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Gene variants in the FTO gene are associated with adiponectin and TNF-alpha levels in gestational diabetes mellitus

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Obesity may have a role in the development of gestational diabetes mellitus (GDM). Single-nucleotide-polymorphisms (SNPs) of the FTO (fat mass and obesity associated) gene have been associated with obesity. The aim of this study was to investigate SNPs rs8050136, rs9939609, and rs1421085 of the FTO gene in women with GDM and their associations with maternal pre-pregnancy weight and body mass index, gestational weight gain and mediators of insulin resistance in GDM like leptin, adiponectin, ghrelin and tumor necrosis factor-alpha (TNF-alpha), compared with healthy pregnant controls.


80 women with GDM and 80 women with normal pregnancy were considered for the present study. Genotyping of selected SNPs in all study subjects was done using the Taq-Man assay and the adipokines and ghrelin were measured by immunoassays. Chi square test, odds ratios (OR) and their respective 95% confidence intervals were used to measure the strength of association between FTO SNPs and GDM.


There was no association among FTO SNPs and GDM. Interestingly, in GDM group, women carrying the risk alleles of the three SNPs had increased TNF-alpha, and decreased adiponectin levels; these associations remained significant after adjusting for pre-gestational body weight and age. Moreover, the risk allele of rs1421085 was also associated with increased weight gain during pregnancy.


The FTP SNPs rs8050136, rs9939609, and rs1421085 are not a major genetic regulator in the etiology of GDM in the studied ethnic group. However, these SNPs were associated with adiponectin and TNF-alpha concentrations in GDM subjects.


The prevalence of obesity and overweight is increasing around the world [1]. Across the Organisation for Economic Co-operation and Development (OECD) countries, Mexico is the country with the second highest obesity rate among adults and a greater proportion of this population are women [2]. In 2012, among women of childbearing age, 18% were obese [3]. Obesity in women of reproductive age is a known risk factor for numerous health problems, including gestational diabetes mellitus (GDM), pregnancy induced hypertension, preeclampsia, caesarean delivery, post-partum hemorrhage, and delivery of large-for-gestational-age infants [4, 5]. Excessive gestational weight has also been associated with adverse health outcomes for both the mother and her child [6].

Obesity is a neuroendocrine disorder in which both genetic predisposition and environmental factors act in concert [7]. In recent years, genome-wide association studies (GWAS) have identified >90 loci containing single-nucleotide-polymorphisms (SNPs), many in intronic regions, associated with human obesity [8, 9]. The strongest genetic association with risk to polygenic obesity is in SNPs in intron 1 and 2 of the FTO (fat mass and obesity associated) gene [10, 11].

The precise mechanism responsible for FTO’s effect on obesity in humans has been elusive. It has been suggested that the obesity-associated FTO SNPs may affect obesity through greater food intake and increased hunger/lowered satiety and through modulating adiposity factors. The FTO SNP rs9939609 has been found to be significantly associated with levels of circulating ghrelin and leptin [12, 13], which are key mediators of ingestive behavior, and has been significantly associated with serum adiponectin, an antihyperglycemic, antiatherogenic, and anti-inflammatory adipokine [14]. Additionally, FTO SNP rs9939609 has been related to systemic inflammation [15], which is implicated in insulin resistance and diabetogenesis [16].

Increasing evidence suggests that the FTO SNPs influence the expression of genes proximal to FTO in the locus, namely, RPGRIP1L, IRX3, and IRX5 [17,18,19]. A recent study identified rs1421085 as a causal variant to obesity, which influences the expression of IRX3 and IRX5 in preadipocytes, changing human adipocytes from fuel utilization through enhanced thermogenesis to the function as substrate storage [20].

FTO variants rs9939609 and rs8050136 also confer higher risk for type 2 diabetes (T2D) in an adiposity-dependent manner and have been associated with body mass index (BMI) and GDM in Caucasians women [21,22,23,24,25]. The present study investigates the polymorphisms rs8050136, rs9939609, and rs1421085 of the FTO gene in women with gestational diabetes and their associations with maternal pre-pregnancy weight and BMI, gestational weight gain and mediators of insulin resistance in GDM like leptin, adiponectin, ghrelin and tumor necrosis factor-alpha (TNF-alpha), compared with healthy pregnant controls.



