Association of adiponectin gene variants with idiopathic recurrent miscarriage according to obesity status: a case–control study

This retrospective case–control study was performed between January 2013 and June 2015. Study population included 308 women with confirmed RPL who were recruited consecutively from the outpatient OB/GYN clinics in Manama and Riffa (Bahrain). In addition, we recruited 310 multiparous women with two or more successful pregnancies as controls. The study protocol was approved by Arabian Gulf University Research and Ethics Committee (IRB approval: 35-PI-01/15), and was done according to Helsinki II Declaration. All patients provided informed written consent before blood sampling.

We defined RPL as ≥ 3 consecutive pregnancy losses of undetermined etiology, which occurred between the 7th–20th week of gestation, and with the same partner. RPL assessment was according to the guidelines of the Royal College of Obstetricians and Gynecologists (https://​www.​rcog.​org.​uk/​guidelines). These required screening for LAC (lupus anticoagulant) and ACL (anticardiolipin) anti-phospholipid antibodies, and the inherited thrombophilias Factor V-Leiden (R506Q) and factor II/prothrombin G20210A. Karyotyping of both parents, and pelvic ultrasound scan by hysteroscopy or sonohysteroscopy for evaluation of uterine anatomy were also performed on all RPL cases. RPL cases were excluded if they were 40 years or older at first pregnancy, incompatibility in Rh blood groups, history of PE, which was defined as elevation in systolic/diastolic blood pressure (BP) exceeding 145/95 mmHg, or increase in systolic/diastolic BP exceeding 30/15 mmHg on at least two occasions, as well as biochemical pregnancy, and preclinical miscarriages. Cases were also excluded if they had systemic autoimmunity, thyroid dysfunction, diabetes, liver function abnormalities, anatomical disorders, and infections (toxoplasmosis, HIV, HCMV, Group B streptococci, Chlamydia trachomatis, hepatitis B and C viruses, rubella, and bacterial vaginosis).

ADIPOQ single nucleotide polymorphisms (SNP) with minor allele frequencies (MAF) that exceeded 5% in Caucasians (HapMap CEU), were selected using SNPbrowser software 4.0 (ABI-ThermoFisher, Foster City, CA). Genotyping was done by the allelic discrimination method using VIC-/FAM-labelled primers (Table 2). Assay-on-demand TaqMan assays were obtained from ABI-ThermoFisher. PCR was performed in 6 μl volume on StepOne Plus real-time PCR system, according to instructions of the manufacturer (ABI-ThermoFisher). A typical RT-PCR consisted of adding 2.2 µl DNA template, and 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) stage was performed for 30 s at 60 °C, and for 10 min at 95 °C. The cycles conditions will be repeated 35 times, and consisted 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 quality control samples (≈ 10% of cases and controls) were included for assessment of genotyping reproducibility; concordance consistently exceeded 99%.

Statistical analysis was done on SPSS v. 24 (IBM, Armonk, NY). Categorical variables were expressed as percent of total, while continuous data were presented as mean ± SD. Differences in means were analyzed using Student’s t test, and inter–group significance was assessed by Pearson χ² or Fisher’s exact test. Hardy–Weinberg equilibrium (HWE) calculation was done for control women using Haploview 4.2 (https://​www.​broad.​mit.​edu/​mpg/​haploview). SNPStats (https://​bioinfo.​iconcologia.​net/​snpstats) was used for genetic association analysis, under the assumption of additive genetic model. Power calculation for detection of association between ADIPOQ variants and RPL was done using CaTS Power Calculator (https://​www.​sph.​umich.​edu/​csg/​abecasis/​cats). We used the following parameters: 308 RPL cases and 310 control women, relative risk for heterozygous and minor allele homozygous genotypes, and MAF for the 14 tested ADIPOQ SNPs RPL in cases and controls, and assuming a 2.5% population RPL prevalence in Bahrain (Bahrain Ministry of Health unpublished statistics). The overall power was calculated as 72.1%, which represented the average power of the included SNPs. Haploview 4.2 was used for determination of linkage disequilibrium (LD) and haplotype reconstruction, the latter done according to expectation maximization (EM) algorithm. Taking control women as the reference group, logistic regression analysis was used in determining odds ratios (OR) and 95% confidence intervals (CI) associated with the risk of RPL; P < 0.05 was taken as statistically significant.

