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Abstract

Recurrent spontaneous miscarriage (RSM) is a gynecological complication has multifactorial etiologies including genetic factors. However, role of thrombophilic gene polymorphisms in RSA among Jordanian women is limited. This study explores the association between polymorphisms in SERPINC1, PROC, PROS1, PROZ, F5, F13A1, and CPB2 and RSA risk in Jordanian pregnant women. Blood samples were taken from 188 women with recurrent spontaneous miscarriage (RSM) and 193 control subjects without a history of miscarriage. Genomic DNA was extracted and analyzed for polymorphisms of thrombophilic genes using Kompetitive Allele Specific Polymerase Chain Reaction. The SNPStats tool was used to assess haplotype, genotype, and allele frequencies, with chi-square (χ²) tests employed to evaluate statistical significance. A total of seven thrombophilic genes were analyzed. The rs8178607 polymorphism in PROS1 was significantly associated with RSA in Jordanian women under the allelic (OR = 2.06, p = .014), codominant (OR = 2.05, p = .021), dominant (OR = 1.27, p = .015), and overdominant (OR = 1.91, p = .03) genetic models. Additionally, significant associations in the recessive model were observed for the rs1799810 and the rs1926447 polymorphisms in PROC (OR = 1.66, p = .038) and in CPB2 (OR = 1.89, p = .046), respectively. Our data preliminary demonstrates that the rs8178607, rs1799810, and rs1926447 genotypes of PROS1, PROC, and CPB2 respectively, are associated with an increased risk of RSA among Jordanian pregnant women. Further investigations with larger cohorts and family-based analyses are essential to elucidate the genetic variation of biochemical pathways and mechanisms influences recurrent miscarriage susceptibility.

Keywords

recurrent spontaneous miscarriage single- nucleotide polymorphism

Introduction

Spontaneous miscarriage refers to the natural termination of a pregnancy before fetal viability. The WHO defines this stage as a fetus or embryo weighing 500 grams or less, usually aligning with a gestational age of 20 to 22 weeks.¹ Historically, recurrent miscarriage is defined as three sequential first-trimester pregnancy losses with the same biological father, excluding cases of molar, ectopic, and biochemical pregnancies.² This condition affects approximately 3%–5% of child-bearing aged women, while patients diagnosed with recurrent spontaneous miscarriage (RSM) experience repeat pregnancy losses at rates as high as 70%–80%.³

Recurrent miscarriage is a globally prevalent issue, impacting over half a million women each year.⁴ Although non-recurrent miscarriage comprises the majority of cases, approximately 1% of cases are recurrent.⁵ Multiple mechanisms have been implicated in the pathogenesis of recurrent spontaneous miscarriage (RSM), including genetic predisposition, exposure to environmental toxins, hormonal disruptions, and infections. Chromosomal abnormalities are the leading cause of spontaneous miscarriage, contributing to 50% of cases due to genetic anomalies in the embryo.⁶ In addition to genetic factors, anatomical abnormalities, endocrine dysfunctions, infections, autoimmunity, sperm quality, lifestyle habits, psychosomatic influences, environmental exposures, the number of previous pregnancies, maternal age at the first birth, and age at the last pregnancy, the cause of 50%–75% of RSM cases remain unexplained.^7,8

Over recent decades, thrombophilia has been increasingly acknowledged as a potential contributor to recurrent spontaneous miscarriage in women.^9–11 Under normal pregnancy conditions, the coagulation system undergoes modulation to enhance fetal survival through an initial hypercoagulable state, ensuring efficient placental oxygenation and nutrient transfer, followed by a transition to a hypercoagulable state to reduce the risk of postpartum hemorrhage.^12,13 Thrombophilia can be categorized into hereditary and acquired forms, both of which contribute to a hypercoagulable blood state that may lead to RSM and other pregnancy complications, including severe preeclampsia, placental abruption, and intrauterine growth restriction.^10,14,15 Inherited thrombophilia (IT) represents a hypercoagulable condition that heightens the risk of thrombosis. The interaction between IT and the physiological changes in hemostasis during pregnancy has been reported to be linked to an elevated risk of pregnancy complications, occurring in 40%–50% of cases^16,17 and, in some reports, up to 80%.¹⁸

Inherited thrombophilia and the combination of inherited and acquired forms are prevalent, with over 15% of the white population possessing an inherited thrombophilic mutation.¹⁹ Inherited thrombophilia (IT) results from mutations that disrupt the genes’ function in the anticoagulant pathway, thereby inducing a thrombotic tendency in the hemostatic system.^20,21 The contribution of genetic thrombophilia to recurrent miscarriage has been evaluated, with evidence suggesting it plays a significant role in both recurrent miscarriage and other reproductive complications. Key genetic factors include Factor V Leiden and Prothrombin mutations and deficiencies in Protein C, Protein S, and Antithrombin.²²

Previous investigations have linked mutations in factor V Leiden (F5) and prothrombin (factor II [F2]) to an elevated risk of recurrent spontaneous miscarriage among Caucasian women.^23,24 However, genetic research on the role of thrombophilic polymorphisms in recurrent miscarriage among Jordanian women is limited. This study seeks to investigate the potential risks associated with polymorphisms in genes such as antithrombin (SERPINC1), protein C (PROC), protein S (PROS1), protein Z (PROZ), Factor V (F5), factor XIII (F13A1), and carboxypeptidase B2 (CPB2), which may contribute to an increased susceptibility to recurrent miscarriage.

