1 Department of Epidemiology and Institute for Public Health Genetics, School of Public Health and Community Medicine, University of Washington, Seattle, Washington
2 Division of General Internal Medicine, Department of Medicine, School of Medicine, University of Washington, Seattle, Washington
3 Laboratory Medicine, Harborview Medical Center University of Washington, Seattle, Washington
4 Department of Anthropology, University of Washington, Seattle, Washington
5 Centre for Cardiovascular Genetics, Department of Medicine, Royal Free and University College London, London, U.K.
6 Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, School of Medicine, University of Washington, Seattle, Washington
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ABSTRACT |
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A rapidly growing body of evidence demonstrates important associations between the metabolic syndrome, characterized by a cluster of risk factors that include dyslipidemia, central obesity, hypertension, and hyperinsulinemia, and both cardiovascular disease (CVD) and type 2 diabetes (14). In addition to these risk factors, recent evidence also indicates that the metabolic syndrome involves inflammatory processes and that markers such as C-reactive protein (CRP) should be considered other components of the syndrome (5,6).
Because the metabolic syndrome is characterized by this constellation of highly intercorrelated quantitative phenotypes, >12 studies have used factor analysis to simplify the syndrome and to potentially provide new insights about the underlying pathophysiological mechanisms that may be involved (1,710). These studies have included diabetic (4) and nondiabetic (2) subjects, different ethnic groups (3,1113), and older individuals (6,12). Importantly, several of these studies have shown that the factors identified predict risk of CVD (2,4), stroke (9), type 2 diabetes (3), and all-cause mortality (1).
Only a few studies have examined whether genetic susceptibility may underlie the metabolic syndrome (13,14). However, it has been suggested that the independent multivariate phenotypes of the syndrome, identified by factor analysis, may be useful in mapping susceptibility genes for the syndrome (15).
The purpose of the present study was to characterize the metabolic syndrome in a sample of Japanese-American families, using factor analysis of the phenotypes, and to estimate the heritability of these factors.
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RESEARCH DESIGN AND METHODS |
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Eligible family members included the parents, spouses, and offspring of the proband, siblings, spouses of siblings, and nieces and nephews of the proband, age 18 years, residing anywhere in the U.S., who were not pregnant and not too ill to participate. Approximately one-quarter of study subjects resided outside of Washington. Thus, the study sample consists primarily of two-generation extended Nisei and Sansei kindreds. Family sizes ranged from 2 relatives to 27 family members, with an average of 8.4 members per family. Each proband and relative was contacted individually by letter and phone and asked to participate in the study, including providing a fasting blood sample. The University of Washington Institutional Review Board approved these methods, and all study participants provided written, informed consent.
A self-administered questionnaire was used to obtain demographic information and medical history information from all local and nonlocal study participants. Study participants were asked to provide information on all medications, and these were coded into 82 different drug classes (ß-blockers, diuretics, hormone replacement for women, diabetes medications, etc.).
Blood pressure was measured in the left arm after the patient had been seated for at least 5 min, and the first- and fifth-phase Korotkoff sounds were recorded (in mmHg), as systolic and diastolic blood pressures, respectively. Waist was self-reported based on a metric tape measure sent with the medical history questionnaire, except for 24 study subjects who had waist and hip measurements performed by a trained technician.
LDL subclasses were characterized by electrophoresis on 214% polyacrylamide gels using standard protocols (17). The estimated diameter for the major peak from the gel scan is denoted "LDL peak particle diameter" (LDL size) and was used as a continuous variable in the analyses. Lipid measurements were performed at the Core Laboratory, Northwest Lipid Research Laboratories (18). High-sensitivity CRP was measured using immunonephelometric methods (19). Total immunoreactive insulin was measured using a double-antibody radioimmunoassay. Glucose was measured using the Beckman Synchron LX system by an oxygen rate method.
Pedigrees for all kindreds were initially constructed based on family information reported by probands. Based on DNA samples, the kindred structures were extensively checked using genetic markers from seven different chromosomes, using the PedCheck program (20).
Statistical analyses.
Because of skewness, plasma triglycerides and CRP values were natural log transformed before the analysis. Subjects with type 2 diabetes (defined as fasting glucose >125 mg/dl, taking known medication for diabetes, self-reported diabetes, and self-report of taking insulin or oral antidiabetic pills by questionnaire), CRP >10 mg/l, or missing glucose, insulin, blood pressure, or waist measurements were excluded. With these exclusions, a total of 432 study subjects were included in the analysis.
