Evidence map›Paper›PMID 41565707›Full record

ArticleNPJ science of food2026

Tailored effects of coarse grain substitution on blood pressure via gut microbiota-metabolite networks and host gene variants: a randomized controlled trial.

Junqi Li, Yifei He, Juan He, Jiawen Xie, Chen He, Kaizhen Jia, Menghan Wang, Wei Li, Xinran Feng, Guoqing Ma and 12 more

Abstract read
In one paragraph

Article in NPJ science of food, 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

22 authors.

Junqi Li *Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Yifei He *Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Juan HeDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Jiawen XieDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Chen HeDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Kaizhen JiaDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Menghan WangDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Wei LiDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Xinran FengDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Guoqing MaDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Amei TangDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Kun XuDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Haozhi NiuDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Xia LiaoDepartment of Nutrition, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Hang YuDepartment of Cardiovascular Medicine, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Lin ShiSchool of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, China.
Lu LiGuilin Seamild Food Co., Ltd, Guilin, China.
Linyuan SiGuilin Seamild Food Co., Ltd, Guilin, China.
Fangyao ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Baibing MiDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Tian TianDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China. yyktiantian@163.com.
Xin LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, China. xinliu@xjtu.edu.cn.

Funding

National Natural Science Foundation of China 82173504
6 · The paper itself

Abstract

We previously reported inverse associations of coarse grain (CG) intake with blood pressure, mediated by metabolites and gut microbiota. In this 12-week randomized controlled trial among 172 prehypertension participants, both the CG (100 g/day) group and the control group (refined grain) showed significant reductions in systolic blood pressure (SBP) and diastolic blood pressure (DBP) over 12 weeks, with no significant time by group interaction. In the exploratory analyses of secondary outcomes, significant time by group interactions were detected for 26 taxa (such as g__Lactococcus and g__Faecalibacterium), associated with 23 differential fecal metabolites, which in turn were correlated with blood pressure changes over the CG intervention. Microbial ATP-binding cassette transporter was highlighted in the pathway annotation for the CG-derived differential microbial taxa. Baseline gut microbiota exhibited predictive potential for blood pressure reduction, while host ABO variance rs514659 modulated the intervention effect on SBP and DBP (P interaction < 0.05), providing preliminary evidence for the tailored nutrition strategies optimizing blood pressure and gut microbiota profiles.

Identifiers

PMID41565707
PMCPMC12901048

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.