Altered circulating mitochondrial DNA and increased inflammation in patients with diabetic retinopathy

Accepted Manuscript Title: Altered circulating mitochondrial DNA and increased inflammation in patients with diabetic retinopathy Author: Afshan N. Malik Chandani K. Parsade Saima Ajaz Roxanne Crosby-Nwaobi Luigi Gnudi Anna Czajka Sobha Sivaprasad PII: DOI: Reference:

S0168-8227(15)00406-4 http://dx.doi.org/doi:10.1016/j.diabres.2015.10.006 DIAB 6481

To appear in:

Diabetes Research and Clinical Practice

Received date: Revised date: Accepted date:

23-3-2015 21-8-2015 2-10-2015

Please cite this article as: A.N. Malik, C.K. Parsade, S. Ajaz, R. Crosby-Nwaobi, L. Gnudi, A. Czajka, S. Sivaprasad, Altered circulating mitochondrial DNA and increased inflammation in patients with diabetic retinopathy, Diabetes Research and Clinical Practice (2015), http://dx.doi.org/10.1016/j.diabres.2015.10.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

 

Title Page: Altered circulating mitochondrial DNA and increased inflammation in patients with diabetic retinopathy

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Mitochondrial DNA changes in diabetic retinopathy

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Afshan N. Malik1, Chandani K. Parsade1, Saima Ajaz1, Roxanne Crosby-Nwaobi2,4, Luigi Gnudi3, Anna Czajka1, Sobha Sivaprasad 2,4 King’s College London, 1Diabetes Research Group, Division of Diabetes and Nutritional Sciences; 2 Laser and Retinal Research Unit, Department of Ophthalmology; 3Division of Cardiovascular Medicine, Faculty of Life Sciences and Medicine;4NIHR Moorfields Biomedical Research Centre

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Corresponding author: Dr Afshan Malik, Diabetes Research Group, Division of Diabetes and Nutritional Sciences, Faculty of Life Sciences and Medicine, King’s College London, Hodgkin Building, London Bridge, London SE1 1UL, UK; phone:+44 (0)20 7848 6271; fax number: +44(0)2078486280; E-mail: [email protected]

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STRUCTURED ABSTRACT Aims: We previously showed that circulating mitochondrial DNA (MtDNA) levels are altered in diabetic nephropathy. The aim of the current study was to determine if circulating MtDNA levels are altered in patients with diabetic retinopathy.

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Methods: Patients with diabetes (n= 220) were studied in a clinical setting using a cross-sectional study design as the following groups: DR-0 (no retinopathy, n= 53), DRm (mild non-proliferative diabetic retinopathy NPDR, n= 98) and DR-s (severe proliferative diabetic retinopathy, n= 69). MtDNA content in peripheral blood DNA was measured as the mitochondrial to nuclear genome ratio using real time qPCR. Circulating cytokines were measured using the luminex assay and MtDNA damage was assessed using PCR. Differences were considered significant at P<0.05.

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Results: Circulating MtDNA values were higher in DR-m compared to DR-0 (P= 0.02) and decreased in DR-s compared to DR-m (P=0.001). These changes remained significant after adjusting for associated parameters. In parallel there were increased levels of circulating cytokines IL-4 (P= 0.005) and TNF-α (P=0.02) in the DR-s group and increased MtDNA damage in DR-m patients compared to DR-0 (P=0.03).

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Conclusions: Our data show that circulating MtDNA levels are independently associated with diabetic retinopathy, showing an increase in DR-m and decrease in DR-s with a parallel increase in MtDNA damage and inflammation. Hyperglycemiainduced changes in MtDNA in early diabetes may contribute to inflammation and progression of diabetic retinopathy. Longitudinal studies should be carried out to determine a potential causality of MtDNA in diabetic retinopathy.

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Key words: mitochondrial DNA, Diabetic retinopathy, inflammation

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INTRODUCTION

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Diabetic retinopathy is a major cause of acquired blindness in the working age population, currently affecting more than 93 million cases [1]. Despite current prevention regimes targeting blood glucose control, blood pressure and lipids, the incidence of diabetic retinopathy remains high and 90% of type 1 and 60% of type 2 diabetes patients are likely to be suffering from the disease by the end of two decades of diagnosed diabetes [2]. There will be an estimated 592 million persons with diabetes globally by the year 2035 [3]. Over half of these will develop retinopathy, representing a nearly insurmountable burden for providing diabetes eye care. Screening programmes are reliant on costly retinal imaging and telemedicine programmes. In addition, type 2 diabetes is increasingly diagnosed at a younger age further increasing the risk of incident diabetic retinopathy and progression of the disease. Although current treatment outcomes of DR are better with the availability of intravitreal therapy, the drug cost and delivery of care adds further burden to the patients and the healthcare system. Therefore, there is a strong need to understand the early molecular mechanisms involved in the development of this disease to design novel diagnostic, preventative and treatment strategies.

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Diabetic retinopathy is asymptomatic in the initial years of diabetes, when irreversible cellular events precede visible microvascular changes, these changes propagate with increased duration of diabetes [4]. Hyperglycemia, a key contributor of damage to the eye, can result in the overproduction of reactive oxygen species (ROS), leading to oxidative stress [5, 6]. Chronic exposure of retinal cells and vasculature to hyperglycemia leads to a vicious cycle in which the oxidative damage persists even after restoration of normoglycemia through unknown mechanisms which have been termed metabolic memory [7].

