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. 2024 Jan-Mar;28(1):78–89. doi: 10.5935/1518-0557.20230044

Immune system cells modulation in patients with reproductive issues: A systematic review approach

Gabriel Acácio de Moura 1,2, Yasmim Mendes Rocha 1,2, Francisca Lariza Damascieira Moura 3, Janaína de Oliveira Freitas 3, João Pedro Viana Rodrigues 1,2, Vanessa Pinheiro Gonçalves 1,2,4, Roberto Nicolete 1,2,4,✉
PMCID: PMC10936913  PMID: 37962966

Abstract

The aim of this study was to carry out a systematic literature review to investigate the main immune cells responsible for implantation failures. We selected papers from PubMed, Embase and Virtual Health Library databases. Eligible articles included publications between January 1, 2010 and April 24, 2022. Inclusion criteria were: observational and case-control studies; and the exclusion criteria were: review papers, letters to the editor, abstracts, animal studies and case reports. We extracted the following information: day of collection, number of patients, control group, age of patients, type of sample used, immune cells and cytokines. As main findings in our mapping, we found that in peripheral blood, CD3+, CD4+, CD8+, CD16+, CD56+, CD57+, CD69+, CD154+, CD158a+, NKp46 cells were increased and the CD4+, CD45+, Foxp3 and NKp46 markers were reduced. From the endometrial biopsies, there was an increase in CD3+, CD4+, CD5+, CD8+, CD16+, CD25+, CD45+, CD56+, CD57+, CD68+, CD127+ and a reduction in CD45+, CD56+, NKp46 and FoxP3 cells. Cytokines found increased in peripheral blood included IL-6, IL-10, IL-17, INF-γ, TGF-ß, TNF-α; while IL-4, IL-6, IL-10, IL-35, FoxP3, TGF-ß, SOCS3 were reduced. As for the biopsies, there was an increase in IL-2, IL-6, IL-17, IL-22, IL-23, INF-A1, INF-B1, INF-γ, TNF-R and a reduction in IL-6, IL-10, INF-γ, TGFß, TNF-α. We concluded that immune cells can be modulated during pregnancy failure, but further studies are needed to elucidate the modulating effect of the immune system on the endometrium of these patients.

Keywords: abortion, embryo implantation, assisted reproductive techniques, cytokines

INTRODUCTION

Assisted Reproductive Techniques (ART) have evolved exponentially to improve the rates of obtaining clinical pregnancy in couples with infertility. Despite these advances, embryo implantation is still a limiting step in the success rate of these ARTs (van Hoogenhuijze et al., 2017). Globally, the in vitro fertilization (IVF) technique enables a rate of 25 to 30% live births per initiated cycle, differing from rodents or rabbits, which have a 95% implantation rates. This fact may be directly associated with endometrial and decidual control in embryo implantation events in different mammalian species (Simon et al., 2020). Several factors can interfere with the embryo implantation process, such as endometrium, embryo, anatomical structure, lifestyle, thrombophilic conditions, and immunological factors (Kalem et al., 2020).

Among these mechanisms, the immunological factor stands out. During the communication between the endometrium and the embryo, a pattern of pro-inflammatory cytokines is established to help regulate the endometrium receptivity (Madkour et al., 2016). We assume that the uterus local immune system (IS) significantly assists in tolerance to the semi-allogeneic graft of the conceptum (Sho et al., 2017). Furthermore, it has been proposed that IS dysfunction in the endometrial milieu is related to mechanisms that compromise embryo implantation, potentially causing problems such as Recurrent Implantation Failure (RIF) and increased Recurrent Abortion Rates (RAR) in ART procedures (Singh et al., 2019). Given the potential relevance of the IS in embryo implantation rates, it may become an excellent reliable, non-invasive biomarker for verifying gestational success rates (Qasemi et al., 2021).

