Abnormal peripheral cellular immune profiles in gestational diabetes mellitus: A meta-analysis

Abstract

BACKGROUND

Gestational diabetes mellitus (GDM) has recently been associated with abnormal profiles of inflammatory cells and cytokines, though the findings remain inconsistent and unclear.

AIM

To elucidate the peripheral immune status in GDM.

METHODS

We systematically screened databases including Web of Science, PubMed, and EMBASE for eligible studies. Original articles reporting different immune cell levels in GDM compared to normal glucose-tolerance pregnant women were included to extract usable data. The pooled mean difference (MD) with 95% confidence interval (CI) was analyzed as the outcome measure. The Newcastle-Ottawa scale was employed to assess study quality.

RESULTS

A total of 19 studies involving various immune cell subgroups were included in our analysis. Specifically, total CD4+ T cells (WMD = 3.08; 95%CI: 0.81-5.35) were significantly increased in GDM groups. In contrast, total lymphocytes (SMD = 0.05; 95%CI: -0.16 to 0.26), CD3+ T cells (SMD = -0.34; 95%CI: -1.01 to 0.32), CD8+ T cells (SMD = 0.21; 95%CI: -0.31 to 0.73), and natural killer T (NKT) Cells (SMD = 0.83; 95%CI: -1.10 to 2.75) showed no significant changes in GDM. Activation markers (HLA-DR+ or CD69+) on CD4+ T cells (WMD = 0.20; 95%CI: 0.06-0.34) were increased in GDM patients. Treg cells, a classical subgroup of CD4+ T cells, showed a decreasing trend in GDM compared to controls (SMD = -0.83; 95%CI: -1.31 to -0.34). These results indicate an abnormal immune status in the peripheral profiles of GDM.

CONCLUSION

GDM may not only be a dysglycemia-related condition but also an immune disorder characterized by abnormal peripheral immune profiles, including higher levels of CD4+ T cells and a reduced population of Treg cells. Treating immune dysregulation could be a new direction for GDM management, although further research is needed to understand the precise mechanisms of immune overactivation in GDM.

Key Words: Gestational diabetes mellitus; Peripheral immune cell; Immune dysregulation; Meta-analysis

Core Tip: Gestational diabetes mellitus (GDM) affects pregnancies globally, leading to serious complications for both mothers and their offspring. GDM is associated with immune dysregulation, including alterations in immune cell profiles. This study analyzed 19 studies and found increased CD4+ T cells and reduced Treg cells in GDM patients, indicating an abnormal immune response. Other immune cells, like CD3+ T cells and NK cells, showed no significant changes. The findings suggest that GDM may not only involve dysglycemia but also immune disorders, highlighting the potential for immune-targeted therapies in GDM management.

INTRODUCTION

Gestational diabetes mellitus (GDM), defined as the onset of glucose intolerance during pregnancy, affects approximately 14% of pregnant women worldwide[1]. It is well known that GDM is associated with numerous obstetric complications, including an increased risk of stillbirth, preterm birth, and cesarean delivery[2]. Additionally, offspring of mothers with GDM are more likely to develop pediatric cardiovascular diseases and metabolic syndrome[2,3]. GDM also poses significant long-term health risks for mothers, such as an increased likelihood of developing type 2 diabetes, obesity, and related metabolic complications[4]. Given these serious complications for both mothers and their babies, there is an urgent need for an in-depth analysis of the mechanisms and characteristics of GDM.

Similar to type 1 diabetes, inflammation disorder has also been found in GDM and accumulating evidence have revealed that immune system exerted its important influence on the process and insulin resistance of GDM[5-7]. Rapid innate immune system and long-lasting adaptive immune system all have been demonstrated to participate in the development of GDM and its complications[8-12]. GDM was therefore been hypothesized to be one of diseases of immunity disorders.

