Role of gut microbiomes in different ocular pathologies: A systematic review

Table 1 Summaries of studies related to ocular diseases based on gut dysbiosis examination

No.	Ref.	Type of study	Participants	Age (mean ± SD)	Ocular disease category	Methodology	Intervention, if any	Primary ocular outcome	GI outcome
1	Jayasudha et al[38], 2019	Case-control	14 uveitis, 24 HC	43.64 ± 14.37, 45.92 ± 16.91	Uveitis	Fecal fungal rRNA sequencing	None	None	Significant ↓ in gut fungal richness and diversity in uveitis patients compared to HC
2	Kalyana Chakravarthy et al[39], 2018	Case-control	13 uveitis, 13 HC	44.54 ± 12.64, 43.08 ± 12.99	Uveitis	Fecal 16S rRNA gene sequencing	None	None	Reduced diversity of several anti-inflammatory organisms in uveitis microbiomes; also ↓ probiotic and antibacterial organisms in uveitis
3	Huang et al[40], 2018	Case-control	38 AAU, 40 HC	33.87 ± 8.77, 36.01 ± 6.87	Uveitis	Fecal 16S rRNA gene sequencing	None	None	Significant difference in beta diversity of gut microbiota composition between AAU and controls; and also significant difference in fecal metabolite phenotype in uveitis patients from HC
4	Morandi et al[41], 2024	Case-control study	20 HLA-B27 uveitis, 27 control	44.5 ± 16.3, 42.1 ± 14.9	Uveitis	Fecal DNA sequencing	None	Bacteroides caccae may therefore play a protective role in the development of AU in HLA-B27-positive individual	AU development is associated with compositional and functional alterations of the GM
5	Wang et al[42], 2023	Case-control	37 Behcet’s uveitis, control-40		Behcet uveitis	Fecal 16S rRNA gene sequencing	None	Restoration of healthy gut microbiota composition correlated with reduced ocular inflammation and slower progression of retinal disease	Targeting gut microbiota showed potential for modulating systemic immunity and ocular pathology
			31 VKH, control-40		VKH		None
6	Ye et al[43], 2020	Case-control	71 active VKH, 11 inactive VKH, 67 HC	40.5 ± 15.1, 41.1 ± 13.5	VKH	Fecal DNA sequencing	None	None	Depleted butyrate-producing bacteria, lactate-producing bacteria and methanogens as well as enriched Gram-negative bacteria were identified in the active VKH patients
7	Tecer et al[44], 2020	Case-control	7 BS, 12 (FMF), 9 CD and 16 HC	35.57 ± 6.60, 32.17 ± 8.64, 35.00 ± 5.27, 39.38 ± 7.69	Behcet’s syndrome	Fecal 16S rRNA gene sequencing	None	None	Significant differences in alpha diversity between four groups. Prevotella copri was dominant in BS group
8	Kim et al[45], 2021	Case-control	9 BD, 7 with RAU, 9 BD-matched HC, and 7 RAU-matched HC	Median 33, 47, 53, 44	Behcet’s syndrome	Fecal 16S rRNA gene sequencing	None	BD patients with uveitis had different abundances of various taxa, compared to those without uveitis. Alterations in the fecal microbiome in patients with BD according to disease activity, and an association of the abundance of fecal bacterial species with BD disease activity and uveitis symptoms	A tendency toward clustering in the beta diversity & ↓ in alpha diversity of the fecal microbiome was observed between the active BD patients and HC. Active BD patients had a significantly higher abundance of fecal Bacteroides uniformis than their matched HC and patients with inactive disease state (P = 0.038)
