Relationship between melatonin receptor 1B and insulin receptor ...

OPEN SUBJECT AREAS: ENDOCRINE REPRODUCTIVE DISORDERS ENDOCRINE SYSTEM AND METABOLIC DISEASES

Received 29 May 2014 Accepted 16 July 2014

Relationship between melatonin receptor 1B and insulin receptor substrate 1 polymorphisms with gestational diabetes mellitus: a systematic review and meta-analysis Yan Zhang1*, Cheng-Ming Sun2*, Xiang-Qin Hu3 & Yue Zhao1 1

Published 22 August 2014

Correspondence and requests for materials should be addressed to Y.Z. (yuezhao_1@ 163.com)

* These authors contributed equally to this work.

School of Nursing, Tianjin Medical University, Tianjin, 300070, P.R., China, 2Department of Clinical Laboratory, Yuhuangding Hospital, Yantai, 264000, P.R., China, 3Tianjin Central Hospital of Gynecology and Obstetrics, Tianjin, 300100, P.R., China.

Studies have investigated the relationship between genetic variants and risk of gestational diabetes mellitus (GDM). However, the results remain inconclusive. The aim of this study was to investigate the association of rs10830963 and rs1387153 variants in melatonin receptor 1B (MTNR1B) and rs1801278 variant in insulin receptor substrate 1 (IRS1) with GDM susceptibility. Electronic database of PubMed, Medline, Embase, and CNKI (China National Knowledge Infrastructure) were searched for relevant studies between 2005 and 2014. The odds ratio (OR) with its 95% confidence interval (CI) were employed to estimate the association. Total ten case-control studies, including 3428 GDM cases and 4637 healthy controls, met the inclusion criteria. Our results showed a significant association between the three genetic variants and GDM risk, rs10830963 with a P-value less than 0.0001, rs1387153 with a P-value of 0.0002, and rs1801278 with a P-value of 0.001. Furthermore, all the genetic models in these three polymorphisms were associated with increased risks of GDM as well (P,50.009). In conclusion, our study found that the genetic polymorphisms rs10830963 and rs1387153 in MTNR1B and rs1801278 in IRS1 were associated with an increased risk of developing GDM. However, further studies with gene-gene and gene-environmental interactions should be considered.

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estational diabetes mellitus (GDM), defined as glucose intolerance with onset or first recognition during pregnancy, is one of the most common medical problems and a growing public health concern1,2. It causes by an increase in the insulin resistance, and the condition is also aggravated by insulin secretion from the b cells of the pancreas3. GDM affects 1–14% of all pregnant women depending on the population studied4: it complicates about 1–3% of all pregnancies in the western world5, whereas 5–10% among Asian women6. GDM is often more common in populations with a high frequency of type 2 diabetes (T2D)7. Furthermore, it increases risk of adverse pregnancy outcomes and has substantial long-term adverse health impacts on both mothers and their offspring. Though the WHO current guidelines for GDM were published in 1999 and are widely used worldwide8, to date, there is still no universal recommendation for the ideal approach for screening and diagnosis of GDM. Thus, identifying patients at a higher risk of GDM has become an important goal. Recently, extraordinary progress was made in identifying susceptible genes of complicated diseases through genome-wide association strategy9,10. Melatonin receptor 1B (MTNR1B) and insulin receptor substrate 1 (IRS1) were two of diabetogenic genes associated with the developing of GDM. Melatonin is a circulating hormone secreted mainly from the pineal gland11, and acts mostly through G-protein-coupled plasma membrane receptors12. MTNR1B, located on human chromosome 11q21–2213, is a member of the G-protein-coupled receptor family, and one of the functional and high-affinity melatonin membrane receptors14. MTNR1B is expressed in human and rodent pancreatic islets. Studies have shown that MTNR1B is a novel candidate gene for T2D15. Variants rs10830963 (C/G) and rs1387153 (C/T) in MTNR1B have been shown with an increased risk of developing T2D16. They may have a possible link in the etiology and pathophysiology of GDM. IRS1 gene, SCIENTIFIC REPORTS | 4 : 6113 | DOI: 10.1038/srep06113

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Figure 1 | Flow chart of literature screening.

