Evidence map›Paper›PMID 39463013›Full record

ArticleJournal of diabetes2024

Gut microbiota, serum metabolites, and lipids related to blood glucose control and type 1 diabetes.

Zhaohe Gu, Lanxin Pan, Huiling Tan, Xulin Wang, Jing Wang, Xueying Zheng, Jianping Weng, Sihui Luo, Tong Yue, Yu Ding

Abstract read
In one paragraph

Article in Journal of diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. [Gut microbiota dysbiosis in type 1 diabetes mellitus: Impacts, mechanisms, and interventions].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
    Review
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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

10 authors.

Zhaohe GuDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0009-0005-6594-0241
Lanxin PanDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.
Huiling TanDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0000-0001-8765-9163
Xulin WangDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.
Jing WangDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.
Xueying ZhengDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.
Jianping WengDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.
Sihui LuoDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0000-0001-8503-0310
Tong YueDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0000-0002-7203-6948
Yu DingDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0000-0003-1617-2125

Funding

the Anhui Provincial Natural Science Foundation 2008085MH248the Anhui Provincial Natural Science Foundation 2008085MH278the Program for Innovative Research Team of The First Affiliated Hospital of USTC CXGG02the Strategic Priority Research Program of Chinese Academy of Sciences XDB38010100the Young Scientists Fund of the National Natural Science Foundation of China 82100822
6 · The paper itself

Abstract

backgroundThe composition and function of gut microbiota, lipids, and metabolites in patients with type 1 diabetes (T1D) or its association with glycemic control remains unknown. We aimed to use multi-omics sequencing technology and machine learning (ML) approaches to investigate potential function and relationships among the gut microbiota, lipids, and metabolites in T1D patients at varied glycemic levels.

methodsWe conducted a multi-omics analysis of the gut microbiome from fecal samples, metabolites, and lipids obtained from serum samples, collected from a cohort of 72 T1D patients. The patients were divided into two groups based on their hemoglobin A1c (HbA1c) levels. 16S rRNA sequencing, and metabolomics methods were applied to analyze changes in composition and function of gut microbiota, metabolites, and lipids.

resultsThe linear discriminant analysis, Shapley additive explanations (SHAP) algorithm, and ML algorithms revealed the enrichment of Bacteroides_nordii, Bacteroides_cellulosilyticus in the glycemic control (GC) group, while Bacteroides_coprocola and Sutterella_wadsworthensis were enriched in the poor glycemic control (PGC) group. Several metabolic enrichment sets like fatty acid biosynthesis and glycerol phosphate shuttle metabolism were different between two groups. Bacteroides_nordii exhibited a negative association with D-fructose, a component involved in the starch and sucrose metabolism pathway, as well as with monoglycerides (16:0) involved in the glycerolipid metabolism pathway.

conclusionsWe identified distinct characteristics of gut microbiota, metabolites, and lipids in T1D patients exhibiting different levels of glycemic control. Through comprehensive analysis, microbiota (Bacteroides_nordii, Bacteroides_coprocola), metabolites (D-fructose), and lipids (Monoglycerides) may serve as potential mediators that communicated the interaction between the gut, circulatory systems, and glucose fluctuations in T1D patients.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 1Gastrointestinal MicrobiomeLipidsAdolescentAdultFecesFemaleGlycated HemoglobinGlycemic ControlHumansMachine LearningMaleMetabolomicsMiddle AgedRNA, Ribosomal, 16SBlood GlucoseGlycated HemoglobinLipidsRNA, Ribosomal, 16Sglycemic controlgut microbiomelipidomicsmetabolomicstype 1 diabetes mellitus

Identifiers

PMID39463013
PMCPMC11513438

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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 OpenQuestion graph.