Nitric oxide metabolism is impaired by type 1 diabetes and diabetic nephropathy

  • Authors:
    • Jelizaveta Sokolovska
    • Alise Dekante
    • Larisa Baumane
    • Leonora Pahirko
    • Janis Valeinis
    • Kristine Dislere
    • Vita Rovite
    • Valdis Pirags
    • Nikolajs Sjakste
  • View Affiliations

  • Published online on: March 4, 2020     https://doi.org/10.3892/br.2020.1288
  • Pages: 251-258
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Diabetes leads to reduced nitric oxide bioavailability, resulting in endothelial dysfunction. However, overproduction of nitric oxide due to hyperglycaemia is associated with oxidative stress and tissue damage. The objective of this study was to characterise nitric oxide production (NO) and added nitrite and nitrate (NO2‑+NO3‑) concentration in the blood and urine of patients with and without diabetic nephropathy. A total of 268 patients with type 1 diabetes and 69 healthy subjects were included. Diabetic nephropathy was defined as macroalbuminuria and/or estimated glomerular filtration rate below 60 ml/min/1.73 cm2. NO2‑+NO3‑ concentration was measured by Griess reaction. Production of NO was detected by electron paramagnetic resonance spectroscopy. Blood NO was demonstrated to be higher (P<0.001) and serum NO2‑+NO3‑ was lower (P=0.003) in patients with type 1 diabetes and no nephropathy vs. healthy subjects. However, serum NO2‑+NO3‑ concentration in patients with diabetes and nephropathy did not differ from the levels observed in healthy controls. Urine excretion of NO2‑+NO3‑ was significantly decreased in patients with nephropathy, compared with patients without diabetic kidney disease (P=0.006) and healthy subjects (P=0.010). A significant positive correlation was observed between urine NO2‑+NO3‑ and estimated glomerular filtration rate in patients with type 1 diabetes (P=0.002) and healthy subjects (P=0.008). Estimated glomerular filtration rate, albuminuria and diabetic nephropathy status were significant predictors of the whole blood NO and NO2‑+NO3‑ in serum and urine in patients with type 1 diabetes, as identified by linear regression models. The present study concludes that NO metabolism is impaired by type 1 diabetes and diabetic nephropathy.

Introduction

The number of patients with diabetes mellitus constantly increases. Vascular complications, including diabetic nephropathy are major reasons for increased morbidity and mortality among patients with diabetes (1). Chronic hyperglycaemia leads to the formation of advanced glycosylation end products, activation of protein kinase C, polyol pathway and glucose autoxidation. These processes are sources of increased oxidative stress, which leads to damage in vasculature and tissues (2). Active research is on-going in the area of other potential mechanisms of diabetic nephropathy, including nitric oxide (NO) metabolism (3).

NO is a pleiotropic molecule important to a number of physiological and pathological processes in humans. In physiological conditions, effects of NO are tissue-dependent and include vasorelaxant, antithrombotic and antibacterial. However, high amounts of NO are associated with pro-inflammatory processes (4). The adverse effects of NO result mainly from peroxynitrite (ONOO-), a product of the interaction of NO with the superoxide anion and a potent toxin. Overproduction of NO and ONOO- is associated with DNA damage, enzyme dysfunction, inflammation, oxidative stress, decreased NO bioavailability and endothelial dysfunction (2,5-11).

Experimental data confirm increased NO and ONOO- production in tissues of animals with diabetes mellitus (5,7,8,12). Existing studies on changes in NO metabolism coupled to diabetes and diabetic nephropathy in humans often demonstrate the opposite findings. Reduced serum nitrite (NO2-) and nitrate (NO3-) synthesis was described in patients with diabetic nephropathy and type 2 diabetes (13), and in patients with type 1 diabetes (T1D) and glomerular hyperfiltration (14). In contrast, increased serum NO2-+NO3- has been reported in patients with T1D and albuminuria (15) and in children with T1D (16). Only a few studies have described changes of concentration of NO metabolites in both the serum and urine of T1D patients, despite the importance of both measurements (14,16). Whereas serum NO2-+NO3- reflects mainly endothelial NO production although it might be influenced by dietary NO2- and NO3- (17), data on urine NO2-+NO3- may reflect the intensity of NO synthesis in the kidney circulation (14) and thus provide information for research on diabetic nephropathy (3).

NO is an unstable molecule, which is metabolized to NO2-+NO3- within seconds. Therefore, the majority of human studies report data on concentrations of NO2-+NO3- in serum and/or urine (13,18). Data on NO production [which can only be measured by electron paramagnetic resonance (EPR) spectroscopy or amperometric electrodes (19-21)] ex vivo in humans with diabetes is lacking, due to technical difficulties of the above methods.

To summarize, the understanding of derangements of NO metabolism in the pathogenesis of diabetic nephropathy in T1D is limited (5,15,16,18).

To reduce the gap in this knowledge, the present study describes data on simultaneous measurement of concentrations of NO in whole blood by EPR spectroscopy and its metabolites NO2-+NO3- in serum and urine of T1D patients with and without diabetic nephropathy.

