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Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods.

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.

SUBMITTER: Nock NL

PROVIDER: S-EPMC2795950 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods.

Nock Nora L NL Wang Xuefeng X Thompson Cheryl L CL Song Yeunjoo Y Baechle Dan D Raska Paola P Stein Catherine M CM Gray-McGuire Courtney C

BMC proceedings 20091215

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 t ...[more]

PMID: 20018043

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Project description:IntroductionIn low and middle-income countries, adolescent mental health is not only a major public health challenge but also a development concern. Depression and anxiety are the most common mental health disorders and somatic symptoms often co-exist with them. Adolescents with common mental health problems are associated with an increased risk of suicide, future unemployment, and poor quality of life. However, little is known about the mental health of adolescents in Ethiopia. Thus, this study aimed to assess the determinants of depression, anxiety, and somatic symptoms among adolescents in Northwest Ethiopia, in 2022.MethodsAn institution-based cross-sectional study was conducted from June 8 to 24, 2022. Two-stage stratified random sampling was used to select 1407 adolescents in Northwest Ethiopia. Structured and standardized self-administered questionnaires were used to collect the data. Non-recursive structural equation modeling was employed to assess the direct, indirect, and total effects of predictors. Adjusted regression coefficients and corresponding 95% confidence intervals were used to interpret the strength of the association.ResultsThe prevalence of depression, anxiety, and somatic symptoms were 28.21% (95% CI: 25.8, 31%), 25.05% (95%CI: 22.8, 27.5), and 25.24(95% CI: 23, 27.6%) respectively. Alcohol use had a significant positive effect on depression [β = 0.14, 95% CI: 0.073, 0.201], anxiety [β = 0.11, 95% CI: 0.041, 0.188], and somatic symptoms [β = 0.12, 95% CI: 0.062, 0.211]. Stress had a significant positive effect on depression [β = 0.76, 95% CI: 0.642, 0.900], anxiety [β = 1.10, 95% CI: 0.955, 1.264], and somatic symptoms [β = 086, 95% C: 0.700, 1.025]. Depression had a direct positive effect on anxiety [β = 0.74, 95% CI: 0.508, 1.010].ConclusionIn this study, the prevalence of depression, anxiety, and somatic symptoms was moderate. Alcohol use and stress were significantly related to depression, anxiety, and somatic symptoms. The bidirectional relationship between anxiety and depression was significant. Therefore, public health interventions should focus on the bidirectional relationship between depression and anxiety, as well as on identified factors to reduce the burden of mental illness in adolescents.

Dataset Information

Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods.

Publications

Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods.

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