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Review

Translating Biomarker Discovery: From Bench to Bedside in Dry Eye Disease

1
Pittsburgh Research Institute, Sewickley, PA 15143, USA
2
Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
3
Department of Biomedical Engineering, College of Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
4
Southwestern PA Eye Center, Corneal Services, Washington, PA 15301, USA
5
Eger Eye Group, Optometry, Coraopolis, PA 15108, USA
6
University of Pittsburgh Medical Center, Corneal Services, Pittsburgh, PA 15260, USA
7
Center for Proteomics & Artificial Intelligence, Allegheny Health Network Cancer Institute, Pittsburgh, PA 15212, USA
8
Center for Clinical Mass Spectrometry, Allegheny Health Network Cancer Institute, Pittsburgh, PA 15212, USA
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(17), 8556; https://doi.org/10.3390/ijms26178556
Submission received: 1 August 2025 / Revised: 23 August 2025 / Accepted: 29 August 2025 / Published: 3 September 2025
(This article belongs to the Special Issue Molecular Advances in Dry Eye Syndrome)

Abstract

Dry Eye Disease (DED) is a complex, multifaceted ocular disease characterized by tear film instability and inflammation. It can sometimes be elusive to identify the type of DED in patients, given the overlapping symptoms with other conditions like allergies and the multitude of stimuli that might trigger DED onset. There is also difficulty due to limitations on the diagnostic testing available to clinicians, as poor reliability and a lack of standardization plague accurate diagnoses. Identified biomarkers can help identify DED pathophysiology and category, and these include molecular biomarkers like matrix metalloproteinase-9 (MMP-9), cytokines, lactotransferrin, and lacritin, as well as functional biomarkers such as tear osmolarity. Diagnostic tools, such as the InflammaDry and I-Pen Tear Osmolarity System, also now allow for point-of-care measurement of select biomarkers, including MMP-9 and osmolarity. Nonetheless, there remains a critical need for additional, reliable, and accurate diagnostic devices to better aid in the diagnosis and management of DED. This review uniquely combines a review on the current understanding of various biomarkers with an overview of the emerging technologies available to healthcare providers, aiding in better-informed diagnosis and treatment of DED.

1. Introduction

Dry Eye Disease (DED) is a prevalent ocular condition characterized by tear film instability and ocular surface inflammation, ultimately leading to cellular damage, discomfort, and visual disturbances [1]. The tear film, comprising an aqueous, lipid, and mucin layer, is essential to ocular surface health and visual acuity. Tear film instability can arise via several mechanisms, including reduced tear production, excessive tear evaporation, and changes in mucin secretion [2]. Often, individuals experiencing tear film instability experience a mixture of underlying etiologies. Contributors to tear film instability include systemic conditions (e.g., autoimmune disorders), environmental factors (e.g., digital eye strain, air pollution), lifestyle choices (e.g., poor nutrition, contact lens use), and geographic influences (e.g., low humidity, high altitude) [1]. Due to the multifaceted nature of DED, diagnosis remains challenging, especially because DED symptoms often overlap with other ocular conditions and can vary in clinical presentations. Molecular biomarkers have emerged as a reliable and objective metric for the diagnosis and screening of DED. These markers also provide new insights into inflammatory pathways, lacrimal gland dysfunction, and tear film dynamics. This review synthesizes current knowledge on DED molecular biomarkers, focusing on their role in advancing mechanistic understanding. An improved understanding of DED-relevant biomarkers and how to best use the tools currently available to quantify these biomarkers will aid in advancing more accurate diagnosis of DED in patients, leading to treatment specific to DED subtype and improved outcomes in the future.

2. Pathophysiology of DED

DED is complex, often driven by a combination of underlying mechanisms. Often, tear instability presents as the central initiating event, beginning with a breakdown in tear film. This is caused either by a decrease in tear secretion, common in aqueous-deficient DED, or by an increase in tear evaporation, more common in evaporative DED. Once the tear film is compromised, the remaining tear fluid is more concentrated with salts and other solutes, leading to a state of hyperosmolarity. The resulting damage to the ocular surface initiates a self-perpetuating cycle of inflammation, which makes symptoms worse over time and prevents the disease from resolving without intervention [2,3,4,5,6,7]. The initial stress and damage to the ocular surface epithelial cells leads to the production and release of pro-inflammatory cytokines and matrix metalloproteinases, most notably including matrix metalloproteinase-9 (MMP-9), which compromises the integrity of the corneal epithelium (Figure 1) [5]. This inflammatory cascade is part of a normal bodily inflammatory response, but the chronic presence of these cytokines results in further ocular surface damage and worsens the tear film’s state of dysregulation. The chronic inflammation not only impacts the ocular surface but concurrently impairs the lacrimal glands as well, leading to reduced tear production. It also damages the meibomian glands, which alters lipid composition and further increases tear evaporation. This further destabilizes the tear film and reinforces the inflammatory environment of the ocular surface [6]. Neurosensory abnormalities resulting from this inflammation, such as impairment of corneal nerve function and increased nociceptive signaling, can further lead to significant patient discomfort [7]. This complex interplay among tear film instability, immune activation, and neurosensory feedback forms a vicious cycle that sustains the chronic nature of DED. Understanding these interrelated mechanisms is essential for identifying targeted biomarkers and developing more effective, personalized therapeutic strategies for DED.

3. Molecular Biomarkers of DED

Biomarkers play an emerging role in improving the diagnosis, subtyping, and management of DED, a condition that typically presents with indistinct symptoms and overlapping clinical features. Traditional diagnostic methods, such as Schirmer’s test or tear break-up time, are limited by variability and lack of sensitivity, emphasizing the need for objective molecular markers [8,9,10]. In recent years, a diverse array of candidate biomarkers—including small molecules, proteins, and lipids—have been identified in the tear film (Table 1) [11,12,13,14,15,16,17,18]. Each marker offers unique insights into the underlying pathophysiology of DED, reflecting inflammation, glandular dysfunction, tear composition, or neurosensory abnormalities. Identification of these markers has elucidated the underlying mechanisms of DED, including key processes such as the recruitment of cytotoxic T cells and CD4+ T-helper cells, activation of antigen-presenting cells, and release of inflammatory mediators such as MMP-9, Tumor Necrosis Factor alpha (TNF-α), Interleukin-1 (IL-1), and Interleukin-6 (IL-6) [2,5,19,20,21,22]. These markers contribute to ocular surface damage and disease chronicity, making them prime candidates for both diagnostic and therapeutic applications. The following sections provide an overview of key biomarker categories and their clinical relevance, with particular emphasis on MMP-9 and other inflammation-related markers closely associated with DED.

3.1. Inflammatory Markers

Inflammation is a key process that perpetuates DED and contributes to many of the symptoms of discomfort experienced by patients daily. The hyperosmolarity that initiates DED, along with mechanical trauma to the cornea due to reduced lubrication of the ocular surface, both trigger and sustain inflammation. This inflammatory response can further exacerbate DED by damaging the ocular surface and lacrimal glands, leading to a chronic state of injury that continuously stimulates immune and inflammatory pathways. Because inflammation is a primary driver of DED progression, inflammatory proteins are often strong biomarkers of disease. These markers frequently correlate with clinical signs, patient-reported symptoms, and disease severity.

3.1.1. Matrix Metalloproteinases and MMP-9

MMP-9 is the most well-known of the molecular biomarkers for DED, having been successfully translated to clinical use through the InflammaDry™ device (QuidelOrtho, San Diego, CA, USA) [23,24,25,26]. As a zinc-dependent endopeptidase, MMP-9 degrades extracellular matrix components, including corneal epithelial tight junction proteins, leading to barrier disruption and accelerated epithelial cell shedding [24]. Elevated MMP-9 levels in tears are strongly correlated with DED severity, shorter tear break-up times, and compromised corneal integrity [27]. Prior clinical studies have supported the implication of MMP-9 in DED patients. One study recruited forty-six patients with newly diagnosed DED and 18 control subjects. They collected 1 microliter of unstimulated tear fluid from each patient and analyzed them for MMP-9 levels. The study found that MMP-9 was significantly higher in DED patients than in the control patients, and the MMP-9 levels even showed to be significantly correlated to DED patients in this study [28]. Mechanistically, MMP-9 is upregulated by pro-inflammatory cytokines like Interleukin-1β (IL-1β) and TNF-α, which are released by activated immune cells, including cytotoxic T cells and CD4+ T-helper cells [19]. This creates an inflammatory feedback loop that exacerbates tissue damage. Due to MMP-9’s responsiveness to inflammatory stimuli and its direct impact on ocular surface health, MMP-9 serves as a valuable biomarker for investigating DED pathophysiology and guiding targeted therapeutic strategies.
MMP-9 is also considered an objective biomarker for DED and is correlated with ocular surface integrity [24,29,30,31]. An increased concentration of MMP-9 is typically associated with a shorter tear break-up time, which serves as a measure of tear film stability. This information is especially useful in clinical settings, as a reduced tear break-up time is reflective of an unstable tear film, making it difficult for patients to maintain visual clarity and comfort. Thus, MMP-9 serves as a meaningful marker of inflammation, ocular surface integrity, and functional tear film deficiency in DED. Other matrix metalloproteinases (MPPs) have also been identified as candidate biomarkers of DED, including MMP-2 and MMP-3, although these are less established.

3.1.2. Cytokines and Chemokines

Cellular communication within the immune system is crucial for coordinating a proper response to pathogens and injury. This communication is mediated by a diverse family of small proteins called cytokines, which act as signaling molecules to regulate the behavior of immune cells. Chemokines are a subset of cytokines that play a specific role in guiding the migration of these cells to sites of inflammation or infection. Cytokines and chemokines both play a significant role in recruiting immune cells to the ocular surface in DED, contributing to the perpetuation of inflammation and corneal damage in DED.
IL-1β is a key pro-inflammatory cytokine involved in ocular surface inflammation, particularly in DED [32,33]. It is primarily produced by activated innate immune cells as an inactive prohormone and can be enzymatically cleaved intracellularly or extracellularly to become active. Extracellular cleavage can be performed by a variety of enzymes, most notably including MMP-9, suggesting IL-1β may play a significant role in the self-perpetuating inflammatory cycle that characterizes DED. IL-1β is widely considered a master regulator of both local and systemic inflammation, playing a pivotal role in the development and progression of acute and chronic inflammation. Although it is present in healthy tear fluid, it exists predominantly in its inactive form. Some studies have shown IL-1β to be present at higher levels in DED tear fluid compared to healthy tear fluid. IL-1β could pose potential as a biomarker for DED, especially considering its role in regulating inflammatory events and association with MMP-9.
Interleukin-6 (IL-6) is a pleiotropic cytokine also involved in DED, possessing both pro- and anti-inflammatory characteristics. IL-6 is consistently found at significantly elevated concentrations in the tears of patients diagnosed with DED when compared to healthy control individuals [34]. This consistent elevation underscores its potential as a key indicator of disease presence and activity. On the ocular surface, IL-6 is largely produced by corneal epithelial cells in response to DED-like triggers such as hyperosmolarity [21]. Interestingly, IL-6 also plays a significant role in initiating the differentiation of T-helper 17 (Th17) cells, which are known to be critical players in chronic inflammatory diseases and disease relapse [35]. Thus, IL-6 is a strong candidate as a target for therapeutic intervention and as a biomarker, given its potential role in the pathogenesis of DED and elevation in DED tear samples.
TNF-α, a pleiotropic cytokine involved in numerous inflammatory responses, has been found to be elevated in the tear film and ocular surface tissues of patients with DED. Its upregulation contributes to the chronic inflammation characteristic of the disease, affecting both the ocular surface and lacrimal glands [36]. However, while TNF-α plays a critical role in DED pathogenesis and is associated with disease severity, it is not a disease-specific biomarker due to its overlap with broader systemic inflammatory processes, limiting its diagnostic specificity.
Similarly, IgE also plays a significant role in ocular surface inflammation [37,38]. The inflammatory environment brought about by IgE-mediated reactions can compromise the epithelial barrier function. When the epithelial barrier is damaged, increased tear evaporation occurs and irritation persists. Evidently, DED symptoms worsen because of the activity of IgE. While increased IgE levels in tear fluid are not directly associated with DED, they are closely linked to a comorbid condition, allergic conjunctivitis. The symptoms of these two conditions are nearly identical, making it difficult to determine whether ocular surface irritation and dryness are present due to disease or allergic reactions. Simultaneously, researchers are investigating whether an underlying allergy component exists in DED. Moreover, IgE, though elevated in tear fluid during allergic conjunctivitis—a condition often overlapping with DED—primarily reflects allergic comorbidity rather than direct DED pathophysiology, necessitating contextual interpretation to avoid misdiagnosis.
Table 1. Key Biomarkers for DED.
Table 1. Key Biomarkers for DED.
BiomarkerRoleClinical RelevanceReference
1. Protein Biomarkers
MMP-9Degrades extracellular matrix; upregulated during inflammationElevated in DED; used in point-of-care test (InflammaDry); marker of ocular surface inflammation[23,24,25,26,27,29,30,31]
LactoferrinIron-binding glycoprotein with antimicrobial and anti-inflammatory propertiesDecreased in aqueous-deficient DED; indicates lacrimal gland
dysfunction
[39,40,41,42]
LacritinTear glycoprotein that promotes epithelial cell survival, autophagy, and secretionDeficient in aqueous-deficient DED; shown to restore tear secretion and corneal integrity in preclinical
models
[43,44,45,46,47]
LysozymeAntimicrobial enzyme secreted by lacrimal glandsReduced levels suggest impaired tear secretion[48,49,50,51,52]
Lipocalin-1Stabilizes the tear film lipid layerAltered levels associated with tear film instability[43,53,54,55,56]
MUC5ACSecreted gel-forming mucin from conjunctival goblet cellsDecreased in DED, especially in mucin-deficient or Sjögren’s
syndrome cases
[57,58,59,60,61,62,63,64,65,66,67]
HLA-DRMajor histocompatibility complex class II moleculeUpregulated in conjunctival epithelial cells; marker of immune activation[68,69,70,71,72]
2. Cytokines and Chemokines
IL-1β, IL-6, TNF-αPro-inflammatory cytokinesElevated levels in tears of DED patients; drive ocular surface inflammation[22,73,74,75,76,77,78,79,80,81]
IL-8 (CXCL8)Neutrophil chemoattractantReflects active inflammation and epithelial damage[5,17,75,82,83,84]
IFN-γActivates immune response, especially Th1-mediatedLinked to goblet cell loss and mucin downregulation[17,75,82,84,85]
CCL5 (RANTES)Recruits T cellsFound in increased levels in tears and conjunctiva of DED patients[5,86,87]
3. Lipid Biomarkers
Meibum Lipids (e.g., wax esters, cholesterol esters)Maintain tear film stability and reduce evaporationAltered composition in Meibomian Gland Dysfunction (MGD) contributes to evaporative DED[88,89,90,91,92,93,94]
Phospholipids, sphingolipidsInflammatory signaling moleculesLipidomics has revealed dysregulated lipid profiles in DED associated with inflammation[95,96,97,98,99,100,101,102]
4. Metabolites and Small Molecules
Lactate, UreaIndicators of metabolic stressElevated levels found in tear fluid of DED patients[103,104,105]
Glutamate, GlutamineLinked to oxidative stress and inflammationAltered profiles can distinguish DED subtypes[106,107,108,109]
Reactive oxygen species (ROS)Oxidative stress markerAssociated with cellular damage in DED pathogenesis[110,111,112,113]
5. Nucleic Acid Biomarkers (Genomic/Epigenomic)
MicroRNAs (e.g., miR-146a, miR-155)Post-transcriptional gene regulation of inflammationDysregulated in tears and conjunctiva; potential non-invasive biomarkers for DED diagnosis and subtype stratification[114,115,116,117,118,119]
HLA gene polymorphismsImmune response genesCertain variants associated with Sjögren’s syndrome and autoimmune-related DED[120,121,122,123]
6. Functional and Imaging Biomarkers
Tear OsmolarityMeasures tear solute concentrationElevated (>308 mOsm/L) in DED; reproducible marker for severity[124,125,126,127,128,129]
Corneal SensitivityAssesses corneal nerve function and ocular surface integrityReduced in DED; associated with neurosensory abnormalities and disease severity[130,131,132,133]
Tear Break-Up Time (TBUT/NITBUT)Measures tear film stabilityDecreased in DED, especially in evaporative forms[134,135,136,137,138]
MeibographyVisualizes meibomian gland structureGland dropout seen in MGD-related DED[139,140,141,142]
In vivo confocal microscopy (IVCM)Assesses corneal nerves and immune cellsReveals corneal nerve loss or dendritic cell activation in DED [143,144,145,146,147,148]

