Gut Microbiome Profiles Are Associated With Type 2 Diabetes in Urban Africans

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Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/31
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
Authors
Doumatey AP, Adeyemo A, Zhou J, Lei L, Adebamowo SN, Adebamowo C, Rotimi CN
Journal
Frontiers in cellular and infection microbiology
Year
2020
Keywords:
16S V4 rRNA sequencing, gut microbiome, microbial composition, type 2 diabetes, urban Africans
Gut dysbiosis has been associated with several disease outcomes including diabetes in human populations. Currently, there are no studies of the gut microbiome composition in relation to type 2 diabetes (T2D) in Africans. Here, we describe the profile of the gut microbiome in non-diabetic adults (controls) and investigate the association between gut microbiota and T2D in urban West Africans. Gut microbiota composition was determined in 291 Nigerians (98 cases, 193 controls) using fecal 16S V4 rRNA gene sequencing done on the Illumina MiSeq platform. Data analysis of operational taxonomic units (OTU) was conducted to describe microbiome composition and identify differences between T2D and controls. The most abundant phyla were Firmicutes, Actinobacteria, and Bacteroidetes. Clostridiaceae, and Peptostreptococcaceaea were significantly lower in cases than controls (p < 0.001). Feature selection analysis identified a panel of 18 OTUs enriched in cases that included Desulfovibrio piger, Prevotella, Peptostreptococcus, and Eubacterium. A panel of 17 OTUs that was enriched in the controls included Collinsella, Ruminococcus lactaris, Anaerostipes, and Clostridium. OTUs with strain-level annotation showing the largest fold-change included Cellulosilyticum ruminicola (log2FC = -3.1; p = 4.2 × 10-5), Clostridium paraputrificum (log2FC = -2.5; p = 0.005), and Clostridium butyricum (log2FC = -1.76; p = 0.01), all lower in cases. These findings are notable because supplementation with Clostridium butyricum and Desulfovibrio piger has been shown to improve hyperglycemia and reduce insulin resistance in murine models. This first investigation of gut microbiome and diabetes in urban Africans shows that T2D is associated with compositional changes in gut microbiota highlighting the possibility of developing strategies to improve glucose control by modifying bacterial composition in the gut.

Experiment 1


Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/31

Curated date: 2021/05/26

Curator: Madhubani Dey

Revision editor(s): Madhubani Dey, Claregrieve1, WikiWorks, Victoria

Subjects

Location of subjects
Nigeria
Host species Species from which microbiome was sampled. Contact us to have more species added.
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,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,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
Individuals diagnosed with Type 2 Diabetes Mellitus; The definition of T2D was based on the American Diabetes Association (ADA) criteria: a fasting plasma glucose concentration (FPG) ≥ 126 mg/dl (7.0 mmol/l) or a 2-h post-load value in the oral glucose tolerance test ≥ 200 mg/dl (11.1 mmol/l) on more than one occasion. Alternatively, a diagnosis of T2D was accepted if an individual was on pharmacological treatment for T2D, and a review of clinical records indicated adequate justification for that therapy.
Group 0 sample size Number of subjects in the control (unexposed) group
193
Group 1 sample size Number of subjects in the case (exposed) group
98

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V4
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
raw counts
Statistical test
DESeq2
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
Yes

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
increased
Richness Number of species
increased

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/31

Curated date: 2021/06/27

Curator: Madhubani Dey

Revision editor(s): Madhubani Dey, Claregrieve1

Source: Table 3, Table 4

Description: Differential microbial abundance between controls and individuals with Type 2 Diabetes

Abundance in Group 1: decreased abundance in Individuals diagnosed with Type 2 Diabetes Mellitus

NCBI Quality ControlLinks
Cellulosilyticum ruminicola
Clostridiaceae
Clostridium butyricum
Clostridium paraputrificum
Bacillota
Peptostreptococcaceae

Revision editor(s): Madhubani Dey, Claregrieve1

Signature 2

Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/31

Curated date: 2021/08/15

Curator: Madhubani Dey

Revision editor(s): Madhubani Dey, Claregrieve1

Source: Table 3, Table 4

Description: Differential microbial abundance between controls and individuals with Type 2 Diabetes

Abundance in Group 1: increased abundance in Individuals diagnosed with Type 2 Diabetes Mellitus

NCBI Quality ControlLinks
Bacteroidota
Desulfovibrio piger ATCC 29098
Euryarchaeota
Prevotella
Terrisporobacter glycolicus
[Ruminococcus] lactaris ATCC 29176

Revision editor(s): Madhubani Dey, Claregrieve1