Evidence Hub

Engineered trophoblast organoids recapitulate molecular and functional features of preeclampsia

Arthurs AL, Lushington C, Medina Garcia DL, Merriman AL, Mora-Roldan GA, Parry L, Boparai A, Polo JM et al.

2026

Abstract

Preeclampsia is a major pregnancy complication driven by placental dysfunction, yet research is limited by reliance on patient-derived tissues and models that do not fully capture human disease. Here, we develop a genetically engineered human trophoblast organoid model of preeclampsia that can be generated without access to placental tissue. Using a CRISPR-based Prime Integrase strategy, we engineered induced trophoblast stem cells to express the preeclampsia-associated soluble fms-like tyrosine kinase-1 (sFlt-1) exon 15a isoform. Engineered organoids showed a transcriptional shift towards primary preeclamptic placentae and developed several features of disease. These included reduced PlGF, increased IL-6 and soluble endoglin, oxidative stress, impaired growth and an elevated sFlt-1/PlGF ratio comparable to primary preeclamptic trophoblast organoids. These broader changes were not reproduced by adding recombinant human sFlt-1 to control organoids. Conditioned media from engineered organoids impaired endothelial network formation, demonstrating a functional effect of the altered trophoblast secretome. Treatment with sulfasalazine and metformin also restored angiogenic balance and organoid growth. Together, these findings establish a tractable human model that reproduces molecular and functional features of preeclampsia and provides a platform to study disease mechanisms and test potential therapies.

How strong is the evidence?

Evidence Hub reads this as a preprint, done in cell cultures (in vitro), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free