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. Author manuscript; available in PMC: 2016 Jun 1.
Published in final edited form as: Am J Ophthalmol. 2015 Mar 17;159(6):1152–1160.e2. doi: 10.1016/j.ajo.2015.03.008

P-selectin plasma levels and genetic variant associated with diabetic retinopathy in African Americans

Alan Penman 1, Suzanne Hoadley 2, James G Wilson 3, Herman A Taylor 4, Ching J Chen 2, Lucia Sobrin 5
PMCID: PMC4426234  NIHMSID: NIHMS672934  PMID: 25794792

Abstract

Purpose

To report the prevalence and risk factors for retinopathy in African Americans with impaired fasting glucose and type 2 diabetes in the Jackson Heart Study and to determine if P-selectin plasma levels are independently associated with retinopathy in this population.

Design

Prospective, cross-sectional observational study

Methods

Setting: Community-based epidemiologic study

Study Population: 629 patients with type 2 diabetes and 266 participants with impaired fasting glucose

Observation Procedures: Bilateral, seven-field fundus photographs were scored by masked readers for diabetic retinopathy (DR) level. Covariate data including P-selectin plasma levels and genotypes were collected in a standardized fashion.

Main Outcome Measures: Association between risk factors, including P-selectin plasma levels and genotypes, and retinopathy

Results

The prevalences of any retinopathy among participants with IFG and type 2 diabetes were 9.4% and 32.4%, respectively. Among those with type 2 diabetes, in multivariate models adjusted for age, gender and other traditional risk factors, higher Pselectin levels were associated with any DR (odds ratio =1.11, 95% confidence interval = 1.02-1.21, P=0.02) and proliferative DR (odds ratio = 1.23, 95% confidence interval = 1.03-1.46, P=0.02). To further investigate the relationship between P-selectin and DR, we examined the association between P-selectin genotype and DR. Minor allele homozygotes for the variant rs6128 were less likely to develop DR (P after Bonferroni correction = 0.03).

Conclusions

Both serologic and genetic data show an association between P-selectin and DR in the Jackson Heart Study. If confirmed in other studies, this association may provide insight into the pathogenesis of retinopathy.

Introduction

Diabetes is the leading cause of blindness among working-age adults in the United States.1 There is evidence that diabetic retinopathy (DR) is more prevalent in African Americans than non-Hispanic whites.2, 3 Epidemiologic and clinical studies have provided information regarding DR in African Americans with type 2 diabetes.2-10 Some of these studies were performed over 20 years ago when diabetes treatment options were limited and patients had poorer glycemic control. Many of these studies only used one or two photographic fields to ascertain DR. Limited field photography can lead to inaccurate DR grading as compared with dilated seven field fundus photography.11 Non-mydriatic limited field photographs are also more likely to be ungradable.12, 13 Studies have shown that subjects with ungradable photographs are more likely to have characteristics consistent with increased retinopathy risk and be African Americans.6, 7 Therefore, retinopathy may be underascertained in African Americans, particularly when a limited number of fields are photographed without pharmacologic pupil dilation.14

Longer diabetes duration, hyperglycemia and hypertension are consistent risk factors for DR,10 and there are other putative risk factors for DR. Hyperlipidemia and obesity impact DR in some, but not all, studies.15-19 Increased urinary albumin has been associated with retinopathy in some populations.20, 21 C-reactive protein has not been a biomarker for DR in most studies,22, 23 but a recent prospective investigation found an association with macular edema.24 P-selectin and E-selectin are molecules involved in leukocyte recruitment and rolling and platelet adhesion. A genetic association between variants in the P-selectin gene, SELP, and DR has been reported in Caucasians.25

Impaired fasting glucose is defined as a fasting plasma glucose between 100 and 125 mg/dl. Retinopathy develops in 7-10% of impaired fasting glucose patients,26-29 and blood pressure and body mass index have been identified as risk factors for retinopathy in Europeans with impaired fasting glucose.26 There is limited information regarding retinopathy prevalence and risk factors in African Americans with impaired fasting glucose.27

The purpose of our study was to estimate the prevalence of and identify risk factors for retinopathy ascertained with seven-field, dilated fundus photography in African Americans with impaired fasting glucose and type 2 diabetes from the Jackson Heart Study. In particular, we were interested in whether there was an association between P-selectin plasma levels and genotype and retinopathy.

Methods

All aspects of this cross-sectional observational study were prospectively approved by the Institutional Review Boards at the University of Mississippi Medical Center and Massachusetts Eye and Ear Infirmary. All participants provided written informed consent. The study was compliant with the regulations of the Health Insurance Portability and Accountability Act.

The Jackson Heart Study is a community-based observational study of cardiovascular disease among African Americans living in Mississippi.30 Standardized phenotyping protocols have measured physical characteristics at the 2004 baseline exam and subsequent exams (Exam 2 in 2005-08 and Exam 3 in 2009-12).31 We established an ancillary retinopathy study which ran concurrently with Exam 3. Jackson Heart Study participants with type 2 diabetes or impaired fasting glucose were invited to participate in the ancillary study. Diabetes was defined as (a) taking anti-diabetic medication or (b) meeting the hemoglobin A1c or fasting plasma glucose criteria for diabetes diagnosis.32 Type 2 diabetes was defined as age at diabetes diagnosis ≥ 30 years. Impaired fasting glucose was defined as specified above.

Enrolled participants had one study visit at the University of Mississippi Medical Center Department of Ophthalmology. A short questionnaire about ocular history and diabetes diagnosis was administered. Bilateral, dilated, seven-standard field fundus photographs including macular stereoscopic pairs were obtained with a TRC-50DX camera (Topcon, Tokyo, Japan). The photographs were scored contemporaneously by two independent, masked ophthalmologist-investigators with the Early Treatment Diabetic Retinopathy Study (ETDRS) scale.33 Clinically significant macular edema was deemed present if ETDRS criteria were met and/or if focal laser treatment scars were present.33 Disagreements were arbitrated by a third masked ophthalmologist-investigator and/or by joint review by the ophthalmologist-investigators. Participants were excluded only if they had another ocular disease that precluded photograph grading.