3.2. Lacrimal Gland Protein Markers

Differential expression of lacrimal gland-derived proteins, which reflect alterations in tear fluid synthesis and secretion, is also commonly reported as a marker of DED. These proteins may indicate dysfunction or damage to the lacrimal glands, a hallmark of certain DED subtypes, particularly aqueous-deficient DED. Changes in expression levels can signal impaired tear production, glandular inflammation, or structural degeneration, all of which contribute to tear film instability and ocular surface stress. As such, lacrimal gland proteins serve not only as potential biomarkers of disease but also as indicators of underlying pathophysiological mechanisms driving DED progression.

3.2.1. Lactoferrin

Lactoferrin (LTF or LF), also known as lactotransferrin, is an 80 kDa multifunctional glycoprotein. It is one of the most abundant proteins in tear fluid and is a key biomarker for diagnosing DED [40,41]. In the tear film, lactoferrin plays a crucial role in maintaining ocular surface health through its antimicrobial, anti-inflammatory, and antioxidant properties. A marked reduction in tear lactoferrin levels is commonly seen in patients with DED, particularly in the aqueous-deficient subtype caused by lacrimal gland dysfunction. This decline correlates with reduced tear production and increased ocular surface damage. Measuring lactoferrin levels provides a non-invasive and reliable method to differentiate between types of DED, such as Sjögren’s syndrome-associated DED or other non-Sjögren’s variants [39]. Emerging diagnostic technologies, such as photo-detection devices and microfluidic assays, have enhanced precision and accessibility in lactoferrin measurement, facilitating more personalized treatment strategies. These advancements underscore lactoferrin’s value as a diagnostic and prognostic biomarker for DED, facilitating targeted therapies to mitigate inflammation and restore tear film homeostasis.

3.2.2. Lysosome

Lysozyme (LYZ) is a glycoside hydrolase that plays a critical antimicrobial role in the tear film, helping to protect the ocular surface from bacterial invasion [42]. Like lactoferrin, it is produced by the lacrimal gland and secreted into the aqueous layer of the tear film, contributing to the innate immune defense of the ocular surface. In the context of DED, decreased concentrations of lysozyme are commonly associated with aqueous-deficient subtypes and may indicate underlying lacrimal gland dysfunction [44,45,46]. Because of its high abundance in healthy tear fluid and its sensitivity to changes in glandular output, lysozyme has been proposed as a useful biomarker for assessing tear film integrity and lacrimal gland health. When evaluated alongside other tear proteins such as lactoferrin and lipocalin-1, lysozyme can contribute to a more comprehensive characterization of the ocular surface environment and aid in the stratification of DED subtypes. Moreover, changes in lysozyme levels over time may provide insight into disease progression or response to therapeutic intervention.

3.3. Lipids

The lipid layer of the tear film plays a crucial role in maintaining ocular homeostasis, primarily by reducing the rate of tear evaporation and preserving tear film stability. Secreted predominantly by the meibomian glands, this outermost layer forms a barrier that minimizes fluid loss from the aqueous layer beneath it. Disruption or deficiency of the lipid layer, as seen in meibomian gland dysfunction (MGD), leads to increased tear evaporation, tear film instability, and hyperosmolar stress—key drivers of evaporative DED. Consequently, alterations in the composition or integrity of the lipid layer are both contributors to disease pathogenesis and potential targets for biomarker discovery and therapeutic intervention.

3.3.1. Omega-6 and Omega-3 Fatty Acids

The Omega-6 to Omega-3 fatty acid ratio reflects the balance of pro-inflammatory and anti-inflammatory lipid precursors in the tear film. Omega-6 polyunsaturated fatty acids (PUFAs), such as arachidonic acid (AA), give rise to inflammatory mediators, while Omega-3 PUFAs, like DHA and EPA, are precursors to pro-resolving, anti-inflammatory molecules [149,150]. This ratio is influenced by systemic diet and local lipid metabolism on the ocular surface, impacting the overall inflammatory milieu of the tear film. In the context of DED, an elevated Omega-6 to Omega-3 ratio is frequently observed, indicative of a pro-inflammatory state that perpetuates the cycle of ocular surface damage and tear film instability. Due to its direct link to inflammation, this ratio has been proposed as a valuable biomarker for assessing the inflammatory component of DED and for monitoring the efficacy of anti-inflammatory treatments. When evaluated in conjunction with other tear film components, the Omega-6 to Omega-3 ratio can contribute to a more nuanced understanding of DED pathophysiology and help guide personalized therapeutic strategies. Moreover, shifts in this ratio over time may provide insight into disease progression or response to interventions targeting inflammation. A recent extension study to the Dry Eye Assessment and Management (DREAM) trial sought to find if discontinuation of Omega-3 supplementation in patients previously given Omega-3 as part of the main DREAM study would yield different outcomes in symptoms and discomfort. 22 patients were randomized to Omega-3 supplements and 21 were given a placebo. The results of the study showed that there was no significant difference in symptom outcomes in the group continuing to take the supplement and the group that discontinued it [151]. This study calls into question the significance that Omega-3 fatty acid supplementation has on improving DED. The study is limited by the small cohort size, however, and further research needs to be done to fully evaluate the impact Omega-3 fatty acids may have in DED.

3.3.2. O-acyl-ω-hydroxy Fatty Acids (OAHFAs)

O-acyl-ω-hydroxy fatty acids (OAHFAs) are a unique class of lipids critical for the structural integrity and function of the tear film lipid layer (TFLL) [99,152]. Produced primarily by the meibomian glands, these specialized lipids contribute significantly to the outermost layer of the tear film, forming a stable barrier that retards evaporation of the underlying aqueous layer. In the context of DED, particularly evaporative subtypes stemming from meibomian gland dysfunction (MGD), decreased concentrations of OAHFAs are commonly associated with increased tear film evaporation and instability. Because of their direct role in maintaining the TFLL’s barrier function and their sensitivity to changes in meibomian gland health, OAHFAs have been proposed as useful biomarkers for assessing evaporative dry eye and meibomian gland function. When evaluated alongside other tear film lipids and structural components, OAHFAs can contribute to a more comprehensive characterization of the tear film’s evaporative resistance and aid in the stratification of DED subtypes. Changes in OAHFA levels over time may also provide important insights into disease progression or response to therapeutic interventions targeting MGD.

3.3.3. Diesters (DiEs)

Diesters (DiEs), specifically Type I and Type II Diesters, are prominent components of the tear film lipid layer (TFLL), playing a crucial role in its physical properties and stability [153,154]. These complex lipids are synthesized by the meibomian glands and are essential for forming a uniform and stable lipid monolayer on the aqueous tear surface, which is vital for preventing rapid tear evaporation and ensuring smooth blinking. In the context of DED, particularly in cases linked to meibomian gland dysfunction (MGD), qualitative and quantitative alterations in diester profiles are frequently observed, contributing to tear film instability and increased evaporation. Because of their significant contribution to the TFLL’s structure and function and their sensitivity to meibomian gland health, diesters have been proposed as valuable biomarkers for assessing tear film quality and meibomian gland function in DED. When evaluated in conjunction with other tear film lipids like OAHFAs and meibomian gland expression, diester analysis can contribute to a more comprehensive characterization of the tear film’s evaporative properties and aid in the diagnosis and subtyping of DED.

3.4. MicroRNAs (miRNAs)

miRNAs are small non-coding RNAs that regulate gene expression and have recently emerged as pivotal biomarkers in DED pathogenesis [117,155]. Research led by Pflugfelder at Baylor College of Medicine, in conjunction with insights from the 2024 TFOS sessions, has elucidated the role of miRNAs in DED’s inflammatory processes. Specific miRNAs, such as miR-204, are upregulated in the conjunctival epithelium and tear film of DED patients, modulating inflammatory pathways by targeting receptors like Toll-like receptors (TLRs) and the TNFR superfamily. These miRNAs regulate the expression of pro-inflammatory cytokines, including IL-1β, TNF-α, and Interferon gamma (IFN-γ), which exacerbate ocular surface inflammation and lacrimal gland dysfunction. Advanced molecular techniques, such as quantitative PCR and RNA sequencing, have been instrumental in identifying these miRNA expression profiles, providing a deeper understanding of DED’s molecular mechanisms.

4. From Biomarkers to Clinical Diagnosis

Multiple devices are commercially available for rapid, in-clinic use that measure a variety of DED biomarkers and measurements (Table 2). These include a device for MMP-9 measurement (InflammaDry, QuidelOrtho, San Diego, CA, USA), and tear osmolarity measurements (I-Pen, I-MED Pharma, Montreal, QC, Canada, and ScoutPro, Bausch & Lomb, Laval, QC, Canada), esthesiometry (Brill corneal esthesiometer, Brill Engines, Barcelona, Spain), and others. Currently, these devices are typically used in the same patients to gather additional data in patients suspected to have DED, yet they do not have the standalone sensitivity to classify the disease etiology (Figure 2).

