Assessment of Kir Genes in the Venezuelan Ad-Mixed Population with Either Idiopathic Recurrent Pregnancy Loss or Unexplained Infertility

Abstract

Killer-cell immunoglobulin-like receptors (KIRs) play a crucial role in the cytotoxic activity of natural killer (NK) cells, encompassing both inhibitory and activating types. A higher ratio of cytotoxic to inhibitory receptors may harm successful pregnancies by disrupting the uterine environment. Ongoing debates surround the impact of KIR gene variations on recurrent pregnancy loss (RPL) and infertility across populations. This study aimed to explore KIR gene polymorphisms in RPL and infertility among the Venezuelan admixed population. The Venezuelan population exhibits a genetic mix of Caucasian, African, and local Amerindian ancestry, distinguishing it from other Latin American admixed populations. This study included 100 controls and 86 patients: 73 women with idiopathic RPL (53 primary and 20 secondary) and 13 infertile patients (4 primary and 9 secondary). The frequency of activating receptors KIR2DS2 and KIR2DS3 was significantly lower (p < 0.05) in the whole patient group compared to controls. However, when analyzing the haplotypes and genotypes, the significance between patients and controls was lost. When comparing RPL and infertile patients, KIR2DS2, KIR2DL3, 2DL5, and 3DL1 were significantly less frequent in infertile women. In infertile women, KIR2DS3 frequency was increased compared to controls and RPL. The results suggest that the frequency of inhibitory receptors may differentiate patients with RPL and infertility. Further studies should ascertain the expression and function of KIRs in uterine NK cells in patients with RPL and infertility.

1. Introduction

Killer-cell immunoglobulin-like receptors (KIRs) are type I transmembrane glycoproteins found on natural killer (NK) cells and some T cells. They are paired receptors, with some having activating functions and others inhibitory ones. Inhibitory KIRs feature long intracellular chains, while activating KIRs typically have short cytoplasmic tails. KIRs, which can have 2–3 intracellular domains (KIR2 or KIR3), play a crucial role in regulating NK cell functions by interacting with MHC class I molecules [1].

The genes for KIRs are found in a 150 kb region of the leukocyte receptor complex on chromosome 19q13.4 [2]. At least 15 genes and 2 pseudogenes encode KIRs, which are polymorphic and exhibit significant variation among individuals [2]. They are also polygenic, so it is rare for two unrelated individuals to possess the same KIR genotype [2]. KIRs can differentiate MHC I allelic variants, helping detect virally infected or transformed cells. Most KIRs are inhibitory, suppressing NK cell cytotoxic activity, and are crucial for fetal survival in the uterus’s tolerogenic environment [3,4].

The ability to spare normal tissues while attacking transformed cells is called the “missing self” hypothesis [5,6]. This phenomenon is related to MHC class I-specific inhibitory receptors, which functionally dominate the triggering potential induced by activating receptors [7]. Thus, NK cells use a complex array of inhibitory or activating receptor/ligand interactions, the balance of which regulates NK cell function and cytolytic activity [8,9].

Most uNK cells express high levels of CD94/NKG2A and variable KIRs, unlike peripheral blood NK cells (pNKs) and decidual NK cells (dNKs) [10]. After the first trimester, KIRs specific for HLA-C are downregulated in uNK cells, which are found in higher proportions than in peripheral NK cells [11,12,13]. The interaction between uNK KIRs and HLA-C may be crucial for placental formation [14,15]. During the first trimester, many decidual (dNK) cells express killing receptors NKp30 and NKG2C, which are rare in pNKs [16,17,18]. Immature NKs in the uterine lining can differentiate into uNKs, acquiring KIRs influenced by factors in the endometrium and decidua [10,19]. uNKs show lower levels of KIR2D than pNKs, and HLA-C expression is positively regulated by stromal cells in the decidua [20,21]. dNKs express the 2B4 receptor, which is excitatory in pNKs but inhibitory in dNKs. Extravillous trophoblasts express HLA-E and G, serving as ligands of inhibitory receptors on uNK and dNK cells [21,22,23]. Studies suggest maternal KIRs and fetal HLA-C genotypes influence trophoblast invasion [24,25]. Although uNKs cannot independently lyse trophoblasts, their cytotoxicity can increase with IL-2, potentially leading to placental damage and miscarriages [26,27].

