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Abstract：
BACKGROUND: The pregnant women with intrahepatic cholestasis were at high risk of fetal distress, preterm birth and unexpected stillbirth. Intrahepatic cholestasis of pregnancy (ICP) was mainly caused by disorder of bile acid metabolism, whereas the specific mechanism was obscure.
METHODS: We performed proteomics analysis of 10 ICP specimens and 10 placenta specimens from patients without ICP through data-independent acquisition (DIA) technique to disclose differentially expressed proteins. We executed metabolomic analysis of 30 ICP specimens and 30 placenta specimens from patients without ICP through UPLC-MS/MS to identify differentially expressed metabolites. Enrichment and correlation analysis was used to obtain the direct molecular insights of ICP development. The ICP rat models were constructed to validate pathological features.
RESULTS: The heatmap of proteomics analysis showed the top 30 up-regulated and 30 down-regulated proteins. The metabolomic analysis revealed 20 richer and 4 less abundant metabolites in ICP samples compared with placenta specimens from patients without ICP, and enrichment pathways by these metabolites included primary bile acid biosynthesis, cholesterol metabolism, bile secretion, nicotinate and nicotinamide metabolism, purine metabolism and metabolic pathways. Combined analysis of multiple omics results demonstrated that bile acids such as Glycohyocholic acid, Glycine deoxycholic acid, beta-Muricholic acid, Noncholic acid, cholic acid, Gamma-Mercholic Acid, alpha-Muricholic acid and Glycochenodeoxycholic Aicd were significantly associated with the expression of GLRX3, MYL1, MYH7, PGGT1B, ACTG1, SP3, LACTB2, C2CD5, APBB2, IPO9, MYH2, PPP3CC, PIN1, BLOC1S1, DNAJC7, RASAL2 and ATCN3 etc. The core protein ACAT2 was involved in lipid metabolic process and animal model showed that ACAT2 was up-regulated in placenta and liver of pregnant rats and fetal rats. The neonates had low birth weight and Safranin O-Fast green FCF staining of animal models showed that poor osteogenic and chondrogenic differentiation of fetal rats.
CONCLUSIONS: Multiple metabolites-alpha-Muricholic acid, beta-Muricholic acid, Glycine deoxycholic acid and Glycochenodeoxycholic Acid etc. were perfect biomarkers to predict occurrence of ICP. Bile acids were significantly associated with varieties of protein expression and these proteins were differentially expressed in ICP samples. Our study provided several biomarkers for ICP detection and potential therapeutic targets for ICP development.
METHODS: We performed proteomics analysis of 10 ICP specimens and 10 placenta specimens from patients without ICP through data-independent acquisition (DIA) technique to disclose differentially expressed proteins. We executed metabolomic analysis of 30 ICP specimens and 30 placenta specimens from patients without ICP through UPLC-MS/MS to identify differentially expressed metabolites. Enrichment and correlation analysis was used to obtain the direct molecular insights of ICP development. The ICP rat models were constructed to validate pathological features.
RESULTS: The heatmap of proteomics analysis showed the top 30 up-regulated and 30 down-regulated proteins. The metabolomic analysis revealed 20 richer and 4 less abundant metabolites in ICP samples compared with placenta specimens from patients without ICP, and enrichment pathways by these metabolites included primary bile acid biosynthesis, cholesterol metabolism, bile secretion, nicotinate and nicotinamide metabolism, purine metabolism and metabolic pathways. Combined analysis of multiple omics results demonstrated that bile acids such as Glycohyocholic acid, Glycine deoxycholic acid, beta-Muricholic acid, Noncholic acid, cholic acid, Gamma-Mercholic Acid, alpha-Muricholic acid and Glycochenodeoxycholic Aicd were significantly associated with the expression of GLRX3, MYL1, MYH7, PGGT1B, ACTG1, SP3, LACTB2, C2CD5, APBB2, IPO9, MYH2, PPP3CC, PIN1, BLOC1S1, DNAJC7, RASAL2 and ATCN3 etc. The core protein ACAT2 was involved in lipid metabolic process and animal model showed that ACAT2 was up-regulated in placenta and liver of pregnant rats and fetal rats. The neonates had low birth weight and Safranin O-Fast green FCF staining of animal models showed that poor osteogenic and chondrogenic differentiation of fetal rats.
CONCLUSIONS: Multiple metabolites-alpha-Muricholic acid, beta-Muricholic acid, Glycine deoxycholic acid and Glycochenodeoxycholic Acid etc. were perfect biomarkers to predict occurrence of ICP. Bile acids were significantly associated with varieties of protein expression and these proteins were differentially expressed in ICP samples. Our study provided several biomarkers for ICP detection and potential therapeutic targets for ICP development.
