Insulin resistance as predictor of the angiographic severity and extent of coronary artery disease

Abstract

Background. Insulin resistance (IR) is frequently observed in patients with coronary artery disease (CAD).

Aim. To examine the association between IR and severity and extent of CAD.

Methods. Quantitative coronary angiography (QCA) was used to assess coronary atherosclerosis in 107 patients with clinically suspected CAD. QCA‐derived indexes reflecting CAD severity, extent, and overall atheroma burden were calculated for the entire coronary tree, and separately for different coronary segments. IR was quantified using the homeostasis model assessment insulin resistance index (HOMA IR). Nondiabetic subjects (n = 83) were divided into group 1 (n = 41) with HOMA IR <1.8 (the median value), and group 2 (n = 42) with HOMA IR ⩾1.8. Group 3 comprised diabetic subjects (n = 24).

Results. Global age‐ and gender‐adjusted indexes for severity (P = 0.007), extent (P = 0.038), and atheroma burden (P = 0.035) of CAD were higher in group 2 than in group 1. Similarly, the global severity (P = 0.027), extent (P = 0.090), and global atheroma burden (P = 0.024) indexes were higher in group 3 compared with group 1. IR was correlated with quantitative angiographic indexes for distal segments only, but not for proximal or mid segments of coronary vessels.

Conclusions. Patients with more severe degree of IR have a more severe, extensive, and distal type of CAD than patients with lower degree of IR.

• Coronary artery disease
• insulin resistance
• quantitative coronary angiography
• the homeostasis model assessment insulin resistance index

Abbreviations
BMI	=	body mass index
CAD	=	coronary artery disease
DM	=	diabetes mellitus
HDL	=	high‐density lipoprotein
HOMA	=	IR, the homeostasis model assessment insulin resistance index
IR	=	insulin resistance
LDL	=	low‐density lipoprotein
OGTT	=	oral glucose tolerance test
QCA	=	quantitative coronary angiography

Introduction

Diabetes mellitus (DM) is well recognized as an important risk factor for coronary artery disease (CAD). Insulin resistance (IR), characterized by a diminished response to the biological effects of insulin, is a strong predictor of type 2 DM 1. In addition, IR has been associated with obesity, predominantly intra‐abdominal distribution of fat, hypertension, low high‐density lipoprotein (HDL) cholesterol, and hypertriglyceridemia, all of which are well known risk factors for CAD 2,3. Given that IR is related to cardiovascular risk factors, it seems reasonable to believe that IR should be strongly related to cardiovascular disease. In fact, some 4,5, but not all studies 6,7 have shown a positive association of IR with CAD. There are some reports available regarding the association between IR and the severity of CAD based on visual estimation of coronary angiograms 8–11.

The homeostasis model assessment insulin resistance index (HOMA IR) estimates insulin sensitivity and β‐cell function from fasting plasma insulin and glucose concentrations. HOMA IR has been shown to provide a reasonable estimate of peripheral tissue sensitivity to insulin, and it is widely used in clinical and epidemiological research 12.

Quantitative coronary angiography (QCA) was developed to overcome the limitations of visual interpretation of coronary angiograms. There is, however, limited information available about the connection between IR and the severity and extent of CAD estimated by QCA 13,14.

The present study was, therefore, undertaken to investigate, in a Finnish cohort of patients with clinically suspected CAD, the association between IR and anatomic distribution of coronary atheroma based on a computer‐assisted analysis of coronary angiograms.

Key messages

• Disturbances in glucose metabolism play a pivotal role in pathogenesis of coronary atherosclerosis.

• Insulin resistance is associated with an increased severity and extent of coronary atherosclerosis.

• Insulin resistance is a stronger predictor of coronary atherosclerosis in the distal parts of the coronary tree than in the proximal and mid parts.

Methods

Study population

The study comprised 107 patients who underwent elective coronary angiography for evaluation of clinically suspected CAD at the Helsinki University Central Hospital in Finland. Patients with a history of coronary artery bypass grafting, percutaneous coronary intervention, and those with insulin‐dependent DM or significant renal failure (serum creatinine >150 µmol/L) were excluded. Written informed consent was obtained from all participants, and the study design was approved by the institutional ethics committee.

