Association of Urinary Biomarkers Noninvasively Forecasts The Extent of Renal Injury In The Early Diabetic Nephropathy Patients With Kidney Qi Deficiency Syndrome: A Retrospective Investigation&nbsp;

doi:10.21203/rs.3.rs-90747/v1

Download PDF

Research

Association of Urinary Biomarkers Noninvasively Forecasts The Extent of Renal Injury In The Early Diabetic Nephropathy Patients With Kidney Qi Deficiency Syndrome: A Retrospective Investigation

https://doi.org/10.21203/rs.3.rs-90747/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background: Recently, diabetic nephropathy (DN) becomes a common health problem in China as one of the major microvascular complications of diabetes mellitus. Therefore, the incipient diagnosis and noninvasive detections in clinic by the association of urinary biomarkers are important for preventing the progress of DN. However, the clinical significance of urinary biomarkers is controversial nowadays. This study thereby aimed to further evaluate the clinical significance of the association of urinary biomarkers in noninvasively predicting the renal damaged extent of the early type 2 DN patients with kidney qi deficiency syndrome in an integrated traditional and western medical center, and preliminarily confirm the correlation between urinary tubular biomarkers and the biological bases of DN patients.

Methods: Ninety-two patients in an integrated traditional and western medical center of China were categorized into 3 groups, 20 patients with normo-albuminuria, 50 patients with micro-albuminuria, and 22 patients with macro-albuminuria. In addition to urinary albumin (UAlb) and urinary albumin-to-creatinine ratio (UACR), serum creatinine, estimated glomerular filtration rate and various urinary tubular biomarkers were tested respectively. Besides, clinical characteristics and kidney asthenia syndrome distribution in all patients were observed.

Results: In these 3 groups, 24-h UAlb and UACR showed stepwise and significant increases. Urinary cystatin C (UCysC), urinary N-acety1-β-D-glucosaminidase (UNAG) and urinary retinal binding protein (URBP) synchronously showed gradual increases consistent with albuminuria degree in 3 groups. Moreover, 24-h UAlb and UACR were positively correlated with UCysC, UNAG and URBP. In the 72 DN patients with albuminuria, there was a positive correlation between UNAG and URBP, and UCysC was also positively correlated with UNAG and URBP. Additionally, TCM syndrome distributional characteristics in all patients were consistent with the clinical manifestations of kidney qi deficiency syndrome.

Conclusion: In this investigation, we ulteriorly demonstrated that the association within UCysC, UNAG, URBP and UAlb may be used as practical targets in noninvasively forecasting the extent of renal injury in the early type 2 DN patients with kidney qi deficiency syndrome. More importantly, we found that urinary tubular biomarkers may be one of the biological bases of DN patients with the specific traditional Chinese medicine syndrome.

Internal Medicine

Urinary biomarkers

Diabetic nephropathy

Traditional Chinese medicine syndrome

Nowadays, diabetic nephropathy (DN) becomes a common health problem in China as one of the major microvascular complications of diabetes mellitus (DM) [1]. 30–40% of the patients with DM develop to DN, which is the dominant cause of end-stage renal disease (ESRD) [2]. Therefore, the clinical incipient diagnosis and noninvasive detections are important for preventing the progress from DN to ESRD. It is reported that, albuminuria is one of the most typical clinical changes in the early stage of DN, and the level of albuminuria excretion can be determined as a way for DN patients screening [3]. However, growing evidences have recently suggested that the detection of albuminuria alone is not comprehensive and sensitive for DN patients, especially for those with inchoate and latent injuries in glomeruli and renal tubules [4]. On the other hand, although renal biopsy is thought to be the best method for the diagnosis of DN at the incipient stage [5], it is impossible to be performed in all cases because of its invasion. Given these shortcomings in clinic, more workable biomarkers in urine other than urinary albumin (UAlb) are crucially required to be explored for the earlier diagnosis and prediction of renal injurious extent in DN patients [6].

Generally speaking, glomerular dysfunction is a major cause of DN development [7]. Even though, the impaired absorption of the filtered proteins from renal tubular epithelium might also play many important roles in incipient DN [8]. Notably, the increasing evidences have demonstrated that, as biomarkers, some tubular injurious indicators in urine have clinical implications [9]. It includes urinary cystatin C (UCysC) [10, 11], urinary N-acety1-β-D-glucosaminidase (UNAG) [12], urinary kidney injury molecule (UKim)-1 [12–13], urinary 1iver-type fatty acid-binding protein (UL-FABP) [14], urinary retinal binding protein (URBP), urinary neutrophil getatinase-associated lipocalin (UNGAL), urinary β2-microglobulin (Uβ2-MG) and so on [15, 16]. Thereinto, UNAG and URBP have been especially reported to be associated with the progression of type 2 DM [15]. On the contrary, recently Macisaac et al. [17] considered there was neither a clinical assay nor an adequate study focuses on defining urinary biomarkers’ prognostic value in the DN progress. Besides, Hus et al. [18] lately reported the urine biomarkers of tubular injury did not improve on the clinical model predicting chronic kidney disease (CKD) progression. Therefore, so far, the clinical significance of urinary biomarkers in predicting renal injurious extent of DN is controversial.