Materials and methods

Patients and ethics

The present study was a part of LatDiane: Latvian prospective diabetic nephropathy study. LatDiane recruits' patients with T1D (defined as the age of diagnosis <40 years, with insulin treatment initiated within 1 year of diagnosis and C-peptide level <0.3 nmol/l). The study is in line with the 1975 Declaration of Helsinki and received the Latvian Central Ethics Committee's approval no. 01-29.1/3. All participants gave their written informed consent to participate. Patients recruited between September and May each year between 2013 and 2016 with a diabetes duration >1 year were included (N=268) in this study. Patient characteristics are shown in Table I. The control group was formed of volunteers (n=69) without previously diagnosed diabetes or impaired glucose tolerance, who were invited to participate in this study in 2013-2014. Exclusion criteria for both groups of patients were pregnancy, acute or chronic urinary infection, signs of acute inflammation (C-reactive protein >5 mg/l, fever, increased erythrocyte sedimentation rate), history of chronic kidney disease apart from diabetic nephropathy, oncologic or rheumatologic diseases, end-stage renal disease (ESRD), current usage of antibiotics or history of immunosuppressive treatment.

Table I

Characteristics of subjects.

Table I

Characteristics of subjects.

CharacteristicsHealthy subjects (N=69)Type 1 diabetes without nephropathy (N=246)Type 1 diabetes and nephropathy (N=22)
Men/women, % (N)38/62 (26/43)46/54 (112/134)46/54 (10/12)
Age, years23 (21-26)36 (24-47)a33 (27.5-47)a,b
Diabetes duration, years-14 (6.2-22)22 (15.2-28.8)b
Body mass index, kg/m222.6 (20.6-26)24.4 (21.8-27.8)23.5 (21.4-24.6)
Systolic blood pressure, mmHg120 (110-125)124 (117-135)a136 (126-149)a,b
Diastolic blood pressure, mmHg75 (70-80)80 (71-85)a89 (80-91)a,b
Hypertension, % (N)1(1) 41(101)c76(19)c,d
On ACEI/ARB, % (N)0 (0)24(61)32(8)
HbA1c%5.3 (5.1-5.5)8.3 (7.4-9.6)a10.1 (8.3-11.1)a,b
HbA1c, mmol/mol34.4 (32.2-36.6)67.2 (57.4-81.4)a86.9 (67.2-97.8)a,b
Triglycerides, mmol/l0.7 (0.6-1.1)1.0 (0.7-1.4)a1.2 (1.0-1.9)a,b
Total cholesterol, mmol/l4.2 (3.7-4.8)4.9 (4.1-5.5)a4.8 (4.0-6.0)
Low-density lipoprotein cholesterol, mmol/l2.3 (1.8-2.7)2.7 (2.1-3.3)2.5 (2-3.5)
On statins, % (N)0 (0)10(26)12(3)
Smoking, % (N)17(12)26(64)28(7)
eGFR, ml/min/1.73 m2108.6 (96.5-121.8)110.8 (97.4-123.1)85.7 (56-98.6)a,b
Albuminuria, %(N)e:
Normoalbuminuria100(69)80(197)9(2)d
Microalbuminuria0 (0)17(42)9(2)
Macroalbuminuria0 (0)0 (0)81(18)d
Urine albumin/creatinine ratio, mg/mmol0.3 (0.2-0.7)0.6 (0.3-1.6)a72.8 (46.8-152.2)a,b
Chronic kidney disease, % (N)0 (0)0 (0)28(7)d
Fundus oculi exam, % (N):-17(43)32(7)
No retinopathy 59(144)18(4)d
Non-proliferative retinopathy 24(59)50(11)d
Proliferative retinopathy and status post LPC
Diabetic polyneuropathy, % (N)-38(94)72(18)c
Vascular hard event, % (N)0 (0)6(15)12(3)

[i] Mean values are shown as median (q0.25-q0.75).

[ii] aP<0.05 vs. ‘healthy subjects’;

[iii] bP<0.05 vs. ‘Type 1 diabetes without nephropathy’, pairwise Wilcoxon test;

[iv] cP<0.05 vs. ‘Healthy subjects’;

[v] dP<0.05 vs. ‘Type 1 diabetes without nephropathy’, Chi-square prop test;

[vi] emissing 7 from ‘Type 1 diabetes without nephropathy’ group. Chronic kidney disease-eGFR <60 ml/min/1.73 m2. Vascular hard event-history of acute myocardial infarction, coronary bypass/percutaneous transluminal coronary angioplasty, stroke, amputation, or peripheral vascular disease. LPC, pan-retinal laser photocoagulation; eGFR, estimated glomerular filtration rate (CKD-EPI); ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker.

Definitions

Albuminuria was assessed using two out of three urine albumin-to-creatinine ratio measurements in morning spot urine according to the guidelines of the National Kidney foundation (22).

Estimated glomerular filtration rate (eGFR) was calculated with the Chronic Kidney Disease Epidemiology Collaboration equation (23). Chronic kidney disease was defined as eGFR<60 ml/min/1.73 m2. ESRD was defined as eGFR <15 ml/min/1.73 m2, dialysis or kidney transplantation. Diabetic nephropathy was defined as macroalbuminuria and eGFR <60 ml/min/1.73 m2. Arterial hypertension was defined as regular usage of antihypertensive drugs, or systolic blood pressure ≥140 mmHg (18.7 kPa) and diastolic blood pressure ≥90 mmHg (12.0 kPa). Diabetic retinopathy was defined as proliferative diabetic retinopathy or status after panretinal-laser photocoagulation, based on conclusion of the fundus oculi examination performed by an ophthalmologist. Cardiovascular disease was defined as history of acute myocardial infarction, coronary bypass/percutaneous transluminal coronary angioplasty, stroke, amputation, or peripheral vascular disease. Diabetic polyneuropathy was defined based on electromyography data (reporting peripheral sensory, senso-motor or motor neuropathy). Smoking was self-reported, patients currently smoking at least one cigarette per day were referred to the ‘smokers’ group. Body mass index (BMI) was calculated as weight (kg)/[height (m2)].

