PDF(Pubmed)
Abstract：
OBJECTIVE: Can we identify genetic variants associated with ectopic pregnancy by undertaking the first genome-wide association study (GWAS) leveraging two large-scale biobank initiatives?
CONCLUSIONS: We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 (mucin 1) as the most plausible affected gene.
BACKGROUND: 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.
METHODS: A GWAS meta-analysis including 7070 women with ectopic pregnancy and 248 810 controls from Estonian Biobank and the FinnGen study.
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.
RESULTS: 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.
METHODS: The GWAS meta-analysis summary statistics are available from the GWAS Catalogue (GCST90272883).
CONCLUSIONS: 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.
CONCLUSIONS: 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.
BACKGROUND: 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.
CONCLUSIONS: We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 (mucin 1) as the most plausible affected gene.
BACKGROUND: 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.
METHODS: A GWAS meta-analysis including 7070 women with ectopic pregnancy and 248 810 controls from Estonian Biobank and the FinnGen study.
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.
RESULTS: 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.
METHODS: The GWAS meta-analysis summary statistics are available from the GWAS Catalogue (GCST90272883).
CONCLUSIONS: 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.
CONCLUSIONS: 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.
BACKGROUND: 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.
摘要：
目的：我们是否可以通过利用两个大规模生物库计划进行第一个全基因组关联研究（GWAS）来识别与异位妊娠相关的遗传变异？
结论：我们确定了两个新的全基因组与异位妊娠的显著关联，突出MUC1（粘蛋白1）是最合理的受影响基因。
背景：异位妊娠是全球孕产妇发病率和死亡率的重要原因。尽管是常见的早期妊娠并发症，这种情况的遗传易感性仍未得到充分研究，到目前为止还没有进行大规模的遗传研究。
方法：一项GWAS荟萃分析，包括来自爱沙尼亚生物银行和FinnGen研究的7070名异位妊娠妇女和248810名对照。
方法：我们通过ICD（国际疾病分类）代码（ICD-10O00）从国家登记册中确定了异位妊娠病例，所有剩下的女性都被认为是对照组。我们进行了标准GWAS荟萃分析，并额外注释了GWAS信号，分析了与数量性状基因座的共定位，估计遗传相关性和确定相关表型来表征遗传信号，以及分析与病情的遗传和表型关系。
结果：我们在1号染色体（rs4971091，P=5.32×10-9）和10号染色体（rs11598956，P=2.41×10-8）上发现了两个可能与异位妊娠相关的全基因组显著位点。后续分析提出MUC1，它编码一种在屏障功能中起重要作用的上皮糖蛋白，作为1号染色体上关联的最可能的候选基因。我们还描述了与其他表型的表型和遗传相关性，确定与吸烟和（天才）泌尿和胃肠道系统疾病的遗传相关性，以及与各种生殖健康诊断的表型相关性，反映了以前已知的流行病学关联。
方法：GWAS荟萃分析汇总统计数据可从GWAS目录（GCST90272883）获得。
结论：主要限制是这些发现是基于欧洲血统人群，其他人群的数据有限，我们只捕获了母体基因组。此外,需要进一步的更大规模的荟萃分析或独立研究来验证这些发现.
结论：这项研究鼓励使用大规模遗传数据集，以揭示与异位妊娠相关的遗传因素。这在实验环境中很难研究。样本量的增加可能会带来与异位妊娠相关的其他遗传因素，并告知其遗传力。总之,我们的结果为异位妊娠的生物学提供了更多的见解，因此,控制胚胎植入的生物过程。
背景：N.P.G.得到了MATERMarieSklodowska-Curie的支持，该项目获得了欧盟Horizon2020研究与创新计划的资助。813707。这项研究是由欧盟通过欧洲区域发展基金项目号资助的。2014-2020.4.01.15-0012转基因。计算是在塔尔图大学的高性能计算中心进行的。作者宣布没有竞争利益。
结论：我们确定了两个新的全基因组与异位妊娠的显著关联，突出MUC1（粘蛋白1）是最合理的受影响基因。
背景：异位妊娠是全球孕产妇发病率和死亡率的重要原因。尽管是常见的早期妊娠并发症，这种情况的遗传易感性仍未得到充分研究，到目前为止还没有进行大规模的遗传研究。
方法：一项GWAS荟萃分析，包括来自爱沙尼亚生物银行和FinnGen研究的7070名异位妊娠妇女和248810名对照。
方法：我们通过ICD（国际疾病分类）代码（ICD-10O00）从国家登记册中确定了异位妊娠病例，所有剩下的女性都被认为是对照组。我们进行了标准GWAS荟萃分析，并额外注释了GWAS信号，分析了与数量性状基因座的共定位，估计遗传相关性和确定相关表型来表征遗传信号，以及分析与病情的遗传和表型关系。
结果：我们在1号染色体（rs4971091，P=5.32×10-9）和10号染色体（rs11598956，P=2.41×10-8）上发现了两个可能与异位妊娠相关的全基因组显著位点。后续分析提出MUC1，它编码一种在屏障功能中起重要作用的上皮糖蛋白，作为1号染色体上关联的最可能的候选基因。我们还描述了与其他表型的表型和遗传相关性，确定与吸烟和（天才）泌尿和胃肠道系统疾病的遗传相关性，以及与各种生殖健康诊断的表型相关性，反映了以前已知的流行病学关联。
方法：GWAS荟萃分析汇总统计数据可从GWAS目录（GCST90272883）获得。
结论：主要限制是这些发现是基于欧洲血统人群，其他人群的数据有限，我们只捕获了母体基因组。此外,需要进一步的更大规模的荟萃分析或独立研究来验证这些发现.
结论：这项研究鼓励使用大规模遗传数据集，以揭示与异位妊娠相关的遗传因素。这在实验环境中很难研究。样本量的增加可能会带来与异位妊娠相关的其他遗传因素，并告知其遗传力。总之,我们的结果为异位妊娠的生物学提供了更多的见解，因此,控制胚胎植入的生物过程。
背景：N.P.G.得到了MATERMarieSklodowska-Curie的支持，该项目获得了欧盟Horizon2020研究与创新计划的资助。813707。这项研究是由欧盟通过欧洲区域发展基金项目号资助的。2014-2020.4.01.15-0012转基因。计算是在塔尔图大学的高性能计算中心进行的。作者宣布没有竞争利益。
