Genetic analysis of 104 pregnancy phenotypes in 39,194 Chinese women

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Abstract

Maternity is a special period in a woman’s life that involves substantial physiological, psychological, and hormonal changes. These changes may cause alterations in many clinical measurements during pregnancy, which can be used to monitor and diagnose maternal disorders and adverse postnatal outcomes. Exploring the genetic background of these phenotypes is key to elucidating the pathogenesis of pregnancy disorders. In this study, we conducted a large-scale molecular biology analysis of 104 pregnancy phenotypes based on genotype data from 39,194 Chinses women. Genome- wide association analysis identified a total of 407 trait-locus associations, of which 75.18% were previously reported. Among the 101 novel associations for 37 phenotypes, some were potentially pregnancy-specific and worth further experimental investigation. For example, ESR1 with fasting glucose, hemoglobin, hematocrit, and several leukocytoses; ZSCAN31 with blood urea nitrogen. We further performed pathway- based analysis and uncovered at least one significant pathway for 24 traits, in addition to previously known functional pathways, novel findings included birthweight with “Reactome signaling by NODAL”, twin pregnancy with “Reactome mitotic G1-G1/S phases”. The partitioning heritability analysis recapitulated known trait-relevant tissue/cell types, and also discovered interesting results including twin pregnancy with “embryoid bodies” cell-type enrichment, the delivery type cesarean section with “fallopian tube”, and birth weight with “ovary and embryonic stem cells”. In terms of both sample size and the variety of phenotypes, our work is one of the largest genetic studies of pregnancy phenotypes across all populations. We believe that this study will provide a valuable resource for exploring the genetic background of pregnancy phenotypes and also for further research on pregnancy-related diseases and adverse neonatal outcomes.

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last seen: 2026-05-19T01:45:01.086888+00:00