4.1. Tools for MMP-9 Measurement

The only device currently available to clinicians for MMP-9 measurement is the InflammaDry device. InflammaDry is a point-of-care diagnostic approach designed to detect the inflammatory biomarker MMP-9 in tears for DED. MMP-9 is the most recognizable molecular biomarker for DED. Recent TFOS discussions emphasized MMP-9’s key role in corneal epithelial abnormalities, noting its utility in differentiating DED subtypes due to its association with evaporative DED and MGD [156].
In the clinic, InflammaDry provides a non-invasive method of confirming the presence of ocular surface inflammation and uses lateral flow to detect the concentration of MMP-9 expression. A positive result of two lines means that the MMP-9 concentration is greater than 40 ng/mL. A negative result of only one line indicates an MMP-9 concentration is less than 40 ng/mL [25,26,157,158].
A randomized control trial of 206 patients was performed to assess the specificity and sensitivity of InflammaDry [159]. 143 of the patients presented with the signs and symptoms of DED in clinic, and the other 63 patients were healthy controls. The results showed that InflammaDry had an 85% sensitivity rate (121 of 143 DED patients) and a specificity of 94% (59 of 63 healthy patients). A follow up clinical study sponsored by the company confirmed this finding, citing an 87% sensitivity rate and 97% specificity rate.
While the InflammaDry device has high specificity and sensitivity rates, it can be limited in its role in diagnosing DED. Its ability to measure MMP-9 levels is not a standalone tool; other measurements and observations are often required to confirm a DED diagnosis. MMP-9 levels are known to be elevated as a result of ocular conditions besides DED, highlighting the need for additional data collection when diagnosing. It also does not provide a quantifiable level of MMP-9 concentration in tear film, only giving a positive or negative result based on if the concentration level relative to 40 ng/mL. This is a clinical limitation, as some patients with milder DED may yield MMP-9 levels below the detectable threshold on the InflammaDry. Additionally, monitoring treatment response may be limited here too, as the MMP-9 level cannot be directly measured and tracked. More nuance in MMP-9 levels may be required, especially in low-level or mild dry eye.
Overall, the InflammaDry device can be a reliable tool for aiding in-clinic diagnosis of DED. While limited in standalone diagnostic ability, the device fills a need for accurate measurement of MMP-9 for patients at risk of DED.

4.2. Tools for Tear Osmolarity Measurement

Tear film osmolarity, integrally linked to lacrimal gland function, plays a crucial role in maintaining ocular surface health [128,129]. Osmolarity, which refers to the concentration of dissolved particles in the tear film, is meticulously regulated under normal conditions. Tear osmolarity reflects the balance of electrolytes, water, and proteins in the tear film, regulated by lacrimal gland secretion. In DED, dysfunction of the lacrimal gland can lead to hyperosmolarity, often because of reduced aqueous production or excessive evaporation [126]. This hyperosmolarity damages the ocular surface epithelium and triggers inflammatory cascades [160]. These changes further exacerbate the symptoms of DED, creating a self-perpetuating cycle of ocular surface damage and inflammation. Given that elevated osmolarity is a hallmark of DED, measurement of tear osmolarity can provide insights into lacrimal gland dysfunction and tear film dynamics and has emerged as a valuable diagnostic tool for DED. Additionally, understanding and targeting tear film osmolarity could potentially lead to more effective treatments for DED, aiming to restore the delicate osmotic balance necessary for optimal ocular surface health.
One common device used in clinics for tear osmolarity measurement is the I-Pen tear osmolarity system. The I-Pen system offers a rapid, handheld method of measuring tear film osmolarity to aid in diagnosing DED in patients. The device uses a single-use sensor probe that is gently placed on the lower eyelid’s inner surface for approximately two seconds to generate the result. The rapid test displays results immediately in mOsm/L. It requires no anesthesia or sample collection and can be easily performed by trained clinical staff. The I-Pen is very portable and delivers results rapidly, making it a convenient tool for in-clinic use. Comparatively, other similar devices like the Wescor or TearLab are somewhat less portable. Primarily, the differences between these devices are in the collection and analysis methods and in the accuracy of reported results based on prior studies.
A clinical study published in 2021 evaluated the efficacy of the I-Pen in comparison to other standard diagnostic methods. 65 patients were enrolled in the study, with 32 patients presenting with DED pathology and 33 patients presenting with no DED symptoms. Using the osmolarity cutoff of 318 mOsm/L, the study revealed a 90.9% sensitivity and a 90.6% specificity for identifying DED [161]. However, a 2017 in vitro study compared the performance of the I-Med Pharma I-Pen, Wescor 5520 Vapro Pressure Osmometer, and TearLab Osmolarity System, and found that the I-Pen was neither accurate nor precise, especially compared to the other two devices. The study used solutions of known osmolarity to evaluate each device. The Wescor and TearLab devices had correlation coefficient values of r2 = 0.98 and r2 = 0.96, respectively, while the I-Pen had a value of r2 = 0.03. Additionally, its coefficients of variation (CVs) were notably high, ranging from 6.1% to 6.4%. This performance contrasts sharply with the Wescor device (CV = 1.0–1.6%) and the TearLab system (CV = 1.2–2.3%), further supporting a lack of accuracy and precision in the I-Pen device.
Another common device for tear osmolarity measurement is the ScoutPro tear osmolarity system. The ScoutPro is an advanced diagnostic tool designed to quantify tear film osmolarity, a critical biomarker in the pathophysiology of DED. Elevated tear film osmolarity is recognized as a central etiology of DED and is known to correlate with DED severity. The ScoutPro’s automated, rapid assay delivers quantitative osmolarity results in milliosmoles per liter (mOsm/L), aiding clinicians in diagnosing DED and objectively assessing disease progression. The system utilizes a test card with a microfluidic channel to collect a tiny tear sample (50 nanoliters) using passive capillary action. Gold electrodes embedded in the channel then measure the electrical impedance of the tear fluid, which is used to calculate and display the osmolarity result. While tear osmolarity may not differentiate DED subtypes, its ability to classify DED severity with accuracy makes it invaluable for diagnosis, including 71% specificity and 64% sensitivity for the device according to a clinical study of 140 patients from Trukera Medical. By targeting this fundamental biomarker, the device facilitates early diagnosis and personalized treatment strategies to mitigate the inflammatory feedback loop in DED [162,163]. A crucial limitation to this device is that it does not aid in diagnosing DED subtype, as it only measures tear osmolarity. This device needs to be used with other metrics and data to effectively determine the most optimal method of treatment for each individual patient.
Table 2. Summary of common diagnostic devices and their utility for DED.
Table 2. Summary of common diagnostic devices and their utility for DED.
DevicePrimary FunctionBiomarkers/Parameters MeasuredRole in DED Diagnosis
InflammaDryImmunoassay for inflammation detectionMMP-9Detects elevated MMP-9 levels (>40 ng/mL). High sensitivity and specificity for rapid, in-clinic diagnosis [152].
I-PenTear osmolarity systemTear osmolarityMeasures osmolarity using electrical impedance of the tear fluid of the palpebral conjunctiva [127,128]
BrillEsthesiometryCorneal sensitivityQuantifies corneal sensitivity to aid in early detection of corneal dysesthesia and monitoring of treatment efficacy [129].
ScoutProTear osmolarity systemTear osmolarityMeasures osmolarity using microfluidics to collect a tiny tear sample for measurement of electrical impedance of the tear fluid, which is used to calculate the osmolarity result with accuracy [162,163]
Corneal TopographyMaps corneal surface to detect irregularitiesCorneal surface irregularities, tear film instabilityIdentifies corneal changes due to tear film instability, enhancing diagnostic precision for DED related ocular surface damage
Anterior Segment OCTHigh-resolution imaging of anterior chamber structuresTear film thickness, corneal epithelium, meibomian gland structure Visualizes alterations in tear film and glands, correlating with DED severity and aiding in diagnosis
KOWA DR-1a InterferometerAnalyzes tear film lipid layer dynamicsLipid layer thickness, tear film stabilityAssesses evaporative DED by evaluating lipid layer dynamics, providing insights into tear film instability [164].
While tear osmolarity is lauded as a strong biomarker for DED detection and severity assessment, it is important to acknowledge its limitations. Notably, osmolarity testing alone cannot differentiate between the two primary categories of DED: aqueous-deficient dry eye and evaporative dry eye. While it excels at identifying the presence and overall severity of DED, it is insufficient for determining the specific underlying etiology or for guiding subtype-targeted therapies. Consequently, tear osmolarity measurement should always be utilized alongside other clinical evaluation methods. This highlights the necessity of a comprehensive diagnostic approach, where osmolarity provides a crucial objective measure within a broader assessment framework.

4.3. Corneal Esthesiometry

Corneal esthesiometry is used to measure the sensitivity of the corneal nerves by applying a controlled stimulus to the corneal surface. The patient’s involuntary reflex, such as a blink, or subjective response to the stimulus is used to quantify the nerve’s responsiveness. The information gathered from this test helps clinicians in differentiating DED from other ocular surface diseases, assessing DED disease severity based on the observed reduction in corneal sensitivity, and in guiding treatment decisions based on the observed nerve function in individual patients.
The current, most widely used method of measuring corneal sensitivity is with the Cochet-Bonnet Esthesiometer. It is largely considered the gold standard for contact-based esthesiometry and has been long in use by clinicians. The device consists of a handle and a retractable, fine nylon monofilament. The Cochet-Bonnet is used to determine the minimum force of the filament required for a patient to feel a sensation on their cornea. When the patient blinks or reacts to the filament, the length is recorded as the objective measurement for corneal sensitivity. The main benefits of this device are the simplicity, low cost, and portability. It provides a quick and direct measure of nerve function without requiring specialized equipment. However, some limitations exist with this device, as well. Its invasive, contact-based method can cause patient discomfort, induce a reflexive blink, and may potentially lead to a corneal abrasion. The results can also be subjective, as it is easily influenced by the operator’s technique and the patient’s subjective response, making it less objective and reproducible than non-contact devices.
The other device available to clinicians for measuring corneal sensitivity is the Brill Corneal Esthesiometer. This is a novel, non-invasive, handheld device that uses controlled air pulses to measure corneal sensitivity [130]. By measuring a patient’s response to brief corneal stimulation, corneal sensitivity test provides valuable insight into the integrity of corneal nerves and their interaction with the ocular surface [130]. Unlike traditional contact-based esthesiometers, like the Cochet-Bonnet, the Brill esthesiometer employs controlled air pulses to stimulate the cornea, ranging from 2 to 10 mbar across five intensity levels, ensuring precise and reproducible measurements [132]. This non-contact approach minimizes patient discomfort and eliminates the risk of corneal abrasion, making it suitable for use in infectious corneal pathologies. Corneal sensitivity, mediated by the ophthalmic branch of the trigeminal nerve, is often compromised in DED and other conditions like neurotrophic keratopathy, reflecting underlying nerve dysfunction [133]. Corneal sensitivity testing provides valuable insights into the integrity of the corneal nerves, which is essential for diagnosing and managing DED and other ocular surface disorders. The Brill esthesiometer is particularly useful for early detection of DED, monitoring treatment efficacy over time, and providing objective sensitivity data that complements other diagnostic findings. Studies have shown good agreement with the Cochet-Bonnet esthesiometer in healthy and DED patients, though values are not interchangeable, underscoring its role as a complementary diagnostic tool [131]. Additionally, the Brill esthesiometer carries a higher cost and more limited availability in comparison to the Cochet-Bonnet esthesiometer. Additionally, the measurement of corneal sensitivity is not a standalone diagnostic value, as increased sensitivity could be a feature of the different subtypes of DED and even other conditions that impact the ocular surface. Overall, by providing objective data on corneal nerve function, however, the Brill esthesiometer supports tailored therapeutic interventions and improves the management of ocular surface disorders.

4.4. Other Imaging Tools

Advancements in biomarker detection technologies are enhancing our ability to study DED’s molecular mechanisms. In ophthalmology, instruments like corneal topography and optical coherence tomography (OCT) are widely used and reliable for assessing DED-related changes. Corneal topography maps the corneal surface to detect irregularities caused by tear film instability, while anterior segment OCT provides high-resolution imaging of the tear film, corneal epithelium, and meibomian glands, revealing structural alterations linked to DED. These imaging modalities enhance diagnosis. The KOWA DR-1α interferometer uses white light illumination to analyze tear film lipid layer dynamics, providing insights into tear film instability. It has a relatively high sensitivity and specificity for diagnosing dry eye, particularly when measuring non-invasive tear break-up time. It is typically used as a complementary device in clinic to help diagnose DED type [164].

4.5. Unmet Needs

The gap between biomarker discovery and clinical translation in DED remains a critical challenge, driven by the complexity of translating molecular insights into practical diagnostic tools. While biomarkers like MMP-9, TNF-α, and lactotransferrin have contributed to our understanding of DED’s inflammatory and cellular mechanisms, the integration of some of them into routine clinical practice is hindered by technical, logistical, and economic barriers. MMP-9 has largely broken through these barriers, becoming a strong DED biomarker that is accessible for in-clinic use. However, despite a strong understanding of TNF-α and its role in DED, assessment of it requires more development to become widely adopted in clinical assessment procedures. Similarly, lactrotransferrin has a strong research basis for its relevance in DED but lacks a rapid and reliable method of assessment. Variability in biomarker expression across DED subtypes and patient demographics further complicates the development of standardized assays. This review of current findings demonstrates a need for a device that can reliably test more biomarkers, providing clinicians with a more comprehensive tool for diagnosis of DED.