Methods

Study Design, Ethical Approval, and Sample Collection

This prospective study was conducted in the Gynecology and Obstetrics Clinic, Royal Medical Services, Amman, Jordan, from April to October 2023 after obtaining ethical approval from the Royal Medical Institutional Review Board and in accordance with the Declaration of Helsinki guidelines in 1946 and its follow amendment. This study included two pregnant women groups with total of (381) and was divided into (188) spontaneous recurrent miscarriage (SRM) women group and (193) matched age healthy pregnant women group. Pregnant women who have a recurrent miscarriage with known either heredity or acquired causes, pregnant diabetics, and hypertension were excluded. Whole blood (5 ml) was collected in EDTA collection tubes (AFCO, Amman, Jordan) from all the included participants and their clinical records.

DNA Extraction and Genotyping by the Kompetitive Allele Specific Polymerase Chain Reaction (KASP) Method

DNA extraction was performed directly after collecting the whole blood from each group using an Exgene^TM Clinic SV extraction kit (GeneAll Company, Korea) per manufacturer instructions. The purity and concentration of the extracted DNA were assessed by Nanodrop^TM 2000c spectrophotometer (Thermo Fisher Scientific, Wilmington, USA). Then, it was stored at −20 °C until later used. The investigated polymorphisms for the target thrombophilic genes include: F5 (rs6025); 2 SNPs in SERPINC1 (rs2227612 and rs5877); 2 SNPs in PROC (rs1799810 and rs5936); 2 SNPs in PROS1 (rs13062355 and rs4857037); 2 SNPs in PROZ (rs3024731 and rs3024735); F13A1 (rs1050782); CPB2 (rs1926447and rs3742264) were selected from the literature²⁵ and haven’t been investigated among recurrent miscarriage women in Jordan yet. Next, the Kompetitive Allele Specific Polymerase Chain Reaction (KASP) Genotyping method was used to detect the specific polymorphisms for each target gene. Briefly, sufficient volume of KASP genotyping mix solution was prepared per well for each of the assays to be run in (96) well-plates, including (5 µl) genomic DNA (4 ng/µl) template or free DNA/ RNAase water as negative control, (0.14 µl) KASP Assay Mix and (5 µl) KASP-TF Master Mix (LGC Biosearch Technologies, Teddington, UK). Then, the KASP PCR reaction for the prepared wells was carried out in Bio-Rad CFX Opus (Bio-Rad Laboratories, Inc., Hercules, USA) and FAM and HEX fluorophores to distinguish genotypes without any background amplification. The thermal profile for KASP chain reaction consist of four stages; first stage (Hot start Taq activation) was lasted for 15 min at 94 °C for one cycle. Then, the second stage (Touch down) was continued at 94 °C for 20 s and followed by 60 s at 61 °C (61 °C decreasing 0.6°/ cycle to achieve a final annealing/extension temperature of 55 °C) for ten cycles. Next, the third stage (Amplification) initially started at 94 °C for 20 s and followed by raising the temperature until 55 °C for 60 s which was lasted for twenty-six cycles. Finally, the reaction of the fourth stage (Read) at 30 °C for 60 s was lasted for single cycle.

Statistical Analysis

Various statistical methods and software tools were utilized to assess the association between genetic variants and recurrent miscarriage status. Data was analyzed using the Statistical Package for Social Sciences (SPSS), version 26.0 (SPSS, Inc., Chicago, IL). Allele and genotype distributions relevant to the risk of recurrent miscarriage were analyzed and compared between the groups. Depending on the appropriateness of the expected counts, chi-square (χ²) or Fisher's exact test was conducted to evaluate the target genes’ frequency distribution between patients and controls. Statistical significance was defined as P < .05. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to estimate genotype-related risk. One-way ANOVA was employed to analyze the association between genotypes and phenotypes. Generalized estimating equations were used to test for the association of the mutant allele with the presence of recurrent miscarriage while adjusting for blood parameters. Furthermore, the SNPStats web tool (https://www.snpstats.net/start.htm) was used to explore various inheritance models, assess Hardy-Weinberg Equilibrium, estimate haplotype frequencies, and examine the association between haplotypes and recurrent miscarriage status. Statistical significance was defined as P < .05.

Results

Clinical Characteristics of the Study Population

The mean age in the study population was 32.2 ± 5.4, ranging from 18 to 46, with a similar distribution in RSM and controls. A marked significant mean difference (P < .001) in the number of miscarriages among the RSM (2.94 ± 2.11) compared to the controls (0.0) which confirmed the selecting of the study groups. Clinical parameters were similar for RSM and controls, but red blood cells (RBC) count (4.2 ± 0.5 vs 4.4 ± 0.8 × 10⁶/µL) mean corpuscular volume (MCV) (81.5 ± 7.7 vs 83.2 ± 8.1 fL) and mean corpuscular hemoglobin (MCH) (26.4 ± 3.1 vs 27.1 ± 3.5 pg/L) were markedly lower in RSM cases. In addition, mean of the platelet count was elevated in RSM cases compared to controls (251 ± 87.5 vs 240 ± 77.8 × 10³/µL) Table 1. All participants have only used folic acid supplement.

Table 1.

Clinical Characteristics of the Study Population.

