect, and their downregulated expression correlated with impaired kidney. In addition, multiple regression revealed that serum creatinine was one of the predictors of CDH2 and MCP-1 mRNAs expression. However, this is an observational study, and we should interpret the results in terms of an associative model rather than a causal relationship. Thus, we require further experimental studies to determine the direction of associations between covariates. All discussed studies had investigated the expression profile of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in various biofluids other than blood EVs. However, recent quantitative RNA sequencing of WT1 and ACE mRNAs from blood EVs of DN patients showed upregulated expression of WT1 mRNA and downregulated expression of ACE mRNA in DN patients compared to DM patients and controls. Moreover, WT1 and ACE mRNAs from blood EVs were associated with the severity of albuminuria and showed good diagnostic performance to discriminate DN from DM [41]. This study, in agreement with our study, indicated the important role of mRNA from blood EVs in DN development and also showed that exploring more mRNA profiles of blood EVs in DN will lead to a better understanding of DN pathophysiology and the discovery of alternative biomarkers for DN management. This study had several limitations that should be expained. First, we conducted a cross-sectional study, and we could not conclude any causal interpretations. Second, we attempted to recruit age- and sex-matched control cases. Nevertheless, the study groups differed significantly in other demographic features such as family history and clinical laboratory tests that might influence the mRNA expression profile of blood EVs. Third, we identified DN cases based on micro/macroalbuminuria in three spot urine samples, whereas the gold standard for DN diagnosis is renal biopsy. Fourth, we did not examine the medications that might differ between study groups and influence the mRNAs expression. Fifth, EVs isolated from blood most likely originate from different cell types, and EVs originating from different cells most likely carry different cargos. Finally, to confirm our findings, we need a multicenter study with a large sample size and diverse participants in ethnicity.

