June 2023
Volume 12, Issue 6
Open Access
Cornea & External Disease  |   June 2023
Differentially Expressed Tear Proteins in Sjögren's Syndrome Keratoconjunctivitis Sicca
Author Affiliations & Notes
  • Stephen P. Yoon
    Ocular Surface Center, Department of Ophthalmology, Cullen Eye Institute, Baylor College of Medicine, Houston, TX, USA
  • Zhiyuan Yu
    Ocular Surface Center, Department of Ophthalmology, Cullen Eye Institute, Baylor College of Medicine, Houston, TX, USA
  • Stephen C. Pflugfelder
    Ocular Surface Center, Department of Ophthalmology, Cullen Eye Institute, Baylor College of Medicine, Houston, TX, USA
  • Cintia S. de Paiva
    Ocular Surface Center, Department of Ophthalmology, Cullen Eye Institute, Baylor College of Medicine, Houston, TX, USA
  • Correspondence: Cintia S. de Paiva, Department of Ophthalmology, Baylor College of Medicine, 6565 Fannin Street, NC505G, Houston, TX 77030, USA. e-mail: cintiadp@bcm.edu 
Translational Vision Science & Technology June 2023, Vol.12, 8. doi:https://doi.org/10.1167/tvst.12.6.8
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      Stephen P. Yoon, Zhiyuan Yu, Stephen C. Pflugfelder, Cintia S. de Paiva; Differentially Expressed Tear Proteins in Sjögren's Syndrome Keratoconjunctivitis Sicca. Trans. Vis. Sci. Tech. 2023;12(6):8. https://doi.org/10.1167/tvst.12.6.8.

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Abstract

Purpose: The purpose of this study was to determine if there are significant differences in the concentrations of tear proteins in Sjögren's syndrome keratoconjunctivitis sicca (SS KCS) compared to healthy controls.

Methods: Tear samples were collected with unmarked Schirmer strips from 15 patients with SS KCS and 21 healthy controls. Tear protein was eluted and the concentration measured. Inflammatory mediators were assayed with a Raybiotech L-507 glass slide array and normalized by strip wetting length. All patients underwent an ocular surface exam to evaluate tear break-up time (TBUT), corneal fluorescein (CF) staining, and conjunctival (CJ) staining. The symptom assessment questionnaire in dry eye (SANDE) scores were collected for all patients.

Results: Two hundred fifty-three of the 507 tear proteins analyzed were significantly different in patients with SS compared to controls. Two hundred forty-one if the proteins were upregulated and 12 were downregulated. One hundred eighty-one differentially expressed proteins were significantly correlated with all four clinical parameters: TBUT, CF staining, CJ staining, and SANDE score.

Conclusions: These findings indicate that hundreds of factors can be assayed in tear proteins collected from a Schirmer strip. The results suggest tear protein concentrations are altered in patients with SS KCS compared to controls. The upregulated tear proteins correlated with clinical measures of dry eye symptoms and disease severity.

Translational Relevance: Tear proteins could serve as important biomarkers for studying pathogenesis and in clinical diagnosis and management of SS KCS.