Quality metrics for contemporaneous and temporal reproducibility were assessed. Intergrader agreement was measured in terms of percentage agreement and weighted kappa. The contemporaneous intergrader exact agreement percentages for ETDRS grade and presence of clinically significant macular edema were 96.3% and 96.8%, respectively. The associated weighted kappas were 0.76 and 0.52, respectively. One hundred photographs graded in the first year were randomly selected and regraded at the study's end with readers masked to original grade assigned. For these regraded photographs, the percentages of exact agreement between the grades assigned in the first year and last year of the study were 95.5% and 94.0%, respectively, for ETDRS grade and presence of clinically significant macular edema. The corresponding weighted kappas were 0.84 and 0.48, respectively. These metrics suggest there was no systematic temporal drift in evaluating ETDRS grade and presence of clinically significant macular edema.

Covariate Data

Covariates were chosen because of association in other populations and data availability from Jackson Heart Study Exams.30 The risk factors considered were: age, gender, hemoglobin A1c, diabetes duration, body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, C-reactive protein, urine albumin, smoking status, diabetic medication use, E-selectin and P-selectin.

Covariate data was selected from the Jackson Heart Study Exam closest to the retinopathy study visit for which the participant had available data. Diabetes duration was calculated from the onset date to the retinopathy exam date. Seated blood pressure was measured three times and the mean was used in the analyses. Smoking status was defined as ever having smoked (current or past smoker) vs. never having smoked. Urine albumin was obtained from a spot urine specimen. Diabetic medication use was defined as taking any diabetic medication. Plasma E-selectin and P-selectin were quantified by enzyme-linked immunosorbent assay (R&D Systems, Minneapolis, MN). The interassay coefficients of variation for the E-selectin and P-selectin detection methods were 9.78% and 5.14%, respectively. A subset of patients in the Jackson Heart Study had been genotyped as part of a larger consortium for several vascular disease candidate genes as previously described.34 This list of candidate genes included three single nucleotide polymorphisms in SELP: rs6128, rs6133, and rs3917779.

Statistical Methods

Retinopathy status was based on the eye with the higher ETDRS level. Absence of retinopathy was defined as ETDRS level < 14. We examined three different outcomes: any retinopathy (ETDRS level ≥ 14), proliferative DR (ETDRS level ≥ 60), and clinically significant macular edema. Clinically significant macular edema was deemed present if at least one eye demonstrated clinically significant macular edema and/or focal laser scars. If one eye was ungradable, the scores for the other eye were used to define these outcomes.

We estimated the prevalence of any retinopathy in impaired fasting glucose participants and of any retinopathy, proliferative diabetic retinopathy (PDR) and clinically significant macular edema in type 2 diabetes participants. We examined risk factors in participants in our ancillary study compared with those who did not participate. Univariate analyses comparing participants with and without any retinopathy were performed separately for impaired fasting glucose and type 2 diabetes participants. For type 2 diabetes participants, univariate analyses comparing participants (1) with PDR (ETDRS level ≥ 60) and without PDR (ETDRS level < 60) and (2) with and without clinically significant macular edema were also performed. Differences in means and proportions were tested by the t-test and chi-square test, respectively. We used the subset of participants with complete information for the covariate of interest in that particular analysis to maximize generalizability and power.

To examine the association between risk factors and retinopathy, we constructed multivariate models using backward stepwise logistic regression to determine the odds ratios and 95% confidence intervals. All models were adjusted for age and gender. A P value < 0.05 was considered statistically significant. For the genetic analyses of the association between single nucleotide polymorphisms in SELP and retinopathy, the chi-square test was used to compare the frequency of minor allele homozygotes between cases and controls. The Bonferroni method was used to correct for multiple hypothesis testing. All analyses were performed using Stata/IC version 12.1(Stata, College Station, TX).

Results

From Jackson Heart Study Exams 1 and 2, we identified 1303 type 2 diabetes participants and 689 impaired fasting glucose participants. 629 type 2 diabetes and 266 impaired fasting glucose participants enrolled in the retinopathy study. Table 1 compares known DR risk factors between enrolled and nonenrolled participants. Enrolled impaired fasting glucose participants had a higher mean age and lower mean diastolic blood pressure. On average, enrolled type 2 diabetes participants had shorter diabetes duration, lower hemoglobin A1c, and lower systolic blood pressure.

Table 1.

Risk factors in Jackson Hear Study participants who enrolled vs. did not enroll in the diabetic retinopathy study.

