The analysis of human conjunctival epithelium proteome in ocular surface diseases using impression cytology and 2D-DIGE

Accepted Manuscript The analysis of human conjunctival epithelium proteome in ocular surface diseases using impression cytology and 2D-DIGE Javier Soria, Arantxa Acera, Juan A. Durán, Ana Boto-de-los-Bueis, Almudena DelHierro-Zarzuelo, Nerea González, Rebeca Reigada, Tatiana Suárez PII:

S0014-4835(17)30205-1

DOI:

10.1016/j.exer.2017.03.006

Reference:

YEXER 7107

To appear in:

Experimental Eye Research

Received Date: 14 July 2016 Revised Date:

1 December 2016

Accepted Date: 17 March 2017

Please cite this article as: Soria, J., Acera, A., Durán, J.A., Boto-de-los-Bueis, A., Del-Hierro-Zarzuelo, A., González, N., Reigada, R., Suárez, T., The analysis of human conjunctival epithelium proteome in ocular surface diseases using impression cytology and 2D-DIGE, Experimental Eye Research (2017), doi: 10.1016/j.exer.2017.03.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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MANUSCRIPT The analysis of humanACCEPTED conjunctival epithelium proteome in

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ocular surface diseases using impression cytology and 2D-DIGE

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Soria Javier1, Acera Arantxa1, Durán Juan A.2,3, Ana Boto-de-los-Bueis4, Almudena Del-Hierro-

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Zarzuelo4, González Nerea1, Reigada Rebeca1, Suárez Tatiana1.

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Bizkaia, Spain. 2

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Instituto Clínico Quirúrgico de Oftalmología (ICQO), Virgen de Begoña Nº 34, E-48006 Bilbao, Bizkaia, Spain.

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Department of Ophthalmology, School of Medicine, University of the Basque Country (UPV/EHU),

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Bioftalmik Applied Research. Bizkaia Science and Technology Park, Building 612, E-48160 Derio,

Leioa, Bizkaia, Spain.

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* Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +34-944-069-659 (ext. 2002).

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Hospital la Paz, Pº de la Castellana, 261, E-28046 Madrid, Spain.

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ACCEPTED MANUSCRIPT Abstract: Conjunctival impression cytology samples from patients with meibomian gland dysfunction

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(MGD), dry eye (DE), and healthy subjects (CT) were collected for determination of the degree of

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squamous metaplasia (SM) by PAS-hematoxylin staining and for comparative proteomic analyses by

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2D-DIGE. The protein spots with discriminant expression were identified by MALDI-TOF/TOF mass

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spectrometry. Three independent statistical studies were conducted: i). Analysis of differential protein

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expression between study groups: We observed increased expression of proteins S100A4, S100A8,

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retinal dehydrogenase-1, peroxiredoxin-1, annexin-A1, annexin-A2, α-enolase, and glutathione S-

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transferase-P in DE, whereas the highest expression of peroxiredoxin-6, actin cytoplasmic-1,

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peroxiredoxin-2, and heat shock protein HSP-90-α was observed in MGD; ii). Correlation between

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changes in the proteome profile and the grade of SM: The expression of 5 different cytokeratins

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(KRT1, KRT4, KRT8, KRT10, and KRT13) correlated with the degree of SM; iii). Proteome profile

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differences between pathological and CT groups: An overall proteome analysis revealed upregulation

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of 9 proteins in the pathological groups (Annexin-A1, α-enolase, Annexin-A2, S100A8, cytokeratin-1,

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Peroxiredoxin-2 and Leukocyte elastase inhibitor) and downregulation of 2 proteins (Galectin-3 and

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Lipocalin-1). In conclusion, a sensitive proteomic approach to study conjunctival tissue collected from

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minimally invasive impression cytology was implemented. Differential proteomics analyses showed

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that in comparison with the MGD, the DE patients presented higher overexpression of proteins related

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to antimicrobial defense, tissue-damage response, and regulation of body fluid secretions. Changes in

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MGD proteome were associated with oxidative stress and anti-apoptotic processes. We found a

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correlation between the grade of SM and expression of proteins associated with cytoskeleton and

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keratinization. The studied pathological groups shared elements related to the defense and

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inflammatory responses. Dot blot assays of proteins ANXA1, S100A8, and S100A4 validated the

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proteomic results obtained from 2D-DIGE experiments and confirmed the correlation between the

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expression of these proteins and the clinical parameters.

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Keywords: Dry eye, meibomian gland dysfunction, conjunctiva, proteomics, 2D-DIGE, scarce

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samples, squamous metaplasia, impression cytology.

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1. Introduction Ocular surface damage can be caused by the dysfunction of the lacrimal functional unit (LFU). The

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LFU consists of lacrimal glands (both main and accessory), the ocular surface (cornea, conjunctiva,

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meibomian glands, and goblet cells), muscles responsible for blinking, and the interconnecting

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innervation (Stern et al., 2004).

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LFU dysfunction seen in ocular surface diseases (OSDs) such as MGD and DE results in symptoms

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of discomfort and it can cause visual impairment. Other consequences might be the tear film instability

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and evaporation due to disturbances in the tear lipid layer, tear hyposecretion, or both, resulting in

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potential damage to the ocular surface (Gilbard, 1999; Lemp and Nichols, 2009; “The definition and

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classification of dry eye disease: report of the Definition and Classification Subcommittee of the

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International Dry Eye WorkShop”, 2007). This deterioration of the ocular surface is promoted by

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processes related to apoptosis and oxidative stress, which activate inflammatory mechanisms (Gulati et

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al., 2006).

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DE is currently recognized as a dysfunction of the LFU, and it is accompanied by increased

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osmolarity of the tear film and inflammation of the ocular surface (“The definition and classification of

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dry eye disease: report of the Definition and Classification Subcommittee of the International Dry Eye

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WorkShop”, 2007). MGD can lead to alterations in the lipid composition of the meibomian gland

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secretions (Joffre et al., 2008; Shine and McCulley, 2003), which in turn induce abnormalities in the

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tear film composition and function, resulting in evaporative dry eye condition (EDE) (Craig and

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Tomlinson, 1997). MGD has frequently been reported in DE patients as the main cause of EDE, with

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significant overlapping of the symptoms and signs (Craig and Tomlinson, 1997; Lemp and Nichols,

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2009).

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These two pathological conditions are common inflammatory OSDs which may coexist and interact

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in the same patient, increasing the severity of the disease (“The definition and classification of dry eye

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disease: report of the Definition and Classification Subcommittee of the International Dry Eye

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WorkShop”, 2007).

