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

Abstract

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.

Keywords: 2D-PAGE; Antimicrobial compounds; Autoantibody; Biomarker panel; Breast cancer; COVID-19; Calgranulin; Cost-efficacy; Diabetic retinopathy; Differential proteomics; Dry eye; ELISA; Electrophoretic techniques; Glaucoma; HPLC; Healthcare economy; In-gel digestion; Individualized patient profiling; Inflammatory cytokines; MALDI-TOF; MMP-9; Mass spectrometry (MS); Meibomian gland dysfunction; Melanoma; Microarrays; Multiple sclerosis; Novel targets; Ocular allergy; Ocular pathologies; Pandemic; Parkinson’s disease; Patterns; Personalized services; Post-translational modification (PTM); Predictive preventive personalized medicine (3PM/PPPM); Prostate cancer; Retinoblastoma; S100; SDS-PAGE; Sample processing; Schirmer test; Sicca syndrome; Sjögren syndrome; Socio-economic impacts; Sub-optimal health; Systemic disorders; Tear fluid; Thyroid-associated ophthalmopathy.

Fig. 1

The three-layered structure of the tear film: an outer lipid layer at the air surface, an intermediate aqueous layer, and an inner mucus layer on the epithelial. Reproduced from Yazdani et al. [2], with copyright permission from MDPI publisher open access article, copyright 2019

Fig. 2

The main workflow for current mass spectrometry-based tear proteomics techniques. 1D: one dimensional. 2D: two dimensional. SELD: surface-enhanced laser desorption/ionization. TOF: time of flight. MALDI: matrix-assisted laser desorption ionization. ESI: electrospray ionization. MS/MS: tandem mass spectrometry. Q-TOF: quadrupole time of flight. iTRAQ: isobaric tags relative or absolute quantification. TMT: tandem mass tags

Fig. 3

MALDI MS/MS analysis of two tryptic peptides derived from proline-rich protein 4 (Q16378) in human tears. Reproduced from Li N et al. [53], with copyright permission from American Chemistry Society publisher, copyright 2005

Fig. 4

MS/MS spectrum of N-linked glycopeptide fragment LSLHRPALEDLLLGSEAN#LTCTLTGLR ([M + 4H]⁴⁺, m/z = 741.9) derived from SNC66 protein in tear fluid of climatic droplet keratopathy. N# represents the N-glycosylation site and the consensus motif of N-glycosylation is in bold. The mass difference of 115 Da between y9 and y10 ion confirms the deamidation of asparagine in the peptide. Reproduced from Zhou et al. [77], with copyright permission from American Chemistry Society publisher, copyright 2009

Fig. 5

Scheme of multiomics, multiomics-based molecular pathway networks, and molecular network-based tear molecular pattern biomarkers for PPPM/3P medicine practice in different disease. Modified from Zhan X et al. [218], with copyright permission from Intech Open publisher, and from Li, Desiderio, and Zhan [219], with copyright permission from Wiley publisher

Fig. 6

The unbalanced contributions of different tear omics to PPPM/3P medicine practice in different disease. PTMs = post-translational modifications. Modified from Zhan, Long, and Lu [221], with copyright permission from Elsevier publisher, and reproduced from Li, Desiderio, and Zhan [219], with copyright permission from Wiley publisher

Fig. 7

Modifications regulate the entire biological system at the levels of DNA, RNA, and protein, which finally results in the formation of proteoforms that are the final structural and functional forms of a gene or a protein. Constructed from Zhan, Long, and Lu [221], with copyright permission from Elsevier publisher, and constructed from Li, Desiderio, and Zhan [219], with copyright permission from Wiley publisher

Fig. 8

The concept and formation of proteoforms in tear fluid. PTMs = post-translational modifications. Modified from Zhan X et al. [223], with copyright permission from Hapres publisher, and from Zhan X et al. [220], with copyright permission from MDPI publisher