We recruited a total of 80 women with GDM and 80 women with normal pregnancy at the Hospital of Gynecology and Obstetrics, Medical Center La Raza, IMSS, Mexico City, Mexico, as described previously [26]. Briefly, the protocol was approved by our institutional review board, and informed consent was obtained from all participants. Gestational diabetes was diagnosed by a 2-h 75 g oral glucose tolerance test at 24–28 weeks of gestation, the cutoff values being >5.2 mmol/L at fasting, >10.0 mmol/L at 1 h, and >7.8 mmol/L at 2 h [27]. All women with GDM began nutritional therapy soon after diagnosis and 40 patients required insulin therapy. Patients with arterial hypertension, renal disease, liver disease, thyroid disorders, or other endocrine or chronic diseases were excluded from this study. In the morning, at gestational week 30 and before initiation of insulin therapy in those women with GDM treated with insulin, anthropometric measurements of height and weight were obtained using a medical scale, and blood samples were taken. Information regarding the demographic features was obtained from all the subjects with the help of a standard questionnaire.


The peripheral blood was obtained by a single venipuncture between 7:30 and 8:30 a.m. after an overnight fast. Samples were centrifuged, and serum was separated and frozen at −70 °C until assayed in a single run. Plasma glucose, triglycerides, and total cholesterol were measured by enzymatic assays with a Roche Cobas Mira analyzer using commercial kits (Stanbio Laboratory, Boerne, TX, USA). Insulin and ghrelin concentrations were determined by radioimmunoassay (RIA); insulin was measured using reagents from Siemens Healthcare Diagnostics (Los Angeles, CA, USA), sensitivity was 8.3 pmol/L and intra- and interassay coefficients of variation (CVs) were 5.2 and 7.3%, respectively. Ghrelin was determined using reagents from EMD Millipore Corporation (Billerica, MA, USA); sensitivity was 6.4 pg/mL and CVs were 4.4 and 9.2%. TNF-alpha was measured by chemiluminescent immunoassay (Immulite Analyzer, Diagnostic Products, Los Angeles, CA). Sensitivity was 1.7 pg/mL and CVs were 3.2 and 5.2%.

Genomic DNA was isolated from anticoagulated blood by using the GFX Genomic Blood DNA Purification Kit (AmershamBiosciences) and stored at −70 °C. Genotyping of selected SNPs in all study subjects was done using the Taq-Man assay (Applied Biosystems). The Taq-Man genotyping reaction was performed according to the manufacturer’s protocol [95 °C (10 min), then 40 cycles of 95 C (15 s), and 60 C (1 min)] on an StepOnePlus Real Time PCR system (Applied Biosystems, USA).

BMI was calculated as weight in kilograms divided by the square of height in meters. Insulin sensitivity was assessed by the validated homeostasis model assessment (HOMA) index [28] using the following formula: \({\text{HOMA-IR}} = \left( {{\text{FPG }}*{\text{ FPI}}} \right)/ 2 2. 5,\) where FPG and FPI are fasting plasma glucose (mmol/L) and fasting plasma insulin (μU/mL), respectively.

Statistical analyses

The Hardy–Weinberg (HW) distribution of the genotypes in the GDM and control groups was assessed. The allele distributions of polymorphisms among patients with GDM patients and normal subjects were evaluated by χ2 test and Fisher exact tests accordingly, calculating odds ratios (ORs), 95% confidence intervals (CIs), and corresponding P values. The Kolmogorov–Smirnov statistical test was used to test the normality of the distributions, and a nonparametric statistical analysis was performed. Data were expressed as median (interquartile range 25–75%). The Mann–Whitney U test was used for continuous variables, and the Chi square test was used for categorical data. The associations between genotypes and anthropometric characteristics, adipokines, ghrelin and TNF-alpha in GDM patients were evaluated using analysis of covariance (ANCOVA) with genotypes as a factor and age, pre-gestational body weight, and insulin therapy as covariates. We performed a multiple logistic regression analysis to estimate whether maternal age, maternal BMI, and FTO genotype were suitable as prognostic factors for GDM. P < 0.05 was considered statistically significant. Data were evaluated by using SPSS 21 (SPSS Inc, Chicago, IL).


