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 Table of Contents  
ORIGINAL ARTICLE
Year : 2016  |  Volume : 2  |  Issue : 1  |  Page : 7-17

Serum allograft inflammatory factor-1 concentration in type 2 diabetes mellitus and its relation to the pathogenesis and progression of diabetic nephropathy


1 Department of Internal Medicine, Minia University Hospital, Minia, Egypt
2 Department of Clinical Pathology, Minia University Hospital, Minia, Egypt

Date of Submission12-Dec-2015
Date of Acceptance23-Sep-2016
Date of Web Publication22-Jun-2016

Correspondence Address:
Fatma El-Zahraa S Bukhary
Department of Internal Medicine, Minia University Hospital, PO Box 61111, Minia
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2356-8062.184401

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  Abstract 


Objective
Inflammatory mechanisms may play a pivotal role in diabetic nephropathy (DN). Allograft inflammatory factor-1 (AIF-1), a marker of activated macrophage, may have a role in the progression of DN.
Aim
The aim of the present study was to examine the relationship between serum AIF-1 concentration and parameters of DN.
Patients and methods
A total of 80 type 2 diabetes patients and 20 healthy volunteers (control group) were included in the present study. Patients with renal dysfunction or inflammatory conditions were excluded. Clinical and laboratory tests for patients and controls were carried out. The patients' group was classified according to the Urinary Albumin Excretion (UAE) level into the following: group IA (normoalbuminuria group), which included 30 patients with UAE less than 30 mg/g of creatinine (mg/g Cr); group IIA (microalbuminuria group), which comprised 25 patients with UAE from 30 to 300 mg/g Cr; and group IIIA (macroalbuminuria group), which included 25 patients with UAE greater than 300 mg/g Cr. All patients were subjected to further classification according to estimated glomerular filtration rate (eGFR) into the following: group IB, which included 31 patients with eGFR less than or equal to 60 ml/min/1.73 m2; and group IIB, which included 49 patients with eGFR greater than 60 ml/min/1.73 m2.
Results
AIF-1 was significantly raised in all patients compared with controls (P = 0.001), and in both group IIA and group IIIA than in group IA (P = 0.001). AIF-1 had significant positive correlation with age, diabetes duration, UAE, log urinary albumin creatinine (A/C) ratio, urea, creatinine, and Fasting Blood Sugar (FBS) (P < 0.001). AIF-1 concentration was inversely correlated with eGFR. Serum AIF-1 was significantly raised in group IB (112.35 ± 26.8) compared with group IIB (83.41 ± 26.23) (P < 0.001). Serum AIF-1 was significantly raised in both groups of simple and proliferative diabetic retinopathy than in the group of nondiabetic retinopathy (P = 0.001).
Conclusion
AIF-1 was significantly raised in type 2 diabetic patients and in those with DN and retinopathy, which may raise a possibility of their pathogenesis as an inflammatory process.

Keywords: allograft inflammatory factor.-1, albuminuria, diabetic nephropathy, retinopathy


How to cite this article:
Zakareya Y, Bukhary FZS, Mohamad EA, Othman KM, Shakoor OA. Serum allograft inflammatory factor-1 concentration in type 2 diabetes mellitus and its relation to the pathogenesis and progression of diabetic nephropathy. Egypt J Obes Diabetes Endocrinol 2016;2:7-17

How to cite this URL:
Zakareya Y, Bukhary FZS, Mohamad EA, Othman KM, Shakoor OA. Serum allograft inflammatory factor-1 concentration in type 2 diabetes mellitus and its relation to the pathogenesis and progression of diabetic nephropathy. Egypt J Obes Diabetes Endocrinol [serial online] 2016 [cited 2017 Jun 22];2:7-17. Available from: http://www.ejode.eg.net/text.asp?2016/2/1/7/184401




  Introduction Top


Recent studies have shown that chronic inflammation is associated with the development and progression of type 2 diabetes mellitus (DM), implying that immunologic and inflammatory mechanisms may play a pivotal role in the disease process. Furthermore, increased infiltration of monocytes/macrophages and activated T lymphocytes, as well as augmented expression of inflammatory cytokines in the kidneys, have also been found in patients with diabetic nephropathy (DN) [[1],[2],[3].

