High performance liquid chromatography analysis of tear protein patterns in diabetic and non-diabetic dry-eye patients

Smart Contact Lenses for Healthcare Monitoring and Therapy

The eye contains a wealth of physiological information and offers a suitable environment for noninvasive monitoring of diseases via smart contact lens sensors. Although extensive research efforts recently have been undertaken to develop smart contact lens sensors, they are still in an early stage of being utilized as an intelligent wearable sensing platform for monitoring various biophysical/chemical conditions. In this review, we provide a general introduction to smart contact lenses that have been developed for disease monitoring and therapy. First, different disease biomarkers available from the ocular environment are summarized, including both physical and chemical biomarkers, followed by the commonly used materials, manufacturing processes, and characteristics of contact lenses. Smart contact lenses for eye-drug delivery with advancing technologies to achieve more efficient treatments are then introduced as well as the latest developments for disease diagnosis. Finally, sensor communication technologies and smart contact lenses for antimicrobial and other emerging bioapplications are also discussed as well as the challenges and prospects of the future development of smart contact lenses.

Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome

Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity.

Mass spectrometry analysis of human tear fluid biomarkers specific for ocular and systemic diseases in the context of 3P medicine

Over the last two decades, a large number of non-communicable/chronic disorders reached an epidemic level on a global scale such as diabetes mellitus type 2, cardio-vascular disease, several types of malignancies, neurological and eye pathologies-all exerted system's enormous socio-economic burden to primary, secondary, and tertiary healthcare. The paradigm change from reactive to predictive, preventive, and personalized medicine (3PM/PPPM) has been declared as an essential transformation of the overall healthcare approach to benefit the patient and society at large. To this end, specific biomarker panels are instrumental for a cost-effective predictive approach of individualized prevention and treatments tailored to the person. The source of biomarkers is crucial for specificity and reliability of diagnostic tests and treatment targets. Furthermore, any diagnostic approach preferentially should be noninvasive to increase availability of the biomaterial, and to decrease risks of potential complications as well as concomitant costs. These requirements are clearly fulfilled by tear fluid, which represents a precious source of biomarker panels. The well-justified principle of a "sick eye in a sick body" makes comprehensive tear fluid biomarker profiling highly relevant not only for diagnostics of eye pathologies but also for prediction, prognosis, and treatment monitoring of systemic diseases. One prominent example is the Sicca syndrome linked to a cascade of severe complications that include dry eye, neurologic, and oncologic diseases. In this review, protein profiles in tear fluid are highlighted and corresponding biomarkers are exemplified for several relevant pathologies, including dry eye disease, diabetic retinopathy, cancers, and neurological disorders. Corresponding analytical approaches such as sample pre-processing, differential proteomics, electrophoretic techniques, high-performance liquid chromatography (HPLC), enzyme-linked immuno-sorbent assay (ELISA), microarrays, and mass spectrometry (MS) methodology are detailed. Consequently, we proposed the overall strategies based on the tear fluid biomarkers application for 3P medicine practice. In the context of 3P medicine, tear fluid analytical pathways are considered to predict disease development, to target preventive measures, and to create treatment algorithms tailored to individual patient profiles.

Human tear fluid analysis for clinical applications: progress and prospects

Introduction: Human blood and saliva are increasingly under investigation for the detection of biomarkers for early diagnosis of non-communicable (e.g.cancers) and communicable diseases like COVID-19. Exploring the potential application of human tears, an easily accessible body fluid, for the diagnosis of various diseases is the need of the hour.Areas covered: This review deals with a comprehensive account of applications of tear analysis using different techniques, their comparison and overall progress achieved till now. The techniques used for tear fluid analysis are HPLC/UPLC/SDS-PAGE, CE, etc., together with ELISA, Mass Spectrometry, etc. But, with advances in instrumentation and data processing methods, it has become easy to couple the various separation methods with highly sensitive optical techniques for the analysis of body fluids.Expert opinion: Tear analysis can provide valuable information about the health condition of the eyes since it contains several molecular constituents, and their relative concentrations may alter under abnormal conditions. Tear analysis has the advantage that it is totally non-invasive. This study recommends tear fluid as a reliable clinical sample to be probed by highly sensitive optical techniques to diagnose different health conditions, with special emphasis on eye diseases.

