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Dry Eye Disease Emerging Approaches To Disease Analysis and Therapy

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Journal of

Clinical Medicine

Review
Dry Eye Disease: Emerging Approaches to Disease
Analysis and Therapy
Mostafa Heidari 1,2 , Farsad Noorizadeh 1 , Kevin Wu 3,4 , Takenori Inomata 5,6, *,† and
Alireza Mashaghi 7,8,9, *,†
1 Basir Eye Health Research Center, Tehran 1418643561, Iran; mostafahaidari70@yahoo.com (M.H.);
farsadnoorizadeh@gmail.com (F.N.)
2 Farabi Eye Hospital, Department of Ophthalmology and Eye Research Center, Tehran University of Medical
Sciences, Tehran 133661635, Iran
3 Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, Ophthalmic Consultation Service,
New York, NY 10029, USA
4 New York Eye and Ear Infirmary of Mount Sinai, New York, NY 10003, USA
5 Department of Ophthalmology, Juntendo University Faculty of Medicine, Tokyo 1130033, Japan
6 Department of Strategic Operating Room Management and Improvement, Juntendo University Faculty of
Medicine, Tokyo 1130033, Japan
7 Systems Biomedicine and Pharmacology Division, Leiden Academic Centre for Drug Research, Leiden
University, 2333CC Leiden, The Netherlands
8 Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
9 Department of Ophthalmology, Shanghai Medical College, Fudan University, Shanghai 200000, China
* Correspondence: tinoma@juntendo.ac.jp (T.I.); a.mashaghi.tabari@lacdr.leidenuniv.nl (A.M.)
† These authors are co-last authors.

Received: 31 July 2019; Accepted: 6 September 2019; Published: 11 September 2019 

Abstract: Dry eye disease (DED) is among the most common ocular disorders affecting tens of millions
of individuals worldwide; however, the condition remains incompletely understood and treated.
Valuable insights have emerged from multidisciplinary approaches, including immunometabolic
analyses, microbiome analyses, and bioengineering. Furthermore, we have seen new developments
in clinical assessment approaches and treatment strategies in the recent past. Here, we review the
emerging frontiers in the pathobiology and clinical management of DED.

Keywords: dry eye disease; immunometabolism; microbiota; omics; eye-on-a-chip; clinical signs;
DED treatment

1. Introduction
Dry eye disease is a multifactorial disease of the ocular surface [1]. The disease imposes a major
healthcare burden, given its high prevalence [2,3] with tens of millions of individuals seeking eye
care [4]. This condition is characterized by a dry, gritty, or burning feeling in the eye, as well as
excessive tearing and photosensitivity [5], thereby compromising clear vision and decreasing quality
of life. Several factors including dryness, trauma, air pollution, and smoke, allergens, dysbiosis, and
UV light, can increase tear osmolarity and destabilize the tear film, resulting in sensory stimulation
and irritation of the ocular surface [6]. This process triggers inflammatory pathways, recruits immune
cells, and leads to cytokine overexpression at the ocular surface, resulting in a vicious cycle that further
damages the area. The Tear Film & Ocular Surface Society International Dry Eye Workshop II (TFOS
DEWS II) released a report in 2017 that classified dry eye disease (DED) into two major classes: aqueous
tear-deficient DED and evaporative DED. The former can itself be classified into two subclasses as
Sjögren syndrome (SS): DED and non-SS DED [7].

J. Clin. Med. 2019, 8, 1439; doi:10.3390/jcm8091439 www.mdpi.com/journal/jcm


J. Clin. Med. 2019, 8, 1439 2 of 21

Despite progress, DED remains incompletely understood and treated. Interdisciplinary approaches
have been increasingly applied to resolve DED complexity and to develop new diagnostic and
treatment strategies. Novel concepts and tools from analytical chemistry, engineering, immunology,
and microbiology are being introduced and examined for the treatment of DED. Here, we review the
developments in DED treatment and care in the last five years, with particular emphasis on emerging
concepts and interdisciplinary approaches that may significantly impact the field in the future.

2. Emerging Insights into DED Pathogenesis


In recent years, we have witnessed the emergence of a new research frontier at the interface
of immunology and metabolic studies. The field of “immunometabolism” has already produced a
substantial number of discoveries and contributed to disease analysis [8]. Immunometabolic analyses
have in particular generated insights into autoimmunity including rheumatoid arthritis [9] and Lupus
erythematosus [10]. What is emerging is a delicate interplay between metabolic reprogramming and
immune signaling, which is providing an extra dimension to our understanding of the inflammatory
processes [11,12].
The field of immunometabolism is new to ophthalmology. There has been a surge in this
type of research in other areas of medicine, including neurology (e.g., Parkinson’s), cardiology (e.g.,
atherosclerosis), and geriatrics [13]. A similar approach could be highly valuable for ophthalmology
and in particular, for studying the inflammatory eye processes. However, this notion is yet new to the
field, and most researchers in ophthalmology have limited knowledge of this emerging area.
DED is an inflammatory disease that involves both metabolic and immune dysregulation.
The ocular surface is home to different microbial organisms that contribute to the metabolism of the
ocular surface. Pathological alteration of the microbial composition of the ocular surface can induce an
immune response. In the following sections, we discuss the changes in the metabolism, immunity, and
microbial composition associated with the pathogenesis of DED. This review strives to address the gap
in the understanding of the pathogenesis of DED and to identify the opportunities for improving the
treatment and care of DED.

2.1. DED-Associated Metabolic Dysregulation


Oxidative stress activates the pathologic cascade associated with DED at several points (Figure 1).
Reactive oxygen species (ROS) damages goblet cells, myelin sheaths of ocular-surface nerves, and
the tear lipid layer, which in turn results in tear-lipid instability and inflammatory dysregulation [14].
Tear instability causes increasing osmolarity, which can induce oxidative conditions at the ocular
surface. When primary human corneal epithelial cells (HCECs) were exposed to hyperosmolar media,
reactive oxidative substances increased significantly, as measured by 20 ,70 -dichlorofluoresceindiacetate,
a membrane-permeable substance that can be oxidized in cells during oxidative stress to produce
highly fluorescent 20 ,70 -dichlorofluorescein (DCF). 4-Hydroxynonenal (4-HNE) and malondialdehyde
(MDA), the toxic products of lipid peroxidation, increased in a dose-dependent manner as the media
osmolarity rose, and there were decreases in anti-oxidative enzymes, such as SOD and glutathione
peroxidase (GPx), in HCECs after exposure to hyperosmotic media [15]. Upon HCEC culturing in
hyperosmotic media (550–550 mOsm), another study showed that DCF staining and NLR family
pyrin-domain-containing (NLRP)3 inflammasome mRNAs, including NLRP3, apoptosis-associated
speck-like protein (ASC), pro-caspase, and pro-interleukin (IL)-1β, increased. Furthermore, these
elevations were inhibited by adding n-acetyl cysteine as an antioxidant to the medium. Interestingly,
silencing NLRP3 expression via small-interfering RNA in HCECs exposed to a hyperosmotic state
attenuated levels of ASC, pro-caspase, and IL-1β mRNA levels. All of these components, as well as
ROS levels, are elevated in DED patients [16]. Chi et al. [17] reported increases in IL-1β and IL-18
expression after reduction of NLRP3 levels by glybenclamide treatment in mice exposed to desiccating
stress (DS). Additionally, treatment with a caspase-1 inhibitor (z-YVAD fmk) did not alter NLPR3
activity but significantly restored NRLP6 production (an inflammasome component) downregulated by
J. Clin. Med. 2019, 7, x FOR PEER REVIEW 3 of 20

activation, as well as its downstream pathways. These findings showed that hyperosmolar stress
accelerates an immune cascade via oxidative stress, thereby offering several targets for potential
prevention and treatment of DED.
J. Clin. Med. 2019, 8, 1439
There are several other anti-oxidative mechanisms that compensate for oxidative stress. Liu et al. 3 of 21
[18] measured the levels of sirtuin 1, FOXO3, and manganese superoxide dismutase (SOD) proteins
in diabetic mice with DED, observing elevated levels at weeks 1 and 4 in the diabetic DED group as
hyperosmolar
compared stress.
with Moreover,
those in thecaspase-8
non-DEDcan stimulate
group, althoughNLRP3 activation,
the levels as well
decreased by weekas its8. downstream
They
pathways. Thesethat
concluded findings showed
this change thattohyperosmolar
was due stress accelerates
compensatory mechanisms antheimmune
to increase levels of cascade
anti- via
oxidative molecules in diabetic mice, but by week 8, the anti-oxidative system was
oxidative stress, thereby offering several targets for potential prevention and treatment of DED. exhausted.

Figure 1. Oxidative metabolism and changes in normal microbiota contribute to dry eye disease
Figure 1. Oxidative metabolism and changes in normal microbiota contribute to dry eye disease (DED)
(DED) by inducing inflammation at the ocular surface. Reactive oxygen species (ROS) directly or
by inducing inflammation at the ocular surface. Reactive oxygen species (ROS) directly or indirectly
indirectly activates the NLRP3 inflammasome by increasing tear-film instability and osmolarity.
activatesDED-associated
the NLRP3 inflammasome by increasing
changes in the microbiota tear-film
is in turn instability
associated and osmolarity.
with changes DED-associated
in the metabolic profile
changesofinthe
theocular
microbiota
surfaceiswhich
in turn associated
changes with changes
the balance between in theand
pro- metabolic profile of arms
anti-inflammatory the ocular
of the surface
which changes
immune the balance
system toward between pro- and anti-inflammatory
the proinflammatory pathways. The inducedarmsinflammation
of the immune system toward
is presumably
the cornerstone of
the proinflammatory DED pathology.
pathways. Abbreviations:
The induced DED: dry eye
inflammation disease, FoxO3:the
is presumably Forkhead box O3,of DED
cornerstone
LPS: lipopolysaccharide, MnSOD: manganese superoxide dismutase, NLRP3: NLR family pyrin-
pathology. Abbreviations: DED: dry eye disease, FoxO3: Forkhead box O3, LPS: lipopolysaccharide,
domain-containing 3, ROS: reactive oxygen species, Sirt1: sirtuin 1, SOD: superoxide dismutase, Treg:
MnSOD: manganese superoxide dismutase, NLRP3: NLR family pyrin-domain-containing 3, ROS:
regulatory T-cell.
reactive oxygen species, Sirt1: sirtuin 1, SOD: superoxide dismutase, Treg: regulatory T-cell.
2.2. DED Immunity and Immunometabolism
There are several other anti-oxidative mechanisms that compensate for oxidative stress.
According to the current models, T helper (Th)17 (IL-17-secreting CD4+ T cells) and Th1 cells are
Liu et al.the[18] measured the levels of sirtuin 1, FOXO3, and manganese superoxide dismutase (SOD)
major immune mediators of DED [19] and are recruited to the ocular surface by C-C motif
proteinschemokine
in diabetic mice (CCR)6
receptor with DED, observing
and CCR3, elevated
respectively. Coursylevels
et al.at weeks
[20] 1 and
reported that4DS
inincreases
the diabetic
the DED
group aspopulation
compared with those and
of CCR6+CD4+ in the non-DEDT cells
CCR3+CD4+ group, although
at the the levels
ocular surface and indecreased by week
regional lymph nodes,8. They
resulting
concluded in their
that this respective
change was duesecretion of IL-17 and IFN-γ.
to compensatory Moreover,
mechanisms ablation ofthe
to increase these twoof
levels receptors
anti-oxidative
avoids
molecules corneal barrier
in diabetic mice, disruption,
but by week T-cell infiltration,
8, the and GC system
anti-oxidative loss in response to DS. Additionally,
was exhausted.
CCR3 ablation avoids corneal barrier disruption and T-cell infiltration but does not decrease the GC
loss
2.2. DED in response
Immunity andto Immunometabolism
DS, whereas IFN-γ secretion does decrease GCs in DED [21,22].

