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Primary congenital glaucoma (PCG) refers to the
disease condition that results from the elevation of the intraocular pressure
due to obstruction of aqueous outflow by an isolated maldevelopment of the
aqueous outflow pathways (Stamper RL, Lieberman MF, Drake MV. Developmental and childhood glaucoma. In: Stamper RL, Lieberman MF, Drake MV, eds. Becker-Shaffer’s
Diagnosis and Therapy of the Glaucomas, 8th ed. Amsterdam: Mosby, Elsevier;
2009:294-329.). The clinical features of the disease encompass the
causative pathology of goniodysgenesis –detected by gonioscopy- as well as the
secondary effects in the eye, including elevated intraocular pressure (IOP),
enlarged –possibly cloudy- cornea with a broad limbus, a deep anterior chamber (AC)
–readily accessible for aqueous humour (AH) sampling- and an enlarged axial
length, among others (Fernandez LM, Martinez-de-la-Casa JM, Garcia-Bella J,
Mendez C, Saenz-Frances F, Garcia M, Escribano J, Garcia-Feijoo J. Clinical
Variability of Primary Congenital Glaucoma in a Spanish Family With Cyp1b1 Gene
Mutations. (J Glaucoma 2015;24:630–634).

The eye develops in utero as an outpouching of the
forebrain that forms the primitive optic vesicle. The anterior segment of the
eye is a descriptive term for the part of the eye that includes and lies
anterior to the pars plicata of the ciliary body. This anterior segment of the
eye develops from all 3 germ layers of the embryo, namely surface ectoderm,
mesoderm, endoderm, as well as neural crest cells (Abdo,
M., Haddad, S. and Emam, M. (2017), Development of the New Zealand White Rabbit
Eye: I. Pre- and Postnatal Development of Eye Tunics. Anat. Histol. Embryol.,
46: 423–430. doi:10.1111/ahe.12284423–430. doi:10.1111/ahe.12284). The
angle of the AC and specifically the trabecular meshwork (TM) develops from
neural crest cells that invade the area of the angle of the AC around the
second gestational month (Seefelder R, Wolfrum (1906) Zur Entwicklung der
Vorderen Kammer und des Kammerwinkels beim Menschen nebts Bemerkungen uber ihre
Entstehung bei Tieren. Grafes Arch Ophthl 63:430–451). Development of the
anterior segment of the eye is under the influence of a number of genes through
their secretory proteins, including PAX6, PAX2, BMP4 and the sonic hedgehog
protein, just to name some (Lupo G, Andreazzoli M, Gestri G, Liu Y, He RQ, Barsacchi G. Homeobox genes in the genetic control of eye
development. Int J Dev Biol. 2000;44(6):627-36.).

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The composition of the aqueous humour (AH) includes
electrolytes, organic solutes, growth factors, cytokines, and proteins (To CH, Kong CW, Chan CY, Shahidullah
M, Do CW. The mechanism of aqueous humour formation. Clin Exp Optom.
2002;85:335–349, Freddo TF. The Glenn A. Fry Award Lecture 1992: aqueous humor
proteins: a key for unlocking glaucoma? Optom Vis Sci. 1993;70:263–270, McLaren JW, Ziai N,
Brubaker RF. A simple three-compartment model of anterior segment kinetics. Exp
Eye Res. 1993;56:355–366), the concentration of the later being quite small, in the range of 120 to
500 ng/?L and although derived from plasma proteins, are structurally and
functionally different. Little is known about the protein composition of the AH,
with less than 150 proteins identified so far by different techniques including
differential protein expression and Multidimensional Protein Identification
Technology (MudPIT) (Richardson MR, Price MO, Price FW, et al. Proteomic
analysis of human aqueous humor using multidimensional protein identification
technology. Mol Vis. 2009;15:2740–2750). One robust method currently available
to analyse peptides, proteins and most other biomolecules –up to the femtomole
level– is the Matrix-assisted laser desorption/ionization time-of-flight mass
spectrometry (MALDI-TOF-MS) (Matrix-assisted Laser Desorption/Ionization Mass
Spectrometry in Peptide and Protein Analysis

