# Evaluation Value of Serum miR-4299 and miR-16-5p in Risk Stratification of Sepsis-Induced Acute Kidney Injury

Authors: Weiwei Pan; Junfeng Zhang; Luqi Hu; Zhiping Huang
Journal: BioMed Research International
 (2022)

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## Abstract

Objective. This study was designed to determine the evaluation value of serum miR-4299 and miR-16-5p in risk stratification of sepsis-induced acute kidney injury (SI-AKI). Methods. A total of 115 sepsis patients were enrolled and assigned to the SI-AKI group (n=64) or the sepsis-non-AKI group (n=51) based on the occurrence of AKI, and 72 healthy individuals were enrolled. Fasting venous blood was sampled from every patient before admission, before therapy, and after therapy, followed by quantification of miR-4299 and miR-16-5p by fluorescence quantitative PCR. Receiver operating characteristic (ROC) curves were drawn to evaluate the value of serum miR-16-5p and miR-4299 expression in predicting SI-AKI, and Pearson’s correlation analysis was performed to explore the associations of the two with Scr, Cys-C, and KIM-1. Results. Cases with sepsis, especially SI-AKI, presented significantly downregulated serum miR-4299 and miR-16-5p. After therapy, the expression in them increased. The area under curve (AUC) of serum miR-4299 and miR-16-5p in the prediction value for early diagnosis of SI-AKI was 0.895 (95% CI: 0.839-0.951, cutoff value: 0.780) and 0.838 (95% CI: 0.767-0.909, cutoff value: 0.775), respectively, and the AUC of them in the prediction value for clinical efficacy on the disease were 0.733 (95% CI: 0.645-0.820, cutoff value: 1.115) and 0.776 (95% CI: 0.698-0.855, cutoff value: 1.125), respectively. Serum miR-16-5p and mIR-4299 were negatively correlated with Scr, Cys-C, and KIM-1, separately. Conclusion. Both miR-16-5p and mIR-4299 are promising factors for early diagnosis of SI-AKI and dynamic evaluation of the efficacy on it.


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## Body

## 1. Introduction

According to the latest definition of sepsis, sepsis is a life-threatening organ dysfunction triggered by infection [1]. In this new definition, sepsis is a pathophysiological change accompanied by severe organ dysfunction that is associated with infection but different from infection. Sepsis and septic shock are the main causes for death worldwide [2]. In China, sepsis has gradually become a primary threat to people’s health. According to a descriptive analysis of sepsis in China [3], the standardized mortality rate of sepsis was 66.7 cases per 100 thousand people in China in 2015, suggesting a possible death toll of 1.03 million due to sepsis in China. Xie et al. [4] believe that sepsis is one of main causes of death of critically ill patients in China, and its mortality within 90 days was 35.5%. In addition, Jiang et al. [5] have pointed out that late-onset sepsis is the core cause of death and morbidity of critically ill newborns in China. In the induction of organ dysfunction by sepsis, acute kidney injury (AKI) is a common complication [6]. Nearly half of the critically ill patients with AKI are accompanied by sepsis. Compared with patients with AKI not triggered by sepsis, sepsis-induced acute kidney injury (SI-AKI) poses a higher risk of death in hospital and requires a longer hospitalization time [7].Early diagnosis and risk stratification are strongly conducive to intervention with the development of SI-AKI. At the current stage, urine volume and serum creatinine (Scr) are mainly utilized as biomarkers for SI-AKI [8], but both of them are insensitive or nonspecific. miRNA has been adopted as a crucial marker of disease progression for its high conservation and widespread existence. It is a crucial regulator of the pathogenesis under sepsis, so it has potential to be a biomarker of SI-AKI [9]. Liu et al. [10] have pointed out that miR-452 has the potential to be an effective biomarker for early screening of SI-AKI because of its sensitivity up to 87.23% in the detection of it. Pietrukaniec et al. [11] believe that miR-29a and miR-10a-5p can be adopted to predict the mortality of patients with SI-AKI in 28 days. Tang et al. [12] have pointed out that miR-29b-3p, miR-152-3p, and miR-223-3p all are probably crucial therapeutic targets for SI-AKI. Bioinformatics analysis revealed significantly downregulated miR-4299 and miR-16-5p in sepsis cases [13], which suggested the potential of the two as biomarkers for early diagnosis and risk stratification of SI-AKI. In the progression of sepsis, miR-16-5p probably takes part in the development of the AKI via mTOR pathway [14]. Despite the absence of definition of the mechanism under the role of miR-4299 in SI-AKI, the abnormal miR-4299 expression may offer a potential idea for screening SI-AKI. The potential roles of miR-4299 and miR-16-5p in sepsis will be determined based on an animal model of sepsis.We observed the significant downregulation of miR-4299 or miR-16-5p in sepsis patients. However, the evaluation value of serum miR-4299 and miR-16-5p in risk stratification of SI-AKI has yet to be reported. Accordingly, we enrolled 115 sepsis patients for analysis of the associations of serum miR-4299 and miR-16-5p with SI-AKI, with the goal of finding reliable biomarkers for risk stratification and early diagnosis of SI-AKI.