9	Yasar Bilge et al[46], 2020	Prospective cohort	27 BD, 10 HC	40.8 ± 9.3, 38.9 ± 4.9	Behcet’s syndrome	Fecal 16S rRNA gene sequencing	None	None	No differences between the BD group and the control group in terms of alpha and beta microbial diversity and abundance indices (P > 0.05), significant differences in the relative abundance of some bacterial taxa between patient with BD and HC
10	Ye et al[47], 2018	Case-control	32 active BD and 74 HC	47.1 ± 5.3, 45.9 ± 7.2	Behcet’s syndrome	Fecal metagenomic DNA sequencing	None	None	Enriched in a SRB along with a lower level of butyrate-producing bacteria and methanogens
11	Zysset-Burri et al[48], 2019	Case-control	29 non-arteritic (RAO) and 30 HC	69.4 ± 1.9, 69.0 ± 1.7	RAO	Fecal DNA sequencing	None	None	Gut derived, TMAO was significantly higher in patients with RAO compared to controls (P = 0.023)
12	Zhang Y et al[49], 2023	Case-control	30 AMD, 17 control	Not applicable	AMD	Fecal 16S rRNA gene sequencing	None	None	Different bacterial compositions noted in the AMD compared to controls
13	Zysset-Burri et al[50], 2020	Case-control	12 nAMD, 11 control	75.4 ± 8.3, 75.3 ± 7.1	AMD	Fecal DNA sequencing	None	None	AMD patients show distinct gut microbiome composition and functional gene enrichment; genetic complement variants modulate these associations; microbiome–complement axis may contribute to AMD pathogenesis
14	Xue et al[51], 2023	Case-control	30 AMD, 30 control	66.05 ± 9.26, 78.4 ± 7.4	AMD	Fecal metagenomic DNA sequencing	None	Depleted Bacteroidaceae in patients with AMD was negatively associated with hemorrhage size	Gut microbiome may affect AMD severity by increasing intestinal permeability, thereby facilitating the translocation of microbes
15	Huang et al[52], 2021	Cross sectional study	25 DM without DR, 25 DM with DR, 25 control	62.5 ± 5.2, 60.3 ± 9.1, 57.8 ± 7.5	DR	Fecal 16S rRNA gene sequencing	None	None	Reduced alpha & beta diversity in both DM and DR groups compared to control
16	Moubayed et al[53], 2019	Case-control	9 diabetic patients without retinopathy, 8 diabetic patients with retinopathy, 18 HC	Not applicable	DR	Fecal DNA sequencing	None	None	Higher ratio of Bacteroides in diabetic groups than controls but no difference between those with and without retinopathy
17	Ye et al[54], 2021	Case-control	45 PDR, 90 diabetic without DR as control	59.9 ± 11.3, 60.9 ± 9.9	DR	Fecal 16S rRNA gene sequencing	None	None	Significantly lower bacterial diversity with significant depletion of 22 families and enrichment of 2 families in the PDR group as compared with the NDR group
18	Das et al[55], 2021	Case-control	25 with T2DM without DR, 28 with T2DM and DR, 30 HC	57.3, 55.2, 52.2	DR	Fecal 16S rRNA gene sequencing	None	None	Dysbiosis more pronounced in DR compared to DM, control & ↓ in anti-inflammatory, probiotic and pathogenic bacteria compared to HC
19	Jayasudha et al[56], 2020	Cohort study	21 DM, 24 DR, 30 HC	57.5, 54.5, 52.2	DR	Fecal DNA sequencing	None	None	More mycobiome dysbiosis in people with T2DM and DR than compared to HC
20	Khan R et al[57], 2021	Case-control	37 with sight Threatening DR, 21 control	57.45 ± 8.08, 57.50 ± 7.60	DR	Fecal DNA sequencing	None	None	No difference in gut microbial abundance between the 2 populations
21	Omar et al[58], 2024	Prospective study	23 were NM, 8 PM, and 21 SM	31.96 ± 7.5, 32.35 ± 4.8, 30.62 ± 8.1	Myopia	Fecal 16S rRNA gene sequencing	None	None	No significant differences in alpha and beta diversity between the three groups (NM, PM, and SM), Prevotella copri was predominant in stable myopia