Despite multiple improvements in ARTs, implantation failure is still considered a relevant issue (van Hoogenhuijze et al., 2017). Such a fact is mainly due to the emotional burden that unsuccessful ART cycles can generate in patients undergoing these procedures (Bashiri et al., 2018). Implementing biomarkers in reproductive medicine may be a viable alternative for reducing implantation problems (Palmer & Barnhat, 2013). As an element distributed throughout the body, the IS may become an effective biomarker for specific implantation events (Qasemi et al., 2021). Thus, our study aims to investigate, through a systematic literature review, the main immune cells present in the process of embryo implantation failure.

MATERIALS AND METHODS

Study

This study is a systematic literature review based on papers from PubMed, Embase, and Virtual Health Library (VHL) databases. To this end, the study was prepared following the guidelines for Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). It is worth noting that the entire protocol of this review was submitted to the National Institute for Health Research database (CRD42022343288).

Eligibility Criteria

For study selection, we adapted the PICOS methodological model used by Rocha et al. (2021). The full summary description of the criteria is presented in Table 1. The eligibility criteria adopted were:

Table 1.

Systematized search using the PICOS method.

Description Abbreviation Question Components
Population P Women who used ARTs had RAR, RIF, and IVF failure.
Intervention I Performance of blood collection or endometrial biopsy for dosage of immune cells and/or inflammatory cytokines before and/or after embryo transfer.
Comparison C Fertile women who achieved clinical pregnancy.
Outcome O Obtained key IS cells and/or secreted cytokines found in peripheral blood or from endometrial cells.
Study S Observational and case-control studies.
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ART: Assisted Reproductive Techniques; IVF: In vitro fertilization; RAR: Recurrent Pregnancy Loss; RIF: Recurrent Implantation Failure; IS: Immune System.

  1. Studies Included: Clinical and case-control trials that addressed the proposed topic;

  2. Publication Period: The selected studies were published between January 1, 2010, and April 24, 2022;

  3. Language of the Studies: we analyzed papers in English, Portuguese (Brazil), and Spanish;

  4. Intervention Used: Patients with RAR, RIF, and fertilization failures submitted to ART, who underwent before or after endometrial biopsy, treatments, or blood collection to study their immune profile; and

  5. Study outcome: Obtaining the major IS cells and/or secreted cytokines found in peripheral blood or endometrial cells.

Database Search

We searched the “PubMed”, “Embase” and VHL databases. The search was done manually using a combination of previously selected keywords from the Medical Subjects Headings (MESH) database in the advanced search. The following keywords were used: (immune system) AND (embryo implantation) AND (women).

Inclusion and Exclusion Criteria

To filter the best results within the suggested scope of the review, we used the following inclusion and exclusion criteria:

Inclusion Criteria

  1. Observational Studies; and

  2. Case-Control Studies.

Exclusion Criteria

  1. Articles out of scope;

  2. Literature reviews;

  3. Letter to the editor;

  4. Abstracts;

  5. Animal Studies; and

  6. Case Reports.

Methodological Quality Assessment of Studies

To reduce the chance of bias among the selected papers we assessed the risk of methodological bias. To do so, we used the Newcastle Ottawa scale for bias assessment of observational studies. Studies considered to have a low risk of bias entered our review assessment. All data from the methodological evaluation are presented in Table 2.

Table 2.

Methodological Quality of Cross-sectional Studies (Newcastle Ottawa Scale).