Conclusions

To sum up, CDH2 and MCP-1 mRNAs of blood EVs were downregulated in DN patients and showed good diagnostic potential for early detection of DN. Besides, the expression levels of these biomarkers are inversely correlated with serum creatinine, degree of albuminuria, and renal injury. Our study suggests novel mediators involved in DN pathogenesis. Further research on mRNA profiling of blood EVs is warranted to uncover new molecular pathways in DN development and may be suggested for the diagnosis, prognosis, prevention, and therapy of DN. (XLSX) Click here for additional data file. 26 Oct 2021
PONE-D-21-29236
The Role of CDH1, CDH2,MCP, and PAI mRNAs of Blood Extracellular Vesicles in PredictingEarly-stage Diabetic Nephropathy
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You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Reviewer Response: Following amendments and corrections may further improve this manuscript. 1) The manuscript needs a thorough revision regarding its “space” formatting, in all the sections including “Title-statement”. 2) Kindly review, Line and Paragraph-spacing. 3) The manuscript needs a thorough revision for its Grammarly- mistakes; use of helping verbs and tenses. 4) Kindly, add Line numbers, as per journal’s format. 5) Section: Abstract: Methods: Line#4: Kindly abbreviate ROC. 6) Section: Abstract: Results: Line#1: Kindly recorrect the statement as; “The mRNA expression found in CDH2 and MCP, was down-regulated in overt DN group”. 7) Section: Abstract: Results: Line#1: Kindly recorrect as: “0.22- and 0.15-fold change” to “0.22- fold change and 0.15-fold change”, respectively. 8) Section: Abstract: Results: Line#2: Kindly recorrect as: “0.60- and 0.43-fold change” to “0.60- fold change and 0.43-fold change”. 9) Section: Abstract: Results: Line#3: Kindly recorrect as: (1.72- and 2.77-fold change) to (1.72-fold change and 2.77-fold change). 10) Section: Abstract: Results: Line#4: Kindly recorrect as: DM group (0.58-fold change) as compare to control. 11) Section: Abstract: Results: Line#8: (95%CI: 0.65, 0.85) should be written as (95%CI: 0.65-0.85), vice versa throughout the text. 12) Section: Introduction:1st Paragraph: Line 22/23: “while we now know EVs”, should be corrected as “While, now we know that EVs”. 13) It is recommended to correct “mRNAs” throughout the text as “mRNA”, in properly manner. 14) Section: Methods: Subjects and ethical considerations: Line 7 & 9: Kindly correct “creatinineon” as “creatinine on”. 15) Section: Methods: mRNA isolation, cDNA preparation and qRT-PCR analysis: Kindly, add thermo-cycle programming in Tabular-Form; Initial Denaturation, Denaturation, Annealing, Extension and Final Extension: timing and temperature/ cycle. 16) Section: Results: Demographic information and clinical laboratory characteristics: Line#20: “significant different creatinineconcentration” should be corrected as “significant difference in creatinine concentration”. 17) Section: Results: Diagnostic ability of 1/CDH2 and 1/MCP mRNAs in overt DN detection: Line#1: Kindly, add helping verb as: “discrimination of overt DN from DM”. 18) Section: Results: Diagnostic ability of 1/CDH2 and 1/MCP mRNAs in overt DN detection: Line#3: What do you mean by guaranteed sensitivity=? 19) Section: Results: Diagnostic ability of 1/CDH2 and 1/MCP mRNAs in overt DN detection: Line# 3rd last Line: should be corrected as: ‘for discrimination of overt DN from DM. 20) Section: Discussion: 1st Para: 2nd last Line: “DN progression and develop”, should be corrected as: “DN progression and development”. 21) The manuscript doesn’t include the brief introduction of CDH1, CDH2, MCP & PAI, neither their abbreviation nor their function. No information or Literature Review regarding: How they act as Biomarkers for disease detection, particularly DN? How they help to investigate DN manifestation? Either, they are genes or proteins or their molecular pathway is associated with DN related Risk Factors? Need to Elaborate exclusively. 22) Kindly also provide with brief explanation of Biomarkers and how they help to investigate disease progression? Reviewer #2: Comments The authors addressed diabetic nephropathy (DN) patients in their study. They studied the expression of a panel of DN related genes in blood extracellular vesicles (EVs) of 4 groups; overt DN patients, incipient DN patients, diabetes mellitus patients (DM), and healthy controls. They reported that CDH2 and MCP mRNA expression is significantly downregulated in blood EVs of overt and incipient DN patients relative to DM patients lacking DN. CDH2 gene was found more downregulated in EVs of overt DN patients compared to incipient and DM patients. Expression of both genes was inversely correlated with serum creatinine levels and degree of albuminuria. They suggested that CDH2 and MCP mRNA expression declines as DN develops, indicating a possible renoprotective effect of these mRNAs in diabetic individuals and their possible role as diagnostic biomarkers for early-stage DN that may allow monitoring its progression. The statistical studies are very good. The study is interesting and concerns a considerable number of researchers and physicians. 1) The full names of the investigated genes should be written in the introduction with a referral to their functions. 2) In the methods section, Subjects and ethical considerations sub-section, please, preferably mention the type of diabetes mellitus from which the samples were obtained. Which type of DM was addressed? or were both types included in the study? 3) In the methods section, Sample collection and clinical laboratory tests section, please, put a reference for the Cockcroft–Gault Equation used in this section. 4) In the methods section, mRNA isolation, cDNA preparation and qRT-PCR analysis sub-section: - “TRIzolTM Reagent(USA, Cat. Num: 15596026. Germany)”: please, mention the company and revise the manufacturer’s country. -“ RevertAid First Strand cDNA Synthesis Kit (Fermentas, Cat Num: K1622, USA), Is it Fermentas or Thermo Scientific? - “Nanodrop (Thermo Scientific 2000)”- “SYBR Green PCR Master Mix (Applied Biosystems)”: please mention the country. - Were the used primers designed by authors or obtained from previous studies? , if so, please, mention the reference(s). 