In traditional Chinese medicine (TCM), DN is recognized as Xiaoke (a disease with symptomatic polydipsia)-related nephropathy. According to the fundamental principles of TCM theory, the main pathogenesis of DN lies in kidney asthenia [19–20]. More importantly, in clinic, Chinese herbal medicine (CHM) formulas focused on nourishing kidney such as Tangshen Formula (TSF) [21] and Liuwei Dihuang Pills (LDP) [22] have played many important roles in the treatment of Xiaoke and its related complications in the kidney. Yang et al. [21] reported that TSF combined with conventional therapy appear to be effective in reducing urinary protein and UL-FABP, which is considered to be associated with the severity of DN as a new urinary renal tubular biomarker. Correspondingly, our previous study based on 108 patients with stage III type 2 DN in China, a unicentral observation with a cross sectional design, indicated that 79 patients with the deficiency states of both kidney and spleen showed different increased levels of UCysC, UNAG and URBP, which as the specific markers of renal tubular dysfunction rather than glomerular damage. Of note, the increase in UCysC has been closely related to UAlb in 30 patients with kidney deficiency syndrome [23]. These results strongly suggested that the association of urinary biomarkers is possibly used as practical targets in noninvasively forecasting the extent of renal injury in the type 2 DN patients with kidney asthenia syndrome. Hence, in this investigation, we aimed to further evaluate the clinical significance of the association of urinary biomarkers in noninvasively predicting the renal damaged extent of the early type 2 DN patients with kidney qi deficiency syndrome in an integrated traditional and western medical center, and preliminarily confirm the correlation between urinary tubular biomarkers and the biological bases of DN patients.

Study population

We retrospectively investigated the samples of urine from the 92 patients with type 2 DM who were consecutively enrolled at the Department of Endocrinology and TCM, Nanjing Drum Tower Hospital from March 2012 to April 2013. The proposal was approved by the Ethics Committee of The Affiliated Hospital of Nanjing University Medical School (Nanjing Drum Tower Hospital). All patients were categorized into 3 groups according to their albuminuria levels based on urinary albumin-to-creatinine ratio (UACR), including 20 patients with normo-albuminuria (< 30 mg/g creatinine), 50 patients with micro-albuminuria (30–300 mg/g creatinine), and 22 patients with macro-albuminuria (> 300 mg/g ceatinine) (Fig. 1).

The eligible subjects meeting the following criteria were included in the study: (1) conforming to the diagnostic criteria for type 2 DM, (2) serum creatinine (Scr) < 106 µmol/L, (3) stable renal function status without 2-fold elevation of Scr for at least 5 months, (4) no history about administration of renin-angiotensin system (RAS) inhibitors including angiotensin converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB). Accordingly, the ineligible criteria were composed of eight conditions: (1) renal disease other than DN, (2) active urinary tract infection, (3) thyroid dysfunction, (4) severe liver dysfunction, (5) neoplastic disorders, (6) active or chronic persistent inflammatory disorders, (7) pregnancy and (8) acute myocardial infarction.

Collection of kidney deficiency syndrome information

Signs and symptoms by kidney deficiency syndrome of TCM diagnostic methods mainly including kidney qi deficiency syndrome, kidney yang deficiency syndrome, kidney yin deficiency syndrome and kidney essence insufficiency syndrome were collected respectively [24, 25, 26]. The clinical manifestations include aching and weakness of loins and knees, dispiritedness and lassitude, frequent micturition, dripping urination, incontinence of urine, light-colored tongue with whitish fur and thin pulse; dizziness and tinnitus, insomnia and amnesia, flushed cheeks in the afternoon, bone-steaming tidal fever, night sweating, dry mouth and throat, emaciation, yellowish and scanty urine, reddish tongue with scanty fur and thin and rapid pulse; cold limbs and body, loose stool, early morning diarrhea, clear and profuse urine, profuse nocturnal urine, bright whitish complexion, light colored tongue with white fur as well as sinking and deep and weak pulse. All of kidney deficiency syndrome information was collected using a unified questionnaire.

Clinical and laboratory measurement

All eligible subjects provided 20 mL second voided clean-catch urine samples in the early morning after an overnight fast. These samples were immediately frozen and stored at -80 °C to prevent protein degradation before the test. Urine samples were centrifuged at speed of 3000 r/min for 10 min. And the supernatants were collected for sample test in 2 hours. Twenty-four-hours UAlb (24-h UAlb) was tested using immunoturbidimetric assay (Yong Ye, ShangHai, China). Subsequently, baseline of albuminuria status was determined according to UACR. The levels of URBP, UNAG and UCysC were measured using immune turbidimetric method (KangTe, Zhejiang, China), colourimetry (Mei Kang, Zhejiang, China) and particle-enhanced nephelometric immunoassay (YanJing, ShangHai, China) respectively. All the relevant procedures were followed by the manufacturer’s instructions.