5. Current Treatment Methods and Limitations

The DEWS TFOS III Report outlines current treatments for dry eye based on the etiologies of the disease. The first line of treatment for all types of DED symptoms is typically artificial tears. Artificial tears, however, provide only temporary relief and do not treat the underlying cause of the DED itself. For evaporative DED, eyelid treatment for blepharitis and lid hygiene are effective. These include warm compresses, lid hygiene, and in-office procedures such as thermal pulsation or Intense Pulsed Light (IPL), which can unblock the glands and improve lipid quality in the tears. Recent advancements in lipid-based artificial tears also directly target the tear film’s oily layer, and use of perfluorohexyloctane ophthalmic solution has been shown to help in patients living with evaporative DED. However, the at-home and in-office procedures are limited by efficacy and are not a cure for the disease, meaning repeated treatments are required to maintain relief. The in-office treatments can often be expensive, especially for multiple treatment rounds. Additionally, while the lipid-based tears are more effective at restoring some of the tear film’s lipid layer, it still lacks the ability to resolve the underlying meibomian gland dysfunction that is responsible for the DED in the first place. For aqueous deficient DED, the goal is to increase tear production and conserve existing tears. Treatments include preservative-free artificial tears, prescription anti-inflammatory eye drops (e.g., cyclosporine, lifitegrast) to stimulate tear production, and punctal plugs to block tear drainage and keep tears on the ocular surface for a longer period. While effective in many cases, cyclosporine and lifitegrast are slow acting and can sometimes be uncomfortable for patients to use, leading to poor patient adherence. Punctal plugs are limited by epiphora in certain cases and can cause irritation and foreign body sensation in rare cases. New treatments on the horizon include reproxalap, a reactive aldehyde species that has been shown to reduce inflammation associated with DED by a recent randomized, double-masked, vehicle-controlled dry eye chamber trial of 132 patients from Aldeyra Therapeutics [165,166]. Reproxalap was well tolerated and significantly reduced DED symptoms in patients compared to a vehicle control. Another new, recently FDA-approved treatment is acoltremon, which is a TRPM8 thermoreceptor agonist that has been shown in the COMET studies to be safe and effective in treating DED. These treatments and many others in development may improve efficacy and outcomes in future patients suffering from DED.

6. Future Directions

Future advancements in DED diagnosis hinge on the integration of multi-omics approaches, artificial intelligence (AI), and point-of-care devices to enhance precision and accessibility. Emerging technologies, such as exosome profiling and microRNA sequencing, are promising in identifying novel biomarkers that capture the heterogeneity of DED subtypes, potentially enabling personalized treatment strategies. However, significant roadblocks persist, including high costs and limited availability of advanced diagnostic tools in resource-constrained settings, hindering global adoption. For integration of multi-omics into point-of-care diagnostics to be made more feasible, development needs to be done to lower the cost and increase the availability for more widespread use in clinics. Given the extent of sample collection required and high cost, multi-omics remains largely unfeasible at this present moment. Alternatively, AI-driven diagnostic platforms could analyze complex biomarker datasets alongside imaging modalities like corneal topography and OCT, improving diagnostic accuracy and predicting disease progression. It could aid in interpretation of imaging and potentially predict disease progression. However, the challenges of regulatory approval and data privacy remain, and integrating this technology into resource-limited settings could be challenging given high costs and current limited technical support. Standardization of biomarker assays across diverse populations remains challenging due to variability in environmental, genetic, and lifestyle factors. Additionally, the need for large-scale clinical validation studies slows the translation of novel biomarkers into routine clinical practice, necessitating collaborative efforts to establish universal diagnostic criteria and affordable technologies.
Exosomes have emerged as a promising marker for DED, offering potential benefits in both early detection and monitoring of the condition. These nano-sized extracellular vesicles, particularly those found in tear fluid, have shown remarkable potential in identifying DED-specific biomarkers. When analyzed in large scale clinical trials using advanced techniques such as proteomics and RNA sequencing, exosomes from tear samples can reveal distinct molecular signatures associated with various stages and subtypes of DED [167]. Studies have demonstrated significant differences in exosome profiles between healthy individuals and those with DED, including variations in protein content and microRNA expression. Mechanistically, these exosomes can provide valuable insights into the underlying pathological processes of DED, such as inflammation and lacrimal gland dysfunction. Furthermore, exosomes play a crucial role in intercellular communication within the ocular surface ecosystem, making them excellent candidates for monitoring disease progression and treatment response in DED patients.

7. Conclusions

DED arises from a complex interplay of inflammation, tear film dysfunction, and cellular responses. Molecular biomarkers such as MMP-9, TNF-α, lactotransferrin, tear osmolarity, exosomes, and miRNAs provide critical insights into the molecular mechanisms underlying the disease. The integration of advanced diagnostic tools, including the KOWA DR-1α interferometer, InflammaDry, ScoutPro, and Brill esthesiometer, with molecular profiling techniques, enables precise diagnosis and monitoring of DED subtypes. These innovations enhance our ability to correlate molecular data with clinical findings, paving the way for personalized therapeutic strategies. By bridging molecular insights with cutting-edge technologies, biomarker-driven research continues to unravel the complexities of DED, fostering global advancements in ocular surface health and driving scientific discoveries toward improved patient outcomes.

Author Contributions

Conceptualization, L.T.L., K.X.; writing—original draft preparation, J.J., J.G., K.F., M.B., M.Z., L.M.; writing—review and editing, J.J., K.F., M.Z., L.M.; supervision, L.T.L., K.X., S.P., N.E., D.D.; project administration, L.T.L., K.X.; funding acquisition, K.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

No new data were created in the making of this article.