22	Sun et al[59], 2024	Case-control study	35 myopia, 45 HC		Myopia	Fecal 16S rRNA gene sequencing	None	None	No significant difference in α diversity while β diversity reached a significant level
23	Skondra et al[60], 2021	Cross sectional study	6 infants with type 1 ROP and 4 preterm infants without any ROP	24.1 weeks, 25.6 weeks	ROP	Fecal 16S rRNA gene sequencing	None	Absence of Enterobacteriaceae overabundance, in addition to enrichment of amino acid biosynthesis pathways, may protect against severe ROP in high-risk preterm infants	Significant enrichment of Enterobacteriaceae & ↓ amino acid biosynthesis pathways in type 1 ROP
24	Chang et al[61], 2024	Case-control study	13 with type 1 ROP, 44 with type 2, and 53 without ROP		ROP	Fecal 16S rRNA gene sequencing	None	Reduced gut microbial diversity may be associated with ROP development in high-risk preterm infants	Type 1 ROP showed no significant difference in microbial diversity up to 8 postnatal weeks (P = 0.057), while type 2 and no ROP groups displayed increased diversity (P = 0.0015 and P = 0.049, respectively)
25	Berkowitz et al[62], 2022	Case-control	25 IIH, 20 HC	35.12, 48.5	IIH	Fecal DNA sequencing	Acetazolamide examined in IIH patients	None	Lower diversity of bacterial species in IIH patients compared with HC, ↑ in Lactobacillus brevis, (beneficial bacterium) in acetazolamide treated patients
26	Gong et al[63], 2020	Case-control	30 POAG, 30 control	54.77 ± 9.32, 53.80 ± 7.87	POAG	Fecal 16S rRNA gene sequencing	None	Mean visual acuity was negatively correlated with Blautia, mean VF-MD was negatively correlated with Faecalibacterium, and average RNFL thickness was positively correlated with Streptococcus	Bacterial profile in the gut microbiome had significant differences between the POAG and control
27	Kalyana Chakravarthy et al[64], 2018	Case-control	32 fungal keratitis, 31 HC	47.1, 42.2	Fungal keratitis	Fecal 16S rRNA gene sequencing	None	None	No significant difference in fungal dysbiosis, but bacterial richness and diversity was significantly decreased in FK patients, strong association of disease phenotype with ↓ in beneficial bacteria and increase in pro-inflammatory and pathogenic bacteria in FK patients
28	Jayasudha et al[65], 2018	Case-control	19 BK, 21 HC	48.8	Bacterial keratitis	Fecal DNA sequencing	None	None	↑ In number of antiinflammatory organisms in HC compared to BK
29	Mendez et al[66], 2020	Case-control	13 with Sjögren + dry eye, 8 with Sjögren without dry eye, 21 HC	58.8 ± 10, 58.4 ± 726.0	Sjögren syndrome	Fecal 16S rRNA gene sequencing	None	None	Shannon’s diversity index showed no differences between groups Faith’s phylogenetic diversity showed increased diversity in cases vs controls, which reached significance when comparing SDE and controls (P = 0.02)
30	Moon et al[67], 2020	Case-control	10 SS, 14 with environmental DES, 12 HC	58.5 ± 3.05, 46.29 ± 2.6, 47.5 ± 4.05	Sjögren syndrome	Fecal 16S rRNA gene sequencing	None	Bacteroidetes, Actinobacteria and Bifidobacterium were significantly related with dry eye signs (P < 0.05), multivariate linear regression analysis revealed tear secretion was strongly affected by Prevotella (P = 0.025)	Gut microbiome showed significant differences in patients with Sjögren than compared to controls & DES; no significant difference in alpha-diversity across all 3 groups
