Analysis of the Associations of the rs12504538 and rs6824447 Polymorphisms of the Elovl6 Gene with Estimated Elongase and Desaturase Activity in Gestational Diabetes Mellitus Patients

Analysis of the Associations of the rs12504538 and rs6824447 Polymorphisms of the Elovl6 Gene with Estimated Elongase and Desaturase Activity in Gestational Diabetes Mellitus Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of the Associations of the rs12504538 and rs6824447 Polymorphisms of the Elovl6 Gene with Estimated Elongase and Desaturase Activity in Gestational Diabetes Mellitus Patients Manuel A. Muñoz-Nava, Martha E. Fajardo Araujo, Elva Perez-Luque, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4578221/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. This study aimed to investigate the possible associations of the rs12504538 and rs6824447 polymorphisms of the Elovl6 gene with estimated elongase and desaturase activity and saturated fatty acid concentrations in Mexican women with gestational diabetes mellitus (GDM). Methods . We recruited 172 women in the second and third trimesters of pregnancy who had undergone an oral glucose tolerance test, including 66 who had diagnosed with GDM according to the 2016 ADA criteria and 106 who had normal glucose tolerance test results, from the General Hospital and Health Centers of the Health Ministry of Guanajuato, México. Participants were matched by gestational week. Data on age, gestational week, and anthropometric characteristics were collected. Blood samples were drawn after an overnight fast for the measurement of serum glucose, lipid, NEFA, serum fatty acid, and insulin levels; SNP genotyping and quantification of fatty acids was performed, and elongase and desaturase activity was estimated. Results. With the exception of HDL-cholesterol, all variables, including NEFA levels, were significantly greater in the GDM group than in the non-GDM group. The rs6824447 polymorphism of the Elovl6 gene, an a ge > 25 years, and HOMA-IR levels were associated with the development of GDM (OR = 5.1, 95% CI 1.56–17.1, p = 0.006; OR = 4.89, 95% CI 1.65–14.4, p = 0.003; OR = 34.1 95% CI 8.7–133, p < 0.000001, respectively). Palmitic acid (OR = 1.08; 95% CI: 1.06–1.11; p < 0.001) and oleic acid (OR = 1.17; 95% CI: 1.14–1.2; p < 0.001) concentrations were also associated with the development of GDM. No differences in the estimated elongase and desaturase activity among the non-GDM and GDM groups were found, and only the activity of Δ9D SCD18 desaturase was marginally high in GDM patients (p = 0.050). Conclusion. The rs6824447 Elovl6 polymorphism is associated with the development of GDM, as are high serum palmitic acid, oleic acid, and stearic acid concentrations and estimated Δ9D SCD18 desaturase activity. gestational diabetes mellitus rs6824447 Elovl6 rs12504538 Elovl6 fatty acids elongase activity desaturase activity Introduction Gestational diabetes mellitus (GDM) is a pregnancy complication in which hyperglycemia spontaneously develops during pregnancy [ 1 ]. The rising obesity epidemic has driven an increase in the incidence of gestational diabetes mellitus, as well as in pregnancy complications in terms of maternal and perinatal outcomes. These factors include known nonmodifiable risk factors for a predisposition to GDM, such as advanced maternal age, the presence of overweight and obesity, ethnicity, and a family history of type 2 diabetes mellitus (T2DM) [ 2 , 3 ]. According to the most recent (2021) International Diabetes Federation (IDF) estimates, 21.1 million (16.7%) women who give birth to live-born infants have some form of hyperglycemia during pregnancy, 80.3% of whom have GDM [ 4 ]. The majority of women with GDM appear to have β cell dysfunction with a background of chronic insulin resistance, to which the normal insulin resistance in pregnancy is partially additive [ 5 ]. The metabolism of the toxic intracellular metabolites triacylglycerol (TAG) and nonesterified fatty acids (NEFAs) has been reported to cause severe insulin resistance [ 6 – 8 ]. Recently, a significant increase in NEFA and TAG levels in GDM patients compared with healthy pregnant women has been reported [ 9 ]. The enzymes required for the synthesis of fatty acids (FAs) are regulated by sterol-regulatory element binding protein (SREBP-1) [ 10 ]. Overexpression of the SREBP-1a or SREBP-1c isoforms in the livers of mice results in increased rates of novo fatty acid synthesis and TAG accumulation [ 11 , 12 ]. Elovl6 is an endoplasmic reticulum enzyme highly induced in the livers of SREBP transgenic mice [ 13 ] that is expressed in lipogenic tissues and regulated by SREBP-1 [ 14 ]. Elovl6 catalyzes the chain elongation of C12 to C16 saturated and monounsaturated FAs to form C18, such as stearic (C18:0), oleic (C18:1n9), and vaccenic (C18:1n7) acids, the most important step for the de novo synthesis of endogenous long-chain FAs [ 15 ]. Elovl6 gene disruption (E6KO) in mice decreases the proportion of stearic (C18:0) and oleic (C18:1n-9) acids and increases that of palmitic (C16:0) and palmitoleic (C16:1n-7) acids in the liver, confirming that Elovl6 catalyzes the chain elongation of palmitic to stearic acids and the elongation of palmitoleic to vaccenic acids [ 15 , 16 ]. In addition, E6KO mice are resistant to obesity-induced insulin resistance, despite being similar to wild-type mice in terms of hepatosteatosis and obesity [ 15 ], suggesting that Elovl6 inhibition could be a potential therapeutic approach for T2DM treatment since Elovl6 deficiency prevents T2DM progression by increasing the insulin secretory capacity of pancreatic β-cells in db/db mice [ 15 , 17 ] and significantly improves hyperglycemia and elevates HbA1c levels [ 18 ]. It has been reported that the regulation of FA structure may participate in the modulatory effects of FAs on β-cells [ 19 ]). Subpopulations of MIN-6 and rat β-cells were shown to be resistant to palmitate-induced apoptosis and associated with increased expression of stearoyl-CoA desaturase (SCD1) and increased conversion of palmitate to monounsaturated fatty acids (MUFAs) [ 20 ]. In addition, T2DM is associated with diminished islet expression of SCD1, which can disrupt the desaturation of saturated FAs to MUFAs, rendering β-cells more susceptible to saturated FA-induced ER stress and apoptosis [ 19 ]. Several studies have shown that genetic variations (SNPs) in the Elovl6 gene are associated with the risk of T2DM and insulin resistance [ 21 – 23 ]. The rs6824447GG genotype was associated with lower insulin levels in a population from southern Spain [ 21 ]. Another study showed that the rs12504538 polymorphism is associated with an increase in insulin resistance and an increased risk of T2DM in the Han Chinese population [ 22 ]. In the Mexican population from Queretaro, the rs6824447 polymorphism was associated with lower total cholesterol and LDL cholesterol levels [ 23 ]. To date, there are few studies on polymorphisms of the Elovl6 gene and their associations with insulin resistance and GDM. Therefore, the aim of this study was to investigate the possible associations of the rs12504538 and rs6824447 polymorphisms of the Elovl6 gene with elongase and desaturase activity and fatty acid concentrations in Mexican women with gestational diabetes mellitus. Methods Patients We conducted an observational transverse study of 172 women in the second and third trimesters of pregnancy, including 66 women who had been diagnosed with GDM according to the 2016 criteria of the American Diabetes Association (GDM group), and 106 women with a normal glucose tolerance test result, matched by gestational week, from the General Hospital and health centers from Health Ministry number VII (in Leon Guanajuato, Mexico. Ethical Statement We fully informed all participants of the aims of this study, and we asked them for signed informed consent to participate in this study and their publication. This study was carried out according to the ethical standards of the Declaration of Helsinki (2013) and in agreement with the Good Clinical Practice guidelines. This study was approved by the Investigation Committee of General Hospital and health centers from Health Ministry number VII in Leon, (Approval # GTSSA002101), (Approval # JS7-04-230615). and by the Institutional Ethics Committee of the University of Guanajuato (Approval # CIBIUG-P-20-2015), León Guanajuato, México The participants were recruited during the second and third trimesters of pregnancy after undergoing an oral glucose tolerance test (OGTT). According to the results of the OGTT, we formed two groups: the non-gestational diabetes mellitus (Non-GDM) group and the gestational diabetes mellitus (GDM) group. Data on age, obstetric history, gestational week, height, prepregnancy weight and actual weight were collected. Body mass index (BMI) was calculated by dividing weight (kg) by height squared (m 2 ) (kg/m 2 ). Blood samples were drawn after an overnight fast for the measurement of serum glucose, lipid, NEFA, fatty acid and insulin levels and DNA extraction. Serum glucose and lipid levels were measured using enzymatic methods with a semiautomatic chemical analyzer (SPINLAB SPINREACT). Serum insulin was measured by an immunoenzymatic assay (GeneWay Biotech Inc., San Diego, CA, USA), and NEFAs were measured by an enzymatic colorimetric method (Wako Life Sciences Inc., Mountain View, CA, USA). The intra-assay variation coefficients were 3.4 to 6.1% for insulin and 1.6% to 2.2% for NEFAs. The quantification of fatty acids was performed by gas chromatography. Genotyping of Elovl6 polymorphisms DNA was extracted from peripheral blood leucocytes according to the TSNT protocol, quantified using a NanoDrop system (Roche), and stored at -20 °C. Single nucleotide polymorphisms (SNPs) were detected by a combination of polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) assays using appropriate restriction enzymes as described previously [22]. Polymerase chain reaction (PCR) was carried out in a total volume of 30 μL in a Thermal Cycler GeneAmp PCR System 2700 (Applied Biosystems). The PCR mixture contained 50 ng of DNA, 0.5 mM of dNTPs (Invitrogen), 10 pM of primers, 2.0 mM of MgCl 2 , 0.6 μL of DMSO, and 5 U of Taq polymerase (Invitrogen) for both polymorphisms. Amplification of the rs12504538 polymorphism was carried out using the following protocol: 95 °C for 5 min; 20 cycles of 95 °C for 30 s; 68 °C for 45 s; 72 °C for 45 s; and 72 °C for 1 min. The annealing temperature decreased by 0.5 °C/cycle. This was followed by 20 cycles of 95 °C for 30 s, 60 °C for 30 s, and 72 °C for 40 s, with a final single extension step of 72 °C for 6 min. rs6824447 polymorphism amplification was carried out using the following protocol: 95 °C for 5 min; 35 cycles of 95 °C for 30 s, 56 °C for 45 s, and 72 °C for 1 min; and 72 °C for 1 min. The PCR product for the rs12504538 polymorphism was a fragment of 295 bp that, after digestion with the restriction enzyme Pag I, an isoschizomer of Rca I (Thermo Scientific, Waltham, MA, USA), yielded 186 and 109 bp products for the C/C genotype and 295, 186, and 109 bp products for the C/T genotype, while the enzyme did not cut the normal T/T genotype sequence. For the rs6824447 polymorphism, PCR generated a product of 133-pb, which, after digestion with Ban II (New England BioLabs, Ipswich, MA, USA), yielded 85- and 48-bp fragments for the G/G genotype and 133, 85 and 48-pb fragments for the A/G genotype, while the PCR products with the normal A/A genotype were not digested. Both fragments were separated by electrophoresis on a 3% ethidium bromide-stained agarose gel [22]. Measurement of serum fatty acids. Serum samples (500 μl) were dried under a gentle stream of nitrogen at room temperature, and the residues were dissolved in 1 ml of NaOH and 0.5 M methanol. An internal standard consisting of 10 μl of nonadecanoic acid (C19:0, 5 mg/ml) was added. The temperature of the solution was held at 90 °C for 1 h; each sample was then cooled to room temperature, and 1 ml of boron trifluorideetherate in methanol (Sigma‒Aldrich) was slowly added. The samples were reincubated at 90 °C for 30 minutes. The solutions were cooled and transferred to a test tube, where 2 ml of deionized water and 4 ml of hexane were added, after which the organic phase was separated. Each solution was dried again under a stream of nitrogen at room temperature and dissolved in 400 μl