·Investigation·
iTRAQ-based
proteomics analysis of aqueous humor in patients with dry age-related macular
degeneration
Si-Chang Qu1, Ding Xu1,
Ting-Ting Li1, Jing-Fa Zhang2, Fang Liu1
1Department of Ophthalmology of Shanghai
Tenth People’s Hospital, Tongji Eye Institute, Tongji University School of
Medicine, Shanghai 200072, China
2Department of Ophthalmology,
Shanghai General Hospital (Shanghai First People’s Hospital), Shanghai Jiao
Tong University, Shanghai 200080, China
Correspondence to: Fang Liu. Department of
Ophthalmology of Shanghai Tenth People’s Hospital, Tongji Eye Institute, Tongji
University School of Medicine, 301 Yanchang Road, Jing’an District, Shanghai
200072, China. fangliu_2004@yahoo.com; Jing-Fa Zhang. Department of
Ophthalmology, Shanghai General Hospital (Shanghai First People’s Hospital),
Shanghai Jiao Tong University, 100 Haining Road, Hongkou District, Shanghai
200080, China. 13917311571@139.com
Received:
Abstract
AIM: To preliminarily test proteomics in aqueous humor in patients with dry
age-related macular degeneration (AMD) by using the proteomic technology.
METHODS: Aqueous humor samples were collected from patients with or without dry AMD,
who underwent cataract surgery. The aqueous samples were analyzed with isobaric
tags for relative and absolute quantification (iTRAQ) combined with liquid
chromatography tandem mass spectrometry (LC-MS/MS) technology. The differential
expressed proteins were analyzed with gene ontology (GO) enrichment, Kyoto
Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI)
network analysis. The data were partly validated by ELISA and Western blot.
False discovery rate (FDR) was used for statistical analysis.
RESULTS: A total of 244 proteins were detected, in which 38 proteins were
up-regulated and 51 were down-regulated significantly in patients with dry AMD
compared with that in control groups (FDR value <1.0%). Several proteins, e.g.,
protein S100-A8 (S
CONCLUSION: iTRAQ-based proteomic analysis of aqueous humor
demonstrate the differential expressions of proteins between dry AMD and
control groups, providing the clues to understand the mechanisms and possible
treatments of dry AMD.
KEYWORDS: age-related macular degeneration;
protein biomarker; isobaric tags for relative and absolute quantification;
differential expression of proteins; aqueous humor
DOI:10.18240/ijo.2019.11.15
Citation: Qu
SC, Xu D, Li TT, Zhang JF, Liu F. iTRAQ-based proteomics analysis of aqueous
humor in patients with dry age-related macular degeneration. Int J
Ophthalmol 2019;12(11):1758-1766
INTRODUCTION
Age-related
macular degeneration (AMD) is a severe disease with the chronic progressive
loss of central vision, which is caused by environmental and multi-genes
interactions[1]. It is the leading cause of
blindness in patients over 60 years old, and the number of patients with AMD is
expected to reach 288 million by 2040[2]. Recent
study showed that the morbidity caused by this globalized disease in Asian
populations was similar to or even higher than Caucasians[3-6]. AMD is divided into atrophic (dry) form with drusen
deposition, in which geographic atrophy (GA) was the severe form, and
neovascular (wet) form with formation of choroidal neovascularization (CNV).
Currently, anti-vascular endotheliall growth factor (VEGF) reagents, like
ranibizumab, aflibercept and conbercept, are widely used to treat CNV secondary
to wet AMD in clinical practice, showing great efficacy in regressing CNV.
However, there are no effective treatments for dry AMD. It is of the importance
to elucidated the mechanisms of dry AMD and thus to find effective treatments
for it. Recent studies reported some differential expressed proteins,
identified from aqueous humor, vitreous body, Bruch’s membrane and plasma[7-11], might be used as the
promising biomarkers for dry AMD, which are associated with oxidative stress,
immune activation and metabolic dysfunction, etc.
The current methods for protein
quantitative partition include two-dimensional fluorescence difference gel
electrophoresis (2D-DIGE) coupled with stain and mass spectrometry-based
detection. 2D-electrophoresis is widely used for its feasibility and low cost,
but it has some limitations, such as to effectively separate extreme high or
relative low molecular weight proteins (>200 kD or <8 kD), low abundant
proteins, hydrophobic proteins and basic proteins. Mass spectrometry-based
detection can be divided into labeling quantitation and label-free
quantitation. Labeling quantitation includes metabolic labeling and
isotope-coded affinity tags (ICAT) in vivo as well as stable isotope
labeling of amino acids in culture (SILAC) and isobaric tags for relative and
absolute quantification (iTRAQ) in vitro. Among them, iTRAQ is an
approach utilizing isotope labeling technology introduced by the American
applied biological systems corporation[12].
