Evidence map›Paper›PMID 33832437›Full record

ArticleBMC microbiology2021

Association between aging-dependent gut microbiome dysbiosis and dry eye severity in C57BL/6 male mouse model: a pilot study.

Chang Ho Yoon, Jin Suk Ryu, Jayoon Moon, Mee Kum Kim

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 13% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Analysis of Oral Microbiota in Elderly Thai Patients with Alzheimer's Disease and Mild Cognitive Impairment.International journal of environmental research and public health · 2024
    Article
  8. Targeting the Gut-Eye Axis: An Emerging Strategy to Face Ocular Diseases.International journal of molecular sciences · 2023
    Review
  9. Article
  10. Review
  11. The Link Between Gastrointestinal Microbiome and Ocular Disorders.Clinical ophthalmology (Auckland, N.Z.) · 2023
    Review
  12. Article
  13. Article
  14. Bacteria and Dry Eye: A Narrative Review.Journal of clinical medicine · 2022
    Review
  15. Article
  16. Article
  17. Aging effects on the diurnal patterns of gut microbial composition in male and female mice.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2021
    Article
  18. Article
  19. 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

4 authors at 1 institution in 1 country.

Chang Ho YoonDepartment of Ophthalmology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Jin Suk RyuLaboratory of Ocular Regenerative Medicine and Immunology, Biomedical Research Institute, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Jayoon MoonDepartment of Ophthalmology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Mee Kum KimDepartment of Ophthalmology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. kmk9@snu.ac.kr.
Seoul National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile aging is a potent risk factor of dry eye disease, age-related gut dysbiosis is associated with inflammation and chronic geriatric diseases. Emerging evidence have demonstrated that gut dysbiosis contributes to the pathophysiology or exacerbation of ocular diseases including dry eye disease. However, the relationship between aging-related changes in gut microbiota and dry eye disease has not been elucidated. In this pilot study, we investigated the association between aging-dependent microbiome changes and dry eye severity in C57BL/6 male mice.

resultsEight-week-old (8 W, n = 15), one-year-old (1Y, n = 10), and two-year-old (2Y, n = 8) C57BL/6 male mice were used. Dry eye severity was assessed by corneal staining scores and tear secretion. Bacterial genomic 16 s rRNA from feces was analyzed. Main outcomes were microbiome compositional differences among the groups and their correlation to dry eye severity. In aged mice (1Y and 2Y), corneal staining increased and tear secretion decreased with statistical significance. Gut microbiome α-diversity was not different among the groups. However, β-diversity was significantly different among the groups. In univariate analysis, phylum Firmicutes, Proteobacteria, and Cyanobacteria, Firmicutes/Bacteroidetes ratio, and genus Alistipes, Bacteroides, Prevotella, Paraprevotella, and Helicobacter were significantly related to dry eye severity. After adjustment of age, multivariate analysis revealed phylum Proteobacteria, Firmicutes/Bacteroidetes ratio, and genus Lactobacillus, Alistipes, Prevotella, Paraprevotella, and Helicobacter to be significantly associated with dry eye severity.

conclusionsOur pilot study suggests that aging-dependent changes in microbiome composition are related to severity of dry eye signs in C57BL/6 male mice.

Indexed as

AgingAnimalsBacteriaBiodiversityDisease Models, AnimalDry Eye SyndromesDysbiosisFecesGastrointestinal MicrobiomeMaleMiceMice, Inbred C57BLPilot ProjectsRNA, Ribosomal, 16SSeverity of Illness IndexRNA, Ribosomal, 16S16S rRNAAgingDry eyeMicrobiomeParaprevotella

Identifiers

PMID33832437
PMCPMC8033717
OpenAlexW3148597144

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.