of isooctane (Fisher Chemical). After that, an aliquot was injected into the chromatograph. Fatty acids were chromatographed on a 30 m fused-silica Zebron ZB-WAX column (0.25 mm i.d.). Analysis was performed with an Agilent Technologies 7890A gas chromatograph equipped with an Agilent Technologies 5975C flame ionization detector. The column temperature was held at 50 °C for 3 min, subsequently increased in a stepwise fashion (10 °C/min) to a plateau of 250 °C, and then held for 3 min. The injection temperature was 220 °C. Helium was used as the carrier gas at 2 ml/min. The quantification was performed for 67 women without GDM and 64 women with GDM. Statistical analysis The Kolmogorov‒Smirnov test was used to assess the normality of the data. The anthropometric and metabolic data are expressed as the mean ± SD or median (25-75 quartiles). Differences between groups were examined using the independent t test, Mann‒Whitney U test or one-way ANOVA and the Kruskal‒Wallis test. Both groups were tested for Hardy‒Weinberg equilibrium for the rs12504538 and rs6824447 Elvol6 polymorphisms. We compared allelic frequency between groups using Yates-corrected χ 2 tests. The association between the polymorphisms and the development of GDM was assessed with logistic regression analysis adjusted for age and IMC using the dominant model. Analyses were performed using a statistical package (Statistica, StatSoft Inc., Tulsa, OK). The level of statistical significance was defined as P < 0.05. Results We included a total of 172 pregnant women, including 66 with GDM and 106 with a normal glucose tolerance test result (non-GDM), with a median gestational week of 27 (25–30) weeks. The clinical and metabolic characteristics of both groups are shown in Table 1. The groups were similar in terms of gestational week, weight gain, total cholesterol levels, triglyceride levels, and LDL cholesterol levels. With the exception of HDL cholesterol levels, all variables, including NEFA levels, were significantly greater in the GDM group. Table 2 summarizes the distributions of the rs6824447 and rs12504538 Elovl6 genotypes and alleles between GDM patients and controls. The genotypic frequencies and allelic frequencies of rs12504538 Elovl6 were similar between the groups (χ 2 = 0.35, p = 0.84; χ 2 = 0.94; p = 0.75, respectively). However, the allelic frequencies of the rs6824447 Elovl6 polymorphism were significantly different between the groups (χ 2 = 4.87, p=0.02). The GG genotype frequency was significantly greater in the GDM group (χ 2 = 6.16, p = 0.04) than in the non-GDM group. The rs12504538 SNP was in accordance with the Hardy‒Weinberg equilibrium, and the rs6824447 SNP showed slight deviation in the GDM group. In the comparison of the rs6824447 Elovl6 genotype, we detected significantly lower levels of HDL cholesterol but significantly higher levels of triglycerides, palmitic acid (C18:0), stearic acid (C18:0), oleic acid (C18:1w9), and eicosenoic acid (C20:1w9) in GDM patients with one or two allelic variants (AG or GG) (Table 3). No differences in the comparison of other variables for genotypes were found. In the comparison of metabolic variables for the rs125504538 Elovl6 genotype, there were no significant differences. Estimation of elongase and desaturase activity and comparison between groups. In women with GDM, the palmitic acid, stearic acid, oleic acid, and eicosenoic acid concentrations were significantly greater than those in women without GDM (Table 4). The estimated elongase activities of Elovl3 (C20:1/C18:2), Elovl6 (C18/C16), and Elovl5 (C20:2/C18:2) and the estimated desaturase activities of D5D (C20:4/C20:3), D6D (C18:3/C18:2), D9D SCD16 (C16:1/C16:0), and D9D SCD18 (C18:1/C18:0) were compared between the GDM and non-GDM groups. No differences between the non-GDM and GDM groups were found, and only the activity of desaturase D9D SCD18 was marginally elevated in the GDM group (Table 4). Logistic regression analysis of associations According to the univariate logistic regression analysis, age, prepregnancy BMI ≥30 kg/m 2 , NEFA levels, serum insulin level, HOMA-IR value, rs6824447 Elovl6 polymorphism, palmitic acid, oleic acid, and eicosenic acid levels and the activity of desaturase D9D SCD18 were significantly associated with gestational diabetes mellitus. Notably, the serum HDL cholesterol concentration had a strong protective effect (Table 5). Multiple logistic regression analysis adjusted for age, including previous variables, showed that age, HOMA-IR levels and the rs6824447 polymorphism remained significantly associated with GDM (Table 5). Discussion In this study, we analyzed the metabolic phenotypes of women with GDM and healthy pregnant women and the associations of the rs12504538 and rs6824447 Elovl6 polymorphisms with GDM and insulin resistance. Additionally, the serum fatty acid concentration and estimated elongase and desaturase activities were evaluated in both groups. We found that the prepregnancy BMI and triglyceride, NEFA, insulin, and insulin resistance levels were significantly greater and that the HDL cholesterol concentration was lower in women with GDM. Similar results have been reported in other studies [9, 24]. Compared with normoglycemic controls, women with GDM were at increased risk of developing T2DM, had abnormalities in insulin secretion [25] and lipid metabolism and had elevated NEFA levels [26]. The rs12504538 Elvol6 polymorphism has been associated with an increased risk of T2DM because of increased insulin resistance, but no association between the rs6824447 polymorphism and the development of T2DM has been reported in the Han Chinese population [22]. Instead, we found a significant association between the rs6824447 Elovl6 polymorphism and the development of GDM but no association between the rs12504538 polymorphism and the development of T2DM. In nondiabetic subjects in the Spanish population, the rs6824447 polymorphism is associated with a low risk of having high HOMA-IR values [21]. In young subjects from Mexican populations with a normal BMI, rs6824447 has been shown to have a protective effect against high cholesterol and high LDL cholesterol levels. Interestingly, our results revealed that triglyceride levels were greater and that HDL cholesterol levels were lower in GDM patients who were carriers of the rs6824447AG and s6824447GG genotypes. There are very few reports on the association of Elovl6 polymorphisms with T2DM, and there are few reports on the association of Elovl6 polymorphisms with GDM. To the best of our knowledge, this is the first report of the contribution of the rs6824447 polymorphism to the development of GDM. In addition, multiple logistic regression showed that age, insulin levels and the rs6824447 polymorphism are factors associated with the risk of GDM. In our work, no differences in estimated Elovl3, Elovl5, or Elovl6 activity were found between women without GDM and women with GDM. There are few studies concerning estimated Elovl6 activity; in children aged 9-12 years, Elovl6 activity is a significant predictor of insulin resistance (IR) [27]. High Elovl6 activity was associated with high IR in Japanese subjects, low activity might be ideal for protection against atherosclerosis, and in nonalcoholic steatohepatitis hepatic (NASH) was proposed [28]. A previous study reported that the palmitic acid, myristic acid, and oleic acid concentrations were significantly increased in GDM patients [29]. In our study, we found that serum palmitic acid, oleic acid, and eicosenoic acid concentrations were significantly associated with the risk of GDM. Several reports have reported similar results [30-32]. An inverse association between C18:2n-6 and GDM has also been reported [32]. Another study showed that the activity of the Δ5D and Δ6D desaturases changed during pregnancy, the estimated Δ6D desaturase activity was elevated, and the Δ5D desaturase activity was attenuated in the first trimester; however, changes were not detected during the second trimester. However, in the third trimester, Δ5D and Δ9D SCD-18 desaturase activities were elevated, and Δ6D desaturase activity was attenuated [33]. In our study, a similar tendency in Δ9D SCD-18 activity (significantly marginal) was found in women with GDM in the third trimester of pregnancy. It has also been reported that increased activation of Δ9D SCD-18, which converts stearic acid (C18:0) to oleic acid (C18:1), is associated with the development of GDM in the third trimester [33]. Controversial results have been reported, while Δ5D desaturase activity was significantly lower and Δ9D SCD-18 desaturase activity was significantly greater during pregnancy [34]. In another study, Δ6D desaturase and Δ9D SCD-18 desaturase activities were significantly lower, but there were no significant changes in Δ5D desaturase activity in women with GDM at 32-35 weeks of gestation [35]. In our study, no differences in Δ5D or Δ6D desaturase activity were found; these results may be due to differences in sample size. Higher serum total n–6 polyunsaturated fatty acid (PUFA), linoleic acid, and arachidonic acid concentrations and estimated Δ5D activity were associated with a lower risk of incident T2DM, and participants with higher γ-linolenic acid and dihomoγ-linolenic acid concentrations and estimated Δ6D activity had a greater risk of T2D [36]. In our study, we did not find significant differences in estimated elongase activity between the non-GDM and GDM groups. However, it has been reported that estimated Elovl6 and Δ5D activities might be useful markers of insulin resistance in Japanese subjects [28]. The elongation of C16 to C18 is mediated by Elovl6 activity and is an important metabolic control point for the conversion of palmitic acid to stearic acid, and for the action of Δ9D SCD-18, it is converted to oleic acid. Both fatty acids influence the decrease in insulin secretion and β-cell function and eventually lead to diabetes development. Stearic acid (C18:0) also increased inflammation and the terminal UPR [18]. In our study, although the estimated Elovl6 activity did not increase significantly in the GDM group, the conversion of palmitic acid to stearic acid suggested major Elovl6 activity, and the conversion of stearic acid to oleic acid also suggested major activity of Δ9D SCD-18 in the second and third trimesters of pregnancy. Our results are interesting but require additional confirmation given the sample size, particularly in the GDM group. Conclusions In our work, metabolic and hormonal parameters, including NEFA levels, were increased in GDM patients. Age, insulin levels and the rs6824447 Elovl6 polymorphism are significantly associated with the development of GDM. Triglyceride levels were greater, and HDL cholesterol levels were lower in GDM patients who were carriers of the rs6824447AG and rs6824447GG genotypes. Palmitic acid, oleic acid, eicosenoic acid and Δ9D SCD-18 desaturase were significantly associated with the risk of GDM. Other estimated Δ5D and Δ6D desaturase and elongase activities were similar between the groups. Declarations This work was supported by the Funding Integration of Thematic Networks of Academic Collaboration 2015 for Dr. Martha Eugenia Fajardo Araujo from the Secretary of Education Public in Mexico. Acknowledgments. The authors would like to thank the doctors and nurses of the Hospital General Regional de Leon and Health Ministry number VII, especially Dr. Luis M. Muñoz-Guevara, for their trust in allowing their staff to help recruit patients. Competing Interests The authors have no competing interests that are relevant to the content of this article to declare. Author contributions: Manuel A. Muñoz-Nava, conceptualization, investigation and methods; Martha E. Fajardo-Araujo conceptualization, investigation, methods, and project administration; Elva Perez-Luque, Data curation, formal analysis, writing original draft; Mónica I. Cardona Alvarado, Data curation, formal analysis; Enrique Ramírez-Chávez, methods; Jorge Molina-Torres, methods. Funding: Integration of the thematic networks of academic collaboration. Secretary of Education Public in Mexico 2015. Acknowledgments. The authors would like to thank the doctors and nurses of the Hospital General Regional de Leon and Health Ministry number VII. References American Diabetes Association. Classification and Diagnosis of Diabetes (2021): Standards of Medical Care in Diabetes. Diabetes Care 44 (Suppl 1):S15–S33. https://doi.org/10.2337/dc21-S002 Plows JF, Stanley JL, Baker PN, Reynolds CM, and Vickers MH (2018) The Pathophysiology of Gestational Diabetes Mellitus. 