Serum Proteomic Profile of Women Undergoing Assisted Reproduction Technology and its Relation to the Outcome
by Vasiliki Kanaka1,2, Efterpi Bouroutzika2, Stavros Proikakis2, Konstantinos Vougas2, Nikos Kanakas3, Dimitrios Loutradis1, Nikolaos Thomakos1, Aikaterini Ntomali1, Petros Drakakis4, George Th. Tsangaris2*
1First Department of Obstetrics and Gynecology, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece.
2Proteomics Research Unit, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
3Embryoland IVF Clinic, Athens, Greece.
4Third Department of Obstetrics and Gynecology, School of Medicine, National and Kapodistrian University of Athens, Attikon Hospital, Athens Greece.
*Corresponding author: Prof. George Th. Tsangaris, Biomedical Research Foundation, Academy of Athens (BRFAA), 4 Soranou Ephessiou Street, 11527, Athens, Greece.
Received Date: 28 February 2024
Accepted Date: 4 March 2024
Published Date: 6 March 2024
Citation: Kanaka V, Bouroutzika E, Proikakis S, Vougas K, Kanakas N, et al. (2024) Serum Proteomic Profile of Women Undergoing Assisted Reproduction Technology and its Relation to the Outcome. Gynecol Obstet Open Acc 8: 189. https://doi.org/10.29011/2577-2236.100189.
Abstract
Infertility is a major public health issue estimated to affect between 8% and 12% of couples globally. Despite the continuous improvements in the assisted reproduction technology (ART) field the success rates still remain modest. Proteomics can identify and quantify overall proteins within a cell, tissue or an organism. As such they can identify alterations in the expression of key proteins (biomarkers) which could then be utilized for prediction of the outcome of an ART cycle, for prevention of an unsuccessful attempt and for monitoring of the cycle in a personalized manner in order to achieve the desirable outcome. Our study examined the serum proteomic profile of women undergoing ART cycle and its relation to the ART outcome. A total of 62 differentially expressed proteins were identified. In our study we found that Vitamin D, Complement C3, Complement C4 and APOA1 may play a crucial role in the in vitro fertilization (IVF) outcome.
Keywords: Proteomics, Assisted Reproduction Technology, In Vitro Fertilization, Vitamin D, Complement C3, Complement C4, APOA1.
Introduction
Infertility is a major public health issue estimated to affect between 8% and 12% of couples globally (1). The actual definition of infertility is the inability to achieve a pregnancy after 12 months or more of regular unprotected sexual intercourse. Infertility can either be primary, when no pregnancy has been achieved before by a person , or secondary when at least one prior pregnancy has been achieved (2). However, the rapidly developing field of assisted reproduction technology (ART) has been an enormous asset for people struggling with infertility. Currently, ART is practiced in over one hundred countries and ART cycles have increased from around 140,000 in 1991 to over 3.2 million in 2018. Approximately 670,000 infants were born in 2018 from ART practices, while around 60 million ART cycles have been performed since the birth of the first IVF baby, Louise Brown in 1978, resulting in approximately 10 million infants (3).
Despite the continuous improvements in the ART field the success rates still remain modest, with only 25%-30% of the cycles resulting in a live birth (4). Therefore, various methods are applied in order for higher success rates to be achieved. The recent developed field of proteomics could be considered a promising addition to the armamentarium of tools available to combat lower success rates and as a result global infertility. Proteomics can identify and quantify overall proteins within a cell, tissue, or an organism. As such they can identify alterations in the expression of key proteins (biomarkers) which could then be utilized for the prediction of the outcome of an IVF cycle, they could prevent an unsuccessful attempt and monitor the cycle in a personalized manner in order to achieve the desirable outcome. This approach is the main scope of predictive, preventive, and personalized medicine (5,6).
