# Decreased ADP-Ribosyl Cyclase Activity in Peripheral Blood Mononuclear Cells from Diabetic Patients with Nephropathy

Authors: Michio Ohtsuji; Kunimasa Yagi; Miyuki Shintaku-Kubota; Yukiko Kojima-Koba; Naoko Ito; Masako Sugihara; Naoto Yamaaki; Daisuke Chujo; Atsushi Nohara; Yoshiyu Takeda; Junji Kobayashi; Masakazu Yamagishi; Haruhiro Higashida
Journal: Experimental Diabetes Research
 (2008)

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## Abstract

Aims/hypothesis. ADP-ribosyl-cyclase activity (ADPRCA) of CD38 and other ectoenzymes mainly generate cyclic adenosine 5'diphosphate-(ADP-) ribose (cADPR) as a second messenger in various mammalian cells, including pancreatic beta cells and peripheral blood mononuclear cells (PBMCs). Since PBMCs contribute to the pathogenesis of diabetic nephropathy, ADPRCA of PBMCs could serve as a clinical prognostic marker for diabetic nephropathy. This study aimed to investigate the connection between ADPRCA in PBMCs and diabetic complications.
Methods. PBMCs from 60 diabetic patients (10 for type 1 and 50 for type 2) and 15 nondiabetic controls were fluorometrically measured for ADPRCA based on the conversion of nicotinamide guanine dinucleotide (NGD+) into cyclic GDP-ribose.
Results. ADPRCA negatively correlated with the level of HbA1c (P=.040, R2=.073), although ADPRCA showed no significant correlation with gender, age, BMI, blood pressure, level of fasting plasma glucose and lipid levels, as well as type, duration, or medication of diabetes. Interestingly, patients with nephropathy, but not other complications, presented significantly lower ADPRCA than those without nephropathy
(P=.0198) and diabetes (P=.0332). ANCOVA analysis adjusted for HbA1c showed no significant correlation between ADPRCA and nephropathy. However, logistic regression analyses revealed that determinants for nephropathy were systolic blood pressure and ADPRCA, not HbA1c.
Conclusion/interpretation. Decreased ADPRCA significantly correlated with diabetic nephropathy. ADPRCA in PBMCs would be an important marker associated with diabetic nephropathy.


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## Body

## 1. Introduction

Diabetes mellitus  is characterized by chronic hyperglycemia and the
development  of diabetes-specific microvascular complications. As a consequence
of these complications, diabetes is a leading cause of end stage renal disease
(ESRD) [1]. Actually, diabetic
nephropathy is the single most common cause of ESRD in Japan [2]. Recent
epidemiologic data indicated that the number of Japanese type 2 diabetic
patients on renal replacement therapy has tripled within less than 15 years,
and Japanese type 2 diabetic patients might be particularly predisposed to
nephropathy [3, 4]. Therefore,
earlier detection of high-risk Japanese subjects for the diabetic nephropathy
is quite important for early intervention to prevent ESRD.Chronic low-grade inflammation and activation of the innate
immune system are closely involved in the pathogenesis of diabetes and its
microvascular complications [5, 6]. Inflammatory events are
central to the pathogenesis of diabetic nephropathy [7–9], and inflammatory cytokines are involved in its development and
progression [10]. Macrophages derived from circulating monocytes have been
recently focused on as playing central roles in the progression of diabetic
nephropathy [11, 12]. Since PBMCs
mainly consist of lymphocytes and monocytes, both of which contribute to the
progression of diabetic nephropathy, intracellular regulatory signals involved
in the activation of PBMCs could serve as a possible therapeutic target and/or
clinical prognostic marker for diabetic nephropathy.Cyclic adenosine 5’diphosphate-ribose (cADPR) plays a second
messenger role in a variety of mammalian cells, including pancreatic beta
cells, kidney mesangial cells, and PBMCs [13]. The rapid release of Ca2+ from the smooth endoplasmic
reticulum (SER), the most characterized Ca2+ organelle, is evoked by
stimulation of two kinds of receptors on the SER for ryanodine and inositol
(1,4,5)-triphosphate. cADPR is catalyzed from beta-NAD+ by
ADP-ribosyl-cyclase activity (ADPRCA) of CD38, CD157, and other
ectocellular membrane-bound enzymes [14–18]. cADPR has
been recently demonstrated to stimulate a variety of mammalian cell functions,
including proliferation, secretion, contraction, and vasodilation [19–25]. For example,
several studies have
examined ADPRCA in kidney mesangial cells [26, 27], and cADPR
has been reported to induce smooth muscle contraction in small renal arteries
[28].Since cADPR modulates adaptive immune recognition process of
PBMCs [29], we hypothesized that impaired regulatory signals of ADPRCA in PBMCs
would result in the progression of diabetic vascular complications. However, no
clinical studies have been performed to examine the relationship between CD38
and diabetic complications.Based on this background, this study investigates the connection
between ADPRCA in PBMCs and diabetic vascular complications, especially
nephropathy.


