O-306 Genome-wide association meta-analysis supports the association between MUC1 and ectopic pregnancy

Abstract

Abstract Study question Can we identify genetic variants associated with ectopic pregnancy by undertaking the first genome-wide association study leveraging two large-scale biobank initiatives? Summary answer We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 as the most plausible affected gene. What is known already Ectopic pregnancy is an important cause of maternal morbidity and mortality worldwide. Despite being a common early pregnancy complication, the genetic predisposition to this condition remains understudied and no large scale genetic studies have been performed so far. Study design, size, duration A GWAS meta-analysis including 7,070 women with ectopic pregnancy and 248,810 controls from Estonian Biobank and the FinnGen study. Several post-GWAS analysis were conducted to characterise the genetic signals, as well as to analyse the genetic and phenotypic relationships with the condition. Participants/materials, setting, methods We identified ectopic pregnancy cases from national registers by ICD codes (ICD-10 O00), and all remaining women were considered controls. Main results and the role of chance We identified two genome-wide significant loci on chromosomes 1 (rs4971091, p = 5.32x10-9 ) and 10 (rs11598956, p = 2.41x10-8 ). Follow-up analyses propose MUC1, an epithelial glycoprotein with an important role in barrier function, as the most likely candidate for the association on chromosome 1. We also characterise the phenotypic and genetic correlations with other phenotypes, identifying a genetic correlation with smoking and diseases of the (genito)urinary and gastrointestinal system, and phenotypic correlations with various reproductive health diagnoses, reflecting the previously known epidemiological associations. Limitations, reasons for caution The main limitation is that the findings apply to European-based ancestry populations and we only captured maternal genomes. Wider implications of the findings This study encourages the use of large scale genetic datasets to unravel genetic factors linked to ectopic pregnancy, which is difficult to study in experimental settings. Increased sample size might bring additional genetic factors associating with ectopic pregnancy and inform its heritability. Trial registration number not applicable