Introduction
Sjögren's syndrome (SS) is an autoimmune disease affecting the exocrine lacrimal and salivary glands, which can lead to keratoconjunctivitis sicca (KCS) and xerostomia. Changes in tear composition combined with systemic factors contribute to an inflammatory cycle and ocular surface disease.1 The activation of stress signaling pathways from desiccation triggers the production of inflammatory mediators, inflammatory cell recruitment, dendritic cell (DC) maturation, and the activation of an adaptive T-cell mediated response.2 
Current methods of diagnosis for KCS focus on measures of eye irritation using symptom questionnaires and ocular surface dye staining. Patients with aqueous deficient dry eye typically have increased scores on symptom questionnaires (such as the Symptom Assessment Questionnaire in Dry Eye [SANDE]), corneal fluorescein (CF) staining, and conjunctival (CJ) lissamine green staining, and decreased tear break-up times (TBUT).3 Identifying disease-relevant biomarkers in SS KCS could improve diagnostic sensitivity, specificity, and classification, and identify disease relevant therapeutic targets. 
The mechanism(s) driving the pathophysiology of SS KCS are not completely understood. Genetic and proteomic analysis in SS may help identify key immune mediators involved in the pathogenesis of KCS and therapeutic targets. Our group has previously identified differentially expressed gene (DEG) pathways as possible biomarkers in SS KCS in cells obtained via conjunctival impression cytology.4 These DEG biomarkers correlated with clinical markers for dry eye. In addition to changes in the conjunctiva, tear proteomic analysis in SS has shown dysregulated expression of proteins involved in inflammation, immunity, and oxidative stress.5 Schirmer strips are widely available in clinical settings and provide an accessible method to sample tear fluid in patients with SS KCS for proteomics analysis. The purpose of this study was to compare levels of immune-related tear proteins of healthy subjects and patients with SS KCS collected by Schirmer strips using the RayBiotech L507 proteomic array. 
Methods
Patients
The study was conducted in accordance with the Declaration of Helsinki, and the Baylor College of Medicine Institutional Review Board approved the protocol (H-8920) and the subjects provided informed consent forms before study initiation. Written informed consent was obtained from all participants after explaining the purpose and possible consequences of the study. Female control subjects and patients with SS were enrolled in the study from January 2019 to January 2021. Patients with SS were recruited from the multispecialty SS clinic at Baylor College of Medicine (BCM) and had a complete ocular, oral, and rheumatologic evaluation, including a panel of serum autoantibodies, and met the proposed American College of Rheumatology/ European League Against Rheumatism diagnostic criteria for SS.6 
Healthy control subjects had no eye irritation, a TBUT ≥7 seconds, Schirmer 1 ≥10 mm, CF score ≤2, CJ score ≤2, and no meibomian gland disease. Subjects were excluded if they had prior laser-assisted in situ keratomileusis or corneal transplantation surgery, cataract surgery in the past year, punctal occlusion with plugs or cautery, a history of contact lens wear, use of topical medications other than preservative-free artificial tears, or chronic use of systemic medications known to reduce tear production. They were instructed not to instill any eye drops on the day of the evaluation. 
The SANDE and Ocular Surface Disease Index (OSDI) symptom questionnaires, fluorescein TBUT, Schirmer I test, cornea fluorescein and conjunctival lissamine green dye staining, and tear meniscus height measurement using optical coherence tomography (OCT) were performed as previously described.7,8 The ocular surface clinical parameters were all measured by the same observer (author S.C.P.). Dry Eye Workshop (DEWS) criteria were used to grade clinical severity.9 All patients with SS KCS had a severity score ≥2.5, and healthy controls had a severity score = 0. 
Tear Collection, Protein Extraction, and Protein Array
