Background Peripheral T-cell lymphoma (PTCL) is a rare and heterogeneous group of hematological malignancies. Treatment options are limited and often unsatisfactory, leading to a poor prognosis in most subtypes.Objective This study aimed to identify potential biomarker genes for PTCL and to explore the underlying mechanisms by integrating machine learning, Mendelian Randomization (MR), and experimental validation.Methods Microarray datasets (GSE6338, GSE14879, and GSE59307) were downloaded from the Gene Expression Omnibus database. Differential expression analysis was conducted to identify the Differentially Expressed Genes (DEGs) between patients with PTCL and controls. A machine learning algorithm was then used to further refine the selection of characteristic genes for PTCL. We integrated genome-wide association studies data with expression quantitative trait loci data to identify genes with potential causal relationships to PTCL. Functional analysis was performed to explore underlying mechanisms. Finally, the identified gene was validated in clinical samples from patients with PTCL and controls.Results Based on 60 DEGs, the least absolute shrinkage and selection operator algorithm identified nine characteristic genes for PTCL. MR analysis revealed 203 genes with causal effects on PTCL, ultimately identifying one co-expressed gene: Basic Leucine Zipper ATF-like Transcription Factor 3 (BATF3). It demonstrated good predictive performance across various PTCL subtypes, with AUC values ranging from 0.7 to 1. Functional analysis suggested that BATF3 may play a role in PTCL through immune-related pathways. Experimental validation using clinical samples further suggested the potential of this biomarker gene in PTCL.Conclusion By combining machine learning, MR, and experimental validation, we identified and validated BATF3 as a promising biomarker of PTCL. These findings provide insights into the molecular mechanisms underlying PTCL and may inform the development of effective treatment strategies for this disease.

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder characterized by dysregulated bile acid metabolism, which can lead to severe adverse pregnancy outcomes. Glycine-conjugated deoxycholic acid (G-DCA) is a small-molecule metabolite that has been reported to be elevated in the serum of patients with ICP; however, its clinical application remains limited because conventional chromatographic methods for its quantification are time-consuming, costly, and not well-suited for rapid clinical screening. To address this gap, we developed a time-resolved fluorescence immunochromatographic test strip (TRF-ICTS) for the quantitative detection of serum G-DCA. Based on a small-molecule competitive binding design, the assay requires only 10 μl of serum sample and enables rapid detection within 16 min. The TRF-ICTS demonstrated good analytical performance, with a linear range of 0.05-10.0 ng/ml and a detection limit of 0.074 ng/ml, and maintained stable performance over two weeks of storage at both 4°C and 37°C. The results showed good quantitative agreement with LC-MS/MS measurements. Evaluation of sensitivity, specificity, and precision demonstrated that all parameters were within acceptable ranges. Clinical validation using serum samples from ICP patients and healthy pregnant women showed that G-DCA levels were elevated across different trimesters and were more pronounced in patients with severe ICP and adverse pregnancy outcomes. Overall, the developed TRF-ICTS provides a rapid and sensitive method for quantifying G-DCA, which may serve as a complementary biomarker for ICP diagnosis and disease stratification, providing additional insights into bile acid changes following UDCA treatment.

Based on the differences in drug resistance characteristics between Candida glabrata and Candida krusei and the clinical need for rapid discrimination, this study established a duplex recombinase polymerase amplification-lateral flow strip (RPA-LFS) detection system using dual-labeled probes. By optimizing ITS2-targeted primers and probes (5′-end labeled with FITC/DIG, 3′-end labeled with biotin) and integrating dual test lines on the strip (streptavidin-T line for directional capture), simultaneous visual detection of both targets was achieved. Performance validation demonstrated: a detection limit of 10 copies/mL and 100 copies/mL, matching qPCR sensitivity; 100% detection rate for 30 target strains (including 12 reference and clinical isolates) with strict discrimination from 8 closely related pathogens (0% cross-reactivity); high concordance with qPCR in 328 clinical samples (sensitivity, specificity, and total concordance all 100%). The system delivers “sample-to-result” output within 30 min without complex instrumentation, providing technical support for precise point-of-care discrimination of drug-resistant Candida infections and rational antifungal drug use, particularly in primary healthcare settings and outbreak scenarios.

