We demonstrated that individuals with dry eye, both those that met full Sjögren’s criteria (SDE) and those that did not (NDE), had gut microbiome alterations compared to controls. In our study, we found that cases had more diverse phyla with disparate genera representation compared to controls. These changes were found not to be driven by age or by the presence of a comorbid autoimmune disease. The microbial changes within Controls, NDE, and SDE included a decrease in genera Faecalibacterium and Viellonella, classes Ruminococcaceae and Lachnospiraceae, and orders Clostridiales and Bacteroides, and an increase in the genera Megasphaera, Parabacteroides and Prevotella from controls to NDE, and then from NDE to SDE. Similar changes in microbial association and networks have been shown to alter virulence and metabolic behavior of microbes in other disease models [25-27] and hence, assumes added importance in the role of host-microbiota interactions in health and disease. In addition, we expanded our exploration of composition beyond diversity to evaluate clustering patterns in disease, noting differences between controls, NDE and SDE with respect to pattern and clustering due to relative perturbations in bacterial populations. These changes in community behavior align with biological context, which demonstrate that compositional changes in microbiota due to disease is not a singular change. Changes in relative abundance of microbial species results in the imposition of constraints on co-occurrence network(s), resulting in induction/expulsion of other species, or complete rearrangement of networks [6]. We also found that several bacterial classes correlated with DE symptoms and signs, suggesting that the gut microbiome may impact disease severity (indirectly assessed via severity of DE metrics).
Our findings demonstrate both similarities and differences compared to prior data in Sjögren’s. In a study of 10 individuals with Sjögren’s, greater relative abundances of Pseudobutyrivibrio, Escherichia/Shigella, Blautia and Streptococcus and lower abundances of Bacteroides, Parabacteroides, Faecalibacterium and Prevotella were noted compared to 45 healthy controls identified from the Human Microbiome Project [10]. Similar to our population, controls were significantly younger than cases (27 ± 5 years old vs 59 ± 14 years old). A common finding in both studies was the presence of dysbiosis in Sjögren’s compared to controls, albeit with differences in bacterial signatures. Both studies noted a decrease in relative abundance of Faecalibacterium and Bacteroides in Sjögren’s, but in our study, we saw an increase in relative abundance of Prevotella, a bacteria implicated in rheumatoid arthritis [28, 29]. Another difference was in phylogenetic diversity, in which we found increased diversity in individuals with Sjögren’s compared to controls whereas the former study found a significant inverse correlation between diversity and disease severity (r = −0.72, P = 0.01). Several differences must be considered when interpreting results between the two studies including differences in hypervariable region targets (V1-3 vs V4-5), curation status (2016 vs 2018) confidence interval (CI) of OTU database (97% vs 99%), controls (Human Microbiome Projects vs OpenBiome Stool Bank), geographical location (Texas vs Florida), and indices used (absolute OTU counts vs Faith’s PD). As a demonstration of how these differences can effect results, when we reanalyzed our data using the SILVA (v123) 97% CI database, the slight but significant increase in Faith’s PD in SDE vs controls was lost (Supplementary Figure 1). As Faith’s PD is a measure of number of nodes in a phylogenetic tree, it is understandable that values would change with a lower number of hits.
Our findings mirror changes noted in other autoimmune conditions, including ones related to Sjögren’s. Similar to our data, increased abundance of Actinobacteria [30], specifically Eggerthella and Actinomyces, Prevotellacopri [28], Lactobacillus [31], and decreased abundance of Faecalibacterium [30], Bacteroides [8], Lachnospiraceae [28], and Clostridiales [28] were reported in individuals with rheumatoid arthritis as compared to controls. Interestingly, some of these dysbiotic signatures normalized with anti-inflammatory therapy [32]. In a similar manner, Viellonella was reduced in ankylosing spondylitis [33], Ruminococcaceae was reduced in inflammatory bowel disease and psoriasis [26], and Megasphaera was increased in primary biliary cirrhosis [34], all mirroring our findings in Sjögren’s. Beyond composition and not tested herein, bacterial metabolites of individuals with autoimmune disease has been found to differ from controls. For example, individuals with Behçet’s had less butyrate production in their gut compared to controls [9]. A similar finding was indirectly noted in Sjögren’s with a 50% decrease in relative abundance of OTUs classified to the high butyrate producer Faecalibacterium prausnitzii compared to controls [10].
