Hypertriglyceridemia Is a Practical Biomarker of Metabolic Syndrome in Individuals with Abdominal Obesity

Abstract

Individuals with the metabolic syndrome have a significantly higher risk of type 2 diabetes mellitus (T2DM) and cardiovascular disease. Body mass index (BMI) and waist circumference are inaccurate methods for assessing abdominal obesity; in addition, some obese individuals are metabolically healthy while some normal weight individuals have metabolic syndrome. The methods used to visualize intra-abdominal fat, such as computed tomography (CT) scan and magnetic resonance imaging (MRI), are not available to primary care practitioners as screening methods for the primary care patient. The present study examined commonly used biomarkers to assess which of them would be most predictive of metabolic syndrome to assess the feasibility of using indicators other than BMI in the assessment of obesity-associated disease risk in the primary care setting. We examined 169 (118 females, 51 males) obese individuals with increased waist circumference (>102 cm for men and >85 cm for women), who were patients at the UCLA Risk Factor Obesity Clinic. Of these, 59 had three or more criteria associated with metabolic syndrome. In a multivariate linear regression model including body weight, BMI, waist circumference, waist-to-hip ratio, systolic blood pressure, diastolic blood pressure, glucose, high-density lipoprotein, and triglycerides (TG), only log TG and glucose values were significantly associated with the presence of metabolic syndrome (p<0.001). Both TG and fasting glucose levels were significantly and positively correlated with fasting insulin (p<0.001), homeostasis model assessment (HOMA) (p<0.001). TG were correlated negatively with adiponectin (p<0.01) and positively with high-sensitivity C-reactive protein. We conclude that the presence of elevated TG is independently associated with metabolic syndrome and is a likely predictor for insulin resistance in individuals with increased waist circumference. This finding has significant implications for screening obese and normal weight individuals in the general population for clinically significant metabolic syndrome and prediabetes, which has a major public health impact given the common occurrence of metabolic syndrome and the need for early intervention to prevent T2DM.

Introduction

I n the United States, obesity has reached epidemic proportions, with a clear increase in prevalence during the past 10–15 years. It is estimated that 70% of all adult Americans are considered overweight or obese. These observations have serious public health implications because overall excess weight is related to increased health expenditures for common chronic diseases, including type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD).¹

Obesity is associated with a constellation of cardiovascular and metabolic disorders, including hypertension, hyperinsulinemia, glucose intolerance, and dyslipidemia, and many of these share common etiology and pathophysiology related to insulin resistance.² This cluster makes up the basic elements of the metabolic syndrome, which was first described over 40 years ago by Vague.³ Clinically, metabolic syndrome is defined by specific criteria as established by the Adult Treatment Panel III of the National Cholesterol Education Program. Individuals having three or more of the following risk factors are defined as having metabolic syndrome⁴: Central obesity (waist circumference >102 cm for men, >88 cm for women), elevated triglycerides (TG) (>150 mg/dL), low high-density lipoprotein cholesterol (HDL-C) (<50 mg/dL in women, <40 mg/dL in men), elevated fasting glucose (>110 mg/dL), and hypertension (>130/85 mmHg). Previous studies have revealed that individuals with the metabolic syndrome have significantly higher cardiovascular morbidity and mortality risks.⁴

Abdominal or visceral adipose tissue (VAT) is an essential contributor to the development of the metabolic syndrome.^5
–7 The most widely used anthropometric measure of abdominal obesity is waist circumference. However, waist circumference is an inaccurate method for assessing abdominal obesity and is inadequate as a sole indicator of metabolic syndrome, as some individuals with central obesity are metabolically healthy.

Because of the important clinical and public health implications, identification of simple reliable metabolic markers that are the most sensitive predictors of metabolic syndrome and insulin resistance/prediabetes is of considerable importance. This study was designed to determine whether there are measurable biomarkers that can predict which patients with abdominal obesity are more likely to have associated metabolic syndrome and insulin resistance by comparing biomarkers in obese patients from the same clinic with and without risk factors for metabolic syndrome.