## 2. Methods

### 2.1. General Data

A total of 115 sepsis patients were enrolled based on the following inclusion and exclusion criteria. The inclusion criteria are as follows: patients confirmed with sepsis according to the diagnostic criteria of ACCP/SCCM [1], patients≥18 years old, patients without a history of sepsis before this study, patients with detailed general data, and those willing to cooperate with the study. The exclusion criteria are as follows: patients during the pregnant or lactating period, patients who had received antibiotic therapy, and those with comorbid malignancies, malignant swelling; chronic inflammatory diseases, or brain injury. The patients were assigned to the SI-AKI group (n=64) or the sepsis-non-AKI group (n=51) based on the diagnostic criteria of AKI developed by the Amsterdam Cooperative Research Association [15]. The two groups presented significant differences in the expression of renal function indexes (Scr, Cys-C, and KIM-1). The former group consisted of 35 males and 29 females, at 72.92±8.09 years old, including 12 cases of Gram-positive infection, 35 cases of Gram-negative infection, 10 cases of noncultured microbial infection, and 7 cases of virus infection. The latter group consisted of 27 males and 24 females, at 71.61±9.92 years old, including 9 cases of Gram-positive infection, 27 cases of Gram-negative infection, 6 cases of noncultured microbial infection, and 9 cases of virus infection. The two groups were similar in general data except for renal function markers (Table 1). After admission, all patients were given routine therapy of sepsis (antibiotic therapy) based on evaluation. Additionally, 72 healthy individuals were enrolled as normal controls. All participants signed informed consent forms after understanding the contents of the study, and the study was approved by the ethics committee of our hospital.Table 1
General data.
CharacteristicsSI-AKI groupSepsis-non-AKI groupχ2/tP valueGender0.040.852Male35 (54.69)27 (52.94)Female29 (45.31)24 (47.06)Age72.92±8.0971.61±9.920.780.436BMI∗ (kg·m-2)19.8620.361.550.124Microbiology1.2180.749Gram-positive129Gram-negative3527Noncultured organism106Virus79SOFA score8.66±1.548.53±1.600.4530.652Scr (mol·L-1)425.27±63.6384.40±27.7835.62<0.0001Cys-C (mg·L-1)1.65±0.260.73±0.1522.76<0.0001KIM-1 (g·L-1)19.63±5.225.36±0.8519.30<0.0001∗Notes: BMI: body mass index; SOFA: Sequential Organ Failure Assessment.


### 2.2. Serum Sample Acquisition

After an 8-hour fasting, 1.5 mL venous blood was sampled from every patient before admission, before therapy, and after therapy, separately. The collected blood was subjected to 10 min centrifugation (3000 rpm) at low temperature to acquire supernatant that was saved at -80°C for subsequent assays.