Serum allograft inflammatory factor-1 (AIF-1) was originally cloned from activated macrophages in human and rat atherosclerotic allogenic heart grafts undergoing chronic transplant rejection [4]. Subsequently, there were reports of macrophages expressing AIF-1 in various diseases, such as macrophages in the pancreatic islets in prediabetic rats [5], in the human allograft kidney undergoing clinical rejection [6], in the brain of experimental autoimmune encephalomyelitis [7], and in the skeletal muscle after devascularization [8].

As regards the possible role of macrophages in DN and AIF-1 being a marker of activated macrophage, the current study aimed to study the relationship between serum AIF-1 concentration and parameters of DN, and whether AIF-1 might be considered as a novel biomarker to assess the progression of DN [i.e., to explore its association with the degree of urinary albumin excretion and estimated glomerular filtration rate (eGFR)].


  Patients and Methods Top


This prospective, cross-sectional study included 80 type 2 diabetic patients (patients' group) after obtaining an informed written consent. Patients were selected from those coming for follow-up at Minia University Hospital, Internal Medicine Outpatient Clinic (from December 2013 till December 2014). They were known to have type 2 DM according to the criteria proposed by the American Diabetic Association [9].

Control group

This study also included 30 healthy individuals of matched age and sex and free of any chronic medical diseases that may affect kidney functions.

Exclusion criteria

Patients with advanced renal dysfunction (serum creatinine ≥2.0 mg/dl) [10], patients with inflammatory conditions, or those on medications such as NSAIDs or steroids were excluded from the present study.

All patients were interviewed according to a standard questionnaire that covered clinical characteristics; smoking status (nonsmokers, ex-smokers, or current smokers); presence of cardiovascular disease (CVD) (defined as previous myocardial or cerebral infarction); and current medication of insulin, oral antidiabetic drugs, statins or angiotensin-converting enzyme inhibitors (ACEIs), and/or angiotensin II receptor blockers (ARBs).

  1. Systolic and diastolic blood pressures were measured after 5 min of rest
  2. BMI was calculated as proposed by the National Institute of Health (BMI = weight in kg/height in m 2). Obesity was defined as a BMI of greater than or equal to 30 kg/m 2 [11]
  3. As regards fundus examination, retinopathy was assessed by an ophthalmologist who was unaware of the data, and graded as follows:



    1. Nondiabetic retinopathy (NDR)
    2. Simple diabetic retinopathy (SDR)
    3. Proliferative diabetic retinopathy (PDR) [12].




If the finding in the left and right fundi were discordant, the worse side was taken as a representative for the participant.

Laboratory investigations

A sample of 10 ml of venous blood after overnight fasting was obtained from all participants to estimate the following:

  1. Fasting blood sugar, serum urea, creatinine, total cholesterol, and triglyceride (TG) were assayed using the fully automated clinical chemistry autoanalyzer system Konelab 60i (Thermo Electron Incorporation, Helsinki, Finland)
  2. eGFR was calculated using CKD-EPI:



    For women, the following values are used: sex = 1.018; α = −0.329; κ = 0.7. For males, the following values are used: sex = 1; α = −0.411; κ = 0.9 [13]

  3. Hemoglobin A1c% (HbA1c) was assayed quantitatively by using boronate affinity by NycoCard Reader II (Alere/Axis-Shield, Oslo, Norway) [14]
  4. Serum AIF-1 was measured quantitatively by using the enzyme-linked immunosorbent assay [15]
  5. A/C ratio was determined in an early morning spot urine with an immune-turbidimetric assay [16].


