Andrée Gruslin award lecture: Metabolomics as an important modality to better understand preeclampsia

Benton, Samantha J.; Ly, Christina; S, Vuković; Bainbridge, Shannon

doi:10.1016/j.placenta.2016.11.006

Cited by 15 publications

(11 citation statements)

References 47 publications

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“…Derived from the clinical observation that pre-eclamptic patients have 4- to 8-fold increased risk of developing cardiovascular disorders later in life (Irgens et al, 2001; Wu et al, 2017), characterization of their metabolic footprint is of major interest. In pre-eclampsia, a change in metabolome has been reported (Benton et al, 2016; Kelly et al, 2017), with specific effects on the fatty acid metabolome, sharing similarities with other cardiovascular and idiopathic inflammatory diseases (Famularo et al, 2004; Ruiz-Núñez et al, 2016). Moreover, pre-eclamptic patients show increased choline levels in plasma and urine (Austdal et al, 2014; Friesen et al, 2007), most probably due to increased oxidative stress.…”

Section: Discussionmentioning

confidence: 99%

A double hit preeclampsia model results in sex-specific growth restriction patterns

Stojanovska

Dijkstra

Vogtmann

et al. 2019

Disease Models &Amp; Mechanisms

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Pre-eclampsia is a multifactorial pregnancy-associated disorder characterized by angiogenic dysbalance and systemic inflammation; however, animal models that combine these two pathophysiological conditions are missing. Here, we introduce a novel double-hit pre-eclampsia mouse model that mimics the complex multifactorial conditions present during pre-eclampsia and allows for the investigation of early consequences for the fetus. Adenoviral overexpression of soluble fms-like tyrosine kinase (sFlt-1) and lipopolysaccharide (LPS) administration at mid-gestation in pregnant mice resulted in hypertension and albuminuria comparable to that of the manifestation in humans. A metabolomics analysis revealed that pre-eclamptic dams have increased plasma concentrations of phosphadytilcholines. The fetuses of both sexes were growth restricted; however, in males a brain-sparing effect was seen as compensation for this growth restriction. According to the plasma metabolomics, male fetuses showed changes in amino acid metabolism, while female fetuses showed pronounced alterations in lipid metabolism. Our results show that combined exposure to sFlt-1 and LPS mimics the clinical symptoms of pre-eclampsia and affects fetal growth in a sex-specific manner, with accompanying metabolome changes.

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Section: Discussionmentioning

confidence: 99%

A double hit preeclampsia model results in sex-specific growth restriction patterns

Stojanovska

Dijkstra

Vogtmann

et al. 2019

Disease Models &Amp; Mechanisms

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“…Discovery of molecular markers for obstetrical complications is often undertaken using “omics” technologies [157–165]: genomics [166,167], transcriptomics [168–175], proteomics [72,165,176–187], metabolomics [188–192], peptidomics [193–198], and lipidomics [199,200]. In particular, maternal proteomic profiles in preeclampsia were reported in maternal serum/plasma [175–177,180,201–210], urine [211–213], amniotic fluid [214,215], and the placenta [179,182,216–228].…”

Section: Discussionmentioning

confidence: 99%

The prediction of early preeclampsia: Results from a longitudinal proteomics study