Quantitative analysis of coronary angiograms

Coronary angiography was performed by standard angiographic techniques and the angiograms were analyzed using third‐generation software, Cardiovascular Measurement System (QCA‐CMS) version 3.0 (Medis, Nuenen, the Netherlands). All QCA analyses were carried out by one investigator (MG). The QCA‐derived parameters were integrated into indexes, as reported elsewhere in detail 15. Briefly, the severity of CAD was defined as an average of the most severe percent diameter stenoses in the left main, the left anterior descending, the left circumflex, and the right coronary arteries. The extent index was calculated as the longitudinal percentage of coronary segments involved in stenoses [100×Σ(stenosis lengths)/Σ(segment lengths)). Based on plaque area (expressed in square millimeters], representing the QCA‐derived two‐dimensional projection of atheroma volume, and reflecting both severity and extent, the atheroma burden index was calculated as 100×Σ(plaque areas)/Σ(segment lengths). These three indexes were calculated for the entire coronary tree of each patient (global) and separately for the proximal, mid, and distal segments.

Biochemical investigations

Blood samples were collected one month after coronary angiography and after an overnight fast for analysis of total cholesterol, triglycerides, HDL cholesterol, LDL cholesterol, concentrations of apolipoproteins A‐I, A‐II, B (apoA‐I, apoA‐II, apoB), lipoprotein A‐I (LpA‐I), and lipoprotein A‐I/A‐II particles (LpA‐I/A‐II) 16,17. LDL peak particle diameter (LDL particle size) was determined using native gradient gel electrophoresis 18.

To avoid bias caused by medications, patients were requested to abstain from any lipid‐lowering drugs between the time of angiography and blood sampling; only highly cardioselective β‐blockers (mainly bisoprolol) were permitted.

Assessment of insulin resistance

All subjects underwent a 75‐g standard oral glucose tolerance test (OGTT) with specimens collected before, and 60 minutes and 120 minutes after loading for determination of plasma glucose and serum insulin concentrations. Fasting and postload glucose were measured by the hexokinase method (Roche Diagnostic Gluco‐quant) using either a Hitachi 917 or a Modular analyzer (Hitachi Ltd, Tokyo, Japan). Serum insulin concentrations were determined by double‐antibody radioimmunoassay (Pharmacia RIA kit, Pharmacia, Uppsala, Sweden) after precipitation with polyethylene glycol. Patients with a previously diagnosed DM or with fasting plasma glucose ⩾7 mmol/L or 2‐h plasma glucose ⩾11.1 mmol/L were classified as diabetic 19. We applied the HOMA IR in nondiabetic subjects (n = 83) using the following formula: HOMA IR = fasting insulin (mU/L)×fasting glucose (mmol/L)/22.5 12.

Demographic variables

Hypertension was defined as current use of antihypertensive drugs. The patients were classified either as nonsmokers or as past or present smokers. The body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared (kg/m²). The waist circumference was used as a measure of intra‐abdominal fat deposition.

Statistical analyses

All statistical analyses were performed with SPSS 11.5 for Windows (SPSS Inc., Chicago, IL, USA). The subjects were categorized into three groups. Nondiabetic subjects (n = 83) were divided into group 1 (n = 41) with HOMA IR <1.8 (the median value), and group 2 (n = 42) with HOMA IR ⩾1.8. Diabetic subjects comprised group 3 (n = 24).

Data are presented as frequencies or percentages for categorical variables, as means±SD for normally distributed continuous variables, and as medians (interquartile ranges) for skewed variables. Normality of continuous variables was checked by the Kolmogorov‐Smirnov test. Logarithmic transformation of variables with skewed distribution was done before any statistical analyses. The values in text, tables, and figures are presented nontransformed. Between‐group differences were examined by one‐way analysis of variance followed by the Bonferroni post hoc test. Categorical data were compared by the chi‐square test. Analysis of covariance was applied to compare the means of the QCA‐derived indexes between groups with adjustment for age and gender. Levene's test was used to assess homogeneity of variances. Multivariate linear regression analysis was performed to assess predictors of global percent diameter stenosis index in the nondiabetic subjects (n = 83). To adjust for confounding, age and sex were included in the model. Moreover, we included the following variables linked to cardiovascular risk or IR: hypertension, smoking, triglycerides, waist circumference, LDL and HDL cholesterol. A P‐value <0.05 was considered significant.