### 2.3. Detection of Renal Function Indexes

Serum KIM-1 level was detected by a KIM-1 enzyme-linked immunosorbent assay (ELISA) kit (E-El-H6029, Elabscience, Wuhan, China); serum Scr was determined by Scr colorimetric assay kit (E-BC-K188-M, Elabscience, Wuhan, China); serum Cys-C was determined by Cys-C ELISA kit (E-EL-H3643c, Elabscience, Wuhan, China).


### 2.4. qPCR Assay

Serum/total RNA was acquired via a serum/plasma miRNA extraction and separation kit (DP503, TIANGEN, Beijing, CN), followed by quantification of serum miR-4299 and miR-16-5p via a fluorescence quantitative (one-step) PCR kit (FP313, TIANGEN, Beijing, CN). Sense strand primer and antisense strand primer of miR-4299: 5′-GGC GCU GGU GAC AUG-3′ and 5′-GTG CAG GGT CCG AGG-3′, respectively; those of miR-16-5p: 5′-CTT AAG AAC CCT CCT TAC TC-3′ and 5′-AAG CTA CCC TAG GGG AAG GA-3′, respectively. This study adopted U6 as the internal reference gene. Sense strand primer and antisense strand primer of it: 5′-GCT TCG GCA GCA CAT ATA CTA AAA T-3′ and 5′-CGC TTC AGA ATT TGC GTG TCA T-3′, respectively. The 2-ΔΔCt method was adopted for relative expression calculation after the ΔCt value was acquired.


### 2.5. Statistics and Analyses

This study used SPSS 20.0 for statistical processing of sample data. The sample data were subjected to variation analysis after normality test. Counting data and measurement data were presented byn (%) and mean±SD, respectively. The data were tested by the Shapiro–Wilk test. Intergroup comparison was performed via the independent sample t-test and chi-square test, and samples before and after therapy were compared via the paired t-test. P<0.05 implies a notable difference of samples within 95% confidence interval. ROC curves were drawn to evaluate the value of the expression of serum miR-16-5p and miR-4299 in predicting SI-AKI, and Pearson’s correlation analysis was performed to explore the associations of the two with Scr, Cys-C, and KIM-1.


## 2.1. General Data

A total of 115 sepsis patients were enrolled based on the following inclusion and exclusion criteria. The inclusion criteria are as follows: patients confirmed with sepsis according to the diagnostic criteria of ACCP/SCCM [1], patients≥18 years old, patients without a history of sepsis before this study, patients with detailed general data, and those willing to cooperate with the study. The exclusion criteria are as follows: patients during the pregnant or lactating period, patients who had received antibiotic therapy, and those with comorbid malignancies, malignant swelling; chronic inflammatory diseases, or brain injury. The patients were assigned to the SI-AKI group (n=64) or the sepsis-non-AKI group (n=51) based on the diagnostic criteria of AKI developed by the Amsterdam Cooperative Research Association [15]. The two groups presented significant differences in the expression of renal function indexes (Scr, Cys-C, and KIM-1). The former group consisted of 35 males and 29 females, at 72.92±8.09 years old, including 12 cases of Gram-positive infection, 35 cases of Gram-negative infection, 10 cases of noncultured microbial infection, and 7 cases of virus infection. The latter group consisted of 27 males and 24 females, at 71.61±9.92 years old, including 9 cases of Gram-positive infection, 27 cases of Gram-negative infection, 6 cases of noncultured microbial infection, and 9 cases of virus infection. The two groups were similar in general data except for renal function markers (Table 1). After admission, all patients were given routine therapy of sepsis (antibiotic therapy) based on evaluation. Additionally, 72 healthy individuals were enrolled as normal controls. All participants signed informed consent forms after understanding the contents of the study, and the study was approved by the ethics committee of our hospital.Table 1
General data.
CharacteristicsSI-AKI groupSepsis-non-AKI groupχ2/tP valueGender0.040.852Male35 (54.69)27 (52.94)Female29 (45.31)24 (47.06)Age72.92±8.0971.61±9.920.780.436BMI∗ (kg·m-2)19.8620.361.550.124Microbiology1.2180.749Gram-positive129Gram-negative3527Noncultured organism106Virus79SOFA score8.66±1.548.53±1.600.4530.652Scr (mol·L-1)425.27±63.6384.40±27.7835.62<0.0001Cys-C (mg·L-1)1.65±0.260.73±0.1522.76<0.0001KIM-1 (g·L-1)19.63±5.225.36±0.8519.30<0.0001∗Notes: BMI: body mass index; SOFA: Sequential Organ Failure Assessment.