Idiopathic infertility and RPL are two different entities. Infertility refers to a lack of implantation and pregnancy, which can be primary, refer to no pregnancy, or refer to secondary infertility after a successful pregnancy. Similarly, RPL can be primary, refer to no successful pregnancy, or a secondary non-successful pregnancy after a successful pregnancy [4,10,14]. NK cells play a role in RPL; however, their role in infertility remains under investigation. Due to the complexity of studies on NK cells in human tissue, genetic studies have become an alternative for understanding the role of KIRs in implantation, pregnancy, fertility, recurrent pregnancy loss, and preeclampsia.

Haplotype analysis of KIRs provides a critical assessment of the genes relevant to the disease. A specific gene can be at a lower or higher frequency, but the haplotype defines the likelihood of association with the disease [28]. KIR2DS1 expression (part of KIR haplotype B) in uNK cells is crucial for successful implantation; however, women with RPL have lower transcription and receptor expression, and their couples exhibit higher HLA-C2 expression, which could be responsible for uNK activation [29,30,31]. In a study conducted in England, women with RPL were found to have a higher frequency of haplotype AA KIRs, a lack of excitatory KIRs, and low expression of KIR2DS1 [32]. The fetuses of these women had higher levels of HLA C2 compared to their mothers (i.e., Mother C1/C1 with fetus C1/C2 or mother C1/C2 with fetus C2/C2), which could explain the increase in abortions [32]. Similar reports were published in other populations [33]. In addition, the same phenomenon was reported in patients with preeclampsia [29,33,34].

A Spanish study highlighted the significance of the CenAA KIR haplotype [35]. KIR haplotype B telomeric genes (Tel-B genes) (3DS1, 2DL5A, 2DS5, and 2DS1) may protect against pregnancy complications (frequent abortion, slow intrauterine growth, and pre-eclampsia) [36,37,38]. In caucasian women positive for KIR2DS1, HLA-C2 expression was associated with frequent miscarriage [32,39,40,41]. On the other hand, in patients with pre-eclampsia and slow intrauterine growth, inhibitory KIRs are expressed more frequently than their activating counterparts [24,25]. Thus, genetic analysis of KIRs provides essential insights into the possible genetic background of patients with idiopathic infertility and RPL.

In genetic epidemiology studies, admixed populations offer unique advantages for association analyses between genotypes, haplotypes, phenotypes, and disease [42]. The study aimed to determine the possible role of KIR genetic polymorphisms in patients with RPL and infertility from a Venezuelan admixed population. The frequencies of individual genes and haplotypes were compared among the three groups: controls, women with RPL, and women with idiopathic infertility.

2. Materials and Methods

2.1. Samples

The investigation was conducted in accordance with the principles outlined in the Declaration of Helsinki, as revised in 2013. The Institute of Immunology’s Ethical Committee approved the study. Faculty of Medicine. Universidad Central de Venezuela (approval number 20052308). Written consent was obtained from all individuals who were interested in participating in the study, and the Ethics Committee approved the publication of the results.

The study involved 100 healthy women with normal pregnancies, free from conditions like viral diseases, hypertension, diabetes, metabolic syndrome, or hormonal imbalances. Control samples were collected during routine gynecological checkups, including ecosonogram, vaginal, and endometrial screening. The women were not pregnant when the blood sample was taken.

The patient group involved 86 women. The RPL group consisted of women with frequent pregnancy loss of 2 or more successive miscarriages before 20 weeks of gestation. Women with no successful pregnancy were categorized as primary RPL. On the contrary, women with a previous successful pregnancy, but subsequent pregnancy losses before 20 weeks of gestation, were considered secondary RPL [40]. Similarly, women with primary infertility were defined by the lack of pregnancy, and secondary infertility was defined as those who had a previous pregnancy, but were unable to conceive [43]. Ecosonogram imaging was performed in all women, as was the assessment of the blood tumor antigen CA125, an indirect marker of endometriosis. Women with clinically proven endometriosis, and couples with chromosomal abnormalities, autoimmunity, antiphospholipid syndrome, endocrinopathies, uterine abnormalities, malnutrition, smoking, alcoholism, drug addiction, sexually transmitted infection diseases, and male infertility were excluded from the study. The blood samples were taken when the women were not scheduled for a medical procedure or pregnant.