INTRODUCTION:Follicular lymphoma (FL) is the second most common lymphoma type. However, the molecular mechanisms underlying its pathogenesis remain poorly understood. This study aimed to identify and validate potential FL biomarkers using a combination of microarray analysis, machine learning, and experimental validation. METHODS:Differential expression analysis was performed to identify differentially expressed genes (DEGs) between FL patients and matched controls using microarray datasets. Multiple machine learning algorithms were used to identify the hub genes for FL. The predictive performance was further evaluated using the receiver operating characteristic curves for all datasets. Functional analyses were performed to explore the underlying mechanisms. The expression of the biomarker was validated in clinical FL samples. Additionally, gene knockdown and overexpression experiments were conducted to assess the effects of the biomarker on biological functions, such as cell proliferation, apoptosis, and migration in FL cells. RESULTS:A total of 144 DEGs were identified between the FL and control samples. Machine learning algorithms refined the four FL hub genes. Following comprehensive evaluations across all datasets, placenta-associated 8 (PLAC8) was identified as the most significant gene with area under the curve values exceeding 0.879 for all datasets. Functional analyses suggested a correlation between PLAC8 and immune-related pathways in FL. In clinical samples, PLAC8 expression was significantly lower in patients with FL than in controls. Experimental validation revealed that reduced PLAC8 expression enhanced FL cell proliferation and migration while, inhibiting apoptosis, whereas increased PLAC8 expression suppressed proliferation, activated apoptotic pathways, and reduced migration in vitro. DISCUSSION:The combination of microarray analysis and machine learning enables the identification of key variables and complex relationships within the data, offering insights that might be overlooked by traditional methods. Our findings were further supported by experimental validation, underscoring the potential clinical relevance. This integrated approach provides a robust framework for the discovery of biomarkers of complex diseases. CONCLUSION:This study identified and validated PLAC8 as a promising biomarker for FL. Functional experiments further demonstrated that PLAC8 plays a regulatory role in FL cell behavior in vitro. These findings provide insights into the molecular mechanisms underlying this disease.

Lung cancer is a highly aggressive malignancy associated with a high global mortality rate. Immunotherapy, particularly anti‑programmed cell death protein 1 (PD‑1) therapy, has offered new hope for patients; however, therapeutic resistance remains a major obstacle to clinical success. In the present study, single‑cell RNA sequencing was utilized to investigate the molecular characteristics of lung cancer and to elucidate the mechanisms underlying resistance to anti‑PD‑1 immunotherapy. Cancer‑associated fibroblasts (CAFs) were identified as key contributors to immune resistance. Functional assays, including CCK‑8, EdU, TUNEL and Transwell experiments, demonstrated that CAFs regulated the expression of lipocalin 2 (LCN2) in lung cancer cells, and elevated LCN2 levels were found to promote resistance to immunotherapy, as well as to enhance cellular proliferation and invasion. The effects of LCN2 on tumor growth, invasion, immune infiltration and ferroptosis were further validated by molecular and histological analyses. The results showed that silencing LCN2 induced ferroptosis in lung cancer cells, resulting in increased sensitivity to anti‑PD‑1 therapy, suppressed tumor growth and reduced invasiveness. These findings highlight the critical role of the CAF‑LCN2 axis in mediating resistance to anti‑PD‑1 immunotherapy and suggest that targeting this pathway may represent a promising strategy to enhance treatment efficacy in lung cancer.

Yao Wang,1,* Meng Lin,1,* Qi Sun,2 Tianfei Fan,1 Minglu Zhou,1 Wei Yang,1 Ting Zhang11Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China; 2Department of Pharmaceutics, School of Pharmaceutical Sciences, Capital Medical university, Beijing, 100069, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ting Zhang, Email zhangtingyx@yeah.netAbstract: Rheumatoid arthritis (RA) is a systemic autoimmune disease associated with a high disability rate. Its core pathogenesis involves immune dysregulation, characterized notably by the aberrant polarization of macrophages toward the pro-inflammatory M1 phenotype, along with the abnormal proliferation and invasion of fibroblast-like synoviocytes. These interrelated processes collectively contribute to progressive joint destruction. Although traditional drug therapies can alleviate symptoms, they are frequently accompanied by significant side effects and fail to achieve curative outcome. In this context, smart polymer nanoparticles (SPNs) have emerged as a promising platform for rheumatoid arthritis therapy, offering multifunctional capabilities. Here, we provide a comprehensive and timely analysis of the multifaceted therapeutic applications of SPNs in RA. By delivering immunomodulatory agents, smart polymer nanoparticles can rebalance macrophage polarization, promoting M1-to-M2 conversion. Moreover, they effectively suppress the pathological activation of fibroblasts, thereby inhibiting synovial proliferation and bone invasion. Furthermore, these nanoparticles can also disrupt the vicious cycle of disease progression by ameliorating metabolic dysregulation within the joint microenvironment. The challenges for the clinical translation of SPNs in RA therapy are discussed and the possible solutions are proposed. Collectively, SPNs fundamentally intervene in RA pathogenesis through precise targeting and intelligent drug release, enabling a highly effective and low-toxicity strategy.Keywords: smart polymer nanoparticles, rheumatoid arthritis, macrophages, fibroblasts, microenvironment

