Original Contributions |
From the Stanford University School of Medicine, Stanford (M.C., F.A., F.W., M.K., P.-W.W., Y.-D.I.C., G.M.R.); the Geriatric Research, Education, and Clinical Center, VA Palo Alto Health Care System (S.A.), Palo Alto; and Shaman Pharmaceuticals, Inc (G.M.R.), South San Francisco, CA.
| Abstract |
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Key Words: oxidized LDL insulin resistance cardiovascular disease risk factors
| Introduction |
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| Methods |
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All studies were performed at the General Clinical Research Center of Stanford University Medical Center after an overnight fast. The degree of obesity, overall and regional, was estimated by BMI and WHR, respectively. Venous blood was used for measurement of plasma cholesterol, triglyceride, and HDL cholesterol concentrations.10 Plasma glucose11 and insulin12 concentrations were determined before and 30, 60, 90, 120, and 180 minutes after oral administration of 75 g glucose. The total integrated area of the plasma concentrations during this 180-minute period was used to quantify plasma glucose and insulin responses. The ability of insulin to promote glucose uptake was estimated by a modification13 of the insulin suppression test as validated by our laboratory.14 After an overnight fast, an intravenous catheter was placed in each of the patient's arms. Blood was sampled from one arm for measurement of plasma glucose and insulin concentrations, and the contralateral arm was used for administration of test substances. Somatostatin was administered [250 µg/h in a solution containing 2.5% (wt/vol) human serum albumin] to suppress endogenous insulin secretion. Simultaneously, insulin and glucose were infused at rates of 25 mU · m-2 · min-1 and 240 mg · m-2 · min-1, respectively. Blood was sampled every 0.5 hour until 150 minutes had elapsed and then every 10 minutes until 180 minutes had elapsed. The four values obtained at 150, 160, 170, and 180 minutes were averaged and considered to represent the SSPG and SSPI concentrations achieved during the infusion. Because SSPI concentrations are similar in all individuals, SSPG concentrations provide a direct estimate of insulin-mediated glucose disposal in each individual: the lower the SSPG, the more insulin sensitive the individual.
An aliquot of fasting venous blood (20 mL) was drawn from each
individual into EDTA tubes and immediately centrifuged. Plasma
was flushed with N2 and stored frozen at -70°
until assayed. LDLs (d=1.025 to 1.063 g/mL) were isolated by
sequential ultracentrifugation using solid KBr for
density adjustment. All plasma samples were supplemented with protease
inhibitors (0.1 mmol/L PMSF and 2 µg/mL aprotinin)
to minimize LDL degradation during isolation. The LDL preparations were
dialyzed against PBS without EDTA, and the protein content was
determined by a modification of the method of Lowry et
al.15 The susceptibility of LDL to oxidation was
assessed as described by Picard et al.7 In brief,
isolated LDLs were diluted in PBS to obtain a final concentration of
200 µg/mL, and oxidation was initiated by adding a concentrated
solution of copper sulfate to a final concentration of 5 µmol/L.
For each sample, the amount of CDs formed during LDL oxidation was
monitored every 5 minutes for 4 hours by the change in absorbance at
234 nm in the presence or absence of 0.1 mmol/L
D,L-alanine. Alanine inhibits LDL fatty acid oxidation, an
effect dependent on the amount of peroxides present in LDL
particles. Thus, the difference between the CD formation half-time
(time corresponding to half of the absorbance) for the curve with and
without alanine (Th0 and Th1, respectively) reflects LDL oxidative
status (Fig 1
), ie, the greater the
difference, the greater the antioxidant effect of alanine on LDL, and
the lower the oxidative state of the LDL.
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As reported by Picard et al,7 the increase in CD
formation half-time induced by alanine can be expressed as the AOC,
which can be calculated as (Th1-Th0)x100/Th0, ie, the percentage
increase due to alanine. As AOC is inversely correlated with the degree
of LDL oxidation, Picard et al expressed their results as the cAOC,
which is equal to 150-AOC (based on their experience that the value of
AOC never exceeded 150%). The cAOC thus varies in direct proportion to
the degree of LDL oxidation. We also calculated cAOC, but for clarity
of presentation, will refer to this value as the amount of
partially oxidized LDL, or poxLDL. Finally, to estimate the
reproducibility of the results, we measured cAOC on the same isolated
LDL sample from 7 subjects. For this purpose, isolated LDL preparations
(10 mg total cholesterol per milliliter) were stored at
4°C under sterile conditions and in the presence of 0.5 mmol/L
EDTA (pH 7.0). Contaminating metal ions were removed from LDL
preparations by dialysis against PBS without calcium or magnesium and
containing Chelex-100 (1 g/L). After addition of EDTA to a final
concentration of 0.5 mmol/L, the dialyzed LDL preparations were
filtered (Millipore, 0.2-µm filter), flushed with
N2, and stored in the dark at 4°C for up to 2
months. These results are shown in Fig 2
, revealing a mean (±SD) difference between the two estimates of 1±6.3
(P<.68 by Student's paired t test). In
addition, in 10 samples we compared the value of cAOC with (1) the lag
phase after the addition of copper before any change in absorbance
(r=.66, P<.05), (2) the maximum CD formation
(r=.64, P<.01), and (3) total lipid peroxide
formation at 100 minutes (r=.61, P<.05).
