Abstract
Retinopathy is a microvascular complication of diabetes mellitus (DM); however, it is also increasingly recognized in persons without DM. The microvascular diseases may play a prominent role in coronary heart disease (CHD) development in individuals with DM. We performed the study to evaluate the relation between non-DM retinopathy and CHD and also the association between baseline retinopathy and incidence and progression of CHD in individuals with and without DM. We included 5709 subjects with and without DM from the Multi-Ethnic Study of Atherosclerosis, who had retinal photos and coronary artery calcium score (CACS) available. We studied the association between baseline retinopathy and incidence and progression of coronary artery calcification (CAC) in subjects with and without DM. In DM group, the presence of retinopathy was significantly associated with an increased rate of CAC (RR 1.3 (95% CI [1.02, 1.66]) after adjusting for age, sex, race, follow-up time, and CHD risk factors. In non-DM group, the presence of retinopathy was not significantly associated with increased risk of CAC, however, the interaction between presence of retinopathy and DM status was not statistically significant. Within the DM group with CAC present at baseline, the presence of retinopathy was significantly associated with greater CAC progression (113 Agatson units (AU) greater, (95% CI [51–174]). In the non-DM group with present CAC at baseline; the presence of retinopathy was associated with 24 (95% CI [−0.69, 48.76]) AU higher CAC progression. All findings were adjusted for CHD risk factors. In conclusion, after adjustment for major CHD risk factors, retinopathy was associated with progression of CAC in both DM and non-DM individuals. However, the association was stronger in those with DM.
Background
Diabetic retinopathy is a microvascular complication of diabetes mellitus (DM). DR presents the physician with the unique opportunity to directly visualize anatomical changes and grade the progression of the disease.1 Retinopathy in persons without DM is thought to be a sign of microvascular disease.2 Coronary heart disease (CHD) is a leading cause of death, particularly among persons with type 2 DM (DM2).3 Microvascular disease may play a prominent role in CHD development in individuals with DM4. There is an emerging recognition that persons with retinal microvascular signs are at higher risk of cardiovascular diseases (CVD) including stroke and CHD.5 These findings support the concept that retinal microvascular signs, unique morphologic pathologies directly observable in vivo, may represent new biomarkers of CHD risk. Coronary artery calcification (CAC) is an independent predictor of CHD risk, and retinopathy is reported to associate independently with CAC.6 Studies have shown independent relation between retinal microaneurysms (MA) and CHD in patients with DM.1,7 Also, studies have shown a correlation between MA count and progression or regression of DR;8,9 however, none of these studies have used CAC as an indicator of CHD or associated retinopathy with the progression of CAC. In this study, we associated retinopathy with the incidence and progression of CAC in both DM and non-DM individuals.
Methods
All research involving human participants have been approved by Institutional Review Board at all participating sites. Written informed consent was obtained from the participants and saved either as a hard copy or an electronic copy in the patient’s charts at all participating sites. Multi-Ethnic Study of Atherosclerosis (MESA) is a multicenter, prospective cohort study of subclinical CVD. Details about the study design and objectives have been published.10 Briefly, 6814 men and women from 4 ethnic origins (Caucasian, African American, Hispanic American, and Asian American), aged 45 to 84 years and free of clinically diagnosed CVD, were enrolled from 6 US field centers (Baltimore City/Baltimore County, MD; Chicago, IL; Forsyth County, NC; Los Angeles County, CA; Northern Manhattan/the Bronx, NY; and St. Paul, MN). MESA participants who had retinal photographs at Exam 2 were eligible for this study.
Details on the retinal photography protocol and measurements have been published previously6. Both eyes were photographed using a 45-degree digital non-mydriatic camera. The images were read at the University of Wisconsin, Madison, and evaluators were masked to the participant’s characteristics. Retinal microvascular signs were defined by the Early Treatment DR Study (ETDRS)11 severity scale. Five retinal signs were considered: 1) Presence of any retinopathy (ETDRS level 14 and higher); 2) ETDRS level 20; microaneurysm (MA) only group; 3) Presence of focal arteriolar narrowing; 4) AV nicking, and 5) Retinal vessel calibers (the central retinal arteriolar equivalent [CRAE] and the central retinal venular equivalent [CRVE]).
Methods of obtaining and interpreting the Computed Tomographic (CT) scans have been published previously12. Baseline images were obtained using ECG gating10 during a single breath-hold by using an ECG-triggered electron-beam CT scanner or prospective ECG- triggered scan acquisition at 50% of the RR interval with a multi-detector computed tomography scanner. All images were read at the Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center (Torrance, CA) as the reading center using an interactive scoring system similar to what has been described by Yaghoubi et al13 The mean Agatston score obtained from two scans was used in all analyses for each subject.14 Excellent intra-observer and interobserver agreement (kappa statistics, 0.93, and 0.90, respectively) were achieved. Calcium scores were measured on exam 1 and then on exams 2, 3, and 4 (on 50%, 50%, and 25% of cases respectively), and incidence and progression of coronary artery calcium were measured.