Serum biomarkers play a key role in the early diagnosis and risk stratification of intrahepatic cholestasis of pregnancy (ICP). Our previous study showed that acyl-CoA oxidase 1 (ACOX1) was elevated in the serum and placenta of ICP patients. In this study, a pair of commercially available anti-ACOX1 antibodies was purchased and used to develop a double-antibody sandwich time-resolved fluorescent nanomicrosphere immunochromatographic (TRFNI) strip for the quantitative detection of ACOX1 in serum. Methodological evaluation showed that the strip exhibited good linearity over a calibration set consisting of a blank and standards from 0.25 to 20 ng/mL, with intra-assay and inter-assay coefficients of variation (CVs) below 10% and 15%, respectively. The buffer-based LOD was 0.19 ng/mL, and the lower limit of the reportable quantitative range should not be set below the calculated LOQ of 0.29 ng/mL. In a preliminary accelerated storage assessment, the T/C ratio at 1 ng/mL remained relatively stable during 20 days at 37 °C. The TRFNI assay also showed correlation with a commercial ELISA kit and exhibited recovery rates of 85.5-100.5%. Furthermore, ACOX1 demonstrated an area under the receiver operating characteristic curve (AUC) of 0.731 for distinguishing severe from mild ICP and an AUC of 0.700 for discriminating adverse perinatal outcomes. This assay may warrant further evaluation as an exploratory adjunctive approach for measuring serum ACOX1 in ICP, pending prospective validation against disease-control cohorts and full serum-matrix analytical characterisation.

This study aimed to assess the predictive capability of a combination of fasting plasma glucose (FPG) and plasma exosomal miRNAs in determining the occurrence of gestational diabetes mellitus (GDM) during the first trimester. We conducted a cross-sectional study involving randomly recruited 193 pregnant women based on exclusion criteria. Blood samples were collected at 10–14 weeks of gestation for analysis of miR-16-5p, miR-29a-3p, and FPG levels. The pregnant women were categorized into 60 GDM cases and 103 without GDM, based on a 75-g oral glucose tolerance test performed between 24 and 28 weeks of pregnancy, and excluded 30 cases. The predictive values of miR-16-5p, miR-29a-3p, and FPG for GDM were assessed using a receiver operating characteristic curve. Three databases, miRDB, TargetScan, and miRWalk, were used to predict the functions of target genes miR-16-5p and miR-29a-3p. The areas under the curve (AUC) of FPG, plasma exosomal miR-16-5p, and miR-29a-3p in predicting GDM were 0.698, 0.743, and 0.727, respectively. Combining the three factors resulted in an AUC of 0.874, with a sensitivity of 0.867 and specificity of 0.767. The selected miRNAs, miR-16-5p and miR-29a-3p, were significantly enriched in carbohydrate metabolism and glucose homeostasis, involved in the P53 signaling pathway in GDM. The combination of FPG with miRNAs demonstrated a larger AUC, along with higher sensitivity and specificity in predicting GDM.

[This corrects the article DOI: 10.3389/fmicb.2025.1643691.].

Previous studies have indicated that the inflammatory microenvironment in pregnant women may contribute significantly to the development of intrahepatic cholestasis of pregnancy (ICP). However, the exact relationship between inflammatory blood parameters and ICP remains uncertain. This study aims to explore the relationship between serum inflammatory factors, inflammatory scoring indicators, and adverse pregnancy outcomes in ICP. Serum samples were collected after 25 weeks of gestation from women clinically diagnosed with ICP, as well as from gestational age-matched healthy pregnant controls. Cytokine levels were subsequently measured using flow cytometry. Correlation analysis was conducted to explore potential relationships between blood inflammatory parameters and other ICP-related markers. Receiver operating characteristic (ROC) curves were generated to evaluate their predictive performance for adverse pregnancy outcomes. Mendelian randomization (MR) analysis was performed to examine potential causal links between inflammation and ICP development. The results revealed significant differences in serum levels of interleukin-6 (IL-6), interleukin-10 (IL-10), tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ) between ICP patients and healthy controls. Additionally, inflammatory scoring indicators were significantly elevated in ICP patients. Most inflammatory parameters correlated with liver function indices and showed positive associations with total bile acids (TBAs). ROC analysis demonstrated that combining inflammatory markers with TBA improved the predictive accuracy for preterm birth (area under the ROC curve [AUC]: 0.865) and low fetal weight (AUC: 0.916). MR analysis identified interleukin-2 (IL-2) and TNF-α as potential risk factors for ICP. Based on these findings, blood inflammatory parameters may serve as accessible and cost-effective indicators for understanding the inflammatory microenvironment in ICP and predicting fetal outcomes.