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Several tear proteome studies searching for discriminative biomarkers of OSDs have been reported

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(Acera et al., 2011; Acera et al., 2011; Grus et al., 2005; Soria et al., 2013; Tong et al., 2011a).

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However, the conjunctival epithelium proteome in those pathologies has not been analyzed in detail.

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Ocular dryness disorders also promote squamous metaplasia (SM), mainly as a consequence of

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inflammation (De Paiva et al., 2007). Most studies of the conjunctival epithelium examine the degree

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of SM, which is used to determine the extent of the epithelium involvement and as a diagnostic tool for

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grading different diseases affecting the ocular surface (Tseng, 1985). The SM is a process of adaptive 3

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response to tissue damage with a transition from stratified nonkeratinized epithelium to nonsecretory

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keratinized epithelium, involving abnormal epithelial differentiation (Collin et al., 1978). It has been

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reported that SM is promoted by involucrin and filaggrin proteins and is associated with changes in the

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expression levels of cytokeratin pair 1/10 and cytokeratin 2 in conjunctival epithelium (Krenzer and

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Freddo, 1997; Nakamura et al., 2001; Resing et al., 1984; Tseng et al., 1984). Previous proteomic studies of this tissue have attempted simultaneous determination of a limited

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number of molecules, mainly related to inflammatory and apoptotic processes (Bensoussan et al.,

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2003; Denoyer et al., 2012; Narayanan et al., 2008; Pisella et al., 2000; Yu et al., 2012). Even though

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these reports represent a substantial progress in the field of OSD studies, more extensive proteomic

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research is needed to understand the exact roles of the proteins involved in the pathophysiology of

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these diseases. The relative scarcity of such studies may be due to the difficulty in obtaining sufficient

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protein material from conjunctival epithelium using noninvasive techniques such as impression

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cytology. To overcome these limitations, we implemented the saturating labeling two-dimensional

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difference gel electrophoresis (2D-DIGE) technology for proteomic analysis of samples with low

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protein content. This sensitive technique can analyze samples with less than 5 µg of total protein,

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exceeding the sensitivity of minimal labeling-DIGE (Greengauz-Roberts et al., 2005), which requires

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50 µg of total protein per sample. The purpose of the present study was to compare conjunctival

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proteome profiles obtained using IC specimens of two main OSDs, DE and MGD, and healthy CT

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individuals. Our study examined: i) proteins whose profiles could be used to distinguish between the

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studied pathologies, ii) correlation between changes in protein expression profiles and the grade of

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SM, iii) proteins which might be involved in the onset and progression of OSD, and iv) the validity of

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three candidate biomarkers by employing an orthogonal technique (dot blot), using independent

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samples.

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2. Materials and Methods

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2.1 Patients

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We enrolled 126 individuals to carry out a prospective case-control study. Samples from 62 patients

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were used in the biomarker search, and the remaining 64 patients supplied the material for the

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validation of candidate biomarkers. The patients with MGD and DE and healthy subjects were

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recruited at the Instituto Clínico Quirúrgico de Oftalmología (ICQO, Bilbao, Vizcaya, Spain) and

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Hospital La Paz (Madrid, Spain). The approval was obtained in strict accordance with the tenets of the

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Declaration of Helsinki on Biomedical Research Involving Human Subjects.

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ACCEPTED MANUSCRIPT The diagnosis of DE was based on symptoms and clinical examination. Dry eye symptoms were

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measured according to each patient answered of VFQ-25 questionnaire.

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Patients were classified as having DE no-associated to MGD (DE patients) if they had a VFQ-25 score

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> 25 (0-100), a Schirmer I test ≤ 5 mm/5 min, a positive fluorescein staining of the corneal epithelium

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(Oxford grade > 1), a tear breakup time (TBUT) ≥ 5 s and total absence of MGD slit lamp signs.

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Patients were classified as having DE associated to MGD (MGD patients) if they had a VFQ-25 score

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>25 (0-100), a TBUT < 5 s, a Schirmer I test result values > 5 mm/5 min and abnormality of the

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Meibomian glands assessed by slit lamp examination (increased hyperviscosity of meibum, obstruction

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or displacement of the Meibomian orifices, keratinization, vascularization, displacement or hyperemia

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of the marginal lid). The MGD clinical signs and meibum quality were evaluated according to the

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MGD features proposed by the International Workshop on Meibomian Gland Dysfunction (Tomlinson

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et al., 2011).

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Healthy subjects recruited for the CT group were not suffering from any ocular disease (no allergic or

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atopic history). They presented Schirmer I test values > 5 mm/5 min, TBUT > 5 s, no corneal

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fluorescein staining or sensations of discomfort, and no evident eyelid inflammation. The individuals

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with (or history of) any systemic or ocular disorder or condition (including ocular surgery, trauma, and

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disease) and patients with Sjögren’s syndrome were excluded. Contact lens users were also excluded to

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avoid any possible interference with the interpretation of the results.

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IC samples were obtained from 19 DE patients, 16 chronic MGD patients, and 27 CT individuals for

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the discovery of candidate biomarkers, and from 24 DE patients, 25 chronic MGD patients, and 15 CT

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individuals for validation assays.

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2.2 Conjunctival tissue collection by IC

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This research was conducted by medically qualified personnel after approval by Institutional Review

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Board Ethics Committee.

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Before IC sample collection, signed informed consent was obtained from all patients once the nature

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and possible consequences of the study had been explained. CIC specimens for proteomic analyses

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were collected using 8 mm diameter cellulose acetate discs. CIC samples for PAS-hematoxylin

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staining were obtained on 5×5 mm strips of cellulose acetate and immediately fixed in 96% ethanol.

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For protein extraction purposes, both sides of each disc were placed in contact with the epithelium of

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the superior bulbar conjunctiva, using sterile tweezers, to obtain the highest possible number of cells.

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Slight pressure was applied to the disc for a few seconds to improve the efficacy of the collection. The

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discs were immediately stored at -80ºC until protein isolation.

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2.3 PAS-hematoxylin staining 5

ACCEPTED MANUSCRIPT PAS-hematoxylin staining was performed according to the Locquin and Langeron protocol, modified

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by Rivas et al. (Rivas et al., 1991). In each IC preparation, we measured cytoplasm and nucleus areas

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of nonsecretory cells. We also examined cytoplasmic alterations and staining, nuclear alterations, and

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obtained the nuclear and cytoplasmic areas ratio (N:C ratio). Goblet cells were counted for SM grade

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evaluation.

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2.4 Sample preparation and protein quantification

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For the selection of candidate biomarkers, proteins were extracted by sonication in a Bandelin

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sonicator (Bandelin, Berlin, Germany), in 200 µl of DIGE Lysis Buffer (30 mM Tris-HCl, pH 8.0, 7 M

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urea, 2 M thiourea, 4% w/v CHAPS) enriched with phenylmethanesulfonyl fluoride (PMSF, Sigma, St.

