An integrated genome-wide analysis identifies HUR/ELAVL1 as a positive regulator of osteogenesis through enhancing the β-catenin signaling activity.
An integrated genome-wide analysis identifies HUR/ELAVL1 as a positive regulator of osteogenesis through enhancing the β-catenin signaling activity.
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DOI：
10.1016/j.gendis.2022.04.022
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发表时间：
2023-03
期刊：
影响因子：
6.8
通讯作者：
Qian, Airong
中科院分区：
文献类型：
--
作者：
Huai, Ying;Chen, Zhihao;Deng, Xiaoni;Wang, Xue;Mao, Wenjing;Miao, Zhiping;Li, Yu;Li, Hui;Lin, Xiao;Qian, Airong
骨质疏松症是一种普遍存在的多因素骨病，具有很强的遗传因素。导致骨质疏松症的特征（骨量、骨矿物质密度 (BMD)、骨大小、骨丢失和骨折）的遗传率范围为 50% 至 85%，这表明对遗传基础的全面了解可能有助于确定新的治疗靶点。 1 然而，遗传特征仍然不清楚，现有的药物靶点面临着各种挑战。大量研究表明，高通量测序数据分析对于识别人类疾病的新靶点是富有成效的。 2 因此，我们通过基因组注释多标记分析 (MAGMA) 和加权基因共表达网络分析 3 (WGCNA) 整合 GWAS 和转录组分析，以确定骨质疏松症的新网络模块和潜在治疗基因。作为说明，展示本研究过程的流程图如图S1所示。本研究使用了2015年骨质疏松症遗传因素（GEFOS）联盟的BMD GWAS数据集和转录组数据集（GSE35956）。这些数据集的质量控制结果显示在图S2中。基于基因的分析表明，1326 个全基因组相关基因通过单核苷酸多态性 (SNP) 注释，与 BMD 相关的 GWAS 具有名义相关性显着性。通过匹配 GWAS 和转录组数据生成 1258 个 BMD 全基因组相关基因的表达谱。然后，对这些基因表达谱进行 WGCNA 分析（图 S3）。在生成的基因模块中（表S1），绿黄色模块表现出与BMD最强的相关性（r Z À0. 93，P Z 1e-04），并被选择用于后续
Osteoporosis is a prevalent multifactorial bone disease with a strong genetic contribution. The heritability of traits that contribute to osteoporosis (bone mass, bone mineral density (BMD), bone size, bone loss and fractures) ranges from 50 to 85%, suggesting that a comprehensive understanding of the genetic basis may help identify new therapeutic targets. 1 However, the genetic characteristics remain obscure, and the existing drug targets are associated with various challenges. Numerous studies have demonstrated that high-throughput sequencing data analysis is fruitful for identifying novel targets of human diseases. 2 We therefore integrated GWAS and transcriptome analyses through Multimarker Analysis of GenoMic Annotation (MAGMA) and weighted gene co-expression network analysis 3 (WGCNA) to identify new network modules and potential therapeutic genes for osteoporosis. As an illustration, the flow chart presenting the process of the present study was shown in Figure S1.The BMD GWAS dataset Genetic Factors for Osteoporosis (GEFOS) Consortium in 2015 and a transcriptome dataset (GSE35956) were used in this study. The quality control results of these datasets are displayed in Figuer S2. Genebased analysis showed that 1326 genome-wide associated genes were annotated by single nucleotide polymorphisms (SNPs) with nominal relevance significance from BMD-associated GWAS. The expression profiles of 1258 BMD genomewide associated genes were generated by matching GWAS and transcriptome data. Then, these gene expression profiles were subjected to WGCNA analysis (Fig. S3). Among the generated gene modules (Table S1), the green-yellow module exhibited the strongest correlation with BMD (r Z À0. 93, P Z 1e-04) and was selected for subsequent
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WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
7.3
作者：
Schultz, Christopher W.;Preet, Ranjan;Brody, Jonathan R.
通讯作者：
Brody, Jonathan R.
影响因子：
30.8
作者：
Ishigaki K;Akiyama M;Kanai M;Takahashi A;Kawakami E;Sugishita H;Sakaue S;Matoba N;Low SK;Okada Y;Terao C;Amariuta T;Gazal S;Kochi Y;Horikoshi M;Suzuki K;Ito K;Koyama S;Ozaki K;Niida S;Sakata Y;Sakata Y;Kohno T;Shiraishi K;Momozawa Y;Hirata M;Matsuda K;Ikeda M;Iwata N;Ikegawa S;Kou I;Tanaka T;Nakagawa H;Suzuki A;Hirota T;Tamari M;Chayama K;Miki D;Mori M;Nagayama S;Daigo Y;Miki Y;Katagiri T;Ogawa O;Obara W;Ito H;Yoshida T;Imoto I;Takahashi T;Tanikawa C;Suzuki T;Sinozaki N;Minami S;Yamaguchi H;Asai S;Takahashi Y;Yamaji K;Takahashi K;Fujioka T;Takata R;Yanai H;Masumoto A;Koretsune Y;Kutsumi H;Higashiyama M;Murayama S;Minegishi N;Suzuki K;Tanno K;Shimizu A;Yamaji T;Iwasaki M;Sawada N;Uemura H;Tanaka K;Naito M;Sasaki M;Wakai K;Tsugane S;Yamamoto M;Yamamoto K;Murakami Y;Nakamura Y;Raychaudhuri S;Inazawa J;Yamauchi T;Kadowaki T;Kubo M;Kamatani Y
通讯作者：
Kamatani Y
影响因子：
16.6
作者：
Siang, Diana Teh Chee;Lim, Yen Ching;Xu, Dan
通讯作者：
Xu, Dan