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GWAS of 165,084 Japanese individuals identified nine loci associated with dietary habits

Nature Human Behaviour volume 4, pages 308–316 (2020)Cite this article

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Abstract

Dietary habits are important factors in our lifestyle, and confer both susceptibility to and protection from a variety of human diseases. We performed genome-wide association studies for 13 dietary habits including consumption of alcohol (ever versus never drinkers and drinks per week), beverages (coffee, green tea and milk) and foods (yoghurt, cheese, natto, tofu, fish, small whole fish, vegetables and meat) in Japanese individuals (n = 58,610–165,084) collected by BioBank Japan, the nationwide hospital-based genome cohort. Significant associations were found in nine genetic loci (MCL1-ENSA, GCKR, AGR3-AHR, ADH1B, ALDH1B1, ALDH1A1, ALDH2, CYP1A2-CSK and ADORA2A-AS1) for 13 dietary traits (P < 3.8 × 10−9). Of these, ten associations between five loci and eight traits were new findings. Furthermore, a phenome-wide association study revealed that five of the dietary trait-associated loci have pleiotropic effects on multiple human complex diseases and clinical measurements. Our findings provide new insight into the genetics of habitual consumption.

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Fig. 1: Manhattan plots for dietary habits from GWAS in a Japanese population.
Fig. 2: Effect of functional ALDH2 variant (rs671) on dietary habits.
Fig. 3: Genetic correlations among dietary habits.
Fig. 4: PheWAS matrix plot of significant SNPs associated with dietary habits.
Fig. 5: Cell-type-specific enrichment of dietary habits.

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Data availability

GWAS summary statistics of the 13 dietary habits investigated are publicly available at the National Bioscience Database Centre (NBDC) Human Database (Research ID: hum0014) as open data with no access restrictions. GWAS genotype data were deposited at the NBDC Human Database (Research ID: hum0014).

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Acknowledgements

We are grateful to all participants enrolled in BBJ. We thank all the clinicians and organizations that contributed to the collection of samples and clinical information. This research was supported by the Tailor-Made Medical Treatment Programme (BBJ) of the Ministry of Education, Culture, Sports, Science and Technology and the Japan Agency for Medical Research and Development (AMED; grant nos. JP17km0305002, JP19km0405201 and JP19km045208), and by the Strategic Research Programme for Brain Sciences of AMED (no. JP19dm0107097). Y.O. was supported by the Japan Society for the Promotion of Science, KAKENHI (nos. 15H05911 and 19H01021), AMED (nos. JP19gm6010001, JP19ek0410041, JP19ek0109413 and JP19km0405211), Takeda Science Foundation and the Bioinformatics Initiative of Osaka University Graduate School of Medicine, Osaka University and Osaka University Centre of Medical Data Science, Advanced Clinical Epidemiology Investigator’s Research Project. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Nana Matoba, Masato Akiyama, Kazuyoshi Ishigaki, Masahiro Kanai, Atsushi Takahashi & Yoichiro Kamatani

  2. Department of Genetics, UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Nana Matoba

  3. Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

    Masato Akiyama

  4. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Masahiro Kanai

  5. Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Suita, Japan

    Atsushi Takahashi

  6. Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Yukihide Momozawa

  7. Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo, Japan

    Shiro Ikegawa

  8. Department of Psychiatry, Fujita Health University School of Medicine, Toyotake, Japan

    Masashi Ikeda & Nakao Iwata

  9. Institute of Medical Science, The University of Tokyo, Tokyo, Japan

    Makoto Hirata

  10. Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan

    Koichi Matsuda

  11. Division of Molecular Pathology, the Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan

    Yoshinori Murakami

  12. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Michiaki Kubo

  13. Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan

    Yoichiro Kamatani

  14. Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan

    Yukinori Okada

  15. Laboratory of Statistical Immunology, Immunology Frontier Research Center, Osaka University, Suita, Japan

    Yukinori Okada

  16. Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan

    Yukinori Okada

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  1. Nana Matoba
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Contributions

N.M., M.A., Y.K. and Y.O. contributed to study concept and design. M.H., K.M., Y. Murakami and M. Kubo collected and managed BBJ samples. Y. Momozawa and M. Kubo performed genotyping. N.M., M.A., K.I., M. Kanai and A.T. performed statistical analysis. S.I., M.I. and N.I. contributed to data acquisition. N.M., Y.K. and Y.O. wrote the manuscript. All authors reviewed and approved the final version of the manuscript.

Corresponding authors

Correspondence to Yoichiro Kamatani or Yukinori Okada.

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Editor recognition statement Primary handling editor: Stavroula Kousta

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–13 and Supplementary Tables 1, 5, 8 and 9.

Reporting Summary

Supplementary Table

Supplementary Table 2. Summary of current studies.

Supplementary Table 3. Covariates used in each association test.

Supplementary Table 4. Associations of previously reported loci.

Supplementary Table 6. Look-up results in UK BioBank.

Supplementary Table 7. Effect of taste sensitivity-related SNPs.

Supplementary Table 10. Full results of cross-trait LDSC analysis across dietary habits.

Supplementary Table 11. Description of complex diseases and laboratory measurements used in PheWAS.

Supplementary Table 12. PheWAS results.

Supplementary Table 13. Full results of heritability enrichment in ten cell type groups.

Supplementary Table 14. Full results of pathway enrichment analysis.

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Matoba, N., Akiyama, M., Ishigaki, K. et al. GWAS of 165,084 Japanese individuals identified nine loci associated with dietary habits. Nat Hum Behav 4, 308–316 (2020). https://doi.org/10.1038/s41562-019-0805-1

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