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Louis, MO, USA). To avoid overheating, the samples were kept at 4 °C at all times; 5 cycles of

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sonication were performed (5 s on, 20 s off). The protein extraction procedure for validation assays

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was the same but the phosphate-buffered saline supplemented with 0.05% of Tween-20 was used

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instead of DIGE Lysis Buffer. The proteins for candidate biomarkers selection were precipitated using

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a 2-D Clean-Up Kit (GE Healthcare, Sunnyvale, CA, USA) following the manufacturer's instructions.

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Finally, the samples were resuspended in 10 µl of DIGE Lysis Buffer and pH adjusted to 8.0.

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The protein concentration in the suspensions was quantified using EZQ Protein Quantification Kit

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(Invitrogen Dynal, Oslo, Norway) and frozen at -80 ºC until further analysis.

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2.5 2D-DIGE for scarce samples

CyDye DIGE Fluor Labeling Kits for Scarce Samples (GE Healthcare) was used to label conjunctiva

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proteins, following the manufacturer's protocol. Briefly, an aliquot of 5 µg of protein from each sample

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was reduced with 2 nmol Tris (2-carboxyethyl) phosphine hydrochloride (TCEP, Sigma) and labeled

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with 4 nmol of Cy5 dye. For internal standardization, a pool of equal aliquots from all samples (5 µg

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per sample) was labeled with Cy3 dye using the same procedure but scaling the quantities of reagents

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according to the amount of protein. Before 2D separation, 5 µg of each sample was mixed with 5 µg of

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the labeled internal standard. Then, all the samples were focused on 24-cm IPG (Bio-Rad, Malvern,

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PA, USA) strips within a pH range of 5–8 in a PROTEAN IEF system (Bio-Rad), following the

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supplier’s instructions. The focused strips were equilibrated with Buffer 1 (6 M urea, 0.375 M Tris-

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HCl, 2% SDS, 20% glycerol) supplemented with 2% (w/v) DTT and subsequently incubated with

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Buffer 1 supplemented with 2.5% (w/v) iodoacetamide. Finally, SDS-PAGE electrophoresis was

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performed in large 15% polyacrylamide gels using the DALT-SIX electrophoresis system (GE

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Healthcare).

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2.6 Image acquisition and data analysis 6

ACCEPTED MANUSCRIPT Proteins were visualized using a VersaDoc Imaging System (Bio-Rad), consecutively scanning the two

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emission channels (Cy3 and Cy5). Image analysis consisting of spot detection, gel-to-gel matching of

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the standard spot maps, and data normalization was performed using Progenesis SameSpots program,

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version 4.0 (Nonlinear Dynamics Ltd., Newcastle, UK).

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Identification of deregulated proteins was achieved by statistical analysis using three different

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classification parameters. First, the samples were grouped according to the pathology by comparing

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expression profiles of the three groups studied, DE, MGD, and CT. Second, the protein profiles

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associated with different grades of SM, determined by conventional PAS-hematoxylin staining, were

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compared. Finally, protein expression profiles common for MGD and DE groups were compared with

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those in the control group.

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Significant differences between the groups were determined using the method of significance analysis

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of microarrays (Tusher et al., 2001). Normalized spot volumes obtained with SameSpots were used

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with a false discovery rate cutoff value of 0.01. Feature subset subtraction and clustering of samples

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were then performed using CDA, employing the candisc package of R statistical program (Friendly,

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2010). 2.7 MALDI-TOF/TOF analyses

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For MALDI-TOF/TOF protein identification, a preparative gel electrophoresis with 315 µg of the Cy3-

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labeled internal standard was carried out. The fluorescent proteins were visualized using VersaDoc

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Imaging System. Immediately afterward, the spots on the preparative gel were matched with the DIGE

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analytical reference gel. The differentially expressed spots were selected for identification. Protein

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spots of interest were automatically picked up from the gel with the Spot Picker (GE Healthcare).

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Protein spots were in-gel digested with trypsin according to the method of Shevchenko (Shevchenko et

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al., 2006). Peptide mass fingerprinting was performed on a Bruker Ultraflex TOF/TOF Mass

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Spectrometer (Bruker Daltonics, Bremen, Germany). Positively charged ions were analyzed in

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reflector mode, using delayed extraction. The spectra were obtained by randomly scanning the sample

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surface. Typically, 600–800 spectra were averaged to improve the signal-to-noise ratio. Spectra were

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externally calibrated, resulting in a mass accuracy < 50 ppm. Protein identification was performed by

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searching against the UniProt/Swiss-Prot release 2013_07 database using the Mascot search engine.

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The charge state was adjusted to +1. Mass tolerance for MS precursors was set to 33 ppm and 0.8 Da

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for MS/MS fragments, methionine oxidation was included as a variable modification, and one missed

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cleavage was allowed.

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2.8 Functional enrichment analysis Once the most significant spots were identified, a functional enrichment analysis using the 7

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bioinformatics tool DAVID was performed to verify the biological functions associated with the

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studied pathologies.

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2.9 Dot blot validation of ANXA1, S100A8, and S100A4 After identification of the most significant spots were identified, a dot blot assay was performed to

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validate the ANXA1, S100A8, and S100A4 proteins as potential biomarkers of the studied pathologies

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on separate independent samples.

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Dot blot assay for each protein was carried out as follows. EZQ® 96-well microplate cassette

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(Invitrogen Dynal) was used as a template for random loading of 24 DE, 25 MGD, and 15 CT

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conjunctival samples onto PVDF membranes. The membranes were blocked with blocking buffer (5%

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non-fat milk in PBS-T) overnight at 4 ºC. Then, the membranes were incubated with 1 ml of purified

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mAbs at 1 µg/ml in blocking buffer, for 1 h at room temperature. Antibody binding was detected with

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HRP-conjugated anti-mouse IgG (1:2500 in blocking buffer). The chemiluminescence signal was

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obtained using the SuperSignal™ ELISA Pico Chemiluminescent Substrate. The signal corresponding

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to protein levels was visualized using a VersaDoc Imaging System (Bio-Rad). After testing for normal

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distribution, significant differences between the groups were determined using Kruskal-Wallis non-

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parametric test, with a post hoc test for pairwise testing between the groups. Finally, the Pearson

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correlation analysis was performed to assess correlations between clinical parameters and protein

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levels. Statistical analysis was conducted using the R statistical program (Friendly, 2010).