Acknowledgments

We thank the AHNCI Moonshot Biomarker Program and Highmark Health for their support. We also gratefully acknowledge additional support from the Prostate Cancer Foundation Challenge Award (to K.X., grant number 2023CHAL4223), The Pittsburgh Foundation (to K.X., cc#45126409), and the Claude Worthington Benedum Foundation.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wolffsohn, J.S.; Arita, R.; Chalmers, R.; Djalilian, A.; Dogru, M.; Dumbleton, K.; Gupta, P.K.; Karpecki, P.; Lazreg, S.; Pult, H.; et al. TFOS DEWS II Diagnostic Methodology report. Ocul. Surf. 2017, 15, 539–574. [Google Scholar] [CrossRef]
  2. Pflugfelder, S.C.; de Paiva, C.S. The Pathophysiology of Dry Eye Disease: What We Know and Future Directions for Research. Ophthalmology 2017, 124, S4–S13. [Google Scholar] [CrossRef]
  3. Messmer, E.M. The pathophysiology, diagnosis, and treatment of dry eye disease. Dtsch. Arztebl. Int. 2015, 112, 71–81; quiz 82. [Google Scholar] [CrossRef] [PubMed]
  4. Rao, S.K.; Mohan, R.; Gokhale, N.; Matalia, H.; Mehta, P. Inflammation and dry eye disease-where are we? Int. J. Ophthalmol. 2022, 15, 820–827. [Google Scholar] [CrossRef]
  5. Stevenson, W.; Chauhan, S.K.; Dana, R. Dry eye disease: An immune-mediated ocular surface disorder. Arch. Ophthalmol. 2012, 130, 90–100. [Google Scholar] [CrossRef]
  6. Baudouin, C.; Messmer, E.M.; Aragona, P.; Geerling, G.; Akova, Y.A.; Benitez-del-Castillo, J.; Boboridis, K.G.; Merayo-Lloves, J.; Rolando, M.; Labetoulle, M. Revisiting the vicious circle of dry eye disease: A focus on the pathophysiology of meibomian gland dysfunction. Br. J. Ophthalmol. 2016, 100, 300–306. [Google Scholar] [CrossRef]
  7. Messmer, E.M. Pathophysiology of dry eye disease and novel therapeutic targets. Exp. Eye Res. 2022, 217, 108944. [Google Scholar] [CrossRef]
  8. Savini, G.; Prabhawasat, P.; Kojima, T.; Grueterich, M.; Espana, E.; Goto, E. The challenge of dry eye diagnosis. Clin. Ophthalmol. 2008, 2, 31–55. [Google Scholar] [CrossRef] [PubMed]
  9. Roy, N.S.; Wei, Y.; Kuklinski, E.; Asbell, P.A. The Growing Need for Validated Biomarkers and Endpoints for Dry Eye Clinical Research. Investig. Ophthalmol. Vis. Sci. 2017, 58, BIO1–BIO19. [Google Scholar] [CrossRef] [PubMed]
  10. Sullivan, B. Challenges in using signs and symptoms to evaluate new biomarkers of dry eye disease. Ocul. Surf. 2014, 12, 2–9. [Google Scholar] [CrossRef]
  11. Choi, W.; Lian, C.; Ying, L.; Kim, G.E.; You, I.C.; Park, S.H.; Yoon, K.C. Expression of Lipid Peroxidation Markers in the Tear Film and Ocular Surface of Patients with Non-Sjogren Syndrome: Potential Biomarkers for Dry Eye Disease. Curr. Eye Res. 2016, 41, 1143–1149. [Google Scholar] [CrossRef]
  12. Pinto-Fraga, J.; Enriquez-de-Salamanca, A.; Calonge, M.; Gonzalez-Garcia, M.J.; Lopez-Miguel, A.; Lopez-de la Rosa, A.; Garcia-Vazquez, C.; Calder, V.; Stern, M.E.; Fernandez, I. Severity, therapeutic, and activity tear biomarkers in dry eye disease: An analysis from a phase III clinical trial. Ocul. Surf. 2018, 16, 368–376. [Google Scholar] [CrossRef]
  13. Fong, P.Y.; Shih, K.C.; Lam, P.Y.; Chan, T.C.Y.; Jhanji, V.; Tong, L. Role of tear film biomarkers in the diagnosis and management of dry eye disease. Taiwan J. Ophthalmol. 2019, 9, 150–159. [Google Scholar] [CrossRef] [PubMed]
  14. Khanal, S.; Bai, Y.; Ngo, W.; Nichols, K.K.; Wilson, L.; Barnes, S.; Nichols, J.J. Human Meibum and Tear Film Derived (O-Acyl)-Omega-Hydroxy Fatty Acids as Biomarkers of Tear Film Dynamics in Meibomian Gland Dysfunction and Dry Eye Disease. Investig. Ophthalmol. Vis. Sci. 2021, 62, 13. [Google Scholar] [CrossRef] [PubMed]
  15. Suarez-Cortes, T.; Merino-Inda, N.; Benitez-Del-Castillo, J.M. Tear and ocular surface disease biomarkers: A diagnostic and clinical perspective for ocular allergies and dry eye disease. Exp. Eye Res. 2022, 221, 109121. [Google Scholar] [CrossRef]
  16. Byambajav, M.; Collier, A.; Shu, X.; Hagan, S. Tear Fluid Biomarkers and Quality of Life in People with Type 2 Diabetes and Dry Eye Disease. Metabolites 2023, 13, 733. [Google Scholar] [CrossRef]
  17. Kumar, N.R.; Praveen, M.; Narasimhan, R.; Khamar, P.; D’Souza, S.; Sinha-Roy, A.; Sethu, S.; Shetty, R.; Ghosh, A. Tear biomarkers in dry eye disease: Progress in the last decade. Indian J. Ophthalmol. 2023, 71, 1190–1202. [Google Scholar] [CrossRef]
  18. Zhao, L.; Zhang, Y.; Duan, H.; Yang, T.; Zhou, Y.; Ma, B.; Chen, Y.; Qi, H. Clinical Characteristics and Tear Film Biomarkers in Patients with Chronic Dry Eye Disease After Femtosecond Laser-Assisted Laser in Situ Keratomileusis. J. Refract. Surg. 2023, 39, 556–563. [Google Scholar] [CrossRef]
  19. Liu, R.; Gao, C.; Chen, H.; Li, Y.; Jin, Y.; Qi, H. Analysis of Th17-associated cytokines and clinical correlations in patients with dry eye disease. PLoS ONE 2017, 12, e0173301. [Google Scholar] [CrossRef] [PubMed]
  20. Kaushik, D.; Xu, B.; Kumar, M. Biomarkers in immunology: Their impact on immune function and response. Adv. Biomark. Sci. Technol. 2025, 7, 95–110. [Google Scholar] [CrossRef]
  21. Chu, L.; Wang, C.; Zhou, H. Inflammation mechanism and anti-inflammatory therapy of dry eye. Front. Med. 2024, 11, 1307682. [Google Scholar] [CrossRef] [PubMed]
  22. Perez, V.L.; Stern, M.E.; Pflugfelder, S.C. Inflammatory basis for dry eye disease flares. Exp. Eye Res. 2020, 201, 108294. [Google Scholar] [CrossRef]
  23. Gupta, S.; Shankar, S.; Bhatta, S.; Mishra, A.; Singh, A. Comparison of tear Matrix Metalloproteinase 9 (MMP-9) estimation with Schirmer’s test in Ocular Surface Disorders. Rom. J. Ophthalmol. 2024, 68, 225–232. [Google Scholar] [CrossRef]
  24. Lanza, N.L.; Valenzuela, F.; Perez, V.L.; Galor, A. The Matrix Metalloproteinase 9 Point-of-Care Test in Dry Eye. Ocul. Surf. 2016, 14, 189–195. [Google Scholar] [CrossRef]
  25. Kang, M.J.; Kim, H.S.; Kim, M.S.; Kim, E.C. The Correlation between Matrix Metalloproteinase-9 Point-of-Care Immunoassay, Tear Film Osmolarity, and Ocular Surface Parameters. J. Ophthalmol. 2022, 2022, 6132016. [Google Scholar] [CrossRef]
  26. Messmer, E.M.; von Lindenfels, V.; Garbe, A.; Kampik, A. Matrix Metalloproteinase 9 Testing in Dry Eye Disease Using a Commercially Available Point-of-Care Immunoassay. Ophthalmology 2016, 123, 2300–2308. [Google Scholar] [CrossRef]
  27. Shoari, A.; Kanavi, M.R.; Rasaee, M.J. Inhibition of matrix metalloproteinase-9 for the treatment of dry eye syndrome; a review study. Exp. Eye Res. 2021, 205, 108523. [Google Scholar] [CrossRef]
  28. Chotikavanich, S.; de Paiva, C.S.; Li, D.Q.; Chen, J.J.; Bian, F.; Farley, W.J.; Pflugfelder, S.C. Production and activity of matrix metalloproteinase-9 on the ocular surface increase in dysfunctional tear syndrome. Investig. Ophthalmol. Vis. Sci. 2009, 50, 3203–3209. [Google Scholar] [CrossRef] [PubMed]
  29. Jamerson, E.C.; Elhusseiny, A.M.; ElSheikh, R.H.; Eleiwa, T.K.; El Sayed, Y.M. Role of Matrix Metalloproteinase 9 in Ocular Surface Disorders. Eye Contact Lens 2020, 46 (Suppl. 2), S57–S63. [Google Scholar] [CrossRef] [PubMed]
  30. Aragona, P.; Aguennouz, M.; Rania, L.; Postorino, E.; Sommario, M.S.; Roszkowska, A.M.; De Pasquale, M.G.; Pisani, A.; Puzzolo, D. Matrix metalloproteinase 9 and transglutaminase 2 expression at the ocular surface in patients with different forms of dry eye disease. Ophthalmology 2015, 122, 62–71. [Google Scholar] [CrossRef]
  31. Caban, M.; Owczarek, K.; Lewandowska, U. The Role of Metalloproteinases and Their Tissue Inhibitors on Ocular Diseases: Focusing on Potential Mechanisms. Int. J. Mol. Sci. 2022, 23, 4256. [Google Scholar] [CrossRef]
  32. Solomon, A.; Dursun, D.; Liu, Z.; Xie, Y.; Macri, A.; Pflugfelder, S.C. Pro- and anti-inflammatory forms of interleukin-1 in the tear fluid and conjunctiva of patients with dry-eye disease. Investig. Ophthalmol. Vis. Sci. 2001, 42, 2283–2292. [Google Scholar]
  33. Na, K.S.; Mok, J.W.; Kim, J.Y.; Rho, C.R.; Joo, C.K. Correlations between tear cytokines, chemokines, and soluble receptors and clinical severity of dry eye disease. Investig. Ophthalmol. Vis. Sci. 2012, 53, 5443–5450. [Google Scholar] [CrossRef]
  34. Zhao, C.S.; Chen, Y.; Ying, G.S.; Asbell, P.A.; Dry Eye, A.; Management Study, G. Association of Tear Cytokine Ratios with Symptoms and Signs of Dry Eye Disease: Biomarker Data from the Dry Eye Assessment and Management Study. Curr. Eye Res. 2024, 49, 16–24. [Google Scholar] [CrossRef]
  35. Shahini, A.; Shahini, A. Role of interleukin-6-mediated inflammation in the pathogenesis of inflammatory bowel disease: Focus on the available therapeutic approaches and gut microbiome. J. Cell Commun. Signal 2023, 17, 55–74. [Google Scholar] [CrossRef] [PubMed]
  36. Yoon, K.C.; Jeong, I.Y.; Park, Y.G.; Yang, S.Y. Interleukin-6 and tumor necrosis factor-alpha levels in tears of patients with dry eye syndrome. Cornea 2007, 26, 431–437. [Google Scholar] [CrossRef] [PubMed]
  37. Dermer, H.; Theotoka, D.; Lee, C.J.; Chhadva, P.; Hackam, A.S.; Galor, A.; Kumar, N. Total Tear IgE Levels Correlate with Allergenic and Irritating Environmental Exposures in Individuals with Dry Eye. J. Clin. Med. 2019, 8, 1627. [Google Scholar] [CrossRef] [PubMed]
  38. Bao, J.; Tian, L.; Meng, Y.; Wu, B.; Wang, J.; He, J.; Shao, Q.; Wang, C.; Jie, Y.; Zhang, L. Total IgE in tears accurately reflects the severity and predicts the prognosis of seasonal allergic conjunctivitis. Clin. Transl. Allergy 2022, 12, e12139. [Google Scholar] [CrossRef]
  39. Tsai, C.Y.; Hong, C.; Hsu, M.Y.; Lai, T.T.; Huang, C.W.; Lu, C.Y.; Chen, W.L.; Cheng, C.M. Fluorescence-based reagent and spectrum-based optical reader for lactoferrin detection in tears: Differentiating Sjogren’s syndrome from non-Sjogren’s dry eye syndrome. Sci. Rep. 2024, 14, 14505. [Google Scholar] [CrossRef]
  40. Zhang, Y.; Lu, C.; Zhang, J. Lactoferrin and Its Detection Methods: A Review. Nutrients 2021, 13, 2492. [Google Scholar] [CrossRef]
  41. Zhang, Y.; Yan, P.; Tang, H.; Zhang, J. Rapid detection of tear lactoferrin for diagnosis of dry eyes by using fluorescence polarization-based aptasensor. Sci. Rep. 2023, 13, 15179. [Google Scholar] [CrossRef]
  42. Connell, S.; Kawashima, M.; Nakamura, S.; Imada, T.; Yamamoto, H.; Tsubota, K.; Fukuda, S. Lactoferrin Ameliorates Dry Eye Disease Potentially through Enhancement of Short-Chain Fatty Acid Production by Gut Microbiota in Mice. Int. J. Mol. Sci. 2021, 22, 12384. [Google Scholar] [CrossRef]
  43. Karnati, R.; Laurie, D.E.; Laurie, G.W. Lacritin and the tear proteome as natural replacement therapy for dry eye. Exp. Eye Res. 2013, 117, 39–52. [Google Scholar] [CrossRef] [PubMed]
  44. Dias-Teixeira, K.; Horton, X.; McKown, R.; Romano, J.; Laurie, G.W. The Lacritin-Syndecan-1-Heparanase Axis in Dry Eye Disease. Adv. Exp. Med. Biol. 2020, 1221, 747–757. [Google Scholar] [CrossRef]
  45. Georgiev, G.A.; Gh, M.S.; Romano, J.; Dias Teixeira, K.L.; Struble, C.; Ryan, D.S.; Sia, R.K.; Kitt, J.P.; Harris, J.M.; Hsu, K.L.; et al. Lacritin proteoforms prevent tear film collapse and maintain epithelial homeostasis. J. Biol. Chem. 2021, 296, 100070. [Google Scholar] [CrossRef]
  46. Vijmasi, T.; Chen, F.Y.; Balasubbu, S.; Gallup, M.; McKown, R.L.; Laurie, G.W.; McNamara, N.A. Topical administration of lacritin is a novel therapy for aqueous-deficient dry eye disease. Investig. Ophthalmol. Vis. Sci. 2014, 55, 5401–5409. [Google Scholar] [CrossRef] [PubMed]
  47. McKown, R.L.; Wang, N.; Raab, R.W.; Karnati, R.; Zhang, Y.; Williams, P.B.; Laurie, G.W. Lacritin and other new proteins of the lacrimal functional unit. Exp. Eye Res. 2009, 88, 848–858. [Google Scholar] [CrossRef]
  48. deLuise, V.P.; Tabbara, K.F. Quantitation of tear lysozyme levels in dry-eye disorders. Arch. Ophthalmol. 1983, 101, 634–635. [Google Scholar] [CrossRef] [PubMed]
  49. Avisar, R.; Menache, R.; Shaked, P.; Rubinstein, J.; Machtey, I.; Savir, H. Lysozyme content of tears in patients with Sjogren’s syndrome and rheumatoid arthritis. Am. J. Ophthalmol. 1979, 87, 148–151. [Google Scholar] [CrossRef]
  50. Jia, Z.; Wei, W.; Tu, K.; Fang, B.; Zhang, M.; Shi, L. Point-of-care monitoring of dry eye disease using lysozyme in tear based on commercial pregnancy test strips. Sens. Actuators B Chem. 2023, 378, 133179. [Google Scholar] [CrossRef]
  51. Berra, M.; Galperin, G.; Berra, F.; Marquez, M.I.; Mandaradoni, M.; Tau, J.; Berra, A. Tear Lysozyme in Sjogren s syndrome, Meibomian gland dysfunction, and non-dry-eye. Arq. Bras. Oftalmol. 2021, 85, 103–108. [Google Scholar] [CrossRef]
  52. Lee, D.; Song, S.; Cho, G.; Dalle Ore, L.C.; Malmstadt, N.; Fuwad, A.; Kim, S.M.; Jeon, T.J. Elucidating the Molecular Interactions between Lipids and Lysozyme: Evaporation Resistance and Bacterial Barriers for Dry Eye Disease. Nano Lett. 2023, 23, 9451–9460. [Google Scholar] [CrossRef]
  53. Yeh, P.T.; Casey, R.; Glasgow, B.J. A novel fluorescent lipid probe for dry eye: Retrieval by tear lipocalin in humans. Investig. Ophthalmol. Vis. Sci. 2013, 54, 1398–1410. [Google Scholar] [CrossRef]
  54. Gasymov, O.K.; Abduragimov, A.R.; Prasher, P.; Yusifov, T.N.; Glasgow, B.J. Tear lipocalin: Evidence for a scavenging function to remove lipids from the human corneal surface. Investig. Ophthalmol. Vis. Sci. 2005, 46, 3589–3596. [Google Scholar] [CrossRef]
  55. Yamada, M.; Mochizuki, H.; Kawai, M.; Tsubota, K.; Bryce, T.J. Decreased tear lipocalin concentration in patients with meibomian gland dysfunction. Br. J. Ophthalmol. 2005, 89, 803–805. [Google Scholar] [CrossRef]
  56. Subbaraman, L.; Mistry, R.; Thangavelu, M.; Jones, L. Quantification of lipocalin-1 in tears and contact lens deposits using a sandwich ELISA technique. Contact Lens Anterior Eye 2013, 36, e45–e46. [Google Scholar] [CrossRef]
  57. Gipson, I.K.; Hori, Y.; Argueso, P. Character of ocular surface mucins and their alteration in dry eye disease. Ocul. Surf. 2004, 2, 131–148. [Google Scholar] [CrossRef] [PubMed]
  58. Hori, Y. Secreted Mucins on the Ocular Surface. Investig. Ophthalmol. Vis. Sci. 2018, 59, DES151–DES156. [Google Scholar] [CrossRef] [PubMed]
  59. Li, G.; Lu, P.; Song, H.; Zheng, Q.; Nan, K. Expression of mucins MUC5AC and MUC19 on the ocular surface in dry eye syndrome model of ovariectomized female rabbits. Adv. Clin. Exp. Med. 2019, 28, 165–169. [Google Scholar] [CrossRef] [PubMed]
  60. Carrington, S.D.; Goodall, C.; Myerscough, N.; Corfield, A.P. Canine ocular mucins in health and dry eye disease. Biochem. Soc. Trans. 1993, 21, 484S. [Google Scholar] [CrossRef]
  61. Shamloo, K.; Barbarino, A.; Alfuraih, S.; Sharma, A. Graft Versus Host Disease-Associated Dry Eye: Role of Ocular Surface Mucins and the Effect of Rebamipide, a Mucin Secretagogue. Investig. Ophthalmol. Vis. Sci. 2019, 60, 4511–4519. [Google Scholar] [CrossRef]
