DIA-based Proteomics Analysis of Serum-derived Exosomal Proteins as Potential Candidate Biomarkers for  Intrahepatic Cholestasis in Pregnancy

doi:10.21203/rs.3.rs-1526689/v1

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Research Article

DIA-based Proteomics Analysis of Serum-derived Exosomal Proteins as Potential Candidate Biomarkers for Intrahepatic Cholestasis in Pregnancy

https://doi.org/10.21203/rs.3.rs-1526689/v1

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Background Data-independent acquisition (DIA) is one of the most powerful and reproducible proteomic technologies for large-scale digital qualitative and quantitative research. The aim of this study was to use proteomic methodologies for the identification of biomarkers that are over- or underexpressed in women with intrahepatic cholestasis of pregnancy (ICP) compared with controls and discover a potential biomarker panel for ICP detection.

Methods The participants included 11 ICP patients and 11 healthy pregnant women as controls. The clinical characteristic data and the laboratory biochemical data were collected at the time of recruitment. Then, a data-independent acquisition (DIA)-based proteomics approach was used to identify differentially expressed proteins (DEPs) in serum exosomes between ICP patients and controls. Finally, bioinformatics analysis was used to identify the relevant processes in which these DEPs were involved.

Results The proteomics results showed that there were 162 DEPs in serum exosomes between pregnant women with ICP and healthy pregnant women, of which 106 were upregulated and 56 were downregulated in ICP. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the identified proteins were functionally related to specific cell processes including apoptosis, lipid metabolism, immune response and cell proliferation, and metabolic disorders, suggesting that these may be primary causative factors in ICP pathogenesis. Meanwhile, complement and coagulation cascades may be closely related to the development of ICP. Receiver operating characteristic curve (ROC) analysis showed that the area under the curve values of Elongation factor 1-alpha 1, Beta-2-glycoprotein I, Zinc finger protein 238, CP protein and Ficolin-3 were all approximately 0.9, indicating the promising diagnostic value of these proteins.

Conclusions This preliminary work provides a better understanding of the proteomic alterations in the serum exosomes of pregnant women with ICP and may provide new insights into ICP pathophysiology and potential novel treatment targets for this disease. However, future studies of the systemic expression of these candidate biomarkers and their exact roles in ICP will be essential for conformation of this hypothesis.

Proteomics analysis

DIA

ICP

Proteome changes

Biomarkers

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disease that usually emerges during the second and third trimester of pregnancy. It is characterized by pruritus and elevated serum bile acids and/or liver enzymes, and the disease symptoms and liver dysfunction resolve quickly after delivery [1]. The incidence of ICP ranges from below 1% to above 15% in different countries, and the risk of recurrence in a future pregnancy is 70% [2, 3]. To date, the exact aetiology of ICP remains elusive. Genetic, endocrinologic, nutritional, and environmental factors are considered to be related to the pathogenesis of the disease [4–6]. Studies have shown that ICP can lead to complications for both the mother and foetus [7]. On the one hand, ICP is associated with intractable pruritus and a strong predisposition to postpartum bleeding, which is the leading cause of maternal morbidity and mortality. On the other hand, ICP is associated with an increased risk of spontaneous preterm labour, meconium-stained amniotic fluid, foetal distress and sudden intrauterine death. However, there is still a lack of effective measures to predict the intrauterine safety of the foetus. Foetus heart monitoring can only reflect the immediate safety status of the foetus. Therefore, how to timely detect ICP and improve these adverse outcomes for both mothers and children are the focus of current research.

To date, no unified ICP diagnostic criteria have been developed, and the cardinal symptoms of pruritus and jaundice and a concomitant elevated level of serum levels of total bile acids (TBA) (≥ 10 µmol/L) and/or alanine aminotransferase (ALT) are considered suggestive for diagnosis in China [8, 9]. The diagnosis should exclude other clinical entities of chronic liver disease. However, itch, as an important symptom of ICP, also occurs in many pregnant women without ICP, and the biochemical indicators, serum bilirubin and ALT are mostly not sensitive and specific. No specific diagnostic biomarker other than the TBA marker is currently available. However, serum TBA also has limited sensitivity for the diagnosis of ICP.

