Polymorphisms in the Uncoupling Protein 2 Gene Are Associated with Diabetic Retinopathy in Han Chinese Patients with Type 2 Diabetes

Abstract

Background:

The uncoupling protein 2 (UCP2) gene plays an important role in the complications of type 2 diabetes (T2D). However, the association between variants in the UCP2 gene and diabetic retinopathy (DR) in Han Chinese T2D patients remains unclear.

Methods:

Two single-nucleotide polymorphisms (SNPs) [rs659366 (−866G/A) and a 45-bp insertion/deletion (I/D) in the 3'-UTR] in the UCP2 gene were genotyped in a study cohort of 209 T2D patients with DR and 199 T2D patients without DR by direct DNA sequencing.

Results:

Logistic regression analysis showed that the AA and GA genotypes of rs659366 were significantly associated with an increased risk for nonproliferative DR (NPDR) in the codominant model (corrected p-value <0.01) and the dominant model (corrected p-value = 0.006). Patients harboring the II and DI genotypes had a higher risk for PDR in the codominant model (corrected p-value = 0.011) and the dominant model (corrected p-value = 0.006), and the DI genotype showed a higher risk for NPDR in the dominant model (corrected p-value = 0.007) or codominant model (corrected p-value = 0.006). Further, haplotype analyses verified that the A-I haplotype is a risk haplotype for NPDR and PDR.

Conclusion:

This study suggests that the UCP2 gene may be involved in the pathogenesis of NPDR and PDR in Han Chinese patients with T2D.

Introduction

Diabetes is strongly associated with microvascular complications, which include diabetic retinopathy (DR), which involves the capillaries of the eyes and may lead to blindness (Yau et al., 2012). Hyperglycemia can induce excessive production of reactive oxygen species (ROS) and increase oxidative stress in the retinal mitochondria of diabetic patients, which subsequently results in retinal mitochondrial dysfunction and capillary cell apoptosis (Kanwar et al., 2007; Santos et al., 2012). However, some antioxidant genes can weaken ROS and protect the retina from damage. Among these genes, uncoupling protein 2 (UCP2), a member of the mitochondrial anion carrier gene family, can uncouple ATP production from mitochondrial respiration and prevent mitochondrial hyperpolarization (Skulachev, 1998; Adams, 2000). A previous report suggested that the elevation in ROS levels upregulates UCP2, resulting in the reduction of membrane potential and ROS production (Fisler and Warden, 2006). However, dysfunctional UCP2 can lead to ROS accumulation and promote the development of DR.

UCP2 is expressed in almost all mammalian tissues and plays a vital role in energy metabolism of cells (Duval et al., 2002). Recent studies have shown that UCP2 polymorphisms are associated with various diseases such as type 2 diabetes (T2D) (Shen et al., 2014), presbycusis (Manche et al., 2016), liver dysfunction (Vimaleswaran et al., 2015), obesity (Brondani et al., 2014), and cardiovascular (Gioli-Pereira et al., 2013) and chronic inflammatory diseases (Yu et al., 2009). Previous studies have specifically examined the UCP2 variants, namely, the −866G/A polymorphism (rs659366) in the promoter region and a 45-bp insertion/deletion (I/D) in the 3′-untranslated region (UTR) of exon 8 (D'Adamo et al., 2004; Dalgaard, 2011; Mutombo et al., 2013; Say et al., 2014).

The 866A/55Val/Ins haplotype in UCP2 is associated with decreased UCP2 gene expression in the human retina (de Souza et al., 2012). However, a limited number of studies have reported discordant results relating to the association between UCP2 polymorphisms and T2D in the Chinese population (Qin et al., 2013; Shen et al., 2014). In addition, the relationship between these two polymorphisms and the risk for DR has rarely been reported in the Chinese population. Thus, we conducted a case-control association study to further evaluate the association between UCP2 variants and DR in the Han Chinese population.