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Moriyama K, Masuda Y, Suzuki N, Yamada Ch, Lishimoto N, Takashimizu S, et al (2022) Estimated Elvol6 and delta-5 desaturase activities might represent potential markers for insulin resistance in Japanese adults. J of Diabetes & Metab Dis 21:197-207. Doi.org/10.1007/s40200-021-00958-1. Raczkowska BA, Mojsak P, Rojo D, Telejko B, Pazkowska-Abdulsalam M, Hryniewicka J, et al (2021) Gas chromatography-mass spectroscopy- based metabolomics analysis reveal potential biochemical markers for diagnosis of gestational diabetes mellitus. Frontiers in Pharmacology doi: 10.3389/fphar.2021.770240. Sun Z, Deng Z, Wei X, Wang N, Yang J, Li W, et al (2022) Circulating saturated acids and risk of gestational diabetes mellitus: A cross-sectional study and meta-analysis. Frontiers in nutr doi 10.3389/fnut.2022.903689. Wang H, Yang W, Liu J, Leng J, Li W, Yu Z, et al (2021) Serum concentrations of SFAs and CDKAL1 single-nucleotide polymorphism rs7747752 are related to an increased risk of gestational diabetes mellitus. Am J Clin Nutr 114:1698-1707. Pan X-F, Huang Y, Li X, Wang Y, Ye Y, Chen H, et al (2021) Circulating fatty acids and the risk of gestational diabetes mellitus: prospective analyses in China. Eur J of Endocrinol 185:87-97. doi.org/10.1530/EJE-21-0118. Liu Y, Xia Y-Y, Zhang T, Yang Y, Cannon RD, Mansell T, et al (2022) Complex interactions between circulating fatty acids levels, desaturase activities, and the risk of gestational diabetes mellitus: A prospective cohort study. Frontiers in Nutr doi: 10.3389/fnut.2022.919357. Burlina S, Dalfra MG, Barison A, Martin R, Ragazzi E, Sartore G, et al (2017) Plasma phospholipid fatty acid composition and desaturase activity in women with gestational diabetes mellitus before and after delivery. Acta Diabetol 54:45-51. Doi: 10.1007/s00592-016-0901-x. Zhao JP, Levy E, Shatenstein B, Fraser WD, Julien P, Montoudis A, et al (2015) Longitudinal circulating concentrations of long-chain polyunsaturated fatty acids in the third trimester of pregnancy in gestational diabetes. Diabetic Med Doi: 10.1111/dme.12978. Yary T, Voutilainen S, Tuomainen T-P, Ruusunen A, Nurmi T, Virtanen JK (2016) Serum n–6 polyunsaturated fatty acids, D5- and D6-desaturase activities, and risk of incident type 2 diabetes in men: The Kuopio Ischaemic Heart Disease Risk Factor Study. Am J Clin Nutr 103:1337-1343. Tables Table 1. Clinical and metabolic characteristics of the two groups of pregnant women Non-GDM N = 106 GDM N = 66 t /z p Age (years) 23 (20-29) 30 (25-34) -5.0 0.000001 Gestational (weeks) 27 (25-30) 28 (25-31) -1.1 0.3 Height (cm) 155 (152-160) 155 (153-159) -0.4 0.7 Prepregnancy BMI (kg/m 2 ) 26.5 ± 5.5 30.0 ± 6.0 -3.9 0.0001 BMI at sample collection (kg/m 2 ) 28.8 ± 5.3 32.5 ± 5.8 -4.2 0.00004 Weight gain (kg) 5 (3.5-9) 5 (2-9) 0.3 0.7 Glucose (mmol/L) 4.4 ± 0.4 5.3 ± 0.9 -7.9 0.000001 Triglycerides (mmol/L) 2.30 (1.83-2.8) 2.61 (2.03-3.41) -2.2 0.02 Cholesterol (mmol/L) 5.56 (4.8–6.49) 5.74 (4.62–6.46) 0.1 0.9 HDL cholesterol (mmol/L) 1.83 (1.68–1.91) 1.57 (1.37–1.81) 5.8 0.000001 LDL cholesterol (mmol/L) 2.76 ± 1.08 2.84 ± 1.03 -0.4 0.7 NEFAs (mmol/L) 0.40 (0.34-0.45) 0.43 (0.35-0.52) -2.2 0.03 Insulin (μUI/mL) 19 (16-22) 23 (18-34) -3.3 0.0009 HOMA-IR 3.6 (3-4) 5.3 (4-8) 5.7 0.000001 The values are expressed as the mean ± SD or median and interquartile range; t = Student’s t test ; z = Mann–Whitney U test. GDM = gestational diabetes mellitus; NGDM = nongestational diabetes mellitus; BMI = body mass index; LDL-cholesterol = lipoprotein density low; HDL cholesterol = high-density lipoprotein NEFAS = nonesterified fatty acid; HOMA-IR = homeostasis model assessment. Table 2. Genotype and allelic frequencies of rs12504538 and rs6824447 SNP n Genotype frequency [n (%)] Allele frequency [n (%)] rs12504538 (T/C) TT TC CC T C Non-GDM 106 57 (0.54) 46 (0.43) 3 (0.03) (0.75) 48 (0.25) GDM 66 35 (0.53) 28 (0.42) 3 (0.05) (0.74) 31 (0.26) χ 2 = 0.35 p = 0.84 χ 2 = 0.94 p = 0.75 rs6824447 (A/G) AA AG GG A G Non-GDM 106 35 (0.33) 57 (0.54) 14 (0.13) 92 (0.60) 71 (0.40) GDM 66 11 (0.17) 41 (0.62) 14 (0.21) 52 (0.48) 55 (0.52) χ 2 = 6.16 p = 0.04 χ 2 = 4.87 p = 0.02 GDM = Gestational diabetes mellitus. Table 3. Analysis by genotypes of polymorphism rs6824447 (dominant model) between the groups Variable NGDM AA N = 35 GDM AA N = 11 p NGDM AG + GG N = 71 GDM AG + GG N = 55 *p **p Age (years) 25 (20-29) 30 (24-33) 0.07 23 (20-29) 31(25-34) 0.0006 0.00001 Prepregnancy Weight 64.4 ± 13.8 78 ± 17.1 0.01 64.5±13.9 72.3±15.5 0.003 0.001 Prepregnancy BMI (kg/m 2 )** 25.1 ± 5.3 30.4 ± 6.7 0.01 25.1±5.6 28.5±5.9 0.004 0.002 Weight at sample collection 71.2 ± 14.8 84.4 ± 14.6 0.01 69.7±13.2 78.4±15.2 0.0009 0.0005 BMI (kg/m 2 ) at sample collection 27.8 ± 5.7 32.9 ± 5.1 0.01 27.2 ±5.1 30.6 ±5.7 0.006 0.0005 Weight gain (kg) 6 (4-9) 4 (1–12) NS 5 (4–9) 6 (2–9) NS NS Glucose (mmol/L) 4.38 (4.14–4.77) 5.38 (5.27–6.16) 0.00004 4.38 (4.0–4.6) 5.21 (4.6–5.99) <0.00001 0.00001 Triglycerides ( mmol/L ) 2.41 (1.93–2.98) 2.15 (2.01–2.93) NS 2.21 (1.81–2.73) 2.77 (2.14–3.5) 0.007 0.06 Total Cholesterol (mmol/L) 5.35 (5.0–4.37) 6.38 (4.37–6.82) NS 5.55 (4.86–6.49) 5.58 (4.62-6.36) NS NS HDL cholesterol ( mmol/L ) 1.83 (1.65–1.91) 1.65 (1.52–1.91) NS 1.83 (1.73–1.91) 1.49 (1.31–1.78) <0.00001 0.00001 LDL cholesterol (mmol/L 2.84 ± 1.21 2.76 ± 1.03 NS 2.74 ± 1.03 2.81 ± 1.0 NS NS NEFAS (mmol/L) 0.39 (0.36-0.47) 0.44 (0.38-0.49) NS 0.40 (0.31-0.44) 0.43 (0.34-0.53) 0.04 NS Insulin (μUI/mL) 19 (16-22) 24 (20-38) 0.05 19 (16-23) 23 (18-34) 0.007 0.01 HOMA-IR 3.7 (3.1-4.5) 5.5 (4.6–10.3) 0.006 3.5 (2.9-4.5) 5.3 (4.1-7.3) 0.000001 0.00001 *Student’s t test: *MWT = Mann–Whitney test; **One-way ANOVA; KWT = Kruskal–Wallis test. The values are expressed as the means ± SDs or medians and interquartile ranges. GDM = gestational diabetes mellitus; NGDM = nongestational diabetes mellitus; BMI = body mass index; LDL cholesterol = lipoprotein density low cholesterol; HDL cholesterol = high-density lipoprotein cholesterol ; NEFAS = nonesterified fatty acid; HOMA-IR = homeostasis model assessment. Table 4. Comparison of fatty acid levels and elongase and desaturase activity between the groups Non-GDM (n = 67) GDM (n = 64) Variable Mean ± SD Mean t student p Myristic acid (C14:0) µg/mL 15.1 ± 8.23 16.3 ± 9.3 0.768 NS Palmitic acid (C16:0) µg/mL 857.4 ± 225 990 ± 321 2.75 0.006 Palmitoleic acid (C16:1) µg/mL 48.8 ± 21.3 54 ± 25 1.26 NS Stearic acid (C18:0) µg/mL 122.3 ± 21.3 135.3 ± 32.6 2.70 0.007 Oleic acid (C18:1 w9) µg/mL 746.3 ± 194 888 ± 297 3.245 0.001 Elaidic acid (C18:1) µg/mL 58.6 ± 11.7 63.6 ± 18.2 1.85 0.06 Linoleic acid (C18:2 w6) µg/mL 1064.2 ± 271.3 1134 ± 295 1.40 NS Alpha-Linolenic acid (C18:3 w3) µg/mL 21.7 ± 7.9 23.5 ± 8.8 1.23 NS Eicosenoic acid (C20:1 w9) µg/mL 7.4 ± 4.2 8.7 ± 2.8 2.10 0.036 Δ9D SCD 16 0.057 ± 0.014 0.053 ± 0.012 1.087 NS Δ9D SCD 18 6.1 ± 1.2 6.5 ± 1.4 -1.937 0.05 Δ5D 2.94 ±1.0 3.04 ± 1.0 0.47 NS Δ6D 0.02 ± 0.05 0.02 ± 0.05 0.256 NS Elovl 3 0.007 ± 0.003 0.008 ± 0.001 1.22 NS Elovl 5 0.007 ± 0.003 0.006 ± 0.0013 -1.33 NS Elovl 6 0.15 ± 0.02 0.14 ± 0.02 -1.20 NS Elovl = Elongase: Δ5D = delta 5 desaturase; Δ6D = delta 6 desaturase: SCD = stearoyl-CoA desaturase; GDM = gestational diabetes mellitus; NGDM = nongestational diabetes mellitus. Table 5. Variables associated with the risk of developing gestational diabetes mellitus ( logistic regression analysis) Univariate Model Variable Odd Ratio IC 95% P Age > 25 (years old) 3.75 1.92–7.34 0.00009 Prepregnancy BMI ≥ 30 (kg/m 2 ) 1.93 1.0–3.7 0.045 NEFAs (mMol/L) 23.9 1.72–333) 0.017 HDL-cholesterol (mg/dl) 0.86 0.81–0.90 0.000001 Insulin (μUI/mL) 1.06 1.02–1.10 0.0005 HOMA-IR 1.56 1.3-1.87 0.000001 rs6824447 (dominant model) 2.46 1.14-5.3 0.02 Palmitic acid (C16:0) µg/mL 1.08 1.06-1.11 <0.001 Oleic acid (C18:1w9) µg/mL 1.17 1.14–1.2 <0.001 Eicosenic acid (C20:1w6) µg/mL 4.56 2.15–9.63) 0.007 D9D SCD 18 activity 1.25 1.19–1.32 25 years 4.89 1.65-14.4 0.0038 HOMA-IR 34.1 8.73-133.3 0.0000003 rs6824447 5.18 1.56–17.1 0.0067 HDL-cholesterol = high-density lipoprotein cholesterol; NEFAS = nonesterified fatty acid; HOMA-IR = homeostasis model assessment; D9D SCD 18 = stearoyl-CoA desaturase (SCD) Additional Declarations No competing interests reported. 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Fajardo Araujo","email":"","orcid":"","institution":"Universidad de Guanajuato","correspondingAuthor":false,"prefix":"","firstName":"Martha","middleName":"E. Fajardo","lastName":"Araujo","suffix":""},{"id":321749507,"identity":"8836de36-f720-4186-b8be-b8ce6191a704","order_by":2,"name":"Elva Perez-Luque","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIie2RMUvDQBTHHxyky8k5yQsn9itcCJwOxXyVC4F2cdYMDpVCswiuEb9HJ4eDg7jkAwRcMmVyiEvpULSJFNohph0F7wcPHo//j8fjAVgsf5FBUyUABbIdMACnX2mTCsROcadHKruB0AcURqhXq3h9zhJSlZ+vo8AvoqqsYxiyM92puDPqo8oFReNcemk1JrIYN00O3vOL6lSEcRSGc0EFAcmpNo4slOQnc1DivVsJjBOtwq9WGSz5Wn9TP50sexVBSIbhtFWo5KA1Crzp34KGZFcq85tb6J33qCOB+cetm+b46y0seZgV9f1FwJ7eFuVKXwcsmSywjkdDxruVfbbvOP1J4sH4nsL0UWmLxWL5P2wAKrlUKBWMo6sAAAAASUVORK5CYII=","orcid":"","institution":"Universidad de Guanajuato","correspondingAuthor":true,"prefix":"","firstName":"Elva","middleName":"","lastName":"Perez-Luque","suffix":""},{"id":321749508,"identity":"77acd3a6-853b-4e45-898f-e57268c398a3","order_by":3,"name":"Monica Irasú Cardona-Alvarado","email":"","orcid":"","institution":"Universidad de Guanajuato","correspondingAuthor":false,"prefix":"","firstName":"Monica","middleName":"Irasú","lastName":"Cardona-Alvarado","suffix":""},{"id":321749509,"identity":"8e94be94-6d51-4ca8-9e0c-efe49f888c2d","order_by":4,"name":"Enrique Ramírez-Chávez","email":"","orcid":"","institution":"Cinvestav Unidad Irapuato","correspondingAuthor":false,"prefix":"","firstName":"Enrique","middleName":"","lastName":"Ramírez-Chávez","suffix":""},{"id":321749510,"identity":"e138ce15-ff4a-4a00-9386-934e607cb41d","order_by":5,"name":"Jorge Molina-Torres","email":"","orcid":"","institution":"Cinvestav Unidad Irapuato","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Molina-Torres","suffix":""}],"badges":[],"createdAt":"2024-06-13 20:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4578221/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4578221/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61643388,"identity":"352eca61-9456-4dc1-88b2-3954123efa6c","added_by":"auto","created_at":"2024-08-02 10:33:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":867548,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4578221/v1/319f06b0-f9c4-4cf9-83e4-18c52d0cd46c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of the Associations of the rs12504538 and rs6824447 Polymorphisms of the Elovl6 Gene with Estimated Elongase and Desaturase Activity in Gestational Diabetes Mellitus Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGestational diabetes mellitus (GDM) is a pregnancy complication in which hyperglycemia spontaneously develops during pregnancy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The rising obesity epidemic has driven an increase in the incidence of gestational diabetes mellitus, as well as in pregnancy complications in terms of maternal and perinatal outcomes. These factors include known nonmodifiable risk factors for a predisposition to GDM, such as advanced maternal age, the presence of overweight and obesity, ethnicity, and a family history of type 2 diabetes mellitus (T2DM) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. According to the most recent (2021) International Diabetes Federation (IDF) estimates, 21.1\u0026nbsp;million (16.7%) women who give birth to live-born infants have some form of hyperglycemia during pregnancy, 80.3% of whom have GDM [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe majority of women with GDM appear to have β cell dysfunction with a background of chronic insulin resistance, to which the normal insulin resistance in pregnancy is partially additive [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The metabolism of the toxic intracellular metabolites triacylglycerol (TAG) and nonesterified fatty acids (NEFAs) has been reported to cause severe insulin resistance [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Recently, a significant increase in NEFA and TAG levels in GDM patients compared with healthy pregnant women has been reported [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe enzymes required for the synthesis of fatty acids (FAs) are regulated by sterol-regulatory element binding protein (SREBP-1) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Overexpression of the SREBP-1a or SREBP-1c isoforms in the livers of mice results in increased rates of novo fatty acid synthesis and TAG accumulation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Elovl6 is an endoplasmic reticulum enzyme highly induced in the livers of SREBP transgenic mice [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] that is expressed in lipogenic tissues and regulated by SREBP-1 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Elovl6 catalyzes the chain elongation of C12 to C16 saturated and monounsaturated FAs to form C18, such as stearic (C18:0), oleic (C18:1n9), and vaccenic (C18:1n7) acids, the most important step for the de novo synthesis of endogenous long-chain FAs [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. \u003cem\u003eElovl6\u003c/em\u003e gene disruption (E6KO) in mice decreases the proportion of stearic (C18:0) and oleic (C18:1n-9) acids and increases that of palmitic (C16:0) and palmitoleic (C16:1n-7) acids in the liver, confirming that Elovl6 catalyzes the chain elongation of palmitic to stearic acids and the elongation of palmitoleic to vaccenic acids [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In addition, E6KO mice are resistant to obesity-induced insulin resistance, despite being similar to wild-type mice in terms of hepatosteatosis and obesity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], suggesting that \u003cem\u003eElovl6\u003c/em\u003e inhibition could be a potential therapeutic approach for T2DM treatment since Elovl6 deficiency prevents T2DM progression by increasing the insulin secretory capacity of pancreatic β-cells in \u003cem\u003edb/db\u003c/em\u003e mice [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and significantly improves hyperglycemia and elevates HbA1c levels [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It has been reported that the regulation of FA structure may participate in the modulatory effects of FAs on β-cells [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]). Subpopulations of MIN-6 and rat β-cells were shown to be resistant to palmitate-induced apoptosis and associated with increased expression of stearoyl-CoA desaturase (SCD1) and increased conversion of palmitate to monounsaturated fatty acids (MUFAs) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, T2DM is associated with diminished islet expression of SCD1, which can disrupt the desaturation of saturated FAs to MUFAs, rendering β-cells more susceptible to saturated FA-induced ER stress and apoptosis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have shown that genetic variations (SNPs) in the \u003cem\u003eElovl6\u003c/em\u003e gene are associated with the risk of T2DM and insulin resistance [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The rs6824447GG genotype was associated with lower insulin levels in a population from southern Spain [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another study showed that the rs12504538 polymorphism is associated with an increase in insulin resistance and an increased risk of T2DM in the Han Chinese population [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the Mexican population from Queretaro, the rs6824447 polymorphism was associated with lower total cholesterol and LDL cholesterol levels [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. To date, there are few studies on polymorphisms of the \u003cem\u003eElovl6\u003c/em\u003e gene and their associations with insulin resistance and GDM. Therefore, the aim of this study was to investigate the possible associations of the rs12504538 and rs6824447 polymorphisms of the \u003cem\u003eElovl6\u003c/em\u003e gene with elongase and desaturase activity and fatty acid concentrations in Mexican women with gestational diabetes mellitus.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe conducted an observational transverse study of 172 women in the second and third trimesters of pregnancy, including 66 women who had been diagnosed with GDM according to the 2016 criteria of the American Diabetes Association (GDM group), and 106 women with a normal glucose tolerance test result, matched by gestational week, from the General Hospital and health centers from Health Ministry number VII (in Leon Guanajuato, Mexico.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cem\u003eEthical Statement\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe fully informed all participants of the aims of this study, and we asked them for signed informed consent to participate in this study and their publication. This study was carried out according to the ethical standards of the Declaration of Helsinki (2013) and in agreement with the Good Clinical Practice guidelines. This study was approved by the Investigation Committee of General Hospital and health centers from Health Ministry number VII in Leon, (Approval # GTSSA002101), (Approval # JS7-04-230615). and by the Institutional Ethics\u0026nbsp;Committee\u0026nbsp;of\u0026nbsp;the\u0026nbsp;University of Guanajuato (Approval # CIBIUG-P-20-2015), Le\u0026oacute;n Guanajuato, M\u0026eacute;xico\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The participants were recruited during\u0026nbsp;the\u0026nbsp;second and third\u0026nbsp;trimesters\u0026nbsp;of pregnancy after undergoing an oral glucose tolerance test (OGTT). According\u0026nbsp;to\u0026nbsp;the results of\u0026nbsp;the\u0026nbsp;OGTT, we\u0026nbsp;formed\u0026nbsp;two groups: the\u0026nbsp;non-gestational\u0026nbsp;diabetes mellitus (Non-GDM) group and the gestational diabetes mellitus (GDM)\u0026nbsp;group. Data on age, obstetric history, gestational week, height,\u0026nbsp;prepregnancy weight\u0026nbsp;and actual weight were collected. Body mass index (BMI) was calculated by dividing\u0026nbsp;weight\u0026nbsp;(kg) by height squared (m\u003csup\u003e2\u003c/sup\u003e) (kg/m\u003csup\u003e2\u003c/sup\u003e). Blood samples were drawn after an overnight fast for the\u0026nbsp;measurement of\u0026nbsp;serum glucose, lipid, NEFA, fatty\u0026nbsp;acid\u0026nbsp;and insulin levels and DNA extraction.\u0026nbsp;Serum glucose and lipid levels were measured using enzymatic methods with a\u0026nbsp;semiautomatic\u0026nbsp;chemical analyzer\u0026nbsp;(SPINLAB\u0026nbsp;SPINREACT).\u0026nbsp;Serum\u0026nbsp;insulin was measured by\u0026nbsp;an immunoenzymatic\u0026nbsp;assay (GeneWay\u0026nbsp;Biotech Inc., San Diego, CA, USA),\u0026nbsp;and NEFAs were measured by\u0026nbsp;an\u0026nbsp;enzymatic colorimetric method (Wako Life Sciences Inc., Mountain View, CA, USA). The intra-assay variation coefficients were 3.4 to 6.1%\u0026nbsp;for insulin and 1.6%\u0026nbsp;to 2.2%\u0026nbsp;for NEFAs. The quantification of fatty acids was performed by gas\u0026nbsp;chromatography.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGenotyping of Elovl6 polymorphisms\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;DNA was extracted from peripheral blood leucocytes according to the TSNT\u0026nbsp;protocol, quantified using a NanoDrop\u0026nbsp;system (Roche), and stored at -20 \u0026deg;C.\u0026nbsp;Single\u0026nbsp;nucleotide polymorphisms (SNPs) were detected by a combination of polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) assays using appropriate restriction enzymes as described previously [22].\u0026nbsp;Polymerase\u0026nbsp;chain reaction (PCR) was carried out in a total volume of 30 \u0026mu;L\u0026nbsp;in a Thermal Cycler GeneAmp\u0026nbsp;PCR System 2700 (Applied Biosystems). The PCR mixture contained 50 ng\u0026nbsp;of\u0026nbsp;DNA, 0.5 mM of dNTPs (Invitrogen), 10 pM\u0026nbsp;of primers, 2.0 mM of MgCl\u003csub\u003e2\u003c/sub\u003e, 0.6 \u0026mu;L\u0026nbsp;of\u0026nbsp;DMSO, and 5 U\u0026nbsp;of\u0026nbsp;Taq polymerase (Invitrogen) for both\u0026nbsp;polymorphisms. Amplification\u0026nbsp;of\u0026nbsp;the rs12504538\u003cem\u003e\u0026nbsp;\u003c/em\u003epolymorphism was carried out using the following protocol: 95 \u0026deg;C for 5 min;\u0026nbsp;20 cycles of 95 \u0026deg;C for 30 s; 68 \u0026deg;C for 45 s; 72 \u0026deg;C for 45 s;\u0026nbsp;and 72 \u0026deg;C for 1 min. The annealing temperature decreased by 0.5 \u0026deg;C/cycle. This was followed by 20 cycles of 95 \u0026deg;C for 30 s, 60 \u0026deg;C for 30 s, and 72 \u0026deg;C for 40 s, with a final single extension step of 72 \u0026deg;C for 6 min. rs6824447\u003cem\u003e\u0026nbsp;\u003c/em\u003epolymorphism amplification was carried out using the following protocol: 95 \u0026deg;C for 5 min; 35 cycles of 95 \u0026deg;C for 30 s, 56 \u0026deg;C for 45 s, and 72 \u0026deg;C for 1 min; and 72 \u0026deg;C for 1 min.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The\u0026nbsp;PCR\u0026nbsp;product\u0026nbsp;for\u0026nbsp;the rs12504538 polymorphism was a fragment of 295\u0026nbsp;bp\u0026nbsp;that,\u0026nbsp;after digestion with the restriction enzyme Pag I, an isoschizomer\u0026nbsp;of Rca\u0026nbsp;I (Thermo\u0026nbsp;Scientific, Waltham, MA, USA),\u0026nbsp;yielded 186 and 109\u0026nbsp;bp products\u0026nbsp;for the C/C genotype\u0026nbsp;and\u0026nbsp;295, 186, and 109\u0026nbsp;bp\u0026nbsp;products for the C/T genotype, while the enzyme did not cut the normal T/T genotype sequence. For the rs6824447\u003cem\u003e\u0026nbsp;\u003c/em\u003epolymorphism, PCR\u0026nbsp;generated\u0026nbsp;a product of 133-pb, which,\u0026nbsp;after digestion with Ban II (New England BioLabs, Ipswich, MA, USA), yielded 85- and 48-bp\u0026nbsp;fragments\u0026nbsp;for the G/G genotype\u0026nbsp;and\u0026nbsp;133, 85 and 48-pb\u0026nbsp;fragments\u0026nbsp;for the A/G genotype, while the PCR\u0026nbsp;products\u0026nbsp;with the normal A/A genotype\u0026nbsp;were\u0026nbsp;not digested. Both fragments were separated by electrophoresis on a 3% ethidium bromide-stained agarose gel [22].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMeasurement of serum fatty acids.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Serum samples\u0026nbsp;(500 \u0026mu;l) were\u0026nbsp;dried under a gentle stream of nitrogen at room temperature,\u0026nbsp;and\u0026nbsp;the\u0026nbsp;residues\u0026nbsp;were\u0026nbsp;dissolved in\u0026nbsp;1\u0026nbsp;ml\u0026nbsp;of NaOH and 0.5\u0026nbsp;M\u0026nbsp;methanol. An internal standard consisting of\u0026nbsp;10 \u0026mu;l\u0026nbsp;of nonadecanoic acid (C19:0,\u0026nbsp;5 mg/ml) was added. The temperature of the solution was held at 90 \u0026deg;C for\u0026nbsp;1 h; each sample was\u0026nbsp;then cooled to room temperature,\u0026nbsp;and\u0026nbsp;1\u0026nbsp;ml\u0026nbsp;of boron trifluorideetherate\u0026nbsp;in methanol (Sigma‒Aldrich) was slowly added. The samples were\u0026nbsp;reincubated\u0026nbsp;at 90 \u0026deg;C for 30 minutes.\u0026nbsp;The solutions\u0026nbsp;were cooled and transferred to a test tube, where\u0026nbsp;2\u0026nbsp;ml\u0026nbsp;of deionized water and\u0026nbsp;4\u0026nbsp;ml\u0026nbsp;of hexane\u0026nbsp;were added,\u0026nbsp;after which the organic phase was separated. Each solution was dried again under a stream of nitrogen at room temperature\u0026nbsp;and dissolved in\u0026nbsp;400 \u0026mu;l\u0026nbsp;of isooctane (Fisher Chemical). After\u0026nbsp;that,\u0026nbsp;an aliquot was injected into the chromatograph. Fatty acids were chromatographed on a\u0026nbsp;30\u0026nbsp;m\u0026nbsp;fused-silica Zebron\u0026nbsp;ZB-WAX\u0026nbsp;column\u0026nbsp;(0.25 mm i.d.).\u0026nbsp;Analysis was performed with an Agilent Technologies 7890A\u0026nbsp;gas chromatograph equipped with\u0026nbsp;an\u0026nbsp;Agilent Technologies 5975C\u0026nbsp;flame ionization detector. The column temperature was held at 50 \u0026deg;C for 3 min, subsequently increased in a stepwise fashion (10 \u0026deg;C/min) to a plateau of 250 \u0026deg;C,\u0026nbsp;and then held for 3 min. The injection temperature was 220 \u0026deg;C. Helium was used as\u0026nbsp;the\u0026nbsp;carrier gas at\u0026nbsp;2 ml/min. The quantification was\u0026nbsp;performed for\u0026nbsp;67 women\u0026nbsp;without GDM\u0026nbsp;and 64 women with GDM.