Comparing with other methods, iTRAQ has several virtues, e.g., analysis
of a wide range of samples including cellular extracts and complex mixture
samples, high-throughput simultaneously quantifying four to eight kinds of
samples, good repeatability and high result consistency, etc[12].
In this study, we used iTRAQ to
detect the differential expressions of aqueous proteins in patients with or
without dry AMD, followed by liquid chromatography tandem mass spectrometry
(LC-MS/MS) for identification. Several differentially expressed proteins (DEPs)
detected by iTRAQ could be served as potential biomarkers for dry AMD, which
helped to elucidate its underlying mechanisms.
SUBJECTS AND METHODS
Ethical Approval The study received Institutional
Review Board (IRB) approval from Ethics Committee of Shanghai Tenth People’s
Hospital, Tongji University School of Medicine, and was conducted in accordance
with ethical standards of the Declaration of Helsinki regulations. All
participants signed the informed consents and didn’t receive any stipends.
Patients and Sampling Total 24 patients were employed,
including 12 patients with cataract only and 12 with both cataract and dry AMD,
who underwent phacoemulsification and intraocular lens implantation at
Department of Ophthalmology of Shanghai Tenth People’s Hospital, Tongji Eye
Institute, Tongji University School of Medicine, Shanghai, China from February
2017 to December 2017. The clinical and demographic data of patients were
detailed in Table 1.
Table 1 The clinical and demographic
data of the subjects
|
Items |
AMD group |
Control group |
|
Age (mean±SD, y) |
80.82±4.17 |
68.81±18.82 |
|
Gender (man vs women) |
5:7 |
6:6 |
|
Stages of dry AMD |
|
|
|
Early stage |
7 |
0 |
|
Intermediate stage |
2 |
0 |
|
Advanced stage |
3 |
0 |
AMD: Age-related macular
degeneration. Early stage: Significant for the presence of multiple drusen
(each drusen <125 µm in size); Intermediate stage: Confluent drusen (≥125 µm
in size) and the RPE often appears atrophic, with easier visualization of the underlying
choroid vascular plexus; Advanced stage: Coalescence of focal islands of
atrophy and formation of large zones of atrophy.
Before the surgery, all patients
were examined thoroughly to exclude systemic diseases and evaluate eye
conditions including routine blood test, slit-lamp examination, fundus
photography, fluorescence fundus angiography (FFA), indocyanine green
angiography (ICGA) and optical coherence tomography (OCT), etc. The
patients with cataract only were served as control. Total twenty-four aqueous
humor samples (0.1 mL/patient) were obtained via paracentesis of
anterior chamber by using
Protein Preparation and iTRAQ
Labeling Protein concentrations were
determined by BCA protein assay according to the manufacturer’s instruction
(Merck, Darmstadt, Germany). Considering the total concentration was five times
lower in aqueous humor than in plasm, the aqueous samples were not processed to
remove the high abundant proteins to prevent the loss of certain binding
proteins. The protein samples (30 μg per sample) were mixed separately as AMD
group or control group, and digested with trypsin (the proportion of trypsin:
protein=1:25). The digestion was carried out overnight at
The peptide mixture was labeled with
iTRAQ reagent according to the manufacturer’s instruction (AB Sciex, Foster City,
CA, USA). Briefly, the aqueous samples from 12 AMD patients were pooled
together, divided equally into two groups and labeled with 114 and 115 tags,
respectively. And the samples from control group were processed with the same
way and labeled with 116 and 117 tags respectively. The quantitative values of
iTRAQ ratios expressed as the average of 114:116 and 115:116 for AMD group, and
as the average of 116:116 (equal to 1) and 117:116 for control group. After
reaction at room temperature for one hour, all labeled samples were collected
into a tube for subsequent reaction.
Quantitative Proteomic Analyses and
Data Processing Firstly, the complex mixed peptides
were classified using strong cation exchanger (SCX) column according to the
ICAT Cation Exchange Buffer Pack kit. Gradient elution was done in order of
increasing KCL concentrations (40, 60, 80, 100, 120, 140, 160, 200, 240 and 460
mmol/L). Eluant was gathered, concentrated and desalted after SCX grading.
Peptides of twice eluting were pooled and dried for liquid chromatography (LC).
