A review of omics approaches to study preeclampsia

Abstract

Preeclampsia is a medical condition affecting 5-10% of pregnancies. It has serious effects on the health of the pregnant mother and developing fetus. While possible causes of preeclampsia are speculated, there is no consensus on its etiology. The advancement of big data and high-throughput technologies enables to study preeclampsia at the new and systematic level. In this review, we first highlight the recent progress made in the field of preeclampsia research using various omics technology platforms, including epigenetics, genome-wide association studies (GWAS), transcriptomics, proteomics and metabolomics. Next, we integrate the results in individual omic level studies, and show that despite the lack of coherent biomarkers in all omics studies, inhibin is a potential preeclamptic biomarker supported by GWAS, transcriptomics and DNA methylation evidence. Using network analysis on the biomarkers of all the literature reviewed here, we identify four striking sub-networks with clear biological functions supported by previous molecular-biology and clinical observations. In summary, omics integration approach offers the promise to understand molecular mechanisms in preeclampsia.

Keywords: Big data; Biomarker; Epigenetics; Integration; Metabolomics; Multi-omics; Network; Omics; Pathway; Preeclampsia; Proteomics; Transcriptomics.

Figure 1.

Bipartite graph merging all omics platforms used to study preeclampsia. A bipartite group is composed of two types of nodes. One type of nodes depicts the biomarkers found in different omic-type studies. Omic-type is annotated by node color as indicated in the plot: Grey = GWAS, orange = Methylation, pink = Transcriptomics, blue = Proteomics, bright green = metabolomics. The other type of nodes, labelled as S, signifies the study information.

Figure 2.

Protein-protein interaction network (STRING database) generated by combining all biomarkers of different omic types, reviewed earlier in the report. The network is done using Cytoscape visualization. Four dominant sub-networks associated with preeclampsia are shown (blue, green, yellow, purple), each enriched with biological functions. Antioxidant pathway involving PRDX2, PRDX3, HSPE1, GCLM and SOD1 (green). Proteasome and cytokine signalling pathway involving PSMA1, PSMD8, NFKB1, NFKB2 (blue). Protein regulation and transport pathways involving C1s, TFRC, CXCL1, TTR, TIMP3 (yellow). Angiogenesis signalling pathway involving FLT1, PGF, FGF, ENG (purple). The other red targets are still associated with preeclampsia but not within the four dominant sub-networks.