Study Newcastle Ottawa Scale-items Score
Criteria
Selection Comparability 1a Results Total
1 2 3 4 1 2 3
Yang et al., 2010 1 1 0 1 1 1 1 1 7
Tuckerman et al., 2010 1 1 0 1 1 0 1 1 6
Karami et al., 2012 1 1 1 1 1 1 1 1 8
Zhou et al., 2012 1 1 1 1 1 1 1 1 8
Junovich et al., 2013 1 1 0 1 1 0 1 1 6
Ozkan et al., 2014 1 1 1 1 1 1 1 1 8
Liu et al., 2014 1 1 1 1 1 1 1 1 8
Saifi et al., 2014 1 1 1 1 1 1 1 1 8
Chernyshov et al., 2014 1 1 1 1 1 1 1 1 8
Santillán et al., 2015 1 1 1 1 1 1 1 1 8
Dons’koi, 2015 1 1 1 1 1 1 1 1 8
Galgani et al., 2015 1 1 1 1 1 1 1 1 8
Saifi et al., 2016 0 1 1 1 1 1 1 1 7
Wang et al., 2017 1 1 0 1 1 1 0 1 6
Yin et al., 2017 1 1 1 1 1 1 1 1 8
Jiang et al., 2017 1 1 0 1 1 1 0 1 6
Kuon et al., 2017 1 1 1 1 1 1 1 1 8
Fukui et al., 2017 1 1 0 1 1 1 0 1 6
Chen et al., 2017 1 1 1 1 1 1 1 1 8
Chen et al., 2018 1 1 1 1 1 1 1 1 8
Kolanska et al., 2019 1 1 0 1 1 1 0 1 6
Liu et al., 2019 1 1 1 1 1 1 1 1 8
Koushaeian et al., 2019 1 1 1 1 1 1 1 1 8
Donoghue et al., 2019 0 1 1 1 1 1 1 1 7
Zhao et al., 2020 0 1 1 1 1 1 1 1 7
Amjadi et al., 2020 0 1 1 1 1 1 0 1 6
Sauerbrunn-Cutler et al., 2021 0 1 1 1 1 1 1 1 7
Comins-Boo et al., 2021 1 1 1 1 1 1 1 1 8
Zhao et al., 2021 0 1 1 1 1 1 0 1 6
Kuroda et al., 2021 1 1 1 1 1 1 1 1 8
Dons’koi et al., 2021 1 1 0 1 1 1 0 1 6
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Selection 1: Representativeness of the exposed cohort; Selection 2: Selection of the unexposed cohort; Selection 3: Exposure determination; Selection 4: Demonstration that the result of interest was not present in the baseline; Comparability 1a and 1b: Comparability of cohorts based on design or analysis; Results 1: Results assessment; Results 2: Follow-up of cohorts; Results 3: Adequacy of cohort follow-up.

Data Collection and Extraction

After screening the articles mentioned above, they were evaluated by four authors (MGA; RYM; FLDM; JOF). In case of divergence, a fifth author (NR) specialized in the field would reevaluate the paper and the results were tabulated. The data extracted from each paper were:

  1. Day on which the sample was collected;

  2. Number of patients;

  3. Control group;

  4. Age of patients;

  5. Type of sample used; and

  6. Immune cell mediators.

RESULTS

Methodological Screening

According to the methodological model used to formulate the review, we found 467 papers. Of these, only 31 were selected for the review. Overall, 1,800 patients with a mean age between 20 to 39.9 years were evaluated. The data are available in Table 1. It is worth pointing out that the primary sampling methodologies to identify immunological profiles of these patients were acquired from endometrial biopsies and peripheral blood sampling. Based on this, we extracted the data extraction from these two different methodologies. Figure 1 depicts the entire methodological screening.

Figure 1.

Figure 1

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Methodological screening.

Immune Cell Mapping in Peripheral Blood

We found that in the peripheral blood of patients with implantation problems, there was an increase in cells compared to controls. The main increased cells were CD3+, CD4+, CD8+, CD16+, CD56+, CD57+, CD69+, CD154+, CD158a+, NKp46 (Yang et al., 2010; Karami et al., 2012; Chernyshov et al., 2014; Santillán et al., 2015; Dons’koi, 2015; Jiang et al., 2017; Dons’koi et al., 2021; Comins-Boo et al., 2021). On the other hand, CD4+, CD45+, Foxp3, and NKp46 cells were reduced in patients with reproductive issues, compared to control groups (Zhou et al., 2012; Fukui et al., 2017; Liu et al., 2019; Comins-Boo et al., 2021). Th1 type immune responses were also increased in two studies (Saifi et al., 2014; Kuroda et al., 2021).