Tears were collected from healthy and SS subjects with unmarked Schirmer strips (Haag-Streit; Harlow Essex, GB) before any drops or dyes were instilled in the eye. Strips were removed after 5 minutes; the wetting length was recorded and the unwet portion of the strip was removed. The wet portion of the strip was placed in a 1 mL screw top tube (Sarstedt, Nümbrecht, AG) and frozen at −80°C until processing. To extract the proteins, the Schirmer membranes were thawed and cut into tiny pieces. A sufficient volume of lysis buffer (0.05% Tween-20) was added to cover all pieces in a 1.5 mL tube and it was shaken at room temperature (RT) for 2 hours, at which time the samples were centrifuged at 14,000 rpm for 10 minutes, all of the supernatants were transferred to another clear tube, protein concentration was measured using a micro BCA protein assay kit (Thermo Fisher, catalog #23235) and stored at −80°C for further analysis until shipping to RayBiotech (Atlanta, GA, USA) where an L507 proteomic slide array was performed. The same concentration of protein (20 ug) for each sample was added to an L507 slide array and the fluorescent signal was captured and quantified using a fluorescent reader. Standards for each protein, as well as blank wells were included. The signal intensities of biomarkers were re-normalized by wetting length on the strips with an assumption that all the strips were rinsed with the same amount of buffer/solution. Specifically, the product of wetting length and the volume of solution used in labeling process were calculated, and then all the products were divided by the maximum values. The array contains capture antibodies to 507 proteins, composed of cytokines, chemokines, growth factors, adipokines, receptors, angiogenic factors, proteases, soluble adhesion molecules, and structural/other proteins. The specificity of the antibodies used in this array have been validated and this platform has been used in numerous studies to detect proteins in biological fluids.1013 The detection sensitivity of the different targets ranges from 1 to 1000 pg/mL, with coefficients of variation <10% among replicate spots (http://www.raybiotech.com/resources.html). 
Data Analysis
All the analyses were conducted in the R programming language version 3.6.3 (R Core Team 2017). 
The log2 transformed biomarker signal intensities were first centered and scaled by subtracting the mean of each biomarker from the data and then dividing it by the standard deviation. Centering and scaling results in a uniform mean and scale across all the biomarkers but leaves their distribution unchanged. 
The fold change between groups was calculated as the ratio of the median of the SS group divided by the median of the control group. The signed-ranked test was used to assess whether the biomarker expression difference was significant between the control group and the SS group. Biomarkers with adjusted P values < 0.05 using the Benjamini-Hochberg method were considered differentially expressed. 
Nonparametric Spearman correlations using GraphPad Prism version 9.0 (GraphPad Inc.) investigated the correlations among SANDE, TBUT, corneal and conjunctival staining scores, and tear protein biomarkers. 
Qiagen Ingenuity Pathway Analysis
First, differentially expressed markers from tear array data were uploaded into QIAGEN's Ingenuity Pathway Analysis (IPA) system for core analysis. Analysis was performed with an experimental false discovery rate of >0.05. Comparison analysis tools were used to identify the most relevant canonical pathways enriched in SS. Second, we compared canonical pathways between tear proteins and conjunctival mRNA using our previously published gene data.4 A heatmap comparing activation Z scores in canonical pathways between the tear proteins and conjunctival mRNA was constructed using GraphPad Prism. 
Results
Patient Demographic Features
Fifteen patients with SS KCS and 21 age and sex matched control subjects were enrolled from January 2019 to January 2021 (Table 1). The control subjects had minimal eye irritation symptoms and no clinical signs of KCS, whereas patients with SS had symptoms and clinical signs of KCS. Statistical comparison of OSDI and SANDE scores, tear meniscus height, TBUT, and corneal and conjunctival staining scores between controls and patients with SS KCS are shown in Table 2
Table 1.
 
