The aim of this study was to investigate variants in UCP2 genes in type 2 diabetes mellitus (DM) and diabetic retinopathy (DR) in Chinese population.
Materials and Methods
We conducted a single nucleotide polymorphism-based and haplotype-based case-control study between the variants of UCP2 and DM and between the variants of UCP2 and DR in 479 Chinese patients with type 2 DM and 479 control subjects without DM. Two SNPs (rs660339 and rs659366) were selected as genetic markers.
The risk allele C at UCP2 rs660339 was closely associated with DM in Chinese population. There was significant difference in rs660339 between DM and controls (P = 0.0016; OR [95%CI] = 1.37 (1.14–1.65)). Subjects who were homozygous of the C allele were more likely to develop DM. The frequency of C allele was higher in DM (58%) than in control (51%). But this locus didn't have a definite effect on the onset of non-proliferative diabetic retinopathy (NPDR) (P = 0.44; OR [95%CI] = 0.80 (0.56–1.14)) and proliferative diabetic retinopathy (PDR) (P = 1.00; OR [95%CI] = 0.99 (0.74–1.34)) comparing to subjects with DM without retinopathy (DWR), respectively. Moreover, the UCP2 rs659366 polymorphism showed no significant difference between DM and control (P = 0.66; OR [95%CI] = 1.10 (0.91–1.32)). However, there was a significant difference between PDR and DWR (P = 0.016; OR [95%CI] = 0.66 (0.49–0.90)), but there was no difference between NPDR and DWR (P = 1.00; OR [95%CI] = 0.96 (0.67–1.37)). Participants who carried the G allele at rs659366 were more likely to develop PDR. For the haplotype, C-A was present more frequently in DM than in control (16% vs 7%), indicating that it was risky, and T-A was present less in DM than in control (29% vs 35%). Haplotype frequencies in DR and DWR showed no significant difference (P = 0.068).
Citation: Shen Y, Wen Z, Wang N, Zheng Z, Liu K, Xia X, et al. (2014) Investigation of Variants in UCP2 in Chinese Type 2 Diabetes and Diabetic Retinopathy. PLoS ONE 9(11): e112670. https://doi.org/10.1371/journal.pone.0112670
Editor: Junwen Wang, The University of Hong Kong, Hong Kong
Received: June 12, 2014; Accepted: October 10, 2014; Published: November 14, 2014
Copyright: © 2014 Shen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.
Funding: This work was sponsored by grants from the National Natural Science Foundation of China (No. 81100679; No. 81273424), Major Basic Research Development Program of China (973 Program) (No. 2011CB707500) and Shanghai Guide Fund for Medical Projects (No. 124119a9600). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Diabetic retinopathy (DR) is a common sight-threatening microvascular complication affecting patients with diabetes mellitus (DM) and it is a major cause of new cases of blindness . In the United States, an estimated 25.8 million children and adults or approximately 8.3% of the population, have diabetes . Meanwhile, according to a recent epidemiological survey in China, the overall prevalence of diabetes was estimated to be 11.6% in Chinese adult population . With such incidence, and prevalence of DM increasing worldwide, DR is expected to reach epidemic proportions.
Many diabetes-induced metabolic abnormalities are implicated in the development of DR, and appear to be mostly influenced by elevated oxidative stress . Consequently, different candidate genes of oxidative stress were paid special attention to . Several genetic and functional studies have implicated the important role of oxidative stress genes in the pathogenesis of retinopathy in diabetes –. However, the exact mechanism underlying its development remains unclear. There is considerable evidence that in patients with diabetes, mitochondrial reactive oxygen species (ROS) generation, especially at high blood glucose levels, is one of the main sources of oxidative stress , . Some antioxidant defense mechanisms exist to neutralize ROS and prevent harm. One of these is represented by human uncoupling proteins (UCPs).
UCPs are mitochondrial transporters present in the inner membrane of mitochondria which are considered pivotal regulators of energy and glucose homeostasis . They belong to the mitochondrial anion carrier gene family and as suggested by their name, UCPs can uncouple ATP production from mitochondrial respiration by causing proton leak . Recent studies demonstrated that UCPs can prevent mitochondrial hyperpolarization and formation of ROS . A group of five different UCPs have been identified. These proteins have distinct tissue distributions and functions. Among them, UCP2 is widely expressed in almost all mammalian tissues including white adipose tissue, liver, kidney, pancreatic islets, macrophages and retinal endothelial cells and pericytes . Recently, the relationships between UCP2 polymorphisms and susceptibility for type 2 DM –, obesity  and cardiovascular disease  have been investigated. Several variants including Ala55Val polymorphism (rs660339) in the exon 4 and −866G/A polymorphism (rs659366) in the promoter region were paid specific attention to, however, the results were contradicting –. Limited studies about the association between UCP2 polymorphisms and DM in Chinese population have found no significant differences . In addition, no study has investigated the relationship between these two polymorphisms and the risk of DR in Chinese population.