The complex peptides were separated
into simple peptides by using LC. A binary gradient with solvent A [2%
acetonitrile (ACN) and 0.1% formic acid (FA)] and solvent B (98%ACN and 0.1%
FA) was employed as the mobile phase. The dried SCX fractions were dissolved in
20 μL of solvent A, followed by centrifugation at 12 000 r for 10min. Totally 8
µL of each sample was loaded and flow rate of loading pump was controlled at 2
µL/min. The peptide solutions were desalted for 15min and then separated
peptides online at 0.3 µL/min. Solvent B was ramped up from 5% to 48% in 85min
and increased to 80% maintained for 5min to elute the highly retained peptide
segments. After that, the concentration was changed to 5% for 10min. The peptide
fractions were finally collected and entered MS analysis after ionized.
The identification of platform of MS
analysis was ABSECX TripleTOFTM 4600, acquisition map model was in
Data Dependent Acquisition (DDA) scanning mode, and the sprayer used New Objective.
The ionization voltage maintained at 2.3 kV and the mass-to-charge ratio of MS
scanning was in the range of 350-1250 (m/z), with cumulative time of 0.25s. The
top 30 multiply-charged ions were selected for MS/MS analysis of each scan from
an m/z 100-1500 range. The cumulative time of MS/MS analysis was 0.1s, dynamic
elimination time was 25s, fluctuation state of collision energy was set as
enabled, and collision voltage difference was 5.
In the LC-MS/MS analysis, a protein
with an unused score below 1% false discovery rate (FDR) and at least 2 unique
peptides with 95% probability should be accepted.
Bioinformatics Analysis Gene ontology (GO) annotation was
performed using the Blast2GO Bioinformatics software (V
Enzyme-linked Immunosorbent Assay Concentration of the high-expressed
protein from plasma samples were detected by enzyme-linked immunosorbent assay
(ELISA) according to the manufacturer’s instructions (R&D systems, Human
alpha 1-Acid Glycoprotein Quantikine ELISA Kit). Briefly, 100 µL of assay
diluent and 50 µL of standard, plasma samples or control were added to each
well and incubate for 2h at room temperature. Then, the wells were sequentially
aspirated, washed four times, followed by adding 200 µL of conjugate to each
well and incubated at room temperature for 2h. After aspirated and washed four times,
the wells were further incubated with 200 µL substrate solution at room
temperature for 30min in darkness. Finally, 50 µL of stop solution was added to
each well and optical density was read at 450 nm on an enzyme label colorimeter
(Multiskan FC, Thermo Scientific, USA).
Western Blot Analysis Five isopyknic protein samples with
the same concentration of total proteins were mixed and subjected to 10%
polyacrylamide gels for electrophoresis, and were transferred onto PVDF
membrane and incubated with the primary antibody (Human alpha 1 Acid
Glycoprotein antibody, 1:500; R&D system, Mab3694) overnight at
Statistical Analysis Protein ratio was analyzed by FDR, a
built-in procedure of ProteinPilot software, which is the corrected P values.
Peptide identifications required an FDR value <1.0%.
RESULTS
Proteomic Identification of
Differentially Expressed Proteins Profiling of DEPs between dry AMD
group and control group were created by quantitative proteomic analysis. To
highlight the key proteins, two key criteria were used to define the specific
proteins, i.e., 1) protein levels in AMD group higher than at least
1.5-fold or lower than at least 0.8-fold of that in control group; 2) protein
levels in control group changed between 0.8-fold and 1.2-fold. Based on this
criterion, a total of 244 proteins were detected; among them, 89 proteins were
identified differentially expressed, with 38 up-regulated proteins and 51
down-regulated proteins (Figure 1). The details of the DEPs were listed in Tables
2 and 3.
Figure 1 The Volcano pattern of DEPs The graph’s horizontal axis represents
log2 (fold change) and the vertical axis represents -log10 (FDR). Two dotted
red lines separates the Figure into three parts. The rightmost part shows 38
proteins were up-regulated and the leftmost part shows 51 proteins were
down-regulated. And the middle part remains relatively unchanged.