## 2. Materials and Methods

### 2.1. Study Population

Patients were
eligible for the study if they exhibited diabetes mellitus. Diabetes mellitus
was diagnosed and classified according to World Health Organization (WHO)
criteria [30, 31]. Subjects
with other endocrine diseases or significant renal and/or hepatic diseases were
excluded. The study, approved by the ethics committee of Kanazawa University
Graduate School of Medical Science, was conducted in accordance with the
Declaration of Helsinki (1964), and all patients gave written informed consent
before participating in the study.Definition of Diabetic Complications
ssessment and
diagnosis of diabetic complications were performed as below [32]. Nephropathy
was diagnosed as the existence of albuminuria, proteinuria, and/or creatinine
clearance <60 mL/min. Albuminuria was defined as urinary albumin excretion
between 20 and 200 mg/24 hr or urinary albumin to urinary creatinine ratio
between 30 and 300 mg/gCr. Proteinuria was defined
as Albustix  [Ames]  positive. Creatinine clearance values were calculated by the Cockroft-Gault formula.  Retinopathy was diagnosed on the basis
of direct ophthalmoscopy (through a dilated pupil) by an experienced
ophthalmologist and/or by fluorescein angiography. Peripheral neuropathy was
assessed by questioning patients about symptoms of neuropathy, including
paresthesia, dulled sensation, and pain in legs and feet and was based on
clinical examination (i.e., measuring abnormal knee/ankle reflexes and a
Semmes-Weinstein monofilament) and confirmed by measurement of conduction
velocities of ulnar (motor and sensory), tibial, peroneal, and sural nerves. Macroangiopathy was considered in
subjects who met the following three conditions: (1) a history of a
cardiovascular event and/or the presence of angina and/or permanent ischemic
electrocardiogram abnormalities at rest or ischemic abnormalities in a stress
test (usually combined with a cardiac noninvasive imaging technique); (2)
claudication and/or abolished peripheral pulses and/or foot lesions due to
vascular disease demonstrated by Doppler echography and/or angiography; or (3)
carotid vascular disease, as assessed by Doppler echography.Medication for Diabetes
Medication for
type 2 diabetics was classified into three categories: dietary therapy without
medication, insulin injection, and oral hypoglycemic agents including
sulphonylureas and alpha-glucosidase inhibitors. No type 2 diabetic subjects
being treated with insulin sensitizers (including thiazolidinediones and
biguanides) were enrolled in this study.


### 2.2. Laboratory Measurements

Body mass index
(BMI) was calculated as weight (in kilograms) divided by height (in meters)
squared. Venous blood samples were obtained after a 12-hour overnight fast.
Blood glucose was measured with the glucose oxidase method and HbA1c by
high-pressure liquid chromatography. Serum total cholesterol (TC) and
triglycerides (TG) were determined by enzymatic methods, and high-density
lipoprotein cholesterol (HDL-C) levels were measured by a
polyanion-polymer/detergent method. Low-density lipoprotein cholesterol (LDL-C)
was calculated using the Friedewald formula.


