Variant in a gene encoding a serotonin receptor increases the risk of gestational diabetes mellitus: a case control study

Variant in a gene encoding a serotonin receptor increases the risk of gestational diabetes mellitus: a case control study | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Variant in a gene encoding a serotonin receptor increases the risk of gestational diabetes mellitus: a case control study Juliana Regina Chamlian Zucare Penno, Daniele Pereira Santos-Bezerra, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2081039/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Jul, 2023 Read the published version in European Journal of Medical Research → Version 2 posted 7 You are reading this latest preprint version Show more versions Abstract Background Given the importance of the serotoninergic system for the adaptation of beta cells to the increased insulin demand during pregnancy, we hypothesized that genetic variants (single nucleotide polymorphisms [SNPs]) in the HTR2B gene could influence the risk of developing gestational diabetes mellitus (GDM). Methods This was a case-control study. Five SNPs (rs4973377, rs765458, rs10187149, rs10194776, and s17619600) in HTR2B were genotyped by real-time polymerase chain reaction in 453 women with GDM and in 443 pregnant women without GDM. Results Only the minor allele C of SNP rs17619600 conferred an increased risk for GDM in the codominant model (odds ratio [OR] 2.15; 95% confidence interval [CI] 1.53–3.09; P < 0.0001) and in the rare dominant model (OR 2.32; CI 1.61–3.37; P < 0.0001). No associations were found between the SNPs and insulin use, maternal weight gain, newborn weight, or the result of postpartum oral glucose tolerance test (OGTT). In the overall population, carriers of the XC genotype (rare dominant model) presented a higher area under the curve (AUC) of plasma glucose during the OGTT, performed for diagnostic purposes, compared with carriers of the TT genotype of rs17619600. Conclusions SNP rs17619600 in the HTR2B gene influences glucose homeostasis, probably affecting insulin release, and the presence of the minor allele C was associated with a higher risk of GDM. HTR2B Single nucleotide polymorphisms Serotonin Beta cell Figures Figure 1 Introduction In order to maintain glycemic homeostasis during pregnancy, the increase in maternal insulin resistance is compensated by hyperplasia and increased function of maternal pancreatic beta cell. The failure of this compensatory mechanism is associated with GDM ( 1 ). GDM occurs in 10–18% of all pregnancies ( 2 – 4 ) and it confers a higher risk of several pregnancy complications for both mother and newborn, such as cesarean delivery, polyhydramnios, preeclampsia, jaundice, macrosomia, and neonatal hypoglycemia. GDM is also considered a risk factor for type 2 diabetes mellitus (T2D), obesity and cardiovascular disease ( 5 , 6 ). Studies conducted in vitro and in rodent models have shown modified expression of many islet genes during pregnancy. Among the most significantly upregulated genes are the ones encoding the two isoforms of tryptophan hydroxylase ( Tph1 and Tph2 ), the rate-limiting enzyme of serotonin (5-hydroxytryptamine, 5-HT) synthesis ( 7 , 8 ). Βeta cells have the ability to synthesize, store and secrete 5-HT and islet 5-HT content increases during pregnancy ( 7 – 9 ), secondarily to stimulation of TPH1 and TPH2 expression in beta cells. This process is dependent on placental lactogen (PL) acting through prolactin receptors (PRLR) ( 9 ); thus, 5-HT acts downstream of PL signaling to drive beta cell expansion ( 8 , 10 , 11 ). 5-HT receptors are classified into seven different families (HTR1–7), some of which contain different subtypes ( 12 ). In pregnant mice, the HTR2B expression closely matched the period of increased beta cell proliferation ( 8 , 13 ) and blocking HTR2B signaling impaired beta cell expansion, causing glucose intolerance ( 8 ). Microarray and RNA sequencing analyses revealed transcripts of almost all 5-HT receptors in human islets ( 14 , 15 ) and an in vitro study have shown that the activation of HTR2B promoted glucose-stimulated insulin secretion (GSIS) not only in mouse, but also in human beta cells, suggesting that 5-HT also stimulates insulin release through HTR2B ( 15 ). Given the importance of the serotoninergic system for the adaptation of beta cells to the increased insulin demand during pregnancy, we hypothesized that genetic variants in the HTR2B gene could influence the risk of developing GDM. Participants And Methods This was a case-control study that initially recruited 1,130 pregnant women between September 2014 and September 2017; 90 refused to participate and 36 were considered ineligible for not meeting the inclusion criteria. Of the 1,004 pregnant women then recruited, 108 were lost to follow-up, resulting in a final number of 896. After a diagnostic evaluation for GDM, women were classified into two study groups: 453 pregnant women that had GDM diagnosis in the current pregnancy and 443 pregnant women without the diagnosis of GDM. All pregnant women were followed-up at the Obstetric Clinic of a tertiary university hospital. The study was carried out in compliance with the Declaration of Helsinki, in accordance with institutional ethics committees. After signing informed consent, participants were evaluated for clinical and biochemical characteristics. Clinical and biochemical variables were collected from the medical records. The weight gain during pregnancy was calculated as the difference between the weight (in kilograms) at the end of pregnancy and the weight at first consultation. The inclusion criteria for women without GDM were: no prior GDM or other metabolic conditions, normal fasting plasma glucose (FPG) in the first trimester and normal 75 g OGTT between 24- and 28-weeks gestational age. The inclusion criteria for women with GDM were: GDM diagnosis in the index pregnancy and no use of steroids before GDM diagnosis. GDM was defined by criteria proposed by the International Association of Diabetes and Pregnancy Study Groups (IADPSG), based on first trimester FPG ≥ 92 mg/dL (5.1 mmol/L) (n = 257) or 2-h OGTT with 75 g of glucose performed between 24–28 weeks of gestation with at least one altered value (FPG ≥ 92 mg [5.1 mmol/L], 1-h plasma glucose ≥ 180 mg/dL ( 16 ) and 2-h plasma glucose ≥ 153 mg/dL [8.5 mmol/L]) (n = 196). Women with GDM who failed to reach 30% of the glycemic targets (FPG < 95 mg/dL, 1-h postprandial glucose < 140 mg/dL), after dietary and lifestyle modifications, were administered insulin. A 2-h OGTT was performed in the GDM group at 6 to 12 weeks postpartum, and the American Diabetes Association (ADA) diagnostic criteria for diabetes mellitus (DM) ( 17 ) were applied. Single nucleotide polymorphisms genotyping Deoxyribonucleic acid extraction from peripheral blood leukocytes was carried out by a salting-out procedure ( 18 ). Single nucleotide polymorphisms (SNPs) were genotyped by real-time polymerase chain reaction (StepOne Plus; Applied Biosystems, USA), using predesigned