Recent research has explored the association between GDM and immune dysregulation, though the mechanisms remain unclear. Several immune indicators have been identified as potential markers for the development of GDM. For instance, activated CD4+ T cells release inflammatory cytokines such as interferon-gamma (IFN-γ), which can directly impair insulin signaling and β-cell function[13]. The shift towards a pro-inflammatory Th1 response in GDM suggests that an imbalance between Th1 and Th2 responses may contribute to the disease by altering immune regulation and promoting systemic inflammation[14]. Regulatory T cells (Tregs), which are essential for maintaining immune tolerance and preventing excessive inflammation, have been observed in the peripheral blood of individuals with GDM[15]. This decrease in Tregs is thought to impair the suppression of pro-inflammatory cytokines and exacerbate systemic inflammation, a key driver of insulin resistance in GDM[16]. Tregs also play a role in maintaining fetal-maternal immune tolerance, and their dysfunction may disrupt this balance, contributing to both metabolic and immune complications during pregnancy. In addition to Tregs, other immune cell subpopulations, including macrophages, natural killer (NK) cells, CD4+ T cells, and CD8+ T cells, have shown alterations in patients with GDM, though findings remain controversial.

For example, M1 type macrophages, which are pro-inflammatory, accumulate in the placenta of GDM patients[17,18]. Paradoxically, other studies suggest that M2 type macrophages, rather than M1, are the predominant cell clusters in the placenta[19,20]. NK cells, which include cytotoxic and cytokine-secreting subsets, have been studied in the placentas of GDM patients, with an observed increase in cytotoxic NK cells[21]. Collectively, these studies indicate that immune dysregulation may be a significant factor in GDM development. However, the specific immune status in GDM has yet to be clearly elucidated.

In summary, while recent studies have investigated immune cell alterations in GDM, existing reviews often lack a comprehensive synthesis of peripheral immune cell profiles across various blood compartments (e.g., venous, cord, and retroplacental blood). Most previous studies have focused on isolated immune cell populations, and there is a need for a broader analysis encompassing a wide range of immune cells, including T cells, NK cells, and macrophages, across different sample types. This gap limits our understanding of the full spectrum of immune dysregulation in GDM and its implications for disease pathogenesis. Our study aims to fill this gap by providing a more comprehensive meta-analysis of immune cell changes throughout pregnancy and discussing their potential contribution to GDM progression. Additionally, our study further investigates the relationship between peripheral immune cells and the progression of GDM, as well as to evaluate the potential of immune cell status in predicting GDM prognosis.

MATERIALS AND METHODS

This meta-analysis was conducted according to the PRISMA statement guidelines, as previously described[22].

Article search strategy

The research was screened from February 15, 2023, to May 7, 2024. We compared three databases, including PubMed, Web of Science, and EMBASE, for eligible studies. The key terms used were: "Gestational diabetes mellitus", "GDM", "immune cell", and "immune". Additionally, other potentially relevant articles were tracked and screened from the references of the citations in related conclusive studies, such as reviews on GDM and immune regulation. All eligible studies published by May 7, 2024, without any language restrictions, were searched and analyzed.

Selection criteria

The final selection criteria were formulated by all authors. Two authors (Yang Y and Zhou J) independently reviewed the searched studies, and a third reviewer resolved any disagreements. The inclusion criteria were as follows: (1) Studies that examined the relationship between GDM and any type of immune cell population; and (2) Studies that included at least two groups (control group and GDM group). Studies were excluded if they lacked the necessary data for analysis or were published as letters, editorials, reviews, or conference abstracts.

Data extraction

EndNote X9 software was used to combine the search results from the three databases, and duplicate studies were removed using EndNote X9's comparison feature. The following information was extracted and imported into Excel: Authors, year, country, type of study, age, sample size, population, immune cell ratio, and GDM outcomes.

Quality assessment of studies

The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the eligible studies[23]. The criteria for quality assessment included study type, sample size, participant selection, representativeness of the sample, adequacy of follow-up, comparability (exposed-unexposed or case-control), and method of ascertaining cases and controls. The NOS range is 0 to 9, with a score of 6 or higher indicating high-quality research.