Variable Enrolled in Retinopathy Study Not Enrolled in Retinopathy Study P value


N % or Mean (SD) N % or Mean (SD)
Impaired Fasting Glucose Participants
Age, years 266 65.7 (9.6) 423 63.0 (12.4) 0.003
Percent Females 266 59.8% 423 52.7% 0.07
Hemoglobin A1C, % 266 5.9 (0.38) 422 5.9 (0.58) 0.34
Body Mass Index, kg/m2 266 31.3 (6.0) 422 32.3 (7.0) 0.06
Waist circumference, cm 266 102.6 (13.6) 423 104.1 (16.0) 0.20
Systolic BP, mmHg 266 128.5 (16.6) 423 130.8 (18.9) 0.11
Diastolic BP, mmHg 266 74.6 (9.9) 423 76.8 (11.1) 0.01
Total Cholesterol, mg/dl 266 199.3 (37.3) 423 202.1 (39.8) 0.36
Triglycerides, mg/dl 266 103.4 (65.7) 423 102.5 (58.3) 0.86
LDL Cholesterol, mg/dl 266 121.1 (34.4) 422 125.9 (37.3) 0.09
HDL Cholesterol, mg/dl 266 57.6 (17.5) 423 55.8 (16.5) 0.16
C-reactive Protein, mg/L 266 4.4 (5.3) 423 5.5 (11.0) 0.12
Urine albumin, mg/L 259 33.7 (119.3) 391 39.0 (152.5) 0.64
Ever smoked, % 266 26.6% 423 29.3% 0.35
Type 2 Diabetes Participants
Age, years 629 66.5 (10.1) 674 66.4 (11.0) 0.95
Percent Females 629 66.1% 674 66.3% 0.94
Diabetes duration, years 629 9.6 (9.0) 655 12.0 (9.8) 7.4 × 10-6
Hemoglobin A1C, % 623 7.2 (1.6) 668 7.5 (1.8) 0.002
Body Mass Index, kg/m2 627 34.1 (6.9) 674 34.0 (7.5) 0.89
Waist circumference, cm 627 109.0 (15.2) 673 109.1 (16.2) 0.94
Systolic BP, mmHg 627 130.0 (20.2) 674 132.9(21.1) 0.01
Diastolic BP, mmHg 627 73.6 (11.1) 674 74.1 (11.7) 0.44
Total Cholesterol, mg/dl 612 188.9 (44.6) 642 190.3 (46.2) 0.58
Triglycerides, mg/dl 612 112.2 (65.4) 642 123.5 (145.2) 0.07
LDL Cholesterol, mg/dl 612 111.7 (39.6) 632 113.6 (40.7) 0.42
HDL Cholesterol, mg/dl 612 54.7 (14.8) 642 53.4 (14.9) 0.12
C-reactive Protein, mg/L 626 5.5 (7.9) 672 5.4 (9.1) 0.81
Urine albumin, mg/L 610 150.2 (621.5) 583 146.8 (526.5) 0.92
Ever smoked, % 625 33.0% 673 33.1% 0.95
Diabetic medication use 624 78.2% 667 80.7% 0.28

SD=standard deviation, BP=blood pressure, LDL= low-density lipoprotein, HDL=high-density lipoprotein

The distribution of retinopathy grades is shown in Table 2. The prevalences of any retinopathy in impaired fasting glucose and type 2 diabetes participants were 9.4% and 32.4%, respectively. No impaired fasting glucose participants had clinically significant macular edema. Among type 2 diabetes participants, 48 (7.8%) had clinically significant macular edema and 28 (4.5%) had PDR. In impaired fasting glucose participants, none of the examined covariates were associated with retinopathy in univariate or multivariate analyses.

Table 2. Distribution of diabetic retinopathy grades among impaired fasting glucose and type 2 diabetes participants in the Jackson Heart Study.

Worst Eye ETDRS Grade Impaired Fasting Glucose Participants (mean age = 65.7 years) Type 2 Diabetes Participants (mean age = 66.5 years)
Unable to grade 1 6
≤14 240 421
15 12 31
20 9 50
35 4 76
43 0 11
47 0 4
53 0 2
71 0 27
81 0 1

Total 266 629

ETDRS= Early Treatment Diabetic Retinopathy Study

In type 2 diabetes participants, longer diabetes duration, higher hemoglobin A1c, higher systolic blood pressure, greater waist circumference, higher urine albumin, diabetic medication use and higher plasma P-selectin levels were associated with retinopathy in univariate analyses (Table 3). In the multivariate model (Table 4), P-selectin levels remained significantly associated with presence of any retinopathy when controlling for other risk factors including C-reactive protein, another inflammatory biomarker. The odds of having retinopathy were 71% higher for every additional 5 years of diabetes (P=5.7×10-13), 25% higher for each percentage point increase in hemoglobin A1c (P=0.002), 13% higher for every 10 mmHg increase in systolic blood pressure (P=0.03), two-fold higher for those using a diabetic medication (P=0.04) and 11% higher for each 5 ng/ml increase in plasma P-selectin (P=0.02). Because higher P-selectin levels have been associated with cardiovascular events in other populations,35 we examined whether inclusion of history of a cardiovascular event (defined as coronary heart disease, stroke or heart failure) to the model would alter the association of P-selectin levels with presence of retinopathy, but this did not alter the results with higher Pselectin levels remaining significantly associated with retinopathy despite adjusting for cardiovascular events (P=0.01).

Table 3.

Risk factors in type 2 diabetes Jackson Heart Study participants with and without any diabetic retinopathy, proliferative diabetic retinopathy and clinically significant macular edema (univariate analyses).

Any Retinopathy (ETDRS grade ≥ 14) Proliferative Diabetic Retinopathy (ETDRS grade ≥ 60) Clinically Significant Macular Edema



No Retinopathy Retinopathy No PDR PDR No CSME CSME





Variable N % or Mean (SD) N % or Mean (SD) P valuea N % or Mean (SD) N % or Mean (SD) P valuea N % or Mean (SD) N % or Mean (SD) P valuea



