Hypertensive disorders in pregnancy, of which the multisystem pathology pre-eclampsia is most severe, often lead to preterm delivery, maternal mortality and life-long complications1. Pre-eclampsia lacks early screening tools2–4 and causal therapies5,6, illustrating the urgent need for a better understanding of early disease dynamics. Here we present the first study comparing single-nuclei transcriptomes of human diseased preterm preeclamptic placentae and healthy controls, embedding the characterisation of the maternal-foetal barrier dysfunction in the context of a comprehensive spatio-temporal study including early and late gestational placentae. Our results highlight and contextualise a disturbed communication from foetal to maternal side during the development of pre-eclampsia starting with a disturbed trophoblast stem-cell maturation. We provide new targets for potential early disease prevention in order to protect mother and child from increased gestational mortality and morbidity but also from life-long increased cardiovascular disease risk. This repository contains microscopy and Visium (10x spatial transcriptomics) data used in the study. It contains the Seurat object and output files. 1. Say, L. et al. Global causes of maternal death: A WHO systematic analysis. The Lancet Global Health 2, (2014). 2. Brown, M. A. et al. Hypertensive disorders of pregnancy: ISSHP classification, diagnosis, and management recommendations for international practice. Hypertension vol. 72 24–43 (2018). 3. Zeisler, H. et al. Predictive Value of the sFlt-1:PlGF Ratio in Women with Suspected Preeclampsia. New England Journal of Medicine 374, 13–22 (2016). 4. National Institute for Health and Care Excellence. 1 Recommendations | PlGF-based testing to help diagnose suspected pre-eclampsia (Triage PlGF test, Elecsys immunoassay sFlt-1/PlGF ratio, DELFIA Xpress PlGF 1-2-3 test, and BRAHMS sFlt-1 Kryptor/BRAHMS PlGF plus Kryptor PE ratio) | Guidance | NICE. https://www.nice.org.uk/guidance/dg23/chapter/1-Recommendations (2019). 5. Gestational Hypertension and Preeclampsia: ACOG Practice Bulletin, Number 222. Obstetrics and gynecology 135, e237–e260 (2020). 6. Hauth, J. C. et al. Pregnancy outcomes in healthy nulliparas who developed hypertension. Calcium for Preeclampsia Prevention Study Group. Obstetrics and gynecology (2000). Funding Details: F. H. and D.N.M. were supported by Deutsche Forschungsgemeinschaft (HE6249/5-1; HE6249/7-1; HE6249/7-2; D.N.M.: Projektnummer 394046635 - SFB 1365). D.N.M. was supported by grants from the German Centre for Cardiovascular Research (DZHK; BER 1.1 VD). O. N. was supported through the PhD program Inflammatory Disorders in Pregnancy (DP-IDP) by the Austrian Science Fund (FWF): Doc 31-B26, PhD program Molecular Medicine at the Medical University of Graz, and through the Marietta Blau Grant by the Austrian Federal Ministry for Education, Science and Research (OeAD; BMBWF), and with grants from the MeFo Graz (PS-Stipendium 2019/2020), German Association of Prenatal Diagnostics and Obstetrics (DGPGM, 2020). K.S., T.K. and A.E-H. were supported by the K1 COMET Competence Center CBmed (Center for Biomarker Research in Medicine), which is funded by the Federal Ministry of Transport, Innovation and Technology (BMVIT), Land Steiermark (Department 12, Business and Innovation), BMWFW, the Styrian Business Promotion Agency (SFG), and the Vienna Business Agency. The COMET programme is executed by the Austrian Research Promotion Agency (FFG). K.S. was supported by the Doctoral School in Translational Molecular and Cellular Biosciences at the Medical University of Graz. M.G. was supported by the FWF: (P 29639, P33554, I 3304, and Doc 31-B26) and the Medical University Graz through the PhD programs Inflammatory Disorders in Pregnancy (DP-IDP) and MolMed. B.H. was supported by the FWF: (Doc 31-B26) and the Medical University Graz through the PhD program Inflammatory Disorders in Pregnancy (DP-IDP). Sebastian Tiesmeyer was supported by Federal Ministry of Education and Research of Germany in the framework of SAGE (031L0265). This work was supported by the BMBF-funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI)