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Peripheral blood mitochondrial DNA content and dysregulation of glucose metabolism
diabetes research and clinical practice 83 (2009) 94–99
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Diabetes Research and Clinical Practice journal homepage: www.elsevier.com/locate/diabres
Peripheral blood mitochondrial DNA content and dysregulation of glucose metabolism Shao-Wen Weng a, Tsu-Kung Lin b, Chia-Wei Liou b, Shang-Der Chen b, Yau-Huei Wei c, Hsin-Chen Lee c, I-Ya Chen a, Ching-Jung Hsieh a, Pei-Wen Wang a,* a
Division of Metabolism, Department of Internal Medicine, Chang Gung Memorial Hospital, Kaohsiung Medical Center, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-sung Hsiang, Kaohsiung Hsien 83305, Taiwan b Department of Neurology, Chang Gung Memorial Hospital, Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung 83305, Taiwan c Department of Biochemistry and Molecular Biology, School of Life Science, National Yang-Ming University, Taipei 112, Taiwan
article info
abstract
Article history:
Objective: The aim of this study was to examine the potential influence of insulin resistance
Received 22 May 2008
(IR), hyperglycemia and oxidative stress on leucocytes mitochondrial DNA (mtDNA) content.
Accepted 2 October 2008
Research design and method: One hundred twenty-five T2DM, 101 IFG and 70 normal subjects
Published on line 18 November 2008
were enrolled in this study. The quantity of relative mtDNA content was measured by a realtime PCR and corrected by simultaneous measurement of the nuclear DNA. Parameters of
Keywords:
lipid peroxidation, thiobarbituric acid reactive substance (TBARS), and total free thiols as
Insulin resistance
antioxidative status were measured from serum samples. IR was assessed by homeostasis
Mitochondria
model assessment in the non-diabetic groups. Relationships among different variables were
Oxidative stress
analyzed by general linear model correlation.
Type 2 diabetes mellitus
Results: In all subjects, after correcting for age, sex and BMI, there were progressive increases of leucocyte mtDNA copy number, TBARS, and total reduced thiols with progressive dysregulation of glucose metabolism (normal vs. IFG vs. T2DM). Furthermore, correlation between mtDNA content and glucose dysregulation persisted after sequential correction for age, sex, BMI and TBARS. The independent predictor of mtDNA content by regression analysis was hyperglycemia. In non-diabetic group, influence of family history of diabetes on mtDNA content turned to non-significant after correcting for fasting plasma glucose (FPG). Correlation study revealed that mtDNA content was correlated with FPG (P < 0.001), but not IR. Conclusion: Our results indicate that hyperglycemia, not IR, is associated with an increase of leucocyte mtDNA copy number in cases of glucose dysregulation. # 2008 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
Linkage of mitochondrial dysfunction and associated oxidative stress to development of type 2 diabetes (T2DM) and
related complications has been documented [1–4]. Petersen et al. [5] have shown that the insulin-resistant offsprings of parents with T2DM have impaired mitochondrial function, which were associated with severe muscle insulin resistance
* Corresponding author. Tel.: +886 7 7317123x8302; fax: +886 7 7322402. E-mail address: [email protected] (P.-W. Wang). 0168-8227/$ – see front matter # 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2008.10.002
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diabetes research and clinical practice 83 (2009) 94–99
Among them, 99 patients had insulin secretagogue or insulin, 97 had metformin and 14 had pioglitazone treatment. The non-diabetic individuals were recruited from our health screening center as well as medical center employees. The history of diabetes in both parents was defined as positive if either parent had T2DM. IR and beta cell function were assessed by homeostasis model assessment (HOMA-IR and HOMA-beta) in the non-diabetic group only, because HOMA-IR is not a reliable method for determining insulin resistance in T2DM treated with anti-diabetic agents [15]. Informed prior consent was obtained from all participants. The studies were conducted according to the guidelines of the Declaration of Helsinki, and the study protocol reviewed and accepted by the Ethics Committee of Chang Gung Memorial Hospital.
(IR). A follow-up study by the same research group found that the reduction in mitochondrial activity in the insulin-resistant offspring could be attributed to a reduction in muscle mitochondrial content [6]. Peripheral blood leucocyte mitochondrial DNA (mtDNA) copy number is decreased in offspring of T2DM patients in Korean population, and the decreased mtDNA content is a risk factor for development of T2DM [7]. However, in a recent study of leucocyte mtDNA content in offspring of T2DM patients in Caucasian population, no correlation with either insulin sensitivity or beta cell function was noted [8]. Oxidative status is elevated in the hyperglycemic state [9– 11]. Within a certain range, reactive oxygen species (ROS) may induce stress responses to help cells to cope with hazardous environments [12,13]. Thus, under pathological conditions, mitochondrial abundance as well as the copy number of mtDNA in cells changes in response to increases in oxidative status. This is supported by a previous study that oxidative stress can increase the copy number of mtDNA in leucocytes in blood circulation [14]. Therefore, the aim of this study was to investigate whether mitochondrial biogenesis may be modified to cope with the elevations in oxidative stress in patients with T2DM. To answer this question, we compared the leucocyte mtDNA copy number in patients with T2DM, impaired fasting glucose (IFG) and normal subjects. We also examined the potential influence of insulin resistance and oxidative stress on mtDNA in peripheral leucocytes.
2.
Research design and methods
2.1.
Subjects
2.2. Determination of relative leucocyte mtDNA copy number Total DNA was isolated from peripheral blood leucocytes using PUREGENE1 DNA Purification kit (Gentra, Minnesota, USA). The extracted DNA samples were frozen at 20 8 C until assay without repeated freeze–thawing cycles. The relative mtDNA copy numbers was measured by a real-time PCR and corrected by simultaneous measurement of the nuclear DNA. The forward and reverse primers for nuclear gene, which are complementary to b-actin gene, were 50 -TCACCCACACTGTGCCCATCTACGA-30 and 50 -CAGCGGAACCGCTCATTGCCAATGG-30 . The forward and reverse primers for mtDNA, which are complementary to the sequence of the ND1 gene, were 50 -TGGGTACAATGAGGAGTAGG-30 and 50 -GGAGTAATCCAGGTCGGT-30 . The PCR was performed in a ABI PRISM 7700 Sequence Detection System (PE Biosystems, California, USA), using the SYBR1 GREEN PCR MASTER MIX kit (Applied Biosystems, New Jersey, USA). DNA (10 ng) was mixed with 12.5 ml SYBR1 GREEN PCR MASTER MIX containing 50 nmol of forward and reverse primers, in a final volume of 25 ml. The PCR conditions were 2 min at 50 8C and 10 min at 95 8C, followed by 40 cycles of denaturation at 95 8C for 15 s, annealing at 60 8C for 20 s and primer extension at 72 8C for15 s. The melting curves analysis was provided by the Dissociation Curve Software and took an additional step of
In this study, we recruited 296 subjects, of which 125 patients had T2DM, 101 patients had IFG and 70 were normal subjects (Table 1). Glucose dysregulation status was defined according to the diagnostic criteria of American Diabetic Association. IFG was defined when subjects had a fasting plasma glucose (FPG) value between 100 mg/dl and 125 mg/dl (6.1–6.9 mmol/l), and diabetes as having FPG of at least 126 mg/dl (7 mmol/l). The T2DM patients were recruited from our out-patient clinic.
Table 1 – Comparison among normal, IFG and T2DM groups.
Age (years) Sex (F%) Family history of T2DM (%) BMI (kg/m2) TBARS (mmol/l) Thiol (mmol/l) mtDNA copy number (log) FPG (mg/dl) Insulin (mU/ml) Homa-IR Homa-beta
Normal (n = 70)
IFG (n = 101)
T2DM (n = 125)
P value
47.2 11.6 44.3 (31/70) 4.3 (3/70) 23.6 3.0 1.24 0.51 1.69 1.0 1.77 1.38 92.3 6.8 12.8 6.6 2.89 1.41 151.8 81.8
52.8 11.5 46.5 (47/101) 22.8 (23/101) 25.3 3.3 1.38 0.56 1.60 0.59 2.14 0.97 110.3 6.5 19.5 9.4 5.35 2.65 147.4 73.5
57.2 12.0 44.8 (56/125) 48 (60/125) 25.6 3.5 1.78 0.55 2.07 0.83 3.09 0.74
0.002*, 0.006**, <0.001*** N.S. <0.001 0.001*, N.S.**, <0.001*** N.S.*, <0.001**, <0.001*** N.S.*, <0.001**, 0.002*** 0.016*, <0.001**, <0.001*** <0.001* <0.001* <0.001* N.S.*
P1: P value was adjusted for age, sex and BMI. P value between normal and IFG. ** P value between IFG and T2DM. *** P value between normal and T2DM. *
– – –
P1 value – – – – N.S.*, <0.001**, <0.001*** N.S.*, <0.001**, <0.001*** 0.011*, <0.001**, <0.001*** <0.001* <0.001* <0.001* N.S.*
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20 min after the real-time PCR. The amplified products were denatured and reannealed at different temperature points to detect their specific melting temperature. Samples showing primer-dimmers or unspecific fragments were excluded. The threshold cycle number (Ct) values of the b-actin gene and the mitochondrial ND1 gene were determined for each individual in the same quantitative PCR run. Each measurement was carried out at least three times and normalized in each experiment against a serial dilution of a control DNA sample. Good reproducibility was found both within and between runs. The intraassay coefficients of variation of Ct values were around 2.2% and 3.8% for ND1 and b-actin gene respectively. The interassay coefficients of variation of Ct values were around 4.9% and 5.4% for ND1 and b-actin gene respectively. Ct values can be used as a measure of the input copy number and Ct value differences used to quantify mtDNA copy number relative to the b-actin gene with the following equation: Relative copy number (Rc) = 2DCt [16], where DCt is the Ctbactin CtND1.
2.3.
Oxidative stress
Serum free thiols were determined by directly reacting thiols with 5,5-dithiobis 2-nitro benzoic acid (DTNB) to form 5-thio-2nitrobenzoic acid (TNB). The amount of thiols was calculated from the absorbance determined using the extinction coefficient of TNB (A412 = 13,600 M1 cm1) [17]. The serum thiobarbituric acid reactive substance (TBARS) concentration was assessed based on the method of Ohkawa et al. [18]. After centrifugation the serum samples were stored at 80 8C for future analysis. Results are expressed as micromoles of TBARS per liter. A standards curve of TBARS was obtained by hydrolysis of 1,1,3,3-tetraethoxypropane (TEPP).
2.4.
Statistical analysis
Logarithmic transformation of data was used since the original values of the relative mtDNA copy number in leucocytes showed a non-normal distribution. Results are expressed as mean standard deviation. Group comparisons were performed using the general linear model or Chi-square test. Power analysis revealed that the total sample of 296 subjects achieved 80% power to detect differences among the
means of the mtDNA copy number vs. the alternative of equal means using an F test with a 0.05 significance level. Linear regression and general linear model was used to identify the independent predictors. Relationships among different variables were analyzed by Pearson and Spearman’s correlation and Partial correlation under the control of the factors of age, sex and BMI. P < 0.05 was considered statistically significant.
3.
Results
3.1. The relationship among the metabolic profile, oxidative stress, and the mtDNA content Table 1 shows the metabolic profile, oxidative status and mtDNA content in patients with T2DM or IFG, or in normal subjects. Compared to normal subjects, patients with T2DM or IFG exhibit higher mean BMI values and greater mtDNA copy numbers. The averaged age was also older in these two groups. The T2DM group had significantly higher TBARS and total reduced thiols than the other two groups. After adjusting for age, sex and BMI, we found that the progressive increases in relative leucocyte mtDNA copy number (1.77 1.38 vs. 2.14 0.97 vs. 3.09 0.74, P < 0.001), TBARS (1.24 0.51 mmol/ l vs. 1.38 0.56 mmol/l vs. 1.78 0.55 mmol/l, P < 0.001) and total reduced thiols (1.69 1.0 mmol/l vs. 1.60 0.59 mmol/l vs. 2.07 0.83 mmol/l, P < 0.001) were closely associated with progression in dysregulation of glucose metabolism (normal vs. IFG vs. T2DM). Table 2 summarizes correlations of experimental variables in age, the metabolic profile, oxidative stress, and the relative mtDNA copy number obtained from the three groups. We found that age was significantly correlated with glucose dysregulation (P < 0.001) and FPG (P < 0.001). Glucose dysregulation, BMI, FPG, and HOMA-IR were well correlated with each other (P < 0.001). HOMA-beta was also significantly correlated with HOMA-IR (P < 0.001) and BMI (P < 0.001). Correlation analysis of the metabolic profiles and oxidative status parameters also showed a significant correlation between TBARS and glucose dysregulation (r = 0.369, P < 0.001), FPG (r = 0.164, P = 0.034), HOMA-IR (r = 0.160, P = 0.048) and mtDNA copy number (r = 0.208, P < 0.001). Thiol was only correlated with glucose dysregulation (r = 0.267, P < 0.001).
Table 2 – Main correlations among study variables.
Age BMI FPGa HOMA-IRa HOMA-betaa Thiol TBARS log mtDNA
Age
BMI
FPGa
HOMA-IRa
HOMA-betaa
Thiol
TBARS
1 0.092 0.258** 0.022 0.086 0.019 0.083 0.062
1 0.219** 0.376** 0.348** 0.039 0.081 0.114
1 0.502** 0.092 0.006 0.164* 0.185*
1 0.711** 0.039 0.160* 0.115
1 0.059 0.028 0.041
1 0.114 0.074
1 0.208**
log mtDNA
1
BMI, body mass index; FPG, fasting plasma glucose; HOMA-IR, homeostasis model assessment-insulin resistance; HOMA-beta, homeostasis model assessment-beta cell function; mtDNA: mitochondrial DNA copy number. a FPG, HOMA-IR and HOMA-beta were analyzed only in non-diabetic subjects. * P < 0.05. ** P < 0.005.
diabetes research and clinical practice 83 (2009) 94–99
Table 3 – Correlation of mtDNA copy number with glucose dysregulation status. Before adjustment Adjusted for age Adjusted for age, sex Adjusted for age, sex and BMI Adjusted for age, sex, BMI and TBARS
r = 0.553 r = 0.484 r = 0.484 r = 0.472 r = 0.444
P < 0.001 P < 0.001 P < 0.001 P < 0.001 P < 0.001
Correlation analysis of mtDNA copy number with other parameters revealed a significant positive correlation of mtDNA copy number between TBARS (r = 0.208, P = 0.001) and glucose dysregulation (r = 0.553, P < 0.001) (Table 3). Furthermore, the association between relative mtDNA copy number and glucose dysregulation remained significant after sequentially adjusting for age, sex, BMI and TBARS (r = 0.444, P < 0.001). In the non-diabetic subjects, mtDNA was significantly correlated with FPG (r = 0.185, P = 0.015), but not HOMAIR, after adjusting for age, sex and BMI. Finally, general linear model analysis of all the parameters obtained from the three study groups revealed that the glucose dysregulation (normal vs. IFG, P < 0.001; normal vs. T2DM, P < 0.001) and FPG (P < 0.001) in the non-diabetic subgroup were independent predictors of mtDNA copy number.
3.2. Impact of hyperglycemic treatment on the mtDNA content in T2DM In patients treated with pioglitazone (N = 14), there was a marginally significant increase of mtDNA copy number as compared to patients without ((3.45 0.34 vs. 3.04 0.76, P = 0.05). The difference gained more significance after correction for age, BMI, TBARS and other two kinds of antidiabetic agents (P = 0.036). However, in patients treated with metformin, there was no increase of mtDNA copy number as compared to patients without, even after correction for age, BMI, TBARS and other two kinds of anti-diabetic agents (3.09 0.75 vs. 3.08 0.71, P = 0.901). There was also no difference of mtDNA content between patients treated with insulin secretagogue and those without after correction for confounders (3.07 0.73 vs. 3.18 0.76, P = 0.46). We further analyzed the data in Table 3 by excluding cases taking pioglitazone treatment, the results did not change. It still indicated glucose dysregulation status to be independent predictor of mtDNA copy number.
3.3. Impact of family history of diabetes on the mtDNA content There was a progressive higher rate of family history of diabetes in patients with IFG or T2DM (3 of the 70 normal subjects, 23 of the 101 patients with IFG, and 60 of 125 people with T2DM). The presence of a family history did not influence mtDNA copy number in the T2DM group. Relative leucocyte mtDNA copy number was 3.12 0.61 or 3.05 0.84 in patients with or without a family history respectively (P = 0.60). However, family history of diabetes was associated with mtDNA content in the non-diabetic group. Compared to those without, patients with a family history of diabetes had a greater mtDNA copy number (2.56 0.67 vs. 1.88 1.20, P = 0.006), higher levels of FPG (111.1 9.6 mg/dl vs.
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101.5 10.7 mg/dl, P < 0.001) and greater IR index (HOMA-IR) (5.35 3.41 vs. 4.09 2.26, P = 0.017). The increase of mtDNA content in cases with positive family history remained significant after adjusting for age, sex, BMI and HOMR-IR (P = 0.015), but became insignificant, after adjusting for FPG (P = 0.081).
4.
Discussion
Our results provide evidence to demonstrate a positive association between dysregulation of glucose metabolism and the increase in leucocytes mtDNA copy number. Furthermore, in the non-diabetic group, in which FPG and HOMA-IR were evaluated, only FPG is the independent predictor. The non-diabetic individuals with positive family history had significantly higher mtDNA contents after correcting for age, sex, BMI and HOMR-IR, but this relationship lost significance after correcting for FPG. Collectively, these data suggest that hyperglycemia is more important than IR in regulating leucocytes mtDNA content. The significance of dysfunction of glucose metabolism in mitochondrial abnormality was reported in animal models of diabetes. Using an OVE26 mouse model of type 1 diabetes (T1DM), a model representing hyperglycemia without IR, diabetes-induced damage was found to stimulate cardiac mitochondrial biogenesis [19]. In that study, mitochondria from the diabetic heart showed evidence of reduced respiratory control ratio and increased oxidative stress. It was also found that the mRNA for the mitochondrial transcription factor A, which plays a key role in the regulation of mtDNA replication, was increased by 50%. Other parameters of mitochondrial content, including surface area, number, protein, and DNA, were significantly elevated to compensate for impaired mitochondria function [19]. Impaired mitochondrial function and increase of mitochondrial protein from kidney and heart were also reported in the streptozotocin-induced diabetic animal models [20–22]. In those studies, the changes were partially reversed by insulin treatment, suggesting that hyperglycemia, not IR, was the main cause of mitochondrial damage and biogenesis. Our intriguing results of a lack of association between IR and increase in mtDNA copy number differ to those reported by others. Morino et al. [6] found a reduction of mtDNA density in muscle tissue in the insulin-resistant offspring of parents with T2DM. Decreased mtDNA copy number in skeletal muscle [23] and adipose tissue [24] has also been found in patients with T2DM. The reasons underlying such discrepancies from our observations are not immediately clear. However, those reports focused mostly on mtDNA copy number in the IR-related target organs of skeletal muscle and adipose tissues, whereas we studied the regulation of mtDNA copy number by blood glucose in circulatory leucocytes. It is thus possible that alterations in mtDNA copy number in response to dysregulation of glucose metabolism might be dictated by the cellular responses to insulin. In addition, in contrast to skeletal muscles that are slow replicating cells, leucocytes are cells with rapid replication property. Discrepancy in the effect of glucose metabolism on
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mtDNA copy number may also be attributed to the nature of cell types. Studies of peripheral blood mtDNA content in diabetes have shown interesting and conflicting data [7,8,25]. In Korea, Lee and co-workers [7] found decreased mtDNA content in the insulin-resistant offspring of parents with T2DM. In a later study [25], they also found that this decrease in peripheral blood mtDNA content preceded the onset of diabetes. However, Singh et al. [8], studying the offspring of Caucasian parents with early onset T2DM, found no such decrease in mtDNA content in the offspring of T2DM patients. Singh et al. noted a small proliferation of mtDNA content in their case subjects with no correlation with insulin sensitivity. In our study of 178 non-diabetic Chinese individuals, there was an increase in peripheral blood mtDNA content in those with a positive family history of diabetes. The increase of mtDNA remained significant after correcting for age, sex, BMI and IR index, but it lost its significance after adjusting for FPG. Therefore, our data supports the findings of Singh et al., whose study, like ours, involved a larger sample that that of Lee et al. [7,25]. Although Singh et al. did not report FPG to have an influence on leucocyte mtDNA content, their study sample may have had a lower range of FPG than ours (93.6 11.5 mg/ dl vs. 102.9 11.1 mg/dl). Our study of 296 subjects had a wide range of glucose dysregulation categorized in normal, IFG, and T2DM. Therefore, the effect of hyperglycemia could be more clearly demonstrated. Anti-diabetic agents, including thiazolidinedione and metformin [24,26,27] have been reported to improve mitochondrial function and increase mitochondrial biogenesis. In our series, pioglitazone showed a positive influence on mitochondrial biogenesis while metformin did not. Since the number of patients taking pioglitazone was quite small in this series (N = 14), the overall results were not significantly changed by the medication history. However, the impact of anti-diabetic medication on mitochondrial function deserves further investigation. Previous reports have showed oxidative stress to be one of the factors involved in the increase of mtDNA copy number in human skeletal muscle [28], fibroblast cells [13], lung fibroblast cell line [12] and rat liver cells [29]. Wei and co-workers [14] have also demonstrated that the copy number of mtDNA in leucocytes is increased by oxidative stress in blood circulation. However, these previous studies were of healthy non-diabetic subjects. The association between alternation of leucocyte mtDNA copy number and oxidative stress in hyperglycemic subjects is still not clear. Our results showed an association between glucose dysregulation and oxidative stress as well as increased leucocyte mtDNA copy number. However, the correlation of mtDNA copy number with glucose dysregulation was more significant than with oxidative stress (measured as TBARS alone) in our study. Therefore, a more comprehensive assessment of stress markers is needed to conclude whether there are underlying mechanisms other than oxidative stress that would increase the leucocyte mtDNA content in subjects with hyperglycemia. In our study, the categorization of non-diabetic subjects was based on fasting plasma glucose without undergoing an oral glucose tolerance test (OGTT). It is well recognized that there are two underlying pathophysiologies of diabetes: IR and
insulin secretion which could be measured with different methods. Piche et al. [30] observed that OGTT was a less accurate method to measure IR. Although, it is likely that some of the normal subjects in our study will have impaired glucose tolerance but normal FPG, our conclusion about IR and mtDNA biogenesis may not be biased by the characterization of the subjects.
Acknowledgements This study was supported by grants from Chang Gung University College of Medicine (CMRPG840551 and CMRPG 850261). The authors wish to thank Professor Julie Chan for her kind revision of the manuscript.
Conflict of interest There are no conflicts of interest.
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Diabetes Research and Clinical Practice journal homepage: www.elsevier.com/locate/diabres
Peripheral blood mitochondrial DNA content and dysregulation of glucose metabolism Shao-Wen Weng a, Tsu-Kung Lin b, Chia-Wei Liou b, Shang-Der Chen b, Yau-Huei Wei c, Hsin-Chen Lee c, I-Ya Chen a, Ching-Jung Hsieh a, Pei-Wen Wang a,* a
Division of Metabolism, Department of Internal Medicine, Chang Gung Memorial Hospital, Kaohsiung Medical Center, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-sung Hsiang, Kaohsiung Hsien 83305, Taiwan b Department of Neurology, Chang Gung Memorial Hospital, Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung 83305, Taiwan c Department of Biochemistry and Molecular Biology, School of Life Science, National Yang-Ming University, Taipei 112, Taiwan
article info
abstract
Article history:
Objective: The aim of this study was to examine the potential influence of insulin resistance
Received 22 May 2008
(IR), hyperglycemia and oxidative stress on leucocytes mitochondrial DNA (mtDNA) content.
Accepted 2 October 2008
Research design and method: One hundred twenty-five T2DM, 101 IFG and 70 normal subjects
Published on line 18 November 2008
were enrolled in this study. The quantity of relative mtDNA content was measured by a realtime PCR and corrected by simultaneous measurement of the nuclear DNA. Parameters of
Keywords:
lipid peroxidation, thiobarbituric acid reactive substance (TBARS), and total free thiols as
Insulin resistance
antioxidative status were measured from serum samples. IR was assessed by homeostasis
Mitochondria
model assessment in the non-diabetic groups. Relationships among different variables were
Oxidative stress
analyzed by general linear model correlation.
Type 2 diabetes mellitus
Results: In all subjects, after correcting for age, sex and BMI, there were progressive increases of leucocyte mtDNA copy number, TBARS, and total reduced thiols with progressive dysregulation of glucose metabolism (normal vs. IFG vs. T2DM). Furthermore, correlation between mtDNA content and glucose dysregulation persisted after sequential correction for age, sex, BMI and TBARS. The independent predictor of mtDNA content by regression analysis was hyperglycemia. In non-diabetic group, influence of family history of diabetes on mtDNA content turned to non-significant after correcting for fasting plasma glucose (FPG). Correlation study revealed that mtDNA content was correlated with FPG (P < 0.001), but not IR. Conclusion: Our results indicate that hyperglycemia, not IR, is associated with an increase of leucocyte mtDNA copy number in cases of glucose dysregulation. # 2008 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
Linkage of mitochondrial dysfunction and associated oxidative stress to development of type 2 diabetes (T2DM) and
related complications has been documented [1–4]. Petersen et al. [5] have shown that the insulin-resistant offsprings of parents with T2DM have impaired mitochondrial function, which were associated with severe muscle insulin resistance
* Corresponding author. Tel.: +886 7 7317123x8302; fax: +886 7 7322402. E-mail address: [email protected] (P.-W. Wang). 0168-8227/$ – see front matter # 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2008.10.002
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diabetes research and clinical practice 83 (2009) 94–99
Among them, 99 patients had insulin secretagogue or insulin, 97 had metformin and 14 had pioglitazone treatment. The non-diabetic individuals were recruited from our health screening center as well as medical center employees. The history of diabetes in both parents was defined as positive if either parent had T2DM. IR and beta cell function were assessed by homeostasis model assessment (HOMA-IR and HOMA-beta) in the non-diabetic group only, because HOMA-IR is not a reliable method for determining insulin resistance in T2DM treated with anti-diabetic agents [15]. Informed prior consent was obtained from all participants. The studies were conducted according to the guidelines of the Declaration of Helsinki, and the study protocol reviewed and accepted by the Ethics Committee of Chang Gung Memorial Hospital.
(IR). A follow-up study by the same research group found that the reduction in mitochondrial activity in the insulin-resistant offspring could be attributed to a reduction in muscle mitochondrial content [6]. Peripheral blood leucocyte mitochondrial DNA (mtDNA) copy number is decreased in offspring of T2DM patients in Korean population, and the decreased mtDNA content is a risk factor for development of T2DM [7]. However, in a recent study of leucocyte mtDNA content in offspring of T2DM patients in Caucasian population, no correlation with either insulin sensitivity or beta cell function was noted [8]. Oxidative status is elevated in the hyperglycemic state [9– 11]. Within a certain range, reactive oxygen species (ROS) may induce stress responses to help cells to cope with hazardous environments [12,13]. Thus, under pathological conditions, mitochondrial abundance as well as the copy number of mtDNA in cells changes in response to increases in oxidative status. This is supported by a previous study that oxidative stress can increase the copy number of mtDNA in leucocytes in blood circulation [14]. Therefore, the aim of this study was to investigate whether mitochondrial biogenesis may be modified to cope with the elevations in oxidative stress in patients with T2DM. To answer this question, we compared the leucocyte mtDNA copy number in patients with T2DM, impaired fasting glucose (IFG) and normal subjects. We also examined the potential influence of insulin resistance and oxidative stress on mtDNA in peripheral leucocytes.
2.
Research design and methods
2.1.