### 2.3. Measurement of Adprca

Isolation of Pbmc Membranous Fraction
After obtaining written informed consent, peripheral blood
samples were collected. PBMCs were isolated using Ficoll-Paque PLUS (Sigma) [33–35] and
centrifuged. Isolated PBMCs were suspended in 10 mM Tris/HCl solution, pH
7.4, with 5 mM MgCl2 (2 mL for each sample) at 4°C for 30 minutes.
The suspension was homogenized in a Teflon-glass homogenizer; the resultant
homogenate was centrifuged at 4°C for 5 minutes at 1000 ×g to remove unbroken
cells and nuclei. Crude membrane fractions were prepared by centrifugation
(twice) of homogenates at 105 000 ×g for 15 minutes. The supernatant was removed, and
precipitates were suspended in 10 mM Tris/HCl solution, pH 6.7 [36, 37]. For each
experiment, membranes were freshly prepared and used immediately for enzymatic
reactions.Fluorometric Measurement of Adp-Ribosyl Cyclase Activity
ADPRCA was determined fluorometrically using a technique based
on measurement of the conversion ofβ-NGD+ into the fluorescent product cGDP-ribose [36–39]. In brief,
2.5 mL of reaction mixtures containing 60 μM β-NGD+, 50 mM Tris/HCl, pH 6.6, 100 mM KCl, 10 μM CaCl2,
and membranes (62–297 μg of
protein) were maintained at 37°C under constant stirring. The samples were
then excited at 300 nm, and fluorescence emission was continuously monitored at
410 nm in a Shimadzu RF-5300PC spectrofluorophotometer (Kyoto, Japan). Activity
was calculated from the data points recorded during 5 minutes per mg membrane protein
as reported previously [37].


### 2.4. Statistical Analysis

All data are
shown as mean  ±  SD. Continuous variables were compared by one-way analyses of
variance (ANOVA) or covariance (ANCOVA) after being adjusted for age, BMI, and
sex. Normality of the distribution of Ln(ADPRCA) was confirmed by
Shapiro-Wilk’s W-test.
Differences between the two groups were compared by chi2 analysis
(categorical variables) or nonparametric Mann-Whitney U-test (continuous variables). Logistic
regression analyses were performed to clarify the clinical parameters
contributing to categorical variables. Stepwise multivariate regression
analyses were performed to clarify the clinical parameters contributing to the
level of continuous variable. All statistical analyses were conducted with JMP
6.03 for Macintosh OS-X 10.5 (SAS Institute Inc, Cary, NC, USA). A
P-value of less than .05 was considered
statistically significant.


## 2.1. Study Population

Patients were
eligible for the study if they exhibited diabetes mellitus. Diabetes mellitus
was diagnosed and classified according to World Health Organization (WHO)
criteria [30, 31]. Subjects
with other endocrine diseases or significant renal and/or hepatic diseases were
excluded. The study, approved by the ethics committee of Kanazawa University
Graduate School of Medical Science, was conducted in accordance with the
Declaration of Helsinki (1964), and all patients gave written informed consent
before participating in the study.Definition of Diabetic Complications
ssessment and
diagnosis of diabetic complications were performed as below [32]. Nephropathy
was diagnosed as the existence of albuminuria, proteinuria, and/or creatinine
clearance <60 mL/min. Albuminuria was defined as urinary albumin excretion
between 20 and 200 mg/24 hr or urinary albumin to urinary creatinine ratio
between 30 and 300 mg/gCr. Proteinuria was defined
as Albustix  [Ames]  positive. Creatinine clearance values were calculated by the Cockroft-Gault formula.  Retinopathy was diagnosed on the basis
of direct ophthalmoscopy (through a dilated pupil) by an experienced
ophthalmologist and/or by fluorescein angiography. Peripheral neuropathy was
assessed by questioning patients about symptoms of neuropathy, including
paresthesia, dulled sensation, and pain in legs and feet and was based on
clinical examination (i.e., measuring abnormal knee/ankle reflexes and a
Semmes-Weinstein monofilament) and confirmed by measurement of conduction
velocities of ulnar (motor and sensory), tibial, peroneal, and sural nerves. Macroangiopathy was considered in
subjects who met the following three conditions: (1) a history of a
cardiovascular event and/or the presence of angina and/or permanent ischemic
electrocardiogram abnormalities at rest or ischemic abnormalities in a stress
test (usually combined with a cardiac noninvasive imaging technique); (2)
claudication and/or abolished peripheral pulses and/or foot lesions due to
vascular disease demonstrated by Doppler echography and/or angiography; or (3)
carotid vascular disease, as assessed by Doppler echography.Medication for Diabetes
Medication for
type 2 diabetics was classified into three categories: dietary therapy without
medication, insulin injection, and oral hypoglycemic agents including
sulphonylureas and alpha-glucosidase inhibitors. No type 2 diabetic subjects
being treated with insulin sensitizers (including thiazolidinediones and
biguanides) were enrolled in this study.