J. Kathleen Lewis, Jing Wei,
and Gary Siuzdak in Encyclopedia of Analytical Chemistry R.A. Meyers (Ed.) pp.
5880-5894 . John Wiley & Sons Ltd, Chichester, 2000, Int J Med Sci. 2011; 8(1): 39–47. MALDI-TOF MS
Combined With Magnetic Beads for Detecting Serum Protein Biomarkers and
Establishment of Boosting Decision Tree Model for Diagnosis of Colorectal
Cancer, Chibo Liu, Chunqin Pan, Jianmin Shen, Haibao Wang, and Liang Yong, Lin Wang, Chuanhao
Tang, Bin Xu, Lin Yang, Lili Qu, Liangliang
Li, Xiaoyan Li, Weixia Wang, Haifeng Qin, Hongjun Gao. Mass
spectrometry-based serum peptidome profiling accurately and reliably predicts
outcomes of pemetrexed plus platinum chemotherapy in patients with advanced
lung adenocarcinoma

PLOS, Published: June 8, 2017). MALDI-TOF-MS
utilizes matrix-assisted laser desorption ionization of functionalized magnetic
beads to provide high sensitivity mass analyses to separate the different
protein components of a study sample (F. Magni, Y. E. M. van der Burgt,
C. Chinello et al. Biomarkers discovery by peptide and protein profiling in
biological fluids based on functionalized magnetic beads purification and mass
spectrometry,” Blood Transfusion, vol. 8, no. 3, pp. s92–s97, 2010. J. F. Peter
and A. M. Otto, “Magnetic particles as powerful purification tool for high
sensitive mass spectrometric screening procedures,” Proteomics, vol. 10, no. 4,
pp. 628–633, 2010.). Highly
consistent high-throughput is assured by automated use of these magnetic beads.

The AH is the secretory product of the non-pigmented
ciliary epithelium of the ciliary body (Civan MM, Macknight AD. The ins and outs of aqueous humour secretion. Exp
Eye Res. 2004 Mar;78(3):625-31.). Its composition is a function of
the ciliary body as well as of the other structures of the anterior segment of
the eye consuming and producing different compounds according to their
functions and normal metabolism (Goel M, Picciani RG, Lee RK, Bhattacharya SK.
Aqueous Humor Dynamics: A Review. The Open Ophthalmology Journal.
2010;4:52-59. doi:10.2174/1874364101004010052.). The AH as such could be viewed as
the tissue fluid of the anterior segment of the eye. Having said so, it would
be reasonable to hypothesise that the AH composition could be an indicator of
the anterior segment development and functioning, and studying the composition
of this majestic fluid is likely to yield valuable information about the
anterior segment of the eye, and proteins are but one component of the AH that
can be studied for this aim. Hence, the aim of this study was to study the
proteomic profile of AH in a number of PCG children using 
MALDI-TOF MS and SPE and compare this to a control group of as
nearest as possible –at least hypothetically- to the normal AH composition. We
present here a preliminary report of the study findings.

Materials and Methods

Patients and samples

The study was conducted on 37 eyes of 37 children
with the diagnosis of PCG that presented to and were operated upon in Alexandria
Main University Hospital, Alexandria, Egypt. These PCG children were designated
as ‘cases’. Additionally, 22 eyes of 22 patients undergoing surgery for senile
cataract were included in the study and were designated
as ‘controls’. These control patients were otherwise generally normal. For all
study patients, the sampling technique was the same. After the administration
of general anaesthesia, prepping of the skin with 10 % povidone iodine and
adequate surgical draping, an initial paracentesis is made into the AC using a
supersharp blade. Then, a tuberculin syringe fitted onto a 27 gauge needle is used
to puncture the cornea, tangential to the limbus, to enter the AC and withdraw
0.1 ml of AH. The AC is then inflated with balanced salt solution (BSS) through
the initial paracentesis and the planned surgical procedure continued. The
withdrawn sample of AH was immediately emptied into an Eppendorf tube which was
closed and sealed firmly and transferred in ice immediately to the laboratory, where
it was aliquoted into 20 uL samples and stored at -80 °C.