At the baseline visit, age, race/ethnicity, smoking status, medication use, body mass index (BMI) (kg/m2), and resting blood pressures were recorded. Fasting cholesterol and glucose levels were measured at the collaborative studies’ clinical laboratory at Fairview-University Medical Center (Minneapolis, MN). Total and high-density lipoproteincholesterol (TC, HDL-C) were measured using cholesterol oxidase methods. Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald equation when triglyceride <400 mg/dl. Diagnosis of dyslipidemia was based on the set criteria and use of lipid-lowering medications15. Serum C-reactive protein (CRP) was measured using the BNII nephelometer (N High Sensitivity CRP; Dade Behring Inc, Deerfield, IL) at the Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT. The inter-assay coefficient of variation ranged from 2.1% to 5.7%. Serum Fibrinogen was quantitatively measured by immunoprecipitation of fibrinogen antigen using the BNII nephelometer (N-Antiserum to Human Fibrinogen, Dade-Behring Inc, Deerfield, IL). Its intra-and inter-assay coefficients of variation were 2.7% and 2.6%, respectively.
Height was measured to the nearest 0.1 cm with the subject in the stocking while weight was measured to the nearest pound with the subject in light clothing using a balanced scale and BMI was calculated by dividing weight in kilograms by height in meters squared. Using a Dinamap model Pro 100 automated sphygmomanometer (Critikon, Tampa, FL); right arm resting seated BP was measured three times at 1-minute intervals with an average of the last two readings used for analysis. Hypertension was defined as receiving antihypertensive medications or a systolic blood pressure (SBP), ≥140 mm Hg or diastolic blood pressure (DBP), ≥90 mm Hg.16 DM was defined as receiving hypoglycemic medications or fasting blood glucose of ≥126 mg/dl. Measurements for calculation of Ankle Brachial Index (ABI) were obtained using a hand-held Doppler instrument with a 5-MHz probe (Nicolet Vascular, Golden, Colorado). Smoking status was categorized as never, former, or current. We assessed the demographic and socioeconomic data: age, gender, race/ethnicity, income, educational attainment, and marital status. We looked for potential confounders or risk factors, such as cigarette smoking status, pack-years of cigarette smoking; alcohol use, SBP, DBP, waist circumference, BMI, DM medications, TC, HDL-C and LDL-C, triglycerides, and use of lipid-lowering agents.
After excluding the participants missing DM status, evaluation of retinopathy at baseline, or follow-up CT scan for CAC, 5709 participants were included in the analysis. Incident CAC was defined as new onset of CAC at any of the follow-up exams (exam 2 or 3 or 5) among the participants free of detectable CAC at baseline (if a participant had no onset of CAC, he/she was considered to be at risk at the longer follow-up exam); CAC progression as a continuous variable was defined as the difference between the baseline CAC score and the follow-up CAC score according to the longest follow-up time. The association between the presence of retinopathy and progression of CAC was evaluated in both DM and non-DM participants separately and compared between the two groups by testing the interaction between DM status and presence of retinopathy in the pooled sample. The association between the grades of retinopathy (mild, moderate, severe) and progression of CAC was also evaluated in DM and non-DM groups.
Relative risk regression with robust standard models17 was used to model the probability of incident CAC among those free of CAC at baseline. Since the exact time for incident CAC development was not measured, a relative risk model adjusting for the follow-up time was determined to be more plausible than the survival model. Among those with detectable CAC at baseline, robust regression models were used to model the change in CAC between exams, accounting for the influence of outliers. CAC progression was modeled while adjusting for the follow-up time, an analogous approach as the model for incident CAC.
Four sets of statistical models for retinopathy were built, ranging from the simplest model to the most complicated ones: adjusting for demographics including age, sex, race, and follow-up time (model A); adjusting for variables in model A plus CHD risk factors including SBP, TC, HDL-C, LDL-C, triglycerides, anti-hypertensive medications, lipid-lowering medications, smoking (model B); adjusting for variables in model B plus other CHD risk factors and inflammatory markers including BMI, the logarithm of CRP, fibrinogen, the logarithm of HbA1c, the logarithm of creatinine, fasting blood glucose, albuminuria, ABI, use of insulin or oral hypoglycemics and family history of myocardial infarction (model C); adjusting for variables in model C plus CRAE and CRVE (model D). We used Model B as our primary model while used Model C/D to evaluate how the association would be attenuated by other CHD risk factors and CRAE/CRVE. All analyses were conducted using R version 2.13.0 (R Foundation for Statistical Computing, Vienna, Austria) and SAS 9.2 (SAS Institute Inc, Cary, NC).
Results
From MESA visit 2 data (immediately after baseline visit), there are 619 subjects with retinopathy based on their most severely affected eye (~65% of whom had both eyes affected). The baseline characteristics for all four groups have been shown in Table 1. Sample sizes for 4 different groups based on presence and absence of retinopathy and/or DM were 248 retinopathy +DM+, 602 retinopathy –DM+, 371 retinopathy retinopathy +DM−, and 4488 retinopathy −DM− respectively. On the eye exam, retinopathy +DM+ individuals were more likely to have pure MAs and CRAE while retinopathy +DM− were also more likely to have MAs only, AV nicking, and CRAE. In the non-DM group, those with retinopathy were more likely to have CACS >0 (Table 1).
