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Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study.

ABSTRACT: Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The 11p23.3 chromosomal region plays a potential role in the pathogenesis of MetS. The present study aimed to assess the association between 18 single nucleotide polymorphisms (SNPs) located at the BUD13, ZPR1, and APOA5 genes with MetS in the Tehran Cardio-metabolic Genetics Study (TCGS). In 5421 MetS affected and non-affected participants, we analyzed the data using two models. The first model (MetS model) examined SNPs' association with MetS. The second model (HTg-MetS Model) examined the association of SNPs with MetS affection participants who had a high plasma triglyceride (TG). The four-gamete rules were used to make SNP sets from correlated nearby SNPs. The kernel machine regression models and single SNP regression evaluated the association between SNP sets and MetS. The kernel machine results showed two sets over three sets of correlated SNPs have a significant joint effect on both models (p < 0.0001). Also, single SNP regression results showed that the odds ratios (ORs) for both models are almost similar; however, the p-values had slightly higher significance levels in the HTg-MetS model. The strongest ORs in the HTg-MetS model belonged to the G allele in rs2266788 (MetS: OR = 1.3, p = 3.6 × 10^-7; HTg-MetS: OR = 1.4, p = 2.3 × 10^-11) and the T allele in rs651821 (MetS: OR = 1.3, p = 2.8 × 10^-7; HTg-MetS: OR = 1.4, p = 3.6 × 10^-11). In the present study, the kernel machine regression models could help assess the association between the BUD13, ZPR1, and APOA5 gene variants (11p23.3 region) with lipid-related traits in MetS and MetS affected with high TG.

SUBMITTER: Masjoudi S

PROVIDER: S-EPMC8119714 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundNon-participation in cohort studies, if associated with both the exposure and occurrence of the event, can introduce bias in the estimates of interest. This study aims to identify factors associated with follow-up participation in Tehran Lipid and Glucose Study, a large-scale community-based prospective study in West Asia.MethodsA sample of 10,368 adults from TLGS was included in the analysis. All analyses were split according to sex and age groups (20-39, 40-59, and 60 years). The associations between socio-demographic, health, and lifestyle factors with response rate were identified using the Generalized Estimating Equations model.ResultsOver the median of 15.7 years of follow up the response rate was 64.5%. The highest response rate was observed in those aged 40-59 years for both sexes. Current smokers had lower odds of response in both sexes for all age groups, ranging from 0.51 to 0.74, p < 0.01. In young adults, being single (OR = 0.79, OR = 0.57, p ≤ 0.01, respectively for men and women) and unemployed (OR = 0.73, OR = 0.76, p ≤ 0.01, respectively for men and women) in both sexes, high physical activity in men (OR = 0.77, p < 0.01), high education (OR = 0.75, p = 0.02) and obesity (OR = 0.85, p = 0.05) in women were associated with lower response rate. For the middle-aged group, diabetes in men (OR = 0.77, p = 0.05) and hypertension (OR = 0.84, p = 0.05), and having a history of cancer (OR = 0.43, p = 0.03) in women were factors associated with lower response rates. Finally, interventions for both sexes (OR = 0.75, OR = 0.77, p ≤ 0.05, respectively for men and women) and being divorced/widow in women (OR = 0.77, p = 0.05) were the factors associated with the lower response rate in the elderly.ConclusionsLong-term participation was influenced by socio-demographic, health, and lifestyle factors in different sex- and age-specific patterns in TLGS. Recruitment strategies targeting these factors may improve participant follow-up in longitudinal studies.

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Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study.

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