Table 1 summarizes the demographic and clinical profiles of RPL cases and control women. Age at entry into the study, fasting plasma glucose, gravida, and number of smokers were not significantly different between women with RPL and control subjects. Significant differences between the two study groups were seen in mean BMI (P = 0.004), menarche (P < 0.001), and in systolic/diastolic blood pressure readings (P < 0.001). While these did not constitute established RPL risk factors, we nevertheless included them as covariates which we controlled for in later analysis.

Table 2 presents the association between ADIPOQ SNP and RPL in women with RPL and control women. Genotype distributions of all 14 tested ADIPOQ variants conformed to HWE among study subjects. Among ADIPOQ SNP tested, higher MAF of rs4632532 (P = 8.00 × 10⁻³), rs17300539 (P = 0.011), rs266729 (P = 4.00 × 10⁻³), rs182052 (P = 7.00 × 10⁻⁴), rs16861209 (P = 9.00 × 10⁻³), rs7649121 (P = 0.044), thereby assigning RPL susceptibility to these variants. On the other hand, MAF of rs2241767 (P = 0.041) and rs1063539 (P = 0.048), was lower in women with RPL than in control women, suggesting RPL-protection associated with these ADIPOQ variants. No significant differences in MAF of the remaining SNPs were seen between women with RPL and controls.

Table 3 lists the distribution of ADIPOQ genotypes between women with RPL and control women. Taking major allele homozygous genotype (1/1) as the reference group (OR = 1.00), after controlling for BMI, systolic/diastolic blood pressure, and menarche, significantly higher frequencies of heterozygous rs17300539 (0.17 vs. 0.08) and rs16861209 (0.32 vs. 0.15), and homozygous rs4632532 (0.13 vs. 0.08), rs266729 (0.11 vs. 0.05), and rs182052 (0.16 vs. 0.05) genotypes were seen in RPL cases vs. control women. In addition, reduced genotype frequencies of heterozygous rs1063539 (0.21 vs. 0.31) and rs2241767 (0.22 vs. 0.31), and homozygous rs2241766 (0.02 vs. 0.07) were seen in women with RPL compared to controls. The distribution of the remaining genotypes was not significantly different between women with RPL and control subjects.

In view of the effect of ADIPOQ SNPs on adiponectin secretion, and the impact of adiposity of pregnancy outcome, we examined the association of the tested ADIPOQ polymorphisms with RPL in obese and non-obese RPL cases and controls. Women with RPL and control women were sub grouped into non-obese and obese according to BMI cutoff of 30 kg/m². Results from Table 4 demonstrate differential association of ADIPOQ SNPs with RPL according to obesity was seen, with rs16861209 (P = 0.034), rs182052 (P = 0.004), and rs7649121 (P = 0.040) being positively associated, while rs1063539 (P = 0.028) was negatively associated with RPL in obese subjects (Table 3). In contrast, rs182052 (P = 0.005), and rs7649121 (P = 0.046) were positively, while rs4632532 (P = 0.002), and rs2241766 (P = 0.021) were negatively associated with RPL in obese subjects.

The interaction between tested ADIPOQ variants, and their mode of inheritance in women with RPL and control women was next evaluated. The interaction between pair of SNP visualized by Haploview (Fig. 1). Haploview analysis showed marked LD among the tested ADIPOQ variants (Fig. 1), and defined two haploblocks. Haploblock 1 spanned 17 kb, and contained rs4632532, rs16861194, rs17300539, rs266729, rs182052, rs16861209, rs822396, and rs7649121, while Haploblock 2 spanned 4 kb, and contained rs2241766, rs1501299, rs2241767, rs3774261, rs6773957, and rs1063539.

“Common haplotype” was defined as the haplotype with frequencies > 2% of the total haplotypes. Within Haploblock 1, 94.8% of 8-locus haplotype diversity was captured by 9 of the possible 256 haplotypes. Higher frequencies of CAGGACAT (P = 5.1 × 10⁻³) and TAACGAAA (P = 0.012), and reduced frequency of TAGCGCAA (P = 7.6 × 10⁻⁵) haplotypes were seen in RPL cases, suggesting RPL-susceptible and RPL-protective aspect of these haplotypes, respectively. The frequencies of remaining haplotypes in Haploblock 1, and all haplotypes in Haploblock 2 were comparable between women with RPL and control women (Table 5).

