Association study of frameshift and splice variant polymorphisms with risk of idiopathic recurrent pregnancy loss
- Authors:
- Published online on: June 21, 2018 https://doi.org/10.3892/mmr.2018.9202
- Pages: 2417-2426
Abstract
Introduction
Recurrent pregnancy loss (RPL) was initially defined as ≥3 consecutive pregnancy losses before 20 weeks of gestation (1,2), but was later redefined by the American Society for Reproductive Medicine as ≥2 consecutive pregnancy losses (3). An estimated 1–5% of women of reproductive age experience a pregnancy loss, and 10–20% of pregnancies end in a miscarriage, which frequently occurs in the second or third month of pregnancy (2,4,5). RPL may be caused by genetic disorders or various other factors, including fetal chromosomal abnormalities, uterine anomalies, thrombophilia, endocrine, immune and anatomical disorders, nutritional or environmental factors, psychological stress, or maternal infections (5). However, in as many as 50% of women who suffer from recurrent miscarriages, the causes are considered idiopathic. RPL is an important reproductive health issue and remains an active field of research (4). In the present study, the potential genetic cause of RPL was investigated. Four candidate genes harboring mutations that have been associated with other diseases were selected at random as they have not been investigated in association with RPL, and their association with RPL in Korean women was assessed.
Frameshift mutations result from insertions or deletions that alter the reading frame, and affect the subsequent coding sequence as well as the stop codon. Therefore, frameshift mutations may result in final polypeptide products with an abnormal length or in nonsense-mediated mRNA decay (6). This type of mutation has been implicated in numerous diseases; for example, Crohn's disease is associated with the nucleotide-binding oligomerization domain 2 3020insC frameshift mutation (7). Alternatively, abnormalities in alternative splicing have also been implicated in various diseases, including cancer (8–10).
Next-generation sequencing (NGS) is a more advanced method of DNA sequencing compared with Sanger sequencing, which permits the sequencing of the entire human genome in 1 day (11,12). It offers efficient analysis and rapid processing time, thereby reducing the labor and expenses associated with other sequencing options (13,14). NGS is a powerful tool used to study genetic diseases (13–16), and was therefore the technique of choice for this study.
In the present study, frameshift mutations in membrane spanning 4-domains A14 (MS4A14) and solute carrier family 2 member 7 (SLC2A7), and splice variants in pregnancy specific β-1-glycoprotein 9 (PSG9) and ATP binding cassette subfamily B member 5 (ABCB5) were investigated. These were selected through whole-exome sequencing (WES). To the best of our knowledge, the following four polymorphisms: MS4A14D>I (rs3217518), SLC2A7D>I (rs60746313), PSG9C>T (rs3746297) and ABCB5C>G (rs17143187), have not been previously studied in RPL. Therefore, the aim of the study was to examine the association between these four gene polymorphisms and RPL in Korean women.
Materials and methods
Study population
The study population included 383 female patients with RPL and 276 control women. Patients with RPL were 22–45 years old, with an average age of 33.11±4.44 years and a body mass index (BMI) of 21.48±3.85 kg/m2. Women in the control group were 20–66 years old, with an average age of 33.09±5.68 years and a BMI of 21.31±3.30 kg/m2.
Blood samples were collected from patients with RPL and control women between March 1999 and February 2012 at the Department of Obstetrics and Gynecology and the Fertility Center of CHA Bundang Medical Center (Seongnam, Korea). The study was approved by the Institutional Review Board of CHA Bundang Medical Center (IRB number: BD2010-123D) and written informed consent was provided by all patients. Women in the control group had regular menstrual cycles, a history of ≥1 naturally-conceived pregnancy, no history of pregnancy losses and a normal karyotype (46,XX). Women were diagnosed with RPL if they had a history of ≥2 consecutive spontaneous pregnancy losses. Before week 20 of gestation, ultrasound and/or physical examinations were performed and human gonadotropic hormone levels were assessed. The average gestational age at the time of miscarriage was 7.35±1.93 weeks, and overall patients had 3.28±1.84 miscarriages.