Clinical Parameters(mean ± SD)	Controls(N = 193)	RSM(N = 188)	p-Value
Age (years)	31.5 ± 5.4	32.8 ± 5.5	.11
Number of miscarriages	2.94 ± 2.1	0.0	<.001**
Glucose (mg/dL)	86.9 ± 29.2	90.7 ± 24.1	.13
Hb (g/dL)	11.3 ± 1.3	11.3 ± 1.5	.36
RBC (10⁶/µL)	4.2 ± 0.5	4.4 ± 0.9	.001**
RDW-SD (fL)	43.1 ± 7.4	43.8 ± 7.9	.24
RDW-CV (%)	14.9 ± 2.6	15.4 ± 3.4	.09
MCV (fL)	83.2 ± 8.1	81.5 ± 7.7	.02*
MCH (pg/L)	27.1 ± 3.5	26.4 ± 3.1	.02*
MCHC (g/dL)	32.9 ± 1.7	32.6 ± 1.5	.08
PCV (%)	34.3 ± 4.1	34.7 ± 5.6	2.0
WBC (10³/µL)	10.4 ± 3.8	10.5 ± 4.1	.42
Lymphocytes (10³/µL)	1.9 ± 0.8	2 ± 1.8	.28
Lymphocytes (%)	20.4 ± 10.5	19.1 ± 10.0	.15
Platelets (10³/µL)	240.0 ± 77.8	251.0 ± 87.5	.09
ALT (U/L)	12.8 ± 13.5	12.4 ± 9.1	.39
AST (U/L)	19.9 ± 12.3	18.8 ± 9.9	.23
ALP (U/L)	137.1 ± 142.6	119.6 ± 55.3	.11
Bilirubin total (mg/dL)	0.5 ± 0.5	1.0 ± 6.8	.19
Urea (mg/L)	7.2 ± 2.9	7.7 ± 2.9	.09
Creatinine (mg/L)	0.5 ± 0.1	0.5 ± 0.1	.38
Uric acid (mg/dL)	4.3 ± 1.4	4.1 ± 1.0	.06

Based on normality, numeric variables are summarized as mean (sd). The following abbreviations indicated as: RSM, recurrent spontaneous miscarriage; Hb, hemoglobin; RBC, red blood cells; RDW-SD, red blood cell distrubition width-standard deviation; RDW-CV, red blood cell distrubition width-coefficient variation; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; PCV, packed cell volume; WBC, white blood cells; ALT, alanine transaminase; AST, aspartate transaminase; ALP, alkaline phosphatase.

Hardy-Weinberg Equilibrium (HWE) and minor Allele Frequencies

The minor allele frequencies of the genetic polymorphisms in the selected genes were determined in both the RSM and control groups. Additionally, the Hardy-Weinberg equilibrium (HWE) was assessed for each identified polymorphism in both groups, revealing no significant deviations from the expected equilibrium, as detailed in Table 2.

Table 2.

The Hardy-Weinberg Equilibrium and the Minor Allele Frequencies for the Selected Genetic Polymorphisms.

Gene	SNP_ID	Controls (n = 193)			RSM (n = 188)
Gene	SNP_ID	MA	MAF	HWE p-Value	MA	MAF	HWE p-Value
SERPINC1	rs2227612	G	23%	.21	G	18%	.81
SERPINC1	rs5877	T	44%	.31	T	48%	.88
F5	rs6025	T	6%	.53	T	7%	1
F13A1	rs1050782	A	41%	.37	A	43%	.1
PROC	rs2069906	A	7%	.052	A	5%	.69
PROC	rs1799810	A	45%	.56	A	51%	.31
PROS1	rs13062355	G	37%	.091	G	42%	.37
PROS1	rs8178607	A	5%	1	A	1%	1
CPB2	rs3742264	T	32%	.41	T	30%	.22
CPB2	rs1926447	A	32%	.51	A	37%	.27
PROZ	rs3024735	A	13%	.53	A	15%	.78
PROZ	rs3024731	A	19%	.15	A	21%	.19

The following abbreviations indicated for: MA, minor allele; MAF, minor allele frequency; HWE, Hardy-Weinberg equilibrium; RSM, recurrent spontaneous miscarriage.

Genotype and Allele Frequencies in Cases and Controls and Association with Recurrent Miscarriage

The genotype at rs3136520 was heterozygous (CT) for all subjects in the study, and genotype frequencies at rs1799963 and rs2069906 were not consistent with Hardy-Weinberg equilibrium in controls (p < .001, p = .030 respectively). Thus, these three SNPs were excluded from the analysis.

Only rs8178607 was found to be significantly associated with RSM (p = .022). The heterozygous genotype (GA) constituted 18.1% of cases compared with 10.4% in controls. The homozygous genotype (AA) was not present in the controls, whereas it represented a 1.1% frequency in RSM. The minor allele (A) frequency was 5.2% in controls and 10% in RSM (p = .014). The presence of this allele was associated with an increased likelihood of being in the RSM group by 2.06 times compared to having the G allele (p = .014) Table 3.

Table 3.

Differences Between Controls and Cases in SNP Genotype and Allele Frequencies.

