Looking deeper into ocular surface health: an introduction to clinical tear proteomics analysis

Tear Proteins Altered in Patients with Persistent Eye Pain after Refractive Surgery: Biomarker Candidate Discovery

Some patients develop persistent eye pain after refractive surgery, but factors that cause or sustain pain are unknown. We tested whether tear proteins of patients with pain 3 months after surgery differ from those of patients without pain. Patients undergoing refractive surgery (laser in situ keratomileusis or photorefractive keratectomy ) were recruited from 2 clinics, and tears were collected 3 months after surgery. Participants rated their eye pain using a numerical rating scale (NRS, 0-10; no pain-worst pain) at baseline, 1 day, and 3 months after surgery. Using tandem mass tag proteomic analysis, we examined tears from patients with pain [NRS ≥ 3 at 3 months (n = 16)] and patients with no pain [NRS ≤ 1 at 3 months (n = 32)] after surgery. A subset of proteins (83 of 2748 detected, 3.0%) were associated with pain 3 months after surgery. High-dimensional statistical models showed that the magnitude of differential expression was not the only important factor in classifying tear samples from pain patients. Models utilizing 3 or 4 proteins had better classification performance than single proteins and represented differences in both directions (higher or lower in pain). Thus, patterns of protein differences may serve as biomarkers of postsurgical eye pain as well as potential therapeutic targets.

Raman spectroscopy assisted tear analysis: A label free, optical approach for noninvasive disease diagnostics

In recent times, tear fluid analysis has garnered considerable attention in the field of biomarker-based diagnostics due to its noninvasive sample collection method. Tears encompass a reservoir of biomarkers that assist in diagnosing not only ocular disorders but also a diverse list of systemic diseases. This highlights the necessity for sensitive and dependable screening methods to employ tear fluid as a potential noninvasive diagnostic specimen in clinical environments. Considerable research has been conducted to investigate the potential of Raman spectroscopy-based investigations for tear analysis in various diagnostic applications. Raman Spectroscopy (RS) is a highly sensitive and label free spectroscopic technique which aids in investigating the molecular structure of samples by evaluating the vibrational frequencies of molecular bonds. Due to the distinct chemical compositions of different samples, it is possible to obtain a sample-specific spectral fingerprint. The distinctive spectral fingerprints obtained from Raman spectroscopy enable researchers to identify specific compounds or functional groups present in a sample, aiding in diverse biomedical applications. Its sensitivity to changes in molecular structure or environment provides invaluable insights into subtle alterations associated with various diseases. Thus, Raman Spectroscopy has the potential to assist in diagnosis and treatment as well as prognostic evaluation. Raman spectroscopy possesses several advantages, such as the non-destructive examination of samples, remarkable sensitivity to structural variations, minimal prerequisites for sample preparation, negligible interference from water, and the aptness for real-time investigation of tear samples. The purpose of this review is to highlight the potential of Raman spectroscopic technique in facilitating the clinical diagnosis of various ophthalmic and systemic disorders through non-invasive tear analysis. Additionally, the review delves into the advancements made in Raman spectroscopy with regards to paper-based sensing substrates and tear analysis methods integrated into contact lenses. Furthermore, the review also addresses the obstacles and future possibilities associated with implementing Raman spectroscopy as a routine diagnostic tool based on tear analysis in clinical settings.

Comparison of early changes in tear film protein profiles after small incision lenticule extraction (SMILE) and femtosecond LASIK (FS-LASIK) surgery

BACKGROUND

Small incision lenticule extraction (SMILE) and femtosecond laser-assisted in situ keratomileusis (LASIK) are widely used surgical methods to correct myopia with comparable efficacy, predictability, and safety. We examined and compared the early changes of tear protein profiles after SMILE and FS-LASIK surgery in order to find possible differences in the initial corneal healing process.

METHODS

SMILE operations for 26 eyes were made with Visumax femtosecond laser. In FS-LASIK surgery for 30 eyes, the flaps were made with Ziemer FEMTO LDV Z6 femtosecond laser and stromal ablation with Wavelight EX500 excimer laser. Tear samples were collected preoperatively, and 1.5 h and 1 month postoperatively using glass microcapillary tubes. Tear protein identification and quantification were performed with sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS).

RESULTS

Immediately (1.5 h) after we found differences in 89 proteins after SMILE and in 123 after FS-LASIK operation compared to preoperative protein levels. Of these differentially expressed proteins, 48 proteins were common for both surgery types. There were, however, quantitative differences between SMILE and FS-LASIK. Upregulated proteins were mostly connected to inflammatory response and migration of the cells connected to immune system. One month after the operation protein expressions levels were returned to baseline levels with both surgical methods.