  62. Portal, C.; Gouyer, V.; Gottrand, F.; Desseyn, J.L. Ocular mucins in dry eye disease. Exp. Eye Res. 2019, 186, 107724. [Google Scholar] [CrossRef]
  63. Floyd, A.M.; Zhou, X.; Evans, C.; Rompala, O.J.; Zhu, L.; Wang, M.; Chen, Y. Mucin deficiency causes functional and structural changes of the ocular surface. PLoS ONE 2012, 7, e50704. [Google Scholar] [CrossRef]
  64. Aldina, R.; Sujuti, H.; Permatasari, N.; Widodo, M.A. The effects of genistein on estrogen receptor-β, IL-1β levels, and MUC5AC expression in ovariectomized rats with dry eye. Clin. Nutr. Exp. 2019, 27, 21–28. [Google Scholar] [CrossRef]
  65. Duan, H.; Yang, T.; Zhou, Y.; Ma, B.; Zhao, L.; Chen, J.; Qi, H. Comparison of mucin levels at the ocular surface of visual display terminal users with and without dry eye disease. BMC Ophthalmol. 2023, 23, 189. [Google Scholar] [CrossRef] [PubMed]
  66. Corrales, R.M.; Narayanan, S.; Fernandez, I.; Mayo, A.; Galarreta, D.J.; Fuentes-Paez, G.; Chaves, F.J.; Herreras, J.M.; Calonge, M. Ocular mucin gene expression levels as biomarkers for the diagnosis of dry eye syndrome. Investig. Ophthalmol. Vis. Sci. 2011, 52, 8363–8369. [Google Scholar] [CrossRef]
  67. Xu, K.; Liu, X.N.; Zhang, H.B.; Zhu, X.P.; Zhang, X.J. Tear film instability is associated with weakened colocalization between occludin and MUC5AC in scopolamine-induced dry eye disease (DED) rats. Int. Ophthalmol. 2023, 43, 463–473. [Google Scholar] [CrossRef] [PubMed]
  68. Blautain, B.; Rabut, G.; Dupas, B.; Riancho, L.; Liang, H.; Luzu, J.; Labbe, A.; Garrigue, J.S.; Brignole-Baudouin, F.; Baudouin, C.; et al. Multimodal Approach in Dry Eye Disease Combining In Vivo Confocal Microscopy and HLA-DR Expression. Transl. Vis. Sci. Technol. 2024, 13, 39. [Google Scholar] [CrossRef] [PubMed]
  69. Roy, N.S.; Wei, Y.; Yu, Y.; Ying, G.S.; Kuklinski, E.; Barry, B.; Maguire, M.G.; Dana, R.; Brightwell-Arnold, M.; Asbell, P.A.; et al. Conjunctival HLA-DR Expression and Its Association with Symptoms and Signs in the DREAM Study. Transl. Vis. Sci. Technol. 2019, 8, 31. [Google Scholar] [CrossRef]
  70. Epstein, S.P.; Gadaria-Rathod, N.; Wei, Y.; Maguire, M.G.; Asbell, P.A. HLA-DR expression as a biomarker of inflammation for multicenter clinical trials of ocular surface disease. Exp. Eye Res. 2013, 111, 95–104. [Google Scholar] [CrossRef]
  71. Roy, N.S.; Yu, Y.; Ying, G.S.; Maguire, M.G.; Asbell, P.A.; Group, D.S. Effect of Omega-3 on HLA-DR Expression by Conjunctival Cells and Tear Cytokine Concentrations in the Dry Eye Assessment and Management Study. Eye Contact Lens 2022, 48, 384–390. [Google Scholar] [CrossRef]
  72. Fernandez, K.B.; Epstein, S.P.; Raynor, G.S.; Sheyman, A.T.; Massingale, M.L.; Dentone, P.G.; Landegger, L.D.; Asbell, P.A. Modulation of HLA-DR in dry eye patients following 30 days of treatment with a lubricant eyedrop solution. Clin. Ophthalmol. 2015, 9, 1137–1145. [Google Scholar] [CrossRef]
  73. Wu, J.; Li, G.J.; Niu, J.; Wen, F.; Han, L. Analyze interleukin-1beta, interleukin-6, and tumor necrosis factor-alpha levels in dry eye and the therapeutic effect of cyclosporine A. World J. Clin. Cases 2024, 12, 5665–5672. [Google Scholar] [CrossRef] [PubMed]
  74. Mrugacz, M.; Ostrowska, L.; Bryl, A.; Szulc, A.; Zelazowska-Rutkowska, B.; Mrugacz, G. Pro-inflammatory cytokines associated with clinical severity of dry eye disease of patients with depression. Adv. Med. Sci. 2017, 62, 338–344. [Google Scholar] [CrossRef]
  75. Wu, X.; Chen, X.; Ma, Y.; Lin, X.; Yu, X.; He, S.; Luo, C.; Xu, W. Analysis of tear inflammatory molecules and clinical correlations in evaporative dry eye disease caused by meibomian gland dysfunction. Int. Ophthalmol. 2020, 40, 3049–3058. [Google Scholar] [CrossRef]
  76. Massingale, M.L.; Li, X.; Vallabhajosyula, M.; Chen, D.; Wei, Y.; Asbell, P.A. Analysis of inflammatory cytokines in the tears of dry eye patients. Cornea 2009, 28, 1023–1027. [Google Scholar] [CrossRef] [PubMed]
  77. Bang, S.P.; Yeon, C.Y.; Adhikari, N.; Neupane, S.; Kim, H.; Lee, D.C.; Son, M.J.; Lee, H.G.; Kim, J.Y.; Jun, J.H. Cyclosporine A eyedrops with self-nanoemulsifying drug delivery systems have improved physicochemical properties and efficacy against dry eye disease in a murine dry eye model. PLoS ONE 2019, 14, e0224805. [Google Scholar] [CrossRef]
  78. Sun, X.; Zhang, J.; Li, X.; Li, Y.; Zhao, X.; Sun, X.; Li, Y. Fenofibrate inhibits activation of cGAS-STING pathway by alleviating mitochondrial damage to attenuate inflammatory response in diabetic dry eye. Free Radic. Biol. Med. 2025, 235, 364–378. [Google Scholar] [CrossRef]
  79. Simmons, K.T.; Xiao, Y.; Pflugfelder, S.C.; de Paiva, C.S. Inflammatory Response to Lipopolysaccharide on the Ocular Surface in a Murine Dry Eye Model. Investig. Ophthalmol. Vis. Sci. 2016, 57, 2443–2451. [Google Scholar] [CrossRef] [PubMed]
  80. Yamaguchi, T. Inflammatory Response in Dry Eye. Investig. Ophthalmol. Vis. Sci. 2018, 59, DES192–DES199. [Google Scholar] [CrossRef]
  81. Yu, L.; Yu, C.; Dong, H.; Mu, Y.; Zhang, R.; Zhang, Q.; Liang, W.; Li, W.; Wang, X.; Zhang, L. Recent Developments About the Pathogenesis of Dry Eye Disease: Based on Immune Inflammatory Mechanisms. Front. Pharmacol. 2021, 12, 732887. [Google Scholar] [CrossRef]
  82. Blanco-Vazquez, M.; Vazquez, A.; Fernandez, I.; Novo-Diez, A.; Martinez-Plaza, E.; Garcia-Vazquez, C.; Gonzalez-Garcia, M.J.; Sobas, E.M.; Calonge, M.; Enriquez-de-Salamanca, A. Inflammation-related molecules in tears of patients with chronic ocular pain and dry eye disease. Exp. Eye Res. 2022, 219, 109057. [Google Scholar] [CrossRef]
  83. Bruscolini, A.; Lambiase, A.; Segatto, M.; La Cava, M.; Nebbioso, M.; Sacchetti, M. Evaluation of IL8 pathway on the ocular surface: New insights in patients with ocular mucous membrane pemphigoid. Acta Ophthalmol. 2020, 98, e173–e177. [Google Scholar] [CrossRef]
  84. Galvez, B.G.; Martinez-Perez, C.; Villa-Collar, C.; Alvarez-Peregrina, C.; Sanchez-Tena, M.A. Influence of Cytokines on Inflammatory Eye Diseases: A Citation Network Study. J. Clin. Med. 2022, 11, 661. [Google Scholar] [CrossRef]
  85. Lopez-Miguel, A.; Teson, M.; Martin-Montanez, V.; Enriquez-de-Salamanca, A.; Stern, M.E.; Gonzalez-Garcia, M.J.; Calonge, M. Clinical and Molecular Inflammatory Response in Sjogren Syndrome-Associated Dry Eye Patients Under Desiccating Stress. Am. J. Ophthalmol. 2016, 161, 133–141.e2. [Google Scholar] [CrossRef]
  86. Lam, H.; Bleiden, L.; de Paiva, C.S.; Farley, W.; Stern, M.E.; Pflugfelder, S.C. Tear cytokine profiles in dysfunctional tear syndrome. Am. J. Ophthalmol. 2009, 147, 198–205.e1. [Google Scholar] [CrossRef]
  87. El Annan, J.; Goyal, S.; Zhang, Q.; Freeman, G.J.; Sharpe, A.H.; Dana, R. Regulation of T-cell chemotaxis by programmed death-ligand 1 (PD-L1) in dry eye-associated corneal inflammation. Investig. Ophthalmol. Vis. Sci. 2010, 51, 3418–3423. [Google Scholar] [CrossRef] [PubMed]
  88. Nagar, S.; Ajouz, L.; Nichols, K.K.; Kumar, S.; Zhao, C.; Naidoo, K.K.; Robinson, M.R.; Borchman, D. Relationship Between Human Meibum Lipid Composition and the Severity of Meibomian Gland Dysfunction: A Spectroscopic Analysis. Investig. Ophthalmol. Vis. Sci. 2023, 64, 22. [Google Scholar] [CrossRef] [PubMed]
  89. Asiedu, K. Candidate Molecular Compounds as Potential Indicators for Meibomian Gland Dysfunction. Front. Med. 2022, 9, 873538. [Google Scholar] [CrossRef]
  90. Zhao, H.; Wu, S.N.; Shao, Y.; Xiao, D.; Tang, L.Y.; Cheng, Z.; Peng, J. Lipidomics Profiles Revealed Alterations in Patients with Meibomian Gland Dysfunction After Exposure to Intense Pulsed Light. Front. Neurol. 2022, 13, 827544. [Google Scholar] [CrossRef] [PubMed]
  91. Lam, S.M.; Tong, L.; Yong, S.S.; Li, B.; Chaurasia, S.S.; Shui, G.; Wenk, M.R. Meibum lipid composition in Asians with dry eye disease. PLoS ONE 2011, 6, e24339. [Google Scholar] [CrossRef]
  92. Nguyen, A.; Naidoo, K.K.; Ajouz, L.; Xu, X.; Zhao, C.; Robinson, M.R.; Borchman, D. Changes in Human Meibum Lipid Composition Related to the Presence and Severity of Meibomian Gland Dysfunction. J. Ocul. Pharmacol. Ther. 2024, 40, 562–570. [Google Scholar] [CrossRef]
  93. Garcia-Queiruga, J.; Pena-Verdeal, H.; Sabucedo-Villamarin, B.; Paz-Tarrio, M.; Guitian-Fernandez, E.; Garcia-Resua, C.; Yebra-Pimentel, E.; Giraldez, M.J. Meibum Lipidomic Analysis in Evaporative Dry Eye Subjects. Int. J. Mol. Sci. 2024, 25, 4782. [Google Scholar] [CrossRef] [PubMed]
  94. Sheppard, J.D.; Nichols, K.K. Dry Eye Disease Associated with Meibomian Gland Dysfunction: Focus on Tear Film Characteristics and the Therapeutic Landscape. Ophthalmol. Ther. 2023, 12, 1397–1418. [Google Scholar] [CrossRef]
  95. Mondal, K.; Mandal, N. Role of Bioactive Sphingolipids in Inflammation and Eye Diseases. Adv. Exp. Med. Biol. 2019, 1161, 149–167. [Google Scholar] [CrossRef] [PubMed]
  96. Paranjpe, V.; Galor, A.; Grambergs, R.; Mandal, N. The role of sphingolipids in meibomian gland dysfunction and ocular surface inflammation. Ocul. Surf. 2022, 26, 100–110. [Google Scholar] [CrossRef]
  97. Ham, B.M.; Cole, R.B.; Jacob, J.T. Identification and comparison of the polar phospholipids in normal and dry eye rabbit tears by MALDI-TOF mass spectrometry. Investig. Ophthalmol. Vis. Sci. 2006, 47, 3330–3338. [Google Scholar] [CrossRef] [PubMed]
  98. Borchman, D. Lipid conformational order and the etiology of cataract and dry eye. J. Lipid Res. 2021, 62, 100039. [Google Scholar] [CrossRef]
  99. Miyamoto, M.; Sassa, T.; Sawai, M.; Kihara, A. Lipid polarity gradient formed by omega-hydroxy lipids in tear film prevents dry eye disease. Elife 2020, 9, e53582. [Google Scholar] [CrossRef]
  100. Wan, X.; Zhang, Y.; Zhang, K.; Mou, Y.; Jin, X.; Huang, X. The alterations of ocular surface metabolism and the related immunity inflammation in dry eye. Adv. Ophthalmol. Pract. Res. 2025, 5, 1–12. [Google Scholar] [CrossRef]
  101. Jantti, J.; Viitaja, T.; Sevon, J.; Lajunen, T.; Raitanen, J.E.; Schlegel, C.; Viljanen, M.; Paananen, R.O.; Moilanen, J.; Ruponen, M.; et al. Early-Stage Development of an Anti-Evaporative Liposomal Formulation for the Potential Treatment of Dry Eyes. ACS Pharmacol. Transl. Sci. 2023, 6, 1518–1530. [Google Scholar] [CrossRef] [PubMed]
  102. Nishiwaki-Dantas, M.C.; de Freitas, D.; Fornazari, D.; Dos Santos, M.S.; Wakamatsu, T.H.; Barquilha, C.N.; Ferrer, M.T.; Holzhausen, H.C.N.; Alves, M. Phospholipid Nanoemulsion-Based Ocular Lubricant for the Treatment of Dry Eye Subtypes: A Multicenter and Prospective Study. Ophthalmol. Ther. 2024, 13, 3203–3213. [Google Scholar] [CrossRef] [PubMed]
  103. Singh, S.; Hammer, C.M.; Paulsen, F. Urea and ocular surface: Synthesis, secretion and its role in tear film homeostasis. Ocul. Surf. 2023, 27, 41–47. [Google Scholar] [CrossRef]
  104. Chai, P.; Zhao, F.; Jia, R.; Zhou, X.; Fan, X. Lactate/lactylation in ocular development and diseases. Trends Mol. Med. 2024. [Google Scholar] [CrossRef]
  105. Mondal, H.; Kim, H.J.; Mohanto, N.; Jee, J.P. A Review on Dry Eye Disease Treatment: Recent Progress, Diagnostics, and Future Perspectives. Pharmaceutics 2023, 15, 990. [Google Scholar] [CrossRef]
  106. Chen, X.; Zhang, C.; Peng, F.; Wu, L.; Zhuo, D.; Wang, L.; Zhang, M.; Li, Z.; Tian, L.; Jie, Y.; et al. Identification of glutamine as a potential therapeutic target in dry eye disease. Signal Transduct. Target. Ther. 2025, 10, 27. [Google Scholar] [CrossRef]
  107. Galbis-Estrada, C.; Pinazo-Duran, M.D.; Martinez-Castillo, S.; Morales, J.M.; Monleon, D.; Zanon-Moreno, V. A metabolomic approach to dry eye disorders. The role of oral supplements with antioxidants and omega 3 fatty acids. Mol. Vis. 2015, 21, 555–567. [Google Scholar]
  108. Jiang, Y.; Yang, C.; Zheng, Y.; Liu, Y.; Chen, Y. A Set of Global Metabolomic Biomarker Candidates to Predict the Risk of Dry Eye Disease. Front. Cell Dev. Biol. 2020, 8, 344. [Google Scholar] [CrossRef]
  109. Yazdani, M.; Elgstoen, K.B.P.; Rootwelt, H.; Shahdadfar, A.; Utheim, O.A.; Utheim, T.P. Tear Metabolomics in Dry Eye Disease: A Review. Int. J. Mol. Sci. 2019, 20, 3755. [Google Scholar] [CrossRef]
  110. Seen, S.; Tong, L. Dry eye disease and oxidative stress. Acta Ophthalmol. 2018, 96, e412–e420. [Google Scholar] [CrossRef] [PubMed]
  111. Dogru, M.; Kojima, T.; Simsek, C.; Tsubota, K. Potential Role of Oxidative Stress in Ocular Surface Inflammation and Dry Eye Disease. Investig. Ophthalmol. Vis. Sci. 2018, 59, DES163–DES168. [Google Scholar] [CrossRef]
  112. Bu, J.; Liu, Y.; Zhang, R.; Lin, S.; Zhuang, J.; Sun, L.; Zhang, L.; He, H.; Zong, R.; Wu, Y.; et al. Potential New Target for Dry Eye Disease-Oxidative Stress. Antioxidants 2024, 13, 422. [Google Scholar] [CrossRef]
  113. Ouyang, W.; Yan, D.; Hu, J.; Liu, Z. Multifaceted mitochondrial as a novel therapeutic target in dry eye: Insights and interventions. Cell Death Discov. 2024, 10, 398. [Google Scholar] [CrossRef] [PubMed]
  114. Shi, H.; Zheng, L.Y.; Zhang, P.; Yu, C.Q. miR-146a and miR-155 expression in PBMCs from patients with Sjogren’s syndrome. J. Oral Pathol. Med. 2014, 43, 792–797. [Google Scholar] [CrossRef] [PubMed]
  115. Zilahi, E.; Tarr, T.; Papp, G.; Griger, Z.; Sipka, S.; Zeher, M. Increased microRNA-146a/b, TRAF6 gene and decreased IRAK1 gene expressions in the peripheral mononuclear cells of patients with Sjogren’s syndrome. Immunol. Lett. 2012, 141, 165–168. [Google Scholar] [CrossRef]
  116. Sun, H.Y.; Lv, A.K.; Yao, H. Relationship of miRNA-146a to primary Sjogren’s syndrome and to systemic lupus erythematosus: A meta-analysis. Rheumatol. Int. 2017, 37, 1311–1316. [Google Scholar] [CrossRef]
  117. Wei, Y.; Li, N.; Zhao, L.; Yang, C.; Ma, B.; Li, X.; Wei, R.; Nian, H. MicroRNAs and Autoimmune-Mediated Eye Diseases. Front. Cell Dev. Biol. 2020, 8, 818. [Google Scholar] [CrossRef] [PubMed]
  118. Benavides-Aguilar, J.A.; Morales-Rodriguez, J.I.; Ambriz-Gonzalez, H.; Ruiz-Manriquez, L.M.; Banerjee, A.; Pathak, S.; Duttaroy, A.K.; Paul, S. The regulatory role of microRNAs in common eye diseases: A brief review. Front. Genet. 2023, 14, 1152110. [Google Scholar] [CrossRef]
  119. Rassi, D.M.; De Paiva, C.S.; Dias, L.C.; Modulo, C.M.; Adriano, L.; Fantucci, M.Z.; Rocha, E.M. Review: MicroRNAS in ocular surface and dry eye diseases. Ocul. Surf. 2017, 15, 660–669. [Google Scholar] [CrossRef]
  120. Kessal, K.; Liang, H.; Rabut, G.; Daull, P.; Garrigue, J.S.; Docquier, M.; Melik Parsadaniantz, S.; Baudouin, C.; Brignole-Baudouin, F. Conjunctival Inflammatory Gene Expression Profiling in Dry Eye Disease: Correlations with HLA-DRA and HLA-DRB1. Front. Immunol. 2018, 9, 2271. [Google Scholar] [CrossRef]
