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Bidirectional two-sample Mendelian randomization analysis identifies causal associations between relative carbohydrate intake and depression

Nature Human Behaviour volume 6, pages 1569–1576 (2022)Cite this article

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Abstract

Growing evidence suggests that relative carbohydrate intake affects depression; however, the association between carbohydrates and depression remains controversial. To test this, we performed a two-sample bidirectional Mendelian randomization (MR) analysis using genetic variants associated with relative carbohydrate intake (N = 268,922) and major depressive disorder (N = 143,265) from the largest available genome-wide association studies. MR evidence suggested a causal relationship between higher relative carbohydrate intake and lower depression risk (odds ratio, 0.42 for depression per one-standard-deviation increment in relative carbohydrate intake; 95% confidence interval, 0.28 to 0.62; P = 1.49 × 10−5). Multivariable MR indicated that the protective effect of relative carbohydrate intake on depression persisted after conditioning on other diet compositions. The mediation analysis via two-step MR showed that this effect was partly mediated by body mass index, with a mediated proportion of 15.4% (95% confidence interval, 6.7% to 24.1%). These findings may inform prevention strategies and interventions directed towards relative carbohydrate intake and depression.

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Fig. 1: MR plots for the relationship of relative carbohydrate intake (N = 268,922) with MDD (N = 143,265).
Fig. 2: Mediation analysis of the effect of relative carbohydrate intake on MDD via potential mediators.

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Data availability

All GWAS summary statistics analysed in this study are publicly available for download by qualified researchers. The GWASs for relative intake of carbohydrate, fat and protein can be obtained through the SSGAC data portal (https://www.thessgac.org/). The GWASs for MDD were provided by the PGC (https://www.med.unc.edu/pgc). All data generated in the current study can be obtained from the Supplementary Information.

Code availability

All the analyses used in this study were conducted using PLINK version 1.07 and R packages TwoSampleMR (version 0.4.10), MRPRESSO (version 1.0), RadialMR (version 0.4) and MendelianRandomization (version 0.5.1). The code to reproduce all results reported in the manuscript is available at https://github.com/studentyaoshi/MR.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (grant nos 82101601 (S.Y.), 32170616 (T.-L.Y.) and 82170896 (Y.G.)), the Natural Science Basic Research Program of Shaanxi Province (grant no. 2021JC-02 (T.-L.Y.)), Innovation Capability Support Program of Shaanxi Province (grant no. 2022TD-44 (T.-L.Y.)), China Postdoctoral Science Foundation (grant nos 2021M702612 (S.Y.), 2020M683454 (S.-S.D.) and 2021T140546 (S.-S.D.)) and the Fundamental Research Funds for the Central Universities. This study was also supported by the High-Performance Computing Platform of Xi’an Jiaotong University. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Author notes

  1. These authors contributed equally: Shi Yao, Meng Zhang, Shan-Shan Dong.

Authors and Affiliations

  1. National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, the Second Affiliated Hospital, Xi’an Jiaotong University, Xi’an, P. R. China

    Shi Yao & Tie-Lin Yang

  2. Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, P. R. China

    Meng Zhang, Shan-Shan Dong, Jia-Hao Wang, Kun Zhang, Jing Guo, Yan Guo & Tie-Lin Yang

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Contributions

S.Y. and T.-L.Y. designed the study. Y.G. and T.-L.Y. supervised the study. M.Z. participated in the data collection. S.Y., M.Z., J.-H.W., K.Z. and J.G. performed the data analyses. S.Y. and M.Z. prepared the tables and figures. S.Y. wrote the paper. S.-S.D. and Y.G. critically revised the content. All authors contributed to editing the paper.

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Correspondence to Yan Guo or Tie-Lin Yang.

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Yao, S., Zhang, M., Dong, SS. et al. Bidirectional two-sample Mendelian randomization analysis identifies causal associations between relative carbohydrate intake and depression. Nat Hum Behav 6, 1569–1576 (2022). https://doi.org/10.1038/s41562-022-01412-9

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