Evidence map›Paper›PMID 37542202›Full record

ArticleEuropean journal of clinical nutrition2023

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

Ryosuke Fujii, Yoshitaka Ando, Hiroya Yamada, Yoshiki Tsuboi, Eiji Munetsuna, Mirai Yamazaki, Genki Mizuno, Keisuke Maeda, Koji Ohashi, Hiroaki Ishikawa and 6 more

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in European journal of clinical nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 8 institutions in 2 countries.

Ryosuke FujiiDepartment of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.ORCID 0000-0003-1730-2059
Yoshitaka AndoDepartment of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Hiroya YamadaDepartment of Hygiene, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Yoshiki TsuboiDepartment of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.ORCID 0000-0001-8145-3949
Eiji MunetsunaDepartment of Biochemistry, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Mirai YamazakiDepartment of Medical Technology, Kagawa Prefectural University of Health Sciences, 281-1 Hara, Mure-cho, Takamatsu, Japan.
Genki MizunoDepartment of Medical Technology, Tokyo University of Technology School of Health Sciences, 5-23-22 Nishi-Kamata, Ota-ku, Japan.
Keisuke MaedaDepartment of Clinical Physiology, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Koji OhashiDepartment of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Hiroaki IshikawaDepartment of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Mami WatanabeDepartment of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Nahomi ImaedaDepartment of Nutrition, Faculty of Wellness, Shigakkan University, 55 Nakoyama, Yokonemachi, Obu, Japan.ORCID 0000-0003-3106-3488
Chiho GotoDepartment of Health and Nutrition, Nagoya Bunri University, 365 Maeda, Inazawa-city, Inazawa, Japan.
Kenji WakaiDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Japan.
Shuji HashimotoDepartment of Hygiene, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan.
Koji SuzukiDepartment of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Japan. ksuzuki@fujita-hu.ac.jp.ORCID 0000-0002-3235-9558
Fujita Health University Hospital · JPFujita Health University · JPEurac Research · ITKagawa Prefectural College of Health Sciences · JPNagoya Bunri University · JPNagoya University · JPShigakkan University · JPTokyo University of Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpigenetic 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).

methodsA 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.

resultsMean 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.

conclusionsThis 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.

Indexed as

DNA MethylationFatty Acids, Omega-3ATP Binding Cassette Transporter 1Cross-Sectional StudiesEatingHumansMaleMiddle AgedQuantitative Trait LociABCA1 protein, humanATP Binding Cassette Transporter 1Fatty Acids, Omega-3

Identifiers

PMID37542202
OpenAlexW4385580360

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.