Evidence mapPaperPMID 41315810Full record

ArticleCommunications medicine2025

Whole-genome profiling of age- and sex-associated DNA methylation signatures in human plasma cell-free DNA.

Wei Chen, Jinjin Xu, Guodan Zeng, Rijing Ou, Changlin Yang, Chuang Xu, Yeqin Wang, Xinxin Wang, Qiuyan Li, Chenhui Zhao and 7 more

Abstract read
In one paragraph

Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

17 authors.

Wei Chen *School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
Jinjin Xu *State Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Guodan Zeng *State Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Rijing OuState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Changlin YangState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Chuang XuState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Yeqin WangState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Xinxin WangState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Qiuyan LiState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Chenhui ZhaoState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Wenwen ZhouState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Yu LinState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Wending PangState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.
Haiqiang ZhangState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.ORCID http://orcid.org/0000-0001-8757-4549
Jianhua YinState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China.ORCID http://orcid.org/0000-0003-1207-7788
Yan ZhangState Key Laboratory of Genome and Multi-Omics Technologies, BGI Research, Shenzhen, China. zhangyan15@genomics.cn.ORCID http://orcid.org/0000-0003-2281-7807
Xin JinSchool of Medicine, South China University of Technology, Guangzhou, Guangdong, China. jinxin@genomics.cn.ORCID http://orcid.org/0000-0001-7554-4975

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAge and sex significantly impact DNA methylation patterns, however, existing datasets typically include only a subset of methylation sites in the human genome, hindering our thorough understanding.

methodsWe recruited 98 generally healthy adults aged from 22 to 77 and investigated the effects of age and sex on plasma cell-free DNA (cfDNA) methylation through whole-genome bisulfite sequencing (WGBS) and association analysis.

resultsHere we show 3,047 age-associated and 1,053 sex-associated CpGs on autosomes, corresponding to 1,587 and 324 genes, respectively. To the best of our knowledge, many of these CpGs are newly discovered to be age- and sex-related at the DNA methylation level. The discovered sex-differential cfDNA methylation patterns on the X chromosome are related to XCI status. Besides, a cfDNA epigenetic clock comprising 125 CpGs is developed, demonstrating relatively high accuracy in predicting chronological age. Tissue-of-origin analysis reveals that cfDNA derived from monocytes/macrophages, granulocytes, and hepatocytes is associated with age and sex. Several individuals with abnormal cfDNA proportions of some specific cell types are found to have individual health problems.

conclusionsOur discovered CpGs and genes help to explain age-related and sex-biased diseases such as psychiatric disorders, diabetes, and autoimmune diseases, and we demonstrate the potential of cfDNA methylation signatures as very promising biomarkers for health monitoring for the general population.

Identifiers

PMID41315810
PMCPMC12663547

What Socratic holds

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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 Socratic graph.