Evidence map›Paper›PMID 40570085›Full record

ArticleGenomics, proteomics & bioinformatics2025

An Integrative Polygenic and Epigenetic Risk Score for Overweight-related Hypertension in Chinese Population.

Yaning Zhang 张亚宁, Qiwen Zheng 郑启文, Qili Qian 钱其溧, Na Yuan 苑娜, Tianzi Liu 刘天资, Xingjian Gao 高行健, Xiu Fan 凡秀, Youkun Bi 毕友坤, Guangju Ji 姬广聚, Peilin Jia 贾佩林 and 3 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Yaning Zhang 张亚宁Henan Academy of Sciences, Zhengzhou 450046, China.ORCID 0000-0002-8073-3137
Qiwen Zheng 郑启文China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0001-6921-6254
Qili Qian 钱其溧CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.ORCID 0009-0005-8797-5242
Na Yuan 苑娜China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-3614-2441
Tianzi Liu 刘天资CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.ORCID 0000-0002-7401-3571
Xingjian Gao 高行健China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-6142-8102
Xiu Fan 凡秀China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-8590-9859
Youkun Bi 毕友坤Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-0195-9294
Guangju Ji 姬广聚Henan Academy of Sciences, Zhengzhou 450046, China.ORCID 0000-0001-8626-3490
Peilin Jia 贾佩林China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-4523-4153
Sijia Wang 汪思佳CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.ORCID 0000-0001-6961-7867
Fan Liu 刘凡Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 12271, Saudi Arabia.ORCID 0000-0001-9241-8161
Changqing Zeng 曾长青Henan Academy of Sciences, Zhengzhou 450046, China.ORCID 0000-0002-0037-1771

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Overweight-related hypertension (OrH), defined by the coexistence of excess body weight and hypertension (HTN), is an increasing health concern elevating cardiovascular disease risks. In this study, we evaluated the prediction performance of polygenic risk scores (PRSs) and methylation risk scores (MRSs) for OrH in 7605 Chinese participants from two cohorts: the Chinese Academy of Sciences (CAS) and the National Survey of Physical Traits (NSPT). In the CAS cohort, which predominantly consists of academics, males showed significantly higher prevalence of obesity, HTN, and OrH, along with worse metabolic syndrome indicators, compared to females. This disparity was less pronounced in the NSPT cohort and in broader Chinese epidemiological studies. Among ten PRS methods, PRS-CSx was the most effective, enhancing prediction accuracy for obesity [area under the curve (AUC) = 0.75], HTN (AUC = 0.74), and OrH (AUC = 0.75), compared to baseline models using only age and sex (AUC = 0.55-0.71). Similarly, least absolute shrinkage and selection operator (LASSO)-based MRS models improved prediction accuracy for obesity (AUC = 0.70), HTN (AUC = 0.73), and OrH (AUC = 0.78). Combining PRS and MRS further boosted prediction accuracy, achieving AUC values of 0.77, 0.76, and 0.80 for obesity, HTN, and OrH, respectively. These models stratified individuals into high (> 0.6) or low (< 0.1) risk categories, covering 59.95% for obesity, 31.75% for HTN, and 43.89% for OrH. Our findings highlight a higher OrH risk among male academics, emphasize the influence of metabolic and lifestyle factors on MRS predictions, and highlight the value of multi-omics approaches in enhancing risk stratification.

Indexed as

Epigenesis, GeneticHypertensionMultifactorial InheritanceOverweightAdultAgedChinaDNA MethylationEast Asian PeopleFemaleHumansMaleMiddle AgedObesityRisk FactorsAcademicMethylation risk scoreMulti-omics predictionOverweight-related hypertensionPolygenic risk score

Identifiers

PMID40570085
PMCPMC12854722

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.