At present, there is no unified diagnostic standard for ICP. In China, elevated serum TBA level is a key indicator for the diagnosis of ICP, and pruritosis without other causes and fasting serum TBA ≥ 10 µmol/L in pregnant women are the main basis for the diagnosis of ICP [8, 9]. Although elevated TBA occurs in a majority of ICP patients, approximately 10% of pregnant women have normal TBA [10]. The Society for Maternal-Fetal Medicine (SMFM) Consult Series #53: Intrahepatic cholestasis of pregnancy recommend measuring serum TBA and liver transaminase levels in patients with suspected ICP for definitive diagnosis [11]. Therefore, ICP can also be diagnosed for pregnant women with normal TBA level but abnormal liver function that cannot be explained by other reasons. These abnormal liver function indicators mainly include serum alanine aminotransferase and aspartate aminotransferase. Meanwhile, a retrospective study found that serum TBA could not distinguish ICP patients with mild itching from healthy pregnant women [12]. In addition, it was suggested that serum TBA level could be affected by postprandial status and present false positive [13]. Thus, new diagnostic and prognostic ICP biomarkers are urgently needed.

For the past few years, there has been growing interest in exploring the potential role of exosomes as noninvasive biomarkers for the early detection and prognosis of diseases. Exosomes, a form of nanoscale vesicles with a size of 40–100 nm, are commonly secreted by most cells and carry various bioactive molecules, such as nucleic acids, proteins, and lipids, reflecting the biological status of their parent cells [14, 15]. Exosomes can transport signalling molecules to adjacent and distant cells, regulating the physiology of recipient cells and participating in the onset and progression of multiple diseases [16]. Melo et al. [17] found that glypican-1 in serum exosomes can be used as a marker for the early diagnosis of pancreatic cancer, with a specificity of up to 100%; Tan et al. [18] found that the plasma exosomal proteins choleramycin B chain and annexin V can be used to monitor the severity of preeclampsia; Ma Li et al. [7] verified the feasibility of using urinary exosomal miRNA in the diagnosis of ICP by detecting the miRNA profile of urinary exosomes. Differential expression of proteins is an important feature to distinguish exosomes from different sources. At present, there are no relevant reports about serum exosomal proteins in the diagnosis of ICP. Proteomics is a key area of research in the postgenomic era. Advances in the use of two-dimensional electrophoresis (2-DE) and mass spectrometry have led to a rapid expansion of this field in biomedical research. Data-independent acquisition (DIA) is one of the most powerful and reproducible proteomic technologies for large-scale digital qualitative and quantitative research [19, 20]. In this study, DIA proteomic techniques were employed to explore a broad spectrum of functional proteins in ICP patients and controls. The aim of this study was to use proteomic methodologies for the identification of biomarkers that are over- or underexpressed in serum exosomes of ICP patients compared with controls and to discover a potential biomarker panel for ICP detection.

Reagents

The reagents used in this work were as follows: Multiple Affinity Removal LC Column-Human 14/Mouse 3 (Agilent, Shanghai, China), 5 kDa Ultrafiltration Tube (Sartorius, Beijing, China), UltraPure™ Tris Hydrochloride (Tris-HCl) (Invitrogen, CA, USA), ammonium bicarbonate (NH₄HCO₃) (Sigma-Aldrich, Shanghai, China), dithiothreitol (DTT) (Bio-Rad, Wuhan, China), iodoacetamide (IAA) (Bio-Rad, Wuhan, China), BCA Protein Assay Kit (Beyotime, Shanghai, China), Sequencing-Grade Modified Trypsin (Trypsin) (Promega, WI, USA), Empore™ SPE Cartridges C18 (Sigma-Aldrich, Shanghai, China), formic acid (FA) (Fluka, Beijing, China), High-pH Reversed-Phase Peptide Fractionation Kit (Thermo Scientific™ Pierce™, Shanghai, China), EASY-SprayTM C18 Trap column (Thermo Scientific, Shanghai, China), iRT-Kits (Biognosys, Beijing, China), trifluoroacetic acid (TFA) (Sigma-Aldrich, Shanghai, China), acetonitrile (ACN) (Merck, Shanghai, China), glycerol (Sangon, Shanghai, China), bromophenol blue (Sangon, Shanghai, China), bovine serum albumin (BSA) (Sangon, Shanghai, China), sodium dodecyl sulfate (SDS) (Bio-Rad, Wuhan, China), and urea (Bio‐Rad, Wuhan, China). The SCX chromatography columns used were as follows: polysulfoethyl 4.6×100 mm column (5 μm, 200Å) (PolyLC Inc., Maryland, USA); C18 trap columns (Acclaim PepMap100, 100 μm*2 cm, Thermo Scientific and nanoViper C18, 3 μm, 100 Å, PolyLC Inc., Maryland, USA); and C18 analytical columns (Thermo Scientific EASY column, 10 cm, ID 75 μm, 3 μm, C18-A2, PolyLC Inc., Maryland, USA).