Demographic and Clinical Characteristics of Patients With SS KCS Versus Healthy Controls
Table 1.
 
Demographic and Clinical Characteristics of Patients With SS KCS Versus Healthy Controls
Table 2.
 
Top 20 Upregulated and Top 10 Downregulated Tear Proteins in Sjögren Syndrome Keratoconjunctivitis Sicca Compared to Controls
Table 2.
 
Top 20 Upregulated and Top 10 Downregulated Tear Proteins in Sjögren Syndrome Keratoconjunctivitis Sicca Compared to Controls
Protein Expression Analysis
Out of the 503 tear protein biomarkers, 253 proteins were significantly modulated in SS KCS compared to controls. A total of 241 proteins were upregulated and 12 were downregulated, as displayed in the volcano plot (Fig. 1). Significance was plotted against fold change (log2 values) using a -log10 of the adjusted P value for each dot. The top 10 upregulated differentially expressed proteins and top 10 downregulated differentially expressed proteins are listed in Table 3
Figure 1.
 
Volcano plot shows −log10 (P value) and Log 2-fold change in gene expression in patients with SS-KCS compared to healthy control subjects (fold increase >1.3 or fold decrease <0.7 and P adjusted value of 0.05).
Figure 1.
 
Volcano plot shows −log10 (P value) and Log 2-fold change in gene expression in patients with SS-KCS compared to healthy control subjects (fold increase >1.3 or fold decrease <0.7 and P adjusted value of 0.05).
Table 3.
 
Spearman Correlation R-Values Between Top 10 Upregulated and Downregulated Tear Proteins and Tear Break-Up Time (TBUT), Corneal Fluorescein (CF) Staining, Conjunctival (CJ) Staining, and SANDE Scores
Table 3.
 
Spearman Correlation R-Values Between Top 10 Upregulated and Downregulated Tear Proteins and Tear Break-Up Time (TBUT), Corneal Fluorescein (CF) Staining, Conjunctival (CJ) Staining, and SANDE Scores
Correlation of Differentially Expressed Proteins with Clinical Markers
Spearman correlation analysis was performed among tear protein biomarker concentrations versus TBUT, CF staining, CJ staining, and SANDE scores. From the 253 differentially expressed tear proteins, 181 were significantly correlated with all 4 clinical markers (TBUT, CF staining, CJ staining, and SANDE) while meeting the threshold for R > 0.4 or R < −0.4. Spearman correlation values for the top 10 upregulated differentially expressed proteins, and top 10 downregulated differentially expressed proteins are listed in Table 3. Significantly correlated upregulated proteins had an inverse correlation to TBUT and a direct correlation to CF staining, CJ staining, and SANDE scores. Conversely, significantly correlated downregulated proteins were directly correlated to TBUT whereas indirectly correlated to CF staining, CJ staining, and SANDE scores. 
Representative Spearman correlation graphs for WIF-1 and Bax are shown in Figures 2 and 3. WIF-1 was inversely correlated with TBUT and directly correlated with CF staining, CJ staining, and SANDE scores. Bax had a direct correlation to TBUT and an inverse correlation with OSDI, TBUT, and conjunctival staining scores. A complete list of correlation R and P values for each tear film protein biomarker can be found in Supplementary Table S1
Figure 2.
 
Representative graph showing Spearman correlations of WIF-1 versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 2.
 
Representative graph showing Spearman correlations of WIF-1 versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 3.
 
Representative graph showing Spearman correlations of Bax versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 3.
 
Representative graph showing Spearman correlations of Bax versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Differential Pathway Analysis
The QIAGEN IPA tool was used to identify significantly modulated inflammatory signaling pathways in patients with SS KCS compared to controls. A comparison of the canonical pathways between tear proteins and conjunctival mRNA using our previously published gene data was performed.4 A heatmap displaying the Z-scores of upregulated and downregulated tear proteins and conjunctival mRNA in the canonical pathways is shown in Figure 4
Figure 4.
 
Heatmap comparing Z scores from the most relevant canonical pathways generated by Qiagen Ingenuity Pathway Analysis in tear proteins versus previously published conjunctival mRNA analysis.
Figure 4.
 