Table 1.
Distribution of baseline characteristics (mean (SD) or frequency (%)) for combinations of diabetes mellitus and retinopathy status
| Diabetes Mellitus | ||||||
|---|---|---|---|---|---|---|
|
|
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| Yes | No | |||||
|
|
|
|||||
| Variables | Retinopathy (n = 248) | No retinopathy (n = 602) | p* | Retinopathy* (n = 371) | No retinopathy (n = 4488) | p |
|
| ||||||
| Age (Years) | 63.3 (9.5%) | 63.7 (9.3%) | 0.50 | 61.7 (10 %) | 61.2 (10.1%) | 0.361 |
| Men | 131 (52.8%) | 316 (52.5%) | 0.99 | 195 (52.6%) | 2090 (46.6%) | 0.03 |
| White | 40 (16.1%) | 155 (25.7%) | 149 (40.2%) | 1932 (43%) | ||
| Chinese American | 25 (10.15) | 73 (12.1%) | 59 (15.9%) | 522 (11.6%) | ||
| Black | 101 (40.7%) | 204 (33.9%) | 101 (27.2%) | 1125 (25.1%) | ||
| Hispanic | 82 (33.1%) | 170 (28.2%) | 0.01 | 62 (16.7%) | 909 (20.3%) | 0.034 |
| Income >25 k | 134 (57%) | 353 (61.4%) | 0.29 | 257 (71%) | 3173 (73%) | 0.443 |
| Education (high school or less as reference) | ||||||
| Some college | 75 (30.2%) | 161 (26.7%) | 116 (31.4%) | 1279 (28.6%) | ||
| Bachelor’s degree | 30 (12.1%) | 89 (14.8%) | 48 (13%) | 867 (19.4%) | ||
| Graduate/ professional degree | 27 (10.9%) | 73 (12.1%) | 0.59 | 82 (22.2%) | 904 (20.2%) | 0.026 |
| Single/Divorced | 134 (54%) | 366 (61.1%) | 0.07 | 227 (61.5%) | 2783 (62.8%) | 0.667 |
| Waist Circumstance (cm) | 105 (14.61%) | 105 (13.82%) | 0.1 | 98.3 (13.8%) | 96.6 (14%) | 0.02 |
| BMI (Kg/m2) | 30.3 (5.78%) | 30.8 (5.79%) | 0.22 | 28.6 (5.4%) | 27.8(5.2%) | 0.014 |
| Smoker (never as reference) | ||||||
| Former | 90 (36.3%) | 240 (39.9%) | 128 (34.6%) | 1644 (36.7%) | ||
| Current | 25 (10.1%) | 78 (13%) | 0.195 | 49 (13.2%) | 552 (12.3%) | 0.683 |
| Cigarette PY | 9.19 (18.89%) | 13.53 (235) | 0.005 | 9.9 (18.2%) | 10.9 (22.6%) | 0.314 |
| Alcohol use (never as reference) | ||||||
| Former | 91 (37%) | 186 (30.9%) | 79 (21.6%) | 935 (21%) | ||
| Current | 91 (37%) | 284 (47.3%) | 0.024 | 212 (60%) | 2660 (60%) | 0.796 |
| SBP (mm Hg) | 191.7 (44.3%) | 188.9 (37.2%) | 0.061 | 131 (21.6%) | 124 (20.6%) | <0.001 |
| DBP (mm Hg) | 46.4 (12.2%) | 45.8 (12.3%) | 0.289 | 75.2 (10.5%) | 71.6 (10.8%) | <0.001 |
| HR (bpm) | 114.5 (34.3%) | 111.7 (32.9%) | 0.006 | 55.8 (16.7%) | 52.6 (16.4%) | <0.001 |
| Total cholesterol (mg/dl) | 4.9 (0.6%) | 4.9 (0.6%) | 0.368 | 194.6 (34.1%) | 195 (34.6%) | 0.825 |
| HDL (mg/dl) | 0.95 (1.2%) | 0.9 (1.2%) | 0.479 | 49.8 (13.7%) | 52.1 (15%) | 0.002 |
| LDL (mg/dl) | 374.5 (83.3%) | 356.8 (77.5%) | 0.286 | 120.3 (31%) | 117.9 (30.5%) | 0.142 |
| Triglycerides, log | 2 (0.2%) | 1.9 (0.2%) | 0.137 | 4.7 (0.5%) | 4.7 (0.5%) | 0.96 |
| CRP, log | −0.1 (0.3%) | −0.1 (0.3%) | 0.38 | 0.6 (1.3%) | 0.6 (1.14%) | 0.978 |
| Fibrinogen mg/dl | 160.3 (65.7%) | 131.4 (39.6%) | 0.004 | 345.6 (70.9%) | 340.8 (70.19%) | 0.212 |
| HbA1c, log | 134 (22.9) | 130.9 (19.7) | <0.001 | 1.7 (0.08) | 1.7 (0.08) | 0.142 |
| Creatinine, log | 71.7 (10.71%) | 72.5 (10.12%) | 0.544 | −0.05 (0.2%) | −0.07 (0.21%) | 0.122 |
| FBS (mg/dL) | 62.3 (20.07%) | 58.3 (15.9%) | <0.001 | 90.8 (10%) | 88.5 (9.67%) | <0.001 |
| Microalbuminuria mcg/min | 63 (25.7%) | 88 (14.7%) | 21 (5.7%) | 234 (5.2%) | ||
| Macroalbuminuria mcg/min | 16 (6.5%) | 19 (3.2%) | 0 | 2 (0.5%) | 22 (0.5%) | 0.933 |
| ABI | 1.1 (0.16%) | 1.1 (0.13%) | 0.736 | 1.1 (0.1%) | 1.1 (0.1%) | 0.316 |
| Use of anti-hypertension medications | 159 (64.1%) | 350 (58.3%) | 0.137 | 145 (39.1%) | 1403 (31.3%) | 0.002 |
| Use of lipid-lowering medications | 68 (27.4%) | 159 (26.5%) | 0.849 | 57 (15.4%) | 634 (14.1%) | 0.564 |
