Skip to content

Advertisement

Open Access

Common genetic variants in the sex hormone-binding globulin (SHBG) gene in idiopathic recurrent pregnancy loss: a case control study

  • Mariam Dendana1,
  • Ramzi R. Finan2,
  • Mariam Al-Mutawa3 and
  • Wassim Y. Almawi3, 4Email author
Translational Medicine Communications20183:5

https://doi.org/10.1186/s41231-018-0024-1

Received: 23 March 2018

Accepted: 6 April 2018

Published: 12 April 2018

Abstract

Background

A role for sex hormone-binding globulin (SHBG) in determining the pregnancy outcome was evidenced by the rise in SHBG levels during pregnancy linked with favorable pregnancy, while reduction in SHBG levels and hyperandrogenemia were linked with poor pregnancy outcome. Since SHBG production is genetically determined, this study investigated the association of SHBG polymorphisms with the susceptibility to recurrent pregnancy loss (RPL).

Methods

Retrospective case-control study, involving 308 women with RPL, and 310 control women RPL, defined as ≥3 consecutive miscarriages, and with the same partner, was the main outcome measure. SHBG genotyping was done by allelic exclusion method (real-time PCR).

Results

Of the seven tested SHBG SNP, lower MAF of rs6257 was seen in RPL cases than in control women, which was linked with lower risk of RPL, after controlling for key covariates. At the genotype level, significantly higher frequencies of heterozygous rs858521 and rs6259, and homozygous rs858521 genotype carriers, and reduced frequency of heterozygous rs6257 and homozygous rs6257 and rs6259 genotype carriers were seen in RPL cases vs. control women, respectively. Univariate regression analysis confirmed the positive association of rs858521 and rs6259 with RPL. Multivariate regression analysis confirmed the positive association of rs858521 heterozygote and homozygote genotypes with RPL; only heterozygous rs6259 remained associated with RPL. Haploview analysis demonstrated marked linkage disequilibrium among 6 of the 7 tested SHBG SNP. Of the possible 6-locus haplotypes, 12 were common, and were included in subsequent analysis. Within these haplotypes, only increased frequency of CCGTGA haplotypes was seen in RPL cases, thus conferring RPL susceptibility.

Conclusions

Specific SHBG variants, and SHBG haplotypes are associated with altered risk of RPL, suggesting role for SHBG as RPL candidate gene.

Keywords

HaplotypesHyperandrogenismPolycystic ovary syndromeRecurrent pregnancy lossSex hormone binding globulin

Background

Recurrent pregnancy loss (RPL), defined as two or more clinically failed pregnancies, is a significant pregnancy complication which affects 2–3% of otherwise healthy women, with poor etiology [13]. RPL is associated with metabolic and hormonal disorders, including hyperprolactinemia [3, 4], hypothyroidism [4, 5], hyperinsulinemia and hyperandrogenemia [2, 3, 6]. Hormonal imbalances, particularly during early stages of pregnancy, were linked with RPL, as inadequate progesterone levels in early pregnancy was linked with termination of pregnancy [1, 7], and as elevated FSH/LH in early pregnancy were linked with pregnancy complications, including RPL [2, 8].

Several studies documented the association of hyperandrogenemia with RPL [2, 9], often with inconclusive findings. This was attributed to the wide variation in androgen levels, the time of sampling (i.e. within 7 days of the cycle), and the testosterone pool examined. The latter was attributed to the lipophilic nature of steroid sex hormones, in which circulating androgens and estrogens bind albumin and sex hormone binding globulin (SHBG), resulting in limited amounts of non-bound sex hormones, and hence reduced bioavailability [9, 10]. Accurate assessment of biochemical hyperandrogenemia requires measurement of either free testosterone, or free androgen index, which require determination of the serum levels SHBG, a 373-amino acid glycoprotein produced mainly by the liver, and binding the testosterone, dihydrotestosterone, and estradiol [11, 12], thus limiting their target tissue availability [12].

A role for SHBG in determining the pregnancy outcome was suggested. A rise in SHBG levels during pregnancy was proposed as protective for the fetus and mother from excessive androgen exposure [13], and reduction in SHBG levels and thus hyperandrogenemia were linked with pregnancy complications [11, 14]. SHBG gene is located on the short arm of chromosome 17 (17p13–17p12) [15], and several genetic variants in SHBG gene were identified, and were associated with varied levels of SHBG [16, 17], and with altered risk of RPL [18].

We hypothesize that genetic variants in SHBG gene associated with reduced SHBG expression, induce hyperandrogenemia, and hence increased risk of RPL. We tested this notion by examining the association of common SHBG gene variants among women with confirmed RPL diagnosis, and age- and ethnically-matched control women. This is the first study to examine this association in a Middle Eastern population.