Results

Baseline characteristics

Demographic and clinical characteristics of the study groups are presented in Table I. Patients in groups 2 and 3 had higher BMI, waist circumference, and were more likely to be hypertensive compared with group 1.

Table I. Demographic and clinical characteristics of the study population (n = 107).

	Group 1 HOMA IR <1.8 (n = 41)	Group 2 HOMA IR ⩾1.8 (n = 42)	Group 3 Diabetic subjects (n = 24)	P^a
Age (years)	60 (56–64)	63 (55–65)	58 (52–66)	0.591
Male/Female	25/16 (61/39)	35/7 (83/17)	20/4 (83/17)	0.035
BMI (kg/m^2)	25.7 (23.6–27.4)	27.9 (25.7–30.0)	28.3 (27.2–31.6)	<0.001
Waist circumference (cm)	98±10.4	105±11.3	108±9.4	<0.001
Current or former smoker	19 (46)	27 (64)	14 (58)	0.250
Hypertension	16 (39)	28 (67)	18 (75)	0.006
Previous myocardial infarction	13 (32)	18 (43)	7 (29)	0.434
Previous cerebrovascular disease	1 (2)	3 (7)	0 (0)	0.290
Canadian Cardiovascular Society class:
I	2 (5)	3 (7)	2 (8)	0.887
II	22 (54)	17 (41)	7 (29)	0.143
III	17 (41)	19 (45)	13 (54)	0.609
IV	‐	3 (7)	2 (9)	0.277
Medication use at baseline:
Aspirin	38 (93)	37 (88)	24 (100)	0.209
β‐blocker	33 (81)	36 (86)	21 (88)	0.708
Statin	27 (66)	33 (79)	16 (68)	0.384
Angiotensin‐converting enzyme inhibitor	7 (17)	13 (31)	11 (46)	0.045
Calcium channel blocker	7 (17)	9 (21)	5 (21)	0.870
Diuretics	4 (10)	4 (10)	5 (21)	0.335
Long‐acting nitrates	16 (39)	20 (48)	13 (54)	0.474
Oral/diabetes	‐	‐	7 (29)	<0.001
Later treatment of CAD:
Medical	20 (49)	11 (26)	6 (25)	0.051
Percutaneous coronary intervention	13 (31)	20 (48)	11 (46)	0.293
Coronary artery bypass grafting	8 (20)	11 (26)	7 (29)	0.637

Data are expressed as means±SD, medians (interquartile ranges) or as frequencies (%).

^aP‐values from analysis of variance (means of continuous variables) or chi‐square test (frequency data) across the three groups.

Biochemical and other study variables

Total cholesterol, LDL cholesterol, and apoB levels were similar among the three groups. Subjects in groups 2 and 3 had lower HDL cholesterol and apoA‐I levels than subjects in group 1. The triglyceride level did not differ significantly between the groups. LDL particle size was smaller in group 3 compared with group 1 (Table II).

Table II. Biochemical characteristics and other study variables.

