Abstract
Objective To investigate the expression of circular RNA (circRNA) in peripheral blood of gravidas with gestational diabetes mellitus (GDM) using gene chip technology, and to provide evidence for studying pathogenesis of GDM. Methods A prospective cohort-based nested case-control study was used to select 1 018 pregnant women who were examined and delivered in Guangzhou Women and Children's Medical Center from September 2014 to April 2016. The information of prenatal examination was recorded and the outcome of delivery was followed up. Six pregnant women diagnosed as GDM were selected as the GDM group. Six normal pregnant women who were collected blood samples by 1∶1 were selected as the control group. The difference of gestational week was less than 7 days, the number of previous pregnancies was less than 2 times, and the difference of previous delivery times as same as the control group. The expression of circRNA in maternal peripheral blood was analyzed by chromosome microarray technique, and the function and the regulation network forecast were analyzed by GO (http://www.geneontology.org/), KEGG PATHWAY (http://www.genome.jp/kegg/pathway.html) and CircNet(http://circnet.mbc.nctu.edu.tw/). t-test was used for data analysis. Results Compared to the normal pregnant women, 2 678 circRNAs were identified to be differentially expressed >2.0 times in GDM women, among which 1 532 were up-regulated and 1 146 were down-regulated. Functional analysis showed that the up-regulated circRNA was enriched in the biological processes of insulin response, gene silencing regulation, glucagon response and cell senescence. Signal pathway analysis showed that circRNA involved in insulin pathway. Taking has_circ_0042852 and has_circ_0004001 as center, the possible GDM-related regulatory networks were predicted. Conclusions The peripheral blood of GDM women is rich in circRNAs, which might involve in many biological processes, insulin signaling pathway and possibly induding GDM-related regulatory networks. Key words: Diabetes, gestational; RNA; Gene expression profiling; Biomarkers
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