Table 2 List of up-regulated
proteins in AMD group compared with control group
|
Accession No. |
Gene name |
Protein name |
Peptides (95%) |
Fold change |
FDR (%) |
Stability ratio |
FDR (%) |
|
P05109 |
S |
Protein S100-A8 |
8 |
8.11285 |
0.0363 |
1.16525 |
0.3044 |
|
Q14118 |
DAG1 |
Dystroglycan |
2 |
7.144 |
0.5497 |
0.9954 |
0.4929 |
|
P01876 |
IGHA1 |
Ig alpha-1 chain C region |
30 |
6.36825 |
0.2284 |
0.8273 |
0.5461 |
|
P07451 |
CAH3 |
Carbonic anhydrase 3 |
3 |
5.37175 |
0.0713 |
1.05845 |
0.8471 |
|
P02763 |
A1AG1 |
Alpha-1-acid glycoprotein |
44 |
5.3211 |
0.3553 |
1.0333 |
0.6994 |
|
P06727 |
APOA4 |
Apolipoprotein A-IV |
47 |
4.9457 |
0.0001 |
1.1966 |
0.3151 |
|
P02788 |
TRFL |
Lactotransferrin |
25 |
4.43605 |
0.1164 |
0.90085 |
0.9119 |
|
P30838 |
AL |
Aldehyde dehydrogenase |
9 |
4.239 |
0.8126 |
1.1902 |
0.3191 |
|
P01042 |
KNG1 |
Kininogen-1 |
41 |
3.8584 |
0.1879 |
1.05845 |
0.8961 |
|
P63261 |
ACTG |
Actin, cytoplasmic 2 |
15 |
3.8377 |
0.2427 |
1.10115 |
0.2811 |
|
P19823 |
ITIH2 |
Inter-alpha-trypsin inhibitor heavy chain H2 |
8 |
3.65595 |
0.1392 |
1.0741 |
0.9467 |
|
P02647 |
APOA1 |
Apolipoprotein A-I |
78 |
3.59195 |
0.0914 |
1.11795 |
0.6642 |
|
P19652 |
A1AG2 |
Alpha-1-acid glycoprotein 2 |
24 |
3.4143 |
0.3822 |
1.1966 |
0.7947 |
|
P07225 |
PROS |
Vitamin K-dependent protein S |
2 |
3.1293 |
0.7689 |
1 |
0.9165 |
|
P25311 |
ZA |
Zinc-alpha-2-glycoprotein |
33 |
3.09115 |
0.0271 |
0.8365 |
0.2774 |
|
P43652 |
AFAM |
Afamin |
26 |
2.96685 |
0.2994 |
0.84275 |
0.1039 |
|
P80748 |
LV302 |
Ig lambda chain V-III region LOI |
6 |
2.94375 |
0.7735 |
0.88635 |
0.339 |
|
P00338 |
LDHA |
L-lactate dehydrogenase A chain |
6 |
2.818 |
0.6028 |
0.8556 |
0.956 |
|
P01024 |
CO3 |
Complement C3 |
139 |
2.7808 |
0.0006 |
1.02355 |
0.8534 |
|
P02750 |
A2GL |
Leucine-rich alpha-2-glycoprotein |
6 |
2.7016 |
0.0263 |
1.10115 |
0.7073 |
|
P02760 |
AMBP |
Protein AMBP |
13 |
2.63815 |
0.0112 |
0.8758 |
0.1804 |
|
P02675 |
FIBB |
Fibrinogen beta chain |
13 |
2.46095 |
0.023 |
0.8556 |
0.3175 |
|
P02774 |
VTDB |
Vitamin D-binding protein |
58 |
2.23515 |
0.2346 |
1.0093 |
0.37 |
|
P04196 |
HRG |
Histidine-rich glycoprotein |
27 |
2.048 |
0.9573 |
0.9315 |
0.5461 |
|
P00734 |
THRB |
Prothrombin |
20 |
2.02405 |
0.7763 |
0.91975 |
0.8888 |
|
P00747 |
PLMN |
Plasminogen |
32 |
1.9724 |
0.582 |
1.1067 |
0.3485 |
|
P05546 |
HEP2 |
Heparin cofactor 2 |
12 |
1.96475 |
0.8765 |
1.09015 |
0.5298 |
|
Q9HCQ7 |
RFRP |
FMRFamide-related peptides |
2 |
1.90125 |
0.2499 |
0.956 |
0.9658 |
|
P61626 |
LYSC |
Lysozyme C |
11 |
1.8574 |
0.3403 |
1.15915 |
0.5153 |
|
P04406 |
G3P |
Glyceraldehyde-3-phosphate dehydrogenase |
9 |
1.8478 |
0.9072 |
0.9731 |
0.1866 |
|
P01775 |
HV314 |
Ig heavy chain V-III region LAY |
2 |
1.81 |
0.5162 |
1.0636 |
0.8005 |
|
P00751 |
CFAB |
Complement factor B |
36 |
1.75395 |
0.4939 |
1.0333 |
0.3176 |
|
P10451 |
OSTP |
Osteopontin |
31 |
1.73075 |
0.5831 |
0.90085 |
0.6573 |
|
P01023 |
A2MG |
Alpha-2-macroglobulin |
67 |
1.70955 |
0.2094 |
1.00465 |
0.6274 |
|
P35749 |
MYH11 |
Myosin-11 |
2 |
1.7088 |
0.4505 |
1.10115 |
0.6608 |
|
P31025 |
LCN1 |
Lipocalin-1 |
7 |
1.61465 |
0.2414 |
1.14115 |
0.8803 |
|
P01861 |
IGHG4 |
Ig gamma-4 chain C region |
157 |
1.59305 |
0.8834 |
0.9688 |
0.9524 |
|
P01772 |
HV311 |
Ig heavy chain V-III region KOL |
5 |
1.5013 |
0.2508 |
1.0956 |
0.5357 |
Fold change: The average of 114:116 and
115:116, represents the differences between dry AMD and control group.