Methods

Study subjects

This retrospective case-control study was performed at outpatient OB/GYN clinics in Manama, and Rifaa (Bahrain). Study subjects comprised 308 consecutively-recruited women with confirmed RPL (mean age 31.6 ± 5.4 years), and 310 age-matched control women. RPL diagnosis was based on Royal College of Obstetricians and Gynecologists guidelines (www.rcog.org.uk/guidelines), which were consistent with American College of Obstetricians and Gynecologists guidelines. These included screening of anti-phospholipid antibodies (lupus anticoagulant and anti-cardiolipin antibodies), karyotyping of both partners, pelvic ultrasound scan for evaluation of uterine anatomy, and screening of inherited thrombophilia (Factor V-Leiden, prothrombin/factor II G20210A).

These procedures were performed on all women with RPL. The inclusion criteria were three or more idiopathic (unknown etiology) miscarriages, which occurred during the 1st trimester of gestation with the same partner. Exclusion criteria were 40 years or older at first pregnancy, incompatibility in Rh blood groups, history of preeclampsia, which was defined as rise in systolic and diastolic blood pressure (BP) above 145/95 mmHg, and/or elevation in systolic/diastolic BP above 30/15 mmHg on two or more occasions, biochemical pregnancy and/or preclinical miscarriages. In addition, systemic autoimmunity, diabetes, and thyroid dysfunction, anatomical disorders, infections, and liver function abnormalities constituted added exclusion criteria. Due to personal, cultural and religious concerns, karyotyping of the products of conception was not routinely done.

Controls consisted of 310 multiparous women, with two or more full-term live pregnancies, no miscarriages (spontaneous or induced), and negative family history of miscarriages. Control women comprised ethnically-matched hospital and university students and employees, and volunteers from the community, and were recruited after a routine check-up after uncomplicated pregnancies. All participants had normo-ovulatory cycles, and none had evidence of polycystic ovary syndrome. Research and Ethics Committee of the Arabian Gulf University approved the study protocol, which was done in accordance with the Helsinki Declaration principle; all participants were asked to sign a consent form prior to inclusion in the study.

SHBG genotyping

Blood samples were taken from all participants in EDTA-containing tube for total genomic DNA extraction, which was done by the Qiagen minispin column method, according to the instructions of the manufacturer (Qiagen, Hilden, Germany). We selected polymorphisms in SHBG gene with a minor allele frequency (MAF) of > 5% in Caucasians, using SNPbrowser software (version 4.0, Applied Biosystems, Foster City, CA, USA). Genotyping was performed in 6-μl volume by the allelic discrimination method on StepOne Plus real-time PCR system, according to manufacturer’s instructions (Applied Biosystems). Assay-on-demand TaqMan primer pairs for the following SNPs: rs9898876, rs13894, rs858521, rs1799941, rs6257, rs6259, and rs727428 were ordered from Applied Biosystems. A typical genotyping reaction consisted of 2.2 μl DNA template added to 4.0 μl TaqMan genotype master mix (TaqMan 2X mix, 1.875 μl nuclease free water, and 0.125 μl 40X SNP primer mix) (Applied Biosystem). Pre-PCR (hold step; 30 s at 60 °C and 10 min at 95 °C) stage was followed by 35 cycles of denaturation (92 °C for 15 s), annealing and extension (60 °C for 1 min), followed by post-PCR stage at 60 °C for 30 s. Replicate blinded quality control samples were included to assess reproducibility of the genotyping procedure; concordance was > 99%.

Statistical analysis

Statistical analysis was performed on SPSS version 24.0 (IBM, Armonk, NY). Continuous variables were expressed as mean ±SD, while categorical data were represented as frequency (percentage of total). Student’s t-test was used to determine differences in means, and Pearson χ2 or Fisher’s exact test was used to assess inter–group significance. Genotypes were tested for departures from Hardy–Weinberg equilibrium (HWE) using Haploview version 4.2 (www.broad.mit.edu/mpg/haploview). All analyses were conducted under additive genetic effect, using SNPStats software (www.bioinfo.iconcologia.net/snpstats/). CaTS Power Calculator (www.sph.umich.edu/csg/abecasis/cats) was used in calculating the power for detecting an association between SHBG variants and RPL. The parameters used were 308 RPL cases and 310 control women, genotypic relative risk for heterozygous and minor allele homozygous, and MAF of the tested SNPs for RPL cases and controls, and assuming a 2.5% RPL prevalence rate (unpublished Bahrain Ministry of Health statistics). Assuming these parameters, the overall power (81.0%) was calculated as the average power of the seven tested SNPs. Linkage disequilibrium (LD) analysis was performed using Haploview 4.2, and haplotype reconstruction was performed by the expectation maximization method (Haploview 4.2). Logistic regression analysis was used to examine the association between SHBG SNP and RPL, presented as odds ratio (OR) with 95% confidence intervals (CI), after controlling for the following potential confounders: BMI, systolic and diastolic blood pressure, number of pregnancies, and age at menarche; statistical significance being set at P <  0.05.

