Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus
Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus
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DOI：
10.1172/jci.insight.140380
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发表时间：
2020-08-06
期刊：
影响因子：
8
通讯作者：
Lipsky, Peter E.
中科院分区：
文献类型：
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作者：
Catalina, Michelle D.;Bachali, Prathyusha;Lipsky, Peter E.
基因表达特征可以对异质性疾病（如系统性红斑狼疮（SLE））患者进行分层，但对祖先背景对这种异质性的贡献还没有很好的理解。我们假设，血统将显着影响基因表达的签名和测量34个基因模块在1566 SLE患者的非洲血统（AA），欧洲血统（EA），或美洲原住民血统（NAA）。健康受试者的祖先特异性基因表达提供了转录组学背景，在此基础上建立了SLE患者的特征。尽管标准治疗影响了每个基因特征并显著增加了骨髓细胞特征，但逻辑回归分析确定祖先背景显著改变了34个基因特征中的23个。此外，与基因表达变化的最强关联被发现与自身抗体，这也有祖先的病因学：AA倾向于具有RNP和dsDNA自身抗体，而EA倾向于仅具有抗dsDNA。使用机器学习方法来确定基因签名特征以区分AA SLE，并且最受AA SLE患者中扰动的B细胞轴的基因特征的影响。
Gene expression signatures can stratify patients with heterogeneous diseases, such as systemic lupus erythematosus (SLE), yet understanding the contributions of ancestral background to this heterogeneity is not well understood. We hypothesized that ancestry would significantly influence gene expression signatures and measured 34 gene modules in 1566 SLE patients of African ancestry (AA), European ancestry (EA), or Native American ancestry (NAA). Healthy subject ancestry-specific gene expression provided the transcriptomic background upon which the SLE patient signatures were built. Although standard therapy affected every gene signature and significantly increased myeloid cell signatures, logistic regression analysis determined that ancestral background significantly changed 23 of 34 gene signatures. Additionally, the strongest association to gene expression changes was found with autoantibodies, and this also had etiology in ancestry: the AA predisposition to have both RNP and dsDNA autoantibodies compared with EA predisposition to have only anti-dsDNA. A machine learning approach was used to determine a gene signature characteristic to distinguish AA SLE and was most influenced by genes characteristic of the perturbed B cell axis in AA SLE patients.