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The\u0026nbsp;Kolmogorov‒Smirnov\u0026nbsp;test was\u0026nbsp;used to assess the\u0026nbsp;normality of\u0026nbsp;the\u0026nbsp;data. The anthropometric and metabolic data are expressed as\u0026nbsp;the\u0026nbsp;mean \u0026plusmn; SD or median (25-75 quartiles). Differences between groups were examined using the independent\u0026nbsp;t\u0026nbsp;test,\u0026nbsp;Mann‒Whitney\u0026nbsp;\u003cem\u003eU\u003c/em\u003e test or one-way\u0026nbsp;ANOVA\u0026nbsp;and\u0026nbsp;the Kruskal‒Wallis test. Both groups were tested for\u0026nbsp;Hardy‒Weinberg\u0026nbsp;equilibrium for\u0026nbsp;the\u0026nbsp;rs12504538 and rs6824447 \u003cem\u003eElvol6\u003c/em\u003e polymorphisms. We compared allelic frequency between groups using Yates-corrected \u0026chi;\u003csup\u003e2\u0026nbsp;\u003c/sup\u003etests. The association between the polymorphisms and the development of GDM was assessed with logistic regression analysis adjusted for age and IMC using the dominant model. Analyses were performed using a statistical package (Statistica, StatSoft Inc., Tulsa, OK). The level of statistical significance was defined as P \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;We included a total of 172 pregnant women, including 66 with GDM and 106 with\u0026nbsp;a\u0026nbsp;normal glucose tolerance test result (non-GDM), with a median gestational\u0026nbsp;week\u0026nbsp;of 27 (25\u0026ndash;30) weeks. The clinical and metabolic characteristics of both groups are shown in Table 1. The groups were similar in\u0026nbsp;terms of\u0026nbsp;gestational week, weight gain, total cholesterol levels, triglyceride levels, and LDL cholesterol levels. With\u0026nbsp;the\u0026nbsp;exception of HDL cholesterol levels, all variables, including NEFA levels,\u0026nbsp;were significantly\u0026nbsp;greater\u0026nbsp;in\u0026nbsp;the\u0026nbsp;GDM group.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Table 2 summarizes the distributions of\u0026nbsp;the\u0026nbsp;rs6824447 and rs12504538 \u003cem\u003eElovl6\u0026nbsp;\u003c/em\u003egenotypes and alleles between GDM\u0026nbsp;patients\u0026nbsp;and controls. The genotypic frequencies and allelic frequencies of rs12504538 \u003cem\u003eElovl6\u0026nbsp;\u003c/em\u003ewere similar between the groups (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 0.35, p = 0.84; \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 0.94; p = 0.75,\u0026nbsp;respectively).\u0026nbsp;However,\u0026nbsp;the allelic frequencies of\u0026nbsp;the\u0026nbsp;rs6824447 \u003cem\u003eElovl6\u0026nbsp;\u003c/em\u003epolymorphism were significantly different between\u0026nbsp;the\u0026nbsp;groups (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 4.87, p=0.02). The GG\u0026nbsp;genotype\u0026nbsp;frequency was significantly\u0026nbsp;greater\u0026nbsp;in the GDM group (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 6.16, p = 0.04) than\u0026nbsp;in the non-GDM group. The rs12504538 SNP was in accordance with\u0026nbsp;the\u0026nbsp;Hardy‒Weinberg equilibrium,\u0026nbsp;and\u0026nbsp;the rs6824447 SNP showed\u0026nbsp;slight\u0026nbsp;deviation in\u0026nbsp;the\u0026nbsp;GDM group.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In the comparison\u0026nbsp;of the\u0026nbsp;rs6824447 \u003cem\u003eElovl6\u0026nbsp;\u003c/em\u003egenotype, we\u0026nbsp;detected significantly lower levels of HDL\u0026nbsp;cholesterol\u0026nbsp;but\u0026nbsp;significantly\u0026nbsp;higher levels of\u0026nbsp;triglycerides, palmitic acid (C18:0), stearic acid (C18:0), oleic acid (C18:1w9), and eicosenoic\u0026nbsp;acid (C20:1w9) in GDM patients with one or two allelic variants (AG or GG) (Table 3). No differences in the comparison of other variables for genotypes were found. In the comparison of metabolic variables for the rs125504538\u0026nbsp;\u003cem\u003eElovl6\u0026nbsp;\u003c/em\u003egenotype,\u0026nbsp;there were no significant differences.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEstimation of\u0026nbsp;\u003c/em\u003e\u003cem\u003eelongase\u003c/em\u003e\u003cem\u003e\u0026nbsp;and\u0026nbsp;\u003c/em\u003e\u003cem\u003edesaturase\u003c/em\u003e\u003cem\u003e\u0026nbsp;activity and comparison between groups.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In women with GDM, the palmitic acid, stearic acid, oleic acid, and eicosenoic\u0026nbsp;acid\u0026nbsp;concentrations were significantly\u0026nbsp;greater\u0026nbsp;than\u0026nbsp;those in women without GDM\u0026nbsp;(Table 4). The estimated\u0026nbsp;elongase activities of\u0026nbsp;Elovl3\u0026nbsp;(C20:1/C18:2), Elovl6 (C18/C16),\u0026nbsp;and\u0026nbsp;Elovl5\u0026nbsp;(C20:2/C18:2) and\u0026nbsp;the\u0026nbsp;estimated\u0026nbsp;desaturase activities of\u0026nbsp;D5D\u0026nbsp;(C20:4/C20:3),\u0026nbsp;D6D\u0026nbsp;(C18:3/C18:2),\u0026nbsp;D9D SCD16\u0026nbsp;(C16:1/C16:0), and\u0026nbsp;D9D SCD18\u0026nbsp;(C18:1/C18:0) were compared between\u0026nbsp;the\u0026nbsp;GDM and non-GDM groups. No differences between\u0026nbsp;the non-GDM and GDM\u0026nbsp;groups\u0026nbsp;were found,\u0026nbsp;and\u0026nbsp;only the activity of desaturase\u0026nbsp;D9D SCD18\u0026nbsp;was marginally elevated in\u0026nbsp;the\u0026nbsp;GDM group (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLogistic\u003c/em\u003e\u003cem\u003e\u0026nbsp;regression analysis\u003c/em\u003e\u003cem\u003e\u0026nbsp;of associations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;According to\u0026nbsp;the univariate logistic regression analysis, age, prepregnancy BMI \u0026ge;30 kg/m\u003csup\u003e2\u003c/sup\u003e, NEFA levels, serum insulin level, HOMA-IR value, rs6824447 \u003cem\u003eElovl6\u003c/em\u003e polymorphism, palmitic acid, oleic acid, and eicosenic acid levels and the activity of desaturase D9D SCD18 were significantly associated with gestational diabetes mellitus. Notably, the serum HDL cholesterol concentration had a strong protective effect (Table 5). Multiple logistic regression analysis adjusted for age, including previous variables, showed that age, HOMA-IR levels and the rs6824447 polymorphism remained significantly associated with GDM (Table 5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In this study, we analyzed the\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003emetabolic phenotypes of women with GDM and healthy\u0026nbsp;pregnant women\u0026nbsp;and the\u0026nbsp;associations\u0026nbsp;of\u0026nbsp;the\u0026nbsp;rs12504538 and rs6824447 \u003cem\u003eElovl6\u0026nbsp;\u003c/em\u003epolymorphisms with GDM and insulin resistance.\u0026nbsp;Additionally,\u0026nbsp;the serum fatty\u0026nbsp;acid\u0026nbsp;concentration and estimated elongase and desaturase activities\u0026nbsp;were evaluated\u0026nbsp;in both groups. We found\u0026nbsp;that the prepregnancy BMI and triglyceride, NEFA, insulin, and\u0026nbsp;insulin resistance levels\u0026nbsp;were\u0026nbsp;significantly\u0026nbsp;greater\u0026nbsp;and\u0026nbsp;that the\u0026nbsp;HDL\u0026nbsp;cholesterol concentration was lower in women with GDM. Similar results\u0026nbsp;have\u0026nbsp;been reported in other studies [9, 24].\u0026nbsp;Compared with normoglycemic controls, women\u0026nbsp;with GDM were at increased risk of developing T2DM, had abnormalities in insulin secretion [25] and lipid metabolism and had elevated\u0026nbsp;NEFA\u0026nbsp;levels [26].\u003c/p\u003e\n\u003cp\u003eThe rs12504538 \u003cem\u003eElvol6\u003c/em\u003e polymorphism has been associated with\u0026nbsp;an\u0026nbsp;increased risk of T2DM because\u0026nbsp;of increased\u0026nbsp;insulin resistance, but no association\u0026nbsp;between\u0026nbsp;the rs6824447 polymorphism\u0026nbsp;and the development\u0026nbsp;of T2DM\u0026nbsp;has\u0026nbsp;been reported in\u0026nbsp;the\u0026nbsp;Han Chinese population [22]. Instead, we found a significant association\u0026nbsp;between the\u0026nbsp;rs6824447 \u003cem\u003eElovl6\u003c/em\u003e polymorphism\u0026nbsp;and the\u0026nbsp;development of GDM but no association\u0026nbsp;between\u0026nbsp;the rs12504538 polymorphism\u0026nbsp;and\u0026nbsp;the development of T2DM. In\u0026nbsp;nondiabetic\u0026nbsp;subjects\u0026nbsp;in the\u0026nbsp;Spanish population, the rs6824447 polymorphism is associated with\u0026nbsp;a\u0026nbsp;low risk of having high HOMA-IR values [21]. In young subjects from Mexican populations with\u0026nbsp;a\u0026nbsp;normal BMI, rs6824447 has been shown to have a protective effect against high cholesterol and high LDL\u0026nbsp;cholesterol levels. Interestingly, our results\u0026nbsp;revealed that triglyceride\u0026nbsp;levels were\u0026nbsp;greater\u0026nbsp;and\u0026nbsp;that\u0026nbsp;HDL\u0026nbsp;cholesterol levels\u0026nbsp;were lower\u0026nbsp;in GDM patients\u0026nbsp;who were\u0026nbsp;carriers of\u0026nbsp;the\u0026nbsp;rs6824447AG\u0026nbsp;and s6824447GG\u0026nbsp;genotypes. There are very few reports\u0026nbsp;on the\u0026nbsp;association of \u003cem\u003eElovl6\u003c/em\u003e polymorphisms with T2DM,\u0026nbsp;and\u0026nbsp;there are few reports on the association of Elovl6 polymorphisms\u0026nbsp;with GDM.\u0026nbsp;To the best of our knowledge, this is the first report of the contribution of the rs6824447 polymorphism to\u0026nbsp;the\u0026nbsp;development of GDM. In addition, multiple logistic regression showed that age, insulin levels and\u0026nbsp;the\u0026nbsp;rs6824447 polymorphism are factors\u0026nbsp;associated\u0026nbsp;with the risk of GDM.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In our work, no differences in estimated Elovl3, Elovl5,\u0026nbsp;or\u0026nbsp;Elovl6\u0026nbsp;activity were found between women\u0026nbsp;without GDM and\u0026nbsp;women with GDM.\u0026nbsp;There are few studies concerning estimated Elovl6 activity;\u0026nbsp;in children aged 9-12 years,\u0026nbsp;Elovl6 activity is a significant predictor of insulin resistance (IR) [27]. High Elovl6 activity was associated with high IR in Japanese subjects, low activity might be ideal for protection against atherosclerosis,\u0026nbsp;and in\u0026nbsp;nonalcoholic steatohepatitis hepatic\u0026nbsp;(NASH) was proposed [28].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;A previous study reported that the palmitic acid, myristic acid, and oleic acid\u0026nbsp;concentrations\u0026nbsp;were significantly increased in GDM\u0026nbsp;patients\u0026nbsp;[29]. In our study,\u0026nbsp;we found that serum palmitic acid, oleic acid,\u0026nbsp;and\u0026nbsp;eicosenoic\u0026nbsp;acid concentrations were significantly associated with\u0026nbsp;the\u0026nbsp;risk of GDM. Several reports have\u0026nbsp;reported\u0026nbsp;similar results [30-32]. An inverse association\u0026nbsp;between\u0026nbsp;C18:2n-6\u0026nbsp;and\u0026nbsp;GDM has\u0026nbsp;also\u0026nbsp;been reported [32].\u0026nbsp;Another\u0026nbsp;study showed that the activity of\u0026nbsp;the\u0026nbsp;\u0026Delta;5D\u0026nbsp;and \u0026Delta;6D\u0026nbsp;desaturases\u0026nbsp;changed\u0026nbsp;during pregnancy,\u0026nbsp;the\u0026nbsp;estimated \u0026Delta;6D\u0026nbsp;desaturase activity was elevated, and\u0026nbsp;the\u0026nbsp;\u0026Delta;5D\u0026nbsp;desaturase activity\u0026nbsp;was\u0026nbsp;attenuated in the first trimester; however, changes were not detected during the second trimester. However, in the third trimester,\u0026nbsp;\u0026Delta;5D\u0026nbsp;and \u0026Delta;9D\u0026nbsp;SCD-18 desaturase activities were elevated, and \u0026Delta;6D\u0026nbsp;desaturase\u0026nbsp;activity was\u0026nbsp;attenuated [33]. In our study,\u0026nbsp;a similar tendency in \u0026Delta;9D\u0026nbsp;SCD-18 activity (significantly marginal) was found in women with GDM in\u0026nbsp;the\u0026nbsp;third trimester\u0026nbsp;of pregnancy. It\u0026nbsp;has also\u0026nbsp;been reported that increased activation of \u0026Delta;9D\u0026nbsp;SCD-18, which converts stearic acid (C18:0) to oleic acid (C18:1),\u0026nbsp;is associated with\u0026nbsp;the\u0026nbsp;development of GDM in the third trimester [33].\u0026nbsp;Controversial results\u0026nbsp;have\u0026nbsp;been reported, while \u0026Delta;5D\u0026nbsp;desaturase activity was significantly lower and \u0026Delta;9D\u0026nbsp;SCD-18 desaturase activity was significantly\u0026nbsp;greater\u0026nbsp;during pregnancy [34].