| Use of insulin or oral hypoglycemics | 196 (79%) | 319 (54.2%) | <0.001 | 1 (0.3%) | 13 (0.3%) | 1 |
| Family history of MI | 102 (44%) | 237 (42.6%) | 0.789 | 153 (44%) | 1787 (42.2%) | 0.565 |
| Exam 1 CAC >0 | 157 (63.3%) | 347 (57.6%) | 0.147 | 194 (52.3%) | 2047 (45.6%) | 0.015 |
| Exam 1 average CACS for those with positive CAC | 438 (670.9) | 339.5 (553) | 0.109 | 270.5 (517.8) | 249 (476) | 0.578 |
| MA only; worse eye | 111 (66.1 %) | 2 (0.3 %) | <0.001 | 234 (64.1 %) | 14 (0.3%) | <0.001 |
| AV nicking | 12 (4.9 %) | 35 (5.8 %) | 0.7 | 28 (7.5 %) | 160 (3.6 %) | <0.001 |
| Focal arteriolar Narrowing | 0 | 2 (0.3%) | 0.9 | 9 (2.4 %) | 38 (0.9 %) | 0.007 |
| CRAE | 146 (13.4%) | 145.1 (13.9%) | 0.375 | 142.3 (13.7%) | 144.2 (14.1%) | 0.012 |
| CRVE | 224 (25.3%) | 217.2 (22.7%) | <0.001 | 212.6 (22.3%) | 213.4 (21.3%) | 0.533 |
ABI = ankle brachial index; AV = arterio-venous, Bpm = beats per minute; BMI = body mass index; CAC = coronary artery calcification; CACS = coronary artery calcium score; CRAE = central retinal arteriolar equivalent; CRP = C-reactive protein; CRVE = central retinal venular equivalent; DBP = diastolic blood pressure; FBS = fasting blood sugar; HDL = high density lipoprotein cholesterol; HbA1c = hemoglobin A1c; Kg/m2 = kilograms per square of the height in meters; Log = logarithm; LDL = low density lipoprotein cholesterol; MA = retinal microaneurysms, mcg/min = micrograms per minutes; MI = myocardial infarction; mg/dl = milligrams per deciliter; mm Hg = millimeters of mercury; PY = pack year; SBP = systolic blood pressure.
T test for continuous variable and Chi-square test for discrete variables.
For DM individuals, the presence of retinopathy was significantly associated with greater CAC incidence (relative risk of 1.35 (95% CI [1.07, 1.7]) after adjusting for age, gender, race/ethnicity, and follow-up time. This association was significant for Model B (RR 1.3, 95% CI [1.02, 1.66]) as well. In the non-DM individuals, however, the presence of retinopathy was not significantly associated with incident CAC in any of the multivariable models. However, the interaction between the presence of retinopathy and DM status was not significant in any of the models, indicating that the association of retinopathy with incident CAC was not statistically significantly different between DM and non-DM individuals (Table 2).
Table 2.
The association of retinopathy and incident CAC among those with zero CAC at baseline
| Cumulative incidence (%; n at risk) | Model A*, relative incident ratio (95% CI) | Model B**, relative incident ratio (95% CI) | Model C+, relative incident ratio (95% CI) | Model D++, relative incident ratio (95% CI) | ||
|---|---|---|---|---|---|---|
|
| ||||||
| DM | RP absent | 42% (255) | 1.00 | 1.00 | 1.00 | 1.00 |
| RP present | 55% (91) | 1.4 (1.1,1.7) | 1.3 (1,1.7) | 1.2 (0.9,1.5) | 1.2 (0.91,1.59) | |
| Non-DM | RP absent | 32% (24) | 1.0 | 1.0 | 1.00 | 1.00 |
| RP present | 37% (177) | 1.1 (0.9,1.4) | 1.1 (0.91,1.32) | 1.1 (0.9,1.3) | 1.09 (0.9,1.31) | |
| Interaction between retinopathy and DM p value | - | 0.1466 | 0.1711 | 0.6348 | 0.6392 | |
ABI = ankle brachial index; BMI = body mass index; CAC = coronary artery calcification; CRAE = central retinal arteriolar equivalent; CRP = C-reactive protein; CRVE = central retinal venular equivalent; DM = diabetes mellitus; HbA1c = hemoglobin A1c HDL = high density lipoprotein cholesterol; Log = logarithm; MI = myocardial infarction; RP = retinopathy; SBP = systolic blood pressure.