In addition, all patients donated fasting venous blood (2 mL) in the morning. And serum was separated by centrifugation. The levels of estimated glomerular filtration rate (eGFR) were calculated using the Modification of Diet in Renal Disease (MDRD) formula: MDRD = 186 × (serum creatinine [mg/dL])^−1.154 × (age in years) ^−0.203 × 0.742 (A correction factor of 0.742 was used for women) [27].

Statistical analysis

All analyses were performed using the SPSS software (Version 16.0, SPSS Inc, USA) and the Graph Pad Prism 5. The data were expressed as mean ± SD for normally distributed values and median (interquartile range) for nonparametric values. Qualitative data were described as frequencies and analyzed using the Chi-square test. Differences among groups were analyzed by the one-way ANOVA followed by the Bonferroni’s test for normally distributed values, and by the Kruskal-Wallis test for nonparametric values. SNK (Student-Newman-Keuls) or LSD (Least significant difference) method was used for multiple comparisons. To test the correlations between different urinary markers, Pearson’s correlation coefficient was employed for normally distributed values and Spearman’s correlation coefficient for skew distributed values. To determine the association between UACR, 24-h UAlb and urinary markers respectively, with the exception of bivariate correlation analysis, we performed linear regression analysis with the urinary markers as independent variables and UACR, 24-h UAlb as dependent variables in order to investigate the urinary markers related to albuminuria. Clinical parameters related to the elevated urinary markers were analyzed using multivariate logistic regression according to the ‘‘Enter’’ procedure. The p-value report was two-sided and value of less than 0.05 was considered statistically significant.

Clinical characteristics in all patients

The study population of type 2 DM is consisted of 20 patients with normo-albuminuria, 50 patients with micro-albuminuria and 22 patients with macro-albuminuria. All patients’ baseline characteristics are summarized in Table 1. The mean age and DM duration of the patients were 63.12 ± 12.07 years and 12.62 ± 1.17 years respectively, and there were 47 males and 45 females. According to the baseline data, we did not find a significant difference in sex, age, DM duration, systolic blood pressure (SBP), diastolic blood pressure (DBP), fast blood glucose (FBG), 2 hours postprandial blood glucose (2-h PBG), glycated hemoglobin (HbA1c), triglyceride (TG), blood urea nitrogen (BUN) and uric acid (UA) among normo-albuminuria, micro-albuminuria and macro-albuminuria groups. Although the levels of body mass index (BMI) and low-density lipoprotein cholesterol (LDL-C) in normo-albuminuria, micro-albuminuria and macro-albuminuria groups showed the stepwise increase with albuminuria level, there was no statistical significance among 3 groups. We also found that the level of total cholesterol (TC) in macro-albuminuria group was significantly higher than that in normo-albuminuria group (p = 0.017), and the levels of Scr and eGFR in macro-albuminuria group were significantly increased compared with those in micro-albuminuria group (p = 0.004, p = 0.022), whereas there were no significant differences between micro-albuminuria and normo-albuminuria groups.

Table 1

Baseline characteristics of laboratory parameters in all patients
	normo-albuminuria (n = 20)	micro-albuminuria (n = 50)	macro-albuminuria (n = 22)	p-value
Sex (male/female)	12/8	22/28	13/9	0.350
Age (years)	64.80 ± 13.90	61.38 ± 11.57	65.55 ± 11.33	0.318
Duration of DM (years)	12.40 ± 1.10	12.68 ± 1.10	12.68 ± 1.39	0.641
BMI (kg/m²)	23.29 ± 1.41	25.17 ± 3.87	25.70 ± 4.38	0.161
SBP (mmHg)	136.10 ± 14.80	136.58 ± 18.18	143.23 ± 17.10	0.278
DBP (mmHg)	78.20 ± 12.67	80.04 ± 10.72	79.09 ± 12.57	0.827
FBG (mmol/L)	9.04 ± 3.00	10.18 ± 2.38	9.16 ± 2.56	0.135
2hPBG (mmol/L)	16.07 ± 5.13	15.22 ± 5.98	15.44 ± 4.87	0.847
HbA1c (%)	8.75 ± 2.01	9.30 ± 2.12	8.57 ± 1.21	0.273
TC (mmol/L)	4.19 (3.57–4.88)	4.54 (3.80–5.29)	5.14 (4.39–5.36)^a	0.049
TG (mmol/L)	1.11 (0.75–1.71)	1.55 (0.94–2.13)	1.43 (1.12–2.02)	0.126
LDL-C (mmol/L)	2.50 ± 0.78	2.68 ± 0.89	2.80 ± 0.71	0.505
BUN (mmol/L)	6.17 ± 1.55	5.95 ± 1.54	6.50 ± 2.09	0.438
Scr (µmol/L)	69.58 ± 16.06	64.85 ± 20.27	78.82 ± 17.07^b	0.017
eGFR (mL/min/1.73 m²)	95.25 (78.97-123.12)	99.52 (80.47-133.22)	81.25 (73.31-106.15)^b	0.056
UA (µmol/L)	286.65 ± 75.28	311.82 ± 95.71	324.95 ± 81.89	0.365
The data are expressed as mean ± SD for parametric variables and median (interquartile range) for nonparametric variables.