## 2.2. Serum Sample Acquisition

After an 8-hour fasting, 1.5 mL venous blood was sampled from every patient before admission, before therapy, and after therapy, separately. The collected blood was subjected to 10 min centrifugation (3000 rpm) at low temperature to acquire supernatant that was saved at -80°C for subsequent assays.


## 2.3. Detection of Renal Function Indexes

Serum KIM-1 level was detected by a KIM-1 enzyme-linked immunosorbent assay (ELISA) kit (E-El-H6029, Elabscience, Wuhan, China); serum Scr was determined by Scr colorimetric assay kit (E-BC-K188-M, Elabscience, Wuhan, China); serum Cys-C was determined by Cys-C ELISA kit (E-EL-H3643c, Elabscience, Wuhan, China).


## 2.4. qPCR Assay

Serum/total RNA was acquired via a serum/plasma miRNA extraction and separation kit (DP503, TIANGEN, Beijing, CN), followed by quantification of serum miR-4299 and miR-16-5p via a fluorescence quantitative (one-step) PCR kit (FP313, TIANGEN, Beijing, CN). Sense strand primer and antisense strand primer of miR-4299: 5′-GGC GCU GGU GAC AUG-3′ and 5′-GTG CAG GGT CCG AGG-3′, respectively; those of miR-16-5p: 5′-CTT AAG AAC CCT CCT TAC TC-3′ and 5′-AAG CTA CCC TAG GGG AAG GA-3′, respectively. This study adopted U6 as the internal reference gene. Sense strand primer and antisense strand primer of it: 5′-GCT TCG GCA GCA CAT ATA CTA AAA T-3′ and 5′-CGC TTC AGA ATT TGC GTG TCA T-3′, respectively. The 2-ΔΔCt method was adopted for relative expression calculation after the ΔCt value was acquired.


## 2.5. Statistics and Analyses

This study used SPSS 20.0 for statistical processing of sample data. The sample data were subjected to variation analysis after normality test. Counting data and measurement data were presented byn (%) and mean±SD, respectively. The data were tested by the Shapiro–Wilk test. Intergroup comparison was performed via the independent sample t-test and chi-square test, and samples before and after therapy were compared via the paired t-test. P<0.05 implies a notable difference of samples within 95% confidence interval. ROC curves were drawn to evaluate the value of the expression of serum miR-16-5p and miR-4299 in predicting SI-AKI, and Pearson’s correlation analysis was performed to explore the associations of the two with Scr, Cys-C, and KIM-1.


## 3. Results

### 3.1. Serum miR-4299 and miR-16-5p in SI-AKI Cases

A total of 115 sepsis patients and 72 healthy individuals were enrolled, and their serum was sampled, followed by quantification of miR-4299 and miR-16-5p. According to Figures1(a) and 1(b), sepsis patients presented significantly downregulated serum miR-4299 and miR-16-5p than healthy individuals (P<0.05). Then, the patients were assigned to the SI-AKI group (n=64) or the sepsis-non-AKI group (n=51) based on the occurrence of AKI, and compared in terms of serum miR-4299 and miR-16-5p expression. Interestingly, compared with the sepsis-non-AKI group, the SI-AKI group also presented significantly down-regulated serum miR-4299 (Figure 1(c)) and miR-16-5p (Figure 1(d)).Figure 1
The expressions of miR-4299 and miR-16-5p in sepsis (independentt-test was used for the comparison between two groups). (a) The difference of serum miR-4299 expression between sepsis patients and healthy individuals. (b) The difference of serum miR-4299 expression between SI-AKI patients and sepsis-non-AKI patients. (c) The difference of serum miR-16-5p expression between sepsis patients and healthy individuals. (d) The difference of serum miR-16-5p expression between SI-AKI and sepsis-non-AKI patients.
(a)(b)(c)(d)


