title: Profiling maternal plasma microRNA expression in early pregnancy to predict gestational diabetes mellitus.
abstract: OBJECTIVE
  To profile the differential expression of plasma miRNAs in gestational diabetes mellitus (GDM).
  
  
  METHODS
  In a pilot study conducted at a tertiary hospital in China between 2010 and 2014, peripheral blood samples were collected from women at 16-19weeks of pregnancy. Pooled samples from 10 women who were subsequently diagnosed with GDM and from 10 healthy controls were used to construct two small RNA libraries. High-throughput sequencing was performed, and differentially expressed miRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR), followed by target prediction, Gene Ontology analysis, and pathway identification.
  
  
  RESULTS
  Sequencing revealed 32 miRNAs that were differentially expressed in GDM, including 12 miRNAs that were upregulated and 20 that were downregulated. Differential expression of five upregulated miRNAs (hsa-miR-16-5p, hsa-miR-17-5p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-20a-5p) was confirmed by qRT-PCR. Target prediction showed that the major targets of these miRNAs were associated with insulin resistance and abnormal pregnancies.
  
  
  CONCLUSIONS
  The five miRNAs that were differentially expressed in GDM could serve as noninvasive biomarkers. The results also provide insights into the molecular mechanisms that underlie GDM, thereby contributing to the diagnosis and treatment of this disease.
authors.affiliation: Key Lab for Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China.
authors.forename: Yanan
authors.initials: Y
authors.lastname: Zhu
authors.affiliation: Key Lab for Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Tian
authors.affiliation: Department of Gynecology and Obstetrics, Zhongda Hospital, Southeast University, Nanjing, China.
authors.forename: Hailing
authors.initials: H
authors.lastname: Li
authors.affiliation: Key Lab for Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China.
authors.forename: Youxia
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: State Key Lab of Bioelectronics, Southeast University, Nanjing, China.
authors.forename: Jiafeng
authors.initials: J
authors.lastname: Lu
authors.affiliation: Key Lab for Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China. Electronic address: geqinyu@seu.edu.cn.
authors.forename: Qinyu
authors.initials: Q
authors.lastname: Ge
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D002681:China; D016640:Diabetes, Gestational / Q000097:blood / Q000175:diagnosis*; D005260:Female; D006801:Humans; D035683:MicroRNAs / Q000097:blood*; D020411:Oligonucleotide Array Sequence Analysis; D010865:Pilot Projects; D011247:Pregnancy; D011262:Pregnancy Trimester, Second / Q000097:blood*; D060888:Real-Time Polymerase Chain Reaction; D062606:Tertiary Care Centers
chemical_list: D015415:Biomarkers; D035683:MicroRNAs
keywords: Gestational diabetes mellitus; Next-generation sequencing; Profiling; microRNA