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In recent years, emerging evidence has highlighted the potential role of mitochondria in the metabolic memory phenomenon as well as in the overproduction of retinal ROS [8, -9]. It has been shown using both animal and cell model systems, that retinal mitochondria can become damaged in diabetes, leading to mitochondrial dysfunction [10]. Specifically, it has been shown using cultured human retinal cells that hyperglycemia can damage mitochondrial DNA (MtDNA) and this has been proposed as an early event contributing to the degeneration of retinal capillary cells [10, 11]. Similar mechanisms have been proposed from animal model work [12]. Despite increasing evidence of mitochondrial dysfunction being a player in the development of diabetic retinopathy, so far there have been no clinical human studies supporting this view. Furthermore it is unclear how potential damage to MtDNA in patients with retinopathy could be assessed using a non-invasive methodology. We have previously reported alterations in circulating MtDNA in diabetic patients with nephropathy and have suggested that these changes resemble systemic diabetes induced changes in the body [13]. MtDNA content measured as mitochondrial genome to nuclear genome ratio (Mt/N) could be a biomarker of mitochondrial dysfunction as MtDNA copy numbers correlate with mitochondrial activity [14].Chronic hyperglycemia is the central initiating factor for diabetes specific microvascular disease in the retina 3   

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and renal glomerulus, both complications share common pathophysiologic features and risk factors [15]. Furthermore, MtDNA has been shown to possess inflammatory properties as it resembles bacterial DNA [16, 17]. Inflammatory processes are regarded as continuous components of all aspects of diabetic retinopathy [18] and it is widely accepted that increases in the production of pro-inflammatory cytokines are hallmarks of inflammation in retina although a cause-effect relationship remains to be validated [19].

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Therefore we proposed that it may be possible to detect systemic mitochondrial dysfunction in peripheral blood samples of patients with diabetic retinopathy by assessing the MtDNA quantity and quality. The aims of this study were to investigate whether the level and integrity of circulating MtDNA is altered in patients with varying severity of diabetic retinopathy and to explore its relation to systemic inflammatory markers.

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MATERIALS AND METHODS SUBJECTS

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Patients were recruited with written informed consent from the Diabetes Clinic , King’s College Hospital under NHS Research Ethics Committee approval (REC; ref number08/H0808/228) and from Guy’s and St Thomas’ hospital clinics under ethical approval from the regional Research Ethics Committee (REC; ref number 07/H0806/120). The study adhered to the Ethical Principles for Medical Research Involving Human Subjects, World Medical Association Declaration of Helsinki. Type 1 diabetes and type 2 diabetes were defined as follows: type 1 diabetes, onset before age 35, insulin therapy within 6 months of diagnosis and no breaks in insulin therapy >6 months; type 2 diabetes, onset after age 35, controlled by diet or established oral hypoglycemic treatment and/or insulin. Of the 220 patients included in the study, 126 were Caucasian, 58 were African, 13 were Asian and 4 were of mixed ethnicity (African and Caucasian). The ethnicity of the remaining 19 patients was missing. In order to identify any associations between circulating MtDNA content and diabetic retinopathy, we analysed the patients as the following four groups: The DR-0 group were defined as patients with long duration of diabetes (>20 years for type 1 diabetes, >5 years for type 2 diabetes) with no evidence of retinopathy (n=53). The DR group were patients with evidence of retinopathy (n=167), We further sub-divided the DR group into two groups based on the severity of retinopathy; these groupings were selected to identify any differences in risk parameter associations between early stages and later stages of retinopathy. The DR-m were patients with mild NPDR (n=98), and DR-s were patients with severe NPDR and PDR (n=69). 4   

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Grading of diabetic retinopathy

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The patients underwent 2-field digital photographs of each eye, one centred on the optic disc and the other on the macula after dilation of the pupils. Photographs were graded in a standardised manner, and DR severity was classified according to the Early Treatment Diabetic Retinopathy Study (ETDRS) severity system [20]. Accordingly, the following categories were created, based on the more severely involved eye: no DR (DR-0) defined as ETDRS <20, mild non-proliferative diabetic retinopathy, NPDR (DRm) defined as ETDRS 35-43, severe NPDR and proliferative diabetic retinopathy, PDR (DR-s) defined as ETDRS 47 and above. Assessment of other risk parameters

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Metabolic status (HbA1c) and lipid levels were assessed by the hospital clinical lab services using standardised assays. The Jaffe assay was used to measure creatinine . Normoalbuminuria was defined as albumin to creatinine ratio (ACR) <2.5 mg/mmol for men, (albumin excretion rate (AER)<25 mg/day) and ACR <3.5 mg/mmol for women (AER <35 mg/day), albuminuria was defined as ACR >2.5 mg/mmol for men (AER >25 mg/day) and >3.5 mg/mmol for women (AER >35 mg/day). Glomerular Filtration Rate (GFR) was assessed using the Modification of Diet in Renal Disease (MDRD) formula [21]. BMI, diastolic blood pressure and systolic blood pressure were recorded during the visit to the clinic at the time of blood sampling.

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Determination of circulating mitochondrial DNA content

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Whole blood/ buffy coat was obtained and frozen within 2h of collection at −20°C and transferred to -80°C within 24 hours. Samples were thawed on ice, and mixed thoroughly before use. Genomic DNA was prepared from 100µl of frozen sample using the DNeasy Blood and Tissue Kit (Qiagen) and kept at 4ᵒC for the duration of this study. DNA samples in a total volume of 100µl were fragmented by sonication for 10min using a Bath Sonicator (Kerry, Pulsa-tron 55). The concentration of DNA was determined using the Nanodrop (Labtech International) and adjusted to 10ng/µl. Realtime quantitative PCR (qPCR) to quantify Mt/N was performed using primers specific to a unique region of the mitochondrial genome (hmitoF3, hmitoR3) and to a unique section of the nuclear genome, β-2-Microglobulin (hB2MF1, hB2MR1) [22, 23]. All qPCR experiments adhered to MIQE guidelines [24] and were conducted in the Roche LC480 LightCycler using Quantifast SYBR green (Qiagen).   The amplification efficiencies of the target (hMito3) and reference (hB2M) sequences displayed >99% efficiencies. Relative quantification (also known as the delta delta Ct method) was used as follows: 5 type 1 diabetes patients with no complications were used as calibrators. The calibrators had a mean age of 66 ± 5 years, mean diabetes duration of 40 ± 13 years and no evidence of retinopathy. ∆Ct for all samples was calculated by subtracting the average hB2M Ct value from the average hMito Ct value ( ∆Ct = h Mito Ct – B2M Ct). The mean ∆Ct value for the calibrator group was calculated. ∆∆Ct for each sample was calculated by subtracting the ∆Ct of the calibrators from the 5   