Furthermore, the SSPG in these 10 samples was also highly correlated
with all four measurements: cAOC (r=.82, P<.01),
lag phase (r=.89, P<.001), CD (r=.78,
P<.01), and lipid peroxides (r=.68,
P<.05).
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Data were stored and analyzed using the Systat 6.0 package for Windows. Insulin response and plasma triglyceride values were logarithmically transformed to improve normality for statistical testing and back-transformed for presentation in tables. Pearson product-moment correlations and partial correlation coefficients were calculated to determine relations between variables of interest. Finally, multiple regression analysis was performed using different models (see "Results") with the dependent variable being cAOC.
| Results |
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Both overall and abdominal obesity16 have been
said to increase LDL oxidizability. In addition, age
may17 or may not18 have
this same effect. Consequently, we performed multiple regression
analysis to determine whether any of these factors could affect
LDL oxidation status independently of insulin resistance or its
metabolic covariates. The data reported in Table 3
show that SSPG (P<.02) but
neither age, BMI, nor WHR was independently related to poxLDL (for the
entire model, r2=.37). We obtained similar
results (data not shown) when SSPG was replaced with either plasma
glucose (r2=.41, P<.005) or
insulin response (r2=.34,
P<.04), triglyceride
(r2=.33, P<.05) or HDL
cholesterol (r2=.31,
P<.08).
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When insulin resistance and all of its metabolic covariates
were forced into the model together, they all lost independent
predictive power, highlighting the close relationship among these
variables. Furthermore, the predictive value of the model including
all variables (r2=.47) was only
marginally higher than the value of the model shown in Table 3
with
SSPG as the only variable.
| Discussion |
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On the other hand, it is equally important to emphasize that we cannot ascribe any biological effect to the measurement of what we are designating as poxLDL. In fact, we have used the phrase "partially oxidized LDL" in this article in contrast to "minimally oxidized LDL" as employed by Picard et al7 to avoid any inference that what is measured corresponds to the in vitro biological effects of minimally oxidized LDL as described by Fogelman and colleagues.20 21 22
In addition to using a method to estimate circulating levels of poxLDL
rather than one based on measurements of the degree to which isolated
LDL is oxidized in vitro, the other striking difference between our
study and the majority of previous reports was that our experimental
population was healthy, nondiabetic, without clinical signs of CHD, and
with normal electrocardiograms. As such, our population
differed considerably from previous studies that have demonstrated an
increase in susceptibility of LDL to oxidation in patients with known
CHD, either with or without diabetes.23 24 25 26
Indeed, we are aware of only two studies in which increases in LDL
oxidizability have been shown to occur in subjects without vascular
disease.16 27 In this context, the results of
Haffner et al27 are most at odds with ours. These
authors compared normal individuals, subjects with impaired glucose
tolerance, and patients with frank noninsulin-dependent diabetes
mellitus and concluded that in vitro LDL oxidizability was increased
only in patients with noninsulin-dependent diabetes mellitus. They
reasoned that since resistance to insulin-mediated glucose disposal is
commonly seen in patients with impaired glucose tolerance or
noninsulin-dependent diabetes mellitus, hyperglycemia but not insulin
resistance was associated with enhanced LDL oxidizability. Although we
cannot fault their logic, it is apparent that we observed a significant
relationship between insulin resistance and poxLDL levels in a group of
nondiabetic patients. It should be noted that neither Stringer et
al24 nor Veláquez and
associates,26 using an assay method similar to
that of Haffner et al, were able to discern any effect of either
diabetes or degree of hyperglycemia on LDL oxidizability in patients
with atherosclerosis. In addition, Veláquez et
al26 reported that in vitro LDL oxidation was
elevated to a comparable degree in diabetic and nondiabetic subjects
with CHD when compared with normal volunteers, and these authors were
unable to define an independent relationship between estimates of
glycemia and in vitro LDL oxidizability. The fact that neither of these
latter two research groups was able to discern any relationship between
plasma glucose concentration and LDL oxidizability suggests that LDL
glycation is not the major mediator of changes in LDL oxidizability.