Study subjects

All participants, including 11 ICP patients and 11 paired healthy pregnant controls, were recruited from Jiangxi Provincial Maternal and Child Health Hospital from March 2020 to September 2020. This study received ethical approval from the Ethics Committee of Jiangxi Provincial Maternal and Child Health Hospital. All participants signed informed consent forms before the start of the study.

All subjects were primiparous Chinese women with a singleton pregnancy. The enrolment criteria for ICP were as described above [8], and causes of liver dysfunction, including preeclampsia, haemolysis, elevated liver enzymes and low platelets syndrome (HELLP), primary biliary cirrhosis, acute fatty liver of pregnancy, viral hepatitis and any ultrasound abnormality that might result in biliary obstruction, were excluded. No patient underwent ursodeoxycholic acid treatment prior to blood sample collection. Healthy controls were volunteers matched by age and gestational age with the ICP patients. No evident disease was detected during the course of the study. The clinical characteristic data of the enrolled participants were recorded at the time of recruitment, and the liver function test data are summarized in Table 1. After fasting for 8 h, a venous blood sample from each participant was collected. The serum samples were stored at -80 ℃ for subsequent assays.

Isolation and purification of exosomes

The method was as follows [21]: after thawing at 37 °C, the plasma was centrifuged at 2 000 g for 30 min at 4 °C to remove cell fragments, and then the supernatant was centrifuged at 10 000 g for 45 min to remove large vesicles. The filtrate was filtered through a 0.45 μm filter membrane and centrifuged twice at 100 000 g × 70 min. Finally, the precipitate was resuspended in 100 μL precooled 1×PBS, and 20 μL was taken for electron microscopy, 10 μL for particle size measurement, 30 μL for protein extraction, and 20 μL for fluorescence assays. The remaining exosomes were stored at -80 °C for subsequent analysis.

Characterization of exosomes

After purification of exosomes, the hydrodynamic size and concentration of samples were measured using nanoparticle tracking analysis (NTA) with Zeta View PMX 110 (Particle Metrix, Meerbusch, Germany) and the corresponding software Zeta View 8.04.02 [22]. The sample solutions were fixed on Formvar-carbon copper grids, negatively stained for 2 min and air dried for morphologic visualization using a transmission electron microscope (TEM, HT7700, Hitachi, Japan) at an acceleration voltage of 80 kV. Digital images were captured by a CCD camera (Veleta; Olympus Soft Imaging Solutions GmbH, Münster, Germany).

Extraction and quantification of exosome protein

The exosomes were rapidly thawed at 37 °C, and 6×RIPA lysis buffer was added immediately. Ice cracking and full mixing were performed for 30 min. The standard sample for protein concentration was prepared by a BCA quantitative kit, and 5 μL sample was added to the BCA mixture. After incubation at 37 ℃ for 30 min, the OD562 nm value was detected and recorded on the microplate analyser, and the protein concentration of the sample to be measured was calculated according to the standard curve [23].

Western blot

Western blotting (WB) was used to detect the protein expression of CD9 and CD81. The exudate volume was 50 µg. Polyacrylamide gel electrophoresis was performed on a 10% separating gel and a 4% stacking gel, and electrophoresis was initially performed at 80 V for the stacking gel. Approximately 30 min later, the protein entered the separation gel, and the voltage was adjusted to 100 V. The film was transferred at 100 V for 120 min by the wet transfer method. After sealing at room temperature for 1 h, the film was placed in the primary antibody diluent of CD9 and CD81 at 1:1000 in a 4 ℃ shaking bed overnight. The next day, the membrane was washed 3 times with TBST, and the goat anti-rabbit secondary antibody was incubated for 1 h. Then, the film was washed, exposed and developed.

