Pregnancy-Associated Bleeding and Genetics: Five Sequence Variants in the Myometrium and Progesterone Signaling Pathway Are Associated with Postpartum Hemorrhage

Bleeding in early pregnancy and postpartum hemorrhage (PPH) bear substantial risks, with the former closely associated with pregnancy loss and the latter being the foremost cause of maternal death, underscoring the severity of these complications in maternal-fetal health. Here, we investigated the genetic variation underlying aspects of pregnancy-associated bleeding and identified five loci associated with PPH through a meta-analysis of 21,512 cases and 259,500 controls. Functional annotation analysis indicated candidate genes, , , and / at three loci and showed that at each locus, associated variants were located within binding sites for progesterone receptors (PGR). Furthermore, there were strong genetic correlations with birth weight, gestational duration, and uterine fibroids. Early bleeding during pregnancy (28,898 cases and 302,894 controls) yielded no genome-wide association signals, but showed strong genetic correlation with a variety of human traits, indicative of polygenic and pleiotropic effects. Our results suggest that postpartum bleeding is related to myometrium dysregulation, whereas early bleeding is a complex trait related to underlying health and possibly socioeconomic status.

References

Sakabe N, Aneas I, Knoblauch N, Sobreira D, Clark N, Paz C . Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth. Sci Adv. 2020; 6(49). PMC: 7710387. DOI: 10.1126/sciadv.abc8696. View

Kong A, Masson G, Frigge M, Gylfason A, Zusmanovich P, Thorleifsson G . Detection of sharing by descent, long-range phasing and haplotype imputation. Nat Genet. 2009; 40(9):1068-75. PMC: 4540081. DOI: 10.1038/ng.216. View

Gudbjartsson D, Helgason H, Gudjonsson S, Zink F, Oddson A, Gylfason A . Large-scale whole-genome sequencing of the Icelandic population. Nat Genet. 2015; 47(5):435-44. DOI: 10.1038/ng.3247. View

Prive F, Arbel J, Vilhjalmsson B . LDpred2: better, faster, stronger. Bioinformatics. 2020; 36(22-23):5424-5431. PMC: 8016455. DOI: 10.1093/bioinformatics/btaa1029. View

Pujol-Gualdo N, Lall K, Lepamets M, Rossi H, Arffman R, Piltonen T . Advancing our understanding of genetic risk factors and potential personalized strategies for pelvic organ prolapse. Nat Commun. 2022; 13(1):3584. PMC: 9226158. DOI: 10.1038/s41467-022-31188-5. View

Islam M, Afrin S, Jones S, Segars J . Selective Progesterone Receptor Modulators-Mechanisms and Therapeutic Utility. Endocr Rev. 2020; 41(5). PMC: 8659360. DOI: 10.1210/endrev/bnaa012. View

Mbatchou J, Barnard L, Backman J, Marcketta A, Kosmicki J, Ziyatdinov A . Computationally efficient whole-genome regression for quantitative and binary traits. Nat Genet. 2021; 53(7):1097-1103. DOI: 10.1038/s41588-021-00870-7. View

Lykke J, Dideriksen K, Lidegaard O, Langhoff-Roos J . First-trimester vaginal bleeding and complications later in pregnancy. Obstet Gynecol. 2010; 115(5):935-944. DOI: 10.1097/AOG.0b013e3181da8d38. View

Karlsson M, Zhang C, Mear L, Zhong W, Digre A, Katona B . A single-cell type transcriptomics map of human tissues. Sci Adv. 2021; 7(31). PMC: 8318366. DOI: 10.1126/sciadv.abh2169. View

10.

Mesiano S . Myometrial progesterone responsiveness. Semin Reprod Med. 2007; 25(1):5-13. DOI: 10.1055/s-2006-956771. View

11.

Sole-Navais P, Flatley C, Steinthorsdottir V, Vaudel M, Juodakis J, Chen J . Genetic effects on the timing of parturition and links to fetal birth weight. Nat Genet. 2023; 55(4):559-567. PMC: 10101852. DOI: 10.1038/s41588-023-01343-9. View

12.

Helgeland O, Vaudel M, Sole-Navais P, Flatley C, Juodakis J, Bacelis J . Characterization of the genetic architecture of infant and early childhood body mass index. Nat Metab. 2022; 4(3):344-358. DOI: 10.1038/s42255-022-00549-1. View

13.

Saraswat L, Maheshwari A, Bhattacharya S . Maternal and perinatal outcome in women with threatened miscarriage in the first trimester: a systematic review. BJOG. 2009; 117(3):245-57. DOI: 10.1111/j.1471-0528.2009.02427.x. View

14.

Pazokitoroudi A, Wu Y, Burch K, Hou K, Zhou A, Pasaniuc B . Efficient variance components analysis across millions of genomes. Nat Commun. 2020; 11(1):4020. PMC: 7419517. DOI: 10.1038/s41467-020-17576-9. View

15.

de Leeuw C, Mooij J, Heskes T, Posthuma D . MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015; 11(4):e1004219. PMC: 4401657. DOI: 10.1371/journal.pcbi.1004219. View

16.

Koel M, Vosa U, Joeloo M, Lall K, Gualdo N, Laivuori H . GWAS meta-analyses clarify the genetics of cervical phenotypes and inform risk stratification for cervical cancer. Hum Mol Genet. 2023; 32(12):2103-2116. PMC: 10244231. DOI: 10.1093/hmg/ddad043. View

17.

Oberg A, Hernandez-Diaz S, Frisell T, Greene M, Almqvist C, Bateman B . Genetic contribution to postpartum haemorrhage in Swedish population: cohort study of 466,686 births. BMJ. 2014; 349:g4984. PMC: 4131501. DOI: 10.1136/bmj.g4984. View

18.

Bulik-Sullivan B, Finucane H, Anttila V, Gusev A, Day F, Loh P . An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015; 47(11):1236-41. PMC: 4797329. DOI: 10.1038/ng.3406. View

19.

Murphy A, Schilder B, Skene N . MungeSumstats: a Bioconductor package for the standardization and quality control of many GWAS summary statistics. Bioinformatics. 2021; 37(23):4593-4596. PMC: 8652100. DOI: 10.1093/bioinformatics/btab665. View

20.

Banasik K, Moller P, Techlo T, Holm P, Walters G, Ingason A . DanMAC5: a browser of aggregated sequence variants from 8,671 whole genome sequenced Danish individuals. BMC Genom Data. 2023; 24(1):30. PMC: 10225079. DOI: 10.1186/s12863-023-01132-7. View