与电子健康记录数据相结合的蛋白质基因组分析揭示了美国黑人的疾病相关变异。

Usman A Tahir,Jacob L Barber,Daniel E Cruz,Meltem Ece Kars,Shuliang Deng,Bjoernar Tuftin,Madeline G Gillman,Mark D Benson,Jeremy M Robbins,Zsu-Zsu Chen,Prashant Rao,Daniel H Katz,Laurie Farrell,Tamar Sofer,Michael E Hall,Lynette Ekunwe,Russell P Tracy,Peter Durda,Kent D Taylor,Yongmei Liu,W Craig Johnson,Xiuqing Guo,Yii-Der Ida Chen,Ani W Manichaikul,Deepti Jain,Thomas J Wang,Alex P Reiner,Pradeep Natarajan,Yuval Itan,Stephen S Rich,Jerome I Rotter,James G Wilson,Laura M Raffield,Robert E Gerszten
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引用次数: 0

摘要

背景大多数血浆蛋白质组学的全基因组关联研究(GWAS)都集中在欧洲血统的白人个体上,从而限制了对其他血统富集蛋白质定量位点(pQTL)的生物学洞察力。方法我们利用基于抗体的 Olink 平台对杰克逊心脏病研究(JHS)中的 1,054 名黑人成年人的约 3,000 种血浆蛋白质进行了发现性 GWAS 测量,并在动脉粥样硬化多种族研究(MESA)中验证了我们的发现。通过精细作图和掺杂关联分析,我们进一步探索了已鉴定 pQTL 的遗传结构。最后,利用我们的 pQTL 发现,我们在 All of Us 和 BioMe 两个大型多种族电子健康记录(EHR)系统中进行了表型组广泛关联研究(PheWAS)。精细图谱和混杂分析表明,不同人群的血浆蛋白质组存在等位基因异质性。我们发现了富含非洲血统的变异体,其中许多与缺乏精确生物标志物的疾病有关,包括分别与肉样瘤病和非霍奇金淋巴瘤有关的酪蛋白酶 L (CTSL) 和 Siglec-9 的顺式-pQTLs。我们在临床诊断和实验室测量中发现了一致的关联,阐明了疾病路径,包括与循环 CD58、白细胞计数和多发性硬化症相关的顺式-pQTL。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proteogenomic analysis integrated with electronic health records data reveals disease-associated variants in Black Americans.
BACKGROUND Most genome wide association studies (GWAS) of plasma proteomics have focused on White individuals of European ancestry, limiting biological insight from other ancestry enriched protein quantitative loci (pQTL). METHODS We conducted a discovery GWAS of ~3,000 plasma proteins measured by the antibody based Olink platform in 1,054 Black adults from the Jackson Heart Study (JHS), and validated our findings in the Multi-Ethnic Study of Atherosclerosis (MESA). The genetic architecture of identified pQTLs were further explored through fine mapping and admixture association analysis. Finally, using our pQTL findings, we performed a phenome wide association study (PheWAS) across two large multi-ethnic electronic health record (EHR) systems in All of Us and BioMe. RESULTS We identified 1002 pQTLs for 925 proteins. Fine mapping and admixture analyses suggested allelic heterogeneity of the plasma proteome across diverse populations. We identified associations for variants enriched in African ancestry, many in diseases that lack precise biomarkers, including cis-pQTLs for Cathepsin L (CTSL) and Siglec-9 that were linked with sarcoidosis and non-Hodgkin's lymphoma, respectively. We found concordant associations across clinical diagnoses and laboratory measurements, elucidating disease pathways, including a cis-pQTL associated with circulating CD58, white blood cell count, and multiple sclerosis. CONCLUSIONS Our findings emphasize the value of leveraging diverse populations to enhance biological insights from proteomics GWAS, and we have made this resource readily available as an interactive web portal.
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