Connolly Ben, McCreight Laura, Slieker Roderick C, Bedair Khaled F, Donnelly Louise, de Klerk Juliette A, Beulens Joline W J, Elders Petra J M, Bergström Göran, Hong Mun-Gwan, Koivula Robert W, Franks Paul W, Schwenk Jochen M, Gummesson Anders, Pearson Ewan R, 't Hart Leen M
Division of Population Health & Genomics, School of Medicine, University of Dundee, UK.
Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
EBioMedicine. 2025 Jul 19;118:105859. doi: 10.1016/j.ebiom.2025.105859.
Metformin is one of the most used drugs worldwide. Given the increasing use of proteomics in trials, bioresources, and clinics, it is crucial to understand the influence of metformin on the levels of the circulating proteome.
We analysed a combined longitudinal proteomics dataset from the IMPOCT, RAMP and S3WP-T2D clinical trials in 98 participants before and after metformin exposure. This discovery analysis contained 372 proteins measured by proximity extension assays (Olink). We followed up experiment-wise statistically significant findings in two cross-sectional cohorts of people with type 2 diabetes comparing metformin treated and untreated individuals: IMI-DIRECT (784 participants, 372 proteins, Olink) and IMI-RHAPSODY (1175 participants, 1195 proteins, SomaLogic).
Overall, 23 protein analytes were robustly associated with exposure to metformin in the discovery and replication. This includes 11 protein-metformin associations that replicated in both replication sets and platforms (REG4, GDF15, REG1A, t-PA, TFF3, CDH5, CNTN1, OMD, NOTCH3, THBS4 and CD93), with the remaining 12 protein-metformin associations replicated using the Olink platform (EPCAM, SPINK1, SAA-4, COMP, ITGB2, ADGRG2, FAM3C, MERTK, COL1A1, HAOX1, VCAN, TIMD4) but not measured on the SomaLogic platform. Gene-set enrichment analysis revealed that the metformin exposure was associated with intestinal associated proteins.
These data highlight the need to account for exposure to metformin, and potentially other drugs, in proteomic studies and where protein biomarkers are used for clinical care.
Innovative Medicines Initiative Joint Undertaking 2, under grant agreement no. 115881 (RHAPSODY) and the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution as well as the Swiss State Secretariat for Education Research' and Innovation (SERI), under contract no. 16.0097 (RHAPSODY).
二甲双胍是全球使用最广泛的药物之一。鉴于蛋白质组学在试验、生物资源和临床中的应用日益增加，了解二甲双胍对循环蛋白质组水平的影响至关重要。
我们分析了来自IMPOCT、RAMP和S3WP-T2D临床试验的98名参与者在二甲双胍暴露前后的综合纵向蛋白质组学数据集。这项发现分析包含通过邻位延伸分析（Olink）测量的372种蛋白质。我们在两个2型糖尿病横断面队列中对实验性统计学显著发现进行了跟进，比较了接受二甲双胍治疗和未接受治疗的个体：IMI-DIRECT（784名参与者，372种蛋白质，Olink）和IMI-RHAPSODY（1175名参与者，1195种蛋白质，SomaLogic）。
总体而言，在发现和重复研究中，有23种蛋白质分析物与二甲双胍暴露密切相关。这包括在两个重复数据集和平台中均重复出现的11种蛋白质-二甲双胍关联（REG4、GDF-15、REG1A、组织型纤溶酶原激活剂、三叶因子3、CDH5、接触蛋白1、骨桥蛋白、Notch3、血小板反应蛋白4和CD93），其余12种蛋白质-二甲双胍关联在Olink平台上重复出现（EPCAM、丝氨酸蛋白酶抑制剂Kazal型1、血清淀粉样蛋白A4、软骨寡聚基质蛋白、整合素β2、黏附G蛋白偶联受体G2、家族性肿瘤标志物3C、酪氨酸激酶受体Mer、Ⅰ型胶原α1链、羟基酸氧化酶1、多功能蛋白聚糖、T细胞免疫球蛋白和粘蛋白结构域蛋白4），但未在SomaLogic平台上测量。基因集富集分析表明，二甲双胍暴露与肠道相关蛋白有关。
这些数据凸显了在蛋白质组学研究以及将蛋白质生物标志物用于临床护理时，需要考虑二甲双胍以及可能其他药物的暴露情况。
创新药物倡议联合事业2，资助协议编号115881（RHAPSODY），以及创新药物倡议联合事业，资助协议编号115317（DIRECT），其资源由欧盟第七框架计划（FP7/2007 - 2013）的财政贡献、EFPIA公司的实物贡献以及瑞士教育研究与创新国务秘书处（SERI），合同编号16.0097（RHAPSODY）组成。