## 2.2. Laboratory Measurements

Body mass index
(BMI) was calculated as weight (in kilograms) divided by height (in meters)
squared. Venous blood samples were obtained after a 12-hour overnight fast.
Blood glucose was measured with the glucose oxidase method and HbA1c by
high-pressure liquid chromatography. Serum total cholesterol (TC) and
triglycerides (TG) were determined by enzymatic methods, and high-density
lipoprotein cholesterol (HDL-C) levels were measured by a
polyanion-polymer/detergent method. Low-density lipoprotein cholesterol (LDL-C)
was calculated using the Friedewald formula.


## 2.3. Measurement of Adprca

Isolation of Pbmc Membranous Fraction
After obtaining written informed consent, peripheral blood
samples were collected. PBMCs were isolated using Ficoll-Paque PLUS (Sigma) [33–35] and
centrifuged. Isolated PBMCs were suspended in 10 mM Tris/HCl solution, pH
7.4, with 5 mM MgCl2 (2 mL for each sample) at 4°C for 30 minutes.
The suspension was homogenized in a Teflon-glass homogenizer; the resultant
homogenate was centrifuged at 4°C for 5 minutes at 1000 ×g to remove unbroken
cells and nuclei. Crude membrane fractions were prepared by centrifugation
(twice) of homogenates at 105 000 ×g for 15 minutes. The supernatant was removed, and
precipitates were suspended in 10 mM Tris/HCl solution, pH 6.7 [36, 37]. For each
experiment, membranes were freshly prepared and used immediately for enzymatic
reactions.Fluorometric Measurement of Adp-Ribosyl Cyclase Activity
ADPRCA was determined fluorometrically using a technique based
on measurement of the conversion ofβ-NGD+ into the fluorescent product cGDP-ribose [36–39]. In brief,
2.5 mL of reaction mixtures containing 60 μM β-NGD+, 50 mM Tris/HCl, pH 6.6, 100 mM KCl, 10 μM CaCl2,
and membranes (62–297 μg of
protein) were maintained at 37°C under constant stirring. The samples were
then excited at 300 nm, and fluorescence emission was continuously monitored at
410 nm in a Shimadzu RF-5300PC spectrofluorophotometer (Kyoto, Japan). Activity
was calculated from the data points recorded during 5 minutes per mg membrane protein
as reported previously [37].


## 2.4. Statistical Analysis

All data are
shown as mean  ±  SD. Continuous variables were compared by one-way analyses of
variance (ANOVA) or covariance (ANCOVA) after being adjusted for age, BMI, and
sex. Normality of the distribution of Ln(ADPRCA) was confirmed by
Shapiro-Wilk’s W-test.
Differences between the two groups were compared by chi2 analysis
(categorical variables) or nonparametric Mann-Whitney U-test (continuous variables). Logistic
regression analyses were performed to clarify the clinical parameters
contributing to categorical variables. Stepwise multivariate regression
analyses were performed to clarify the clinical parameters contributing to the
level of continuous variable. All statistical analyses were conducted with JMP
6.03 for Macintosh OS-X 10.5 (SAS Institute Inc, Cary, NC, USA). A
P-value of less than .05 was considered
statistically significant.