Study Design

This study was a cross sectional observation study in which new patients from the UCLA Risk Factor Obesity Program were enrolled. All subjects came to the Center for Human Nutrition after fasting for 8 hr and completed all study assessments. The morning blood pressure medication(s) were held until the completion of the study assessments. The study protocol was approved by The Institutional Review Board of University of California, Los Angeles. All subjects provided written informed consent.

Subjects

The Risk Factor Obesity program is a multidisciplinary, medically supervised outpatient obesity management program using either low- or very-low-calorie diets including the use of meal replacements, group classes in nutrition and behavior modification, an exercise prescription, and lifestyle modification. New patients to the clinic ages 30–60 years old were enrolled in the study if they also had abdominal obesity (male patients with waist circumference >102 cm and body mass index (BMI) >25; female patients with waist circumference >85 cm and BMI >25). Subjects with any chronic medical conditions other than hypertension, dyslipidemia on no lipid-lowering medications, or glucose intolerance were excluded.

Study procedures

Body weight, height, waist and hip circumference were measured. Blood pressure was measured twice in the sitting position using standard protocols, and the two values were averaged. Fasting blood samples were obtained by venipuncture. Glucose, insulin, lipid, adiponectin, and high-sensitivity C-reactive protein (hsCRP) levels were analyzed by Quest Diagnostics (San Juan Capistrano, CA). Insulin sensitivity was estimated using the homeostasis model assessment (HOMA) equation: Homeostasis model assessment of insulin resistance (HOMA-IR)=[fasting glucose (mmol/L)×fasting insulin (μU/mL)/22.5].⁹

Statistical analysis

Statistical analysis of clustering using factor analysis was used. Factor analysis is a multivariate correlation method that is well suited for revealing underlying patterns or structure among variables showing high degrees of intercorrelation, as in the case of risk variables comprising the metabolic syndrome.

Results

The characteristics of the study subjects are displayed in Table 1. A total of 169 subjects (118 females, 51 males) were studied. Men had higher blood pressure and lower HDL than women overall. Women and men were comparable with respect to age and BMI. There were 110 subjects with two or fewer risk factors without metabolic syndrome, whereas 59 subjects had three or more risk factors and metabolic syndrome (34 females, 25 males) (Fig. 1).

FIG. 1.

Number of subjects according to metabolic syndrome risk factors.

Table 1.

Characteristics of Study Subjects

	Women	Men	p value
N	118	51
Age (year)
Mean (SD)	48.9 (10.8)	45.7 (10.5)	0.08
Race
Asian	6	0
Black	14	6
Caucasian	86	38
Hispanic	6	5
Other	6	2
BMI (kg/m²)
Mean (SD)	38 (6.6)	39.8 (7.0)	0.130
SBP (mmHg)
Mean (SD)	122.0 (12.7)	129.0 (15.1)	0.001
DBP (mmHg)
Mean (SD)	78.7 (7.3)	83.5 (9.7)	0.002
Glucose (mg/dL)
Mean (SD)	95.0 (16.0)	104.0 (49.0)	0.420
Triglycerides (mg/dL)
Mean (SD)	158.0 (132.0)	202.0 (114.0)	0.070
HDL mg/dL)
Mean (SD)	66.0 (16.0)	51.0 (14.0)	<0.001

Values shown are mean±SD. The comparison was performed with SAS.

SD, standard deviation; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL, high-density lipoprotein.

In a multivariate linear regression model including body weight, BMI, waist circumference, waist-to-hip ratio, systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, HDL, and TG, only log TG and glucose were significantly associated with the presence of metabolic syndrome (p<0.001).