SNP	Genotype	Controlsn (%)	RSMn (%)	p-Value	Allele	Controln (%)	RSMn (%)	p-Value	OR	95% CI
SERPINC1	TT	119 (62)	126 (67)	.347	T	299 (77)	307 (82)	.199	0.78	0.54-1.13
rs2227612	TG	61 (32)	55 (29)		G	87 (23)	69 (18)
rs2227612	GG	13 (7)	7 (4)		G	87 (23)	69 (18)
SERPINC1	TC	88 (46)	93 (49)	.402	C	216 (56)	195 (52)	.274	1.18	0.88–1.59
rs5877	CC	64 (33)	51 (27)		T	170 (44)	181 (48)
rs5877	TT	41 (21)	44 (23)		T	170 (44)	181 (48)
F5	CC	170 (88)	163 (87)	.642	C	362 (94)	351 (93)	.924	1.07	0.58–2
rs6025	CT	22 (11)	25 (13)		T	24 (6)	25 (7)
rs6025	TT	1 (1)	0 (0)		T	24 (6)	25 (7)
F13A1	AG	100 (52)	81 (43)	.183	G	228 (59)	215 (57)	.650	1.08	0.8–1.46
rs1050782	GG	64 (33)	67 (36)		A	158 (41)	161 (43)
rs1050782	AA	29 (15)	40 (21)		A	158 (41)	161 (43)
PROC	GG	169 (88)	171 (91)	.564	G	359 (93)	357 (95)	.261	0.71	0.38–1.29
rs2069906	GA	21 (11)	15 (8)		A	27 (7)	19 (5)
rs2069906	AA	3 (2)	2 (1)		A	27 (7)	19 (5)
PROC	AT	100 (52)	87 (46)	.078	T	212 (55)	183 (49)	.098	1.28	0.96–1.73
rs1799810	TT	56 (29)	48 (26)		A	174 (45)	193 (51)
rs1799810	AA	37 (19)	53 (28)		A	174 (45)	193 (51)
PROS1	GA	79 (41)	85 (45)	.457	A	243 (63)	219 (58)	.209	1.22	0.9–1.65
rs13062355	AA	82 (42)	67 (36)		G	143 (37)	157 (42)
rs13062355	GG	32 (17)	36 (19)		G	143 (37)	157 (42)
PROS1	GG	173 (90)	152 (81)	. 022	G	366 (95)	338 (90)	. 014	2.06	1.14–3.8
rs8178607	GA	20 (10)	34 (18)		A	20 (5)	38 (10)
rs8178607	AA	0 (0)	2 (1)		A	20 (5)	38 (10)
CPB2	CC	92 (48)	88 (47)	.225	C	263 (68)	263 (70)	.644	0.92	0.67–1.26
rs3742264	CT	79 (41)	87 (46)		T	123 (32)	113 (30)
rs3742264	TT	22 (11)	13 (7)		T	123 (32)	113 (30)
CPB2	AG	89 (46)	80 (43)	.151	G	263 (68)	238 (63)	.159	1.26	0.92–1.72
rs1926447	GG	87 (45)	79 (42)		A	123 (32)	138 (37)
rs1926447	AA	17 (9)	29 (15)		A	123 (32)	138 (37)
PROZ	GG	147 (76)	135 (72)	.718	G	336 (87)	318 (85)	.382	1.23	0.8–1.89
rs3024735	GA	42 (22)	48 (26)		A	50 (13)	58 (15)
rs3024735	AA	4 (2)	5 (3)		A	50 (13)	58 (15)
PROZ	TT	131 (68)	121 (64)	.808	T	314 (81)	298 (79)	.526	1.14	0.79–1.66
rs3024731	AT	52 (27)	56 (30)		A	72 (19)	78 (21)
rs3024731	AA	10 (5)	11 (6)		A	72 (19)	78 (21)

The following abbreviations indicated for: RSA, recurrent spontaneous miscarriage; OR, odd ratio; CI, confidence interval.

Genetic Models of Selected Polymorphisms

Statistical testing of the association between rs8178607 in the PROS1 gene and RSM revealed significant differences between the two study groups, specifically under the codominant (OR = 1.39, P = .021), dominant (OR = 2.05, P = .015), and overdominant (OR = 1.91, P = .03) inheritance models. The presence of the heterozygous G/A genotype was associated with a 1.93 times increased likelihood of RSM compared to the homozygous G/G genotype in the codominant model. rs1926447 in the CPB2 gene showed a significant association with RSM under the recessive model (OR = 1.89, P = .046), where the presence of the A/A genotype increased the risk of RSM by 1.89 times compared to the presence of the G/G-A/G genotype. Additionally, the association of rs1799810 in the PROC gene under the recessive model (OR = 1.66, P = .038) showed that the presence of the A/A genotype increased the risk of RSM by 1.66 times compared to the presence of the T/T-A/T genotype, as detailed in Table 4.

Table 4.

Genetic Model Analysis of Selected Polymorphisms.

