Evidence map›Paper›PMID 38079576›Full record

ArticleDiabetes2024

Multiomics Analyses With Stool-Type Stratification in Patient Cohorts and Blautia Identification as a Potential Bacterial Modulator in Type 2 Diabetes Mellitus.

Qian Guo, Zezheng Gao, Linhua Zhao, Han Wang, Zhen Luo, Doris Vandeputte, Lisha He, Mo Li, Sha Di, Yanwen Liu and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in Diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% of its field
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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
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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

14 authors at 6 institutions in 3 countries.

Qian GuoDepartment of Biomedical Engineering, College of Future Technology, and Center for Quantitative Biology, Peking University, Beijing, China.
Zezheng GaoInstitute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing.
Linhua ZhaoInstitute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing.ORCID 0000-0002-0362-7365
Han WangInstitute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing.
Zhen LuoInfinitus (China) Company Ltd., Jiangmen, China.
Doris VandeputteMeinig School of Biomedical Engineering, Cornell University, Ithaca, NY.
Lisha HeChengdu University of Traditional Chinese Medicine, Chengdu, China.
Mo LiDepartment of Biomedical Engineering, College of Future Technology, and Center for Quantitative Biology, Peking University, Beijing, China.
Sha DiInstitute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing.
Yanwen LiuDepartment of Endocrinology, Zhengzhou Traditional Chinese Medicine Hospital, Zhengzhou, China.
Jiaheng HouDepartment of Biomedical Engineering, College of Future Technology, and Center for Quantitative Biology, Peking University, Beijing, China.
Xiaoqing JiangDepartment of Biomedical Engineering, College of Future Technology, and Center for Quantitative Biology, Peking University, Beijing, China.
Huaiqiu ZhuDepartment of Biomedical Engineering, College of Future Technology, and Center for Quantitative Biology, Peking University, Beijing, China.ORCID 0000-0002-6376-218X
Xiaolin TongInstitute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing.ORCID 0000-0002-9873-4154
Chinese Academy of Medical Sciences & Peking Union Medical College · CNPeking University · CNChengdu University of Traditional Chinese Medicine · CNCornell University · USInfinitus (China) · CNZhengzhou City Hospital · CN

Funding

Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine ZYYCXTD-D-202001National Natural Science Foundation of China 31671366Research and Development Program of China 2021YFC2300300
6 · The paper itself

Abstract

Heterogeneity in host and gut microbiota hampers microbial precision intervention of type 2 diabetes mellitus (T2DM). Here, we investigated novel features for patient stratification and bacterial modulators for intervention, using cross-sectional patient cohorts and animal experiments. We collected stool, blood, and urine samples from 103 patients with recent-onset T2DM and 25 healthy control subjects (HCs), performed gut microbial composition and metabolite profiling, and combined it with host transcriptome, metabolome, cytokine, and clinical data. Stool type (dry or loose stool), a feature of the stool microenvironment recently explored in microbiome studies, was used for stratification of patients with T2DM as it explained most of the variation in the multiomics data set among all clinical parameters in our covariate analysis. T2DM with dry stool (DM-DS) and loose stool (DM-LS) were clearly differentiated from HC and each other by LightGBM models, optimal among multiple machine learning models. Compared with DM-DS, DM-LS exhibited discordant gut microbial taxonomic and functional profiles, severe host metabolic disorder, and excessive insulin secretion. Further cross-measurement association analysis linked the differential microbial profiles, in particular Blautia abundances, to T2DM phenotypes in our stratified multiomics data set. Notably, oral supplementation of Blautia to T2DM mice induced inhibitory effects on lipid accumulation, weight gain, and blood glucose elevation with simultaneous modulation of gut bacterial composition, revealing the therapeutic potential of Blautia. Our study highlights the clinical implications of stool microenvironment stratification and Blautia supplementation in T2DM, offering promising prospects for microbial precision treatment of metabolic diseases. ARTICLE HIGHLIGHTS:

Indexed as

Diabetes Mellitus, Type 2AnimalsBacteriaCross-Sectional StudiesFecesHumansMiceMultiomics

Identifiers

PMID38079576
PMCPMC10882154
OpenAlexW4389537513

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.