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Association of polymorphisms and other risk factors with cholesterol level over time using logic random effect model: Tehran Lipid and Glucose Study
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Parvin Sarbakhsh   , Yadollah Mehrabi , Maryam Daneshpour , Farid Zayeri , Mahshid Namdari |
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Abstract: (4946 Views) |
| Introduction: changes in cholesterol level can be a product of Genetic interactions of some factors. These interactions are time-dependent. Since a time-dependent genetic interaction study related to blood cholesterol levels has not been performed until now, this study is proposed to evaluate the time-dependent association of SNPs and cholesterol by using a logic random effect model of assessment . Materials and Methods: logic random effect model was proposed in the frame of random effects models by using negative likelihood as the score function to analyze the interactions related to longitudinal quantitative responses. Data of 329 participants in TLGS prospective cohort study was analyzed using proposed model to identify effective interactions related to cholesterol. Annealing algorithm was used to search interaction effects. Coefficient of these interactions and random effect were estimated using maximum likelihood method. Results : The results for male or other subjects with GG genotype for ApoAIV who had normal blood pressure and waist circumference had shown significant lower cholesterol levels (19.8 mg/dl, CI 95%: 13.9, 25.69) (p< 0.001) than other subjects without this combination. Also, having (high triglyceride or allele e2 for ApoE) was significantly associated with an increasing effect on cholesterol (β=16.1, CI 95%: 11.64, 20.55). The level of the cholesterol in phase 1 of study was 21.4 mg/dl (CI 95%: 18.35, 24.44) more than other phases (p< 0.001). The model’s random effect was estimated 165.82 with standard deviation 30.89 (p |
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| Keywords: Cholesterol, Logic regression, Longitudinal data, Random effect model |
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Full-Text [PDF 580 kb]
(1250 Downloads)
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Type of Study: Research |
Subject:
General
Received: 2013/09/11 | Accepted: 2014/07/9 | Published: 2014/12/16
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