Patients with a history of smoking or alcohol abuse, or whose miscarriages were attributed to infection or anatomical, hormonal, chromosomal, autoimmune or thrombotic causes were excluded from the study. Anatomical causes of miscarriage were determined using hysterosalpingography, hysteroscopy, computerized tomographic scanning or magnetic resonance imaging, to identify intrauterine adhesion, septate uterus or uterine fibroids. Hormonal causes of miscarriage included hyperprolactinemia, luteal insufficiency and thyroid disease; these were determined by measuring relevant hormone levels in blood samples. The chromosomal causes for miscarriage were assessed by standard chromosome analysis using the G-banding method (17). Miscarriages caused by infection with Ureaplasma urealyticum or Mycoplasma hominis were identified by bacterial culture. The following autoimmune diseases: Lupus and antiphospholipid syndrome, were selected for their strong association with miscarriages; these were identified by measuring lupus anticoagulant and anticardiolipin antibodies. Thrombophilia was defined as a thrombotic disorder associated with miscarriages, and was identified by protein C and protein S deficiency, and presence of anti-β-2 glycoprotein.
Genotyping
Genomic DNA was extracted from peripheral blood of each study participant using the G-DEX DNA extraction kit (Intron Biotechnology, Inc., Seongnam, Korea). Macrogen, Inc. (Seoul, Korea) was commissioned to perform NGS of 20 patients with RPL. NGS was conducted using a HiSeq Instrument (Macrogen, Inc., Seoul, Korea) and paired-end sequences produced by a HiSeq Instrument were first mapped to the human genome using the mapping program ‘BWA’ (version 0.7.12) (https://sourceforge.net/projects/bio-bwa/files/). Based on the BAM file previously generated, variant genotyping for each sample was performed with Haplotype Caller of GATK (Broad Institute, Cambridge, MA, USA). Then, an in-house program and SnpEff (snpeff.sourceforge.net/) was applied to filter additional databases, including ESP6500 (https://esp.gs.washington.edu/), ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), and dbNSFP2.9 (https://sites.google.com/site/jpopgen/dbNSFP). WES statistical analyses were also conducted by Macrogen, Inc. The frameshift and splice variants genes were identified from the human genome single nucleotide polymorphism (SNP) database (http://www.ncbi.nlm.nih.gov/snp), and selected from the WES statistical list. The four polymorphisms selected were as follows: MS4A14D>I (rs3217518), SLC2A7D>I (rs60746313), PSG9C>T (rs3746297) and ABCB5C>G (rs17143187). The four SNPs were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis; the primers, PCR conditions and restriction enzymes used, are detailed in Table I (18).
 | Table I.Frameshift and splice variant gene polymorphisms determined using polymerase chain reaction-restriction fragment length polymorphism analysis. |
The MS4A14D>I polymorphism was amplified using forward (5′-TTGGATGGAGGGAAAGGTGTG-3′) and reverse (5′-TTTTGCCGTGAAGGGAGCT-3′) primers, and was amplified by the Solg™ 2X h-Taq PCR Pre-mix (SolGent co., Ltd., Daejeon, Korea) under the following conditions: 95°C for 15 min; 35 cycles of denaturation at 95°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 30 sec; and a final extension at 72°C for 5 min. The PCR products were digested with the restriction enzyme TspRI (New England BioLabs, Inc., Ipswich, MA, USA) at 65°C for 16 h.
The SLC2A7D>I polymorphism was amplified using forward (5′-AAGATGGCGGCTACCTTC-3′) and reverse (5′-CTACAACCTCTCTGTGGTCA-3′) primers, and was amplified by PCR under the following conditions: 95°C for 15 min; 35 cycles of denaturation at 95°C for 30 sec, annealing at 53°C for 30 sec, and extension at 72°C for 30 sec; and a final extension at 72°C for 5 min. The genotypes of the amplified products were identified by electrophoretic separation on a 5% agarose gel using EcoDye™ Nucleic Acid Staining Solution (BioFact Co., Ltd., Daejeon, Korea).
The PSG9C>T polymorphism was amplified using forward (5′-GTAATGGTAGAGGTCCGTCA-3′) and reverse (5′-CGTGTGTGTATCTTCAAGGC-3′) primers, and was amplified by PCR under the following conditions: 95°C for 15 min; 35 cycles of denaturation at 95°C for 30 sec, annealing at 57°C for 30 sec, and extension at 72°C for 30 sec; and a final extension at 72°C for 5 min. The PCR products were digested with the restriction enzyme BfaI (New England BioLabs, Inc.) at 37°C for 16 h.
