| Background:Intrahepatic cholestasis of pregnancy(ICP), a pregnancy-related syndrome that incidence varies geographically from 0.1 % to 15.6 %, is characterized by mild to severe pruritus and disturbed liver function tests.The disease symptoms and liver dysfunction appear mainly in the late second or third trimester of pregnancy and recover quickly after delivery.However, ICP leads to complications for both mother and fetus. ICP is associated with intractable pruritus and high predisposition to postpartum bleeding, being the leading causes of maternal morbidity. On the other hand,ICP is associated with an increased risk of spontaneous preterm labor, fetal distress and sudden intrauterine death. Currently, the exact cause of ICP is unknown. Genetic, endocrinologic, nutritional, and environmental factors are considered to be related to the pathogenesis of the disease. There is lack of international uniformity regarding the ascertainment and diagnosis of ICP. The diagnosis of ICP is based on pruritus and the disorder of liverfunction tests with exclusion of other clinical entities in China. The elevated total bile acid(TBA) levels are considered as the most useful laboratory indicator for the diagnosis of ICP. However, normal level of TBA was also observed in serum of pregnant women with ICP in some cases. Therefore, more sensitive and specific biomarkers are useful for the diagnosis of ICP as early as possible and improvement the prognosis of ICP.Circulating mRNAs existed in most extracellular fluids. Moreover, these circulating miRNAs are highly stable and easily detected which usually reflect a tissue specific injury or expression. Circulating miRNA was a kind of easy approachable and non-invasive biomarker. Non-targeted metabolomics based on HPLC-MS, which focuses on the dynamic changes of all small molecules, is powerful in the discovery of biomarkers.Objective:Since there is lack sensitive and specific biomarker for ICP and the exact cause of ICP is unknown, mulit plantform bsaed on circulating miRNA profile and metabolism was used to screen the urinary biomarkers for ICP.Methods:A differential miRNA profiling was initially analyzed by individual quantitative reverse transcriptase polymerase chain reaction(qRT-PCR)assay in urinary samples from a screening set including 10 ICPs and 10 healthy pregnancies. The selected candidate miRNAs were then validatedby a validation set with 40 ICPs and 50 healthy pregnancies using individual qRT-PCR assay. A binary logistic regression model to estimate the risk of being diagnosed with ICP was applied to the validation set. The combination biomarker for diagnosis of ICP was evaluated by receiver operating characteristic(ROC) curve.In this study, non-targeted metabolomic approach based on high performance liquid chromatography/mass spectrometry was used to investigate the differential metabolites in urine samples from 30 ICPs and30 healthy pregnancies. The differential metabolites were screened by supervised and unsupervised data recognize model. The candidate biomarkers were validated by statistical methods, extraction from the raw data and non information model construction. The HMDB database and isotope ratio distribution method were used for the identification of metabolic markers. The pathway analysis was used for identified metabolites. A binary logistic regression model to estimate the risk of being diagnosed with ICP was applied to the identified metabolites. The combination biomarker for diagnosis of ICP was evaluated by ROC curve.Results:1. Compared with the expression in urine of healthy pregnant women,23 miRNAs presented significant differential expression levels. Among them, 14 miRNAs were up-regulated(P < 0.05) and 9 were down-regulated(P < 0.05) in ICP group. The hot map on the 23 differential expressionmiRNAs could discrimination the ICP group with the control group.2. Compared with the expression in urine of healthy pregnant women,the expression levels of hsa-miR-151-3p and hsa-miR-300 were significantly down-regulated, whereas hsa-miR-671-3p and hsa-miR-369-5p were significantly up-regulated in urine from ICP patients(P < 0.05 and false discovery rate<0.05) in validation set.3. A binary logistic regression model was constructed by the six miRNAs and found hsa-miR-151-3p, hsa-miR-671-3p, hsa-miR-369-5p and hsa-miR-300 were the significant biomarkers for the diagnosis of ICP.The ROC curve was constructed by the four miRNA and the area under the curve was 0.913 with sensitivity at 82.9% and specificity at 87.0%.4. The peaks were numerous and even distribution after optimization of the chromatographic conditions. The established urinary non-target metabolism assay was with inter-batch(n=5) variation of retention time less than 1.9% and peak area less than 11.3% and inta–batch(n=5)variation of retention time less than 4% and peak area less than 16.6% in positive ion model. In negative ion model, the inter-batch(n=5) variation of retention time was less than 3% and peak area was less than 12.5%; the inta–batch(n=5) variation of retention time was less than 3.8% and peak area was less than 14.1%.5. Urinary metabolites allow for the discrimination of ICP pregnant women from controls by orthogonal partial least squares discriminantanalysis. 109 variables in positive model and 119 variables in negative model were significantly different(P < 0.05) and with variable importance in the project more than 1.6. 14 metabolites in positive model and 18 metabolites in negative model were selected and identified. Most of these metabolites were involved in bile acid biosynthesis and metabolism, hormone metabolism and lipid metabolism.7. A binary logistic regression model constructed by these metabolites and a metabolite panel(MG(22:5), LysoPE(22:5), L-homocysteine sulfonic acid, glycocholic acid and chenodeoxycholic acid 3-sulfate) was identified with a high diagnostic accuracy for ICP. The area under the receiver operating characteristic curve was 0.988 with sensitivity at 90.0%and specificity at 93.3%.Conclusion:1. The urinary circulating miRNA profile was significant different between ICP group and control group.2. The hsa-miR-151-3p, hsa-miR-671-3p, hsa-miR-369-5p and hsa-miR-300 were the significant biomarkers for the diagnosis of ICP. The combined miRNA was with high diagnostic accuracy for ICP.3. Urinary metabolites allow for the discrimination of ICP pregnant women from controls by orthogonal partial least squares discriminant analysis. Most of these metabolites were involved in bile acid biosynthesisand metabolism, hormone metabolism and lipid metabolism and revealed that these dysfunction of metabolism might cause the ICP.4. The metabolites panel of MG(22:5), LysoPE(22:5),L-homocysteine sulfonic acid, glycocholic acid and chenodeoxycholic acid3-sulfate) was with a high diagnostic accuracy for ICP. |
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