Evidence map›Paper›PMID 40585172›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Cell type proportions rather than DNA methylation in the cord blood show significant associations with severe preeclampsia.

Xiaotong Yang, Wenting Liu, Zhixin Mao, Yuheng Du, Cameron Lassiter, Fadhl M AlAkwaa, Paula A Benny, Lana X Garmire

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiaotong YangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI.
Wenting LiuDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI.
Zhixin MaoDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI.
Yuheng DuDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI.
Cameron LassiterUniversity of Hawaii Cancer Center, Epidemiology, Honolulu, HI.
Fadhl M AlAkwaaDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI.
Paula A BennyUniversity of Hawaii Cancer Center, Epidemiology, Honolulu, HI.
Lana X GarmireDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI.

Funding

University of Hawaii Cancer Center CCSGP30CA071789 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI Pallav Pokhrel · 1996 to 2026
$56.2M
An Integrative Omics Approach to Identify Biomarkers Related to Preeclampsia and Breast Cancer RisksR01HD084633 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2016 to 2020
$3.0M
Biomedical Informatics and Data Science Training Program (BIDS-TP)T32GM141746 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Ivo D Dinov, RYAN E MILLS · 2021 to 2026
$2.6M
Cancer precision medicine through spatially informative single cell image and transcriptomics data analysisR01LM012373 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2016 to 2024
$2.4M
DR. EPS: Drug Repurposing for Extended Patient SurvivalR01LM012907 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2019 to 2022
$1.0M
NCI NIH HHS P30 CA071789NICHD NIH HHS R01 HD084633NIGMS NIH HHS T32 GM141746NLM NIH HHS R01 LM012373NLM NIH HHS R01 LM012907
6 · The paper itself

Abstract

Preeclampsia (PE) is a severe pregnancy complication that threatens maternal and neonatal health. Previous epigenome-wide association studies (EWAS) on PE have produced inconsistent results, possibly due to inadequate adjustment for confounders. Here, we analyzed DNA methylation changes in cord blood from newborns affected by PE, using a multi-ethnic cohort from Hawaii. We comprehensively adjusted for clinical variables (maternal age, BMI, parity) and estimated cell proportions. Additionally, we re-analyzed two public datasets with similar adjustments and conducted a meta-analysis combining all three datasets to increase statistical power. To further address confounding by gestational age, we also included idiopathic preterm samples as controls. After adjusting for cell type proportions and clinical characteristics, all previously reported significant CpG methylation changes associated with severe PE disappeared across our data, the two public datasets, and the meta-analysis. This result remained even after including idiopathic preterm samples. Instead, severe PE was associated with shifts in CD8T and natural killer (NK) cell proportions. We validated this lack of CpG changes using multiple published cord blood methylation datasets. Moreover, we observed that gestational progression itself is accompanied by significant changes in granulocyte, nRBC, CD8T, and B cell proportions. In summary, our study demonstrates that many previously reported DNA methylation changes in severe PE are artifacts caused by confounding factors such as cell type heterogeneity and gestational age. Severe PE is associated with changes in cell proportions rather than direct methylation alterations. These findings emphasize the importance of rigorous confounder adjustment in EWAS.

Indexed as

cell-type deconvolutioncord bloodDNA methylationepigenome-wide association studypreeclampsiawomen’s health

Identifiers

PMID40585172
PMCPMC12204453

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.