Ninety-three percent of subjects who met the criteria for metabolic syndrome had elevated TG, whereas only 20% subjects who did not meet the criteria for metabolic syndrome had elevated TG. Twenty-six percent of subjects who met the criteria for metabolic syndrome had elevated blood glucose, whereas only 0.9% of subjects who did not meet the criteria had elevated blood glucose. Only 4 subjects (3 African American and 1 Caucasian) had elevated fasting blood glucose without elevated TG (Table 2).

Table 2.

Individuals with Hypertriglyceridemia or Elevated Fasting Glucose

	Hypertriglyceridemia	Elevated fasting glucose
Metabolic syndrome presence	93%	26%
Metabolic syndrome absence	20%	0.9%

Ninety-three percent of subjects who met the criteria for metabolic syndrome had elevated triglycerides, whereas only 20% subjects who did not meet the criteria for metabolic syndrome had elevated triglycerides. Twenty-six percent of subjects who met the criteria for metabolic syndrome had elevated blood glucose, whereas only 0.9% of subjects who did not meet the criteria had elevated blood glucose.

TG were significantly correlated with insulin level (r=0.48, p<0.001), HOMA (r=0.49, p<0.001), and adiponectin (r=−0.26, p<0.01). Glucose was correlated with insulin (r=0.27, p<0.001), and HOMA (r=0.42, p<0.001), but not adiponectin (r=−0.1, p=0.31). TG were significantly correlated with hsCRP (r=0.19, p=0.023) but not glucose (r=0.06, p=0.513).

Discussion

The metabolic syndrome is defined by a set of metabolic risk factors based on specific threshold levels of waist circumference, glucose, TG, HDL-C, and blood pressure with some differences in exact criteria used by different organizations issuing guidelines. VAT is an important risk factor for obesity-related metabolic disorders.⁸ However, a causal link between VAT and metabolic dysfunction has not been demonstrated in humans. Recently, it has become clear that increased whole-body adiposity without a concomitant increase in liver fat is not associated with augmented metabolic dysfunction.^9,10 Therefore, the ability to identify individuals most likely to develop metabolic syndrome associated with insulin resistance with a simple clinical test would be helpful in evaluating primary care patients and determining their care.

In the present study, hypertriglyceridemia was significantly associated with development of metabolic syndrome, insulin resistance, and increased hs-CRP, a marker of chronic inflammation. In a previous study conducted in Spain, patients with hypertriglyceridemia had a high prevalence of metabolic syndrome (79.6%). The prevalence of diabetes was double that of the general population and the prevalence of CVD was 14.6%.¹¹

Numerous studies have shown a univariate association between elevated plasma TG and subsequent heart disease,¹² particularly in subjects with normal or low total cholesterol.¹³ Laws and Reaven have demonstrated that moderately overweight, nondiabetic men with insulin resistance had higher plasma insulin and TG levels and lower HDL-C concentrations, and that TG-to-HDL-C ratios are useful markers of insulin resistance. Krauss et al. demonstrated that increased plasma TG and reduced HDL-C are key features of the metabolic syndrome and suggested smaller low-density lipoprotein (LDL) particles as a marker for insulin resistance, especially for subjects with low HDL and TG <150 mg/dlL.^14,15

Longitudinal and cross-sectional studies have suggested that a “hypertriglyceridemic waist,” as defined by elevated TG and increased waist circumference, was associated with CVD.^16
–18 In the Quebec Cardiovascular Study,¹⁸ Lemieux et al. first suggested that the simultaneous interpretation of waist circumference and fasting TG may be a comprehensive and cost-effective screening method for the identification of patients characterized by a cluster of anthrogenic risk factors.¹⁹ The EPIC-Norfolk prospective population study examined the relationship between the hypertriglyceridemic waist phenotype to the risk of coronary artery disease in total of 21,787 participants aged 45–79 years who were followed for a mean of 9.8 years. Compared with participants who had a waist circumference and TG level below the threshold, those with the hypertriglyceridemic waist phenotype had higher blood pressure indices, higher levels of apolipoprotein B and CRP, lower levels of HDL-C and apolipoprotein A-I, and smaller LDL particles, indicating that the hypertriglyceridemic waist phenotype was associated with a deteriorated cardiometabolic risk profile and an increased risk for coronary artery disease.¹⁶

