ArticleTherapeutic advances in endocrinology and metabolism2025
Multi-omics investigation of prospective therapeutic targets for type 1 diabetes.
Article in Therapeutic advances in endocrinology and metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Artificial intelligence-driven therapeutics for disease modification in type 1 diabetes: a digital public health and clinical translation framework.Frontiers in public health · 2026Review
- Causal Risk Factors for Type 1 Diabetes in Mendelian Randomization Studies: A Systematic Review and Meta-Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Review
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4 authors.
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Abstract
Background: In recent years, the incidence of type 1 diabetes has been rising steadily, positioning its prevention and treatment as a central focus of global public health initiatives. Previous Mendelian randomization (MR) studies have investigated the relationship between proteomics and type 1 diabetes. Consequently, this study aims to identify prospective therapeutic targets for type 1 diabetes through a comprehensive multi-omics analysis. Methods: This study primarily utilized the MR method, drawing on genetic data from several large-scale, publicly accessible genome-wide association studies. Within this framework, we applied two-sample MR to evaluate the relationship between five omics components and type 1 diabetes. Finally, we conducted various sensitivity analyses and bidirectional MR to ensure the robustness and reliability of our findings. Results: The inverse variance weighted method revealed that, following false discovery rate correction, 39 plasma proteins and 3 plasma protein ratios exhibited significant associations with type 1 diabetes. The genetically predicted risk of type 1 diabetes ranged from 0.05 for RBP2 to 394.51 for FMNL1. Furthermore, 4-chlorobenzoic acid levels demonstrated a potential association with type 1 diabetes. Conclusion: Our research identified numerous omics components associated with type 1 diabetes. These findings offer novel insights into the disease's etiology, diagnosis, and treatment.
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