摘要：
背景：肝内胆汁淤积的孕妇有胎儿窘迫的高风险，早产和意外死产。妊娠期肝内胆汁淤积症(ICP)主要由胆汁酸代谢紊乱引起,而具体机制是模糊的。
方法：我们通过数据独立采集（DIA）技术对10个ICP标本和10个无ICP患者胎盘标本进行了蛋白质组学分析，以揭示差异表达的蛋白质。我们通过UPLC-MS/MS对来自无ICP患者的30个ICP标本和30个胎盘标本进行了代谢组学分析，以鉴定差异表达的代谢物。使用富集和相关性分析来获得ICP发展的直接分子见解。构建ICP大鼠模型以验证病理特征。
结果：蛋白质组学分析的热图显示了前30个上调和30个下调的蛋白质。代谢组学分析显示，与无ICP患者的胎盘样本相比，ICP样本中有20种更丰富的代谢物和4种更少的代谢物。这些代谢物的富集途径包括初级胆汁酸生物合成，胆固醇代谢，胆汁分泌，烟酸和烟酰胺代谢，嘌呤代谢和代谢途径。对多个组学结果的联合分析表明，胆汁酸如甘胆酸，甘氨酸脱氧胆酸,β-Muricholic酸,非胆酸,胆酸,γ-甲胆酸,α-Muricholic酸和甘牛脱氧胆酸Aicd与GLRX3，MYL1，MYH7，PGGT1B的表达显着相关，ACTG1,SP3,LACTB2,C2CD5,APBB2,IPO9,MYH2,PPP3CC,PIN1、BLOC1S1、DNAJC7、RASAL2和ATCN3等。核心蛋白ACAT2参与脂质代谢过程，动物模型显示ACAT2在孕鼠和胎鼠胎盘和肝脏中表达上调。新生儿出生体重低，SafraninO-FastGreenFCF染色动物模型显示胎鼠成骨和软骨分化差。
结论：多种代谢物-α-Muricholic酸，β-Muricholic酸,甘氨酸脱氧胆酸和甘氨酸脱氧胆酸等。是预测ICP发生的完美生物标志物。胆汁酸与各种蛋白质表达显着相关，并且这些蛋白质在ICP样品中差异表达。我们的研究为ICP检测提供了几种生物标志物，并为ICP开发提供了潜在的治疗靶标。
方法：我们通过数据独立采集（DIA）技术对10个ICP标本和10个无ICP患者胎盘标本进行了蛋白质组学分析，以揭示差异表达的蛋白质。我们通过UPLC-MS/MS对来自无ICP患者的30个ICP标本和30个胎盘标本进行了代谢组学分析，以鉴定差异表达的代谢物。使用富集和相关性分析来获得ICP发展的直接分子见解。构建ICP大鼠模型以验证病理特征。
结果：蛋白质组学分析的热图显示了前30个上调和30个下调的蛋白质。代谢组学分析显示，与无ICP患者的胎盘样本相比，ICP样本中有20种更丰富的代谢物和4种更少的代谢物。这些代谢物的富集途径包括初级胆汁酸生物合成，胆固醇代谢，胆汁分泌，烟酸和烟酰胺代谢，嘌呤代谢和代谢途径。对多个组学结果的联合分析表明，胆汁酸如甘胆酸，甘氨酸脱氧胆酸,β-Muricholic酸,非胆酸,胆酸,γ-甲胆酸,α-Muricholic酸和甘牛脱氧胆酸Aicd与GLRX3，MYL1，MYH7，PGGT1B的表达显着相关，ACTG1,SP3,LACTB2,C2CD5,APBB2,IPO9,MYH2,PPP3CC,PIN1、BLOC1S1、DNAJC7、RASAL2和ATCN3等。核心蛋白ACAT2参与脂质代谢过程，动物模型显示ACAT2在孕鼠和胎鼠胎盘和肝脏中表达上调。新生儿出生体重低，SafraninO-FastGreenFCF染色动物模型显示胎鼠成骨和软骨分化差。
结论：多种代谢物-α-Muricholic酸，β-Muricholic酸,甘氨酸脱氧胆酸和甘氨酸脱氧胆酸等。是预测ICP发生的完美生物标志物。胆汁酸与各种蛋白质表达显着相关，并且这些蛋白质在ICP样品中差异表达。我们的研究为ICP检测提供了几种生物标志物，并为ICP开发提供了潜在的治疗靶标。