The ABCB5C>G polymorphism was amplified using forward (5′-GAGAAAGGAAGCAGTTGG-3′) and reverse (5′-TAGTTCCCTCTTTCCCAC-3′) primers, and was amplified by PCR under the following conditions: 95°C for 5 min; 35 cycles of denaturation at 95°C for 30 sec, annealing at 52°C for 30 sec, extension at 72°C for 30 sec; and a final extension at 72°C for 5 min. The PCR products were digested with the restriction enzyme DdeI (Enzynomics, Daejeon, Korea) at 37°C for 16 h.
To validate the PCR-RFLP analysis, DNA sequencing was performed on randomly selected samples (~20% of total samples), using a BigDye™ Terminator v3.1 Cycle Sequencing kit (Applied Biosystems; Thermo Fisher Scientific, Inc.), ABI 3730×L DNA Analyzer (Applied Biosystems; Thermo Fisher Scientific, Inc.). PCR-RFLP genotyping was 100% concordant with DNA sequencing.
Laboratory tests
Plasma homocysteine, folate, total cholesterol, uric acid, blood urea nitrogen (BUN) and creatinine were measured in blood samples collected from patients with RPL after 12 h of fasting. Homocysteine was measured by IMx fluorescent polarizing immunoassay using the Abbott IMx analyzer (Abbott Pharmaceutical Co. Ltd., Lake Bluff, IL, USA). Folic acid was determined with a radioassay kit (ACS:180; Bayer AG, Leverkusen, Germany). Total cholesterol, uric acid, BUN and creatinine were measured using commercially available enzymatic colorimetric tests of the MODULAR PRE ANALYTICS PLUS system (Roche Diagnostics GmbH, Mannheim. Germany). Platelet (PLT) and white blood cell (WBC) counts were measured using the Sysmex XE-2100 Automated Hematology system (Sysmex Corporation, Kobe, Japan). Prothrombin time (PT) and activated partial thromboplastin time (aPTT) were measured with the ACL TOP automated photo-optical coagulometer (Mitsubishi Gas Chemical Company, Inc., Tokyo, Japan). Blood was collected from the control group by venipuncture on the second or third day of the menstrual cycle for the measurement of FSH, LH, E2, TSH, and prolactin levels. Serum was prepared as previously described (19) and hormone levels were determined using either radioimmunoassays [E2 (cat. no. A21854), TSH (cat. no. IM3712) and PRL (cat. no. IM2121); Beckman Coulter, Inc., Brea, CA, USA], or enzyme immunoassays using IMMULITE® 1000 Systems (FSH and LH; Siemens AG, Munich, Germany) according to the manufacturer's protocols.
Flow cytometric analysis of cluster of differentiation (CD)56+ natural killer cells
For cell surface marker staining, peripheral blood samples (50 µl) were mixed with monoclonal anti-CD56+ antibodies labeled with fluorescein isothiocyanate (cat. no. 340417, BD Biosciences, Franklin Lakes, NJ, USA) to a ratio of 5:2, for 15 min at room temperature. A total of 450 µl 1X BD FACS™ lysing solution (cat. no. 349202, BD Biosciences) was added followed by gentle vortexing and two washes with 2 ml fluorescence-activated cell sorting buffer (PBS supplemented with 1% bovine serum albumin and 0.01% sodium azide; Lonza Group, Ltd., Basel, Switzerland). Cells were fixed in 200 ml 1% paraformaldehyde (Sigma-Aldrich; Merck KGaA, Darmstadt, Germany) at 30 min in 4°C and washed with BD Perm/Wash™ buffer (cat. no. 554723, BD Biosciences) prior to acquisition on a BD FACSCalibur (BD Biosciences) (20,21). The data were analyzed using Cell Quest software (BD Biosciences).