Table 1 displays the anthropometric and biochemical characteristics from control and GDM subjects. Age, weight, BMI, glucose, insulin, HOMA-IR and triglycerides were significantly higher in the GDM women compared with controls. GDM patients also had a high prevalence of diabetes in their family history. Gestational weight gain, total cholesterol, leptin, adiponectin, ghrelin and TNF-alpha were not significantly different between groups.

Table 1 Anthropometric and biochemical characteristics at the time of recruitment

All genotypes in both groups were in HW equilibrium (P > 0.05). We estimated linkage disequilibrium (LD) among the three studied variants: rs8050136 was in complete linkage disequilibrium with rs9939609 and these SNPs and rs1421082 were in a tight LD block (D′ 0.94 and γ2 0.89).

The genotype and allele frequencies of the three studied polymorphisms were not significantly different between the groups (Table 2). As a result of the small number of homozygotes for the rare alleles, we compared the common allele homozygotes and the carriers of the rare allele in a dominant model.

Table 2 Genotypic distribution of the studied SNPs in controls and GDM patients

In GDM group, women carrying the A risk allele of rs8050136 and the A risk allele of rs9939609 had increased plasma TNF-alpha, and decreased adiponectin levels; these associations remained significant after adjusting for age and pre-gestational body weight. Moreover, C risk allele of rs1421085 was also associated with both increased weight gain during pregnancy and with TNF-alpha (Table 3). In contrast, no significant associations of FTO rs8050136, rs9939609, and rs1421085 were found with any of the studied biomarkers analyzed in control group (data not shown).

Table 3 Association of FTO SNPs with anthropometric characteristics, adipokines, ghrelin and TNF-α in GDM patients

In the logistic regression analysis, the association between GDM and maternal age as well as weight was significant (OR 1.24, 95% CI 1.15–1.35, and P = 0.001; OR 1.08, 95% CI 1.05–1.12, and P = 0.001, respectively).


GDM accounts for one of the most frequent gestational complications, affecting 4–18% of all pregnancies worldwide, depending on the GDM criteria used [29]. In recent decades, the number of patients with GDM has increased significantly; the main factors for this rise are the increasing prevalence of overweight and obesity in both developed and developing countries [30, 31]. Likewise, some other risk factors for GDM include age, ethnic origin and a family history of T2D [32]. In this study, GDM patients were reported to be associated with older age, higher BMI and greater parental history of T2D, when compared to healthier pregnant women.

Additionally, evidence is accumulating that susceptibility to GDM has a genetic component [25, 33]. FTO has been reported to be associated with obesity, and recent studies have shown the association of some FTO SNPs with GDM, like rs8050136 or rs9939609 [23,24,25]; however, to our knowledge, no studies on rs1421085 have been previously reported. In the present study, we examined the association of these genetic variants in FTO gene in women with GDM.

We found no association between the FTO SNPs rs8050136 and rs9939609 with GDM, in accordance with Cho et al. and Fabrico et al. [34, 35]. However, our results differed from three studies that examined rs9939609, which demonstrated an association among the A-alleles and the risk for GDM [23,24,25]. We hypothesized that the A-alleles’ low frequency added to the small sample size of this study could be the major factors for the divergence of our results. It has been suggested that the effects of all three SNPs in the FTO gene may be apparent only in populations with higher minor allele frequency [36]. The frequencies of the rare A-alleles observed for the GDM group were lower than those reported for Europeans and Euro-Brazilians [23,24,25, 35]. On the other hand, these frequencies are similar to those reported for Korean women [34]. To date, most of the genetic association studies have been performed in white populations.