According to the current models, T helper (Th)17 (IL-17-secreting CD4+ T cells) and Th1 cells
are the major immune mediators of DED [19] and are recruited to the ocular surface by C-C motif
chemokine receptor (CCR)6 and CCR3, respectively. Coursy et al. [20] reported that DS increases the
population of CCR6+CD4+ and CCR3+CD4+ T cells at the ocular surface and in regional lymph nodes,
resulting in their respective secretion of IL-17 and IFN-γ. Moreover, ablation of these two receptors
avoids corneal barrier disruption, T-cell infiltration, and GC loss in response to DS. Additionally, CCR3
ablation avoids corneal barrier disruption and T-cell infiltration but does not decrease the GC loss in
response to DS, whereas IFN-γ secretion does decrease GCs in DED [21,22].
Th17 cells migrate to the ocular surface by expressing CCR6 on their surface. CCR6 binds to C-C
motif chemokine ligand (CCL)20, which is expressed on the ocular surface epithelium and upregulated
in DED patients. However, blockade using an anti-CCL20 antibody decreases Th17 propagation and
J. Clin. Med. 2019, 8, 1439 4 of 21

infiltration of the ocular surface in DED and improves clinical signs of DED while decreasing the
cytokine expression (IL-6, IL-23, TNFα, and IFN-γ). CD11b+ cells are antigen-presenting cells (APCs)
recruited to the cornea during inflammatory conditions. When treated with subconjunctival injection of
an anti-CCL20 antibody, CD11b+ cell infiltration to the cornea decreases [23]. Additionally, treatment
with an antibody against granulocyte-colony-stimulating factor reduces in vivo and in vitro migration
and maturation [expressing major histocompatibility complex (MHC) II] of CD11b+ dendritic cells
(DCs) at the ocular surface and improves clinical signs of DED in murine models. Furthermore,
granulocyte-macrophage colony-stimulating factor (GM-CSF) recruits CD11b+ APCs to the ocular
surface. It has been shown that Th17 cells are the sources of upregulated GM-CSF in DED at the ocular
surface [24].
IFN-γ is an inflammatory cytokine secreted by the Th1 lymphocytes and mediates cellular changes
during DED progression [25]. IFN-γ increases aqueous tear deficiency (ATD; both Sjögren and
non-Sjögren), with the IL13:IFN-γ ratio decreasing in both ATD groups as compared with that in
controls [26]. Mucin proteins promote GC density, and mucin 5AC (MUC5AC) transcripts were lower
in both ATD groups while levels of conjunctival IFN-γ were negatively correlated with tear meniscus
(TM) height (TMH) and conjunctival GC density. Additionally, small proline-rich protein 2G transcripts
were higher in patients with ATD and positively correlated with IFN-γ levels. IFN-γ and IL-13,
the inflammatory cytokine release by Th2 lymphocytes, stimulates proliferation of less-differentiated
GCs and the expression of MUC5AC [27]. In addition, IL-13 stimulates the expression of the Fas
ligand, CCL26, chloride channel calcium-activated 3, trefoil factor 3, and restin-like molecule β, which
function as an apoptotic receptor on lymphocytes, a chemotactic factor of CD4+ Th cells, eosinophils,
and basophils, a marker of GC hyperplasia and secretory activity, and a repair and maintenance factor
for mucosal epithelial-barrier function, respectively. IFN-γ inhibits the GC proliferation in murine
models [22] and increases levels of proteins involved in the unfolded protein response (UPR), which
inhibits MUC2 and MUC5AC mRNA translation. Dexamethasone treatment of GC cultures reduces
IFN-γ-mediated caspase-3 and UPR-related activities, thereby preventing attenuated MUC5AC levels.
Glucose-regulated protein 78 kD and spliced X-box-binding protein-1 are significantly increased in
the conjunctival epithelium of patients with SS. Garcia-Posadas et al. [28] found that IFN-γ increases
the intracellular calcium concentrations but inhibits cholinergic intracellular increases of calcium.
Additionally, long-term elevations in IFN-γ levels prevents cholinergic stimulation of GC-related mucin
production by activation of the Janus kinase (JAK)-signal transducer and activator of transcription
(STAT) signaling pathway.
Chen et al. [19] reported that conjunctival mRNA expression of Th17-associated cytokines (IL-17A,
IL-6, and IL-23) were elevated in DED patients, with IL-17A and IL-6 higher in Sjögren DED than in
non-Sjögren DED and no significant difference in IL-23 levels between groups. Interestingly, the levels
of these cytokines correlated with DED-specific ocular-surface parameters, such as ocular surface
disease index (OSDI), tear-film break-up time (TBUT), the Schirmer I test, and cornea fluorescein
staining [29].
IL-17 secreted by Th17 cells triggers the B cell proliferation and differentiation, and both Th17
and Th1 cells significantly increase B cell proliferation; however, Th17 is more functional than Th1 in
this regard. IL-17 increases the proliferation of autoimmune B cells after stimulation with anti-CD40
and anti-IgM antibodies, which also increase the expression of the IL-17 receptor on the B cell surface.
Additionally, IL-17 and IFN-γ secretion increase the B cell differentiation and proliferation as dominant
factors in promoting DS-induced ocular-surface damage [30].
Although the adaptive immune response promotes DED-specific inflammatory processes, primary
activation of this cascade does not require Th cells. DS induces MHC I-related protein A and protein B
production, which activates the natural killer (NK) cells that release IFN-γ, thereby triggering epithelial
cells of the corneal conjunctiva to produce Th1-related chemokines to promote the infiltration of Th1.
However, the absence of Th1 cells does not inhibit the initiating phase of this process, indicating that
the innate immune system is critical in initiating IFN-γ release to produce Th1-related chemokines [31].
J. Clin. Med. 2019, 8, 1439 5 of 21

Both CD4+ and CD8+ Tregs suppress the inflammatory process in DED [32]. In murine models,
J. Clin. Med.
depletion 2019, 7, x FOR PEER
or inactivation REVIEW T cells by anti-CD8 antibodies promoted corneal infiltration
of CD8+ 5 of 20 of
CD4+ T cells and their increased levels in draining cervical lymph nodes (CLNs). Furthermore,
Both CD4+ and CD8+ Tregs suppress the inflammatory process in DED [32]. In murine models,
IL-17A production by both ocular-surface cells and CD4+ T cells increased, whereas IFN-γ production
depletion or inactivation of CD8+ T cells by anti-CD8 antibodies promoted corneal infiltration of
decreased
CD4+ in ocular-surface
T cells cells andlevels
and their increased IL-13inlevels decreased
draining cervicalinlymph
CD4+nodes
T cells. Additionally,
(CLNs). CD8+
Furthermore, IL-T-cell
depletion increases Th17
17A production cellocular-surface
by both pathogenicitycells andand
increases
CD4+ TIL-17 and CCL20
cells increased, production
whereas IFN-γ and subsequent
production
matrix metalloproteinase
decreased (MMP)-3
in ocular-surface cellsand
and MMP-9 levels,
IL-13 levels which in
decreased play a central
CD4+ T cells.role in DS-induced
Additionally, CD8+ corneal
T-
cell depletion
barrier disruption. increases Th17 cell pathogenicity and increases IL-17 and CCL20 production and
subsequent
Under matrix metalloproteinase
DS conditions, (MMP)-3 and TMMP-9
levels of CD8+CD103+ levels, which
cells increase and play
playaan central role in DS-
immunoregulatory
role atinduced corneal
the ocular barrier
surface anddisruption.
in CLNs; however, co-transfer of CD8+CD103+ Tregs does not suppress
Under DS conditions, levels of CD8+CD103+ T cells increase and play an immunoregulatory role
Th17 pathogenic response at the ocular surface, indicating that these Tregs suppress the production of
at the ocular surface and in CLNs; however, co-transfer of CD8+CD103+ Tregs does not suppress
pathogenic Th17 cells before their initiation by suppressing DC activation [31].
Th17 pathogenic response at the ocular surface, indicating that these Tregs suppress the production
Metabolic components of the microenvironment markedly contribute to the differentiation of
of pathogenic Th17 cells before their initiation by suppressing DC activation [31].
CD4+ T cells into components
Metabolic Th17 or Treg cells
of the (See Figure 2).markedly
microenvironment Under contribute
Th17-promoting conditions, ofCD4+
to the differentiation
T cells undergo glucose uptake and a shift to aerobic glycolysis; however,
CD4+ T cells into Th17 or Treg cells (See Figure 2). Under Th17-promoting conditions, CD4+ in the presence
T cells of
anti-inflammatory
undergo glucose conditions,
uptake andCD4+ a T cellstotake-up
shift aerobiclipids and oxidize
glycolysis; lipids
however, in for
theenergy production
presence of anti- [33].
inflammatory microenvironment
The inflammatory conditions, CD4+ T cells whichtake-up lipids
results fromand
DSoxidize lipidscan
conditions for transform
energy production
Tregs to[33].
“exTreg”
cells. The
Theinflammatory microenvironment
phenotypic plasticity which results from
of CD4+CD25+forkhead boxDS P3conditions
(Foxp3)+ can transform
T cells makes Tregs to
them unable
“exTreg” cells. The phenotypic plasticity of CD4+CD25+forkhead box P3
to express Foxp3 in an inflammatory microenvironment [34]. These exTregs express IL17 and IFN-γ (Foxp3)+ T cells makes them
unable to express Foxp3 in an inflammatory microenvironment [34]. These exTregs express IL17 and
and do not suppress the inflammatory response [35].
IFN-γ and do not suppress the inflammatory response [35].

FigureFigure 2. Metabolic
2. Metabolic requirementsofofTh17
requirements Th17andand Treg
Treg responses.
responses. Th17
Th17 cells areare
cells dependent on aerobic
dependent on aerobic
glycolytic metabolism. Inducers of lipid oxidative metabolism inhibit Th17 cell generation.
glycolytic metabolism. Inducers of lipid oxidative metabolism inhibit Th17 cell generation. Conversely,
Conversely, Treg generation is enhanced by treatments that promote lipid oxidative metabolism and
Treg generation is enhanced by treatments that promote lipid oxidative metabolism and suppressed
suppressed by inhibitors of lipid transport such as etomoxir. Cholesterol derivatives are required for
by inhibitors of lipid transport such as etomoxir. Cholesterol derivatives are required for Th17 cell
Th17 cell differentiation and blockade of cholesterol biosynthesis, for example, with ketoconazole,
differentiation
suppressesand blockade of
the generation cholesterol
of Th17 cells butbiosynthesis, forTregs.
has no effect on example,
Figurewith
takenketoconazole,
from Bringer. suppresses
K et al.
the generation of Th17
with permission [33]. cells but has no effect on Tregs. Figure taken from Binger, K.J. et al. with
permission [33].
J. Clin. Med. 2019, 8, 1439 6 of 21

Another principal part of the innate immune system is the promotion of inflammation in DED via
the neutrophil extracellular trap (NET), which is a complex comprising extracellular DNA (eDNA),
histones, cathelicidin, and neutrophil elastase. eDNA is released from dead epithelial cells, which
increases in DED because of increased epithelial-cell turnover, and as neutrophils are an essential
source of NET formation. Moreover, nuclease and DNase I activity is decreased in the tear films of
DED patients, which also decreases the eDNA degradation. These data suggest that NET formation
and accumulation in tear films are a primary source of ocular-surface inflammation in DED [36].
Currently, LFA-1/ICAM-1 interaction is being developed as a new therapeutic target in DED [37].
The LFA-1/ICAM-1 interaction plays a vital role in the cell-mediated immune response and inflammation
associated in the immunoinflammatory pathway of DED. Blocking the binding of LFA-1 and ICAM-1
with Lifitegrast could be a novel approach to targeting ocular surface cell-mediated immune response
and inflammation.

2.3. DED-Associated Changes in Normal Microbiota


An important emerging frontier in studying mucosal inflammation is the microbiota analysis.
Human body harbors a significantly diverse microbiome of at least 1000 species [38]. 10–100 trillion
microbial cells are distributed in skin, and mucosa of ocular, nasal, oral, and reproductive organs and
co-exist in a delicate balance with the host immune system [39,40]. Direct crosstalk between resident
microbes and host immune cells in mucosa emerges as a key determinant of inflammatory responses
in disease conditions [41]. Th-17 and T-reg cells are in particular affected by the human microbiota
(see Figures 1 and 3). Furthermore, the microbiota is a major contributor to the muscosal metabolism.
Resident bacteria generate a wide range of metabolites and participate in drug metabolism at the
mucosa, thus affecting immunometabolic processes and pharmacotherapy [42–45].
There are several idiopathic diseases involving the ocular surface, including but not limited to
DED, follicular conjunctivitis, pterygium, and Thygeson’s disease. Inflammatory dysregulation is a
basic element of all such diseases, and it is logical to assume that dysregulation of the normal ocular
microbiome contributes to many or all of these conditions [46]. Changes in the mucosal microbiome alter
the mucosal immunity and host response to environmental insult, thereby initiating an autoimmune
response, such as inflammatory bowel disease [47,48]. Paiva et al. [49] reported a decrease in
operational taxonomic units in the stool of mice receiving antibiotics (AB) and exposed to DS after
10 days, with decreases in Bacteroidetes and Firmicutes phyla and increases in the Proteobacteria after
DS. Additionally, they reported significant decreases in Blautia, Alistipes, Lactobacillus, Allobaculum,
Bacteroides, Desulfovibrio, Intestinimonas, and Clostridium as compared with significant increases
in Enterobacter, Parasutterella, Escherichia/Shigella, Pseudomonas, and Staphylococcus. Moreover,
mice receiving AB + DS displayed increased goblet cell (GC) loss, infiltrating CD4+ T cells in the
conjunctival epithelium, and corneal barrier disruption relative to mice subjected to DS alone. Gene
expression analysis showed that AB treatment in non-stressed (NS) B6 mice increased IL-17 and
decreased interferon (IFN)-γ mRNA levels in the conjunctiva tissue relative to those in NS mice without
AB treatment; however, AB + DS increased IFN-γ mRNA and significantly decreased IL-13 and the
IL-13:IFN-γ ratio [49]. These findings suggest that AB therapy might alter immune activity and ocular
response to DS.
J. Clin. Med. 2019, 8, 1439 7 of 21
J. Clin. Med. 2019, 7, x FOR PEER REVIEW 7 of 20

Figure 3. Microbiome
Figure 3. Microbiomeand and Th17
Th17 autoimmunity.
autoimmunity. Research
Research in intestinal
in intestinal mucosalmucosal microbiome
microbiome has
has revealed
revealed a link with Th17 response and epithelial integrity. These studies may provide useful
a link with Th17 response and epithelial integrity. These studies may provide useful hints to researchers hints to
researchers working on other mucosal linings. Furthermore, direct links between
working on other mucosal linings. Furthermore, direct links between the intestinal microbiota and the intestinal
microbiota and have
ocular diseases ocular diseases
been have including
suggested, been suggested, including
a link with uveitis a[50],
linkand
with uveitis
dry [50], and
eye disease [49].dry eye
Figure
disease [49].Kenya
taken from FigureHonda
taken from
et al. Kenya Honda
[51] with et al. [51] with permission.
permission.