31	Watane et al[68], 2021	Non-randomized clinical trial	10 dry eye due to Sjögren syndrome	60.4 ± 4.2	Sjögren syndrome	Fecal DNA sequencing	FMT	Improvement of subjective dry eye symptoms in 5 individuals after FMT at 3 month follow up	No side effect after FMT
32	Filippelli et al[69], 2021	RCT	26 children with chalazion	8.3	Chalazion	None	Probiotic supplementation	Decreased time to resolution of chalazion in probiotic group (P < 0.0001)	No adverse effect
33	Filippelli et al[70], 2022	RCT	20 adults with chalazion	48.25	Chalazion	None	Probiotic supplementation	Decreased time to resolution of small size. Chalazion in probiotic group (P < 0.039). Failure to resolve medium or large chalazion	No adverse effect
34	Yang et al[71], 2024	Case-control study	145 GD, 156 GO, 100 HC	36, 44.50, 38	Grave’s disease	Fecal 16S rRNA gene sequencing	None	Levels of IAA were negatively correlated with clinical activity score and serum TRAb in GO patients	Trp metabolites IAA maybe a novel biomarker for GO progression. and IPA, ILA and IAA may play a protective role in GO
35	Zhang et al[72], 2024	Case-control study	30 TAO, 29 HC	43.40 ± 10.38, 41.79 ± 7.61	Thyroid ophthalmopathy	Fecal 16S rRNA gene sequencing	None	Veillonella demonstrated a positive correlation with exophthalmos. Conversely, Alloprevotella showed a negative correlation with exophthalmos. Dialister and Clostridium sensu stricto 1 exhibited positive correlations with disease severity, while Streptococcus showed a negative correlation with disease severity	Reduced gut richness and diversity observed in patients with TAO
36	Zhang et al[73], 2023	Case-control study	62 GO, 18 HC		Graves orbitopathy	Fecal 16S rRNA gene sequencing	None	Klebsiella pneumoniae was positively correlated with disease severity	No remarkable difference in gut microbiota diversity between groups; however, the gut microbial community and dominant microbiota significantly differed among groups

IIH: Idiopathic intracranial hypertension; DM: Diabetes mellitus; PM: Progressive myopes; SM: Stable myopes; NM: Nonmyopes; HC: Healthy controls; rRNA: Ribosomal ribonucleic acid; AAU: Acute anterior uveitis; AU: Anterior uveitis; HLA: Human leukocyte antigen; GM: Gut microbiota; VKH: Vogt Koyanagi Harada; FMF: Familial mediterranean fever; BS: Behcet’s syndrome; BD: Behcet disease; RAU: Recurrent aphthous ulcer; SRB: Sulfate-reducing bacteria; RAO: Retinal artery occlusion; TMAO: Trimethylamine-N-oxide; AMD: Age related macular degeneration; nAMD: Neovascular Age related macular degeneration; DR: Diabetic retinopathy; PDR: Proliferative diabetic retinopathy; NDR: Non-proliferative diabetic retinopathy; ROP: Retinopathy of prematurity; POAG: Primary open angle glaucoma; RNFL: Retinal nerve fiber layer; FK: Fungal keratitis; BK: Bacterial keratitis; SDE: Sjogren associated dry eye; SS: Sjogren syndrome; DES: Dry eye syndrome; FMT: Fecal microbiota transplant; RCT: Randomized controlled trial; GO: Graves’ orbitopathy; GD: Graves’ disease; IAA: Indole-3- acetic acid; TRAb: Thyrotropin receptor antibody; ILA: Lndole-3-lactate; IPA: Indole propionic acid; TAO: Thyroid associated orbitopathy.