ADIPOQ is a highly polymorphic gene (https://​www.​ncbi.​nlm.​nih.​gov/​gene/​9370), and 2376 variants were identified, some of which modulate circulating adiponectin concentrations [18, 23, 25]. We investigated the association between RPL and variants in the intergenic, 5′-near gene, promoter, introns, exons, and 3′-UTR regions of ADIPOQ gene. Among the 14 tested variants, significant association with RPL risk was seen with intergenic (rs4632532), intronic (rs7649121, rs2241767), and exonic (rs2241766, rs1501299) ADIPOQ variants. This is the first report that identified these ADIPOQ variants as RPL at-risk loci, further supporting a role for adiponectin in the pathogenesis of RPL.

The association between (exonic) rs1501299 (+ 276G > T) and RPL seen here was in apparent disagreement with a study on North Indian women, which reported marginal association of the + 276G > T variant (P = 0.0360) with reduced risk of RPL [16]. This discrepancy is likely attributed to differences in ethnic background of study participants, study selection criteria and genotyping conditions. The rs1501299 (+ 276G > T) variant was associated with altered adiponectin serum levels [26], and with hypertensive disorder complicating pregnancy (HDCP) in Chinese subjects [27].

In addition to rs1501299, rs266729 was associated with GDM in Polish [22] and Bulgarian [20], but not Brazilian women [21]; its minor (G) allele conferring protection against GDM [20]. Functionally, rs266729 was linked with altered adiponectin levels in Caucasians [17, 28], which was attributed to the capacity of its minor (G) allele to destroy Sp1 transcription factor DNA binding in the ADIPOQ promoter region [29].

ADIPOQ rs7649121 was linked with reduced risk of coronary heart disease in Chinese [30]. In addition, r rs17300539 was reportedly associated with reduced adiponectin levels in white women [31], and in T2DM patients [32]. Our study is the first to demonstrate positive association between rs7649121 and rs17300539 and RPL. On the other hand, rs2241767 was negatively associated with RPL in our cohort. This variant was associated with T2DM in Tunisian Arabs [33], and with insulin resistance in Mexican Americans [34].

ADIPOQ rs2241766 variant is present in exon 2, and its functional attributes are not understood, although it does not alteration of target amino acid sequence. It was reported that the carriage of rs2241766 is associated with altered mRNA splicing and/or stability [26]. While a number of studies documented association of (exonic) rs2241766 variant with pregnancy complications [21, 35], including PCOS in Brazilian [21], but not Chinese [36] women, it was not associated with RPL in our cohort. This was in agreement with the earlier study on non-obese North Indian women [16], which documented lack of association of rs2241766 with RPL.

Obesity is a major contributor to infertility, and is associated with reduced success of assisted reproductive technologies [4, 37]. Given the association of reduced adiponectin to obesity and insulin resistance, a role for adiponectin in promoting successful pregnancy was suggested [14, 15]. There is a solid link between adiposity, obesity, insulin resistance and RPL [38]. Obesity was consistently associated with conditions linked with poor pregnancy outcome, including idiopathic RPL [3, 38].

Adiponectin was proposed to constitute an at-risk modulator of RPL. An earlier systematic review involving 24,738 women, concluded that obesity increases the risk of sporadic miscarriage [37], and was attributed to reduced adiponectin secretion [39, 40]. By controlling steroidogenesis and expression of genes involved in ovulation [13, 41], and induction of metabolic changes linked with adipose tissues dysfunction, particularly in genetically predisposed women [42], a central role of adiponectin in pregnancy outcome was established. In our hands, RPL-susceptible and—protective ADIPO SNP and haplotypes were identified, when unselected RPL cases were compared to control women, and also when RPL cases were stratified according to obesity.

Furthermore, we demonstrated that rs16861209, rs182052, and rs7649121 amplify RPL risk in non-obese women. This was in contrast to rs1063539 which was negatively associated with RPL, and presumably having a protective effect on pregnancy. On the other side, in obese subjects, rs4632532, rs182052, and rs7649121 were linked with increased RPL susceptibility, while rs2241766 was generally protective of RPL. This underscores the need for controlling for modifiable covariates in genetic association studies.

The strength of our study is that it is sufficiently powered, and that RPL cases and control women were matched according to ethnicity, which reduces the problems of ethnic differences inherent in genetic association studies. Another strength is controlling for potential covariates. Our study has also some shortcomings. We could not measure serum adiponectin levels in cases and control women, which did not allow for addressing the functionality of this association, thus could not ascertain genotype–phenotype correlations. Another limitation lies in its retrospective nature, which prompts speculation on cause-effect relationship.