## 3. Results

Relationship between Adprca and Clinical Parameters
In total, sixty Japanese diabetic patients (31 males and 29
females) and fifteen nondiabetic controls (6 males and 9 females) were enrolled
in this study. The baseline characteristics of the subjects are shown in Table1. ADPRCA showed statistically significant negative correlation with the level
of HbA1c (P  =  .040, R2  =  0.073, Figure 1). As shown in Table 2, no significant correlation was observed between ADPRCA and other clinical
parameters (level of fasting plasma glucose, systolic and diastolic blood
pressure, serum total cholesterol, logarithm of serum TG, HDL-C, LDL-C, age,
duration of diabetes, BMI, gender difference, type of diabetes (Figure 2(a)), or
medication for diabetes (Figure 2(b))).Table 1
Baseline characteristics of subjects. Results are expressed as mean  ±  S.D.
Type
1 diabetesType 2 diabetesNondiabetic controlNumber of subjects105015Gender (male/female)5/526/246/9Age (years)36.0±14.263.0±12.051.0±22.0BMI (kg/m2)21.4±2.622.9±3.922.1±2.4Duration of diabetes (years)11.0±9.216.0±9.7—Fasting plasma glucose (mg/dl)244  ±  130164  ±  5481  ±  12HbA1c (%)8.0±1.57.6±1.34.6±0.7Medication for diabetesDiet alone—4—Oral hypoglycemic agents—30—Insulin1016—Diabetic complicationsNephropathy320Retinopathy422Neuropathy425Macroangiopathy018ADP-ribosyl cyclase activity (nmol/min/mg protein)16.9±7.516.6±7.617.8±4.6Table 2
Correlation of ADP-ribosyl-cyclase activity with subject
parameters (calculated
with logarithm-transformed TG).
FactorR2P-valueFasting plasma glucose0.0120NSHbA1c0.0731.040Systolic blood pressure0.0133NSDiastolic blood pressure0.0301NSTotal cholesterol (TC)0.0424NSHDL-C0.0042NSLDL-C0.0258NSTriglyceride (TG)0.0588NSDuration of diabetes0.0150NSAge0.0367NSBMI0.0174NSGender0.0151NSFigure 1
ADP-ribosyl cyclase activities and the level of HbA1c. Statistically
significant relationship was observed between ADPRCA and HbA1c (P  =  .040, R2  =  0.073, Ln(ADPRC)  = 3.4277567–0.093904*HbA1c).(a) ADP-ribosyl cyclase activities and type of
diabetes. No significant relationship was observed between ADPRCA and type of
diabetes. (b) ADP-ribosyl cyclase activities and medication for type 2 diabetes.
No significant relationship was observed between ADPRCA and medication for type
2 diabetes. CTL: control; OHA: oral hypoglycemic agent.
(a)(b)Adprca in Individuals with Diabetic Complications
Figure3 shows the relationship between ADPRCA and the diabetic
vascular complications. ADPRCA was significantly lower in subjects with
nephropathy than those without (P  =  .0198) and nondiabetic controls (P  =  .0332) (Figure 3(a)). Subjects with other complications also showed similar
tendencies; however, no significant correlations between ADPRCA and
retinopathy, neuropathy, or macroangiopathy were observed (Figures 3(b)–3(d)).  Although HbA1c level showed relationship with ADPRCA, no significant
difference was observed in ADPRCA between subjects with any diabetic
complications (data not shown).Relationship between logarithm of ADP-ribosyl-cyclase
activity Ln(ADPRCA) and diabetic vascular complications. Figures show
relationship between nondiabetic control, subjects with each complication, and
those without. (a) Subjects with nephropathy showed lower ADPRCA than those
without nephropathy (P  =  .0198) and
nondiabetic controls (P  =  .0332). (b)–(d) No significant
difference in ADPRCA was observed in subjects with retinopathy, neuropathy, and
macroangiopathy. CTL: control.
(a)(b)(c)(d)As HbA1c was significantly related to ADPRCA, we examined
whether HbA1c contributed to the relationship between ADPRCA and nephropathy.  The results of ANCOVA showed that the difference just failed to meet
statistical significance after adjusting for HbA1c (Table3). Next, to examine
whether ADPRCA could be an independent contributor to the existence of
nephropathy, we performed logistic analyses adjusted for systolic blood
pressure, diastolic blood pressure, TG, HDL, LDL, gender, type of diabetes,
duration of diabetes, medication for diabetes, HbA1c, and BMI. Systolic blood pressure and ADPRCA contributed
significantly to the existence of nephropathy (Table 4).Table 3
Comparison of ADPRCA influence on nephropathy, adjusted
for HbA1c.
FactorAverageS.E.95% C.I.P-valueNephropathy (−)2.7990.0762.646–2.951.075Nephropathy (+)2.5760.0952.386–2.765Table 4
Logistic analysis between nephropathy and parameters in
diabetic subjects. Carrier of complication  =  1, noncarrier  =  0; medication:
insulin  = 2, OHA  =  1, diet  =  0; gender: male  =  1, female  =  0; type of diabetes: type 2  = 1, type 1  =  0.
FactorRegression coefficientR2P-valueSystolic blood pressure−0.091156.040.0140ADP-ribosyl-cyclase activity2.617583.707.0229