Fluorescent labelling and nanoflow detection of exosomes

Exosomes (30 μL) were diluted to 120 μL, and 30 μL diluted exosomes were added to 20 μL fluorescently labelled antibodies (CD9, CD63, CD81 and IgG), mixed, and incubated at 37 °C for 30 min with shielding from light. Then, 1 mL of precooled PBS was added, and the mixture was centrifuged at 110,000 × g for 70 min at 4 ℃ twice. The supernatant was carefully removed, and the precipitate was resuspended in 50 μL precooled 1×PBS. After passing the instrument performance test with the standard product, the exosome samples were loaded. Protein index results were obtained after the samples were tested.

Sample Preparation and Fractionation for DDA Library Generation

Serum pools were separated into most and least abundant proteins using the Human 14/Mouse 3 Multiple Affinity Removal System Column following the manufacturer’s protocol (Agilent Technologies). The high- and low-abundance proteins were collected, and a 5 kDa ultrafiltration tube was used for desalination and concentration of high- and low-abundance components. SDT buffer (4% SDS, 100 mM DTT, 150 mM Tris-HCl pH 8.0) was added, boiled for 15 min and centrifuged at 14000 g for 20 min. The supernatant was quantified with the BCA Protein Assay Kit. The sample was stored at -80 °C.

Filter-aided sample preparation (FASP) procedure

Both proteins with high and low abundance were subjected to a digestion procedure modified from the FASP protocol described previously. Briefly, 200 μg of protein was placed into a ultrafiltration tube, and the detergent, DTT and other low-molecular-weight components were removed using UA buffer (8 M urea, 150 mM Tris-HCl pH 8.0) by repeated ultrafiltration (Microcon units, 10 kD). Then, 100 μL iodoacetamide (100 mM IAA in UA buffer) was added to block reduced cysteine residues, and the samples were incubated for 30 min in darkness. The filters were washed with 100 μL UA buffer three times and then 100 μL 25 mM NH₄HCO₃ buffer twice. Finally, the protein suspensions were digested with 4 μg trypsin (Promega) in 40 μL 25 mM NH₄HCO₃ buffer overnight at 37 °C, and the resulting peptides were collected as a filtrate. The peptides of each sample were desalted on C18 cartridges (Empore™ SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma), concentrated by vacuum centrifugation and reconstituted in 40 μL of 0.1% (v/v) formic acid. The peptide content was estimated by UV light spectral density at 280 nm using an extinction coefficient of 1.1 for a 0.1% (g/L) solution that was calculated on the basis of the frequency of tryptophan and tyrosine in vertebrate proteins.

Digested pooled peptides were then fractionated into 10 fractions using a High pH Reversed-Phase Peptide Fractionation Kit (Thermo Scientific™ Pierce™). Each fraction was concentrated by vacuum centrifugation and reconstituted in 15 μL of 0.1% (v/v) formic acid. Collected peptides were desalted on C18 cartridges (Empore™ SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 mL, Sigma) and reconstituted in 40 μL of 0.1% (v/v) formic acid.

The iRT-Kit (Biognosys) reagent was added to correct the relative retention time differences between runs with a volume proportion of 1:3 for iRT standard peptides versus sample peptides.

Data Dependent Acquisition (DDA) Mass Spectrometry Assay

All fractions for DDA library generation were analysed by a Thermo Scientific Q Exactive HF X mass spectrometer connected to an Easy nLC 1200 chromatography system (Thermo Scientific). The peptide (1.5 μg) was first loaded onto an EASY-SprayTM C18 Trap column (Thermo Scientific, P/N 164946, 3 µm, 75 µm*2 cm) and then separated on an EASY-SprayTM C18 LC Analytical Column (Thermo Scientific, ES802, 2 µm, 75 µm*25 cm) with a linear gradient of buffer B (84% acetonitrile and 0.1% formic acid) at a flow rate of 250 NL/min over 120 min. The MS detection method was positive ion, the scan range was 300-1800 m/z, the resolution for the MS1 scan was 60000 at 200 m/z, the target of AGC (automatic gain control) was 3e6, the maximum IT was 25 ms, and dynamic exclusion was 30.0 s. Each full MS-SIM scan followed 20 dd MS2 scans. The resolution for the MS2 scan was 15000, the AGC target was 5 e4, the maximum IT was 25 ms and the normalized collision energy was 30 eV.

