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Placenta-tropic VEGF mRNA lipid nanoparticles ameliorate murine pre-eclampsia

Abstract

Pre-eclampsia is a placental disorder that affects 3–5% of all pregnancies and is a leading cause of maternal and fetal morbidity worldwide1,2. With no drug available to slow disease progression, engineering ionizable lipid nanoparticles (LNPs) for extrahepatic messenger RNA (mRNA) delivery to the placenta is an attractive therapeutic option for pre-eclampsia. Here we use high-throughput screening to evaluate a library of 98 LNP formulations in vivo and identify a placenta-tropic LNP (LNP 55) that mediates more than 100-fold greater mRNA delivery to the placenta in pregnant mice than a formulation based on the Food and Drug Administration-approved Onpattro LNP (DLin-MC3-DMA)3. We propose an endogenous targeting mechanism based on β2-glycoprotein I adsorption that enables LNP delivery to the placenta. In both inflammation- and hypoxia-induced models of pre-eclampsia, a single administration of LNP 55 encapsulating vascular endothelial growth factor (VEGF) mRNA resolves maternal hypertension until the end of gestation. In addition, with our VEGF mRNA LNP 55 therapeutic, we demonstrate improvements in fetal health and partially restore placental vasculature, the local and systemic immune landscape and serum levels of soluble Fms-like tyrosine kinase-1, a clinical biomarker of pre-eclampsia1. Together, these results demonstrate the potential of this mRNA LNP platform for treating placental disorders such as pre-eclampsia.

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Fig. 1: High-throughput in vivo screening to identify a placenta-tropic LNP formulation for the treatment of pre-eclampsia.

Fig. 2: A potential protein-adsorption-based endogenous targeting mechanism for LNP delivery to the placenta.

Fig. 3: Inflammation-induced pre-eclampsia increases LNP 55 delivery to placental immune cells while decreasing off-target delivery to splenic T cells.

Fig. 4: VEGF mRNA LNP 55 alleviates maternal hypertension in inflammation- and hypoxia-induced models of pre-eclampsia.

Data availability

Demultiplexed next-generation sequencing data from b-DNA LNP screening are available at https://upenn.box.com/v/VEGF-LNPs-pre-eclampsia. Source data are provided with this paper.

Code availability

Supplementary Code 1 for read extraction and tabulation and Supplementary Code 2 for data transformation/normalization are provided with this paper.

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Acknowledgements

M.J.M. acknowledges support from a US National Institutes of Health (NIH) Director’s New Innovator Award (DP2 TR002776), a Burroughs Wellcome Fund Career Award at the Scientific Interface (CASI), a US National Science Foundation CAREER Award (CBET-2145491) and the NIH (NICHD R01 HD115877). K.L.S., A.G.H., H.C.S., H.C.G., A.S.T., A.M.M., E.L.H. and A.J.M. acknowledge support from the US National Science Foundation Graduate Research Fellowship. R.P. was supported by an NIH National Heart, Lung, and Blood Institute Ruth L. Kirschstein Pre-Doctoral National Research Service Award. We thank the Next-Generation Sequencing Core at the University of Pennsylvania (RRID:SCR_022382) for assistance with next-generation sequencing. Data for this manuscript were generated in the Penn Cytomics and Cell Sorting Shared Resource Laboratory at the University of Pennsylvania (RRID:SCR_022376), which was partially supported by an Abramson Cancer Center NCI Grant (P30 016520). We also thank the Cell and Development Biology Microscopy Core at the University of Pennsylvania for access to the confocal laser scanning microscope used in this work (RRID:SCR_022373), and F. Chen from the Histotechnology Facility at the Wistar Institute for preparing histological samples for this work. Funding support for the Wistar Institute core facilities was provided by a Cancer Center Support Grant (P30 CA010815).

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Authors and Affiliations

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

Kelsey L. Swingle, Alex G. Hamilton, Hannah C. Safford, Hannah C. Geisler, Ajay S. Thatte, Rohan Palanki, Amanda M. Murray, Emily L. Han, Alvin J. Mukalel, Xuexiang Han, Ryann A. Joseph, Aditi A. Ghalsasi & Michael J. Mitchell

Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Mohamad-Gabriel Alameh & Drew Weissman

Penn Institute for RNA Innovation, Perelman School of Medicine, Philadelphia, PA, USA

Mohamad-Gabriel Alameh, Drew Weissman & Michael J. Mitchell

Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Michael J. Mitchell

Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Michael J. Mitchell

Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Michael J. Mitchell

Institute for Regenerative Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Michael J. Mitchell

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Kelsey L. Swingle

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2. Alex G. Hamilton

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3. Hannah C. Safford

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Contributions

K.L.S. and M.J.M. contributed to conceptualization, writing of the original draft and project administration. K.L.S., A.G.H., and M.J.M. contributed to the methodology and review and editing of the paper. K.L.S. and A.G.H. contributed to software and/or code and formal data analysis. K.L.S., A.G.H., H.C.S., H.C.G., A.S.T., R.P., A.M.M., E.L.H., A.J.M., X.H., R.A.J. and A.A.G. contributed to investigation. M.-G.A. and D.W. contributed resources. M.J.M. was responsible for supervision and funding acquisition.

Corresponding author

Correspondence to Michael J. Mitchell.

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Competing interests

K.L.S., H.C.S., H.C.G. and M.J.M. have filed a patent application based on this work. M.J.M. is an inventor on a patent related to this work filed by the Trustees of the University of Pennsylvania (PCT/US20/56252). D.W. is an inventor on several patents related to this work filed by the Trustees of the University of Pennsylvania (11/990,646; 13/ 585,517; 13/839,023; 13/839,155; 14/456,302; 15/339,363; 16/299,202). The remaining authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 High-throughput in vivo evaluation of a 98 LNP library using molecular barcoding in non-pregnant and pregnant mice.

a, A large library of 98 LNP formulations was designed by synthesizing 24 unique ionizable lipid structures from 8 polyamine cores and 3 epoxide tails. 12 of these ionizable lipids were then further explored to formulate LNPs of varied excipient composition. b, Each of the 98 LNPs was formulated encapsulating a unique DNA barcode (b-DNA) to enable high-throughput, in vivo screening. The pooled LNPs were administered i.v. to non-pregnant and pregnant mice (n = 6 biological replicates) following which tissues were collected, processed, and prepared for next generation sequencing. Demultiplexing and subsequent data analysis identified a placenta-tropic LNP formulation. c, Heatmap depicting relative accumulation for each LNP/b-DNA in non-pregnant mouse tissues. Ion., ionizable; chol., cholesterol. Illustrations in b were created using BioRender (https://biorender.com).

Source Data

Extended Data Fig. 2 Enrichment and correlation analysis of b-DNA LNP delivery in non-pregnant and pregnant mice.

a–c, Volcano plots depicting significantly enriched (top right quadrant) and significantly depleted (top left quadrant) LNPs compared with the liver-tropic C12-200 LNP formulation in (a) non-pregnant and (b) pregnant tissues as well as (c) placentas and fetuses. Normalized delivery is reported as the mean (n = 6 biological replicates). For each tissue, two-sided, one-way ANOVAs with post hoc Student’s t tests using the Holm-Bonferroni correction for multiple comparisons with the C12-200 LNP were used to compare normalized delivery across LNP formulations for generating p values. d–g, The squared Pearson’s correlation coefficient for mean normalized delivery (r2) was calculated for each tissue pair and is presented as a heatmap for (d) non-pregnant mouse tissues, (e) pregnant mouse tissues, (f) between non-pregnant and pregnant mouse tissues, and (g) between pregnant mouse tissues and the placentas and fetuses. Dist., distal; Prox., proximal.

Source Data

Extended Data Fig. 3 Validation of results from high-throughput screening via luciferase mRNA delivery in non-pregnant mice.

LNP 6 (negative control), LNP 55 (placenta-tropic), LNP 97 (C12-200), and LNP 98 (DLin-MC3-DMA) were formulated with luciferase mRNA and administered to non-pregnant mice at a dose of 0.6 mg kg−1 mRNA. a, Six hours after administration, tissues (H: heart, Lu: lungs, Li: liver, K: kidneys, S: spleen) were dissected and imaged using an in vivo imaging system (IVIS). b–e, Luminescence was quantified in the (b) lungs, (c) liver, and (d) spleen which was then used to calculate (e) a spleen-to-liver ratio. Luminescence measurements are reported as the mean ± s.e.m. (n = 4 biological replicates). Ordinary two-sided, one-way ANOVAs with post hoc Student’s t tests using the Holm-Šídák correction for multiple comparisons were used to compare luminescence across treatment groups.

Source Data

Extended Data Fig. 4 Cellular LNP delivery in the spleen and placenta for industry and clinical standard LNPs in healthy and inflammation-induced pre-eclamptic mice.

To evaluate differences in biodistribution between healthy and pre-eclamptic pregnant mice,inflammation-induced pre-eclampsia was established via i.p. administration of 1 µg kg−1 lipopolysaccharide (LPS). DiD-labelled LNPs 97 and 98 were administered at an mRNA dose of 1 mg kg−1. Twelve hours later, cellular LNP delivery was evaluated in the (a–f) spleen and (g–l) placenta via flow cytometry. The percentage of DiD+ cells is reported as the mean ± s.e.m. (PBS, LNP 97, LNP 98, LPS + LNP 98: n = 4 biological replicates; LPS + LNP 97: n = 3 biological replicates). Either ordinary (a–f) or nested (g–l) two-sided, one-way ANOVAs with post hoc Student’s t tests using the Holm-Šídák correction for multiple comparisons were used to compare the percentage of DiD+ cells across treatment groups. CK7: cytokeratin 7.