Results

Demographic and clinical characteristics of RPL cases and control women

The demographic and clinical characteristics of RPL cases and control women are shown in Table 1. Mean age at entry of study, serum glucose, gravida, and prevalence of smoking were comparable between cases and controls. Mean BMI (P = 0.004), menarche (P <  0.001), and systolic and diastolic blood pressure (P <  0.001) were different between RPL cases and control women. These were the main covariates selected that were controlled for in subsequent analysis.
Table 1

Demographics & Clinical Characteristics of Cases and Controls

 

Casesa

Controlsa

P b

Age at inclusion in study c

31.6 ± 5.4

31.6 ± 4.9

0.94

Body-mass index (kg/m2) c

26.3 ± 5.4

25.2 ± 4.3

0.004

Obesity [n (%)] d

58 (19.6)

37 (12.1)

0.02

Smokers [n (%)] d

30 (10.1)

32 (10.8)

0.69

Systolic blood pressure (mmHg) c

114.2 ± 11.9

120.2 ± 17.0

< 0.001

Diastolic blood pressure (mmHg) c

72.0 ± 8.4

75.8 ± 9.1

< 0.001

Glucose (mmol/L) c

5.1 ± 0.9

5.2 ± 0.7

0.55

Menarche (years)c

12.2 ± 1.1

12.8 ± 1.0

< 0.001

Number of pregnancies c

4.2 ± 1.5

4.0 ± 1.1

0.11

Number of Children c

0.8 ± 1.1

4.0 ± 1.1

< 0.001

Miscarriages c

3.6 ± 1.0

0.0 ± 0.1

< 0.001

Serum IL-10 (pg/ml) c

5.3 ± 1.8

6.1 ± 1.2

0.002

aA total of 308 RPL cases and 310 control women were included

bStudent’s t-test (continuous variables), Pearson’s χ2 test (categorical variables)

cMean ± SD

dPercent of total within each group/subgroup

Association between SHBG SNP and the risk of RPL

Genotype distributions of the tested SHBG variants were in Hardy-Weinberg equilibrium among study subjects Table 2. summarizes the association between SHBG SNP and RPL in cases and control subjects. At the allele level, lower MAF of rs6257 (P = 0.001) was seen in RPL cases than in control women, which translated into lower risk of RPL, after controlling for BMI, menarche, systolic and diastolic blood pressure [aOR (95% CI) = 0.59 (0.43–0.81)]. MAF of the remaining SHBG SNPs were not significantly different between RPL cases and control women.
Table 2

SHBG SNPs analyzed in RPL cases and control women

#

SNP

Position

HWE P

Alleles

Cases a

Controls a

χ2

P

aOR b (95% CI)

Power

1

rs9898876

7,623,644

0.154

G:T

0.121

0.089

2.453

0.117

 

90

2

rs13894

7,626,584

0.149

C:T

0.345

0.370

0.751

0.386

 

63

3

rs858521

7,626,829

0.461

C:G

0.536

0.494

1.832

0.176

 

100

4

rs1799941

7,630,105

0.686

G:A

0.175

0.206

1.603

0.206

 

83

5

rs6257

7,630,399

0.084

T:C

0.163

0.249

10.82

0.001

0.59 (0.43–0.81)

100

6

rs6259

7,633,209

0.050

G:A

0.041

0.039

0.011

0.917

 

89

7

rs727428

7,634,474

0.783

G:A

0.411

0.433

0.262

0.609

 

42

aMAF frequency

baOR = adjusted OR; variables that were controlled for were BMI, menarche, systolic and diastolic blood pressure

The distribution of SHBG genotypes between RPL cases and control women are shown in Table 3. Significantly higher frequencies of heterozygous rs858521 (0.51 vs. 0.44) and rs6259 (0.07 vs. 0.03), and homozygous rs858521 (0.28 vs. 0.26) genotype carriers, and reduced frequency of heterozygous rs6257 (0.23 vs. 0.32) and homozygous rs6257 (0.05 vs. 0.08) and rs6259 (0.003 vs 0.03) genotype carriers were seen in RPL cases vs. control women, respectively. The distribution of the remaining genotypes was comparable between RPL cases and control women.
Table 3

SHBG Genotype Frequencies

 

1/1 a

1/2 a

2/2 a

 

SNP

Cases

Controls

Cases

Controls

Cases

Controls

P b

rs9898876

247 (0.80) c

260 (0.84)

49 (0.16)

43 (0.14)

12 (0.04)

7 (0.02)

0.425

rs13894

136 (0.44)

133 (0.43)

131 (0.43)

131 (0.42)

41 (0.13)

46 (0.15)

0.872

rs858521

64 (0.21)

94 (0.30)

158 (0.51)

135 (0.44)

86 (0.28)

81 (0.26)

0.035

rs1799941

204 (0.66)

202 (0.65)

96 (0.31)

94 (0.30)

8 (0.03)

14 (0.05)

