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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sajedeh Masjoudi ◽  
Bahareh Sedaghati-khayat ◽  
Niloufar Javanrouh Givi ◽  
Leila Najd Hassan Bonab ◽  
Fereidoun Azizi ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Regression Models ◽  
High Plasma ◽  
Joint Effect ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Kernel Machine ◽  
Kernel Machine Regression ◽  
Significance Levels ◽  
Apoa5 Gene

AbstractMetabolic 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.

scholarly journals Association between single nucleotide polymorphisms rs72525532, rs45596738, rs148759216, rs188133936, and rs114627122 of APOA5 gene in children and adolescents with metabolic syndrome

2019 ◽  
Vol 21 (4) ◽  
pp. 175-180
Author(s):  
Samaneh Salehi ◽  
Modjtaba Emadi-Baygi ◽  
Parvaneh Nikpour ◽  
Roya Kelishadi
Keyword(s):  
Metabolic Syndrome ◽  
Single Nucleotide Polymorphisms ◽  
Children And Adolescents ◽  
Control Group ◽  
Nucleotide Polymorphisms ◽  
Normal Children ◽  
Single Nucleotide ◽  
Increased Risk ◽  
Significant Difference ◽  
Apoa5 Gene

Background and aims: The APOA5 gene is one of the genes involved in metabolic syndrome (MetS), as a constellation of several cardiovascular disease (CVD) risk factors. The present study evaluated the possible associations between five single nucleotide polymorphisms (SNPs) in the microRNA target site (miR-TS-SNPs) of the APOA5 gene with MetS. Methods: This case-control study included 57 MetS cases, along with 59 normal children and adolescents aged 9-18 years. All miR-TSSNPs rs188133936, rs72525532, rs45596738, rs148759216, and rs114627122 were genotyped by polymerase chain reaction-sequencing. Independent t-test, as well as the chi-square test and logistic regression analysis was used to determine the association of SNPs with MetS risk and its clinical components. Results: The mean (SD) age of MetS participants and controls was 12.35 (0.25) and 13.39 (0.38) years, respectively. Although no nucleotide changes were present in rs188133936, rs45596738, rs148759216, and rs114627122, a greater frequency of A insertion was detected in rs72525532 in MetS cases compared with the control group (P=0.012). This variant showed a significant difference in triglycerides (TG) and high-density lipoprotein cholesterol (HDL) levels between different genotype groups (P<0.0001 and P=0.05, respectively) in controls. Furthermore, AA insertion genotype was correlated with an increased risk of MetS (Odds ratio [95% CI] = 8.12 [0.966-68.27], P=0.05). Conclusion: This study was the first to investigate the association between rs188133936, rs45596738, rs148759216, rs76463524, and rs72525532 variants of the APOA5 gene and MetS. Our findings reveal that rs72525532 might have an impact on TG, HDL levels, and the risk of MetS

scholarly journals Power of a reproducing kernel-based method for testing the joint effect of a set of single-nucleotide polymorphisms

Genetica ◽  
2012 ◽  
Vol 140 (10-12) ◽  
pp. 421-427 ◽  
Author(s):  
Hong He ◽  
Hongmei Zhang ◽  
Arnab Maity ◽  
Yubo Zou ◽  
James Hussey ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Reproducing Kernel ◽  
Joint Effect ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide

scholarly journals Coffee Consumption, Genetic Polymorphisms, and the Risk of Type 2 Diabetes Mellitus: A Pooled Analysis of Four Prospective Cohort Studies

2020 ◽  
Vol 17 (15) ◽  
pp. 5379
Author(s):  
An Na Kim ◽  
Hyun Jeong Cho ◽  
Jiyoung Youn ◽  
Taiyue Jin ◽  
Moonil Kang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Regression Models ◽  
Coffee Consumption ◽  
Pooled Analysis ◽  
Random Effects Model ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Logistic Regression Models