## 4. Discussion

The main finding of
this study was that diabetic subjects with nephropathy showed decreased ADPRCA.
However, PBMCs in proinflammatory states like diabetic vasculopathy might be
relating to increased ADPRCA as several cytokines including IL-8, IFN-gamma
upregulate intracellular CD38 activity [17], our results interestingly showed
decreased ADPRCA in PBMCs. Logistic analysis revealed that only systolic blood
pressure and ADPRCA, but not HbA1c, were significantly related to the incidence
of nephropathy. Therefore, contribution of HbA1c to the relationship between
ADPRCA and nephropathy should be considered small in extent. ADPRCA’s correlation with nephropathy seems reasonable.First, to discuss the
role of cADPR-mediated signals in PBMCs, since ADPRCA could be stimulated by angiotensin-II [37], kidney tissue
with diabetic
nephropathy could show increased ADPRCA. Recent report by Kim et al. showed
increased ADPRCA in the kidney of STZ-induced diabetes mice [18]. As we
measured ADPRCA in PBMCs, this discrepancy could be acceptable. Interestingly, the
roles of CD38 on PBMCs’ effect on vascular complications are bidirectional. In
PBMCs, binding of agonistic anti-CD38 antibodies, which stimulate ADPRCA,
induces release of proinflammatory cytokines including IL-1, IL-6, and
TNF-alpha over the short term [40]. Cytokine release could make an important
contribution to inflammation responsible in the early stages of diabetic
vascular complications. On the other hand, agonistic CD38 ligation inhibits
cell growth and induces apoptosis in B-cell precursors [41] mediating
phosphatidylinositol 3-kinase signaling [42], although having stimulatory
effects on mature lymphocytes. The suppressive effect mediated by CD38 was also
observed in experiments with patient-derived myeloid leukemia cells and with the murine cell
line [43]. In addition, CD38 expression has been reported
in circulating monocytes but not in resident macrophages and dendritic cells [44, 45].
Differentiation of monocytes to macrophages resulted in the downregulation of
surface expression of CD38 [46]. CD38 is strongly expressed in lymphocyte
precursors, declined
during differentiation, and then upregulated again in mature plasma cells [47].
CD157 was suggested to display a similar expression tendency in myeloid cells [48].
Since hyperglycemia directly enhances protein ADP-ribosylation in cultured
neuroblastoma cells [49], resulting in increased ADPRCA in diabetic subjects, we
speculate that decreased ADPRCA in PBMCs could reflect decreased suppressive
effects of CD38 and CD157 and increased numbers of differentiated cells.Second, let us consider the agonistic effects of autoantibodies
against CD38, which is shown to exert insulin secretion from cultured human
islets [50] through ADPRCA activation. In humans, the majority of anti-CD38
autoantibodies (~60%) display agonistic properties [51, 52], which
demonstrate the capability to trigger Ca2+ release in lymphocytic
cell lines [53]. In agreement with these functional features, the presence of
anti-CD38 autoantibodies in type 2 diabetic patients was associated with
significantly higher levels of fasting plasma C-peptide and insulin, as
compared with anti-CD38 negative subjects. Thus, anti-CD38 autoimmunity might
indicate a relative protection against beta-cell failure and a lower risk of
