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Assessing the potential causal effects of 1099 plasma metabolites on 2099 binary disease endpoints

Author

Listed:
  • Xianyong Yin

    (Nanjing Medical University)

  • Jack Li

    (University of Michigan School of Public Health)

  • Debraj Bose

    (University of Michigan School of Public Health)

  • Jeffrey Okamoto

    (University of Michigan School of Public Health)

  • Annie Kwon

    (University of Michigan School of Public Health)

  • Anne U. Jackson

    (University of Michigan School of Public Health)

  • Lilian Fernandes Silva

    (University of Eastern Finland and Kuopio University Hospital)

  • Anniina Oravilahti

    (University of Eastern Finland and Kuopio University Hospital)

  • Xiaomeng Chu

    (Nanjing Medical University)

  • Heather M. Stringham

    (University of Michigan School of Public Health)

  • Lei Liu

    (Nanjing Medical University)

  • Ruyi Peng

    (Nanjing Medical University)

  • Zhijie Xia

    (Nanjing Medical University)

  • Samuli Ripatti

    (University of Helsinki
    University of Helsinki
    Broad Institute of MIT & Harvard)

  • Mark Daly

    (University of Helsinki
    University of Helsinki
    Massachusetts General Hospital)

  • Aarno Palotie

    (University of Helsinki
    University of Helsinki
    Massachusetts General Hospital)

  • Laura J. Scott

    (University of Michigan School of Public Health)

  • Charles F. Burant

    (University of Michigan)

  • Eric B. Fauman

    (Development and Medical)

  • Xiaoquan Wen

    (University of Michigan School of Public Health)

  • Michael Boehnke

    (University of Michigan School of Public Health)

  • Markku Laakso

    (University of Eastern Finland and Kuopio University Hospital)

  • Jean Morrison

    (University of Michigan School of Public Health)

Abstract

Metabolites are small molecules that are useful for estimating disease risk and elucidating disease biology. Here, we perform two-sample Mendelian randomization to systematically infer the potential causal effects of 1099 plasma metabolites measured in 6136 Finnish men from the METSIM study on risk of 2099 binary disease endpoints measured in 309,154 Finnish individuals from FinnGen. We find evidence for 282 putative causal effects of 70 metabolites on 183 disease endpoints. We also identify 25 metabolites with potential causal effects across multiple disease domains, including ascorbic acid 2-sulfate affecting 26 disease endpoints in 12 disease domains. Our study suggests that N-acetyl-2-aminooctanoate and glycocholenate sulfate affect risk of atrial fibrillation through two distinct metabolic pathways and that N-methylpipecolate may mediate the putative causal effect of N6,N6-dimethyllysine on anxious personality disorder.

Suggested Citation

  • Xianyong Yin & Jack Li & Debraj Bose & Jeffrey Okamoto & Annie Kwon & Anne U. Jackson & Lilian Fernandes Silva & Anniina Oravilahti & Xiaomeng Chu & Heather M. Stringham & Lei Liu & Ruyi Peng & Zhijie, 2025. "Assessing the potential causal effects of 1099 plasma metabolites on 2099 binary disease endpoints," Nature Communications, Nature, vol. 16(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58129-2
    DOI: 10.1038/s41467-025-58129-2
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    References listed on IDEAS

    as
    1. Luca A Lotta & Robert A Scott & Stephen J Sharp & Stephen Burgess & Jian’an Luan & Therese Tillin & Amand F Schmidt & Fumiaki Imamura & Isobel D Stewart & John R B Perry & Luke Marney & Albert Koulman, 2016. "Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis," PLOS Medicine, Public Library of Science, vol. 13(11), pages 1-22, November.
    2. Noam Bar & Tal Korem & Omer Weissbrod & David Zeevi & Daphna Rothschild & Sigal Leviatan & Noa Kosower & Maya Lotan-Pompan & Adina Weinberger & Caroline I. Roy & Cristina Menni & Alessia Visconti & Ma, 2020. "A reference map of potential determinants for the human serum metabolome," Nature, Nature, vol. 588(7836), pages 135-140, December.
    3. Xianyong Yin & Lap Sum Chan & Debraj Bose & Anne U. Jackson & Peter VandeHaar & Adam E. Locke & Christian Fuchsberger & Heather M. Stringham & Ryan Welch & Ketian Yu & Lilian Fernandes Silva & Susan K, 2022. "Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Mitja I. Kurki & Juha Karjalainen & Priit Palta & Timo P. Sipilä & Kati Kristiansson & Kati M. Donner & Mary P. Reeve & Hannele Laivuori & Mervi Aavikko & Mari A. Kaunisto & Anu Loukola & Elisa Lahtel, 2023. "Author Correction: FinnGen provides genetic insights from a well-phenotyped isolated population," Nature, Nature, vol. 615(7952), pages 19-19, March.
    5. Mitja I. Kurki & Juha Karjalainen & Priit Palta & Timo P. Sipilä & Kati Kristiansson & Kati M. Donner & Mary P. Reeve & Hannele Laivuori & Mervi Aavikko & Mari A. Kaunisto & Anu Loukola & Elisa Lahtel, 2023. "FinnGen provides genetic insights from a well-phenotyped isolated population," Nature, Nature, vol. 613(7944), pages 508-518, January.
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