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mean ∆Ct of the sample (i.e. ∆∆Ct = ∆Ct of sample - ∆Ct of calibrators). MtDNA content was calculated as relative values using the formula 2 [2, -∆∆Ct] [23,25] Mitochondrial DNA damage

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MtDNA damage was assessed using a modification of the method described by Furda et al., [26]. 15 ng of genomic DNA was used to amplify an 8.9kb long fragment of the mitochondrial genome (primers 14841 and 5999) [27] using elongase polymerase (Invitrogen) and a 127bp fragment was amplified using primers hmitoF3 and hmitoR3 [22] and DreamTaq Green DNA Polymerase (Thermo Fisher Scientific) under previously described PCR conditions [27]. PCR products were electrophoresed on a 1.5% agarose gel for the 127bp fragment and a 1% agarose gel for the 8.9kb fragment prior to densitometry. Resultant values were normalised for the gel by dividing with the densitometry values of a control DNA sample which was run on every gel, and then expressed as large fragment relative to the small fragment.

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Serum inflammatory markers

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20ml of venous blood, collected in BD Vacutainer SST tubes, was centrifuged (3000rpm, 15min), serum was decanted and stored (-80oC). IL-1α, IL-1B, IL-1RA, IL-4, IL-6 and IL-10 cytokine levels were measured by Luminex bead analyte assay using Milliplex MAP Kit according to the instructions (Millipore (UK) Ltd. Watford, UK). Statistical analysis

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Analysis was performed using GraphPad and IBM SPSS. The effect size (Cohen’s d) for this study was 0.56, the desired statistical power was 0.9 (i.e 90% confidence interval) and probability level was 0.05. The minimum total sample size (two-tailed hypothesis) was determined to be 138 and the minimum sample size per group size (two-tailed hypothesis) was 69. Data distribution was determined using the Kolmogorov-Smirnov test and histograms in SPSS and parametric /non-parametric tests were used on raw or log transformed data.Data were stated either as mean ± standard deviation (SD) or as median and range. P values < 0.05 were considered significant and P values < 0.001 were regarded as highly significant. For parametric analysis, groups were compared using Independent t-test (2 groups) or one-way ANOVA with post-hoc Tukey’s multiple comparison test (>2 groups). For nonparametric analysis, groups were compared using Mann-Whitney (2 groups) or Kruskal Wallis with Dunn’s post hoc test with Bonferroni correction (>2groups).Chi-squared test was used to compare categorical variables (type of diabetes, gender). Binomial logistic regression was used to test the effect of MtDNA and other associated covariates on the outcome of diabetic retinopathy.

RESULTS 1. Patient groupings

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The 220 diabetic patients used in this cross-sectional study comprised both type 1 diabetes (n=54) and type 2 diabetes (n=166), aged between 26 to 87 years old (mean ± SD of 62 ± 14) and had been diagnosed with diabetes for between 1 to 64 years (mean ± SD of 17 ± 11). Besides their retinopathy status, information about a number of demographic (diabetes, age, duration, gender, BMI) and clinical variables was obtained. The clinical variables were metabolic control (HbA1c), renal function (eGFR, ACR), hemodynamic control (systolic BP, diastolic BP), and lipid profile (LDL, HDL, cholesterol). Their BMI ranged between 18.1 and 82.7 (mean ± SD of 30.8 ± 8.3) and HbA1c ranged between 5.3 to 13.1% (34 to120 mmol/mol) with a mean ± SD of 7.8 ± 1.5% (62 ± 16mmol/mol).

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All subjects were studied as either DR-0 (no retinopathy) versus DR (retinopathy both mild and severe), or as Dr-0, DR-m (mild diabetic retinopathy) and DR-s (severe diabetic retinopathy), groupings were made as described above (materials and methods).

2. Association of parameters for risk of development of Diabetic Retinopathy

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The DR-0 patients (n=53) were compared with DR patients (n=167) to identify if any of the demographic/clinical variables showed association with the development of retinopathy (Table 1, columns 2 and 3). Amongst the demographic variables, DR patients had a longer duration of diabetes (P=0.01), although type of diabetes, age and sex were not statistically different between the two groups (P>0.05). In terms of clinical variables, DR patients had elevated HbA1c (P=0.04) but did not differ in terms of BMI, renal function, blood pressure, and lipids (P>0.05). These data suggest that as previously reported [ 28. 29] longer duration of diabetes and poor metabolic control measured as HbA1c are associated with risk of developing DR in our patient population, validating our cohort.

3. Changes in parameters in early stages of diabetic retinopathy The DR-0 patients were compared with the DR-m group to identify if any of the demographic/clinical variables showed association with early stages of DR (Table 1, columns 2 and 4). The DR-m patients were younger (P=0.02), had a longer duration of diabetes (P=0.04), but showed no differences to the DR-0 group in terms of type of diabetes, gender or BMI (P>0.05).DR-m had increased eGFR (P=0.01) but there was no change in ACR, HbA1c, blood pressure and lipids profile compared to DR-0 (P>0.05). These data show, as in previous findings [30] that age, duration of diabetes, increased eGFR, and increased HbA1c may be associated with early changes in DR, and support the view that our cohort shows similar characteristics to larger studies of diabetic retinopathy. 4. Association of risk parameters in the progression of diabetic retinopathy

