Plasminogen Activator Inhibitor-1 Activity Is Independently Related to Both Insulin Sensitivity and Serum Triglycerides in 70-Year-Old Men

From the Department of Geriatrics (L. Byberg, L. Berglund, R.R., H.L.) and the Department of Clinical Chemistry (A.S.), Uppsala University, Sweden; and the Department of Epidemiology and Population Sciences, London School of Hygiene and Tropical Medicine, UK (P.M.).

Correspondence to Liisa Byberg, Department of Geriatrics, Uppsala University, PO Box 609, S-751 25 Uppsala, Sweden. E-mail liisa.byberg{at}geriatrik.uu.se

	Abstract

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Abstract—Increased levels of plasminogen activator inhibitor-1 (PAI-1) have been discussed as a part of the insulin resistance syndrome. However, it is not clear whether the relationship between PAI-1 and insulin resistance is independent of or mediated by increased triglycerides levels. The aim of this study was to investigate whether PAI-1 activity is associated with insulin sensitivity independently of serum triglycerides (sTG) and of other potential confounders. Seventy-year-old men (n=871), participating in a cohort study undergoing extensive metabolic investigations, had blood samples taken for determination of PAI-1 activity. Insulin sensitivity was determined by the euglycemic hyperinsulinemic clamp. In multivariate correlation and regression analyses, insulin sensitivity was a statistically significant determinant of PAI-1 activity (partial r=-.12; P<.001), independent of sTG, body mass index, waist-hip ratio, and other potential confounders. The levels of sTG were also independently related to PAI-1 activity (partial r=.18; P<.001). The relationships between PAI-1 and insulin sensitivity and sTG were independent of fasting glucose levels. Aggregation of risk factors of the insulin resistance syndrome was associated with increased activity of PAI-1 in men with normal glucose tolerance. We conclude that PAI-1 activity is related to insulin sensitivity and sTG, independently of each other and of other potential confounders, and that increased levels of PAI-1 should be regarded as a component of the insulin resistance syndrome.

Key Words: plasminogen activator inhibitor-1 • insulin sensitivity • triglycerides • hyperglycemia • cardiovascular disease

	Introduction

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Non–insulin-dependent diabetes mellitus has a high and increasing prevalence, especially in countries that are rapidly becoming affluent. In white and South Asian populations, NIDDM is associated with a twofold to threefold increase in cardiovascular disease.¹ An early characteristic in the development of NIDDM is "insulin resistance," a state in which the promoting effect of insulin on glucose uptake is decreased. The "insulin resistance syndrome" comprises several cardiovascular risk factors, including elevated blood pressure, glucose intolerance, central obesity, and an atherogenic lipoprotein pattern characterized by elevated concentrations of plasma triglycerides, decreased HDL cholesterol, and increased levels of small, dense LDL particles.² The insulin resistance syndrome is associated with an increased risk for cardiovascular disease, even at normoglycemia.³

Although insulin has been associated with an increased risk of ischemic heart disease,⁴ it is possible that elevated levels of the major rapid inhibitor of fibrinolysis in blood, PAI-1, is an important mediator of the increased incidence of cardiovascular disease in insulin-resistant states.⁵ Both insulin and triglyceride-rich lipoproteins stimulate the production of PAI-1 in cultured cells.^{6 7 8 9 10 11 12} PAI-1 has been shown to be associated with insulin resistance or hyperinsulinemia,^{13 14 15 16 17 18 19 20 21} but it is not clear whether the association is independent of triglyceride levels. To further elucidate the relationships between PAI-1 and insulin sensitivity, triglycerides, and other factors, we measured the activity of PAI-1 in a large cohort study of elderly men undergoing extensive metabolic investigations. Our aim was to explore whether PAI-1 activity was associated with insulin sensitivity and triglyceride levels independently of each and of other potential confounders. We further wanted to study to what extent any such associations were changed by the hyperglycemia characteristic of NIDDM.