located on chromosome 2q3617, is expressed in insulin-sensitive tissues. It is an endogenous substrate of the insulin receptor18, and plays a crucial role in the insulin signaling pathway. The IRS1 gene variant rs1801278, a nucleotide T/C substitution in codon 972 (Gly972Arg), has been identified to be associated with increased risk of T2D and GDM19. Although numerous studies have demonstrated the association between genetic polymorphisms and the developing of GDM, inconsistent results were presented for each polymorphism among study populations. The purpose of this meta-analysis is to summarize the existing evidence on the prevalence of the genetic polymorphisms in patients diagnosed with GDM.

ultimately included in the systematic review and meta-analysis. The study selection process is shown in Figure 1. All the 10 reports, one in Chinese20 and nine in English21–29, included cases and controls from 7 countries concerning 3 genetic variants in 2 genes (MTNR1B and IRS1). The detailed characteristics of the studies included were shown in Table 1. The distributions of genotypes and alleles in the individual studies were presented in Table 2. Association between MTNR1B rs10830963 variant and GDM. For MTNR1B rs10830963 variant, five studies, containing 2122 GDM cases and 2664 healthy controls, were included. The results of each allele and genetic models in this meta-analysis were listed in Table S1. The heterogeneity between studies was assessed, and the fixed-effects model and the random-effects model were employed for calculating the pooled odds ratio (OR). Overall, this meta-analysis showed that the frequency of MTNR1B rs10830963 G allele is higher in GDM patients than that in the healthy controls (48.4% vs. 42.3%), and

Results Study selection and characteristics. The electronic database search identified 107 references. After applying the inclusion criteria, 10 articles including 3428 GDM cases and 4637 healthy controls were Table 1 | Main characteristics of studies included in this meta-analysis First author’s Last name

Mean age Year

Total

BMI Controls

Case/Control

Genotype method

OGTT confirmed OGTT confirmed OGTT confirmed ADA criteria OGTT and IADPSG

Normal glucose tolerant Normal glucose tolerant Normal glucose tolerant Normal glucose tolerant Normal glucose tolerant

23.6/21.5 23.32/21.40 21.72/21.48 25.83/26.76 25.34/24.69

Sequencing TaqMan TaqMan PCR-RFLP PCR-RFLP

EASD-DPSG criteria OGTT confirmed NDDG criteria Fourth IWCGDM criteria 300 OGTT confirmed

Normal glucose tolerant Normal glucose tolerant Normal glucose tolerant Normal glucose tolerant

24.5/23.1 23.4/22.8 25.1/24.7 26/24

TaqMan PCR-RFLP PCR-RFLP PCR-RFLP

Normal glucose tolerant

34.4/33.3

PCR-RFLP

Country Case/Control Cases Controls

MTNR1B Deng Kim Wang Vlassi Li IRS1 Shaat Fallucca Tok Pappa

2011 China 2011 Korea 2011 China 2012 Greece 2013 China

31.8/29.7 33.1/32.2 32/30 35.4/31.3 32.4/31.9

87 928 725 77 350

91 990 1039 98 480

2005 Sweden 2006 Italy 2006 Turkey 2011 Greece

32.2/30.5 34.1/32.7 32.5/26.6

587 309 62 148

1189 277 100 107

Alharbi

2014

32.4/31.3

200

Saudi

Definition Cases

OGTT, the oral glucose tolerance test; ADA, the American Diabetes Association; IADPSG, the International Association of Diabetes in Pregnancy Study Groups; EASD-DPSG, the European Association for the Study of Diabetes-Diabetic Pregnancy Study Group; IWCGDM, International Workshop-Conferences on Gestational Diabetes Mellitus.

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Table 2 | Distribution of genotypes and alleles in the individual studies First author’s last name MTNR1B rs10830963 (C/G) Deng Kim Wang Vlassi Li MTNR1B rs1387153 (C/T) Kim Vlassi IRS1 rs1801278 (C/T) Shaat Fallucca Tok Pappa Alharbi

