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Cross-Tissue Regulatory Network Analyses Reveal Novel Susceptibility Genes and Potential Mechanisms for Endometriosis
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Cross-Tissue Regulatory Network Analyses Reveal Novel Susceptibility Genes and Potential Mechanisms for Endometriosis
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Journal Article
Cross-Tissue Regulatory Network Analyses Reveal Novel Susceptibility Genes and Potential Mechanisms for Endometriosis
2024
Overview
Endometriosis (EMT) is a common gynecological disease with a strong genetic component, while its precise etiology remains elusive. This study aims to integrate transcriptome-wide association study (TWAS), Mendelian randomization (MR), and bioinformatics analyses to reveal novel putatively causal genes and potential mechanisms. We obtained summary-level data of the Genotype-Tissue Expression Project (GTEx), v8 expression quantitative loci (eQTL) data, and the genome-wide association study (GWAS) data of EMT and its subtypes from the R11 release results of the FinnGen consortium for analysis. GWAS data of modifiable risk factors were collected from IEU Open GWAS. Cross-tissue TWAS analyses were performed using the unified test for molecular signature (UTMOST), while functional summary-based imputation (FUSION) was employed for single-tissue TWAS analyses. Furthermore, we also conducted multi-marker analysis of genomic annotation (MAGMA) analyses to validate the significant associations. Subsequent Mendelian randomization (MR) and colocalization analysis elucidated the causal associations between the identified genes across various tissues and EMT. To further delve into mechanisms, two-sample network MR analyses were conducted. At last, bioinformatics analyses were employed to enhance our understanding of the functional implications and expression patterns of these identified genes. For EMT, 22 significant gene signals were identified by UTMOST, 615 by FUSION, and 354 by MAGMA. Ultimately, six genes, including CISD2, EFRB, GREB1, IMMT, SULT1E1, and UBE2D3, were identified as candidate susceptibility genes for EMT. Through similar procedures, we identified GREB1, IL1A, and SULT1E1 for EMT of the ovary, and we identified GREB1 for EMT of the pelvic peritoneum, EMT of rectovaginal septum and vagina, and deep EMT. In MR analyses, the expression of IMMT in 21 tissues, EFR3B in the adrenal gland, CISD2 in 17 tissues, and UBE2D3 in 7 tissues demonstrated causal relationships with EMT risk. In addition, CISD2, IMMT, and UBE2D3, across different tissues, exhibited strong colocalization with EMT (PPH4 > 0.7). Two-sample network MR analyses revealed that CISD2, EFR3B, and UBE2D3 could potentially regulate the levels of blood lipids and hip circumference so as to influence the risk of EMT. Furthermore, bioinformatics analyses confirmed our findings and delved into the biological functions of the identified genes. Our study unveiled seven novel candidate genes whose predicted expression was associated with the risk of EMT, providing new insights into the underlying genetic framework of EMT. These findings will facilitate a deeper comprehension of the tissue-specific transcriptional regulatory mechanisms associated with EMT, paving the way for optimizing the management and treatment of EMT.