Statistical analysis

Stata software was used for data analysis and plotting. The outcomes of the immune cell ratio in GDM were expressed as the mean difference (MD) with 95% confidence intervals (CI) using random-effects models. The degree of heterogeneity was assessed using the I² statistic, with low heterogeneity defined as less than 25%, moderate heterogeneity as around 50%, and high heterogeneity as 75% or higher. Publication bias was assessed using funnel plots and Begg’s and Egger’s tests. The trim-and-fill method was employed to address significant publication bias. Sensitivity analysis was also performed using the leave-one-out method to examine the stability of the results.

RESULTS

Study selection and quality assessment

The detailed process of research screening and selection is shown in Figure 1. Initially, 1393 studies were identified. After excluding 332 duplicates, titles and abstracts of the remaining studies were further assessed according to exclusion criteria, such as non-human subjects, leading to the removal of 113 publications. Of the 948 remaining studies, 929 were excluded based on our selection criteria after full-text screening. Ultimately, 19 studies passed the selection process and underwent NOS quality assessment. All 19 studies[11,12,16,19,21,24-37] were classified as high-quality articles according to NOS criteria, indicating their eligibility. The characteristics of the included studies are presented in Table 1. Among the eligible studies, four were conducted in Brazil, seven in China, two in Germany, two in Australia, one in Italy, one in Kuwait, one in Greece, and one in Benin. All 19 studies were cohort, case-control, or cross-sectional studies.

Figure 1 Flow diagram of the study selection process.

Table 1 Description of eligible studies reporting the profile of maternal immune status in gestational diabetes mellitus.