Gene	SNP_ID	Model	Genotype	Controls n (%)	RSM n (%)	OR (95% CI)	p-Value
SERPINC1	rs2227612	Codominant	T/T	119 (61.7%)	126 (67%)	1	.32
			T/G	61 (31.6%)	55 (29.3%)	0.85 (0.55-1.33)
			G/G	13 (6.7%)	7 (3.7%)	0.51 (0.20-1.32)
		Dominant	T/T	119 (61.7%)	126 (67%)	1	.27
		Dominant	T/G-G/G	74 (38.3%)	62 (33%)	0.79 (0.52-1.20)	.27
		Recessive	T/T-T/G	180 (93.3%)	181 (96.3%)	1	.18
		Recessive	G/G	13 (6.7%)	7 (3.7%)	0.54 (0.21-1.37)	.18
		Overdominant	T/T-G/G	132 (68.4%)	133 (70.7%)	1	.62
		Overdominant	T/G	61 (31.6%)	55 (29.3%)	0.89 (0.58-1.39)	.62
	rs5877	Codominant	C/C	64 (33.2%)	51 (27.1%)	1	.44
			T/C	88 (45.6%)	93 (49.5%)	1.33 (0.83-2.12)
			T/T	41 (21.2%)	44 (23.4%)	1.35 (0.77-2.36)
		Dominant	C/C	64 (33.2%)	51 (27.1%)	1	.2
		Dominant	T/C-T/T	129 (66.8%)	137 (72.9%)	1.33 (0.86-2.07)	.2
		Recessive	C/C-T/C	152 (78.8%)	144 (76.6%)	1	.61
		Recessive	T/T	41 (21.2%)	44 (23.4%)	1.13 (0.70-1.84)	.61
		Overdominant	C/C-T/T	105 (54.4%)	95 (50.5%)	1	.45
		Overdominant	T/C	88 (45.6%)	93 (49.5%)	1.17 (0.78-1.75)	.45
F5	rs6025	Codominant	C/C	170 (88.1%)	163 (86.7%)	1	.44
			C/T	22 (11.4%)	25 (13.3%)	1.19 (0.64-2.19
			T/T	1 (0.5%)	0 (0%)	0.00 (0.00-NA)
		Dominant	C/C	170 (88.1%)	163 (86.7%)	1	.68
		Dominant	C/T-T/T	23 (11.9%)	25 (13.3%)	1.13 (0.62-2.08)	.68
		Recessive	C/C-C/T	192 (99.5%)	188 (100%)	1	.24
		Recessive	T/T	1 (0.5%)	0 (0%)	0.00 (0.00-NA)	.24
		Overdominant	C/C-T/T	171 (88.6%)	163 (86.7%)	1	.57
		Overdominant	C/T	22 (11.4%)	25 (13.3%)	1.19 (0.65-2.20)	.57
F13A1	rs1050782	Codominant	G/G	64 (33.2%)	67 (35.6%)	1	.15
			A/G	100 (51.8%)	81 (43.1%)	0.77 (0.49-1.21)
			A/A	29 (15%)	40 (21.3%)	1.32 (0.73-2.37)
		Dominant	G/G	64 (33.2%)	67 (35.6%)	1	.61
		Dominant	A/G-A/A	129 (66.8%)	121 (64.4%)	0.90 (0.59-1.37)	.61
		Recessive	G/G-A/G	164 (85%)	148 (78.7%)	1	.11
		Recessive	A/A	29 (15%)	40 (21.3%)	1.53 (0.90-2.59)	.11
		Overdominant	G/G-A/A	93 (48.2%)	107 (56.9%)	1	.08
		Overdominant	A/G	100 (51.8%)	81 (43.1%)	0.70 (0.47-1.05)	.08
PROC	rs2069906	Codominant	G/G	169 (87.6%)	171 (91%)	1	.56
			G/A	21 (10.9%)	15 (8%)	0.71 (0.35-1.42)
			A/A	3 (1.6%)	2 (1.1%)	0.66 (0.11-3.99)
		Dominant	G/G	169 (87.6%)	171 (91%)	1	.28
		Dominant	G/A-A/A	24 (12.4%)	17 (9%)	0.70 (0.36-1.35)	.28
		Recessive	G/G-G/A	190 (98.5%)	186 (98.9%)	1	.67
		Recessive	A/A	3 (1.6%)	2 (1.1%)	0.68 (0.11-4.12)	.67
		Overdominant	G/G-A/A	172 (89.1%)	173 (92%)	1	.33
		Overdominant	G/A	21 (10.9%)	15 (8%)	0.71 (0.35-1.42)	.33
	rs1799810	Codominant	T/T	56 (29%)	48 (25.5%)	1	.12
			A/T	100 (51.8%)	87 (46.3%)	1.01 (0.63-1.64)
			A/A	37 (19.2%)	53 (28.2%)	1.67 (0.95-2.96)
		Dominant	T/T	56 (29%)	48 (25.5%)	1	.45
		Dominant	A/T-A/A	137 (71%)	140 (74.5%)	1.19 (0.76-1.87)	.45
		Recessive	T/T-A/T	156 (80.8%)	135 (71.8%)	1	. 038
		Recessive	A/A	37 (19.2%)	53 (28.2%)	1.66 (1.03-2.67)	. 038
		Overdominant	T/T-A/A	93 (48.2%)	101 (53.7%)	1	.28
		Overdominant	A/T	100 (51.8%)	87 (46.3%)	0.80 (0.54-1.20)	.28
PROS1	rs13062355	Codominant	A/A	82 (42.5%)	67 (35.6%)	1	.39
			G/A	79 (40.9%)	85 (45.2%)	1.32 (0.84-2.05)
			G/G	32 (16.6%)	36 (19.1%)	1.38 (0.77-2.45)
		Dominant	A/A	82 (42.5%)	67 (35.6%)	1	.17
		Dominant	G/A-G/G	111 (57.5%)	121 (64.4%)	1.33 (0.88-2.02)	.17
		Recessive	A/A-G/A	161 (83.4%)	152 (80.8%)	1	.51
		Recessive	G/G	32 (16.6%)	36 (19.1%)	1.19 (0.70-2.01)	.51
		Overdominant	A/A-G/G	114 (59.1%)	103 (54.8%)	1	.4
		Overdominant	G/A	79 (40.9%)	85 (45.2%)	1.19 (0.79-1.79)	.4
	rs8178607	Codominant	G/G	173 (89.6%)	152 (80.8%)	1	. 021
			G/A	20 (10.4%)	34 (18.1%)	1.93 (1.07-3.50)
			A/A	0 (0%)	2 (1.1%)	NA (0.00-NA)
		Dominant	G/G	173 (89.6%)	152 (80.8%)	1	. 015
		Dominant	G/A-A/A	20 (10.4%)	36 (19.1%)	2.05 (1.14-3.69)	. 015
		Recessive	G/G-G/A	193 (100%)	186 (98.9%)	1	.092
		Recessive	A/A	0 (0%)	2 (1.1%)	NA (0.00-NA)	.092
		Overdominant	G/G-A/A	173 (89.6%)	154 (81.9%)	1	. 03
		Overdominant	G/A	20 (10.4%)	34 (18.1%)	1.91 (1.05-3.46)	. 03
CPB2	rs3742264	Codominant	C/C	92 (47.7%)	88 (46.8%)	1	.25
			C/T	79 (40.9%)	87 (46.3%)	1.15 (0.75-1.76)
			T/T	22 (11.4%)	13 (6.9%)	0.62 (0.29-1.30)
		Dominant	C/C	92 (47.7%)	88 (46.8%)	1	.87
		Dominant	C/C-T/T	101 (52.3%)	100 (53.2%)	1.04 (0.69-1.55)	.87
		Recessive	C/C-C/T	171 (88.6%)	175 (93.1%)	1	.13
		Recessive	T/T	22 (11.4%)	13 (6.9%)	0.58 (0.28-1.18)	.13
		Overdominant	C/C-T/T	114 (59.1%)	101 (53.7%)	1	.29
		Overdominant	C/T	79 (40.9%)	87 (46.3%)	1.24 (0.83-1.86)	.29
	rs1926447	Codominant	G/G	87 (45.1%)	79 (42%)	1	.14
			A/G	89 (46.1%)	80 (42.5%)	0.99 (0.64-1.52)
			A/A	17 (8.8%)	29 (15.4%)	1.88 (0.96-3.68)
		Dominant	G/G	87 (45.1%)	79 (42%)	1	.55
		Dominant	A/G-A/A	106 (54.9%)	109 (58%)	1.13 (0.76-1.70)	.55
		Recessive	G/G-A/G	176 (91.2%)	159 (84.6%)	1	. 046
		Recessive	A/A	17 (8.8%)	29 (15.4%)	1.89 (1.00-3.57)	. 046
		Overdominant	G/G-A/A	104 (53.9%)	108 (57.5%)	1	.48
		Overdominant	A/G	89 (46.1%)	80 (42.5%)	0.87 (0.58-1.30)	.48
PROZ	rs3024735	Codominant	G/G	147 (76.2%)	135 (71.8%)	1	.62
			G/A	42 (21.8%)	48 (25.5%)	1.24 (0.77-2.00)
			A/A	4 (2.1%)	5 (2.7%)	1.36 (0.36-5.17)
		Dominant	G/G	147 (76.2%)	135 (71.8%)	1	.33
		Dominant	G/A-A/A	46 (23.8%)	53 (28.2%)	1.25 (0.79-1.99)	.33
		Recessive	G/G-G/A	189 (97.9%)	183 (97.3%)	1	.71
		Recessive	A/A	4 (2.1%)	5 (2.7%)	1.29 (0.34-4.88)	.71
		Overdominant	G/G-A/A	151 (78.2%)	140 (74.5%)	1	.39
		Overdominant	G/A	42 (21.8%)	48 (25.5%)	1.23 (0.77-1.98)	.39
	rs3024731	Codominant	T/T	131 (67.9%)	121 (64.4%)	1	.77
			A/T	52 (26.9%)	56 (29.8%)	1.17 (0.74-1.83)
			A/A	10 (5.2%)	11 (5.8%)	1.19 (0.49-2.90)
		Dominant	T/T	131 (67.9%)	121 (64.4%)	1	.47
		Dominant	A/T-A/A	62 (32.1%)	67 (35.6%)	1.17 (0.77-1.79)	.47
		Recessive	T/T-A/T	183 (94.8%)	177 (94.2%)	1	.77
		Recessive	A/A	10 (5.2%)	11 (5.8%)	1.14 (0.47-2.74)	.77
		Overdominant	T/T-A/A	141 (73.1%)	132 (70.2%)	1	.54
		Overdominant	A/T	52 (26.9%)	56 (29.8%)	1.15 (0.74-1.80)	.54

