| Title: | Allantoin Serves as a Novel Risk Factor for the Progression of MASLD |
| Journal: | Antioxidants |
| Published: | 22 Apr 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40427382/ |
| DOI: | https://doi.org/10.3390/antiox14050500 |
| URL: | https://www.mdpi.com/2076-3921/14/5/500/pdf?version=1745308303 |
Publication 15794
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Abstract
Uric acid (UA), traditionally recognized as an extracellular antioxidant, exhibits paradoxical associations with metabolic disorders such as metabolic dysfunction-associated steatotic liver disease (MASLD), though its mechanistic contributions remain elusive. Here, we integrate multi-modal evidence to explore the role of UA and its oxidative metabolite, allantoin, in MASLD progression. Analysis of UK Biobank data revealed a strong association between elevated UA levels and increased risks of MASLD and type 2 diabetes (T2D). However, Mendelian randomization analysis of over 2 million samples demonstrated causal effects of urate solely on serum triglycerides and T2D risk. Targeted metabolomics in an elderly Chinese cohort identified allantoin, an oxidative by-product of UA, significantly elevated in individuals with dyslipidemia or T2D, with serum allantoin levels positively correlated with fasting glucose, triglycerides, and cholesterol. Animal studies indicated that allantoin exacerbates hepatic lipid accumulation and glucose intolerance in high-fat diet mice, driven by increased hepatic lipid biogenesis and reduced bile acid production. Notably, further research revealed a strong binding affinity of allantoin for PPARα, leading to the suppression of PPARα activity, which promotes the progression of MASLD. These findings underscore the critical role of allantoin, rather than UA, as a critical driver of MASLD development, offering valuable insights for the prediction and management of hepatic metabolic disorders.</p>
16 Authors
- Weiqiang Lv
- Xueqiang Wang
- Zhaode Feng
- Cunxiao Sun
- Hansen Wu
- Mengqi Zeng
- Tianlin Gao
- Ke Cao
- Jie Xu
- Xuan Zou
- Tielin Yang
- Hao Li
- Lei Chen
- Jiankang Liu
- Shanshan Dong
- Zhihui Feng
1 Application
| Application ID | Title |
|---|---|
| 46387 | Integration of regulatory elements and multi-trait genomic and phenomic data to improve the accuracy of risk prediction of human complex diseases/traits |
Enabling scientific discoveries that improve human health