The ocular
ocular microbiota
microbiotasignificantly
significantlyaffects
affects
thethe metabolic
metabolic profile
profile of the
of the ocular
ocular surface,
surface, whichwhich
in turnin
turn affects
affects the ocular
the ocular surfacesurface
immunity.immunity. Short
Short fatty fatty
acids acidssuch
(FAs), (FAs), such as from
as butyrate butyrate from butyrate-
butyrate-producing
producing bacteria
bacteria (e.g., (e.g., Faecalibacteriums)
Faecalibacteriums) play an important
play an important role in differentiating
role in differentiating regulatoryregulatory
T-cell (Treg) T-
cell (Treg) lymphocytes
lymphocytes [47], andpopulations
[47], and increased increased populations
of Gram-negative of Gram-negative
bacteria might bacteria
accountmight account
for a more for
severe
ainflammatory
more severe response
inflammatory in DED response
patients.inDisruption
DED patients. Disruption
of the of thebarrier
ocular-surface ocular-surface
by diseases,barrier
suchby as
diseases, such as
DED, activate theDED, activate
Toll-like the Toll-like
receptor receptor (TLR)4
(TLR)4 pathway pathway [52]. Lipopolysaccharide
[52]. Lipopolysaccharide (LPS) is an endotoxin(LPS)
is an endotoxin
excreted excreted by bacteria
by Gram-negative Gram-negative bacteria
and increases theand increasesofthe
expression expression of
inflammatory inflammatory
cytokines in the
cytokines in the cornea (IL-1β and C-X-C motif chemokine ligand (CXCL)10)
cornea (IL-1β and C-X-C motif chemokine ligand (CXCL)10) and conjunctiva (IL-1β, CXCL10, IL-6, and conjunctiva (IL-1β,
CXCL10, IL-6, factor
tumor necrosis tumor(TNF)α,
necrosisIL-12α,
factor and
(TNF)α,
IFN-γ) IL-12α, and IFN-γ)
by activating by activating
the TLR4 the TLR4
pathway. These pathway.
findings show
These findings
that altered show that
mucosal altereddiversity
microbial mucosaland microbial
mucosal diversity andcan
dysbiosis mucosal
impactdysbiosis can impact Treg
Treg differentiation [53],
differentiation
and production[53], and production
of microbial of microbial
flora, such as LPS, can flora, such ascytokine
increase LPS, cansecretion
increasefrom
cytokine
immunesecretion
cells.
from immune
Therefore, cells.suggest
the data Therefore, the datain suggest
that changes that changes
normal microbiota in in
result normal microbiota
an abnormal immuneresult in an
response
abnormal
(particularlyimmune response (particularly
via immunometabolic via immunometabolic
mechanisms), which is part of mechanisms),
the underlyingwhich is part of the
pathophysiology of
underlying
DED (Figures pathophysiology
1 and 3). of DED (Figures 1 and 3).

Emerging Measurement
3. Emerging Measurement Techniques
Techniques and Disease Models

3.1. Clinical
3.1. Clinical Approaches
Approaches
Despitethe
Despite thehigh
highprevalence
prevalence ofof DED,
DED, there
there is gold
is no no gold standard
standard diagnostic
diagnostic approach
approach to diagnose
to diagnose DED.
DED. Routine clinical exams poorly correlate with patient symptoms and are subject
Routine clinical exams poorly correlate with patient symptoms and are subject to observer bias [54–56]. to observer
bias [54–56].
Several Severalexist
assessments assessments exist
to evaluate toquality
the evaluate and thequantity
quality of
and quantity of ocular-surface
ocular-surface facets
facets and tear-unit
and tear-unit
functions; functions;
however, however,
the set the set ofcapable
of assessments assessments capable DED
of diagnosing of diagnosing DED with
with acceptable acceptable
specificity and
specificity and sensitivity remains unknown [57]. In this section, we focus on the
sensitivity remains unknown [57]. In this section, we focus on the assessment of tear volume and tear assessment of tear
volume and tear osmolarity, which, in DED, cause oxidative stress at the ocular
osmolarity, which, in DED, cause oxidative stress at the ocular surface as discussed earlier. surface as discussed
earlier. Furthermore,
Furthermore, other recently
other recently developed
developed techniques techniques
in DEDin DED assessment
assessment will alsowill
be also be discussed.
discussed.
TM is conventionally assessed by the use of fluorescein staining, with Keratograph 44 capable
TM is conventionally assessed by the use of fluorescein staining, with Keratograph capable of
of
measuring TBUT non-invasively. Based on the interclass values and 95% confidence
measuring TBUT non-invasively. Based on the interclass values and 95% confidence intervals, the intervals, the
between-visit and
between-visit and after-visit
after-visit agreement
agreement ofof non-invasive
non-invasive keratography
keratographyTBUT
TBUT andand fluorescein,
fluorescein, TBUT
TBUT does
does
not differ significantly [58]. TMH measured from images of a fourth-generation
not differ significantly [58]. TMH measured from images of a fourth-generation OCULUS keratographOCULUS keratograph
correlates significantly
correlates significantly andand positively
positively with
with TBUT
TBUT andand thethe Schirmer
Schirmer test
test [59].
[59]. Recently,
Recently, different
different optical
optical
coherence tomography (OCT) systems were studied to measure TMH, and Raj et al. [60] reported no
significant correlation between TM area measured by Fourier domain OCT (FD-OCT), TBUT, and the
J. Clin. Med. 2019, 8, 1439 8 of 21

coherence tomography (OCT) systems were studied to measure TMH, and Raj et al. [60] reported no
significant correlation between TM area measured by Fourier domain OCT (FD-OCT), TBUT, and the
Schirmer test. Additionally, Fukuda et al. [61] reported a significant correlation between upper TM
volume, lower TM volume, and lower TMH with the Schirmer test but not with TBUT. Another study
revealed a significant correlation between TMH measured with keratography and FD-OCT, although
keratography tends to report lower results in elevated TMH [62]. Assessment of hyperosmolarity is
the aim of some other measurement techniques [1,63]. Traditionally, tear-fluid osmolarity is measured
by freezing-point depression and vapor pressure; however, these techniques are not visible and are
limited by reflex tearing during sampling [64]. Rocha et al. [65] compared the accuracy and precision of
the Wescor 5520 Vapor Pressure Osmometer, the TearLab Osmolarity System, and i-Pen for evaluating
tear osmolarity, revealing that the two former devices correlated significantly with each other and
were accurate and precise, whereas results from the third device did not significantly correlate with
the other devices and were less accurate. Another study compared the precision and accuracy of the
TearLab Osmometer using the freezing-point depression method, concluding that the results were
accurate and precise at assessing osmolarity, even for hyperosmotic solutions [66]. Badugua et al. [67]
introduced a novel technique to determine the individual ion concentrations in tears using silicon
hydrogel, claiming that this approach can measure six dominant ionic species in the tear.
Recently, maximum blinking interval (MBI), the number of seconds eyes can stay open without
blinking, was measured as an indicator of tear instability [68]. The authors reported significantly
shortened MBI in the DED group as compared with the non-DED group, as well as a positive correlation
between MBI and TBUT and a negative correlation between MBI and corneal fluorescein staining.
They observed a sensitivity of 82.5% and specificity of 51.0% for diagnosing DED with MBI; however,
further assessments are needed to confirm these results. The inter-blinking interval (IBI) is a similar
evaluation that assesses the routine blinking rate of patients and is thought to be less related to corneal
and conjunctival factors than MBI [68,69]. Results from IBI studies are preliminary; therefore, no
conclusions have been made.
As mentioned in Section 2.1, DED-associated oxidative stress can result in tear lipid instability;
thus, characterization of the Meibomian gland can be used for DED diagnosis. Keratography and
OCT systems utilize infrared radiation to assess Meibomian gland loss. Using OCT, Palamar et al. [70]
reported significant Meibomian gland loss in the lower eyelids of individuals with ocular rosacea
rather than in healthy controls. Finis et al. [71] carried out Keratograph 5M meibography and
reported that the degree of Meibomian gland atrophy in the lower and upper eyelids (Meiboscore)
was significantly and inversely correlated with TBUT and positively correlated with age. Confocal
microscopic imaging of the orifice of the Meibomian gland helps assess the lipid-layer thickness, using
Tearscope and a Korb gland evaluator, thus serving as an alternative to evaluating Meibomian gland
function [72,73]. MMP-9 is another quantifiable target for diagnosing DED [74,75]. InflammaDry is a
point-of-care MMP-9 immunoassay device to qualitatively assess MMP-9 levels in tears [76,77]. One
study reported a sensitivity of 85% and specificity of 94% for InflammaDry in diagnosing DED [78].
Finally, conjunctival-impression cytology (CIC) of conjunctival epithelial cells facilitates transcriptome
analysis using Eyeprim, a new CIC device designed to decrease patient discomfort and anesthetic use;
however, the efficacy of this device remains unknown [68,69,79]. DryEyeRhythm is a smartphone
application that gathers large-scale individual real-world data and reveals risk factors including
female sex, collagen disease, hay fever, depression, current contact lens use, extended screen time,
and smoking, all of which contribute to the severe DED-type symptoms [80]. Internet of Medical Things
(IoMT) devices such as smartphones could be implemented for telemedicine and remote monitoring
approaches [81].
J. Clin. Med. 2019, 8, 1439 9 of 21

3.2. Molecular Profiling and Omics Approaches


Omics approaches (genomics, transcriptomics, and proteomics) have improved the understanding
of the molecular pathogenesis of ocular diseases by providing a non-invasive, easily accessible,
and individualized approach to identify the disease markers for diagnosis and treatment.
Lipidomics analyses have provided valuable information regarding DED development. Altered
lipid profiles of the ocular surface are associated with clinical signs and symptoms of DED. Lam SM
et al. [82] observed that normalized levels of cholesteryl sulfates (CSs), glucosylceramides (GluCers),
NeuAcα2-3Galβ1-4Glcβ-Cers (GM3s), lyso-phosphatidylcholines (LPCs), and low-molecular-mass
wax esters (WEs) were positively correlated with tear volume, and that absolute concentrations
of these molecules decrease as tear secretion decreases, while the total concentration of tear lipids
and molar fractions of phosphatidic acids (PAs) and phosphatidylglycerols (PGs) were negatively
correlated with tear volume. WEs containing saturated FAs, PAs, and phosphatidylglycerols were
significantly reduced in contrast to their increasing levels according to the Schirmer 1 test. This
may have occurred owing to the emergence of the aforementioned lipids from the lacrimal gland.
Lam et al. [83] did not observe significant differences in meibum lipids obtained from DED eyes
and healthy eyes; however, the amount of unsaturated triacylglycerols, some phosphatidylcholines,
glucosyceramides, and sphingolipid species were elevated in DED patients. Another study showed
that 12 weeks of eyelid-warming resulted in a dramatic change in tear-lipid composition rather than the
quantity of tear lipids. Lysophospholipid classes (i.e., lyso-plasmalogen phosphatidylethanolamines,
LPCs, and lysophosphatidylinositols) were reduced after treatment, whereas their respective diacyl
counterparts increased. Moreover, polyunsaturated FAs (PUFAs) containing diacylglycerol were
reduced after treatment. Furthermore, reductions in such lipids and increases of O-acyl-ω-hydroxy
FAs (amphiphilic lipids) correlated with decreases in evaporation rate of the cornea and sclera [84].
Another study showed that 4-HNE and MDA, two lipid peroxidation markers, negatively correlated
with TBUT, the Schirmer test, tear-clearance rate, and GC density and positively correlated with
kerato-epitheliopathy and symptom persistence [85].
Proteomic analysis of tear fluid is a personalized approach increasingly used to diagnose and
treat DED [86,87]. Although Schirmer’s strip is the most common instrument for tear collection
and protein extraction [88], it can result in sample loss. Single-unit filter-aided methods have been
introduced to decrease sample loss and increase the number of proteins identified from tears [89].
Global and targeted metabolomics analyses performed on human conjunctival epithelial cells incubated
in serum-free media at 280 mOsm (control), 380 mOsm, and 480 mOsm for 24 h showed that carnitine
is the preferred anti-inflammatory or anti-apoptotic agent [90] while glycerophosphocholine, thought
to be an osmoprotectant, is the preferred endogenous osmolyte. The results showed that increases
in intermediate filament-like keratin and vimentin proteins suggested that cytoskeleton remodeling
is activated under hyperosmotic stress. Additionally, they reported upregulated [heat shock protein
70-kDa (HSP70)-5, dual-specificity mitogen-activated protein kinase 3, prostaglandin G/H synthase 2,
uridine diphosphate (UDP)-N-acetylglucosamine pyrophosphorylase 1, and UDP-N-acetylglucosamine,
intercellular adhesion molecule 1, IL-10, IL-17, prostaglandin 2 and E2, and prostacyclins] and
downregulated (plastin-2, 26S proteasome non-ATPase regulatory subunit 1, and protein glutamine
gamma-glutamyl-transferase 2) proteins [90]. Another study compared the proteomic profiles of reflex
tears and basal tears, observing that highly acidic proline-rich protein (PRR)4 was more abundant in
reflex tears, indicating a possible protective function of this protein. These findings further the current
knowledge of the metabolic markers of DED and potentially provide therapeutic targets. Another
report indicated that proline-rich protein 4 and zymogen granule protein 16 homolog B protein were
upregulated in reflex tears and might play a secretory role. Additionally, increased serum leakage
during reflex tearing causes increased serum albumin in tears, and upregulated levels of mesothelin in
tear reflex might heighten the function of MUC16, which encodes mucin. The amount of polymeric
immunoglobulin receptor and Ig alpha-1 chain C region, which are secreted mainly by the transcytotic
pathway, were decreased in reflex tears, and mammaglobin-B, clusterin, and cystatin S and SN were
J. Clin. Med. 2019, 8, 1439 10 of 21