Statistical analysis
The gene frequencies of MS4A14, SLC2A7, PSG9 and ABCB5 in patients and controls were assessed by logistic regression, Fisher's exact test and Mann-Whitney test. All genotype frequencies followed the Hardy-Weinberg equilibrium (HWE). The association between the MS4A14, SLC2A7, PSG9 and ABCB5 gene polymorphisms and RPL risk factors were examined by odds ratio (OR), adjusted odds ratio (AOR) and 95% confidence intervals (CIs). Data are presented as the means ± standard deviation. P≤0.05 was considered to indicate a statistically significant difference. The correlations of each genotype or allele with the proportion of NK cells and plasma Hcy, folate, total cholesterol, and uric acid levels were assessed by the Kruskal-Wallis and Mann-Whitney tests. The false discovery rate (FDR) was used for multiple comparisons correction. An FDR adjusted P<0.05 (q-value) was deemed statistically significant (22). MedCalc version 12.1.4 (MedCalc Software bvba, Ostend, Belgium) or GraphPad Prism version 4.0 (GraphPad Software, Inc., La Jolla, CA, USA) were used for statistical analysis. The HAPSTAT version 3.0 (www.bios.unc.edu/~lin/hapstat/) was used to estimate the frequency of the polymorphic haplotype.
Results
Study population
In the present study, patients with RPL and control women were compared. The clinical characteristics of the two study groups are summarized in Table II. There was a significant difference between patients with RPL and control women for several of the parameters tested. The PLT values were significantly higher in the RPL patient group than in the control group. Furthermore, LH values were significantly higher in the RPL patient group than in the control group.
Combined effects between clinical factors and gene polymorphism
Interaction analysis was performed to evaluate the association between adjusted factors, such as age and the different gene polymorphisms; the results are presented in Table III. The MS4A14 DI+II genotype was associated with PT≥12 sec (AOR=3.575; 95% CI=1.115–11.464) and aPTT≤22.1 sec (AOR=0.453; 95% CI=0.211–0.973). The SLC2A DI+II genotype was associated with PT≥12 sec (AOR=6.517; 95% CI=1.783–23.825). The PSG9 CT+TT genotype was associated with PLT≥279×103/µl (AOR=2.069; 95% CI=1.079–3.967) and aPTT≤22.1 sec (AOR=0.390; 95% CI=0.172–0.881). The ABCB5 CG+GG genotype was associated with PT≥12 sec (AOR=4.224; 95% CI=1.404–12.706). The AOR between the two different gene polymorphisms and PT are summarized in Fig. 1A and B. Overall, these genotypes appeared to be associated with coagulation indicators.
Genotype frequencies of the VEGF polymorphisms
The genotype frequencies of the four selected gene polymorphisms in patients with RPL and normal women are shown in Table IV. According to the results, there was no difference in the frequency of these genotypes between the two study populations, with respect to these polymorphisms. The genotypes between the two groups did not differ with respect to the number of pregnancy losses either, regardless as to whether normal women did not experience pregnancy loss (data not shown). In addition, to determine if various allele combinations were associated with the prevalence of RPL, allele combination analyses were performed with two, three and four allele combinations. The four-allele combination data are presented in Table V (data not shown for two and three allele combinations). Amongst all possible allele combinations of the four genes, MS4A14I/SLC2A7D/PSG9T/ABCB5G was associated with decreased RPL risk (OR=0.448; 95% CI=0.223–0.901; P=0.033).
Genotype combination analysis
Finally, genotype combination analysis was performed. The following combinations were significantly associated with decreased RPL occurrence: MS4A14II/PSG9CT (OR=0.446; 95% CI=0.200–0.995; P=0.049), MS4A14II/ABCB5CG (OR=0.397; 95% CI=0.185–0.851; P=0.018), SLC2A7DI/ABCB5GG (OR=0.485; 95% CI=0.240–0.981; P=0.044) and SLC2A7II/ABCB5CC (OR=0.376; 95% CI=0.152–0.932; P=0.035). A summary of the results is shown in Table VI.
Discussion
In the present study, the association between four gene polymorphisms, namely MS4A14D>I (rs3217518), SLC2A7D>I (rs60746313), PSG9C>T (rs3746297) and ABCB5C>G (rs17143187), and RPL were examined. These frameshift mutations and splice variants have been associated with other diseases, such as colorectal cancer (23,24) and are also implicated in RPL.