Adjusted for age, gender, race, and follow up time.
Adjusted for variables in model a plus cardiovascular risk factors including total cholesterol, HDL-C, log of triglycerides, lipid-lowering medications, SBP, anti-hypertension medications, smoking status and cigarette pack-years.
Adjusted for variables in model B plus and BMI, log of CRP, Fibrinogen, log of HbA1C, log of creatinine, glucose, albuminuria, ABI, use of insulin or oral hypoglycemics and family history of MI.
Adjusted for variables in model C and CRAE and CRVE.
Within the DM group, the presence of retinopathy was significantly associated with CAC progression in all adjustment models. Similarly, within the non-DM group, the presence of retinopathy was associated with 24.03 (95% CI [−0.69, 48.76]) Agatston units higher CAC progression in Model B and yielded similar values after adjusting for variables in other models. The interaction between the prevalence of retinopathy and DM status was significant in Model A and B indicating that the association of retinopathy with the progression of CAC was greater within the DM group than the non-DM group. However, this interaction was not significant after adjusting for other risk-factors in Model C and D which might indicate associations are independent of major conventional CHD risk factors. (Table 3, Figure 1)
Table 3.
The association of DM retinopathy and progression of CAC (AU) among those with positive CAC at baseline
| Average CAC progression per year (SD) | Model A*, difference in average CAC progression (95% CI) | Model B** difference in average CAC progression (95% CI) | Model C+ difference in average CAC progression (95% CI) | Model D++ difference in average CAC progression (95% CI) | ||
|---|---|---|---|---|---|---|
|
| ||||||
| DM | RP absent | 68.2 (95.5) | Ref | Ref | Ref | Ref |
| RP present | 96 (117.4) | 102.9 (45.7, 160.1) | 112.6 (51, 174.2) | 88.1 (14.2, 161.9) | 78.3 (2, 154.6) | |
| No-DM | RP absent | 37.5 (62.8) | Ref | Ref | Ref | Ref |
| RP present | 44.1 (71.5) | 27.1 (2.9, 51.2) | 24.03 (−0.7, 48.8) | 30 (3.6, 56.2) | 30.53 (4.1, 57) | |
| Interaction between RP and DM, p value | - | 0.0096 | 0.005 | 0.149 | 0.2076 | |
ABI = ankle brachial index; AU = agatston units; BMI = body mass index; CAC = coronary artery calcification; CRAE = central retinal arteriolar equivalent; CRP = c-reactive protein; CRVE = central retinal venular equivalent; DM = diabetes mellitus; HbA1c = hemoglobin A1c; HDL = high density lipoprotein cholesterol; Log = logarithm; MI = myocardial infarction; No-DM = no diabetes mellitus; Ref=reference; RP = retinopathy; SBP = systolic blood pressure.
Adjusted for age, gender, race, follow up time
Adjusted for variables in model A plus cardiovascular risk factors including total cholesterol, HDL, log of triglycerides, lipid-lowering medications, SBP, anti-hypertension medications, smoking status and cigarette pack-years
Adjusted for variables in model B plus and BMI, log of CRP, Fibrinogen, log of HbA1C, log of creatinine, glucose, albuminuria, ABI, use of insulin or oral hypoglycemics and family history of MI
Adjusted for variables in model C and central retinal arteriolar equivalent CRAE and CRVE
Figure 1.
represent the progression of CAC among those with positive CAC at baseline by retinopathy status among individuals with and without DM in four sets of statistical models for adjusting various factors: demographic characteristics, CHD risk factors, and retinal vessel calibers. In both DM and non-DM group, the presence of retinopathy was significantly associated with CAC progression in all adjustment models.
We repeated the analysis for MA only. The Presence of MA was not associated with an incidence or progression of CAC in DM or non-DM individuals. We analyzed the association of grades of retinopathy with incidence and progression of CAC among those with zero CAC and positive CAC at baseline from robust regression models. The grades of retinopathy were defined as: none, minimal non-proliferative (ETDRS level 14 −20), early to moderate non-proliferative (ETDRS level 31–41), and severe non-proliferative or proliferative (level 51–80). Among those with zero CAC, in the DM group, early to moderate and severe NPDR had significantly higher incident CAC risk than the non- retinopathy group. The minimal NPDR group had a similar incident CAC risk as the non- retinopathy group. Among those with positive CAC at baseline, in the DM group, the early to moderate NPDR group had higher CAC progression than the non- retinopathy group. In the non-DM group, the minimal NPDR group had significantly higher CAC progression than the non- retinopathy group (Data are available in a supplementary article).