Insulin resistance has been proposed as the common underlying pathophysiological risk factor for the development of T2DM in metabolic syndrome. Mechanisms of dyslipidemia in insulin resistance are driven by an increased influx of free fatty acids (FFAs) from adipose tissue to the liver. FFAs promote increased TG synthesis in the liver, which can lead to the secretion of very-low-density lipoprotein (VLDL).²⁰ In our study population, TG correlated positively with insulin level and HOMA and negatively with adiponectin. It has been demonstrated in longitudinal studies that high TG with normal or impaired fasting glucose predict the development of T2DM.^21,22 In a prospective study with a total of 2605 subjects with normal glucose tolerance who were followed for 5 years for impaired glucose tolerance or diabetes onset, a nonlinear increase was seen with serum TG.²³ It has been suggested by the American Heart Association that hypertriglyceridemic states should prompt close surveillance of patients for T2DM.²⁴

High fasting TG levels evidently reflect increased hepatic synthesis of VLDL and/or a reduction in the efficiency of TG clearance. It is argued that the elevated TGs are a marker for insulin resistance, rather than any inherent pathogenic role of TGs per se. The increased CVD risk was seen in those hypertriglyceridemic subjects who were associated with visceral obesity and were insulin resistant, and is absent in patients whose markedly elevated TG reflect genetically defective lipoprotein lipase activity.²⁵ In the United States, mean TGs have risen since 1976, in concert with the growing epidemic of obesity, insulin resistance, and T2DM.^26,27 As shown in the present study, 93% of subjects with metabolic syndrome had hypertriglyceridemia. Therefore, fasting TGs represent a practical and potentially useful screening method for primary care practitioners to identify obese individuals with increased risks for metabolic syndrome.

TG levels are more variable when drawn in the nonfasting state; therefore, careful attention to fasting is very important in obtaining a true measure of TGs. There are also physiological variations in levels of plasma TGs.²⁸ Coefficients of variation of about 25% for TGs are reported in retesting. Retest reliability showed little or no dependence on other factors studied.²⁹ Repeated measures should be used to assess this important biomarker.

The present study has a few weaknesses. First, the study sample is small and the study population consisted predominantly of women. In the current study, the log TG association with prevalence of metabolic syndrome may be driven by the dominance of women in the study. Second, African Americans had a lower prevalence of elevated TGs as compared with non-Hispanic whites. In Multi-Ethnic Study of Atherosclerosis study, African-American women had higher prevalence rates than white women of abdominal obesity, elevated blood pressure, low HDL-C, elevated fasting glucose, and HOMA when TG values were <150 mg/dL. In men, the prevalence rates of high blood pressure, elevated fasting glucose, and HOMA were significantly higher in African Americans than in whites. Further evaluation is warranted regarding the cutoffs for elevated TGs and its clustering effect with other cardiometabolic risk factors in predicting risk for diabetes and CVD in African Americans.³⁰ Last, little is known regarding the degree to which TG levels need to be reduced to observe a clinical benefit except in subjects with severe hypertriglyceridemia.³¹

In summary, individuals with an increased waist size, obesity, and hypertriglyceridemia should be targeted for aggressive lifestyle and diet interventions to reduce the incidence of metabolic syndrome and T2DM. The public health cost savings of early intervention with diet and lifestyle, rather than waiting for glucose levels to reach a predetermined level necessary for the diagnosis of diabetes obligating pharmacological intervention, could be in the billions of dollars.

Footnotes

Acknowledgment

This study was supported by the Department of Medicine, David Geffen School of Medicine at UCLA.

Author Disclosure Statement

None of the authors has any conflicts of interest deemed relevant to the current study.

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