Human TaqMan Genotyping Assays 40X: C__2398885_30 (rs765458), C__30043265_10 (rs10187149), C__32997861_10 (rs17619600), C__27918443_10 (rs4973377), C__29863060_10 (rs10194776) (Thermo Fisher Scientific, Waltham, USA). The five Tag SNPs cover approximately 95% of the genetic variability of the extended region of HTR2B gene and were selected using a pair wise approach, a r 2 ≥ .8 and a minor allele frequency (MAF) of at least 0.1. The genotyping success rate was ~ 99% for all SNPs. The SNP rs4973377 was not evaluated because only one genotype was found in the studied population. The Hardy–Weinberg equilibrium (HWE) was tested; the distribution of genotypes was consistent with HWE for all remained SNPs. Statistical analysis Continuous variables are expressed as median and 25–75% interquartile ranges, and categorical variables are expressed as number of cases and percentage of affected individuals. The Mann-Whitney test for independent samples was used to compare continuous variables between the studied groups while categorical variables were compared by Pearson's χ2 test, which was also used to compare the frequency of SNPs between the groups. The HWE was determined using the frequency of alleles in the Pearson's χ2 test at a significance level of 0.05. The SNPs were evaluated in the rare dominant model and in the codominant model. The magnitude of the risk conferred by the SNPs was estimated using odds ratio (OR) with a 95% confidence interval (CI). To estimate the OR adjusted for potential confounding factors (age at last menstrual period [LMP], previous body mass index [BMI], and weight gain during pregnancy), a binary logistic regression analysis was performed with these factors as covariates in the regression model. The correction for multiple comparisons due to the multiple SNPs tested was made by Bonferroni's correction, dividing 0.05 by the number of studied SNPs in the HTR2B gene. Thus, a P < 0.01 (two-tailed) was considered significant. This study was exploratory in nature. Thus, a convenience sample was used, in which we sought to include as many participants as possible. The power calculation was performed a posteriori using the GAS Power Calculator (Genetic Association Study power calculator) ( 19 ). The power of the study was > 90% (100% and 99.7%, respectively) to detect associations of the SNP rs17619600 in the HTR2B gene with GDM in the codominant model and in the rare dominant model. Haplotype analysis was performed using the software available online SHEsis. All haplotypes with a frequency < 0.03 were ignored for analysis. For the evaluation of the different combinations, Pearson's χ 2 test was used, with a value of P < 0.05 being considered significant ( 20 ). The area under the curve (AUC) of plasma glucose during the OGTT was calculated using the trapezoidal method and the results were expressed as mean ± standard deviation. For comparison of the AUC of plasma glucose between genotypes, one-way ANOVA was used, adjusted for age at LMP, previous BMI, and weight gain during pregnancy. Results The characteristics of the pregnant women with and without GDM are shown in Table 1 . Table 1 Characteristics of women with and without gestational diabetes mellitus. Without GDM With GDM P- value N 443 453 Age (years) 29.1 (24.4–33.4) 33.2 (28.8–37.1) < 0.0001 White* (%) 85 85 0.94 Parity 1.5 ± 0.5 1.7 ± 0.4 < 0.0001 Pre-pregnancy BMI (kg/m 2 ) 24.7 (21.8–28.1) 28.2 (24.8–32.9) < 0.0001 Positive family history of T2D (%) 49 58 < 0.0001 Weight gain during pregnancy (kg) 12.0 (8.7–15.2) 9.0 (5.0–13.3) < 0.0001 Preeclampsia (%) 8.4 8.5 0.76 Arterial hypertension (%) 7.5 23.8 < 0.0001 Use of medicines (%) 28 51 < 0.0001 Insulin treatment† (%) - 18.7 - Fasting plasma glucose (mg/dL) 78 (74–82) 92 (83–97) < 0.0001 Cesarean delivery (%) 48 60 0.001 Newborn birth weight (g) 3,240 (2,897-3,542) 3,210 (2,780-3,512) 0.04 Results expressed as median and interquartile range, except for parity (mean ± standard deviation); BMI: body mass index; GDM: gestational diabetes mellitus; T2D: type 2 diabetes mellitus. *Self-defined ethnicity. † Only the participants with GDM needed insulin. P ≤ 0.05 was considered significant. The missing data (percentage) for each reported variable is as follows: age (0.77%), ethnicity (8.7%), parity (1.2%), BMI (18.8%), family history (0%), weight gain (4.5%), preeclampsia (0.33%), arterial hypertension (1.2%), use of medicines (1.4%), insulin treatment (0.5%), fasting plasma glucose (5.5%), type of delivery (16.4%), newborn birth weight (16.7%). Compared to the group without GDM, women with GDM were older, had a higher number of previous pregnancies, a higher pre-pregnancy BMI with a higher frequency of family history of T2D. Women with GDM had less weight gain during pregnancy, higher frequency of hypertension and use of medications, and higher FPG compared to women without GDM. Cesarean delivery was more frequent in women with GDM and the weight of newborns from women with GDM was lower than the weight of newborns from women without GDM. Among women with GDM, 18.7% used insulin. The SNPs rs10187149, rs10194776 and rs765458 did not associate with GDM (Table 2 ). The minor allele C of SNP rs17619600 conferred an increased risk for GDM in the codominant model (OR 2.15; 95% CI 1.53–3.09; P < 0.0001) and in the rare dominant model (OR 2.32; CI 1.61–3.37; P < 0.0001). The SNPs were not associated with insulin use, maternal weight gain, newborn birth weight or glycemic change in the postpartum OGTT (data not shown). Table 2 Genotype frequencies of single nucleotide polymorphisms in HTR2B according to status of gestational diabetes mellitus. SNPs Without GDM With GDM OR (CI 95%) P value HTR2B 443 453 rs765458 AA 0.248 0.239 0.90 (0.64–1.27) 0.55 (RD) AG 0.542 0.518 1.02 (0.82–1.27) 0.82 (CD) GG 0.210 0.243 MAF 0.481 0.502 rs10187149 AA 0.324 0.338 AC 0.509 0.498 0.94 (0.77–1.45) 0.70 (RD) CC 0.167 0.164 0.92 (0.74–1.14) 0.46 (CD) MAF 0.422 0.413 rs10194776 TT 0.277 0.279 TC 0.526 0.495 0.99 (0.79–1.52) 0.57 (RD) CC 0.197 0.226 0.96 (0.78–1.19) 0.74 (CD) MAF 0.479 0.473 rs17619600 TT 0.839 0.614 2.32 (1.61–3.37) < 0.0001 (RD) TC 0.149 0.329 2.15 (1.53–3.09) < 0.0001 (CD) CC 0.012 0.057 MAF 0.087 0.223 CI: confidence interval; GDM: gestational diabetes mellitus; MAF: minor allele frequency; OR: odds ratio; SNPs: single nucleotide polymorphisms. Analyses were performed in the rare dominant (RD) and in the co-dominant (CD) models after adjustment for age, pre-gestational body mass index and weight gain. In evaluating the association between haplotypes in the HTR2B gene and the presence of DMG, the selected SNPs were placed in the following order for analysis: rs10194776, rs765458, rs10187149 and rs17619600. The TACC haplotype, which contains the rare allele C of rs17619600, was associated with an increased risk of GDM, as shown in Table 3 (the total number of carriers of the haplotype was 83). Table 3 Frequency of the haplotype TACC in HTR2B according to the status of gestational diabetes mellitus. Without GDM With GDM OR (CI 95%) P- value N 443 453 TACC 60 (0.072) 99 (0.113) 1.70 (1.22–2.39) 0.001 Sequence of single nucleotide polymorphisms: rs10194776, rs765458, rs10187149 and rs17619600. Results expressed in absolute numbers (each carrier with two haplotypes) and relative frequency in the overall population. CI: confidence Interval; GDM: gestational diabetes mellitus; OR: odds ratio. The analysis of plasma glucose during the OGTT performed between 24–28 weeks of gestation, for diagnostic purpose, in 636 women with (n = 196) and without GDM (n = 440) showed that carriers of the XC genotype (rare dominant model) (n = 135) presented a significantly higher AUC compared to carriers of the TT genotype (n = 501) of rs17619600 (121.52 ± 29.69 versus 113.45 ± 24.76; P < 0.001) (Fig. 1 ). Discussion The main finding of the present study was that the presence of the rare allele C in the HTR2B rs17619600 SNP conferred an increased risk of GDM in the population evaluated. In addition to the analysis of isolated SNP, the TACC haplotype, which contains the aforementioned allele, was associated with a higher risk of GDM. HTR2B encodes a Gαq-coupled 5-HT receptor. 5-HT is believed to be critical in regulating pancreatic beta cell proliferation ( 7 , 9 ). In pregnant rodent islets, there is an increase in the expression of HTR2B during the period of increased beta cell replication; blocking the signaling of this receptor prevents the expansion of these cells and is associated with GDM ( 8 ). In human islets, the activation of this receptor is associated with GSIS ( 7 , 21 ). Thus, 5-HT signaling through HTR2B plays an important role in the maintenance of glycemic homeostasis during pregnancy ( 15 , 22 , 23 ). The only study that evaluated the SNP rs17619600 in HTR2B found no association with GDM. However, it was a case-control study which compared women with GDM with non-pregnant women, aged 60 and older with no personal and family history of DM. The study did not find any association of this SNP with weight gain during pregnancy, postpartum BMI, FPG, or fasting insulin concentration in women with GDM. Additionally, this variant did not associate with waist circumference and BMI in non-diabetic control subjects and in the independent population cohort from the Korean Genome Epidemiology Study, or with T2D in this same cohort ( 24 ). No functional studies were performed with rs17619600, but according to the GTEx Consortium atlas, this SNP has the potential to be functional, as it has a cis-expression quantitative trait loci (eQTL) effect, that is, it modulates gene expression by influencing its transcription rate ( 25 ). In 7 out of 9 tissues evaluated, the presence of the allele C was associated with a lower expression of the HTR2B gene. Given these findings, we hypothesized that SNP rs17619600 could modulate the expression of the HTR2B gene in beta cells. Thus, in presence of the rare allele C, there would be a lower expression of this receptor, which could impair maternal beta cell adaptation. The finding that carriers of the genotypes containing the allele C presented a higher AUC of plasma glucose during OGTT than carriers of the TT genotype corroborate that SNP rs17619600 influences glucose homeostasis, probably affecting insulin release, since activation of HTR2B promotes GSIS. This study has the limitation of having been carried out in a tertiary hospital, in which a significant number of patients have other comorbidities. The small number of patients who used insulin, only 84 participants, made it difficult to assess the association of SNPs with GDM severity. As GDM is a prevalent clinical condition, the lack of replication in an independent population and the sample size are also limitations of the study, although the present series is larger than those included in several previously published studies ( 26 – 30 ). Conclusion SNP rs17619600 in the HTR2B gene influences glucose homeostasis, probably modulating insulin release, and the presence of the minor allele C was associated with a higher risk of GDM. Abbreviations 5-HT- 5-hydroxytryptamine ADA- American Diabetes Association AUC- area under the curve BMI- body mass index CI- confidence interval DM- diabetes mellitus eQTL- expression quantitative trait loci FPG- fasting plasma glucose GAS- genetic association study GDM- gestational diabetes mellitus GSIS- glucose -stimulated insulin secretion HTR1-7- serotonin receptor subtypes 1-7 HWE- Hardy-Weinberg equilibrium IADPSG - International Association of Diabetes and Pregnancy Study Groups LMP- last menstrual period MAF- minor allele frequency OGTT- oral glucose tolerance test OR- odds ratio PL- placental lactogen PRLP- prolactin receptor RNA- ribonucleic acid SNP- single nucleotide polymorphisms T2D- type 2 diabetes mellitus Tph1- isoform 1 of tryptophan hydroxylase Tph2- isoform 2 of tryptophan hydroxylase Declarations Ethics approval and consent to participate The study was carried out in compliance with the Declaration of Helsinki. This project was submitted to the Committees for the analysis of research project (Discipline of Endocrinology and Metabology and Department of Obstetrics and Gynecology) at HCFMUSP and to the Ethics Committee of the Institution (CAPPesq document 777.904 of 09/03/2014). All participants signed an informed consent term. Consent for publication Not applicable. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding This study was funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Authors' contributions JRCZP, RPVF and MLCG: have made substantial contributions to the conception and design of the work. JRCZP, DPSB, AMC, AMSS, TAZ, RAC, RPVF and MLCG: have made substantial contributions to the acquisition, analysis, or interpretation of data for the work. JRCZP, DPSB, TAZ, RAC, MLCG and RPVF: Drafted the work or revised it critically for important intellectual content. All authors have agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Huang C, Snider F, Cross JC. Prolactin receptor is required for normal glucose homeostasis and modulation of beta-cell mass during pregnancy. Endocrinology. 2009;150(4):1618–26. Centers for Disease Control and Prevention 2019 [Available from: https://www.cdc.gov/diabetes/basics/gestational.html . Huhn EA, Massaro N, Streckeisen S, Manegold-Brauer G, Schoetzau A, Schulzke SM, et al. 