Materials and Methods
Study Group and collection
The population under study consisted of 22 women undergoing an ART cycle in the IVF University Clinic of Alexandra Hospital in Athens, Greece which was working in collaboration with Embryoland IVF Clinic, Athens, Greece. The study was approved by the 574/21.09.2018 of the Greek National Authority of Assisted Reproduction and all the women included in the study provided informed consent. From each woman four total blood samples were collected, one earlier than the beginning of the fertility medication, one at the time of embryo transfer (ET) day, one 6 days after ET and one 12 days after ET. Out of the 22 women, 15 achieved implantation and/or pregnancy (successful cycles) and 7 did not (unsuccessful cycles). The inclusion criteria were as follows: (i) woman’s age between 28 and 42 years; (ii) absence of uterine or endometrial conditions (myomas, polyps, malformations, endometritis, thin endometrium); (iii) absence of hydrosalpinx; (v) no infectious risk; (vi) transfer on day 5 of 1–2 fresh embryos, at least one being of good quality; and (vii) fresh own oocyte cycles without preimplantation genetic diagnosis or testicular biopsy. The ART cycle was performed either with IVF or intracytoplasmic sperm injection (ICSI) method, depending on the infertility cause. The demographic and clinical characteristics of the study population are detailed in Table 1. The indications for IVF were male factor (50%), female (32%), and unexplained infertility (23%).
Table 1. Demographic and Clinical characteristics of the recruited patients undergoing ART program.
Sample |
Race |
Age |
Infertility cause |
Number of attempts |
Number of oocytes retrieved |
Sperm (millions) |
Fertilization method |
Pregnancy |
Outcome |
1 |
Caucasian |
33 |
Oligoasthenospermia |
1 |
14 |
5 |
ICSI |
- |
- |
2 |
Caucasian |
36 |
Unovulation |
3 |
2 |
100 |
ICSI |
+ |
1 infant |
3 |
Caucasian |
31 |
Unexplained |
1 |
11 |
29 |
ICSI + IVF |
+ |
Miscarriage |
4 |
Caucasian |
38 |
Unexplained |
1 |
4 |
137 |
ICSI |
+ |
Biochemical |
5 |
Caucasian |
37 |
Unovulation |
3 |
4 |
84 |
ICSI |
+ |
1 infant |
6 |
Caucasian |
31 |
Blocked tubes/asthenospermia |
1 |
5 |
40 |
ICSI |
+ |
1 infant |
7 |
Caucasian |
36 |
Severe asthenorspermia |
5 |
6 |
Donor sperm |
IVF |
+ |
1 infant |
8 |
Caucasian |
42 |
Unexplained |
1 |
8 |
32 |
ICSI |
- |
- |
9 |
Caucasian |
35 |
Asthenospermia |
1 |
11 |
18 |
ICSI |
- |
- |
10 |
Caucasian |
36 |
Oligospermia |
3 |
7 |
1,7 |
ICSI |
+ |
1 infant |
11 |
Caucasian |
35 |
Tubal factor |
1 |
5 |
80 |
ICSI |
+ |
2 infants |
12 |
Caucasian |
32 |
Bad oocyte quality |
1 |
3 |
112 |
IVF |
- |
- |
13 |
Caucasian |
30 |
Unexplained |
2 |
7 |
2 |
ICSI |
- |
- |
14 |
Caucasian |
32 |
PCOS |
4 |
4 |
13 |
ICSI |
+ |
miscarriage |
15 |
Caucasian |
37 |
Unexplained |
1 |
7 |
17 |
ICSI |
+ |
1 infant |
16 |
Caucasian |
37 |
Asthenospermia |
3 |
2 |
39 |
ICSI |
+ |
1 infant |
17 |
Caucasian |
35 |
Asthenospermia |
1 |
11 |
58 |
ICSI |
+ |
1 infant |
18 |
Caucasian |
35 |
Asthenospermia |
1 |
4 |
41 |
ICSI |
+ |
1 infant |
19 |
Caucasian |
33 |
Asthenospermia |
1 |
3 |
18 |
ICSI |
+ |
1 infant |
20 |
Caucasian |
40 |
Asthenospermia |
1 |
3 |
35 |
ICSI |
- |
- |
21 |
Other |
28 |
Asthenospermia |
1 |
10 |
2 |
ICSI |
+ |
1 infant |
22 |
Caucasian |
42 |
Bad oocyte quality |
1 |
1 |
32 |
ICSI |
- |
- |
Sample collection
Our standard IVF protocol has been described previously. Briefly, it consists of a conventional antagonist protocol, ovarian stimulation being performed with only recombinant follicle-stimulating hormone (rFSH). Ovulation was triggered with recombinant human chorionic gonadotropin (rec hCG) (Ovitrelle, Merck) when ≥ 3 follicles ≥ 18.5 mm were observed. Oocyte retrieval was scheduled 36 h after triggering ovulation. After IVF/ICSI was performed, embryos were frozen. The luteal phase was supported by progesterone 200 mg every 8 h, starting from day 13-14 where the endometrium was ≥ 8mm. The hormone was administered vaginally. In all the artificial cycles 6mg/day of estradiol was also administered orally from the 3rd day of menstruation.