5) In the Results section, Demographic information and clinical laboratory characteristics subsection: - In table 1, does the p value represent the difference between the 4 groups? It will be better to put the p value of the pairwise comparison (the difference between each 2 groups) by subdividing the p value column so that the results become clearer. - For the creatinin concentration results, in the following part: “Incipient DN group had higher creatinine concentration than DM group (p = 0.001) and no significant different creatinine concentration compared to control (p = 0.151).” Do you mean no significant difference between DN group and control group or between DM group and control group? Please, clarify. 6) In the Results section, Characterization of blood Evs subsection, in the following part: “Figure 1 showed the results of the size and morphology of isolated exosomes which were analyzed by SEM and DLS. The results revealed that size of isolated EVs were between 80-150 nm”, you mentioned that the isolated EVs are exosomes, however the size stated was “80-150 nm” which means that not all the isolated EVs are exosomes according to the classification mentioned in the introduction: “Exosomes are 30–100 nm in diameter, derived from the endosomal pathway and fusion of multivesicular bodies to plasma membranes, while microvesicles, with a diameter of 100-1,000 nm, are derived from budding and evagination of plasma membranes.(16)” -Figure 1a shows an EV with a diameter of 152 nm so the size range would be: (80-152 nm) to be more precise. 7) In the Results section, mRNAs expression level in blood EVs subsection: -In table 2, it is better to present the p values of the pairwise comparison (presented later in Table S 1 with no referral to this table in the text), as these results are important and should be presented in the main table (Table 2) not in a supplementary one. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Syeda Zahra Abbas Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. Submitted filename: PONE-D-21-29236.docx Click here for additional data file. 26 Dec 2021 Response to Reviewers Reviewer #1: Reviewer Response: Following amendments and corrections may further improve this manuscript. 1) The manuscript needs a thorough revision regarding its “space” formatting, in all the sections including “Title-statement”. Done, you are right. Thanks for your appropriate comment. We correct “space” formatting of all part of the text in the revised manuscript. 2) Kindly review, Line and Paragraph-spacing. Done, Thanks for your comment. Manuscript text was double-spaced. 3) The manuscript needs a thorough revision for its Grammarly- mistakes; use of helping verbs and tenses. Done, Thanks for your precise comment. We corrected the Grammarly- mistakes to the best of our knowledge. 4) Kindly, add Line numbers, as per journal’s format. Done, you are right. We added continuous Line numbers. 5) Section: Abstract: Methods: Line#4: Kindly abbreviate ROC. Done, you are right. We wrote the full name of ROC in this part of revised manuscript. 6) Section: Abstract: Results: Line#1: Kindly recorrect the statement as; “The mRNA expression found in CDH2 and MCP, was down-regulated in overt DN group”. Done, Thanks for your excellent comment. We recorrect this statement in the abstract section of revised manuscript. 7) Section: Abstract: Results: Line#1: Kindly recorrect as: “0.22- and 0.15-fold change” to “0.22- fold change and 0.15-fold change”, respectively. Done, Thanks for your precise comment. We recorrected this statement in the revised manuscript. 8) Section: Abstract: Results: Line#2: Kindly recorrect as: “0.60- and 0.43-fold change” to “0.60- fold change and 0.43-fold change”. Done, Thanks for your precise comment. We recorrected this statement in the revised manuscript. 9) Section: Abstract: Results: Line#3: Kindly recorrect as: (1.72- and 2.77-fold change) to (1.72-fold change and 2.77-fold change). Done, Thanks for your comment. We recorrected this statement in the revised manuscript. 10) Section: Abstract: Results: Line#4: Kindly recorrect as: DM group (0.58-fold change) as compare to control. Done, Thanks for your appropriate comment. We recorrected it in the revised manuscript. 11) Section: Abstract: Results: Line#8: (95%CI: 0.65, 0.85) should be written as (95%CI: 0.65-0.85), vice versa throughout the text. Done, Thanks for your promising comment. We recorrect this issue throughout the text. 12) Section: Introduction:1st Paragraph: Line 22/23: “while we now know EVs”, should be corrected as “While, now we know that EVs”. Done, Thanks a lot for your precise comment. We recorrect this statement. 13) It is recommended to correct “mRNAs” throughout the text as “mRNA”, in properly manner. Done, thanks for your promising comment. We correct “mRNAs” as “mRNA” throughout the text in proper manner. 14) Section: Methods: Subjects and ethical considerations: Line 7 & 9: Kindly correct “creatinineon” as “creatinine on”. Done, you are right. We correct it. Besides, we revised the text in the manner of “spacing”. 15) Section: Methods: mRNA isolation, cDNA preparation and qRT-PCR analysis: Kindly, add thermo-cycle programming in Tabular-Form; Initial Denaturation, Denaturation, Annealing, Extension and Final Extension: timing and temperature/ cycle. Done, Thanks for your comment. 16) Section: Results: Demographic information and clinical laboratory characteristics: Line#20: “significant different creatinineconcentration” should be corrected as “significant difference in creatinine concentration”. Done, Thanks for your comment. We correct this. 17) Section: Results: Diagnostic ability of 1/CDH2 and 1/MCP mRNAs in overt DN detection: Line#1: Kindly, add helping verb as: “discrimination of overt DN from DM”. Done, Thanks for your precise comment. We corrected it in the revised manuscript. 