### 3.2. Predictive Value of Serum miR-4299 and miR-16-5p in Early Screening of SI-AKI

In order to determine the predictive value of serum miR-4299 and miR-16-5p in early screening of SI-AKI, the differential expression of miR-4299 and miR-16-5p between sepsis patients and healthy individuals was analyzed based on ROC curves. The AUC and cutoff value of serum miR-4299 in sepsis diagnosis was 0.782 (95% CI: 0.717-0.846), and 0.745, respectively (Figure2(a) and Table 2), and the AUC and cutoff value of serum miR-16-5p in it was 0.776 (95% CI: 0.710-0.842) and 0.945, respectively (Figure 2(b) and Table 2). Then, ROC curves were drawn to evaluate the value of them in predicting SI-AKI. According to Figures 2(c) and 2(d) and Table 2, the AUCs of them in diagnosing SI-AKI were 0.895 (95% CI: 0.839-0.951) and 0.838 (95% CI: 0.767-0.909), respectively, and the cutoff value of them in diagnosing SI-AKI were 0.780 and 0.775, respectively. These results suggest the potential of serum miR-4299 and miR-16-5p serum in the early screening of SI-AKI.Figure 2
Predictive value of serum miR-4299 and miR-16-5p in early screening of SI-AKI based on ROC curves. (a) ROC curve of serum miR-4299 in diagnosing early sepsis. (b) ROC curve of serum miR-16-5p in diagnosing early sepsis. (c) ROC curve of serum miR-4299 in diagnosing SI-AKI. (d) ROC curve of serum miR-16-5p in diagnosing SI-AKI.
(a)(b)(c)(d)Table 2
Predictive value of serum miR-4299 and miR-16-5p in early screening of SI-AKI.
AUC95% CIS.ECutoffmiR-4299Sepsis vs. normal0.7820.717-0.8460.0330.745SI-AKI vs. sepsis-non-AKI0.8950.839-0.9510.0290.780miR-16-5pSepsis vs. normal0.7760.710-0.8420.0340.945SI-AKI vs. sepsis-non-AKI0.8380.767-0.9090.0360.775


### 3.3. Associations of Serum miR-4299 and miR-16-5p with Clinical Pathology of SI-AKI

Pearson’s correlation analysis was conducted to explore the associations of serum miR-4299 and miR-16-5p with Scr, Cys-C, and KIM-1. The results revealed that serum miR-4299 was negatively correlated with Scr (P<0.0001), Cys-C (P<0.0001), and KIM-1 (P<0.0001) and serum miR-16-5p was also negatively associated with them (P<0.0001, P<0.0001, and P<0.0001) (Figure 3), suggesting that the down-regulation of serum miR-4299 and miR-16-5p might be the causes of sepsis complicated with AKI.Figure 3
Associations of serum miR-4299 and miR-16-5p with clinical pathology of SI-AKI based on Pearson correlation analysis. (a) Association of serum miR-4299 with Scr. (b) Association of serum miR-4299 with Cys-C. (c) Association of serum miR-4299 with KIM-1. (d) Association of serum miR-16-5p with Scr. (e) Association of serum miR-16-5p with Cys-C. (f) Association of serum miR-16-5p with KIM-1.
(a)(b)(c)(d)(e)(f)