Biochemical parameters

Total cholesterol, low-density lipoproteins and triglyceride (enzymatic colour reaction), HbA1c (high-pressure liquid chromatography), C-reactive protein (immuno-turbidimethric method) and albumin to creatinine ratio in urine (immunoturbidimetric test and enzymatic kinetic reaction) were measured in certified clinical laboratories.

Measurement of NOin whole blood

NO production was measured essentially as described (24). A total of 20 mg diethylthiocarbamate (Sigma-Aldrich; Merck KGaA) was added to 1 ml fresh blood, stirred and incubated for 30 min at room temperature. Then the mixture was aspirated into an insulin syringe and frozen in liquid nitrogen, the frozen cylinder was extruded from the syringe and placed in a quartz finger Dewar flask ER 167 FDS-Q (Bruker Corporation) filled with liquid nitrogen. NO concentration was detected measuring the NO component in the spectrum of Fe-DETC-NO (g=2.031) and compared with the calibration curve. To build up the calibration curve different quantities of NaNO2 (final concentrations 0, 10, 20, 30, 40, 60 and 100 µM) were mixed with DETC (33 mg/ml) and FeSO4. 7H2O (3.3 mM), an excess of Na2S2O4 (2 M) was added to the mixture. The EPR spectra were taken as described above. Thus, the calibration curve contained both negative and positive controls.

EPR spectra were recorded in liquid nitrogen using the EPR spectrometer Radiopan SE/X2544. Conditions of EPR measurements were: 2.5 mW microwave power, 9.24 GHz microwave frequency, 100 kHz modulation frequency, 0.5 mT modulation amplitude, and 5x105 receiver gain. Limits of detection for NO were 5-50 ng/g tissue. The observed deviation between measurements was 5-10%.

Measurement of NO2-+NO3- in patients' serum samples

Serum samples were deproteinised, using Amicon Ultra filters for centrifugation (cat. no. UFC800324; EMD Millipore). NO2-+NO3- was measured with the Cayman's Nitrate/Nitrite Colorimetric assay kit (cat. Nr 780001; Cayman Chemical Company) and Perkin Elmer Lambda 25 UV/VIS spectrophotometer (PerkinElmer, Inc.) (21). NO2-+NO3- concentration was quantitated using the nitrate standard curve (final concentrations 0, 5, 10, 15, 20, 25, 30 and 35 µM), which was performed according to the protocol in the kit. The detection limit of sample was 2.5 µM. Inter-assay and intra-assay coefficients of variation are 3.4 and 2.7%, respectively.

Statistical analysis

All measurements for NO and NO2-+NO3- were performed in triplicate, and the mean values were used for analysis. NO levels in whole blood was measured in 269 samples, NO2-+NO3- levels in serum was measured in 310 samples, and NO2-+NO3- levels in urine was measured in 308 samples. At the initial analysis stage, chi-square test for proportions for categorical variables and the Wilcoxon signed-rank test for quantitative variables (Table I) were used. As none of the variables analysed followed normality (tested using the Shapiro test), nonparametric statistical procedures were used. Data are presented as medians with the respective interquartile range. The equality of medians was tested using the and the Kruskal-Wallis test followed by Wilcoxon sum rank test for pairwise comparisons. For multiple comparisons P-value correction method by Holm was used. Healthy subjects differed from both groups of patients with T1D in age and HbA1c. Therefore, ANCOVA procedure on ranks was used to adjust for age and other potential confounders (gender, BMI, HbA1c% and smoking), although it did not lead to any significant P-value changes.

Other differences between the groups (duration of diabetes, blood pressure, lipids, eGFR, albuminuria and prevalence of complications of diabetes) were attributable to diagnosis of T1D or diabetic nephropathy, therefore adjustment for these parameters was not performed.

A Spearman correlation coefficient was used to study association between markers of NO metabolism. Regression analysis was performed only for data of patients with T1D. A total of three linear regression models with either whole blood NO, or serum and urine NO2-+NO3- as dependent variables were used. Initially, full models adjusted for age, sex, diabetes duration, systolic and diastolic blood pressure, body mass index, smoking, HbA1c, lipids, urine albumin/creatinine ratio, eGFR, diabetic nephropathy status were used. To identify predictors with major impact on nitric oxide metabolism markers, a stepwise regression model based on AIC selection was applied. All statistical tests were using R version 3.6.1(25).

Results

Characteristics of study groups

Study subjects included 268 patients with T1D and 69 healthy subjects. Patients with T1D were stratified according to the presence of diabetic nephropathy. Anthropometric and clinical characteristics of three groups (healthy subjects, patients with T1D without diabetic nephropathy, patients with T1D with diabetic nephropathy) are summarised in Table I. Subjects in the control group did not have any chronic diseases, except hypertension in one case.

Concentration of NO in the whole blood of patients with T1D and healthy subjects

The concentration of whole blood NO was significantly increased in patients with T1D, compared with controls (P<0.05). Within T1D patients, the presence of diabetic nephropathy did not lead to a further increase in NO (Fig. 1A and Table II).

Table II

Markers of nitric oxide metabolism in healthy subjects and patients with type 1 diabetes with and without nephropathy.

Table II

Markers of nitric oxide metabolism in healthy subjects and patients with type 1 diabetes with and without nephropathy.