18) Section: Results: Diagnostic ability of 1/CDH2 and 1/MCP mRNAs in overt DN detection: Line#3: What do you mean by guaranteed sensitivity=? Done, you are right. This sentence was vague; so we replaced it with “Based on Youden's J statistic, 1/CDH2 mRNA had optimal diagnostic performance at 2.14-fold change. In this cutoff, 1/CDH2 mRNA had sensitivity of 74.3%, specificity of 69.4%, PPV of 57.8%, and NPV of 82.7% for overt DN detection.”. In this sentence, we reported the sensitivity, specificity, PPV, and NPV of 1/CDH2 mRNA at cutoff of 2.14-fold change. 19) Section: Results: Diagnostic ability of 1/CDH2 and 1/MCP mRNAs in overt DN detection: Line# 3rd last Line: should be corrected as: ‘for discrimination of overt DN from DM. Done, Thanks for your precise comment. We corrected it in the revised manuscript. 20) Section: Discussion: 1st Para: 2nd last Line: “DN progression and develop”, should be corrected as: “DN progression and development”. Done, Thanks for your precise comment. We corrected it. 21) The manuscript doesn’t include the brief introduction of CDH1, CDH2, MCP & PAI, neither their abbreviation nor their function. No information or Literature Review regarding: How they act as Biomarkers for disease detection, particularly DN? How they help to investigate DN manifestation? Either, they are genes or proteins or their molecular pathway is associated with DN related Risk Factors? Need to Elaborate exclusively. Done, Thanks for your precise comment. We wrote the full name of the investigated genes and their abbreviations. We explained the productions and function of the investigated genes. We explained the pathological conditions related to the abnormal expression of the investigated genes. We provided the literature review regarding the potential ability of the investigated mRNAs (the transcript of investigated genes) that act as Biomarkers for renal fibrosis detection, especially due to DN. We wrote the usefulness of the investigated mRNAs for DN manifestations including “these biomarkers can accurately detect DN patients in its early-stage, stratify them into different stages for individualized management, and monitor their response to therapy”. We presented that the expression mRNA levels of the investigated genes were evaluated to identify whether they were associated with DN or not. Introduction section; page 3; lines 136-139 Introduction section; page 4; lines 164-170 Introduction section; page 5; lines 170-190 22) Kindly also provide with brief explanation of Biomarkers and how they help to investigate disease progression? Done, Thanks for your excellent comment. We explained the usefulness of new biomarkers, especially when combined with currently used biomarkers, for detecting, stratifying, and monitoring disease progression in the introduction section of revised manuscript. Introduction section; page 3; lines 136-139 Reviewer #2: Comments The authors addressed diabetic nephropathy (DN) patients in their study. They studied the expression of a panel of DN related genes in blood extracellular vesicles (EVs) of 4 groups; overt DN patients, incipient DN patients, diabetes mellitus patients (DM), and healthy controls. They reported that CDH2 and MCP mRNA expression is significantly downregulated in blood EVs of overt and incipient DN patients relative to DM patients lacking DN. CDH2 gene was found more downregulated in EVs of overt DN patients compared to incipient and DM patients. Expression of both genes was inversely correlated with serum creatinine levels and degree of albuminuria. They suggested that CDH2 and MCP-1 mRNA expression declines as DN develops, indicating a possible renoprotective effect of these mRNAs in diabetic individuals and their possible role as diagnostic biomarkers for early-stage DN that may allow monitoring its progression. The statistical studies are very good. The study is interesting and concerns a considerable number of researchers and physicians. 1) The full names of the investigated genes should be written in the introduction with a referral to their functions. Done, you are right. Thanks for your appropriate comment. We added the full names of the investigated genes as well as their functions in the introduction section of the revised manuscript. Introduction section; page 4; lines 164-170 Introduction section; page 5; lines 170-188 2) In the methods section, Subjects and ethical considerations sub-section, please, preferably mention the type of diabetes mellitus from which the samples were obtained. Which type of DM was addressed? or were both types included in the study? Done, Thanks for your suitable comment. All participants had type 2 diabetes mellitus and we mentioned it in the method section of revised manuscript. 3) In the methods section, Sample collection and clinical laboratory tests section, please, put a reference for the Cockcroft–Gault Equation used in this section. Done, Thanks for your comment. We added the reference for Cockcroft–Gault Equation in the revised manuscript. 4) In the methods section, mRNA isolation, cDNA preparation and qRT-PCR analysis sub-section: - “TRIzolTM Reagent(USA, Cat. Num: 15596026. Germany)”: please, mention the company and revise the manufacturer’s country. -“ RevertAid First Strand cDNA Synthesis Kit (Fermentas, Cat Num: K1622, USA), Is it Fermentas or Thermo Scientific? - “Nanodrop (Thermo Scientific 2000)”- “SYBR Green PCR Master Mix (Applied Biosystems)”: please mention the country. - Were the used primers designed by authors or obtained from previous studies? , if so, please, mention the reference(s). Done, Thanks for your comment. 5) In the Results section, Demographic information and clinical laboratory characteristics subsection: - In table 1, does the p value represent the difference between the 4 groups? Yes, you are right. This p value represents the difference between the 4 groups. It will be better to put the p value of the pairwise comparison (the difference between each 2 groups) by subdividing the p value column so that the results become clearer. Done, Thanks for your appropriate comment. We did the pairwise comparisons of parameters that were significantly different between the 4 groups in Table 1 and we showed the pairwise comparisons in Table 2. - For the creatinin concentration results, in the following part: “Incipient DN group had higher creatinine concentration than DM group (p = 0.001) and no significant different creatinine concentration compared to control (p = 0.151).” Do you mean no significant difference between DN group and control group or between DM group and control group? Please, clarify. Done, you are right. This statement was vague. We mean no significant difference between incipient DN group and control group. We clarified this finding in the revised manuscript. 