Multi-omics investigation of prospective therapeutic targets for type 1 diabetes
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 diab...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-05-01
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| Series: | Therapeutic Advances in Endocrinology and Metabolism |
| Online Access: | https://doi.org/10.1177/20420188251337988 |
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| author | Yue-Yang Zhang Qing-Tian Qiao Bing-Xue Chen Qin Wan |
| author_facet | Yue-Yang Zhang Qing-Tian Qiao Bing-Xue Chen Qin Wan |
| author_sort | Yue-Yang Zhang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-99053578d2d64db397282eb64b16225d |
| institution | Kabale University |
| issn | 2042-0196 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Therapeutic Advances in Endocrinology and Metabolism |
| spelling | doaj-art-99053578d2d64db397282eb64b16225d2025-08-20T03:52:39ZengSAGE PublishingTherapeutic Advances in Endocrinology and Metabolism2042-01962025-05-011610.1177/20420188251337988Multi-omics investigation of prospective therapeutic targets for type 1 diabetesYue-Yang ZhangQing-Tian QiaoBing-Xue ChenQin WanBackground: 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.https://doi.org/10.1177/20420188251337988 |
| spellingShingle | Yue-Yang Zhang Qing-Tian Qiao Bing-Xue Chen Qin Wan Multi-omics investigation of prospective therapeutic targets for type 1 diabetes Therapeutic Advances in Endocrinology and Metabolism |
| title | Multi-omics investigation of prospective therapeutic targets for type 1 diabetes |
| title_full | Multi-omics investigation of prospective therapeutic targets for type 1 diabetes |
| title_fullStr | Multi-omics investigation of prospective therapeutic targets for type 1 diabetes |
| title_full_unstemmed | Multi-omics investigation of prospective therapeutic targets for type 1 diabetes |
| title_short | Multi-omics investigation of prospective therapeutic targets for type 1 diabetes |
| title_sort | multi omics investigation of prospective therapeutic targets for type 1 diabetes |
| url | https://doi.org/10.1177/20420188251337988 |
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