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3. Results

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3.1 Patients

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The 126 individuals enrolled in this study were clinically diagnosed and classified within DE, MGD,

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or CT groups. The male vs. female ratio was 44% vs. 66% for DE; 46% vs. 64% for MGD, and 48%

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vs. 52% for CT. Group age range was well balanced. No statistical significant differences were

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observed in the age between males or females in groups, according to Kruskal-Wallis one-way

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ANOVA nonparametric test, (p-value > 0.05). Demographic data are presented in Table 1.

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3.2 PAS-hematoxylin staining for SM grade determination in the discovery study

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We found that SM of patients included in the discovery study was of grade 0 (healthy) to 4 (severe)

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according to the Locquin and Langeron protocol, modified by Rivas et al. (Rivas et al., 1991). PAS-

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hematoxylin IC analyses indicated that in 27 CT samples, 59% of individuals did not have SM (G0),

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whereas the remaining 41% presented grade 1, 2, 3, and 4 (G1, G2, G3, and G4; Table 2). 8

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The ocular surface epithelium was not affected in 58% of patients in the DE and 37% in MGD group.

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The remaining patients presented low (G1) and moderate (G2) grades (16% of the DE and 25% of

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MGD group). Advanced (G3) and severe (G4) grades of SM were found in 26% of the DE and 37% of

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MGD patients.

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Figure 1 shows representative images of cell morphology in CIC samples with different grades of SM.

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3.3 2D-DIGE analysis of conjunctival epithelium proteome using IC samples

We used a comparative 2-D DIGE saturation labeling approach, specifically standardized for CIC

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samples, in combination with MALDI-MS protein identification technology. We obtained a proteome

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map for conjunctival epithelium tissue, formed by 348 resolved spots in the pH range between 5 and 8,

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each spot corresponding to an isoform of a specific conjunctival protein (Figure 2D).

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Representative images of the proteome of each studied group, highlighting the spots with significant

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differences, are presented in Figure 2A-C. These images demonstrate clear differences between the

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protein profiles associated with different pathologies.

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3.4 Statistical analysis

To establish which protein spots can discriminate best between the pathological groups, the data were

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filtered according to the statistical significance as described above. The proteins with significant

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expression changes were picked up from the gel and identified using MALDI-TOF/TOF mass

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spectrometry.

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Based on stepwise discriminant analysis, 3 statistical filtering procedures were followed, searching for:

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i) The proteins differentially expressed between study groups. When analyzing the proteins with

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significant differences in their expression levels in the 3 experimental groups, the number of spots was

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reduced to 17 discriminatory variables (p-value < 0.01) (Table 3).

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The analysis revealed a substantial overexpression of several proteins in DE group: protein

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S100A4 (S100A4), protein S100A8 (S100A8), retinal dehydrogenase-1 (ALDH1A1), peroxiredoxin-1

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(Prdx1), annexin A1 (ANXA1), α-enolase (ENO1), annexin A2 (ANXA2), and glutathione S-

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transferase P (GSTP1). In most cases, the lowest expression levels for these proteins were found in CT

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group. The only exception was ALDHA1, whose expression was at its lowest level in MGD group.

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There was also a cluster of proteins with the highest expression in MGD group and lowest in CT. The

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cluster was formed by peroxiredoxin-6 (PRDX6), actin cytoplasmic1 (ACTB), peroxiredoxin-2

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(PRDX2), and heat shock protein HSP-90-α (HSP90A). Lipocalin-1 (LCN1), heat shock protein beta-1

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(HSPB1), cystatin-SN (CST1), disulfide isomerase A3 (PDIA3), and galectin-3 (LGALS3) were

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underexpressed in one of the two pathological groups in comparison with CT group. HSPB1, CST1,

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and PDIA3 were downregulated in the MGD group, and LCN1 and LGALS3, in the DE group. The

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differences between the expression levels of these proteins in each group are illustrated in the relief

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map shown in Figure 3A, and the statistics are shown in Table 3. The canonical discriminant analysis

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(CDA) using the entire set of 17 proteins showed that the samples were correctly assigned to the

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appropriate pathological groups except for one MGD individual whose profiles were similar to those in

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group CT (Figure 3B). ii) Correlation between proteome profile changes and the grade of SM. We performed a

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comparative analysis of the protein profiles and associated grades of SM. The analysis took into

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account the SM grades (0–4), not the membership of study group (CT, MGD, or DE). Stepwise

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discriminant analysis of the expression data revealed a set of 11 significant spots clearly differentiating

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between samples with lower SM grades (0 and 1) and samples with SM grade 4. Notably, the set

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contained 5 different types of cytokeratins (KRT1, KRT4, KRT8, KRT10, and KRT13; Table 4).

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KRT1, KRT4, and KRT10 had the highest expression levels in the individuals with SM of grade 4

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(group G4, positive fold values). KRT8 had the highest expression levels in SM-group G0 and KRT13,

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in group G1. In the samples with SM of grade 4, proteins HSPB1, S100A4, and ALDH1A1 were also

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overexpressed, while LGALS3, PDIA3, and LCN1were underexpressed. The differences between

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expression levels of these proteins and the associated statistical values are shown in Figure 4A and

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Table 4. The CDA showed a clear separation between the most severe grades of SM (G4) and the

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lowest grade (G1) or absence of SM (G0). Likewise, although to a lesser degree, there was a difference

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between the projections onto the axes for SM grades G0 and G1 (Figure 4B). The differences between

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the grades G2 or G3 in comparison with G0 or G4 were not significant for the studied proteins (data

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not shown).

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iii) Differences between proteome profiles in OSD patients and healthy individuals. Finally, the

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pathological groups DE and MGD were analyzed together; their expression profiles were jointly

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compared with the profiles of CT group. Stepwise discriminant analysis revealed a statistically

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significant set of 9 protein spots. This set was formed by a cluster of proteins overexpressed in the

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pathological group: ANXA1, ENO1, ANXA2, S100A8, KRT1, PRDX2, and leukocyte elastase

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inhibitor (SERPINB1). The levels of expression of LGALS3 and LCN1were lower in the samples from

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the pathological group than in the CT group (Figure 5A and Table 5).

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The analysis demonstrated the correct separation of the samples belonging to the two groups.

