4.2 Article

Beyond Endometriosis Genome-Wide Association Study: From Genomics to Phenomics to the Patient

期刊

SEMINARS IN REPRODUCTIVE MEDICINE
卷 34, 期 4, 页码 242-254

出版社

THIEME MEDICAL PUBL INC
DOI: 10.1055/s-0036-1585408

关键词

endometriosis; genes; genome-wide association study; epigenetic; phenotype; EPHect

资金

  1. MRC [MR/K011480/1]
  2. NHMRC [339446, 619667]
  3. Wellcome Trust [WT098017]
  4. MRC [MR/K011480/1] Funding Source: UKRI
  5. Medical Research Council [MR/K011480/1] Funding Source: researchfish

向作者/读者索取更多资源

Endometriosis is a heritable, complex chronic inflammatory disease, for which much of the causal pathogenic mechanism remains unknown. Genome-wide association studies (GWAS) to date have identified 12 single nucleotide polymorphisms at 10 independent genetic loci associated with endometriosis. Most of these were more strongly associated with revised American Fertility Society stage III/IV, rather than stage III. The loci are almost all located in intergenic regions that are known to play a role in the regulation of expression of target genes yet to be identified. To identify the target genes and pathways perturbed by the implicated variants, studies are required involving functional genomic annotation of the surrounding chromosomal regions, in terms of transcription factor binding, epigenetic modification (e.g., DNA methylation and histone modification) sites, as well as their correlation with RNA transcription. These studies need to be conducted in tissue types relevant to endometriosis in particular, endometrium. In addition, to allow biologically and clinically relevant interpretation of molecular profiling data, they need to be combined and correlated with detailed, systematically collected phenotypic information (surgical and clinical). The WERF Endometriosis Phenome and Biobanking Harmonisation Project is a global standardization initiative that has produced consensus data and sample collection protocols for endometriosis research. These now pave the way for collaborative studies integrating phenomic with genomic data, to identify informative subtypes of endometriosis that will enhance understanding of the pathogenic mechanisms of the disease and discovery of novel, targeted treatments.

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