Considering the role of UCP2 in the protection against oxidative stress, we conducted an association analysis between variants of UCP2 and DM and between variants of UCP2 and DR in subjects with type 2 DM in Chinese population.
Materials and Methods
The study population comprised of 479 unrelated patients with type 2 diabetes mellitus (mean age ± SD, 58.80±12.02; ratio of male to female, 45.3∶54.7) and 479 unrelated controls subjects without DM (mean age ± SD, 58.74±12.22; ratio of male to female, 42.4∶57.6), all of Han Chinese ethnicity. The subjects with DM were randomly recruited from the data bank in the department of ophthalmology of Shanghai First People's Hospital, Shanghai Jiao Tong University. The diagnosis of diabetes was based on criteria outlined by the American Diabetes Association in 1997. Control subjects without DM were chosen from a population of the outpatient of Shanghai First People's Hospital, Shanghai Jiao Tong University. The inclusion criteria of the control group was healthy blood donors of Chinese ancestry who did not have DM or family history for this disease. This study was approved by the Ethics committee of Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai, China (permit number: 2013KY095). An informed consent process was established following the guidelines of the Helsinki Declaration, and consent forms were signed by all subjects.
We obtained blood samples from all the 958 subjects for DNA extraction. All subjects with DM underwent a standard ophthalmic examination, including measurement of visual acuity, slit-lamp biomicroscopy and dilated fundus examination. The evaluation of DR was according to the diagnostic criteria of the American Academy of Ophthalmology (AAO) 2001 Annual Meeting.
Among the 479 subjects with DM, there were 324 patients with DR (n = 215 of proliferative diabetic retinopathy (PDR) and n = 109 of non-proliferative diabetic retinopathy (NPDR)), 155 subjects with DM without retinopathy (DWR). The data of patients' age, gender, duration of diabetes, fasting blood glucose levels, systolic blood pressure, diastolic blood pressure, height and weight were all recorded.
Age, gender, systolic blood pressure, diastolic blood pressure and BMI were comparable in the control, DWR and DR groups. Besides, there was no significant difference in the duration of diabetes and the fasting blood glucose between DWR and DR groups (P>0.05). Demographic characteristics of all patients included in the study were shown in Table 1.
We selected rs660339 in the exon 4, and rs659366 in the promoter region of UCP2 gene for our study. Genomic DNA was extracted from venous blood using standard phenol-chloroform extraction for the genotyping of these two polymorphisms. PCR amplifications producing two genomic segments, rs659366 and for rs660339, were performed on the GeneAmp PCR 9700 System (Applied Biosystems, ABI, USA) in a 15.0 µl reaction containing 10 ng genomic DNA,1.2 U Taq polymerase, 0.2 µl of each primer (10 PM), 1.5 µl PCR buffer (10×, Qiagen), and 1.5 µl dNTPs (each 2 mM). Amplification conditions consisted of an initial 3 min at 95°C, 35 cycles of 30 sec at 94°C, and 30 sec at 57°C for the two segments. We then genotyped the two variants using DNA sequencing on an ABI 3100 genetic analyzer using the BigDye Terminator Cycle Sequencing Kit (Applied Biosystems, ABI, USA). The primers and the sequence number definition of UCP2 were constructed on the basis of NC_000006. Primer sequences were listed in the Table S1.
The parameters, allele and genotype frequencies, Hardy-Weinberg equilibrium (HWE), pair-wised linkage disequilibrium, and haplotype analysis were conducted online using a software platform called SHEsis (http://analysis.bio-x.cn) . A case-control format was adopted for data analysis. The P values of allele and genotype frequencies were obtained based on chi-square distribution. We adjusted the P values using the Bonferroni correction. The threshold value of HWE was set at 0.05. Haplotype analysis was conducted using the PLEM algorithm, and those haplotypes that exhibited a frequency less than 0.03 were abandoned.
Totally, 479 subjects with DM and 479 controls were enrolled in our study. All of the polymorphisms investigated were proved to be in HWE. The results of HWE testing were showed in the Table S2. The total number of samples genotyped differed between the variants because not all were capable of being amplified with PCR.