  121. Brignole-Baudouin, F.; Riancho, L.; Ismail, D.; Deniaud, M.; Amrane, M.; Baudouin, C. Correlation Between the Inflammatory Marker HLA-DR and Signs and Symptoms in Moderate to Severe Dry Eye Disease. Investig. Ophthalmol. Vis. Sci. 2017, 58, 2438–2448. [Google Scholar] [CrossRef] [PubMed]
  122. Paik, B.; Tong, L. Polymorphisms in Lymphotoxin-Alpha as the “Missing Link” in Prognosticating Favourable Response to Omega-3 Supplementation for Dry Eye Disease: A Narrative Review. Int. J. Mol. Sci. 2023, 24, 4236. [Google Scholar] [CrossRef]
  123. Roshandel, D.; Semnani, F.; Rayati Damavandi, A.; Masoudi, A.; Baradaran-Rafii, A.; Watson, S.L.; Morgan, W.H.; McLenachan, S. Genetic predisposition to ocular surface disorders and opportunities for gene-based therapies. Ocul. Surf. 2023, 29, 150–165. [Google Scholar] [CrossRef]
  124. Kim, W.; Woo, I.H.; Eom, Y.; Song, J.S. Short-term changes in tear osmolarity after instillation of different osmolarity eye drops in patients with dry eye. Sci. Rep. 2023, 13, 11012. [Google Scholar] [CrossRef]
  125. Baudouin, C.; Aragona, P.; Messmer, E.M.; Tomlinson, A.; Calonge, M.; Boboridis, K.G.; Akova, Y.A.; Geerling, G.; Labetoulle, M.; Rolando, M. Role of hyperosmolarity in the pathogenesis and management of dry eye disease: Proceedings of the OCEAN group meeting. Ocul. Surf. 2013, 11, 246–258. [Google Scholar] [CrossRef]
  126. Lemp, M.A.; Bron, A.J.; Baudouin, C.; Benitez Del Castillo, J.M.; Geffen, D.; Tauber, J.; Foulks, G.N.; Pepose, J.S.; Sullivan, B.D. Tear osmolarity in the diagnosis and management of dry eye disease. Am. J. Ophthalmol. 2011, 151, 792–798.e1. [Google Scholar] [CrossRef]
  127. Tashbayev, B.; Utheim, T.P.; Utheim, O.A.; Raeder, S.; Jensen, J.L.; Yazdani, M.; Lagali, N.; Vitelli, V.; Dartt, D.A.; Chen, X. Utility of Tear Osmolarity Measurement in Diagnosis of Dry Eye Disease. Sci. Rep. 2020, 10, 5542. [Google Scholar] [CrossRef]
  128. Tomlinson, A.; Khanal, S.; Ramaesh, K.; Diaper, C.; McFadyen, A. Tear film osmolarity: Determination of a referent for dry eye diagnosis. Investig. Ophthalmol. Vis. Sci. 2006, 47, 4309–4315. [Google Scholar] [CrossRef]
  129. Suzuki, M.; Massingale, M.L.; Ye, F.; Godbold, J.; Elfassy, T.; Vallabhajosyula, M.; Asbell, P.A. Tear osmolarity as a biomarker for dry eye disease severity. Investig. Ophthalmol. Vis. Sci. 2010, 51, 4557–4561. [Google Scholar] [CrossRef] [PubMed]
  130. Galor, A.; Lighthizer, N. Corneal Sensitivity Testing Procedure for Ophthalmologic and Optometric Patients. J. Vis. Exp. 2024, 210, e66597. [Google Scholar] [CrossRef] [PubMed]
  131. Merayo-Lloves, J.; Gomez Martin, C.; Lozano-Sanroma, J.; Renedo Laguna, C. Assessment and safety of the new esthesiometer BRILL: Comparison with the Cochet-Bonnet Esthesiometer. Eur. J. Ophthalmol. 2024, 34, 1036–1045. [Google Scholar] [CrossRef] [PubMed]
  132. Ruiz-Lozano, R.E.; Quiroga-Garza, M.E.; Ramos-DÁVila, E.M.; PantaleÓN-GarcÍA, J.; Khodor, A.L.I.; Komai, S.; Rodriguez-Gutierrez, L.A.; Ma, S.; Mousa, H.M.; Mattes, R.; et al. Comparative Evaluation of the Corneal Sensitivity Thresholds between the Novel Non-Contact and Cochet-Bonnet Esthesiometers. Am. J. Ophthalmol. 2025, 271, 407–416. [Google Scholar] [CrossRef]
  133. Vazquez, A.; Blanco-Vazquez, M.; Martinez-Plaza, E.; Sobas, E.M.; Gonzalez-Garcia, M.J.; Lopez-Miguel, A.; Ortega, E.; Enriquez-de-Salamanca, A.; Calonge, M. Corneal Sensory Changes and Nerve Plexus Abnormalities in Chronic Neuropathic Ocular Pain and Dry Eye Postrefractive Surgery. Am. J. Ophthalmol. 2025, 276, 170–185. [Google Scholar] [CrossRef]
  134. Vidas Pauk, S.; Petricek, I.; Jukic, T.; Popovic-Suic, S.; Tomic, M.; Kalauz, M.; Jandrokovic, S.; Masnec, S. Noninvasive Tear Film Break-up Time Assessment Using Handheld Lipid Layer Examination Instrument. Acta Clin. Croat. 2019, 58, 63–71. [Google Scholar] [CrossRef]
  135. Tsubota, K. Short Tear Film Breakup Time-Type Dry Eye. Investig. Ophthalmol. Vis. Sci. 2018, 59, DES64–DES70. [Google Scholar] [CrossRef] [PubMed]
  136. Correa-Sandoval, D.C.; Quintanilla-Treviño, P.M.; Amparo, F.; Garza-Leon, M.A. Noninvasive tear breakup time evaluation with multifunctional topography supports the diagnosis of evaporative dry eye disease. Pan-Am. J. Ophthalmol. 2024, 6, 80. [Google Scholar] [CrossRef]
  137. Yazdani, M.; Fiskadal, J.; Chen, X.; Utheim, O.A.; Raeder, S.; Vitelli, V.; Utheim, T.P. Tear Film Break-Up Time and Dry Eye Disease Severity in a Large Norwegian Cohort. J. Clin. Med. 2021, 10, 884. [Google Scholar] [CrossRef]
  138. El Barche, F.Z.; Benyoussef, A.A.; El Habib Daho, M.; Lamard, A.; Quellec, G.; Cochener, B.; Lamard, M. Automated tear film break-up time measurement for dry eye diagnosis using deep learning. Sci. Rep. 2024, 14, 11723. [Google Scholar] [CrossRef]
  139. Pondelis, N.; Dieckmann, G.M.; Jamali, A.; Kataguiri, P.; Senchyna, M.; Hamrah, P. Infrared meibography allows detection of dimensional changes in meibomian glands following intranasal neurostimulation. Ocul. Surf. 2020, 18, 511–516. [Google Scholar] [CrossRef]
  140. Palamar, M.; Kiyat, P.; Ertam, I.; Yagci, A. Evaluation of dry eye and meibomian gland dysfunction with meibography in vitiligo. Eye 2017, 31, 1074–1077. [Google Scholar] [CrossRef] [PubMed]
  141. Wise, R.J.; Sobel, R.K.; Allen, R.C. Meibography: A review of techniques and technologies. Saudi J. Ophthalmol. 2012, 26, 349–356. [Google Scholar] [CrossRef]
  142. Li, S.; Wang, Y.; Yu, C.; Li, Q.; Chang, P.; Wang, D.; Li, Z.; Zhao, Y.; Zhang, H.; Tang, N.; et al. Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features. Investig. Ophthalmol. Vis. Sci. 2023, 64, 43. [Google Scholar] [CrossRef]
  143. Alhatem, A.; Cavalcanti, B.; Hamrah, P. In vivo confocal microscopy in dry eye disease and related conditions. Semin. Ophthalmol. 2012, 27, 138–148. [Google Scholar] [CrossRef] [PubMed]
  144. Aggarwal, S.; Kheirkhah, A.; Cavalcanti, B.M.; Cruzat, A.; Jamali, A.; Hamrah, P. Correlation of corneal immune cell changes with clinical severity in dry eye disease: An in vivo confocal microscopy study. Ocul. Surf. 2021, 19, 183–189. [Google Scholar] [CrossRef] [PubMed]
  145. Shetty, R.; Dua, H.S.; Tong, L.; Kundu, G.; Khamar, P.; Gorimanipalli, B.; D’Souza, S. Role of in vivo confocal microscopy in dry eye disease and eye pain. Indian J. Ophthalmol. 2023, 71, 1099–1104. [Google Scholar] [CrossRef]
  146. Sim, R.; Yong, K.; Liu, Y.C.; Tong, L. In Vivo Confocal Microscopy in Different Types of Dry Eye and Meibomian Gland Dysfunction. J. Clin. Med. 2022, 11, 2349. [Google Scholar] [CrossRef]
  147. He, J.; Ogawa, Y.; Mukai, S.; Saijo-Ban, Y.; Kamoi, M.; Uchino, M.; Yamane, M.; Ozawa, N.; Fukui, M.; Mori, T.; et al. In Vivo Confocal Microscopy Evaluation of Ocular Surface with Graft-Versus-Host Disease-Related Dry Eye Disease. Sci. Rep. 2017, 7, 10720. [Google Scholar] [CrossRef] [PubMed]
  148. Nicolle, P.; Liang, H.; Reboussin, E.; Rabut, G.; Warcoin, E.; Brignole-Baudouin, F.; Melik-Parsadaniantz, S.; Baudouin, C.; Labbe, A.; Reaux-Le Goazigo, A. Proinflammatory Markers, Chemokines, and Enkephalin in Patients Suffering from Dry Eye Disease. Int. J. Mol. Sci. 2018, 19, 1221. [Google Scholar] [CrossRef]
  149. Walter, S.D.; Gronert, K.; McClellan, A.L.; Levitt, R.C.; Sarantopoulos, K.D.; Galor, A. omega-3 Tear Film Lipids Correlate with Clinical Measures of Dry Eye. Investig. Ophthalmol. Vis. Sci. 2016, 57, 2472–2478. [Google Scholar] [CrossRef]
  150. Huang, S.C.; Lei, Y.P.; Hsiao, M.C.; Hsieh, Y.K.; Tang, Q.P.; Chen, C.; Hsu, M.Y. Multicomponent Dietary Supplementation: Impact on Tear Secretion and Ocular Surface Inflammation in Dry Eye Syndrome Patients. Antioxidants 2025, 14, 103. [Google Scholar] [CrossRef]
  151. Hussain, M.; Shtein, R.M.; Pistilli, M.; Maguire, M.G.; Oydanich, M.; Asbell, P.A.; Group, D.S.R. The Dry Eye Assessment and Management (DREAM) extension study—A randomized clinical trial of withdrawal of supplementation with omega-3 fatty acid in patients with dry eye disease. Ocul. Surf. 2020, 18, 47–55. [Google Scholar] [CrossRef]
  152. Khanal, S.; Ngo, W.; Nichols, K.K.; Wilson, L.; Barnes, S.; Nichols, J.J. Human meibum and tear film derived (O-acyl)-omega-hydroxy fatty acids in meibomian gland dysfunction. Ocul. Surf. 2021, 21, 118–128. [Google Scholar] [CrossRef]
  153. Bland, H.C.; Moilanen, J.A.; Ekholm, F.S.; Paananen, R.O. Investigating the Role of Specific Tear Film Lipids Connected to Dry Eye Syndrome: A Study on O-Acyl-omega-hydroxy Fatty Acids and Diesters. Langmuir 2019, 35, 3545–3552. [Google Scholar] [CrossRef] [PubMed]
  154. Viitaja, T.; Raitanen, J.E.; Moilanen, J.; Paananen, R.O.; Ekholm, F.S. The Properties and Role of O-Acyl-omega-hydroxy Fatty Acids and Type I-St and Type II Diesters in the Tear Film Lipid Layer Revealed by a Combined Chemistry and Biophysics Approach. J. Org. Chem. 2021, 86, 4965–4976. [Google Scholar] [CrossRef] [PubMed]
  155. Pucker, A.D.; Ngo, W.; Postnikoff, C.K.; Fortinberry, H.; Nichols, J.J. Tear Film miRNAs and Their Association with Human Dry Eye Disease. Curr. Eye Res. 2022, 47, 1479–1487. [Google Scholar] [CrossRef]
  156. Wolffsohn, J.S.; Benítez-Del-Castillo, J.; Loya-Garcia, D.; Inomata, T.; Iyar, G.; Liang, L.; Pult, H.; Sabater, A.L.; Starr, C.E.; Vehof, J.; et al. TFOS DEWS III Diagnostic Methodology. Am. J. Ophthalmol. 2025, 1–101. [Google Scholar] [CrossRef]
  157. Park, J.Y.; Kim, B.G.; Kim, J.S.; Hwang, J.H. Matrix Metalloproteinase 9 Point-of-Care Immunoassay Result Predicts Response to Topical Cyclosporine Treatment in Dry Eye Disease. Transl. Vision. Sci. Technol. 2018, 7, 31. [Google Scholar] [CrossRef] [PubMed]
  158. Schargus, M.; Ivanova, S.; Kakkassery, V.; Dick, H.B.; Joachim, S. Correlation of Tear Film Osmolarity and 2 Different MMP-9 Tests with Common Dry Eye Tests in a Cohort of Non-Dry Eye Patients. Cornea 2015, 34, 739–744. [Google Scholar] [CrossRef]
  159. Sambursky, R.; Davitt, W.F., 3rd; Latkany, R.; Tauber, S.; Starr, C.; Friedberg, M.; Dirks, M.S.; McDonald, M. Sensitivity and specificity of a point-of-care matrix metalloproteinase 9 immunoassay for diagnosing inflammation related to dry eye. JAMA Ophthalmol. 2013, 131, 24–28. [Google Scholar] [CrossRef]
  160. Bron, A.J.; Willshire, C. Tear Osmolarity in the Diagnosis of Systemic Dehydration and Dry Eye Disease. Diagnostics 2021, 11, 387. [Google Scholar] [CrossRef]
  161. Park, J.; Choi, Y.; Han, G.; Shin, E.; Han, J.; Chung, T.Y.; Lim, D.H. Evaluation of tear osmolarity measured by I-Pen osmolarity system in patients with dry eye. Sci. Rep. 2021, 11, 7726. [Google Scholar] [CrossRef] [PubMed]
  162. Greiner, J.V.; Ying, G.S.; Pistilli, M.; Maguire, M.G.; Asbell, P.A.; Dry Eye, A.; Management Study Research, G. Association of Tear Osmolarity with Signs and Symptoms of Dry Eye Disease in the Dry Eye Assessment and Management (DREAM) Study. Investig. Ophthalmol. Vis. Sci. 2023, 64, 5. [Google Scholar] [CrossRef]
  163. Harrell, C.R.; Feulner, L.; Djonov, V.; Pavlovic, D.; Volarevic, V. The Molecular Mechanisms Responsible for Tear Hyperosmolarity-Induced Pathological Changes in the Eyes of Dry Eye Disease Patients. Cells 2023, 12, 2755. [Google Scholar] [CrossRef]
  164. Pflugfelder, S.; Nakhleh, L.; Kikukawa, Y.; Tanaka, S.; Kosugi, T. Non-Invasive Tear Break-Up Detection with the Kowa DR-1alpha and Its Relationship to Dry Eye Clinical Severity. Int. J. Mol. Sci. 2022, 23, 14774. [Google Scholar] [CrossRef] [PubMed]
  165. Aldeyra Therapeutics, Inc. Reproxalap: Our Novel Small Molecule Drug Candidate for Dry Eye; Aldeyra Therapeutics, Inc.: Lexington, MA, USA, 2024. [Google Scholar]
  166. Aldeyra Therapeutics, Inc. Aldeyra Therapeutics achieves primary endpoint in phase 3 dry eye disease clinical trial of reproxalap. Business Wire, 8 August 2024. [Google Scholar]
  167. Hu, L.; Zhang, T.; Ma, H.; Pan, Y.; Wang, S.; Liu, X.; Dai, X.; Zheng, Y.; Lee, L.P.; Liu, F. Discovering the Secret of Diseases by Incorporated Tear Exosomes Analysis via Rapid-Isolation System: iTEARS. ACS Nano 2022, 16, 11720–11732. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Pathophysiology of DED. This figure illustrates the pathological mechanisms underlying the inflammatory cycle of DED, emphasizing key contributors such as tear film instability, environmental or cellular stress, and systemic conditions. The cycle initiates with tear film instability, which induces ocular surface stress and nerve stimulation, leading to the release of pro-inflammatory cytokines and the activation of an inflammatory response. Elevated levels of MMP-9 further amplify this response by compromising corneal integrity, thereby perpetuating the cycle of inflammation and ocular surface damage. This schematic was developed by the authors’ own concept.
Figure 1. Pathophysiology of DED. This figure illustrates the pathological mechanisms underlying the inflammatory cycle of DED, emphasizing key contributors such as tear film instability, environmental or cellular stress, and systemic conditions. The cycle initiates with tear film instability, which induces ocular surface stress and nerve stimulation, leading to the release of pro-inflammatory cytokines and the activation of an inflammatory response. Elevated levels of MMP-9 further amplify this response by compromising corneal integrity, thereby perpetuating the cycle of inflammation and ocular surface damage. This schematic was developed by the authors’ own concept.
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Figure 2. Diagnostic Devices for DED. This figure presents an overview of four distinct medical devices utilized in ophthalmic and diagnostic applications, including (A) InflammaDry (MMP-9 detection), (B) I-Pen (tear osmolarity), (C) Brill Esthesiometer (corneal sensitivity), and (D) ScoutPro (tear osmolarity). These tools represent a range of technological innovations aimed at enhancing the accuracy and efficiency of medical assessments in research and clinical settings. Together, these devices provide clinicians with accessible and objective tools for identifying and monitoring biomarkers associated with DED.
Figure 2. Diagnostic Devices for DED. This figure presents an overview of four distinct medical devices utilized in ophthalmic and diagnostic applications, including (A) InflammaDry (MMP-9 detection), (B) I-Pen (tear osmolarity), (C) Brill Esthesiometer (corneal sensitivity), and (D) ScoutPro (tear osmolarity). These tools represent a range of technological innovations aimed at enhancing the accuracy and efficiency of medical assessments in research and clinical settings. Together, these devices provide clinicians with accessible and objective tools for identifying and monitoring biomarkers associated with DED.
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MDPI and ACS Style