Subjects
2.2. Determination of relative leucocyte mtDNA copy number Total DNA was isolated from peripheral blood leucocytes using PUREGENE1 DNA Purification kit (Gentra, Minnesota, USA). The extracted DNA samples were frozen at 20 8 C until assay without repeated freeze–thawing cycles. The relative mtDNA copy numbers was measured by a real-time PCR and corrected by simultaneous measurement of the nuclear DNA. The forward and reverse primers for nuclear gene, which are complementary to b-actin gene, were 50 -TCACCCACACTGTGCCCATCTACGA-30 and 50 -CAGCGGAACCGCTCATTGCCAATGG-30 . The forward and reverse primers for mtDNA, which are complementary to the sequence of the ND1 gene, were 50 -TGGGTACAATGAGGAGTAGG-30 and 50 -GGAGTAATCCAGGTCGGT-30 . The PCR was performed in a ABI PRISM 7700 Sequence Detection System (PE Biosystems, California, USA), using the SYBR1 GREEN PCR MASTER MIX kit (Applied Biosystems, New Jersey, USA). DNA (10 ng) was mixed with 12.5 ml SYBR1 GREEN PCR MASTER MIX containing 50 nmol of forward and reverse primers, in a final volume of 25 ml. The PCR conditions were 2 min at 50 8C and 10 min at 95 8C, followed by 40 cycles of denaturation at 95 8C for 15 s, annealing at 60 8C for 20 s and primer extension at 72 8C for15 s. The melting curves analysis was provided by the Dissociation Curve Software and took an additional step of
In this study, we recruited 296 subjects, of which 125 patients had T2DM, 101 patients had IFG and 70 were normal subjects (Table 1). Glucose dysregulation status was defined according to the diagnostic criteria of American Diabetic Association. IFG was defined when subjects had a fasting plasma glucose (FPG) value between 100 mg/dl and 125 mg/dl (6.1–6.9 mmol/l), and diabetes as having FPG of at least 126 mg/dl (7 mmol/l). The T2DM patients were recruited from our out-patient clinic.
Table 1 – Comparison among normal, IFG and T2DM groups.
Age (years) Sex (F%) Family history of T2DM (%) BMI (kg/m2) TBARS (mmol/l) Thiol (mmol/l) mtDNA copy number (log) FPG (mg/dl) Insulin (mU/ml) Homa-IR Homa-beta
Normal (n = 70)
IFG (n = 101)
T2DM (n = 125)
P value
47.2 11.6 44.3 (31/70) 4.3 (3/70) 23.6 3.0 1.24 0.51 1.69 1.0 1.77 1.38 92.3 6.8 12.8 6.6 2.89 1.41 151.8 81.8
52.8 11.5 46.5 (47/101) 22.8 (23/101) 25.3 3.3 1.38 0.56 1.60 0.59 2.14 0.97 110.3 6.5 19.5 9.4 5.35 2.65 147.4 73.5
57.2 12.0 44.8 (56/125) 48 (60/125) 25.6 3.5 1.78 0.55 2.07 0.83 3.09 0.74
0.002*, 0.006**, <0.001*** N.S. <0.001 0.001*, N.S.**, <0.001*** N.S.*, <0.001**, <0.001*** N.S.*, <0.001**, 0.002*** 0.016*, <0.001**, <0.001*** <0.001* <0.001* <0.001* N.S.*
P1: P value was adjusted for age, sex and BMI. P value between normal and IFG. ** P value between IFG and T2DM. *** P value between normal and T2DM. *
– – –
P1 value – – – – N.S.*, <0.001**, <0.001*** N.S.*, <0.001**, <0.001*** 0.011*, <0.001**, <0.001*** <0.001* <0.001* <0.001* N.S.*
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20 min after the real-time PCR. The amplified products were denatured and reannealed at different temperature points to detect their specific melting temperature. Samples showing primer-dimmers or unspecific fragments were excluded. The threshold cycle number (Ct) values of the b-actin gene and the mitochondrial ND1 gene were determined for each individual in the same quantitative PCR run. Each measurement was carried out at least three times and normalized in each experiment against a serial dilution of a control DNA sample. Good reproducibility was found both within and between runs. The intraassay coefficients of variation of Ct values were around 2.2% and 3.8% for ND1 and b-actin gene respectively. The interassay coefficients of variation of Ct values were around 4.9% and 5.4% for ND1 and b-actin gene respectively. Ct values can be used as a measure of the input copy number and Ct value differences used to quantify mtDNA copy number relative to the b-actin gene with the following equation: Relative copy number (Rc) = 2DCt [16], where DCt is the Ctbactin CtND1.
2.3.
Oxidative stress
Serum free thiols were determined by directly reacting thiols with 5,5-dithiobis 2-nitro benzoic acid (DTNB) to form 5-thio-2nitrobenzoic acid (TNB). The amount of thiols was calculated from the absorbance determined using the extinction coefficient of TNB (A412 = 13,600 M1 cm1) [17]. The serum thiobarbituric acid reactive substance (TBARS) concentration was assessed based on the method of Ohkawa et al. [18]. After centrifugation the serum samples were stored at 80 8C for future analysis. Results are expressed as micromoles of TBARS per liter. A standards curve of TBARS was obtained by hydrolysis of 1,1,3,3-tetraethoxypropane (TEPP).
2.4.
Statistical analysis
Logarithmic transformation of data was used since the original values of the relative mtDNA copy number in leucocytes showed a non-normal distribution. Results are expressed as mean standard deviation. Group comparisons were performed using the general linear model or Chi-square test. Power analysis revealed that the total sample of 296 subjects achieved 80% power to detect differences among the
means of the mtDNA copy number vs. the alternative of equal means using an F test with a 0.05 significance level. Linear regression and general linear model was used to identify the independent predictors. Relationships among different variables were analyzed by Pearson and Spearman’s correlation and Partial correlation under the control of the factors of age, sex and BMI. P < 0.05 was considered statistically significant.
3.