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As diabetic retinopathy follows a progressive path and DR-m represents patients at an earlier stage of disease than DR-s, we compared parameters between DR-m and DR-s to see if we could establish any parallel changes in risk markers alongside progression of DR-m to DR-s (Table 1, columns 4 and 5). There were more cases of Type 2 diabetes and more males in the DR-s group compared to the DR-m groupThe DR-s group had higher HbA1c levels (P<0.05), reduced eGFR (P<0.001) and increased systolic blood pressure (P=0.03).There were no significant differences between the two groups in terms of ACR, diastolic blood pressure and lipids (P>0.05). After binary regression analysis, Type of diabetes, HbA1c, eGFR and MtDNA content remained independently associated with DR-s (Supplementary Table 1) 5. Circulating Mitochondrial DNA copy number

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Absolute MtDNA copy number ranged between 21-365 copies per nuclear genome in the whole data set (mean ± SD of 88 ± 65, n=220). The relative MtDNA values normalised to a calibration cohort [24] ranged from1.3 to 2.6 (mean ± SD of 1.9 ±0.2) with the frequency distribution showing a skewed pattern. Log transformation did not result in a normal distribution for the relative values; therefore for group comparison purposes we used non-parametric analysis on untransformed relative values of MtDNA

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6. Circulating mitochondrial DNA levels are altered at different stages of diabetic retinopathy

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Comparison between the three groups showed that relative MtDNA values differ highly significantly. MtDNA levels were higher in DR-m (mean ± SD of 2.22±1.9) compared to DR-0 (mean ± SD of 1.96±1.5), (P=0.02) and decreased in DR-s (mean ± SD of 1.65±0.95) compared to DR-m, (P=0.001) suggesting that MtDNA content increases in early or mild retinopathy and decreases in moderate and severe retinopathy (Figure 1).

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As the DR-m group were younger, had a longer duration of diabetes and a higher eGFR than the DR-0 group (P<0.05, Table 1), it is possible that one of these factors contributes to the increased MtDNA seen in DR-m versus DR-0. A binary logistic regression analysis was performed with DR-m as the dependent variable and MtDNA, age, eGFR and duration of diabetes as predictor variables (Supplementary Table 1). MtDNA continued to show a significant (P=0.004) positive (Exp(B)=7.43) association with DR-m, eGFR also showed a slightly positive association with DR-m (P=0.01, Exp(B)= 1.03). A positive association (Exp(B) = 1.07) was also found with the duration of diabetes (P=0.045). However age was no longer significantly associated with DR-m after the regression analysis. As the DR-s group has shown significant difference from the DR-m group in various others parameters (Table 1), we wished to determine if correcting for any of these differences would affect the observation that MtDNA levels are reduced in DR-s. The decreased MtDNA in DR-s compared to DR-m remained highly associated (P= 0.000) even after adjusting for all other associated parameters (type of diabetes, age, duration, HbA1c, eGFR, gender and SBP). Age, HbA1c. gender and systolic blood pressure were no longer associated after adjustments whereas type of diabetes, reduced eGFR and diabetes duration remained independently associated. Therefore the binary 8   

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regression analysis shows that after correcting for all associated parameters, both diabetes duration and increased MtDNA in DR-m patients and diabetes duration and decreased MtDNA in DR-s patients show the highest effect size compared to all other risk markers (Supplementary Table 1). 7. Circulating Mitochondrial DNA is damaged in patients with diabetic retinopathy

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The above data suggests that the amount of circulating MtDNA is altered during the development and progression of diabetic retinopathy however it does not provide any information on the integrity of the MtDNA. As oxidative stress is known to be associated with diabetic retinopathy [7], and others have shown that retinal MtDNA is damaged in experimental animal and cell models [8,11, 31], we wished to examine whether circulating MtDNA in our cohort shows any signs of damage. MtDNA damage was assessed in a sub group of patients, using a PCR based method where reduced amplification is indicative of damage to the MtDNA [26].

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We found that both DR-m (mean ± SD 54±17, n=7) and DR-s (mean 63±20, n=8) showed reduced amplification compared to DR-0 (mean ± SD 81±20, n=8) however this difference was only significant (P= 0.03) for the DR-m group. Combining all patients with retinopathy continued to show more MtDNA damage in the DR (mean ± SD 58.6±18.6, n=15) compared to DR-0 patients (mean ± SD 81.4±20, n=8), P= 0.01 (Figure 2). 8. Increased inflammation in patients with diabetic retinopathy

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In order to determine if there was any evidence of inflammation in patients with retinopathy, samples from a subset of 74 patients were used to measure circulating cytokines. In total we had serum samples from 19 DR-0 and 55 DR patients, which comprised of 24 DR-m and 31 DR-s patients (Supplementary Table 2).

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Comparison of the control versus DR group showed that levels of IL-10 were higher in the DR group but this was not quite significant (P= 0.06). No differences were seen when the DR-m and DR-s groups were analysed separately for IL-1A, IL-1RA, IL-1B, IL-6, and IL-10 (P>0.05). TNF-α was detected in all of the 74 patients examined, the values ranged between 1.6 and 59.6 pg/ml (mean ± SD of 14.9 ± 10). Comparison of log transformed values showed that TNF-α levels were significantly higher in the DR-s group compared to DR0 patients (P=0.02) and those with DR-m (P= 0.008) suggesting that there is enhanced inflammation in DR-s (Figure 3). IL-4 was detected in 28 patients out of 74 representing 12 controls and 16 DR patients, 8 in the DR-m group and 8 in the DR-s group. The IL-4 levels ranged between 0 and 250 pg/ml with a mean ± SD of 16.3 ± 42.2. Comparison of the log transformed values of IL-4 in patients where this cytokine was detected showed that there was a significant increase in IL-4 in DR-s compared to patients with no retinopathy (P=0.005). IL-4 was also higher in DR-s compared to DR-m but this was not significant (P=0.07).