No	Ref.	Country	Population of outcomes	BMI of GDM women	Location of immune cells	Period of pregnancy	Type of immune cells	Age	Type of study	Sample size	NOS
1	Lapolla et al[24]	Italy	Maternal and fetal outcomes	23 ± 5	Peripheral venous blood	At third trimester of pregnancy	Lymphocyte subsets and cytokines: Total lymphocytes, T lymphocyte subsets CD3 and CD8	33 ± 4	Cross-section	62 GDM patients and 74 women with normal glucose tolerance	7
2	Mahmoud et al[25]	Kuwait	Maternal outcomes	NA	Peripheral venous blood	At third trimester of pregnancy	Naïve T cells were decreased and memory T-cells and activated T cells (CD4+HLA-DR+, CD4+CD29+)	Maternal age was matched without detail information	Cohort	63 GDM and 16 pregnant women with Type 2 diabetes and 48 healthy, women	6
3	Schober et al[26]	Germany	Maternal outcomes	NA	Peripheral venous blood	At third trimester of pregnancy	Four different Treg subsets: Naïve Treg cells, memory Treg cells, the highly differentiated and activated Treg cells	31 (21-44)	Cohort	64 healthy pregnant women, 121 pregnant women with dietary-adjusted gestational diabetes	7
4	Pendeloski et al[27]	Brazil	Maternal outcomes	25.7 (23.4-29.0)	Peripheral venous blood	At third trimester of pregnancy	T subpopulations (CD4+ and CD8+), the expression of immunoregulatory molecules (CD28, ICOS, CTLA-4, and PD-1) and activation markers (CD69 and HLA-DR)	23–36	Case-control study	30 healthy pregnant women and 20 GDM patients	6
5	Gomes Fagundes et al[28]	Brazil	Maternal and fetal outcomes	BMI was divided into < 25 and > 25	Maternal blood, cord blood and colostrum	At third trimester of pregnancy	The subsets of cells (both CD3+ and CD4+ populations, the ‘naıve’ cells were CD45RA+ and the ‘memory’ cells were CD45RO+) and cytokine profile	18-45 years old	Cross-section	15 healthy pregnant women, 13diabetes mellitus gestational women	8
6	Friebe-Hoffmann et al[12]	Germany	Maternal outcomes	NA	Peripheral venous blood	At third trimester	CD3-, CD4-, CD8- and γδ T-cells as well as B-, NK-, NKT- and dendritic cells	19-44 years old	Cross-section	24 pregnant controls, 18 women with GDM	6
7	Lobo et al[29]	Brazil	Maternal outcomes	Overweight (pre- pregnancy BMI ≥ 25 kg/m2)	Peripheral venous blood	At third trimester of pregnancy	Treg and NK cells	34.14 ± 1.99	Case-control study	27 glucose- tolerant (controls) and 31 GDM overweight pregnant women	6
8	Sheu et al[16]	Australia	Maternal outcomes	25.4 ± 6.0	Peripheral venous blood	At third trimester of pregnancy and 7 weeks postpartum	Th17, Th2, Th1 and Treg cells	33.6 ± 3.4	Cohort	55 women with GDM (cases) and 65 healthy controls	7
9	Sifnaios et al[30]	Greece	Maternal outcomes	NA	Peripheral venous blood	At third trimester of pregnancy and 6 months postpartum	Th17, Th2, Th1 and Treg cells	≥ 18 years old	Cross-section	26 women with GDM (cases) and 23 healthy controls	6
10	Zhao et al[31]	China	Maternal outcomes	NA	Maternal Blood, Cord Blood and Placenta	At third trimester of pregnancy	CD3+, CD4+, and CD8+ T cells	27.45 ± 1.25	Cohort	28 women with GDM (cases) and 28 healthy controls	7
11	Schliefsteiner et al[19]	Austria	Maternal outcomes	32.8 ± 7.6	Placenta	The second trimester	M1 or M2 phenotype macrophages	NA	Pilot-study	Healthy women (n = 5) and women with GDM (n = 6)	6
12	Huang et al[11]	China	Maternal outcomes	23.28 ± 3.37	Peripheral venous blood	At third trimester of pregnancy	Lymphocyte, neutrophils, inflammatory cytokines, placenta-derived macrophages, and their products	29.26 ± 4.65	A case-control and cohort study	214 women with GDM and 926 women without	7
13	Angelo et al[32]	Brazil	Maternal outcomes	29.65 ± 4.58	Peripheral venous blood	At third trimester of pregnancy	Flow cytometry was used to assess peripheral blood monocytes subsets (classical, intermediate, non-classical)	34.74 ± 1.64	Case-control study	18 women with GDM (cases) and 20 healthy controls	6
14	Xiong et al[21]	China	Maternal outcomes	21.08 ± 2.60	Peripheral venous blood	At third trimester of pregnancy	NK cell subsets	32.9 ± 3.21	Cross-section	10 women with GDM (cases) and 10 healthy controls	6
15	Ye et al[33]	China	Maternal outcomes	24.54 ± 4.49	Peripheral venous blood	At third trimester of pregnancy	PD-1 expressed on T-cell subsets	29.91 ± 4.43	Cross-section	55 women with GDM (cases) and 55 healthy controls	8
16	Wang et al[34]	China	Maternal outcomes	28.42 ± 3.26	Peripheral venous blood	At third trimester of pregnancy	Leukocyte, neutrophil, monocyte, and lymphocyte counts	29.13 ± 4.39	Case-control study	147 women with GDM (cases) and 161 healthy controls	8
17	Yang et al[35]	China	Maternal outcomes	BMI ≥ 25 kg/m2	Peripheral venous blood	At first trimester of pregnancy	CD4+CD25+FOXP3+	Cohort	21 women with GDM (cases) and 34 healthy controls	7
18	Wang et al[36]	China	Maternal outcomes	Second 23.1 ± 1.3; Third 26.1 ± 1.6	Peripheral venous blood	Second and third trimesters	Treg cells	26.8 ± 1.7	Cohort	GDM: 45 (17 = 2nd.28 = 3rdT); Control: 104 (28 in the first trimester, 43 in the second trimester,	6
19	Fagninou et al[37]	Benin	Maternal outcomes	NA	Peripheral venous blood	At third trimester of pregnancy	Serum IL-10 and Th1 and Th2ratio measured. NK cells and monocytes	30.6 ± 3.04	Case control	15 women with GDM (cases) and 25 healthy controls	6

GDM: Gestational diabetes mellitus; NOS: Newcastle-Ottawa Scale; BMI: Body mass index; NK: Natural killer.

