Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses
Background: In recent years, driven by the rapid advancement of proteomics research, numerous scholars have investigated the intricate associations between plasma proteins and various diseases. Thus, this study aimed to identify novel therapeutic targets for preventing and treating metabolic-related...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-05-01
|
| Series: | Therapeutic Advances in Endocrinology and Metabolism |
| Online Access: | https://doi.org/10.1177/20420188251343140 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850183695316549632 |
|---|---|
| author | Yue-Yang Zhang Bin-Lu Wang Bing-Xue Chen Qin Wan |
| author_facet | Yue-Yang Zhang Bin-Lu Wang Bing-Xue Chen Qin Wan |
| author_sort | Yue-Yang Zhang |
| collection | DOAJ |
| description | Background: In recent years, driven by the rapid advancement of proteomics research, numerous scholars have investigated the intricate associations between plasma proteins and various diseases. Thus, this study aimed to identify novel therapeutic targets for preventing and treating metabolic-related diseases through Mendelian randomization (MR). Methods: This study primarily utilized the MR method, leveraging genetic data from multiple large-scale publicly available genome-wide association studies. We employed two-sample MR within this framework to assess the associations between 1001 plasma proteins and 5 metabolism-related diseases. Finally, we strengthen the robustness and reliability of the MR results by conducting a series of sensitivity analyses, including bidirectional MR, colocalization analysis, Cochran’s Q test, and the MR-Egger intercept test. Results: The results from the inverse variance weighted method revealed that, following false discovery rate correction, many plasma proteins are significantly associated with metabolic-related diseases. Genetically predicted risks vary across diseases: for coronary artery disease, from 0.82 FGR proto-oncogene, Src family tyrosine kinase (FGR) to 1.13 (interleukin-6); for obesity, from 0.992 (POLR2F) to 1.005 (PRKAB1); for osteoporosis, from 0.998 (AIF1) to 1.001 (CLC); for stroke, from 0.71 (TNFRSF1A) to 1.47 (TGM2); and for type 2 diabetes, from 0.79 (KRT18) to 1.47 (RAB37). Conclusion: Our findings reveal numerous plasma proteins linked to metabolic-related diseases. These findings offer fresh insights into the etiology, diagnostics, and treatment of these conditions. |
| format | Article |
| id | doaj-art-8462749c01974a8d8a543e7f4c3896cd |
| institution | OA Journals |
| 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-8462749c01974a8d8a543e7f4c3896cd2025-08-20T02:17:14ZengSAGE PublishingTherapeutic Advances in Endocrinology and Metabolism2042-01962025-05-011610.1177/20420188251343140Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analysesYue-Yang ZhangBin-Lu WangBing-Xue ChenQin WanBackground: In recent years, driven by the rapid advancement of proteomics research, numerous scholars have investigated the intricate associations between plasma proteins and various diseases. Thus, this study aimed to identify novel therapeutic targets for preventing and treating metabolic-related diseases through Mendelian randomization (MR). Methods: This study primarily utilized the MR method, leveraging genetic data from multiple large-scale publicly available genome-wide association studies. We employed two-sample MR within this framework to assess the associations between 1001 plasma proteins and 5 metabolism-related diseases. Finally, we strengthen the robustness and reliability of the MR results by conducting a series of sensitivity analyses, including bidirectional MR, colocalization analysis, Cochran’s Q test, and the MR-Egger intercept test. Results: The results from the inverse variance weighted method revealed that, following false discovery rate correction, many plasma proteins are significantly associated with metabolic-related diseases. Genetically predicted risks vary across diseases: for coronary artery disease, from 0.82 FGR proto-oncogene, Src family tyrosine kinase (FGR) to 1.13 (interleukin-6); for obesity, from 0.992 (POLR2F) to 1.005 (PRKAB1); for osteoporosis, from 0.998 (AIF1) to 1.001 (CLC); for stroke, from 0.71 (TNFRSF1A) to 1.47 (TGM2); and for type 2 diabetes, from 0.79 (KRT18) to 1.47 (RAB37). Conclusion: Our findings reveal numerous plasma proteins linked to metabolic-related diseases. These findings offer fresh insights into the etiology, diagnostics, and treatment of these conditions.https://doi.org/10.1177/20420188251343140 |
| spellingShingle | Yue-Yang Zhang Bin-Lu Wang Bing-Xue Chen Qin Wan Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses Therapeutic Advances in Endocrinology and Metabolism |
| title | Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses |
| title_full | Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses |
| title_fullStr | Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses |
| title_full_unstemmed | Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses |
| title_short | Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses |
| title_sort | novel therapeutic targets for metabolism related diseases proteomic mendelian randomization and colocalization analyses |
| url | https://doi.org/10.1177/20420188251343140 |
| work_keys_str_mv | AT yueyangzhang noveltherapeutictargetsformetabolismrelateddiseasesproteomicmendelianrandomizationandcolocalizationanalyses AT binluwang noveltherapeutictargetsformetabolismrelateddiseasesproteomicmendelianrandomizationandcolocalizationanalyses AT bingxuechen noveltherapeutictargetsformetabolismrelateddiseasesproteomicmendelianrandomizationandcolocalizationanalyses AT qinwan noveltherapeutictargetsformetabolismrelateddiseasesproteomicmendelianrandomizationandcolocalizationanalyses |