Evidence map›Paper›PMID 36363762›Full record

ArticleMicroorganisms2022

Identification of Human Gut Microbiome Associated with Enterolignan Production.

Kento Sawane, Koji Hosomi, Jonguk Park, Kouta Ookoshi, Hinako Nanri, Takashi Nakagata, Yi-An Chen, Attayeb Mohsen, Hitoshi Kawashima, Kenji Mizuguchi and 2 more

Open access · goldAbstract read
In one paragraph

Article in Microorganisms, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

13 citing papers in PubMed, 16 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Kento SawaneCentral Laboratory Innovation Center, Nippn Corporation, 5-1-3 Midorigaoka, Atsugi 243-0041, Kanagawa, Japan.
Koji HosomiLaboratory of Vaccine Materials, Center for Vaccine and Adjuvant Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.
Jonguk ParkArtificial Intelligence Center for Health and Biomedical Research, NIBIOHN, 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.ORCID 0000-0003-4872-385X
Kouta OokoshiCentral Laboratory Innovation Center, Nippn Corporation, 5-1-3 Midorigaoka, Atsugi 243-0041, Kanagawa, Japan.
Hinako NanriDepartment of Physical Activity Research, NIBIOHN, 1-23-1 Toyama, Shinjuku, Tokyo 162-8636, Japan.
Takashi NakagataDepartment of Physical Activity Research, NIBIOHN, 1-23-1 Toyama, Shinjuku, Tokyo 162-8636, Japan.ORCID 0000-0003-4326-3604
Yi-An ChenArtificial Intelligence Center for Health and Biomedical Research, NIBIOHN, 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.
Attayeb MohsenArtificial Intelligence Center for Health and Biomedical Research, NIBIOHN, 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.ORCID 0000-0003-0690-8012
Hitoshi KawashimaArtificial Intelligence Center for Health and Biomedical Research, NIBIOHN, 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.ORCID 0000-0003-3612-4294
Kenji MizuguchiArtificial Intelligence Center for Health and Biomedical Research, NIBIOHN, 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.ORCID 0000-0003-3021-7078
Motohiko MiyachiDepartment of Physical Activity Research, NIBIOHN, 1-23-1 Toyama, Shinjuku, Tokyo 162-8636, Japan.
Jun KunisawaLaboratory of Vaccine Materials, Center for Vaccine and Adjuvant Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), 7-6-8 Saito-Asagi, Ibaraki 567-0085, Osaka, Japan.
National Institute of Biomedical Innovation, Health and Nutrition · JPWaseda University · JP

Funding

the Japan Agency for Medical Research and Development 22ae0121035s0102the Japan Agency for Medical Research and Development 22ae0121042h0002the Japan Agency for Medical Research and Development 22gm1010006h0004the Ministry of Health and Welfare of Japan and Public /Private R&D Investment Strategic Expansion PrograM 20AC5004
6 · The paper itself

Abstract

Dietary plant lignans are converted inside the gut to enterolignans enterodiol (ED) and enterolactone (EL), which have several biological functions, and health benefits. In this study, we characterized the gut microbiome composition associated with enterolignan production using data from a cross-sectional study in the Japanese population. We identified enterolignan producers by measuring ED and EL levels in subject's serum using liquid chromatography-tandem mass spectrometry. Enterolignan producers show more abundant proportion of Ruminococcaceae and Lachnospiraceae than non-enterolignan producers. In particular, subjects with EL in their serum had a highly diverse gut microbiome that was rich in Ruminococcaceae and Rikenellaceae. Moreover, we built a random forest classification model to classify subjects to either EL producers or not using three characteristic bacteria. In conclusion, our analysis revealed the composition of gut microbiome that is associated with lignan metabolism. We also confirmed that it can be used to classify the microbiome ability to metabolize lignan using machine learning approach.

Indexed as

enterolignangut microbiomelignanmachine learningmetabolism

Identifiers

PMID36363762
PMCPMC9697123
OpenAlexW4308119178

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.