Results
3.1. The relationship among the metabolic profile, oxidative stress, and the mtDNA content Table 1 shows the metabolic profile, oxidative status and mtDNA content in patients with T2DM or IFG, or in normal subjects. Compared to normal subjects, patients with T2DM or IFG exhibit higher mean BMI values and greater mtDNA copy numbers. The averaged age was also older in these two groups. The T2DM group had significantly higher TBARS and total reduced thiols than the other two groups. After adjusting for age, sex and BMI, we found that the progressive increases in relative leucocyte mtDNA copy number (1.77 1.38 vs. 2.14 0.97 vs. 3.09 0.74, P < 0.001), TBARS (1.24 0.51 mmol/ l vs. 1.38 0.56 mmol/l vs. 1.78 0.55 mmol/l, P < 0.001) and total reduced thiols (1.69 1.0 mmol/l vs. 1.60 0.59 mmol/l vs. 2.07 0.83 mmol/l, P < 0.001) were closely associated with progression in dysregulation of glucose metabolism (normal vs. IFG vs. T2DM). Table 2 summarizes correlations of experimental variables in age, the metabolic profile, oxidative stress, and the relative mtDNA copy number obtained from the three groups. We found that age was significantly correlated with glucose dysregulation (P < 0.001) and FPG (P < 0.001). Glucose dysregulation, BMI, FPG, and HOMA-IR were well correlated with each other (P < 0.001). HOMA-beta was also significantly correlated with HOMA-IR (P < 0.001) and BMI (P < 0.001). Correlation analysis of the metabolic profiles and oxidative status parameters also showed a significant correlation between TBARS and glucose dysregulation (r = 0.369, P < 0.001), FPG (r = 0.164, P = 0.034), HOMA-IR (r = 0.160, P = 0.048) and mtDNA copy number (r = 0.208, P < 0.001). Thiol was only correlated with glucose dysregulation (r = 0.267, P < 0.001).
Table 2 – Main correlations among study variables.
Age BMI FPGa HOMA-IRa HOMA-betaa Thiol TBARS log mtDNA
Age
BMI
FPGa
HOMA-IRa
HOMA-betaa
Thiol
TBARS
1 0.092 0.258** 0.022 0.086 0.019 0.083 0.062
1 0.219** 0.376** 0.348** 0.039 0.081 0.114
1 0.502** 0.092 0.006 0.164* 0.185*
1 0.711** 0.039 0.160* 0.115
1 0.059 0.028 0.041
1 0.114 0.074
1 0.208**
log mtDNA
1
BMI, body mass index; FPG, fasting plasma glucose; HOMA-IR, homeostasis model assessment-insulin resistance; HOMA-beta, homeostasis model assessment-beta cell function; mtDNA: mitochondrial DNA copy number. a FPG, HOMA-IR and HOMA-beta were analyzed only in non-diabetic subjects. * P < 0.05. ** P < 0.005.
diabetes research and clinical practice 83 (2009) 94–99
Table 3 – Correlation of mtDNA copy number with glucose dysregulation status. Before adjustment Adjusted for age Adjusted for age, sex Adjusted for age, sex and BMI Adjusted for age, sex, BMI and TBARS
r = 0.553 r = 0.484 r = 0.484 r = 0.472 r = 0.444
P < 0.001 P < 0.001 P < 0.001 P < 0.001 P < 0.001
Correlation analysis of mtDNA copy number with other parameters revealed a significant positive correlation of mtDNA copy number between TBARS (r = 0.208, P = 0.001) and glucose dysregulation (r = 0.553, P < 0.001) (Table 3). Furthermore, the association between relative mtDNA copy number and glucose dysregulation remained significant after sequentially adjusting for age, sex, BMI and TBARS (r = 0.444, P < 0.001). In the non-diabetic subjects, mtDNA was significantly correlated with FPG (r = 0.185, P = 0.015), but not HOMAIR, after adjusting for age, sex and BMI. Finally, general linear model analysis of all the parameters obtained from the three study groups revealed that the glucose dysregulation (normal vs. IFG, P < 0.001; normal vs. T2DM, P < 0.001) and FPG (P < 0.001) in the non-diabetic subgroup were independent predictors of mtDNA copy number.
3.2. Impact of hyperglycemic treatment on the mtDNA content in T2DM In patients treated with pioglitazone (N = 14), there was a marginally significant increase of mtDNA copy number as compared to patients without ((3.45 0.34 vs. 3.04 0.76, P = 0.05). The difference gained more significance after correction for age, BMI, TBARS and other two kinds of antidiabetic agents (P = 0.036). However, in patients treated with metformin, there was no increase of mtDNA copy number as compared to patients without, even after correction for age, BMI, TBARS and other two kinds of anti-diabetic agents (3.09 0.75 vs. 3.08 0.71, P = 0.901). There was also no difference of mtDNA content between patients treated with insulin secretagogue and those without after correction for confounders (3.07 0.73 vs. 3.18 0.76, P = 0.46). We further analyzed the data in Table 3 by excluding cases taking pioglitazone treatment, the results did not change. It still indicated glucose dysregulation status to be independent predictor of mtDNA copy number.
3.3. Impact of family history of diabetes on the mtDNA content There was a progressive higher rate of family history of diabetes in patients with IFG or T2DM (3 of the 70 normal subjects, 23 of the 101 patients with IFG, and 60 of 125 people with T2DM). The presence of a family history did not influence mtDNA copy number in the T2DM group. Relative leucocyte mtDNA copy number was 3.12 0.61 or 3.05 0.84 in patients with or without a family history respectively (P = 0.60). However, family history of diabetes was associated with mtDNA content in the non-diabetic group. Compared to those without, patients with a family history of diabetes had a greater mtDNA copy number (2.56 0.67 vs. 1.88 1.20, P = 0.006), higher levels of FPG (111.1 9.6 mg/dl vs.
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101.5 10.7 mg/dl, P < 0.001) and greater IR index (HOMA-IR) (5.35 3.41 vs. 4.09 2.26, P = 0.017). The increase of mtDNA content in cases with positive family history remained significant after adjusting for age, sex, BMI and HOMR-IR (P = 0.015), but became insignificant, after adjusting for FPG (P = 0.081).
4.