Sustained human papillomavirus (HPV) infection induces cervical intraepithelial neoplasia (CIN), a well-established precursor lesion and risk factor for cervical cancer. However, the specific long noncoding RNAs (lncRNAs) that regulate CIN progression remain poorly characterized. Herein, we identified a novel lncRNA, designated CIN-related lncRNA (CRL), and explored its role in CIN pathogenesis. Clinically, reduced CRL expression was significantly associated with advanced CIN stages, suggesting a potential correlation with disease severity. HPV oncoproteins E6 and E7 suppressed CRL expression through KDM2B-mediated modification of histone H3 lysine 4 trimethylation (H3K4me3). CRL repressed CIN progression and cell death in vitro. Further mechanistic investigations revealed that CRL exerted this inhibitory effect by suppressing ferroptosis. Importantly, CRL accelerated the degradation of transferrin receptor (TFRC) mRNA by interacting with the iron-sensing protein iron-responsive element-binding protein 2 (IREB2). Collectively, our findings highlight the functional importance of lncRNA CRL in HPV-induced CIN progression, specifically through its regulation of ferroptosis via the IREB2-TFRC axis. This study provides new insights into the molecular mechanisms underlying CIN development and identifies CRL as a potential candidate for CIN diagnosis or intervention.

Intrahepatic cholestasis of pregnancy (ICP) is characterized by bile acid accumulation, placental dysfunction, and adverse perinatal outcomes. However, there is currently no reliable tool to predict the occurrence of severe ICP or its associated complications, and its pathophysiology remains incompletely understood. The objective of this study was to identify more sensitive and specific biomarkers for the clinical diagnosis, early prediction, and prognostic assessment of adverse outcomes in ICP, and to explore the biological relevance of the identified pathway at the maternal-fetal interface. We performed integrated serum metabolomic-proteomic analysis, followed by trimester-specific clinical validation, placental tissue analysis, in vitro trophoblast experiments, and in vivo validation in an estrogen-induced ICP rat model. Exploratory multi-omics analysis highlighted the thyroxine-binding globulin-thyroxine (TBG-T4) axis, related to thyroid hormone transport and availability, as a biologically relevant pathway in ICP. Although total and free T4 remained within physiological reference ranges, circulating TBG, total T4, and free T4 were significantly reduced across pregnancy in women with ICP and were associated with biochemical cholestasis, earlier delivery, and lower neonatal birth weight. Mechanistic analyses showed that reduced TBG availability was associated with decreased local T4 availability and enhanced trophoblast apoptosis under bile acid stress. In the ICP rat model, Ad-TBG-mediated TBG overexpression partially restored thyroid hormone homeostasis, attenuated placental and hepatic injury, and improved fetal growth and survival. These findings identify disruption of the TBG-T4 axis as a mechanistic link between cholestatic stress, impaired thyroid hormone availability, and trophoblast apoptosis in ICP.

A specific liver disease during pregnancy is intrahepatic cholestasis of pregnancy (ICP). The current clinical diagnosis mainly depends on the level of serum total bile acid (TBA), which lacks sensitivity and specificity. Lactate dehydrogenase A (LDHA) is a new biomarker highly expressed in the serum of ICP patients, which was screened by data-independent acquisition (DIA) proteomic technology in our previous studies. There is currently a lack of a rapid, quantitative, and sensitive detection method to measure LDHA levels in serum. This study aimed to establish a time-resolved fluorescent nanomicrospheres immunochromatographic test strip to detect LDHA in serum and evaluate its value in clinical diagnosis and treatment of ICP. Subsequently, the mechanism of LDHA in mediating the inflammatory of ICP was explored in vitro. In vitro, taurocholic acid (TCA) at a concentration of 100 μM was used to simulate an ICP environment. The AKT/mTOR/HIF-1α signaling pathway was activated in TCA-treated HTR-8/SVeno cells, leading to an increase in LDHA levels. The lactic acid produced by LDHA-mediated glycolytic metabolism may be related to the regulation of inflammation in placental trophoblast cells. According to these findings, LDHA could be a new target that provide promising ideas for the diagnosis, prediction and treatment of ICP.