Total lymphocytes and CD3+ T cells in GDM

Five studies reporting total lymphocytes in maternal peripheral venous blood of GDM patients were analyzed (SMD = 0.05, 95%CI: -0.16 to 0.26) (Supplementary Figure 1A). A significant increase in total lymphocytes was observed in GDM patients compared to controls, with high heterogeneity existed (Supplementary Figure 1A). The funnel plot (Supplementary Figure 1B) and sensitivity analysis (Supplementary Figure 1C) demonstrated the stability of this result. Egger’s (P = 0.018) and Begg’s tests (P = 0.462) indicated the presence of publication bias, which was addressed using the trim-and-fill method (Supplementary Figure 1D).

Similarly, CD3+ T cells showed no overall change in the GDM group (overall SMD = -0.34, 95%CI: -1.01 to 0.32) (Figure 2A), as well as in subgroup analyses of different maternal samples, including peripheral venous blood (SMD = -0.99, 95%CI: -2.07 to 0.09), cord blood (SMD = 0.33, 95%CI: -1.44 to 2.11), and placental blood (SMD = -0.32, 95%CI: -0.84 to 0.21), with a normal funnel plot (Supplementary Figure 2A) and sensitivity analysis (Supplementary Figure 2B). However, CD3+ T cells were higher in the colostrum of GDM patients (SMD = 1.05, 95%CI: 0.22 to 1.87) (Figure 2A).

Figure 2 Forest plot. A: Forest plot for SMD in CD3+T cells between gestational diabetes mellitus (GDM) cases and controls; B: Forest plot of total CD4+T cells between GDM cases and controls; C: Forest plot of activation markers positive on CD4+T cells between GDM cases and controls; D: Forest plot of Treg cells between GDM cases and controls; E: Forest plot of total CD8+T cells between GDM cases and controls.

CD4+ T lymphocytes in GDM

A total of five studies investigated the relationship between CD4+ T cells and GDM. The overall level of CD4+ T cells was significantly increased in GDM patients (WMD = 3.08, 95%CI: 0.81-5.35) (Figure 2B). Begg’s (P = 0.288) and Egger’s (P = 0.583) tests indicated no significant publication bias, and the funnel plot displayed a symmetrical distribution (Supplementary Figure 3A). Additionally, sensitivity analysis, performed by sequentially excluding each study, did not alter the results (Supplementary Figure 3B), confirming the stability of the findings. Activated CD4+ T cells, defined by positive markers such as CD69 and HLA-DR, were also elevated in GDM patients compared to controls (WMD = 0.20, 95%CI: 0.06-0.34) (Figure 2C). Further analysis using funnel plots and sensitivity analysis showed normal distribution (Supplementary Figure 4). However, PD1+ CD4+ T cells levels were similar between GDM patients and controls in peripheral venous blood (SMD = 0.06, 95%CI: -0.99-1.11) (Supplementary Figure 5A), with Egger’s test indicating statistical bias (P = 0.009). Consequently, additional analyses, including funnel plot, sensitivity analysis, and trim-and-fill analysis, were conducted (Supplementary Figure 5B-D).

Treg cells in GDM

For Treg cells, significant heterogeneity (I² = 86.5%, P < 0.001) was observed in the SMD analysis between GDM patients and controls (Figure 2D). The overall results, as well as the subgroup analysis of the three trimesters, indicated that Treg cells were generally lower in the GDM group (SMD = -0.83, 95%CI: -1.31 to -0.34) (Figure 2D). However, the limited number of extractable results from the first and second trimesters made it difficult to draw definitive conclusions, while the third trimester data suggested a decrease in Treg cell levels in GDM patients (Figure 2D). The funnel plot (Supplementary Figure 6A) and sensitivity analysis (Supplementary Figure 6B) confirmed the stability of these overall findings.

CD8+ T lymphocytes in GDM

The overall association between the CD8+ T cell population and GDM was examined in four eligible studies. Specifically, maternal CD8+ T cells from different samples (peripheral venous blood, cord blood, and retro-placental blood) showed no significant changes in GDM samples compared to normal controls (SMD = 0.21, 95%CI: -0.31 to 0.73) (Figure 2E). Further analysis using funnel plots (Supplementary Figure 7A) and sensitivity analysis (Supplementary Figure 7B) demonstrated no evidence of publication bias.