The following abbreviations indicated for: RSA, recurrent spontaneous miscarriage; OR, odd ratio; CI, confidence interval.

Linkage Disequilibrium and Haplotype Analysis

The haplotype analysis of the studied SNPs in SERPINC1 (rs2227612 and rs5877), PROC (rs2069906 and rs1799810), CPB2 (rs3742264 and rs1926447), and PROZ (rs3024735 and rs3024731) revealed no significant association with RSM (P > .05). However, the (G A) haplotype block of the rs8178607 and rs13062355 SNPs in the PROS1 showed a significant association (P = .031), as presented in Table 5. Furthermore, rs8178607 and rs13062355 were found to be in linkage disequilibrium (D = 0.040, D′ = 0.873, correlation = 0.311, P < .0001).

Table 5.

Haplotype Analysis of Selected Genetic Polymorphisms.

Gene	Haplotypes	Frequency		OR (95% CI)	p-Value
Gene	Haplotypes	Controls	RSM	OR (95% CI)	p-Value
SERPINC1	T T	0.4367	0.4814	1	—
	T C	0.3379	0.3351	0.90 (0.65-1.24)	.53
	G C	0.2217	0.1835	0.76 (0.53-1.10)	.15
PROC	G A	0.4462	0.5094	1	—
	G T	0.4839	0.4401	0.80 (0.60-1.08)	.14
	A T	0.0653	0.0466	0.64 (0.33-1.23)	.18
RPOS1	A G	0.6295	0.5704	1	—
	G G	0.3187	0.3285	1.13 (0.84-1.51)	.43
	G A	0.0518	0.0891	1.92 (1.06-3.48)	. 031
CPB2	C G	0.3627	0.3367	1	—
	C A	0.3187	0.3628	1.22 (0.87-1.71)	.26
	T G	0.3187	0.2963	1.00 (0.70-1.42)	1
PROZ	G T	0.8135	0.7812	1	—
	A A	0.1295	0.1429	1.14 (0.76-1.73)	.52
	G A	0.057	0.0645	1.15 (0.64-2.07)	.64

The following abbreviations indicated for: RSM: Recurrent Spontaneous Miscarriage, RO: Odd Ratio, CI: Confidence Interval.