\u0026nbsp;In\u0026nbsp;another\u0026nbsp;study, \u0026Delta;6D\u0026nbsp;desaturase and \u0026Delta;9D\u0026nbsp;SCD-18 desaturase activities were significantly lower,\u0026nbsp;but\u0026nbsp;there were\u0026nbsp;no significant changes in \u0026Delta;5D\u0026nbsp;desaturase activity in women with GDM at 32-35 weeks of gestation [35]. In our study,\u0026nbsp;no differences in \u0026Delta;5D\u0026nbsp;or\u0026nbsp;\u0026Delta;6D\u0026nbsp;desaturase\u0026nbsp;activity were found;\u0026nbsp;these results may be due to\u0026nbsp;differences in\u0026nbsp;sample\u0026nbsp;size. Higher serum total n\u0026ndash;6 polyunsaturated fatty\u0026nbsp;acid (PUFA), linoleic acid, and arachidonic acid concentrations and estimated\u0026nbsp;\u0026Delta;5D\u0026nbsp;activity were associated with a lower risk of incident T2DM, and participants with higher \u0026gamma;-linolenic acid and dihomo\u0026gamma;-linolenic acid concentrations and estimated\u0026nbsp;\u0026Delta;6D\u0026nbsp;activity\u0026nbsp;had a\u0026nbsp;greater\u0026nbsp;risk of T2D [36].\u0026nbsp;In our study,\u0026nbsp;we did not\u0026nbsp;find\u0026nbsp;significant differences in estimated\u0026nbsp;elongase\u0026nbsp;activity between\u0026nbsp;the\u0026nbsp;non-GDM and GDM groups. However, it\u0026nbsp;has been\u0026nbsp;reported that estimated Elovl6 and \u0026Delta;5D\u0026nbsp;activities might\u0026nbsp;be\u0026nbsp;useful markers of insulin resistance in Japanese subjects [28].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; The elongation of C16 to C18 is mediated by Elovl6 activity and is an important metabolic control point for the conversion of palmitic acid to stearic acid, and for the action of \u0026Delta;9D SCD-18, it is converted to oleic acid. Both fatty acids influence the decrease in insulin secretion and \u0026beta;-cell function and eventually lead to diabetes development. Stearic acid (C18:0) also increased inflammation and the terminal UPR [18]. In our study, although the estimated Elovl6 activity did not increase significantly in the GDM group, the conversion of palmitic acid to stearic acid suggested major Elovl6 activity, and the conversion of stearic acid to oleic acid also suggested major activity of \u0026Delta;9D SCD-18 in the second and third trimesters of pregnancy. Our results are interesting but require additional confirmation given the sample size, particularly in the GDM group.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn our work, metabolic and hormonal parameters,\u0026nbsp;including NEFA levels, were\u0026nbsp;increased in GDM\u0026nbsp;patients. Age, insulin levels and\u0026nbsp;the\u0026nbsp;rs6824447 \u003cem\u003eElovl6\u003c/em\u003e polymorphism are significantly associated with the development of GDM. Triglyceride levels were greater, and HDL cholesterol levels were lower in GDM patients who were carriers of the rs6824447AG and rs6824447GG genotypes. Palmitic acid, oleic acid, eicosenoic acid and \u0026Delta;9D SCD-18 desaturase were significantly associated with the risk of GDM. Other estimated \u0026Delta;5D and \u0026Delta;6D desaturase and elongase activities were similar between the groups.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eThis work was supported by the Funding\u0026nbsp;\u003c/em\u003eIntegration of Thematic Networks of Academic Collaboration 2015\u003cem\u003e\u0026nbsp;for Dr. Martha Eugenia Fajardo Araujo from the\u0026nbsp;\u003c/em\u003eSecretary of Education Public in Mexico.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u003c/strong\u003e The authors would like to thank the doctors and nurses of the Hospital General Regional de Leon and Health Ministry number VII, especially Dr. Luis M. Mu\u0026ntilde;oz-Guevara, for their trust in allowing their staff to help recruit patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests that are relevant to the content of this article to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions:\u0026nbsp;\u003c/strong\u003eManuel\u0026nbsp;A. Mu\u0026ntilde;oz-Nava, conceptualization, investigation and methods; Martha E. Fajardo-Araujo conceptualization, investigation, methods, and project administration;\u0026nbsp;Elva Perez-Luque, Data curation, formal analysis, writing original draft; M\u0026oacute;nica I. Cardona Alvarado, Data curation, formal analysis; Enrique Ram\u0026iacute;rez-Ch\u0026aacute;vez, methods; Jorge Molina-Torres, methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Integration of the thematic networks of academic collaboration. Secretary of Education Public in Mexico 2015.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u003c/strong\u003e The authors would like to thank the doctors and nurses of the Hospital General Regional de Leon and\u0026nbsp;Health Ministry number VII.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmerican Diabetes Association. Classification and Diagnosis of Diabetes (2021): Standards of Medical Care in Diabetes. 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J Lipid Res 55:2597-2605.\u003c/li\u003e\n\u003cli\u003eZhao H, Matsuzaka T, Nakano Y, Motomura K, Tang N, Yokoo T, et al (2017) ElovI6 deficiency improves glycemic control in diabetic db/db mice by expanding \u0026beta;-cell mass and increasing insulin secretory capacity. Diabetes 66:1833-1846.\u003c/li\u003e\n\u003cli\u003eMatsuzaka T (2021) Role of fatty acid elongase Elovl6 in the regulation of energy metabolism and pathophysiological significance in diabetes. Diabetol Int 12:68-673. Doi.org/10.1007/s13340-020-00481-3.\u003c/li\u003e\n\u003cli\u003eGreen ChD, Olson LK (2011) Modulations of palmitate-induced endoplasmatic reticulum stress and apoptosis in pancreatic \u0026beta;-cell by stearoyl-CoA desaturase and ElovI6. Am J Physiol Endocrinol Metab 300:E640-E649. Doi:10.1152/ajpendo.00544.2010.\u003c/li\u003e\n\u003cli\u003eBusch AK, Gurisik E, Cordery DV, Sudlow M, Denyer GS, Laybutt DR, et al (2005) Increased fatty acid desaturation and enhanced expression of stearoyl CoA desaturase protects pancreatic \u0026beta;-cell from lipoapoptosis. Diabetes 54:2917-2925.\u003c/li\u003e\n\u003cli\u003eMorcillo S, Mart\u0026iacute;n-N\u0026uacute;\u0026ntilde;ez GM, Rojo-Mart\u0026iacute;nez G, Almaraz MC, Garc\u0026iacute;a-Escobar E, Mansego ML, et al (2011) ELOVL6 genetic variation is related to insulin sensitivity: a new candidate gene in energy metabolism. PLoS One 6:e21198.\u003c/li\u003e\n\u003cli\u003eLiu Y, Wang F, Yu XL, Miao ZM, Wang ZC, Chen Y, et al (2013) Genetic analysis of the ELOVL6 gene polymorphism associated with type 2 diabetes mellitus. Braz J Med Biol Res 46:623-628. http//dx.doi.org/10.1590/1414-431X20133103.\u003c/li\u003e\n\u003cli\u003eMaycotte-Cervantes ML, Aguilar-Galarza A, Anaya-Loyola MA, Anzures-Cortes ML, Haddad-Talanc\u0026oacute;n L, M\u0026eacute;ndez-Rangel AS, et al (\u003cem\u003e2\u003c/em\u003e020) Influence of Single Nucleotide Polymorphisms of ELOVL on Biomarkers of Metabolic Alterations in the Mexican Population. \u003cem\u003eNutrients\u003c/em\u003e\u003cem\u003e \u003cem\u003e12:\u003c/em\u003e\u003c/em\u003e3389; https://doi.org/10.3390/nu12113389. \u003c/li\u003e\n\u003cli\u003eRyckman KK, Spracklen CN, Smith CJ, Robinson JG, Saftlas AF(2015) Maternal lipid levels during pregnancy and gestational diabetes: a systematic review and meta-analysis. Int J of Obst and Gynaecol Doi:10.1111/1471-0528.13261.\u003c/li\u003e\n\u003cli\u003eReyes-Lopez Ruth, Perez-Luque Elva, Malacara Juan M (2019) Relationship of lactation, BMI, and rs12255372 TCF7L2 polymorphism on the conversion to type 2 Diabetes Mellitus in women with previous Gestational Diabetes. Gynecol Endocrinol doi:10.1080/09513590.2018.1531984.\u003c/li\u003e\n\u003cli\u003eMeyer B, Calvert D, Moses R (1996) Free fatty acid and gestational diabetes mellitus. Austral New Zeal Journal of Obst and Gynaecol 36:255-257.\u003c/li\u003e\n\u003cli\u003eBeccarelli LM, Scherr RE, Newman JW, Borkowska AG, Grey iJ, Linnell JD (2018) Association among fatty acid, desaturase and elongase, and insulin resistance in children. J of the Am College of Nutr 37:44-50. Doi.org/10.1080707315724.2017.1347908.\u003c/li\u003e\n\u003cli\u003eMoriyama K, Masuda Y, Suzuki N, Yamada Ch, Lishimoto N, Takashimizu S, et al (2022) Estimated Elvol6 and delta-5 desaturase activities might represent potential markers for insulin resistance in Japanese adults. J of Diabetes \u0026amp; Metab Dis 21:197-207. Doi.org/10.1007/s40200-021-00958-1.\u003c/li\u003e\n\u003cli\u003eRaczkowska BA, Mojsak P, Rojo D, Telejko B, Pazkowska-Abdulsalam M, Hryniewicka J, et al (2021) Gas chromatography-mass spectroscopy- based metabolomics analysis reveal potential biochemical markers for diagnosis of gestational diabetes mellitus. Frontiers in Pharmacology doi: 10.3389/fphar.2021.770240.\u003c/li\u003e\n\u003cli\u003eSun Z, Deng Z, Wei X, Wang N, Yang J, Li W, et al (2022) Circulating saturated acids and risk of gestational diabetes mellitus: A cross-sectional study and meta-analysis. Frontiers in nutr doi 10.3389/fnut.2022.903689.\u003c/li\u003e\n\u003cli\u003eWang H, Yang W, Liu J, Leng J, Li W, Yu Z, et al (2021) Serum concentrations of SFAs and \u003cem\u003eCDKAL1\u003c/em\u003e single-nucleotide polymorphism rs7747752 are related to an increased risk of gestational diabetes mellitus. Am J Clin Nutr 114:1698-1707.\u003c/li\u003e\n\u003cli\u003ePan X-F, Huang Y, Li X, Wang Y, Ye Y, Chen H, et al (2021) Circulating fatty acids and the risk of gestational diabetes mellitus: prospective analyses in China. Eur J of Endocrinol 185:87-97. doi.org/10.1530/EJE-21-0118.\u003c/li\u003e\n\u003cli\u003eLiu Y, Xia Y-Y, Zhang T, Yang Y, Cannon RD, Mansell T, et al (2022) Complex interactions between circulating fatty acids levels, desaturase activities, and the risk of gestational diabetes mellitus: A prospective cohort study. Frontiers in Nutr doi: 10.3389/fnut.2022.919357.\u003c/li\u003e\n\u003cli\u003eBurlina S, Dalfra MG, Barison A, Martin R, Ragazzi E, Sartore G, et al (2017) Plasma phospholipid fatty acid composition and desaturase activity in women with gestational diabetes mellitus before and after delivery. Acta Diabetol 54:45-51. Doi: 10.1007/s00592-016-0901-x.\u003c/li\u003e\n\u003cli\u003eZhao JP, Levy E, Shatenstein B, Fraser WD, Julien P, Montoudis A, et al (2015) Longitudinal circulating concentrations of long-chain polyunsaturated fatty acids in the third trimester of pregnancy in gestational diabetes. Diabetic Med Doi: 10.1111/dme.12978.\u003c/li\u003e\n\u003cli\u003eYary T, Voutilainen S, Tuomainen T-P, Ruusunen A, Nurmi T, Virtanen JK (2016) Serum n\u0026ndash;6 polyunsaturated fatty acids, D5- and D6-desaturase activities, and risk of incident type 2 diabetes in men: The Kuopio Ischaemic Heart Disease Risk Factor Study. Am J Clin Nutr 103:1337-1343.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Clinical and metabolic characteristics of the two groups of pregnant women\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-GDM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN = 106\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN = 66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e/z\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e23 (20-29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e30 (25-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eGestational (weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e27 (25-30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e28 (25-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e155 (152-160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e155 (153-159)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003ePrepregnancy BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\"\u003e\n \u003cp\u003e26.5 \u0026plusmn; 5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\"\u003e\n \u003cp\u003e30.0 \u0026plusmn; 6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e-3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eBMI at sample collection (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e28.8 \u0026plusmn; 5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e32.5 \u0026plusmn; 5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.00004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eWeight gain (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e5 (3.5-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e5 (2-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eGlucose (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e4.4 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e5.3 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.30 (1.83-2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e2.61 (2.03-3.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eCholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e5.56 (4.8\u0026ndash;6.