Subjects and Methods

Study subjects and data collection

A total of 408 unrelated Han Chinese patients with T2D, including 209 patients with DR and 199 patients without DR, were recruited from the Second People's Hospital of Yunnan Province, Kunming, China. Diabetes was diagnosed according to the current American Diabetes Association criteria (American Diabetes Association, 2018). All T2D patients underwent a complete ophthalmologic examination, including corrected visual acuity, fundoscopic examination, and fundus photography. The evaluation of DR was performed according to the diagnostic criteria of the American Academy of Ophthalmology (AAO) 2001 Annual Meeting. Among 209 patients with DR, 117 patients were diagnosed with proliferative DR (PDR) and 92 patients with nonproliferative DR (NPDR). To avoid the confounding effect of impaired kidney function, the patients with overt nephropathy were not enrolled in this study. The demographic and clinical features of the study participants in this study are shown in Table 1.

Table 1.

Characteristics and the Clinical Profile of Type 2 Diabetes Mellitus Patients With and Without Retinopathy

	DR (n = 209)	WDR (n = 199)	p value
Gender
Male	96 (46%)	117 (58.81%)	0.013
Female	113	82
Age at diagnosis (years)	44.82 ± 10.62	45.54 ± 11.15	0.51
Diabetes duration (years)	8.34 ± 5.45	9.2 4 ± 4.65	0.064
BMI (kg/m²)	24.78 ± 3.42	24.74 ± 3.25	0.971
Waist (cm)	89.42 ± 11.53	90.55 ± 9.94	0.307
Hip (cm)	96.87 ± 8.21	97.41 ± 7.42	0.168
W/R ratio	0.91 ± 0.13	0.951 ± 0.14	0.718
Systolic blood pressure (mmHg)	138.31 ± 20.74	129.35 ± 18.18	<0.001
Diastolic blood pressure (mmHg)	85.45 ± 13	82.74 ± 11.45	0.047
Chol (mM)	5.38 ± 1.47	4.88 ± 1.14	0.003
Trig (mM)	2.98 ± 2.84	3 ± 2.92	0.875
HDL (mM)	1 ± 0.35	1.1 4 ± 0.57	0.319
LDL (mM)	2.8 ± 1	2.7 ± 0.9	0.481
apOA (g/L)	1.27 ± 0.38	1.35 ± 0.62	0.003
apOB (g/L)	0.94 ± 0.35	1 ± 0.85	0.749
BUN (mM)	6.77 ± 3.71	5.25 ± 1.82	<0.001
UA (μM)	359.35 ± 111.36	354.21 ± 95.53	0.586
CRE (μM)	88.65 ± 62.29	70.43 ± 22.54	0.085
HbA1c (%)	9.64 ± 2.45	9.16 ± 2.58	0.038

BMI, body mass index; DR, type 2 diabetes with diabetic retinopathy; WDR, type 2 diabetes without diabetic retinopathy; NPDR, nonproliferative DR; PDR, proliferative DR; Chol, cholesterol; Trig, triglyceride; HDL, high-density lipoprotein; LDL, low-density lipoprotein; apOA, apolipoprotein a; apOB, apolipoprotein b; BUN, blood urea nitrogen; UA, uric acid; CRE, creatinine; HbA1c, glycosylated hemoglobin.

This study was approved by the Second People's Hospital of Yunnan Province Institutional Review Board and in accordance with the principle of the Helsinki Declaration II. Written informed consent was obtained from all study participants.

Single-nucleotide polymorphism selection and genotyping

Two UCP2 single-nucleotide polymorphisms (SNPs), namely, rs659366 and 3′-UTR 45-bp I/D, were selected for genotyping. Genomic DNA was extracted from peripheral blood leukocytes using a genomic DNA kit (Qiagen, Valencia, CA) in accordance with the manufacturer's instructions. The genotypes of the patients were determined using DNA sequencing on an ABI3730 genetic analyzer using the BigDye Terminator Cycle Sequencing Kit (Applied Biosystems, Foster City, CA). The reaction mixture for the polymerase chain reaction (PCR) contained 10 ng of genomic DNA, 20 μL of the PCR mixture, and 0.2 μL of each primer (10 pM). The PCR conditions included an initial denaturation of 2 min at 98°C, followed by 40 cycles of denaturation at 95°C for 30 s, annealing at 59°C or 60°C for 15 s, and extension at 72°C for 15 s; and a final extension at 72°C for 5 min. The primers for the UCP2 gene were designed based on NC_000006 (www.ncbi.nlm.nih.gov/nuccore/NC_000006). The primer sequences are listed in Supplementary Table S1(Supplementary Data are available online at www.liebertpub.com/gtmb).

