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全转录组关联研究鉴定多发性骨髓瘤的候选易感基因。

Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes.

机构信息

Division of Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey, SM2 5NG, UK.

Division of Molecular Pathology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey, SM2 5NG, UK.

出版信息

Hum Genomics. 2019 Aug 20;13(1):37. doi: 10.1186/s40246-019-0231-5.

Abstract

BACKGROUND

While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS).

RESULTS

GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80-491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus.

CONCLUSIONS

Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.

摘要

背景

虽然多发性骨髓瘤(MM)的全基因组关联研究(GWAS)已经确定了 23 个影响风险的区域变异,但这些关联的基因在很大程度上尚不清楚。为了确定这些区域的候选因果基因并寻找新的风险区域,我们进行了多组织转录组全基因组关联研究(TWAS)。

结果

GWAS 数据包括 7319 例 MM 病例和 234385 例对照,与 48 种组织(样本量为 80-491)的基因型组织表达项目(GTEx)数据整合,以预测基因表达。我们在 13 个独立的 MM 风险区域识别出了 108 个基因,这些基因都在已知的 MM GWAS 风险变异的 1Mb 内。其中,94 个基因,位于 8 个区域,以前没有被认为是该基因座的候选基因。

结论

我们的研究结果强调了利用来自多种组织的表达数据来识别与 GWAS 关联相关的候选基因的价值,这为 MM 的肿瘤发生提供了新的见解。在所鉴定的基因中,有许多具有 MM 生物学上的合理作用,特别是 APOBEC3C、APOBEC3H、APOBEC3D、APOBEC3F、APOBEC3G,或者以前与其他恶性肿瘤有关。本 TWAS 中鉴定的基因可以进一步探索其在 MM 生物学中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d220/6700979/86ee1477f1e7/40246_2019_231_Fig1_HTML.jpg

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