Immune Cell Assessment in Endometrial Biopsy Samples

The literature also infers that implantation issues may modulate the immune response in the endometrium. There was a marked increase of cells in samples from these patients when compared to control groups. Among these, CD3+, CD4+, CD5+, CD8+, CD16+, CD25+, CD45+, CD56+, CD57+, CD68+, CD127+ (Tuckerman et al., 2010; Junovich et al., 2013; Santillán et al., 2015; Galgani et al., 2015; Wang et al., 2017; Kuon et al., 2017; Jiang et al., 2017; Chen et al., 2017; 2018; Zhao et al., 2020; 2021; Sauerbrunn-Cutler et al., 2021). In contrast, cells such as CD45+, CD56+, NKp46 and Foxp3 had reduced levels in endometrial biopsies from patients with RIF, RAR, or who resorted to ART (Jiang et al., 2017; Fukui et al., 2017; Sauerbrunn-Cutler et al., 2021).

Inflammatory cytokines in the peripheral blood of patients

In our review, there was an increase in inflammatory cytokines in the peripheral blood of patients with gestational complications, among which we list IL-6, IL-10, IL-17, INF-γ, TGF-ß, TNF-α (Ozkan et al., 2014; Saifi et al., 2014; Yin et al., 2017). In contrast, a group of inflammatory cytokines was reduced in patients with gestational complications in six studies, such as IL-4, IL-6, IL-10, IL- 35, FoxP3, TGF-ß, SOCS3 (Junovich et al., 2013; Zhou et al., 2012; Ozkan et al., 2014; Saifi et al., 2014; 2016; Koushaeian et al., 2019). All data are detailed in Table 3.

Table 3.

Immunological profile of patients with peripheral blood collection.

Author Collection Day Number of Patients Control Group Age (Average) Cytokine panel Immune Cells
Yang et al., 2010 - 18 RIF group
17 RAR group		 Fertile women RIF (35.6 years)
RAR (35.1 years)		 No significant differences ↑ CD154+
↑ CD69+
Karami et al., 2012 - 20 RIF group
23 RAR group		 Fertile women RIF (31.5 years)
RAR (30 years)		 - ↑ CD56+
Zhou et al., 2012 - 34 non-pregnant women Pregnant 32.4 years - ↓ CD4+;
↓ FoxP3
Junovich et al., 2013 After LH peak (5-9 days) 26 fertile group Fertile women - ↓ IL-6 No significant differences
Ozkan et al., 2014 Cycle (21 day) 80 infertile group Fertile women 30.2 years ↓SOCS3;↓IL-35;↓IL-4;
↑ IFN-γ;↑ IL-17;↑ TGFβ;
↑ IL-6;↑ TNF-α;↑ IL-10		 -
Saifi et al., 2014 Cycle (19-23 days) 20 RAR group Fertile women - ↑ IL-17;↓ TGFβ -
Chernyshov et al., 2014 Cycle (17-23 days) 75 failure to conceive group
18 abortion group		 Conception group 23-35 years - ↑CD56+; ↑CD158a+;
↑CD4+; ↑CD8+
Santillán et al., 2015 After LH peak (5-9 days) 73 RIF group Fertile women - - ↑ CD56+
Dons’koi, 2015 - 90 non-pregnant group Conception group 28.2 years - ↑ T CD3+
↑ T CD8+
Saifi et al., 2016 Cycle (19-23 days) 20 RPL group Fertile women 30.72 years ↓ IL-10 -
Jiang et al., 2017 After LH peak (7-9 days) 32 RIF group Fertile women 32 years - ↓ CD45+
Yin et al., 2017 Cycle (3-5 days) 56 RIF women Fertile women 34,9 years ↑ IFN-γ;↑ TNF-α No significant differences
Fukui et al., 2017 - 34 RIF group
28 RAR group		 Fertile women RIF (35.3 years)
RAR (33.8 years)		 - ↓ NKp46
Kolanska et al., 2019 - 41 RIF group
54 RAR group		 Fertile women RIF (36.3 years)
RAR (36.3 years)		 - No significant differences
Liu et al., 2019 Luteal phase (7-9 days) 7 RIF group
20 RAR group		 Fertile women RIF (31.1 years)
RAR (33.3 years)		 - No significant differences
Koushaeian et al., 2019 - 23 RIF group Fertile women 39.9 years ↓ IL-10 No significant differences
Kuroda et al., 2021 - 79 RIF group
81 RAR group
40 infertile group		 Fertile women RIF (37.6 years)
RAR (38 years)
Infertile (35.4 years)		 - ↑ Th1
Dons’koi et al., 2021 Implementation phase (16-20 days) 57 RIF group Fertile women 29.5 years - ↑ NKp46+
Comins-Boo et al., 2021 - 25 RIF group
58 RAR group		 Fertile women RIF (36.0 years)
RAR (36.9 years)		 - ↓ NKp46+
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Inflammatory cytokines from endometrial biopsies