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e5.74 (4.62\u0026ndash;6.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eHDL cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e1.83 (1.68\u0026ndash;1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e1.57 (1.37\u0026ndash;1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eLDL cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e2.76 \u0026plusmn; 1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e2.84 \u0026plusmn; 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eNEFAs (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e0.40 (0.34-0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e0.43 (0.35-0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eInsulin (\u0026mu;UI/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e19 (16-22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e23 (18-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e-3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.0009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.92156862745098%\" valign=\"top\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e3.6 (3-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.568627450980394%\" valign=\"top\"\u003e\n \u003cp\u003e5.3 (4-8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe values are expressed as\u0026nbsp;the\u0026nbsp;mean\u0026nbsp;\u0026plusmn; SD\u0026nbsp;or median and interquartile range;\u003cstrong\u003e\u003cem\u003e\u0026nbsp;t =\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eStudent\u0026rsquo;s t test\u003cstrong\u003e; z\u003c/strong\u003e = Mann\u0026ndash;Whitney U test. GDM = gestational diabetes mellitus; NGDM = nongestational diabetes mellitus; BMI = body mass index; LDL-cholesterol = lipoprotein density low; HDL cholesterol = high-density lipoprotein NEFAS = nonesterified fatty acid; HOMA-IR = homeostasis model assessment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Genotype and allelic frequencies of rs12504538 and rs6824447\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003eSNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.1764705882353%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eGenotype frequency [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.209150326797385%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAllele frequency [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ers12504538 (T/C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.72549019607843%\" valign=\"top\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.562091503267974%\" valign=\"top\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.320261437908496%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003eNon-GDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.72549019607843%\" valign=\"top\"\u003e\n \u003cp\u003e57 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e46 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.562091503267974%\" valign=\"top\"\u003e\n \u003cp\u003e3 (0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.320261437908496%\" valign=\"top\"\u003e\n \u003cp\u003e(0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e48 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.72549019607843%\" valign=\"top\"\u003e\n \u003cp\u003e35 (0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e28 (0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.562091503267974%\" valign=\"top\"\u003e\n \u003cp\u003e3 (0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.320261437908496%\" valign=\"top\"\u003e\n \u003cp\u003e(0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e31 (0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.1764705882353%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 0.35 \u0026nbsp; \u0026nbsp; p = 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.209150326797385%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 0.94 \u0026nbsp; p = 0.75\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ers6824447 (A/G)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.72549019607843%\" valign=\"top\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.562091503267974%\" valign=\"top\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.320261437908496%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003eNon-GDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.72549019607843%\" valign=\"top\"\u003e\n \u003cp\u003e35 (0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e57 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.562091503267974%\" valign=\"top\"\u003e\n \u003cp\u003e14 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.320261437908496%\" valign=\"top\"\u003e\n \u003cp\u003e92 (0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e71 (0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.72549019607843%\" valign=\"top\"\u003e\n \u003cp\u003e11 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e41 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.562091503267974%\" valign=\"top\"\u003e\n \u003cp\u003e14 (0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.320261437908496%\" valign=\"top\"\u003e\n \u003cp\u003e52 (0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e55 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.281045751633986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.1764705882353%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 6.16 \u0026nbsp; \u0026nbsp; p = 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.209150326797385%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 4.87 \u0026nbsp; \u0026nbsp;p = 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eGDM = Gestational diabetes mellitus.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Analysis by genotypes of polymorphism rs6824447 (dominant model) between the groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNGDM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;N = 35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;N = 11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNGDM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAG + GG\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN = 71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAG + GG\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN = 55\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e*p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e**p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e25 (20-29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e30 (24-33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e23 (20-29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e31(25-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003ePrepregnancy Weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e64.4 \u0026plusmn; 13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e78 \u0026plusmn; 17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e64.5\u0026plusmn;13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e72.3\u0026plusmn;15.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003ePrepregnancy BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e25.1 \u0026plusmn; 5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e30.4 \u0026plusmn; 6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e25.1\u0026plusmn;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e28.5\u0026plusmn;5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eWeight at sample collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e71.2 \u0026plusmn; 14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e84.4 \u0026plusmn; 14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e69.7\u0026plusmn;13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e78.4\u0026plusmn;15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.0009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e) at sample collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e27.8 \u0026plusmn; 5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e32.9 \u0026plusmn; 5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e27.2 \u0026plusmn;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e30.6 \u0026plusmn;5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eWeight gain (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e6 (4-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1\u0026ndash;12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5 (4\u0026ndash;9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e6 (2\u0026ndash;9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eGlucose (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003cp\u003e(4.14\u0026ndash;4.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.38\u003c/p\u003e\n \u003cp\u003e(5.27\u0026ndash;6.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.00004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003cp\u003e(4.0\u0026ndash;4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.21\u003c/p\u003e\n \u003cp\u003e(4.6\u0026ndash;5.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTriglycerides (\u003c/strong\u003emmol/L\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003cp\u003e(1.93\u0026ndash;2.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003cp\u003e(2.01\u0026ndash;2.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.21\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.81\u0026ndash;2.73)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.77\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(2.14\u0026ndash;3.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eTotal Cholesterol\u003c/p\u003e\n \u003cp\u003e(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.35\u003c/p\u003e\n \u003cp\u003e(5.0\u0026ndash;4.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e6.38\u003c/p\u003e\n \u003cp\u003e(4.37\u0026ndash;6.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.55\u003c/p\u003e\n \u003cp\u003e(4.86\u0026ndash;6.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.58\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(4.62-6.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL cholesterol (\u003c/strong\u003emmol/L\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003cp\u003e(1.65\u0026ndash;1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003cp\u003e(1.52\u0026ndash;1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.83\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.73\u0026ndash;1.91)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.49\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.31\u0026ndash;1.78)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.00001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eLDL cholesterol (mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e2.84 \u0026plusmn; 1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e2.76 \u0026plusmn; 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e2.74 \u0026plusmn; 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e2.81 \u0026plusmn; 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eNEFAS (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003cp\u003e(0.36-0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003cp\u003e(0.38-0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003cp\u003e(0.31-0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003cp\u003e(0.34-0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eInsulin (\u0026mu;UI/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e(16-22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e(20-38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e(16-23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e(18-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.357910906298002%\" valign=\"top\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003cp\u003e(3.1-4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003cp\u003e(4.6\u0026ndash;10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003cp\u003e(2.9-4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003cp\u003e(4.1-7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Student\u0026rsquo;s t test: *MWT =\u0026nbsp;Mann\u0026ndash;Whitney test; **One-way ANOVA; KWT = Kruskal\u0026ndash;Wallis test.