decreased in reflex tears [91]. These proteins in tears may be the key players in the protection and
maintenance of the dynamic balance of the ocular surface among individuals with DED. Finally,
MMP-9 is another quantifiable target to diagnose DED [74,75]. InflammaDry is a point-of-care MMP-9
immunoassay device to qualitatively assess MMP-9 levels in tears [76,77]. One study reported a
sensitivity of 85% and specificity of 94% for InflammaDry in diagnosing DED [78].
Proteomics analyses have been applied to study DED associated with systemic diseases including
thyroid eye disease, SS, and graft-versus-host disease. Thyroid eye disease (or thyroid-associated
ophthalmopathy) is the most prevalent extrathyroidal manifestation of Grave’s disease. DED results
from thyroid-associated ophthalmopathy (TAO) owing to lacrimal gland involvement, eyelid retraction,
impaired Bell’s phenomenon, reduced blinking, and proptosis [92]. Matheis et al. [93] analyzed the
tear-fluid proteome of TAO patients via mass spectrometry. This study shows that patients with
TAO displayed an increase in inflammatory proteins (i.e., POTE ankyrin-domain family member 1)
and a reduction in protective and anti-inflammatory proteins (i.e., proline-rich lacrimal protein 1
(PROL1), protein-rich protein 4 (PRP4), and annexin A1) and a significantly different protein panel
(PRP4, PROL1, and UDP-glucose-dehydrogenase) in individuals with TAO and those with DED and/or
healthy controls. Therefore, the spectrum of inflammatory and protective proteins might be a useful
indicator for DED activity in patients with TAO.
SS is an autoimmune disorder mostly targeting exocrine glands, especially salivary and lacrimal
glands [94]. Li et al. [95] examined and compared the tear proteome of patients with SS, those with
DED, and healthy participants. The results showed that DED in SS patients is associated with an
altered proteomic profile with dysregulated expression of proteins involved in inflammation, apoptosis,
immunity, and oxidative stress. Characterization of these proteins would yield potential diagnostic
markers and therapeutic targets.
Graft-versus-host disease (GVHD) is a major cause of mortality and morbidity following allogeneic
hematological stem cell transplantation (HSCT). The immune response destroys the conjunctiva and
lacrimal gland tissues, resulting in decreases in tear production and DED onset [96]. Cocho et al. [97]
reported a significant decrease in tear level epidermal growth factor and the IFN-γ-induced protein-10
(IP-10):CXCL10 ratio, whereas IL-1 receptor-α, the IL-8:CXCL8 ratio and IL-10 levels were significantly
elevated as compared with healthy individuals. They suggested a predictive model for diagnosing
ocular GVHD based on the IP-10: CXCL10 ratio adjusted to sex and age, finding a sensitivity of 86.36%
and a specificity of 95.24% [97]. Jung et al. [98] reported a significant increase in tear IL-2, IL-10,
IL-17α, IFN-γ, IL-6, and TNFα levels in ocular GVHD, with adjustment for age, sex, and time after
HSCT showing that the diagnostic capabilities of these cytokines were significant and independent.
Moreover, IL-10, IL-6, and TNFα displayed the strongest correlation to GVHD severity relative to other
cytokines [98].
Remarkably, analyses of ocular GVHD has shown that DED was already present in a significant
percentage of patients suffering from hematological diseases before HSCT [99,100]. A comprehensive
ophthalmic assessment pre- and post-HSCT is recommended for the early treatment and potential
reduction of postoperative ocular damage [101,102].

3.3. Bioengineering Approaches


The increasing research expense for developing new drugs [103] and the pronounced difference
in drug effects between humans and other species [104] have resulted in emerging techniques
to model human physiology in preclinical studies [105]. Organ-on-a-chip technology introduced
three-dimensional (3D) techniques to mimic in vivo conditions by employing microfluidics and
bioengineering [104]. Human blinking eye-on-a-chip is an example of this technology for
ophthalmology [106]. In this model, 3D shell scaffolds are used to generate similar curvatures
to corneas, followed by impregnating with primary human keratocytes and sandwiching between a
microfluid channel and a circular chamber. The epithelial cells are then placed on the scaffold surface
by a color-coded method, with green fluorescence in the center and red fluorescence on the periphery
J. Clin. Med. 2019, 8, 1439 11 of 21

of the scaffold surface. The 3D-printed eyelids, which mimic normal blinking, are electromechanically
actuated, thereby allowing recapitulation of tear-film spreading and ocular-surface hydration.
Corneal organoid, the minatory cornea produced by tissue engineering, mimics in vivo conditions
to allow the study of organ development, course, and treatment of diseases. Pluripotent stem cells are
an alternative source compared to embryonic stem cells for organoid generation [107]. Microcornea or
corneal organoids are produced in later stages of retinal organoid formation [108] and can be used for
drug screening, disease modeling (e.g., DED), and tissue replacement.
Given that immunometabolic alterations play a principal role in DED pathogenesis, it will
J. Clin. Med. 2019, 7, x FOR PEER REVIEW 11 of 20
be very helpful to include both immune factors and metabolic elements in the engineered models.
Jeongyun
Jeongyun Seo Seo et
et al.
al. recently
recentlydeveloped
developedananeye-on-a-chip
eye-on-a-chipmodel
model that
that can
can mimic
mimic thethe pathogenesis
pathogenesis of
of DED
DED [109].
[109]. This This model
model includes
includes a blinking
a blinking cornealsurface
corneal surfaceand
andcan
canbe
beused
used toto induce
induce aa DED
DED
phenotype
phenotype (see (see Figure
Figure 4).4). Jeongyun
Jeongyun Seo
Seo et
et al. assessed IL-8,
al. assessed IL-8, TNF-α,
TNF-α, IL-1β,
IL-1β, and
and MMP-9
MMP-9 expression
expression in
in
their model after inducing DED and monitored the response of these cytokines to DED
their model after inducing DED and monitored the response of these cytokines to DED treatment by treatment by
administering lubricin.
administering lubricin.

Figure 4. An
Figure 4. engineered model
An engineered modelof ofevaporative
evaporativedry dryeye
eyedisease.
disease.(a) (a)Evaporation
Evaporation causes
causes thethe break-up
break-up of
of the tear film and increases tear osmolarity that together leads to a loss
the tear film and increases tear osmolarity that together leads to a loss of homeostasis. (b) Absorptionof homeostasis. (b)
Absorption of tears
of tears into the into strips
Schirmer the Schirmer strips and
in the healthy in the
dryhealthy and dry
eye models. Teareye models. is
absorption Tear absorption
visualized by theis
visualized
smearing ofbythe theblue
smearing of thethe
ink within blue ink within
strips. (c) Tearthe strips. (c)inTear
osmolarity the osmolarity
DED (closed in triangle)
the DEDand (closed
the
triangle) and the
normal (closed normal
circle) (closed
models. circle)
Human models.
clinical dataHuman clinicalare
of osmolarity data of osmolarity
from are from
normal subjects (opennormal
circle)
subjects
and DED(open circle)
subjects (openand DED subjects
triangle). (open triangle).
(d) Keratographs showing(d) Keratographs
concentric rings showing
projected concentric
on the humanrings
projected on the human ocular surface (top) and the engineered ocular surface
ocular surface (top) and the engineered ocular surface (bottom). (e) Representative images of projected (bottom). (e)
Representative
ring patterns onimages of projected
the engineered ring surface
ocular patternsofonthethehealthy
engineered
(top ocular surface
row) and of the(bottom
the DED healthy row)
(top
row)
groupsand the DED
captured t = 0 s (left
at(bottom row) groups and
column) t = 10at
captured t = 0 s column).
s (right (left column) and t =mapping
(f) Spatial 10 s (rightof column).
tear film
(f) Spatialtime
break-up mapping of tear film
in the normal (top) break-up
and the DED time(bottom)
in the normal
models.(top) and the
Different DED
colors (bottom)
in the models.
representative
Different colors in the representative circular heat maps indicate different tear
circular heat maps indicate different tear break-up times. (g) Fluorescein staining of the eye model and break-up times. (g)
Fluorescein
human subjects.staining of the eye model
(h) Concentrations and humanmediators
of inflammatory subjects.(IL-8,
(h) Concentrations
TNF-α, IL-1β, and of MMP-9)
inflammatory
in the
mediators (IL-8,and
normal (circle) TNF-α,
the DEDIL-1β, and MMP-9)
(triangle) groupsinplotted
the normal
against (circle) and theofDED
the duration (triangle)
culture. Figuregroups
taken
plotted against Seo
from Jeongyun the duration
et al. withofpermission
culture. Figure[109].taken from Jeongyun Seo et al. with permission [109].

4. Emerging
4. Emerging DED-Treatment
DED-Treatment Strategies
Strategies
DED treatment
DED treatment depends
depends on
on its
its severity
severity and
and the presence of
the presence of any
any underlying
underlying conditions. Systemic
conditions. Systemic
diseases, if
diseases, if any,
any, must
must be
be controlled. Improvement of
controlled. Improvement of tear
tear quality
quality and
and quantity
quantity with
with artificial
artificial tears,
tears,
anti-inflammatory medication, diet and lifestyle modification, and treatment of associated
anti-inflammatory medication, diet and lifestyle modification, and treatment of associated eyelid eyelid
diseases are
diseases are the
the primary
primary therapeutic
therapeutic strategies.
strategies.
Tiny disk-like membranes called nanowafers containing drugs can be applied on the eye for
sustained drug release instead of repeated administration of drops. Sustained release of
dexamethasone by loaded nanowafers showed an equivalent effect to (either oral or topical)
betamethasone administered twice daily and restored ocular-surface smoothness and corneal
epithelial-barrier function while reducing levels of inflammatory cytokines [110]. Another study
J. Clin. Med. 2019, 8, 1439 12 of 21