Cases GG 26 256 137 16 79 TT 241 12 TT 4 4 0 17 1

GC 38 435 364 31 158 TC 433 26 TC 49 34 9 73 10

CC 23 217 199 30 113 CC 235 39 CC 534 271 53 58 189

demonstrated a statistically significant positive association between the risk factor G allele carriers and GDM susceptibility [OR51.24, 95% confidence interval (CI)51.14–1.35, P,0.00001)], as shown in Figure 2. This significant association was found in other genetic models as well in a fixed-effects model (GG vs. CC: OR51.53, 95% CI51.30–1.80, P,0.00001; GG1GC vs. CC: OR51.30, 95% CI51.14–1.47, P,0.0001; GG vs. GC1CC: OR51.37, 95% CI51.19–1.57, P,0.0001). As shown in Figure 3. Association between MTNR1B rs1387153 variant and GDM. Two studies including 986 cases and 1070 controls focused on the relationship between rs1387153 variant and GDM. The frequency of the T allele was higher in GDM cases than that in controls (48.9% vs. 43.0%). As shown in Figure 4, our result demonstrated that the T allele had a positive relationship between rs1387153 variant and GDM risk (OR51.26, 95% CI51.12–1.43, P50.0002). Various genetic models also demonstrated that the T allele was associated with an increased risk of GDM (TT vs. CC: OR51.56, 95% CI51.23– 1.99, P50.0003; TT1TC vs. CC: OR51.33, 95% CI51.10–1.61, P50.003; TT vs. TC1CC: OR51.36, 95% CI51.11–1.68, P50.003) (Figure 5). No significant heterogeneity was found between these two studies (I250%). Association between IRS1 rs1801278 variant and GDM. The association between rs1801278 and GDM has been examined in five studies, including 1306 GDM cases and 1973 controls. Our meta-analysis of these studies showed that the frequency of the T allele of rs1801278 was higher in GDM than that in controls (8.7% vs. 5.1%), and indicated a significant association with an increased risk of GDM (OR51.42, 95% CI51.15–1.75, P50.001) (Figure 6). As shown in Figure 7 and Figure S1, the dominant model and recessive model were also significant with GDM susceptibility,

Controls G 90 947 638 63 316 T 915 50 T 57 42 9 107 12

C 84 869 762 91 384 C 903 104 C 1117 576 115 189 388

GG 15 203 191 12 75 TT 204 11 TT 0 0 0 7 0

GC 45 469 509 30 233 TC 455 35 TC 111 22 11 40 5

CC 31 294 329 56 172 CC 313 52 CC 1078 255 89 60 295

G 75 875 891 54 383 T 863 57 T 111 22 11 54 5

C 107 1057 1167 142 577 C 1081 139 C 2267 532 189 160 595

respectively (TT1TC vs. CC: OR51.54, 95% CI51.02–2.32, P50.04; TT vs. TC1CC: OR53.01, 95% CI51.38–6.56, P50.006). Sensitivity analysis and publication bias. The influence of each study on the overall meta-analysis estimate was assessed by eliminating one study at a time, respectively. The OR was not significantly influenced by omitting any single study. Begger’s funnel plot was used to identify individual studies in relation to their respective standard deviation, as shown in Figure 8 and Figure S2, which revealed no evidence of asymmetry. Egger’s test was employed to provide further statistical evidence, similarly, no significant publication bias was found for all these three polymorphisms (P50.263 for MTNR1B rs10830963, P50.378 for MTNR1B rs1387153, P50.149 for IRS1 rs1801278). Thus, there does not appear to be a publication bias risk in the meta-analysis.

Discussion GDM is usually recognized as a temporary form of diabetes that occurs during pregnancy, and is associated with an increased risk of complications during pregnancy and birth30. Women with GDM are at a high risk of developing T2D later in life31, and the risk of developing type 1 diabetes (T1D) is also increased32. Moreover, GDM increases the risk of macrosomia and caesarean delivery33. Therefore, there is an urgent need to study the pathogenesis and establish diagnosis criteria for GDM. Many studies have shown that gene polymorphisms could provide insight into underlying pathogenetic mechanisms and the relationship between candidate genes and complex diseases. Functional studies showed that those diabetogenic genes took part in many steps of the process of developing GDM. For instance, impaired b-cell function (MTNR1B), insulin resistance (IRS1), and abnormal utilization of glucose. In our meta-analysis, we found that the frequency

Figure 2 | Forest plot on the association for allelic model (G vs. C) of MTNR1B rs10830963 and risk of GDM in a fixed-effects model. SCIENTIFIC REPORTS | 4 : 6113 | DOI: 10.1038/srep06113

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Figure 3 | Forest plot on the association for the dominant model (GG1GC vs. CC) of MTNR1B rs10830963 and GDM in a fixed-effects model.

