P reeclampsia (PE) is a potentially life-threatening, systemic, hypertensive disorder affecting 3% to 5% of all pregnancies. Responsible for >60 000 maternal deaths each year, 1 PE is also a leading cause of fetal/neonatal mortality and morbidity. Classically, PE has been defined as new-onset hypertension and proteinuria after 20 weeks of gestation. However, the clinical presentation of PE is highly variable among women, and diagnostic guidelines now include signs and symptoms that are reflective of disease in ≥1 organ systems (liver, kidney, blood, and brain 2,3 ). Apart from expectant management and delivery of the infant and the placenta, there currently exists no cure or effective treatments for PE.The placenta is widely considered to be the central component of the PE disease process, and as it is not required after birth, this presents a unique opportunity to assess a clinically relevant tissue involved in a hypertensive pathology. Accordingly, numerous placental analyses have been conducted with the aim of identifying early detection markers or candidates for therapeutic intervention in PE. These studies have uncovered involvement of molecular pathways, such as oxidative stress and secretion, [4][5][6] and many secreted factors with disrupted expression during PE have been investigated as candidate blood biomarkers of this pathology. [7][8][9][10] However, the predictive power of these molecules demonstrate low sensitivity at clinically relevant false-positive rates 7 and, therefore, are not presently recommended for use as screening tools for PE. 11 We, [12][13][14] and others, 15,16 have proposed that this lack of robust biomarkers and effective treatments for PE is because of the multifactorial nature of this disease, a notion supported by considerable evidence within the human literature. [17][18][19][20][21] Further support also exists in the numerous developed animal models of PE that recapitulate many of the human symptoms and pathologies because these are the result of a range of initial insults, involving disruptions in placental 22,23 or maternal 24 genes, or a predisposing baseline maternal hypertension. 25 As such, past placental microarray, and even meta-analysis, 26,27 studies with small and highly selected patient cohorts, predominately assessed using a binary classification system (of PE versus control), do not accurately reflect the true clinical presentation of patients. Even the separation of women into earlyonset (diagnosis before 34 weeks) and late-onset PE groups 18,21 Abstract-Preeclampsia (PE) is a complex, hypertensive disorder of pregnancy, demonstrating considerable variability in maternal symptoms and fetal outcomes. Unfortunately, prior research has not accounted for this variability, resulting in a lack of robust biomarkers and effective treatments for PE. Here, we created a large (N=330) clinically relevant human placental microarray data set, consisting of 7 previously published studies and 157 highly annotated new samples from a single BioBank. Applying unsupervise...

BackgroundPreeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3–5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify “PE-specific” genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups.ResultsTo address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a “canonical” PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia.ConclusionOur analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

Placental health is a key component to a successful pregnancy. Placental insufficiency (PI), inadequate nutrient delivery to the fetus, is associated with preeclampsia (PE), a maternal hypertensive disorder, and intrauterine growth restriction (IUGR), pathologically poor fetal growth. PI is more common in early-onset PE (EOPE) than late-onset PE (LOPE). However, the relationship between these disorders remains unclear. While DNA methylation (DNAm) alterations have been identified in PE and IUGR, these entities can overlap and few studies have analysed them separately. This study aims to utilize DNAm profiling to better understand the underlying placental variation associated with PE and IUGR. Placental samples from a discovery (43 controls, 22 EOPE, 18 LOPE, 11 IUGR) and validation cohort (15 controls, 22 EOPE, 11 LOPE) were evaluated using the Illumina HumanMethylation450 array. To account for gestational age (GA) effects, EOPE samples were compared with pre-term births of varying etiologies (GA <37 weeks). LOPE and IUGR were compared with term controls (GA >37 weeks). While 1703 sites were differentially methylated (DM) (FDR < 0.05, Δβ > 0.1) in EOPE, few changes were associated with LOPE (N = 5), or IUGR (N = 0). Of the 1703 EOPE sites, 599 validated in the second cohort. Using these 599 sites, both cohorts clustered into three distinct groups. Interestingly, LOPE samples diagnosed between 34 and 36 weeks with co-occurring IUGR clustered with the EOPE. DNAm profiling may provide an independent tool to refine clinical/pathological diagnoses into subgroups with more uniform pathology. Despite large changes observed in EOPE, there were challenges in reproducing genome-wide DNAm hits that are discussed.

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