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Identification of blood metabolites linked to the risk of cholelithiasis: a comprehensive Mendelian randomization study

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Abstract

Background and aims

Observational and Mendelian randomization (MR) studies have identified several modifiable risk factors of cholelithiasis. However, there is limited evidence about the causal effect of blood metabolites on the cholelithiasis risk.

Methods

To have a comprehensive understanding to causal relations between blood metabolites and cholelithiasis, for the primary discovery, we applied two MR methods to explore the associations between 249 circulating metabolites and cholelithiasis. For secondary validations, we replicated the examinations using another metabolic dataset with 123 metabolites. The summary statistics of cholelithiasis were retrieved from FinnGen Consortium Release 5 and UK Biobank. Inverse-variance weighted, weight median and MR-egger methods were used for calculating causal estimates. Furthermore, Bayesian model averaging MR (MR-BMA) method was employed to detect the dominant causal metabolic traits with adjustment for pleiotropy effects.

Results

In the primary analysis, sphingomyelin showed consistent protective causal associations with cholelithiasis; while plasma cholesterol-associated traits showed generally inverse correlation with cholelithiasis risk. Notably, large numbers of traits within the (un)saturated fatty acid category demonstrated significant causal effects. Secondary analyses demonstrated similar results, with traits related to the levels of bisallylic groups in fatty acids showing protective effects. Lastly, MR-BMA analyses discovered that the degree of unsaturation plays a predominant role in reducing the risk of cholelithiasis.

Conclusion

Our MR study provides a complete atlas of associations between plasma metabolites on cholelithiasis risk. It highlighted that genetically predicted sphingomyelin and degree of unsaturation of fatty acid were causally associated with the reduced risk of cholelithiasis.

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Data availability

The summary statistics of GWAS dataset for metabolic traits can be accessed from IEU open GWAS project (https://gwas.mrcieu.ac.uk/datasets/) or MR-Base (https://www.mrbase.org/) website under the accession ID met-d and met-c. The summary-level results of cholelithiasis datasets can be obtained from FinnGen Round 5 (https://r5.finngen.fi/). The summary-level results of cholelithiasis from UK BioBank can be obtained from GWAS atlas website (https://atlas.ctglab.nl/traitDB/3675). All analytical results been uploaded to the OSF data respiratory (https://osf.io/dq4fr/).

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Acknowledgements

The authors thank all participants and investigators for the contributions of GWAS data.

Funding

This study is supported by the Fundamental Research Funds for the Center Universities (3332021007).

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Authors

Contributions

JRM, LJJ, ZYL and XYB conceptualized and designed the study, analyzed the data and wrote the manuscript. XW, NZ and YZW helped analyze the data. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xiaoyin Bai.

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Jiarui Mi, Lingjuan Jiang, Zhengye Liu, Xia Wu, Nan Zhao, Yuanzhuo Wang, Xiaoyin Bai declare no conflict of interest.

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Mi, J., Jiang, L., Liu, Z. et al. Identification of blood metabolites linked to the risk of cholelithiasis: a comprehensive Mendelian randomization study. Hepatol Int 16, 1484–1493 (2022). https://doi.org/10.1007/s12072-022-10360-5

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