GroupsNO, ng/g whole blood NO2-+NO3-, µM, serum NO2-+NO3-, µM, urine
Healthy subjects, n22.8 (20.6-25.1), 6932.1 (26.5-53.3), 39842.7 (370.9-1304.8), 39
Type 1 diabetes without nephropathy; n26.0 (21.3-29.3), 185a26.3 (17.6-37.5), 246c729.0 (417.9-1215.8), 245
Type 1 diabetes and nephropathy; n28.2 (23.7-33.5), 15b34.0 (22.9-64.5), 22f365.4 (188.8-626.7), 21d,e

[i] Data are presented as median and interquartile range.

[ii] aP<0.001 vs. ‘Healthy subjects’;

[iii] bP=0.006 vs. ‘Healthy subjects’;

[iv] cP=0.003 vs. ‘Healthy subjects’;

[v] dP=0.006 vs. ‘Type 1 diabetes without nephropathy’;

[vi] eP=0.010 vs. ‘Healthy subjects’;

[vii] fP=0.098 vs. ‘Type 1 diabetes without nephropathy’. Kruskal Wallis test followed by pairwise Wilcoxon test. Wilcoxon test was followed by Ancova on ranks for adjustment for age, gender, BMI, HbA1c%, smoking. NO, nitric oxide; NO2, nitrite; NO3, nitrate.

Concentration of NO2-+NO3- in the serum of patients with T1D and healthy subjects

The concentration of NO2-+NO3- in the serum was significantly decreased (P=0.003) in patients with T1D and no nephropathy compared with healthy subjects. However, in patients with T1D and nephropathy, serum concentration of NO2-+NO3- did not differ from the control group (Fig. 1B and Table II).

Concentration of NO2-+NO3- in the urine of patients with T1D and healthy subjects

NO2-+NO3- in urine did not differ between patients with uncomplicated T1D and controls. Within the T1D group, the concentration of NO2-+NO3- in urine was significantly decreased in patients with diabetic nephropathy, when compared with patients without diabetic nephropathy (P=0.006) and healthy subjects (P=0.010; Fig. 1C and Table II).

Correlation between parameters of nitric oxide metabolism in patients with T1D and healthy subjects

A strong positive significant correlation was observed between eGFR and urine NO2-+NO3- in healthy subjects (R=0.688; P=0.008). This correlation was also significant, although weak in patients with type 1 diabetes (R=0.190; P=0.002).

A medium positive significant correlation was observed between NO2-+NO3- in serum and NO2-+NO3- in urine in healthy subjects (R=0.492; P=0.002) and T1D patients without diabetic nephropathy (R=0.559; P<0.001), but not in T1D patients with diabetic nephropathy (R=0.351; P=0.120).

In patients with diabetes, a weak negative correlation was observed between diabetes duration and urine NO2-+NO3- (R=-0.131; P=0.032) and a weak positive correlation between albuminuria and serum NO2-+NO3- (R=0.150; P=0.015).

No correlation was observed between blood NO and NO2-+NO3- in urine and serum (Table III).

Table III

Correlation of nephropathy-related parameters with markers of nitric oxide metabolism.

Table III

Correlation of nephropathy-related parameters with markers of nitric oxide metabolism.

GroupsVariable 1Variable 2Correlation coefficient (R)P-value
Healthy subjectseGFR NO2-+NO3- urine0.6880.008
Type 1 diabeteseGFR NO2-+NO3- urine0.1900.002
Healthy subjectseGFR NO2-+NO3- serum0.0900.762
Type 1 diabeteseGFR NO2-+NO3- serum-0.0510.406
Healthy subjectseGFRNO-0.2150.222
Type 1 diabeteseGFRNO-0.0990.165
Type 1 diabetesDiabetes duration NO2-+NO3- urine-0.1310.032
Type 1 diabetesDiabetes duration NO2-+NO3- serum0.0490.425
Type 1 diabetesDiabetes durationNO-0.0290.684
Type 1 diabetesAlbuminuria NO2-+NO3- urine-0.0640.304
Type 1 diabetesAlbuminuria NO2-+NO3- serum0.1500.015
Type 1 diabetesAlbuminuriaNO0.0940.184
Healthy subjects NO2-+NO3- urine NO2-+NO3- serum0.4920.002
Type 1 diabetes + no DN NO2-+NO3- urine NO2-+NO3- serum0.559<0.001
Type 1 diabetes + DN NO2-+NO3- urine NO2-+NO3- serum0.3510.120
Healthy subjectsNO NO2-+NO3- serum-0.2530.120
Type 1 diabetes + no DNNO NO2-+NO3- serum-0.0950.200
Type 1 diabetes + DNNO NO2-+NO3- serum-0.3390.216
Healthy subjectsNO NO2-+NO3- urine-0.2160.188
Type 1 diabetes + no DNNO NO2-+NO3- urine-0.0420.570
Type 1 diabetes + DNNO NO2-+NO3- urine-0.3320.246

[i] R-Spearman correlation coefficient. eGFR, estimated glomerular filtration rate; DN, diabetic nephropathy; albuminuria, albumin/creatinine ratio in morning spot urine; NO, nitric oxide; NO2, nitrite; NO3, nitrate.

Predictors of markers of NO metabolism identified by linear regression models in patients with T1D

To identify predictors of NO in whole blood, NO2-+NO3- in serum and urine in patients with T1D, three regression models adjusted for age, sex, diabetes duration, blood pressure, BMI, smoking, HbA1c, serum lipids, urine albumin/creatinine ratio, eGFR and nephropathy status were used. After application of a stepwise selection model based on AIC for a model with NO as a dependent variable, significant predictors remaining in the model were diabetes duration, sex, albuminuria and diabetic nephropathy. For NO2-+NO3- in serum, significant predictors were only HbA1c and eGFR. For NO2-+NO3- in urine, significant predictors were sex, BMI, albuminuria and eGFR (Table IV).