These dysbiotic signatures may have a causal role in SDE. Inflammation is a hallmark of DE in individuals with and without Sjögren’s [35, 36], and it is well-established that the gut microbiome has an impact on inflammation and immunity [6, 11-14]. The commensal gut microbiome monitors mucosal immunity through the generation of anti-inflammatory regulatory T cells (Treg cells) and pro-inflammatory Th17 cells. The balance between these cells protects the mucosa from pathogenic microorganisms and limits excessive T cell responses via key mediators, including TGF-B, IL-6, retinoic acid and SCFA. For example, specific Clostridia species have been found to specifically induce Th17 cells in the small intestine and in extraintestinal sites during autoimmune inflammation. Other Clostridia clusters have been shown to induce Tregs and produce SCFAs to support Treg development [37]. In a similar manner, Bacteroides species can express polysaccharide A which suppresses Th17 inflammatory responses, allowing mucosal tolerance and subsequent colonization [37]. Putting this in context of our findings, reductions in commensals such as Clostridiales and Bacteroides may have an impact on the balance of Th17 and Treg cells, tipping the body towards autoimmunity.
Specific to the eye, altering the intestinal microbiome has been shown to influence eye disease. For example, CD25 knock out (KO) mice spontaneously develop DE and thus serve as a model of SDE. Germ-free CD25KO mice had a worse DE phenotype compared to CD25KO control mice, including increased lacrimal gland inflammation and IFN-ϫ producing T cells. Interestingly, recolonization of the gut microbiome improved the DE phenotype, with decreased lacrimal gland inflammation, IFN-ϫ producing T cells and corneal staining [38]. Similar findings have been seen in other mice models. Desiccating stress applied to the ocular surface with a fan in germ-free mice led to corneal staining and ocular surface inflammation, resulting in a worse DE phenotype compared to conventionally house mice [39]. In another experiment, antibiotics administered in addition to desiccating stress reduced Bacteroidetes and Firmicutes and increased Proteobacteria in the gut and concomitantly caused a more severe DE phenotype compared to desiccating stress alone [40]. These experiments reinforce the idea of a gut-eye axis and highlight the possibility of gut microbiome modulation and a therapeutic approach in DE.
Our findings should be interpreted bearing in mind our study limitations, which included a small, heterogenous population. The rationale for including both individuals who met full Sjögren’s criteria and who did not is that Sjögren’s is often diagnosed late in the disease course as the traditional markers, SSA and SSB, become positive years after disease initiation, if at all [41]. As such, many individuals with DE that have a specific profile (aqueous tear deficiency, early marker positivity, DE in the setting of an established autoimmune disease such as rheumatoid arthritis) are considered as having Sjögren’s-like DE but do not fit the ACR criteria for disease. In this study, we were interested in understanding gut microbiome profiles in both groups, although we acknowledge that the NDE group likely has a more heterogeneous makeup. Fortunately, as evident from our PCA plot, data from our diverse patient population is driven into a tight cluster, suggesting significant disease-mediated microbial changes in both groups, compared to controls. However, findings from our study will need to be replicated and expanded in larger populations. In addition, we chose controls provided by a stool bank (Openbiome) so as to compare our population to a well-phenotyped, healthy control group, which differed significantly in age and varied in gender. An issue with contemporary controls (e.g. age-matched veterans) is that other co-morbidities may affect microbiome health. As such, we modeled our work on prior studies, in which a similar approach also resulted in an age difference between cases to controls [10]. While age related differences in the gut microbiome have been noted when comparing very young children to adults, it seems that microbiome stabilizes to an adult-like composition by age 5 [42, 43]. Another limitation is that diet and consumption of probiotics were not considered in our evaluation, which may affect the composition of individuals’ gut microbiome [44]. In addition, 16s rRNA sequencing method has limited genera coverage, which limits a detailed study of the microbiome. Finally, our study did not measure metabolic products of bacteria, such as butyrate, which would be indicative of the function of the microbiome.
Despite these limitations, our study findings are important as they set the foundation for modulating the gut microbiome as a potential therapeutic approach in DE. There are several ways to modulate the gut microbiome, including dietary intake, probiotics and fecal microbial transplantation (FMT). For example, FMT was used to modulate the gut microbiome in Graft Versus Host Disease (GVHD), another condition associated with DE. In four individuals with GVHD, FMT increased abundances of the beneficial bacteria Lactobacillus, Bacteroides, Bifidobacterium and Faecalibacterium, and concomitantly improved gastrointestinal symptoms such as defecation consistency and frequency [45]. Future studies are needed to translate these findings to Sjögren’s-associated DE.