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There was one OSD patient who appeared as an outlier in the CT group, indicated by an arrow in

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Figure 5B. This result is in agreement with the results obtained in the comparison of individual

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pathological groups (Figure 3B), where the same patient (MGD) was also associated with CT group. 10

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3.5 Functional enrichment analysis To find the biological processes in which the identified differentially expressed proteins are

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involved, we carried out a functional enrichment analysis with the 17 most discriminative proteins

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(Table 3), using DAVID bioinformatics web tool. The analysis showed a cluster of Gene Ontology

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terms including epidermis and endodermis development, response to oxidative stress, cellular response

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to stress, regulation of apoptosis, and peptidase inhibitor activity processes. Only the terms enriched

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with a false discovery rate q-value < 0.05 were considered. These categories were significantly

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overrepresented in relation to their frequency. A considerable involvement in response to wounding,

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defense response to bacteria, and inflammatory and immune responses was also observed. Our results

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suggest that these physiological processes are implicated in the studied diseases.

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3.6 Validation of ANXA1, S100A8, and S100A4

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To verify the 2D-DIGE findings, the expression levels of proteins ANXA1, S100A8, and S100A4

14

were measured in the conjunctival tissue from an independent sample group of DE and MGD patients

15 16 17

and controls, using dot blot chemiluminescence assays (Figure 6).

Dot blot results showed that the levels of conjunctival ANXA1, S100A8 and S100A4 were

18

significantly higher in the DE and MGD group than in the control group (Figure 7), which confirmed

19

the 2D-DIGE results. Significant differences between the DE and MGD groups were only observed in

20

the case of S100A8 protein (Table 6).

21

The chemiluminescence levels of proteins ANXA1, S100A8, and S100A4 were used to assess the

22

correlation between the biomarkers and clinical parameters. A post hoc Pearson correlation analysis

23

was performed to determine whether the individual protein levels were associated with the tested

24

clinical parameters (Schirmer I test, TBUT (tear breakup time), and SM). The results showed that

25

increased S100A8and S100A4 levels were significantly associated with enhanced levels of ANXA1. A

26

similar association was also observed between the levels of S100A8 and S100A4 proteins. High values

27

obtained in Schirmer I tests were significantly associated with decreased levels of ANXA1 and

28

S100A8. TBUT values were correlated with the levels of S100A4 protein, and there was a positive

29

correlation between the TBUT and Schirmer test results. Finally, the SM grade showed a significant

30

positive correlation with S100A8 and S100A4 levels and a negative correlation with Schirmer I and

31

TBUT test results (Table 7).

32

4. Discussion

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ACCEPTED MANUSCRIPT Conjunctival proteome study is a pivotal approach to identify disease-specific proteins involved in

2

several ophthalmic diseases. However, such analyses have been limited by the necessity of obtaining

3

conjunctival tissue samples using invasive surgical techniques such as biopsies or from the post-

4

mortem donor tissues. This limitation has made a detailed proteome characterization of conjunctival

5

tissue difficult. In fact, the Human Eye Proteome Project report published in 2013 does not contain any

6

annotations referring to this tissue (Semba et al., 2013).

7

Implementation of noninvasive conjunctival sample collection techniques such as CIC in proteomic

8

studies has been hindered by the scarcity of the cellular material obtained using such tissue collection

9

techniques. Thus, in the few previously reported conjunctival proteomic studies, as in the case of the

10

conjunctival analysis of pterygium proteome using one-dimensional gel electrophoresis and LC-ESI-

11

MS/MS analysis, large amounts of proteins (50 µg) were required (Kim et al., 2014). In our study, the

12

standardization of 2D-DIGE technique for scarce samples (such as those obtained from CIC), let us

13

use much lower amounts of proteins, 5 µg per sample (ten-fold reduction in the amount of protein).

14

This study is the first report in which such sensitive proteomic techniques are applied to the minimal

15

ocular surface samples.

16

As the conjunctival epithelium and tear film are in close contact, any alteration in the LFU might

17

induce a serious perturbation in the system (Stern et al., 1998; Tseng and Tsubota, 1997). Considerable

18

effort has been put into the studies of the function of the tear fluid. However, the proteome of the

19

conjunctival tissue and its changes in pathologies like DE and MGD have not been analyzed in detail.

20

In particular, differential proteomic analysis of samples obtained from the conjunctiva collected by

21

noninvasive methods has not been widely applied. The knowledge of specific changes in the proteome

22

of conjunctival epithelium in different pathologies allows a comparative assessment of the biological

23

processes governing the disorders in this tissue.

24

Using the information obtained in the proteomic analysis, we conducted statistical tests to address

25

three fundamental questions of clinical interest: i) What are the specific differences between the

26

conjunctival proteomes of the pathological study groups? ii) Is there a correlation between the

27

alteration in the conjunctival epithelium determined by SM grading and the expression of certain

28

proteins? iii) Which proteins can define the distinct pathological factors associated with OSDs such as

29

DE and MGD and differentiate between the disease and a healthy state?

30

Our comparative analysis of conjunctival epithelium proteome revealed that the expression of various

31

proteins is significantly altered in the affected tissue and can be used to distinguish between the three

32

study groups.

33

GO analysis showed that these proteins are involved in inflammatory and defense response to bacteria

34

(ANXA1, ANXA2, S100A4, S100A8, PRDX1, and PRDX2), oxidative stress and response to stimulus

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ACCEPTED MANUSCRIPT (PRDX1, PRDX2 y PRDX6, GSTP1, HSP90A, and HSPB1), and the regulation of apoptosis

2

(ANXA1, GSTP1, PRDX1, PRDX2, and HSPB1). Preliminary studies have shown that these proteins

3

are also associated with the processes occurring during tissue damage and wound healing, which are

4

implicated in the biological mechanisms of DE and MGD pathologies (Reinoso et al., 2011;

5

Wakamatsu et al., 2008). Cluster analysis performed in our study showed that the two conditions

6

clearly differ, on the basis of the changes in the expression levels of these proteins. In the MGD group,

7

we found a characteristic substantial overexpression of the proteins related to the oxidative stress,

8

stress response, and anti-apoptotic processes: PRDX2, PRDX6, ACTB, and HSP90A. In contrast,

9

ALDH1A1, HSPB1, CST1, and PDIA3 were significantly underexpressed in this group.

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The main difference between DE and the other groups was the association with the proteins related to

11

inflammatory processes, such as S100 protein family or annexins. Notably, one of the proteins

12

overexpressed in DE group was ANXA2. This protein has been implicated in the regulation of body

13

fluid secretion in other species as can be inferred from the annotations in Rat Genome Database

14

(http://rgd.mcw.edu/). This is a very interesting result given that in the individuals with DE, the tear

15

secretion level may be substantially altered.