A pilot study on 10
patient and 10 control samples was first conducted to choose between
hydrophobic interaction and weak cation exchange chromatography magnetic beads.
Hydrophobic interaction chromatography C8 beads produced more peaks and
achieved better cross validation and recognition capability. Patients and
controls were then stratified into the training and validation sets. The
training group was used to develop peptide models that could discriminate
patients from controls. The validation group was then used to test the
predictive power of the model derived from the training set.

 

Sample
preparation and mass analysis (peptide profiling)

Using magnetic beads based on Hydrophobic
Interaction Chromatography (MB-HIC8, Bruker Daltonics Inc., Bremen, Germany) AH
samples were thawed on ice and fractionated before mass spectrometry (MS)
analysis, which was conducted in the period from January to September 2017.
These magnetic beads have good peptide-capturing performance and were used for
protein and peptide enrichment of AH samples according to the manufacturer’s
instructions. We added 20 ?L of the AH sample to 40 ?L of binding buffer then 5
?L of MB-WCX beads in a polymerase chain reaction tube which was  placed on a magnetic separator to isolate the unbound solution after careful mixing and incubation for 1 minute. The bound peptides were eluted from
the magnetic beads after three rounds of bead separation and washing. Finally,
1 ?L of the peptide eluate was mixed with 1 ?L of HCCA matrix (1.2mg of ?-Cyano-4-hydroxycinnamic
acid in 50% acetonitrile with 1% trifluoroacetic acid), which was then spotted
onto the sample anchor spots of a polished steel target plate (Bruker Daltonics
Inc., Bremen, Germany). The following settings were used for the MALDI-TOF MS
analyses on an Ultraflex III MALDI-TOF MS device (Bruker Daltonics Inc.): linear
positive ion mode, repetition rate of 200 Hz, ion source voltages of 25 kV and
23.65 kV, lens voltage of 6.8 kV, pulsed ion extraction time of 300 ns. All
signals with a signal-to-noise ratio of 3 in a mass range of 1,000–20,000 Da
were recorded using FlexAnalysis software (version 3.4; Bruker Daltonics Inc.).
The peptidomic patterns and models were processed using ClinPro Tools
bioinformatics software (version 3.0; Bruker Daltonics Inc.). The
Anderson-Darling test was used for testing for specific distributions in the
training group. Subsequently, peptide peaks, expressing the same mass-to-charge
ratios (m/z) were compared between the patients and controls using Wilcoxon
test for nonparametric data and t-test for parametric data. The ClinPro Tools
3.0 software package (Bruker Daltonics) was used to analyze all serum sample
data derived from the training set. The peptidome MS data from the patients and
controls in the training set were compared. Using ClinPro and to establish the
prediction models, tools data from the training set were subjected to three
different mathematical model algorithms: the Genetic Algorithm (GA), Supervised
Neural Network (SNN), and Quick Classifier (QC). Subsequently, each model was applied
to the validation set to test its ability to identify patients and controls.

 

Data
processing and statistical analysis

The
ClinPro Tools software was used for the data processing and analysis according
to the following workflow: spectra were normalized, baseline subtracted, peaks
smoothed and peak areas were calculated for each spectrum. All peak signals
were processed for noise reduction using a top-hat baseline in the 800–20,000
Da range.

The
expressions of the same mass-to-charge ratios (m/z) for the peptide peaks were
compared between the patients and controls. Spectra of the training set were
used for model construction. Three algorithms (genetic algorithm GA,
supervised neural networks SNN, and quick classifier QC) were used to
establish the prediction models. Each model was then applied to the validation
set to test its ability to identify patients and controls.