6) In the Results section, Characterization of blood Evs subsection, in the following part: “Figure 1 showed the results of the size and morphology of isolated exosomes which were analyzed by SEM and DLS. The results revealed that size of isolated EVs were between 80-150 nm”, you mentioned that the isolated EVs are exosomes, however the size stated was “80-150 nm” which means that not all the isolated EVs are exosomes according to the classification mentioned in the introduction: “Exosomes are 30–100 nm in diameter, derived from the endosomal pathway and fusion of multivesicular bodies to plasma membranes, while microvesicles, with a diameter of 100-1,000 nm, are derived from budding and evagination of plasma membranes.(16)” Done, you are absolutely right. The isolated EVs were both exosomes and microvesicles. Therefore, we revised the manuscript and in every statement that we wrongly stated exosomes, we replaced them with extracellular vesicle (EV). -Figure 1a shows an EV with a diameter of 152 nm so the size range would be: (80-152 nm) to be more precise. Done, you are right. We corrected it in the revised manuscript. 7) In the Results section, mRNAs expression level in blood EVs subsection: -In table 2, it is better to present the p values of the pairwise comparison (presented later in Table S 1 with no referral to this table in the text), as these results are important and should be presented in the main table (Table 2) not in a supplementary one. Done, you are right. Thanks for your appropriate comment. We presented Table S1 as Table 4 in the main text. Submitted filename: Response to Reviewers.docx Click here for additional data file. 19 Jan 2022
PONE-D-21-29236R1
The role of CDH1, CDH2, MCP-1, and PAI-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy
PLOS ONE Dear Dr. Hashemi, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Mar 05 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Muhammad Tarek Abdel Ghafar, M.D Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Additional Editor Comments (if provided): There are several structural, grammatical, punctuation, and capitalization errors that require heavy editing by a native English speaker. Please revise the organization of the tables as there are supplementary tables uploaded but not indicated in the text. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: No ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. 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If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Syeda Zahra Abbas Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.
Submitted filename: Comments2.docx Click here for additional data file. 22 Jan 2022 Response to Reviewers Reviewer #2: Comments I am satisfied with the response and the revision of authors, however, I suggest to make a couple of corrections: 1. As authors’ results did not indicate a role for CH1 and PAI mRNA of blood EVs in early detection of DN, would it be better to modify the title of the manuscript to be more relevant to the results? Done. You are right. We modified the title in the revised manuscript. 2. I would recommend some close proofreading; some punctuation still needed, and the reference number should be placed in the end of the sentence before the full stop not after. Done. Thanks for your accurate comment. We corrected the punctuation and other grammatical errors to the best of our knowledge. Submitted filename: Response to Reviewers (2).docx Click here for additional data file. 14 Feb 2022
PONE-D-21-29236R2
The role of CDH2 and MCP-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy
PLOS ONE Dear Dr. Hashemi, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Mar 31 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Muhammad Tarek Abdel Ghafar, M.D Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Additional Editor Comments: There are several structural, grammatical, punctuation, and capitalization errors that require heavy editing by a native English speaker. Please revise the organization of the tables as there are supplementary tables uploaded but not indicated in the text. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.
27 Feb 2022 Response to Reviewers: Additional Editor Comments: There are several structural, grammatical, punctuation, and capitalization errors that require heavy editing by a native English speaker. Please revise the organization of the tables as there are supplementary tables uploaded but not indicated in the text. Done, Thanks for your comment. A native English speaker has heavily edited the final version of this manuscript in terms of structural, grammatical, punctuation, and capitalization errors. We also organized all the tables in the revised manuscript. In this case, we had 8 tables in the revised manuscript that were cited in ascending numeric order upon first appearance in the manuscript file from Table 1 to Table 8. Besides, we provided the raw data of participants as S1 Appendix. Submitted filename: Response to Reviewers (4).docx Click here for additional data file. 7 Mar 2022 The role of CDH2 and MCP-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy PONE-D-21-29236R3 Dear Dr. Hashemi, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Muhammad Tarek Abdel Ghafar, M.D Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: 22 Mar 2022 PONE-D-21-29236R3 The role of CDH2 and MCP-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy Dear Dr. Hashemi: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Prof Muhammad Tarek Abdel Ghafar Academic Editor PLOS ONE
  50 in total