Distribution of kidney deficiency syndrome

TCM syndrome could be validated by corresponding diagnostic standards of kidney asthenia [26]. Kidney deficiency syndrome of all patients was divided into the following types, including kidney qi deficiency syndrome, kidney yang deficiency syndrome, kidney yin deficiency syndrome and kidney essence insufficiency syndrome. As shown in Table 2, among these 92 patients with type 2 DM, the syndromes that occurred at least 30% included: aching and weakness of loins and knees (78.3%), dispiritedness and lassitude (78.3%), frequent micturition (47.8%), dripping urination (33.7%), dizziness and tinnitus (31.5%), light-colored tongue with whitish fur (86.9%) and thin pulse (30.4%). There is no doubt that these TCM syndrome distributional characteristics in all patients were consistent with the clinical manifestations of kidney qi deficiency syndrome.

Table 2

Distribution of kidney asthenia syndrome distribution in all patients
	normo-albuminuria (n = 20)	micro-albuminuria (n = 50)	macro-albuminuria (n = 22)
aching and weakness of loins and knees	14 (70%)	40 (80%)	18 (81.8%)
dispiritedness and lassitude	12 (60%)	42 (84%)	18 (81.8%)
frequent micturition	4 (20%)	29 (38%)	11 (50%)
dripping urination	3 (15%)	18 (36%)	10 (45.5%)
incontinence of urine	0	0	0
light-coloured tongue with whitish fur	18 (90%)	45 (90%)	17 (77.3%)
thin pulse	8 (40%)	10 (20%)	10 (45.5%)
dizziness and tinnitus	3 (15%)	18 (36%)	8 (36.4%)
insomnia and amnesia	1 (5%)	2 (4%)	1 (4.5%)
flushed cheeks in the afternoon	0	1 (2%)	0
bone-steaming tidal fever	0	0	0
night sweating	2 (10%)	1 (2%)	0
dry mouth and throat	2 (10%)	4 (8%)	2 (9%)
emaciation	0	0	0
yellowish and scanty urine	0	0	0
reddish tongue with scanty fur	1 (5%)	1 (2%)	2 (9%)
thin rapid pulse	0	1 (2%)	1 (4.5%)
cold limbs and body	0	0	0
loose stool	1 (5%)	2 (4%)	2 (9%)
early morning diarrhea	1 (5%)	1 (2%)	0
clear and profuse urine	1 (5%)	1 (2%)	1 (4.5%)
profuse nocturnal urine	2 (10%)	1 (2%)	1 (4.5%)
bright whitish complexion	0	0	1 (4.5%)
light coloured tongue with white fur as well as sinking	0	0	0
deep and weak pulse	0	0	0

Differences of Scr, eGFR, 24-h UAlb and UACR

Figure 2 shows the differences of Scr, eGFR, 24-h UAlb and UACR among normo-albuminuria, micro-albuminuria and macro-albuminuria groups. We found that the levels of Scr and eGFR in macro-albuminuria group were significantly higher than micro-albuminuria group, but there were no significant differences between micro-albuminuria group and normo-albuminuria group. In addition, compared with the levels of Scr and eGFR, we concluded that the levels of 24-h UAlb and UACR showed a stepwise increase in normo-albuminuria, micro-albuminuria and macro-albuminuria groups (p = 0.000).

Changes of UCysC, UNAG and URBP

Table 3 and Fig. 3 show the changes of urinary tubular biomarkers’ levels in normo-albuminuria, micro-albuminuria and macro-albuminuria groups according to the levels of albuminuria. We found that the levels of UNAG, URBP and UCysC synchronously showed a gradual and significant increase consistent with albuminuria degrees in 3 groups.

Table 3

Differences of urinary tubular biomarkers based on albuminuria in all patients
	normo-albuminuria	micro-albuminuria	macro-albuminuria	p-value
UNAG (U/L)	16.21 ± 2.52	23.78 ± 3.88^a	38.90 ± 6.07^{a b}	0.000
URBP (mg/L)	0.72 ± 0.33	1.77 ± 0.84^a	3.36 ± 1.67^{a b}	0.000
UCysC (mg/L)	0.20 ± 0.09	0.45 ± 0.07^a	0.75 ± 0.13^{a b}	0.000
The data are expressed as mean ± SD for continuous variables. p-values were obtained by ANOVA.

Associations of 24-h UAlb, UACR with UCysC, UNAG and URBP

Table 4 and Fig. 4 illustrate the associations of 24-h UAlb, UACR with UNAG, URBP and UCysC in all 92 patients with type 2 DM. We concluded that 24-h UAlb, UACR positively correlated with UNAG (r = 0.706, p = 0.000; r = 0.808, p = 0.000, respectively), URBP (r = 0.687, p = 0.000; r = 0.701, p = 0.000, respectively) and UCysC (r = 0.727, p = 0.000; r = 0.790, p = 0.000, respectively). In addition, there was a weak positive correlation between UACR and SBP (r = 0.262, p = 0.012).

