PO.BCS01.09 · 生物信息与计算
整合分析识别与肾细胞癌及其风险因素相关的潜在蛋白质组中介物
Integrative analysis identifies potential proteomic intermediates associated with renal cell carcinoma and its risk factors
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：肾细胞癌（RCC）是肾癌的主要形式，受多种风险因素（RF）影响，包括肥胖、高血压和吸烟。然而，将这些RF与RCC联系起来的分子机制仍不清楚。
方法：我们采用两阶段孟德尔随机化（TSMR）方法，研究血浆蛋白（PP）作为RF对RCC影响标志物的潜在中介物。在第一阶段，我们利用来自UK Biobank Pharma Proteomics Project（N=34,557）的PP汇总水平蛋白质遗传学数据，识别与所评估的19种RF（如人体测量特征、血压、吸烟行为、血细胞计数和肾功能）各自相关的PP。在第二阶段，我们使用迄今最大规模的RCC GWAS（N=864,690；病例数=29,020），评估这些RF相关PP对RCC的影响。
结果：在2,940个PP中，2,339个与19种RF中的至少一种显著相关（P<1.7E-05）。其中，33个对RCC显示出显著影响（FDR<5%），有28个映射在RCC GWAS位点之外。使用多变量MR，我们估计了相关PP的中介效应，发现CDA和PILRB等蛋白介导了BMI对RCC影响的多达17.41%，APOL1介导了白细胞影响的2.76%。来自cis-MR、共定位和TCGA差异表达等多项计算机模拟分析的一致证据进一步将TYMP、UMOD和USP28优先列为RF对RCC影响的关键蛋白中介物。TYMP和USP28与RCC风险呈负相关，显示出免疫相关和肿瘤抑制作用，而UMOD呈正相关，可能将肾功能障碍与癌变联系起来。功能注释揭示了这些蛋白附近的增强子活性和转录因子（HIF）结合。
结论：我们的方法和结果识别出可能将流行病学风险因素与RCC联系起来的分子中介物，并突出了可用于实验室研究的可操作候选物。优先列出的与RCC及至少一种RF相关的PP，以及来自多项计算机模拟分析的结果 血浆蛋白 总体MR cis-MR 共定位 差异基因表达（TCGA） 最近GWAS信号* 名称 区域 Beta P值 Beta P值 FoldChange P值(FDR) RSID P值 TYMP 22q13.33 -0.17 2.6E-06 -0.29 4.9E-08 9.95E-01 6.81 1.7E-14 rs131813 5.4E-09 UMOD 16p12.3 0.05 1.4E-06 0.06 1.3E-08 8.93E-01 0.00 5.1E-15 rs7203642 8.2E-06 USP28 11q23.2 -0.31 4.5E-05 -0.46 4.1E-05 9.98E-01 0.85 5.0E-05 rs4288784 1.2E-05 * 蛋白转录起始位点+/-1Mb范围内最强的GWAS关联
查看英文原文 English abstract
Background: Renal cell carcinoma (RCC), the predominant form of kidney cancer, is influenced by several risk factors (RFs) including obesity, hypertension, and smoking. However, the molecular mechanisms linking these RFs to RCC remain unclear.
Methods: We investigated plasma proteins (PP) as potential intermediates of markers of the effects of RFs on RCC using two-stage Mendelian randomization (TSMR) approach. In stage 1, we identified PPs associated with each of the 19 RFs evaluated (e.g., anthropometric traits, blood pressure, smoking behavior, blood cell counts, and kidney function), leveraging summary-level proteogenetic data on PPs from the UK Biobank Pharma Proteomics Project (N=34,557). In stage 2, we evaluated the effects of these RF-associated PPs on RCC, using the largest-to-date RCC GWAS (N = 864,690; cases=29,020).
Results: Among 2,940 PPs, 2,339 were significantly associated (P<1.7E-05) with at least one of the 19 RFs. Of these, 33 showed a significant effect on RCC (FDR<5%) with 28 mapping outside RCC GWAS loci. Using multivariable MR, we estimated mediation effects of associated PPs, finding that proteins such as CDA and PILRB mediated up to 17.41% of BMI's effect on RCC, and APOL1 mediated 2.76% of white blood cell's effect. Convergent evidence from multiple in silico analyses with cis-MR, colocalization, and TCGA differential expression further prioritized TYMP, UMOD and USP28 as key protein intermediaries of the RF effects on RCC. TYMP and USP28, inversely associated with RCC risk, showed immune-related and tumor-suppressive effects, while UMOD was positively associated, potentially linking renal dysfunction to carcinogenesis. Functional annotation revealed enhancer activity and transcription factor (HIF) binding near these proteins.
Conclusion: Our approach and results identify molecular intermediates that may link epidemiologic risk factors to RCC and highlight actionable candidates for laboratory investigation. Prioritized PPs associated to RCC and at least one RF, with results from multiple in-silico analyses Plasma-Protein Overall-MR cis-MR Colocalization Differential-Gene-Expression(TCGA) Nearest-GWAS-Signal* Name Region Beta P-value Beta P-value FoldChange P-value(FDR) RSID P-value TYMP 22q13.33 -0.17 2.6E-06 -0.29 4.9E-08 9.95E-01 6.81 1.7E-14 rs131813 5.4E-09 UMOD 16p12.3 0.05 1.4E-06 0.06 1.3E-08 8.93E-01 0.00 5.1E-15 rs7203642 8.2E-06 USP28 11q23.2 -0.31 4.5E-05 -0.46 4.1E-05 9.98E-01 0.85 5.0E-05 rs4288784 1.2E-05 * Strongest GWAS association within +/- 1Mb of the transcription start site of the protein
利益披露 Disclosure
I. Sajal, None..
A. J. Song, None.