Abstract
The Metabolic Syndrome (MetSyn), which is a clustering of traits including insulin resistance, obesity, hypertension and dyslipidemia, is estimated to have a substantial genetic component, yet few specific genetic targets have been identified. Factor analysis, a sub-type of structural equation modeling (SEM), has been used to model the complex relationships in MetSyn. Therefore, we aimed to define the genetic determinants of MetSyn in the Framingham Heart Study (Offspring Cohort, Exam 7) using the Affymetrix 50 k Human Gene Panel and three different approaches: 1) an association-based "one-SNP-at-a-time" analysis with MetSyn as a binary trait using the World Health Organization criteria; 2) an association-based "one-SNP-at-a-time" analysis with MetSyn as a continuous trait using second-order factor scores derived from four first-order factors; and, 3) a multivariate SEM analysis with MetSyn as a continuous, second-order factor modeled with multiple putative genes, which were represented by latent constructs defined using multiple SNPs in each gene. Results were similar between approaches in that CSMD1 SNPs were associated with MetSyn in Approaches 1 and 2; however, the effects of CSMD1 diminished in Approach 3 when modeled simultaneously with six other genes, most notably CETP and STARD13, which were strongly associated with the Lipids and MetSyn factors, respectively. We conclude that modeling multiple genes as latent constructs on first-order trait factors, most proximal to the gene's function with limited paths directly from genes to the second-order MetSyn factor, using SEM is the most viable approach toward understanding overall gene variation effects in the presence of multiple putative SNPs.
Highlights
The Metabolic Syndrome (MetSyn) is a clustering of metabolic disturbances that increases the risk of type 2 diabetes and cardiovascular disease [1], and may contribute to the pathogenesis of other complex diseases, including cancer [2]
Studies conducted in adults using 8 to 10 metabolic measures (fasting insulin, fasting glucose, post-challenge insulin, post-challenge glucose, body mass index (BMI), waist circumference or waist-to-hip ratio (WHR), high density lipoprotein-cholesterol (HDL), triglycerides (TG), systolic blood pressure (SBP), diastolic blood pressure (DBP)) have shown that the MetSyn is best described, statistically, as a unifying, second-order factor defined by four first-order factors (Insulin Resistance, Obesity, Hypertension, Lipids) [8,9,10]
We aimed to define the genetic determinants of MetSyn in the Framingham Heart Study (Offspring Cohort, Exam 7) using the Affymetrix 50 k Human Gene Panel data and three different approaches: 1) an association-based “onesingle-nucleotide polymorphism (SNP)-at-a-time” analysis with MetSyn defined as a binary trait using the WHO criteria [7]; 2) an association-based “one-SNP-ata-time” analysis with MetSyn defined as a continuous trait using second-order factor scores derived from insulin resistance, obesity, hypertension, and dyslipidemia factors; and, 3) a multivariate SEM analysis with MetSyn defined as a second-order continuous factor trait modeled simultaneously with putative genes, which we represented as latent constructs defined by multiple SNPs within each gene
Summary
The Metabolic Syndrome (MetSyn) is a clustering of metabolic disturbances that increases the risk of type 2 diabetes and cardiovascular disease [1], and may contribute to the pathogenesis of other complex diseases, including cancer [2]. It is well established that MetSyn involves the co-occurrence of multiple metabolic traits, there are differences in the formal definitions set forth by the World Health Organization (WHO), the National Cholesterol Education Program Third Adult Treatment Panel (NCEP-ATP III), the American Heart Association/ National Heart, Lung and Blood Institute (AHA/NHLBI) and the International Diabetes Federation (IDF), predominantly in defining the most relevant elements and their biological cut-points, which has contributed to confusion in the literature [7] All of these definitions include criteria on four common traits: 1) insulin resistance, 2) obesity, 3) hypertension, and 4) dyslipidemia. Studies conducted in adults using 8 to 10 metabolic measures (fasting insulin, fasting glucose, post-challenge insulin, post-challenge glucose, body mass index (BMI), waist circumference or waist-to-hip ratio (WHR), high density lipoprotein-cholesterol (HDL), triglycerides (TG), systolic blood pressure (SBP), diastolic blood pressure (DBP)) have shown that the MetSyn is best described, statistically, as a unifying, second-order factor defined by four first-order factors (Insulin Resistance, Obesity, Hypertension, Lipids) [8,9,10]
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