Statistical analysis

Demographic and clinical data were compared between the T2D patients with DR and without DR using the Student's t-test or nonparametric Mann-Whitney U-test for continuous variables and the Chi-square test for categorical variables. Hardy-Weinberg equilibrium (HWE), haplotype analysis, and pairwise linkage disequilibrium were evaluated using SHEsis (http://analysis.bio-x.cn).The threshold value of HWE was 0.05. The PLEM algorithm was used to conduct haplotype analysis, and haplotypes with a frequency less than 0.03 were abandoned.

The genotype and allele frequencies of the polymorphisms were compared between the T2D patients with DR and without DR using the Chi-square test or the Fisher's exact test. The odds ratio (OR) was calculated for genotype frequencies and allele frequencies with a 95% confidence interval (95% CI) using the logistical regression. Logistic regression analysis was further performed to evaluate whether the UCP2 SNPs were independently associated with DR after adjusting for potential confounding factors, including gender, systolic blood pressure, glycosylated hemoglobin (HbA1c), diastolic blood pressure, apolipoprotein a (apOA), cholesterol (Chol), and blood urea nitrogen (BUN) levels, which were significantly associated with DR in the univariate models. All statistical analyses were conducted using SPSS statistical software, version 17.0 (SPSS, Inc., Chicago, IL). Multiple testing corrections were conducted by Benjamini and Hochberg's step-up procedures for strong control of the false discovery rate. A p-value of less than 0.05 (two sided) was considered statistically significant.

Results

Genotypes of both polymorphisms deviated from HWE among subjects with DR (p < 0.05), while neither of the two UCP2 SNPs investigated in this study violated HWE in subjects without DR (p > 0.05) (Supplementary Table S2). Although there was a moderate linkage disequilibrium between the two SNPs (D′ = 0.87, r² = 0.14), these SNPs cannot substitute each other. No significant differences between the T2D patients with DR and without DR with respect to age at diagnosis, diabetes duration, BMI, waist, hip, W/R ratio, Trig, HDL, LDL, apOB, UA, and CRE were observed (p > 0.05; Table 1). The T2D patients with DR had a lower male-to-female ratio compared to the T2D patients without DR (p = 0.013; Table 1). Systolic blood pressure, diastolic blood pressure, HBA1C, Chol, and BUN levels were significantly higher in the T2D patients with DR compared to those without DR (p < 0.05; Table 1), but apOA levels showed an adverse trend.

Our results showed that the genotype and allele distributions of both SNPs significantly differed between the T2D patients with DR and without DR (Table 2). The A allele of rs659366 was significantly more frequent in patients with DR than in those without DR (57% vs. 44%; OR = 1.64, 95% CI: 1.24-2.16; corrected p-value <0.001). The frequencies of the AA and AG genotypes of rs659366 were significantly higher in patients with DR than in those without DR (AA: 27% vs. 17%; GA: 58% vs. 55%; corrected p-value <0.001). When DR was divided into NPDR and PDR, except for the relationship of AA and AG genotypes of rs659366 with PDR, significant associations were identified between rs659366 and PDR or NPDR (corrected p-value <0.05 for alleles and genotypes).

Table 2.

Allele and Genotype Distributions of the UCP2 Single-Nucleotide Polymorphisms in Patients With Diabetic Retinopathy and Those Without Diabetic Retinopathy