Jones, J.; Frenia, K.; Gelman, J.; Beatty, M.; Zhou, M.; Ma, L.; Pieramici, S.; Eger, N.; Dhaliwal, D.; Labriola, L.T.; et al. Translating Biomarker Discovery: From Bench to Bedside in Dry Eye Disease. Int. J. Mol. Sci. 2025, 26, 8556. https://doi.org/10.3390/ijms26178556

AMA Style

Jones J, Frenia K, Gelman J, Beatty M, Zhou M, Ma L, Pieramici S, Eger N, Dhaliwal D, Labriola LT, et al. Translating Biomarker Discovery: From Bench to Bedside in Dry Eye Disease. International Journal of Molecular Sciences. 2025; 26(17):8556. https://doi.org/10.3390/ijms26178556

Chicago/Turabian Style

Jones, Jeremy, Kyla Frenia, Julia Gelman, Maria Beatty, Melody Zhou, Levin Ma, Sean Pieramici, Noah Eger, Deepinder Dhaliwal, Leanne T. Labriola, and et al. 2025. "Translating Biomarker Discovery: From Bench to Bedside in Dry Eye Disease" International Journal of Molecular Sciences 26, no. 17: 8556. https://doi.org/10.3390/ijms26178556

APA Style

Jones, J., Frenia, K., Gelman, J., Beatty, M., Zhou, M., Ma, L., Pieramici, S., Eger, N., Dhaliwal, D., Labriola, L. T., & Xiao, K. (2025). Translating Biomarker Discovery: From Bench to Bedside in Dry Eye Disease. International Journal of Molecular Sciences, 26(17), 8556. https://doi.org/10.3390/ijms26178556

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