Association of Recurrent Miscarriage with rs8178607 Controlling for Blood Parameters

The mutant allele A was not associated with an increased likelihood of recurrent miscarriage compared to the major allele G when the effect was adjusted for RDW-SD, MCV, platelet count, and RBC count. None of these blood parameters were found to be associated with the outcome Table 6.

Table 6.

Generalized Estimating Equations Result in an Association of rs8178607 with Recurrent Miscarriage Adjusting for Blood Parameters.

Predictors	OR (95% CI)	p-Value
rs8178607 allele [A versus G]	0.92 (0.61-1.41)	.710
RDW-SD (fL)	1.01 (0.97-1.05)	.506
MCV (%)	0.97 (0.93-1.01)	.178
Platelets (×10³)	1.00 (1.00-1.00)	.509
RBC (×10⁶)	1.42 (0.91-2.22)	.126

The following abbreviations indicated for RDW-SD, red blood cell distrubition width; MCV, mean corpuscular volume; RBC, red blood cells; OR, odd ratio; CI, confidence intervals.

Clinical and Genotypic Associations in Recurrent Miscarriage

The association between the selected genetic polymorphisms and clinical outcomes in recurrent miscarriage was analyzed statistically, as shown in (Supplementary Table S1). The results indicate that rs5877 of the SERPINC1 gene is significantly associated with age (p = .015), glucose levels (p = .026), WBC counts (p = .015), ALP levels (p = .023), and urea levels (p = .031). Additionally, rs2227612 of the SERPINC1 gene is significantly associated with age (p = .015). rs6025 of the F5 gene is significantly associated with RDW-CV (p = .029). Furthermore, rs1050782 of the F13A1 gene is associated with age (p = .048), number of miscarriages (p = .028), hemoglobin (Hb) level (p = .049), mean corpuscular volume (MCV) (p = .021), and packed cell volume (PCV) (p = .039). rs2069906 of the PROC gene is significantly associated with lymphocyte percentage (p = .0002), while rs1799810 of the PROC gene is significantly associated with the number of miscarriages (p = .015). rs13062355 of the PROS1 gene is significantly associated with ALT levels (p = .042) rs1926447 of the CPB2 gene is significantly associated with the number of miscarriages (p = .013) and lymphocyte percentage (p = .031), while rs3742264 of the CPB2 gene is significantly associated with glucose levels (p = .026), RDW-CV (p = .014), ALP levels (p = .044), and total bilirubin (p = .0002).

Discussion

Numerous studies have aimed to investigate the potential link between genetic mutation associated with inherited thrombophilia and RSA. However, as far as we know, there is a scarcity of data explicitly addressing this relationship between Jordanian women and RSM. This study employed a case-control design to evaluate the possible link between 11 SNPs in key genes regulating the coagulation and fibrinolytic systems and susceptibility to RSM.

F5 (rs6025) is the most extensively studied thrombophilic polymorphism associated with RSM. While individual studies conducted in Iranian,²⁶ Russian,²⁷ Chinese,²⁵ Sinhalese (Sri Lankan),²⁸ and Jordanian²⁹ women found no significant association between this SNP and RSA, a meta-analysis of 62 studies highlighted an increased risk of RSM in Iranian, Asian, European, and African populations, specifically in studies using a case-control design. In contrast, this association was not observed in South American populations or cohort studies.³⁰ Similarly, in the present study, we found no significant association between the rs6025 SNP and recurrent miscarriage.

Deficiency of protein Z has been implicated in the development of various thrombotic disorders, including venous and arterial thrombosis,³¹ as well as complications during pregnancy.³² Genetic variations are thought to play a significant role in protein Z deficiency, and previous research has explored the association of various polymorphisms with RSM. The rs3024735 variant has been reported to be associated with RSM.^33,34 However, one study indicated that low protein Z levels might contribute to unexplained pregnancy loss independently of the rs3024735 variant.³⁵ A study from Bahrain demonstrated significant differences in the allele frequencies of rs3024731 and rs3024735 between RSM cases and controls.

Additionally, the GA and AA genotypes of rs3024735 were reported to be associated with reduced protein Z levels.³⁶ A significant association between rs3024731 and RSM was observed in Chinese women, whereas rs3024735 was found to have no association with RSM in both Chinese²⁵ and Saudi Arabian³⁷ women. Similarly, our study demonstrated no association between the rs3024731 and rs3024735 SNPs and RSM.

FXIII, also known as coagulation factor XIII and previously referred to as the fibrin-stabilizing factor, is the final zymogen in the coagulation process, stabilizing the fibrin clot through a series of reactions.³⁸ Factor XIII is composed of two A subunits and two B subunits. The A subunits, encoded by the F13A1 gene, exhibit catalytic activity, whereas the B subunits primarily serve as carriers.^39,40 Numerous studies have explored the relationship between the Val34Leu polymorphism in exon 2 of the F13A1 gene and RSA,^41–43 whereas limited research has focused on rs1050782. Situated in the 3′ untranslated region of F13A1, rs1050782 might regulate F13A1 expression as a functional element, although its specific influence remains uncertain. A study conducted on Chinese Han women reported an association between the rs1050782 SNP and recurrent miscarriage, with the AG + GG genotypes and the G allele of rs1050782 potentially linked to a reduced risk of recurrent miscarriage.²⁵ Conversely, our study found no significant association between the rs1050782 SNP and recurrent miscarriage.