Stability ratio: The average of 117:116 and 116:116, represents the stability
of experimental.
Table 3 List of down-regulated
proteins in AMD group compared with control group
|
Accession No. |
Gene name |
Protein name |
Peptides (95%) |
Fold change |
FDR (%) |
Stability ratio |
FDR (%) |
|
P49788 |
TIG1 |
Retinoic acid receptor responder protein 1 |
4 |
0.79175 |
0.7269 |
0.9477 |
0.3415 |
|
O95967 |
FBLN4 |
EGF-containing fibulin-like extracellular matrix
protein 2 |
2 |
0.78015 |
0.7237 |
0.8365 |
0.456 |
|
Q9BRK5 |
CAB45 |
45 kDa calcium-binding protein |
2 |
0.77985 |
0.4855 |
0.9518 |
0.4635 |
|
P13591 |
NCAM1 |
Neural cell adhesion molecule 1 |
2 |
0.7792 |
0.1763 |
0.9775 |
0.5542 |
|
P03950 |
ANGI |
Angiogenin |
3 |
0.7774 |
0.7888 |
1.04825 |
0.8322 |
|
P23142 |
FBLN1 |
Fibulin-1 |
15 |
0.7672 |
0.4822 |
0.9819 |
0.9004 |
|
P01779 |
HV318 |
Ig heavy chain V-III region TUR |
5 |
0.7603 |
0.9268 |
0.98635 |
0.9713 |
|
P11021 |
GRP78 |
78 kDa glucose-regulated protein |
3 |
0.75905 |
0.3494 |
0.9315 |
0.3553 |
|
P06309 |
KV205 |
Ig kappa chain V-II region GM607 (fragment) |
8 |
0.7586 |
0.7575 |
1.0533 |
0.9666 |
|
O00391 |
QSOX1 |
Sulfhydryl oxidase 1 |
4 |
0.7185 |
0.3163 |
0.87235 |
0.3321 |
|
Q92563 |
TICN2 |
Testican-2 |
4 |
0.7145 |
0.3223 |
0.8828 |
0.6172 |
|
P61812 |
TGFB2 |
Transforming growth factor beta-2 |
2 |
0.69935 |
0.7418 |
0.90455 |
0.7235 |
|
Q16270 |
IBP7 |
Insulin-like growth factor-binding protein 7 |
16 |
0.6812 |
0.0721 |
1.10115 |
0.7936 |
|
P00738 |
HPT |
Haptoglobin |
21 |
0.67985 |
0.9968 |
1.1471 |
0.7978 |
|
P28799 |
GRN |
Granulins |
2 |
0.66815 |
0.8388 |
1.14115 |
0.9648 |
|
Q96KN2 |
CNDP1 |
Beta-Ala-His dipeptidase |
9 |
0.658 |
0.5946 |
0.8793 |
0.5747 |
|
P30041 |
PRDX6 |
Peroxiredoxin-6 |
2 |
0.65225 |
0.5452 |
0.8126 |
0.8256 |
|
Q15113 |
PCOC1 |
Procollagen C-endopeptidase enhancer 1 |
13 |
0.6438 |
0.227 |
1.1123 |
0.8747 |
|
P51693 |
APLP1 |
Amyloid-like protein 1 |
5 |
0.63985 |
0.9855 |
1.1353 |
0.6148 |
|
P02452 |
CO |
Collagen alpha-1(I) chain |
5 |
0.62645 |
0.5824 |
0.83035 |
0.3598 |
|
Q06481 |
APLP2 |
Amyloid-like protein 2 |
19 |
0.62055 |
0.3582 |
1.1237 |
0.7933 |
|
Q16568 |
CART |
Cocaine-and amphetamine-regulated transcript
protein |
2 |
0.5856 |
0.947 |
0.8097 |
0.4122 |
|
O15031 |
PLXB2 |
Plexin-B2 |
3 |
0.5732 |
0.6615 |
1.18385 |
0.419 |
|
P35555 |
FBN1 |
Fibrillin-1 |
30 |
0.5557 |
0.1014 |
0.9236 |
0.9677 |
|
Q8WXD2 |
SCG3 |
Secretogranin-3 |
6 |
0.5546 |
0.1091 |
1.0432 |
0.4877 |
|