Patient
characteristics

The
study included 56 subjects which were equally divided (28 subjects each) into
training and validation groups, stratified as 17 patients and 11 controls in
each group. The demographic and clinical characteristics of the study subjects
are presented in Table 1.

Comparison
of peptidomic data

The
ClinPro Tools 3.0 software package identified 109 peptide peaks of which 69 (63%)
had significantly different intensities between the 2 groups as shown in figure
1. The pseudogel view of the results is presented in figure 2.

Construction
of predictive peptide models in the training set

The
performances of the three models, which were assessed by considering the
cross-validation and recognition capability, are presented in table 2. The QC
algorithm yielded the best results and was used to set a prediction model, and
a peptidome pattern classification was constructed. This model generated eight
significantly different peaks at m/z 4257.84, 4307.89, 4896.5, 4938.35, 5569.3, 7345.89, and 9493.65
Da, which provided a recognition capability of 82.1% and cross-validation value of 81.1% as presented in table 3. Seven peptides were over-expressed
in PCG patients; m/z 4257.84, 4307.89, 4896.5, 4938.35, 5569.3, 5583.12 and 9493.65 Da while only one peak was
under-expressed in patients; m/z 7345.89
Da. This classification model correctly identified 71.3% of PCG patients and 90.9%
of controls in the training set (Table 3 and Figure 3). The peaks
achieved areas under the curve of 0.824641, 0.804611, 0.860922, 0.818216,
0.830688, 0.866213, 0.804233 and 0.812925 respectively. (Figure 4)

Testing
of the predictive peptide model in the validation set

The
peptide prediction model thus established was tested in the validation set of
28 samples in a blinded manner. The model successfully classified 80.3 % as the
patients and 82.9% as the controls in the validation set (Table 4).

Diagnosis of PCG is largely
clinical, and the molecular mechanisms underlying the responsible genetic
defects are not clearly understood so far. The concept of biological markers,
many of which are proteins, has facilitated and improved the accuracy of disease
diagnosis in recent years as well as directing treatment regimens in some cases
(Pandey
A, Mann M. Proteomics to study genes and genomes. Nature.2000 Jun
15;405(6788):837-46.). Besides, studying the composition of AH might shed light on the
expression of genes involved in the development of the anterior segment of the
eye. Indeed, relative quantification of protein expression has been made possible
through gel-based and gel-free techniques of protein analysis using mass
spectrometry and isotope labeling-based or label-free techniques. The aim of
the current study was to characterise the protein content of AH in eyes with
PCG. A preliminary report is presented herein. The study identified 109 protein
peaks of which 63 % were different between PCG patients and controls. There
have been published reports about the protein content of AH in primary open
angle glaucoma (Grus, F.H., Joachim, S.C., Sandmann, S., Thiel, U., Bruns, K., Lackner,
K.J., Pfeiffer, N.,2008.Transthyretin and complex protein pattern in aqueous
humor of patients with primary open-angle glaucoma. Mol. Vis. 14, 1437e1445.), uveitic glaucoma
(Ladas,
J.G., Yu, F., Loo, R., Davis, J.L., Coleman, A.L., Levinson, R.D., Holland,
G.N., 2001. Relationship between aqueous humor protein level and outflow
facility in patients with uveitis. Invest. Ophthalmol. Vis. Sci. 42, 2584e2588.) and myopia (Duan, X., Lu, Q.,
Xue, P., Zhang, H., Dong, Z., Yang, F., Wang, N., 2008. Proteomic analysis of
aqueous humor from patients with myopia. Mol. Vis. 14, 370e377.) (Kliuchnikova AA,
Samokhina NI, Ilina IY, Karpov DS, Pyatnitskiy MA, Kuznetsova KG, Toropygin IY,
Kochergin SA, Alekseev IB, Zgoda VG, Archakov AI, Moshkovskii SA. Human aqueous
humor proteome in cataract, glaucoma, and pseudoexfoliation syndrome.
Proteomics. 2016 Jul;16(13):1938-46. doi: 10.1002/pmic.201500423.).