Tiny disk-like membranes called nanowafers containing drugs can be applied on the eye for
sustained drug release instead of repeated administration of drops. Sustained release of dexamethasone
by loaded nanowafers showed an equivalent effect to (either oral or topical) betamethasone
administered twice daily and restored ocular-surface smoothness and corneal epithelial-barrier
function while reducing levels of inflammatory cytokines [110]. Another study revealed that
nanowafer-loaded dexamethasone decreased inflammatory cytokine expression, especially in
later stages of inflammation [111]. Additionally, a vehicle-controlled clinical trial showed that
treatment with 0.1% fluorometholone preserved corneal integrity under environmental stress [112].
Immunomodulatory drugs modify the function of the immune system to control autoimmune diseases.
Rapamycin (sirolimus), an immunomodulatory drug, reduces inflammation in DED. Treatment of
non-obese diabetic mice (NOD) with rapamycin twice daily for 12 weeks decreased lymphocyte
infiltration into lacrimal gland lysates. Moreover, tear secretion was increased following topical
administration of rapamycin, although, GC density did not change, while decreasing cathepsin S levels
in the lacrimal glands and tears of the mice [113].
Essential FAs modulate the function of the immune system by conversion into pro-inflammatory
and anti-inflammatory cytokines; a previous study reported that ω3 FAs convert into anti-inflammatory
cytokines, and ω6 FAs convert into pro-inflammatory cytokines [114]. They showed that consumption of
ω3 supplements for 90 days reduced tear osmolality, OSDI, ocular redness, and ocular-surface staining,
thereby increasing tear-film stability and that these effects were heightened when using the phospholipid
form of ω3 (krill oil) as compared with the triacylglyceride form (fish oil) [115]. Ovariectomy decreases
lacrimal production according to Schirmer test results; however, supplementation with n-3 PUFAs,
docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and α-lipoic acid restored partial lacrimal
production while only alkaline phosphatase (ALP) resulted in complete restoration. SOD and aconitase
levels were not altered by ovariectomy or supplementation with FAs, although supplementation with
ALP increased glutathione peroxidase (GPx) activity. Furthermore, ovariectomy decreased nitrite and
nitric oxide levels on the ocular surface, which was not recovered by FAs in the conjunctiva but was
restored by ALP in the cornea. Moreover, DHA, EPA, and ALP restored nitrite and nitric oxide levels
in lacrimal glands, and EPA and DHA also increased MDA levels in lacrimal glands. DHA, EPA, and
ALP function by avoiding microvilli loss, preventing cellular-junction irregularity, and preventing
ovariectomy-induced cellular desquamation [116]. Another study showed that oral omega-3 essential
FA supplementation for symptomatic DED in computer users improved TBUT and results from the
Schirmer test while also changing the cytology of GCs and epithelial cells [117]. Administration of
topical 0.2% omega-3 FA mixed with hyaluronic acid reduces the severity of corneal irregularity, which
was significantly improved relative to results using hyaluronic acid alone or mixed with 0.02% omega-3
FA [118]. Additionally, adding mineral oil to eye drops significantly increases lipid-layer thickness at
the ocular surface of patients with Meibomian gland dysfunction (MGD) and preserves the tear film
from evaporation [119].
Eyelid-warming liquefies Meibomian gland secretions and facilitates their release onto the tear
film. Eye-mask and eye-bag compresses are devices used to warm the eyelid. Outer and inner
eyelid temperatures were significantly increased using an eye-bag compress, and although there was
no significant difference in lipid-layer grade and non-invasive TBUT with the eye-mask compress,
there was improvement between treatments. Subjectively, the majority of subjects preferred eye-bag
compresses over eye-mask compresses [120].
In a survey comparing the effects of TNFα–stimulated gene/protein-6 (TSG-6), topical prednisolone,
and topical cyclosporine (CsA) on reducing DED-associated changes in NOD mice, all three increased
tear production and conjunctival GC count. Additionally, 1% prednisolone drops did not decrease
corneal epithelial staining, whereas TSG-6 and CsA (0.05%) did. Moreover, topical administration of
TSG-6, Restasis (CsA), and Pred Forte (prednisolone acetate, 1%) significantly decreased transcript
levels of Tnfa and Ifng at the ocular surface and intraorbital glands, and Pred Forte also increased
epithelial-cell apoptosis and decreased corneal thickness [121]. In rat models, diclofenac, a non-steroidal
J. Clin. Med. 2019, 8, 1439 13 of 21

anti-inflammatory drug, prevented DED changes without decreasing tear-fluid volume and reduced
cell damage and apoptosis induced by hyperosmolarity [122].
CsA is an anti-inflammatory medication used to treat DED. Because of several adverse effects
associated with systemic administration of CsA, topical drops are the route of choice for treatment
of the ocular surface; however, formulating a safe delivery system for this hydrophobic drug is
challenging. Available topical CsA brands are often associated with adverse effects, including ocular
burning, foreign-body sensation, and epiphora [123]. However, 6- and 12-week treatment with
topical CsA 0.05% ophthalmic emulsion twice daily increased the conjunctival density of GCs and
transforming growth factor β2–positive GCs, suggesting that this treatment increases the production
of the immunoregulatory factor TGF-β2 by increasing conjunctival GCs [124]. Another study showed
that vitamin B12 supplementation restored tear volume and TBUT in a murine model of DED, with
1-month treatment with B12 and 0.15% hyaluronic acid decreasing oxidative stress and OSDI [125].
Oxidative stress is involved in DED pathogenesis. A previous study assessed the anti-oxidative
effect of SkQ1, a synthetic antioxidant, on preventing general-anesthesia-induced DED, showing
that premedication with instilled SkQ1 (7.5 µM) displayed preventive effects against pathological
corneal changes after recovery and completely neutralized clinical signs of DED as early as the
first day of the post-anesthetic period. Treatment after anesthesia was 1 week, with these findings
suggesting that SkQ1 protected the corneal epithelium rather than participated in corneal wound
healing. Moreover, SkQ1 administration increased GPx and glutathione reductase activities, accelerated
normalization of SOD and other oxidant levels in tear fluid, increased IL-10 secretion, accelerated the
recovery of IL-4 levels, and suppressed TNFα and IL-6 secretion. Furthermore, MDA concentration
decreases significantly in animals premedicated with SkQ1 before anesthesia relative to control animals,
supporting its anti-oxidative effect [126].
Diquafosol tetrasodium (DQS) is a purinergic P2Y2 agonist that reportedly improves DED via
several mechanisms of action, including improvement of fluid transport, secretion of mucin from
the conjunctival epithelium, and stimulation of lipid production [127]. Ikeda et al. [128] investigated
the effect of 3% DQS eye drops on functional changes of MGD in Sod1−/− mice, observing that DQS
instillation increased aqueous tear production. Additionally, Sod1−/− mice displayed significantly lower
TBUT, and a 2-week treatment significantly decreased corneal fluorescein staining and lissamine green
staining. Moreover, they found increased cytokeratin-4 and IL-13 expression in Meibomian gland acinar
epithelium and decreased transglutaminase-1 mRNA and protein levels in DQS-treated mice [128].
Thrombospondin-1 (TSP-1) activates TGF-β, which plays an immunomodulatory role at the ocular
surface [129]. Tan et al. [130] found that TSP-1 levels are upregulated in the corneas of mice with DED,
and interestingly, expression of MHC II by bone-marrow-derived DCs (BMDCs) decreased significantly
following co-culture with epithelial cells from DED mice. Further addition of recombinant (r)TSP-1
potentiated the suppressive effect of epithelial cells on BMDC maturation, whereas TSP-1 blockade
ameliorated this effect. Furthermore, rTSP-1 decreased the Th17 population in draining lymph nodes
of mice with DED and decreased cytokine expression in the conjunctiva and cornea relative to levels in
controls. Studies suggest that the interaction between pro-inflammatory and immune-regulatory Th17
cells play a principal role in DED pathogenesis [20,32]. Sustained release of CCL22 from microspheres
injected locally in lacrimal glands prevented the loss of tear production and GCs, increased CD4+ T
cells in regional draining lymph nodes, increased CD4+ IFN-γ+ T cells, and decreased CD4+ Foxp3+
T cells in lacrimal glands and corneas in DED animal models [131].
In summary, most of the available treatment strategies are focused on increasing ocular surface
humidity and decreasing its osmolarity and inflammation. Future medications and supplementations
improve oxidative condition and metabolic regulation at the ocular surface. This strategy should be
considered in future studies and clinical trials. For example, TLR signaling pathway is one of the
presumed pathways connecting oxidative stress and inflammation and is the target of some proposed
supplementations in the recent studies which can be assessed in future DED treatment development
studies [132,133].
J. Clin. Med. 2019, 8, 1439 14 of 21

5. Future Directions
DED poses a significant clinical challenge. Previous reports reveal discrepancies between dry eye
signs and symptoms [134,135], indicating a need for new disease markers with higher predictive values.
Identification of such markers often requires the use of new measurement techniques [80]. In this
review, we highlighted recent advances in analytical chemistry, microbiology, and bioengineering and
their applications in DED diagnosis and treatment. In particular, we highlighted the newly identified
immunometabolic pathways and microbiota-related factors that are involved in DED pathogenesis.
The newly found biomarkers offer hope for improved diagnosis and disease prediction; however,
further studies are required to determine the most predictive biomarkers regarding disease severity.
Modeling approaches, including machine-learning techniques, and artificial intelligence, are being
increasingly utilized by ophthalmologists, and can be used to identify clinically meaningful patterns in
the data. Additionally, in vitro disease models, such as eye-on-a-chip, will provide efficient screening
platforms for future drug development.

Funding: This research received no external funding.


Acknowledgments: We thank Fatemeh Vafaei for her help with graphics and Tina Shiang for help with the
arrangements related to the preparation of this manuscript.
Conflicts of Interest: The authors declare no conflict of interest.

References
1. Craig, J.P.; Nichols, K.K.; Akpek, E.K.; Caffery, B.; Dua, H.S.; Joo, C.-K.; Liu, Z.; Nelson, J.D.; Nichols, J.J.;
Tsubota, K.; et al. TFOS DEWS II Definition and Classification Report. Ocul. Surf. 2017, 15, 276–283.
[CrossRef] [PubMed]
2. Le, Q.; Zhou, X.; Ge, L.; Wu, L.; Hong, J.; Xu, J. Impact of Dry Eye Syndrome on Vision-Related Quality of
Life in a Non-Clinic-Based General Population. BMC Ophthalmol. 2012, 12, 22. [CrossRef] [PubMed]
3. Inomata, T.; Shiang, T.; Iwagami, M.; Sakemi, F.; Fujimoto, K.; Okumura, Y.; Ohno, M.; Murakami, A. Changes
in Distribution of Dry Eye Disease by the New 2016 Diagnostic Criteria from the Asia Dry Eye Society.
Sci. Rep. 2018, 8, 1918. [CrossRef] [PubMed]
4. Stapleton, F.; Alves, M.; Bunya, V.Y.; Jalbert, I.; Lekhanont, K.; Malet, F.; Na, K.-S.; Schaumberg, D.; Uchino, M.;
Vehof, J.; et al. TFOS DEWS II Epidemiology Report. Ocul. Surf. 2017, 15, 334–365. [CrossRef] [PubMed]
5. Paulsen, A.J.; Cruickshanks, K.J.; Fischer, M.E.; Huang, G.-H.; Klein, B.E.K.; Klein, R.; Dalton, D.S. Dry Eye
in the Beaver Dam Offspring Study: Prevalence, Risk Factors, and Health-Related Quality of Life. Am. J.
Ophthalmol. 2014, 157, 799–806. [CrossRef] [PubMed]
6. Pflugfelder, S.C.; Stern, M.E. Mucosal environmental sensors in the pathogenesis of dry eye. Expert Rev. Clin.
Immunol. 2014, 10, 1137–1140. [CrossRef] [PubMed]
7. Nelson, J.D.; Craig, J.P.; Akpek, E.K.; Azar, D.T.; Belmonte, C.; Bron, A.J.; Clayton, J.A.; Dogru, M.; Dua, H.S.;
Foulks, G.N. TFOS DEWS II Introduction. Ocul. Surf. 2017, 15, 269–275. [CrossRef] [PubMed]
8. O’Neill, L.A.J.; Kishton, R.J.; Rathmell, J. A guide to immunometabolism for immunologists. Nat. Rev.
Immunol. 2016, 16, 553–565. [CrossRef] [PubMed]
9. Rhoads, J.P.; Major, A.S.; Rathmell, J.C. Fine tuning of immunometabolism for the treatment of rheumatic
diseases. Nat. Rev. Rheumatol. 2017, 13, 313–320. [CrossRef]
10. Morel, L. Immunometabolism in systemic lupus erythematosus. Nat. Rev. Rheumatol. 2017, 13, 280–290.
[CrossRef]
11. Huang, N.; Perl, A. Metabolism as a Target for Modulation in Autoimmune Diseases. Trends Immunol. 2018,
39, 562–576. [CrossRef] [PubMed]
12. Gaber, T.; Strehl, C.; Buttgereit, F. Metabolic regulation of inflammation. Nat. Rev. Rheumatol. 2017, 13,
267–279. [CrossRef] [PubMed]
13. Hotamisligil, G.S. Foundations of Immunometabolism and Implications for Metabolic Health and Disease.
Immunity 2017, 47, 406–420. [CrossRef] [PubMed]
14. Seen, S.; Tong, L. Dry eye disease and oxidative stress. Acta Ophthalmol. 2018, 96, e412–e420. [CrossRef]
[PubMed]
J. Clin. Med. 2019, 8, 1439 15 of 21