P02766 |
TTHY |
Transthyretin |
21 |
0.53735 |
0.0087 |
0.9645 |
0.7666 |
|
P22352 |
GPX3 |
Glutathione peroxidase 3 |
23 |
0.53365 |
0.0067 |
1.11795 |
0.4594 |
|
Q02809 |
PLOD1 |
Procollagen-lysine,2-oxoglutarate 5-dioxygenase 1 |
2 |
0.5083 |
0.3454 |
1.0093 |
0.9497 |
|
P06865 |
HEXA |
Beta-hexosaminidase subunit alpha |
2 |
0.4977 |
0.1839 |
0.90085 |
0.376 |
|
Q99435 |
NELL2 |
Protein
kinase C-binding protein NELL2 |
2 |
0.49765 |
0.2352 |
0.9315 |
0.4598 |
|
P01034 |
CYTC |
Cystatin-C |
30 |
0.48975 |
0.0024 |
0.9477 |
0.6458 |
|
P05154 |
IPSP |
Plasma serine protease inhibitor |
8 |
0.47985 |
0.6772 |
0.99085 |
0.4351 |
|
Q13510 |
ASAH1 |
Acid ceramidase |
3 |
0.47905 |
0.3238 |
1.1471 |
0.5318 |
|
Q12907 |
LMAN2 |
Vesicular integral-membrane protein VIP36 |
2 |
0.4665 |
0.346 |
0.90085 |
0.681 |
|
P06396 |
GELS |
Gelsolin |
57 |
0.4229 |
0.0012 |
0.956 |
0.6997 |
|
P13645 |
K |
Keratin, type I cytoskeletal 10 |
14 |
0.418 |
0.2382 |
0.9602 |
0.8642 |
|
P07339 |
CATD |
Cathepsin D |
21 |
0.4131 |
0.0792 |
1.01875 |
0.5453 |
|
P16870 |
CBPE |
Carboxypeptidase E |
11 |
0.4007 |
0.01 |
0.9236 |
0.2487 |
|
Q9HCB6 |
SPON1 |
Spondin-1 |
10 |
0.3956 |
0.6449 |
0.8334 |
0.9428 |
|
Q92520 |
FAM |
Protein FAM |
5 |
0.3774 |
0.5027 |
0.9775 |
0.5558 |
|
P07477 |
TRY1 |
Trypsin-1 |
29 |
0.37515 |
0.0695 |
0.9688 |
0.6649 |
|
Q12805 |
FBLN3 |
EGF-containing fibulin-like extracellular matrix
protein 1 |
36 |
0.37485 |
0.0363 |
0.9436 |
0.9729 |
|
Q13822 |
ENPP2 |
Ectonucleotide pyrophosphatase/phosphodiesterase
family member 2 |
35 |
0.36485 |
0 |
1.0093 |
0.7491 |
|
P39060 |
COIA1 |
Collagen alpha-1(XVIII) chain |
8 |
0.35235 |
0.0136 |
0.9477 |
0.8467 |
|
P04264 |
K |
Keratin, type II cytoskeletal 1 |
25 |
0.3503 |
0.025 |
1.0741 |
0.5077 |
|
P10745 |
RET3 |
Retinol-binding protein 3 |
49 |
0.3321 |
0.0429 |
1.0636 |
0.3677 |
|
P41222 |
PTGDS |
Prostaglandin-H2 D-isomerase |
90 |
0.27485 |
0.0029 |
0.8184 |
0.3224 |
|
Q9BU40 |
CRDL1 |
Chordin-like protein 1 |
6 |
0.20485 |
0.1811 |
0.8155 |
0.2359 |
|
O15537 |
XLRS1 |
Retinoschisin |
6 |
0.18485 |
0.0263 |
0.8013 |
0.7073 |
|
P16035 |
TIMP2 |
Metalloproteinase inhibitor 2 |
3 |
0.15235 |
0.1206 |
0.86555 |
0.5001 |
|
Q8N475 |
FSTL5 |
Follistatin-related protein 5 |
8 |
0.12455 |
0.0357 |
0.9159 |
0.9342 |
Fold change: The average of 114:116
and 115:116, represents the differences between dry AMD and control group. Stability
ratio: The average of 117:116 and 116:116, represents the stability of
experimental.