The genetic admixture of both the patients and the control group has been previously validated [44,45].

2.2. Genomic DNA, PCR Amplification, and Analysis of Results

Genomic DNA isolation was performed using the AxyPrep Blood Genomic DNA Miniprep Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions. Briefly, 500 µL of AP1 lysis buffer was mixed with 200 µL of the buffy coat in a 1.5 mL Eppendorf tube, and the mixture was vortexed for 10 s. Then, 100 µL of AP2 buffer was added; the mixture was vortexed for 20 s and centrifuged at 90× g for 10 min at room temperature. The supernatant was placed on a special AxyPrep column in a 2 mL tube and centrifuged at 200× g for 2 min. The filtered product was discarded, and the column was reloaded with 700 µL of W1A washing buffer at room temperature for 2 min, followed by centrifugation at 200× g for 1 min. After the filtered material was discarded, 800 µL of W2 washing buffer was added, and the mixture was centrifuged at 200× g for 1 min. This step was repeated using 500 µL of the same washing buffer. Lastly, the column was placed in a 1.5 mL Eppendorf tube containing 200 µL TE buffer, and the mixture was centrifuged for 1 min at 90× g to obtain genomic DNA.

DNA concentration was determined using the GeneQuant II spectrophotometer for DNA/RNA (Amersham Pharmacia Biotech, Chalfont St. Giles, UK). The absorbance ratio at 260 and 280 nm was approximately 1.9 for each sample, and the DNA concentration was adjusted to 40 ng/µL. Purified DNA was stored at −20 °C until needed.

PCR was performed using specific initiation sequences (PCR-SSP), as listed in Supplementary Table S1, following the protocol described previously [46]. The protocol includes growth hormone (GH) 1 Initiator as the control of DNA amplification. The final volume of the reaction mixture was 25 μL with 9.85 μL of nuclease-free water and 2.5 μL of 10× buffer (200 mM Tris-HCl and 500 mM KCl), 3.3 mM MgCl₂, 2.5 mM KCl, 0.4 mM Tris-HCl, 0.2 mM dNTP mix, 0.5 μL forward and reverse initiators for each KIR gene (final concentrations indicated in the Supplemental Table S1), 0.5 mM of each GH1 Initiator, 1U of Taq polymerase (Platinum; Invitrogen, Waltham, MA, USA). The PCR was performed using the MJ Research PTC-200 thermocycler under the following conditions: initial denaturing for 2 min at 95 °C, then 10 circles of 20 s at 94 °C, 10 s at 65 °C and 1.5 min at 72 °C (denaturing, hybridization, and extension temperatures) followed by 20 cycles of 20 s at 94 °C, 10 s at 61 °C and 1.5 min at 72 °C. The amplified products were analyzed by 2% agarose gel. The PCR products were separated by 2% agarose electrophoresis, and the gels were then labeled with a standard Ethidium Bromide solution. The size of the amplified product was quantified using a 1 kb molecular weight ladder (100 bp to 12,000 bp).

As a control, the amplified products were sequenced by the sequencing service of the Venezuelan Institute of Scientific Research (IVIC) to certify the results. All of the results were certified.

2.3. Statistical Analysis

All data in the manuscript are expressed as percentages.

KIR frequency (F) was calculated by directly counting the number of KIR genes that were present or absent, and the final values were expressed as a percentage of the total number of KIR genes.

Gene frequency (f) or relative gene frequency in a population was calculated with the formula shown below:

$$\mathrm{f} =1-\surd \left(\right(1-\mathrm{F}\left)\right)$$

f: gene frequency. F: the presence of the gene in percentage over a hundred (%/100).

The statistical tests were performed using GraphPad software version 5. In the analysis, Chi-square χ² and ANOVA tests were employed. p-values that were lower than 0.05 were considered to be statistically significant.

3. Results

The characteristics of controls and patients are represented in

Table 1. Characteristics of the population.

	n	Age (Mean ± DE)	# Pregnancies	# Abortions	Weeks of Gestation
RPL primary	53	35.53 ± 5.64	1.8 ± 1.2	2 (30%) >2 (70%)	8.6 ± 2.6
RPL secondary	20	36.11± 4.62	2.7 ± 0.9	2 (40%) >2 (60%)	7.3 ± 3.9
Primary infertility	4	35.85 ± 4.73	0	0	0
Secondary infertility	9	38.9 ± 4.73	1 ± 0.2	0	0
Control	100	34.5 ± 5.5	1 (10%) 2 (60%) 3 (30%)	0	37.3 ± 2.2

# means “number of”.

. No significant differences in age were observed across the groups. As expected, the critical differences are recorded between patients and controls in the number of abortions and weeks of gestation (RPL group, p < 0.0001). No gestations were recorded in the infertile group. In addition, gestational weeks were significantly different (p < 0.0001).

Table 2. Frequencies in KIR inhibitory genes in patients and controls.

	C	Total Patients	p	Patients Rpl Infertile		p
N	100	86	-	73	13	-
KIR2DL1	89	93	0.60	96	77	0.06
KIR2DL2	47	40	0.70	40	39	0.9
KIR2DL3	80	82	0.89	89	39	0.01
KIR2DL4	100	100	-	100	100	-
KIR2DL5	60	49	0.25	63	31	0.03
KIR3DL1	90	93	0.7	97	69	0.04
KIR3DL2	100	100	-	100	100	-
KIR3DL3	100	100	-	100	100	-

depicts the frequencies of inhibitory and activator receptors. No differences in the presence of inhibitor genes were recorded when the total number of patients was analyzed. However, the patients were divided into two groups based on RPL and infertility; the frequencies of the genes KIR2DL3, KIR2DL5, and KIR3DL1 were significantly different between infertile women and the RPL group. The KIR2DL1 gene showed marginal significance; the frequency was also lower in infertile women. The number of infertile patients is a limiting factor for strict statistical analysis.

The frequency values in the table are expressed in percentages. No significant differences were found when analyzing each gene individually between the control and patient groups. However, when the patient groups were divided into RPL and infertile groups, significant differences emerged in the frequencies of the genes KIR2DL3, KIR2DL5, and KIR3DL1. Caution is advised due to the small sample size of the infertile group.

Table 3. Frequency of excitatory KIR genes and pseudogenes in patients and controls.

	C	Total Patients	p	Patient Rpl Infertility		p
N	100	86		73	13
KIR2DS1	45	46	0.9	48	38	0.8
KIR2DS2	68	48	0.04	54	23	0.02
KIR2DS3	30	17	0.03	12	47	0.02
KIR2DS4	77	86	0.09	86	85	0.9
KIR2DS5	41	41	0.9	42	31	0.7
KIR3DS1	45	45	0.9	53	46	0.8
KIR2DP1	84	87	0.9	88	80	0.9
KIR3DP1	100	100	100	100	100	-

illustrates the activating receptor cluster. Significant differences were observed in KIR genes 2DS2 and 2DS3 when the total patient group was compared to the control group. Nevertheless, these differences were also observed between the frequencies observed between RPL and infertile patients. Interestingly, the frequency of KIR2DS2 is low, whereas that of KIR2DS3 is higher in the infertile group than in the RPL group. In the case of KIR2DS2 frequency, the decrease is observed in both patient groups, whereas in KIR2DS3, it is observed only in the RPL group.

The frequency values in the table are expressed in percentages. When comparing the control group with the total patient group, the frequencies of KIR2DS2 and KIR2DS3 were significantly lower in the patient group. However, when the patient groups were divided into those with RPL and those with infertility, significant differences emerged in the frequencies of the KIR2DS2 and KIR2DS3 genes. Caution is advised due to the small sample size of the infertile group.

The different haplotypes were generated from the data for each individual.

Table 4. Analysis of the Haplotype A between controls and patients. Percentage of expression.

Haplotype	Gene	C	RPL	INF	p	Haplotype-	Gene	C	RPL	INF	p
A-CenA-TelA	3DL3	100	100	100	0.32	A Cen A-TelB	3DL3	100	100	100	0.55
	2DL3	100	100	100			2DL3	80	89	38
	2DP1	84	87	69			2DP1	84	88	69
	2DL1	90	95	77			2DL1	90	95	77
	3DP1	100	100	100			3DP1	100	100	100
	2DL4	100	100	100			2DL4	100	100	100
	3DL1	90	97	69			3DS1	45	61	46
	3DS4	77	86	85			2DL5	60	63	30
	3DL2	100	100	100			2DS5	41	15	30
							2DS1	45	48	38
							3DL2	100	100	100

,

Table 5. Analysis of the Haplotype B between controls and patients. Percentage of expression.