	Group 1 HOMA IR <1.8 (n = 41)	Group 2 HOMA IR ⩾1.8 (n = 42)	Group 3 Diabetic subjects (n = 24)	P^a
Total cholesterol (mmol/L)	5.74±1.18	5.66±1.27	5.48±1.43	0.728
HDL cholesterol (mmol/L)	1.45±0.32	1.28±0.25	1.22±0.27	0.003
LDL cholesterol (mmol/L)	3.58±1.00	3.57±0.99	3.11±0.89	0.128
Triglycerides (mmol/L)	1.66 (1.23–2.20)	1.99 (1.44–2.36)	1.82 (1.44–3.76)	0.058
LDL particle size (nm)	26.00 (25.55–26.50)	25.50 (24.40–26.30)	24.70 (24.05–26.35)	0.026
ApoA‐I (mmol/L)	3.70 (3.26–4.18)	3.24 (3.03–3.82)	3.31 (2.87–3.83)	0.016
ApoA‐II (mmol/L)	0.93 (0.84–1.11)	0.93 (0.81–1.14)	0.84 (0.72–1.01)	0.070
ApoB (mmol/L)	3.02±0.74	3.28±0.84	3.28±1.05	0.406
LpA‐I (mmol/L)	1.37±0.44	1.22±0.37	1.24±0.26	0.237
LpA‐I/A‐II (mmol/L)	2.38±0.50	2.20±0.43	2.04±0.45	0.018
Fasting plasma glucose (mmol/L)	5.2 (4.9–5.6)	5.4 (5.2–5.7)	7.1 (6.5‐7.9)	<0.001
1‐hour plasma glucose (mmol/L)	8.2 (6.0–10.4)	9.2 (7.3–10.1)	12.7 (11.1–15.6)	<0.001
2‐hour plasma glucose (mmol/L)	6.1 (5.1–7.4)	6.6 (4.9–7.9)	11.8 (7.8–15.1)	<0.001
Fasting plasma insulin (mU/L)	4.9 (4.2–6.4)	9.8 (8.3–15.6)	11.9 (6.6–20.9)	<0.001
1‐hour plasma insulin (mU/L)	46.7 (28.4–61.4)	64.5 (49.9–109.4)	58.2 (42.1–85.9)	0.001
2‐hour plasma insulin (mU/L)	35.8 (25.1–43.7)	52.5 (33.6–84.1)	55.4 (27.8–98.1)	0.004

Data are presented as means±SD or as medians (interquartile ranges).

^aP‐values from analysis of variance (means of continuous variables) across the three groups.

Insulin resistance and severity and extent of CAD

The age‐ and gender‐adjusted QCA‐derived global indexes for the severity, extent, and overall atheroma burden of CAD were significantly higher in group 2 than in group 1. Similarly, the global severity, extent, and atheroma burden indexes were higher in group 3 compared with group 1 (Figure 1).

Figure 1. Box plots showing median(horizontal lines), 25th to 75th percentiles (boxes), and 95th percentiles (whiskers) in the different groups by global percent diameter stenosis index (A), global extent index (B), and global atheroma burden index (C), respectively. P¹² value indicates comparison between group 1 (HOMA IR <1.8) and group 2 (HOMA IR ⩾1.8) and P¹³ value between group 1 (HOMA IR <1.8) and group 3 (diabetic subjects). P‐values from analysis of covariance with adjustment for age and gender. For definition of indexes, see Methods.

We found heterogeneity in associations between IR and CAD indexes according to the anatomical location of CAD. Compared with group 1, individuals in group 2 had more severe and extensive CAD in distal segments only, but not in the left main coronary artery, proximal, or mid coronary segments. Similar results were seen when group 3 was compared with group 1 (Table III).

Table III. Quantitative coronary angiography results.

	Group 1 HOMA IR <1.8 (n = 41)	Group 2 HOMA IR ⩾1.8 (n = 42)	P^a	Group 3 Diabetic subjects (n = 24)	P^b
PDS index
Left main coronary artery	0 (0–0)	0 (0–0)	0.680	0 (0–0)	0.123
Proximal segment	9 (0–17)	16 (8–23)	0.391	14 (2–24)	0.587
Mid segment	10 (0–26)	20 (15–30)	0.227	22 (8–30)	0.519
Distal segment	12 (6–23)	20 (16–24)	0.016	24 (13–34)	0.002
Extent index
Left main coronary artery	0 (0–0)	0 (0–0)	0.586	0 (0–0)	0.147
Proximal segment	10 (0–23)	16 (5–27)	0.596	19 (2–24)	0.495
Mid segment	8 (0–23)	18 (13–27)	0.085	13 (6–26)	0.545
Distal segment	10 (5–15)	15 (10–18)	0.037	15 (8–22)	0.026
Atheroma burden index
Left main coronary artery	0 (0–0)	0 (0–0)	0.424	0 (0–0)	0.160
Proximal segment	5 (0–14)	8 (2–19)	0.307	9 (1–16)	0.157
Mid segment	4 (0–13)	10 (6–18)	0.128	8 (2–15)	0.362
Distal segment	4 (1–7)	6 (4–8)	0.125	6 (3–11)	0.048

Values are expressed as medians (interquartile ranges).