insulin requirement [52, 54, 55]. Previous
reports on the clinical characteristics of anti-CD38 autoantibodies carriers
have not gone into depth on diabetic complications, although the possible exacerbation
of diabetic complications by the agonistic effect of anti-CD38 autoantibodies
on PBMCs was noted by Mallone et al. [51]. However, several discussions should be needed for the
relationship between CD38 autoantibodies and diabetic vasculopathy as agonistic
CD38 autoantibodies possibly stimulate both insulin rsecretion resulting in hyperinsulinemia, the prominent
risk factor for diabetic  macroangiopathy, and angiotensin-II induced renal
artery contraction. We just speculate that those with
anti-CD38 autoantibodies should show lower frequencies of diabetic nephropathy,
and other vascular complications in long-term follow-up studies due to better
glycemic control and increased ADPRCA reflecting less maturated PBMCs.Third, as all of our subjects
were diabetic, it behooves us mention the Okamoto model of diabetes pathogenesis. CD38-related signal has been well documented in diabetes
mellitus [18, 56–58]. Our results showing decreased ADPRCA
being significantly correlated to increased HbA1c is compatible with previous
studies reflecting to some degree
the Okamoto model [59–61].
Interestingly, in our study, no significant relationship was observed between
ADPRCA and fasting plasma glucose. We suggest that ADPRCA might be more related
to postprandial than fasting plasma glucose level, the former being strongly
responsive to insulin secretion [27, 29].Finally, the clinical significance of our results: CD38
expression, representative of ADP-ribosyl cyclase, is already used clinically
as a prognostic marker for HIV infected subjects [62, 63] and chronic
lymphoid leukemia (CLL) [13, 56, 64]. Since other ADP ribosyl cyclases including CD157 reside
on the cell surface of PBMCs, restricting examination to CD38 would not
entirely cover cADPR-mediated signaling impairment. Measuring ADPRCA would thus
be a better approach in flagging up groups at risk for diabetic nephropathy
from among general diabetic subjects. We envision
ADPRCA measurement being similarly introduced into clinical settings for
detecting subjects at high-risk for diabetic nephropathy and thus prompting
early intervention to prevent ESRD.This study had a number of limitations. First, we did not have
data on anti-CD38 autoantibodies. ADPRCA in each subject is partly determined by preexisting
factors independent of diabetes, including CD38 genetic polymorphisms and
autoantibodies against CD38. We speculate that higher
ADPRCA values might reflect possession of anti-CD38 autoantibodies. Second, we
did not examine any markers of lymphocyte or monocyte maturation/differentiation.
Both should be examined in further studies.In conclusion, our
findings suggest that decreased ADPRCA in PBMCs is
significantly correlated with diabetic nephropathy and that measurement of
ADPRCA in PBMCs could serve as an important marker associated with diabetic
nephropathy. Further
prospective studies should be introduced to clarify the mechanism and
predictive significance of decreased ADPRCA in diabetic complications.



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*Source: 897508-2009-03-17.xml*