The Alteration in Composition and Function of Gut Microbiome in Patients with Type 2 Diabetes
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
Authors
Zhao X, Zhang Y, Guo R, Yu W, Zhang F, Wu F, Shang J
Journal
Journal of diabetes research
Year
2020
Background: Diabetes mellitus (DM) has become one of the most common chronic metabolic diseases worldwide. Due to the increasing prevalence and various complications, diabetes brings about a huge financial burden to DM patients. Nowadays, more and more studies reveal the relationship between diseases and gut microbial community. We aimed to explore the alteration in composition and function of the gut microbiome in T2DM patients. Methods: A total of 137 patients with diabetes and 179 age- and gender-matched healthy controls selected from the healthy people sample center in the First Affiliated Hospital of Zhengzhou University were divided into the DM group and the Con group, respectively. We collected their venous blood for laboratory tests and stool samples for 16S rRNA sequencing. The comparison between the two groups including both composition and function of the gut microbiome is presented. Results: We found that the α-diversity of bacterial taxa in the DM group had an evident decrease compared to that in the Con group. At the phylum level, the DM group had an obvious decrease of Bacteroidetes and a marked increase of Proteobacteria, Actinobacteria, and Verrucomicrobia. At the genus level, Bacteroides and Prevotella decreased the most while Escherichia-Shigella, Lachnospiraceae_incertae_sedis, Subdoligranulum, Enterococcus, and Klebsiella had different degrees of expansion in the DM group. The ROC based on 246 optimum OTUs had very high test efficiency with an AUC of 92.25% in the training set and 90.48% in the test set. As for prediction of metabolic function, the gut microbiome of DM patients was predicted to be more active in environmental information processing and human diseases but less in metabolism. Conclusion: We observed alteration of composition and function of the gut microbiome in the DM group. These changes may provide a new treatment strategy for DM patients and new research targets.
Experiment 1
Needs review
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled (if applicable)
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- type II diabetes mellitus adult onset diabetes,Adult-Onset Diabetes,adult-onset diabetes,Adult-Onset Diabetes Mellitus,diabetes mellitis type 2,diabetes mellitis type II,DIABETES MELLITUS TYPE 02,diabetes mellitus type 2,Diabetes Mellitus, Adult Onset,Diabetes Mellitus, Adult-Onset,Diabetes Mellitus, Ketosis Resistant,Diabetes Mellitus, Ketosis-Resistant,Diabetes Mellitus, Maturity Onset,Diabetes Mellitus, Maturity-Onset,Diabetes Mellitus, Non Insulin Dependent,Diabetes Mellitus, Non-Insulin-Dependent,Diabetes Mellitus, Noninsulin Dependent,diabetes mellitus, noninsulin-dependent,Diabetes Mellitus, Slow Onset,Diabetes Mellitus, Slow-Onset,Diabetes Mellitus, Stable,Diabetes Mellitus, Type 2,diabetes mellitus, type 2,diabetes mellitus, type 2, protection against,Diabetes Mellitus, Type II,Diabetes, Type 2,diabetes, type 2,insulin resistance, susceptibility to,Ketosis-Resistant Diabetes Mellitus,Maturity Onset Diabetes Mellitus,maturity-onset diabetes,Maturity-Onset Diabetes Mellitus,MODY,NIDDM,Non-Insulin Dependent Diabetes,non-insulin dependent diabetes,Non-Insulin Dependent Diabetes Mellitus,non-insulin dependent diabetes mellitus,non-insulin-dependent diabetes mellitus,noninsulin dependent diabetes,noninsulin-dependent diabetes mellitus,Slow-Onset Diabetes Mellitus,Stable Diabetes Mellitus,T2DM - Type 2 Diabetes mellitus,T2DM - type 2 diabetes mellitus,Type 2 Diabetes,type 2 diabetes,Type 2 Diabetes Mellitus,type 2 diabetes mellitus,Type 2 Diabetes Mellitus Non-Insulin Dependent,type 2 diabetes mellitus non-insulin dependent,Type II Diabetes,type II diabetes,type II diabetes mellitus
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy controls
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Individuals diagnosed with Type 2 Diabetes Mellitus
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients with Type 2 Diabetes who were admitted to the First Affiliated Hospital of Zhengzhou University from October 2018 to October 2019; The diagnostic criteria of diabetes mellitus were as follows: (1) twice fasting plasma glucose ðFPGÞ ≥ 7:0 mmol/L, (2) twice oral glucose tolerance test (OGTT ≥ 11:1 mmol/L), and (3) diabetic symptoms (polyuria, thirst, drinking more water, and unexplained weight loss) accompanied with twice random blood glucose ≥ 11:1 mmol/L.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 179
- Group 1 sample size Number of subjects in the case (exposed) group
- 137
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- long-term antibiotic application
Lab analysis
- Sequencing type
- 16S
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- V3-V4
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Illumina
Statistical Analysis
- Statistical test
- LEfSe
- Mann-Whitney (Wilcoxon)
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
- Matched on Factors on which subjects have been matched on in a case-control study
- age, sex
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
Signature 1
Needs review
Source: Figure 2
Description: Decreased abundance of bacterial communities in individuals with Type 2 Diabetes
Abundance in Group 1: decreased abundance in Individuals diagnosed with Type 2 Diabetes Mellitus
Revision editor(s): Madhubani Dey, Aiyshaaaa
Signature 2
Needs review
Source: Figure 2
Description: Increased abundance of bacterial communities in individuals with Type 2 Diabetes
Abundance in Group 1: increased abundance in Individuals diagnosed with Type 2 Diabetes Mellitus
Revision editor(s): Lwaldron, Madhubani Dey
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