Two studies reported an increase in inflammatory cytokines in endometrial biopsies, such as IL-2, IL-6, IL-17, IL-22, IL-23, INF-A1, INF-B1, INF-γ, TNF- R (Galgani et al., 2015; Amjadi et al., 2020). In endometrial tissues, some inflammatory cytokines had their levels reduced in four studies, such as IL-6, IL-10, INF-γ, TGFß, TNF-α (Junovich et al., 2013; Galgani et al., 2015; Wang et al., 2017; Fukui et al., 2017). All data are detailed in Table 4.

Table 4.

Immunological profile of patients who underwent endometrial biopsy procedures.

Author Collection Day Patients (n) Control Group Age (Average) Cytokine panel Immune Cells
Tuckerman et al., 2010 After LH peak (7-9 days) 40 RIF group Fertile women 35 years - ↑ CD56+
Junovich et al., 2013 After LH peak (5-9 days) 26 infertile group Fertile women - ↓ IL-6 ↑ CD16+
Liu et al., 2014 After LH peak (7-9 days) 72 RIF group
94 RAR group		 Fertile women RIF (33.4 years)
RAR (33.1years)		 - No significant differences
Santillán et al., 2015 After LH peak (5-9 days) 73 RIF group Fertile women - - ↑ CD56+
Galgani et al., 2015 Cycle (21-23 days) 15 RIF group
13 RAR group		 Fertile women RIF (34.5 years)
RAR (33.6 years)		 ↑ TNF-R;↑IL-22; ↑ CD3+;↑ CD4+
↑ CD5+’↑ CD8+
↓ FoxP3+
Wang et al., 2017 +14 TE 53 pregnant group Pregnant women 33.1 years ↓ IL-10;
↓ TGF-β		 ↑ CD4+;↑ CD25+
↑ CD127dim
Kuon et al., 2017 After LH peak (7-10 days) 58 RAR group Fertile women 34.7 years - ↑ CD56+
Jiang et al., 2017 After LH peak (7-9 days) 32 RIF group Fertile women 32 years - ↑ CD57+;↓ CD45+
↓ CD56+↓ FoxP3+
Fukui et al., 2017 - 34 RIF group
28 RAR group		 Fertile women RIF (35.3 years)
RAR (33.8 years)		 ↓ TNF-α;
↓ INF-γ		 ↓ NKp46
Chen et al., 2017 After LH peak (7th day) 34 RIF group
97 RAR group		 Fertile women RIF (35 years)
RAR (37 years)		 - ↑ CD56+
Chen et al., 2018 After LH peak (7th day) 18 RAR group Fertile women 34 years - ↑ CD56+
Donoghue et al., 2019 After LH peak (6-8 days) 14 RIF group
9 PRIF group		 Implantation success RIF (37.4 years)
PRIF (38.1 years)		 - No significant differences
Amjadi et al., 2020 After LH peak (6-7 days) 11 RIF group Fertile women 32.6 years ↑IL-2;↑ IL-6
↑IFN-↑;↑IL-17A
↑IL-23A; ↑ IFN-A1
↑ IFN-B1		 -
Zhao et al., 2020 After LH peak (7th day) 30 RAR group Fertile women 20 - 42 years - ↑ CD3+;↑ CD56+
↑ CD68+
Sauerbrunn-Cutler et al., 2021 After LH peak (9th day) 17 non-pregnant group Pregnant women 34.3 years - ↑ CD16+,↓ FoxP3+
Zhao et al., 2021 After LH peak (7th day) 44 non-pregnant group Pregnant women 35.92 years - ↑ CD56+;↑ CD68+
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CD: Cluster of Differentiation; RIF: Recurrent Implantation Failure; RAR: Recurrent Abortion Rates; LH: Luteinizing Hormone; Th: Helper T Cells; NKp: Natural Cytotoxicity Receptor Protein; and - : not available.