Mass Spectrometry Assay for DIA

The peptides from each sample were analysed by LC-MS/MS operating in DIA mode by Shanghai Applied Protein Technology Co., Ltd. Each DIA cycle contained one full MS-SIM scan, and 30 DIA scans covered a mass range of 350-1800 m/z with the following settings: SIM full scan resolution 120000 at 200 m/z; AGC 3e6; maximum IT 50 ms; profile mode; DIA scan resolution 15 000; AGC target 3e6; Max IT auto; normalized collision energy 30 eV. The run time was 120 min with a linear gradient of buffer B (84% acetonitrile and 0.1% formic acid) at a flow rate of 250 NL/min. QC samples (pooled sample of equal aliquots of each sample in the experiment) were injected with DIA mode at the beginning of the MS study and after every 6 injections throughout the experiment in order to monitor the MS performance.

Mass spectrometry data analysis

For DDA library data, the FASTA sequence database was searched with SpectronautTM 14.4.200727.47784 software. The Uniprot_human database was used, and the iRT peptide sequence was added (Biognosys|iRTKit|). The parameters were set as follows: enzyme, trypsin; max missed cleavages, 2; fixed modification, carbamidomethyl ©; dynamic modifications, oxidation (M) and acetylation (protein N-terminus). All reported data were based on 99% confidence for protein identification as determined by false discovery rate (FDR = N(decoy)*2/(N(decoy)+ N(target))) ≤ 1%. A spectral library was constructed by importing the original raw files and DDA search results into Spectronaut Pulsar X TM_12.0.20491.4 (Biognosys).

DIA data were analysed with SpectronautTM 14.4.200727.47784 by searching the above constructed spectral library. The main software parameters were set as follows: the retention time prediction type was dynamic iRT, interference on MS2 level correction was enabled, and cross-run normalization was enabled. All results were filtered based on a Q value cut-off of 0.01 (equivalent to FDR < 1%).

Bioinformatic analysis

A protein whose abundance (fold change, FC) was upregulated by more than 1.5 times or downregulated by less than 0.67 times with a p value < 0.05 was regarded as a differentially expressed protein. All DEPs were subjected to hierarchical clustering analysis with Cluster 3.0 (http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm) and Java Tree View software (http://jtree view. source forge. net). The classified proteins were subjected to Gene Ontology (GO) analysis using Blast 2 GO software (http://www.blast2go.com/b2ghome) based on functional annotations for biological processes, molecular functions and cellular components. Following the annotation steps, the studied proteins were blasted against the online Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://geneontology.org/) to retrieve their KEGG orthology identifications and were subsequently mapped to pathways in KEGG. Enrichment analysis was applied based on Fisher’s exact test, considering all quantified proteins as the background dataset. Benjamini-Hochberg correction for multiple testing was further applied to adjust derived p values. Only functional categories and pathways with p values under a threshold of 0.05 were considered significant.

Statistical Analysis

Quantitative data are expressed as the mean ± standard deviation values. The characteristics of participants between controls and women with ICP were compared using independent samples t tests, and the difference in identified proteins was evaluated by one-way ANOVA. ROC analysis was utilized to screen for a biomarker combination for the diagnosis of ICP. All statistical analyses were performed with SPSS Statistics v23.0 (SPSS, Inc., Chicago, USA). A p value < 0.05 was considered statistically significant, and all tests were two tailed.

The clinical characteristics of ICP patients and healthy pregnant women

The characteristics of the participants are summarized in Table 1. The cases and controls were well matched for age, body mass index and gestational week. However, the serum TBA, ALT, and aspartate transferase (AST) levels of patients with ICP were significantly different from those of the normal controls.

Characterization of Exosomes

The morphology of the exosomes purified from the plasma of healthy individuals was visualized by transmission electron microscopy (TEM). As shown in Fig. 1A, typical cup-shaped vesicle exosomes could be observed. Nanoparticle tracking analysis (NTA) (Fig. 1B) indicated that exosomes had an variable size distribution ranging from 30 to 150 nm, in accordance with previous reports. WB tests and flow cytometry indicated that CD9, CD63 and CD81 were present in extracellular vesicles, and calnexin was absent (Fig. 1C, D and E). The above data indicated that the extracellular vesicles isolated from the peripheral blood of ICP patients were exosomes.