Several genetic variants of FTO have been related to body weight, hip and waist circumference and BMI in numerous populations of European origin [37,38,39]. Nevertheless, we did not find any association between the FTO SNPs and the pre-pregnancy anthropometric characteristics analyzed. Our results differed from those of Lawlor et al. and Gaillard et al. which demonstrated an association among the risk variants in rs9939609, and rs8050136 and pre-pregnancy weight and BMI [40, 41]. However, we observed that the risk allele C in SNP rs1421085 was associated with greater gestational weight gain in GDM group. Nevertheless, given the composite nature of gestational weight gain, further examination of this outcome might be undertaken by examining the association of this variant with maternal fat stores and fetal adiposity. It should be pointed out that this variant was identified recently as a causal variant in preadipocytes, where the risk allele affects the basic anabolic function of the adipocyte, shifting it from substrate storage to fuel dissipation through increased mitochondrial uncoupling [20].

The genetic variant rs9939609 evaluated in the present study has been involved in appetite ratings through regulation of circulating ghrelin and leptin [12, 13]. Our data did not show these associations; however, we measured total ghrelin, which includes both acylated and desacylated forms. Measuring the acylated form of this hormone, might have been an advantage if we consider that ghrelin is biologically active only in the acylated form [42]. Regarding leptin, the association of FTO polymorphisms with this adipokine appears to be mediated via increased adiposity, as in some studies the association disappears when correcting by BMI [43, 44]. In our study, we did not find an association of FTO polymorphisms with BMI.

In addition, considerable data support a role for adipocyte-derived cytokines, such as adiponectin, and TNF-alpha in the pathogenesis of GDM [45,46,47]. Therefore, we undertook to investigate the influence of FTO genetic variants on maternal adipokines. In the present study, no statistical differences were found at these hormone levels between GDM and controls. However, interestingly higher levels of pro-inflammatory TNF-alpha and lower levels of adiponectin were associated with the FTO rs8050136 and rs9939609 risk allele A in GDM group. Both associations remained significant after adjusting for age, maternal pre-gestational body weight and insulin therapy. Our results are mainly consistent with those of De Luis et al., who also observed that the minor A allele of the FTO rs9939609 was significantly associated with lower serum adiponectin concentrations independently of potential confounders including adiposity [14]. Regarding the association of the FTO SNPs with systemic inflammation, a German study has shown that rs9939609 A-allele was associated with increased levels of C-reactive protein (CRP) [15]. These findings were significant, independent of the adiposity level. However, a recent study by Zimmermann et al. in a population of Danish men representing a broad range of BMI did not find an independent association between the obesity associated FTO rs9939609 variant and systemic inflammation [43]. To our knowledge no previous studies have investigated the relationship between FTO SNPs and TNF-alpha, only one study to date has examined the association between FTO mRNA expression and expression of TNF-alpha in subcutaneous adipose tissue (SAT), and found that SAT FTO mRNA expression was related to SAT TNF-alpha expression, linking adipose tissue FTO expression and a proinflammatory molecule implicated in insulin resistance [48]. Several studies have suggested that increased levels of TNF-alpha may be related to the development of GDM independent of BMI [49]. TNF-alpha impairs insulin signalling by increasing serine phosphorylation of insulin receptor substrate (IRS)-1, and diminishing insulin receptor (IR) tyrosine kinase activity [50].

This study is subject to certain limitations, the first being the differences in age and weight between women with GDM and women with normal pregnancy. A control group consisting of age- and BMI-matched pregnant women without GDM might have been more suitable. Second, our study was underpowered to detect associations of FTO SNPs with GDM, probably because of their low frequencies. Finally, for adiposity, we only considered BMI, a surrogate for body fatness, and body fat percentage is a more accurate measurement.