CD: Cluster of Differentiation; RIF: Recurrent Implantation Failures; PRIF: Potential Recurrent Implantation Failures; RAR: Recurrent Abortion Rates; ET: Embryo transfer; LH: Luteinizing Hormone; NKp: Natural Cytotoxicity Receptor Protein; FoxP3+: Forkhead box P3 protein; and -- : not available.

Common Points Between Collections

To better plot, the commonalities between both collections, the main immune cells found in the studies were selected and placed in a Venn diagram, as shown in Figures 2 and 3. By plotting the main immune cells, we noticed that there was a common immune enhancement in both techniques in CD3 +, CD8 +, CD16 +, and CD57 + cells. In the cells found, there was an intersection point of the FoxP3+ phenotype. Interestingly, among the inflammatory cytokines in the endometrial biopsies used in the review, the only intersection point found in the study was the increase in IL-17 levels.

Figure 2.

Figure 2

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Venn diagram containing peripheral blood immune cells and embryo biopsy in RIF, RAR, and infertile patients. Caption: Immune cells from different types of collection. In blue: increase in cell quantity. In pink: Reduction of cell quantity. A: Peripheral blood immune cells. B: Immune cells derived from embryonic biopsies. C: Just enlarged cells between the two collection types. D: Just reduced cells between the two collection types.

Figure 3.

Figure 3

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Venn diagram containing peripheral blood inflammatory cytokines and endometrial biopsies from RIF, RAR and infertile patients. Caption: Cytokines from different types of collection. In blue: increase in the number of cytokines. In pink: Reduction in the number of cytokines. A: peripheral blood immunological cytokines. B: Immune cytokines derived from embryonic biopsies. C: Only amplified cytokine pattern between the two types of collection. D: Only reduced cytokine pattern between the two types of collection.

DISCUSSION

In a successful pregnancy, the body must undergo many physiological processes that act directly on proper endometrial function and dynamic interaction between the endometrium and the blastocyst (Mrozikiewicz et al., 2021). This implantation process is somewhat inefficient in human reproduction, since about 25% of conceptual matings generate live births, and 5-15% can be identified clinically (Nowak et al., 2017). In this context, investigating biomarkers and clinical trials to determine or prospect possible treatment and/or immune abnormalities in these patients could effectively improve conception rates (Parhizkar et al., 2021).

One of the methodologies found in this search was the study of immune components from the peripheral blood of patients. Peripheral blood cell analyses consist mainly of evaluating lymphocytes and monocytes that are enabled in a wide range of assays, from the most straight forward, such as cytotoxicity assessments, to the most complex, such as functional and phenotypic evaluation of immune cells (Navas et al., 2019). Among the significant disadvantages of peripheral blood cell analyses is the similarity between immune responses in the body, which can lead to erroneous analysis and interpretation of data. However, non-generic-specific biomarkers can improve tissue specificity (Jogia et al., 2021). However, one of the main advantages of peripheral blood collection over other collection types is its better accessibility (Medrone Junior, 2009).

Another well-used methodology for the identification of immunological biomarkers was an endometrial biopsy. The primary purpose of this technique is to obtain a sampling of endometrial material to evaluate lesions of the endometrial lining and investigate other benign pathologies (Nicholls-Dempsey et al., 2018). One of the main disadvantages of endometrial biopsy is still the invasiveness of the technique. Although it is less harmful compared to other methodologies, such as laparoscopy, it still requires anesthesia or strong analgesics in some cases (Al-Jefout et al., 2007). However, the endometrial tissue structure has many distinct molecules that may contribute to adhesion, cell distribution, transit, and more specific signaling processes involved in implantation disorders (Marron et al., 2019).