SNP	Samples	N	Alleles		Corrected p-value	OR (95% CI)	Genotypes			Corrected p-value
			G	A			GG	GA	AA
rs659366 (G > A)	DR	209	182 (0.43)	236 (0.57)	<0.001	1.64 (1.24-2.16)	30 (0.15)	122 (0.58)	57 (0.27)	<0.001
	NPDR	92	73 (0.4)	111 (0.6)	<0.001	1.92 (1.34-2.74)	6 (0.07)	61 (0.66)	25 (0.27)	<0.001
	PDR	117	109 (0.47)	125 (0.53)	0.025	1.45 (1.05-2)	24 (0.21)	61 (0.52)	32 (0.27)	0.05
	WDR	199	222 (0.56)	176 (0.44)			56 (0.28)	110 (0.55)	33 (0.17)
			D	I			DD	DI	II
3'-UTR 45-bp (D > I)	DR	209	330 (0.79)	88 (0.21)	<0.001	2.15 (1.45-3.17)	125 (0.6)	80 (0.38)	4 (0.02)	<0.001
	NPDR	92	144 (0.78)	40 (0.22)	<0.001	2.23 (1.4-3.58)	52 (0.57)	40 (0.43)	0 (0)	<0.001
	PDR	117	186 (0.8)	48 (0.2)	0.002	2.08 (1.33-3.24)	73 (0.63)	40 (0.34)	4 (0.03)	0.006
	WDR	199	354 (0.89)	44 (0.11)			156 (0.78)	42 (0.21)	1 (0.01)

Corrected p-value: Corrected by Benjamini and Hochberg's methods for strong control of the false discovery rate based on six tests.

SNP, single-nucleotide polymorphism.

For the 3′-UTR 45-bp I/D polymorphism, the I allele had significantly higher frequency in patients with DR than in those without DR (21% vs. 11%; OR = 2.15, 95% CI: 1.45-3.17; corrected p-value <0.001), whereas significant associations were also identified between the 3′-UTR 45-bp I/D polymorphism and NPDR and PDR (corrected p-value <0.001 and 0.003, respectively). Significant associations were found between the genotypes of the 3′-UTR 45-bp I/D polymorphism and DR (corrected p-value <0.001), NPDR (corrected p-value <0.001), and PDR (corrected p-value = 0.009).

The results of logistic regression analysis of the UCP2 SNPs after adjusting for potential confounding factors are shown in Table 3. For the 3′-UTR 45-bp I/D polymorphism, the DI genotype was significantly associated with the increased risk for DR compared to the DD genotype (OR = 2.55, 95% CI = 1.5-4.33; corrected p-value = 0.001) in the codominant model. The high risk of this polymorphism (DI and II) with DR was observed when applying the dominant model (OR = 2.63, 95% CI = 1.56-4.44; corrected p-value = 0.005). Moreover, a significant association was found between the A allele of rs659366 and DR in the codominant model (OR_AA = 3.12, 95% CI = 1.51-6.46; corrected p-value = 0.006) and the dominant model (OR = 2.06, 95% CI = 1.15-3.71; corrected p-value = 0.026).

Table 3.

Logistic Regression Analysis of the UCP2 Single-Nucleotide Polymorphisms in Patients With and Without Diabetic Retinopathy After Adjusting for Potential Confounding Factors

