格雷夫斯病
医学
疾病
Graves眼病
计算生物学
生物信息学
内科学
生物
作者
Chao Ke,Yuefeng Yu,Jiang Li,Yuetian Yu,Ying Sun,Yuying Wang,Bin Wang,Yingli Lu,Mengjun Tang,Ningjian Wang,Yi Chen
摘要
Background: The blood proteome is a major source of biomarkers and therapeutic targets. We aimed to identify the causal proteins and potential targets for Graves' disease (GD) and Graves' ophthalmopathy (GO) via systematic genetic analyses. Methods: Genome-wide association studies (GWASs) on the UK Biobank- Pharma Proteomics Project (UKB-PPP) collected 2923 Olink proteins from 54,219 participants. We conducted a proteome-wide Mendelian randomization (MR) study with cis-pQTLs to identify candidate proteins for GD and GO risk. Colocalization analysis and the Heidi test were used to examine whether the identified proteins and diseases shared the same variant. More proteins with potential causal associations were identified in Summary-data-based MR (SMR) analyses using trans-pQTLs. Then, downstream analyses were performed to detect protein interactions, gene function, cell type-specific expression and druggable information. Results: This study genetically predicted levels of 62 plasma proteins were associated with GD risk. Four proteins (CD40, TINAGL1, GMPR and CXCL10) were prioritized with the evidence of sharing the same variants with GD. Specifically, some proteins had potential associations with GD with trans-pQTLs mapping in CD40. The four prioritized protein-coding genes were mainly enriched in the regulation of apoptotic and death processes. In addition, GMPR was associated with both GO and GD in a consistent direction. BTN1A1 and FCRL1 were prioritized as the causal proteins for GO onset and were not associated with GD. Conclusion: By synthesizing proteomic and genetic data, we identified several protein biomarkers for GD, with one linked to both GD and GO and two other protein biomarkers specific to GO onset, which provides valuable insights into the etiology and potential therapeutic targets for the two diseases. Keywords: plasma proteomics, Graves' disease, Olink, Mendelian randomization
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