CONCLUSIONS

Our study showed that immediate changes in protein profiles after SMILE and FS-LASIK surgeries and differences between the methods are connected to inflammatory process, and the protein levels quickly return to the baseline within 1 month. The differences in protein profiles between the methods are probably associated with the different size of the epithelial wound induced.

Potential Biomarkers for Noninfectious Scleritis Identified by Serum and Tear Fluid Proteomics

Purpose

Scleritis is an extremely painful and potentially blinding inflammation of the sclera with unknown pathogenesis and unpredictable course. To gain insight in its disease process and identify biomarker candidates, we performed extensive proteomics in serum and tear fluid.

Design

Prospective multicenter cohort study.

Participants

A total of 121 patients with noninfectious scleritis (of which 39 active cases), 30 healthy controls, and 23 disease controls (uveitis and rheumatoid arthritis) were enrolled in the Netherlands from 2020 to 2022.

Methods

Serum, tear fluid of both eyes, and clinical data were gathered. The level of 368 inflammatory proteins was measured using proximity extension assays. Results were validated in an independent cohort of 15 patients with scleritis, and using addressable laser bead immunoassay, or enzyme-linked immunoassays. In addition, we studied an extended panel of matrix metalloproteinases in tear fluid of necrotizing scleritis with addressable laser bead immunoassay.

Main Outcome Measures

Statistically significant differences in the level of inflammatory proteins between patients with scleritis and control groups.

Results

Proteomics revealed 18 significantly upregulated or downregulated serum proteins in active scleritis cases compared with all control groups in both the discovery cohort and the validation cohort. The most upregulated protein was nuclear migration protein nudC (NudC; P = 0.0032), a protein involved in neurogenesis. The other significant hits included proteins involved in T-cell activation, apoptosis, epithelial barrier maintenance, and angiogenesis. Our tear fluid analysis showed matrix metalloproteinase 9 (MMP9) to be upregulated in the tear fluid of patients with scleral necrosis.

Conclusions

The results of our proteomics analysis suggest a role for neurogenesis, T-cell activation, disruption of epithelial barrier, and angiogenesis in the pathogenesis of scleritis, and highlight MMP9 and NudC as biomarkers with potential clinical relevance.

Funding Disclosures

The authors have no proprietary or commercial interest in any materials discussed in this article.

Protein profile pattern analysis: A multifarious, in vitro diagnosis technique for universal screening

Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare.

Profiling tear film enzymes reveals major metabolic pathways involved in the homeostasis of the ocular surface

The ocular surface (OS) enzymes are of great interest due to their potential for novel ocular drug development. We aimed first to profile and classify the enzymes of the OS to describe major biological processes and pathways that are involved in the maintenance of homeostasis. Second, we aimed to compare the enzymatic profiles between the two most common tear collection methods, capillary tubes (CT) and Schirmer strips (ScS). A comprehensive tear proteomic dataset was generated by pooling all enzymes identified from nine tear proteomic analyses of healthy subjects using mass spectrometry. In these studies, tear fluid was collected using CT (n = 4), ScS (n = 4) or both collection methods (n = 1). Classification and functional analysis of the enzymes was performed using a combination of bioinformatic tools. The dataset generated identified 1010 enzymes. The most representative classes were hydrolases (EC 3) and transferases (EC 2). Phosphotransferases, esterases and peptidases were the most represented subclasses. A large portion of the identified enzymes was common to both collection methods (n = 499). More enzymes were specifically detected in the ScS-extracted proteome. The major pathways in which the identified enzymes participate are related to the immune system and protein, carbohydrate and lipid metabolism. Metabolic processes for nucleosides, cellular amides, sugars and sulfur compounds constituted the most enriched biological processes. Knowledge of these molecules highly susceptible to pharmacological manipulation might help to predict the metabolism of ophthalmic medications and develop novel prodrug strategies as well as new drug delivery systems. Combining such extensive knowledge of the OS enzymes with new analytical approaches and techniques might create new prospects for understanding, predicting and manipulating the metabolism of ocular pharmaceuticals. Our study reports new, essential data on OS enzymes while also comparing the enzyme profiles obtained via the two most popular methods of tear collection, capillary tubes and Schirmer strips.

Proteomic analysis of tears in dry eye disease: A prospective, double-blind multicenter study

PURPOSE

To identify specific dry eye disease (DED) tear biomarker(s) using tear proteomic analysis, clinical parameters, and their correlations before and after DED treatment.