We also analyzed the association of AV nicking and focal arteriolar narrowing with incidence and progression of CAC among those with zero and positive CAC at baseline, however, no association was seen between AV nicking and focal arteriolar narrowing with the incidence and progression of CAC (data not shown).
Discussion
The current study demonstrated that among DM and non-DM individuals who were free of clinical CHD, retinopathy was associated with progression of CAC, an indicator of CAD, however, this association was stronger in those with DM compared to those without. The association was present after adjusting for major CHD risk factors indicating its independence from major CHD risk factors. CAC is an independent predictor of CHD risk and represents subclinical CHD. In a previous cross-sectional analysis in MESA, there were significant associations between retinal microvascular signs and CAC.6 What remained unclear is whether these retinal microvascular signs are associated with the incidence or progression of CHD, independent of risk indicators of CHD. In the Atherosclerosis Risk in Communities study,17,18 it was shown that in persons with DM2, the presence of retinopathy was associated with a two-fold higher risk of incident CHD and a three-fold higher risk of fatal CHD, independent of glycemic levels, cardiovascular risk factors and large vessel atherosclerosis. This association was significant in men and women, and in those without Hypertension. While associations were seen for most retinopathy lesions, they were statistically significant only for retinal MAs. In our study, however, we did not find an association of MAs with incidence and progression of CAC.
Studies have shown that DM individuals with retinopathy are more likely to have myocardial perfusion abnormalities19, poorer coronary flow reserve20, and lower coronary collateral development21 than those without retinopathy. Moreover, DR has also been associated with higher degrees of coronary calcification22, and more diffuse and severe coronary artery stenosis on angiograms.23 These observations support the concept that microvascular and macrovascular complications of DM may share common pathogenic mechanisms.24,25 It is uncertain what these pathways may be (e.g., endothelial dysfunction, oxidative stress, and platelet dysfunction), but one potential candidate that has gained recent interest involves the advanced glycation end-products, which can cause both microvascular and macro-vascular injury in DM.25,26
In physiological conditions, vasa vasorum (VV) provides oxygen and nutrients to the arterial wall. Hyperglycemia alters the structure of the VV in individuals with DM.27 Studies have shown that in patients with DM, the VV undergoes pathologic changes initially with endothelial dysfunction and loss of capillaries; and in more advanced stages with ischemia leading to angiogenesis and plaque neovascularization.28 Thus, atherosclerosis is promoted by abnormalities in the capillary rich VV of the conductance vessels. Similar findings have been seen in retina and kidneys in patients with DM. This common pathophysiologic pathway may explain why coronary atherosclerosis is more severe in patients with DR as evidenced by higher CACs.29
CAD, which often remains asymptomatic for a long period of time, is a leading cause of morbidity and mortality in patients with DM2. Timely diagnosis of CAD and appropriate monitoring of its progression is of great importance in patients with DM2.3 According to the results of the present study, in patients with DM2; the presence of DR is associated with significant progression of CAC as a marker of CAD. Retinal examination is a simple, noninvasive, and routinely employed test used in the follow-up of these patients. By using this simple test as a screening method, the clinicians can distinguish patients who need further evaluation for CAD, enabling earlier detection of CAD. This study suggests that CAD may be investigated once DR is diagnosed in a patient with DM2.
There are also some limitations of this study. Subtle differences in prevalence and risk factors of retinopathy in MESA compared with other studies may be related to differences in retinal photography such as 45 degrees non-stereoscopic digital photographs were taken without pharmacological dilation in MESA, as compared with 30 degrees stereoscopic film-based photographs taken with pharmacological mydriasis in some other studies.30 Exclusion of persons with symptomatic CVD in MESA could also have operated differently across ethnic groups as a result of differences in access to care and diagnosis of disease. Lastly, we find that missing data is higher for the DM group with zero CAC at baseline than the non-DM group, secondary to more dropouts at exam 5 in the DM group which may indicate poorer health in the DM group. However, these groups had similar baseline characteristics and there was no difference in missing data neither for people with and without DM nor for those with and without retinopathy among those with positive CAC at baseline. The incidence of new retinopathy in those with progression in CAC was not studied separately in our study. Further study is needed to address this issue.
Conclusion
Our study has found that, in a multiethnic cohort, retinopathy was associated with progression of CAC more significantly in those with DM compared to those without; and may suggest that DM patients with retinopathy would benefit from more intense CVD risk factor modification and closer monitoring to prevent progression of CHD.
Acknowledgment
The author thanks other investigators, the staff, and the participants of MESA for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. This publication was developed under a STAR research assistance agreement, No. RD831697 (MESA Air), awarded by the U. S Environmental protection Agency. It has not been formally reviewed by the EPA. The views expressed in this document are solely those of the authors and the EPA does not endorse any products or commercial services mentioned in this publication.
Funding:
This material is the result of work supported by the Endocrinology, Metabolism, and Nutrition training Grant (T32 DK007571) to Los Angeles Biomedical Research Institute. The MESA study was supported by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, and N01-HC-95169, the NIH Intramural Research Award (ZIAEY000403), and NIH grant R01HL69979.
Footnotes
Disclosures
None of the authors have any financial conflict of interest.