Monocytes in GDM

Three studies with five extractable results examined monocyte levels in GDM. Overall, there was no significant difference in monocyte levels between GDM patients and controls (SMD = -0.19, 95%CI: -0.46 to 0.07) (Supplementary Figure 8A). The funnel plot and sensitivity analysis indicated stability, showing no study needed to be excluded for instability (Supplementary Figure 8B and C).

Cytotoxic NK and NKT cells in GDM

Three studies reported on the population ratios of NK cells and NKT cells in GDM. The results indicated that GDM did not significantly affect NK cell levels in maternal peripheral immune profiles (SMD = -0.54, 95%CI: -1.28 to 0.20) (Supplementary Figure 9A). Similarly, NKT cells showed no significant changes in GDM peripheral blood (SMD = 0.83, 95%CI: -1.10 to 2.75) (Supplementary Figure 9B).

Macrophages, Th1, and Th17 cells in GDM

One study compared the macrophage population in the placenta of GDM patients and controls, finding a significant increase in macrophages in GDM subjects compared to the control group[19]. Another study observed higher levels of circulating macrophage markers, including sCD163 and sCD14, in GDM patients during pregnancy and at a five-year follow-up[38]. In addition to macrophages, two other studies found that Th1 and Th17 cell populations were increased in the peripheral immune profiles of GDM patients[16,30].

DISCUSSION

Chronic low-grade inflammation, similar to that observed in obesity and type 2 diabetes, is often associated with GDM and may be one of its pathogenic mechanisms[39]. As crucial components of the inflammatory system, various immune cell populations show significant changes in GDM patients, potentially playing a critical role in GDM development[40]. To elucidate the pathology and contribution of the immune system in GDM progression, our study systematically analyzed different types of immune cells, including total lymphocytes, CD4+ T and CD8+ T cells, monocytes, NK and NKT cells, Treg, Th1, Th17 cells, and macrophages.

CD4+ T cell subsets have been reported to play significant roles in the pathogenesis of GDM. The involvement of CD4+ T cells in GDM can be described through their impact on inflammation and insulin resistance. In GDM, there often existed a shift towards a proinflammatory state[16]. Th1 cells produce IFN-γ, which can exacerbate inflammation, while Th17 cells secrete interleukin-17 (IL-17), contributing to the recruitment of inflammatory cells and promoting an inflammatory environment in tissues such as the placenta[40]. For CD4+T cells in insulin resistance, the inflammatory cytokines produced by CD4+ T cells, including IFN-γ and tumor necrosis factor-alpha, can interfere with insulin signaling pathways, leading to insulin resistance[41,42]. This is a key feature in the development of GDM, where the body's normal response to insulin is impaired, resulting in elevated blood glucose levels. Tregs, another subset of CD4+ T cells, play a crucial role in maintaining immune tolerance and preventing excessive inflammation. In GDM, the balance between pro-inflammatory T cells and Tregs may be disrupted, leading to a reduction in the anti-inflammatory effects of Tregs. This imbalance can contribute to the chronic inflammatory state seen in GDM. Overall, CD4+ T cell subsets influence the development and progression of GDM through their roles in promoting inflammation and inducing insulin resistance. Understanding these mechanisms can help in developing targeted therapies to modulate immune responses and improve outcomes for patients with GDM. Our study observed immune dysregulation in GDM patients, with peripheral immune cells such as CD4+ T cells (including total CD4+ T cells and activated CD4+ T cells) being highly expressed in GDM (WMD = 3.08; 95%CI: 0.81-5.35), indicating an active peripheral immune status. Among the classical subgroups of CD4+ T lymphocytes, Treg cells tended to be lower in GDM compared with controls (SMD = -0.83; 95%CI: -1.31 to -0.34). However, there were too few eligible studies to confirm the changes in Th1 and Th17 cells.

