Integrated system biology approaches to fetal medicine problems

Jezid Miranda, Fátima Crispi, and Eduard Gratacós

Introduction

Pregnancy is a physiological state that demands intricate and timely hormonal, immunological, metabolic, and physiological adaptations of multiple interconnected molecular and cellular systems. In the past decades, research advances in the molecular pathways implicated in physiological and pathological gestations were achieved by means of the analysis of selected biomarkers using a wide range of available laboratory techniques. However, the introduction of the “omics” technologies has resulted in a revolution in the possibilities for research. The scope of research has expanded, and these approaches offer the means to understand from a much wider perspective the molecular pathways that regulate cells, tissues, and organs. The promise of the omics techniques is to improve radically the understanding of the physiology of pregnancy, the maladaptive processes underlying most of the main obstetrical syndromes, and eventually to enable targeted interventions even in the preclinical phases, long before the clinical onset of the main complications of pregnancy.

However, “omics-based research” is accompanied by new challenges, including the need for new statistical techniques for the interpretation of the massive amount of data available, and the realization that a more complex insight often leads to a more complex reality than we originally imagined. For these reasons, the hypothesis-driven approach that has characterized many studies using omics techniques in the past two decades has not brought us closer to the understanding of the pathogenesis or biomolecular mechanisms implicated in pregnancy complications. A new generation of statistical methods, including bioinformatics and machine/deep learning approaches, has emerged, and with it the evidence that this research is sometimes more in the hands of statisticians and systems biology experts than in those of clinicians. Or, at least, that a strong interaction is required to achieve real advances in the understanding of the mechanisms governing normal and abnormal maternal adaptations and fetal development. In this chapter, we briefly review some examples of the applications of the omics in research of the main complications of pregnancy, and we conclude with some comments and conclusions. The authors of this chapter are clinicians, and consequently, the text here provided cannot and does not intend to address or clarify any technical insight as to the use of these methods, but to illustrate the potential and the caveats to consider on attempting an integrated research approach to pregnancy complications.

Main “omics” methods and their applications in pregnancy complications

Figure 12.1 describes the different questions that omics techniques can answer based on the appraisal employed. In the next paragraphs, we describe successful experiences using techniques for each of the great obstetrical syndromes and the lesson that can be learned from their approaches.

Transcriptomics

The transcriptome is defined as the entire collection of RNA transcripts produced from the genome of a cell in any given state. Transcriptomics techniques are used to describe the global messenger RNA (mRNA) expression of a particular tissue, providing information on how genes are regulated yielding information about which cellular processes are active and which are dormant. Two main techniques lead the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences (1). Over the last decade, RNA-seq coupled with computational analysis have led to the recognition that different regulatory noncoding RNAs (microRNAs [miRNAs], long noncoding RNAs [lncRNAs], and circular RNAs [circRNas]) interact with each other and with regulatory proteins to modify gene expression and mRNA to protein translation. Transcriptome analysis has been used to assess placental development and dysfunction in pregnancy complications such as preeclampsia, fetal growth restriction, and preterm labor (2–4). It is important to highlight that as an alternative to isolated studies with few biological samples, meta-transcriptome analysis of case-control data sets of previous transcriptome studies in preeclampsia (5–7) have identified consistent alterations in known mediators of clinical symptoms of preeclampsia such as FLT1, endoglin, transcription factor IIH, ATF3, and other genes involved in hypoxia regulation and blood vessel development as drivers of preeclampsia, with the advantages of allowing efficient elimination of false-positive findings pertaining to relatively small study sample sizes, variability in platforms, patient characteristics, and statistical methods used. However, several points should be taken into account in the analysis and interpretation of meta-transcriptomics studies: the tissue origins of the RNA identified in transcriptomics analysis of amniotic fluid cannot be traced; male and female placentas can have different gene expression during development (8); and microarray-based meta-analyses are feasible but have several limitations. Another interesting approach is the use of amniotic fluid supernatant cell-free RNA transcriptome analysis of living fetuses to unravel fetal development (9,10), which can also help to describe molecular pathways altered in fetal conditions such as common autosomal aneuploidies (11,12), monosomy X (13), fetal growth restriction (14), twin-to-twin transfusion syndrome (15), and open myelomeningocele (16). Table 12.1 describes the variety of fetal diseases in which transcriptomics have been used.

The proteome is the whole set of proteins that is or can be expressed by a given genome in cells, tissues, or organisms. Proteomics is the study of proteomes and their functions. The interest in proteomics increased substantially with the recognition that there are many more proteins than gene products (more than 100,000 human proteins have been recognized so far) (17). Specifically, during pregnancy, proteomics analysis can be applied to test maternal blood, placental tissue, trophoblast cells, amniotic fluid, and cervicovaginal fluid (Table 12.2). The most important challenge in the study of the proteome is that it is a highly complex and dynamic system, since protein expression varies within the cell depending on its physiological or pathological state. In addition, posttranslational modifications as well as chemical damages such as glycation, oxidation, and nitration took place, increasing the diversity and heterogeneity of the proteome.

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