References
- 1.Ohno T, Takamoto S, Motomura N. Diabetic retinopathy and coronary artery disease from the cardiac surgeon’s perspective. Ann Thorac Surg 2008;85:681–689. 10.1016/j.athoracsur.2007.07.066. [DOI] [PubMed] [Google Scholar]
- 2.Wang JJ, Rochtchina E, Kaushik S, Kifley A, Cugati S, Wong TY, Mitchell P. Ten-year evolution of retinopathy lesions in an older non-diabetic population. Arch Ophthalmol 2012;130:796–797. 10.1001/archophthalmol.2011.1574. [DOI] [PubMed] [Google Scholar]
- 3.Grundy SM, Benjamin IJ, Burke GL, Chait A, Eckel RH, Howard BV, Mitch W, Smith SC, Sowers JR. Diabetes and cardiovascular disease: a statement for healthcare professionals from the american heart association. Circulation 1999;100:1134–1146. 10.1161/01.CIR.100.10.1134. [DOI] [PubMed] [Google Scholar]
- 4.Di Carli MF, Janisse J, Grunberger G, Ager J. Role of chronic hyperglycemia in the pathogenesis of coronary microvascular dysfunction in diabetes. J Am Coll Cardiol 2003;41:1387–1393. 10.1016/S0735-1097(03)00166-9. [DOI] [PubMed] [Google Scholar]
- 5.Wang JJ, Liew G, Wong TY, Smith W, Klein R, Leeder SR, Mitchel P. Retinal vascular calibre and the risk of coronary heart disease-related death. Heart 2006;92:1583–1587. 10.1136/hrt.2006.090522. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Wong TY, Cheung N, Islam FMA, Klein R, Criqui M, Cotch MF, Carr JJ, Klein BE, Sharrett AR. Relation of retinopathy to coronary artery calcification: the multi-ethnic study of atherosclerosis. Am J Epidemiol 2008;167:51–58. 10.1093/aje/kwm256. [DOI] [PubMed] [Google Scholar]
- 7.Kannel WB, McGee DL. Diabetes and cardiovascular disease: the Framingham Study. JAMA J Am Med Assoc 1979;241:2035–2038. 10.1001/jama.1979.03290450033020. [DOI] [PubMed] [Google Scholar]
- 8.Klein R, Meuer SM, Moss SE, Klein BEK. The relationship of retinal microaneurysm counts to the 4-year progression of diabetic retinopathy. Arch Ophthalmol 1989;107:1780–1785. 10.1001/archopht.1989.01070020862028. [DOI] [PubMed] [Google Scholar]
- 9.Sjølie AK, Klein R, Porta M, Orchard T, Fuller J, Parving HH, Bilous R, Aldington S, Chaturvedi N. Retinal microaneurysm count predicts progression and regression of diabetic retinopathy. Post-hoc results from the DIRECT Programme. Diabet Med 2011;28:345–351. 10.1111/j.1464-5491.2010.03210.x. [DOI] [PubMed] [Google Scholar]
- 10.Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux A V, Folsom AR, Greenland P, Jacob DR, Kronmal R, Liu K, Nelson JC, O’Leary D, Saad MF, Shea S, Szklo M, Tracy RP. Multi-Ethnic Study of atherosclerosis: objectives and design. Am J Epidemiol 2002;156:871–881. 10.1093/aje/kwf113. [DOI] [PubMed] [Google Scholar]
- 11.Grading Diabetic Retinopathy from Stereoscopic Color Fundus Photographs—An Extension of the Modified Airlie House Classification: ETDRS Report Number 10. Ophthalmology 1991;98(5 Suppl):786–806. 10.1016/S0161-6420(13)38012-9. [DOI] [PubMed] [Google Scholar]
- 12.Carr JJ, Nelson JC, Wong ND, Nathan DW, McNitt-Gray M, Arad Y, Jacobs DR, Sidney S, Bild DE, Williams OD, Detrano RC. Calcified coronary artery plaque measurement with cardiac CT in population-based studies: Standardized protocol of Multi-Ethnic Study of Atherosclerosis (MESA) and Coronary Artery Risk Development in Young Adults (CARDIA) study. Radiology20;234: 35–43.doi: 10.1148/radiol.2341040439 [DOI] [PubMed] [Google Scholar]
- 13.Yaghoubi S, Tang W, Wang S, Reed J, Hsiai J, Detrano R, Brundage B. Offline assessment of atherosclerotic coronary calcium from electron beam tomograms. Am J Card Imaging 1995;9:231–236. [PubMed] [Google Scholar]
- 14.Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990;15:827–832. 10.1016/0735-1097(90)90282-T. [DOI] [PubMed] [Google Scholar]
- 15.National Cholesterol Education Program. Third Report of the Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults - Adult Treatment Panel III, 285; 2002. p. 20022486–2497. 10.1001/jama.285.19.2486. [DOI] [Google Scholar]
- 16.Roccella EJ. The sixth report of the joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Arch Intern Med 1997;157:2413–2446. 10.1001/archinte.157.21.2413. [DOI] [PubMed] [Google Scholar]