Sample preparation
In total, four blood samples were collected from each patient. More precisely, the first sample was collected prior to the beginning of the ART program, the second at the day of ET, the third 6 days post ET and the fourth 12 days post ET. Following centrifugation at 3000g for 5 minutes, serum was collected and stored at -80˚C until use. The protein concentration was determined with a Bioanalyzer system (Agilent Technologies Inc., Waldbornn, Germany), using Protein 200 plus kit (Agilent Technologies Inc.).
Two-dimensional gel electrophoresis (2-DE)
Two-dimensional gel electrophoresis (2-DE) was performed as previously described (7). The gel images were scanned in a GS800 Calibrated Densitometer (Bio-Rad, Hercules, CA, USA). The images were stored in digital format for further analysis.
Protein Visualization and Image analysis
PD-Quest v8.o image processing software (Bio-Rad) was used for the detection, alignment, matching and quantification of the protein spots, in all the gels that were analyzed, according to the manufacturer’s instructions. In order to verify the accuracy of matching, manual inspection of the spots was done. Protein expression was quantified by spot volume. After subtraction of the background values, normalization of the protein spots was carried out according to the total quantity of the valid spots. Optical density (O.D.) level (%) of each protein from the 4 groups of the quartets was determined separately and calculated as the sum of the percentage volume of all spots from the gels containing the same protein. The protein spot selection for MS identification was based on the O.D. alterations observed between the four groups.
Protein identification by MALDI -TOF-MS
For the analysis of the serum proteins, MALDI-TOF-MS analysis was performed as previously described (7). The matching of peptides as well as the protein searches were performed automatically with the use of MASCOT Server 2 (Matrix Science). The peptide masses were compared with the theoretical peptide masses of all available proteins from the Homo sapiens in the SWISS -PROT and TremBL databases.
Stringent criteria were used for protein identification with a maximum allowed mass error of 25 ppm and a minimum of four matching peptides. Probability score with p < 0.05 was used as the criterion for affirmative protein identification. Monoisotopic masses were used, and one missed trypsin cleavage site was calculated for proteolytic products. Search parameters included potential residue mass modification for carbamidomethylation and oxidation. Redundancy of proteins that appeared in the database under different names and accession numbers was eliminated. If more than one protein was identified under one spot, the single protein member with the highest protein score was singled out from the multiprotein family. MASCOT search score is −10 log (p), where p is the probability that an observed match is a random event. Scores >50 indicate identity or extensive homology at the p<0.05 level.
Verification methods
Four proteins were further measured in the same serum samples using automated methods. The methods have previously been described (8,9). More specifically, vitamin D was measured with automated chemiluminescence immunoassay (CLIA) method on Atellica® IM Analyzer (Siemens Healthineers Tarrytown, NY 10591 USA), while Complement C3, Complement C4 and APOA1 proteins were measured with automated immunoturbidimetric assay on Atellica® CH Analyzer (Siemens Healthineers Tarrytown, NY 10591 USA).
Statistical analysis
In order to ensure confidence in our experiments, we used an experimental design based on quadruple 2-DE gels per patient and separate preparations per experiment. Comparisons were performed between samples (pre-IVF medical treatment, ET day, 6 days post ET, 12 days post ET of pregnant and nonpregnant individuals). Mean densitometric values of all spots corresponding to a specific protein from each group were first checked for normal distribution using unequal variances. Data with normally distributed densitometric values were exported to Microsoft Excel 2019 software (Microsoft Corp., Redmond, WA, USA) and compared with the two pair t-test assuming unequal variance. Means of spot intensities for proteins with non-normally distributed values were compared for statistical significance with the Mann-Whitney nonparametric test (GraphPad Instant 3 software: GraphPad Software Inc., La Jolla, CA, USA). Statistical significance (alpha-level) was defined as p<0.05.
