Research Article

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.

9k=

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.

9k=

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.

iy4zDPlEwc6b60HGQSW1PsXTaZYsX6yHhEQiCIHwdAf4HZ0RT1QTOBe4AAAAASUVORK5CYII=

Figure 3. STRING protein network in pregnant women.