Age, years 421 66.6 (9.9) 202 65.8 (10.4) 0.31 595 66.2 (10.0) 28 70.2 (9.9) 0.04 571 66.2 (9.9) 48 67.5 (11.0) 0.38
Percent Females 421 64.6% 202 69.8% 0.20 595 65.9% 28 75.0% 0.32 571 66.5% 48 64.6% 0.78
Diabetes duration, years 421 6.8 (6.9) 202 15.3 (10.1) 1.5 × 10-31 595 8.8 (8.1) 28 26.7 (9.2) 4.7 × 10-27 571 8.6 (8.2) 48 20.5 (10.1) 6.0 × 10-20
Hemoglobin A1C, % 415 6.9 (1.2) 202 7.9 (1.9) 3.5 × 10-14 589 7.2 (1.6) 28 7.8 (1.7) 0.03 565 7.1 (1.5) 48 8.2 (2.0) 2.4 × 10-6
Body Mass Index, kg/m2 419 33.8 (7.0) 202 34.6 (6.4) 0.17 593 34.0 (6.8) 28 36.7 (7.0) 0.04 569 34.0 (6.8) 48 34.6 (6.9) 0.56
Waist circumference, cm 419 108.2 (15.4) 202 111.0 (14.7) 0.03 593 108.7 (14.9) 28 117.4 (19.0) 0.003 569 108.8 (15.0) 48 112.4 (16.6) 0.11
Systolic Blood Pressure, mmHg 419 128.7 (18.4) 202 132.4 (23.4) 0.03 593 129.7 (19.8) 28 134.9 (28.3) 0.18 569 129.8 (20.1) 48 132.3 (22.2) 0.42
Diastolic Blood Pressure, mmHg 419 74.0 (10.3) 202 72.9 (12.5) 0.23 593 73.9 (10.9) 28 69.2 (13.1) 0.03 569 74.0 (10.9) 48 70.3 (12.4) 0.03
Total Cholesterol, mg/dl 412 190.0 (42.9) 194 186.5 (48.2) 0.37 579 189.6 (44.6) 27 171.8 (41.6) 0.04 556 189.0 (44.0) 46 191.2 (51.6) 0.74
Triglycerides, mg/dl 412 110.2 (62.4) 194 116.6 (71.6) 0.27 579 112.0 (65.9) 27 117.7 (56.4) 0.66 556 112.6 (66.8) 46 106.8 (48.9) 0.57
LDL Cholesterol, mg/dl 412 112.9 (39.3) 194 109.2 (40.3) 0.29 579 112.5 (39.6) 27 95.3 (35.5) 0.03 556 111.9 (39.0) 46 113.1 (45.9) 0.85
HDL Cholesterol, mg/dl 412 55.0 (15.2) 194 54.1 (13.9) 0.46 579 54.8 (14.9) 27 53.0 (12.3) 0.54 556 54.6 (14.9) 46 56.8 (12.5) 0.33
C-reactive Protein, mg/L 418 5.9 (8.7) 202 4.9 (5.9) 0.13 592 5.5 (8.0) 28 6.4 (5.0) 0.55 568 5.6 (8.2) 48 4.8 (4.5) 0.47
Urine albumin, mg/L 412 88.0 (424.6) 193 283.3 (901.3) 0.0003 581 135.8 (595.8) 24 502.1(1064.8) 0.005 555 131.0 (579.3) 46 393.0 (1013) 0.006
Ever smoked 418 33.2% 201 31.0% 0.59 592 32.3% 27 37.0% 0.60 568 32.0% 47 38.3% 0.38
Diabetic medication use 416 70.2% 202 94.6% 6.2 × 10-12 590 77.1% 28 100% 0.004 566 76.3% 48 97.9% 0.001
E-selectin, ng/ml 393 47.7 (23.8) 189 48.7 (24.5) 0.16 556 46.8 (24.2) 26 43.4 (19.9) 0.47 531 46.5 (24.5) 47 46.9 (18.5) 0.91
P-selectin, ng/ml 393 32.8 (12.2) 189 36.6 (13.2) 0.0007 556 33.8 (12.5) 26 38.9 (15.7) 0.04 531 33.7 (12.6) 47 37.3 (12.8) 0.06

SD=standard deviation, ETDRS= Early Treatment Diabetic Retinopathy Study, PDR= Proliferative Diabetic Retinopathy, CSME=Clinically Significant Macular Edema, LDL=low-density lipoprotein, HDL=high-density lipoprotein

a

T-test for continuous variables, Chi-square test for dichotomous variables

Table 4. Risk factors for any diabetic retinopathy in type 2 diabetes participants in the Jackson Heart Study: results of multivariate analyses controlling for age and gender.

Variable OR (95% CI) P value
Diabetes duration, yearsa 1.71 (1.48-1.98) 5.7 × 10-13
Hemoglobin A1C, % 1.25 (1.08-1.44) 0.002
Systolic Blood Pressure, mmHgb 1.13 (1.01-1.25) 0.03
Diabetic medication use 2.14 (1.04-4.38) 0.04
P-selectin, ng/mlc 1.11 (1.02-1.21) 0.02

OR= Odds Ratio, CI= Confidence Interval

a

Odds ratio calculated per 5 year increase in duration of diabetes

b

Odds ratio calculated per 10 mmHg increase in systolic blood pressure

c

Odds ratio calculated per 5 ng/ml increase in P-selectin level

Results for the univariate analyses for PDR are shown in Table 3. Older age, longer diabetes duration, higher hemoglobin A1c, higher body mass index, larger waist circumference, lower diastolic blood pressure, lower total cholesterol, lower low-density lipoprotein cholesterol, higher urine albumin, diabetic medication use and higher Pselectin were associated with PDR. In the multivariate model, P-selectin remained significantly associated with PDR (Table 5). The odds of having PDR were more than 2-fold higher for every 5 year increase in duration of diabetes (P=3.8×10-8), 26% higher for every 10 mmHg increase in systolic blood pressure (P=0.03), 23% higher for each 5 ng/ml increase in plasma P-selectin (P=0.02) and 2% lower for every mg/dl increase in total cholesterol (P=0.01). Again the association between P-selectin and retinopathy remained significant after controlling for history of cardiovascular events.

Table 5.

Risk factors for proliferative diabetic retinopathy in type 2 diabetes participants in the Jackson Heart Study: significant results in multivariate analyses controlling for age and gender.