Proteomics analysis of exosomes in ICP patients and controls

Twenty-two raw DIA LC-MS/MS datasets were processed using Spectronaut software, and a total of 162 exosomal proteins were found to be significantly different in ICP patients and healthy controls based on the criterion of a p value less than 0.05 after Benjamini-Hochberg FDR adjustment. Among these proteins, 56 were downregulated and 106 were upregulated (Fig. 2A, fold change ≥ 1.50 or ≤ 0.67 and t test p value < 0.05). After normalization based on the z score, a clustered heatmap (Fig. 2B) was generated to show the expression intensity of these proteins, and these two sets of proteins (upregulated and downregulated) were separated into distinct clusters in the samples between the ICP and control groups, suggesting that DEPs could be used as an indicator for the classification of the samples.

Bioinformatics analysis of the proteomic results

GO analysis of DEPs was performed to understand their spectrum of biological and functional properties. GO terms were divided into three categories: biological process (BP), molecular function (MF), and cellular component (CC). The 20 most statistically significant items (p value < 0.05) of GO analysis are listed in Fig. 3A. Among BP categories, the exosomal proteins were mainly involved in cellular process (n = 59), biological regulation (n = 57), response to stimulus (n = 54), regulation of biological process (n = 53), metabolic process (n = 47), localization (n = 42), immune system process (n = 42), positive regulation of biological process (n = 41), etc. These results indicated that the molecular profiles and molecular mechanisms might differ between the ICP and healthy control groups. Furthermore, GO enrichment analysis revealed that these 162 proteins were involved in the MFs binding (n = 65), catalytic activity (n = 23), and molecular function regulation (n = 13). Among CC terms, these proteins were mainly associated with cell, cell part, organelle and extracellular region part, suggesting that these proteins originated from exosomes.

KEGG pathway enrichment analysis was used to analyse the significantly affected metabolic and signal transduction pathways associated with the DEPs. As shown in Fig. 3 (3B and 3C), the proteins with differential regulation between the ICP and healthy control groups (Groups B vs. A) participated mainly in the regulation of complement and coagulation cascades, coronavirus disease-COVID-19, staphylococcus aureus infection, neutrophil extracellular trap formation, systemic lupus erythematosus, phagosome, prion disease, pertussis, PI3K-Akt signalling pathway and Rap1 signalling pathway, which were the top ten modulated signalling pathways enriched among the dysregulated proteins. The KEGG pathways included complement and coagulation cascades, neutrophil extracellular trap formation, systemic lupus erythematosus, and the PI3K-Akt signalling pathway, which may be closely related to the development of ICP.

ROC curve analysis

To explore the diagnostic potential of these 162 proteins in ICP cases, all 162 proteins were further subjected to ROC curve analysis. The top five proteins with the greatest area under the curve (AUC) values are presented in Table 2 and are Elongation factor 1-alpha 1 (eEF1A1), Beta-2-glycoprotein I (β2-GP-I), Zinc finger protein 238 (ZNF238), CP protein and Ficolin-3. The AUCs of eEF1A1, β2-GP-I, ZNF238, CP protein and Ficolin-3 were all approximately 0.9 (AUC = 0.950, 0.901, 0.893, 0.950, 0.942, respectively), and they were all significantly differentially abundant in ICP and control subjects, indicating their promising diagnostic value.

Exosomes are phospholipid bilayer-enclosed extracellular vesicles that carry active substances, such as proteins and nucleic acids, derived from their parent cells. Exosomes have been found in various bodily fluids, including serum, plasma, urine and saliva. Due to their biocompatibility, low immunogenicity and ability to cross biological barriers, a large and growing number of studies exploring their potential role as noninvasive biomarkers for the early detection and prognosis of diseases have been produced [24]. Melo et al. [17] detected Glypican-1 (GPC1) + exosomes in almost 100% of early pancreatic cancer tissues, and Worst et al. [25] reported a potential diagnostic role of claudin 3 exosomes in prostate cancer screening. Ma Li et al. [7] verified the feasibility of using urinary exosomal miRNAs in the diagnosis of ICP by detecting the miRNA profile of urinary exosomes. Although various ICP biomarkers derived from omics data have been described, simple but robust proteomic analysis of serum-derived exosomes from ICP patients based on the DIA method has not been reported. In this study, by using quantitative DIA proteomics, we discovered that serum-derived exosomes completely distinguished ICP patients from healthy controls, suggesting that exosomal proteins could be used as a potential complementary tool in diagnosing ICP.

