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Gene-based GWAS analysis for consecutive studies of GEFOS.
Osteoporosis International ( IF 4 ) Pub Date : 2018-10-12 , DOI: 10.1007/s00198-018-4654-y
W Zhu 1, 2 , C Xu 2 , J-G Zhang 2 , H He 2 , K-H Wu 2 , L Zhang 2 , Y Zeng 2, 3 , Y Zhou 2 , K-J Su 2 , H-W Deng 1, 2
Affiliation  

By integrating the multilevel biological evidence and bioinformatics analyses, the present study represents a systemic endeavor to identify BMD-associated genes and their roles in skeletal metabolism. INTRODUCTION Single-nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) have already identified about 100 loci associated with bone mineral density (BMD), but these loci only explain a small proportion of heritability to osteoporosis risk. In the present study, we performed a gene-based analysis of the largest GWASs in the bone field to identify additional BMD-associated genes. METHODS BMD-associated genes were identified by combining the summary statistic P values of SNPs across individual genes in the two consecutive meta-analyses of GWASs from the Genetic Factors for Osteoporosis (GEFOS) studies. The potential functionality of these genes to bone was partially assessed by differential gene expression analysis. Additionally, the consistency of the identification of potential bone mineral density (BMD)-associated variants were evaluated by estimating the correlation of the P values of the same single-nucleotide polymorphisms (SNPs)/genes between the two consecutive Genetic Factors for Osteoporosis Studies (GEFOS) with largely overlapping samples. RESULTS Compared to the SNP-based analysis, the gene-based strategy identified additional BMD-associated genes with genome-wide significance and increased their mutual replication between the two GEFOS datasets. Among these BMD-associated genes, three novel genes (UBTF, AAAS, and C11orf58) were partially validated at the gene expression level. The correlation analysis presented a moderately high between-study consistency of potential BMD-associated variants. CONCLUSIONS Gene-based analysis as a supplementary strategy to SNP-based genome-wide association studies, when applied here, is shown that it helped identify some novel BMD-associated genes. In addition to its empirically increased statistical power, gene-based analysis also provides a higher testing stability for identification of BMD genes.

中文翻译:

用于 GEFOS 连续研究的基于基因的 GWAS 分析。

通过整合多层次的生物学证据和生物信息学分析,本研究代表了一项系统性的努力,以识别 BMD 相关基因及其在骨骼代谢中的作用。引言 基于单核苷酸多态性 (SNP) 的全基因组关联研究 (GWAS) 已经确定了大约 100 个与骨矿物质密度 (BMD) 相关的基因座,但这些基因座仅能解释骨质疏松症风险的一小部分遗传性。在本研究中,我们对骨领域中最大的 GWAS 进行了基于基因的分析,以识别其他 BMD 相关基因。方法 在骨质疏松症遗传因素 (GEFOS) 研究的 GWAS 的两个连续荟萃分析中,通过结合单个基因的 SNP 的汇总统计 P 值来鉴定 BMD 相关基因。这些基因对骨骼的潜在功能部分通过差异基因表达分析进行评估。此外,通过估计骨质疏松症研究的两个连续遗传因素之间相同单核苷酸多态性 (SNP)/基因的 P 值的相关性,评估了潜在骨矿物质密度 (BMD) 相关变异的鉴定的一致性。 GEFOS) 与大量重叠的样本。结果 与基于 SNP 的分析相比,基于基因的策略确定了其他具有全基因组意义的 BMD 相关基因,并增加了它们在两个 GEFOS 数据集之间的相互复制。在这些 BMD 相关基因中,三个新基因(UBTF、AAAS 和 C11orf58)在基因表达水平上得到了部分验证。相关性分析显示潜在 BMD 相关变异的研究间一致性中等。结论 作为基于 SNP 的全基因组关联研究的补充策略的基于基因的分析,当在这里应用时,表明它有助于识别一些新的 BMD 相关基因。除了凭经验增加统计能力外,基于基因的分析还为 BMD 基因的识别提供了更高的测试稳定性。
更新日期:2018-10-10
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