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利用汇总统计数据识别与子痫前期相关的基因和特征。

Identifying genes and traits associated with pre-eclampsia using summary statistics.

作者信息

Zhu Wenyan, Wang Qi, Chen Min

机构信息

Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.

Department of gynecology and obstetrics, Nanjing Women and Children's Healthcare Hospital, Women's Hospital of Nanjing Medical University, Nanjing, China.

出版信息

PLoS One. 2025 May 30;20(5):e0323683. doi: 10.1371/journal.pone.0323683. eCollection 2025.

Abstract

The occurrence and development of pre-eclampsia (PE) is closely related to genetics. However, multi-omics analysis does not provide sufficient evidence to define significant genes. Therefore, we aimed to identify significant genes and pathways using summary statistics from genome-wide association studies (GWAS). Based on the summary statistics, we used linkage disequilibrium score regression (LDSC) to discover genetic correlation between PE and complex traits. Leveraging summary statistics of tissue-specific expression quantitative trait loci (eQTL), we used FUSION to define significant genes, Bayesian colocalization analysis to identify pleiotropic genes, and Multi-marker Analysis of GenoMic Annotation (MAGMA) to determine the associated pathways. Specifically, considering the potential relationship between PE and tissues, we included 11 tissues, such as kidney cortex. Our integrative analysis revealed that the observed heritability of PE was 0.0179 (standard error [SE] = 0.0021, P-value < 0.001). Also, based on the Bonferroni correction, we defined 238 traits genetically correlated to PE, such as the other cardiovascular diseases (r = -0.55) and furosemide (r = 0.79). Integrating eQTL summary statistics across eleven tissues, we identified 30 significant genes, such as EIF2S1 in the uterus (TWAS. Z = 4.44, TWAS. P = 8.95 × 10-6), and PAWRP2 in ovary (TWAS. Z = 4.34, TWAS. P = 1.45 × 10-5). Based on colocalization, we identified 26 pleiotropic genes. We found that three genes, including RPS26, SULT1A2, OBSCN-AS1, and SUOX, were simultaneously defined by FUSION and colocalization. Moreover, we found that the significant enrichment was in the FOXG1_TARGET_GENES pathway regulated by the transcription factor FOXG1 (PFDR = 0.049). The findings of post-GWAS analysis for PE indicate that there are 30 significant genes and 26 pleiotropic genes. Future studies are required to investigate the efficacy of targeting pleiotropic genes to reduce the risk of PE.

摘要

子痫前期(PE)的发生与发展与遗传学密切相关。然而,多组学分析并未提供足够的证据来确定重要基因。因此,我们旨在利用全基因组关联研究(GWAS)的汇总统计数据来识别重要基因和通路。基于汇总统计数据,我们使用连锁不平衡评分回归(LDSC)来发现PE与复杂性状之间的遗传相关性。利用组织特异性表达数量性状位点(eQTL)的汇总统计数据,我们使用FUSION来定义重要基因,使用贝叶斯共定位分析来识别多效性基因,并使用基因组注释多标记分析(MAGMA)来确定相关通路。具体而言,考虑到PE与组织之间的潜在关系,我们纳入了11种组织,如肾皮质。我们的综合分析显示,PE的观察到的遗传力为0.0179(标准误[SE]=0.0021,P值<0.001)。此外,基于Bonferroni校正,我们定义了238种与PE遗传相关的性状,如其他心血管疾病(r=-0.55)和呋塞米(r=0.79)。整合11种组织的eQTL汇总统计数据,我们鉴定出30个重要基因,如子宫中的EIF2S1(TWAS.Z=4.44,TWAS.P=8.95×10-6)和卵巢中的PAWRP2(TWAS.Z=4.34,TWAS.P=1.45×10-5)。基于共定位,我们鉴定出26个多效性基因。我们发现,包括RPS26、SULT1A2、OBSCN-AS1和SUOX在内的三个基因同时被FUSION和共定位所定义。此外,我们发现显著富集于由转录因子FOXG1调控的FOXG1_TARGET_GENES通路(PFDR=0.049)。PE的GWAS后分析结果表明存在30个重要基因和26个多效性基因。未来的研究需要调查靶向多效性基因以降低PE风险的效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebf9/12124566/1e07d6e95c31/pone.0323683.g001.jpg

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