Our study demonstrated that exosomes derived from ICP patients contained more exosomal proteins than those derived from normal controls. We found that 162 proteins were significantly differentially expressed between ICP patients and controls, including 56 downregulated and 106 upregulated proteins in ICP. GO analysis showed that the exosomal proteins in patients with ICP were enriched in cellular process, biological regulation, response to stimulus, metabolic process, localization, immune system process, etc., suggesting that a combination of genetic disposition and hormonal and environmental factors favours ICP onset. ICP is caused by impaired hepatobiliary transport resulting in the retention of substances that are physiologically excreted with bile [9]. ICP is recognized to be associated with an abnormal metabolic profile [26], including glucose intolerance and dyslipidaemia, although it is considered to be secondary to aberrant maternal bile acid homeostasis, in which biological regulation, response to stimulus, and metabolic process play pivotal roles. Similarly, it has been reported that individuals with an abnormal metabolic profile are predisposed to developing ICP [27]. Our GO results showed that metabolic disorders may be primary causative factors of ICP pathogenesis. The KEGG pathway analysis revealed that the complement and coagulation cascades may be closely related to the development of ICP. Several studies have shown that the complement and coagulation cascades are not merely reactive to inflammation, immunity and haemostasis but are also critical determinants of liver disease pathogenesis.

The bioinformatic analysis revealed that most of the DEPs were functionally related to specific cell processes, including apoptosis, oxidative stress, lipid metabolism, cell cycle, immune response, cell proliferation and cell growth. Wei J et al. [28] identified differentially expressed genes in the placental tissues of ICP patients compared with normal controls, and most of the differentially expressed genes were involved in apoptosis, cell growth, immune response and transportation, which was essentially consistent with our DIA data. Our ROC curve results showed that the AUCs of eEF1A1, β2-GP-I, ZNF238, CP protein and Ficolin-3 were all approximately 0.9 (AUC = 0.950, 0.901, 0.893, 0.950, 0.942, respectively), indicating a significant role for these five proteins in differentiating ICP from controls. Proteomics analysis showed that all five DEPs were upregulated in ICP patients, with ICP/control ratios of 4.20, 3.22, 2.86, 2.40 and 2.21, respectively.

eEF1A1 is widely present in eukaryotic cells. It is a protein that plays an important role in promoting and controlling protein synthesis by catalysing the extension of amino acid chains on ribosomes. Studies have shown that eEF1A1 is involved in various signal transduction pathways in cells, including those related to translation control, cell growth, stress response and motility [29]. In addition, eEF1A1 is involved in a number of biochemical processes in the human body, including cell-cell interactions, apoptosis, cell proliferation and the occurrence and development of various tumours. The overexpression of eEF1A1 is closely related to the proliferation, invasion and migration of many types of cancer, such as ovarian cancer [30], cervical cancer [31], colon adenocarcinoma [32] and liver diseases [33]. β2-GP-I is a dominant plasma protein produced by the liver. Recent studies have shown that β2-GP-I has a certain relationship with HBV infection. β2-GP-I can bind to HbsAg and act as a carrier to mediate the invasion of HBV into hepatocytes. It also acts as a second messenger in the cell division regulation pathway by binding to annexin II and participates in cell proliferation [34]. ZNF238 is a class of C2H2-type zinc finger proteins with a length of approximately 58 kD, also known as RP58, TAZ-1, ZBTB18 and C2H2-171. Its N-terminus contains a BTB/POZ domain. Recent studies have found that the protein has functions in transcriptional inhibition and transcriptional activation and participates in chromatin assembly, which can promote cell growth and metastasis in a variety of tumour cells. ZNF238 was screened as a potentially novel biomarker with statistical significance among liver-specific proteins through initial enrichment analysis, indicating that it is particularly amenable to downstream clinical validation experiments [35].

Ceruloplasmin (CP) is another protein that was found to have an AUC over 0.9 in ICP analysis. As has been reported, CP is a copper-containing glycoprotein found in the globulin portion of human blood serum [36]. It is secreted by hepatocytes and excreted through the biliary tract. CP is an effective antioxidant that prevents lipid peroxidation by removing oxygen, and studies have shown that CP plays vital roles in copper ion transport and blood coagulation. When the liver is injured, CP acts as the acute phase reactive protein, and its levels can change significantly, indicating that CP could be used as a biomarker in the diagnosis of liver diseases such as cirrhosis and liver cancer [37]. Ficolin-3 (also called H-ficolin or Hakata antigen) is a complement-activating pattern recognition molecule that is synthesized by hepatocytes, bile duct epithelial cells, and ciliated bronchial and type II alveolar epithelial cells. Existing research shows that ficolin 3 is an important member of the ficolin family. It participates in the body's natural immunity by activating the lectin pathway[38]. The main pathological changes of chronic hepatitis are related to immune damage, and inflammatory factors may affect the progression of the disease. Research shows that the expression of plasma Ficolin-3 in chronic hepatitis is closely related to the degree of liver inflammation [39]. The above proteins play very important roles in cell proliferation and differentiation, energy conversion, signal transduction, and material transportation, strongly suggesting that exosomal proteins are closely related to the development of liver-specific disease.