### 3.4. Predictive Value of Serum miR-4299 and miR-16-5p in the Clinical Efficacy on SI-AKI

This study was designed to determine the evaluation value of serum miR-4299 and miR-16-5p in risk stratification of SI-AKI, so the expression differences of serum miR-4299 and miR-16-5p between SI-AKI patients before and after therapy was analyzed (Figure4). Surprisingly, after therapy, serum miR-4299 and miR-16-5p increased significantly after therapy (P<0.05).Figure 4
miR-4299 and miR-16-5p expression changes before and after therapy (the comparison between the two timepoints was processed by pair t test). (a) Changes of serum miR-4299 expression before and after therapy. (b) Change of serum miR-16-5p expression before and after therapy.
(a)(b)In view of the notable upregulation of serum miR-4299 and miR-16-5p after therapy, we inferred that the two were promising in predicting the clinical efficacy on patients and then facilitating timely analysis of patients’ prognosis. Accordingly, ROC curves were drawn to evaluate the value of serum miR-4299-5p and miR-16 expression in predicting the clinical efficacy on SI-AKI. According to Figure5 and Table 3, the AUCs of serum miR-4299 and miR-16-5p in predicting clinical efficacy of SI-AKI was 0.733 (0.945-0.820) and 0.776 (0.698-855), respectively, and the cutoff values of them were 1.115 and 1.125, respectively.Figure 5
(a) ROC curve of serum miR-4299 before therapy in predicting the efficacy on SI-AKI. (b) ROC curve of serum miR-16-5p before therapy in predicting the efficacy on SI-AKI.
(a)(b)Table 3
Predictive value of serum miR-4299 and miR-16-5p in clinical efficacy on SI-AKI.
AUC95% CIS.ECutoffmiR-42990.7330.645-0.8200.0451.115miR-16-5p0.7760.698-0.8550.0401.125


## 3.1. Serum miR-4299 and miR-16-5p in SI-AKI Cases

A total of 115 sepsis patients and 72 healthy individuals were enrolled, and their serum was sampled, followed by quantification of miR-4299 and miR-16-5p. According to Figures1(a) and 1(b), sepsis patients presented significantly downregulated serum miR-4299 and miR-16-5p than healthy individuals (P<0.05). Then, the patients were assigned to the SI-AKI group (n=64) or the sepsis-non-AKI group (n=51) based on the occurrence of AKI, and compared in terms of serum miR-4299 and miR-16-5p expression. Interestingly, compared with the sepsis-non-AKI group, the SI-AKI group also presented significantly down-regulated serum miR-4299 (Figure 1(c)) and miR-16-5p (Figure 1(d)).Figure 1
The expressions of miR-4299 and miR-16-5p in sepsis (independentt-test was used for the comparison between two groups). (a) The difference of serum miR-4299 expression between sepsis patients and healthy individuals. (b) The difference of serum miR-4299 expression between SI-AKI patients and sepsis-non-AKI patients. (c) The difference of serum miR-16-5p expression between sepsis patients and healthy individuals. (d) The difference of serum miR-16-5p expression between SI-AKI and sepsis-non-AKI patients.
(a)(b)(c)(d)


## 3.2. Predictive Value of Serum miR-4299 and miR-16-5p in Early Screening of SI-AKI

In order to determine the predictive value of serum miR-4299 and miR-16-5p in early screening of SI-AKI, the differential expression of miR-4299 and miR-16-5p between sepsis patients and healthy individuals was analyzed based on ROC curves. The AUC and cutoff value of serum miR-4299 in sepsis diagnosis was 0.782 (95% CI: 0.717-0.846), and 0.745, respectively (Figure2(a) and Table 2), and the AUC and cutoff value of serum miR-16-5p in it was 0.776 (95% CI: 0.710-0.842) and 0.945, respectively (Figure 2(b) and Table 2). Then, ROC curves were drawn to evaluate the value of them in predicting SI-AKI. According to Figures 2(c) and 2(d) and Table 2, the AUCs of them in diagnosing SI-AKI were 0.895 (95% CI: 0.839-0.951) and 0.838 (95% CI: 0.767-0.909), respectively, and the cutoff value of them in diagnosing SI-AKI were 0.780 and 0.775, respectively. These results suggest the potential of serum miR-4299 and miR-16-5p serum in the early screening of SI-AKI.Figure 2
Predictive value of serum miR-4299 and miR-16-5p in early screening of SI-AKI based on ROC curves. (a) ROC curve of serum miR-4299 in diagnosing early sepsis. (b) ROC curve of serum miR-16-5p in diagnosing early sepsis. (c) ROC curve of serum miR-4299 in diagnosing SI-AKI. (d) ROC curve of serum miR-16-5p in diagnosing SI-AKI.
(a)(b)(c)(d)Table 2
Predictive value of serum miR-4299 and miR-16-5p in early screening of SI-AKI.
AUC95% CIS.ECutoffmiR-4299Sepsis vs. normal0.7820.717-0.8460.0330.745SI-AKI vs. sepsis-non-AKI0.8950.839-0.9510.0290.780miR-16-5pSepsis vs. normal0.7760.710-0.8420.0340.945SI-AKI vs. sepsis-non-AKI0.8380.767-0.9090.0360.775