Heatmap comparing Z scores from the most relevant canonical pathways generated by Qiagen Ingenuity Pathway Analysis in tear proteins versus previously published conjunctival mRNA analysis.
Among the topmost upregulated pathways, focal adhesion kinases (FAK) and IL-17 pathways were strongly upregulated at both protein and mRNA levels in patients with SS. FAK leads to the maturation of focal adhesions expressed by leukocytes infiltrating lacrimal glands.14 IL-17 signaling is strongly upregulated in the tear film of patients with SS KCS. IL-17 is a potent inflammatory cytokine that has been linked to the pathogenesis of SS. IL-17 blocking factor decreased lymphocytic infiltrations of salivary glands in mice that develop SS.15 IL-17 production by γδT cells, as well as IL-17 inducible mediators (matrix metalloproteases and SPRR2), are alsoimplicated in the development of dry eye disease.15 The B cell signaling pathway was significantly upregulated in both the tear protein and conjunctival mRNA samples. In SS, B cells are overstimulated and produce excess immunoglobins and autoantibodies. B effector cells also activate T cells through Th1 or Th2 differentiation.16 A mouse model of spontaneous autoimmunity mimicking SS found a higher frequency of autoreactivity and polyreactivity among B-cell clones as compared to wild type mice.17 NFκB is an established pro-inflammatory pathway in SS and was upregulated in both tear proteins and conjunctival mRNA. A mouse model of constitutively active NFκB displayed chronic keratitis with increased corneal expression of TNFα, IL-1β, and MMP-9.18 
The innate immune system plays an important role in the inflammatory cascade seen in SS KCS. The DC maturation pathway was upregulated in both tear proteins and conjunctival mRNA. Corneal DCs are antigen-presenting cells that induce T cell activation and an inflammatory cascade crucial in the pathogenesis of SS KCS. Patients with SS KCS were found to have higher corneal DC density, larger DC size, and larger DC field compared to non-SS dry eye subjects via confocal microscopy.19 The toll-like receptor (TLR) pathway was upregulated in tear proteins and conjunctival mRNA. TLR stimulation leads to type I interferon (IFN) activation, BAFF production, and the production of autoantibodies.20 
Two related pathways were downregulated in tear proteins and mRNA of patients with SS: peroxisome proliferator-activated receptor alpha (PPAR-α)/retinoic X receptor alpha (RXRα) and liver X receptor (LXR)/retinoic X receptor (RXR) pathways. RXRα suppresses the generation of dry eye disease-inducing IL-17 inducers (IL-23, IL-1β, and TNF-α) by myeloid cells and directly suppresses IL-17 production by activated γδ T cells.21 IL-17 promotes the disruption of the corneal barrier by decreasing epithelial lubricity, sealing goblet cell openings, and decreasing mucin-filled conjunctival goblet cells.21 LXR agonists were found to improve dry eye disease in a murine model by increasing zona occludens 1 immunoreactivity and preventing disruption of cellular tight junctions.22 
Our results indicate pro-inflammatory pathways are upregulated in SS KCS, whereas anti-inflammatory pathways protective against dry eye syndrome are downregulated both at protein and RNA levels. 
Discussion
Our study investigated the differences between patients with SS KCS and healthy controls through tear film protein analysis. Tear film samples were collected noninvasively with Schirmer strips that are readily available in clinical settings and are frequently used to measure tear secretion in patients with dry eye.23 Our study identified 253 differentially expressed tear proteins in patients with SS KCS compared to controls. This study builds on a previous study by our group that identified 53 differentially expressed genes in cells obtained from patients with SS KCS through noninvasive impression cytology of the conjunctiva.4 The results both support previous findings and provide new insights into the proteomic changes in SS KCS. Improved understanding of the pathogenesis of SS KCS will lead to better diagnostic and therapeutic modalities. 
Correlation analyses revealed that 181 of the differentially expressed proteins were significantly correlated with all four clinical parameters of dry eye disease: TBUT, CF staining, CJ staining, and SANDE score. Upregulated proteins were directly correlated with CF staining, CJ staining, and SANDE score, whereas being inversely correlated to TBUT. Downregulated proteins were inversely correlated with CF staining, CJ staining, and SANDE score, whereas being directly correlated to TBUT. Patients with SS KCS also had significantly decreased TBUT, increased CF staining, increased CJ staining, and SANDE score compared to controls.24 These significant correlations validate the clinical relevance of these biomarkers. 