Table IV

Associations between concentrations of NO in whole blood, NO2-+NO3- in serum and urine and clinical characteristics.

Table IV

Associations between concentrations of NO in whole blood, NO2-+NO3- in serum and urine and clinical characteristics.

Dependent variablesPredictorsB (95% CI)P-valueR-squared
NO in whole blood, ng/gIntercept25.951 (23.938, 27.964)<0.0010.134
 Diabetes duration, years-0.101 (-0.192, -0.01)0.032 
 Sex, male/female2.962 (0.91, 5.014)0.005 
 Albumin/creatinine in urine, mg/mmol-0.029 (-0.048, -0.01)0.003 
 Diabetic nephropathy, yes/no10.241 (5.271, 15.212)<0.001 
NO2-+NO3- in serum, µMIntercept34.561 (11.73, 57.392)0.0030.028
 HbA1c, %1.844 (-0.045, 3.733)0.057 
 eGFR, ml/min/1.73 cm2-0.158 (-0.327, 0.011)0.069 
NO2-+NO3- in urine, µMIntercept1285.682 (158.895, 2412.469)0.0260.106
 Sex, male/female-329.72 (-552.273, -107.166)0.004 
 Body mass index, kg/m2-27.377 (-55.448, 0.694)0.057 
 Albumin/creatinine in urine, mg/mmol-1.707 (-3.345, -0.069)0.042 
 eGFR, ml/min/1.73 cm24.886 (-1.019, 10.792)0.106 

[i] Linear regression models for NO in whole blood, NO2/NO3 in serum and urine as dependent variables. Data are presented as B (95% CI). Analysis was performed only for data of patients with type 1 diabetes (N=268). Only predictors selected after application of AIC stepwise model are indicated. Initial models were adjusted for age, sex, diabetes duration, systolic and diastolic blood pressure, body mass index, smoking, HbA1c, lipids, urine albumin/creatinine ratio, eGFR, diabetic nephropathy status. eGFR, ml/min, 1.72 cm2 and diabetic nephropathy, macroalbuminuria and eGFR <60 ml/min/1.73 m2. eGFR, estimated glomerular filtration rate; NO, nitric oxide; NO2, nitrite; NO3, nitrate.

Discussion

The present study aimed to assess the impact of T1D and diabetic nephropathy on the concentrations of NO in whole blood, and its metabolites NO2-+NO3- in serum and urine in patients with T1D.

In the present study, it was demonstrated that T1D resulted in increased NO production in whole blood and decreased NO2-+NO3- concentration in the serum. However, when T1D is complicated by diabetic kidney disease, urine excretion of NO2-+NO3- is decreased, which results in serum NO2-+NO3- not differing from the levels of healthy controls.

To the best of our knowledge, the present study is the first to measure NO concentration in whole blood measured by EPR in T1D patients. As in human tissues one can measure NO in ex vivo specimens only; in the present study, blood specimens were collected and incubated with a spin trap for 30 min. Therefore, the measured NO should have been produced by blood cells during the incubation or released from transporting molecules. Indeed, the ability to produce NO was reported for several types of blood cells. Previously, increased NO production in aged erythrocytes of patients with type 2 diabetes was reported (26). Increased NO production in whole blood of T1D patients in the present study could result from several processes. Besides being a NO depot due to the formation of NO and haemoglobin complexes, erythrocytes can produce NO, as they contain endothelial NO synthase (27). White blood cells and platelets produce NO via NO synthases (28-31) or independently of NO synthases (32). Finally, a nitric oxide synthase (NOS)-independent NO production from NO2-+NO3- is possible, especially in conditions characterised by endothelial dysfunction, low systemic pH and hypoxia, such as diabetes (10). Despite the fact that the present study could not demonstrate higher whole blood NO in patients with diabetic nephropathy, regression analysis indicated positive association between whole blood NO and diabetic nephropathy status. Therefore, the present results could be the first indication of increased NO production in blood cells of T1D patients.

In contrast to data on NO in the whole blood, lower serum NO2-+NO3- concentration were observed in patients with T1D and no diabetic nephropathy, compared with control subjects. Considering the above-mentioned increase of NO production by blood cells, this result underlines the differences of NO metabolism in different tissues. Indeed, in blood serum total NO2-+NO3- was measured, which consists of metabolites of NO produced by endothelium, blood cells and other tissues. To evaluate the contribution of the measured whole blood NO concentration in the present study (~25 ng/g) to blood serum NO2-+NO3-, this was recalculated in micromoles: It gives <1 µM in 30 min, which should be insignificant, as the measured serum NO2-+NO3- concentrations in the present study were on average >25 µM. To support the lack of direct association between blood NO and serum NO2-+NO3-, no correlation was found between these markers. Therefore, it can be can concluded that T1D leads to a decrease in serum NO2-+NO3- concentration and these changes are not dependent on NO production by blood cells. This decrease might be explained by decreased NO bioavailability due to diabetes-induced oxidative stress, when NO is scavenged by reactive oxygen species and ONOO- is formed (4,33). Data similar to the current findings have been reported in T1D (14) and type 2 diabetes (34). However, there are studies which report no differences in serum NO2-+NO3- concentrations in T2D patients compared with control subjects (35) and increased serum NO2-+NO3- in early T1D (16,36).

