Evidence map›Paper›PMID 37310549›Full record

ArticleJournal of gastrointestinal cancer2024

Gut Microbiome Composition in Lynch Syndrome With and Without History of Colorectal Neoplasia and Non-Lynch Controls.

S B Rifkin, M A Sze, K Tuck, E Koeppe, E M Stoffel, P D Schloss

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of gastrointestinal cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Intratumoural pksEBioMedicine · 2025
    Article
  5. Review
  6. iScience · 2024
    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

6 authors at 1 institution in 1 country.

S B RifkinDepartment of Internal Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, 48109, USA. srifkin@med.umich.edu.
M A SzeDepartment of Immunology and Microbiology, University of Michigan, Ann Arbor, MI, 48109, USA.
K TuckDepartment of Internal Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, 48109, USA.
E KoeppeDepartment of Internal Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, 48109, USA.
E M StoffelDepartment of Internal Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, 48109, USA.
P D SchlossDepartment of Immunology and Microbiology, University of Michigan, Ann Arbor, MI, 48109, USA.
University of Michigan–Ann Arbor · US

Funding

Identification of Microbiome Based Markers to Improve Colorectal Cancer DetectionR01CA215574 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RUFFIN, MACK T., SCHLOSS, PATRICK DAVID · 2018 to 2021
$1.4M
NCI NIH HHS R01 CA215574
6 · The paper itself

Abstract

backgroundWhile Lynch syndrome (LS) is a highly penetrant colorectal cancer (CRC) syndrome, there is considerable variation in penetrance; few studies have investigated the association between microbiome and CRC risk in LS. We analyzed the microbiome composition among individuals with LS with and without personal history of colorectal neoplasia (CRN) and non-LS controls.

methodsWe sequenced the V4 region of the 16S rRNA gene from the stool of 46 individuals with LS and 53 individuals without LS. We characterized within community and in between community microbiome variation, compared taxon abundance, and built machine learning models to investigate the differences in microbiome.

resultsThere was no difference within or between community variations among LS groups, but there was a statistically significant difference in both within and between community variation comparing LS to non-LS. Streptococcus and Actinomyces were differentially enriched in LS-CRC compared to LS-without CRN. There were numerous differences in taxa abundance comparing LS to non-LS; notably, Veillonella was enriched and Faecalibacterium and Romboutsia were depleted in LS. Finally, machine learning models classifying LS from non-LS controls and LS-CRC from LS-without CRN performed moderately well.

conclusionsDifferences in microbiome composition between LS and non-LS may suggest a microbiome pattern unique to LS formed by underlying differences in epithelial biology and immunology. We found specific taxa differences among LS groups, which may be due to underlying anatomy. Larger prospective studies following for CRN diagnosis and microbiome composition changes are needed to determine if microbiome composition contributes to CRN development in patients with LS.

Indexed as

Colorectal Neoplasms, Hereditary NonpolyposisGastrointestinal MicrobiomeRNA, Ribosomal, 16SAdultAgedBacteriaCase-Control StudiesColorectal NeoplasmsFecesFemaleHumansMachine LearningMaleMiddle AgedRNA, Ribosomal, 16SColorectal cancer (CRC)Colorectal neoplasia (CRN)DNA mismatch repair (MMR)Lynch syndrome (LS)Microbiome

Identifiers

PMID37310549
OpenAlexW4380422278

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.