0.398

rs6257

222 (0.72)

187 (0.60)

70 (0.23)

98 (0.32)

16 (0.05)

25 (0.08)

0.019

rs6259

284 (0.92)

293 (0.95)

23 (0.07)

10 (0.03)

1 (0.003)

7 (0.02)

0.042

rs727428

115 (0.37)

107 (0.35)

143 (0.46)

142 (0.46)

50 (0.16)

61 (0.20)

0.877

aGenotypes were coded as per “1” = major allele, “2” = minor allele

b2-way ANOVA

cNumber of subjects (frequency)

Risk of RPL associated with SHBG genotypes

The risk of RPL imparted by the tested SHBG variants was evaluated by logistic regression analysis, which was performed first at the univariate, and later at the multivariate levels, taking control status as an independent variable and the SHBG SNPs as dependent variables, after controlling for BMI, menarche, and systolic and diastolic blood pressure. Univariate regression analysis confirmed the positive association of rs858521 [P = 0.01; OR (95% CI) = 1.72 (1.13–2.60)] and rs6259 [P = 0.03; OR (95% CI) = 15.75 (1.29–192.46)] with RPL (Table 4). Multivariate regression analysis confirmed the positive association of rs858521 heterozygote [P = 0.007; aOR (95% CI) =1.80 (1.17–2.77)] and homozygote [P = 0.05; aOR (95% CI) = 1.60 (1.00–2.58)] genotypes with RPL. On the other hand, only heterozygous rs6259 remained associated with RPL after controlling for the confounders [P = 0.03; aOR (95% CI) = 16.08(1.28–202.08)] (Table 3).
Table 4

Univariate and multivariate analysis of SHBG genotypes association with RPLa

 

Univariate

Multivariate

 

1/2 b

2/2

1/2

2/2

SNP

P

OR (95% CI)

P

OR (95% CI)

P

aOR c (95% CI)

P

aOR (95% CI)

rs9898876

0.46

1.56 (0.49–5.02)

0.26

1.87 (0.63–5.58)

0.34

1.78 (0.54–5.87)

0.20

2.07 (0.69–6.23)

rs13894

0.65

0.89 (0.54–1.48)

0.61

0.88 (0.53–1.45)

0.84

0.95 (0.57–1.59)

0.77

0.93 (0.56–1.55)

rs858521

0.01

1.72 (1.13–2.60)

0.07

1.53 (0.96–2.44)

0.007

1.80 (1.17–2.77)

0.05

1.60 (1.00–2.58)

rs1799941

0.19

1.94 (0.72–5.25)

0.19

1.92 (0.73–5.08)

0.16

2.15 (0.75–6.16)

0.19

1.99 (0.71–5.57)

rs6257

0.85

0.93 (0.44–1.99)

0.11

0.56 (0.27–1.14)

0.68

0.84 (0.38–1.89)

0.07

0.50 (0.23–1.06)

rs6259

0.03

15.75 (1.29–192.46)

0.11

6.42 (0.66–62.33)

0.03

16.08 (1.28–202.08)

0.11

6.42 (0.65–63.70)

rs727428

0.70

0.83 (0.32–2.17)

0.61

0.77 (0.28–1.10)

0.67

0.81 (0.31–2.13)

0.59

0.76 (0.28–2.08)

aHomozygous major allele genotypes were taken as reference (OR = 1.00)

bGenotypes were coded as per “1” = major allele, “2” = minor allele

caOR = adjusted odds ratios; BMI and age were the main covariates that were controlled for

Identification of SHBG haplotypes associated with RPL

We evaluated the interaction between the six tested SHBGSNPs and their mode of inheritance in RPL cases and control women. The SHBG SNPs were aligned according to their chromosomal locations (www.ncbi.nlm.nih.gov/snp), and the interaction between any all possible pair of SNPs was visualized by Haploview (Fig. 1). Haploview analysis demonstrated marked LD among SHBG SNPs (Fig. 1). Each haplotype contains the next six loci: rs13894- rs858521- rs1799941- rs6257- rs6259- rs727428 and only 12 haplotypes were captured. Of the theoretical 64 haplotypes, only 12 were found to be common, capturing 91.8% of all haplotype pool, and were included in subsequent analysis. Within these haplotypes, only increased frequency of CCGTGA (P = 6.5 × 10− 3) haplotypes was seen in RPL cases, thus conferring disease susceptibility (OR = 1.66 (1.16–2.38) (Table 5).
Figure 1
Fig. 1

Haploview graph of SHBG SNPs analyzed. The positions of the seven SNPs used (Build 37.3) are indicated along with the basic gene structure, and displayed above the Haploview output. The relative LD between specific pair of SHBG SNPs is indicated by the color scheme, which represents the LD relationships. This is based on D’ values (normalized linkage disequilibrium measure or D) multiplied by 100; D’ is calculated as D divided by the theoretical maximum for the observed allele frequencies. Values approaching zero indicate absence of LD, and those approaching 100 indicate complete LD. The square colored red represent varying degrees of LD < 1 and LOD (logarithm of odds) > 2 scores; darker shades indicating stronger LD