Although one would expect that in patients with T1D and diabetic nephropathy the concentration of serum NO2-+NO3- should decrease even further, in the present study, it did not differ from the levels observed in the control group. The reason for this observation might be the decreased eGFR in diabetic nephropathy group and thus some accumulation of serum NO2-+NO3-. Indeed, although serum and urine NO2-+NO3- demonstrated medium positive correlation in healthy subjects and patients with diabetes and no nephropathy, this correlation was not observed in patients with nephropathy. Moreover, regression analysis indicated that in patients with T1D, an increase in serum NO2-+NO3- is expected when eGFR decreases. Therefore, it is hypothesized that this accumulation of NO2-+NO3- in circulation might become a source of the NOS-independent NO synthesis (9,10) and consequent nitrosative stress that has been observed in diabetes (37). Thus, the authors hypothesized that the idea of inorganic nitrate/nitrite supplementation as a tool for prevention and treatment of complications of diabetes and atherosclerosis is controversial (4,10,17,18,38,39). Indeed, other researchers have also reported increased serum NO2-+NO3- in diabetic complications (15,34,35,40).

To supplement the present data on NO2-+NO3- in serum, decreased urine NO2-+NO3- concentrations were reported in patients with diabetic nephropathy. Moreover, albuminuria was a significant negative predictor of urine NO2-+NO3- in regression analysis. Decreased urine NO2-+NO3- excretion in diabetic nephropathy might be the consequence of deregulated NO synthesis in the microvasculature of kidney in diabetes due to altered expression of NOS isoforms (6,8). It can also result from a decrease in kidney function characteristic for diabetic nephropathy and leading to accumulation of NO metabolites in the blood, as discussed above. Indeed, a positive correlation was observed between urine NO2-+NO3- and eGFR in patients with T1D and healthy subjects, in agreement with the data of other studies (14,15,41).

The present study has some limitations. Major concerns are: The cross-sectional design of the study and the low number of patients with diabetic nephropathy. Subjects in the control group differ from T1D patients in age; all other differences between the groups are associated with diabetes and diabetic nephropathy.

The advantages of this study include previously unpublished data on NO in whole blood measured by EPR spectroscopy, a relatively large population of patients with T1D included and analysis of different markers of NO metabolism in patients with T1D and diabetic nephropathy.

To conclude, whole blood NO, serum and urine NO2-+NO3- are affected differently by T1D and diabetic nephropathy. Uncomplicated T1D is characterised by increased whole blood NO and decreased serum NO2-+NO3-. In diabetic kidney disease, urine excretion of NO2-+NO3- is decreased, which results in serum NO2-+NO3- not differing from the levels of healthy controls. Thus, kidney function is associated with NO metabolism in T1D. Studies with larger number of T1D patients with diabetic nephropathy are needed for an improved understanding of derangements of NO metabolism in diabetic kidney disease.

Acknowledgements

The authors of the present study would like to thank Mrs. Sanita Kalva-Vaivode and Mrs. Mārīte Cirse for patient recruitment, Dr Rihards Mallons, Dr Zane Dzērve and Dr Sabīne Skrebinska for their assistance with data management and Dr Carol Forsblom from the FinnDiane group for her valuable comments concerning presentation of data. LatDiane acknowledges all physicians involved in the recruitment of patients.

Funding

The present study was supported by the State Genome database project, Latvian Association of Endocrinology, a project of the University of Latvia: ‘Research of biomarkers and natural substances for acute and chronic diseases’ diagnostics and personalised treatment’.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

JS designed the clinical set up of the study and wrote the manuscript. LB performed all measurements of nitric oxide by EPR method. KD performed all measurements of nitrite and nitrite. AD organized the logistics of the study. LP and JV did the statistical analysis. VR was responsible for biobanking. VP contributed to interpretation of the results and edited the manuscript. NS designed the study as well as wrote and edited the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

This study is in line with the 1975 Declaration of Helsinki and received the Latvian Central Ethics Committee approval Nr.01-29.1/3. All subjects gave their written informed consent to participate.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References

1 

Davies MJ, D'Alessio DA, Fradkin J, Kernan WN, Mathieu C, Mingrone G, Rossing P, Tsapas A, Wexler DJ and Buse JB: Management of hyperglycaemia in type 2 diabetes, 2018. A consensus report by the American diabetes association (ADA) and the European association for the study of diabetes (EASD). Diabetologia. 61:2461–2498. 2018.PubMed/NCBI View Article : Google Scholar

2 

Brownlee M: The pathobiology of diabetic complications: A unifying mechanism. Diabetes. 54:1615–1625. 2005.PubMed/NCBI View Article : Google Scholar

3 

Dellamea BS, Leitão CB, Friedman R and Canani LH: Nitric oxide system and diabetic nephropathy. Diabetol Metab Syndr. 6(17)2014.PubMed/NCBI View Article : Google Scholar

4 

Yamagishi S and Matsui T: Nitric oxide, a janus-faced therapeutic target for diabetic microangiopathy-Friend or foe? Pharmacol Res. 64:187–194. 2011.PubMed/NCBI View Article : Google Scholar

5 

Pacher P, Beckman J and Liaudet L: Nitric oxide and peroxynitrite in health and disease. Physiol Rev. 87:315–424. 2007.PubMed/NCBI View Article : Google Scholar

6 

Tessari P: Nitric oxide in the normal kidney and in patients with diabetic nephropathy. J Nephrol. 28:257–268. 2015.PubMed/NCBI View Article : Google Scholar