Table 4

Correlations of 24hUAlb, UACR and urinary tubular markers in all patients
	UNAG (U/L)	UCysC (mg/L)	URBP (mg/L)
24hUAlb (mg)	r = 0.706, p = 0.000	r = 0.727, p = 0.000	r = 0.687, p = 0.000
UACR (mg/g)	r = 0.808, p = 0.000	r = 0.790, p = 0.000	r = 0.701, p = 0.000
p < 0.05 is considered to be statistically significant.

Correlations of UCysC, UNAG and URBP in the 72 type 2 DN patients

The correlations of UNAG, URBP and UCysC are analyzed in the 72 type 2 DN patients with micro-albuminuria and macro-albuminuria in Table 5. There was a positive correlation between UNAG and URBP (r = 0.652, p = 0.000). UCysC was also positively correlated with UNAG and URBP (r = 0.785, p = 0.000; r = 0.673, p = 0.000, respectively).

Table 5

Correlations analysis of urinary tubular markers in the 72 type 2 DN patients
	UNAG (U/L)	UCysC (mg/L)	URBP (mg/L)
UNAG (U/L)	-	0.785^a	0.652^a
UCysC (mg/L)	0.785^a	-	0.673^a
URBP (mg/L)	0.652^a	0.673^a	-
p < 0.05 is considered to be statistically significant.

Associations of clinical baseline parameters with UCysC, UNAG and URBP in the 72 type 2 DN patients

Using the multivariate logistic regression analysis, we accidentally found in the 72 type 2 DN patients with micro-albuminuria and macro-albuminuria, the clinical baseline parameters including BMI and FBG were the predictive factors for the increased UCysC (OR 5.002, 95% CI: 1.45–17.24, p = 0.011; OR 3.529, 95% CI: 1.03–12.14, p = 0.046). Besides, the relevant clinical parameters could not predict the increased UNAG and URBP.

Under the fundamental principles of TCM theory, the differentiation and treatment of DM and its complications have focused on the asthenia syndromes including the deficiency of lung, spleen (stomach) and kidney for a long time, of them, kidney asthenia is considered to be the key pathogenesis of DN, which is a well-known complication of long-standing DM [28, 29, 30]. However, there is no further observation on the distribution of kidney deficiency syndrome in the early DN patients. In the present study, firstly, we unexpectedly found that TCM syndrome distributional characteristics of DM without or with abnormal albuminuria wholly belong to kidney qi deficiency syndrome, which is different from the previous investigation about the 108 stage III type 2 DN patients with massive proteinuria [23]. Hence, we preliminarily suggest kidney qi deficiency is the potential pathogenesis of these 92 patients with type 2 DM.

In clinic, the incipient diagnosis and noninvasive detections of renal harmful risk of DM are undoubtedly important. In general, glomerular dysfunction is thought to be a main factor for DN at the early stage. The routine and classical evaluation of glomerular filtration dysfunction in DN patients includes the increased levels of UAlb and Scr, which is the basis of the calculation for eGFR [28]. Despite this, lamentedly, the overt increase in Scr might be lately found after the serious glomerular impairments [5], moreover, a decline of eGFR in the patients with DM is not always accompanied by an increase of UAlb [28]. Therefore, neither Scr nor eGFR is the perfect marker for the early detection of glomerular dysfunction in DN patients. Our results in the present study showed that 24-h UAlb and UACR, in comparison to Scr and eGFR, appeared a stepwise rise and a significant difference in the individuals with normo-albuminuria, micro-albuminuria and macro-albuminuria. In a nutshell, based on these 92 type 2 DM with kidney qi deficiency syndrome, we secondly confirmed that there is a really renal lesion characterized by the different levels of UAlb and UACR, the markers of injurious glomeruli.

The recent studies have demonstrated that renal tubulointersititial lesion plays a critical role along with glomerular injury in the pathogenesis of DN patients [30]. The several biomarkers indicating proximal tubular impairment have the potential to be the clinical markers for predicting renal damage extent of DN patients at the early stage. Thereupon, to evaluate the clinical implication of urinary tubular biomarkers in diagnosing renal lesion, we then investigated the changes of UCysC, UNAG and URBP in all type 2 DM patients with kidney qi deficiency syndrome.