Haplotype	Gene	Controls	RPL	INF	p	Haplotype-	Gene	Controls	RPL	INF	p
Cen B-TelA	3DL3	100	100	100	0.8	CenB-TelB	3DL3	100	100	100	0.66
	2DS2	68	54	38			2DS2	68	54	38
	2DL2	47	40	39			2DL2	47	40	39
	2DL5	60	63	31			2DL5	60	63	31
	2DS3	30	14	39			2DS3	30	14	39
	2DP1	84	88	69			2DP1	84	88	69
	2DL1	90	96	77			2DL1	90	96	77
	3DP1	100	100	100			3DP1	100	100	100
	2DL4	100	100	100			2DL4	100	100	100
	3DL1	90	97	69			3DS1	45	62	46
	2DS4	77	79	100			2DL5	60	63	31
	3DL2	100	100	100			2DS5	41	15	31
							2DS1	45	48	39
							3DL2	100	100	100

and

Table 6. Analysis of the Haplotype C between controls and patients.

Haplotype	Gene	Controls	RPL	INF	p	Haplotype-	Gene	Controls	RPL	INF	p
C-A	3DL3	100	100	100	0.3	C-B	3DL3	100	100	100	0.7
	2DL3	80	89	38			2DS2	68	54	38
	2DP1	84	88	69			2DL2	47	40	39
	2DL1	89	95	77			2DL5	60	63	31
	3DP1	100	100	100			2DS5	41	15	31
	2DL4	100	100	100			2DS1	45	48	39
	3DS1	45	62	46			3DL2	100	100	100
	3DP1	100	100	100
	2DL4	100	100	100
	3DL1	90	97	69
	3DS4	77	86	85
	3DL2	100	100	100

represent haplotypes A, B, and C, respectively. In haplotype A (Table 4), which is primarily composed of inhibitory genes, a more stringent statistical analysis of the genes comprising haplotype B (Table 5) revealed no statistical significance. In Haplotype C (Table 6), there are no significant differences between the two groups.

The statistical assessment was performed across the three groups, and the p-value represents the analysis of each gene within each group. No statistically significant difference was found when the entire patient group was compared to the controls.

In

Table 7. Genotype expression of controls and patients.

2DL2					3DL			2DS					3DS	2DP	3DP
1	2	3	4	5	1	2	3	1	2	3	4	5	1	1	1	G	CONTROLS	PATIENTS	P
																1	16	26	0.3
																2	7	9	0.8
																3	7	6	0.6
																4	7	6	0.9
																7	5	3	0.7
																10	2	3	0.8
																14	0	3	0.3
																21	5	2	0.2
																25	2	0	0.5
																27	0	0	0
																64	2	0	0.5
																69	0	2	0.8
																71	0	2	0.8
																72	7	3	0.2
																73	7	6	0.8
																76	2	5	0.6
																86	2	5	0.6
																195	2	3	0.8
																260	2	0	0.4
																* 1	2	0	0.4
																* 2	7	0	0
																* 3	5	5	0.6
																* 4	0	3	0.9
																* 5	0	3	0.2
																* 6	7	3	0.4
																* 7	2	2	0.9
																* 8	2	0	0.7

* atypical gene.

, the different genotypes are represented by the distribution of genes. There are no significant differences in the genotypes encountered. Eight genotypes in the lower part of the table are considered atypical compared to other populations [47]; however, their frequencies are very low. The first 8 genotypes account for more than 50% of the genotypes in both groups. It is expected that no significant differences will be encountered in the wide variety of genotypes. The results should be analyzed with caution due to the genetic diversity of the genotypes, which is typically encountered in mixed populations.

The genotype (G) was analyzed based on the presence or absence of specific genes, as documented previously [46,47]. There are no statistical differences between controls and patients in the 27 genotype variations. The asterics denote new genotypes.

