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中国人群中基因多态性与妊娠期糖尿病易感性的关联

Association between genetic polymorphisms and gestational diabetes mellitus susceptibility in a Chinese population.

作者信息

Zeng Qiaoli, Liu Jia, Liu Xin, Liu Na, Wu Weibiao, Watson Ray Gyan, Zou Dehua, Wei Yue, Guo Runmin

机构信息

Department of Internal Medicine, Shunde Women and Children's Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China.

Key Laboratory of Research in Maternal and Child Medicine and Birth Defects, Guangdong Medical University, Foshan, Guangdong, China.

出版信息

Front Endocrinol (Lausanne). 2024 Nov 26;15:1397423. doi: 10.3389/fendo.2024.1397423. eCollection 2024.


DOI:10.3389/fendo.2024.1397423
PMID:39659616
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11628248/
Abstract

BACKGROUND: Although the association between HHEX, IGF2BP2, and FTO polymorphisms and the risk of GDM has been investigated in several studies, the findings have been inconsistent across different populations. The study aimed to investigate the association between genetic polymorphisms and GDM risk in a Chinese population. METHODS: 502 control volunteers and 500 GDM patients were enrolled. IGF2BP2 rs11705701 and rs4402960, FTO rs9939609, and HHEX rs1111875 and rs5015480 were all genotyped using the SNPscan™ genotyping assay. The independent sample t-test, logistic regression, and chi-square test were used to assess the variations in genotype and allele and their relationships with the risk of GDM. The blood glucose level, gestational week of delivery, and newborn weight were compared using a one-way ANOVA. RESULTS: After adjusting for confounding factors, the results show that the rs1111875 heterozygous (OR=1.370; 95% CI: 1.040-1.805; = 0.025) and overdominant (OR=1.373; 95% CI: 1.049-1.796; = 0. 021) models are significantly associated with an increased risk of GDM, especially for the age ≥ 30 years group: heterozygote (OR=1.646; 95% CI: 1.118-2.423; =0.012) and overdominant (OR=1.553; 95% CI: 1.064-2.266; = 0.022) models. In the age ≥ 30 years, the rs5015480 overdominant model (OR=1.595; 95% CI: 1.034-2.459; = 0.035) and the rs9939609 heterozygote model (OR=1.609; 95% CI: 1.016-2.550; =0.043), allele (OR=1. 504; 95% CI: 1.006-2.248; P = 0.047), dominant model (OR=1.604; 95% CI: 1.026-2.505; = 0.038), and overdominant model (OR=1.593; 95% CI: 1.007-2.520; = 0.047) were associated with a significantly increased risk of GDM; Additionally, people with the TC genotype of rs1111875 had a substantially higher 1-hour blood glucose level than TT genotype ( < 0.05). The results of the meta-analysis showed that the A allele of rs11705701 was associated with an increased risk of diabetes mellitus ( < 0.05). CONCLUSION: The study indicates that the TC genotype of rs1111875 is linked to a higher risk of GDM, particularly in women aged 30 years or older. Additionally, rs5015480 and rs9939609 were significantly associated with GDM in the same age group. These SNPs may therefore be more closely linked to GDM in older mothers.

摘要

背景:尽管已有多项研究探讨了HHEX、IGF2BP2和FTO基因多态性与妊娠期糖尿病(GDM)风险之间的关联,但不同人群的研究结果并不一致。本研究旨在调查中国人群中基因多态性与GDM风险之间的关联。 方法:招募了502名对照志愿者和500名GDM患者。使用SNPscan™基因分型检测法对IGF2BP2 rs11705701和rs4402960、FTO rs9939609以及HHEX rs1111875和rs5015480进行基因分型。采用独立样本t检验、逻辑回归和卡方检验来评估基因型和等位基因的差异及其与GDM风险的关系。使用单因素方差分析比较血糖水平、分娩孕周和新生儿体重。 结果:在调整混杂因素后,结果显示rs1111875杂合子(OR = 1.370;95% CI:1.040 - 1.805;P = 0.025)和超显性(OR = 1.373;95% CI:1.049 - 1.796;P = 0.021)模型与GDM风险增加显著相关,尤其是在年龄≥30岁的人群中:杂合子(OR = 1.646;95% CI:1.118 - 2.423;P = 0.012)和超显性(OR = 1.553;95% CI:1.064 - 2.266;P = 0.022)模型。在年龄≥30岁的人群中,rs5015480超显性模型(OR = 1.595;95% CI:1.034 - 2.459;P = 0.035)、rs9939609杂合子模型(OR = 1.609;95% CI:1.016 - 2.550;P = 0.043)、等位基因(OR = 1.504;95% CI:1.006 - 2.248;P = 0.047)、显性模型(OR = 1.604;95% CI:1.026 - 2.505;P = 0.038)和超显性模型(OR = 1.593;95% CI:1.007 - 2.520;P = 0.047)与GDM风险显著增加相关;此外,rs1111875的TC基因型个体的1小时血糖水平显著高于TT基因型个体(P < 0.05)。荟萃分析结果显示,rs11705701的A等位基因与糖尿病风险增加相关(P < 0.05)。 结论:该研究表明,rs1111875的TC基因型与GDM风险较高相关,尤其是在30岁及以上的女性中。此外,rs5015480和rs9939609在同一年龄组中与GDM显著相关。因此,这些单核苷酸多态性可能与高龄母亲的GDM关系更为密切。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/6352d0161515/fendo-15-1397423-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/afeff70ca606/fendo-15-1397423-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/3c7e1a7ab020/fendo-15-1397423-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/8dcf141fedae/fendo-15-1397423-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/78b66ad2230e/fendo-15-1397423-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/a6af58b0aacf/fendo-15-1397423-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/54af1823755a/fendo-15-1397423-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/b8fd17572172/fendo-15-1397423-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/240ad22d42e6/fendo-15-1397423-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/6352d0161515/fendo-15-1397423-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/afeff70ca606/fendo-15-1397423-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/3c7e1a7ab020/fendo-15-1397423-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/8dcf141fedae/fendo-15-1397423-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/78b66ad2230e/fendo-15-1397423-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/a6af58b0aacf/fendo-15-1397423-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/54af1823755a/fendo-15-1397423-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/b8fd17572172/fendo-15-1397423-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/240ad22d42e6/fendo-15-1397423-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e00c/11628248/6352d0161515/fendo-15-1397423-g009.jpg

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[2]
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Biochem Genet. 2023-12

[3]
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[4]
Contribution of genetic variant identified in gene in the overweight Saudi patients confirmed with type 2 diabetes mellitus.

Saudi J Biol Sci. 2022-2

[5]
Genetic risk factors associated with gestational diabetes in a multi-ethnic population.

PLoS One. 2021-12-20

[6]
Risk of type 2 diabetes mellitus and cardiovascular complications in , and genetic polymorphisms carriers: A case-control study.

Heliyon. 2021-11-17

[7]
Association of Common Genetic Risk Variants With Gestational Diabetes Mellitus and Their Role in GDM Prediction.

Front Endocrinol (Lausanne). 2021

[8]
Association Between Single Nucleotide Polymorphisms in and and Type 2 Diabetes in Chinese Population.

Diabetes Metab Syndr Obes. 2021-1-5

[9]
Association Between CDKAL1, HHEX, CDKN2A/2B and IGF2BP2 Gene Polymorphisms and Susceptibility to Type 2 Diabetes in Uttarakhand, India.

Diabetes Metab Syndr Obes. 2021-1-6

[10]
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