A Systematic Review of Single Nucleotide Polymorphisms Associated With Metabolic Syndrome in Children and Adolescents

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Roya Kelishadi ◽  
Silva Hovsepian ◽  
Shaghayegh Haghjooy Javanmard
Keyword(s):  
Systematic Review ◽  
Metabolic Syndrome ◽  
Single Nucleotide Polymorphisms ◽  
Children And Adolescents ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide

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 Associations between Single Nucleotide Polymorphisms and Total Energy, Carbohydrate, and Fat Intakes: A Systematic Review

2018 ◽  
Vol 9 (4) ◽  
pp. 425-453 ◽  
Author(s):  
Theresa Drabsch ◽  
Jennifer Gatzemeier ◽  
Lisa Pfadenhauer ◽  
Hans Hauner ◽  
Christina Holzapfel
Keyword(s):  
Systematic Review ◽  
Single Nucleotide Polymorphisms ◽  
Total Energy ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide

scholarly journals Association between melatonin receptor gene polymorphisms and polycystic ovarian syndrome: a systematic review and meta-analysis

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Shiqi Yi ◽  
Jiawei Xu ◽  
Hao Shi ◽  
Wenbo Li ◽  
Qian Li ◽  
...  
Keyword(s):  
Systematic Review ◽  
Single Nucleotide Polymorphisms ◽  
Polycystic Ovarian Syndrome ◽  
Meta Analysis ◽  
Genetic Models ◽  
Cochrane Library ◽  
Nucleotide Polymorphisms ◽  
Melatonin Receptor ◽  
Single Nucleotide ◽  
Ovarian Syndrome

Abstract Background: Polycystic ovarian syndrome (PCOS) is a kind of common gynecological endocrine disorder. And the mutations of melatonin receptor (MTNR) genes are related to the occurrence of PCOS. But previous researches have shown opposite results. So, the object of our systematic review and meta-analysis is to investigate the relationship between MTNR 1A/B polymorphisms and PCOS. Methods: PubMed, Embase, Ovid, the Cochrane Library, Web of Science and three Chinese databases (VIP, CNKI and Wanfang) were used to retrieve eligible articles published between January 1980 and February 2020. And we used the odds ratio (OR) and its 95% confidence interval (CI) to investigate the strength of the association by six genetic models, allelic, codominant (homozygous and heterozygous), dominant, recessive and superdominant models. Review Manager 5.3, IBM SPSS statistics 25 and Stata MP 16.0 software were used to do this meta-analysis. Results: Our meta-analysis involved 2553 PCOS patients and 3152 controls, for two single nucleotide polymorphisms (rs10830963 C&gt; G in MTNR1B and rs2119882 T&gt; C in MTNR1A) and significant associations were found in some genetic models of these single nucleotide polymorphisms (SNPs). For rs10830963, strongly significant was found in the heterozygote model (GC vs. CC, P=0.02). Additionally, a slight trend was detected in the allelic (G vs. C), homozygote (GG vs. CC) and dominant (GG+GC vs. CC) model of rs10830963 (P=0.05). And after further sensitivity analysis, a study with high heterogeneity was removed. In the allelic (P=0.000), homozygote (P=0.001), dominant (P=0.000) and recessive (GG vs. GC+CC, P=0.001) model, strong associations between rs10830963 and PCOS were found. Moreover, for rs2119882, five genetic models, allelic (C vs. T, P=0.000), codominant (the homozygote (CC vs. TT, P=0.000) and heterozygote model (CT vs. TT, P=0.02), dominant (CC + CT vs. TT, P=0.03) and recessive model (CC vs. CT + TT, P=0.000) showed significant statistical associations with PCOS. Conclusion: MTNR1B rs10830963 and MTNR1B rs2119882 polymorphisms are associated with PCOS risk. However, the above conclusions still require being confirmed by much larger multi-ethnic studies.

scholarly journals Effects of four single nucleotide polymorphisms of EZH2 on cancer risk: a systematic review and meta-analysis

2018 ◽  
Vol Volume 11 ◽  
pp. 851-865 ◽  
Author(s):  
Zhixin Ling ◽  
Zonghao You ◽  
Ling Hu ◽  
Lei Zhang ◽  
Yiduo Wang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cancer Risk ◽  
Single Nucleotide Polymorphisms ◽  
Meta Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide
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