15. Deng, R.; Hua, X.; Li, J.; Chi, W.; Zhang, Z.; Lu, F.; Zhang, L.; Pflugfelder, S.C.; Li, D.-Q. Oxidative Stress
Markers Induced by Hyperosmolarity in Primary Human Corneal Epithelial Cells. PLoS ONE 2015, 10,
e0126561. [CrossRef] [PubMed]
16. Zheng, Q.; Ren, Y.; Reinach, P.S.; Xiao, B.; Lu, H.; Zhu, Y.; Qu, J.; Chen, W. Reactive oxygen species activated
NLRP3 inflammasomes initiate inflammation in hyperosmolarity stressed human corneal epithelial cells and
environment-induced dry eye patients. Exp. Eye Res. 2015, 134, 133–140. [CrossRef] [PubMed]
17. Chi, W.; Hua, X.; Chen, X.; Bian, F.; Yuan, X.; Zhang, L.; Wang, X.; Chen, D.; Deng, R.; Li, Z.; et al.
Mitochondrial DNA Oxidation Induces Imbalanced Activity of NLRP3/NLRP6 Inflammasomes by Activation
of Caspase-8 and BRCC36 in Dry Eye. J. Autoimmun. 2017, 80, 65–76. [CrossRef]
18. Liu, H.; Sheng, M.; Liu, Y.; Wang, P.; Chen, Y.; Chen, L.; Wang, W.; Li, B. Expression of SIRT1 and oxidative
stress in diabetic dry eye. Int. J. Clin. Exp. Pathol. 2015, 8, 7644–7653.
19. Chen, Y.; Chauhan, S.K.; Shao, C.; Omoto, M.; Inomata, T.; Dana, R. Interferon-γ-expressing Th17 cells
are required for development of severe ocular surface autoimmunity. J. Immunol. 2017, 199, 1163–1169.
[CrossRef]
20. Coursey, T.G.; Gandhi, N.B.; Volpe, E.A.; Pflugfelder, S.C.; de Paiva, C.S. Chemokine receptors CCR6 and
CXCR3 are necessary for CD4+ T cell mediated ocular surface disease in experimental dry eye disease.
PLoS ONE 2013, 8, e78508. [CrossRef]
21. De Paiva, C.; Villarreal, A.; Corrales, R.; Rahman, H.; Chang, V.; Farley, W.; Stern, M.; Niederkorn, J.; Li, D.Q.;
Pflugfelder, S. IFN–Promotes goblet cell loss in response to desiccating ocular stress. Investig. Ophthalmol.
Vis. Sci. 2006, 47, 5579.
22. Coursey, T.G.; Henriksson, J.T.; Barbosa, F.L.; De Paiva, C.S.; Pflugfelder, S.C. Interferon-γ–Induced Unfolded
Protein Response in Conjunctival Goblet Cells as a Cause of Mucin Deficiency in Sjögren Syndrome. Am. J.
Pathol. 2016, 186, 1547–1558. [CrossRef] [PubMed]
23. Dohlman, T.H.; Chauhan, S.K.; Kodati, S.; Hua, J.; Chen, Y.; Omoto, M.; Sadrai, Z.; Dana, R. The CCR6/CCL20
Axis Mediates Th17 Cell Migration to the Ocular Surface in Dry Eye Disease. Investig. Ophthalmol. Vis. Sci.
2013, 54, 4081–4091. [CrossRef] [PubMed]
24. Dohlman, T.H.; Ding, J.; Dana, R.; Chauhan, S.K. T Cell–Derived Granulocyte-Macrophage
Colony-Stimulating Factor Contributes to Dry Eye Disease Pathogenesis by Promoting CD11b+ Myeloid
Cell Maturation and Migration. Investig. Ophthalmol. Vis. Sci. 2017, 58, 1330–1336. [CrossRef] [PubMed]
25. Inomata, T.; Hua, J.; Nakao, T.; Shiang, T.; Chiang, H.; Amouzegar, A.; Dana, R. Corneal Tissue from Dry Eye
Donors Leads to Enhanced Graft Rejection. Cornea 2018, 37, 95–101. [CrossRef] [PubMed]
26. Pflugfelder, S.C.; De Paiva, C.S.; Moore, Q.L.; Volpe, E.A.; Li, D.-Q.; Gumus, K.; Zaheer, M.L.; Corrales, R.M.
Aqueous Tear Deficiency Increases Conjunctival Interferon-γ (IFN-γ) Expression and Goblet Cell Loss.
Investig. Ophthalmol. Vis. Sci. 2015, 56, 7545–7550. [CrossRef] [PubMed]
27. Henriksson, J.T.; Coursey, T.G.; Corry, D.B.; De Paiva, C.S.; Pflugfelder, S.C. IL-13 Stimulates Proliferation
and Expression of Mucin and Immunomodulatory Genes in Cultured Conjunctival Goblet Cells. Investig.
Ophthalmol. Vis. Sci. 2015, 56, 4186–4197. [CrossRef]
28. Garcia-Posadas, L.; Hodges, R.; Li, D.; Shatos, M.; Storr-Paulsen, T.; Diebold, Y.; Dartt, D. Interaction of
IFN-γ with cholinergic agonists to modulate rat and human goblet cell function. Mucosal Immunol. 2016, 9,
206. [CrossRef] [PubMed]
29. Liu, R.; Gao, C.; Chen, H.; Li, Y.; Jin, Y.; Qi, H. Analysis of Th17-associated cytokines and clinical correlations
in patients with dry eye disease. PLoS ONE 2017, 12, e0173301. [CrossRef] [PubMed]
30. Subbarayal, B.; Chauhan, S.K.; Di Zazzo, A.; Dana, R. IL-17 augments B cell activation in ocular surface
autoimmunity. J. Immunol. 2016, 197, 3464–3470. [CrossRef]
31. Coursey, T.G.; Bohat, R.; Barbosa, F.L.; Pflugfelder, S.C.; De Paiva, C.S. Desiccating stress-induced chemokine
expression in the epithelium is dependent on upregulation of NKG2D/RAE-1 and release of IFN-γ in
experimental dry eye. J. Immunol. 2014, 193, 5264–5272. [CrossRef] [PubMed]
32. Zhang, X.; Schaumburg, C.; Coursey, T.; Siemasko, K.; Volpe, E.; Gandhi, N.; Li, D.; Niederkorn, J.; Stern, M.;
Pflugfelder, S. CD8+ cells regulate the T helper-17 response in an experimental murine model of Sjögren
syndrome. Mucosal Immunol. 2014, 7, 417. [CrossRef] [PubMed]
33. Binger, K.J.; Côrte-Real, B.F.; Kleinewietfeld, M. Immunometabolic Regulation of Interleukin-17-Producing T
Helper Cells: Uncoupling New Targets for Autoimmunity. Front. Immunol. 2017, 8, 305. [CrossRef]
J. Clin. Med. 2019, 8, 1439 16 of 21

34. Inomata, T.; Hua, J.; Di Zazzo, A.; Dana, R. Impaired Function of Peripherally Induced Regulatory T Cells in
Hosts at High Risk of Graft Rejection. Sci. Rep. 2016, 6, 39924. [CrossRef] [PubMed]
35. Hua, J.; Inomata, T.; Chen, Y.; Foulsham, W.; Stevenson, W.; Shiang, T.; Bluestone, J.A.; Dana, R. Pathological
conversion of regulatory T cells is associated with loss of allotolerance. Sci. Rep. 2018, 8, 7059. [CrossRef]
[PubMed]
36. Sonawane, S.; Khanolkar, V.; Namavari, A.; Chaudhary, S.; Gandhi, S.; Tibrewal, S.; Jassim, S.H.; Shaheen, B.;
Hallak, J.; Horner, J.H.; et al. Ocular Surface Extracellular DNA and Nuclease Activity Imbalance: A New
Paradigm for Inflammation in Dry Eye Disease. Investig. Ophtalmol. Vis. Sci. 2012, 53, 8253–8263. [CrossRef]
[PubMed]
37. Pflugfelder, S.C.; Stern, M.; Zhang, S.; Shojaei, A. LFA-1/ICAM-1 Interaction as a Therapeutic Target in Dry
Eye Disease. J. Ocul. Pharmacol. Ther. 2017, 33, 5–12. [CrossRef] [PubMed]
38. Lloyd-Price, J.; Abu-Ali, G.; Huttenhower, C. The healthy human microbiome. Genome Med. 2016, 8, 1024.
[CrossRef]
39. Savage, D.C. Microbial Ecology of the Gastrointestinal Tract. Annu. Rev. Microbiol. 1977, 31, 107–133.
[CrossRef]
40. Donaldson, G.P.; Lee, S.M.; Mazmanian, S.K. Gut biogeography of the bacterial microbiota. Nat. Rev.
Microbiol. 2016, 14, 20–32. [CrossRef]
41. Pandiyan, P.; Bhaskaran, N.; Zou, M.; Schneider, E.; Jayaraman, S.; Huehn, J. Microbiome Dependent
Regulation of Tregs and Th17 Cells in Mucosa. Front. Immunol. 2019, 10, 426. [CrossRef] [PubMed]
42. Cani, P.D. Microbiota and metabolites in metabolic diseases. Nat. Rev. Endocrinol. 2019, 15, 69–70. [CrossRef]
[PubMed]
43. Zimmermann, M.; Zimmermann-Kogadeeva, M.; Wegmann, R.; Goodman, A.L. Mapping human microbiome
drug metabolism by gut bacteria and their genes. Nature 2019, 570, 462–467. [CrossRef] [PubMed]
44. Nichols, R.G.; Peters, J.M.; Patterson, A.D. Interplay between the Host, the Human Microbiome, and Drug
Metabolism. Hum. Genom. 2019, 13, 27. [CrossRef] [PubMed]
45. Guthrie, L.; Kelly, L. Bringing microbiome-drug interaction research into the clinic. EBioMedicine 2019, 44,
708–715. [CrossRef] [PubMed]
46. Zegans, M.E.; Van Gelder, R.N. Considerations in Understanding the Ocular Surface Microbiome. Am. J.
Ophthalmol. 2014, 158, 420–422. [CrossRef] [PubMed]
47. Furusawa, Y.; Obata, Y.; Fukuda, S.; Endo, T.A.; Nakato, G.; Takahashi, D.; Nakanishi, Y.; Uetake, C.; Kato, K.;
Kato, T.; et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells.
Nature 2013, 504, 446–450. [CrossRef]
48. Arpaia, N.; Campbell, C.; Fan, X.; Dikiy, S.; Van Der Veeken, J.; DeRoos, P.; Liu, H.; Cross, J.R.; Pfeffer, K.;
Coffer, P.J.; et al. Metabolites produced by commensal bacteria promote peripheral regulatory T cell
generation. Nature 2013, 504, 451–455. [CrossRef]
49. De Paiva, C.S.; Jones, D.B.; Stern, M.E.; Bian, F.; Moore, Q.L.; Corbiere, S.; Streckfus, C.F.; Hutchinson, D.S.;
Ajami, N.J.; Petrosino, J.F.; et al. Altered Mucosal Microbiome Diversity and Disease Severity in Sjögren
Syndrome. Sci. Rep. 2016, 6, 23561. [CrossRef]
50. Horai, R.; Zárate-Bladés, C.R.; Dillenburg-Pilla, P.; Chen, J.; Kielczewski, J.L.; Silver, P.B.; Jittayasothorn, Y.;
Chan, C.-C.; Yamane, H.; Honda, K.; et al. Microbiota-Dependent Activation of an Autoreactive T Cell
Receptor Provokes Autoimmunity in an Immunologically Privileged Site. Immunity 2015, 43, 343–353.
[CrossRef]
51. Honda, K.; Littman, D.R. The microbiota in adaptive immune homeostasis and disease. Nature 2016, 535,
75–84. [CrossRef] [PubMed]
52. Simmons, K.T.; Xiao, Y.; Pflugfelder, S.C.; De Paiva, C.S. Inflammatory Response to Lipopolysaccharide on
the Ocular Surface in a Murine Dry Eye Model. Investig. Ophthalmol. Vis. Sci. 2016, 57, 2443–2451. [CrossRef]
[PubMed]
53. Omenetti, S.; Pizarro, T.T. The Treg/Th17 Axis: A Dynamic Balance Regulated by the Gut Microbiome. Front.
Immunol. 2015, 6, 845. [CrossRef] [PubMed]
54. Vehof, J.; Smitt-Kamminga, N.S.; Nibourg, S.A.; Hammond, C.J. Predictors of Discordance between Symptoms
and Signs in Dry Eye Disease. Ophthalmology 2017, 124, 280–286. [CrossRef] [PubMed]
J. Clin. Med. 2019, 8, 1439 17 of 21

