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Identifying genes and traits associated with pre-eclampsia using summary statistics
Wenyan Zhu1, Qi Wang2, Min Chen2
1Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Abstract:
The occurrence and development of pre-eclampsia (PE) is closely related to genetics. However, multi-omics analysis does not provide sufficient evidence to define significant genes. Therefore, we aimed to identify significant genes and pathways using summary statistics from genome-wide association studies (GWAS). Based on the summary statistics, we used linkage disequilibrium score regression (LDSC) to discover genetic correlation between PE and complex traits. Leveraging summary statistics of tissue-specific expression quantitative trait loci (eQTL), we used FUSION to define significant genes, Bayesian colocalization analysis to identify pleiotropic genes, and Multi-marker Analysis of GenoMic Annotation (MAGMA) to determine the associated pathways. Specifically, considering the potential relationship between PE and tissues, we included 11 tissues, such as kidney cortex. Our integrative analysis revealed that the observed heritability of PE was 0.0179 (standard error [SE] = 0.0021, P-value < 0.001). Also, based on the Bonferroni correction, we defined 238 traits genetically correlated to PE, such as the other cardiovascular diseases (r = -0.55) and furosemide (r = 0.79). Integrating eQTL summary statistics across eleven tissues, we identified 30 significant genes, such as EIF2S1 in the uterus (TWAS. Z = 4.44, TWAS. P = 8.95 × 10-6), and PAWRP2 in ovary (TWAS. Z = 4.34, TWAS. P = 1.45 × 10-5). Based on colocalization, we identified 26 pleiotropic genes. We found that three genes, including RPS26, SULT1A2, OBSCN-AS1, and SUOX, were simultaneously defined by FUSION and colocalization. Moreover, we found that the significant enrichment was in the FOXG1_TARGET_GENES pathway regulated by the transcription factor FOXG1 (PFDR = 0.049). The findings of post-GWAS analysis for PE indicate that there are 30 significant genes and 26 pleiotropic genes. Future studies are required to investigate the efficacy of targeting pleiotropic genes to reduce the risk of PE.