^a P‐values are presented for analysis of covariance between groups 1 and 2 with adjustment for age and gender.

^bP‐values are presented for analysis of covariance between groups 1 and 3 with adjustment for age and gender.

As outlined in Table IV, factors independently correlated with the global percent diameter stenosis index were gender, HOMA IR group, and to a lesser degree waist circumference. Together, these factors explained 29.7% of the severity of CAD. Age, hypertension, smoking status, triglycerides, and HDL and LDL cholesterols did not reach statistical significance in this model.

Table IV. Multivariate regression model of global percent diameter stenosis index.

Independent variables	Nondiabetic subjects (n = 83)
	Beta		P
Age (log)	0.160		0.140
Gender	‐0.434		0.002
HOMA IR group	0.284		0.010
Hypertension	‐0.016		0.881
Current or former smoking	0.163		0.158
LDL cholesterol	0.048		0.639
HDL cholesterol	‐0.127		0.274
Triglycerides (log)	0.006		0.954
Waist circumference	‐0.227		0.059
Adjusted R^2 and F‐ratio	0.297	4.806	<0.001

log = logarithmic transformation of the variable.

Discussion

This study showed, in a cohort of patients undergoing elective coronary angiography, that IR, expressed as HOMA IR, was associated with quantitative angiographic indexes of severity, extent, and overall atheroma burden of CAD. In addition, IR seemed to be a stronger predictor of coronary atherosclerosis in the distal parts of the coronary tree than in the proximal and mid parts. In the multivariate analysis IR was a significant predictor of the severity of CAD.

The euglycemic hyperinsulinemic clamp technique has been regarded as the reference method for evaluating IR. However, this method is expensive, technically complex, and therefore unsuitable in clinical practice. In the present study the HOMA model was chosen because it is a widely used surrogate measure of IR. The HOMA method derives an estimate of insulin sensitivity from the mathematical modeling of fasting glucose and insulin concentrations 12. In comparison with the euglycemic clamp, the HOMA model is an easy, practical, and inexpensive method for assessing IR. The HOMA model has been shown to correlate moderately well with insulin sensitivity as measured using the euglycemic clamp technique 12. However, HOMA IR has been reported to reflect more closely hepatic IR than peripheral glucose uptake 20. Of note, hepatic IR can coexist with fatty liver and excess secretions of substances correlated with cardiovascular risk, such as very low‐density lipoprotein, C‐reactive protein, and antifibrinolytic and coagulation factors 21.

There is some information available about the association between IR and the characteristics of coronary atherosclerosis estimated by conventional visional interpretation of coronary angiography. Bressler and co‐workers 8 concluded in a small study comprising 13 normal glucose‐tolerant subjects that IR, as measured by the clamp technique, was positively correlated with the severity of CAD. Sasso et al. 9 showed that, in 234 men with normal glucose tolerance, the number of stenosed coronary vessels was correlated with HOMA IR. Moreover, Yanase and colleagues 10 reported that HOMA IR was an independent risk factor of a new cardiovascular event in patients with prior CAD and normal glucose tolerance. Conversely, Satoh et al. 11 did not find a significant relationship between HOMA IR and the number of diseased coronary arteries.

To our knowledge, only two studies have investigated the relationship between IR and coronary atherosclerosis utilizing quantitative imaging techniques. Korpilahti et al. 13 showed that, in a 5‐year follow‐up study of 228 coronary artery bypass surgery patients, IR determined as the insulin sensitivity index was associated with both progression of preoperative atherosclerotic lesions and development of new lesions. In studying a cohort of 95 nondiabetic Japanese subjects with CAD verified with semiquantitative coronary angiography, Tsuchihashi et al. 14 found that hyperinsulinemia was an important risk factor for CAD explaining the severity of coronary atherosclerosis.