In this study, we applied a simple but robust DIA-based quantitative exosomal proteomic profiling approach to distinguish ICP patients from healthy controls. The workflow is promising for clinical applications because it requires small serum amounts, various parent proteins are captured in exosomes, and the DIA method is reproducible and rapid. ROC curve analysis showed that the AUCs of eEF1A1, β2-GP-I, ZNF238, CP protein and Ficolin-3 were all approximately 0.9, indicating that these exosomal proteins from serum are promising and potentially efficient candidate biomarkers for ICP diagnosis. Future studies comparing the systemic expression of these candidate biomarkers and their precise roles in ICP are essential for conformation of this hypothesis.

Author contributions NLJ manuscript draft and interpretation. XSM experiments perform. ZJS oversaw the study design. LY data analysis. ZY and LXX text revision. CHY and LXZ samples and clinical data collect. ZXM and LH design, text revision and final approval.

Funding This work was financially supported by the Science and Technology Project of Jiangxi Province (grant nos. 20212BAB216065 and 20212BAG70006).

Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflict of Interest None of the authors declare a conflict of interest of any kind.

Ethical statement This study was approved by the Ethics Committee of Jiangxi Provincial Maternal and Child Health Hospital (registration number: EC-KT-202204 and EC-KT-202206, registered on January 5, 2022).

Informed consent: Informed consent was obtained from patients.

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Table 1 The clinical characteristics of ICP patients and healthy pregnant women

Parameter	ICP (n = 11)	Control (n = 11)	p value	T value/Z value
Age (years)	28.91 ± 1.87¹	29.27 ± 2.72	0.719	-.365³
BMI (kg/m²)	27.85 ± 2.36	25.74 ± 1.72	0.027	2.391
GA (days)	263.54 ± 16.71	277.00 ± 7.51	0.024	-2.436
ALT (U/L)	46.00 (8.00, 265.00)²	8.00 (6.00, 13.00)	0.016	-2.414⁴
AST (U/L)	38.00 (16.00, 244.00)	14.00 (13.00, 19.00)	0.010	-2.570
TBA (μmol/L)	58.70 (42.40, 68.00)	2.30 (1.70, 2.70)	0.000	-3.974
UA (μmol/L)	412.36 ± 116.07	325.63 ± 71.03	0.047	2.114
DBIL (μmol/L)	5.10 (4.00, 8.50)	3.80 (3.70, 4.30)	0.028	-2.203

BMI, body mass index; GA, gestational age; ALT, alanine transaminase; AST, aspartate transaminase; TBA, total bile acids; UA, uric acid; DBIL, direct bilirubin; ¹, mean ± standard deviation; ², median (25th percentile, 75th percentile). ³, Independent sample t test. ⁴, Mann–Whitney U test.

Table 2 Top five proteins ranked based on area under ROC curve

Name	Protein	AUC	FC (ICP/Con)	p value
A0A087WVQ9	eEF1A1	0.950	4.20673699	0.00017421
D9IWP9	β2-GP-I	0.901	3.221315174	0.000185999
A0A024R5T6	ZNF238	0.893	2.860499755	0.0000652829
A5PL27	CP protein	0.950	2.398264631	0.000382704
O75636	Ficolin-3	0.942	2.209914131	0.000371564

eEF1A1, Elongation factor 1-alpha 1; β2-GP-I, Beta-2-glycoprotein I; ZNF238, Zinc finger protein 238; AUC, area under curve; FC, fold change; ICP, intrahepatic cholestasis of pregnancy; Con, control.

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DIA-based Proteomics Analysis of Serum-derived Exosomal Proteins as Potential Candidate Biomarkers for Intrahepatic Cholestasis in Pregnancy

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