	Methods

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Subjects
Subjects in this study were 871 men with the median age 70.8 years (range 69.4 to 72.5), who were participants in a health survey that was started in Uppsala, Sweden, in 1970. All men born from 1920 to 1924 and living in the municipality of Uppsala were invited to participate in this health survey. Two thousand eight hundred forty-one men were invited and 2322 accepted (participation rate 82%). Twenty years later, the participants were invited to take part in a reinvestigation. During the intervening 20 years, 422 had died and 219 had moved out of the Uppsala region. Of the 1681 men invited, 460 did not participate in this follow-up, leaving 1221 men aged around 70. Of these 1221 men, PAI-1 activity was analyzed in 914 of the 965 men born from 1921 to 1924, and of these, 871 also had measurements of insulin sensitivity, as determined by clamp. These men were included in the present study. The study was approved by the local ethical committee, and all participants gave their informed consent. All investigations started between 7:30 and 8:30 in the morning after an overnight fast. The oral glucose tolerance test and the clamp procedure took place on separate days within 1 week.

Reproducibility Study
A subgroup of 21 subjects was investigated twice within 4 to 6 weeks to determine the combined effects of biological variation and measurement error on repeatedly measured variables. The ICCs for variables used in the analysis are reported in Table 3. The intraclass correlation influences the power of the test when correlations are tested, ie, describes the ability of a variable to associate to other variables, and is based on a quotient of a variable's variation between (s_B²) and within (s_W²) subjects (ICC=s_B²/[s_B²+s_W²]).

Anthropometric Measurements
Height was measured to the nearest whole centimeter, and body weight to the nearest 0.1 kg. The BMI was calculated as the ratio of the weight (in kilograms) to the height (in meters squared). The waist and hip circumferences were measured midway between the lowest rib and the iliac crest and over the widest part of the hip, respectively.

Blood Pressure
Blood pressure was measured in the right arm with the subject in the supine position after a 10-minute rest. A large cuff was used when appropriate. Systolic and diastolic blood pressures were defined as Korotkoff phases I and V, respectively. The value was recorded twice and to the nearest even figure. The mean of the two values was used in analyses.

Oral Glucose Tolerance Test
An oral glucose tolerance test was performed by measuring the concentrations of plasma glucose and insulin immediately before and 30, 60, 90, and 120 minutes after challenge with 75 g anhydrous dextrose dissolved in 300 mL water. Plasma insulin was assayed by using an enzymatic immunological assay (Enzymmun, Boehringer Mannheim) performed in an ES300 automatic analyzer (Boehringer Mannheim). Plasma insulin concentrations are given in milliunits per liter (for conversion to picomoles per liter, multiply by 6.0²²). Plasma glucose was measured by the glucose dehydrogenase method (Gluc-DH, Merck). Diabetes was diagnosed if the 120-minute and one or more of the 30- to 90-minute plasma glucose values were 11.1 mmol/L. Impaired glucose tolerance was diagnosed when the fasting plasma glucose value was <7.8 mmol/L and one or more of the 30- to 90-minute plasma glucose values were 11.1 mmol/L and the 120-minute plasma glucose value was between 7.8 and 11.1 mmol/L. The classification was made according to the National Diabetes Data Group criteria, 1979.²³

Insulin Sensitivity
Insulin sensitivity was measured by the euglycemic hyperinsulinemic clamp procedure as described by DeFronzo et al,²⁴ slightly modified. Insulin (Actrapid Human, Novo) was infused at a rate of 56 (instead of 40) mU/min per body surface area (meters squared). Such a high concentration of insulin inhibited hepatic glucose output by 88% to 95%, also in diabetics.²⁵ Plasma glucose was assayed in duplicate in a Beckman Glucose Analyzer II (Beckman Instruments). M was calculated as the amount of glucose (milligrams) infused per minute per body weight (kilograms). M/I was calculated by dividing M by the mean plasma insulin concentration (milliunits per liter) during the last 60 minutes of the insulin/glucose infusion and multiplying by 100 to represent glucose disposal at a plasma insulin level of 100 mU/L (the values for M/I are given as milligrams per minute per kilogram/[100 mU/L]). M/I compensates for differences in insulin levels attained during the clamp and can therefore be considered a more accurate index of peripheral insulin sensitivity than M.

Lipid and Lipoprotein Measurements
Cholesterol and triglyceride concentrations in serum were assayed by enzymatic techniques (Instrumentation Laboratories) in a Monarch 2000 centrifugal analyzer. HDLs were separated by precipitation with magnesium chloride/phosphotungstate. LDL cholesterol was calculated using Friedewald's formula: LDL=serum cholesterol–HDL–(0.45 · serum triglycerides). Serum nonesterified fatty acids were measured by an enzymatic colorimetric method (Wako Chemical GmbH) applied for use in the Monarch 2000 centrifugal analyzer. The laboratory at the Department of Geriatrics is an accredited reference laboratory by the Centers for Disease Control and Prevention (Atlanta, Ga).