- 17.Klein R, Sharrett AR, Klein BEK, Moss SE, Folsom AR, Wong TY, Brancati FL, Hubbard LD, Couper D, ARIC Group. The association of atherosclerosis, vascular risk factors, and retinopathy in adults with diabetes: The Atherosclerosis Risk in Communities Study. Ophthalmology 2002;109:1225–1234. 10.1016/S0161-6420(02)01074-6. [DOI] [PubMed] [Google Scholar]
- 18.Cheung N, Jie JW, Klein R, Couper DJ, Sharrett AR, Wong TY. Diabetic retinopathy and the risk of coronary heart disease: the atherosclerosis risk in communities study. Diabetes Care 2007;30:1742–1746. 10.2337/dc07-0264. [DOI] [PubMed] [Google Scholar]
- 19.Ioannidis G, Peppa M, Rontogianni P, Rontoqianni P, Callifronas M, Papadimitriou C, Chrysanthopoulou G, Anthopoulos L, Kesse M, Thalassinos N. The concurrence of Microalbuminuria and Retinopathy with Cardiovascular Risk Factors; reliable predictors of Asymptomatic Coronary Artery Disease in Type 2 Diabetes. Hormones 2004;3:198–203. 10.14310/horm.2002.11127. [DOI] [PubMed] [Google Scholar]
- 20.Akasaka T, Yoshida K, Hozumi T, Takagi T, Kaji S, Kawamoto T, Morioka S, Yoshikawa J. Retinopathy identifies marked restriction of coronary flow reserve in patients with diabetes mellitus. J Am Coll Cardiol 1997;30:935–941. 10.1016/S0735-1097(97)00242-8. [DOI] [PubMed] [Google Scholar]
- 21.Celik T, Berdan ME, Iyisoy A, Kursakliglu H, Turhan H, Kilic S, Gulec M, Ozturk S, Isik E. Impaired coronary collateral vessel development in patients with proliferative diabetic retinopathy. Clin Cardiol 2005;28:384–388. 10.1002/clc.4960280808. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Elkeles RS, Godsland IF, Feher MD, Rubens MB, Roughton M, Nugara F, Humphries SE, Richmond W, Flather MD. Coronary calcium measurement improves prediction of cardiovascular events in asymptomatic patients with type 2 diabetes: The PREDICT study. Eur Heart J 2008;29:2244–2251. 10.1093/eurheartj/ehn279. [DOI] [PubMed] [Google Scholar]
- 23.Norgaz T, Hobikoglu G, Aksu H, Guveli A, Aksoy S, Ozer O, Bolca O, Narin A. Retinopathy is related to the angiographically detected severity and extent of coronary artery disease in patients with type 2 diabetes mellitus. Int Heart J 2005;46:639–646. 10.1536/ihj.46.639. [DOI] [PubMed] [Google Scholar]
- 24.Juutilainen A, Lehto S, Rönnemaa T, Pyörälä K, Laakso M. Retinopathy predicts cardiovascular mortality in type 2 diabetic men and women. Diabetes Care 2007;30:292–299. 10.2337/dc06-1747. [DOI] [PubMed] [Google Scholar]
- 25.Simó R, Bañeras J, Hernández C, Rodriguez-Palomares J, Valento F, Gutierrez L, Gonzalez-Alujas T, Ignacio F, Aguade-Bruix S, Montaner J, Seron D, Genesca J, Boixadera A, Garcia-Arumi J, Alejandra P, Simo-Servat O, Garcia-Dorado D. Diabetic retinopathy as an independent predictor of subclinical cardiovascular disease: Baseline results of the PRECISED study. BMJ Open Diabetes Res Care 2019;7. 10.1136/bmjdrc-2019-000845.29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Goldin A, Beckman JA, Schmidt AM, Creager MA. Advanced glycation end products: sparking the development of diabetic vascular injury. Circulation 2006;114:597–605. 10.1161/CIR-CULATIONAHA.106.621854. [DOI] [PubMed] [Google Scholar]
- 27.Gerstein HC, Nair V, Chaube R, Stoute H, Werstuck G. Dysglycemia and the density of the coronary vasa vasorum. Diabetes Care 2019;42:980–982. 10.2337/dc18-2483. [DOI] [PubMed] [Google Scholar]
- 28.Sedding DG, Boyle EC, Demandt JAF, Sluimer JC, Dutzmann J, Haverich A, Bauersachs J. Vasa vasorum angiogenesis: Key player in the initiation and progression of atherosclerosis and potential target for the treatment of cardiovascular disease. Front Immunol 2018;9:706.. 10.3389/fimmu.2018.00706.17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Wong TY, Cheung CMG, Larsen M, Sharma S, Simó R. Diabetic retinopathy. Nat Rev Dis Prim 2016;2:16012. 10.1038/nrdp.2016.12. [DOI] [PubMed] [Google Scholar]
- 30.Mitchell P, Smith W, Chey T, Wang Jie Jin, Chang A. Prevalence and associations of epiretinal membranes: The blue mountains eye study, Australia. Ophthalmology 1997;104:1033–1040. 10.1016/S0161-6420(97)30190-0. [DOI] [PubMed] [Google Scholar]