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妊娠大鼠伴发脂质代谢紊乱的机制探讨及基因分析 被引量:1

Study on the mechanism and genetic analysis of lipid metabolism disorder in pregnant rats
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摘要 目的:分析肠道菌群失调妊娠大鼠脂质代谢特征及可能机制。方法:将129只性成熟的雌性SD大鼠分为3组,未妊娠组(未经处理健康大鼠)、妊娠健康组(自然授精妊娠的大鼠)、妊娠菌群失调组(自然授精妊娠的大鼠经混合抗生素灌胃造模),每组43只。全自动生化分析仪检测甘油三酯(TG)、低密度脂蛋白胆固醇(LDL-c)、高密度脂蛋白胆固醇(HDL-c)、总胆固醇(TC)含量。荧光定量PCR技术检测大鼠硬脂酰辅酶A去饱和酶1(SCD1)、过氧化物酶体增殖物激活受体γ共激活因子1(PGC-1α)、磷酸烯醇式丙酮酸羧激酶(PEPCK)、载脂蛋白E(ApoE)、微粒体甘油三酸酯转移蛋白(MTTP)基因含量,比较3组各指标含量的统计学差异。回归分析的方法探索各基因对大鼠总胆固醇表达含量的综合影响,主成分分析的方法探索肠道菌群失调妊娠大鼠脂质代谢发生的内部机制。结果:各组大鼠进行TG、TC、LDL-c、HDL-c含量的比较,均有妊娠健康组>未妊娠组>妊娠菌群失调组,差异均有统计学意义(P<0.05)。各组大鼠相关基因(SCD1、PGC-1α、PEPCK、ApoE、MTTP)表达含量比较,差异均有统计学意义(P<0.05);两两组别比较,差异均有统计学意义(P<0.05)。多元线性回归分析显示,各基因含量对TC含量的影响从大到小依次为:SCD1(OR=4.572)、PGC-1α(OR=3.387)、PEPCK(OR=3.935)、ApoE(OR=3.597)、MTTP(OR=3.096)。主成分分析显示,肠道菌群失调妊娠大鼠脂质代谢5个相关基因可提取3个主成分,分别是:SCD1/PEPCK通路(贡献率36.28%)、PGC-1α/ApoE通路(贡献率30.42%)、MTTP通路(贡献率15.37%)。结论:妊娠后大鼠血脂有明显升高,而肠道菌群失调则会导致血脂降低。肠道菌群失调妊娠大鼠发生脂质代谢紊乱主要与相关基因表达失常,进而影响SCD1/PEPCK、PGC-1α/ApoE、MTTP通路的功能有关。 Objective: To analyze the characteristics and possible mechanism of lipid metabolism in pregnant rats with intestinal flora imbalance. Methods: 129 sexually mature female SD rats were divided into three groups: the non-pregnant group (untreated healthy rats), the pregnant healthy group (natural insemination pregnant rats), and the pregnant microflora disorder group (natural insemination pregnant rats were given a mixed antibiotic gavage model), with 43 rats in each group. The contents of TG, LDL-c, HDL-c and TC were detected by automatic biochemical analyzer, and the contents of SCD1, pgc-1 alpha, PEPCK, ApoE and MTTP genes were detected by fluorescence quantitative PCR technology. Regression analysis was used to explore the comprehensive influence of each gene on total cholesterol expression in rats. Principal component analysis was used to explore the internal mechanism of lipid metabolism in pregnant rats with intestinal flora disorder. Results: The contents of TG, TC, LDL-c and HDL-c were compared among the three groups of rats, and the differences were statistically significant ( P <0.05). The expression levels of related genes (SCD1, pgc-1, PEPCK, ApoE, MTTP) in the three groups were statistically significant ( P <0.05), SCD1 content in the non-pregnant group (0.92±0.12 μg/mL), healthy pregnancy group (1.20±0.15 μg/mL), and disordered pregnancy bacteria group (1.53±0.20 μg/mL). Pgc-1 alpha content in the non-pregnant group (1.34±0.21 μg/mL), healthy pregnancy group (0.93±0.12 micron /mL), and disordered pregnancy group (0.41±0.08 μg/mL). PEPCK content in the non-pregnant group (0.48±0.06 μg/mL), healthy pregnancy group (0.35±0.09 μg/mL), and disordered pregnancy group (0.22±0.05 μg/mL), and the differences were statistically significant ( P <0.05). Multivariate linear regression analysis showed that the influence of gene content on TC content was SCD1 ( OR =4.572), pgc-1 ( OR =3.387), PEPCK ( OR =3.935), ApoE ( OR =3.597), MTTP ( OR =3.096). Principal component analysis showed that three principal components could be extracted from five related genes of lipid metabolism in pregnant rats with intestinal dysbiosis: SCD1/PEPCK pathway (contribution rate: 36.28%), pgc-1/ApoE pathway (contribution rate: 30.42%), and MTTP pathway (contribution rate: 15.37%). Conclusions: After pregnancy, blood lipids in rats were significantly increased, while imbalance of intestinal flora would lead to decreased blood lipids. The disorder of lipid metabolism in pregnant rats with intestinal flora imbalance is mainly related to the disorder of gene expression, which further affects the functions of SCD1/PEPCK, pgc-1 /ApoE and MTTP pathways.
作者 孙莉 严振威 彭迎港 肖区龙 袁怡雯 周玲 胡昊 李万峰 SUN Li;YAN Zhen-wei;PENG Ying-gang;XIAO Qu-long;YUAN Yi-wen;ZHOU Ling;HU Hao;LI Wan-feng(Changsha Medical University,Changsha, Hunan,410219)
机构地区 长沙医学院
出处 《海南医学院学报》 CAS 2019年第17期1295-1299,共5页 Journal of Hainan Medical University
基金 2018年湖南省大学生研究性学校和创新性实验计划项目,湘教通[2018]255号-1097 长沙医学院大学生研究性学习和创新性实验计划项目,长医教[2018]77号-264~~
关键词 肠道菌群失调 妊娠 脂质代谢紊乱 基因 通路 主成分分析 多元线性回归分析 Imbalance of intestinal flora Pregnancy Lipid metabolism disorder Genes Pathways Principal component analysis Multiple linear regression analysis
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