## 3.3. Associations of Serum miR-4299 and miR-16-5p with Clinical Pathology of SI-AKI

Pearson’s correlation analysis was conducted to explore the associations of serum miR-4299 and miR-16-5p with Scr, Cys-C, and KIM-1. The results revealed that serum miR-4299 was negatively correlated with Scr (P<0.0001), Cys-C (P<0.0001), and KIM-1 (P<0.0001) and serum miR-16-5p was also negatively associated with them (P<0.0001, P<0.0001, and P<0.0001) (Figure 3), suggesting that the down-regulation of serum miR-4299 and miR-16-5p might be the causes of sepsis complicated with AKI.Figure 3
Associations of serum miR-4299 and miR-16-5p with clinical pathology of SI-AKI based on Pearson correlation analysis. (a) Association of serum miR-4299 with Scr. (b) Association of serum miR-4299 with Cys-C. (c) Association of serum miR-4299 with KIM-1. (d) Association of serum miR-16-5p with Scr. (e) Association of serum miR-16-5p with Cys-C. (f) Association of serum miR-16-5p with KIM-1.
(a)(b)(c)(d)(e)(f)


## 3.4. Predictive Value of Serum miR-4299 and miR-16-5p in the Clinical Efficacy on SI-AKI

This study was designed to determine the evaluation value of serum miR-4299 and miR-16-5p in risk stratification of SI-AKI, so the expression differences of serum miR-4299 and miR-16-5p between SI-AKI patients before and after therapy was analyzed (Figure4). Surprisingly, after therapy, serum miR-4299 and miR-16-5p increased significantly after therapy (P<0.05).Figure 4
miR-4299 and miR-16-5p expression changes before and after therapy (the comparison between the two timepoints was processed by pair t test). (a) Changes of serum miR-4299 expression before and after therapy. (b) Change of serum miR-16-5p expression before and after therapy.
(a)(b)In view of the notable upregulation of serum miR-4299 and miR-16-5p after therapy, we inferred that the two were promising in predicting the clinical efficacy on patients and then facilitating timely analysis of patients’ prognosis. Accordingly, ROC curves were drawn to evaluate the value of serum miR-4299-5p and miR-16 expression in predicting the clinical efficacy on SI-AKI. According to Figure5 and Table 3, the AUCs of serum miR-4299 and miR-16-5p in predicting clinical efficacy of SI-AKI was 0.733 (0.945-0.820) and 0.776 (0.698-855), respectively, and the cutoff values of them were 1.115 and 1.125, respectively.Figure 5
(a) ROC curve of serum miR-4299 before therapy in predicting the efficacy on SI-AKI. (b) ROC curve of serum miR-16-5p before therapy in predicting the efficacy on SI-AKI.
(a)(b)Table 3
Predictive value of serum miR-4299 and miR-16-5p in clinical efficacy on SI-AKI.
AUC95% CIS.ECutoffmiR-42990.7330.645-0.8200.0451.115miR-16-5p0.7760.698-0.8550.0401.125