7 

Ošiņa K, Rostoka E, Sokolovska J, Paramonova N, Bisenieks E, Duburs G, Sjakste N and Sjakste T: 1,4-Dihydropyridine derivatives without Ca2+-antagonist activity up-regulate Psma6 mRNA expression in kidneys of intact and diabetic rats. Cell Biochem Funct. 34:3–6. 2016.PubMed/NCBI View Article : Google Scholar

8 

Leonova E, Sokolovska J, Boucher JL, Isajevs S, Rostoka E, Baumane L, Sjakste T and Sjakste N: New 1,4-Dihydropyridines down-regulate nitric oxide in animals with streptozotocin-induced diabetes mellitus and protect deoxyribonucleic acid against peroxynitrite action. Basic Clin Pharmacol Toxicol. 119:19–31. 2016.PubMed/NCBI View Article : Google Scholar

9 

Zweier JL and Talukder MA: The role of oxidants and free radicals in reperfusion injury. Cardiovasc Res. 70:181–190. 2006.PubMed/NCBI View Article : Google Scholar

10 

Alef MJ, Tzeng E and Zuckerbraun BS: Nitric oxide and nitrite-based therapeutic opportunities in intimal hyperplasia. Nitric Oxide. 26:285–294. 2012.PubMed/NCBI View Article : Google Scholar

11 

Chen JY, Ye ZX, Wang XF, Chang J, Yang MW, Zhong HH, Hong FF and Yang SL: Nitric oxide bioavailability dysfunction involves in atherosclerosis. Biomed Pharmacother. 97:423–428. 2018.PubMed/NCBI View Article : Google Scholar

12 

Ceriello A and Testa R: Antioxidant anti-inflammatory treatment in type 2 diabetes. Diabetes Care. 32 (Suppl 2):S232–S236. 2009.PubMed/NCBI View Article : Google Scholar

13 

Tessari P, Cecchet D, Cosma A, Vettore M, Coracina A, Millioni R, Iori E, Puricelli L, Avogaro A and Vedovato M: Nitric oxide synthesis is reduced in subjects with type 2 diabetes and nephropathy. Diabetes. 59:2152–2159. 2010.PubMed/NCBI View Article : Google Scholar

14 

Cherney DZ, Reich HN, Jiang S, Har R, Nasrallah R, Hébert RL, Lai V, Scholey JW and Sochett EB: Hyperfiltration and effect of nitric oxide inhibition on renal and endothelial function in humans with uncomplicated type 1 diabetes mellitus. Am J Physiol Regul Integr Comp Physiol. 303:R710–R718. 2012.PubMed/NCBI View Article : Google Scholar

15 

Chiarelli F, Cipollone F, Romano F, Tumini S, Costantini F, di Ricco L, Pomilio M, Pierdomenico SD, Marini M, Cuccurullo F and Mezzetti A: Increased circulating nitric oxide in young patinets with type 1 diabetes and persistent microalbuminuria: Relation to glomerular hyperfiltration. Diabetes. 49:1258–1263. 2000.PubMed/NCBI View Article : Google Scholar

16 

Savino A, Pelliccia P, Schiavone C, Primavera A, Tumini S, Mohn A and Chiarelli F: Serum and urinary nitrites and nitrates and doppler sonography in children with diabetes. Diabetes Care. 29:2676–2681. 2006.PubMed/NCBI View Article : Google Scholar

17 

Ma L, Hu L, Feng X and Wang S: Nitrate and nitrite in health and disease. Aging Dis. 9:938–945. 2018.PubMed/NCBI View Article : Google Scholar

18 

Bahadoran Z, Ghasemi A, Mirmiran P, Azizi F and Hadaegh F: Beneficial effects of inorganic nitrate/nitrite in type 2 diabetes and its complications. Nutr Metab (Lond). 12(16)2015.PubMed/NCBI View Article : Google Scholar

19 

Vanin AF: Dinitrosyl iron complexes and S-nitrosothiols are two possible forms for stabilization and transport of nitric oxide in biological systems. Biochemistry (Mosc). 63:782–793. 1998.PubMed/NCBI

20 

Zhang X: Real time and in vivo monitoring of nitric oxide by electrocehmical sensors-from dream to reality. Front Biosci. 9:3434–3446. 2004.PubMed/NCBI View Article : Google Scholar

21 

Sun J, Zhang X, Broderick M and Fein H: Measurement of nitric oxide production in biological systems by using griess reaction assay. Sensors. 3:276–284. 2003.

22 

National Kidney Foundation: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39 (Suppl 1): S1-S266, 2002.

23 

Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF III, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T and Coresh J: CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med. 150:604–612. 2009.PubMed/NCBI View Article : Google Scholar

24 

Borisovs V, Ļeonova E, Baumane L, Kalniņa J, Mjagkova N and Sjakste N: Blood levels of nitric oxide and DNA breaks assayed in whole blood and isolated peripheral blood mononucleated cells in patients with multiple sclerosis. Mutat Res. 843:90–94. 2018.PubMed/NCBI View Article : Google Scholar

25 

R Core Team (2012) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL. http://www.R.project.org/.