Variable OR (95% CI) P value
Diabetes durationa 2.19 (1.66-2.89) 3.8 × 10-8
Systolic Blood Pressure, mmHgb 1.26 (1.02-1.57) 0.03
P-selectin, ng/mlc 1.23 (1.03-1.46) 0.02
Total cholesterol, mg/dl 0.98 (0.969-0.996) 0.01

OR= Odds Ratio, CI= Confidence Interval

a

Odds ratio calculated per 5 year increase in duration of diabetes

b

Odds ratio calculated per 10 mmHg increase in systolic blood pressure

c

Odds ratio calculated per 5 ng/ml increase in P-selectin level

Longer diabetes duration, higher hemoglobin A1c, lower diastolic blood pressure, higher urine albumin, and diabetic medication use were associated with clinically significant macular edema in univariate analyses (Table 3). In the multivariate regression model, diabetes duration and hemoglobin A1c remained significantly associated. The odds of having clinically significant macular edema were 68% higher for each 5 year increase in duration of diabetes (odds ratio=1.68, 95% confidence interval=1.42-2.00, P=1.3×10-9) and 37% higher for every hemoglobin A1c percentage point (odds ratio=1.37, 95% confidence interval=1.15-1.63, P=0.001).

To further explore the association of P-selectin with DR, we examined the association between the three variants in the SELP gene and the presence of DR. Table 6 shows the results of association testing between SELP genotypes and DR. Participants without retinopathy were more likely to be minor allele homozygotes (TT) for rs6128 than those with retinopathy (P=0.03). To investigate whether this result might be influenced by differences in the genotype distribution in the overall Jackson Heart Study participant population by glycemic status (no diabetes vs. impaired fasting glucose vs. type 2 diabetes) we examined rs6128 genotype among these three groups using the chi-square test. There was no significant difference among these groups in rs6128 genotype distribution (P=0.84). There was also no significant difference in rs6128 genotype distribution between type 2 diabetes participants who chose to enroll in the retinopathy ancillary study vs. those who did not (P=0.42). We also examined the association between P-selectin levels and SELP genotypes for these three variants. Minor allele homozygotes at rs6128 had lower mean P-selectin levels than major allele carriers (25.8 ng/ml vs. 34.5 ng/ml, P=0.046). There were no significant associations between P-selectin plasma levels and SELP genotypes for rs6133 and rs3917779.

Table 6. Association between SELP genotype and presence of any diabetic retinopathy in the Jackson Heart Study.

No Retinopathy Retinopathy

SELP SNP N % Minor allele homozygotes N % Minor allele homozygotes P valuea
rs6128 (C/T) 174 5.7% 102 0% 0.03
rs6133 (A/C) 135 19.3% 71 16.9% 0.68
rs3917779 (A/G) 135 24.4% 50 26.8% 0.72

SNP= Single nucleotide polymorphism

a

corrected for multiple hypothesis testing by Bonferroni method

Discussion

Our ancillary study of DR in the Jackson Heart Study provides information about retinopathy and its risk factors in African Americans with impaired fasting glucose and type 2 diabetes using gold standard seven-field fundus photography in the era of enhanced options for glycemic control. We confirmed the well-established risk factors for DR - increased duration of diabetes, poor glycemic control and hypertension – in the Jackson Heart Study. In addition, we have found a novel association between Pselectin plasma levels and DR in this African American cohort and as well as an association between P-selectin genotype and presence of retinopathy.

When we compare our study's 9.4% retinopathy prevalence in African Americans with impaired fasting glucose with that reported for other ethnic groups with impaired fasting glucose, we find the results to be consistent. Studies of Caucasians and Asians with impaired fasting glucose have found retinopathy prevalences of 10% and 10.3%, respectively.26, 28 One study of participants with impaired fasting glucose and/or impaired glucose tolerance, another pre-diabetic state, found a 6.7% retinopathy prevalence.29 The Diabetes Prevention Program which included multiple ethnicities found a 7.9% retinopathy prevalence among participants with impaired fasting glucose and/or impaired glucose tolerance.27 Our data reinforces that retinopathy can develop in some patients before the onset of overt type 2 diabetes.

We did not find any traditional DR risk factors, P-selectin or E-selectin to be associated with retinopathy in impaired fasting glucose participants. One study found increased blood pressure and body mass index to be risk factors for retinopathy in Europeans with impaired fasting glucose,26 but this has not seen by other investigators.29 The lack of an association with blood pressure, body mass index and other risk factors could explained by the limited number of impaired fasting glucose participants with retinopathy (n=25) or by varying risk factors profiles in different populations.

When we compare the 32.4% retinopathy prevalence in type 2 diabetic participants in this study with that reported in African Americans in other relatively recent studies, the results are also consistent. In the Veterans Affairs Diabetes Trial published in 2005, the retinopathy prevalence was 29% among African Americans.36 In the Multi-Ethnic Study of Atherosclerosis published in 2006, African Americans had a retinopathy prevalence of 37%.8 In the National Health and Nutrition Examination Survey 2005-2008 study, the crude DR prevalence was 38.8% among non-Hispanic blacks.2 Of note, the participants who enrolled in our ancillary study were more likely to have better glycemic control, shorter diabetes duration, and lower systolic blood pressure than those who did not enroll. Since these are significant retinopathy risk factors in our cohort, it is likely that the DR prevalence in the entire group of Jackson Heart Study type 2 diabetes participants is higher. The prevalences of PDR and clinically significant macular edema in the Jackson Heart Study are also in line with those observed in other populations.8, 10

The presence of any DR in the type 2 diabetes participants was associated with longer diabetes duration, poorer glycemic control and higher systolic blood pressure. This is consistent with other studies of DR in type 2 diabetes.2, 5-8, 10 Longer duration of diabetes and higher systolic blood pressure were associated with PDR but hemoglobin A1c was not. This same lack of association between hemoglobin A1c and PDR has been found in a Latino population.19 The association between hemoglobin A1c and DR may weaken with more advanced forms of retinopathy. One explanation for this phenomenon is that the diagnosis of PDR can be the impetus for tighter blood sugar control. Patients with PDR may be motivated to achieve better hemoglobin A1c levels after receiving this diagnosis and their hemoglobin A1c after PDR diagnosis may be not be reflective of their glycemic control for the majority of the duration of their diabetes.