## 4. Discussion

Sepsis has captured attention by becoming a serious public health problem over the past few years. Sepsis pathogens can be bacteria, fungi, or viruses, and no specific therapy strategy has been developed for it [16]. Clinical outcome of sepsis is strongly correlated with timely diagnosis and proper early therapy [17]. Unfortunately, the complexity of sepsis pathogenesis and the heterogeneity of clinical symptoms result in the lack of “gold standard” in early sepsis screening. Some people believe that miRNA molecule is a novel marker of sepsis for its involvement in the regulation of pathophysiology of sepsis [18]. AKI is one of common complications of sepsis and the main cause of death from disease. Therefore, an effective marker is urgently required for timely detection of SI-AKI. In our study, serum miR-4299 and miR-16-5p were significantly downregulated in sepsis patients, and the ROC curve-based analysis revealed their potential for early diagnosis and clinical efficacy evaluation on SI-AKI.With the increasingly deepening understanding of the pathogenesis of sepsis, more attention is paid to the pathophysiological regulation of miRNA. In the present study, serum miR-4299 and miR-16-5p showed significant downregulation in cases with SI-AKI compared with healthy individuals and sepsis patients without AKI, which implied that serum miR-4299 and miR-16-5p were strongly associated with SI-AKI. miR-16-5p has been verified to take a crucial regulatory part in septic lung injury. Yin et al. [19] have pointed out that lncRNA NETA1 promotes the up-regulation of BRD4 via sponge adsorption of miR-16-5p and further aggravates the development of sepsis-induced lung injury. In the process of induction of sepsis to AKI, some people hold a view that miR-16-5p participates in autophagy of kidney tissue by targeting mTORC protein [14, 20], and there is also evidence that miR-16-5p suppresses the release of proinflammatory macrophages as a urine biomarker of AKI and then regulates the renal inflammatory response [21]. Based on the above research and the results of the present study, the downregulation of miR-16-5p is probably a landmark event of SI-AKI, during which the downregulation promotes the pathophysiological process of SI-AKI through macrophage polarization conversion and autophagy mediated by the mTOR pathway. Accordingly, we also believe serum miR-4299 involves in a similar mechanism in SI-AKI. At the current stage, the specific mechanism of miR-4299 in sepsis has not been reported. Wu et al. [22] predicted the possible targeting of miR-4299 in gene expression including SMAD3, BTC, and IGF1R in the process of cisplatin-induced renal injury and its involvement in series of biological processes such as protein degradation and intercellular receptor signaling pathway. This potential regulatory network may explain the significant downegulation of miR-4299 in SI-AKI. The specific mechanism of miR-4299 still requires more research for better confirmation.Interestingly, serum miR-4299 and miR-16-5p in cases with SI-AKI increased significantly after therapy in our study, implying the crucial role of the two in alleviating SI-AKI. In addition, before therapy, serum miR-4299 and miR-16-5p expressions were significantly negatively associated with Scr, Cys-C, and KIM-1 [8, 11, 23], suggesting that their expression was promising for prediction or evaluation of adverse outcome of sepsis patients. Accordingly, we adopted ROC curves for analysis of the value of serum miR-4299 and miR-16-5 in the risk stratification of SI-AKI. According to the results, first of all, serum miR-4299 and miR-16-5p are promising in distinguishing SI-AKI in early diagnosis. Then, the two have favorable value in predicting the efficacy on patients. We only discussed the application value of miR-4299 and miR-16-5p in sepsis risk stratification and diagnosis but failed to explore their evaluation value in sepsis prognosis. Also, this study is based on 115 patients with sepsis and 72 healthy people. It may still need to include a larger sample size for model validation.To sum up, serum miR-4299 and miR-16-5p have evaluation value in risk stratification of SI-AKI. They are promising in distinguishing SI-AKI. During therapy, serum miR-4299 and miR-16-5p expressions in the course of therapy are also helpful for clinical detection of renal function changes in patients with SI-AKI, which has a potential value for dynamically evaluating the efficacy on SI-AKI. The value of serum miR-4299 and miR-16-5p in SI-AKI deserves further study and discussion.



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*Source: 5165892-2022-07-08.xml*