Racial and Ethnic Differences in the Association Between Diabetes Mellitus and Dry Eye Disease

Purpose:To examine the association between dry eye and diabetes mellitus among a large North Carolina patient population. Methods:A retrospective cross-sectional study of patients seen within the University of North Carolina medical system between July 1, 2008, and September 1, 2017, was performed. De-identified medical records contained within the Carolina Data Warehouse of adult patients who have had an ocular evaluation were studied. Four categories of disease states were identified by ICD-9 and ICD-10 codes. Patients were grouped based on being diagnosed with Dry Eye Disease (ICD-9: 375.15, 370.33, and ICD-10: H04.12, H16.221), Diabetes Mellitus (ICD-9: 250.00-250.93 and ICD-10: E08-E11, E13), neither, or both diseases. Odds ratios of the association between diabetes and dry eye were calculated for the following racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black/African American, Asian, and Hispanic. Results:A total of 81,480 patients were included in the analysis; of those, 8978 patients had dry eye disease and 18,361 patients had diabetes. The remaining 54,141 patients had neither disease. Dry eye prevalence among patients with diabetes was 14.39% (95% CI: 13.89-14.91%) and 10.11% (95%CI: 9.88-10.35%) among patients without diabetes. The odds of a patient with diabetes having dry eye are 1.15 (95% CI: 1.09-1.21) times that of a patient without diabetes. Asian patients with diabetes demonstrated the highest odds of having dry eye at 1.49 (95% CI: 1.12-1.98). Conclusions:Dry eye is common among patients with diabetes, and the association between these diseases is strongest among Asian patients. Race and ethnicity are important demographic factors that may guide providers in the diagnosis and treatment of dry eye in the setting of diabetes.

Tears and ocular surface disorders: Usefulness of biomarkers

INTRODUCTION

Corroborating data suggest that the analysis of tear fluid might represent an additional tool in the ophthalmological practice.

AREAS COVERED

The purpose of this review was to sum up the tear protein profiles in healthy and diseased ocular surface and to highlight biomarker usefulness in the early diagnosis as well as at follow-up. This analysis encompasses a deep examination of the protein profile expression under physiological and pathological conditions. Tear protein profile analysis will allow in the near future discriminating between different grades of inflammation, from acute trauma toward immune-, endocrine-, and nervous-related disorders of the ocular surface.

CONCLUDING REMARKS

The review provides an overview of old and recent findings about inflammatory mediators identified at the ocular surface, under physiological and pathological conditions. To date, the analysis of tear fluid represents a new additional approach for diagnosis and management of ocular surface diseases. Understanding the pathophysiological mechanism could also offer significant advantages to develop strategies addressed to better clarify some complex ocular surface disorders. To sum up, the possibility to provide selective biomarkers as a future target of specific diseases should be considered for supporting diagnosis and management of ocular surface diseases.

Metabolomics and Trace Element Analysis of Camel Tear by GC-MS and ICP-MS

Camel tear metabolomics and elemental analysis are useful in getting the information regarding the components responsible for maintaining the protective system that allows living in the desert and dry regions. The aim of this study was to correlate that the camel tears can be used as artificial tears for the evaluation of dryness in the eye. Eye biomarkers of camel tears were analyzed by gas chromatography-mass spectroscopy (GC-MS) and inductively coupled plasma mass spectroscopy (ICP-MS). The major compounds detected in camel tears by GC-MS were alanine, valine, leucine, norvaline, glycine, cadaverine, urea, ribitol, sugars, and higher fatty acids like octadecanoic acid and hexadecanoic acid. GC-MS analysis of camel tears also finds several products of metabolites and its associated metabolic participants. ICP-MS analysis showed the presence of different concentration of elemental composition in the camel tears.

Practical issues concerning tear protein assays in dry eye

Dry eye is a common clinical condition diagnosed by cumulative evidence of symptoms and signs. Many new treatments in dry eye are either expensive, invasive, have potential for side effects, or are not easily accessible. In severe dry eye, the ideal modality of treatment to begin with is often not clear as specific molecular disturbances are not evident from just examination of clinical manifestations. Assessing the effects of ongoing treatment is not straight forward since there is lack of agreement between clinical signs and symptoms. There is a need to have more objective methods of selecting treatment for dry eye and monitoring the effect of treatment. Recently, there are many new technologies applied to the discovery of tear biomarkers, for e.g., mass spectrometry based proteomics techniques and multiplex assays such as the bead-based sandwich indirect immunofluorescent assays. Tear proteins assays have even been made available as point-of-care devices. This review focuses on the evidence for the involvements of tear proteins in dry eye, possible changes in tear concentrations with therapy and the strength of evidence regarding dry eye pathology. Much remains to be done in terms of developing office-based assays and ascertaining their reliability, but current evidence suggests that tear proteins have a role in the clinical practice of dry eye.

Tear fluid proteomics multimarkers for diabetic retinopathy screening

Background

The aim of the project was to develop a novel method for diabetic retinopathy screening based on the examination of tear fluid biomarker changes. In order to evaluate the usability of protein biomarkers for pre-screening purposes several different approaches were used, including machine learning algorithms.

Methods

All persons involved in the study had diabetes. Diabetic retinopathy (DR) was diagnosed by capturing 7-field fundus images, evaluated by two independent ophthalmologists. 165 eyes were examined (from 119 patients), 55 were diagnosed healthy and 110 images showed signs of DR. Tear samples were taken from all eyes and state-of-the-art nano-HPLC coupled ESI-MS/MS mass spectrometry protein identification was performed on all samples. Applicability of protein biomarkers was evaluated by six different optimally parameterized machine learning algorithms: Support Vector Machine, Recursive Partitioning, Random Forest, Naive Bayes, Logistic Regression, K-Nearest Neighbor.