Gene Ontology Analysis of Differentially Expressed
Proteins GO enrichment characterized the DEPs on biological process
(BP), cell components (CC), and molecular function (MF). Each top 10 categories
were calculated based on the protein counts and were shown in Figure 2.
Figure 2 GO enrichment analysis of
DEPs GO enrichment characterized the DEPs on
BP, CC, and MF. Each top 10 categories were calculated based on the protein
counts. The left and right y-axes represent percent of genes and number of
genes, respectively.
For the analysis of BP, majority of
obtained proteins were involved in single-multicellular organism process or
multicellular organismal process. Beyond that, response to stress and external
stimulus accounted for a large proportion with pathological significance. In
the CC analysis, the most of proteins located in extracellular regions and
membrane-bounded vesicles or organelles. In terms of MF, the results indicated
that protein binding is one of the important functions. GO analysis of DEPs
consistent with the known pathogenic mechanism of AMD. Besides, vesicle
mediated transport in BP, extracellular vesicle and exosome in CC suggested
that some specific proteins were related with exosome.
Kyoto Encyclopedia of Genes and
Genomes Pathway Analysis of Differentially Expressed Proteins KEGG enrichment highlighted 15
significantly accumulated pathways involving the DEPs (Figure 3).
Figure 3 KEGG pathway analysis of
DEPs Eleven DEPs which account for 10.09% were
accumulated in the complement and coagulation cascades pathway. The cross
columns refer to different pathways and the longitudinal column refer to
classification of pathways.
Eleven DEPs (10.09%) were
accumulated in the complement and coagulation cascades pathway, and 5 DEPs
(4.59%) were enriched in staphylococcus aureus infection pathway. Moreover, the
enrichment of extracellular matrix (ECM)-receptor interaction pathway (3 DEPs,
2.75%) was observed, which is consistent with the GO enrichment analysis.
Protein-Protein Interaction Network
Analysis PPI analysis displayed the signaling
network and interactions among the DEPs (Figure 4). The result showed that
up-regulated proteins were related to complement and coagulation cascades and
glycolysis/gluconeogenesis, while the down-regulated proteins were involved in
the pathways in protein digestion and absorption.
Figure 4 PPI network PPI analysis displayed the signaling
network between the DEPs. Red dots represent up-regulated proteins and green
dots represent down-regulated proteins. Squares link to proteins represent the
main functions of relevant proteins. Solid lines represent direct relationships
and imaginary lines represent predictive relationships.
Glyceraldehyde-3-phosphate
dehydrogenase, plasminogen, kininogen-1, lysozyme C, and prothrombin tended to
be key regulators in the network of PPI, which deserved further investigation.
Up-regulation of Immuno-inflammatory
Protein in Serum To validate the changes of DEPs
detected by iTRAQ, serum alpha-1-acid glycoprotein 1 (A1AG1, aliases for ORM1
gene) was selected and verified with both Western blot (Figure
Figure 5 Serum A1AG1 protein
detection with Western blot (A) and ELISA (B) Each of five protein samples from dry
AMD group or control group were isovolumetric mixed and detected with Western
blot and ELISA. Con: Serum from control group; AMD: Serum from patients with
dry AMD.
DISCUSSION
AMD is one of the most serious eye
diseases, still lack of effective treatments, especially for its dry form. It
is necessary to find the potential biomarkers for dry AMD to understand the
pathogenesis, predict its progression and prognosis, and find potential
targets, thus to provide effective treatments. The proteomics for biomarkers in
aqueous humor is a valuable method. Because there is evidence that pathological
concentrations of several proteins present in the aqueous fluid are closely
associated with fundus diseases[17].
In this study, total of 244 proteins
were identified, in which 38 proteins were increased significantly in dry AMD patients.
By using bioinformatics analysis (GO enrichment analysis, KEGG pathway, PPI),
we found that immune and inflammation seems to play a major role in the
pathogenesis of AMD. Most of the up-regulated proteins are serum proteins and
primarily involved in physiological and pathological processes including
inflammation and immune reaction, oxidative stress, coagulation process and
formation of the extracellular matrix. From single protein function to pathways
they involved in, and signaling networks constructed from proteins, these
up-regulated proteins provided the clues for the novel targets for dry AMD
treatment.
Immune and Inflammation Related
Proteins The KEGG pathway showed 11 DEPs were
enriched in the complement and coagulation cascades accounting for the largest
part. Most of these proteins were reported to have pro-inflammatory function
and some of them were also found to be up-regulated in AMD patients, e.g.,
Complement C3 (CO3)[18] and Ig gamma-1 chain C region
(IGHG1)[19].