It is well known that, the clinical biomarkers of renal tubular injury contain urinary enzymes (enzymuria) and urinary proteins with the low molecular weight (LW-protienuria), while LW-protienuria originates from the deficient reabsorption of plasma proteins by tubular epithelial cells [29]. CysC, as its low molecular weight, is freely filtered by glomeruli and metabolized by renal proximal tubule without the influences of age or muscle mass in healthy conditions. It is reported that CysC in urine (UCysC) along with albuminuria could predict tubular impairment in the type 2 DN patients [31]. RBP, a low molecular weight protein, is synthesized mainly in hepatocytes, easily filtered by glomeruli and almost completely reabsorbed in renal proximal tubule. The level of urinary RBP (URBP) is thus very low in the final urine. Several researchers have demonstrated that the increased level of URBP was correlated with renal tubular dysfunction in DM patients [16, 28]. In addition to these, it has already been reported that urinary NAG (UNAG), a proximal tubular brush border lysosomal enzyme, plays a crucial role in diagnosing tubular impairment in DM patients [12]. The data in this observation indicated that the above-mentioned urinary tubular biomarkers, UCysC, UNAG and URBP, were simultaneously increased in normo-albuminuria, micro-albuminuria and macro-albuminuria groups accompanied by the rise of 24hUAlb and UACP, which are the earliest known clinical indexes for the diagnosis of DN. Furthermore, these biomarkers in urine were independently related to 24hUAlb and UACP. In brief, we also confirmed that UCysC, together with UNAG and URBP, as the acknowledged tubular dysfunctional biomarkers, have an independent association with renal injurious extent in the early type 2 DM patients with kidney qi deficiency syndrome.

Thirdly, we paid attention to the interrelation of UCysC, UNAG and URBP in the 72 type 2 DN patients with micro-albuminuria and macro-albuminuria. To our surprise, the results in this report unexpectedly displayed that UCysC was positively correlated with UNAG and URBP, moreover, there was also a positive relationship between UNAG and URBP in DN patients. Whereupon, we naturally speculated a possibility that which one is the more sensitive and specific tubular dysfunctional biomarker among UCysC, UNAG and URBP based on the different levels of UAlb. To our knowledge, CysC is synthesized and secreted at a nearly constant rate by virtually all nucleated cells. Given its molecular weight is 13 kDa, in healthy subjects in human, CysC is almost freely filtered by glomeruli and entirely reabsorbed in renal proximal tubular epithelial cell like other urinary proteins with the low molecular weight. Therefore, it is not excreted in urine and the increased level of UCysC, an independent of serum CysC, is particularly useful for estimating renal tubular impairment [31]. Kim et al. [10] reported that UCysC was mainly increased in the type 2 DN patients with macro-albuminuria and not significantly different between those with micro-albuminuria and normo-albuminuria. By contrast, being different from the above consequences, we amazedly found in the present study that UCysC was not only increased significantly in the type 2 DN patients with unnormal albuminuria but also closely related to a raise in UNAG and URBP. Additionally, we detected that UCysC was associated with BMI and FBG, the clinical baseline parameters of DM patients. Consequently, it was further confirmed the clinical significance of assessing the levels of UCysC, UNAG and URBP in the type 2 DM patients on the basis of the different levels of albuminuria, especially in unnormal albuminuric individuals. More importantly, it is emphasized that UCysC, UNAG and URBP are all considered as sensitive and specific tubular dysfunctional biomarkers.

Lastly, to be frank, there are several limitations in this report. First, except for the insufficient sample size in a signal-center, the study was difficult to illustrate the causal relationship between the risk factors and the natural course of normo-albuminuric renal insufficiency since it was conducted with a retrospective cross sectional design rather than based on a longitudinal observation. Second, due to the lack of healthy control group, we failed to clarify the relationship among the levels of UNAG, URBP and UCysC under healthy condition. Third, it is unknown whether the synchronized rise of UCysC, UNAG and URBP could assuredly indicate renal tubular impairment in the type 2 DN patients at the early stage without the histopathologic evidences in the kidney. Fourth, we only found kidney qi deficiency was the main TCM syndrome in these 92 DM patients, and could not demonstrate the relationships between urinary biomarkers and kidney yin or yang deficiency syndromes. Despite these, we have reasons to believe that the clinical implication of UCysC, UNAG and URBP in these 92 type 2 DM patients were clearly described, and the associated detection of urinary biomarkers could noninvasively forecast renal injurious extent in the incipient type 2 DN patients with kidney qi deficiency syndrome.

In this investigation, we ulteriorly demonstrated that the association within UCysC, UNAG, URBP and UAlb may be used as practical targets in noninvasively forecasting the extent of renal injury in the early type 2 DN patients with kidney qi deficiency syndrome. More importantly, we found that urinary tubular biomarkers may be one of the biological bases of DN patients with the specific TCM syndrome.

DN, diabetic nephropathy; DM, diabetes mellitus; ESRD, end-stage renal disease; UAlb, urinary albumin; UCysC, urinary cystatin C; UNAG, urinary N-acety1-β-D-glucosaminidase; UKim-1, urinary kidney injury molecule-1; UL-FABP, urinary 1iver-type fatty acid-binding protein; URBP, urinary retinal binding protein; UNGAL, urinary neutrophil getatinase-associated lipocalin; Uβ2-MG, urinary β2-microglobulin; UACR, urinary albumin-to-creatinine ratio; RAS, renin-angiotensin system; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; eGFR, estimated glomerular filtration rate; BMI, body mass index; SBP and DBP, systolic and diastolic blood pressure; FBG, fasting blood glucose; 2-h PBG, 2-h postprandial blood glucose; HbA1c, glycosylated hemoglobin A1c; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; BUN, blood urea nitrogen; Scr, serum creatinine; eGFR, estimated glomerular filtration; UA, uric acid.