Appressoria are specialized penetration structures for many plant pathogenic fungi, including the rice blast fungus Magnaporthe oryzae, which evolves a set of complicated regulatory mechanisms to control appressorium development and function. Cell cycle control is essential for appressorium-mediated penetration, but the mechanism underlying its role remains largely elusive. Here, a conserved protein MoMtg1 is identified in filamentous fungi as a novel transcriptional repressor that plays a crucial role in cell cycle regulation. MoMtg1 directly interacts with transcription factor MoSwi6 and inhibits its transcriptional activity. Deletion of MoMtg1 or MoSwi6 results in cell cycle defects during appressorium development. Both mutants are abnormal in melanization, appressorium turgor generation, reactive oxygen species (ROS) accumulation, and septin assembly. MoSwi6 positively and MoMtg1 negatively regulate the expression of MoCYC1, the cyclin gene essential for maintaining normal appressorium development. Overexpression of MoCYC1 in the wild type resulted in similar defects in appressorium development and function with ∆Momtg1 and ∆Moswi6 mutants. It is also shown that silencing MoMTG1 with the host-induced gene silencing strategy conferred resistance against M. oryzae in transgenic plants. Furthermore, a small molecule is identified as a MoMtg1-inhibitor by protein modelling and shows to inhibit MoMtg1 functions and reduce M. oryzae infection. Overall, the study reports a novel cell cycle regulator and its underlying mechanisms during appressorium-mediated penetration, which has great potentials as a target for disease control.

BACKGROUND:Hepatocellular carcinoma exhibits high heterogeneity regarding its molecular and cellular characteristics. Biochanin A (Bio-A) has demonstrated promising clinical anti-tumor effects. PURPOSE:This study aimed to examine the effects of Bio-A treatment on the proliferation, apoptosis, invasion, and migration of the human hepatocellular carcinoma cell line HepG2. METHODS:HepG2 cells were treated with varying concentrations of Biochanin A. The MTT assay was employed to assess cell proliferation, the scratch test was utilized to evaluate cell migration, and flow cytometry was conducted to analyze the cell cycle. Potential targets were identified through network pharmacology and subsequently verified via molecular docking. RESULTS:Bio-A treatment significantly inhibited the proliferation and migration of HepG2 cells (p < 0.05). There was a significant increase in the proportion of cells in the G1/G0 phase in the Bio-A group (p < 0.05). A total of 16 intersection targets between Bio-A and liver cancer were identified through bioinformatics analysis. The potential targets were predominantly enriched in cancer-related signaling pathways. Molecular docking confirmed that Bio-A formed stable complexes with NCOA3 and PPARG. CONCLUSION:Biochanin A exerts a significant inhibitory effect on the biological functions of HepG2 cells.

Group B Streptococcus (GBS), a primary pathogen associated with perinatal and maternal infections, can lead to severe complications such as preterm birth, miscarriage, and stillbirth. In this study, we report the isolation of GBS from the blood of a patient with sepsis who had delivered a stillborn. Genome sequencing was performed using the Pacbio Sequel II and DNBSEQ platform. GBS-B4009 contained a circular chromosome with a total length of 2,277,992 bp and the GC content of the chromosome was determined to be 35.97 %. The whole genome sequence contained 2256 predicted coding sequences, including 21 ribosomal RNA (rRNA), 81 transfer RNA (tRNA), and 24 small RNAs (sRNAs). Additionally, we also isolated GBS from two additional pregnant women: GBS-M14, isolated from the pregnant woman whose newborn developed an early-onset GBS infection (EOGBS), and GBS-M18, isolated from the pregnant woman whose newborn remained healthy. Further analysis of the three genomes revealed unique genetic features in each strain, providing insights into the genetic diversity of GBS and its role in different clinical outcomes. Sequences and sample data for all three strains have been deposited in GenBank under accession numbers CP163561 (GBS-B4009), CP180685 (GBS-M14) and CP180684 (GBS-M18).