Source Data

Extended Data Fig. 5 VEGF mRNA LNP 55 improves maternal weight and serum concentration of inflammatory cytokines in inflammation-induced pre-eclampsia.

Inflammation-induced pre-eclampsia was established through i.p. administration of 1 µg kg−1 lipopolysaccharide (LPS) on gestational day E7.5. 1 mg kg−1 VEGF mRNA LNP 55 was then administered i.v. on gestational day E11. a–c, Change in maternal weight was measured daily (a), and on gestational day E17 (b,c) fetal and placental weight were recorded. d–j, Serum levels of (d) VEGF, (e) sFlt-1, (f) alanine transaminase (ALT), (g) aspartate aminotransferase (AST), (h) tumour necrosis factor (TNF), (i) interleukin-6 (IL-6), and (j) interferon-γ (IFNγ) were evaluated on gestational days E11.5 and E17. k, Mean blood vessel area in the placental labyrinth was quantified from H&E-stainined placental sections. Maternal weight change and serum protein levels are reported as the mean ± s.e.m. (n = 8 biological replicates). Fetal and placental weight are reported as the median with the 25th and 75th percentiles (n = 8 biological replicates, 6–9 fetuses or placentas per mouse). Mean blood vessel area is reported as the median with the 25th and 75th percentiles (n = 8 biological replicates, 1–2 placentas per mouse, 2 sections per placenta, 2–3 images per section). Ordinary two-sided, two-way (a, d–j) or nested two-sided, one-way (b–c, k) ANOVAs with post hoc Student’s t tests using the Holm-Šídák correction for multiple comparisons were used to compare responses across treatment groups.

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Extended Data Fig. 6 VEGF mRNA LNP 55 reduces liver enzyme levels in serum and improves placental blood vessel area in hypoxia-induced pre-eclampsia.

Hypoxia-induced pre-eclampsia was established through i.v. administration of 1 × 109 plaque forming units (PFU) of soluble Fms-like tyrosine kinase-1 adenovirus (Adv-sFlt-1) on gestational day E7.5. 1 mg kg−1 VEGF mRNA LNPs 55 or 98 were then administered i.v. on gestational day E11. a–d, Maternal weight change was recorded daily (a), and on gestational day E17 (b) total litter weight, (c) litter size, and (d) albumin concentration in urine were measured. e–j, Serum levels of (e) VEGF, (f) alanine transaminase (ALT), (g) aspartate aminotransferase (AST), (h) tumour necrosis factor (TNF), (i) interleukin-6 (IL-6), and (j) interferon-γ (IFNγ) were evaluated on gestational days E11.5 and E17. k, Placental vasculature in the labyrinth was visualized with H&E staining; stained sections were used to quantify mean blood vessel area. l, Similarly, renal histology was visualized using H&E staining with arrows indicating glomeruli. Maternal weight change, total litter weight, litter size, urine albumin concentration, and serum protein levels are reported as the mean ± s.e.m. (Adv-sFlt-1 + VEGF mRNA LNP 55: n = 5 biological replicates; PBS, Adv-sFlt-1: n = 4 biological replicates; Adv-sFlt-1 + VEGF mRNA LNP 98: n = 3 biological replicates). Mean blood vessel area is reported as the median with the 25th and 75th percentiles (1–2 placentas per mouse, 2 sections per placenta, 2–3 images per section). Ordinary (b–d) or nested (k) two-sided, one-way ANOVAs or ordinary two-sided, two-way ANOVAs (a, e–j) with post hoc Student’s t tests using the Holm-Šídák correction for multiple comparisons were used to compare responses across treatment groups.

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Extended Data Fig. 7 In inflammation-induced pre-eclampsia, VEGF mRNA LNP 55 partially restores a healthy immune landscape in the blood and placenta.

a–c, Immunophenotyping was performed to evaluate differences in the proportion of immune cell populations in the (a) blood, (b) spleen, and (c) placenta in inflammation-induced pre-eclampsia following administration of the VEGF mRNA LNP 55 therapeutic. The proportion of immune cells are reported as mean±s.e.m. (n = 8 biological replicates). Ordinary two-sided, one-way (a–b) or nested two-sided, one-way (c) ANOVAs with post hoc Student’s t tests using the Holm-Šídák correction for multiple comparisons were used to compare responses across treatment groups.

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Swingle, K.L., Hamilton, A.G., Safford, H.C. et al. Placenta-tropic VEGF mRNA lipid nanoparticles ameliorate murine pre-eclampsia. Nature (2024). https://doi.org/10.1038/s41586-024-08291-2

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Received:18 September 2023

Accepted:25 October 2024

Published:11 December 2024

DOI:https://doi.org/10.1038/s41586-024-08291-2

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