Suppr超能文献

一项关于糖尿病前期状态变化的全基因组关联研究。

A Genome-Wide Association Study of Prediabetes Status Change.

机构信息

College of Nursing, Florida State University, Tallahassee, FL, United States.

College of Nursing, University of Illinois at Chicago, Chicago, IL, United States.

出版信息

Front Endocrinol (Lausanne). 2022 Jun 13;13:881633. doi: 10.3389/fendo.2022.881633. eCollection 2022.

Abstract

We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher's method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted.

摘要

我们对 900 名参加动脉粥样硬化风险社区研究(ARIC)的白人参与者的糖尿病前期状态变化(向糖尿病或正常血糖转变)进行了首次全基因组关联研究。通过逻辑回归模型,基于单核苷酸多态性(SNP)进行分析,控制年龄、性别、体重指数和前 3 个遗传主成分。通过使用有效的卡方检验方法组合 SNP 基于的 p 值进行基因基础分析。在弗雷明汉心脏研究(FHS)的 514 名白人参与者中,对有希望的 SNP(p<1×10-5)和基因(p<1×10-4)进行了进一步的复制评估。为了适应家族相关性,在 FHS 中使用广义估计方程模型进行 SNP 基于的分析。使用逆方差加权荟萃分析方法对 ARIC 和 FHS 的分析结果进行了组合,用于 SNP 和 Fisher 方法的基因。我们使用基因基础分析稳健地鉴定了 5 个与糖尿病前期状态变化相关的新基因,包括位于 8p22 的 (ARIC p=9.93×10-6,FHS p=2.00×10-3,Meta p=3.72×10-7)、位于 10q24.2 的 (ARIC p=8.26×10-19,FHS p=5.85×10-3,Meta p<8.26×10-19)、位于 10q26.3 的 (ARIC p=1.34×10-5,FHS p=1.13×10-3,Meta p=2.88×10-7)、位于 11q25 的 (ARIC p=3.71×10-6,FHS p=4.51×10-3,Meta p=3.16×10-7)和位于 15q26.3 的 (ARIC p=6.51×10-6,FHS p=1.10×10-2,Meta p=1.25×10-6)。eQTL 分析表明,这些基因在与糖尿病发展相关的组织中高度表达。然而,我们在单 SNP 基于的分析中没有发现任何新的基因座。未来需要对糖尿病前期状态变化进行大规模的基因组研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f8/9234217/3f228ce021b6/fendo-13-881633-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验