The carboxypeptidase B2 (CPB2), also known as the thrombin-activatable fibrinolysis inhibitor gene, plays a role in suppressing fibrinolysis, and specific genetic polymorphisms, including rs3742264 (505G/A) and rs1926447 (1040C/T), may increase the risk of venous thrombosis.^44,45 One study suggested that the rs3742264 A allele acts as a protective factor against recurrent miscarriage.⁴⁶ However, no significant association between the rs3742264 SNP and recurrent miscarriage was observed in studies conducted on Iranian⁴⁷ and Chinese Han²⁵ women. Our findings are consistent with these results. Regarding rs1926447, one study suggests that the C allele may protect against recurrent miscarriage and be linked to genetic susceptibility for recurrent miscarriage in Chinese women.⁴⁸ Conversely, some researchers have reported no association between this polymorphism and recurrent miscarriage in Egyptian⁴⁹ and Chinese Han women.²⁵ The findings of the present study identified an association under the recessive genetic model, indicating that the A/A genotype may be associated with an increased risk of recurrent miscarriage.

The protein C pathway is recognized as a critical regulator of coagulation.⁵⁰ Protein S, encoded by the PROS1, is a vitamin K-dependent glycoprotein that plays a key role in the anticoagulation cascade by acting as a cofactor for protein C.⁵¹ Antithrombin, protein C, and protein S deficiencies are risk factors for unfavorable pregnancy outcomes, such as fetal loss.^52,53 In the present study, we examined the association between the rs1799810 SNP of the PROC and recurrent miscarriage, finding a significant association under recessive genetic models, with the A/A genotype potentially linked to an increased risk of recurrent miscarriage. These findings contradict a study on Chinese Han women,²⁵ which reported no association.

Protein S deficiency, either inherited or acquired, is associated with an elevated risk of thrombosis.⁵⁴ Mutations in the PROS1 may predispose individuals to venous thromboembolic disorders.⁵⁵ The rs13062355 and rs8178607 SNPs of the PROS1 were investigated to assess their association with recurrent miscarriage. According to a study on Chinese Han women, no association was found,²⁵ consistent with our findings for the rs13062355 SNP. However, for rs8178607, our results indicate a significant association with recurrent miscarriage (p = .022), with the G/A genotype associated with an increased risk of recurrent miscarriage. The association was observed in the codominant, dominant, and overdominant genetic models (p = .021, .015, and .03, respectively). The results from the haplotype analysis of rs8178607 and rs13062355 SNPs showed a significant association for the (G A) haplotype block (P = .031), which was associated with an increased risk of recurrent miscarriage.

Conclusion

Our findings indicate the involvement of the SERPINC1, PROC, PROS1, PROZ, F5, F13A1, and CPB2 in the susceptibility to recurrent miscarriage among Jordanian women, emphasizing the genetic basis of this condition and highlighting the role of thrombophilic genes in its etiology. Notably, our data demonstrate for the first time that the rs8178607 rs1799810, and rs1926447 genotypes of the PROS1, PROC, and CPB2 respectively are associated with an increased risk of recurrent spontaneous miscarriage. Further investigations with larger sample sizes and family-based analyses are essential to elucidate the biochemical pathways and mechanisms through which this genetic variation influences recurrent miscarriage susceptibility. While the p-values suggest statistical significance, validation of these results in an independent cohort with a similar genetic background is necessary to confirm the robustness of these associations.

Supplemental Material

sj-docx-1-cat-10.1177_10760296251333783 - Supplemental material for Novel Association of Thrombophilic PROS1, PROC and CPB2 Genes Polymorphisms with Recurrent Spontaneous Miscarriage Women in Jordan

Supplemental material, sj-docx-1-cat-10.1177_10760296251333783 for Novel Association of Thrombophilic PROS1, PROC and CPB2 Genes Polymorphisms with Recurrent Spontaneous Miscarriage Women in Jordan by Ola M. Al-Sanabra, Laith N. AL-Eitan, Yazun Jarrar, Maryam Alasmar, Hala M. Al-Taleb and Njoud M. Altaleb in Clinical and Applied Thrombosis/Hemostasis

Footnotes

ORCID iD

Ola M. Al-Sanabra

Laith N. AL-Eitan

Yazun Jarrar

Maryam Alasmar

Hala M. Al-Talib

Njoud M. Altaleb

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Deanship of Scientific Research and Innovation at Al-balqa Applied University, (grant number 1342).

Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

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Novel Association of Thrombophilic PROS1,PROC and CPB2 Genes Polymorphisms with Recurrent Spontaneous Miscarriage Women in Jordan

Abstract

Keywords

Introduction

Methods

Study Design, Ethical Approval, and Sample Collection

DNA Extraction and Genotyping by the Kompetitive Allele Specific Polymerase Chain Reaction (KASP) Method

Statistical Analysis

Results

Clinical Characteristics of the Study Population

Hardy-Weinberg Equilibrium (HWE) and minor Allele Frequencies

Genotype and Allele Frequencies in Cases and Controls and Association with Recurrent Miscarriage

Genetic Models of Selected Polymorphisms

Linkage Disequilibrium and Haplotype Analysis

Association of Recurrent Miscarriage with rs8178607 Controlling for Blood Parameters

Clinical and Genotypic Associations in Recurrent Miscarriage

Discussion

Conclusion

Supplemental Material

sj-docx-1-cat-10.1177_10760296251333783 - Supplemental material for Novel Association of Thrombophilic PROS1, PROC and CPB2 Genes Polymorphisms with Recurrent Spontaneous Miscarriage Women in Jordan

Footnotes

ORCID iD

Funding

Conflicting Interests

Supplemental Material

References

Supplementary Material