Evidence map›Paper›PMID 36709262›Full record

ArticleBMC microbiology2023

Dysbiotic microbiome variation in colorectal cancer patients is linked to lifestyles and metabolic diseases.

Tung Hoang, Minjung Kim, Ji Won Park, Seung-Yong Jeong, Jeeyoo Lee, Aesun Shin

Erratum issuedAbstract read
In one paragraph

Article in BMC microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Systematic review: The gut microbiota as a link between colorectal cancer and obesity.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Pooled it
  3. Review
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  5. Article
  6. Article
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  9. A study on the effect of nutrition education based on the goal attainment theory on oral nutritional supplementation after colorectal cancer surgery.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Tung HoangDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, 03080, South Korea.
Minjung KimDepartment of Surgery, Seoul National University College of Medicine, Seoul, 03080, South Korea. minjungkim@snuh.org.
Ji Won ParkDepartment of Surgery, Seoul National University College of Medicine, Seoul, 03080, South Korea.
Seung-Yong JeongDepartment of Surgery, Seoul National University College of Medicine, Seoul, 03080, South Korea.
Jeeyoo LeeDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, 03080, South Korea.
Aesun ShinDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, 03080, South Korea.

Funding

National Research Foundation of Korea 2022R1A2C1004608Seoul National University Hospital 0420190530
6 · The paper itself

Abstract

backgroundDifferences in the composition and diversity of the gut microbial communities among individuals are influenced by environmental factors. However, there is limited research on factors affecting microbiome variation in colorectal cancer patients, who display lower inter-individual variations than that of healthy individuals. In this study, we examined the association between modifiable factors and the microbiome variation in colorectal cancer patients.

methodsA total of 331 colorectal cancer patients who underwent resection surgery at the Department of Surgery, Seoul National University Hospital between October 2017 and August 2019 were included. Fecal samples from colorectal cancer patients were collected prior to the surgery. Variations in the gut microbiome among patients with different lifestyles and metabolic diseases were examined through the network analysis of inter-connected microbial abundance, the assessment of the Anna Karenina principle effect for microbial stochasticity, and the identification of the enriched bacteria using linear discrimination analysis effect size. Associations of dietary diversity with microbiome variation were investigated using the Procrustes analysis.

resultsWe found stronger network connectivity of microbial communities in non-smokers, non-drinkers, obese individuals, hypertensive subjects, and individuals without diabetes than in their counterparts. The Anna Karenina principle effect was found for history of smoking, alcohol consumption, and diabetes (with significantly greater intra-sample similarity index), whereas obesity and hypertension showed the anti-Anna Karenina principle effect (with significantly lower intra-sample similarity index). We found certain bacterial taxa to be significantly enriched in patients of different categories of lifestyles and metabolic diseases using linear discrimination analysis. Diversity of food and nutrient intake did not shape the microbial diversity between individuals (p

conclusionsOur findings suggested an immune dysregulation and a reduced ability of the host and its microbiome in regulating the community composition. History of smoking, alcohol consumption, and diabetes were shown to affect partial individuals in shifting new microbial communities, whereas obesity and history of hypertension appeared to affect majority of individuals and shifted to drastic reductions in microbial compositions. Understanding the contribution of modifiable factors to microbial stochasticity may provide insights into how the microbiome regulates effects of these factors on the health outcomes of colorectal cancer patients.

Indexed as

Colorectal NeoplasmsMetabolic DiseasesMicrobiotaBacteriaHumansLife StyleObesityAnna Karenina principleColorectal cancerDietDysbiosisLifestyleMetabolic disease

Identifiers

PMID36709262
PMCPMC9883847

What Socratic holds

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LicenceCC BY
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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 Socratic graph.