Discussion
Our results provide evidence to demonstrate a positive association between dysregulation of glucose metabolism and the increase in leucocytes mtDNA copy number. Furthermore, in the non-diabetic group, in which FPG and HOMA-IR were evaluated, only FPG is the independent predictor. The non-diabetic individuals with positive family history had significantly higher mtDNA contents after correcting for age, sex, BMI and HOMR-IR, but this relationship lost significance after correcting for FPG. Collectively, these data suggest that hyperglycemia is more important than IR in regulating leucocytes mtDNA content. The significance of dysfunction of glucose metabolism in mitochondrial abnormality was reported in animal models of diabetes. Using an OVE26 mouse model of type 1 diabetes (T1DM), a model representing hyperglycemia without IR, diabetes-induced damage was found to stimulate cardiac mitochondrial biogenesis [19]. In that study, mitochondria from the diabetic heart showed evidence of reduced respiratory control ratio and increased oxidative stress. It was also found that the mRNA for the mitochondrial transcription factor A, which plays a key role in the regulation of mtDNA replication, was increased by 50%. Other parameters of mitochondrial content, including surface area, number, protein, and DNA, were significantly elevated to compensate for impaired mitochondria function [19]. Impaired mitochondrial function and increase of mitochondrial protein from kidney and heart were also reported in the streptozotocin-induced diabetic animal models [20–22]. In those studies, the changes were partially reversed by insulin treatment, suggesting that hyperglycemia, not IR, was the main cause of mitochondrial damage and biogenesis. Our intriguing results of a lack of association between IR and increase in mtDNA copy number differ to those reported by others. Morino et al. [6] found a reduction of mtDNA density in muscle tissue in the insulin-resistant offspring of parents with T2DM. Decreased mtDNA copy number in skeletal muscle [23] and adipose tissue [24] has also been found in patients with T2DM. The reasons underlying such discrepancies from our observations are not immediately clear. However, those reports focused mostly on mtDNA copy number in the IR-related target organs of skeletal muscle and adipose tissues, whereas we studied the regulation of mtDNA copy number by blood glucose in circulatory leucocytes. It is thus possible that alterations in mtDNA copy number in response to dysregulation of glucose metabolism might be dictated by the cellular responses to insulin. In addition, in contrast to skeletal muscles that are slow replicating cells, leucocytes are cells with rapid replication property. Discrepancy in the effect of glucose metabolism on
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mtDNA copy number may also be attributed to the nature of cell types. Studies of peripheral blood mtDNA content in diabetes have shown interesting and conflicting data [7,8,25]. In Korea, Lee and co-workers [7] found decreased mtDNA content in the insulin-resistant offspring of parents with T2DM. In a later study [25], they also found that this decrease in peripheral blood mtDNA content preceded the onset of diabetes. However, Singh et al. [8], studying the offspring of Caucasian parents with early onset T2DM, found no such decrease in mtDNA content in the offspring of T2DM patients. Singh et al. noted a small proliferation of mtDNA content in their case subjects with no correlation with insulin sensitivity. In our study of 178 non-diabetic Chinese individuals, there was an increase in peripheral blood mtDNA content in those with a positive family history of diabetes. The increase of mtDNA remained significant after correcting for age, sex, BMI and IR index, but it lost its significance after adjusting for FPG. Therefore, our data supports the findings of Singh et al., whose study, like ours, involved a larger sample that that of Lee et al. [7,25]. Although Singh et al. did not report FPG to have an influence on leucocyte mtDNA content, their study sample may have had a lower range of FPG than ours (93.6 11.5 mg/ dl vs. 102.9 11.1 mg/dl). Our study of 296 subjects had a wide range of glucose dysregulation categorized in normal, IFG, and T2DM. Therefore, the effect of hyperglycemia could be more clearly demonstrated. Anti-diabetic agents, including thiazolidinedione and metformin [24,26,27] have been reported to improve mitochondrial function and increase mitochondrial biogenesis. In our series, pioglitazone showed a positive influence on mitochondrial biogenesis while metformin did not. Since the number of patients taking pioglitazone was quite small in this series (N = 14), the overall results were not significantly changed by the medication history. However, the impact of anti-diabetic medication on mitochondrial function deserves further investigation. Previous reports have showed oxidative stress to be one of the factors involved in the increase of mtDNA copy number in human skeletal muscle [28], fibroblast cells [13], lung fibroblast cell line [12] and rat liver cells [29]. Wei and co-workers [14] have also demonstrated that the copy number of mtDNA in leucocytes is increased by oxidative stress in blood circulation. However, these previous studies were of healthy non-diabetic subjects. The association between alternation of leucocyte mtDNA copy number and oxidative stress in hyperglycemic subjects is still not clear. Our results showed an association between glucose dysregulation and oxidative stress as well as increased leucocyte mtDNA copy number. However, the correlation of mtDNA copy number with glucose dysregulation was more significant than with oxidative stress (measured as TBARS alone) in our study. Therefore, a more comprehensive assessment of stress markers is needed to conclude whether there are underlying mechanisms other than oxidative stress that would increase the leucocyte mtDNA content in subjects with hyperglycemia. In our study, the categorization of non-diabetic subjects was based on fasting plasma glucose without undergoing an oral glucose tolerance test (OGTT). It is well recognized that there are two underlying pathophysiologies of diabetes: IR and
insulin secretion which could be measured with different methods. Piche et al. [30] observed that OGTT was a less accurate method to measure IR. Although, it is likely that some of the normal subjects in our study will have impaired glucose tolerance but normal FPG, our conclusion about IR and mtDNA biogenesis may not be biased by the characterization of the subjects.
Acknowledgements This study was supported by grants from Chang Gung University College of Medicine (CMRPG840551 and CMRPG 850261). The authors wish to thank Professor Julie Chan for her kind revision of the manuscript.
Conflict of interest There are no conflicts of interest.
reference
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