Differential expression of circulating miRNAs in maternal plasma in pregnancies with fetal macrosomia

Ge,Qinyu; Zhu,Yanan; Li,Hailing; Tian,Fei; Xie,Xueying; Bai,Yunfei

doi:10.3892/ijmm.2014.1989

Differential expression of circulating miRNAs in maternal plasma in pregnancies with fetal macrosomia

Authors:
- Qinyu Ge
- Yanan Zhu
- Hailing Li
- Fei Tian
- Xueying Xie
- Yunfei Bai
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Affiliations: Key Laboratory for Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing 2100096, P.R. China, Department of Gynecology and Obstetrics, Zhongda Hospital, Southeast University, Nanjing 210009, P.R. China, State Key Laboratory of Bioelectronics, Southeast University, Nanjing 2100096, P.R. China
Published online on: October 31, 2014 https://doi.org/10.3892/ijmm.2014.1989
Pages: 81-91
Copyright: © Ge et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

Macrosomia is associated with problems at birth and has life-long health implications for the infant. The aim of this study was to profile the plasma microRNAs (miRNAs or miRs) and evaluate the potential of circulating miRNAs to predict fetal macrosomia. The expression levels of miRNAs in plasma samples obtained from pregnant women with fetal macrosomia and from women with normal pregnancies (controls) were analyzed using TaqMan Low-Density Arrays (TLDAs) followed by quantitative reverse transcription polymerase chain reaction (RT-qPCR) validation and analysis. The TLDA data revealed that 143 miRNAs were differentially expressed in the plasma samples from pregnant women with fetal macrosomia compared with the controls (43 upregulated and 100 downregulated miRNAs). Twelve of these miRNAs were selected for RT-qPCR analysis. Receiver operational characteristic (ROC) curve analysis indicated that several miRNAs (e.g., miR‑141-3p and miR-200c-3p) were clearly distinguished between pregnancies with fetal macrosomia and other types of abnormal pregnancy and healthy pregnancies with high sensitivity and specificity (AUC >0.9). The expression of miRNA clusters also showed a similar trend in pregnancies with fetal macrosomia. This study provides a platform for profiling circulating miRNAs in maternal plasma. Our data also suggest that altered levels of maternal plasma miRNAs have great potential to serve as non-invasive biomarkers and as a mechanistic indicator of abnormal pregnancies.