55. Baudouin, C.; Aragona, P.; Van Setten, G.; Rolando, M.; Irkec, M.; Del Castillo, J.B.; Geerling, G.; Labetoulle, M.;
Bonini, S.; ODISSEY European Consensus Group Members. Diagnosing the severity of dry eye: A clear and
practical algorithm. Br. J. Ophthalmol. 2014, 98, 1168–1176. [CrossRef] [PubMed]
56. Bartlett, J.D.; Keith, M.S.; Sudharshan, L.; Snedecor, S.J. Associations between signs and symptoms of dry
eye disease: A systematic review. Clin. Ophthalmol. 2015, 9, 1719–1730. [CrossRef] [PubMed]
57. Roy, N.S.; Wei, Y.; Kuklinski, E.; Asbell, P.A. The Growing Need for Validated Biomarkers and Endpoints for
Dry Eye Clinical Research. Investig. Ophthalmol. Vis. Sci. 2017, 58, BIO1–BIO19. [CrossRef]
58. Cox, S.M.; Nichols, K.K.; Nichols, J.J. Agreement between Automated and Traditional Measures of Tear Film
Breakup. Optom. Vis. Sci. 2015, 92, e257–e263. [CrossRef]
59. Wei, A.; Le, Q.; Hong, J.; Wang, W.; Wang, F.; Xu, J. Assessment of lower tear meniscus. Optom. Vis. Sci. 2016,
93, 1420–1425. [CrossRef]
60. Raj, A.; Dhasmana, R.; Nagpal, R.C. Anterior Segment Optical Coherence Tomography for Tear Meniscus
Evaluation and its Correlation with other Tear Variables in Healthy Individuals. J. Clin. Diagn. Res. 2016, 10,
NC01–NC04. [CrossRef]
61. Fukuda, R.; Usui, T.; Miyai, T.; Yamagami, S.; Amano, S. Tear Meniscus Evaluation by Anterior Segment
Swept-Source Optical Coherence Tomography. Am. J. Ophthalmol. 2013, 155, 620–624.e2. [CrossRef]
[PubMed]
62. Baek, J.; Doh, S.H.; Chung, S.K. Comparison of Tear Meniscus Height Measurements Obtained with the
Keratograph and Fourier Domain Optical Coherence Tomography in Dry Eye. Cornea 2015, 34, 1209–1213.
[CrossRef] [PubMed]
63. Najafi, L.; Malek, M.; Valojerdi, A.E.; Khamseh, M.E.; Aghaei, H. Dry eye disease in type 2 diabetes mellitus;
comparison of the tear osmolarity test with other common diagnostic tests: A diagnostic accuracy study
using STARD standard. J. Diabetes Metab. Disord. 2015, 14, 1264. [CrossRef] [PubMed]
64. Stahl, U.; Willcox, M.; Stapleton, F. Osmolality and tear film dynamics. Clin. Exp. Optom. 2012, 95, 3–11.
[CrossRef] [PubMed]
65. Rocha, G.; Gulliver, E.; Borovik, A.; Chan, C.C. Randomized, masked, in vitro comparison of three
commercially available tear film osmometers. Clin. Ophthalmol. 2017, 11, 243–248. [CrossRef] [PubMed]
66. Yoon, D.; Gadaria-Rathod, N.; Oh, C.; Asbell, P.A. Precision and Accuracy of TearLab Osmometer in
Measuring Osmolarity of Salt Solutions. Curr. Eye Res. 2014, 39, 1247–1250. [CrossRef] [PubMed]
67. Badugu, R.; Jeng, B.H.; Reece, E.A.; Lakowicz, J.R. Contact lens to measure individual ion concentrations in
tears and applications to dry eye disease. Anal. Biochem. 2018, 542, 84–94. [CrossRef] [PubMed]
68. Inomata, T.; Iwagami, M.; Hiratsuka, Y.; Fujimoto, K.; Okumura, Y.; Shiang, T.; Murakami, A. Maximum
blink interval is associated with tear film breakup time: A new simple, screening test for dry eye disease.
Sci. Rep. 2018, 8, 13443. [CrossRef] [PubMed]
69. Johnston, P.R.; Rodriguez, J.; Lane, K.J.; Ousler, G.; Abelson, M.B. The interblink interval in normal and dry
eye subjects. Clin. Ophthalmol. 2013, 7, 253–259. [CrossRef]
70. Palamar, M.; Degirmenci, C.; Ertam, I.; Yagci, A. Evaluation of Dry Eye and Meibomian Gland Dysfunction
with Meibography in Patients with Rosacea. Cornea 2015, 34, 497–499. [CrossRef]
71. Finis, D.; Ackermann, P.; Pischel, N.; König, C.; Hayajneh, J.; Borrelli, M.; Schrader, S.; Geerling, G. Evaluation
of meibomian gland dysfunction and local distribution of meibomian gland atrophy by non-contact infrared
meibography. Curr. Eye Res. 2015, 40, 982–989. [CrossRef] [PubMed]
72. Menzies, K.L.; Srinivasan, S.; Prokopich, C.L.; Jones, L. Infrared imaging of meibomian glands and evaluation
of the lipid layer in Sjögren’s syndrome patients and nondry eye controls. Investig. Ophthalmol. Vis. Sci.
2015, 56, 836–841. [CrossRef]
73. Villani, E.; Beretta, S.; De Capitani, M.; Galimberti, D.; Viola, F.; Ratiglia, R. In vivo confocal microscopy
of meibomian glands in Sjögren’s syndrome. Investig. Ophthalmol. Vis. Sci. 2011, 52, 933–939. [CrossRef]
[PubMed]
74. Messmer, E.M.; Von Lindenfels, V.; Garbe, A.; Kampik, A. Matrix Metalloproteinase 9 Testing in Dry Eye
Disease Using a Commercially Available Point-of-Care Immunoassay. Ophthalmology 2016, 123, 2300–2308.
[CrossRef]
75. Chan, T.C.; Ye, C.; Chan, K.P.; Chu, K.O.; Jhanji, V. Evaluation of point-of-care test for elevated tear matrix
metalloproteinase 9 in post-LASIK dry eyes. Br. J. Ophthalmol. 2016, 100, 1188–1191. [CrossRef] [PubMed]
J. Clin. Med. 2019, 8, 1439 18 of 21

76. Sambursky, R.; Davitt, W.F., III; Friedberg, M.; Tauber, S. Prospective, multicenter, clinical evaluation of
point-of-care matrix metalloproteinase-9 test for confirming dry eye disease. Cornea 2014, 33, 812–818.
[CrossRef] [PubMed]
77. Lanza, N.L.; McClellan, A.L.; Batawi, H.; Felix, E.R.; Sarantopoulos, K.D.; Levitt, R.C.; Galor, A. Dry Eye
Profiles in Patients with a Positive Elevated Surface Matrix Metalloproteinase 9 Point-of-Care Test Versus
Negative Patients. Ocul. Surf. 2016, 14, 216–223. [CrossRef]
78. Sambursky, R.; Davitt, W.F.; Latkany, R.; Tauber, S.; Starr, C.; Friedberg, M.; Dirks, M.S.; McDonald, M.
Sensitivity and Specificity of a Point-of-Care Matrix Metalloproteinase 9 Immunoassay for Diagnosing
Inflammation Related to Dry Eye. JAMA Ophthalmol. 2013, 131, 24. [CrossRef]
79. López-Miguel, A.; Gutiérrez-Gutiérrez, S.; García-Vázquez, C.; Enríquez-De-Salamanca, A. RNA Collection
from Human Conjunctival Epithelial Cells Obtained with a New Device for Impression Cytology. Cornea
2017, 36, 59–63. [CrossRef]
80. Inomata, T.; Nakamura, M.; Iwagami, M.; Shiang, T.; Yoshimura, Y.; Fujimoto, K.; Okumura, Y.; Eguchi, A.;
Iwata, N.; Miura, M.; et al. Risk Factors for Severe Dry Eye Disease: Crowdsourced Research Using
DryEyeRhythm. Ophthalmology 2019, 126, 766–768. [CrossRef]
81. Basatneh, R.; Najafi, B.; Armstrong, D.G. Health Sensors, Smart Home Devices, and the Internet of Medical
Things: An Opportunity for Dramatic Improvement in Care for the Lower Extremity Complications of
Diabetes. J. Diabetes Sci. Technol. 2018, 12, 577–586. [CrossRef] [PubMed]
82. Lam, S.M.; Tong, L.; Reux, B.; Duan, X.; Petznick, A.; Yong, S.S.; Khee, C.B.S.; Lear, M.J.; Wenk, M.R.; Shui, G.
Lipidomic analysis of human tear fluid reveals structure-specific lipid alterations in dry eye syndrome.
J. Lipid Res. 2014, 55, 299–306. [CrossRef] [PubMed]
83. Lam, S.M.; Tong, L.; Yong, S.S.; Li, B.; Chaurasia, S.S.; Shui, G.; Wenk, M.R. Meibum Lipid Composition in
Asians with Dry Eye Disease. PLoS ONE 2011, 6, e24339. [CrossRef] [PubMed]
84. Lam, S.M.; Tong, L.; Duan, X.; Acharya, U.R.; Tan, J.H.; Petznick, A.; Wenk, M.R.; Shui, G. Longitudinal
changes in tear fluid lipidome brought about by eyelid-warming treatment in a cohort of meibomian gland
dysfunction. J. Lipid Res. 2014, 55, 1959–1969. [CrossRef] [PubMed]
85. Choi, W.; Lian, C.; Ying, L.; Kim, G.E.; You, I.C.; Park, S.H.; Yoon, K.C. Expression of Lipid Peroxidation
Markers in the Tear Film and Ocular Surface of Patients with Non-Sjogren Syndrome: Potential Biomarkers
for Dry Eye Disease. Curr. Eye Res. 2016, 41, 1143–1149. [CrossRef] [PubMed]
86. Hagan, S.; Martin, E.; Enríquez-De-Salamanca, A. Tear fluid biomarkers in ocular and systemic disease:
Potential use for predictive, preventive and personalised medicine. EPMA J. 2016, 7, 15. [CrossRef] [PubMed]
87. Azkargorta, M.; Soria, J.; Acera, A.; Iloro, I.; Elortza, F. Human tear proteomics and peptidomics in
ophthalmology: Toward the translation of proteomic biomarkers into clinical practice. J. Proteom. 2017, 150,
359–367. [CrossRef] [PubMed]
88. Huang, Z.; Du, C.-X.; Pan, X.-D. The use of in-strip digestion for fast proteomic analysis on tear fluid from
dry eye patients. PLoS ONE 2018, 13, e0200702. [CrossRef]
89. Aass, C.; Norheim, I.; Eriksen, E.F.; Thorsby, P.M.; Pepaj, M. Single unit filter-aided method for fast proteomic
analysis of tear fluid. Anal. Biochem. 2015, 480, 1–5. [CrossRef]
90. Chen, L.; Li, J.; Guo, T.; Ghosh, S.; Koh, S.K.; Tian, D.; Zhang, L.; Jia, D.; Beuerman, R.W.; Aebersold, R.;
et al. Global Metabonomic and Proteomic Analysis of Human Conjunctival Epithelial Cells (IOBA-NHC) in
Response to Hyperosmotic Stress. J. Proteome Res. 2015, 14, 3982–3995. [CrossRef]
91. Perumal, N.; Funke, S.; Wolters, D.; Pfeiffer, N.; Grus, F.H. Characterization of human reflex tear proteome
reveals high expression of lacrimal proline-rich protein 4 (PRR4). Proteomics 2015, 15, 3370–3381. [CrossRef]
[PubMed]
92. Bartalena, L.; Fatourechi, V. Extrathyroidal manifestations of Graves’ disease: A 2014 update. J. Endocrinol.
Investig. 2014, 37, 691–700. [CrossRef] [PubMed]
93. Matheis, N.; Grus, F.H.; Breitenfeld, M.; Knych, I.; Funke, S.; Pitz, S.; Ponto, K.A.; Pfeiffer, N.;
Kahaly, G.J. Proteomics differentiate between thyroid-associated orbitopathy and dry eye syndrome. Investig.
Opthalmology Vis. Sci. 2015, 56, 2649. [CrossRef] [PubMed]
94. Vissink, A.; Bootsma, H.; Spijkervet, F.K.; Hu, S.; Wong, D.T.; Kallenberg, C.G. Current and Future Challenges
in Primary Sjogren’s Syndrome. Curr. Pharm. Biotechnol. 2012, 13, 2026–2045. [CrossRef] [PubMed]
J. Clin. Med. 2019, 8, 1439 19 of 21