16

Physiologically, both DE and MGD progress via inflammatory processes damaging the ocular surface

17

epithelium and causing mild to advanced SM. However, the SM is not exclusively the consequence of

18

DE and MGD; it is also associated with other conditions that damage the ocular surface. SM can be

19

caused by chemical injury, Sjögren's syndrome, vitamin A deficiency, conjunctivochalasis,

20

keratoconjunctivitis, or limbal stem cell deficiency, pterygium, among others (Chan et al., 2002; Kim

21

et al., 2014; López-García et al., 2006; Tseng, 1985). Therefore, we also evaluated the differences in

22

the protein profiles as a function of the grade of SM. The results showed a positive correlation between

23

protein expression levels in the conjunctiva and the grade of SM. Interestingly, the different SM grades

24

correlated with different expression levels of several cytokeratins: KRT1, KRT4, KRT8, KRT10, and

25

KRT13. These proteins are heavily involved in the organization of the cytoskeleton. Changes in the

26

levels of expression of HSPB1, PDIA3, LCN1, S100A4, LGALS3, and ALDH1A1 accompanied the

27

progression to the most severe grades of SM. In particular, protein ALDH1A1 was overexpressed in

28

the individuals with SM of grade 4 (2.5-fold). This protein is involved in the metabolism of retinol

29

(vitamin A); it catalyzes the reaction producing retinoate from retinal. Retinal is the product of

30

dehydrogenation of vitamin A or retinol. The overexpression of ALDH1A1 could shift the reaction

31

toward the production of retinoate and increase the consumption of vitamin A, thus reducing its levels.

32

It has been shown that vitamin A is necessary for normal differentiation of nonsquamous epithelium.

33

Vitamin A deficiency causes abnormal differentiation of the ocular surface, resulting in keratinization

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ACCEPTED MANUSCRIPT of both conjunctival and corneal epithelial cells (Sommer, 1983). Therefore, dysregulation of the

2

expression of this protein might push the differentiation of the conjunctiva toward more advanced SM.

3

These results are biologically consistent, as it has been shown that the keratinization of the

4

conjunctival epithelium occurs in SM of higher grades. The keratinization is promoted by involucrin

5

and filaggrin and also by overexpression of cytokeratins KRT1, KRT2, and KRT10 (Krenzer and

6

Freddo, 1997; Nakamura et al., 2001; Resing et al., 1984; Tseng et al., 1984). The results of our study

7

are in agreement with those findings; we demonstrated that the overexpression of keratins KRT1 and

8

KRT10 was associated with the keratinization of the conjunctival epithelium. We also observed that

9

overexpression of cytokeratins KRT4 and KRT13 was associated with an increased deterioration of

10

ocular surfaces. Although a preliminary study has not found any alterations in the expression of these

11

cytokeratins (Nakamura et al., 2001), changes in their expression have been reported in other types of

12

stratified epithelium, such as stratified oral epithelium (Bragulla and Homberger, 2009).

13

These results led us to hypothesize that the keratin pairs KRT4/KRT13 and KRT1/KRT10 might

14

jointly participate in the process of keratinization of the stratified conjunctival epithelium. We also

15

demonstrated a reduced expression of KRT8, the protein characteristic for nonkeratinized conjunctival

16

tissues, in samples with advanced SM grades. Thus, the presence of keratinization can be determined

17

by examining the expression of cytokeratin pairs KRT4/KRT13 and KRT1/KRT10. KRT13 was the

18

only protein overexpressed in the samples with low-grade SM (G1). This overexpression was probably

19

promoted by cellular signaling molecules such as HSPB1 (protein implicated in the activation of

20

keratin polymerization) (Magin et al., 2007).

21

Our comparison of the controls with the two pathologies grouped together as one disease group

22

showed dysregulation of proteins involved in the defense response to bacteria, inflammatory and

23

immune response, and response to wounding (S100A8, ANXA1, KRT1, and PRDX2). We also found

24

a decrease in the levels of expression of LGALS3 in the pathological groups. This protein is involved

25

in the biological processes associated with cellular adhesion and the cellular matrix organization. Its

26

reduced expression could account for the progressive deterioration in intercellular communication,

27

characteristic for both pathologies (Tseng, 1985). In this last comparison, we found an individual who

28

had been clinically classified as MGD but was clustered with the control group. The same patient was

29

found grouped with the CT individuals when we conducted the analysis of the three separate groups

30

(Figure 2). A review of his medical history revealed some mild episodes of MGD in the past; there was

31

no inflammation at the time of sampling. This explains the placement of this individual in the CT

32

group; it also confirms the validity and effectiveness of such differential proteomics studies in

33

obtaining classification models not based solely on clinical parameters.

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ACCEPTED MANUSCRIPT Validation of candidate biomarkers by orthogonal techniques and independent samples is a crucial step

2

in differential expression analysis. Due that 2D-DIGE may detect changes in isoforms of proteins, this

3

validation step is especially determinant to verify that the expression change observed corresponds to

4

the entire protein, and not only to a particular isoform of a protein. Accordingly, we validated the three

5

most highly expressed candidate biomarkers observed in the 2D-DIGE study, ANXA1, S100A8, and

6

S100A4, using dot blot assays. The dot blot results corroborated the findings of the proteomic 2D-

7

DIGE experiments and revealed significantly increased levels of ANXA1, S100A8, and S100A4 in the

8

DE and MGD patients in comparison with the control group. However, only the levels of S100A8

9

differed significantly between DE and MGD groups; the protein was highly expressed in the DE

10

patients. Thus, S100A8 protein is a promising candidate for the discrimination between DE, MGD, and

11

CT groups in conjunctival samples.

12

Finally, Pearson correlation analysis was performed to assess the correlation between clinical

13

parameters (Schirmer, TBUT, and SM) and the levels of validated biomarkers. The results showed a

14

significant correlation between these parameters and the levels of the 3 biomarkers in the conjunctiva.

15

Schirmer I test results were negatively associated with ANXA1 and S100A8 levels, TBUT values were

16

negatively associated with S100A8 and S100A4, and SM grade showed a positive correlation with

17

S100A8 and S100A4 levels. Overexpression of S100A protein family, including S100A4 and S100A8,

18

have also been reported in the conjunctival tissue of pterygium patients (Riau et al., 2009). S100A8 is

19

overexpressed in the tears (Boehm et al., 2013; Grus et al., 2005; Matheis et al., 2015; Soria et al.,

20

2013; Zhou et al., 2009) and conjunctiva of DE patients and MGD patients (Tong et al., 2011).

21

S100A4 is overexpressed in the tears of DE patients (Soria et al., 2013; Zhou et al., 2009). Finally, an

22

increased expression of ANXA1 has been reported in the tears of DE patients (Li et al., 2013; Matheis

23

et al., 2015).