Statistical significance of protein quantification by CLIA method and immunoturbidimetric assay was performed by the use of student t-test of the quantity values of each protein. Mean values of the samples from the four different days (pre-IVF treatment, ET, 6 days post ET, 12 days post ET) were compared between successful and unsuccessful cycles by the t-test. Statistical significance was defined as p<0.05.
Results
Figure 1 shows the types of comparisons that our study focused on. Figure 2 represents a quartet of the 2DE-gels of a pregnant and a non-pregnant woman. Table 2 represents the differentially expressed proteins that were found in our study. Functional relationships analysis of the differentially expressed proteins was performed using the STRING v.10 database (Search Tool for the Retrieval of Interacting Genes/Proteins, http://stringdb.org). Figure 3 and 4 show the functional relationships of the differentially expressed proteins in pregnant and non-pregnant women. The PANTHER database was used to reveal the biological function of each identified protein which are represented in figure 5 and 6 (http://panther.appliedbiosystems.com/). APOA1, Complement C3, Complement C4, and Vitamin D blood serum levels, after verification methods were performed, are represented in figures 7-10. Figures 11-14 each represent the mean levels of each protein at the four different days in pregnant and non-pregnant individuals together.
Figure 1. Types of comparisons of the differential protein expression in serum samples of women who achieved pregnancy (orange color) and women that did not achieve pregnancy (blue color) after an IVF cycle. ET: Embryo Transfer.
Figure 2. 2-DE Gel images with differentially expressed spots. I: A quartet of samples in the first row are the gels from a pregnant woman: a. prior to IVF treatment, b. on ET day, c. 6 days post ET and d. 12 days post IVF. II: Second row represents a quartet of the samples of a non-pregnant woman: a. prior to IVF treatment, b. on ET day, c. 6 days post ET and d. 12 days post IVF.
Table 2. Differentially expressed proteins (DEPs).
Full protein name |
Abbreviation |
Mascot Score |
Coverage |
Protein MW |
pI |
Afamin |
AFAM |
52 |
7 |
70963.00 |
5.60 |
Albumin |
ALBU |
55 |
14 |
71317.00 |
5.90 |
Alpha-1-antitrypsin |
A1AT |
76 |
16 |
46878.00 |
5.30 |
Alpha-1B-glycoprotein |
A1BG |
89 |
31 |
54790.00 |
5.50 |
Alpha-2-macroglobulin |
A2MG |
59 |
13 |
164613 |
6.02 |
Alpha-ketoglutarate-dependent dioxygenase alkB homolog 2 |
ALKB2 |
46 |
30 |
29475 |
10.28 |
Angiotensinogen |
ANGT |
102 |
26 |
53406.00 |
5.90 |
Antithrombin-III |
ANT3 |
129 |
35 |
53025.00 |
6.30 |
Apolipoprotein A-I |
APOA1 |
246 |
62 |
30759.00 |
5.50 |
Apolipoprotein A-IV |
APOA4 |
134 |
26 |
45371.00 |
5.20 |
Apolipoprotein E |
APOE |
130 |
38 |
36246.00 |
5.50 |
Beta-2-glycoprotein 1 |
APOH |
61 |
25 |
39584 |
9.49 |
CD5 antigen-like |
CD5L |
200 |
57 |
39603.00 |
5.20 |
Ceruloplasmin |
CERU |
140 |
18 |
122983.00 |
5.40 |
Complement C1q subcomponent subunit B |
C1QB |
89 |
34 |
26933.00 |
9.60 |