RIF, RAR, and infertile patients, had higher T lymphocyte counts (CD3+, CD4+, CD8+, CD69+, CD154+) in their peripheral blood and (CD3+, CD4+, CD8+, CD25+, and CD127+) in endometrial biopsies (Yang et al., 2010; Chernyshov et al., 2014; Dons’koi, 2015; Galgani et al., 2015; Wang et al., 2017; Zhao et al., 2020). The literature has already described that T-type lymphocytes are located in the tissue stroma and glandular epithelium. These cells control the Th1 response involved in immune surveillance, preventing excessive trophoblast invasion and assisting in allograft immune tolerance (Zolfaghari et al., 2021). However, the literature also reports that in many cases of maternal anti-fetal rejection and gestational problems, there is an increased infiltration of cytotoxic T-lymphocytes into the fetal tissues (Kim et al., 2015). This fact was previously observed in the study by Quinn et al. (2011) who found an increased infiltration of cytotoxic CD8+ cells in women who had severe late preeclampsia.

Cells of the innate immune response have also been shown to be affected in cases of conception failure. The amount of CD68+ macrophages in endometrial biopsies increased in patients who intended to achieve clinical pregnancy from ART (Zhao et al., 2020; 2021). Under normal conditions, peripheral blood macrophages can reduce the invasiveness of trophoblast implantation. However, when these macrophages are dysregulated, there is no complete explanation for their effects on implantation (Han et al., 2021). In a previous study by Kim et al. (2008) there was an increase of macrophages in chorionic villi of patients with villitis of unknown cause, in addition to the macrophage infiltrate increase in the presence of CD8+ T cells in these patients.

One of the main unknowns in the literature is the impact of NK cells on embryo implantation. The attack of cytotoxic NK cells is immediate and does not require prior antigen preparation. Instead, these cells orchestrate the attack uniquely from interactions with receptors or inhibitory functions (Becker et al., 2016). An increase of NK cells in peripheral blood and endometrial biopsies (CD8+, CD16+, CD56+, CD57+, and CD158a+) in most studies (Tuckerman et al., 2010; Karami et al., 2012; Junovich et al., 2013; Chernyshov et al., 2014; Dons’koi, 2015; Santillán et al., 2015; Jiang et al., 2017; Kuon et al., 2017; Chen et al., 2017; 2018; Sauerbrunn-Cutler et al., 2021; Comins-Boo et al., 2021; Zhao et al., 2021). In a previous retrospective study evaluating the ovarian reserve of women undergoing cycles of ART, they found that the high rate of NK cells led to a reduction in ovarian reserve, which confirms the reproductive impacts shown previously (Hur et al., 2020). However, NK cells in the peripheral blood of healthy individuals can vary around 5%-29% depending on gender, stress, ethnicity, and age. Based on this, confirming their actual activity on fecundity it is still a controversial issue in the literature (Canella et al., 2021).

A curious finding was that some immune system cells adopted both a growth and a declining pattern in the different studies analyzed. These patterns occurred in dendritic cell lineages (CD86+) in the peripheral blood and NK cells expressing NKp46 receptors. In addition, regulatory T (Foxp3) and (CD4+) cells were also expressed in a lower amount in endometrial biopsies (Jiang et al., 2017; Fukui et al., 2017; Liu et al., 2019; Comins-Boo et al., 2021; Sauerbrunn-Cutler et al., 2021). As for the lower expression in dendritic cells, the literature already reports that this low amount of cells can lead to a reduction in IL-10 that controls tissue levels of effector T-cells that consequently infiltrate the endometrium (Kong et al., 2018). Recent studies have reported that reducing NK cells expressing NKp46 receptors on endometrial cells increases the high risk of gestational loss. However, their correlation with this loss is still unknown in the literature (Fukui et al., 2006; Takeyama et al., 2021).