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Association of Polymorphism rs17576 of the Metalloproteinase 9 Gene with Gestational Diabetes in Euro-Brazilian Pregnant Women. Clin Lab. 2018;64(4):645–9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 21 Jul, 2023 Read the published version in European Journal of Medical Research → Version 2 posted Editorial decision: Major revision 25 May, 2023 Reviews received at journal 10 Apr, 2023 Reviewers agreed at journal 27 Mar, 2023 Reviewers invited by journal 15 Nov, 2022 Editor assigned by journal 31 Oct, 2022 Submission checks completed at journal 14 Oct, 2022 First submitted to journal 13 Oct, 2022 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Article","associatedPublications":[],"authors":[{"id":152377691,"identity":"617b5860-af52-49fc-9383-26c37576b58e","order_by":0,"name":"Juliana Regina Chamlian Zucare Penno","email":"","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Juliana","middleName":"Regina Chamlian Zucare","lastName":"Penno","suffix":""},{"id":152377692,"identity":"e060de6f-41a4-410c-aed0-23d5213d4d21","order_by":1,"name":"Daniele Pereira Santos-Bezerra","email":"","orcid":"","institution":"Universidade de São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniele","middleName":"Pereira","lastName":"Santos-Bezerra","suffix":""},{"id":152377693,"identity":"6970c4e6-9547-4ddb-b1b9-3d9bee0b29d2","order_by":2,"name":"Ana Mercedes Cavaleiro","email":"","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Mercedes","lastName":"Cavaleiro","suffix":""},{"id":152377694,"identity":"230c468a-c8b3-4b7c-afbb-50c0a7181863","order_by":3,"name":"Ana Maria Silva Sousa","email":"","orcid":"","institution":"Universidade de São Paulo, Instituto Central – Hospital das Clínicas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Maria Silva","lastName":"Sousa","suffix":""},{"id":152377695,"identity":"91067515-ec81-4ba5-97d5-071e64ff1b8e","order_by":4,"name":"Tatiana Assunção Zaccara","email":"","orcid":"","institution":"Universidade de São Paulo, Instituto Central – Hospital das Clínicas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tatiana","middleName":"Assunção","lastName":"Zaccara","suffix":""},{"id":152377696,"identity":"084e0a85-6c5c-4e29-95a1-3af17a4b0745","order_by":5,"name":"Rafaela Alkmin Costa","email":"","orcid":"","institution":"Universidade de São Paulo, Instituto Central – Hospital das Clínicas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rafaela","middleName":"Alkmin","lastName":"Costa","suffix":""},{"id":152377697,"identity":"54667b87-67c5-4829-a1cf-6d48af4be5dc","order_by":6,"name":"Rossana Pulcineli Vieira Francisco","email":"","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rossana","middleName":"Pulcineli Vieira","lastName":"Francisco","suffix":""},{"id":152377698,"identity":"2ca5abdc-f941-434c-85ef-c28c32b00ffd","order_by":7,"name":"Maria Lucia Correa-Giannella","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYJCCA0DMA2Y9KGCQY2+AiCYQpyXBgMGY5wARWhAAqCWxh5AW3fazDw/8YKiV4Z/de/BBgoFdeo/YATbJnzsY8swbsGsxO5NucLCH4TiPxJ1zyQYJBsm5PdIJbNK8ZxiKZQ7g0HIgjeEAD8MxHoYbOWYSCQbMuftBWhjbGBJn4HCY2flnDAf/ALXI38gx/5FgUJ/OA9Qi+ROflhtpDId5GGp4DIC2AL1/OAGkRYIXr5ZnDIdlDA7wGN7IMQY67Lhhj3RiszXvGYliCZwOS2P++Kaizl7uRo7hhw8V1fI80skHb/7cYZOHSwsEGBxG5jE2ABF+DUBQh8YH6hoFo2AUjIJRAAMARzJXsGADGHYAAAAASUVORK5CYII=","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Lucia","lastName":"Correa-Giannella","suffix":""}],"badges":[],"createdAt":"2022-09-19 13:14:35","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-2081039/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-2081039/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40001-023-01211-6","type":"published","date":"2023-07-21T21:41:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":29152851,"identity":"91d65415-49e0-4128-9e59-ccfb10adbb4a","added_by":"auto","created_at":"2022-11-16 19:15:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142930,"visible":true,"origin":"","legend":"\u003cp\u003ePlasma glucose during oral glucose tolerance test (OGTT) according to genotypes of rs17619600 (rare dominant model). OGTT was performed between 24-28 weeks of gestation in 636 women with (n= 196) and without (n= 440) gestational diabetes mellitus. \u003cem\u003eP\u003c/em\u003evalue was adjusted for age at last menstrual period, previous body mass index, and weight gain during pregnancy.\u003c/p\u003e","description":"","filename":"figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2081039/v2/7ea35567d5dbcdcb0b6067c6.jpg"},{"id":44736148,"identity":"a2b9dbcd-0d7e-4039-b31e-2df1892d5874","added_by":"auto","created_at":"2023-10-16 22:29:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":392348,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2081039/v2/f3f906c4-932b-4960-883f-c0919c2c2c59.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Variant in a gene encoding a serotonin receptor increases the risk of gestational diabetes mellitus: a case control study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn order to maintain glycemic homeostasis during pregnancy, the increase in maternal insulin resistance is compensated by hyperplasia and increased function of maternal pancreatic beta cell. The failure of this compensatory mechanism is associated with GDM (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGDM occurs in 10\u0026ndash;18% of all pregnancies (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and it confers a higher risk of several pregnancy complications for both mother and newborn, such as cesarean delivery, polyhydramnios, preeclampsia, jaundice, macrosomia, and neonatal hypoglycemia. GDM is also considered a risk factor for type 2 diabetes mellitus (T2D), obesity and cardiovascular disease (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies conducted \u003cem\u003ein vitro\u003c/em\u003e and in rodent models have shown modified expression of many islet genes during pregnancy. Among the most significantly upregulated genes are the ones encoding the two isoforms of tryptophan hydroxylase (\u003cem\u003eTph1\u003c/em\u003e and \u003cem\u003eTph2\u003c/em\u003e), the rate-limiting enzyme of serotonin (5-hydroxytryptamine, 5-HT) synthesis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Βeta cells have the ability to synthesize, store and secrete 5-HT and islet 5-HT content increases during pregnancy (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), secondarily to stimulation of TPH1 and TPH2 expression in beta cells. This process is dependent on placental lactogen (PL) acting through prolactin receptors (PRLR) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e); thus, 5-HT acts downstream of PL signaling to drive beta cell expansion (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e5-HT receptors are classified into seven different families (HTR1\u0026ndash;7), some of which contain different subtypes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In pregnant mice, the HTR2B expression closely matched the period of increased beta cell proliferation (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and blocking HTR2B signaling impaired beta cell expansion, causing glucose intolerance (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMicroarray and RNA sequencing analyses revealed transcripts of almost all 5-HT receptors in human islets (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and an \u003cem\u003ein vitro\u003c/em\u003e study have shown that the activation of HTR2B promoted glucose-stimulated insulin secretion (GSIS) not only in mouse, but also in human beta cells, suggesting that 5-HT also stimulates insulin release through HTR2B (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the importance of the serotoninergic system for the adaptation of beta cells to the increased insulin demand during pregnancy, we hypothesized that genetic variants in the \u003cem\u003eHTR2B\u003c/em\u003e gene could influence the risk of developing GDM.