Polymorphism	Risk allele	Model	Number of cases/controls	OR (95% CI)	p-value	Corrected p-value
DR and WDR
rs659366 G/A	A	Codominant:
		AA vs. GG (ref.)	57/33 vs. 30/56	3.12(1.51-6.46)	0.002	0.006
		GA vs. GG (ref.)	122/110 vs. 30/56	1.8 (0.95-3.38)	0.07	0.088
		Dominant:
		AA + GA vs. GG (ref.)	179/143 vs. 30/56	2.06 (1.15-3.71)	0.016	0.026
		Recessive:
		AA vs. GA + GG (ref.)	57/33 vs. 132/166	1.88(1.07-3.3)	0.029	0.043
3'-UTR 45-bp D/I	I	Codominant:
		DI vs. DD (ref.)	80/42 vs. 125/156	2.55 (1.5-4.33)	0.001	0.006
		Dominant:
		DI + II vs. DD (ref.)	84/43 vs. 125/156	2.63 (1.56-4.44)	0.0003	0.005
PDR and WDR
rs659366 G/A	A	Codominant:
		AA vs. GG (ref.)	32/33 vs. 24/56	2.15 (0.93-4.95)	0.073	0.088
		GA vs. GG (ref.)	61/110 vs. 24/56	0.94 (0.45-1.97)	0.875	0.875
		Dominant:
		AA + GA vs. GG (ref.)	93/143 vs. 24/56	1.26 (0.64-2.45)	0.506	0.536
		Recessive:
		AA vs. GA + GG (ref.)	32/33 vs. 85/166	1.94 (0.99-3.79)	0.053	0.073
3'-UTR 45-bp D/I	I	Codominant:
		DI vs. DD (ref.)	40/42 vs. 73/156	2.45 (1.3-4.65)	0.006	0.011
		Dominant:
		DI + II vs. DD (ref.)	44/43 vs. 73/156	2.7 (1.45-5.03)	0.002	0.006
NPDR and WDR
rs659366 G/A	A	Codominant:
		AA vs. GG (ref.)	25/33 vs. 6/56	5.27 (1.75-15.82)	0.003	0.007
		GA vs. GG (ref.)	61/110 vs. 6/56	4.49 (1.61-12.58)	0.004	0.008
		Dominant:
		AA + GA vs. GG (ref.)	86/143 vs. 6/56	4.49(1.74-11.64)	0.002	0.006
		Recessive:
		AA vs. GA + GG (ref.)	25/33 vs. 67/166	1.55 (0.77-3.12)	0.223	0.251
3'-UTR 45-bp D/I	I	Codominant:
		DI vs. DD (ref.)	40/42 vs. 52/156	2.83 (1.5-5.35)	0.001	0.006
		Dominant:
		DI + II vs. DD (ref.)	40/43 vs. 52/156	2.66 (1.41-5.02)	0.003	0.007

Potential confounding factors include gender, systolic blood pressure, HbA1c, diastolic blood pressure, apOA, Chol, and BUN levels; corrected p-value: corrected by Benjamini and Hochberg's methods for strong control of the false discovery rate assuming 18 tests.

To investigate the genotypic distribution in DR patients with different severities, we compared the susceptibility genotypes in the patients with NPDR and PDR with those without DR (Table 3). In patients without DR, the AA and GA genotypes of the rs659366 polymorphisms were significantly associated with an increased risk for NPDR compared to the GG genotype (OR_AA = 5.27, 95% CI = 1.75-15.82, corrected p-value = 0.007; OR_GA = 4.49, 95% CI = 1.61-12.58, corrected p-value = 0.008) in the codominant model. The association of the rs659366 with NPDR was observed in the dominant model (OR = 4.49, 95% CI = 1.74-11.64; corrected p-value = 0.006). The DI genotype was significantly associated with an increased risk for NPDR compared to the DD genotype (OR = 2.83, 95% CI = 1.5-5.35; corrected p-value = 0.006) in the codominant model. The association between high risk for NPDR and the I/D polymorphism was observed when applying the dominant model (OR = 2.66, 95% CI = 1.41-5.02; corrected p-value = 0.007). The association of the AA genotype of the rs659366 polymorphism with PDR was not significant in the recessive, codominant, or dominant model (Table 3). The DI genotypes were significantly associated with an increased risk for PDR compared to the DD genotype (OR_DI = 2.45, 95% CI = 1.3-4.65; corrected p-value = 0.011) in the codominant model. The high risk for PDR and this polymorphism was observed when applying the dominant model (OR = 2.7, 95% CI = 1.45-5.03; corrected p-value = 0.006) (Table 3).

Haplotype analysis showed that the A-I haplotype was more frequent in patients with DR than in those without (20.0% vs.10.0%; OR = 2.25, 95% CI: 1.5-3.37; corrected p-value <0.001; Table 4). The A-I haplotype was also more frequent in patients with NPDR than in those without (21% vs.10.0%; OR = 2.33, 95% CI: 1.44-3.78; corrected p-value <0.001). A significant association was also observed between the A-I haplotype and PDR (OR = 2.19, 95% CI: 1.38-3.47; corrected p-value = 0.001).

Table 4.