24

5. Conclusions

25

This study sheds new light onto some of the processes taking place in the conjunctival epithelium. We

26

presented some detailed proteomic data obtained using samples with low protein content collected by

27

noninvasive IC technique. We also presented a panel of proteins that can differentiate between the

28

processes associated with DE and MGD pathologies. The expression profiles of these proteins are

29

related to different SM grades and allow the detection of pathological components in the conjunctiva

30

samples.

31

In conclusion, our study showed that: i) In comparison with MGD group, DE samples were

32

characterized by a substantial overexpression of proteins related to defense response, tissue damage,

33

wound healing, and regulation of body fluid secretion. MGD individuals overexpressed the proteins

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ACCEPTED MANUSCRIPT associated with oxidative stress, stress response, and anti-apoptotic processes. Moreover, the proteins

2

that are involved in these processes can be used to differentiate both between the pathological groups

3

and between each of these groups and control group. ii) There is a correlation between the changes in

4

the expression profiles of some cytokeratin pairs (and other proteins related to the organization of

5

cytoskeleton and keratinization) and the severity of SM. iii) There is a common component in the two

6

studied pathologies (associated with processes of defense response to bacteria and inflammatory and

7

immune responses) that allows the correct differentiation between the two pathologies and healthy

8

state. iv) Dot blot immunoassays validated the proteomic results obtained in the experiments using 2D-

9

DIGE for the selected proteins ANXA1, S100A8, and S100A4.

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The tear fluid and conjunctival tissues are in close contact at all times and interact directly. Integral

11

analysis of OSDs ought to include an evaluation of both scarce samples: the conjunctiva and tear film.

12

The present study is the first to focus on IC conjunctival proteome from a high-throughput perspective.

13

Ultimately, we should be able to conduct integral studies of tear/conjunctiva proteome profiles in the

14

same patient. Such an approach should improve our understanding of OSDs and provide pivotal keys

15

to the differentiation and stratification of diseases that share signs and symptoms. It should also

16

improve monitoring of the response to treatment.

17

Financial support

18

This work has been partially supported by the Spanish Ministry of Science and Innovation through the

19

INNPACTO subprogram, grant IPT-2011-1429-010000, and the Centre for the Development of

20

Industrial Technology (CDTI), NEOTEC Program, grant IDI-20080118. The funding organizations

21

had no role in the design or conduct of this research.

22

Acknowledgments

23

Mass spectrometry analysis for protein identification was performed at the Proteomics Platform

24

(member of ProteoRed-ISCIII) of CIC bioGune.

25

Figure Legends

26

Figure 1. Representative images of PAS-hematoxylin staining of samples from patients with

27

different grades of SM A. CIC specimen from a healthy subject with normal conjunctival epithelium.

28

The cells are small and round, forming sheets of completely joined cells. The cytoplasm is

29

eosinophilic. The nucleus is large, without alterations, the N:C ratio is 1:2. There are numerous goblet

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ACCEPTED MANUSCRIPT cells. B. Sample from a patient with SM of grade 1. The nonsecretory epithelial cells are larger, with

2

N:C ratio of 1:3. C. Conjunctival cytology of a patient with SM of grade 2. The cells are larger and

3

polygonal and are separated; the intercellular connections are lost. The N:C ratio is 1:5. D. Sample

4

from a patient with SM of grade 3. The changes are similar to grade 2 SM, with the N:C ratio 1:15. E.

5

IC from a patient with SM grade 4. Goblet cells are absent. The cytoplasm of epithelial cells is larger.

6

The cells are keratinized, N:C ratio is 1:20 (cellulose acetate filters and PAS-hematoxylin staining,

7

×20).

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Figure 2. Representative conjunctival epithelium proteome map corresponding to Cy5-labeled 2D-

10

PAGE gel image of the DE group (A), MGD group (B), and control group (C). Significant proteins are

11

indicated by gray spots. The representative conjunctival proteome is shown in (D), with the spot

12

numbers of proteins identified by MALDI-TOF/TOF. Spot numbers and protein IDs are shown in

13

Tables 3-5.

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Figure 3. A. Three-dimensional view of the most representative protein spots from 2D-DIGE obtained

16

using Progenesis SameSpots, in the comparison of DE, MGD, and CT groups. Peaks were obtained by

17

multiplying the fluorescent intensity of the spot (in the mean gel) by its area. They represent the most

18

significant proteins obtained in the stepwise discriminant analysis. B. CDA showing the separation

19

between the samples as a function of the protein expression. In this representation, each of the points

20

represents a sample from each group. A good separation between the groups can be observed. Squares,

21

DE group; circles, MGD group; triangles, CT group. The MGD patient classified by CDA as a control

22

individual is indicated by an arrow.

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Figure 4. A. Three-dimensional view of the most representative protein spots from 2D-DIGE,

25

obtained using Progenesis SameSpots program, in the comparison of SM grade 0 (G0), grade 1 (G1),

26

and grade 4 (G4) groups. Peaks were obtained by multiplying the fluorescent intensity of the spot (in

27

the mean gel) by its area. They represent the most significant proteins obtained by stepwise

28

discriminant analysis. B. CDA showing the separation between the samples as a function of the protein

29

expression vs. SM grade. Each of the points represents a sample. A good separation between the

30

groups can be observed. Squares, G4 group; triangles, G1 group; circles, G0 group. A CT patient,

31

indicated by an arrow, was found in the interface between G0 and G1 grade of SM.

32

17

ACCEPTED MANUSCRIPT Figure 5. A. Three-dimensional view of the most representative protein spots from 2D-DIGE,

2

obtained using Progenesis SameSpots, in the comparison of the pathological condition (DE and MGD)

3

and control (CT) groups. Peaks were obtained by multiplying the fluorescent intensity of the spot (in

4

the mean gel) by its area. They represent the most significant proteins obtained by stepwise

5

discriminant analysis. B. Canonical discriminant analysis showing the separation between the samples

6

as a function of the values of the variables included in the analysis. In this representation, each of the

7

points represents a sample, and a good separation between the groups can be observed. A pathological

8

group-related outlier assigned to the control group is indicated by an arrow. Triangles, CT group;

9

circles, pathology-related group.

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Figure 6. Dot blot immunoassays of three biomarker candidates in the conjunctival tissue. Samples

11

were randomly positioned on the PVDF membranes to avoid technical bias. A. ANXA1. B. S100A8.

12

C. S100A4. D. Merged image shows an overlay of ANXA1 (blue), S100A4 (green), and S100A8 (red)

13

signals for each sample. Chemiluminescence of each dot blot was imaged independently using the

14

VersaDoc MP 4000 gel imager.

15

Figure 7. Comparison of control (CT), dry eye (DE), and meibomian gland dysfunction (MGD)

16

groups for 3 candidate biomarkers. The differential expression levels of ANXA1, S100A8, and

17

S100A4 obtained in 2D-DIGE were verified using the dot blot assay.

