Genome-wide association study meta-analysis supports association between MUC1 and ectopic pregnancy

Abstract

Study question: Can we identify genetic variants associated with ectopic pregnancy by undertaking the first genome-wide association study (GWAS) leveraging two large-scale biobank initiatives?

Summary answer: We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 (mucin 1) 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 7070 women with ectopic pregnancy and 248 810 controls from Estonian Biobank and the FinnGen study.

Participants/materials, setting, methods: We identified ectopic pregnancy cases from national registers by ICD (International Classification of Disease) codes (ICD-10 O00), and all remaining women were considered controls. We carried out standard GWAS meta-analysis and additionally annotated GWAS signals, analysed co-localization with quantitative trait loci, estimated genetic correlations and identified associated phenotypes to characterize the genetic signals, as well as to analyse the genetic and phenotypic relationships with the condition.

Main results and the role of chance: We identified two genome-wide significant loci on chromosomes 1 (rs4971091, P = 5.32×10-9) and 10 (rs11598956, P = 2.41×10-8) potentially associated with ectopic pregnancy. Follow-up analyses propose MUC1, which codes for an epithelial glycoprotein with an important role in barrier function, as the most likely candidate gene for the association on chromosome 1. We also characterize 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.

Large scale data: The GWAS meta-analysis summary statistics are available from the GWAS Catalogue (GCST90272883).

Limitations, reasons for caution: The main limitation is that the findings are based on European-based ancestry populations, with limited data on other populations, and we only captured maternal genomes. Additionally, further larger meta-analysis or independent studies are needed to validate these findings.

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. Altogether, our results provide more insight into the biology of ectopic pregnancy and, accordingly, the biological processes governing embryo implantation.

Study funding/competing interest(s): N.P.G. was supported by MATER Marie Sklodowska-Curie which received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 813707. This study was funded by European Union through the European Regional Development Fund Project No. 2014-2020.4.01.15-0012 GENTRANSMED. Computations were performed in the High-Performance Computing Center of University of Tartu. The authors declare no competing interests.

Keywords: GWAS; MUC1; ectopic pregnancy; genome-wide association study; pregnancy complication.

Figure 1.

Manhattan and locus zoom plots for genome-wide association study (GWAS) meta-analysis for ectopic pregnancy. On the Manhattan plot, the y axis represents −log₁₀(P-values) for association of variants with ectopic pregnancy. The horizontal dashed line represents the threshold for genome-wide significance (P < 5 × 10⁻⁸). Regional plots display the lead variants of genome-wide significant loci on chromosomes 1 (left) and 10 (right), respectively. The x-axis shows position on the chromosome in megabases (Mb), while the y axis represents −log₁₀(P-values) for association (left) and recombination rate at each genomic position (right). The variant indicated in purple is the index variant, and other variants are colour coded according to their linkage disequilibrium (R-squared) with the index variant.

Figure 2.

Genetic correlations between ectopic pregnancy and anthropometric, educational, health-related, reproductive, and smoking phenotypes. Points show the estimated genetic correlation (rg), which is presented as a dot and error bars indicate 95% confidence limits. Dotted red line indicates no genetic correlation.

Figure 3.

Disease codes associated with a diagnosis of ectopic pregnancy (O00) in the Estonian Biobank. Each triangle represents one ICD-10 (International Classification of Disease 10) maincode, while different colours correspond to different chapters. The direction of the triangle illustrates effect direction—upward pointing triangles show increased prevalence of the diagnosis code in ectopic pregnancy cases. The pink line shows the Bonferroni corrected threshold for statistical significance.