Our study confirms these previous findings and extends them as: 1) our study population included men and women; 2) we encompassed a wide array of disease severity, ranging from angiographically normal coronaries to widespread CAD requiring bypass surgery; 3) our study comprised CAD patients with normal and abnormal responses to a 75‐g OGTT; 4) we used detailed computer‐assisted scoring of CAD; and 5) we found a positive relationship between age‐ and gender‐adjusted severity of IR and coronary atherosclerosis. In fact, nondiabetic subjects with a HOMA IR score above the upper median level of 1.8 were comparable with diabetic subjects in terms of severity and extent of CAD.

Consistent with other reports we found that, besides having a more severe and extensive CAD, type 2 diabetic patients more frequently had lesions located on distal arteries than nondiabetic patients 22,23. In addition our data show that even nondiabetic subjects with a more severe degree of IR had a more distal type of CAD compared with individuals with a lower degree of IR. To the best of our knowledge, this has not been previously published.

The process of lesion formation in CAD is complex. Endothelial dysfunction, an imbalance between endothelium‐derived vasodilative (e.g. nitric oxide) and vasoconstrictive (e.g. endothelin‐1) factors, is regarded as an early pivotal event in atherogenesis and cardiovascular disease, and is closely linked to obesity and IR 24. In addition, obesity, IR, and endothelial dysfunction coexist, and they can all be identified in individuals with type 2 DM as well as in various groups at risk for type 2 DM, such as in individuals with impaired glucose tolerance, family history of type 2 DM, hypertension and dyslipidemia 25. Recently, Prior and co‐workers 26 demonstrated that, even in the absence of traditional coronary risk factors, the greatest loss in nitric‐oxide‐mediated, endothelium‐dependent flow occurred when IR was the only abnormality, and this seemed to worsen progressively with more severe states of IR.

During the development of coronary atherosclerosis, compensatory arterial enlargement preserves the intraluminal space and delays clinically important lumen stenosis 27,28. The mechanism for compensatory enlargement is thought to be predominantly mediated by the vascular endothelium in response to changes in the hemodynamic, shear‐stress, and humoral changes in the vessel lumen 29. This coronary artery remodeling has been shown to be inadequate or negative in diabetic patients 30,31. Arterial remodeling, however, is not a homogeneous process within the vessel wall. Interestingly, Nishioka et al. 32 reported that, despite a similar degree of luminal narrowings, the proximal coronary segments showed more prominent compensatory enlargement than the distal arterial segments. Recently, Fischer et al. 33 found that, in families with myocardial infarction, coronary artery stenoses are particularly heritable at proximal localizations, whereas no heritability was found for distal disease. In our study the reason for a different impact of IR on anatomic characteristics of coronary atherosclerosis remains unclear, but our results support a regional heterogeneity in remodeling responses.

Study limitations

The present study was only of moderate size, however, comparatively homogenous, comprising patients referred for coronary angiography. In addition, a high percentage of patients was already receiving medical treatment for traditional CAD risk factors, which may have overshadowed the relationship between IR and the severity and extent of CAD. On the other hand, all patients were rigorously characterized for coronary angiographic phenotype. Furthermore, this study has by nature a cross‐sectional design showing factors associated with CAD. Thus, it is not possible to draw definite conclusions regarding independent risk factors for CAD.

Conclusions

We observed, in subjects with clinically suspected CAD, that IR is associated with an increased severity and extent of coronary atherosclerosis. This relationship appeared to be more prominent in distal coronary segments. Our results suggest that disturbances in glucose metabolism play a pivotal role in pathogenesis of coronary atherosclerosis. In view of our results, it seems appropriate to intensify efforts to identify insulin‐resistant individuals so that efficient treatment strategies can be directed to lower their risk of CAD and to delay the onset of type 2 DM.

Conflict of interests

Dr Taskinen has received honoraria and consulting fees from Merck Sharp and Dome, Pfizer, Laboratoires Fournier, GlaxoSmithKline, Bristol‐Myers Squibb, Takeda, Sanofi‐Aventis, and research support from Laboratoires Fournier, Eli Lilly, and Novartis.

Acknowledgements

This work was supported by grants from Helsinki University Central Hospital Research Foundation, the Finnish Foundation for Cardiovascular Research, the Aarne Koskelo Foundation, and the Wilhelm and Else Stockmann Foundation.

The authors thank Tina Svahn, Hannele Hildén, and Helinä Perttunen‐Nio for their excellent technical assistance.