4. Discussion

The findings of the current study elucidate specific differences in the frequencies of the activating genes KIR2DS2 and KIR2DS3 across the entire patient cohort. Upon categorizing patients by infertility and RPL status, significant differences emerged in the frequencies of KIR2DL3, KIR2DL5, and KIR2DL2, with KIR2DL5 showing marginal significance. Notably, the expression of these genes was lower in the infertile group. Although the limited sample size constrains the results, they suggest a potential divergence in KIR gene polymorphisms between the two patient groups. There is an inverse relationship between the frequency of KIR2DS2 and KIR2DS3 in patients. KIR2DS2 is decreased in the infertile group compared to the RPL group, while KIRDS3 is increased. These differences were also significant. The statistical significance of these findings was lost when genotypes and haplotypes were calculated, most likely due to the small sample size.

Endometriosis significantly impacts fertility outcomes, and it is noteworthy that none of the women in the studied cohort demonstrated clinical endometriosis at the time of sample collection (negative CA-125 blood test and ultrasound). Significant differences were observed between the infertile and RPL groups in the frequencies of KIR2DL2, KIR2DL5, and KIR3DL1; KIR2DL1 frequency was also lower in the infertile group. In addition, the decrease in frequency of KIR2DS2 and the increase in frequency of KIR2DS3 in infertile women as compared with those with RPL suggest that the two groups significantly differ. Even though there are no differences in the general haplotypes, these differences may be biologically relevant in uNK and dNK cells. Further studies are required to ascertain this possibility.

Previous studies have shown that women who experience frequent pregnancy loss exhibit reduced expression of the KIR2DL2 gene, which has strong inhibitory capabilities and readily binds to HLA-C, compared with KIR2DL3 [48,49,50,51]. In our cohort, no difference in KIR2DL2 frequencies was observed; however, in infertile women, KIR2DL3 was significantly lower than in the RPL group, suggesting that the analysis of clusters of activating genes and inhibitory genes should be carefully revised [49,50,51,52]. Witt et al. found no significant differences in the frequency of inhibitory or excitatory KIR genes in a group of 51 Caucasian women with frequent miscarriages and 55 women with successful pregnancies in Brazil [52]. Similarly, another study in China by Hong et al. in 2008 [53] arrived at the same conclusion. It is noteworthy that in the study by Hong et al. [53], the inhibitory gene KIR2DL2 was found in higher proportions in women with frequent pregnancy loss, which differs from the data obtained from a study on a population of Mexican women [54] and the present report, where the gene KIR2DL2 was expressed at a low frequency. Torres et al. reported, in a review, that several studies found higher proportions of excitatory KIR genes and diminished expression of their inhibitory counterparts in NK cells of women with RPL [54]. Moreover, Vargas et al. [55] reported a higher frequency of excitatory KIR genes in Brazilian women with frequent spontaneous miscarriages. Varla-Leftherioti et al. [56] reported that patients with a history of frequent miscarriages have a limited repertoire of inhibitory KIRs. These receptors lack the specificity required to promote HLA-Cw binding that may be expressed in the trophoblast [56]. Hence, interactions between inhibitory KIRs and HLA-C molecules may play a significant role in fetal recognition by NK cells during pregnancy [56]. In a meta-analysis, Akbari et al. [57] found that KIR2DS2 and KIR2DS3 were risk factors for RPL, while KIR3DL1 was a protective factor.

The analysis of inheritance and genomic KIR gene structure is complicated because they segregate within haplotypes formed by the presence or absence of genes that encode these molecules, which have inhibitory or excitatory properties for NK cells. Therefore, it is unlikely that randomly selected, unrelated individuals share the same genotype of KIR genes [46,47,48]. More than 390 KIR genotypes have been reported in various studies (Allele Frequencies in Worldwide Populations) and 400 in the Brazilian population [49]. In our study, we identified 27 patient genotypes, each with 8 to 15 genes. Genotype 1 comprises 9 KIR genes, of which 6 are inhibitory (KIR2DL1, 2DL3, 2DL4, 3DL1, 3DL2, and 3DL3), 1 is an activator (KIR2DS4), and 2 are pseudogenes (KIR2DP1 and 3DP1). This genotype was more frequent in patients than in controls, although the difference was not significant. Genotype 2, the second most frequent, comprises 13 KIR genes (7 inhibitory, 4 excitatory, and 2 pseudogenes); again, no significant difference was observed. The frequency of genotype 1 in our group of patients and controls differs from that reported in the Chinese and Japanese populations [45] and in Brazil [49], where it is 40% and 30%, respectively. In the present report, the frequency of genotype 1 is similar to that previously published for the general mixed Venezuelan population (25.85%) and the local Amerindian populations Yucpa (24.59%) and Warao (30.34%) [45].