A1AG1, an immune and inflammation
related protein which was found more than five times higher in our study, was
proven to have the immune modulatory function, to decrease the pro-inflammatory
cytokines and reduce the synthesis of cytokines of lymphocytes through changing
its surface properties, thus exert the immune-suppression[15].
As an immune regulator and inflammation inhibitor, A1AG1 might play a
protective role in the pathogenesis of dry AMD. In addition, A1AG1 can be
induced by the acute phase inflammatory reaction[20].
The presence of acute phrase proteins suggested a local temporary inflammation
in the eye of dry AMD patients and persistent inflammation will insult the
retina, resulting in AMD.
To explore the potential biomarkers
for dry AMD, the serum is easier to be obtained than aqueous humor, which was
further considered to be a more practical approach for clinical diagnosis.
Therefore, the blood samples were collected from all patients and up-regulated
A1AG1 level was detected, indicating serum A1AG1 might be a potential biomarker
for dry AMD.
Oxidative Stress Related Proteins Oxidative stress is involved in the
pathological process of AMD, like lipofuscin in retinal pigment epithelium
(RPE) cells was proved to be from oxidatively damaged photoreceptor outer
segments[21]. A series of up-regulated
proteins was found in our study like L-lactate dehydrogenase A chain (LDHA). It
was also reported to be increased in RPE exosomes caused by oxidative stress[22]. Protein S100-A8 with highest expression
level in dry AMD group, its extracellular function involves oxidant-scavenging and
has a protective role in preventing exaggerated tissue damage by scavenging
oxidants. Besides, carbonic anhydrase 3 (CAH3) was found, for the first time,
to be five times higher in AMD group than that in control group. It is regarded
as a scavenger of oxygen free radicals in many studies and has a protective
effect on cells in oxidative stress reaction[23].
Roy et al[24] found that H2O2-induced
apoptosis in fibroblast can be restored when CAH3 expression is forcibly
increased in cells. These facts indicated the causal role of oxidative stress
in the pathogenesis of dry AMD.
Metabolism Related Proteins Macular region is one of the most
active metabolic areas of human body. Maintenance of the homeostasis plays a
prominent role in keeping normal functions. Inter-alpha-trypsin inhibitor heavy
chain H2 (ITIH2) with three-fold increase in AMD group acts as a carrier of
hyaluronan in serum or as a binding protein between hyaluronan and other matrix
protein. Hyaluronan is the main component of ECM, which associated with ITIH2
might be involved in the pathological process of AMD. Up-regulation of
hyaluronan means the activation of cells and tissues remodeling of
physiological or pathological processes[25], and
the remodeling of ECM plays an important role in the pathological process of
AMD patients. The development of drusen, changes in the Bruch membrane and the
infiltration of immune cells are all related to the remodeling of dense or loose
extracellular structures[7]. It can be speculated
that the up-regulation of ITIH2 destabilize the ECM environment by affecting
the production of hyaluronan, thus promoting the development of AMD. Beyond
this, proteins of actin, cytoplasmic 2 (ACTG) and zinc-alpha-2-glycoprotein (ZA
AMD is caused by multiple factors,
utilizing the proteomics technology to look for biomarkers can help us to
elucidate the pathogenesis of this disease and screen the novel targets. By
comparing the protein abundance spectra of the same tissue under physiological
and pathological conditions, we can identify DEPs, facilitating early diagnosis
and potential targets screening. The result of confirmatory discovery in serum
bring us a reflect on whether AMD is a systemic disease or a local lesion, but
the answer is still debated. Multiple factors may interact each other in the
development of dry AMD. By applying different treatments for potential targets,
the progress of the disease could be regulated, meanwhile the therapeutic
effect and prognosis can be evaluated. Although the limitations exist, such as
small sample size caused by difficulty in obtaining samples, the present study
reported the differential expressions of proteins in the aqueous humor, which
could provide a clue for the elucidating the pathogenesis of dry AMD as well as
the potential therapy to targeting these biomarkers.
ACKNOWLEDGEMENTS
Thanks to
all the contributions of authors. Qu SC performed the experiments, analyzed the
data, interpreted results and wrote the manuscript. Xu D collected the sample.
Li TT participated in data analyses. Liu F designed the experiment, analyzed
and discussed the data, played an important role in interpreting the results
and approved the final version. Zhang JF designed the experiment, analyzed and
discussed the data, and revised the manuscript.
Foundations: Supported by National Natural
Science Foundation of China (No.81570852); the Shanghai Municipal Health and
Planning Commission Foundation (No.201540046).
Conflicts of
Interest: Qu SC,
None; Xu D, None; Li TT, None; Zhang JF, None; Liu F, None.
REFERENCES