Complement C1r subcomponent |
C1R |
83 |
17 |
81606.00 |
5.80 |
Complement C1s subcomponent |
C1S |
265 |
39 |
78174.00 |
4.70 |
Complement C3 |
CO3 |
194 |
16 |
188569.00 |
6.00 |
Complement C4-A |
CO4A |
71 |
11 |
194261.00 |
6.70 |
Complement component C6 |
CO6 |
107 |
18 |
108367.00 |
6.40 |
Complement factor B |
CFAB |
55 |
18 |
86847 |
6.74 |
Complement factor H |
CFAH |
96 |
15 |
143680.00 |
6.20 |
G patch domain and ankyrin repeat-containing protein 1 |
GPAN1 |
51 |
22 |
39518 |
9.36 |
Glucosamine-6-phosphate isomerase 2 |
GNPI2 |
54 |
22 |
31293 |
6.50 |
Growth/differentiation factor 2 |
GDF2 |
50 |
15 |
47861 |
6.03 |
Haptoglobin |
HPT |
85 |
25 |
45861.00 |
6.10 |
Hemoglobin subunit beta |
HBB |
224 |
84 |
16102.00 |
6.90 |
Hemoglobin subunit delta |
HBD |
87 |
39 |
16159 |
9.06 |
Hemopexin |
HEMO |
164 |
40 |
52385.00 |
6.60 |
Ig gamma-1 chain C region |
IGHG1 |
64 |
28 |
36596.00 |
9.40 |
Ig kappa chain C region |
IGKC |
87 |
86 |
11773.00 |
5.50 |
Ig mu chain C region |
IGHM |
76 |
16 |
49960.00 |
6.40 |
Ig mu heavy chain disease protein |
MUCB |
65 |
17 |
43543 |
4.99 |
Immunoglobulin gamma-1 heavy chain |
IGG1 |
64 |
14 |
49925.00 |
9.70 |
Immunoglobulin heavy constant gamma 1 |
IGHG1 |
52 |
13 |
45861.00 |
6.10 |
Immunoglobulin kappa constant |
IGKC |
50 |
47 |
11929.00 |
6.10 |
Immunoglobulin lambda constant 1 |
IGLC1 |
51 |
46 |
11512.00 |
9.20 |
Kelch-like protein 23 |
KLH23 |
51 |
16 |
65079 |
5.31 |
Keratin, type I cytoskeletal 10 |
K1C10 |
110 |
26 |
59020.00 |
5.00 |
Keratin, type I cytoskeletal 9 |
K1C9 |
74 |
19 |
62255.00 |
5.00 |
Keratin, type II cytoskeletal 1 |
K2C1 |
60 |
15 |
66170 |
8.82 |
Keratin, type II cytoskeletal 2 epidermal |
K22E |
59 |
16 |
65678 |
8.85 |
Kininogen-1 |
KNG1 |
140 |
25 |
72996.00 |
6.40 |
Leucine-rich alpha-2-glycoprotein |
A2GL |
55 |
12 |
38382.00 |
6.50 |
Parvalbumin alpha |
PRVA |
61 |
56 |
12051 |
4.84 |
Perilipin-4 |
PLIN4 |
55 |
17 |
135204 |
9.73 |
Plasminogen |
PLMN |
77 |
19 |
93247.00 |
7.30 |
Protein AMBP |
AMBP |
109 |
26 |
39886.00 |
5.90 |
Prothrombin |
THRB |
126 |
28 |
71475.00 |
5.60 |
Retinol-binding protein 4 |
RET4 |
86 |
42 |
23337.00 |
5.70 |
S-adenosylmethionine decarboxylase proenzyme |
DCAM |
52 |
29 |
38714.00 |
5.60 |
Serotransferrin |
TRFE |
183 |
26 |
79294.00 |
7.00 |
Serum albumin |
ALBU |
92 |
16 |
71317.00 |
5.90 |
Serum amyloid P-component |
SAMP |
68 |
24 |
25485.00 |
6.10 |
Serum paraoxonase/arylesterase 1 |
PON1 |
83 |
31 |
39877 |
4.96 |
Small ubiquitin-related modifier 3 |
SUMO3 |
51 |
33 |
11687.00 |
5.20 |
Transthyretin |
TTHY |
96 |
63 |
15991.00 |
5.40 |
Tyrosine-protein kinase STYK1 |
STYK1 |
65 |
28 |
48116 |
7.82 |
Uncharacterized protein C11orf70 |
CK070 |
55 |
38 |
31296.00 |
6.40 |
Vitamin D-binding protein |
VTDB |
75 |
28 |
54480.00 |
5.20 |
Vitronectin |
VTNC |
61 |
18 |
55069 |
5.46 |
Zinc finger protein 273 |
ZN273 |
53 |
16 |
66868 |
10.54 |
A total of 62 DEPs were identified. MASCOT score>50 indicate identity or extensive homology at the p<0.05 level.
Figure 3. STRING protein network in pregnant women.