The protein encoded by the MS4A14 gene serves an important role in embryo development and fertilization in rats (25). SLC2A7, also known as the glucose transporter 7 gene, catalyzes the cellular uptake of sugars. During pregnancy, the transplacental nutrient transport of amino acids, lipids and carbohydrates is important for proper fetal development, and glucose from the maternal circulation is a principal source of energy for the fetus (26). The protein encoded by the PSG9 gene is a member of the pregnancy-specific glycoprotein (PSG) family. In several studies, it was demonstrated that reduced serum concentration of PSG was associated with reduced fetal growth (27,28). The ABCB5 gene is a biomarker for physiological and pathological stem cells, and is a mediator of cell fusion, vasculogenesis and drug efflux (29). A successful pregnancy requires the development of a complex maternal and fetal vascular network that can support the increasing oxygen and metabolic demands of the growing fetus (30). Furthermore, placental development occurs through the vasculogenesis and angiogenesis stage (31). Therefore, it may be hypothesized that a mutation in ABCB5 would influence RPL.
Although the individual gene variations examined in this study were not associated with RPL, gene combinations were demonstrated to be associated with RPL. Allele combination analysis (MS4A14I/SLC2A7D/PSG9T/ABCB5G) and genotype combination analysis (MS4A14II/PSG9CT and MS4A14II/ABCB5CG) revealed that the I allele affected RPL when the MS4A14D>I polymorphism was present with other genes.
The present study also demonstrated that all the selected gene polymorphisms were associated with RPL when the blood coagulation factors PLT, PT and aPTT were included in the interaction analysis. During pregnancy, fibrinolysis and coagulation must be precisely balanced so that excess fibrin deposition in placental vessels and intravillous spaces does not occur, and to ensure fibrin polymerization and stabilization of the placental basal plate. Defects in this process can have a negative impact on trophoblast transplantation and placenta development, ultimately leading to miscarriage (32). Therefore, if blood coagulation factors deviate from their normal levels this may result in an unsuccessful pregnancy.
The present study has several limitations. Firstly, it is unclear whether these polymorphisms can affect gene transcription and/or translation. Secondly, the study only included Korean women who visited the CHA Bundang Medical Center, and it would be useful to validate the findings in a different cohort. Lastly, the control group size was smaller than the patient group. Nevertheless, to the best of our knowledge, this study is the first of its kind to investigate the association between the gene polymorphisms MS4A14D>I (rs3217518), SLC2A7D>I (rs60746313), PSG9C>T (rs3746297) and ABCB5C>G (rs17143187), and RPL. These genes have been implicated in cancer and some other diseases, but have not been previously studied in the context of RPL. Therefore, these findings may help to improve our understanding of frameshift mutations and splice variants in pregnancy.
In conclusion, the association between RPL and four gene polymorphisms, MS4A14D>I (rs3217518), SLC2A7D>I (rs60746313), PSG9C>T (rs3746297) and ABCB5C>G (rs17143187), was investigated in Korean women. These four polymorphisms were not associated with RPL individually, but were associated with RPL when combined with other genes or when factoring in blood coagulation factors. Notably, the MS4A14 I allele, alongside a PT≥12 sec, may be a potential biomarker for the diagnosis, prevention and prognosis of RPL. Further studies are required to clarify the associations between the four gene polymorphisms and RPL in an ethnically diverse cohort.
Acknowledgements
Not applicable.
Funding
The present study was partly supported by the Basic Science Research Programs through the National Research Foundation of Korea funded by the Ministry of Education, Science, and Technology (grant no. 2009-0093821, 2015R1D1A1A09057432 and 2017R1D1A1B03031542). The present study was also partly supported by a grant from the Korea Healthcare Technology R&D Project, Ministry for Health, Welfare & Family Affairs, Republic of Korea (grant no. HI15C1972010015).
Availability of data and materials
Not applicable.
Authors' contributions
WSL and NKK conceived and designed the experiments. HAL, CSR, JYL and JOK performed the experiments. EHA, JHK, CSR, JYL and SHC performed the analysis and interpretation of data for this study. WSL and NKK. prepared reagents/materials/analytical tools for experiments and analysis. HAL and EHA wrote the paper. JHK, SHC, WSL and NKK revised the manuscript for important intellectual information.
Ethics approval and consent to participate
The study was approved by the Institutional Review Board of CHA Bundang Medical Center (IRB number: BD2010-123D) and written informed consent was provided by all patients.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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