Figure 4 | Forest plot on the association for allelic model (T vs. C) of MTNR1B rs1387153 and GDM risk in a fixed-effects model.

of G allele in rs10830963, and T alleles in both rs1387153 and rs1801278 respectively, were higher in GDM cases than that in healthy controls, demonstrating strong statistical association with an increased risk of GDM. GDM is associated with both insulin resistance and an impaired insulin secretion34. GDM could develop when a genetic predisposition of pancreatic islet b-cell impairment is unmasked by an increased insulin resistance during pregnancy35. MTNR1B variants are related to insulin secretion and impaired b-cell function. Liao et al. have showed that MTNR1B is likely to be involved in the regulation of glucose homeostasis during pregnancy36. MTNR1B rs10830963 has been shown to influence the fasting plasma glucose (FPG)37 and to be associated with T2D38; rs1387153 has been reported to be associated with an increased FPG and a higher risk of T2D39. In our study, we found that the SNPs rs1387153 and rs10830963 in MTNR1B occur more frequently in women with GDM than in normal pregnant women, supporting a potential association of these polymorphisms with an increased risk of developing GDM. This may due to the observation that MTNR1B down-regulates GCK expression and glucose-stimulated insulin secretion by lowering intracellular cAMP level40. An increased expression of MTNR1B on b-cells leads to impaired insulin secretion. Previous studies have shown that the G allele of rs10830963 polymorphism in the MTNR1B exhibits a higher expression of this melatonin receptor on the b-cell as compared with that of the C allele41.

IRS1, a substrate of the insulin receptor tyrosine kinase and a participant in insulin signaling42, is related to insulin resistance. It plays a crucial role in the signal transduction pathway43. Epidemiological studies confirmed that the prevalence of GDM is in direct proportion to the prevalence of T2D. A meta-analysis conducted by Jellema et al. has shown that carriers of the R972 variant of the IRS1 gene are at a 25% increased risk of having T2D compared with non-carriers44. While Morini et al. investigating 32 studies found that the relatively infrequent R972 variant was not significantly associated with T2D45. Our result showed a significant association between IRS1 rs1801278 polymorphism and GDM risk. IRS1 protein is expressed in many insulin-sensitive tissues, and its tyrosine phosphorylation can elicit the downstream effects of insulin, such as activation of phosphatidylinositol 3-kinase (PI3K) and translocation of glucose transporter 446. Previous studies have shown that the IRS1 G972R polymorphism, which reduces insulin content and impairs insulin secretion in isolated human islets, is associated with impaired b-cell function29. Evidence suggests that susceptibility to GDM has a genetic component, family studies indicate that GDM aggregates within families and is associated with a history of T2D47. Several limitations were presented in this meta-analysis. Firstly, the number of studies included was relatively small. For MTNR1B rs1387153 variant, only two studies were included. Secondly, studies were mainly focused on Asian populations or Caucasian populations, other populations should also be included. Thirdly, these poly-

Figure 5 | Forest plot on the association for the dominant model (TT1TC vs. CC) of MTNR1B rs1387153 and GDM in a fixed-effects model. SCIENTIFIC REPORTS | 4 : 6113 | DOI: 10.1038/srep06113

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Figure 6 | Forest plot on the association for allelic model (T vs. C) of IRS1 rs1801278 and GDM risk in a fixed-effects model.

Figure 7 | Forest plot on the association for the dominant model (TT1TC vs. CC) of IRS1 rs1801278 and GDM in a random-effects model.

morphisms may interact with other risk factors which should be considered. Fourthly, the selected studies could be more subject to bias and artifact than prospective studies. In conclusion, our meta-analysis demonstrated that genetic polymorphisms rs10830963 and rs1387153 in MTNR1B and rs1801278 in IRS1 were associated with an increased risk of developing GDM. However, further studies with large sample sizes and accounting for the interaction of genetic and environmental risk factors are needed

to understand associations between the genetic polymorphisms and risk of GDM.

