PubMed HealthSearch

PubMed · 41232153

Role of HLA-DRA-CREB3L4 regulatory axis in the pathogenesis of ovarian endometriosis: Inhibition of CREB3L4 expression by HLA-DRA increases the risk of disease.

Abstract

BACKGROUND: Ovarian endometriosis is a common gynecological condition characterized by the abnormal growth of endometrial-like tissue in locations outside the uterus, and its development remains poorly understood. This study aims to investigate potential protein regulatory networks and assess their impact on disease risk using both protein quantitative trait locus (pQTL) analysis and Mendelian randomization (MR) techniques. METHODS: This study systematically integrates two major genome-wide pQTL databases, UKB-PPP and deCODE, to identify pQTL signals associated with ovarian endometriosis. Additionally, we utilized the GEO database to validate differences in protein expression. We conducted a Mendelian randomization analysis to further explore the regulatory relationships between proteins and their roles in disease development. RESULTS: After the Bonferroni correction, we identified 33 pQTL signals from UKB-PPP and 19 pQTL signals from deCODE. Among these, 8 signals from UKB-PPP and 3 signals from deCODE were validated based on expression differences. The mediation analysis results indicate that HLA-DRA significantly increases the risk of developing ovarian endometriosis by inhibiting the expression of CREB3L4 (with a mediation proportion of 13.99 %), and the direction of the mediation effect is consistent with the total effect. CONCLUSION: This study provides new insights that HLA-DRA downregulates the expression of CREB3L4, which may affect the risk of developing endometriosis. The results provide new evidence for understanding the genetic and molecular basis of ovarian endometriosis and establish a theoretical foundation for the development of future diagnostic markers and targeted treatment strategies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Weiwei Song, Sisi Jin, Gang Wang, Yining Zhou, Juan Yu. 2025-11-11. Role of HLA-DRA-CREB3L4 regulatory axis in the pathogenesis of ovarian endometriosis: Inhibition of CREB3L4 expression by HLA-DRA increases the risk of disease.. https://doi.org/10.1016/j.jri.2025.104798

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans