Evidence mapPaperPMID 42318308Full record

ArticleJournal of ophthalmology2026

Causal Effects of Gut Microbiota and Associated Metabolites on Retinal Diseases and Visual Impairment: A Mendelian Randomization Study.

Chuyao Yu, Li Dong, Ruiheng Zhang, Heyan Li, Xuhan Shi, Haotian Wu, Wenda Zhou, Yitong Li, Wen-Bin Wei

Abstract read
In one paragraph

Article in Journal of ophthalmology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Chuyao YuBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0009-0005-5548-9557
Li DongBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0003-0120-5756
Ruiheng ZhangBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0002-1324-4739
Heyan LiBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0002-6822-839X
Xuhan ShiBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0009-0007-9053-8785
Haotian WuBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0002-4765-1623
Wenda ZhouBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0001-8019-771X
Yitong LiBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0003-4432-2936
Wen-Bin WeiBeijing Tongren Eye Center, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China, ccmu.edu.cn.ORCID https://orcid.org/0000-0003-2386-0989

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous observational study findings have indicated a vital association between gut microbiota features and retinal diseases based on the "gut-retina" axis. However, whether their relationships underlie causal effects remains to be established. Methods: Instrumental variables of 211 gut microbiota taxa were obtained from a genome-wide association study (GWAS), and 28 gut-associated metabolites and pathways were included as exposures. A two-sample Mendelian randomization (MR) study was carried out to estimate gut microbiota effects on diabetic retinopathy (DR), early age-related macular degeneration (eAMD), retinal detachments and breaks (RDs/RBs), retinal vascular occlusion (RVO), disorders of the choroid and retina (D-C/R), and visual impairment. MR methods, including inverse variance weighted (IVW), MR‒Egger, weighted median, simple mode, and weighted mode methods, were used to investigate the causal relationship between gut microbiota features and various outcomes. Heterogeneity, pleiotropy, and stability tests of MR results were performed, and Bonferroni's correction was used to test the strength of the causal relationships between exposures and outcomes, as well as reverse and multivariable MR analyses. Results: Through MR analysis of 211 microbes and six clinical phenotypes, a total of 35 gut microbiome and 3 associated metabolites were found to be associated with various outcomes. Cochrane's Conclusion: We confirmed a potential causal relationship between some gut microbiota features and retinal diseases, thus providing new insights into the gut microbiota-mediated mechanism of retinopathy and indicating vital biomarkers for potential diagnostic, therapeutic, and prevention strategies.

Indexed as

causalitygut microbiotagut–retina axisMendelian randomizationmetabolitesretinal diseasesvisual impairment

Identifiers

PMID42318308
PMCPMC13273394

What Socratic holds

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Registered trials

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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.