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1	Boulet SL, Alexander GR, Salihu HM and Pass M: Macrosomic births in the united states: determinants, outcomes, and proposed grades of risk. Am J Obstet Gynecol. 188:1372–1378. 2003. View Article : Google Scholar : PubMed/NCBI
2	Henriksen T: The macrosomic fetus: a challenge in current obstetrics. Acta Obstet Gynecol Scand. 87:134–145. 2008. View Article : Google Scholar : PubMed/NCBI
3	Schwartz R and Teramo KA: What is the significance of macrosomia? Diabetes Care. 22:1201–1205. 1999. View Article : Google Scholar : PubMed/NCBI
4	Haram K, Pirhonen J and Bergsjø P: Suspected big baby: a difficult clinical problem in obstetrics. Acta Obstet Gynecol Scand. 81:185–194. 2002. View Article : Google Scholar : PubMed/NCBI
5	Ehrenberg HM, Mercer BM and Catalano PM: The influence of obesity and diabetes on the prevalence of macrosomia. Am J Obstet Gynecol. 191:964–968. 2004. View Article : Google Scholar : PubMed/NCBI
6	Jang HC, Cho NH, Min YK, Han IK, Jung KB and Metzger BE: Increased macrosomia and perinatal morbidity independent of maternal obesity and advanced age in Korean women with GDM. Diabetes Care. 20:1582–1588. 1997. View Article : Google Scholar : PubMed/NCBI
7	Yu Z, Sun JQ, Haas JD, Gu Y, Li Z and Lin X: Macrosomia is associated with high weight-for-height in children aged 1–3 years in Shanghai. China. Int J Obes (Lond). 32:55–60. 2008. View Article : Google Scholar
8	Segregur J, Buković D, Milinović D, et al: Fetal macrosomia in pregnant women with gestational diabetes. Coll Antropol. 33:1121–1127. 2009.
9	Suhonen L, Hiilesmaa V, Kaaja R and Teramo K: Detection of pregnancies with high risk of fetal macrosomia among women with gestational diabetes mellitus. Acta Obstet Gynecol Scand. 87:940–945. 2008. View Article : Google Scholar : PubMed/NCBI
10	Vohr BR and Boney CM: Gestational diabetes: the forerunner for the development of maternal and childhood obesity and metabolic syndrome? J Matern Fetal Neonatal Med. 21:149–157. 2008. View Article : Google Scholar : PubMed/NCBI
11	Ornoy A: Prenatal origin of obesity and their complications: Gestational diabetes, maternal overweight and the paradoxical effects of fetal growth restriction and macrosomia. Reprod Toxicol. 32:205–212. 2011. View Article : Google Scholar : PubMed/NCBI
12	Van Assche FA, Holemans K and Aerts L: Long-term consequences for offspring of diabetes during pregnancy. Br Med Bull. 60:173–182. 2001. View Article : Google Scholar
13	Kim YS, Yoon YJ, Jatoi I and Kim Y: Fetal macrosomia in experimental maternal diabetes. Am J Obstet Gynecol. 139:27–32. 1981.PubMed/NCBI
14	Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 116:281–297. 2004. View Article : Google Scholar : PubMed/NCBI
15	Mattick JS and Makunin IV: Non-coding RNA. Hum Mol Genet. 15(Spec 1): R17–R29. 2006. View Article : Google Scholar : PubMed/NCBI
16	Mitchell PS, Parkin RK, Kroh EM, et al: Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 105:10513–10518. 2008. View Article : Google Scholar : PubMed/NCBI
17	Reid G, Kirschner MB and van Zandwijk N: Circulating microRNAs: Association with disease and potential use as biomarkers. Crit Rev Oncol Hematol. 80:193–208. 2011. View Article : Google Scholar
18	Tan KS, Armugam A, Sepramaniam S, et al: Expression profile of microRNAs in young stroke patients. PLoS One. 4:e76892009. View Article : Google Scholar : PubMed/NCBI
19	Zampetaki A, Willeit P, Drozdov I, Kiechl S and Mayr M: Profiling of circulating microRNAs: from single biomarkers to re-wired networks. Cardiovasc Res. 93:555–562. 2012. View Article : Google Scholar :
20	Wang G, Tam LS, Li EK, et al: Serum and urinary free microRNA level in patients with systemic lupus erythematosus. Lupus. 20:493–500. 2011. View Article : Google Scholar : PubMed/NCBI
21	Corsten MF, Dennert R, Jochems S, et al: Circulating microRNA-208b and microRNA-499 reflect myocardial damage in cardiovascular disease. Circ Cardiovasc Genet. 3:499–506. 2010. View Article : Google Scholar : PubMed/NCBI
22	Ng EK, Tsang WP, Ng SS, et al: MicroRNA-143 targets DNA methyltransferases 3A in colorectal cancer. Br J Cancer. 101:699–706. 2009. View Article : Google Scholar : PubMed/NCBI