PAI-1 Activity
The activity of PAI-1 was analyzed with a commercial two-step indirect enzymatic assay (Spectrolyse/pL PAI kits, Biopool AB), as described by Eriksson et al.²⁶ The activity is given in units per milliliter, where one unit is the amount of PAI-1 that inhibits 1 IU of human single-chain tissue-type plasminogen activator. Blood samples were drawn in 5-mL evacuated tubes (Vacutainer, Becton Dickinson), prefilled with 0.5 mL buffered 0.129 mol/L sodium citrate (pH 5.8), with the subject at rest in the supine position with minimal venous stasis. The tubes were put on ice until centrifugation at 4°C at 2000g for 10 minutes. The plasma was stored at –70°C. The measurement error, expressed as intra- and interassay coefficients of variation, were 2.6% and 7.2%, respectively.

Lifestyle Factors and Medical History
Data on lifestyle habits and medical history, including medication, were collected with a questionnaire. Information about angina pectoris and previous myocardial infarction was also retrieved from the questionnaire. Hypertension was defined as medical treatment for hypertension and/or a diastolic blood pressure 95 mm Hg. Drugs with antihypertensive effect were in 69 of 281) cases (24.6%) given for other causes than hypertension, for example, angina pectoris or arrhythmias, and these men were not regarded as hypertensives (if the diastolic blood pressure was not 95 mm Hg). Current smoking status was classified as smoking or nonsmoking. Alcohol consumption was determined according to the subject's estimate of the average intake of different alcoholic drinks per week. Alcohol consumption was defined as intake of spirits, wine, or beer of 3.5 vol % alcohol and above.

Statistical Analyses
Variables with skewed distributions were log transformed to improve normality. The log transformations were used in all statistical analyses. The activity of PAI-1 was measured to be zero in 2.3% of the subjects (n=20). In these cases, the activity of PAI-1 was set at an arbitrary value of 0.05 before the log transformation to enable us to include them in the analyses. To make sure this arbitrary value did not lead to false results, all statistical analyses were verified with their nonparametric equivalents (Wilcoxon rank-sum test, Spearman's rank correlation, and Spearman's partial rank correlation). Descriptive measurements used are median and range or, where indicated, geometric mean (the antilog of the arithmetic mean of a log-transformed variable). For continuous variables, Student's t test and ANOVA were used for testing differences between groups. Associations between pairs of continuous variables were tested by Pearson correlation analysis. Associations between PAI-1 activity and dichotomous categorical variables were tested by logistic regression, with PAI-1 activity standardized to 1 SD. Multivariate and stepwise regression analyses were performed, with the natural logarithm of PAI-1 activity as the dependent variable, and the predetermined independent continuous variables were standardized to 1 SD. The multivariate analyses were adjusted for age. Test for interaction was performed with multivariate regression analysis, with the tertiles of insulin sensitivity and serum triglycerides and the product of those included; the results were not significant. Adjusted means were calculated from linear regression estimates, and tests for trend were performed using Spearman's partial rank correlation. The statistical analyses were performed with the statistical software packages JMP, SAS (SAS Institute Inc), and Stata (Stata Corporation). Differences and correlations mentioned in the text are statistically significant (P<.05) if not otherwise stated.

PAI-1 activity was calculated in men with different clusters of risk factors, and the association between PAI-1 and increasing numbers of risk factors was tested with Spearman's rank correlation. Only men with NGT were included to avoid situation in which several risk factors would be only a reflection of an increased number of diabetics. The limit for the continuous risk factors was set at the fourth quintile of each variable. Risk factors used were high levels of serum triglycerides (>1.72 mmol/L) and fasting glucose (>5.70 mmol/L), high BMI (>28.4 kg/[m]²), and hypertension.

	Results

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The characteristics of the study population are shown in Tables 1 and 2. Of the 871 subjects in this study, 128 (14.7%) had NIDDM and 112 (12.9%) had IGT. PAI-1 activity correlated with many of the investigated factors, as shown in Table 3. There were positive associations between PAI-1 activity and BMI, WHR, systolic and diastolic blood pressures, LDL/HDL ratio, plasma levels of fasting and 2-hour glucose and insulin, and levels of serum triglycerides. The activity of PAI-1 correlated negatively with HDL cholesterol and insulin sensitivity. Men with NIDDM or IGT had higher PAI-1 activity than men with NGT (Fig 1). The associations between different categorical variables and PAI-1 activity are shown in Table 2. Alcohol-consuming subjects had higher PAI-1 activity than subjects not consuming alcohol, but there was no correlation between PAI-1 activity and the amount of alcohol consumed (data not shown). The prevalence of hypertension and angina pectoris was increased when PAI-1 activity increased, as was the prevalence of treatment with antihypertensive drugs. The association between PAI-1 and myocardial infarction was not significant. Smoking did not influence the activity of PAI-1.

