Mendelian randomization analysis of 233 metabolites in chronic rhinosinusitis and nasal polyps
Recent studies have suggested potential associations between specific metabolites and chronic rhinosinusitis (CRS) with nasal polyps (NP). However, robust causal evidence remains limited. This study applies Mendelian randomization (MR) to investigate these relationships. A 2-sample MR design was employed, utilizing genetic variants from publicly available genome-wide association studies. CRS data included 4617 cases and 152,226 controls (ebi-a-GCST90018603), while NP data comprised 5093 cases and 444,966 controls (ebi-a-GCST90018883). Data on 233 circulating metabolites were derived from 33 cohorts, encompassing 136,016 participants. The primary analysis used the inverse variance weighted method, with additional analyses using MR-Egger, simple mode, weighted median, and weighted mode. To address complexities related to polygenicity and pleiotropy, Bayesian weighted Mendelian randomization was also applied. The analysis demonstrated that higher ratios of total cholesterol to total lipids and free cholesterol to total lipids in very small very low-density lipoproteins particles were significantly associated with an increased risk of CRS. In contrast, elevated levels of 3-hydroxybutyrate and histidine were linked to a reduced risk of CRS. For NP, an increase in fatty acid chain length, though not the actual carbon number, was associated with a higher risk, while a higher triglycerides to phosphoglycerides ratio was linked to a lower risk of NP (odds ratio: 0.8789; 95% CI: 0.7977-0.9685; P = .0091). The findings clarify the metabolic pathways potentially impacting CRS and NP, suggesting new targets for prevention and treatment strategies.
Authors
- Xiao Fang Zhu (ORCID: https://orcid.org/0000-0003-2052-2212)
- Junxia Yao
- Weili Yang (ORCID: https://orcid.org/0000-0002-0108-5638)
- Zhe Zhu (ORCID: https://orcid.org/0009-0003-1249-5813)
- Chunzheng Xun
- Junwei Huang (ORCID: https://orcid.org/0009-0009-7144-0437)
Institutions
- Hunan University of Traditional Chinese Medicine (CN)
- First Affiliated Hospital of Hunan University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Medicine
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1097/md.0000000000043765
- Citations
- 1
- Primary Topic
- Biochemical Analysis and Sensing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.12