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September 5, 2025Open Access

Integrative proteomic analysis provides novel therapeutic insights for etiological subtypes of diabetes

JWJiahe WeiSir Run Run Shaw Hospital HWHanzhang WuSir Run Run Shaw Hospital NWNingjian WangShanghai University

Key Points

Significant associations between circulating proteins and diabetes subtypes were found, indicating new drug targets.
Analysis identified proteins linked to different subtypes of diabetes, including severe autoimmune and insulin-deficient types.
Utilization of Mendelian randomisation and pathway analysis provided insights into protein functions and druggability.
Findings support the need for more personalized treatment strategies for type 2 diabetes based on its heterogeneity.

Abstract

Abstract Aims Type 2 diabetes (T2D) is a highly heterogeneous disease characterised by subtypes with variations in aetiology, disease progression, and risk of complications. However, potential drug targets for these subtypes have not been explored. This study aims to investigate potential drug targets by integrating proteomics. Materials and methods Summary‐level data of circulating proteins were extracted from the UK Biobank and the deCODE Health Study. Genetic associations with five diabetes subtypes were obtained from Swedish All New Diabetics in Scania and Malmö Diet and Cancer cohort, including severe autoimmune diabetes (SAID), severe insulin‐deficient diabetes (SIDD), severe insulin‐resistant diabetes (SIRD), mild obesity‐related diabetes (MOD), and mild age‐related diabetes (MARD). The associations between circulating proteins and diabetes subtypes were assessed through Mendelian randomisation, followed by multiple sensitivity and colocalization analyses. Additionally, tissue‐specific, pathway and functional enrichment analysis, assessment of protein druggability, and the protein–protein interaction (PPI) networks were used to further explore biological mechanisms and therapeutic potential. Results Genetically predicted levels of 2, 2, 9, 3, and 5 circulating proteins were associated with SIRD, SIDD, MARD, MOD, and SAID, respectively. Colocalization analyses further revealed links between GRN with MARD/SIRD, LILRB5 with SIDD/MARD, CR1 with MARD, TNFSF12 with MOD, and DAPK2 with SAID. Enrichment analysis suggested that these proteins were mainly enriched in blood and adipose tissues and involved in immune and inflammatory related pathways. PPI analysis revealed GRN, TNFSF12, and DAPK2 are associated with known T2D targets. Conclusions Our study identified several potential drug targets for different subtypes of diabetes using an integrated genetic approach, yielding new insights for precision medicine of diabetes.

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