Bouhenni et al (Bouhenni RA, Al Shahwan S, Morales J, Wakim BT, Chomyk AM, Alkuraya FS, Edward DP. Identification of
differentially expressed proteins in the aqueous humor of primary congenital
glaucoma. Exp Eye Res. 2011
Jan;92(1):67-75. doi: 10.1016/j.exer.2010.11.004. Epub 2010 Nov 13.) attempted to identify
proteins that may be altered in PCG. The report by Bouhenni et al included 7
PCG cases and 4 controls. To the best of the authors’ knowledge, the number of
cases and controls reported in the current study is the biggest so far
published. The identification of 109 different peaks in AH samples highlights
the diversity of the protein content of AH; and confirms the notion that
although the protein content of AH is quite minute under normal conditions, it
is quite diverse in its constituents. The fact that 63 % of protein peaks were
different between cases and controls points out how different AH protein composition
can be in PCG cases from older controls. This difference could be attributed to
either a difference in age between cases and controls or to the presence of the
pathology of PCG in the cases. In this context it is important to emphasize a very
crucial limitation in the current study and similar studies involving the same
pediatric age group; the practical impossibility to sample true controls for
accurate comparison in the study. The authors draw the attention that true
controls are children of the same age group and who are ophthalmologically
totally free. Obviously, for ethical reasons, such sampling is practically
impossible. Hence, the authors of this study (and similar studies involving
pediatric patients) are obliged to include as controls adults with senile cataract,
assuming the AH composition to be the closest to the normal, though the age range
difference remains an issue.

In the current
study, the QC algorithm provided the best result as a prediction model. The efficacy
of the QC algorithm as a prediction model is in accordance with the studies by Li
et al (Li, B., Li, B., Guo, T., Sun, Z., Li, X.,
Li, X., … Mao, Y. (2017). Application Value of Mass Spectrometry in the
Differentiation of Benign and Malignant Liver Tumors. Medical
Science Monitor?: International Medical Journal of Experimental and Clinical
Research, 23, 1636–1644. http://doi.org/10.12659/MSM.901064.
) and Fan et al (Fan, N.-J., Gao, C.-F., Wang,
X.-L., Zhao, G., Liu, Q.-Y., Zhang, Y.-Y., & Cheng, B.-G. (2012). Serum
Peptidome Patterns of Colorectal Cancer Based on Magnetic Bead Separation and
MALDI-TOF Mass Spectrometry Analysis. Journal of Biomedicine and Biotechnology, 2012, 985020. http://doi.org/10.1155/2012/985020.
). Studying the protein peaks in the cases revealed 7 out of 8 peptides that
are over-expressed in PCG eyes. It remains to be proven whether these peptides
represent over-expression of genes that regulate development of the anterior
segment of the eye or the angle of the anterior chamber and that should have
been suppressed or down-regulated during normal development, or whether they
represent metabolic bi-products of structures of the anterior segment of the
eye under the stressful situation of elevated IOP. After all, PCG is the
clinical result of goniodysgenesis, and exhibits an elevated IOP as an important
pathology. The significance of the under-expressed peak remains to be
elucidated as well. It is hoped that identification of these peptide peaks and
characterisation of these proteins would help in a better understanding of the
dysgenetic process responsible for PCG. This knowledge, substantiated with
knowledge of the genetic backgrounds of gene mutations in PCG, and perhaps with
a study of the transcriptomics in PCG, might present hope for proper genetic
counselling and possible gene therapy in the near future. The limitation of
this preliminary report is already highlighted which is the nature of the
controls being in a different age group and demonstrating an obvious age
related disease in the eye. The excuse –as explained- is the ethical issue of
sampling a normal eye of a child.

In conclusion,
AH of children with PCG is significantly different from the AH of adult
patients, with the majority of proteins over-expressed in PCG eyes.

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