Evidence mapPaperPMID 41634745Full record

ArticleBMC medicine2026

Association of DNA methylation with hypertension and blood pressure: a 7-year longitudinal study from KORA F4/FF4.

Liye Lai, Angelina Shin Yee Jong, Thomas Delerue, Jiesheng Lin, Barbara Thorand, Margit Heier, Holger Prokisch, Aiman Farzeen, Juliane Winkelmann, Elisabeth Thiering and 3 more

Abstract read
In one paragraph

Article in BMC medicine, 2026. 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

13 authors.

Liye LaiResearch Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany. LaiLiye@outlook.com.
Angelina Shin Yee JongResearch Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Thomas DelerueResearch Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Jiesheng LinInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Barbara ThorandInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Margit HeierInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Holger ProkischInstitute of Neurogenomics, Computational Health Center, Helmholtz Zentrum München, Neuherberg, Germany.
Aiman FarzeenResearch Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Juliane WinkelmannInstitute of Neurogenomics, Computational Health Center, Helmholtz Zentrum München, Neuherberg, Germany.
Elisabeth ThieringInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Christian GiegerResearch Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Annette PetersInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Melanie WaldenbergerResearch Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany. melanie.waldenberger@helmholtz-munich.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypertension (HTN) has been linked to changes in DNA methylation. However, longitudinal epigenome-wide analyses are still limited.

methodsWe analyzed data from the KORA F4 and FF4 studies, conducted approximately 7 years apart. The dataset included 2614 participants, each with DNA methylation measured at least once. Leucocyte DNA methylation was profiled using the Illumina 450 k and EPIC arrays. Linear mixed-effects models were employed to identify associations between methylation sites and HTN status, systolic (SBP) and diastolic blood pressure (DBP). Interaction terms with follow-up time captured longitudinal methylation trajectories. We further examined CpG sites related to reversed, persistent, or progressive HTN and assessed their correlations with gene expression.

resultsOne CpG site was associated with SBP and four with DBP, all representing novel loci, including RILP (cg08625564) and SVIL (cg15298791). Differential annual methylation changes were observed for 2, 23, and 12 CpG sites by HTN status, SBP, and DBP, respectively, highlighting genes such as RHPN2, CLDND1, ZNF69, and FKBP1B. Twenty CpG sites were associated with persistent HTN, including PLCB2 and MPPE1. In whole blood, 22 significant CpG-transcript pairs were detected, involving 14 CpG sites and 19 gene transcripts.

conclusionsThis longitudinal epigenome-wide study identified novel CpG sites associated with blood pressure and persistent HTN. We observed differential DNA methylation trajectories over time linked to HTN, SBP, and DBP, with several changes correlating with gene expression, suggesting functional relevance. These findings underscore the dynamic role of DNA methylation in blood pressure regulation and provide new insights into epigenetic mechanisms of HTN.

Indexed as

Blood PressureDNA MethylationHypertensionAgedCpG IslandsEpigenesis, GeneticFemaleHumansLongitudinal StudiesMaleMiddle AgedBlood pressureDNA methylationGene expressionHypertensionMethylation trajectory

Identifiers

PMID41634745
PMCPMC12930669

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.