Regulatory T-cells are defined by their expression of CD4+, CD25+, and the Foxp3 domain, which control the developmental function of naturally occurring T-reg populations (Heitmann et al., 2017). In this review, we found increased CD4+ cells in peripheral blood and a reduction in FoxP3. The primary function of these regulatory cells is endometrium modulation to receive the semi-allograft without complete immunosuppression during implantation, in addition to its protective function against opportunistic infections, which may risk the mother’s health (Royster et al., 2019). In a previous study, Teles et al. (2013) used mouse models with depletion for regulatory T-lymphocytes and reported that they had potential problems in embryo implantation, which is in tune with the findings of this review.

From the studies analyzed, we found a panel of cytokines sharply increased in the peripheral blood of the patients, including cytokines IL-6, IL-10, IL-17, INF-γ, TGF-ß, TNF-α (Ozkan et al., 2014; Saifi et al., 2014; Yin et al., 2017). However, according to a review by Chaouat et al. (2003), after the coitus phase until the apposition phase, the uterus is subjected to an inflammatory reaction with a transient cellular influx of lymphocytes and macrophages near the uterine lumen, leading to a high production of interleukins such as IL-6 and TNF-a, which could explain this change in peripheral blood cytokines, which also showed a reduction in IL-4, IL-6, IL-10, IL-35, FoxP3, TGF-ß, SOCS3 cytokines (Junovich et al., 2013; Zhou et al., 2012; Ozkan et al., 2014; Saifi et al., 2014; 2016; Koushaeian et al., 2019). On the other hand, when we checked the expression patterns of inflammatory cytokines in endometrial biopsies, IL-2, IL-6, IL-17, IL-22, IL-23, INF-A1, INF-B1, INF-γ, TNF-R were relatively increased in patients with reproductive complications (Galgani et al., 2015; Amjadi et al., 2020). This fact was reported by Saini et al. (2011) saying that Th1- cells, especially IL-2 and gamma interferon producers, play a crucial role in allograft rejection during fetal implantation. On the other hand, the levels of IL-6, IL-10, INF-γ, TGFß, TNF-α had their levels reduced (Junovich et al., 2013; Galgani et al., 2015; Wang et al., 2017; Fukui et al., 2017). This fact can also be explained by Chaouat et al. (2003) as previously mentioned, in which the reduction of cytokines by defense cells can lead to an unfavorable environment for embryo development, resulting in development imbalance and pregnancy loss. One of the main limitations of that study is the unspecificity of immune factors collected mainly from peripheral blood, as mentioned before, which may account for the increase and decrease in some immune cells (Jogia et al., 2021). Another factor that can lead to failures in these methodologies is the collections performed at different times, which can modulate the proliferation of immune cells and make it impossible to collect more homogeneous data and responses. Hormonal balance may be an interesting parameter to be addressed in further studies to investigate its correlation with the immune system and its implantation impacts on ART outcomes (Kim et al., 2015).

In conclusion, identifying immunological biomarkers may be an effective way to address fertility issues. Increased cytotoxic T-lymphocytes such as CD3+, CD25+, CD69+, CD127+, and CD154+ have been shown to correlate with fertility in patients. Innate immune response cells CD68+ were also increased in patients with problems to achieve pregnancy. CD8+, CD16+, CD56+, CD57+, and CD158a+ NK cells may exhibit a possible increase in the rates of reproductive problems. However, this finding is still uncertain in the literature. Regulatory T-cells such as Foxp3 have been shown to have the potential to aid in implantation immune tolerance, and their reduction has been seen in patients with reproductive disorders. In this context, further studies are needed to verify these cells’ main activity in the IS and identify functional biomarkers. In addition, the data presented in this review can be of great value for the design of studies aimed at developing methodologies, such as rapid tests that could predict the implantation rate of patients who resort to ARTs, enhancing the chances of clinical pregnancy success.

Abbreviations

RIF

Recurrent implantation failure

IVF

In vitro fertilization

MESH

Medical Subjects Headings

RAR

Recurrent Abortion Rates

ART

Assisted Reproductive Techniques

PRISMA

Reporting Items for Systematic Reviews and Meta-Analysis and

IS

Immune system

REFERENCES

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