Table 5

Haplotype frequencies across 7 SHBG SNPs analyzed a

Haplotypeb

Frequency

Case:Control frequencies

χ2

P

aOR (95% CI)

C C G T G A

0.138

0.165; 0.108

7.405

6.5 × 10−3

1.66 (1.16–2.38)

C G G T G G

0.128

0.132; 0.124

0.163

0.687

 

C C A T G G

0.115

0.106; 0.125

1.001

0.317

 

T G G T G G

0.087

0.092; 0.081

0.420

0.517

 

C G G C G G

0.069

0.061; 0.078

1.158

0.282

 

T C G T G A

0.066

0.064; 0.067

0.030

0.863

 

C G G C G A

0.060

0.047; 0.074

3.422

0.064

 

T G G C G A

0.055

0.045; 0.067

2.411

0.121

 

C C G T G G

0.054

0.062; 0.045

1.626

0.202

 

T C A T G G

0.052

0.052; 0.052

0.001

0.986

 

T C G T G G

0.047

0.044; 0.051

0.329

0.567

 

C G G T G A

0.047

0.048; 0.045

0.055

0.814

 

aSHBG haplotypes: rs13894- rs858521- rs1799941- rs6257- rs6259- rs727428

bUnderlined indicates minor allele

Discussion

Overview of the association of SHBG SNPs with RPL

Mounting evidence suggests that hyperandrogenemia in RPL is associated with abnormal LH levels and altered sex hormone production by ovaries or adrenal glands [2, 9], increased peripheral aromatase activity, or decreased testosterone clearance [19, 20]. Since SHBG is key to hyperandrogenemia, and as SHBG production is genetically determined [17], we investigated the association of SHBG variants with RPL. SHBG gene is highly polymorphic, and 902 variants were identified in NCBI database (www.ncbi.nlm.nih.gov/gene/6462), some of which modulate circulating SHBG concentrations.

Significance of the findings

While many SHBG gene variants were reported, the novel finding here was the strong association of three of the seven tested variants (rs6257, rs6259, rs858521) with RPL. Compared to previous studies, this study is distinct in the relatively large sample size, new SHBG variants investigated, and the population investigated. This extends the list of SHBG gene variants implicated in RPL pathogenesis, thereby supporting a key role for SHBG in RPL, presumably through controlling hyperandrogenemia.

Main findings

The main finding here was the strong association of rs6257 with reduced risk of RPL at the allele level, while both rs858521 and rs6259 were positively associated with RPL at the genotype level. Of these, only heterozygous rs6259 remained associated with RPL after controlling for mean BMI, menarche, and blood pressure, since RPL cases were not matched to controls. Six-locus (rs13894-rs858521-rs1799941-rs6257-rs6259-rs727428) SHBG haplotype identified CCGTGA haplotype to be positively associated with increased risk of RPL. Significant differences were noted with respect to mean BMI, menarche, and systolic and diastolic blood pressure readings were different between RPL cases and control women. Although they did not constitute strong risk factors of RPL, they were selected as the covariates that were controlled for in subsequent analysis.

MAF of the tested SHBG variants among control women reflect the ethnic diversity of present-day Tunisians, which results from admixture of the ethnicities who sequentially invaded and populated Tunisia throughout history [21]. MAF of rs858521, rs1799941, and rs727428 was comparable between Bahraini and Caucasians (HapMap-CEU), and Africans. On the other hand, MAF of rs13894 and rs6257 were the highest recorded for any ethnic group, while MAF of rs6259 (0.039) was intermediate between those recorded for Caucasians (0.124) and Africans (0.009). Furthermore, MAF of rs9898876 recorded for Bahraini (0.089) was lower than that established for Caucasians (0.222) and Africans (0.132). This underscores the need for evaluation of differences in ethnic/racial background in genetic association studies.

Interpretation of results

Progressive increases in maternal SHBG levels are seen throughout pregnancy, ranging from 1.61% in first trimester to almost 6% during mid-to-late pregnancy [6, 11, 22], which were suggested to protect mothers from androgen derived from the fetus [6, 23]. In contrast, minimal fluctuations in total testosterone (1.21–2.15%) and free testosterone (3.02–4.30%) levels were noted during pregnancy, suggesting that additional mechanisms operate in minimizing pregnancy-induced hyperandrogenemia [22, 23]. A role for SHBG in maintaining pregnancy was highlighted by the findings that reduction in SHBG levels were seen in miscarrying women compared to controls [14]. Insofar as genetic factors contribute to variation in SHBG levels, and thus and thus to the pathogenesis of gynecological diseases, low plasma SHBG levels, resulting from genetic variations in SHBG gene were associated with pregnancy complications, including RPL [24]. In this context, the present study evaluated the implication of seven SNPs in SHBG on RPL.