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ACCEPTED MANUSCRIPT Tomlinson, A., Bron, A.J., Korb, D.R., Amano, S., Paugh, J.R., Ian Pearce, E., Yee, R., Yokoi, N., Arita, R., Dogru, M., 2011. The international workshop on meibomian gland dysfunction: Report of the diagnosis subcommittee. Investig. Ophthalmol. Vis. Sci. 52, 2006–2049. doi:10.1167/iovs.10-6997f

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ACCEPTED MANUSCRIPT Table 1. Demographic data of patients included in the proteomic study.

Male

DE

MGD

CT Age ± SD

TOTAL

n

Age ± SD

n

Age ± SD

n

4

54.3 ± 21.7

5

43.8 ± 4.8

11 51.1 ± 22.1

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Female

15 53.9 ± 13.4

11 53.3 ± 10.7

16 55,9 ± 23.3

Male

15 64.9 ± 17.5

14 52.3 ± 17.5

9

33.3 ± 10.0

38

Female

9

59.2 ± 17.4

11 62.9 ± 12.5

6

53.3 ± 18.6

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43 58.1 ± 16.1

41 53.1 ± 14.1

42 49.5 ± 19.7

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DE = Dry eye, MGD = Meibomian gland dysfunction, CT = Control

Table 2. PAS-Hematoxylin results. SM grades of patients included in the discovery study,

by Rivas et al. [26]

DE 11 2 1 2 3 19

MGD 6 2 2 2 4 16

CT 16 3 2 0 6 27

TOTAL 33 7 5 4 13 62

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SM Healthy (G0) Mild (G1) Moderate (G2) Moderate (G3) Severe (G4) TOTAL

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according to PAS-Hematoxylin staining, following the Locquin and Langeron protocol modified

DE = Dry eye, MGD = Meibomian gland dysfunction, CT = Control SM = Squamous metaplasia

Table 3. Proteins identified by MALDI-TOF/TOF that undergo the most significant changes in

Spot Nº

Gene Name S100A4 S100A8 ALDH1A1 PRDX1 ANXA1 ENO1 ANXA2 GSTP1 PRDX6 ACTB PRDX2 HSP90A LCN1 HSPB1 CST1 PDIA3 LGALS3

PROTEIN NAME

ANOVA

FOLD

HIGH

LOW

Protein S100A4 Protein S100A8 Retinal Dehydrogenase-1 Peroxiredoxin-1 Annexin A1 α-Enolase Annexin A2 Glutathione S-transferase P Peroxiredoxin-6 Actin, cytoplasmic-1 Peroxiredoxin-2 Heat Shock protein HSP 90-α Lipocalin-1 Heat Shock protein-β1 Cystatin-SN Protein disulfide isomerase-A3 Galectin-3

5.24E-04 2.06E-02 6.68E-03 9.89E-03 1.12E-04 3.23E-03 1.18E-03 1.92E-03 5.02E-04 3.58E-04 2.31E-02 4.18E-03 2.09E-02 2.07E-03 1.15E-02 2.76E-02 1.32E-02

8.6 8.2 5.4 5.2 5.1 4.6 4.4 3.6 3.1 3.1 3.1 2.3 5.5 3.2 2.3 1.9 1.5

DE DE DE DE DE DE DE DE MGD MGD MGD MGD CT CT CT CT CT

CT CT MGD CT CT CT CT CT CT CT CT CT DE MGD MGD MGD DE

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their expression levels associated with the diseases.

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Table 4. Proteins identified by MALDI-TOF/TOF that undergo the most significant changes

89

PDIA3

409

LCN1

Protein Name

ANOVA

FOLD

HIGH

LOW

Heat Shock Protein-β1 Cytokeratin-13 Protein S100A4 Retinal dehydrogenase-1 Cytokeratin-4 Cytokeratin-10 Cytokeratin-1 Galectin-3 Cytokeratin-8 Protein disulfide isomeraseA3 Lipocalin-1

6.94E-03 3.56E-03 8.23E-03 1.63E-02 7.38E-04 1.22E-02 1.93E-02 1.31E-02 1.19E-02

3.9 3.3 2.8 2.5 2.4 2.3 2.1 2.2 2.3

G4 G1 G4 G4 G4 G4 G4 G0 G0

G0 G0 G0 G0 G0 G0 G0 G4 G4

1.48E-03

2.5

G0

G4

7.76E-03

3.8

G0

G4

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Gene Name HSPB1 KRT13 S100A4 ALDH1A1 KRT4 KRT10 KRT1 LGALS3 KRT8

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correlated with SM grades.

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239 188 268 630 116 366 236

Gene Name ANXA1 ENO1 ANXA2 S100A8 KRT1 PRDX2 SERPINB1

308 409

LGALS3 LCN1

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Spot Nº

Protein Name

Annexin A1 α-enolase Annexin A2 Protein S100A8 Cytokeratin-1 Peroxirredoxin-2 Leukocyte elastase inhibitor Galectin-3 Lipocalin-1

ANOVA

FOLD

2.26E-04 2.18E-04 3.97E-05 4.16E-03 1.36E-04 3.07E-03 1.03E-03

4.3 4.0 3.9 2.6 2.4 2.3 1.7

2.61E-04 7.27E-05

-1.9 -4.7

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ACCEPTED MANUSCRIPT Table 6. Statistical significance of differences between protein expression levels in the study groups. Significant values are indicated in bold (p-value < 0.05).

Post Hoc pvalue CT:MGD

Post Hoc pvalue DE:MGD

ANXA1

<0.0005

0.014

S100A8 S100A4

< 0.0001 < 0.0001

0.001 < 0.0001

0.139 0.019 0.995

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Post Hoc pvalue CT:DE

Table 7. Pearson correlation matrix for deregulated protein expression and clinical parameters. Significant values are indicated in bold (p-value < 0.05).

TBUT

SC

ANXA1 S100A8 S100A4 SCHIRMER

SM

1.000

S100A8

0.333

1.000

S100A4

0.378

0.421

1.000

SCHIRMER

-0.338

-0.430

-0.151

1.000

TBUT

-0.204

-0.459

-0.526

0.285

1.000

0.521 SM 0.176 SM = Squamous metaplasia

0.375

-0.468

-0.543 1.000

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ACCEPTED MANUSCRIPT We performed 2DE-DIGE analysis of dry eye and MGD diseases in conjunctiva We optimized conjunctival proteome analysis obtained by impression cytology We present a panel of proteins able to differentiate between studied groups Validation by dot-blot assays of three proteins confirmed 2DE-DIGE results

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