Results

Out of the six investigated machine learning algorithms the result of Recursive Partitioning proved to be the most accurate. The performance of the system realizing the above algorithm reached 74% sensitivity and 48% specificity.

Conclusions

Protein biomarkers selected and classified with machine learning algorithms alone are at present not recommended for screening purposes because of low specificity and sensitivity values. This tool can be potentially used to improve the results of image processing methods as a complementary tool in automatic or semiautomatic systems.

A novel fluorescent lipid probe for dry eye: retrieval by tear lipocalin in humans

PURPOSE

A fluorescent probe was used to identify mucin-depleted areas on the ocular surface and to test the hypothesis that tear lipocalin retrieves lipids from the eyes of normal and dry eye subjects.

METHODS

Fluorescein-labeled octadecyl ester, FODE, was characterized by mass spectrometry and absorbance spectrophotometry. The use of FODE to define mucin defects was studied with impression membranes under conditions that selectively deplete mucin. The kinetics of FODE removal from the ocular surface were analyzed by sampling tears from control and dry eye patients at various times. The tear protein-FODE complexes were isolated by gel filtration and ion exchange chromatographies, monitored with absorption and fluorescent spectroscopies, and analyzed by gel electrophoresis. Immunoprecipitation verified FODE complexed to tear lipocalin in tears.

RESULTS

FODE exhibits an isosbestic point at 473 nm, pKa of 7.5, and red shift relative to fluorescein. The low solubility of FODE in buffer is enhanced with 1% Tween 80 and ethanol. FODE adheres to the ocular surface of dry eye patients. FODE produces visible staining at the contact sites of membranes, which correlates with removal of mucin. Despite the fact that tear lipocalin is reduced in dry eye patients, FODE removal follows similar rapid exponential decay functions for all subjects. FODE is bound to tear lipocalin in tears.

CONCLUSIONS

Tear lipocalin retrieves lipid rapidly from the human ocular surface in mild to moderate dry eye disease and controls. With improvements in solubility, FODE may have potential as a fluorescent probe to identify mucin-depleted areas.

Tear analysis in ocular surface diseases

The thin layer of tears covering the ocular surface are a complex body fluid containing thousands of molecules of varied form and function of several origins. In this review, we have discussed some key issues in the analysis of tears in the context of understanding and diagnosing eye disease using current technologies of proteomics and metabolomics, and for their potential for clinical application. In the last several years, advances in proteomics/metabolomics/lipidomics technologies have greatly expanded our knowledge of the chemical composition of tear fluid. The quickened pace of studies has shown that tears as a complex extra-cellular fluid of the ocular surface contains a great deal of molecular information useful for the diagnosis, prognosis, and treatment of ocular surface diseases that has the ability to addresses the emphasis on personalized medicine and biomarkers of disease. Future research directions will likely include (1) standardize tear collection, storage, extraction, and sample preparation; (2) quantitative proteomic analysis of tear proteins using multiple reaction monitoring (MRM)-based mass spectrometry; (3) population based studies of human tear proteomics/metabolomics; (4) tear proteomics/metabolomics for systemic diseases; and (5) functional studies of tear proteins.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

Identification of 491 proteins in the tear fluid proteome reveals a large number of proteases and protease inhibitors

BACKGROUND

The tear film is a thin layer of fluid that covers the ocular surface and is involved in lubrication and protection of the eye. Little is known about the protein composition of tear fluid but its deregulation is associated with disease states, such as diabetic dry eyes. This makes this body fluid an interesting candidate for in-depth proteomic analysis.

RESULTS

In this study, we employ state-of-the-art mass spectrometric identification, using both a hybrid linear ion trap-Fourier transform (LTQ-FT) and a linear ion trap-Orbitrap (LTQ-Orbitrap) mass spectrometer, and high confidence identification by two consecutive stages of peptide fragmentation (MS/MS/MS or MS3), to characterize the protein content of the tear fluid. Low microliter amounts of tear fluid samples were either pre-fractionated with one-dimensional SDS-PAGE and digested in situ with trypsin, or digested in solution. Five times more proteins were detected after gel electrophoresis compared to in solution digestion (320 versus 63 proteins). Ontology classification revealed that 64 of the identified proteins are proteases or protease inhibitors. Of these, only 24 have previously been described as components of the tear fluid. We also identified 18 anti-oxidant enzymes, which protect the eye from harmful consequences of its exposure to oxygen. Only two proteins with this activity have been previously described in the literature.

CONCLUSION

Interplay between proteases and protease inhibitors, and between oxidative reactions, is an important feature of the ocular environment. Identification of a large set of proteins participating in these reactions may allow discovery of molecular markers of disease conditions of the eye.