The top-upregulated protein in our study was WNT Inhibitory Factor 1 (WIF-1). WIF-1 levels were significantly directly correlated with clinical parameters of dry eye disease (see Fig. 2). WIF-1 is an inhibitory factor for the Wnt/beta-catenin signaling pathway.25 The activation of the Wnt/beta-catenin pathway in DCs is important for tolerance to self-antigens and suppression of chronic autoimmune pathologies.26,27 In a mouse model for inflammatory bowel disease, DC-specific deletion of beta-catenin lead to severe colonic epithelial layer destruction and upregulation of Th1 and Th17 responses.28 Karatas et al. demonstrated that the Wnt/beta-catenin pathway may be altered in in the salivary glands of patients with SS.29 In the eyes, WIF-1 is preferentially expressed at the limbus where limbal epithelial stem cells (LESCs) reside.30 Naktasu et al. also showed Wnt2, Wnt6, Wnt11, Wnt16b, and 4 Wnt inhibitors (including WIF-1) were predominantly expressed in the limbal region.31 This suggests altered Wnt/beta-catenin signaling in SS KCS could lead to dysregulation of LESC and impaired corneal regeneration.32 
Bcl-2-associated X protein (Bax) was significantly downregulated in our study and had a significant inverse correlation with clinical markers of dry eye disease (see Fig. 3). Bax belongs to the BCL2 protein family and is a pro-apoptotic regulator.33 The ratio of Bax to BCL2 (anti-apoptotic regulator) determines survival or death of a cell following an apoptotic stimulus.34 Szodoray et al. showed patients with SS had a significantly upregulated percentage of Bcl-2 positive peripheral blood B cells, whereas a nonsignificant downregulation of Bax positive peripheral blood B cells when compared to controls.35 Ohlsson et al. showed expression of BCL-2 but rarely Bax in SS salivary gland infiltrating mononuclear cells.36 Kong et al. demonstrated increased BCL-2 expression in SS infiltrating mononuclear cells and ductal cells, which may have contributed to their increased survival.37 Downregulation of Bax may be leading to the dysregulation of the apoptotic pathway in proinflammatory cells in SS KCS. 
The IL-17 signaling pathway was significantly upregulated in patients with SS KCS compared to controls. Tear protein biomarkers IL-17C, IL-17RC, IL-17E, and IL-17D were significantly directly correlated with clinical markers of dry eye disease. IL-17 stimulates matrix metalloproteinase-9 (MMP-9) expression, which disrupts the tight junctions in the corneal epithelium.38 IL-17 is also involved in neutrophil recruitment and activation.39 Lee et al. showed IL-17 tear concentrations were higher in patients with SS KCS compared to non-SS dry eye patients and healthy control subjects via multiplex immunobead assay.40 Our previously reported study showed increased levels of Th-17 inducers in humans with dry eye syndrome, as well as increased MMP-9 and Th-17-associated genes in a murine model following desiccating stress.41 A different study by our group showed significantly higher tear concentrations of the IL-17 inducer IL-23 in a Pinkie mouse strain with loss of function RXRα mutation.21 RXRα was also found to be an important regulator of IL-17 production by γδT cells, which secrete large amounts of the pro-inflammatory cytokines.21,42 The RXRα pathway is significantly downregulated in the SS KCS tear samples in our study. 
In addition to upregulated T cell receptor signaling, the B cell signaling pathway was significantly upregulated in our study. CD40 ligand, CNTF, CSK, IL-3, IL-4, IL-11, IL-15, IL-21, TNSF4, TNSF8, and TNSF15 biomarkers were significantly directly correlated with clinical markers of dry eye disease. The role of B cell dysregulation in SS has been well established. In primary SS, there is a decrease in CD27+ memory B cells in the peripheral blood and an increase of these cells in the lacrimal and salivary glands.43 Increased levels of autoantibody-producing plasma cells within the affected glands have been associated with tissue destruction.44 
Innate immune signals including TLRs play an important role in activating the B cell signaling pathway. TLR1, TLR2, and TLR3 were among the top 10 significantly upregulated proteins in our study and were significantly directly correlated with clinical markers of dry eye disease. Kwok et al. demonstrated that increased expression of TLR2, TLR4, and TLR6 in the salivary glands of patients with SS induced the production of IL-23/IL-17 via IL-6, STAT3, and NF-κB signaling pathways.45 IL-17 increased the expression of TLR3 via the STAT3 pathway in subjects with rheumatoid arthritis.46 The STAT3 pathway was significantly upregulated in our study. STAT3 was constitutively activated in peripheral CD3(+) lymphocytes from patients with SS.47 TLR signaling also stimulates the production of IL-17, and IL-22.48 TLRs are expressed in innate immune cells, such as DCs and macrophages.49 DCs are considered the most efficient antigen-presenting cells, and the DC maturation pathway was significantly upregulated in our sample.50,51 DCs produce type-I IFN, which has a pivotal role in the pathogenesis of SS.52,53 