Two polymorphisms of UCP2 (rs660339 and rs659366) were genotyped by sequencing in the 958 subjects. The frequency distribution of the alleles and genotypes were present in Table 2, Table 3 and Table 4.
When Bonferroni corrections were strictly adopted, there was significant difference in rs660339 between DM and controls (P = 0.0016; OR [95%CI] = 1.37 (1.14–1.65)). The frequency of C allele was higher in DM (58%) than in control (51%). The percentage of genotype CC at rs660339 were higher in DM (35%) and than in control subjects (28%) (P<0.05). Multiple comparison for the 3 genotypes (CC, CT, TT) showed that there were significant differences between CC and TT (χ2 = 10.688, P = 0.001) and between CT and TT (χ2 = 4.364, P = 0.037), but no difference was found between CC and CT (χ2 = 2.535, P = 0.111). The results of multiple comparison were showed in the Table S3. It suggested that the risk allele C was closely associated with type 2 DM in Chinese population. Moreover, rs659366 showed no significant difference between DM and control (P = 0.66; OR [95%CI] = 1.10 (0.91–1.32)). We observed no significant difference in genotype distribution at rs659366 between DM and control group (P>0.05) (Table 2).
To investigate the association between UCP2 variants and DR, we found no significant difference between DR and DWR (P = 0.57; OR [95%CI] = 0.92 (0.70–1.22)) for rs660339. Nevertheless, for rs659366, there was a significant difference between DR and DWR (P = 0.045; OR [95%CI] = 0.75 (0.57–0.99)). For the genotype distribution analysis, we found no significant difference between DR and DWR at rs660339 and rs659366 (Table 3).
Then, we further compared the distribution of alleles between DR subtypes (NPDR, PDR) and DWR. For rs660339, we found no significant difference neither between NPDR and DWR (P = 0.44; OR [95%CI] = 0.80 (0.56–1.14)) nor between PDR and DWR (P = 1.00; OR [95%CI] = 0.99 (0.74–1.34)). Interestingly, for rs659366, there was a significant difference between PDR and DWR (P = 0.016; OR [95%CI] = 0.66 (0.49–0.90)). But, there was no difference between NPDR and DWR (P = 1.00; OR [95%CI] = 0.96 (0.67–1.37)). For the genotype distribution analysis, we found no significant difference among NPDR, PDR and DWR groups at rs660339 and rs659366. However, participants who were homozygous for the G allele at rs659366 were more likely to develop PDR but there was no statistical significance (P = 0.06) (Table 4).
Within UCP2, pair-wised linkage disequilibrium analysis in DM case showed rs660339 was in moderate linkage disequilibrium (D′ = 0.52) with rs659366 (Table S4).
For the haplotype analysis, one significant association was noted for C-A haplotype that was present two times frequently in DM than in control (16% vs 7%), indicating that it was risky. Another significant association was T-A haplotype which was present less frequently in DM than in control (29% vs 35%) (Table 5). Moreover, haplotype frequencies in DR and DWR showed no significant difference (P = 0.068) (Table 6).
DM and its chronic complications are complex diseases associated with both genetic and environmental risk factors . Considering the important role of UCP2 in ROS formation by mitochondria, the relationship between UCP2 locus and susceptibility for DM and its chronic complications –, – has been investigated. Over the past few years, several studies have suggested that there was an association between the UCP2-866G/A (rs659366) and Ala55Val (rs660339) polymorphisms and the risk of type 2 DM –. However, the results showed significant between-study variation. Prior studies examining these two variants in the UCP2 gene have produced controversial results –: population of different races, ethnic backgrounds, and environmental exposures might influence the final result. Moreover, the evidence in Chinese population was quite limited. Recent study conducted in Hubei Han Chinese have reported no significant association between UCP2 polymorphisms and type 2 DM . Therefore, we found it still necessary to enlarge the sample size and conduct further investigation about the effects of UCP2 genetic polymorphisms on type 2 DM.