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No significant correlation was found between TNF-α and Mt/N as well as between IL-4 and Mt/N using Pearson’s correlation. DISCUSSION

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In recent years, hyperglycemia mediated mitochondrial dysfunction has emerged as a key player involved in the early stages of retinal damage which may contribute to the development of diabetes induced blindness [32]. However, the majority of the data supporting this view are derived from studies conducted in animal models or cultured retinal cells from humans and rodents [8,11, 31]. Some of these studies have provided compelling evidence of MtDNA damage as a key step leading to mitochondrial dysfunction [32, 33]. Our study makes an important contribution by providing evidence of mitochondrial dysfunction directly in clinical samples from patients. We show that the severity of retinopathy is associated with circulating MtDNA content, with an increase in circulating MtDNA in early disease (DR-m) and a significant decline in late disease (DRs). We also show that patients with retinopathy show signs of damage to MtDNA as well as increased circulating IL-4 and TNF-ɑ indicating increased inflammation in patients with DR. Our data support the hypothesis that hyperglycemia-induced quantitative and qualitative changes to MtDNA, may contribute to the development and progression of retinopathy.

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In a healthy cell, MtDNA is found outside of the nuclear genome in the mitochondria located close to the electron transport chain within mitochondria, where it is used as a template to transcribe numerous mRNAs required for correct mitochondrial functioning [34]. Unlike nuclear DNA, MtDNA is not protected by histones but is found associated with the protein TFAM and arranged as nucleoids with each mitochondrion often containing numerous MtDNA genome [35] and each cell containing numerous mitochondria depending on its bioenergetics requirements. The location of MtDNA makes it particularly susceptible to oxidative stress damage, resulting in deletions, mutations and oxidation [14] and often leading to a situation described as heteroplasmy, where the same cell can harbour both intact and damaged MtDNA molecules [36]. The consequences of damaged MtDNA could affect cells in two ways. Firstly, if the mutant load exceeds a certain threshold then the cell may not be able to maintain a healthy electron transport chain resulting in lack of energy for basic cellular processes and repair. The retina, a tissue rich in polyunsaturated fatty acid, uses more oxygen and glucose oxidation than any other tissue in the body, and therefore is likely to have a high bioenergetics demand [37] and could be particularly susceptible to bioenergetic deficit. A second consequence could be that the damaged MtDNA leaves the mitochondria and is not removed or destroyed from cells and ends up either in the cytoplasm of the cell or is leaked into circulation. This “out of place” MtDNA can activate toll like receptor because it resembles bacterial DNA and is largely unmethylated unlike nuclear DNA (16). TLR9 activation by bacterial or MtDNA results in an inflammatory cascade via NFKB and blocking degradation of MtDNA can lead to TLR9 mediated inflammation resulting in heart failure [17]. Damaged MtDNA in the cytosol can also result in activation of an innate antiviral response [38]. We used peripheral blood from patients with diabetes to assess whether circulating MtDNA was different in patients with diabetic retinopathy. Peripheral blood cells have 10   

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been used widely to evaluate biomarkers for many diseases [39-41]. Circulating erythrocytes have also been used as bio-indicators of the vascular environment, with the redox state of erythrocytes being linked to retinopathy status [42]. Systemic decrease in MtDNA and mitochondrial dysfunction has also been shown in oxidative skeletal muscle in a mouse model of obesity, db/db mice [43] suggesting that systemic MtDNA contributes selectively to organ damage. However, in the current study, rather than suggesting that circulating cells are surrogate for changes seen in the retina, we propose that the observed changes in circulating MtDNA are systemic and would predict that similar changes would be present in other cells and organs, including the retina. Based on our data we postulate that in early diabetes certain retinal cell types may show increased MtDNA content in response to oxidative stress, and in late diabetic retinopathy MtDNA content would decline. In parallel, there may be accumulation of mutations in the MtDNA due to its lack of histones and close proximity to the electron transport chain, and persistence of damaged MtDNA may lead to an inflammatory response as well as bioenergetic deficit. There is evidence from model systems of all these changes in the diabetic retina. The presence of damaged MtDNA in retinal tissue has been shown in animal models. For example mitochondria become dysfunctional in the retina and its capillary cells [44] and MtDNA becomes damaged and there is a hampered MtDNA repair system in the diabetic retina [8]. Selective mitochondrial oxidative stress and MtDNA damage have been observed in the early phase of other ocular conditions such as experimental autoimmune uveitis before inflammatory cell infiltration in the retina and uvea [45]. Such oxidative damage in the mitochondria may be the initial event leading to DR. Activation of NF-κB was shown to be induced by diabetes in retinal pericytes [46] and in diabetic rat retinas [47] and it was proposed that this activation may be part of the apoptotic response. We suggest that NF-κB may be directly activated by damaged MtDNA which has failed to be removed by mitophagy. This could then lead to chronic inflammation which is often a part of diabetic retinopathy [19] and could explain the increased circulating TNF alpha that we and others [48] have reported. It has been postulated that the blood retinal barrier is compromised in diabetes [49] and therefore it is possible that cell free MtDNA or cytokines could enter or leave the retinal space. Among circulating cytokines, TNF-α in particular causes tissue damage by generating ROS [50]. Our study has some limitations. The blood samples in our study represent a single time point and it would be of value to take samples at multiple points to determine if there is any prognostic value. Although animal studies have illustrated mitochondrial dysfunction and MtDNA mutations in the diabetic retina, there are no studies looking at the time course of changes in circulating MtDNA in animal models, these could be employed to understand the relationship between progression of retinopathy and MtDNA changes. There is a possibility that the association we report here reflects an association with diabetic nephropathy which we have previously reported [13]. However, in our cohort 20% of Dr-m and 20% of DR-s patients had both diabetic nephropathy and diabetic retinopathy, suggesting that any influence may be cancelled out by equal representation of nephropathy in the groups, furthermore there was no correlation between MtDNA and eGFR. Currently no methods exist to identify the source of the circulating MtDNA, therefore we are unable to determine if some of the MtDNA in circulation is leaking from retinal cells. Whilst statistically significant , the 11   

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levels of circulating MtDNA in individuals overlap in the groups making it difficult to use MtDNA levels alone as a diagnostic tool. A larger sample size is required to fully confirm and extend our observations, nevertheless as the first study showing a link between MtDNA, inflammation and DR this work makes an important contribution towards deciphering the mechanisms linking mitochondrial function and MtDNA changes in diabetic retinopathy.