Factor analysis was used to investigate the interrelationships among the phenotypes of the metabolic syndrome, including LDL size, ln triglycerides, HDL cholesterol, systolic and diastolic blood pressure, waist circumference, fasting insulin and glucose, and CRP. In addition, the analyses were repeated substituting BMI for waist measurements, as well as using only subjects with self-reported waist measurements, and the results did not differ substantially. We conducted factor analysis using SAS version 8.2 (21). The analyses were adjusted for age and sex by multiple regression analysis, and standardized residuals were used in the factor analysis. Briefly, factor analysis consists of principle components analysis, a varimax rotation, and identification of the variables with factor loadings 0.4 to facilitate interpretation (7,22). The standardized scoring coefficients were then used to compute factor scores for each study subject, consisting of a weighted sum of the values of the standardized phenotypes for that factor.
The Statistical Analysis for Genetic Epidemiology (SAGE) (23) program was applied to calculate heritability of the factor scores. We conducted variance-components analysis to estimate the heritability of CRP levels using ASSOC program in SAGE. Polygenic effect was specified in the computation of heritability.
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RESULTS |
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DISCUSSION |
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The only other study of Asian Americans using factor analysis was performed based on older men in the Honolulu Heart Program (12). Similar results were found among subjects with and without diabetes, resulting in four factors: weight/waist, blood pressure, lipids, and insulin/glucose. Studies of African Americans and Hispanics have found only two factors (11,24), while three or four factors were found among Pima Indians and Canadian Aboriginal groups (3,25). In both the Framingham and Rancho Bernardo studies of European-American men and women (8,10), three independent factors were also observed. Thus, although direct comparisons of the factors are difficult due to the use of different phenotypes, all studies have found at least two, and often three or four, independent factors characterizing the metabolic syndrome, indicating that several pathophysiological pathways are likely to underlie the metabolic syndrome.
Due to the recent recognition that inflammatory factors are also important components of the metabolic syndrome, two studies have included CRP in factor analyses of the metabolic syndrome. The addition of procoagulation, inflammation, and fibrinolysis variables to a factor analysis among the nondiabetic elderly men and women in the Cardiovascular Health Study (6) led to the emergence of a separate "inflammation" factor that included CRP and fibrinogen. In an analysis of middle-aged Finnish men, fibrinogen also loaded on a separate factor (1). Thus, there is growing evidence that inflammatory phenotypes are an independent component of the metabolic syndrome.
Two previous studies have reported heritability values for multivariate factors of the metabolic syndrome, one based on the Kaiser Permanente Womens Twin Study (14) and the other based on the San Antonio Family Diabetes Study (13); both found significant genetic influences on all of the factors. In the latter study, three factors were identified, similar to those reported here for Japanese-American families, and the heritability of the lipid factor was nearly identical to the value of 0.52. Among the Mexican-American families, heritabilities of the adiposity/insulin (0.51) and blood pressure (0.58) factors were higher than in this study. Taken together, these results demonstrate important underlying genetic susceptibility to the metabolic syndrome.
In summary, this factor analysis of phenotypes of the metabolic syndrome in Japanese Americans confirms previous studies showing that the syndrome consists of three to four independent factors, reflecting different underlying mechanisms for disease risk. Furthermore, each of these factors is genetically influenced, with 2550% of the variance attributable to polygenic influences. Therefore, genetic mapping studies are needed to identify the specific genes that influence each of the multivariate factors of the syndrome in order to better understand genetic susceptibility to CVD and diabetes.
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ACKNOWLEDGMENTS |
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The authors would like to thank Cherry Tamblyn, Carrie Nelson, Brian Fish, and Jing Wang for excellent technical assistance.
Address correspondence and reprint requests to Melissa A. Austin, PhD, Department of Epidemiology, 1959 N.E. Pacific Ave, Box 357236, University of Washington, Seattle, WA 98195-7236. E-mail: maustin{at}u.washington.edu
Received for publication August 26, 2003 and accepted in revised form January 13, 2004
CRP, C-reactive protein; CVD, cardiovascular disease
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REFERENCES |
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