\u003c/p\u003e"},{"header":"Participants And Methods","content":"\u003cp\u003eThis was a case-control study that initially recruited 1,130 pregnant women between September 2014 and September 2017; 90 refused to participate and 36 were considered ineligible for not meeting the inclusion criteria. Of the 1,004 pregnant women then recruited, 108 were lost to follow-up, resulting in a final number of 896. After a diagnostic evaluation for GDM, women were classified into two study groups: 453 pregnant women that had GDM diagnosis in the current pregnancy and 443 pregnant women without the diagnosis of GDM. All pregnant women were followed-up at the Obstetric Clinic of a tertiary university hospital. The study was carried out in compliance with the Declaration of Helsinki, in accordance with institutional ethics committees. After signing informed consent, participants were evaluated for clinical and biochemical characteristics.\u003c/p\u003e\n\u003cp\u003eClinical and biochemical variables were collected from the medical records. The weight gain during pregnancy was calculated as the difference between the weight (in kilograms) at the end of pregnancy and the weight at first consultation.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria for women without GDM were: no prior GDM or other metabolic conditions, normal fasting plasma glucose (FPG) in the first trimester and normal 75 g OGTT between 24- and 28-weeks gestational age. The inclusion criteria for women with GDM were: GDM diagnosis in the index pregnancy and no use of steroids before GDM diagnosis. GDM was defined by criteria proposed by the International Association of Diabetes and Pregnancy Study Groups (IADPSG), based on first trimester FPG\u0026thinsp;\u0026ge;\u0026thinsp;92 mg/dL (5.1 mmol/L) (n\u0026thinsp;=\u0026thinsp;257) or 2-h OGTT with 75 g of glucose performed between 24\u0026ndash;28 weeks of gestation with at least one altered value (FPG\u0026thinsp;\u0026ge;\u0026thinsp;92 mg [5.1 mmol/L], 1-h plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;180 mg/dL (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e) and 2-h plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;153 mg/dL [8.5 mmol/L]) (n\u0026thinsp;=\u0026thinsp;196). Women with GDM who failed to reach 30% of the glycemic targets (FPG\u0026thinsp;\u0026lt;\u0026thinsp;95 mg/dL, 1-h postprandial glucose\u0026thinsp;\u0026lt;\u0026thinsp;140 mg/dL), after dietary and lifestyle modifications, were administered insulin. A 2-h OGTT was performed in the GDM group at 6 to 12 weeks postpartum, and the American Diabetes Association (ADA) diagnostic criteria for diabetes mellitus (DM) (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e) were applied.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eSingle nucleotide polymorphisms genotyping\u003c/h2\u003e\n \u003cp\u003eDeoxyribonucleic acid extraction from peripheral blood leukocytes was carried out by a salting-out procedure (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e). Single nucleotide polymorphisms (SNPs) were genotyped by real-time polymerase chain reaction (StepOne Plus; Applied Biosystems, USA), using predesigned Human TaqMan Genotyping Assays 40X: C__2398885_30 (rs765458), C__30043265_10 (rs10187149), C__32997861_10 (rs17619600), C__27918443_10 (rs4973377), C__29863060_10 (rs10194776) (Thermo Fisher Scientific, Waltham, USA). The five Tag SNPs cover approximately 95% of the genetic variability of the extended region of \u003cem\u003eHTR2B\u003c/em\u003e gene and were selected using a pair wise approach, a r\u003csup\u003e2\u003c/sup\u003e \u0026ge; .8 and a minor allele frequency (MAF) of at least 0.1. The genotyping success rate was ~\u0026thinsp;99% for all SNPs. The SNP rs4973377 was not evaluated because only one genotype was found in the studied population. The Hardy\u0026ndash;Weinberg equilibrium (HWE) was tested; the distribution of genotypes was consistent with HWE for all remained SNPs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eContinuous variables are expressed as median and 25\u0026ndash;75% interquartile ranges, and categorical variables are expressed as number of cases and percentage of affected individuals. The Mann-Whitney test for independent samples was used to compare continuous variables between the studied groups while categorical variables were compared by Pearson\u0026apos;s \u0026chi;2 test, which was also used to compare the frequency of SNPs between the groups.\u003c/p\u003e\n \u003cp\u003eThe HWE was determined using the frequency of alleles in the Pearson\u0026apos;s \u0026chi;2 test at a significance level of 0.05. The SNPs were evaluated in the rare dominant model and in the codominant model. The magnitude of the risk conferred by the SNPs was estimated using odds ratio (OR) with a 95% confidence interval (CI). To estimate the OR adjusted for potential confounding factors (age at last menstrual period [LMP], previous body mass index [BMI], and weight gain during pregnancy), a binary logistic regression analysis was performed with these factors as covariates in the regression model. The correction for multiple comparisons due to the multiple SNPs tested was made by Bonferroni\u0026apos;s correction, dividing 0.05 by the number of studied SNPs in the \u003cem\u003eHTR2B\u003c/em\u003e gene. Thus, a P\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;0.01 (two-tailed) was considered significant.\u003c/p\u003e\n \u003cp\u003eThis study was exploratory in nature. Thus, a convenience sample was used, in which we sought to include as many participants as possible. The power calculation was performed \u003cem\u003ea posteriori\u003c/em\u003e using the \u003cem\u003eGAS Power Calculator\u003c/em\u003e (Genetic Association Study power calculator) (\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e). The power of the study was \u0026gt;\u0026thinsp;90% (100% and 99.7%, respectively) to detect associations of the SNP rs17619600 in the \u003cem\u003eHTR2B\u003c/em\u003e gene with GDM in the codominant model and in the rare dominant model.\u003c/p\u003e\n \u003cp\u003eHaplotype analysis was performed using the software available online SHEsis. All haplotypes with a frequency\u0026thinsp;\u0026lt;\u0026thinsp;0.03 were ignored for analysis. For the evaluation of the different combinations, Pearson\u0026apos;s \u0026chi;\u003csup\u003e2\u003c/sup\u003e test was used, with a value of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 being considered significant (\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe area under the curve (AUC) of plasma glucose during the OGTT was calculated using the trapezoidal method and the results were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. For comparison of the AUC of plasma glucose between genotypes, one-way ANOVA was used, adjusted for age at LMP, previous BMI, and weight gain during pregnancy.