The present study suggests that the FTP SNPs rs8050136, rs9939609, and rs1421085 are not a major genetic regulator in the etiology of GDM in the studied ethnic group. However, these SNPs were associated with serum adiponectin and TNF-alpha concentrations in GDM subjects. Additional larger studies are required to examine the association of FTO genetic variants in Mexican women.



gestational diabetes mellitus




fat mass and obesity associated


body mass index


tumor necrosis factor-alpha


odds ratio


Organisation for Economic Co-operation and Development


genome-wide association studies


deoxyribonucleic acid


polymerase chain reaction


homeostasis model assessment index


confidence intervals


analysis of covariance




linkage disequilibrium


type 2 diabetes


C-reactive protein


subcutaneous adipose tissue


insulin receptor substrate


insulin receptor


  1. 1.

    NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from, to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet. 1975;2016(387):1377–96.

  2. 2.

    OECD. Obesity among adults. In: Health at a Glance 2015: OECD Indicators. Paris: OECD Publishing. 2015. p. 74–75. doi:10.1787/health_glance-2015-19-en

  3. 3.

    Gutiérrez JP, Rivera-Dommarco J, Shamah-Levy T, et al. Encuesta Nacional de Salud y Nutrición 2012. Resultados Nacionales. México: Instituto Nacional de Salud Pública (MX), 2012.

  4. 4.

    Marchi J, Berg M, Dencker A, Olander EK, Begley C. Risks associated with obesity in pregnancy, for the mother and baby: a systematic review of reviews. Obes Rev. 2015;16:621–38.

  5. 5.

    Norman JE, Reynolds RM. The consequences of obesity and excess weight gain in pregnancy. Proc Nutr Soc. 2011;70:450–6.

  6. 6.

    Ma RC, Schmidt MI, Tam WH, McIntyre HD, Catalano PM. Clinical management of pregnancy in the obese mother: before conception, during pregnancy, and postpartum. Lancet Diabetes Endocrinol. 2016;4:1037–49.

  7. 7.

    Walley AJ, Asher JE, Froguel P. The genetic contribution to non-syndromic human obesity. Nat Rev Genet. 2009;10:431–42.

  8. 8.

    Rankinen T, Zuberi A, Chagnon YC, et al. The human obesity gene map: the 2005 update. Obesity. 2006;14:529–644.

  9. 9.

    El-Sayed Moustafa JS, Froguel P. From obesity genetics to the future of personalized obesity therapy. Nat Rev Endocrinol. 2013;9:402–13.

  10. 10.

    Frayling TM, Timpson NJ, Weedon MN, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007;316:889–94.

  11. 11.

    Scuteri A, Sanna S, Chen W, et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet. 2007;3:e115.

  12. 12.

    Karra E, O’Daly OG, Choudhury AI, et al. A link between FTO, ghrelin, and impaired brain food-cue responsivity. J Clin Invest. 2013;123:3539–51.

  13. 13.

    Labayen I, Ruiz JR, Ortega FB, et al. Association between the FTO rs9939609 polymorphism and leptin in European adolescents: a possible link with energy balance control. The HELENA study. Int J Obes. 2011;35:66–71.

  14. 14.

    De Luis DA, Aller R, Izaola O, Primo D, Romero E. Association of the rs9939609 gene variant in FTO with insulin resistance, cardiovascular risk factor and serum adipokine levels in obese patients. Nutr Hosp. 2016;33:573.

  15. 15.

    Fisher E, Schulze MB, Stefan N, et al. Association of the FTO rs9939609 single nucleotide polymorphism with C-reactive protein levels. Obesity. 2009;17:330–4.

  16. 16.

    Vozarova B, Weyer C, Lindsay RS, Pratley RE, Bogardus C, Tataranni PA. High white blood cell count is associated with a worsening of insulin sensitivity and predicts the development of type 2 diabetes. Diabetes. 2002;51:455–61.

  17. 17.

    Stratigopoulos G, LeDuc CA, Cremona ML, Chung WK, Leibel RL. Cut-like homeobox 1 (CUX1) regulates expression of the fat mass and obesity-associated and retinitis pigmentosa GTPase regulator-interacting protein-1-like (RPGRIP1L) genes and coordinates leptin receptor signaling. J Biol Chem. 2011;286:2155–70.