Based on its allele and genotypes distribution in RPL cases and controls, our results suggest that SHBG rs6257 (Intron 1) gene variant may modulate the risk of RPL. While this variant was previously associated with OB/GYN complications [25, 26] including PCOS [16, 27], this is the first report to document its association with RPL. Despite its intronic location, rs6257 appears to have functional capacity, as it maps to a potential binding site for Hepatocyte Nuclear Factor 3/Fox transcription factor, which was shown to influence SHBG levels [28]. While not tested here, carriage of rs6257 minor allele alters testosterone binding to SHBG, and hence testosterone bioavailability and action at target tissue site, including reproductive organs and tissues [29].

On the other hand, both rs6259 (D327N) and rs858521 were positively associated with RPL. While SHBG rs6259 is the most investigated of all reported SHBG variants, this is the first report describing its association with RPL. Mixed association of this variant with obstetric complications. For example, rs6259 was not associated with PCOS in Bahraini [16], Turkish [30], and Spanish [27] subjects. Moreover, this polymorphism was also studied in hormone-sensitive cancers and the results revealed that rs6259 minor allele was associated with reduced risk of endometrial cancer in postmenopausal, but not premenopausal women [31]. Reduced frequency of rs6259 minor allele was also reported in ovarian cancer [32], and breast cancer [33], presumably by increasing serum SHBG levels, particularly among postmenopausal women. Asn327 allele was associated with increased circulating SHBG levels, and with reduced estradiol-to-SHBG ratio, suggesting that rs6259 contributes the bioavailability of estrogens [34]. The functionality of D327N resides in the capacity of the (minor) Asn327 allele to decreases clearance rate of SHBG, resulting in increased half-life of SHBG and hence increased circulating SHBG levels [35].

Study strengths and shortcomings

Our study has strengths. RPL cases and control women were ethnically matched, hence minimizing the problems of differences in genetic background inherent in genetic association studies. It was also sufficiently powered, and key covariates were controlled for in single SHBG variant and haplotype analysis. However, our study had several limitations. We did not measure circulating SHBG levels, and thus could not address the cause-effect relationship, as well as determine free testosterone levels and free androgen index (hallmarks of hyperandrogenemia). Furthermore, matching for ethnic origin was dependent on self-declared Arab vs. Non-Arab Tunisian origin, thus prompting the speculation of genetic population stratification bias. Lastly, the study examined the association of RPL with seven common SHBG gene variants distributed between intronic, exonic, and 5′ and 3′ untranslated regions, thus questioning of the potential association of other (untested) SHBG variants with RPL.

Conclusion

In conclusion, this is the first study that demonstrated that SHBG rs858521 and rs6259, and to a lesser extent rs6257 variants, are associated with RPL. As mounting evidence suggest that some SHBG genetic variants influence SHBG levels, the mechanism by which SHBG influence the risk of RPL will expand on the role of SHBG in infertility. Follow up studies on additional SHBG variants, and populations of related and distant ethnic origin are needed to fully elucidate the association of altered SHBG production stemming from the presence of specific SHBG variants, and consequently hyperandrogenemia with the risk of RPL.

Abbreviations

BP: 

blood pressure

LD: 

Linkage disequilibrium

MAF: 

minor allele frequency

RPL: 

Recurrent pregnancy loss

SHBG: 

sex hormone binding globulin

SNP: 

single nucleotide polymorphism

Declarations

Acknowledgments

The authors wish to thank Dr. Mona Arekat for her helpful suggestions. The expert technical assistance of Ms. Zainab H. Malalla is greatly acknowledged.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

MD Sample processing, drafting of manuscript. RRF Patient screening and referral. MM Genotyping assays. WYA Project leader, finalizing the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The study protocol was approved by Arabian Gulf University Research & Ethics Committee (IRB approval: 35-PI-01/15, granted on 17 October 2014), and was done according to Helsinki II Declaration. All patients provided informed written consent before blood sampling.

Competing interests

The authors declare that they have no competing interests to declare.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Faculty of Pharmacy, University of Monastir, Monastir, Tunisia
(2)
Department of Obstetrics and Gynecology, Hôtel Dieu de France, CHU Université St. Joseph, Beirut, Lebanon
(3)
Faculty of Sciences Tunis, University of Tunis El Manar, Tunis, Tunisia
(4)
School of Pharmacy, Lebanese American University, Byblos, Lebanon