Pathway analysis of the tear proteins in this study was compared to a previous study performed by our group on differentially expressed genes in SS KCS using conjunctival impression cytology (see Fig. 4).4 There is strong agreement on the pathways upregulated and downregulated in both studies. Type I and type II IFN signaling, TLR signaling, B cell signaling pathway, DC maturation, PKR IFN induction, TREM1 signaling, and LPS/IL-1 mediated inhibition of RXR function were strongly activated in both studies. IL-2 receptor gamma is involved in cytokine signaling and was found to be upregulated and significantly directly correlated with clinical markers of dry eye disease in both the tear film and conjunctival mRNA. IL-4 in tear film proteins and IL-4 receptor in conjunctival mRNA are also involved in cytokine signaling and were found to be significantly directly correlated with clinical markers of dry eye disease. 
Type I and type II IFN signaling dysregulation leads to lymphocyte infiltration into exocrine glands, autoantibody production, and glandular cell apoptosis.54,55 IFN-alpha, IFN-beta, IFN-gamma, and IFN-gamma R1 biomarkers were significantly directly correlated with clinical markers of dry eye disease in tear proteins. The genes for these proteins were not tested in the conjunctival mRNA study. The HLA-A, HLA-B, IRF7, and STAT1 genes are involved in type I IFN and type II IFN signaling and were upregulated in SS KCS conjunctival mRNA.4 These were not tested in the tear film. Further studies are needed to evaluate these important proteins in the tear film. 
TLR signaling was significantly upregulated in the SS group for both tear film proteins and conjunctival mRNA. TLR1, TLR2, TLR3, and TLR4 were significantly upregulated in tear proteins but these were not tested in the conjunctival mRNA study. The DUSP4, IRF7, LY96, S100A8, S100A9, and STAT1 genes involved in TLR signaling were upregulated in the conjunctival mRNA study, but these were not tested in the tear film. Further studies including these important proteins in the tear film are needed. 
Interestingly, Bax was downregulated in the tear film but upregulated in the conjunctival mRNA. Bax is important in the apoptosis pathway. Kong et al.37 showed infiltrating mononuclear cells had higher BCL-2 in SS salivary glands, whereas acinar cells had higher Bax concentrations and underwent apoptosis. The expression of BCL-2 and Bax may differ depending on cell type. Increased Bax expression in conjunctival mRNA may point toward increased apoptosis of conjunctival goblet cells. On the other hand, decreased Bax in the tear film may be related to inflammatory cells in the tear film with reduced rates of apoptosis. Both tear film protein analysis and conjunctival impression cytology are noninvasive methods and may be useful in identifying new biomarkers for SS KCS. 
Our group previously studied reduced corneal innervation in CD25 null model of SS by quantifying genetic expression through corneal epithelial mRNA.56 The study found increased expression of genes regulating phagocytosis and autophagy (Beclin-1, Lc3, Lamp-1, Lamp-2, Cxcl1, and Bdnf). Bdnf was the only protein investigated in both the corneal epithelial mRNA and the tear film protein, but was not found to be significantly differently expressed in the tear film. There was increased expression of CXCL1 in both our conjunctival mRNA and corneal epithelial mRNA studies. Another study by our group provided evidence that IFN-gamma produced by CD4+ T cells played a role in corneal epithelial apoptosis in a murine model with features resembling SS.57 Desiccating stress leads to increased expression of caspase-3 and caspase-8 in corneal epithelial mRNA. Both IFN-gamma and IFN-gamma receptor had increased expression in tear films in our current study, but only IFN-gamma receptor was statistically significant. Further studies investigating caspases in the tear film of SS and BCL-2/Bax in corneal epithelial mRNA are needed. 
Limitations of the study include the relatively limited number of proteins evaluated in the RayBiotech L507 proteomic slide array. A larger sample size may have yielded even stronger correlations or may have uncovered additional biomarkers. Further studies are necessary to validate the differentially expressed proteins identified in this study. The results of this study are in agreement with previously published studies while identifying new potential biomarkers in SS KCS. The differentially expressed tear proteins correlated strongly with clinical parameters and show promise as potential therapeutic targets for SS KCS. 
Acknowledgments
All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 
Supported by the NIH/NEI EY026893 (C.S.d.P.), NIH EY11915 (S.C.P.), Research to Prevent Blindness (Department of Ophthalmology), The Hamill Foundation, The Sid Richardson Foundation, and the Mike Hogg Foundation (C.S.d.P.). 
The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. 
Meeting Presentations: This work was presented at The Association for Research in Vision and Ophthalmology Annual Meeting 2022 in Denver, Colorado, USA. 
Disclosure: S.P. Yoon, None; Z. Yu, None; S.C. Pflugfelder, Yuyu Pharma (F), F. Hoffmann-La Roche Ltd. (F), Bioaegis Therapeutics Inc. (F), and Aeries Pharmaceuticals Inc. (F); C.S. de Paiva, Spring Discoveries (C). S.C. Pflugfelder, Allergan (C), Dompe (C), Kala (C), Kowa (C), Novartis Pharma AG (C), and Senju (C). S.C. Pflugfelder, Dompe (F), Santen (F), and Yuyu Pharma (F) 
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Figure 1.
 