Clinical study

Patients were classified according to UAE level into the following:

  1. Group IA (normoalbuminuria group), which included 30 patients with UAE less than 30 mg/g of creatinine (mg/g Cr)
  2. Group IIA (microalbuminuria group), which included 25 patients with UAE from 30–300 mg/g Cr
  3. Group IIIA (macroalbuminuria group), which included 25 patients with UAE greater than 300 mg/g Cr


Patients were subjected to another classification on the basis of the eGFR into the following [17]

  1. Group IB, which included 31 patients with eGFR less than or equal to 60 ml/min/1.73 m 2
  2. Group IIB, which included 49 patients with eGFR greater than 60 ml/min/1.73 m 2.


Statistical study

The collected data were tabulated and statistically analyzed using SPSS program software (version 20; SPSS Inc., Chicago, Illinois, USA). Numerical data were described by using mean ± SD and minimum and maximum of the range, whereas categorical data were described by using number and percentage. Analyses were carried out for quantitative variables using the independent sample t-test for parametric data between the two groups. The χ2-test was used for qualitative data between groups. Correlation between two quantitative variables was established by using Pearson's correlation coefficient, and for nonparametric variables by using Spearman's ρ correlation test. Correlation coefficient ranged from 0 to 1: weak (r = 0–0.24), fair (r = 0.25–0.49), moderate (r = 0.5–0.74), and strong (r = 0.75–1). Cut-off value of AIF-1 was estimated to define the level at which albuminuria could be indirectly detected. Multiple linear regression analysis was carried out for estimating whether AIF-1 is an independent variable for predicting A/C ratio and eGFR. Level of significance was set at a P value of less than 0.05.


  Results Top


The mean age increased significantly for patients with macroalbuminuria, with significant difference compared with other groups (P < 0.001 and <0.019, respectively) ([Table 1],[Table 2],[Table 3]). There was a gradual increase in the duration of diabetes with increased severity of albuminuria, with significant difference between all groups (P < 0.001). Group IIIA comprised 14 (56%) patients with hypertension, with a significant difference with other groups (P < 0.01). This group (group IIIA) showed significant long duration of hypertension and increased prevalence of ACE intake compared with other groups (P < 0.05). As regards fundus examination, group IA included 96.7% patients with NDR and one (3.3%) patient with SDR. Group IIA included 84% patients with NDR, 3.3% patients with SDR, and one (4%) patient with PDR, whereas group IIIA included 52% patients with NDR, 32% patients with SDR, and 16% patients with PDR. There was a significant difference between all groups (P < 0.002).
Table 1: Comparative study between patients and controls as regards demographic and clinical data

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Table 2: Comparative study between patients and controls as regards laboratory results

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Table 3: Comparative study of the demographic and the clinical data of group IA, group IIA, and group IIIA

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[Table 4] reveals that fasting blood glucose was raised in group IIIA, with a significant difference between this group and group IA (P < 0.01). Regarding serum creatinine, there was a significant difference between all groups (P < 0.001). eGFR and HbA1c showed significant difference between all groups (P < 0.001). [Figure 1] shows that, in group I, AIF-1 showed significant difference between group I and III (P < 0.001), between group II and III (P < 0.001), and between all groups (P < 0.001).
Table 4: Comparative study of the laboratory data of group IA, group IIA, and group IIIA

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Figure 1: Allograft inflammatory factor-1 (AIF-1) in patient's groups classified according to albuminuria

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[Table 5] shows that AIF-1 had significant positive correlation with age, diabetes duration, UAE, log A/C ratio, urea and creatinine, FBS, with P less than 0.001 for all of them except for age (P < 0.006) and FBS (P < 0.03), whereas AIF-1 concentration inversely correlated with eGFR. [Table 6] shows the patients' group classified according to their eGFR level into two groups: group IB, which included 31 patients with eGFR less than or equal to 60 ml/min/1.73 m 2; and group IIB, which included 49 patients with eGFR greater than 60 ml/min/1.73 m 2.
Table 5: Correlation between allograft inflammatory factor-1 and other variables in patients as a whole group

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Table 6: Comparative study between group IB and group IIB as regards demographic data

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The mean age and duration of diabetes increased significantly in patients with eGFR less than 60 compared with other groups (P < 0.001 and <0.03, respectively). There was a significant increase in the prevalence of hypertensive patients with lower eGFR (P < 0.001). As regards the history of ACEI/ARBs drugs intake, there was a significant difference between the two groups (P < 0.001).