References

  1. Christiansen OB, Steffensen R, Nielsen HS, Varming K. Multifactoria etiology of recurrent miscarriage and its scientific and clinical implications. Gynecol Obstet Investig. 2008;66:257–67.View ArticleGoogle Scholar
  2. Pluchino N, Drakopoulos P, Wenger JM, Petignat P, Streuli I, Genazzani AR. Hormonal causes of recurrent pregnancy loss (RPL). Hormones (Athens). 2014;13:314–22.View ArticleGoogle Scholar
  3. Smith ML, Endocrinology SDJ. Recurrent early pregnancy loss. Semin Reprod Med. 2011;29:482–90.View ArticlePubMedGoogle Scholar
  4. Ke RW. Endocrine basis for recurrent pregnancy loss. Obstet Gynecol Clin N Am. 2014;41:103–12.View ArticleGoogle Scholar
  5. Benhadi N, Wiersinga WM, Reitsma JB, Vrijkotte TG, Bonsel GJ. Higher maternal TSH levels in pregnancy are associated with increased risk for miscarriage, fetal or neonatal death. Eur J Endocrinol. 2009;160:985–91.View ArticlePubMedGoogle Scholar
  6. Makieva S, Saunders PT, Norman JE. Androgens in pregnancy: roles in parturition. Hum Reprod Update. 2014;20:542–59.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Arck PC, Rücke M, Rose M, Szekeres-Bartho J, Douglas AJ, Pritsch M, Blois SM, Pincus MK, Bärenstrauch N, Dudenhausen JW, Nakamura K, Sheps S, Klapp BF. Early risk factors for miscarriage: a prospective cohort study in pregnant women. Reprod BioMed Online. 2008;17:101–13.View ArticlePubMedGoogle Scholar
  8. Gürbüz B, Yalti S, Ozden S, Ficicioglu C. High basal estradiol level and FSH/LH ratio in unexplained recurrent pregnancy loss. Arch Gynecol Obstet. 2004;270:37–9.View ArticlePubMedGoogle Scholar
  9. Cocksedge KA, Saravelos SH, Wang Q, Tuckerman E, Laird SM, Li TC. Does free androgen index predict subsequent pregnancy outcome in women with recurrent miscarriage? Hum Reprod. 2008;23:797–802.View ArticlePubMedGoogle Scholar
  10. Hammond GL. Plasma steroid-binding proteins: primary gatekeepers of steroid hormone action. J Endocrinol. 2016;230:R13–25.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Hammond GL. Diverse roles for sex hormone-binding globulin in reproduction. Biol Reprod. 2011;85:431–41.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Mazer NAA. Novel spreadsheet method for calculating the free serum concentrations of testosterone, dihydrotestosterone, estradiol, estrone and cortisol: with illustrative examples from male and female populations. Steroids. 2009;74:512–9.View ArticlePubMedGoogle Scholar
  13. Kerlan V, Nahoul K, Le Martelot MT, Bercovici JP. Longitudinal study of maternal plasma bioavailable testosterone and androstanediol glucuronide levels during pregnancy. Clin Endocrinol. 1994;40:263–7.View ArticleGoogle Scholar
  14. Spencer K, Yu CK, Rembouskos G, Bindra R, Nicolaides KH. First trimester sex hormone-binding globulin and subsequent development of preeclampsia or other adverse pregnancy outcomes. Hypertens Pregnancy. 2005;24:303–11.View ArticlePubMedGoogle Scholar
  15. Berube D, Seralini GE, Gagne R, Hammond GL. Localization of the human sex hormone binding globulin gene (SHBG) to the short arm of chromosome 17 (17p12–p13). Cytogenet Cell Genet. 1990;54:65–7.View ArticlePubMedGoogle Scholar
  16. Abu-Hijleh TM, Gammoh E, Al-Busaidi AS, Malalla ZH, Madan S, Mahmood N, Almawi WY. Common variants in the sex hormone-binding globulin (SHBG) gene influence SHBG levels in women with polycystic ovary syndrome. Ann Nutr Metab. 2016;68:66–74.View ArticlePubMedGoogle Scholar
  17. Xita N, Tsatsoulis A. Genetic variants of sex hormone-binding globulin and their biological consequences. Mol Cell Endocrinol. 2010;316:60–5.View ArticlePubMedGoogle Scholar
  18. Su MT, Lin SH, Chen YC. Association of sex hormone receptor gene polymorphisms with recurrent pregnancy loss: a systematic review and meta-analysis. Fertil Steril. 2011;96:1435–44.View ArticlePubMedGoogle Scholar
  19. Cupisti S, Fasching PA, Ekici AB, Strissel PL, Loehberg CR, Strick R, Engel J, Dittrich R, Beckmann MW, Goecke TW. Polymorphisms in estrogen metabolism and estrogen pathway genes and the risk of miscarriage. Arch Gynecol Obstet. 2009;280:395–400.View ArticlePubMedGoogle Scholar
  20. Suryanaryana VV, Rao L, Kanakavalli MK, Padmalatha VV, Deenadayal M, Singh L. Role of CYP17 and CYP19 polymorphisms in idiopathic recurrent miscarriages among south Indian women. Reprod BioMed Online. 2007;14:341–7.View ArticlePubMedGoogle Scholar