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe characteristics of the pregnant women with and without GDM are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCharacteristics of women with and without gestational diabetes mellitus.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWithout GDM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWith GDM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e443\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e453\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.1 (24.4\u0026ndash;33.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33.2 (28.8\u0026ndash;37.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWhite* (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-pregnancy BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.7 (21.8\u0026ndash;28.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.2 (24.8\u0026ndash;32.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePositive family history of T2D (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWeight gain during pregnancy (kg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.0 (8.7\u0026ndash;15.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.0 (5.0\u0026ndash;13.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePreeclampsia (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eArterial hypertension (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUse of medicines (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin treatment\u0026dagger; (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFasting plasma glucose (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78 (74\u0026ndash;82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e92 (83\u0026ndash;97)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCesarean delivery (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNewborn birth weight (g)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3,240 (2,897-3,542)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3,210 (2,780-3,512)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003eResults expressed as median and interquartile range, except for parity (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation); BMI: body mass index; GDM: gestational diabetes mellitus; T2D: type 2 diabetes mellitus. *Self-defined ethnicity. \u0026dagger; Only the participants with GDM needed insulin. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered significant. The missing data (percentage) for each reported variable is as follows: age (0.77%), ethnicity (8.7%), parity (1.2%), BMI (18.8%), family history (0%), weight gain (4.5%), preeclampsia (0.33%), arterial hypertension (1.2%), use of medicines (1.4%), insulin treatment (0.5%), fasting plasma glucose (5.5%), type of delivery (16.4%), newborn birth weight (16.7%).\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompared to the group without GDM, women with GDM were older, had a higher number of previous pregnancies, a higher pre-pregnancy BMI with a higher frequency of family history of T2D. Women with GDM had less weight gain during pregnancy, higher frequency of hypertension and use of medications, and higher FPG compared to women without GDM. Cesarean delivery was more frequent in women with GDM and the weight of newborns from women with GDM was lower than the weight of newborns from women without GDM. Among women with GDM, 18.7% used insulin.\u003c/p\u003e\n\u003cp\u003eThe SNPs rs10187149, rs10194776 and rs765458 did not associate with GDM (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The minor allele C of SNP rs17619600 conferred an increased risk for GDM in the codominant model (OR 2.15; 95% CI 1.53\u0026ndash;3.09;\u0026nbsp;\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and in the rare dominant model (OR 2.32; CI 1.61\u0026ndash;3.37;\u0026nbsp;\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The SNPs were not associated with insulin use, maternal weight gain, newborn birth weight or glycemic change in the postpartum OGTT (data not shown).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eGenotype frequencies of single nucleotide polymorphisms in \u003cem\u003eHTR2B\u003c/em\u003e according to status of gestational diabetes mellitus.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSNPs\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWithout GDM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWith GDM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR (CI 95%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eHTR2B\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e443\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e453\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers765458\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.239\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.90 (0.64\u0026ndash;1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.55 (RD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.542\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.518\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.02 (0.82\u0026ndash;1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.82 (CD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.210\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.243\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.481\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.502\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers10187149\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.324\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.338\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.509\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.498\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.94 (0.77\u0026ndash;1.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.70 (RD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.167\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.164\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.92 (0.74\u0026ndash;1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.46 (CD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.422\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.413\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers10194776\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.277\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.279\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.526\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.495\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.99 (0.79\u0026ndash;1.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.57 (RD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.197\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.226\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.96 (0.78\u0026ndash;1.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.74 (CD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.479\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.473\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers17619600\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.839\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.614\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.32 (1.61\u0026ndash;3.