1.  Diabetic Kidney Disease: Challenges, Progress, and Possibilities.

Authors:  Radica Z Alicic; Michele T Rooney; Katherine R Tuttle
Journal:  Clin J Am Soc Nephrol       Date:  2017-05-18       Impact factor: 8.237

2.  A PAI-1 mutant, PAI-1R, slows progression of diabetic nephropathy.

Authors:  Yufeng Huang; Wayne A Border; Ling Yu; Jiandong Zhang; Daniel A Lawrence; Nancy A Noble
Journal:  J Am Soc Nephrol       Date:  2008-01-23       Impact factor: 10.121

3.  Wilm's tumor-1 protein levels in urinary exosomes from diabetic patients with or without proteinuria.

Authors:  Anuradha Kalani; Aradhana Mohan; Madan M Godbole; Eesh Bhatia; Amit Gupta; Raj Kumar Sharma; Swasti Tiwari
Journal:  PLoS One       Date:  2013-03-27       Impact factor: 3.240

4.  FTO modulates fibrogenic responses in obstructive nephropathy.

Authors:  Chao-Yung Wang; Shian-Sen Shie; Ming-Lung Tsai; Chia-Hung Yang; Kuo-Chun Hung; Chun-Chieh Wang; I-Chang Hsieh; Ming-Shien Wen
Journal:  Sci Rep       Date:  2016-01-04       Impact factor: 4.379

Review 5.  Diabetic Nephropathy: Perspective on Extracellular Vesicles.

Authors:  Yanfang Lu; Dongwei Liu; Qi Feng; Zhangsuo Liu
Journal:  Front Immunol       Date:  2020-06-03       Impact factor: 7.561

6.  The circulating exosomal microRNAs related to albuminuria in patients with diabetic nephropathy.

Authors:  Hyoungnae Kim; Yun-Ui Bae; Jin Seok Jeon; Hyunjin Noh; Hyeong Kyu Park; Dong Won Byun; Dong Cheol Han; Seongho Ryu; Soon Hyo Kwon
Journal:  J Transl Med       Date:  2019-07-22       Impact factor: 5.531

7.  Urinary Exosomal MicroRNA Signatures in Nephrotic, Biopsy-Proven Diabetic Nephropathy.

Authors:  Wen-Chin Lee; Lung-Chih Li; Hwee-Yeong Ng; Pei-Ting Lin; Terry Ting-Yu Chiou; Wei-Hung Kuo; Chien-Te Lee
Journal:  J Clin Med       Date:  2020-04-23       Impact factor: 4.241

8.  Systems-level differential gene expression analysis reveals new genetic variants of oral cancer.

Authors:  Syeda Zahra Abbas; Muhammad Imran Qadir; Syed Aun Muhammad
Journal:  Sci Rep       Date:  2020-09-04       Impact factor: 4.379

9.  Urinary exosomal microRNAs in incipient diabetic nephropathy.

Authors:  Federica Barutta; Marinella Tricarico; Alessandro Corbelli; Laura Annaratone; Silvia Pinach; Serena Grimaldi; Graziella Bruno; Daniela Cimino; Daniela Taverna; Maria Chiara Deregibus; Maria Pia Rastaldi; Paolo Cavallo Perin; Gabriella Gruden
Journal:  PLoS One       Date:  2013-11-04       Impact factor: 3.240

10.  Urinary Exosomal miRNA Signature in Type II Diabetic Nephropathy Patients.

Authors:  Denis Delić; Claudia Eisele; Ramona Schmid; Patrick Baum; Franziska Wiech; Martin Gerl; Heike Zimdahl; Steven S Pullen; Richard Urquhart
Journal:  PLoS One       Date:  2016-03-01       Impact factor: 3.240

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