\u0026nbsp;The values are expressed as\u0026nbsp;the means \u0026plusmn; SDs or medians\u0026nbsp;and interquartile\u0026nbsp;ranges. GDM =\u0026nbsp;gestational\u0026nbsp;diabetes mellitus; NGDM =\u0026nbsp;nongestational\u0026nbsp;diabetes mellitus; BMI =\u0026nbsp;body\u0026nbsp;mass index; LDL\u0026nbsp;cholesterol =\u0026nbsp;lipoprotein density low\u0026nbsp;cholesterol; HDL\u0026nbsp;cholesterol =\u0026nbsp;high-density lipoprotein\u0026nbsp;cholesterol\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eNEFAS\u003cstrong\u003e\u0026nbsp;=\u0026nbsp;\u003c/strong\u003enonesterified\u0026nbsp;fatty acid; HOMA-IR =\u0026nbsp;homeostasis\u0026nbsp;model assessment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Comparison of fatty\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eacid levels and elongase and desaturase\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;activity between the groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-GDM (n = 67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDM (n = 64)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;student\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003eMyristic \u0026nbsp;acid (C14:0) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e15.1 \u0026plusmn; 8.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e16.3 \u0026plusmn; 9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Palmitic acid (C16:0)\u0026nbsp;\u003c/strong\u003e\u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e857.4 \u0026plusmn; 225\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e990 \u0026plusmn; 321\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003ePalmitoleic acid (C16:1) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e48.8 \u0026plusmn; 21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e54 \u0026plusmn; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStearic acid (C18:0)\u0026nbsp;\u003c/strong\u003e\u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e122.3 \u0026plusmn; 21.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e135.3 \u0026plusmn; 32.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOleic acid \u0026nbsp;(C18:1 w9)\u0026nbsp;\u003c/strong\u003e\u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e746.3 \u0026plusmn; 194\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e888 \u0026plusmn; 297\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.245\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003eElaidic acid (C18:1) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e58.6 \u0026plusmn; 11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e63.6 \u0026plusmn; 18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003eLinoleic acid (C18:2 w6) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1064.2 \u0026plusmn; 271.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e1134 \u0026plusmn; 295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Alpha-Linolenic acid (C18:3 w3) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e21.7 \u0026plusmn; 7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e23.5 \u0026plusmn; 8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEicosenoic acid (C20:1 w9)\u0026nbsp;\u003c/strong\u003e\u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.4 \u0026plusmn; 4.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.7 \u0026plusmn; 2.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.036\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026Delta;9D SCD 16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e0.057 \u0026plusmn; 0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e0.053 \u0026plusmn; 0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e1.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;9D SCD 18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.1 \u0026plusmn; 1.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.5 \u0026plusmn; 1.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.937\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026Delta;5D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e2.94 \u0026plusmn;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e3.04 \u0026plusmn; 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026Delta;6D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e0.02 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e0.02 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003eElovl 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e0.007 \u0026plusmn; 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e0.008 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003eElovl 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e0.007 \u0026plusmn; 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e0.006 \u0026plusmn; 0.0013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e-1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.80757097791798%\" valign=\"top\"\u003e\n \u003cp\u003eElovl 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.397476340694006%\" valign=\"top\"\u003e\n \u003cp\u003e0.15 \u0026plusmn; 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.400630914826497%\" valign=\"top\"\u003e\n \u003cp\u003e0.14 \u0026plusmn; 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.406940063091483%\" valign=\"top\"\u003e\n \u003cp\u003e-1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eElovl = Elongase: \u0026Delta;5D =\u0026nbsp;delta 5 desaturase; \u0026Delta;6D =\u0026nbsp;delta 6 desaturase: SCD = stearoyl-CoA desaturase;\u0026nbsp;GDM =\u0026nbsp;gestational\u0026nbsp;diabetes mellitus; NGDM =\u0026nbsp;nongestational\u0026nbsp;diabetes mellitus.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Variables associated with the risk of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edeveloping\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;gestational diabetes mellitus (\u003c/strong\u003e\u003cstrong\u003elogistic\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;regression analysis)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003eOdd Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003eIC 95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eAge \u0026gt; 25 (years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.92\u0026ndash;7.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.00009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003ePrepregnancy BMI \u0026ge; 30 (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.0\u0026ndash;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eNEFAs\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(mMol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e23.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.72\u0026ndash;333)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eHDL-cholesterol (mg/dl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u0026ndash;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eInsulin (\u0026mu;UI/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.02\u0026ndash;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.3-1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003ers6824447 (dominant model)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.14-5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003ePalmitic acid (C16:0) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.06-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eOleic acid (C18:1w9) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.14\u0026ndash;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eEicosenic acid (C20:1w6) \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e2.15\u0026ndash;9.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eD9D SCD 18 activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.19\u0026ndash;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Adjusted for age)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eAge \u0026gt;25 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e4.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.65-14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.0038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e34.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e8.73-133.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.61460101867572%\" valign=\"top\"\u003e\n \u003cp\u003ers6824447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.431239388794568%\" valign=\"top\"\u003e\n \u003cp\u003e5.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\" valign=\"top\"\u003e\n \u003cp\u003e1.56\u0026ndash;17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.713073005093378%\" valign=\"top\"\u003e\n \u003cp\u003e0.0067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHDL-cholesterol =\u0026nbsp;high-density lipoprotein\u0026nbsp;cholesterol; NEFAS\u003cstrong\u003e\u0026nbsp;=\u0026nbsp;\u003c/strong\u003enonesterified fatty acid; HOMA-IR = homeostasis model assessment; D9D SCD 18 = stearoyl-CoA desaturase (SCD)\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"gestational diabetes mellitus, rs6824447 Elovl6, rs12504538 Elovl6, fatty acids, elongase activity, desaturase activity","lastPublishedDoi":"10.21203/rs.3.rs-4578221/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4578221/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003eThis study aimed to investigate the possible associations of the rs12504538 and rs6824447 polymorphisms of the \u003cem\u003eElovl6\u003c/em\u003e gene with estimated elongase and desaturase activity and saturated fatty acid concentrations in Mexican women with gestational diabetes mellitus (GDM).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e. We recruited 172 women in the second and third trimesters of pregnancy who had undergone an oral glucose tolerance test, including 66 who had diagnosed with GDM according to the 2016 ADA criteria and 106 who had normal glucose tolerance test results, from the General Hospital and Health Centers of the Health Ministry of Guanajuato, M\u0026eacute;xico. Participants were matched by gestational week. Data on age, gestational week, and anthropometric characteristics were collected. Blood samples were drawn after an overnight fast for the measurement of serum glucose, lipid, NEFA, serum fatty acid, and insulin levels; SNP genotyping and quantification of fatty acids was performed, and elongase and desaturase activity was estimated.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eWith the exception of HDL-cholesterol, all variables, including NEFA levels, were significantly greater in the GDM group than in the non-GDM group. The rs6824447 polymorphism of the \u003cem\u003eElovl6\u003c/em\u003e gene, an \u003cem\u003ea\u003c/em\u003ege\u0026thinsp;\u0026gt;\u0026thinsp;25 years, and HOMA-IR levels were associated with the development of GDM (OR\u0026thinsp;=\u0026thinsp;5.1, 95% CI 1.56\u0026ndash;17.1, p\u0026thinsp;=\u0026thinsp;0.006; OR\u0026thinsp;=\u0026thinsp;4.89, 95% CI 1.65\u0026ndash;14.4, p\u0026thinsp;=\u0026thinsp;0.003; OR\u0026thinsp;=\u0026thinsp;34.1 95% CI 8.7\u0026ndash;133, p\u0026thinsp;\u0026lt;\u0026thinsp;0.000001, respectively). Palmitic acid (OR\u0026thinsp;=\u0026thinsp;1.08; 95% CI: 1.06\u0026ndash;1.11; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and oleic acid (OR\u0026thinsp;=\u0026thinsp;1.17; 95% CI: 1.14\u0026ndash;1.2; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) concentrations were also associated with the development of GDM. No differences in the estimated elongase and desaturase activity among the non-GDM and GDM groups were found, and only the activity of Δ9D SCD18 desaturase was marginally high in GDM patients (p\u0026thinsp;=\u0026thinsp;0.050).\u003c/p\u003e\u003ch2\u003eConclusion.\u003c/h2\u003e \u003cp\u003eThe rs6824447\u003cem\u003eElovl6\u003c/em\u003e polymorphism is associated with the development of GDM, as are high serum palmitic acid, oleic acid, and stearic acid concentrations and estimated Δ9D SCD18 desaturase activity.\u003c/p\u003e","manuscriptTitle":"Analysis of the Associations of the rs12504538 and rs6824447 Polymorphisms of the Elovl6 Gene with Estimated Elongase and Desaturase Activity in Gestational Diabetes Mellitus Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 10:48:08","doi":"10.21203/rs.3.rs-4578221/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3fec5bc4-b424-47f6-9a30-3ecf38764ef0","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-02T10:25:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 10:48:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4578221","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4578221","identity":"rs-4578221","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}