  21. Hajjej A, Almawi WY, Hattab L, Hmida S. Anthropological analysis of Tunisian populations as inferred from HLA class I and class II genetic diversity: a meta-analysis. Immunol Lett. 2017;185:12–26.View ArticlePubMedGoogle Scholar
  22. Grzesiak M, Knapczyk-Stwora K, Ciereszko RE, Golas A, Wieciech I, Slomczynska M. Androgen deficiency during mid- and late pregnancy alters progesterone production and metabolism in the porcine corpus luteum. Reprod Sci. 2014;21:778–90.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Crisosto N, Echiburu B, Maliqueo M, Perez V, Ladron de Guevara A, Preisler J, Sanchez F, Sir-Petermann T. Improvement of hyperandrogenism and hyperinsulinemia during pregnancy in women with polycystic ovary syndrome: possible effect in the ovarian follicular mass of their daughters. Fertil Steril. 2012;97:218–24.View ArticlePubMedGoogle Scholar
  24. Hogeveen KN, Cousin P, Pugeat M, Dewailly D, Soudan B, Hammond GL. Human sex hormone-binding globulin variants associated with hyperandrogenism and ovarian dysfunction. J Clin Invest. 2002;109:973–81.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Sunbul M, Eren F, Nacar C, Agirbasli M. Sex hormone binding globulin gene polymorphisms and metabolic syndrome in postmenopausal Turkish women. Cardiol J. 2013;20:287–93.View ArticlePubMedGoogle Scholar
  26. Thompson DJ, Healey CS, Baynes C, Kalmyrzaev B, Ahmed S, Dowsett M, Folkerd E, Luben RN, Cox D, Ballinger D, Pharoah PD, Ponder BA, Dunning AM, Easton DF. Studies in epidemiology and risks of Cancer heredity team. Identification of common variants in the SHBG gene affecting sex hormone-binding globulin levels and breast cancer risk in postmenopausal women. Cancer Epidemiol Biomark Prev. 2008;17:3490–8.View ArticleGoogle Scholar
  27. Martinez-Garcia MA, Gambineri A, Alpanes M, Sanchon R, Pasquali R, Escobar-Morreale HF. Common variants in the sex hormone binding globulin gene (SHBG) and polycystic ovary syndrome (PCOS) in Mediterranean women. Hum Reprod. 2012;27:3569–76.View ArticlePubMedGoogle Scholar
  28. Riancho JA, Valero C, Zarrabeitia MT, García-Unzueta MT, Amado JA, González-Macías J. Genetic polymorphisms are associated with serum levels of sex hormone binding globulin in postmenopausal women. BMC Med Genet. 2008;9:112.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Mannerås-Holm L, Baghaei F, Holm G, Janson PO, Ohlsson C, Lönn M, Coagulation S-VE. Fibrinolytic disturbances in women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2011;96:1068–76.View ArticlePubMedGoogle Scholar
  30. Hacıhanefioğlu B, Aybey B, Hakan Özön Y, Berkil H, Karşıdağ K. Association of anthropometric, androgenic and insulin-related features with polymorphisms in exon 8 of SHBG gene in women with polycystic ovary syndrome. Gynecol Endocrinol. 2013;29:361–4.View ArticlePubMedGoogle Scholar
  31. Kataoka N, Cai Q, Xu WH, Xiang YB, Cai H, Zheng W, Shu XO. Association of endometrial cancer risk with a functional polymorphism (asp(327)Asn) in the sex hormone-binding globulin gene. Cancer. 2007;109:1296–302.View ArticlePubMedGoogle Scholar
  32. Garcia-Closas M, Brinton LA, Lissowska J, Richesson D, Sherman ME, Szeszenia- Dabrowska N, Peplonska B, Welch R, Yeager M, Zatonski W, Chanock SJ. Ovarian cancer risk and common variation in the sex hormone binding globulin gene: a population-based case–control study. BMC Cancer. 2007;7:60.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Cui Y, Shu XO, Cai Q, Jin F, Cheng JR, Cai H, Gao YT, Zheng W. Association of breast cancer risk with a common functional polymorphism (Asp327Asn) in the sex hormone-binding globulin gene. Cancer Epidemiol Biomark Prev. 2005;14:1096–101.View ArticleGoogle Scholar
  34. Dunning AM, Dowsett M, Healey CS. Tee L, Luben RN, Folkerd E, Novik KL, Kelemen L, Ogata S, Pharoah PD, Easton DF, day NE, ponder BA. Polymorphisms associated with circulating sex hormone levels in postmenopausal women. J Natl Cancer Inst. 2004;96:936–45.View ArticlePubMedGoogle Scholar
  35. Cousin P, Déchaud H, Grenot C, Lejeune H, Pugeat M. Human variant sex hormone-binding globulin (SHBG) with an additional carbohydrate chain has a reduced clearance rate in rabbit. J Clin Endocrinol Metab. 1998;83:235–40.PubMedGoogle Scholar

Copyright

© The Author(s) 2018

Advertisement