View larger version (37K): [in this window] [in a new window]   Figure 1. PAI-1 activity in groups of glucose tolerance, presented as geometric means. The values are adjusted for serum triglycerides, insulin sensitivity, age, systolic and diastolic blood pressures, BMI, WHR, medication with blood pressure–lowering drugs, and in the second adjustment also for fasting glucose (f-glucose) levels. indicates Spearman's partial rank correlation. *P<.05.

To investigate the PAI-1 activity in relation to different expressions of the insulin resistance syndrome, we calculated the activity of PAI-1 in men with NGT who had different clusters of the components of the syndrome. Risk factors used were high levels of serum triglycerides and fasting glucose, high BMI, and hypertension. The results are shown in Fig 2. Higher PAI-1 activity was observed in men with an increased number of risk factors (P<.001).

View larger version (15K): [in this window] [in a new window]   Figure 2. Clustering of risk factors and activity of PAI-1 in 70-year-old men with NGT. The medians of PAI-1 activity are presented. Risk factors are hypertension, high BMI, and high levels of fasting glucose and serum triglycerides. The increase in PAI-1 activity with increasing numbers of risk factors is highly significant (P<.001).

Multivariate regression and correlation analyses were performed with the intention to study the relationship between the activity of PAI-1 and some predefined factors related to the insulin resistance syndrome, in particular insulin sensitivity and serum triglycerides, corrected for potential confounders. Variables included in the analyses were insulin sensitivity, serum triglycerides, BMI, WHR, systolic and diastolic blood pressures, age, and use of drugs with antihypertensive effect. The bivariate and partial regression and correlation coefficients for the variables independently related to PAI-1 are shown in Table 4. In the whole material, there were still, after adjusting for potential confounders, highly significant negative and positive correlations between PAI-1 activity and insulin sensitivity and serum triglycerides, respectively. BMI and WHR were also independently associated with PAI-1. The combined effect of insulin sensitivity and serum triglycerides on PAI-1 activity is illustrated in Fig 3. Stepwise regression analyses were performed, with the same variables as in the multivariate analysis above, but also with the levels of fasting insulin included, to investigate whether fasting insulin, rather than insulin sensitivity, was a predictor of PAI-1 activity. This was not the case, either in the whole study population, or in men with NGT only (data not shown). To investigate whether the hyperglycemia characteristic of NIDDM changed the associations found between PAI-1 and insulin sensitivity and serum triglycerides, the fasting levels of plasma glucose were included in the multivariate analyses. Fasting glucose was independently associated with PAI-1 activity (partial b=.09; partial r=.07; partial P=.032) but did not change the associations between PAI-1 and the other variables in the model and caused only minor effects on the partial b, r, and P. When PAI-1 activity was adjusted for insulin sensitivity, serum triglycerides, BMI, WHR, systolic and diastolic blood pressures, age, and treatment with antihypertensive drugs, PAI-1 activity was still significantly higher in men with NIDDM than in men with NGT (Fig 1). However, the difference between the groups was reduced, and the levels of PAI-1 in men with IGT did not significantly differ from either of the groups. Additional adjustment for fasting glucose levels did not substantially change the levels of PAI-1 in the groups. The same pattern was achieved when we adjusted for only insulin sensitivity and fasting plasma glucose. Although the differences in adjusted PAI-1 activity were not all statistically significant, there was a trend over the groups of glucose tolerance, such that PAI-1 activity was highest in men with NIDDM and lowest in men with NGT (P<.001; Fig 1).

View larger version (23K): [in this window] [in a new window]   Figure 3. Combined effect of insulin sensitivity and serum triglycerides on PAI-1 activity. The test for interaction between M/I and serum triglycerides (sTG) was nonsignificant. The geometric means of PAI-1 activity are presented.

