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利用 GWAS 汇总统计数据鉴定七种自身免疫性疾病的共同遗传结构。

Identification of the shared genetic architecture underlying seven autoimmune diseases with GWAS summary statistics.

机构信息

Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.

出版信息

Front Immunol. 2024 Jan 8;14:1303675. doi: 10.3389/fimmu.2023.1303675. eCollection 2023.

DOI:10.3389/fimmu.2023.1303675
PMID:38259487
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10800382/
Abstract

BACKGROUND

The common clinical symptoms and immunopathological mechanisms have been observed among multiple autoimmune diseases (ADs), but the shared genetic etiology remains unclear.

METHODS

GWAS summary statistics of seven ADs were downloaded from Open Targets Genetics and Dryad. Linkage disequilibrium score regression (LDSC) was applied to estimate overall genetic correlations, bivariate causal mixture model (MiXeR) was used to qualify the polygenic overlap, and stratified-LDSC partitioned heritability to reveal tissue and cell type specific enrichments. Ultimately, we conducted a novel adaptive association test called MTaSPUsSet for identifying pleiotropic genes.

RESULTS

The high heritability of seven ADs ranged from 0.1228 to 0.5972, and strong genetic correlations among certain phenotypes varied between 0.185 and 0.721. There was substantial polygenic overlap, with the number of shared SNPs approximately 0.03K to 0.21K. The specificity of SNP heritability was enriched in the immune/hematopoietic related tissue and cells. Furthermore, we identified 32 pleiotropic genes associated with seven ADs, 23 genes were considered as novel genes. These genes were involved in several cell regulation pathways and immunologic signatures.

CONCLUSION

We comprehensively explored the shared genetic architecture across seven ADs. The findings progress the exploration of common molecular mechanisms and biological processes involved, and facilitate understanding of disease etiology.

摘要

背景

多种自身免疫性疾病(AD)存在共同的临床症状和免疫病理机制,但共享的遗传病因尚不清楚。

方法

从 Open Targets Genetics 和 Dryad 下载了七种 AD 的 GWAS 汇总统计数据。应用连锁不平衡评分回归(LDSC)来估计整体遗传相关性,使用双变量因果混合模型(MiXeR)来确定多基因重叠,分层-LDSC 划分遗传率以揭示组织和细胞类型特异性富集。最终,我们进行了一种新的自适应关联测试,称为 MTaSPUsSet,用于识别多效基因。

结果

七种 AD 的高遗传率范围从 0.1228 到 0.5972,某些表型之间的强遗传相关性在 0.185 到 0.721 之间。存在大量的多基因重叠,共享的 SNP 数量约为 0.03K 到 0.21K。SNP 遗传率的特异性在免疫/造血相关组织和细胞中得到了富集。此外,我们确定了 32 个与七种 AD 相关的多效基因,其中 23 个被认为是新基因。这些基因参与了几个细胞调节途径和免疫特征。

结论

我们全面探讨了七种 AD 之间共享的遗传结构。这些发现促进了对共同涉及的分子机制和生物学过程的探索,并有助于理解疾病的病因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/bc08c2628c9e/fimmu-14-1303675-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/899722d48451/fimmu-14-1303675-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/13228945fd8e/fimmu-14-1303675-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/483a05860175/fimmu-14-1303675-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/36f9ebe63ce7/fimmu-14-1303675-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/bc08c2628c9e/fimmu-14-1303675-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/899722d48451/fimmu-14-1303675-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/13228945fd8e/fimmu-14-1303675-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/483a05860175/fimmu-14-1303675-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/36f9ebe63ce7/fimmu-14-1303675-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d0/10800382/bc08c2628c9e/fimmu-14-1303675-g005.jpg

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本文引用的文献

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Multi-trait and cross-population genome-wide association studies across autoimmune and allergic diseases identify shared and distinct genetic component.
跨自身免疫性疾病和过敏性疾病的多性状及跨人群全基因组关联研究确定了共同和独特的遗传成分。
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