Evidence mapPaperPMID 41786719Full record

ArticleNature communications2026

Genetic variations interact with polybrominated diphenyl ether exposure to alter lipid homeostasis.

Naifan Hu, Bin Li, Yifu Lu, Qi Jiang, Ying Zhu, Zheng Li, Yingli Qu, Tian Qiu, Donghui Zhang, Zhuo Wang and 15 more

Abstract read
In one paragraph

Article in Nature communications, 2026. 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. Review
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

25 authors.

Naifan Hu *Department of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Bin Li *Department of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Yifu Lu *China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Qi Jiang *Department of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.ORCID http://orcid.org/0000-0002-3872-6312
Ying Zhu *Department of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.ORCID http://orcid.org/0000-0002-3813-7577
Zheng Li *China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Yingli QuChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Tian QiuChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Donghui ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Zhuo WangDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Yunfei MaDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Huibin JinDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Peijie SunChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Haocan SongChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Yunhao ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Yifan ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Ming ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
Feng ZhaoChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Saisai JiChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Bifeng YuanDepartment of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan, China.ORCID http://orcid.org/0000-0001-5223-4659
Ying ZhuChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. zhuying@nieh.chinacdc.cn.
Yuebin LvChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. lvyuebin@nieh.chinacdc.cn.ORCID http://orcid.org/0009-0006-5532-3917
Jianbo TianDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China. tianjb@whu.edu.cn.ORCID http://orcid.org/0000-0001-9493-694X
Xiaoping MiaoDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China. xpmiao@whu.edu.cn.ORCID http://orcid.org/0000-0002-6818-9722
Xiaoming ShiDepartment of Epidemiology and Biostatistics, School of Public Health, State Key Laboratory of Metabolism and Regulation in Complex Organisms, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China. shixm@chinacdc.cn.ORCID http://orcid.org/0000-0002-7071-571X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82404355
6 · The paper itself

Abstract

Polybrominated diphenyl ethers (PBDEs) are implicated in dyslipidemia, but the molecular basis of individual susceptibility remains elusive. Here we report an analysis based on the China National Human Biomonitoring cohort, where we integrate exposome, genomic, and metabolomic data to identify 3,571 genetic variants that interact with PBDE exposure to influence dyslipidemia risk. Metabolomic analysis highlights glycine and glycerophosphate as key mediators. A polygenic risk score derived from these PBDE-interactive variants significantly enhances dyslipidemia prediction in highly exposed individuals. Among these, rs9869609 emerges as a candidate causal variant, showing the strongest association with hypercholesterolemia risk (β = 1.18, FDR = 0.0078). Further functional validation using single-base CRISPR/Cas9 editing reveals that the rs9869609-G allele downregulates SLC6A20 expression by strengthening BHLHE40 binding, which further impairs glycine transport and promotes cholesterol accumulation, particularly under 2,2',4,4'-Tetrabromodiphenyl ether exposure. Collectively, our study elucidates a gene-environment interaction mechanism through which genetic variants modulate lipid metabolism in response to PBDE exposure.

Indexed as

Genetic VariationHalogenated Diphenyl EthersHomeostasisLipid MetabolismChinaEnvironmental ExposureGene-Environment InteractionGenetic Risk ScoreHumansPolymorphism, Single Nucleotide2,2',4,4'-tetrabromodiphenyl etherHalogenated Diphenyl Ethers

Identifiers

PMID41786719
PMCPMC13087138

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.