This conclusion is further supported by the fact that the differences
in poxLDL described in the current study were seen in nondiabetic
volunteers. On the other hand, although the values were all within the
normal range, there was a significant relationship noted in Table 2
between the plasma glucose response to oral glucose and poxLDL. Thus,
we cannot exclude the possibility that there were changes in LDL
glycation, secondary to minor variations in plasma glucose
concentration within this nondiabetic population, that contributed to
the increase in poxLDL seen in insulin-resistant
individuals.
If we now focus on nondiabetic individuals without clinical evidence of atherosclerosis, we are aware of only one publication16 other than ours that claims to have shown any change in LDL oxidation. More specifically, in a recent review, Van Gaal and colleagues16 presented evidence that in vivo oxidizability of a non-HDL fraction was increased in postmenopausal, obese women compared with a matched group of nonobese women and that this relationship was related to both BMI and WHR. Since insulin resistance is commonly seen in obese individuals,28 it is likely that this defect was also present in the obese women studied by Van Gaal et al.16 It is apparent from our results that the positive relationship between SSPG (insulin resistance) and poxLDL was independent of differences in sex, BMI, and WHR. Based on these considerations, it seems entirely possible that the changes in in vitro LDL oxidizability described by Van Gaal et al16 in obese women were secondary to the insulin resistance in these individuals. As such, their results are quite consistent with ours.
If we now turn attention to our results, it is apparent from
Table 2
that there were significant relationships between poxLDL and
the other variables known to be associated with insulin resistance,
ie, the plasma glucose and insulin responses to oral glucose, higher
plasma triglyceride concentrations, and lower levels of HDL
cholesterol.1 2 8 Furthermore, these
relationships persisted after adjustment for differences in age, sex,
BMI, and WHR, with only HDL cholesterol losing statistical
power. As such, the amount of circulating poxLDL in the healthy
volunteers we studied was related to all of the components of syndrome
X.1 2 8 When a series of variables is related
to the biological event being studied, multivariate
analysis is conventionally used in an effort to define the
independent predictors of the phenomenon in question. An example of
this approach is seen in Table 3
. When age, weight, sex, and SSPG
(insulin resistance) were entered into the regression model, SSPG
accounted for 36% of the variability of poxLDL and was the only
statistically significant predictor. Essentially similar results were
seen when insulin response, a surrogate measure of insulin resistance,
replaced SSPG in the model. However, when all of the
metabolic abnormalities associated with syndrome X were
added to the model, the r2 value increased
from .36 to only .46, and none of the variables were found to be
independent predictors of poxLDL. We believe that this finding
reinforces the notion of a cluster of risk factors for CHD that are
closely related to insulin resistance and suggest that statistical
efforts to define independence may not be overly useful. Indeed, we
believe that the point to emphasize is that the degree of insulin
resistance per se accounted for 36% of the amount of variability in
the circulating poxLDL level in a group of healthy volunteers.
Finally, though not the goal of this study, some speculation as to the link between the components of syndrome X and LDL oxidative states seems warranted. For example, Galvan et al29 have recently raised the possibility of a pro-oxidant action of insulin in vivo by demonstrating a consistent decrement in plasma vitamin E concentrations, a major free radicalscavenger molecule, during physiological hyperinsulinemia.29 Furthermore, Rifici et al30 were able to demonstrate that supraphysiological insulin concentrations may induce in vitro LDL oxidation by peripheral blood mononuclear cells and that this effect was mediated by an increase in O2. Raised plasma glucose levels may also induce glycosylation of LDLs, and this effect has been demonstrated to increase LDL susceptibility to oxidation.31 It has also been hypothesized that normal to elevated HDL cholesterol concentrations may protect LDLs from oxidation by acting as a "scavenger" system for circulating lipoperoxides.24 Finally, it should be pointed out that the positive relationship between insulin resistance and poxLDL was seen in this study, despite the presumptive protective effect of the higher uric acid concentrations that are characteristic of subjects with syndrome X.32 33 Thus, there appear to be several potential means by which the various components of syndrome X could modify LDL oxidative status.
In conclusion, we have demonstrated in healthy volunteers that poxLDL concentrations are correlated with resistance to insulin-mediated glucose uptake, increased glucose and insulin responses to oral glucose, higher plasma triglyceride levels, and lower HDL cholesterol concentrations. These data suggest that an increase in LDL oxidative status should be added to the list of metabolic changes related to syndrome X. How insulin resistance or its consequences increase LDL oxidation in vivo is still unclear and requires further investigation. Nonetheless, these relations may well contribute to the increased risk of CHD that has been previously shown to be linked to insulin resistance and compensatory hyperinsulinemia.
| Selected Abbreviations and Acronyms |
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| Acknowledgments |
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| Footnotes |
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Received May 2, 1997; accepted December 9, 1997.
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