| Title: | Characterizing metabolomic signatures related to coffee and tea consumption and their association with incidence and dynamic progression of type 2 diabetes: A multi-state analysis |
| Journal: | American Journal of Epidemiology |
| Published: | 16 Oct 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39415441/ |
| DOI: | https://doi.org/10.1093/aje/kwae400 |
Publication 13613
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Abstract
Our study aimed to investigate the impact of tea and coffee consumption and related metabolomic signatures on dynamic transitions from diabetes-free status to incident type 2 diabetes (T2D), and subsequently to T2D-related complications and death. We included 438,970 participants in the UK Biobank who were free of diabetes and diabetes complications at baseline. Of these, 212,146 individuals had information on all metabolic biomarkers. We identified tea- and coffee-related metabolomic signatures using elastic net regression models. We examined associations of tea and coffee intake and related metabolomic signatures with the onset and progression of T2D using multi-state regression models. We observed that tea and coffee consumption and related metabolomic signatures were inversely associated with the risk of five T2D transitions. For example, HRs (95% CIs) per SD increase of the tea-related metabolomic signature were 0.87 (0.85, 0.89), 0.97 (0.95, 0.99), 0.91 (0.90, 0.92), 0.92 (0.91, 0.94), and 0.91 (0.90, 0.92) for transitions from diabetes-free state to incident T2D, from diabetes-free state to total death, from incident T2D to T2D complications, from incident T2D to death, and from T2D complications to death. These findings highlight the benefit of tea and coffee intake in reducing the risk of occurrence and progression of T2D.</p>
10 Authors
- Guzhengyue Zheng
- Shanshan Ran
- Jingyi Zhang
- Zhengmin Qian
- Fei Tian
- Hui Shi
- Michael Elliott
- Maya Tabet
- Yin Yang
- Hualiang Lin
1 Application
| Application ID | Title |
|---|---|
| 69550 | Identifying the potential effects of environmental and other healthcare related factors influencing health outcomes, mediated by genetic variances |
Enabling scientific discoveries that improve human health