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Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities
medRxiv - Genetic and Genomic Medicine Pub Date : 2024-03-19 , DOI: 10.1101/2024.03.15.24304200
Douglas P. Loesch , Manik Garg , Dorota Matelska , Dimitrios Vitsios , Xiao Jiang , Scott C. Ritchie , Benjamin B. Sun , Heiko Runz , Christopher D. Whelan , Rury R. Holman , Robert J. Mentz , Filipe A. Moura , Stephen D. Wiviott , Marc S. Sabatine , Miriam S. Udler , Ingrid A. Gause-Nilsson , Slavé Petrovski , Jan Oscarsson , Abhishek Nag , Dirk S. Paul , Michael Inouye

Introduction: Type 2 diabetes (T2D) is a heterogeneous disorder for which disease-causing pathways are incompletely understood. Here, we mapped genetic risk for T2D and its comorbidities to proteins, mechanistic pathways and clinical outcomes using proteogenomic data from a population-scale biobank and two randomized controlled trials. Methods: We tested polygenic scores (PGS) for T2D and its cardiometabolic comorbidities, plus five partitioned T2D PGS (beta cell, lipodystrophy, liver lipid, obesity, and liver lipid), for association with 2,922 circulating proteins in 54,306 multi-ancestry participants (of which 42,452 were unrelated and without prevalent cardiometabolic disease) from the UK Biobank (UKB). Then, we tested the PGS-associated proteins for association with incident cardiometabolic complications in two cardiovascular outcome trials among T2D patients with proteogenomic data: EXSCEL (N=2,823) and DECLARE-TIMI 58 (N=915). We assessed causality using two-sample Mendelian randomization and mediation. Results: We identified 839 unique proteins significantly associated with any T2D PGS and 1,005 proteins that were associated with at least one cardiometabolic PGS. Some PGS-associated proteins such as TFF3, EFEMP1, and MMP12 were in turn associated with renal and cardiovascular trial outcomes. PGS association patterns revealed shared pathways, e.g., complement cascade, cholesterol metabolism, IGF signaling. The proteins underlying these pathways, such as LPA, C1S, and IGFBP2, were consistently associated with clinical trial outcomes or identified via causal inference. Conclusions: This proteogenomic study revealed proteins and mechanistic pathways underlying T2D and related comorbidities, advancing our understanding of T2D pathobiology and identifying putative biomarkers. All our results are available in an online data portal (https://public.cgr.astrazeneca.com/t2d-pgs/v1/).

中文翻译:

鉴定 2 型糖尿病及相关合并症多基因风险背后的血浆蛋白质组标记物

简介:2 型糖尿病 (T2D) 是一种异质性疾病,其致病途径尚不完全清楚。在这里,我们利用来自人口规模生物库和两项随机对照试验的蛋白质基因组数据,将 T2D 及其合并症的遗传风险与蛋白质、机制途径和临床结果进行了映射。方法:我们测试了 T2D 及其心脏代谢合并症的多基因评分 (PGS),加上五种划分的 T2D PGS(β 细胞、脂肪营养不良、肝脂质、肥胖和肝脂质),以与 54,306 名多血统参与者中的 2,922 种循环蛋白相关。其中 42,452 例与英国生物银行 (UKB) 无关且没有流行的心脏代谢疾病。然后,我们在两项针对 T2D 患者的心血管结果试验中使用蛋白质基因组数据测试了 PGS 相关蛋白与事件心脏代谢并发症的关联:EXSCEL (N=2,823) 和 DECLARE-TIMI 58 (N=915)。我们使用两个样本孟德尔随机化和中介评估因果关系。结果:我们鉴定出 839 种独特的蛋白质与任何 T2D PGS 显着相关,以及 1,005 种蛋白质与至少一种心脏代谢 PGS 相关。一些 PGS 相关蛋白(例如 TFF3、EFEMP1 和 MMP12)反过来又与肾脏和心血管试验结果相关。PGS 关联模式揭示了共同的途径,例如补体级联、胆固醇代谢、IGF 信号传导。这些通路背后的蛋白质,例如 LPA、C1S 和 IGFBP2,与临床试验结果一致相关或通过因果推断来识别。结论:这项蛋白质组学研究揭示了 T2D 和相关合并症的蛋白质和机制途径,增进了我们对 T2D 病理学的理解并确定了假定的生物标志物。我们的所有结果均可在在线数据门户网站 (https://public.cgr.astrazeneca.com/t2d-pgs/v1/) 中获取。
更新日期:2024-03-19
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