As regards fundus examination, group IB included 58.1% patients with NDR, 29% patients with SDR, and 12.9% patients with PDR. Whereas group IIB included 91.84% patients with NDR, 6.12% patients with SDR, and one (2.04%) patient with PDR. There was a significant difference between all groups (P < 0.002). [Table 7] shows that UAE ratio and HbA1c both showed significant difference between both groups (P < 0.001). Serum AIF-1 in group IB ranged between 70 and 168 pg/ml (112.35 ± 26.8), whereas in group IIB it ranged from 45 to 170 pg/ml (83.41 ± 26.23), with a significant difference between the two groups (P < 0.001) ([Figure 2]).
Table 7: Comparative study of the laboratory data of group IB and group IIB

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Figure 2: Comparative study of serum allograft inflammatory factor-1 in group. IB with estimated glomerular filtration rate. (eGFR) less than 60 ml/min/1.73 m2 and group. IIB with eGFR more than 60 ml/min/1.73 m2

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[Table 8] and [Figure 3] show that serum AIF-1 was significantly raised in group III with PDR, with a significant difference between this group and group I (NDR) (P < 0.001) [Figure 4] and [Table 9],[Table 10][Table 11][Table 12]).
Table 8: Sensitivity and specificity of allograft inflammatory factor.1 in the diagnosis of diabetic nephropathy

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Table 9: Evaluation of serum allograft inflammatory factor-1 concentration as an independent determinant of estimated glomerular filtration rate by multivariate linear regression analysis after adjustment for the following variables: duration of diabetes, body mass index, hemoglobin A1c%, systolic blood pressure, total cholesterol, triglyceride

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Table 10: Evaluation of serum allograft inflammatory factor-1 concentration as an independent determinant of log urinary albumin creatinine ratio by multivariate linear regression analysis after adjustment for the following variables: duration of diabetes, body mass index, hemoglobin A1c%, systolic blood pressure, total cholesterol, triglyceride

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Table 11: Evaluation of serum allograft inflammatory factor-1 concentration as an independent determinant of urinary albumin creatinine ratio by multivariate linear regression analysis after adjustment for the following variables: duration of diabetes, body mass index, hemoglobin A1c, systolic blood pressure, total cholesterol, triglyceride

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Table 12: Comparative study of serum allograft inflammatory factor-1 as regards fundal examination

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Figure 3: Receiver operating characteristic curve analysis for sensitivity and specificity of allograft inflammatory factor-1 in the prediction of albuminuria

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Figure 4: Serum allograft inflammatory factor-1 (AIF-1) and fundus examination. NDR, nondiabetic retinopathy; PDR, proliferative diabetic retinopathy; SDR, simple diabetic retinopathy

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  Discussion Top


In contrast to type 1 DM, type 2 DM is a nonautoimmune form of DM characterized by insulin resistance and relative (rather than absolute) insulin deficiency [18]. Macrophage accumulation is a feature of type 2 DM and is associated with the development of diabetic complications (nephropathy, atherosclerosis, neuropathy, and retinopathy) [19],[20]. Albuminuria serves as a tool for monitoring nephron injury and as a response to therapy in DN. Microalbuminuria may be less predictive of DN and progression to macroalbuminuria in type 2 DM, as it may be secondary to factors unrelated to DM, such as hypertension, congestive heart failure, prostate disease, or infection [21].

In the current study, no significant difference was found between the groups as regards sex. This is in agreement with a study conducted by Fukui et al. [22], who reported that the UAE was not affected by gender. In contrast, a study by Furtner et al. [18] reported significant difference between UAE in female versus male patients, and a study by Valmadrid et al. [23]reported that the patients with increasing levels of proteinuria were older, more likely to be male, and were to be maintained on insulin because of side effects of oral hypoglycemic drugs.

