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. 2024 Feb;13(2):e12413.
doi: 10.1002/jev2.12413.

Lipid profile of circulating placental extracellular vesicles during pregnancy identifies foetal growth restriction risk

Miira M Klemetti #  1   2 , Ante B V Pettersson #  3 , Aafaque Ahmad Khan #  4 , Leonardo Ermini  1 , Tyler R Porter  1 , Michael L Litvack  3 , Sruthi Alahari  1 , Stacy Zamudio  5 , Nicholas P Illsley  5 , Hannes Röst  4 , Martin Post  3   6   7 , Isabella Caniggia  1   2   6   7
Affiliations

Lipid profile of circulating placental extracellular vesicles during pregnancy identifies foetal growth restriction risk

Miira M Klemetti et al. J Extracell Vesicles. 2024 Feb.

Erratum in

Abstract

Small-for-gestational age (SGA) neonates exhibit increased perinatal morbidity and mortality, and a greater risk of developing chronic diseases in adulthood. Currently, no effective maternal blood-based screening methods for determining SGA risk are available. We used a high-resolution MS/MSALL shotgun lipidomic approach to explore the lipid profiles of small extracellular vesicles (sEV) released from the placenta into the circulation of pregnant individuals. Samples were acquired from 195 normal and 41 SGA pregnancies. Lipid profiles were determined serially across pregnancy. We identified specific lipid signatures of placental sEVs that define the trajectory of a normal pregnancy and their changes occurring in relation to maternal characteristics (parity and ethnicity) and birthweight centile. We constructed a multivariate model demonstrating that specific lipid features of circulating placental sEVs, particularly during early gestation, are highly predictive of SGA infants. Lipidomic-based biomarker development promises to improve the early detection of pregnancies at risk of developing SGA, an unmet clinical need in obstetrics.

Keywords: SGA pregnancies; lipidomics; placenta; small extracellular vesicles.

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Conflict of interest statement

All authors declare no competing interests.