Haplotype Analysis of the UCP2 Single-Nucleotide Polymorphisms in Patients With Diabetic Retinopathy and Those Without Diabetic Retinopathy

Haplotype	Case (frequency)	Control (frequency)	OR (95% CI)	Corrected p-value
DR and WDR
G-D	178 (0.43)	218 (0.55)	0.61 (0.46-0.81)	<0.001
A-D	152 (0.37)	136 (0.34)	1.1 (0.83-1.47)	0.512
A-I	84 (0.2)	40 (0.1)	2.25 (1.5-3.37)	<0.001
NPDR and WDR
G-D	71 (0.39)	218 (0.55)	0.52 (0.36-0.74)	<0.001
A-D	73 (0.4)	136 (0.34)	1.27 (0.88-1.82)	0.198
A-I	38 (0.21)	40 (0.1)	2.33 (1.44-3.78)	<0.001
PDR and WDR
A-D	79 (0.34)	136 (0.34)	0.981 (0.7-1.38)	0.916
G-D	107 (0.46)	218 (0.55)	0.7 (0.5-0.96)	0.037
A-I	46 (0.2)	40 (0.1)	2.19 (1.38-3.47)	0.001

The numbers reflect the number of haplotypes (G-D, A-D, or A-I) among our samples; corrected p-value: corrected by Benjamini and Hochberg's methods for strong control of the false discovery rate assuming nine tests.

Discussion

DR is a common microvascular complication of T2D, which is a primary cause of blindness in adults. One common viewpoint is that DR is caused by the chronic condition of diabetes and poor glycemic control (Klein et al., 1984). However, some patients develop DR with well-controlled blood glucose and not all diabetic patients with poor glycemic control develop retinal complications. This suggests that genetic susceptibility plays a key role in the development of T2D complications. As a member of the mitochondrial inner membrane carrier family, UCP2 mediates the release of energy in several tissue types (Lee et al., 2008). In pancreatic cells, an increased expression of UCP2 results in blunted glucose-stimulated insulin secretion, which is associated with a reduction in cellular ATP levels (D'Adamo et al., 2004). Considering the important role of UCP2 in energy metabolism, the association between UCP2-866G/A (rs659366) and 3′-UTR 45-bp I/D polymorphisms and the risk of metabolic disorders has been extensively investigated. However, previous studies have generated discordant results that are most likely due to population-based differences, including race, ethnic background, and environmental exposures (Shen et al., 2014).

In this study, we evaluated the associations between rs659366 and 3′-UTR 45-bp I/D polymorphisms and DR in a Han Chinese T2D population. Our results demonstrated that the A allele of rs659366 is significantly associated with DR, NPDR, and PDR (Table 2), indicating that Han Chinese T2D patients who carry the A allele of rs659366 had a higher risk to develop DR. We also showed that the I allele of 3'-UTR 45-bp I/D polymorphism is significantly associated with DR, NPDR, and PDR (Table 2). However, no homozygous I allele was detected in patients with NPDR, possibly due to their smaller sample size (n = 92).

Previous reports have demonstrated that the duration of T2D and the levels of serum HbA1c and blood pressure are major factors responsible for the onset and progression of DR (Chen et al., 2014). In our study, higher systolic/diastolic blood pressure, higher Chol, BUN, CRE, and HbA1c levels, and lower apOA levels were observed. Therefore, these potential confounding factors were adjusted in the logistic regression analysis. Consistent with the univariate analysis, the AA and GA genotypes of the rs659366 polymorphisms were significantly associated with an increased risk for DR compared to the GG genotype in the codominant and dominant models (Table 3).

Shen et al. (2014) reported that T2D patients with PDR presented a higher frequency for the rs659366 G allele. However, Rudofsky et al. (2007) did not detect an association between the rs659366 polymorphism and DR in Caucasian type 2 DM patients. Our findings were consistent with the study reported by Crispim et al. (2010), wherein the A allele is a risk factor for DR. Similar to the study of Crispim et al., we detected a significant correlation between the AA genotype and PDR in the recessive model (Table 2). Several studies on rs659366 in patients with DR suggest that this polymorphism plays an important role in the onset and development of DR (Sesti et al., 2003; Sasahara et al., 2004; Crispim et al., 2010; Shen et al., 2014). However, these contradicting results may be attributed to factors such as race or sample size. A larger sample size is needed to confirm our findings. It is worth noting that studies investigating UCP2 function showed that the −866A/A genotype is associated with impaired β-cell function (Sesti et al., 2003), abnormal insulin sensitivity (D'Adamo et al., 2004), and more severe diabetes (Sasahara et al., 2004). Our results show that patients who were homozygous or heterozygous for the A allele at rs659366 were more likely to develop DR, indicating that the A allele is associated with the onset of DR in Han Chinese patients with T2D.