Volcano plot shows −log10 (P value) and Log 2-fold change in gene expression in patients with SS-KCS compared to healthy control subjects (fold increase >1.3 or fold decrease <0.7 and P adjusted value of 0.05).
Figure 1.
 
Volcano plot shows −log10 (P value) and Log 2-fold change in gene expression in patients with SS-KCS compared to healthy control subjects (fold increase >1.3 or fold decrease <0.7 and P adjusted value of 0.05).
Figure 2.
 
Representative graph showing Spearman correlations of WIF-1 versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 2.
 
Representative graph showing Spearman correlations of WIF-1 versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 3.
 
Representative graph showing Spearman correlations of Bax versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 3.
 
Representative graph showing Spearman correlations of Bax versus TBUT, corneal staining score, conjunctival staining score, and SANDE score.
Figure 4.
 
Heatmap comparing Z scores from the most relevant canonical pathways generated by Qiagen Ingenuity Pathway Analysis in tear proteins versus previously published conjunctival mRNA analysis.
Figure 4.
 
Heatmap comparing Z scores from the most relevant canonical pathways generated by Qiagen Ingenuity Pathway Analysis in tear proteins versus previously published conjunctival mRNA analysis.
Table 1.
 
Demographic and Clinical Characteristics of Patients With SS KCS Versus Healthy Controls
Table 1.
 
Demographic and Clinical Characteristics of Patients With SS KCS Versus Healthy Controls
Table 2.
 
Top 20 Upregulated and Top 10 Downregulated Tear Proteins in Sjögren Syndrome Keratoconjunctivitis Sicca Compared to Controls
Table 2.
 
Top 20 Upregulated and Top 10 Downregulated Tear Proteins in Sjögren Syndrome Keratoconjunctivitis Sicca Compared to Controls
Table 3.
 
Spearman Correlation R-Values Between Top 10 Upregulated and Downregulated Tear Proteins and Tear Break-Up Time (TBUT), Corneal Fluorescein (CF) Staining, Conjunctival (CJ) Staining, and SANDE Scores
Table 3.
 
Spearman Correlation R-Values Between Top 10 Upregulated and Downregulated Tear Proteins and Tear Break-Up Time (TBUT), Corneal Fluorescein (CF) Staining, Conjunctival (CJ) Staining, and SANDE Scores
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