探讨原发性中重度干眼(DED)患者肠道菌群结构特征及其与眼表功能参数的相关性。

收集2024年5月至2025年9月在包头医学院第二附属医院眼科就诊的中重度DED患者30例(30只眼)和同期招募年龄和性别匹配的健康对照者30例(30只眼)为研究对象。其中，DED患者男性15例(15只眼)，女性15例(15只眼)；年龄22~67岁，平均年龄(41.5±14.3)岁。对照者男性15例(15只眼)，女性15例(15只眼)；年龄20~69岁，平均年龄(42.5±16.5)岁。收集所有受试者眼表疾病指数(OSDI)问卷，采用眼表综合分析仪检测非侵入性首次泪膜破裂时间(NIBUT-f)、非侵入性平均泪膜破裂时间(NIBUT-av)、泪河高度(TMH)及眼结膜潮红分析，完成Schirmer Ⅰ试验。采集受试者粪便样本，用16S核糖体核糖核酸基因高通量测序技术分析肠道菌群的Alpha多样性、Beta多样性及物种组成差异。OSDI评分、NIBUT-av、TMH及Schirmer Ⅰ值符合正态分布的计量资料以±s表示，组间比较采用独立样本t检验；不符合正态分布的用[M(P25，P75)]表示，组间比较采用Mann-Whitney U检验；计数资料以率(%)表示，组间比较采用χ²检验。两组肠道菌群整体结构采用非参数多元方差分析；采用Spearman秩相关分析和线性回归模型分析差异菌属丰度与眼表临床指标的相关性。

两组年龄、性别分布差异无统计学意义(t＝-0.25，χ²＝0.00，P>0.05)。DED患者OSDI评分、眼结膜潮红分析、NIBUT-f、NIBUT-av、TMH及Schirmer I试验值分别为(44.93±6.11)分、(2.75±0.53)分、(3.70±0.64)s、(6.34±0.54)s、(0.10±0.03)mm及(3.61±1.93)mm/5 min；对照者分别为(10.76±5.50)分、(1.60±0.51)分、(13.74±1.55)s、(16.73±0.69)s、(0.26±0.04)mm及(13.45±1.32)mm/5 min，组间比较的差异均有统计学意义(t＝22.76，8.52，32.76，64.81，17.29，23.02；P<0.05)。经Alpha多样性分析，DED患者Chao1指数为91(71~107)，Shannon指数为2.61(2.37~3.06)；对照者分别为160(149.5~170)和3.41(3.25~3.73)，两组Chao1指数与Shannon指数比较的差异均具有统计学意义(Z＝-6.34，-5.87；P<0.05)。基于Bray-Curtis距离矩阵的主坐标分析，DED患者与对照者样本在空间分布上形成各自独立的聚类簇，组间菌群结构界限清晰。第一主坐标可解释总变异度的30.4%，第二主坐标可解释总变异度的11.8%。经非参数多元方差分析，两组肠道菌群整体结构差异有统计学意义(R²＝0.267，P<0.05)。经门水平物种组成分析，两组受试者肠道菌群均以厚壁菌门和拟杆菌门为核心优势菌门。DED患者和对照者变形菌门和厚壁菌门相对丰度分别为20.2%、2.1%、49.8%及68.2%，差异有统计学意义(t＝5.01，3.48；P<0.05)。目和科水平分析，变形菌门丰度升高主要由肠杆菌目和肠杆菌科丰度显著增加导致。DED患者和对照者肠杆菌科和拟杆菌科相对丰度分别为17.7%、0.7%、24.9%及12.5%，差异有统计学意义(t＝4.66，3.48；P<0.05)。DED患者和对照者厚壁菌门下瘤胃球菌科丰度分别为10.2%和27.1%，差异有统计学意义(t＝6.62，P<0.05)。属水平分析，DED患者和对照者拟杆菌属、副拟杆菌属及粪杆菌属相对丰度分别为26.4%、1.5%、12.9%、0.4%、7.6%及23.8%，差异有统计学意义(t＝3.57，3.81，7.47；P<0.05)。种水平分析，大肠埃希菌、普通拟杆菌是两组菌群结构差异的关键菌种，丰度分别为15.8%、3.3%、0.02%及0.3%，差异有统计学意义(t＝4.53，4.47；P<0.05)。而DED患者和对照者产短链脂肪酸相关的普氏粪杆菌相对丰度分别为3.9%和8.8%，差异有统计学意义(t＝3.45，P<0.05)。Spearman秩相关分析与线性回归分析，主观症状方面，丁酸单胞菌属和粪杆菌属相对丰度与OSDI评分负相关且有统计学意义(r＝-0.75，-0.60；P<0.05)；副拟杆菌属相对丰度与OSDI评分正相关且有统计学意义(r＝0.50，P<0.05)。客观眼表指标方面，普雷沃氏菌科相对丰度与NIBUT-av正相关且有统计学意义(r＝0.78, P<0.05);丁酸单胞菌属相对丰度与TMH正相关(r＝0.67，P<0.05)；普雷沃氏菌科相对丰度与Schirmer Ⅰ值正相关且有统计学意义(r＝0.77，P<0.05)。对照者多数样本以厚壁菌门为主要优势菌门，DED患者厚壁菌门相对丰度下降。同时，DED患者变形菌门相对丰度高于对照者。DED患者患者肠道菌群结构偏移，以变形菌门增多和厚壁菌门减少为特征的菌群结构紊乱。DED患者拟杆菌属和副拟杆菌属等潜在致病菌数量增多，而粪杆菌属和瘤胃球菌属等产短链脂肪酸等有益菌大量减少。