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In summary we show evidence of altered MtDNA in circulation in diabetic retinopathy patients and that MtDNA levels are an independent risk factor for disease progression. We postulate that the increase in circulating MtDNA in DR-m may be a consequence of hyperglycemia -induced ROS mediated damage to MtDNA. Damaged out of place MtDNA may directly contribute to increased inflammation in DR-s as it resembles bacterial DNA. If damaged MtDNA contributes to the progression of retinopathy then design of strategies for removal of damaged circulating MtDNA could provide a novel therapeutic target for treatment/prevention of diabetic retinopathy progression.

Acknowledgments

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a. Funding/ Support

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b. Financial Disclosures

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The study was partly funded by a Kings Initiative Grant 2009, SS and RCN were partly funded by NIHR Moorfields Biomedical Research Centre, AC and SA were supported by KCL PhD scholarships.

No financial disclosures.

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c. Other Acknowledgments None.

Conflict of interest

We confirm that all the authors have read and approved the manuscript and declare that they have no conflict of interest.

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REFERENCES 1. Yau JW, Rogers SL, Kawasaki R, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. Mar 2012;35(3):556-564.

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2. Klein R, Klein BE, Moss SE, Davis MD, DeMets DL. The Wisconsin epidemiologic study of diabetic retinopathy. III. Prevalence and risk of diabetic retinopathy when age at diagnosis is 30 or more years. Arch Ophthalmol. Apr 1984;102(4):527-532.

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3. Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2013. Diabetes Research and Clinical Practice and projections for 2035. 2014; 103(2):137-149.

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4. Antonetti DA, Barber AJ, Bronson SK, et al. Diabetic retinopathy: seeing beyond glucose-induced microvascular disease. Diabetes. Sep 2006;55(9):2401-2411.

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5. Giacco F, Brownlee M. Oxidative stress and diabetic complications. Circ Res. Oct 29 2010;107(9):1058-1070.

M

6. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. Sep 30 1993;329(14):977-986.

d

7. Kowluru RA, Chan PS. Oxidative stress and diabetic retinopathy. Exp Diabetes Res. 2007;2007:43603.

Ac ce p

te

8. Madsen-Bouterse SA, Zhong Q, Mohammad G, Ho YS, Kowluru RA. Oxidative damage of mitochondrial DNA in diabetes and its protection by manganese superoxide dismutase. Free Radic Res. Mar 2010;44(3):313-321. 9. Chan PS1, Kanwar M, Kowluru RA. Resistance of retinal inflammatory mediators to suppress after reinstitution of good glycemic control: novel mechanism for metabolic memory. J Diabetes Complications. 2010 Jan-Feb;24(1):55-63. 10. Xie L, Zhu X, Hu Y, et al. Mitochondrial DNA oxidative damage triggering mitochondrial dysfunction and apoptosis in high glucose-induced HRECs. Invest Ophthalmol Vis Sci. Sep 2008;49(9):4203-4209. 11. Madsen-Bouterse SA, Mohammad G, Kanwar M, Kowluru RA. Role of mitochondrial DNA damage in the development of diabetic retinopathy, and the metabolic memory phenomenon associated with its progression. Antioxid Redox Signal. Sep 15 2010;13(6):797-805. 12. Kanwar M, Chan PS, Kern TS, Kowluru RA. Oxidative damage in the retinal mitochondria of diabetic mice: possible protection by superoxide dismutase. Invest Ophthalmol Vis Sci. 2007 Aug;48(8):3805-11

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  13. Czajka A, Ajaz S, Gnudi L, et al. Altered mitochondrial function, mitochondrial DNA and reduced metabolic flexibility in patients with diabetic nephropathy. 2015 (in Press) 14. Malik AN, Czajka A. Is mitochondrial DNA content a potential biomarker of mitochondrial dysfunction? Mitochondrion. Oct 22 2012.

ip t

15. Jawa A, Kcomt J, Fonseca VA. Diabetic nephropathy and retinopathy. Med Clin North Am. Jul 2004;88(4):1001-1036, xi.

cr

16. Collins LV, Hajizadeh S, Holme E, Jonsson IM, Tarkowski A. Endogenously oxidized mitochondrial DNA induces in vivo and in vitro inflammatory responses. J Leukoc Biol. Jun 2004;75(6):995-1000.

us

17. Oka T, Hikoso S, Yamaguchi O, et al. Mitochondrial DNA that escapes from autophagy causes inflammation and heart failure. Nature. May 10 2012;485(7397):251-255.

an

18. Adamis AP. Is diabetic retinopathy an inflammatory disease? Br J Ophthalmol. Apr 2002;86(4):363-365.

M

19. Tang J, Kern TS. Inflammation in diabetic retinopathy. Prog Retin Eye Res. Sep 2011;30(5):343-358.

te

d

20. Grading diabetic retinopathy from stereoscopic color fundus photographs--an extension of the modified Airlie House classification. ETDRS report number 10. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology. May 1991;98(5 Suppl):786-806.