	Discussion

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In this study we have shown an inverse relationship between PAI-1 activity and insulin sensitivity, independent of serum triglycerides and other potential confounders. There were also positive independent associations between PAI-1 activity and serum triglycerides, BMI, and WHR. Previous studies investigating the relationship between PAI-1 and the insulin resistance syndrome presented varying results. In bivariate analyses, PAI-1 correlated inversely with insulin sensitivity,^{13 14 15 16 17 18} but in multivariate analyses, only one study¹³ found an independent association between PAI-1 and peripheral insulin resistance. The other studies investigating PAI-1 in relation to insulin sensitivity and other metabolic variables found that triglyceride levels,^{15 16 17} proinsulin,¹⁷ plasma glucose, and insulin-induced suppression of NEFA¹⁸ predicted PAI-1 in men, and in women, HDL cholesterol¹⁶ and BMI, WHR, and insulin-induced NEFA suppression¹⁸ were independent determinants of PAI-1. Studies investigating PAI-1 in relation to the insulin resistance syndrome without measuring insulin sensitivity found that PAI-1 levels are independently related to fasting levels of insulin^{19 20} and serum triglycerides.^{19 21} Elevated levels of PAI-1 have been regarded as a part of the insulin resistance syndrome,^{13 14 18 20 21 27} but this view has been questioned, because no independent relationship was found between insulin sensitivity and PAI-1.¹⁶ To further investigate the relationship between the insulin resistance syndrome and PAI-1, we studied the activity of PAI-1 in subjects with NGT characterized by clusters of risk factors associated with the insulin resistance syndrome (Fig 2). The activity of PAI-1 was increased with increasing numbers of risk factors. This finding, in addition to the independent relationships between PAI-1 activity and insulin sensitivity, serum triglycerides, BMI, and WHR, strongly suggests that PAI-1 should be considered as an element of the insulin resistance syndrome.

PAI-1 has been suggested as a possible link between insulin resistance and coronary disease,⁵ and elevated levels of PAI-1 were associated with reinfarction in young men.²⁸ We found an association between increased PAI-1 activity and an increased prevalence of angina pectoris, but the association between PAI-1 and myocardial infarction was nonsignificant. This examination of 70-year-old men will provide the basis for a prospective study in which the influence of PAI-1 on the incidence of cardiovascular disease will be further investigated.

In the present study, we have used the euglycemic hyperinsulinemic clamp procedure to determine the insulin sensitivity, a method that permits measurement of insulin resistance also in diabetics, in whom fasting insulin is not an appropriate proxy measurement. The clamp method has not been used in previous large studies. The ICC is a measure of the reliability of a measurement, based on the measurement error and the biological variation of a variable's replicate determinations. The clamp measure of insulin sensitivity, which is shown as a high ICC (0.930), is reliable. The low variation and good reliability of the measurements of BMI and WHR (ICC=0.998 and 0.887, respectively) may also be one explanation of why these variables statistically were independent determinants of PAI-1 activity. Likewise, there may be variables that were not independently related to PAI-1 statistically because of low ICCs, such as blood pressure. The ICCs for the variables used in this study are presented in Table 3. The PAI-1 activity had a rather low ICC (0.606), mainly because of its large intraindividual variation. The low ICC of PAI-1 results in underestimated correlation coefficients (r and partial r) but does not affect the ranking of the predictors of PAI-1 activity.²⁹

In vitro studies have shown that insulin can induce production and release of PAI-1 from hepatocytes,⁶ HepG2 cells,^{7 8 9} and porcine aortic endothelial cells.¹⁰ VLDL triglycerides stimulate release and production of PAI-1 from HepG2 cells¹¹ and human umbilical vein endothelial cells.^{11 12} However, studies with in situ hybridization have shown that liver parenchymal cells do not express PAI-1 mRNA, whereas liver endothelial cells do.³⁰ Although the results are contradictory with respect to which cells actually synthesize PAI-1 in vivo, it seems as if both insulin and triglycerides can stimulate the production of PAI-1.