23	Huang Z, Huang D, Ni S, Peng Z, Sheng W and Du X: Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. Int J Cancer. 127:118–126. 2010. View Article : Google Scholar
24	Chen X, Ba Y, Ma L, et al: Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 18:997–1006. 2008. View Article : Google Scholar : PubMed/NCBI
25	Ng EK, Tsui NB, Lau TK, Leung TN, Chiu RW, Panesar NS, Lit LC, Chan KW and Lo YM: mRNA of placental origin is readily detectable in maternal plasma. Proc Natl Acad Sci USA. 100:4748–4753. 2003. View Article : Google Scholar : PubMed/NCBI
26	Fanson BG, Osmack P and Di Bisceglie AM: A comparison between the phenol-chloroform method of RNA extraction and the QIAamp viral RNA kit in the extraction of hepatitis C and GB virus-C/hepatitis G viral RNA from serum. J Virol Methods. 89:23–27. 2000. View Article : Google Scholar : PubMed/NCBI
27	Liu J, Leng J, Tang C, Liu G, Hay J, Wang J, Wen S, Li Z and She Y: Maternal glucose level and body mass index measured at gestational diabetes mellitus screening and the risk of macrosomia: results from a perinatal cohort study. BMJ Open. 4:e0045382014. View Article : Google Scholar : PubMed/NCBI
28	Prats-Puig A, Ortega FJ, Mercader JM, et al: Changes in circulating microRNAs are associated with childhood obesity. J Clin Endocrinol Metab. 98:E1655–E1660. 2013. View Article : Google Scholar : PubMed/NCBI
29	Ortega FJ, Mercader JM, Catalán V, et al: Targeting the circulating microRNA signature of obesity. Clin Chem. 59:781–792. 2013. View Article : Google Scholar : PubMed/NCBI
30	Jordan SD, Krüger M, Willmes DM, et al: Obesity-induced overexpression of miRNA-143 inhibits insulin-stimulated AKT activation and impairs glucose metabolism. Nat Cell Biol. 13:434–446. 2011. View Article : Google Scholar : PubMed/NCBI
31	Fu T, Choi SE, Kim DH, et al: Aberrantly elevated microRNA-34a in obesity attenuates hepatic responses to FGF19 by targeting a membrane coreceptor β-Klotho. Proc Natl Acad Sci USA. 109:16137–16142. 2012. View Article : Google Scholar
32	Yang Q, Lu J, Wang S, Li H, Ge Q and Lu Z: Application of next-generation sequencing technology to profile the circulating microRNAs in the serum of preeclampsia versus normal pregnant women. Clin Chim Acta. 412:2167–2173. 2011. View Article : Google Scholar : PubMed/NCBI
33	Davoren PA, McNeill RE, Lowery AJ, Kerin MJ and Miller N: Identification of suitable endogenous control genes for microRNA gene expression analysis in human breast cancer. BMC Mol Biol. 9:762008. View Article : Google Scholar : PubMed/NCBI
34	Xie T, Liang J, Guo R, Liu N, Noble PW and Jiang D: Comprehensive microRNA analysis in bleomycin-induced pulmonary fibrosis identifies multiple sites of molecular regulation. Physiol Genomics. 43:479–487. 2011. View Article : Google Scholar : PubMed/NCBI
35	Cortez MA, Welsh JW and Calin GA: Circulating microRNAs as noninvasive biomarkers in breast cancer. Recent Results Cancer Res. 195:151–161. 2012. View Article : Google Scholar : PubMed/NCBI
36	Bianchi F, Nicassio F, Marzi M, et al: A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer. EMBO Mol Med. 3:495–503. 2011. View Article : Google Scholar : PubMed/NCBI
37	Chen X, Hu Z, Wang W, et al: Identification of ten serum microRNAs from a genome-wide serum microRNA expression profile as novel noninvasive biomarkers for nonsmall cell lung cancer diagnosis. Int J Cancer. 130:1620–1628. 2012. View Article : Google Scholar
38	Zhang Y, Zhang R and Su B: Diversity and evolution of microRNA gene clusters. Sci China C Life Sci. 52:261–266. 2009. View Article : Google Scholar : PubMed/NCBI
39	Kim VN and Nam JW: Genomics of microRNA. Trends Genet. 22:165–173. 2006. View Article : Google Scholar : PubMed/NCBI
40	Xu J and Wong C: A computational screen for mouse signaling pathways targeted by microRNA clusters. RNA. 14:1276–1283. 2008. View Article : Google Scholar : PubMed/NCBI
41	Baskerville S and Bartel DP: Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA. 11:241–247. 2005. View Article : Google Scholar : PubMed/NCBI
42	Hsu SD, Lin FM, Wu WY, et al: miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic Acids Res. 39:D163–D169. 2011. View Article : Google Scholar