系统性硬化症的基因水平关联分析：非裔美国人和白人人群的比较。
Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations.
作者信息
Gorlova Olga Y, Li Yafang, Gorlov Ivan, Ying Jun, Chen Wei V, Assassi Shervin, Reveille John D, Arnett Frank C, Zhou Xiaodong, Bossini-Castillo Lara, Lopez-Isac Elena, Acosta-Herrera Marialbert, Gregersen Peter K, Lee Annette T, Steen Virginia D, Fessler Barri J, Khanna Dinesh, Schiopu Elena, Silver Richard M, Molitor Jerry A, Furst Daniel E, Kafaja Suzanne, Simms Robert W, Lafyatis Robert A, Carreira Patricia, Simeon Carmen Pilar, Castellvi Ivan, Beltran Emma, Ortego Norberto, Amos Christopher I, Martin Javier, Mayes Maureen D
机构信息
Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
Department of Internal Medicine, Division of Rheumatology, University of Texas McGovern Medical School, Houston, TX, United States of America.
出版信息
PLoS One. 2018 Jan 2;13(1):e0189498. doi: 10.1371/journal.pone.0189498. eCollection 2018.
Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.
此前尚未有关于系统性硬化症（SSc，硬皮病）的免疫芯片基因水平分析或全基因组关联研究（GWAS）数据的报道。本研究的目的是利用免疫芯片和GWAS基因分型研究的数据，在基因水平上分析SSc的遗传易感性位点，并确定在非裔美国人和白人人群中检测到的关联是否具有共性。白人样本包括1833例病例和3466例对照（956例病例和2741例对照来自美国，877例病例和725例对照来自西班牙），非裔美国人样本包括291例病例和260例对照。在白人和非裔美国人中，我们使用基于通用基因的关联研究（VEGAS）软件进行了基因水平分析，该分析整合了可能含有多个对疾病风险影响较弱的单核苷酸多态性（SNP）的基因中的关联统计数据。SNP水平分析使用PLINK v.1.07进行。在白人患者的基因水平分析中，我们鉴定出4个显著相关的新候选基因（STAT1、FCGR2C、NIPSNAP3B和SCT）以及4个提示性相关的基因（SERBP1、PINX1、TMEM175和EXOC2）与SSc相关。作为探索性分析，我们将白人的结果与非裔美国人的结果进行了比较。在白人中先前确定的易感基因中，在免疫芯片数据的基因水平分析中，只有TNFAIP3在非裔美国人中在名义水平上显著（p = 6.13×10-3）。在基于免疫芯片数据在白人中确定的顶级提示性新基因中，FCGR2C和PINX1在非裔美国人中仅在名义水平上显著（分别为p = 0.016和p = 0.028），而在非裔美国人基因水平分析中确定的顶级新基因中，UNC5C（p = 5.57×10-4）和CLEC16A（p = 0.0463）在白人中也在名义水平上显著。我们还展示了白人中SSc临床和自身抗体表型的基因水平分析。我们的发现需要通过独立研究进行验证，特别是由于非裔美国人的样本量有限。
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