  18. 18.

    Stratigopoulos G, Carli JFM, O’Day DR, et al. Hypomorphism for RPGRIP1L, a ciliary gene vicinal to the FTO locus, causes increased adiposity in mice. Cell Metab. 2014;19:767–79.

  19. 19.

    Smemo S, Tena JJ, Kim KH, et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature. 2014;507:371–5.

  20. 20.

    Claussnitzer M, Dankel SN, Kim KH, et al. FTO obesity variant circuitry and adipocyte browning in humans. N Engl J Med. 2015;373:895–907.

  21. 21.

    Zeggini E, Weedon MN, Lindgren CM, et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–41.

  22. 22.

    Scott LJ, Mohlke KL, Bonnycastle LL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341–5.

  23. 23.

    Huopio H, Cederberg H, Vangipurapu J, et al. Association of risk variants for type 2 diabetes and hyperglycemia with gestational diabetes. Eur J Endocrinol. 2013;169:291–7.

  24. 24.

    Pagán A, Sabater-Molina M, Olza J, et al. A gene variant in the transcription factor 7-like 2 (TCF7L2) is associated with an increased risk of gestational diabetes mellitus. Eur J Obstet Gynecol Reprod Biol. 2014;180:77–82.

  25. 25.

    Lauenborg J, Grarup N, Damm P, et al. Common type 2 diabetes risk gene variants associate with gestational diabetes. J Clin Endocrinol Metab. 2009;94:145–50.

  26. 26.

    Saucedo R, Zarate A, Basurto L, et al. Relationship between circulating adipokines and insulin resistance during pregnancy and postpartum in women with gestational diabetes. Arch Med Res. 2011;42:318–23.

  27. 27.

    American Diabetes Association. Diagnosis and classification of diabetes mellitus (position statement). Diabetes Care. 2010;33(suppl 1):62e69.

  28. 28.

    Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.

  29. 29.

    Cundy T, Ackermann E, Ryan EA. Gestational diabetes: new criteria may triple the prevalence but effect on outcomes is unclear. BMJ. 2014;348:g1567.

  30. 30.

    Lavery JA, Friedman AM, Keyes KM, Wright JD, Ananth CV. Gestational diabetes in the United States: temporal changes in prevalence rates between 1979 and 2010. BJOG. 2017;124(5):804–13. doi:10.1111/1471-0528.14236.

  31. 31.

    Guariguata L, Linnenkamp U, Beagley J, Whiting DR, Cho NH. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract. 2014;103:176–85.

  32. 32.

    Cypryk K, Szymczak W, Czupryniak L, Sobczak M, Lewiński A. Gestational diabetes mellitus—an analysis of risk factors. Endokrynol Pol. 2008;59:393–7.

  33. 33.

    Lowe WL Jr, Scholtens DM, Sandler V, Hayes MG. Genetics of gestational diabetes mellitus and maternal metabolism. Curr Diab Rep. 2016;16:15.

  34. 34.

    Cho YM, Kim TH, Lim S, et al. Type 2 diabetes-associated genetic variants discovered in the recent genome-wide association studies are related to gestational diabetes mellitus in the Korean population. Diabetologia. 2009;52:253–61.

  35. 35.

    de Melo SF, Frigeri HR, dos Santos-Weiss IC, et al. Polymorphisms in FTO and TCF7L2 genes of Euro-Brazilian women with gestational diabetes. Clin Biochem. 2015;48:1064–7.

  36. 36.

    Li H, Wu Y, Loos RJ, et al. Variants in the fat mass- and obesity-associated (FTO) gene are not associated with obesity in a Chinese Han population. Diabetes. 2008;57:264–8.

  37. 37.

    Dina C, Meyre D, Gallina S, et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet. 2007;39:724–6.

  38. 38.

    Hinney A, Nguyen TT, Scherag A, et al. Genome Wide Association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants. PLoS ONE. 2007;2:e1361.

  39. 39.