Acknowledgements

The authors thank Dr. Le Zhang and Dr. Xun-Yang Luo (Department of Laboratory Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China) for their technical assistance and instructions. The authors also thank Prof. Jian Yao (Division of Molecular Signaling, Department of Advanced Biomedical Research, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Yamanashi, Japan) for his helpful discussion.

Authors’ contributions

WW and XJM contributed equally to this work. WW, XJM, WWW, QJF, HYY, CCY and MZW collected the blood and urine samples respectively. WW, XJM and ZYW performed the statistical analysis. WW, XJM, YGW and SMS drafted the manuscript. FLC helped edit the manuscript. YGW and SMS conceived of the study, and participated in its design and coordination and helped draft the manuscript. All authors read and approved the final manuscript.

Funding

This study was supported by two grants from the National Natural Science Foundation of China (81573903 and 81374030), a grant from Nanjing Medical Science and Technique Development Foundation (QRX17042) and a grant from Nanjing Famous TCM Doctor's Studio Programme.

Availability of data and materials

Data are all contained within the paper.
Ethical approval and consent to participate

The ethical approval was given, this study had been approved by the Research Ethical Committee of Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School on 29 July 2019 (ref: 2019-148‑01). The clinical trial was registered, the data was published on the registration website (Trial registration site: http//isrctn.org. Registration number: ChiCTR2000029784).

Consent for publication
Not applicable.

Competing interests
The authors declare that they have no competing interests.

Author details

¹ Department of Traditional Chinese Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, 321 Zhongshan Road, Nanjing 210008, China. ²Department of Nephrology, Affiliated Yancheng Hospital of Nanjing University of Chinese Medicine, 53 Renmin Middle Road, Yancheng 234001, China.

³ Department of Traditional Chinese Medicine, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, 321 Zhongshan Road, Nanjing 210008, China. ⁴ The School of Pharmacy, Management and Science University, Section 13, Shah Alam 40100, Malaysia.

⁵ Department of Social Work, Meiji Gakuin University, 1-2-37 Shirokanedai Minato-ku, Tokyo 108-8636, Japan. ⁶ Department of Endocrinology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, 321 Zhongshan Road, Nanjing 210008, China.

