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Genomics and personalized strategies in nutrition

Integration of methylation quantitative trait loci (mQTL) on dietary intake on DNA methylation levels: an example of n-3 PUFA and ABCA1 gene

European Journal of Clinical Nutrition volume 77, pages 881–887 (2023)Cite this article

Subjects

Abstract

Background

Epigenetic studies have reported relationships between dietary nutrient intake and methylation levels. However, genetic variants that may affect DNA methylation (DNAm) pattern, called methylation quantitative loci (mQTL), are usually overlooked in these analyses. We investigated whether mQTL change the relationship between dietary nutrient intake and leukocyte DNAm levels with an example of estimated fatty acid intake and ATP-binding cassette transporter A1 (ABCA1).

Methods

A cross-sectional study on 231 participants (108 men, mean age: 62.7 y) without clinical history of cancer and no prescriptions for dyslipidemia. We measured leukocyte DNAm levels of 8 CpG sites within ABCA1 gene by pyrosequencing method and used mean methylation levels for statistical analysis. TaqMan assay was used for genotyping a genetic variant of ABCA1 (rs1800976). Dietary fatty acid intake was estimated with a validated food frequency questionnaire and adjusted for total energy intake by using residual methods.

Results

Mean ABCA1 DNAm levels were 5% lower with the number of minor alleles in rs1800976 (CC, 40.6%; CG, 35.9%; GG, 30.6%). Higher dietary n-3 PUFA intake was associated with lower ABCA1 DNAm levels (1st (ref) vs. 4th, β [95% CI]: –2.52 [–4.77, –0.28]). After controlling for rs180076, the association between dietary n-3 PUFA intake and ABCA1 DNAm levels was attenuated, but still showed an independent association (1st (ref) vs. 4th, β [95% CI]: –2.00 [–3.84, –0.18]). The interaction of mQTL and dietary n-3 PUFA intake on DNAm levels was not significant.

Conclusions

This result suggested that dietary n-3 PUFA intake would be an independent predictor of DNAm levels in ABCA1 gene after adjusting for individual genetic background. Considering mQTL need to broaden into other genes and nutrients for deeper understanding of DNA methylation, which can contribute to personalized nutritional intervention.

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Fig. 1
Fig. 2: Violin plots of ABCA1 DNA methylation levels (%) across three genotypes of rs1800976.

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Data availability

The datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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Acknowledgements

We are grateful to residents for participation in our study and to staff of the Health Examination Program for Residents for their support.

Funding

This study was supported by the JSPS KAKENHI Grants-in-Aid for Scientific Research (Nos. 26293144 and 17K09139), Grants-in-Aid for Scientific Research on Innovative Areas [CoBiA] (Nos. 16H06277 22H04923), and the Suzuken Memorial Foundation (No. 18-031).

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Authors and Affiliations

  1. Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan

    Ryosuke Fujii, Yoshiki Tsuboi, Mami Watanabe & Koji Suzuki

  2. Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Alessandro Volta 21, Bolzano/Bozen, Italy

    Ryosuke Fujii

  3. Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan

    Yoshitaka Ando, Koji Ohashi & Hiroaki Ishikawa

  4. Department of Hygiene, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan

    Hiroya Yamada & Shuji Hashimoto

  5. Department of Biochemistry, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan

    Eiji Munetsuna

  6. Department of Medical Technology, Kagawa Prefectural University of Health Sciences, 281-1 Hara, Mure-cho, Takamatsu, Japan

    Mirai Yamazaki

  7. Department of Medical Technology, Tokyo University of Technology School of Health Sciences, 5-23-22 Nishi-Kamata, Ota-ku, Japan

    Genki Mizuno

  8. Department of Clinical Physiology, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan

    Keisuke Maeda

  9. Department of Nutrition, Faculty of Wellness, Shigakkan University, 55 Nakoyama, Yokonemachi, Obu, Japan

    Nahomi Imaeda

  10. Department of Health and Nutrition, Nagoya Bunri University, 365 Maeda, Inazawa-city, Inazawa, Japan

    Chiho Goto

  11. Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Japan

    Kenji Wakai

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  1. Ryosuke Fujii
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Contributions

KS and KW designed the health checkup; RF, YA, HY, YT, MY, GM, KO, HI, and KS contributed for data acquisition; YA, HY, EM, MY, and GM conducted genotyping and measured methylation levels; NI and CG were responsible for nutritional survey; RF and YA analyzed data and wrote the paper; KM and MW reviewed the paper critically for important intellectual content; and KS and RF had primary responsibility for final content. All authors reviewed and approved the final paper.

Corresponding author

Correspondence to Koji Suzuki.

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The authors declare no competing interests.

Ethics approval

This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of Fujita Health University (No. HG19-069).

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Fujii, R., Ando, Y., Yamada, H. et al. Integration of methylation quantitative trait loci (mQTL) on dietary intake on DNA methylation levels: an example of n-3 PUFA and ABCA1 gene. Eur J Clin Nutr 77, 881–887 (2023). https://doi.org/10.1038/s41430-023-01315-6

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