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Updated: May 7, 2026

Mouse In Vivo Placental Targeted CRISPR Manipulation
Published on: April 14, 2023
Genome-wide and candidate gene association studies of placental abruption
Tsegaselassie Workalemahu1, Daniel A Enquobahrie, Amy Moore
1Department of Epidemiology, Harvard School of Public Health, Harvard University Boston, Massachusetts.
Abstract:
Placental abruption (PA), a pregnancy-related vascular disorder, is a leading cause of maternal and perinatal morbidity and mortality. The success of identifying genetic susceptibility loci for PA, a multi-factorial heritable disorder, has been limited. We conducted a genome-wide association study (GWAS) and candidate gene association study using 470 PA cases and 473 controls from Lima, Peru. Genotyping for common genetic variations (single nucleotide polymorphisms, SNPs) was conducted using the Illumina Cardio-Metabo Chip platform. Common variations in 35 genes that participate in mitochondrial biogenesis (MB) and oxidative phosphorylation (OS) were selected for the candidate gene study. Regression models were fit to examine associations of each SNP with risk of PA. In pathway analyses, we examined functions and functional relationships of genes represented by the top GWAS hits. Genetic risk scores (GRS), based on top hits of the GWAS and candidate gene analyses, respectively, were computed using the risk allele counting method. The top hit in the GWAS analyses was rs1238566 (empirical P-value=1.04e-4 and FDR-adjusted P-value=5.65E-04) in FLI-1 gene, a megakaryocyte-specific transcription factor. Networks of genes involved in lipid metabolism and cell signaling were significantly enriched by the 51 genes whose SNPs were among the top 200 GWAS hits (P-value <2.1e-3). SNPs known to regulate MB (e.g. CAMK2B, NR1H3, PPARG, PRKCA, and THRB) and OP (e.g., COX5A, and NDUF family of genes) were associated with PA risk (P-value <0.05). GRS was significantly associated with PA risk (trend P-value <0.001 and 0.01 for GWAS and candidate gene based GRS, respectively). Our study suggests that integrating multiple analytical strategies in genetic association studies can provide opportunities for identifying genetic risk factors and novel molecular mechanisms that underlie PA.
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