Figures

FIGURE 1
FIGURE 1
Characterization and validation of placental sEVs isolated from maternal plasma. (a) Representative NTA measurements of P‐sEVs isolated from maternal plasma of normal and SGA pregnancies. (b) Immunoblots for CD63, ALIX, TSG101, PLAP and CALNEXIN (negative control) of P‐sEVs isolated from maternal plasma of normal and SGA pregnancies at gestational windows G1, G2, G3 and G4 of pregnancy (n = 3 different sEV isolations). (c) Representative electron micrographs of P‐sEVs isolated from maternal plasma of normal pregnancy. Bar = 100 nm. (d) Immunoblots for ApoB and ALIX of total (T‐sEV) and placental (P‐sEV) extracellular vesicles isolated from maternal plasma of normal pregnancy (n = 3 different sEV isolations). (e‐upper panels) Representative flow cytometry density plots for CD63 and ApoB in T‐sEVs and P‐sEVs isolated from maternal plasma of normal pregnancy. (e‐lower panel, left) Representative cytometry density plots for CD63, PLAP and ApoB in P‐sEVs from maternal plasma of normal pregnancy. (e‐lower panel, right) Percentage of double positive CD63/ApoB EVs in total and placental sEVs (n = 4 different sEV isolations). EV, extracellular vesicles; NTA, nanoparticle tracking analysis; sEV, small EV; SGA, small‐for‐gestational age.
FIGURE 2
FIGURE 2
Size and concentration of circulating placental sEVs across normal and SGA pregnancies. Violin plots of placental extracellular vesicle size (a) and concentration (b) in maternal plasma of normal and SGA pregnancies at gestational windows G1, G2, G3 and G4 of pregnancy measured with NTA. Control n = 195 and SGA n = 41. NTA, nanoparticle tracking analysis; sEV, small EV; SGA, small‐for‐gestational age. One‐way ANOVA and Tukey posthoc test, * p < 0.05.
FIGURE 3
FIGURE 3
Lipid composition of circulating placental sEVs changes with gestation in normal pregnancy. (a) Partial least squares‐discriminant analysis (PLS‐DA) plots of global lipid profiles of P‐sEVs between gestational time points G1 versus G2, G3 and G4, respectively; and combined G1, G2, G3 and G4. (b) Top 25 lipids in P‐sEVs identified by PLS‐DA that exhibit changes across pregnancy (G1 to G4). Coloured boxes on the right indicate the relative concentrations of the corresponding lipid in each gestational group. Importance of each lipid change is represented by their variable importance in projection (VIP) score. (c) Pearson (r) correlation patterns of the identified top 25 lipids in circulating P‐sEVs across pregnancy (G1 to G4). PLS‐DA, partial least square discriminant analysis; P‐sEVs, placental sEVs; sEV, small EV.
FIGURE 4
FIGURE 4
Maternal ethnicity affects lipid composition of circulating placental sEVs across normal pregnancy. PLS‐DA plots separate global lipid profiles of P‐sEVs isolated from plasma of normal pregnancies based on ethnic background at gestational timepoints G1, G2, G3 and G4 of pregnancy. PLS‐DA, partial least square discriminant analysis; P‐sEVs, placental sEVs; sEV, small EV.
FIGURE 5
FIGURE 5
Parity‐based changes in lipid composition of circulating placental sEVs across normal pregnancy. (a) PLS‐DA plots separate global lipid profiles of P‐sEVs isolated from plasma of normal pregnancies based on parity (primi‐ vs. multipara) at gestational time points G1, G2, G3 and G4 of pregnancy. (b) Top 25 lipids identified by PLS‐DA that differ between primi‐ and multiparous controls across gestation (G1 to G4). Colored boxes on the right indicate the relative concentrations of the corresponding lipid in each parity group. Importance of each lipid difference is represented by their variable importance in projection (VIP) score. PLS‐DA, partial least square discriminant analysis; P‐sEVs, placental sEVs; sEV, small EV.
FIGURE 6
FIGURE 6
Lipid composition of circulating placental sEVs differs between normal and small‐for‐gestational age (SGA) pregnancies. All P‐sEVs isolated from maternal blood were categorized into three groups according to infant birthweight percentile: Small‐for‐gestational age (SGA; < 10th percentile), appropriate‐for‐gestational age (AGA; 10th–90th percentile) and large‐for‐gestational age (LGA; > 90th percentile). (a) PLS‐DA plots separates global lipid profiles of P‐sEVs between AGA versus. LGA versus SGA samples at different gestational timepoints (G1 to G4) of pregnancy. (b) Sparse PLS‐DA plots showing the separation according to placental sEV lipids of control versus SGA samples at different gestational timepoints (G1 to G4) of pregnancy according to low (< 2.2 g/m3) neonatal ponderal index (PI). PLS‐DA, partial least square discriminant analysis; P‐sEVs, placental sEVs; sEV, small EV.
FIGURE 7
FIGURE 7
Most significant variances in lipid composition of circulating placental sEVs among normal and small‐for‐gestational age (SGA) pregnancies. (a) Top 25 lipids identified by PLS‐DA that differ between control (normal) versus SGA pregnancies across gestation. Colored boxes on the right indicate the relative concentrations of the corresponding lipid in each group. Importance of each lipid difference is represented by their variable importance in projection (VIP) score. (b) Heatmap showing the top 25 lipids that differ between placental sEVs isolated from maternal plasma of control (normal) versus SGA pregnancies at gestational timepoints G1 to G4. PLS‐DA, partial least square discriminant analysis; sEV, small EV
FIGURE 8
FIGURE 8
Lipid composition of circulating placental sEVs predicts the birth of a small‐for‐gestational age (SGA) infant. Receiver operating characteristic curves for the Random Forest classifier and area under the curve (AUC) scores for SGA prediction. Top 25 differentially expressed placental sEV lipids in control (normal) versus SGA pregnancies with and without maternal clinical (maternal age, BMI, and parity) characteristics were used for model development. (a) Prediction of SGA using top 25 differentially expressed P‐sEV lipids at different gestational timepoints (G1 to G4) without maternal clinical data. (b) Prediction of SGA using top 25 P‐sEV lipids at different gestational timepoints (G1 to G4) combined with maternal clinical variables. BMI, body mass index; P‐sEVs, placental sEVs; sEV, small EV.
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