原发性中重度DED患者存在显著的肠道菌群失调，核心特征为条件致病菌相对丰度升高，产丁酸盐等有益菌丰度降低；特定肠道菌群结构改变与患者眼表主观症状加重、泪膜稳定性下降及泪液分泌减少密切相关，调节肠道菌群平衡有望成为DED干预的潜在新靶点。

The aim of this study is to investigate the structural characteristics of gut microbiota in patients with primary moderate-to-severe dry eye disease (DED) and analyze their correlation with ocular surface functional parameters.

A total of 30 patients (30 eyes) with moderate-to-severe DED who attended the Department of Ophthalmology of the Second Affiliated Hospital of Baotou Medical College from May 2024 to September 2025, and 30 age-and gender-matched healthy controls (30 eyes) recruited during the same period were enrolled. Among the DED patients, there were 15 males (15 eyes) and 15 females (15 eyes), aged 22 to 67 years, with a mean age of (41.5±14.3) years. Among the controls, there were 15 males (15 eyes) and 15 females (15 eyes) with a mean age of (42.5±16.5) years (ranging from 20 to 69 years). The ocular surface disease index (OSDI) questionnaires were collected from all subjects. Non-invasive tear break-up time (NIBUT-f), non-invasive average break-up time (NIBUT-av), tear meniscus height (TMH), and conjunctival redness were measured using an ocular surface comprehensive analyzer, and the Schirmer Ⅰ test was performed. Fecal samples were collected, and 16S ribosomal RNA gene high-throughput sequencing was used to analyze the Alpha diversity, Beta diversity, and species composition of gut microbiota. Measurement data conforming to normal distribution, including OSDI score, NIBUT-av, TMH, and Schirmer Ⅰ test values, were expressed as ±s, with comparisons between groups performed using the independent samples t-test. Measurement data not conforming to normal distribution were expressed as [M(P25, P75)], with comparisons between groups performed using the Mann-Whitney U test. Count data were expressed as rates (%), with comparisons between groups performed using the χ² test. The overall structure of gut microbiota between the two groups was analyzed using permutational multivariate analysis of variance. Spearman′s rank correlation analysis and linear regression models were applied to explore the associations between the relative abundance of differential bacterial genera and ocular surface clinical parameters.