Zearalenone (ZEN) is a toxic compound in the metabolism of genus Fusarium, posing a threat to food and feed safety, and it is necessary to develop recognition elements for ZEN. Recombinant antibody (rAb) is a promising alternative for immunoassays. In this study, the recombinant single-chain antibody (ZEN-scFv) was produced in Escherichia coli (E. coli), Pichia pastoris (P. pastoris) GS115, and Expi293F cells, respectively. Meanwhile, a recombinant full-length antibody (ZEN-IgG) was successfully obtained from Expi293F cells, achieving a maximum yield of approximately 50 mg/L. Property analysis revealed that rAbs from Expi293F cells exhibited greater sensitivity and better affinity than those generated in E. coli BL21 and P. pastoris GS115. The interactions between ZEN and anti-ZEN rAb were further analyzed using molecular docking. Finally, a colloidal gold immunoassay test strip (CGIT) was established based on ZEN-IgG from Expi293F cells, with a visual limit of detection (vLOD) of 10 ng/mL. The results of real sample determination indicated that ZEN-IgG served as a suitable rAb for CGIT in mycotoxin detection.

Intrahepatic cholestasis of pregnancy (ICP) is associated with adverse fetal outcomes, while current biomarkers such as total bile acid remain suboptimal. This study aimed to identify novel biomarkers and clarify metabolic pathways underlying ICP through integrated metabolomic and proteomic analyses. Placental profiles were obtained from ICP model rats and healthy controls, with differential metabolites and proteins validated in human placental and serum samples. Multiomics integration revealed prominent dysregulation of lipid metabolism, particularly fatty acid degradation and biosynthesis, highlighting lipids as central players in ICP. Palmitic acid and acyl-CoA synthetase long chain family member 1 (ACSL1) were central to these pathways, markedly elevated in ICP, and showed high diagnostic value (area under the curve 0.794 and 0.825), with combined detection reaching 0.894. Both markers also stratified patients by disease severity, suggesting their potential use for disease monitoring and risk classification. Moreover, ferroptosis was implicated in ICP pathophysiology, supported by validations in both patient placental tissues and taurocholic acid (TCA)-treated trophoblast cells, showing reduced glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) together with increased six-transmembrane epithelial antigen of prostate 3 (STEAP3), transferrin receptor protein 1 (CD71), and acyl-CoA synthetase long-chain family member 4 (ACSL4). In summary, palmitic acid and ACSL1 represent promising biomarkers for ICP diagnosis and classification, while ferroptosis contributes to ICP-related placental dysfunction. These findings provide comprehensive evidence linking altered lipid metabolism and ferroptosis to ICP, offering new insights for clinical diagnosis and potential therapeutic strategies.

Intrahepatic cholestasis of pregnancy (ICP) is a prevalent liver disorder that typically occurs during the second and third trimesters of pregnancy and is associated with adverse perinatal outcomes. Currently, total bile acid (TBA) serves as the primary diagnostic biomarker in clinical settings. but its sensitivity and specificity are limited. The relationship between microRNA (miRNA) encoded by human cytomegalovirus (HCMV) and ICP remains unclear. This study retrospectively analyzed serum samples from 151 pregnant women diagnosed with ICP and 158 age-matched healthy controls between October 2021 and July 2024. A three-phase research design (training set, validation set, and testing set) was implemented to comprehensively assess the expression levels of 24 HCMV-encoded miRNAs using TaqMan probe-based RT-qPCR, a highly specific detection method. The receiver operating characteristic (ROC) curve and logistic regression analysis were used for evaluation. Meanwhile, serum HCMV IgG/IgM levels and whole-blood HCMV DNA copy numbers were measured, and potential target genes were predicted. RT-qPCR results revealed six miRNAs (hcmv-miR-UL22A-5p, hcmv-miR-US4-5p, hcmv-miR-US4-3p, hcmv-miR-UL112-5p, hcmv-miR-UL148D and hcmv-miR-US25-2-5p) were significantly upregulated in ICP patients (p < 0.001) and their combined detection yielded the maximum area under the curve(AUC) of 0.814. Logistic regression analysis indicated that they could potentially serve as independent risk factors for ICP. Serological analysis showed comparable HCMV IgG positivity rates between the two groups (96.8% in controls vs. 97.4% in ICP cases). Although HCMV DNA was undetectable in both groups, the IgM level in ICP pregnant women was increased (p < 0.05). Target gene prediction suggests that these miRNAs may be involved in the pathogenesis of ICP by regulating multiple host genes. The panel of six HCMV miRNAs identified in this study holds promise as a novel liquid biopsy-based diagnostic molecular marker, which could enhance the accuracy of ICP diagnosis in clinical practice and provide molecular evidence supporting the role of latent viral infection in ICP development.