Wang F, Yang C, Long J, Zhao X, Tang W, Zhang D, et al. Executive summary for the 2015 Annual Data Report of the China Kidney Disease Network (CK-NET). Kidney Int. 2019;95(3):501–5.
Umanath K, Lewis JB. Update on diabetic nephropathy: core curriculum 2018. Am J Kidney Dis. 2018;71(6):884–95.
Groop PH, Thomas M, Feodoroff M, Forsblom C, Harjutsalo V. Excess mortality in patients with type 1 diabetes without albuminuria-separating the contribution of early and late risks. Diabetes Care. 2018;41(4):748–54.
Colhoun HM, Marcovecchio ML. Biomarkers of diabetic kidney disease. Diabetologia. 2018;61(5):996–1011.
Furuichi K, Yuzawa Y, Shimizu M, Hara A, Toyama T, Kitamura H, et al. Nationwide multicentre kidney biopsy study of Japanese patients with type 2 diabetes. Nephrol Dial Transplant. 2018;33(1):138–48.
Persson F, Rossing P: Diagnosis of diabetic kidney disease: state of the art and future perspective. Kidney Int Suppl (2011). 2018;8(1):2–7.
Abdel-Rahman EM, Saadulla L, Reeves WB, Awad AS. Therapeutic modalities in diabetic nephropathy: standard and emerging approaches. J Gen Intern Med. 2012;27(4):458–68.
Vallon V, Thomson SC. Renal function in diabetic disease models: the tubular system in the pathophysiology of the diabetic kidney. Annu Rev Physiol. 2012;74:351–75.
Fiseha T. Urinary biomarkers for early diabetic nephropathy in type 2 diabetic patients. Biomark Res. 2015;3:16.
Kim SS, Song SH, Kim IJ, Jeon YK, Kim BH, Kwak IS, et al. Urinary cystatin C and tubular proteinuria predict progression of diabetic nephropathy. Diabetes Care. 2013;36(3):656–61.
Khosravi N, Zadkarami M, Chobdar F, Hoseini R, Khalesi N, Panahi P, et al. The value of urinary cystatin C level to predict neonatal kidney injury. Curr Pharm Des. 2018;24(25):3002–4.
Vaidya VS, Niewczas MA, Ficociello LH, Johnson AC, Collings FB, Warram JH, et al. Regression of microalbuminuria in type 1 diabetes is associated with lower levels of urinary tubular injury biomarkers, kidney injury molecule-1, and N-acetyl-β-D-glucosaminidase. Kidney Int. 2011;79(4):464–70.
Moresco RN, Bochi GV, Stein CS, De Carvalho JAM, Cembranel BM, Bollick YS. Urinary kidney injury molecule-1 in renal disease. Clin Chim Acta. 2018;487:15–21.
Watanabe S, Ichikawa D, Sugaya T, Ohata K, Inoue K, Hoshino S, et al. Urinary level of liver-type fatty acid binding protein reflects the degree of tubulointerstitial damage in polycystic kidney disease. Kidney Blood Press Res. 2018;43(6):1716–29.
Rotbain Curovic V, Hansen TW, Eickhoff MK, von Scholten BJ, Reinhard H, Jacobsen PK, et al. Urinary tubular biomarkers as predictors of kidney function decline, cardiovascular events and mortality in microalbuminuric type 2 diabetic patients. Acta Diabetol. 2018;55(11):1143–50.
Caplin B, Nitsch D. Urinary biomarkers of tubular injury in chronic kidney disease. Kidney Int. 2017;91(1):21–3.
Maclsaac RJ, Ekinci EI, Jerums G. ‘Progressive diabetic nephropathy. How useful is microalbuminuria?: contra’. Kidney Int. 2014;86(1):50–7.
Hsu CY, Xie D, Waikar SS, Bonventre JV, Zhang X, Sabbisetti V, et al. Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression. Kidney Int. 2017;91(1):196–203.
Sun GD, Li CY, Cui WP, Guo QY, Dong CQ, Zou HB, et al. Review of herbal traditional Chinese medicine for the treatment of diabetic nephropathy. J Diabetes Res. 2016;2016:5749857.
Lu Z, Zhong Y, Liu W, Xiang L, Deng Y. The Efficacy and mechanism of Chinese herbal medicine on diabetic kidney disease. J Diabetes Res. 2019;2019:2697672.
Yang X, Zhang B, Lu X, Yan M, Wen Y, Zhao T, et al. Effects of Tangshen Formula on urinary and plasma liver-type fatty acid binding protein levels in patients with type 2 diabetic kidney disease: post-hoc findings from a multi-center, randomized, double-blind, placebo-controlled trial investigating the efficacy and safety of Tangshen Formula in patients with type 2 diabetic kidney disease. BMC Complement Altern Med. 2016;16:246.
Lin L, Wang Q, Yi Y, Wang S, Qiu Z. Liuwei Dihuang Pills enhance the effect of western medicine in treating diabetic nephropathy: a meta-analysis of randomized controlled trials. Evid Based Complement Alternat Med. 2016;2016:1509063.
Wan YG, Meng XJ, Shen SM, Luo XY, Gu LB, Shi XM, et al. Characteristic of urinary protein spectrum in patients with stage III diabetic nephropathy and its regression analysis with traditional Chinese medicine symptom. Zhongguo Zhong Yao Za Zhi. 2013;38(23):4157–63. [in Chinese].
Chen RQ, Wong CM, Lam TH. Construction of a traditional Chinese medicine syndrome-specific outcome measure: the Kidney Deficiency Syndrome Questionnaire (KDSQ). BMC Complement Altern Med. 2012;12:73.
Mou X, Zhou DY, Liu WH, Zhou DY, Liu YH, Hu YB, et al. Study on the relationship between Chinese medicine constitutive susceptibility and diversity of syndrome in diabetic nephropathy. Chin J Integr Med. 2013;19(9):656–62.
Wang XD, Zhang PT. Discussion on the hierarchical diagnostic model of TCM syndrome. China Journal of Traditional Chinese Medicine Pharmacy (CJTCMP). 2017;32(3):1209–13. [in Chinese].
Andrassy KM. Comments on 'KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease'. Kidney Int. 2013;84(3):622–23.
Takahashi N, Tsujimoto T, Chujo D, Kajio H. High risk of renal dysfunction in patients with fulminant type 1 diabetes. J Diabetes Investig. 2018;9(1):146–51.
Garg V, Kumar M, Mahapatra HS, Chitkara A, Gadpayle AK, Sekhar V. Novel urinary biomarkers in pre-diabetic nephropathy. Clin Exp Nephrol. 2015;19(5):895–900.
Eriguchi M, Lin M, Yamashita M, Zhao TV, Khan Z, Bernstein EA, et al. Renal tubular ACE-mediated tubular injury is the major contributor to microalbuminuria in early diabetic nephropathy. Am J Physiol Renal Physiol. 2018;314(4):F531-42.
Onopiuk A, Tokarzewicz A, Gorodkiewicz E. Cystatin C: a kidney function biomarker. Adv Clin Chem. 2015;68:57–69.

Download PDF

Version 1

posted

You are reading this latest preprint version

Association of Urinary Biomarkers Noninvasively Forecasts The Extent of Renal Injury In The Early Diabetic Nephropathy Patients With Kidney Qi Deficiency Syndrome: A Retrospective Investigation

Status:

Version 1

Abstract

Figures

Background

Methods

Statistical analysis

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Status:

Version 1