NK cell-mediated responses in homozygous individuals for haplotype A are primarily inhibitory [40,56,58]. In a study by Hiby et al. [59], haplotype KIR AA was found to have a higher frequency than in controls in a population of women with frequent pregnancy loss in London. In assisted fertility, implantation was increased in women with the KIR AA KIR haplotype; however, these women had a higher probability of pregnancy loss [37]. Gil Laborda et al. [35] also defined the centromeric AA motif as an optimal marker of RPL; however, no significant differences in haplotypes were encountered in the present report.

Based on genetic data from our targeted population, we observed that the B haplotype was more frequent in both patients and controls, and the excitatory B haplotype was more prevalent in controls. This haplotype is highly diverse, including many excitatory KIR genes. Faridi et al. [60] reported a significant increase in the frequency of haplotype KIR BB in a group of patients compared to the control, increasing the risk of miscarriage by 4.4 times in women from India. On the other hand, homozygote A is associated with genotype 1, which was expressed similarly in both groups. There are no significant differences between genotypes C and D. In summary, the differences reported should be analyzed in combination with activating and inhibitory genes and not only in the composition with pseudo and constitutive genes.

The trophoblast plays a crucial role in modulating the immune system to prevent fetal rejection. Unlike other cells, the trophoblast does not express classical HLA class I and II molecules. Instead, it represents “non-classical” HLA class I molecules—specifically HLA-E and HLA-G—along with lower levels of HLA-C. These non-classical molecules are highly polymorphic compared to the classical ones [61,62]. NK cells interact with the trophoblast via several receptors (KIR, ILT, and CD94/NKG2A), which bind the HLA-C, HLA-G, and HLA-E molecules. These interactions can inhibit NK cell-mediated lysis of trophoblast cells and stimulate cytokine production that promotes normal placental growth and healthy pregnancies [42]. However, the microenvironment plays a crucial role in the process [40,61], and some of the inconsistencies encountered in the literature may be due to the lack of a complete medical history in patients with idiopathic infertility and recurrent pregnancy loss. Endometriosis is independent of KIR expression, providing the inflammatory milieu that prevents successful implantation and enhances miscarriage [63].

Analysis of other genetic polymorphisms, as described by Pierkarska et al. [64], may be essential to examine differences between infertility and RPL, which, as proposed in the present report, may differ genetically.

Although the number of samples with infertility in our cohort is small, the decreased frequencies of inhibitory receptors KIR2DL1, KIR2DL3, KIR2DL5, and KIR3DL1 may be associated with an increased risk of implantation failure [62,63]. The results contrast with those obtained with RPL patients and suggest significant differences in KIR expression. A larger sample size may be necessary to unambiguously demonstrate the importance of KIRs in both infertile and RPL patients. The importance of KIR 2DS2 and 2DS3 on RPL in the Venezuelan admixed population should also be analyzed in the context of HLA-C from the partner. KIR expression in local tissue and biological material from abortions is also necessary.

5. Limitations of the Study

There are several limitations of the study: (1) the low number of samples in the infertility group; (2) the low number of patients with secondary RPL, since there may be differences in KIR gene frequencies between primary and secondary; (3) the lack of HLA class I data; (4) the lack of biological material to analyze the expression of KIR in uNK and dNK cells.

6. Conclusions

Notable differences in the frequencies of KIR2DL2 and KIR2DS3 are observed within the patient cohort. Although the number of infertile patients is relatively small, significant variations were identified, with decreased frequencies of KIR2DL3, KIR2DL5, and KIR2DL1, and a discernible tendency towards a decrease in KIR2DL1 frequency. These discrepancies suggest that the function of KIRs may differ in RPL and infertility.

Although the haplotypes and genotypes of KIRs did not differ significantly between patients and controls, the decreased frequency of KIR2DS2 and KIR2DS3 may be a risk factor for infertility or RPL in the Venezuelan admixed population.