Methods Identification and eligibility of relevant studies. A comprehensive literature search was conducted for relevant articles published between January 2005 and March 2014 using the electronic database of PubMed, Medline, Embase, Wanfang and CNKI (China National Knowledge Infrastructure). We retrieved the related articles using

Figure 8 | Funnel plot on the association for allelic model (G vs. C) of MTNR1B rs10830963 and risk of GDM in a fixed-effects model (P50.263 for Egger’s test). SCIENTIFIC REPORTS | 4 : 6113 | DOI: 10.1038/srep06113

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www.nature.com/scientificreports the following terms: ‘‘gestational diabetes mellitus’’, ‘‘melatonin receptor 1B or MTNR 1B’’, ‘‘insulin receptor substrate 1 or IRS1’’, ‘‘polymorphisms or variants’’ as well as their combinations. The corresponding Chinese terms were used in the Chinese library. References of retrieved articles were searched with no language restrictions. The search was focused on studies that had been conducted in humans. Only full-text articles and the most recent studies were included in this meta-analysis. Criteria for inclusion. The inclusion criteria were as follows: 1) the paper should be case-control or cohort studies; 2) identification of gestational diabetes mellitus cases was confirmed pathologically and the controls should be non-diabetic; 3) each study included at least one of the three polymorphisms, rs10830963 and rs1387153 in MTNR1B, rs1801278 in IRS1; 4) genotype distribution information and OR with its 95% CI were available; and 5) genotype distribution of control for a certain polymorphism must be in Hardy-Weinberg equilibrium. Data extraction. Two investigators independently assessed the quality of the included studies according to the descriptions provided by the authors of the included studies. Any disagreement was subsequently resolved by discussion with a third author. The following information was extracted from each article: first author, year of publication, country, ethnicity, mean age, body mass index (BMI), total numbers, definition and genotype distributions in GDM cases and controls. Statistical analysis. The overall association between genetic polymorphisms and GDM risk was measured by OR and its 95% CI. The Z test was employed to determine the significance of the pooled ORs, and a P value less than 0.05 was considered statistically significant. For rs10830963, the allelic model (G vs. C) and genotype genetic models (co-dominant effects: GG vs. CC; dominant effect: GG1GC vs. CC; and recessive effect: GG vs. GC1CC) were examined; for rs1387153 and rs1801278, the allelic model (T vs. C) and genotype genetic models (co-dominant effects: TT vs. CC; dominant effect: TT1TC vs. CC; and recessive effect: TT vs. TC1CC) was identified. The I2 test was used to assess the proportion of statistical heterogeneity and the Q-statistic test was used to define the degree of heterogeneity. A P-value less than 0.10 for the Q-test and I2 more than 50% was considered significant among the studies. Data were combined using both a fixed-effects model (the inverse varianceweighted method) and a random-effects model (DerSimonian and Laird method)48,49. The fixed-effects model is used when the effects are assumed to be homogenous, while the random-effects model is used when they are heterogenous. The evidence of publication bias was assessed by visual funnel plot inspection. Egger’s regression test was also conducted to identify study effects (P-value less than 0.10 was considered significant). To evaluate whether our results were influenced by the presence of any individual study, we conducted a sensitivity analysis by systematically removing each study and reassessing the significance of the result. 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Acknowledgments This study was supported by the Scientific Research Program of the Health Department of Tianjin, China (grant No. 2013KZ085).


Author contributions Conceived and designed the study: Y.Z., C.M.S., X.Q. and Y.Z.; Performed the experiments: Y.Z., C.M.S., X.Q. and Y.Z.; Statistical analyses and paper writing: Y.Z., C.M.S., X.Q. and Y.Z.

Additional information Supplementary information accompanies this paper at http://www.nature.com/ scientificreports Competing financial interests: The authors declare no competing financial interests. How to cite this article: Zhang, Y., Sun, C.-M., Hu, X.-Q. & Zhao, Y. Relationship between melatonin receptor 1B and insulin receptor substrate 1 polymorphisms with gestational diabetes mellitus: a systematic review and meta-analysis. Sci. Rep. 4, 6113; DOI:10.1038/ srep06113 (2014). This work is licensed under a Creative Commons Attribution-NonCommercialNoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http:// creativecommons.org/licenses/by-nc-nd/4.0/

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