et al. 2019

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Objectives To identify maternal plasma protein markers for early preeclampsia (delivery <34 weeks of gestation) and to determine whether the prediction performance is affected by disease severity and presence of placental lesions consistent with maternal vascular malperfusion (MVM) among cases. Study design This longitudinal case-control study included 90 patients with a normal pregnancy and 33 patients with early preeclampsia. Two to six maternal plasma samples were collected throughout gestation from each woman. The abundance of 1,125 proteins was measured using high-affinity aptamer-based proteomic assays, and data were modeled using linear mixed-effects models. After data transformation into multiples of the mean values for gestational age, parsimonious linear discriminant analysis risk models were fit for each gestational-age interval (8–16, 16.1–22, 22.1–28, 28.1–32 weeks). Proteomic profiles of early preeclampsia cases were also compared to those of a combined set of controls and late preeclampsia cases (n = 76) reported previously. Prediction performance was estimated via bootstrap. Results We found that 1) multi-protein models at 16.1–22 weeks of gestation predicted early preeclampsia with a sensitivity of 71% at a false-positive rate (FPR) of 10%. High abundance of matrix metalloproteinase-7 and glycoprotein IIbIIIa complex were the most reliable predictors at this gestational age; 2) at 22.1–28 weeks of gestation, lower abundance of placental growth factor (PlGF) and vascular endothelial growth factor A, isoform 121 (VEGF-121), as well as elevated sialic acid binding immunoglobulin-like lectin 6 (siglec-6) and activin-A, were the best predictors of the subsequent development of early preeclampsia (81% sensitivity, FPR = 10%); 3) at 28.1–32 weeks of gestation, the sensitivity of multi-protein models was 85% (FPR = 10%) with the best predictors being activated leukocyte cell adhesion molecule, siglec-6, and VEGF-121; 4) the increase in siglec-6, activin-A, and VEGF-121 at 22.1–28 weeks of gestation differentiated women who subsequently developed early preeclampsia from those who had a normal pregnancy or developed late preeclampsia (sensitivity 77%, FPR = 10%); 5) the sensitivity of risk models was higher for early preeclampsia with placental MVM lesions than for the entire early preeclampsia group (90% versus 71% at 16.1–22 weeks; 87% versus 81% at 22.1–28 weeks; and 90% versus 85% at 28.1–32 weeks, all FPR = 10%); and 6) the sensitivity of prediction models was higher for severe early preeclampsia than for the entire early preeclampsia group (84% versus 71% at 16.1–22 weeks). Conclusion We have presented herein a catalogue of proteome changes in maternal plasma proteome that precede the diagnosis of preeclampsia and can distinguish among early and late phenotypes. The sensitivity of maternal plasma protein models for early preeclampsia is higher in women with underlying vascular placental disease an...

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“…To date, no single screening test has shown sufficiently accurate specificity and sensitivity to predict preeclampsia cases 37 . The value of clinical risk factors, biochemical markers, uterine Doppler as predictive markers addressed separately remains modest at best for all women destined to develop preeclampsia 38 . This is probably due to the multifactorial aetiology of the condition.…”

Section: Discussionmentioning

confidence: 99%

Incidence and risk factors for Preeclampsia in a cohort of healthy nulliparous pregnant women: a nested case-control study

Mayrink

Souza

Feitosa

et al. 2019

Sci Rep

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The objective of this study is to determine the incidence, socio-demographic and clinical risk factors for preeclampsia and associated maternal and perinatal adverse outcomes. This is a nested case-control derived from the multicentre cohort study Preterm SAMBA, in five different centres in Brazil, with nulliparous healthy pregnant women. Clinical data were prospectively collected, and risk factors were assessed comparatively between PE cases and controls using risk ratio (RR) (95% CI) plus multivariate analysis. Complete data were available for 1,165 participants. The incidence of preeclampsia was 7.5%. Body mass index determined at the first medical visit and diastolic blood pressure over 75 mmHg at 20 weeks of gestation were independently associated with the occurrence of preeclampsia. Women with preeclampsia sustained a higher incidence of adverse maternal outcomes, including C-section (3.5 fold), preterm birth below 34 weeks of gestation (3.9 fold) and hospital stay longer than 5 days (5.8 fold) than controls. They also had worse perinatal outcomes, including lower birthweight (a mean 379 g lower), small for gestational age babies (RR 2.45 [1.52–3.95]), 5-minute Apgar score less than 7 (RR 2.11 [1.03–4.29]), NICU admission (RR 3.34 [1.61–6.9]) and Neonatal Near Miss (3.65 [1.78–7.49]). Weight gain rate per week, obesity and diastolic blood pressure equal to or higher than 75 mmHg at 20 weeks of gestation were shown to be associated with preeclampsia. Preeclampsia also led to a higher number of C-sections and prolonged hospital admission, in addition to worse neonatal outcomes.

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Andrée Gruslin award lecture: Metabolomics as an important modality to better understand preeclampsia

Cited by 15 publications

References 47 publications

A double hit preeclampsia model results in sex-specific growth restriction patterns

A double hit preeclampsia model results in sex-specific growth restriction patterns

The prediction of early preeclampsia: Results from a longitudinal proteomics study

Incidence and risk factors for Preeclampsia in a cohort of healthy nulliparous pregnant women: a nested case-control study

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