Regarding the various sample types (venous, cord, colostrum, and retroplacental blood) for the analysis of immune cells, we found that changes in immune cell populations may not be uniform across different sample types, and the inter-sample variability may impact the interpretation of pooled results. For example, colostrum, as an early postpartum secretion, contains immune cells that may reflect maternal immune responses post-delivery, whereas peripheral blood primarily represents the maternal immune system during pregnancy. The immune cells in colostrum may have undergone activation or differentiation in response to parturition and lactation, potentially altering their profiles compared to those in peripheral blood[43]. Secondly, variations in immune cell composition across gestational stages may also contribute to these inconsistencies. These findings underscore the importance of considering sample type and timing when interpreting immune responses in GDM. Future studies should aim to stratify data by sample type and gestational stage to better capture the nuances of immune cell variations across different conditions.

Although the mechanisms underlying immune system disorders in GDM are not fully understood, several explanations may help elucidate the relationship between immune regulation and GDM. The effect of trace elements on immune cell regulation may be a significant factor. Zinc (Zn++) and copper (Cu++) have been shown to be related to GDM and its immune regulation[25]. Increased circulating Cu++ levels in GDM patients are consistent with the active immune status characterized by elevated immune cells, including CD3+ T, CD4+ T, CD8+ T, monocytes, NK, and NKT cells. Additionally, the balance of pro-inflammatory and anti-inflammatory cytokines may contribute to the underlying mechanisms. Th17 cells and their secreted cytokines play a pro-inflammatory role in GDM[44]. Maternal hyperglycemia is positively correlated with the cytokine IL-17 during GDM[28], indicating that inflammatory cytokines significantly impact GDM development. Conversely, the reduction in Treg cells observed in GDM may further amplify immune dysregulation. Treg cells are critical for maintaining immune tolerance and preventing excessive inflammatory responses. A decrease in Tregs may thus promote the chronic low-grade inflammation seen in GDM, impairing insulin sensitivity and increasing the risk of metabolic disturbances. Further elucidating these molecular interactions, such as the dysregulation of cytokine networks and alterations in signaling pathways may help clarify the mechanistic links between immune cell changes and GDM pathogenesis. Future research investigating these pathways in detail is essential for identifying potential therapeutic targets for GDM.

There are several limitations in our study. First, the treatment of GDM may be a confounding factor for the immune cell populations in our results. Insulin treatment, known for its anti-inflammatory effects in diabetes and GDM[45-47], may influence immune changes in GDM patients. Future studies on GDM and immune homeostasis should distinguish between subjects receiving insulin treatment and those not. Publication bias is a potential concern in any meta-analysis, particularly in the context of immune cell studies in GDM. Moreover, the lack of longitudinal data represents a significant limitation. Most included studies were cross-sectional, making it challenging to assess causality or to observe the temporal dynamics of immune cell changes in GDM. Longitudinal studies are crucial to understanding how immune alterations evolve over time during pregnancy and contribute to the pathogenesis of GDM. Additionally, the variability in study types and the unusual examination of some cell groups led to the exclusion of some immune indicators, such as macrophages, Th1, and Th2 cells. Consistently, the analysis of certain immune cells (e.g., NK and NKT cells) is based on a small number of studies, which limits the generalizability of the findings. Additionally, other immune cells like eosinophil counts, which also linked to insulin resistance, was also unknown with GDM in this study as the limited available studies. Moreover, the pro-inflammatory and anti-inflammatory cytokines secreted by immune cells including TNF, IL-6, INF-γ, and IL-17 were not analyzed by this study, which also because of the limited included studies. Due to the limited number of included studies, further large-scale research is needed to confirm these findings. Additionally, the pooling of data from diverse blood samples, including venous, cord, colostrum, and retroplacental blood, presents a potential issue in interpretation. While a random effects model and subgroup analysis were employed to account for the inherent variability between studies, the underlying assumption of homogeneity in immune cell distributions across these different blood sources may not hold. Therefore, future studies addressing these issues with more standardized sampling methods and stratified analyses would enhance the robustness of findings in this area.

CONCLUSION

In conclusion, our study found that GDM is characterized by dysregulated immune status, including increased subgroups of CD4+ T cells and decreased Treg cells. Peripheral immune disorders are evident in GDM, highlighting the need for greater attention to immune regulation in the treatment of GDM in the future.