95. Li, B.; Sheng, M.; Li, J.; Yan, G.; Lin, A.; Li, M.; Wang, W.; Chen, Y. Tear proteomic analysis of Sjögren
syndrome patients with dry eye syndrome by two-dimensional-nano-liquid chromatography coupled with
tandem mass spectrometry. Sci. Rep. 2014, 4, 5772. [CrossRef] [PubMed]
96. Cocho, L.; Fernandez, I.; Calonge, M.; Martínez, V.; González-García, M.J.; Caballero, D.; López-Corral, L.;
García-Vázquez, C.; Vazquez, L.; Stern, M.E.; et al. Gene Expression–Based Predictive Models of Graft Versus
Host Disease–Associated Dry Eye. Investig. Ophthalmol. Vis. Sci. 2015, 56, 4570. [CrossRef] [PubMed]
97. Cocho, L.; Fernandez, I.; Calonge, M.; Martínez, V.; González-García, M.J.; Caballero, D.; López-Corral, L.;
García-Vázquez, C.; Vazquez, L.; Stern, M.E.; et al. Biomarkers in Ocular Chronic Graft Versus Host Disease:
Tear Cytokine- and Chemokine-Based Predictive Model. Investig. Ophthalmol. Vis. Sci. 2016, 57, 746.
[CrossRef] [PubMed]
98. Jung, J.W.; Han, S.J.; Song, M.K.; Kim, T.-I.; Kim, E.K.; Min, Y.H.; Cheong, J.-W.; Seo, K.Y. Tear Cytokines
as Biomarkers for Chronic Graft-versus-Host Disease. Boil. Blood Marrow Transplant. 2015, 21, 2079–2085.
[CrossRef]
99. Giannaccare, G.; Bonifazi, F.; Sessa, M.; Fresina, M.; Arpinati, M.; Bandini, G.; Versura, P. Dry Eye Disease Is
Already Present in Hematological Patients before Hematopoietic Stem Cell Transplantation. Cornea 2016, 35,
638–643. [CrossRef]
100. Schaumberg, D.A.; Sullivan, D.A.; Dana, M.R. Epidemiology of dry eye syndrome. Adv. Exp. Med. Biol.
2002, 506, 989–998.
101. Lelli, G.J.; Musch, D.C.; Gupta, A.; Farjo, Q.A.; Nairus, T.M.; Mian, S.I. Ophthalmic Cyclosporine Use in
Ocular GVHD. Cornea 2006, 25, 635–638. [CrossRef] [PubMed]
102. Malta, J.B.; Soong, H.K.; Shtein, R.M.; Musch, D.C.; Rhoades, W.; Sugar, A.; Mian, S.I. Treatment of Ocular
Graft-Versus-Host Disease with Topical Cyclosporine 0.05%. Cornea 2010, 29, 1392–1396. [CrossRef] [PubMed]
103. DiMasi, J.A.; Grabowski, H.G.; Hansen, R.W. Innovation in the pharmaceutical industry: New estimates of
R&D costs. J. Health Econ. 2016, 47, 20–33. [PubMed]
104. Zhang, B.; Radisic, M. Organ-on-a-chip devices advance to market. Lab Chip 2017, 17, 2395–2420. [CrossRef]
[PubMed]
105. Baker, M. Tissue models: A living system on a chip. Nature 2011, 471, 661. [CrossRef]
106. Seo, J.; Byun, W.Y.; Frank, A.; Massaro-Giordano, M.; Lee, V.; Bunya, V.Y.; Huh, D. Human blinking
‘eye-on-a-chip’. Investig. Ophthalmol. Vis. Sci. 2016, 57, 3872.
107. Foster, J.W.; Wahlin, K.; Adams, S.M.; Birk, D.E.; Zack, D.J.; Chakravarti, S. Cornea organoids from human
induced pluripotent stem cells. Sci. Rep. 2017, 7, 41286. [CrossRef]
108. Susaimanickam, P.J.; Maddileti, S.; Pulimamidi, V.K.; Boyinpally, S.R.; Naik, R.R.; Naik, M.N.; Reddy, G.B.;
Sangwan, V.S.; Mariappan, I. Generating minicorneal organoids from human induced pluripotent stem cells.
Development 2017, 144, 2338–2351. [CrossRef]
109. Seo, J.; Byun, W.Y.; Alisafaei, F.; Georgescu, A.; Yi, Y.-S.; Massaro-Giordano, M.; Shenoy, V.B.; Lee, V.;
Bunya, V.Y.; Huh, D. Multiscale reverse engineering of the human ocular surface. Nat. Med. 2019, 25,
1310–1318. [CrossRef]
110. Coursey, T.G.; Henriksson, J.T.; Marcano, D.C.; Shin, C.S.; Isenhart, L.C.; Ahmed, F.; De Paiva, C.S.;
Pflugfelder, S.C.; Acharya, G. Dexamethasone nanowafer as an effective therapy for dry eye disease.
J. Control. Release 2015, 213, 168–174. [CrossRef]
111. Bian, F.; Shin, C.S.; Wang, C.; Pflugfelder, S.C.; Acharya, G.; De Paiva, C.S. Dexamethasone Drug Eluting
Nanowafers Control Inflammation in Alkali-Burned Corneas Associated with Dry Eye. Investig. Ophthalmol.
Vis. Sci. 2016, 57, 3222–3230. [CrossRef] [PubMed]
112. Pinto-Fraga, J.; López-Miguel, A.; González-García, M.J.; Fernández, I.; López-de-la-Rosa, A.;
Enríquez-de-Salamanca, A.; Stern, M.E.; Calonge, M. Topical fluorometholone protects the ocular surface of
dry eye patients from desiccating stress: A randomized controlled clinical trial. Ophthalmology 2016, 123,
141–153. [CrossRef] [PubMed]
113. Shah, M.; Edman, M.C.; Janga, S.R.; Yarber, F.; Meng, Z.; Klinngam, W.; Bushman, J.; Ma, T.; Liu, S.; Louie, S.
Rapamycin eye drops suppress lacrimal gland inflammation in a murine model of Sjögren’s syndrome.
Investig. Ophthalmol. Vis. Sci. 2017, 58, 372–385. [CrossRef]
114. Simopoulos, A. The importance of the ratio of omega-6/omega-3 essential fatty acids. Biomed. Pharmacother.
2002, 56, 365–379. [CrossRef]
J. Clin. Med. 2019, 8, 1439 20 of 21

115. Deinema, L.A.; Vingrys, A.J.; Wong, C.Y.; Jackson, D.C.; Chinnery, H.R.; Downie, L.E. A Randomized,
Double-Masked, Placebo-Controlled Clinical Trial of Two Forms of Omega-3 Supplements for Treating Dry
Eye Disease. Ophthalmology 2017, 124, 43–52. [CrossRef]
116. Andrade, A.S.; Salomon, T.B.; Behling, C.S.; Mahl, C.D.; Hackenhaar, F.S.; Putti, J.; Benfato, M.S. Alpha-lipoic
acid restores tear production in an animal model of dry eye. Exp. Eye Res. 2014, 120, 1–9. [CrossRef]
[PubMed]
117. Bhargava, R.; Kumar, P.; Phogat, H.; Kaur, A.; Kumar, M. Oral omega-3 fatty acids treatment in computer
vision syndrome related dry eye. Contact Lens Anterior Eye 2015, 38, 206–210. [CrossRef] [PubMed]
118. Li, Z.; Choi, J.-H.; Oh, H.-J.; Park, S.-H.; Lee, J.-B.; Yoon, K.C. Effects of Eye Drops Containing a Mixture of
Omega-3 Essential Fatty Acids and Hyaluronic Acid on the Ocular Surface in Desiccating Stress-induced
Murine Dry Eye. Curr. Eye Res. 2014, 39, 871–878. [CrossRef]
119. Lembach, C.; Fogt, J.; Kowalski, M.; King-Smith, P.E.; Epitropoulos, A.; Hendershot, A.; Maszczak, J.;
Jones-Jordan, L.; Barr, J. Tear lipid layer thickness with eye drops in meibomian gland dysfunction. Clin.
Ophthalmol. 2016, 10, 2237–2243.
120. Wang, M.T.M.; Jaitley, Z.; Lord, S.M.; Craig, J.P. Comparison of Self-Applied Heat Therapy for Meibomian
Gland Dysfunction. Optom. Vis. Sci. 2015, 92, e321–e326. [CrossRef]
121. Kim, Y.J.; Ryu, J.S.; Park, S.Y.; Lee, H.J.; Ko, J.H.; Kim, M.K.; Wee, W.R.; Oh, J.Y. Comparison of Topical
Application of TSG-6, Cyclosporine, and Prednisolone for Treating Dry Eye. Cornea 2016, 35, 536–542.
[CrossRef] [PubMed]
122. Sawazaki, R.; Ishihara, T.; Usui, S.; Hayashi, E.; Tahara, K.; Hoshino, T.; Higuchi, A.; Nakamura, S.; Tsubota, K.;
Mizushima, T. Diclofenac Protects Cultured Human Corneal Epithelial Cells Against Hyperosmolarity and
Ameliorates Corneal Surface Damage in a Rat Model of Dry Eye. Investig. Ophthalmol. Vis. Sci. 2014, 55,
2547–2556. [CrossRef] [PubMed]
123. Agarwal, P.; Rupenthal, I.D. Modern approaches to the ocular delivery of cyclosporine A. Drug Discov. Today
2016, 21, 977–988. [CrossRef] [PubMed]
124. Pflugfelder, S.C.; De Paiva, C.S.; Villarreal, A.L.; Stern, M.E. Effects of Sequential Artificial Tear and
Cyclosporine Emulsion Therapy on Conjunctival Goblet Cell Density and Transforming Growth Factor-β2
Production. Cornea 2008, 27, 64–69. [CrossRef] [PubMed]
125. Macri, A.; Scanarotti, C.; Bassi, A.M.; Giuffrida, S.; Sangalli, G.; Traverso, C.E.; Iester, M. Evaluation of
oxidative stress levels in the conjunctival epithelium of patients with or without dry eye, and dry eye patients
treated with preservative-free hyaluronic acid 0.15% and vitamin B12 eye drops. Graefes Arch. Clin. Exp.
Ophthalmol. 2015, 253, 425–430. [CrossRef] [PubMed]
126. Zernii, E.Y.; Gancharova, O.S.; Baksheeva, V.E.; Golovastova, M.O.; Kabanova, E.I.; Savchenko, M.S.;
Tiulina, V.V.; Sotnikova, L.F.; Zamyatnin, A.A.; Philippov, P.P.; et al. Mitochondria-Targeted Antioxidant
SkQ1 Prevents Anesthesia-Induced Dry Eye Syndrome. Oxidative Med. Cell. Longev. 2017, 2017, 9281519.
[CrossRef] [PubMed]
127. Bremond-Gignac, D.; Gicquel, J.-J.; Chiambaretta, F. Pharmacokinetic evaluation of diquafosol tetrasodium
for the treatment of Sjögren’s syndrome. Expert Opin. Drug Metab. Toxicol. 2014, 10, 905–913. [CrossRef]
[PubMed]
128. Ikeda, K.; Simsek, C.; Kojima, T.; Higa, K.; Kawashima, M.; Dogru, M.; Shimizu, T.; Tsubota, K.; Shimazaki, J.
The effects of 3% diquafosol sodium eye drop application on meibomian gland and ocular surface alterations
in the Cu, Zn-superoxide dismutase-1 (Sod1) knockout mice. Graefes Arch. Clin. Exp. Ophthalmol. 2018, 256,
739–750. [CrossRef]
129. Contreras-Ruiz, L.; Masli, S. Immunomodulatory Cross-Talk between Conjunctival Goblet Cells and Dendritic
Cells. PLoS ONE 2015, 10, e0120284. [CrossRef]
130. Tan, X.; Chen, Y.; Foulsham, W.; Amouzegar, A.; Inomata, T.; Liu, Y.; Chauhan, S.K.; Dana, R.
The immunoregulatory role of corneal epithelium-derived thrombospondin-1 in dry eye disease. Ocul. Surf.
2018, 16, 470–477. [CrossRef]
131. Ratay, M.L.; Glowacki, A.J.; Balmert, S.C.; Acharya, A.P.; Polat, J.; Andrews, L.P.; Fedorchak, M.V.;
Schuman, J.S.; Vignali, D.A.; Little, S.R. Treg-recruiting microspheres prevent inflammation in a murine
model of dry eye disease. J. Control. Release 2017, 258, 208–217. [CrossRef] [PubMed]
132. Gill, R.; Tsung, A.; Billiar, T. Linking oxidative stress to inflammation: Toll-like receptors. Free Radic. Biol. Med.
2010, 48, 1121–1132. [CrossRef] [PubMed]
J. Clin. Med. 2019, 8, 1439 21 of 21

133. Zhang, H.; Tsao, R. Dietary polyphenols, oxidative stress and antioxidant and anti-inflammatory effects.
Curr. Opin. Food Sci. 2016, 8, 33–42. [CrossRef]
134. Saldanha, I.J.; Li, T.; Yang, C.; Owczarzak, J.; Williamson, P.R.; Dickersin, K. Clinical trials and systematic
reviews addressing similar interventions for the same condition do not consider similar outcomes to be
important: A case study in HIV/AIDS. J. Clin. Epidemiol. 2017, 84, 85–94. [CrossRef] [PubMed]
135. Novack, G.D.; Asbell, P.; Barabino, S.; Bergamini, M.V.; Ciolino, J.B.; Foulks, G.N.; Goldstein, M.; Lemp, M.A.;
Schrader, S.; Woods, C.; et al. TFOS DEWS II Clinical Trial Design Report. Ocul. Surf. 2017, 15, 629–649.
[CrossRef] [PubMed]

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