In the univariate analyses, we found that higher plasma P-selectin levels were associated with DR and PDR. These associations remained significant in the multivariate models that controlled for both C-reactive protein, another measure of inflammation, and cardiovascular events, which have been associated with higher Pselectin levels. P-selectin is a protein that functions as a cell adhesion molecule on the surface of activated endothelial cells and platelets. Previous studies have not found an independent association between P-selectin and DR,37, 38 but these studies were smaller than the current investigation. Other lines of evidence also suggest P-selectin could play a role in DR. P-selectin is found in fibrovascular membranes removed from patients with PDR.39 An association between single nucleotide polymorphisms in the gene that encodes P-selectin, SELP, and DR was previously found in Caucasians although it has not been independently replicated.25 In the current study we found an association between one of these single nucleotide polymorphisms, rs6128, and presence of any DR in African Americans. The direction of effect was the same as in Caucasians with the minor allele, T, conferring a decreased risk of DR. The previous study had looked at this SNP in African Americans from other cohorts, including a small subset of the participants from the Jackson Heart Study, and did not find the association.25 Most of the African Americans in the cohorts used in the previous study were phenotyped with a limited number of non-dilated fields in each eye which may have contributed to the null findings. In the current study, we verified that there were no differences in the rs6128 genotype distribution in Jackson Heart Study participants by glycemic status nor in participants who enrolled in the retinopathy study vs. those who did not. This makes it less likely that there are skews in the genotype distribution in the larger or nonenrolled Jackson Heart Study population that would explain the observed association between rs6128 genotype and retinopathy.

We also found an association between SELP genotype and P-selectin levels with major allele carriers having higher plasma P-selectin levels. Higher P-selectin levels may indicate that patients with DR have greater activation of their endothelial cells and platelets than those without DR. More study is required to understand if the elevated Pselectin levels are an initiating event in DR pathogenesis or whether they are a downstream product of a higher propensity for microvascular damage in these patients. The association between SELP genotype, P-selectin levels and DR status suggest it is possible that P-selectin levels have an upstream effect on DR development.

The strengths of this study include the excellent phenotyping with dilated, seven-field retinal photography; the largest single sample of African Americans with type 2 diabetes and retinopathy data to date; and novel data on impaired fasting glucose and retinopathy in African Americans. There are also limitations to our study. Mydriatic retinal photography is the most effective DR detection strategy with a higher sensitivity than ophthalmoscopy.40 However, ideally, photography could be supplemented with ophthalmoscopy for cases where photographs are ungradable,40 but we did not have ophthalmoscopic data available. A reading center was not used for photograph grading, but readers were ophthalmologists and quality metrics indicated high intergrader agreement and no significant temporal drift in severity grading. Focal laser scars were used as a criterion to ascertain clinically significant macular edema and might have falsely increased clinically significant macular edema cases as focal laser could have been performed, depending on the physician's discretion, for microaneurysms threatening the fovea but not actually causing clinically significant macular edema. Because of the varied Jackson Heart Study recruitment methods, the sample is not statistically representative of the population and therefore results are not directly generalizable to all African Americans. Although we had very high rates of completeness for covariate data, this data was not always available from the Jackson Heart Study Main Exam that was contemporaneous with our ancillary study, and this could introduce some imprecision for detecting associations. The cross-sectional design limits our ability to judge the causal relationships of the associations found. Finally, for the genotype associations, only a subset of participants had consented to genotyping so the power to detect modest genetic effects was limited.

In summary, we present new data on the retinopathy frequency in African Americans with impaired fasting glucose and updated data on DR prevalence in African Americans with type 2 diabetes in the modern era of increased options for glycemic control. We confirm the associations of DR with longer diabetes duration, hyperglycemia and increased systolic blood pressure. We also report a novel association of DR with plasma P-selectin levels which remained significant after adjustment for other known risk factors, as well as an association between SELP rs6128 genotype and presence of DR. Further investigation of these associations in other DR cohorts is required to confirm the potential relationship between P-selectin and retinopathy.

Acknowledgments

Funding/Support: National Eye Institute K12-EY16335, Bethesda, MD; Research to Prevent Blindness Career Development Award and William & Mary Greve Special Scholar Award, New York City, NY; Harvard Catalyst | The Harvard Clinical and Translations Science Center Faculty Fellowship, Boston, MA, Massachusetts Lions Eye Research Fund, Abington, MA; Eleanor and Miles Shore Fellowship, Boston, MA; Sara Elizabeth O'Brien Trust, Boston, MA. The Jackson Heart Study is supported by contracts HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, and HHSN268201300050C from the National Heart, Lung and Blood Institute and the National Institute on Minority Health and Health Disparities, Bethesda, MD.

None

Biographies

Dr. Penman is a Professor in the Center of Biostatistics and Bioinformatics and the Department of Medicine at the University of Mississippi Medical Center, Jackson, Mississippi. He is the medical statistician for the Jackson field site of the Atherosclerosis Risk in Communities Study, and directs and teaches courses in biostatistics, epidemiology, public health, and disease prevention. He is a listed author on more than 60 peer-reviewed publications.

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Dr. Lucia Sobrin is an Associate Professor of Ophthalmology at Harvard Medical School and a member of the Retina and Uveitis Services of the Massachusetts Eye and Ear Infirmary. Her primary research interest is in the epidemiology and genetics of diabetic retinopathy, particularly in African American populations. Her primary clinical interests are diabetic retinopathy and posterior uveitis, and she performs clinical outcomes research in uveitis.

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Footnotes

Financial Disclosures: Dr. Sobrin is a consultant for Santen (Osaka, Japan). Dr. Chen is a member of the clinical advisory board for Allergan (Irvine, California).