Table 2 Quality of evidence of studies examined

Ref.	Type of study	Quality of evidence (NIH tool for observational studies) (ROBINS-I for non-randomized trial) (ROB2 for RCT)
Jayasudha et al[38], 2019	Case-control	8
Kalyana Chakravarthy et al[39], 2018	Case-control	6
Huang et al[40], 2018	Case-control	8
Morandi et al[41], 2024	Case-control	8
Wang et al[42], 2023	Case-control	8
Ye et al[43], 2020	Case-control	8
Tecer et al[44], 2020	Case-control	8
Kim et al[45], 2021	Case-control	8
Yasar Bilge et al[46], 2020	Cohort	9
Ye et al[47], 2018	Case-control	8
Zysset-Burri et al[48], 2019	Case-control	8
Zhang et al[49], 2023	Case-control	8
Zysset-Burri et al[50], 2020	Case-control	8
Xue et al[51], 2023	Case-control	6
Huang et al[52], 2021	Cross-sectional	8
Moubayed et al[53], 2019	Case-control	8
Ye et al[54], 2021	Case-control	8
Das et al[55], 2021	Case-control	8
Jayasudha et al[56], 2020	Cohort study	9
Khan et al[57], 2021	Case-control	8
Omar et al[58], 2024	Cohort	8
Sun et al[59], 2024	Case-control	8
Skondra et al[60], 2021	Cross-sectional	8
Chang et al[61], 2024	Case-control	7
Berkowitz et al[62], 2022	Case-control	8
Gong et al[63], 2020	Case-control	8
Kalyana Chakravarthy et al[64], 2018	Case-control	8
Jayasudha et al[65], 2018	Case-control	8
Mendez et al[66], 2020	Case-control	8
Moon et al[67], 2020	Case-control	8
Watane et al[68], 2021	Non-randomized clinical trial	Low risk of bias
Filippelli et al[69], 2021	Randomized control Trial	Low risk of bias
Filippelli et al[70], 2022	Randomized control trial	Low risk of bias
Yang et al[71], 2024	Case-control	8
Zhang et al[72], 2024	Case-control	8
Zhang et al[73], 2023	Case-control	8

RCT: Randomized controlled trial; NIH: National institutes of health; ROB2: Revised Cochrane Risk-of-Bias Tool for Randomized Trials; ROBINS-I: Risk of Bias in Non-Randomized Studies-of Interventions.

Table 3 Microorganisms highlighted in dysbiosis of ocular diseases

Ocular disease category	Implicated micro-organisms increase	Implicated micro-organisms decrease
Uveitis	Malassezia, Candida, Candida, Aspergillus gracilis	Faecalibacterium, Lachnospira, Ruminococcus, Bacteroides
Behcet’s syndrome	Veillonellaceae, Succinivibrionaceae	Bacteroidaceae
Vogt-Koyanagi-Harada syndrome	Ramularia, Alternaria and Rhizophagus, Alistipes	Methanoculleus, Candidatus Methanomethylophilus and Azospirillum Dorea
Retinal artery occlusion	Actinobacter, Bifidobacterium, Bacteroides, Faecalibacterium
Age related macular degeneration	Ruminococcus, Oscillibacter, Anaerotruncus, Eubacterium
Diabetic retinopathy	Bacteriodes, Bifidobacterium, Burkholderiaceae	Firmicutes, Actinobacteria, Faecalibacterium, Clostridium, Escherichia Shigella, Coriobacteriaceae, Veillonellaceae, Streptococcaceae
Myopia	Bifidobacterium, Bacteroides, Megamonas, Faecalibacterium, Coprococcus, Dorea, Roseburia, and Blautia
Retinopathy of prematurity	Enterobacteriaceae
Idiopathic intracranial hypertension		Lactobacillus, Atopobium, Megamonas, Ruminococcus, Streptococcus
Glaucoma	Prevotellaceae, Enterobacteriaceae, Escherichia coli	Megamonas, Bacterioides
Fungal keratitis		Bifidobacterium, Lactospira, Faecalibacterium, Lachnospira, Ruminococcus, Mitsuokella, Megasphera and Lachnospiraceae
Bacterial keratitis		Dialister, Megasphaera, Faecalibacterium, Lachnospira, Ruminococcus, Mitsuokella, Firmicutes, Veillonellaceae, Ruminococcaceae and Lachnospiraceae
Sjögren syndrome	Bacteriodetes, Alistipes, Streptococcus, Prevotella, Odoribacter, Actinomycetaceae, Eggerthellaceae, Lactobacillaceae, Akkermanciaceae, Coriobacteriaceae, and Eubacteriaceae	Faecalibacterium, Prevotella, and Ruminococcus, Actinobacteria, Bifidobacterium, Dorea, Agathobacter
Grave’s disease	Firmicutes, Bacteroidetes, Proteobacteria, Bacteroides, Ruminococcus gnavus