Insulin sensitivity may exert its effect on PAI-1 through elevated insulin levels. PAI-1 synthesis was upregulated by insulin in HepG2 cells with reduced insulin sensitivity, an effect inhibited by the insulin-sensitizing agent metformin.³¹ Insulin sensitivity may also act on PAI-1 production via insulin propeptides. Subjects with NIDDM who are insulin resistant have an increased amount of proinsulin relative to insulin levels,^{32 33} and the conventional radioimmunoassay method for measuring plasma insulin cannot distinguish insulin from proinsulin and its split products, which leads to an overestimation of the insulin concentration.³² PAI-1 production was increased when HepG2 cells, but not endothelial cells, were stimulated by proinsulin.^{34 35} However, one study has shown increased PAI-1 production from proinsulin-stimulated porcine endothelial cells.¹⁰ Insulin increases PAI-1 activity by decreasing the degradation of PAI-1 mRNA and has no effect on the transcription of the PAI-1 gene.³⁶ Proinsulin, on the other hand, increases the mRNA production and PAI-1 protein synthesis concordantly, and proinsulin split products have similar effects. This effect of proinsulin on PAI-1 is independent of insulin and the insulin receptor.³⁷ Although the magnitude of proinsulin on PAI-1 production in vitro is not clear,³⁵ proinsulin has been shown to increase PAI-1 production in vivo.³⁸ When patients with NIDDM were treated with exogenous insulin, the concentration of proinsulin decreased, as did the levels of PAI-1.³⁹ It has been hypothesized that the mechanism by which insulin resistance leads to increased PAI-1 levels in diabetics is not through insulin but through proinsulin or its split products.³⁴ Since we did not use an assay specific for active insulin and proinsulin, respectively, we cannot address this question.

Hyperglycemia, which is a characteristic of NIDDM, did not change the associations between PAI-1 activity and serum triglycerides and insulin sensitivity. However, the fasting levels of plasma glucose were also independently related to the PAI-1 activity. It is known that PAI-1 is increased in subjects with NIDDM,^{5 37} and in vitro studies have shown that endothelial cells increase the production of PAI-1 when stimulated by glucose.^{9 40} In the present study, PAI-1 activity was elevated in men with NIDDM. Furthermore, men with IGT had as high PAI-1 activity as diabetics. In a recent study, PAI-1 activity was found to be elevated in subjects with NIDDM only, and not in subjects with IGT.⁴¹ However, the NGT and IGT groups were more similar than in our study population, partly because of the use of less restrictive diagnostic criteria for IGT. The differences in PAI-1 between the glucose tolerance groups in our study could not completely be explained by any of the investigated variables; although the differences decreased, there was still a trend showing the highest PAI-1 activity in diabetics and lowest in men with NGT (Fig 1). Genetic variations may be part of the explanation, as well as the additive effect of the combination of proinsulin and insulin on PAI-1 levels seen in vitro.³⁷

Recent studies have shown PAI-1 production by murine adipocytes in culture^{42 43} and that the visceral fat area was correlated with the levels of PAI-1 in humans.^{44 45} These results provide an explanation for the associations of BMI and WHR with PAI-1 whereby increased adipose tissue mass may contribute to the elevated levels of PAI-1 present in obesity.

The mechanism by which triglyceride-rich lipoproteins increase PAI-1 activity is as yet not fully known. It may be the NEFA, and not the triglyceride molecule itself, that acts on PAI-1 production. Hydrolysis of VLDL triglycerides by lipoprotein lipase at the endothelial cell surface is linearly related to the triglyceride concentration up to 3 to 5 mmol/L, and the degree of hydrolysis sets the concentration of NEFA at the endothelial cell surface. As a consequence, the regulatory factor of PAI-1 production and release may be NEFA, rather than triglycerides or VLDL particles. This also means that the concentration of NEFA measured in blood probably does not represent the concentration at the endothelial cell surface. Accordingly, we found no correlation between PAI-1 and fasting levels of NEFA.

On the basis of the findings in this study that PAI-1 activity is independently related to insulin sensitivity, we conclude that elevated levels of PAI-1 should be regarded as an element of the insulin resistance syndrome.

	Selected Abbreviations and Acronyms

 

BMI = body mass index ICC = intraclass correlation coefficient IGT = impaired glucose tolerance M = glucose disposal M/I = insulin sensitivity index NEFA = nonesterified fatty acid NGT = normal glucose tolerance NIDDM = non–insulin-dependent diabetes mellitus PAI-1 = plasminogen activator inhibitor-1 WHR = waist-hip ratio

	Acknowledgments

 
This study was supported in part by Axel and Margaret Ax:son Johnson Foundation, Ernfors Foundation, King Gustaf V and Queen Victoria Foundation, Swedish Medical Research Council No. 5446, Trygg Hansa, Uppsala Geriatric Research Foundation, and Uppsala University.

Received May 22, 1997; accepted October 22, 1997.

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