Ac ce p

21. Stoves J, Lindley EJ, Barnfield MC, Burniston MT, Newstead CG. MDRD equation estimates of glomerular filtration rate in potential living kidney donors and renal transplant recipients with impaired graft function. Nephrol Dial Transplant. Nov 2002;17(11):2036-2037. 22. Malik AN, Shahni R, Rodriguez-de-Ledesma A, Laftah A, Cunningham P. Mitochondrial DNA as a non-invasive biomarker: accurate quantification using real time quantitative PCR without co-amplification of pseudogenes and dilution bias. Biochem Biophys Res Commun. Aug 19 2011;412(1):1-7. 23. Ajaz S, Czajka A, Malik AN. Accurate Measurement of Circulating Mitochondrial DNA Content from Human Blood Samples Using Real-Time Quantitative PCR. Methods Mol Biol. 2014; 1264. 24. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clinical Chemistry. Apr 2009; 55(4):611-622. 25. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. Dec 2001;25(4):402-408. 15   

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  26. Furda A, Santos JH, Meyer JN, Van Houten B. Quantitative PCR-based measurement of nuclear and mitochondrial DNA damage and repair in mammalian cells. Methods Mol Biol. 2014;1105:419-437.

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27. Hunter SE, Jung D, Di Giulio RT, Meyer JN. The QPCR assay for analysis of mitochondrial DNA damage, repair, and relative copy number. Methods. Aug 2010;51(4):444-451.

cr

28. Effect of intensive diabetes treatment on the development and progression of long-term complications in adolescents with insulin-dependent diabetes mellitus: Diabetes Control and Complications Trial. Diabetes Control and Complications Trial Research Group. J Pediatr. Aug 1994;125(2):177-188.

an

us

29. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. Sep 12 1998;352(9131):837-853.

M

30. Chen YH, Chen HS, Tarng DC. More impact of microalbuminuria on retinopathy than moderately reduced GFR among type 2 diabetic patients. Diabetes Care. Apr 2012;35(4):803-808.

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31. Tewari S, Santos JM, Kowluru RA. Damaged mitochondrial DNA replication system and the development of diabetic retinopathy. Antioxid Redox Signal. Aug 1 2012;17(3):492-504.

Ac ce p

te

32. Santos JM, Mishra M, Kowluru RA. Posttranslational modification of mitochondrial transcription factor A in impaired mitochondria biogenesis: implications in diabetic retinopathy and metabolic memory phenomenon. Exp Eye Res. Apr 2014;121:168177. 33. Santos JM, Tewari S, Lin JY, Kowluru RA. Interrelationship between activation of matrix metalloproteinases and mitochondrial dysfunction in the development of diabetic retinopathy. Biochem Biophys Res Commun. Sep 6 2013;438(4):760-764. 34. Scheffler IE. Drug-Induced Mitochondria Dysfunction. Basic Molecular Biology of Mitochondrial Replication. In: Dykens, J.A., Will, Y. (Eds.),: John Willey & Sons. Inc., New Yersey; 2008. 35. Falkenberg M, Larsson NG, Gustafsson CM. DNA replication and transcription in mammalian mitochondria. Annu Rev Biochem. 2007;76:679-699. 36. Bannwarth S, Procaccio V, Paquis-Flucklinger V. Rapid identification of unknown heteroplasmic mutations across the entire human mitochondrial genome with mismatch-specific Surveyor Nuclease. Nat Protoc. 2006;1(4):2037-2047. 37. Wong-Riley M T.T. Energy metabolism of the visual system. Eye and Brain. July 2010;2:99-116. 16   

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  38. West AP, Khoury-Hanold W, Staron M, et al. Mitochondrial DNA stress primes the antiviral innate immune response. Nature. Feb 2 2015. 39. Mohr S, Liew CC. The peripheral-blood transcriptome: new insights into disease and risk assessment. Trends in molecular medicine. Oct 2007;13(10):422-432.

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40. Lunnon K, Ibrahim Z, Proitsi P, et al. Mitochondrial dysfunction and immune activation are detectable in early Alzheimer's disease blood. J Alzheimers Dis. 2012;30(3):685710.

us

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41. Rudkowska I, Raymond C, Ponton A, et al. Validation of the use of peripheral blood mononuclear cells as surrogate model for skeletal muscle tissue in nutrigenomic studies. Omics. Jan-Feb 2011;15(1-2):1-7.

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42. Choudhuri S, Mandal LK, Paine SK, et al. Role of hyperglycemia-mediated erythrocyte redox state alteration in the development of diabetic retinopathy. Retina. Jan 2013;33(1):207-216.

M

43. Holmstrom MH, Iglesias-Gutierrez E, Zierath JR, Garcia-Roves PM. Tissue-specific control of mitochondrial respiration in obesity-related insulin resistance and diabetes. Am J Physiol Endocrinol Metab. Mar 15 2012;302(6):E731-739.

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44. Kanwar M, Chan PS, Kern TS, Kowluru RA. Oxidative damage in the retinal mitochondria of diabetic mice: possible protection by superoxide dismutase. Invest Ophthalmol Vis Sci. Aug 2007;48(8):3805-3811.

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45. Khurana RN, Parikh JG, Saraswathy S, Wu GS, Rao NA. Mitochondrial oxidative DNA damage in experimental autoimmune uveitis. Invest Ophthalmol Vis Sci. Aug 2008;49(8):3299-3304. 46. Romeo G, Liu WH, Asnaghi V, Kern TS, Lorenzi M. Activation of nuclear factor-kappaB induced by diabetes and high glucose regulates a proapoptotic program in retinal pericytes. Diabetes. Jul 2002;51(7):2241-2248. 47. Kowluru RA, Koppolu P, Chakrabarti S, Chen S. Diabetes-induced activation of nuclear transcriptional factor in the retina, and its inhibition by antioxidants. Free Radic Res. Nov 2003;37(11):1169-1180. 48. Preciado-Puga MC, Malacara JM, Fajardo-Araujo ME, et al. Markers of the progression of complications in patients with type 2 diabetes: a one-year longitudinal study. Exp Clin Endocrinol Diabetes. Sep 2014;122(8):484-490. 49. Cunha-Vaz JG. Studies on the pathophysiology of diabetic retinopathy. The bloodretinal barrier in diabetes. Diabetes. May 1983;32 Suppl 2:20-27. 50. Sakon S, Xue X, Takekawa M, et al. NF-kappaB inhibits TNF-induced accumulation of ROS that mediate prolonged MAPK activation and necrotic cell death. Embo J. Aug 1 2003;22(15):3898-3909. 17   