METHODS

A prospective, double-blinded, national multicenter clinical study was performed using data from 80 DED patients. The patients were treated with 0.1% cyclosporine (CsA, n = 28), 0.05% CsA (n = 26), or 3% diquafosol (DQS, n = 26) eye drops, and tear proteome changes and clinical outcomes (tear break-up time [TBUT], corneal erosion [Cor-Er], conjunctival erosion [Conj-Er], and symptom assessment in dry eye [SANDE] scores) were observed at 4, 8, and 12 weeks. For all clinical parameters, correlation analysis was performed between the three drug conditions and the differentially expressed proteins (DEPs) from the proteomic analysis.

RESULTS

AFM, ALCAM, CFB, H1-4, PON1, RAP1B, and RBP4 were identified in all treatment groups and were downregulated after treatment. All clinical parameters significantly improved at 12 weeks than at baseline (p-value <0.0001); however, their values were not significantly different among groups, except for Cor-Er (p-value = 0.007). Compared with the DQS group, Cor-Er score significantly improved after treatment with 0.1% and 0.05% CsA. The seven DEPs identified in all groups were not consistently correlated with the clinical parameters (p-value >0.05).

CONCLUSIONS

Despite differences in drug concentration and action mechanisms, the improvement levels of TBUT, Cor-Er, and SANDE scores were clinically adequate. However, useful tear protein biomarkers, clinically acceptable biomarker combinations correlating with clinical parameters, and clinically acceptable levels of specificity and sensitivity were not identified.

Evaluation of pre-processing methods for tear fluid proteomics using proximity extension assays

Tear fluid forms a potential source for biomarker identification, and can be minimal invasively collected via Schirmer strips. The lack of knowledge on the processing of Schirmer strips however complicates the analysis and between-study comparisons. We studied two different pre-processing methods, specifically the use of punches of the strip versus elution of the strip in a buffer. Tear fluid filled Schirmer strips were collected from 5 healthy participants, and divided into two halves over the length of the strip. In either part, punches or eluates were obtained from 4 different locations, from the first part touching the eye (head) to the end, to assess the protein distribution along the strips. The levels of 92 inflammatory proteins were measured in the punches/eluates using proximity extension assays. The punch method yielded higher protein detectability compared to the elution method (76% vs 66%; p ≤ 0.001). Protein expression level was found to be slightly higher in the head of the strip, however, 3 out of 5 punches from the head failed quality control. Protein expression levels over the remaining parts of the strips were similar. Our study showed beneficial use of punches of any part of the strip except the head in future biomarker research.

Clinical Tear Fluid Proteomics—A Novel Tool in Glaucoma Research

Tear fluid forms the outermost layer of the ocular surface and its characteristics and composition have been connected to various ocular surface diseases. As tear proteomics enables the non-invasive investigation of protein levels in the tear fluid, it has become an increasingly popular approach in ocular surface and systemic disease studies. Glaucoma, which is a set of multifactorial diseases affecting mainly the optic nerve and retinal ganglion cells, has also been studied using tear proteomics. In this condition, the complete set of pathophysiological changes occurring in the eye is not yet fully understood, and biomarkers for early diagnosis and accurate treatment selection are needed. More in-depth analyses of glaucoma tear proteomics have started to emerge only more recently with the implementation of LC-MS/MS and other modern technologies. The aim of this review was to examine the published data of the tear protein changes occurring during glaucoma, its topical treatment, and surgical interventions.

Pathogenesis of keratoconus: NRF2-antioxidant, extracellular matrix and cellular dysfunctions

Keratoconus (KC) is a degenerative disease associated with cell and extracellular matrix (ECM) loss that causes gradual thinning and steepening of the cornea and loss of vision. Collagen cross linking with ultraviolet light treatment can strengthen the ECM and delay weakening of the cornea, but severe cases require corneal transplantation. KC is multifactorial and multigenic, but its pathophysiology is still an enigma. Multiple approaches are being pursued to elucidate the molecular changes that underlie the corneal phenotype to identify relevant genes for tailored candidate searches and to develop potential biomarkers and targets for therapeutic interventions. Recent proteomic and transcriptomic studies suggest dysregulations in oxidative stress, NRF2-regulated antioxidant programs, WNT-signaling, TGF-β, ECM and matrix metalloproteinases. This review aims to provide a broad update on the transcriptomic and proteomic studies of KC with a focus on findings that relate to oxidative stress, and dysregulations in cellular and extracellular matrix functions.