In the present study, the mean age increased significantly in patients with macroalbuminuria compared with other groups. In their study, Furtner et al. [18] reported that UAE was significantly related to age and reflected systemic endothelial leakiness. It may arise from an interaction between noxious influences of vascular risk attributes and a predisposing genetic background.

As regards smoking habits and BMI, there was an insignificant difference between the studied groups. This is in agreement with the results of a study by Furtner et al. [18], who found that UAE was not affected by BMI or smoking.

On the other hand, Fukui et al. [22] suggested that obesity is associated with low-grade chronic inflammation that is characterized by an inflamed adipose tissue with increased infiltration of macrophages and accumulation of other immune cells, such as T cells, which may have a role in the pathogenesis of UAE in diabetes and possibly in of CVD [24],[25].

Activated macrophages in the adipose tissue, besides contributing to insulin resistance [26], may also be directly involved in the regulation of fat mass [25]. Adipose tissue macrophages produce a number of proinflammatory cytokines that promote adipose dysfunction and insulin resistance [27].

In their respective studies, Thorleifsson et al. [28], Casimiro [29], and Lorente-Cebrián et al. [30] found that AIF-1 was secreted in a time-dependent fashion from the white adipose tissue from resident macrophages. They also observed that expression of AIF-1 was similar in visceral and subcutaneous white adipose tissue and there was a two-fold increase in obese women, and its levels were normalized after weight reduction. They also found that expression of AIF-1 was inversely correlated with insulin sensitivity as assessed by using the insulin tolerance test, and circulating levels of adiponectin, and positively correlated with insulin resistance as estimated by homeostasis model assessment for insulin resistance (HOMA-IR).

As regards the duration of diabetes, there was a significant difference between all groups (P < 0.001). Large cohort studies by Valmadrid et al. [23] and Fukui et al. [22] reported that UAE was positively correlated with the duration of diabetes, and the duration of diabetes was independently correlated with log UAE.

As DN progresses, there is a progressive increase in UAE and diminished renal function, which results from the thickening of the pathological basement membrane, atrophy, and interstitial fibrosis [1]. During the first 5 years of DM, thickening of the glomerular basement membrane, glomerular hypertrophy, and mesangial volume expansion occur as the GFR returns to normal [1]. After 5–10 years of DM, many individuals begin to excrete small amounts of albumin with urine [31].

A study by Park et al. [17] suggested that proteinuria was a more important indicator for DR than was decreased eGFR due to endothelial leakiness.

HbA1c showed significant difference between group IA and group IIIA (P < 0.01). Furtner et al. [18], in their study, stated that impaired glycemic control is associated with increased microvascular complication. Hyperglycemia induces macrophage production of IL-12, which stimulates CD-4 cell production of IFN-γ, and activates nuclear factor-κB through Protein Kinase C (PKC) and reactive oxygen species to rapidly stimulate the expression of cytokines [32]. Furthermore, longer disease duration results in increased advanced glycosylation end (AGE) products and AGE-modified proteins, which could bind to the receptor for AGE on macrophages and T cells, stimulating synthesis and release of proinflammatory cytokines in DM [2],[29].

Intensive glycemic control was associated with significantly decreased rates of DN in patients with type 2 DM. Glucotoxicity and lipotoxicity cause synergistic effects on the development and progression of DN. Macrophages have emerged as potential contributors in mediating glucolipotoxicity through the activation of MRP8/toll-like receptor 4 (TLR4) signaling in diabetic glomeruli [33].