In this study, we genotyped rs659366 and rs660339 of UCP2 in 958 participants. The SNP analysis demonstrated that the C allele of rs660339 had significantly higher frequency in DM (P = 0.0016; OR [95%CI] = 1.37 (1.14–1.65)) than in control subjects, indicating that the risk C allele was related with the onset of DM in Chinese population. Meanwhile, participants who were homozygous for the C allele at rs660339 were more likely to develop DM. Haplotype analysis demonstrated that C-A haplotype was present two times more in DM than in control, while T-A haplotype was present less frequently in DM than in control, indicating that C was risky. The result of haplotype analysis was in accordance with those of allele and genotype analysis between DM and control. Our result complied with prior studies conducted by Lee et al.  and Vimaleswaran et al.  in Asian ethnicity. Nevertheless, the UCP2 rs659366 polymorphism showed no significant difference between DM and control (P = 0.66; OR [95%CI] = 1.10 (0.91–1.32)). Other studies conducted in Asian ethnicity have reported different results , –. Some indicated that patients with G alleles at rs659366 were more likely to suffer from DM , and the others showed no significant difference –. According to a recent meta-analysis of seventeen published articles, rs659366 was not a candidate for susceptibility to type 2 DM in any ethnic population, however, rs660339 was type 2 DM susceptibility loci in population of Asian, but not European descent . Our study has consolidated these findings in Chinese population.
As a severe sight-threatening microvascular complication of DM, DR represents a major cause of new cases of blindness in adults . There already had evidence showed that longer duration of diabetes, poorer control of blood glucose and elevated blood pressure were the major factors responsible for the onset and progression of DR. However, DR still occurs in subjects with normal glucose and blood pressure . In addition, the prevalence of DR also showed racial differences and familial clustering indicating that genetic factors may have a significant effect in promoting the severity and the speed of onset of retinopathy in patients with DM . Thus, identifying the genes contributing to the susceptibility of DR is quite important. Experimental research demonstrated that an overproduction of ROS was a triggering cause in the pathogenesis of diabetic complications. UCP2 can protect retinal vascular endothelial cells from damage by inhibiting the overproduction of mitochondrial ROS , a phenomenon that revealed the important role of UCP2 in DR. Although the genetic association between UCP2 and DM has already been investigated, how UCP2 polymorphsms influence the onset of DR still requires more evidences based on case-control genetic study. Crispim D et al.  has reported an association between the polymorphisms of UCP2 and PDR in subjects with both type 2 and type 1 DM in European ancestry. However, there was no evidence about the relationship between UCP2 and DR in Asian population. Therefore, we examined the two common UCP2 gene polymorphisms, rs660339 and rs659366 variants, in Chinese participants to try to confirm this association.
For rs660339, we found no significant difference for the SNP analysis between DR and DWR. Although Crispim D et al.  indicated that type 2 DM patients with PDR presented higher frequencies of the T allele than type 2 DM patients without this complication, we observed no significant difference between NPDR or PDR and DWR, respectively. We guess that their result might only be limited to European ethnicity. Besides, for UCP2 rs659366 polymorphism, there was a significant difference between DR and DWR. It was interesting that when we compared the SNP distributions in DR subtypes and DWR, we observed a significant difference between PDR and DWR, but there was no difference between NPDR and DWR. Participants who were homozygous for the G allele at rs659366 were more likely to develop PDR, indicating that the risk G allele was associated with the onset of PDR. When Bonferroni corrections were strictly adopted, we found that haplotype frequencies in DR and DWR showed no significant difference. In previous studies, Rudofsky et al.  reported no association of the rs659366 polymorphism with DR in a sample of Caucasian type 2 DM patients. However, Crispim D et al.  found that type 2 DM patients with PDR presented higher frequency of A allele. Our finding contradicted with prior studies in European ethnicity probably due to a racial difference, and our preliminary results need further consolidation by larger sample studies. It is worth pointing out that most studies focused on the genetic epidemiology of UCP2 gene, and its function or protein expression changes by the influence of gene mutations were rarely investigated. Recently, one study indicated that the presence of the −866A/55Val/Ins haplotype was associated with decreased UCP2 gene expression in human retina , which shed light on further research.
In conclusion, we examined the frequencies of two common polymorphisms in UCP2, rs660339 and rs659366, in the type 2 DM patients consist of NPDR, PDR, DWR and also control subjects without DM. The result indicated that homozygous of the C allele at UCP2 rs660339 were more likely to develop DM, but this locus doesn't have a definite effect on the onset of NPDR and PDR. Moreover, the UCP2 rs659366 polymorphism demonstrated a modest relationship with DM, but the DR patients who were homozygous for the G allele at rs659366 were more likely to develop PDR. Although the genetic susceptibilities to DR and to DM were sometimes similar, the difference still existed.
SNPs in the UCP2 may be implicated in the pathogenesis of type 2 DM and DR in Chinese population. As far as our knowledge concerns, this is the first genetic study showing that UCP2 polymorphisms are associated with DR in Asian population. However, this is a preliminary study and further functional studies are required to confirm its effect in human retinal cells.
