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特发性肺纤维化相关基因与其他疾病共享位点的综合分析。

Integrative analyses for the identification of idiopathic pulmonary fibrosis-associated genes and shared loci with other diseases.

机构信息

Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.

Section of Pulmonary, Critical Care and Sleep Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.

出版信息

Thorax. 2023 Aug;78(8):792-798. doi: 10.1136/thorax-2021-217703. Epub 2022 Oct 10.

Abstract

BACKGROUND

Although genome-wide association studies (GWAS) have identified many genomic regions associated with idiopathic pulmonary fibrosis (IPF), the causal genes and functions remain largely unknown. Many single-cell expression data have become available for IPF, and there is increasing evidence suggesting a shared genetic basis between IPF and other diseases.

METHODS

We conducted integrative analyses to improve the power of GWAS. First, we calculated global and local genetic correlations to identify IPF genetically associated traits and local regions. Then, we prioritised candidate genes contributing to local genetic correlation. Second, we performed transcriptome-wide association analysis (TWAS) of 44 tissues to identify candidate genes whose genetically predicted expression level is associated with IPF. To replicate our findings and investigate the regulatory role of the transcription factors (TF) in identified candidate genes, we first conducted the heritability enrichment analysis in TF binding sites. Then, we examined the enrichment of the TF target genes in cell-type-specific differentially expressed genes (DEGs) identified from single-cell expression data of IPF and healthy lung samples.

FINDINGS

We identified 12 candidate genes across 13 genomic regions using local genetic correlation, including the locus (=0.00041), which contained variants with protective effects on lung cancer but increasing IPF risk. We identified another 13 novel genes using TWAS. Two TFs, and , showed significant enrichment in both partitioned heritability and cell-type-specific DEGs.

INTERPRETATION

Our integrative analysis identified new genes for IPF susceptibility and expanded the understanding of the complex genetic architecture and disease mechanism of IPF.

摘要

背景

尽管全基因组关联研究(GWAS)已经确定了许多与特发性肺纤维化(IPF)相关的基因组区域,但因果基因和功能仍在很大程度上未知。许多单细胞表达数据可用于 IPF,越来越多的证据表明 IPF 与其他疾病之间存在共同的遗传基础。

方法

我们进行了综合分析以提高 GWAS 的功效。首先,我们计算了全局和局部遗传相关性,以确定与 IPF 具有遗传相关性的性状和局部区域。然后,我们优先考虑对局部遗传相关性有贡献的候选基因。其次,我们对 44 种组织进行了全转录组关联分析(TWAS),以鉴定候选基因,其遗传预测表达水平与 IPF 相关。为了复制我们的发现并研究转录因子(TF)在鉴定的候选基因中的调节作用,我们首先在 TF 结合位点中进行了遗传力富集分析。然后,我们检查了在 IPF 和健康肺样本的单细胞表达数据中鉴定的细胞类型特异性差异表达基因(DEG)中 TF 靶基因的富集情况。

结果

我们使用局部遗传相关性鉴定了 13 个基因组区域中的 12 个候选基因,包括 基因座(=0.00041),其中包含对肺癌有保护作用但增加 IPF 风险的变异。我们使用 TWAS 鉴定了另外 13 个新基因。两个 TF, 和 ,在分区遗传力和细胞类型特异性 DEG 中均表现出显著富集。

结论

我们的综合分析确定了新的 IPF 易感性基因,并扩展了对 IPF 复杂遗传结构和疾病机制的理解。

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Comprehensive Integration of Single-Cell Data.单细胞数据的综合整合。
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