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References

  • 1.National Institute of Diabetes and Digestive and Kidney Diseases. National Diabetes Statistics. Bethesda, MD: US Department of Health and Human Services, National Institute of Health; 2011. Publication No 11-3892. [Google Scholar]
  • 2.Zhang X, Saaddine JB, Chou CF, et al. Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649–656. doi: 10.1001/jama.2010.1111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Varma R, Bressler NM, Doan QV, et al. Prevalence of and risk factors for diabetic macular edema in the United States. JAMA Ophthalmol. 2014;132(11):1334–1340. doi: 10.1001/jamaophthalmol.2014.2854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Munoz B, West SK, Rubin GS, et al. Causes of blindness and visual impairment in a population of older Americans: The Salisbury Eye Evaluation Study. Arch Ophthalmol. 2000;118(6):819–825. doi: 10.1001/archopht.118.6.819. [DOI] [PubMed] [Google Scholar]
  • 5.Klein R, Klein BE, Moss SE, Linton KL. The Beaver Dam Eye Study. Retinopathy in adults with newly discovered and previously diagnosed diabetes mellitus. Ophthalmology. 1992;99(1):58–62. doi: 10.1016/s0161-6420(92)32011-1. [DOI] [PubMed] [Google Scholar]
  • 6.Klein R, Marino EK, Kuller LH, et al. The relation of atherosclerotic cardiovascular disease to retinopathy in people with diabetes in the Cardiovascular Health Study. Br J Ophthalmol. 2002;86(1):84–90. doi: 10.1136/bjo.86.1.84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Klein R, Sharrett AR, Klein BE, et al. The association of atherosclerosis, vascular risk factors, and retinopathy in adults with diabetes: the Atherosclerosis Risk in Communities Study. Ophthalmology. 2002;109(7):1225–1234. doi: 10.1016/s0161-6420(02)01074-6. [DOI] [PubMed] [Google Scholar]
  • 8.Wong TY, Klein R, Islam FM, et al. Diabetic retinopathy in a multi-ethnic cohort in the United States. Am J Ophthalmol. 2006;141(3):446–455. doi: 10.1016/j.ajo.2005.08.063. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Davis MD, Fisher MR, Gangnon RE, et al. Risk factors for high-risk proliferative diabetic retinopathy and severe visual loss: Early Treatment Diabetic Retinopathy Study Report #18. Invest Ophthalmol Vis Sci. 1998;39(2):233–252. [PubMed] [Google Scholar]
  • 10.Yau JW, Rogers SL, Kawasaki R, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012;35(3):556–564. doi: 10.2337/dc11-1909. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Vujosevic S, Benetti E, Massignan F, et al. Screening for diabetic retinopathy: 1 and 3 nonmydriatic 45-degree digital fundus photographs vs 7 standard early treatment diabetic retinopathy study fields. Am J Ophthalmol. 2009;148(1):111–118. doi: 10.1016/j.ajo.2009.02.031. [DOI] [PubMed] [Google Scholar]
  • 12.Pugh JA, Jacobson JM, Van Heuven WA, et al. Screening for diabetic retinopathy. The wide-angle retinal camera. Diabetes Care. 1993;16(6):889–895. doi: 10.2337/diacare.16.6.889. [DOI] [PubMed] [Google Scholar]
  • 13.Williams GA, Scott IU, Haller JA, et al. Single-field fundus photography for diabetic retinopathy screening: a report by the American Academy of Ophthalmology. Ophthalmology. 2004;111(5):1055–1062. doi: 10.1016/j.ophtha.2004.02.004. [DOI] [PubMed] [Google Scholar]
  • 14.Baker RS. Diabetic retinopathy in African Americans: vision impairment, prevalence, incidence, and risk factors. Int Ophthalmol Clin. 2003;43(4):105–122. doi: 10.1097/00004397-200343040-00011. [DOI] [PubMed] [Google Scholar]
  • 15.Klein BE, Moss SE, Klein R, Surawicz TS. The Wisconsin Epidemiologic Study of Diabetic Retinopathy. XIII. Relationship of serum cholesterol to retinopathy and hard exudate. Ophthalmology. 1991;98(8):1261–1265. doi: 10.1016/s0161-6420(91)32145-6. [DOI] [PubMed] [Google Scholar]
  • 16.Chew EY, Klein ML, Ferris FL, 3rd, et al. Association of elevated serum lipid levels with retinal hard exudate in diabetic retinopathy. Early Treatment Diabetic Retinopathy Study (ETDRS) Report 22. Arch Ophthalmol. 1996;114(9):1079–1084. doi: 10.1001/archopht.1996.01100140281004. [DOI] [PubMed] [Google Scholar]
  • 17.Stratton IM, Kohner EM, Aldington SJ, et al. UKPDS 50: risk factors for incidence and progression of retinopathy in Type II diabetes over 6 years from diagnosis. Diabetologia. 2001;44(2):156–163. doi: 10.1007/s001250051594. [DOI] [PubMed] [Google Scholar]
  • 18.van Leiden HA, Dekker JM, Moll AC, et al. Risk factors for incident retinopathy in a diabetic and nondiabetic population: the Hoorn study. Arch Ophthalmol. 2003;121(2):245–251. doi: 10.1001/archopht.121.2.245. [DOI] [PubMed] [Google Scholar]
  • 19.Nittala MG, Keane PA, Zhang K, Sadda SR. Risk factors for proliferative diabetic retinopathy in a Latino American population. Retina. 2014;34(8):1594–1599. doi: 10.1097/IAE.0000000000000117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Lee WJ, Sobrin L, Lee MJ, et al. The relationship between diabetic retinopathy and diabetic nephropathy in a population-based study in Korea (KNHANES V-2, 3) Invest Ophthalmol Vis Sci. 2014;55(10):6547–6553. doi: 10.1167/iovs.14-15001. [DOI] [PubMed] [Google Scholar]