Primers used in PCR for each of the two polymorphisms.
Hardy-Weinberg equilibrium testing.
Multiple comparison of genotypes distribution in rs660339 between DM and control.
Conceived and designed the experiments: YS ZW NW X. Xu. Performed the experiments: YS ZW NW ZZ KL X. Xia QG. Analyzed the data: YS NW. Contributed reagents/materials/analysis tools: ZW QG YS. Wrote the paper: YS NW.
- 1. Yau JW, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, et al. (2012) Global prevalence and major risk factors of diabetic retinopathy. Diabetes care 35: 556–564.
- 2. Threatt J, Williamson JF, Huynh K, Davis RM (2013) Ocular disease, knowledge and technology applications in patients with diabetes. Am J Med Sci 345: 266–270.
- 3. Xu Y, Wang L, He J, Bi Y, Li M, et al. (2013) Prevalence and control of diabetes in Chinese adults. JAMA 310: 948–959.
- 4. Kowluru RA, Chan PS (2007) Oxidative stress and diabetic retinopathy. Exp Diabetes Res 2007: 43603.
- 5. Petrovič D (2013) Candidate genes for proliferative diabetic retinopathy. Biomed Res Int 2013: 540416.
- 6. Santos JM, Tewari S, Kowluru RA (2012) A compensatory mechanism protects retinal mitochondria from initial insult in diabetic retinopathy. Free Radic Biol Med 53: 1729–1737.
- 7. Cilenšek I, Mankoč S, Petrovič MG, Petrovič D (2012) GSTT1 null genotype is a risk factor for diabetic retinopathy in Caucasians with type 2 diabetes, whereas GSTM1 null genotype might confer protection against retinopathy. Dis Markers 32: 93–99.
- 8. Kanwar M, Chan PS, Kern TS, Kowluru RA (2007) Oxidative damage in the retinal mitochondria of diabetic mice: possible protection by superoxide dismutase. Invest Ophthalmol Vis Sci 48: 3805–3811.
- 9. Nishikawa T, Edelstein D, Du XL, Yamagishi S, Matsumura T, et al. (2000) Normalizing mitochondrial superoxide production blocks three pathways of hyperglycaemic damage. Nature 404: 787–790.
- 10. Piconi L, Quagliaro L, Ceriello A (2003) Oxidative stress in diabetes. Clin Chem Lab Med 41: 1144–1149.
- 11. Lee HJ, Ryu HJ, Shin HD, Park BL, Kim JY, et al. (2008) Associations between polymorphisms in the mitochondrial uncoupling proteins (UCPs) with T2DM. Clin Chim Acta 398: 27–33.
- 12. Adams SH (2000) Uncoupling protein homologs: emerging views of physiological function. J Nutr 130: 711–714.
- 13. Skulachev VP (1998) Uncoupling: new approaches to an old problem of bioenergetics. Biochim Biophys Acta 1363: 100–124.
- 14. Duval C, Nègre-Salvayre A, Dogilo A, Salvayre R, Pénicaud L, et al. (2002) Increased reactive oxygen species production with antisense oligonucleotides directed against uncoupling protein 2 in murine endothelial cells. Biochem Cell Biol 80: 757–764.
- 15. Yu X, Jacobs DR Jr, Schreiner PJ, Gross MD, Steffes MW, et al. (2005) The uncoupling protein 2 Ala55Val polymorphism is associated with diabetes mellitus: the CARDIA study. Clin Chem 51: 1451–1456.
- 16. D'Adamo M, Perego L, Cardellini M, Marini MA, Frontoni S, et al. (2004) The −866A/A genotype in the promoter of the human uncoupling protein 2 gene is associated with insulin resistance and increased risk of type 2 diabetes. Diabetes 53: 1905–1910.
- 17. Bulotta A, Ludovico O, Coco A, Di Paola R, Quattrone A, et al. (2005) The common -866G/A polymorphism in the promoter region of the UCP-2 gene is associated with reduced risk of type 2 diabetes in Caucasians from Italy. J Clin Endocrinola Metab 90: 1176–1180.
- 18. Oktavianthi S, Trimarsanto H, Febinia CA, Suastika K, Saraswati MR, et al. (2012) Uncoupling protein 2 gene polymorphisms are associated with obesity. Cardiovasc Diabetol 11: 41.