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FIGURES

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Figure 1: Circulating Mitochondrial DNA is increased in mild retinopathy and decreased in severe retinopathy

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Total DNA was isolated from peripheral blood of diabetes patients DR-0 (no retinopathy, n=53), mild non-proliferative diabetic retinopathy (DR-m, n=98) and severe non-proliferative retinopathy and proliferative retinopathy (DR-s, n=69), After pretreatment of DNA 28, Mitochondrial DNA (MtDNA) content was quantified using real time qPCR as the mitochondrial DNA to nuclear DNA ratio. Data, given as relative values according to the δδCTmethod, are shown as box plots with whiskers showing median, quartiles and range which were analysed using non-parametric Kruskal –Wallis test with Dunn’s multiple comparison test, where *, P < 0.05 and **, P <0.01.

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Figure 2: Increased MtDNA damage in diabetic retinopathy as compared to control group.

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Mitochondrial DNA (MtDNA) damage was assessed using a PCR based method by quantifying the amplification of a large fragment (8.9kb) relative to a small fragment (0.127kb) of the mitochondrial genome 30. Total DNA isolated from blood samples of healthy controls (n=3), diabetic patients with no retinopathy, DR-0 (n=8), and diabetic patients with retinopathy, DR (n=15 of which 7 were had mild retinopathy (DR-m) and 8 were DR-s). Resulting bands were subjected to densitometry and data were expressed as a % of mean values of healthy controls. Data are presented as mean ±SEM. Independent t-test, where *, P<0.05.

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Figure 3. Increased circulating TNF-alpha and IL-4 levels in patients with diabetic retinopathy.

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Serum was isolated from peripheral blood of diabetic patients: no retinopathy (DR-0, n=19), mild retinopathy (DR-m, n=24) and severe retinopathy (DR-s, n=31). TNF-alpha was detected in all of the 74 patients examined. Comparison of log transformed values showed that TNF-alpha levels were significantly higher in the DR-s group compared to DR-0 (P= 0.02) and also compared to DR-m (P=0.008) suggesting that there is enhanced inflammation in DR-s. Comparison of the log transformed values of IL-4 in patients where this cytokine was detected showed a significant increase in IL-4 in DR-s compared to controls (P= 0.005). IL-4 was also higher in DR-s compared to DR-m but this was not quite significant (P= 0.07). There was no difference in levels of other examined cytokines (IL-1A, IL-1B, IL-1RA, IL-6 and IL-10) between the groups.

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 Table 1 - Baseline characteristics of patients used in this study Variable Diabetes Diabetic Mild Diabetic Severe patients with Retinopathy Retinopathy Diabetic no (DR-m + (DR-m) Retinopathy retinopathy DR-s) (DR-s) (DR-0)

167 125 (74.9%)

98 64 (65.3%)

69 61 (88.4%)‡

65 ±14 10 (5-60)

61± 14 16(1-64)*

59±16* 15(3-51)*

64 ± 11† 18(1-64)*

23 (43.4%) 29.0 (18.143.0)

95 (56.9%) 29.3 (19.682.7)

54 (55.1%) 28.5(19.660.0)

42 (60.9%)* 30.3(20.082.7)*

7.2± 1.5 55± 16

7.9± 1.5* 63 ± 16

7.7± 1.4 61± 16

8.3 ± 1.4*† 67± 16

67± 23

72 ± 27

80±29*

62 ± 22‡

ACR median (range) (mg/mmol)

0.9(0.1-54)

1.6(0.2-84.3)

1.3(0.2-51.0)

3.3(0.384.3)

Systolic BP (mmHg) Diastolic BP (mmHg) LDL median (range) mmol/L HDL median (range) mmol/L Total Cholesterol (mmol/L)

133 ±17

134 ±17

132±17

138 ± 16†

74±10

74±9

74±11

2.0 (0.8-5.0)

2.1 (0.6-7.2)

2.1 (0.7-7.2)

2.0 (0.6-4.5)

1.3 (0.7-3.5)

1.2 (0.7-18.1)

1.3 (0.7-18.1)

3.9 (2.9-8.0)

4.1 (2.2-7.4)

4.1 (2.2-7.4)

1.2 (0.810.2) 4.0 (2.4-7.4)

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75±11

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53 41 (77.4%)

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N Diabetes (Type 2) Age (years) Duration median (range) (years) Gender (male) BMI median (range) Kg/m2 HbA1c (%) HbA1c(mmol/m ol) eGFR (ml min–1 1.73 m–2)

p Value

DR-0 = Diabetic with no retinopathy; DR-m = non-proliferative diabetic retinopathy; DR-s = severe non-proliferative and proliferative retinopathy; BMI = Body Mass Index; HbA1c = Glycated haemoglobin; eGFR = Estimated glomerular filtration rate; ACR = Albumin to creatinine ratio; BP = Blood Pressure; LDL: Low Density Lipoprotein; HDL: High Density Lipoprotein; *= P<0.05 compared with DR-0; † = P<0.05 compared with DR-m; ‡ = P<0.001 compared with DR-m.aData are means ± SD, except where otherwise indicated. For continuous variables, groups were compared using Independent t-test, Levene’s test for equality of variances was used to decide equal variance (p>.05 equal variance assumed), categorical values (Gender, Type of diabetes) were compared using Chi-squared test. 21   

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      Highlights  Circulating Mitochondrial DNA level shows a biphasic trend in diabetic retinopathy.

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We detected Mitochondrial DNA damage in blood samples of retinopathy patients.

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Damaged Mitochondrial DNA may directly cause inflammation.

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Circulating Mitochondrial DNA levels are an independent risk marker for retinopathy.

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