Evidence map›Paper›PMID 42050615›Full record

ArticleBioData mining2026

Divide-and-conquer analysis reveals hidden immune cell influencers across the placenta in preeclampsia.

Hyojung Paik, Tae Lyun Ko, Myungsun Park, Jong-Eun Park, Daniel Bunis, Marina Sirota, Byung Soo Lee, Hyoung-Sam Heo, Sung Ki Lee

Abstract read
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Article in BioData mining, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Hyojung Paik *Center for Biomedical Computing, Korea Institute of Science and Technology Information (KISTI), Department of Data and HPC Science, Department of Advanced Bioconvergence, Korea National University of Science and Technology (UST), Daejeon, 34141, Republic of Korea. hyojungpaik@gmail.com.
Tae Lyun Ko *Center for Biomedical Computing, Korea Institute of Science and Technology Information (KISTI), Department of Data and HPC Science, Department of Advanced Bioconvergence, Korea National University of Science and Technology (UST), Daejeon, 34141, Republic of Korea.
Myungsun ParkGraduate School of Medical Science and Engineering, KAIST, Daejeon, 34141, Republic of Korea.
Jong-Eun ParkGraduate School of Medical Science and Engineering, KAIST, Daejeon, 34141, Republic of Korea.
Daniel BunisCoLabs, Bakar ImmunoX Initiative, University of California, San Francisco, CA94143, USA.
Marina SirotaBakar Computational Health Sciences Institute (BCHSI), University of California, San Francisco, CA94158, USA.
Byung Soo LeeDepartment of Obstetrics and Gynecology, College of Medicine, Myunggok Medical Research Institute, Konyang University, Daejeon, 158, Republic of Korea.
Hyoung-Sam HeoNew Drug Development Center, OSONG Medical Innovation Foundation, Chungbuk, 28515, Republic of Korea.
Sung Ki LeeDepartment of Obstetrics and Gynecology, College of Medicine, Myunggok Medical Research Institute, Konyang University, Daejeon, 158, Republic of Korea. sklee@kyuh.ac.kr.

Funding

the Health Industry Development Institute HI22C1318
6 · The paper itself

Abstract

backgroundPlacenta is a focal point of cellular interactions of maternal and fetal immune systems, fostering immune tolerance essential for a successful pregnancy. However, the mechanisms underlying immune dysregulation in disorders such as preeclampsia remain poorly understood.

methodsWe constructed a multilayered atlas of the human placenta by performing single-cell RNA sequencing across distinct placental layers from both normal and severe preeclamptic pregnancies. Rather than focusing on specific regions of placenta, such as the villi and decidua, we explore placental architecture by collecting pair-matched tissues from individual pregnancies to suggest appropriate placental-wide immune atlas. To interpret intercellular communication in those unexplored placental layers, we designed two conceptual models: one based on immune interaction frequency (IIF) and another on immune tolerance influencers (IT). We applied machine learning classifiers to identify gene signatures associated with preeclampsia.

resultsWe observed extensive admixture of semi-allogeneic fetal and maternal cells across all placental layers, regardless of disease status. This contradicts the IIF-based model, which is premised on that such intermixing frequency is a pathologic feature specific to preeclampsia. Instead, analysis under the IT framework revealed key molecular determinants of preeclampsia. Notably, classifier-prioritized genes associated with preeclampsia were enriched for ligands and receptors supporting a role for intercellular immune interactions. Among them, the ligand-receptor pair SPP1-CD44 between fetus and maternal immune cells emerged as peculiarly associated influencers of preeclampsia. Spatial image analysis confirmed co-localization of SPP1-CD44 expression within immune cell populations in preeclamptic placental tissue. Our study provides a comprehensive map of the human placenta and identifies disease-specific immune signaling pathways in preeclampsia using the divide and rule approach. The findings highlight SPP1-CD44 as a putative target of immune dysregulation, offering new insight into the cellular basis of maternal-fetal tolerance and its breakdown in pregnancy-related disorders. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Immune toleranceMachine learningMultilayer placentaPreeclampsiaSingle-cell transcriptomics

Identifiers

PMID42050615
PMCPMC13267352

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