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001 (RD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.149\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.15 (1.53\u0026ndash;3.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.0001 (CD)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.087\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.223\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eCI: confidence interval; GDM: gestational diabetes mellitus; MAF: minor allele frequency; OR: odds ratio; SNPs: single nucleotide polymorphisms. Analyses were performed in the rare dominant (RD) and in the co-dominant (CD) models after adjustment for age, pre-gestational body mass index and weight gain.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn evaluating the association between haplotypes in the\u0026nbsp;\u003cem\u003eHTR2B\u003c/em\u003e\u0026nbsp;gene and the presence of DMG, the selected SNPs were placed in the following order for analysis: rs10194776, rs765458, rs10187149 and rs17619600. The TACC haplotype, which contains the rare allele C of rs17619600, was associated with an increased risk of GDM, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026nbsp;(the total number of carriers of the haplotype was 83).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eFrequency of the haplotype TACC in \u003cem\u003eHTR2B\u003c/em\u003e according to the status of gestational diabetes mellitus.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWithout GDM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWith GDM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR (CI 95%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e443\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e453\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTACC\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60 (0.072)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e99 (0.113)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.70 (1.22\u0026ndash;2.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eSequence of single nucleotide polymorphisms: rs10194776, rs765458, rs10187149 and rs17619600. Results expressed in absolute numbers (each carrier with two haplotypes) and relative frequency in the overall population. CI: confidence Interval; GDM: gestational diabetes mellitus; OR: odds ratio.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe analysis of plasma glucose during the OGTT performed between 24\u0026ndash;28 weeks of gestation, for diagnostic purpose, in 636 women with (n\u0026thinsp;=\u0026thinsp;196) and without GDM (n\u0026thinsp;=\u0026thinsp;440) showed that carriers of the XC genotype (rare dominant model) (n\u0026thinsp;=\u0026thinsp;135) presented a significantly higher AUC compared to carriers of the TT genotype (n\u0026thinsp;=\u0026thinsp;501) of rs17619600 (121.52 \u0026plusmn; 29.69\u0026nbsp;\u003cem\u003eversus\u003c/em\u003e\u0026nbsp;113.45 \u0026plusmn; 24.76;\u0026nbsp;\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main finding of the present study was that the presence of the rare allele C in the \u003cem\u003eHTR2B\u003c/em\u003e rs17619600 SNP conferred an increased risk of GDM in the population evaluated. In addition to the analysis of isolated SNP, the TACC haplotype, which contains the aforementioned allele, was associated with a higher risk of GDM.\u003c/p\u003e \u003cp\u003e \u003cem\u003eHTR2B\u003c/em\u003e encodes a Gαq-coupled 5-HT receptor. 5-HT is believed to be critical in regulating pancreatic beta cell proliferation (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In pregnant rodent islets, there is an increase in the expression of HTR2B during the period of increased beta cell replication; blocking the signaling of this receptor prevents the expansion of these cells and is associated with GDM (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In human islets, the activation of this receptor is associated with GSIS (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Thus, 5-HT signaling through HTR2B plays an important role in the maintenance of glycemic homeostasis during pregnancy (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe only study that evaluated the SNP rs17619600 in \u003cem\u003eHTR2B\u003c/em\u003e found no association with GDM. However, it was a case-control study which compared women with GDM with non-pregnant women, aged 60 and older with no personal and family history of DM. The study did not find any association of this SNP with weight gain during pregnancy, postpartum BMI, FPG, or fasting insulin concentration in women with GDM. Additionally, this variant did not associate with waist circumference and BMI in non-diabetic control subjects and in the independent population cohort from the Korean Genome Epidemiology Study, or with T2D in this same cohort (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNo functional studies were performed with rs17619600, but according to the GTEx Consortium atlas, this SNP has the potential to be functional, as it has a cis-expression quantitative trait loci (eQTL) effect, that is, it modulates gene expression by influencing its transcription rate (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In 7 out of 9 tissues evaluated, the presence of the allele C was associated with a lower expression of the \u003cem\u003eHTR2B\u003c/em\u003e gene.\u003c/p\u003e \u003cp\u003eGiven these findings, we hypothesized that SNP rs17619600 could modulate the expression of the \u003cem\u003eHTR2B\u003c/em\u003e gene in beta cells. Thus, in presence of the rare allele C, there would be a lower expression of this receptor, which could impair maternal beta cell adaptation. The finding that carriers of the genotypes containing the allele C presented a higher AUC of plasma glucose during OGTT than carriers of the TT genotype corroborate that SNP rs17619600 influences glucose homeostasis, probably affecting insulin release, since activation of HTR2B promotes GSIS.\u003c/p\u003e \u003cp\u003eThis study has the limitation of having been carried out in a tertiary hospital, in which a significant number of patients have other comorbidities. The small number of patients who used insulin, only 84 participants, made it difficult to assess the association of SNPs with GDM severity. As GDM is a prevalent clinical condition, the lack of replication in an independent population and the sample size are also limitations of the study, although the present series is larger than those included in several previously published studies (\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSNP rs17619600 in the \u003cem\u003eHTR2B\u003c/em\u003e gene influences glucose homeostasis, probably modulating insulin release, and the presence of the minor allele C was associated with a higher risk of GDM.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e5-HT- 5-hydroxytryptamine\u003c/p\u003e\n\u003cp\u003eADA- American Diabetes Association\u003c/p\u003e\n\u003cp\u003eAUC- area under the curve\u003c/p\u003e\n\u003cp\u003eBMI- body mass index\u003c/p\u003e\n\u003cp\u003eCI- confidence interval\u003c/p\u003e\n\u003cp\u003eDM- diabetes mellitus\u003c/p\u003e\n\u003cp\u003eeQTL- expression quantitative trait loci\u003c/p\u003e\n\u003cp\u003eFPG- fasting plasma glucose\u003c/p\u003e\n\u003cp\u003eGAS- genetic association study\u003c/p\u003e\n\u003cp\u003eGDM- gestational diabetes mellitus\u003c/p\u003e\n\u003cp\u003eGSIS- glucose -stimulated insulin secretion\u003c/p\u003e\n\u003cp\u003eHTR1-7- serotonin receptor subtypes 1-7\u003c/p\u003e\n\u003cp\u003eHWE- Hardy-Weinberg equilibrium\u003c/p\u003e\n\u003cp\u003eIADPSG - International Association of Diabetes and Pregnancy Study Groups\u003c/p\u003e\n\u003cp\u003eLMP- last menstrual period\u003c/p\u003e\n\u003cp\u003eMAF- minor allele frequency\u003c/p\u003e\n\u003cp\u003eOGTT- oral glucose tolerance test\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOR- odds ratio\u003c/p\u003e\n\u003cp\u003ePL- placental lactogen\u003c/p\u003e\n\u003cp\u003ePRLP- prolactin receptor\u003c/p\u003e\n\u003cp\u003eRNA- ribonucleic acid\u003c/p\u003e\n\u003cp\u003eSNP- single nucleotide polymorphisms\u003c/p\u003e\n\u003cp\u003eT2D- type 2 diabetes mellitus\u003c/p\u003e\n\u003cp\u003eTph1- isoform 1 of tryptophan hydroxylase\u003c/p\u003e\n\u003cp\u003eTph2- isoform 2 of tryptophan hydroxylase\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was carried out in compliance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eThis project was submitted to the Committees for the analysis of research project (Discipline of Endocrinology and Metabology and Department of Obstetrics and Gynecology) at HCFMUSP and to the Ethics Committee of the Institution (CAPPesq document 777.904 of 09/03/2014). All participants signed an informed consent term.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJRCZP, RPVF and MLCG: have made substantial contributions to the conception and design of the work.\u003c/p\u003e\n\u003cp\u003eJRCZP, DPSB, AMC, AMSS, TAZ, RAC, RPVF and MLCG: have made substantial contributions to the acquisition, analysis, or interpretation of data for the work.\u003c/p\u003e\n\u003cp\u003eJRCZP, DPSB, TAZ, RAC, MLCG and RPVF: Drafted the work or revised it critically for important intellectual content.\u003c/p\u003e\n\u003cp\u003eAll authors have agreed both to be personally accountable for the author\u0026apos;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHuang C, Snider F, Cross JC. Prolactin receptor is required for normal glucose homeostasis and modulation of beta-cell mass during pregnancy. Endocrinology. 2009;150(4):1618\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eCenters for Disease Control and Prevention\u003c/em\u003e 2019 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/diabetes/basics/gestational.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/diabetes/basics/gestational.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuhn EA, Massaro N, Streckeisen S, Manegold-Brauer G, Schoetzau A, Schulzke SM, et al. Fourfold increase in prevalence of gestational diabetes mellitus after adoption of the new International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. J Perinat Med. 2017;45(3):359\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown FM, Wyckoff J. 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Clin Lab. 2018;64(4):645\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HTR2B, Single nucleotide polymorphisms, Serotonin, Beta cell","lastPublishedDoi":"10.21203/rs.3.rs-2081039/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2081039/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGiven the importance of the serotoninergic system for the adaptation of beta cells to the increased insulin demand during pregnancy, we hypothesized that genetic variants (single nucleotide polymorphisms [SNPs]) in the \u003cem\u003eHTR2B\u003c/em\u003e gene could influence the risk of developing gestational diabetes mellitus (GDM).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was a case-control study. Five SNPs (rs4973377, rs765458, rs10187149, rs10194776, and s17619600) in \u003cem\u003eHTR2B\u003c/em\u003e were genotyped by real-time polymerase chain reaction in 453 women with GDM and in 443 pregnant women without GDM.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOnly the minor allele C of SNP rs17619600 conferred an increased risk for GDM in the codominant model (odds ratio [OR] 2.15; 95% confidence interval [CI] 1.53\u0026ndash;3.09; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and in the rare dominant model (OR 2.32; CI 1.61\u0026ndash;3.37; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). No associations were found between the SNPs and insulin use, maternal weight gain, newborn weight, or the result of postpartum oral glucose tolerance test (OGTT). In the overall population, carriers of the XC genotype (rare dominant model) presented a higher area under the curve (AUC) of plasma glucose during the OGTT, performed for diagnostic purposes, compared with carriers of the TT genotype of rs17619600.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSNP rs17619600 in the \u003cem\u003eHTR2B\u003c/em\u003e gene influences glucose homeostasis, probably affecting insulin release, and the presence of the minor allele C was associated with a higher risk of GDM.\u003c/p\u003e","manuscriptTitle":"Variant in a gene encoding a serotonin receptor increases the risk of gestational diabetes mellitus: a case control study","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2022-11-16 19:15:44","doi":"10.21203/rs.3.rs-2081039/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-05-25T15:48:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-04-10T19:04:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6fbd4f5d-3e5f-4384-89a9-564978cc16a8","date":"2023-03-27T14:37:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-11-15T19:36:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-10-31T15:18:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-10-14T11:47:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2022-10-13T14:31:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"80e44223-325d-4e5a-8360-6f79b5accd58","owner":[],"postedDate":"November 16th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T22:17:49+00:00","versionOfRecord":{"articleIdentity":"rs-2081039","link":"https://doi.org/10.1186/s40001-023-01211-6","journal":{"identity":"european-journal-of-medical-research","isVorOnly":false,"title":"European Journal of Medical Research"},"publishedOn":"2023-07-21 21:41:09","publishedOnDateReadable":"July 21st, 2023"},"versionCreatedAt":"2022-11-16 19:15:44","video":"","vorDoi":"10.1186/s40001-023-01211-6","vorDoiUrl":"https://doi.org/10.1186/s40001-023-01211-6","workflowStages":[]},"version":"v2","identity":"rs-2081039","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2081039","identity":"rs-2081039","version":["v2"]},"buildId":"wLkW0s4AflPzk-lpfg-fK","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}