    Loos RJ, Bouchard C. FTO: the first gene contributing to common forms of human obesity. Obes Rev. 2008;9:246–50.

  40. 40.

    Lawlor DA, Fraser A, Macdonald-Wallis C, et al. Maternal and offspring adiposity-related genetic variants and gestational weight gain. Am J Clin Nutr. 2011;94:149–55.

  41. 41.

    Gaillard R, Durmus B, Hofman A, Mackenbach JP, Steergers EA, Jaddoe VW. Risk factors and outcomes of maternal obesity and excessive weight gain during pregnancy. Obesity. 2013;21:1046–55.

  42. 42.

    Kojima M, Hosoda H, Date Y, Nakazato M, Matsuo H, Kangawa K. Ghrelin is a growth-hormone-releasing acylated peptide from stomach. Nature. 1999;402:656–60.

  43. 43.

    Zimmermann E, Skogstrand K, Hougaard DM, et al. Influences of the common FTO rs9939609 variant on inflammatory markers throughout a broad range of body mass index. PLoS ONE. 2011;6:e15958.

  44. 44.

    Qi L, Kang K, Zhang C, et al. Fat mass-and obesity-associated (FTO) gene variant is associated with obesity: longitudinal analyses in two cohort studies and functional test. Diabetes. 2008;57:3145–51.

  45. 45.

    Retnakaran R, Hanley AJ, Raif N, Connelly PW, Sermer M, Zinman B. Reduced adiponectin concentration in women with gestational diabetes. Diabetes Care. 2004;27:799–800.

  46. 46.

    Gao XL, Yang HX, Zhao Y. Variations of tumor necrosis factor-alpha, leptin and adiponectin in mid-trimester of gestational diabetes mellitus. Chin Med J. 2008;121:701–5.

  47. 47.

    Kirwan JP, Hauguel-De Mouzon S, Lepercq J, et al. TNF-alpha is a predictor of insulin resistance in human pregnancy. Diabetes. 2002;51:2207–13.

  48. 48.

    Samaras K, Botelho NK, Chisholm DJ, Lord RV. Subcutaneous and visceral adipose tissue FTO gene expression and adiposity, insulin action, glucose metabolism, and inflammatory adipokines in type 2 diabetes mellitus and in health. Obes Surg. 2010;20:108–13.

  49. 49.

    Xu J, Zhao YH, Chen YP, et al. Maternal circulating concentrations of tumor necrosis factor-α, leptin, and adiponectin in gestational diabetes mellitus: a systematic review and meta-analysis. Sci World J. 2014;2014:926932.

  50. 50.

    Barbour LA, McCurdy CE, Hernandez TL, Kirwan JP, Catalano PM, Friedman JE. Cellular mechanisms for insulin resistance in normal pregnancy and gestational diabetes. Diabetes Care. 2007;30(Suppl 2):S112–9.

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Authors’ contributions

RS designed the study, analyzed and interpreted the data, and obtained the funding. JV and CG analyzed and interpreted the patient data. LB and MH were major contributors in writing the manuscript. EP, GR, GV and AZ did a critical revision of the manuscript. All authors read and approved the final manuscript.


RS, GR, LB, MH, and AZ hold a fellowship from the National System of Investigators. We thank the Hospital of Gynecology and Obstetrics, Medical Center La Raza, Mexican Social Security Institute, for providing patient care services.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

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

Ethics approval and consent to participate

The protocol was approved by our institutional review board (R-2007-3504-12), and informed consent was obtained from all participants.


This work was supported by scientific grants from IMSS (FIS/IMSS/PROT/MD15/1495) and CONACYT (2007-01-69232). They did not take part in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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Saucedo, R., Valencia, J., Gutierrez, C. et al. Gene variants in the FTO gene are associated with adiponectin and TNF-alpha levels in gestational diabetes mellitus. Diabetol Metab Syndr 9, 32 (2017) doi:10.1186/s13098-017-0234-0

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  • Adipokines
  • FTO
  • Gestational diabetes
  • Obesity
  • Single nucleotide polymorphism