As regards the presence of hypertension, there was a significant difference between all groups (P < 0.010). This is in agreement with studies conducted by Furtner et al. [18] and Fukui et al. [22], in which there was a positive correlation between hypertension and UAE, which can be attributed to endothelial dysfunction and high intraglomerular pressure, which cause increased albumin excretion. However, a subset of patients with type 2 DM developed chronic kidney disease without nephrotic-range proteinuria. Whether this difference represents a fundamental difference in the pathophysiology of the two conditions or represents the synergistic effects of other kidney injuries, such as hypertensive renal disease, is unclear [21]. Hypertension is usually absent in the early stages in patients with type 1 DM but is present in 10–25% of the patients with type 2 DM at their initial evaluations. Microalbuminuria is a more specific sign of DN in type 1 DM than in type 2 DM because of the high incidence of hypertension, which itself may lead to microalbuminuria in the latter [21].

Increased plasma prorenin activity was noted as a risk factor for the development of DN. Prorenin binds to a specific tissue receptor that promotes activation of mitogen-activating protein kinases (MAPK) [34].

Furthermore, activated renin–angiotensin–aldosterone system and endothelial dysfunction have been proven to be crucial determinants of leukocyte activation and cytokine expression in generating proinflammatory and proliferative effects [13],[35].

Early identification of patients with DN allows for the intensification of the therapy, which slows the progression of kidney disease and helps in the management of the increased risk for CVD [36].

Hyperlipidemia represents an independent metabolic risk factor for the progression of DN. Its molecular mechanism involves TLR4 interacting with its potent ligand S100 calcium-binding protein A8 (calgranulin-A; S100A8) in macrophages, infiltrating the glomeruli of DN patients [37].

Statins were found to either prevent, delay, or even reverse the decline of GFR, as well as to reduce albuminuria in patients with type 2 DM [38], with CVD risk reduction in patients with CKD [in the Study of Heart and Renal Protection (SHARP)] [33],[39].

As regards TGs and total cholesterol, no significant difference was found in the studied groups. In contrast, a study by Fukui et al. [22] reported an independent correlation between serum total lipids and log UAE. This may be due to the fact that most of our patients took statins for a short period of time and/or postponed taking statins until late.

Serum AIF-1 revealed significant difference between all groups (P < 0.001) with significant positive correlation with diabetes duration, UAE, log A/C ratio, urea and creatinine (P < 0.001), age (P < 0.006), and FBS (P < 0.03), whereas it showed inverse correlation with eGFR (P < 0.001).

This is in agreement with a study by Fukui et al. [22], who revealed that serum AIF-1 levels were higher in patients with macroalbuminuria than in those with normoalbuminuria (P = 0.0001) or with microalbuminuria (P = 0.009). Serum AIF-1 concentrations positively correlated with age and log UAE, whereas inversely correlated with eGFR. In addition, they found that serum AIF-1 levels positively correlated with the levels of FBS (P = 0.006), HbA1c% (P = 0.003), TG (P = 0.02), and BMI (P = 0.001), and inversely correlated with high-density lipoprotein (P = 0.002). Stepwise multiple regression analysis indicated that HbA1c% (β = 0.133, F = 5.490, P < 0.05) and waist circumference (β = 0.197, F = 11.954, P < 0.05) were independent predictors of serum AIF-1 levels. They suggested that AIF-1 plays an additional role in the dysfunction of β cells and may be considered as an early marker for DN and a significant predictor of activated macrophages, as well as CVD in humans [22].

In the current study, mean serum AIF-1 concentration was higher in patients with PDR (P < 0.001) than in patients with NDR, and in patients with SDR than in patients with NDR (P < 0.001). These results are in agreement with a theory proposed by Wu et al. [40], who demonstrated that macrophages were prominent in sections from diabetic patients with advanced diabetic retinopathy.

The current study showed that the mean age and duration of diabetes increased significantly in patients with eGFR less than or equal to 60 (P < 0.001). No significant difference was found between the two groups as regards gender. This is in agreement with a study by Park et al. [17]. Sex hormones may influence hyperfiltration, as Cherney et al. [41] in their study observed a decrease in the renal blood flow and vascular resistance in response to hyperglycemia in women, but not in men. The same study [41] showed that the addition of ACEI resulted in a decrease in the blood pressure in both men and women, but GFR decreased only in women.