The 45-bp I/D polymorphism is located in the UTR of the UCP2, which controls transcription of the gene (Yanovski et al., 2000). In fetal myoblast cells, UCP2 mRNA that is transcribed from the insertion allele has a shorter half-life than that transcribed from the deletion allele (de Souza et al., 2012). Therefore, the insertion allele may affect UCP2 mRNA stability (Esterbauer et al., 2001) and could decrease UCP2 transcription. In this study, we found that patients who carry the II and DI genotypes had a higher risk for PDR, but only the DI genotype was associated with NPDR. However, we did not detect any patients with NPDR who were homozygous for the II genotype. The II genotype was observed in four patients with PDR who developed diabetes more than 10 years ago and one patient without DR who developed diabetes less than 4 years ago. Further studies with a larger sample size are needed to confirm these preliminary results.

Haplotype analysis demonstrated that the A-I haplotype was present nearly twice as much in patients with NPDR or PDR than in those without DR, while the G-D haplotype was present less frequently in patients with NPDR than in those without DR, indicating that the A-I haplotype is a risk haplotype for NPDR or PDR, whereas the G-D haplotype is a protective haplotype for NPDR. Our haplotype analysis results were in agreement with previous haplotype analyses that examined UCP2 polymorphisms between patients with DR and those without, which suggests that the A-I haplotype might be associated with decreased UCP2 expression in the human retina (Crispim et al., 2010; de Souza et al., 2012).

This study has some limitations. First, although we hypothesized that II genotypes might be associated with DR, the number of patients harboring the II genotype in our study population was too small for statistical analysis. Second, our retrospective case-control study did not have sufficient follow-up information. Third, without an a priori hypothesis, all the genetic models were tested, which may favor false-positive findings. Finally, two SNPs selected in our study might not fully explain DR risk of other variants in the UCP2 gene. We plan to screen for additional variants in this gene to determine the contribution of UCP2 to DR.

In conclusion, our results suggest that the A allele of rs659366 and the I allele of the 3'-UTR 45-bp I/D polymorphism, as well as the A-I haplotype may increase the risk for the development of DR in the Han Chinese T2D patients. To the best of our knowledge, this is the first study demonstrating that UCP2 polymorphisms are associated with both PDR and NPDR. However, more samples from other ethnic populations and functional studies are required to elucidate how the 866G/A and Ins/Del polymorphisms may influence UCP2 function in retinal cells of T2D patients individually or in combination.

Declarations

Ethics approval and consent to participate

The laboratory testing for diabetes was performed upon request by medical institutions in accordance with the Act on the Prevention and Control of Infectious Diseases. The collection of materials used in this study complied with the Helsinki Declaration.

Footnotes

Author Contributions

Y.Y. and T.-C.Z. designed the study; Y.-Y.L. and Y.Q. collected the samples and clinical information; Y.-Y.L. and L.Z. conducted the experiments; T.-C.Z. performed data analysis; and Y.Y., T.-C.Z., and L.Y. drafted the article. All authors contributed to and have approved the final article.

Acknowledgments

We are grateful to all of the participants for their willingness to participate in this study. This work was supported by grants from the Natural Science Foundation of China (No. 81760734) and the Natural Science Foundation of Yunnan Province (No. 2017FA048), Specific Association Foundation Program of Yunnan Provincial Science and Technology Department and Kunming Medical University (No. 2017FE468 and No. 2014FA016), the Fund of Diabetic Innovation Team of Yunnan Province, and Found of Yunnan Province's Key Clinical Specialties and Fund of Medical Leader in Yunnan Province (No. L-201609). The funding agency had no role in the study design, data collection, analysis, decision to publish, or preparation of the article.

Author Disclosure Statement

The authors have no competing interests to declare.

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