The association between coffee consumption and the risk of type 2 diabetes may vary by genetic variants. Our study addresses the question of whether the incidence of type 2 diabetes is related to the consumption of coffee and whether this relationship is modified by polymorphisms related to type 2 diabetes. We performed a pooled analysis of four Korean prospective studies that included 71,527 participants; median follow-up periods ranged between 2 and 13 years. All participants had completed a validated food-frequency questionnaire (FFQ) at baseline. The odds ratios (ORs) and 95% confidence intervals (CIs) for type 2 diabetes were calculated using logistic regression models. The ORs were combined using a fixed or random effects model depending on the heterogeneity across the studies. Compared with 0 to <0.5 cups/day of coffee consumption, the OR for type 2 diabetes was 0.89 (95% CI: 0.80–0.98, p for trend = 0.01) for ≥3 cups/day of coffee consumption. We did not observe significant interactions by five single nucleotide polymorphisms (SNPs) related to type 2 diabetes (CDKAL1 rs7756992, CDKN2A/B rs10811661, KCNJ11 rs5215, KCNQ1 rs163184, and PEPD rs3786897) in the association between coffee and the risk of type 2 diabetes. We found that coffee consumption was inversely associated with the risk of type 2 diabetes.

scholarly journals Genome-Wide Association Study of Body Weight Traits in Chinese Fine-Wool Sheep

Animals ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 170 ◽  
Author(s):  
Zengkui Lu ◽  
Yaojing Yue ◽  
Chao Yuan ◽  
Jianbin Liu ◽  
Zhiqiang Chen ◽  
...  
Keyword(s):  
Body Weight ◽  
Muscle Development ◽  
Genome Wide Association Study ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Economic Trait ◽  
Significance Levels ◽  
Genomic Regions ◽  
Selection Of

Body weight is an important economic trait for sheep and it is vital for their successful production and breeding. Therefore, identifying the genomic regions and biological pathways that contribute to understanding variability in body weight traits is significant for selection purposes. In this study, the genome-wide associations of birth, weaning, yearling, and adult weights of 460 fine-wool sheep were determined using resequencing technology. The results showed that 113 single nucleotide polymorphisms (SNPs) reached the genome-wide significance levels for the four body weight traits and 30 genes were annotated effectively, including AADACL3, VGF, NPC1, and SERPINA12. The genes annotated by these SNPs significantly enriched 78 gene ontology terms and 25 signaling pathways, and were found to mainly participate in skeletal muscle development and lipid metabolism. These genes can be used as candidate genes for body weight in sheep, and provide useful information for the production and genomic selection of Chinese fine-wool sheep.

scholarly journals Top Single Nucleotide Polymorphisms Affecting Carbohydrate Metabolism in Metabolic Syndrome: From the LIPGENE Study

2014 ◽  
Vol 99 (2) ◽  
pp. E384-E389 ◽  
Author(s):  
Javier Delgado-Lista ◽  
Pablo Perez-Martinez ◽  
Juan Solivera ◽  
Antonio Garcia-Rios ◽  
A. I. Perez-Caballero ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Single Nucleotide Polymorphisms ◽  
Carbohydrate Metabolism ◽  
Insulin Response ◽  
Intravenous Glucose Tolerance Test ◽  
Sensitivity Index ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Intravenous Glucose

Rationale: Metabolic syndrome (MetS) is a high-prevalence condition characterized by altered energy metabolism, insulin resistance, and elevated cardiovascular risk. Objectives: Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS. Methods: A total of 904 SNPs (tag SNPs and functional SNPs) were tested for influence on 8 fasting and dynamic markers of carbohydrate metabolism, by performance of an intravenous glucose tolerance test in 450 participants in the LIPGENE study. Findings: From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (16% of the preselected variables) remained significant after bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose, rs26125 (PPARGC1B); fasting insulin, rs4759277 (LRP1); C-peptide, rs4759277 (LRP1); homeostasis assessment of insulin resistance, rs4759277 (LRP1); quantitative insulin sensitivity check index, rs184003 (AGER); sensitivity index, rs7301876 (ABCC9), acute insulin response to glucose, rs290481 (TCF7L2); and disposition index, rs12691 (CEBPA). Conclusions: We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among approximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.

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