  • 21.Lunetta M, Infantone L, Calogero AE, Infantone E. Increased urinary albumin excretion is a marker of risk for retinopathy and coronary heart disease in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract. 1998;40(1):45–51. doi: 10.1016/s0168-8227(98)00024-2. [DOI] [PubMed] [Google Scholar]
  • 22.Laursen JV, Hoffmann SS, Green A, et al. Associations between diabetic retinopathy and plasma levels of high-sensitive C-reactive protein or von Willebrand factor in long-term type 1 diabetic patients. Curr Eye Res. 2013;38(1):174–179. doi: 10.3109/02713683.2012.713153. [DOI] [PubMed] [Google Scholar]
  • 23.Lim LS, Tai ES, Mitchell P, et al. C-reactive protein, body mass index, and diabetic retinopathy. Invest Ophthalmol Vis Sci. 2010;51(9):4458–4463. doi: 10.1167/iovs.09-4939. [DOI] [PubMed] [Google Scholar]
  • 24.Muni RH, Kohly RP, Lee EQ, et al. Prospective study of inflammatory biomarkers and risk of diabetic retinopathy in the diabetes control and complications trial. JAMA Ophthalmol. 2013;131(4):514–521. doi: 10.1001/jamaophthalmol.2013.2299. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Sobrin L, Green T, Sim X, et al. Candidate gene association study for diabetic retinopathy in persons with type 2 diabetes: the Candidate gene Association Resource (CARe) Invest Ophthalmol Vis Sci. 2011;52(10):7593–7602. doi: 10.1167/iovs.11-7510. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Tyrberg M, Melander A, Lovestam-Adrian M, Lindblad U. Retinopathy in subjects with impaired fasting glucose: the NANSY-Eye baseline report. Diabetes Obes Metab. 2008;10(8):646–651. doi: 10.1111/j.1463-1326.2007.00759.x. [DOI] [PubMed] [Google Scholar]
  • 27.The prevalence of retinopathy in impaired glucose tolerance and recent-onset diabetes in the Diabetes Prevention Program. Diabet Med. 2007;24(2):137–144. doi: 10.1111/j.1464-5491.2007.02043.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Kawasaki R, Wang JJ, Wong TY, Kayama T, Yamashita H. Impaired glucose tolerance, but not impaired fasting glucose, is associated with retinopathy in Japanese population: the Funagata study. Diabetes Obes Metab. 2008;10(6):514–515. doi: 10.1111/j.1463-1326.2007.00824.x. [DOI] [PubMed] [Google Scholar]
  • 29.Wong TY, Barr EL, Tapp RJ, et al. Retinopathy in persons with impaired glucose metabolism: the Australian Diabetes Obesity and Lifestyle (AusDiab) study. Am J Ophthalmol. 2005;140(6):1157–1159. doi: 10.1016/j.ajo.2005.07.030. [DOI] [PubMed] [Google Scholar]
  • 30.Taylor HA, Jr, Wilson JG, Jones DW, et al. Toward resolution of cardiovascular health disparities in African Americans: design and methods of the Jackson Heart Study. Ethn Dis. 2005;15(4 Suppl 6):S6–4. 17. [PubMed] [Google Scholar]
  • 31.Wilson JG, Rotimi CN, Ekunwe L, et al. Study design for genetic analysis in the Jackson Heart Study. Ethn Dis. 2005;15(4 Suppl 6):S6–30. 37. [PubMed] [Google Scholar]
  • 32.Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care. 2003;26(Suppl 1):S5–20. doi: 10.2337/diacare.26.2007.s5. [DOI] [PubMed] [Google Scholar]
  • 33.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. 1991;98(5 Suppl):786–806. [PubMed] [Google Scholar]
  • 34.Musunuru K, Lettre G, Young T, et al. Candidate gene association resource (CARe): design, methods, and proof of concept. Circ Cardiovasc Genet. 2010;3(3):267–275. doi: 10.1161/CIRCGENETICS.109.882696. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Ridker PM, Buring JE, Rifai N. Soluble P-selectin and the risk of future cardiovascular events. Circulation. 2001;103(4):491–495. doi: 10.1161/01.cir.103.4.491. [DOI] [PubMed] [Google Scholar]
  • 36.Emanuele N, Sacks J, Klein R, et al. Ethnicity, race, and baseline retinopathy correlates in the veterans affairs diabetes trial. Diabetes Care. 2005;28(8):1954–1958. doi: 10.2337/diacare.28.8.1954. [DOI] [PubMed] [Google Scholar]
  • 37.Gustavsson C, Agardh E, Bengtsson B, Agardh CD. TNF-alpha is an independent serum marker for proliferative retinopathy in type 1 diabetic patients. J Diabetes Complications. 2008;22(5):309–316. doi: 10.1016/j.jdiacomp.2007.03.001. [DOI] [PubMed] [Google Scholar]
  • 38.Lip PL, Jones AF, Price N, et al. Do intraocular angiotensin II levels, plasma prothrombotic factors and endothelial dysfunction contribute to proliferative diabetic retinopathy? Acta Ophthalmol Scand. 1998;76(5):533–536. doi: 10.1034/j.1600-0420.1998.760504.x. [DOI] [PubMed] [Google Scholar]
  • 39.Limb GA, Chignell AH, Green W, LeRoy F, Dumonde DC. Distribution of TNF alpha and its reactive vascular adhesion molecules in fibrovascular membranes of proliferative diabetic retinopathy. Br J Ophthalmol. 1996;80(2):168–173. doi: 10.1136/bjo.80.2.168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Hutchinson A, McIntosh A, Peters J, et al. Effectiveness of screening and monitoring tests for diabetic retinopathy--a systematic review. Diabet Med. 2000;17(7):495–506. doi: 10.1046/j.1464-5491.2000.00250.x. [DOI] [PubMed] [Google Scholar]

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