26 

Bizjak DA, Brinkmann C, Bloch W and Grau M: Increase in red blood cell-nitric oxide synthase dependent nitric oxide production during red blood cell aging in health and disease: A study on age dependent changes of rheologic and enzymatic properties in red blood cells. PLoS One. 10(e0125206)2015.PubMed/NCBI View Article : Google Scholar

27 

Cortese-Krott MM and Kelm M: Endothelial nitric oxide synthase in red blood cells: Key to a new erythrocrine function? Redox Biol. 2:251–258. 2014.PubMed/NCBI View Article : Google Scholar

28 

Garcia-Bonilla L, Moore JM, Racchumi G, Zhou P, Butler JM, Iadecola C and Anrather J: Inducible nitric oxide synthase in neutrophils and endothelium contributes to ischemic brain injury in mice. J Immunol. 193:2531–2537. 2014.PubMed/NCBI View Article : Google Scholar

29 

Gambaryan S and Tsikas D: A review and discussion of platelet nitric oxide and nitric oxide synthase: Do blood platelets produce nitric oxide from l-arginine or nitrite? Amino Acids. 7:1779–1793. 2015.PubMed/NCBI View Article : Google Scholar

30 

Saluja R, Saini R, Mitra K, Bajpai VK and Dikshit M: Ultrastructural immunogold localization of nitric oxide synthase isoforms in rat and human eosinophils. Cell Tissue Res. 340:381–388. 2010.PubMed/NCBI View Article : Google Scholar

31 

Bogdan C: Nitric oxide synthase in innate and adaptive immunity: An update. Trends Immunol. 36:161–178. 2015.PubMed/NCBI View Article : Google Scholar

32 

Tse WY, Williams J, Pall A, Wilkes M, Savage CO and Adu D: Antineutrophil cytoplasm antibody-induced neutrophil nitric oxide production is nitric oxide synthase independent. Kidney Int. 59:593–600. 2001.PubMed/NCBI View Article : Google Scholar

33 

Tousoulis D, Kampoli AM, Tentolouris C, Papageorgiou N and Stefanadis C: The role of nitric oxide on endothelial function. Curr Vasc Pharmacol. 10:4–18. 2012.PubMed/NCBI View Article : Google Scholar

34 

Miyata S, Noda A, Hara Y, Ueyama J, Kitaichi K, Kondo T and Koike Y: Nitric oxide plasma level as a barometer of endothelial dysfunction in factory workers. Exp Clin Endocrinol Diabetes. 125:684–689. 2017.PubMed/NCBI View Article : Google Scholar

35 

Doganay S, Evereklioglu C, Er H, Türköz Y, Sevinç A, Mehmet N and Savli H: Comparison of serum NO, TNF-alpha, IL-1beta, sIL-2R, IL-6 and IL-8 levels with grades of retinopathy in patients with diabetes mellitus. Eye (Lond). 16:163–170. 2002.PubMed/NCBI View Article : Google Scholar

36 

Hoeldtke RD, Bryner KD and Vandyke K: Oxidative stress and autonomic nerve function in early type 1 diabetes. Clin Auton Res. 21:19–28. 2011.PubMed/NCBI View Article : Google Scholar

37 

Ceriello A: Nitrotyrosine: New findings as a marker of postprandial oxidative stress. Int J Clin Pract Suppl. 51–58. 2002.PubMed/NCBI

38 

Stepanova YI, Kolpakov IY, Zyhalo VM and Boyarsky VG: Correction of endothelial dysfunction in children-residents of radioactively contaminated areas by nitric oxide donator. Probl Radiac Med Radiobiol. 21:336–344. 2016.PubMed/NCBI

39 

Norouzirad R, González-Muniesa P and Ghasemi A: Hypoxia in obesity and diabetes: Potential therapeutic effects of hyperoxia and nitrate. Oxid Med Cell Longev. 2017(5350267)2017.PubMed/NCBI View Article : Google Scholar

40 

Gumanova NG, Teplova NV, Ryabchenko AU and Denisov EN: Serum nitrate and nitrite levels in patients with hypertension and ischemic stroke depend on diet: A multicenter study. Clin Biochem. 48:29–32. 2015.PubMed/NCBI View Article : Google Scholar

41 

Schneider MP, Ott C, Schmidt S, Kistner I, Friedrich S and Schmieder RE: Poor glycemic control is related to increased nitric oxide activity within the renal circulation of patients with type 2 diabetes. Diabetes Care. 36:4071–4075. 2013.PubMed/NCBI View Article : Google Scholar

Related Articles

Journal Cover

May-2020
Volume 12 Issue 5

Print ISSN: 2049-9434
Online ISSN:2049-9442

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Sokolovska J, Dekante A, Baumane L, Pahirko L, Valeinis J, Dislere K, Rovite V, Pirags V and Sjakste N: Nitric oxide metabolism is impaired by type 1 diabetes and diabetic nephropathy. Biomed Rep 12: 251-258, 2020.
APA
Sokolovska, J., Dekante, A., Baumane, L., Pahirko, L., Valeinis, J., Dislere, K. ... Sjakste, N. (2020). Nitric oxide metabolism is impaired by type 1 diabetes and diabetic nephropathy. Biomedical Reports, 12, 251-258. https://doi.org/10.3892/br.2020.1288
MLA
Sokolovska, J., Dekante, A., Baumane, L., Pahirko, L., Valeinis, J., Dislere, K., Rovite, V., Pirags, V., Sjakste, N."Nitric oxide metabolism is impaired by type 1 diabetes and diabetic nephropathy". Biomedical Reports 12.5 (2020): 251-258.
Chicago
Sokolovska, J., Dekante, A., Baumane, L., Pahirko, L., Valeinis, J., Dislere, K., Rovite, V., Pirags, V., Sjakste, N."Nitric oxide metabolism is impaired by type 1 diabetes and diabetic nephropathy". Biomedical Reports 12, no. 5 (2020): 251-258. https://doi.org/10.3892/br.2020.1288