No statistically significant differences were observed between the two groups in age or gender distribution (t=-0.25, χ²=0.00, P>0.05). The OSDI score, conjunctival redness score, NIBUT-f, NIBUT-av, TMH, and Schirmer I test values in the DED group were (44.93±6.11) points, (2.75±0.53) points, (3.70±0.64) s, (6.34±0.54) s, (0.10±0.03) mm, and (3.61±1.93) mm/5 min, respectively, while those in the control group were (10.76±5.50) points, (1.60±0.51) points, (13.74±1.55) s, (16.73±0.69) s, (0.26±0.04) mm, and (13.45±1.32) mm/5 min, respectively, with statistically significant differences between the two groups (t=22.76, 8.52, 32.76, 64.81, 17.29, 23.02; P<0.05). Alpha diversity analysis showed that the Chao1 index reflecting species richness and the Shannon index reflecting species diversity in the DED group were 91 (71 to 107) and 2.61 (2.37 to 3.06), respectively, while those in the control group were 160 (149.5 to 170) and 3.41 (3.25 to 3.73), respectively, with statistically significant differences between the two groups (Z=-6.34, -5.87; P<0.05). Principal coordinate analysis based on the Bray-Curtis distance matrix revealed that the DED group and control group samples formed distinct independent clusters in spatial distribution, with a clear boundary in the intergroup microbial community structure. The first principal coordinate explained 30.4% of the total variance, and the second principal coordinate explained 11.8% of the total variance. Permutational multivariate analysis of variance showed a statistically significant difference in the overall gut microbiota structure between the two groups (R²=0.267, P<0.05). At the phylum level, the gut microbiota of both groups was dominated by Firmicutes and Bacteroidetes. The relative abundances of Proteobacteria and Firmicutes in the DED group and control group were 20.2% vs 2.1% and 49.8% vs 68.2%, respectively, with statistically significant differences (t=5.01, 3.48; P<0.05). At the order and family levels, the increase in Proteobacteria abundance was mainly driven by the significant elevation of Enterobacterales and Enterobacteriaceae. The relative abundances of Enterobacteriaceae and Bacteroidaceae in the DED group and control group were 17.7% vs 0.7% and 24.9% vs 12.5%, respectively, with statistically significant differences (t=4.66, 3.48; P<0.05). The abundance of Ruminococcaceae under Firmicutes in the DED group and control group was 10.2% and 27.1%, respectively, with a statistically significant difference (t=6.62, P<0.05). At the genus level, the relative abundances of Bacteroides, Parabacteroides, and Faecalibacterium in the DED group and control group were 26.4% vs 1.5%, 12.9% vs 0.4%, and 7.6% vs 23.8%, respectively, with statistically significant differences (t=3.57, 3.81, 7.47; P<0.05). At the species level, Escherichia coli and Bacteroides vulgatus were identified as the key species driving the structural differences between the two groups, with abundances of 15.8% vs 3.3% and 0.02% vs 0.3%, respectively, showing statistically significant differences (t=4.53, 4.47; P<0.05). The relative abundance of short-chain fatty acid-producing Faecalibacterium prausnitzii in the DED group and control group was 3.9% and 8.8%, respectively, with a statistically significant difference (t=3.45, P<0.05). Spearman rank correlation analysis and linear regression analysis revealed that, in terms of subjective symptoms, the relative abundances of Butyricimonas and Faecalibacterium were significantly negatively correlated with the OSDI score (r=-0.75, -0.60; P<0.05); the relative abundance of Parabacteroides was significantly positively correlated with the OSDI score (r=0.50, P<0.05). Regarding objective ocular surface parameters, the relative abundance of Prevotellaceae was significantly positively correlated with NIBUT-av (r=0.78, P<0.05); the relative abundance of Butyricimonas was significantly positively correlated with TMH (r=0.67, P<0.05); and the relative abundance of Prevotellaceae was significantly positively correlated with Schirmer I test values (r=0.77, P<0.05). In most control subjects, Firmicutes was the dominant phylum, while its relative abundance decreased in the DED group. Meanwhile, the relative abundance of Proteobacteria in the DED group was higher than that in the control group. The gut microbiota structure of DED patients showed a shift, characterized by increased Proteobacteria and decreased Firmicutes. The abundances of potential opportunistic pathogens such as Bacteroides and Parabacteroides were increased in the DED group, while beneficial bacteria such as Faecalibacterium and Ruminococcus, which produce short-chain fatty acids, were markedly reduced.

Patients with primary moderate-to-severe DED exhibit significant gut microbiota dysbiosis, characterized by increased relative abundance of opportunistic pathogens and decreased abundance of beneficial bacteria such as butyrate-producing genera. The alterations in specific gut microbiota are closely associated with the exacerbation of subjective ocular surface symptoms, decreased tear film stability, and reduced tear secretion. Modulating gut microbiota balance may emerge as a potential novel target for DED intervention.