As regards the BMI, there was no significant difference between the two groups. This was in agreement with the results obtained in a study by Park et al. [17], who found a insignificant association between BMI and eGFR.

As regards fundus examination, there was a significant difference between all groups (P = 0.002). These results are in agreement with Park et al. [17], who suggested that eGFR is an indicator for DR but not as significant as proteinuria due to endothelial leakiness.

The mean serum AIF-1 concentration was significantly higher in patients whose eGFR was less than or equal to 60 ml/min/1.73 m 2 compared with the other groups (P < 0.001). It correlated with log UAE and eGFR even after adjusting for the duration of diabetes, BMI, HbA1c, systolic blood pressure, serum total cholesterol, and TGs. This is in agreement with a study by Fukui et al. [22], who found that the serum AIF-1 concentration was higher in patients whose eGFR was less than 60 ml/min/1.73 m 2 compared with patients whose eGFR was greater than 90 ml/min/1.73 m 2 (P = 0.002) or with patients whose eGFR was between 60 and 90 ml/min/1.73 m 2 (P = 0.007).

They found that the systolic blood pressure, duration of diabetes, serum total cholesterol, TG, and AIF-1 concentrations were independently correlated with log UAE and the duration of diabetes. Furthermore, HbA1c% and serum TG and AIF-1 concentrations were independently correlated with eGFR. AIF-1 levels in healthy humans have been found to be positively correlated with metabolic indicators, such as BMI, TGs, and FBS [22].

Activated renin–angiotensin–aldosterone system proved to be a crucial determinant of leukocyte activation and cytokine expression in generating proinflammatory and proliferative effects [35]. AIF-1 protein is not expressed in quiescent cultured human Vascular smooth muscle cells (VSMCs) but is induced in cells challenged with various inflammatory cytokines, primarily by INF-γ, IL-1β, and T-cell-conditioned media [42].

Overexpression of AIF-1 in human VSMCs results in enhanced growth of these cells. This cytokine-induced activation and proliferation of medial VSMCs lead to intimal hyperplasia, the most critical cellular event in the formation of arteriosclerosis [43].

In their study, Chen et al. [4] proved that AIF-1 enhances VSMC growth by autocrine production of Granulocyte colony stimulating factor (G-CSF), and AIF-1-transduced VSMCs are chemotactic for human monocytes. Thus, its expression may influence VSMC–inflammatory cell communication.

Tian et al. [44] and Mishima et al. [45] found that the stimulation of human macrophages with oxidized low-density lipoprotein significantly increased AIF-1 expression above basal levels. They suggested a tight association between AIF-1 expression and macrophage activation. These data indicate that AIF-1 mediates atherogenesis-initiated signaling and activation of macrophages.

In their study, Tian et al. [44] found the following. First, AIF-1 is detected in Endothelial cells (EC) within the intima if inflamed human arteries and its expression can be induced in cultured EC by inflammatory and angiogenic factors. Second, knock-down of AIF-1 protein by stable transfection of siRNA reduces the several indices of EC pathophysiology, including proliferation and migration. These functions could be rescued by the exogenous expression of AIF-1. Third, signal transduction cascades could be reduced by AIF-1 abrogation. Fourth, although angiogenesis assays were not negatively affected by a reduction in AIF-1, angiogenic potential of EC was enhanced by AIF-1 overexpression.

Future strategies

The use of immunosuppressants and neutralizing antibodies may have a role in reducing leukocyte accumulation, inhibiting renal macrophage recruitment, and hence suppressing the development of renal injury. Future studies are needed to evaluate the anti-inflammatory strategies to demonstrate antiproteinuric and renoprotective effects [2]. Macrophage migration inhibitory factor, which is a proinflammatory cytokine produced by both immune and nonimmune cells, may be a potential therapeutic strategy for DN [46].

Acknowledgements

The authors thank the Faculty of Medicine, Minia University, for the financial support of this study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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