- 19. Gioli-Pereira L, Santos PC, Sugaya LS, Ferreira NE, Krieger JE, et al. (2013) Association between UCP2 A55V polymorphism and risk of cardiovascular events in patients with multi-vessel coronary arterial disease. BMC Med Genet 14: 40.
- 20. Qin LJ, Wen J, Qu YL, Huang QY (2013) Lack of association of functional UCP2 −866G/A and Ala55Val polymorphisms and type 2 diabetes in the Chinese population based on a case-control study and a meta-analysis. Genet Mol Res 12: 3324–3334.
- 21. Shi YY, He L (2005) SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res 15: 97–98.
- 22. Souza BM, Assmann TS, Kliemann LM, Gross JL, Canani LH, et al. (2011) The role of uncoupling protein 2 (UCP2) on the development of type 2 diabetes mellitus and its chronic complications. Arq Bras Endocrinol Metabol 55: 239–248.
- 23. Crispim D, Fagundes NJ, dos Santos KG, Rheinheimer J, Bouças AP, et al. (2010) Polymorphisms of the UCP2 gene are associated with proliferative diabetic retinopathy in patients with diabetes mellitus. Clin Endocrinol (Oxf) 72: 612–619.
- 24. Rudofsky G Jr, Schrödter A, Voron'ko OE, Schlotterer A, Humpert PM, et al. (2007) Promoter polymorphisms of UCP1, UCP2, and UCP3 are not associated with diabetic microvascular complications in type 2 diabetes. Horm Metab Res 39: 306–309.
- 25. Rudofsky G, Schroedter A, Schlotterer A, Voron'ko OE, Schlimme M, et al. (2006) Functional polymorphisms of UCP2 and UCP3 are associated with a reduced prevalence of diabetic neuropathy in patients with type 1 diabetes. Diabetes Care 29: 89–94.
- 26. Lindholm E, Klannemark M, Agardh E, Groop L, Agardh CD (2004) Putative role of polymorphisms in UCP1-3 genes for diabetic nephropathy. J Diabetes Complications 18: 103–107.
- 27. Vimaleswaran KS, Radha V, Ghosh S, Majumder PP, Sathyanarayana Rao MR, et al. (2011) Uncoupling protein 2 and 3 gene polymorphisms and their association with type 2 diabetes in Asian Indians. Diabetes Technol Ther 13: 19–25.
- 28. Sasahara M, Nishi M, Kawashima H, Ueda K, Sakagashira S, et al. (2004) Uncoupling protein 2 promoter polymorphism− 866G/A affects its expression in beta-cells and modulates clinical profiles of Japanese type 2 diabetic patients. Diabetes 53: 482–485.
- 29. Hsu YH, Niu T, Song Y, Tinker L, Kuller LH, et al. (2008) Genetic variants in the UCP2-UCP3 gene cluster and risk of diabetes in the Women's Health Initiative Observational Study. Diabetes 57: 1101–1107.
- 30. Heidari J, Akrami SM, Heshmat R, Amiri P, Fakhrzadeh H, et al. (2010) Association study of the-866G/A UCP2 gene promoter polymorphism with type 2 diabetes and obesity in a Tehran population: a case control study. Arch Iran Med 13: 384–390.
- 31. Xu K, Zhang M, Cui D, Fu Y, Qian L, et al. (2011) UCP2 −866G/A and Ala55Val, and UCP3 −55C/T polymorphisms in association with type 2 diabetes susceptibility: a meta-analysis study. Diabetologia 54: 2315–2324.
- 32. Fong DS, Aiello L, Gardner TW, King GL, Blankenship G, et al. (2004) Retinopathy in diabetes. Diabetes Care 27: 84–87.
- 33. Klein R, Klein BE, Moss SE, Davis MD, DeMets DL (1984) The Wisconsin epidemiologic study of diabetic retinopathy. II. Prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years. Arch Ophthalmol 102: 520–526.
- 34. Liew G, Klein R, Wong TY (2008) The role of genetics in susceptibility to diabetic retinopathy. Int Ophthalmol Clin 49: 35–52.
- 35. He Y, Wang N, Shen Y, Zheng Z, Xu X (2014) Inhibition of high glucose-induced apoptosis by uncoupling protein 2 in human umbilical vein endothelial cells. Int J Mol Med 33: 1275–1281.
- 36. de Souza BM, Assmann TS, Kliemann LM, Marcon AS, Gross JL, et al. (2012) The presence of the −866A/55Val/Ins haplotype in the uncoupling protein 2 (UCP2) gene is associated with decreased UCP2 gene expression in human retina. Exp Eye Res 94: 49–55.