Suppr超能文献

元基因组全基因组关联研究鉴定出 1 号染色体上的一个位点和 MHC 区域内的多个变体与 1 型糖尿病患者血清 C 肽有关。

Meta-genome-wide association studies identify a locus on chromosome 1 and multiple variants in the MHC region for serum C-peptide in type 1 diabetes.

机构信息

Genetics and Genome Biology Program, Peter Gilgan Centre for Research and Learning (PGCRL), The Hospital for Sick Children, 686 Bay Street, Toronto, ON, M5G 1H3, Canada.

University Hospitals Case Western Medical Center, Cleveland, OH, USA.

出版信息

Diabetologia. 2018 May;61(5):1098-1111. doi: 10.1007/s00125-018-4555-9. Epub 2018 Feb 5.

Abstract

AIMS/HYPOTHESIS: The aim of this study was to identify genetic variants associated with beta cell function in type 1 diabetes, as measured by serum C-peptide levels, through meta-genome-wide association studies (meta-GWAS).

METHODS

We performed a meta-GWAS to combine the results from five studies in type 1 diabetes with cross-sectionally measured stimulated, fasting or random C-peptide levels, including 3479 European participants. The p values across studies were combined, taking into account sample size and direction of effect. We also performed separate meta-GWAS for stimulated (n = 1303), fasting (n = 2019) and random (n = 1497) C-peptide levels.

RESULTS

In the meta-GWAS for stimulated/fasting/random C-peptide levels, a SNP on chromosome 1, rs559047 (Chr1:238753916, T>A, minor allele frequency [MAF] 0.24-0.26), was associated with C-peptide (p = 4.13 × 10), meeting the genome-wide significance threshold (p < 5 × 10). In the same meta-GWAS, a locus in the MHC region (rs9260151) was close to the genome-wide significance threshold (Chr6:29911030, C>T, MAF 0.07-0.10, p = 8.43 × 10). In the stimulated C-peptide meta-GWAS, rs61211515 (Chr6:30100975, T/-, MAF 0.17-0.19) in the MHC region was associated with stimulated C-peptide (β [SE] = - 0.39 [0.07], p = 9.72 × 10). rs61211515 was also associated with the rate of stimulated C-peptide decline over time in a subset of individuals (n = 258) with annual repeated measures for up to 6 years (p = 0.02). In the meta-GWAS of random C-peptide, another MHC region, SNP rs3135002 (Chr6:32668439, C>A, MAF 0.02-0.06), was associated with C-peptide (p = 3.49 × 10). Conditional analyses suggested that the three identified variants in the MHC region were independent of each other. rs9260151 and rs3135002 have been associated with type 1 diabetes, whereas rs559047 and rs61211515 have not been associated with a risk of developing type 1 diabetes.

CONCLUSIONS/INTERPRETATION: We identified a locus on chromosome 1 and multiple variants in the MHC region, at least some of which were distinct from type 1 diabetes risk loci, that were associated with C-peptide, suggesting partly non-overlapping mechanisms for the development and progression of type 1 diabetes. These associations need to be validated in independent populations. Further investigations could provide insights into mechanisms of beta cell loss and opportunities to preserve beta cell function.

摘要

目的/假设:本研究的目的是通过全基因组关联研究(meta-GWAS),确定与 1 型糖尿病β细胞功能相关的遗传变异,β细胞功能通过血清 C 肽水平来衡量。

方法

我们进行了一项 meta-GWAS,将 5 项研究的结果结合在一起,这些研究涉及了 3479 名欧洲参与者,对他们的 1 型糖尿病患者进行了横断面检测,检测指标包括受刺激的、空腹的或随机的 C 肽水平。在考虑了样本量和效应方向后,对各研究中的 p 值进行了合并。我们还分别对受刺激(n = 1303)、空腹(n = 2019)和随机(n = 1497)C 肽水平进行了单独的 meta-GWAS。

结果

在受刺激/空腹/随机 C 肽水平的 meta-GWAS 中,1 号染色体上的 SNP rs559047(Chr1:238753916,T > A,次要等位基因频率 [MAF] 0.24-0.26)与 C 肽相关(p = 4.13 × 10),达到了全基因组显著性阈值(p < 5 × 10)。在同一 meta-GWAS 中,MHC 区域的一个基因座(rs9260151)接近全基因组显著性阈值(Chr6:29911030,C > T,MAF 0.07-0.10,p = 8.43 × 10)。在受刺激 C 肽 meta-GWAS 中,MHC 区域的 rs61211515(Chr6:30100975,T/-,MAF 0.17-0.19)与受刺激 C 肽相关(β[SE] = -0.39 [0.07],p = 9.72 × 10)。rs61211515 还与在有年度重复测量的时间内,多达 6 年(n = 258)的个体中受刺激 C 肽的下降率相关(p = 0.02)。在随机 C 肽的 meta-GWAS 中,MHC 区域的另一个 SNP rs3135002(Chr6:32668439,C > A,MAF 0.02-0.06)与 C 肽相关(p = 3.49 × 10)。条件分析表明,MHC 区域中鉴定出的三个变异体彼此独立。rs9260151 和 rs3135002 与 1 型糖尿病有关,而 rs559047 和 rs61211515 与 1 型糖尿病的发病风险无关。

结论/解释:我们确定了 1 号染色体上的一个基因座和 MHC 区域的多个变异体,其中至少有一些与 1 型糖尿病风险基因座不同,这些变异体与 C 肽相关,这表明 1 型糖尿病的发生和进展存在部分非重叠的机制。这些关联需要在独立人群中进行验证。进一步的研究可以深入了解β细胞缺失的机制,并为保护β细胞功能提供机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4a7/5876265/575ca3edb864/125_2018_4555_Fig1_HTML.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