Alterations to the Gut Microbiota and Their Correlation With Inflammatory Factors in Chronic Kidney Disease

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Reviewed Marked as Reviewed by Claregrieve1 on 2022/07/3
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Li F, Wang M, Wang J, Li R, Zhang Y
Journal
Frontiers in cellular and infection microbiology
Year
2019
Keywords:
16S rDNA deep sequencing, Akkermansia, chronic kidney disease, gut microbiota, inflammatory factors
Alterations to the gut microbiota have been previously suggested to be tightly linked to chronic systemic inflammation, which is a major contributing factor to complications and disease progression in chronic kidney disease (CKD). Nevertheless, the effect of gut dysbiosis on the pathogenesis and/or production of inflammatory factors in CKD has not been extensively studied to date. In the present study, we conducted 16S ribosomal DNA pyrosequencing using fecal microbiota samples and analyzed the production of serum inflammatory factors in 50 patients with CKD and 22 healthy control (HC) subjects. The results revealed that compared to the HC subjects, patients with CKD exhibited a significant reduction in the richness and structure of their fecal microbiota. At the phylum level, compared to the HC group, patients with CKD also presented reduced abundance of Actinobacteria but increased abundance of Verrucomicrobia. Moreover, the genera Lactobacillus, Clostridium IV, Paraprevotella, Clostridium sensu stricto, Desulfovibrio, and Alloprevotella were enriched in the fecal samples of patients with CKD, while Akkermansia and Parasutterella were enriched in those of the HC subjects. The abundance of Akkermansia in the CKD group was significantly lower than that in the HC group (3.08 vs. 0.67%); this decrease in the abundance of Akkermansia, an important probiotic, in patients with CKD is a striking discovery as it has not been previously reported. Finally, we analyzed whether these changes to the fecal microbiota correlated with CKD clinical characteristics and/or the production of known inflammatory factors. Altered levels of the microbiota genera Parasutterella, Lactobacillus, Paraprevotella, Clostridium sensu stricto, and Desulfovibrio were shown to be correlated with CKD disease-severity indicators, including the estimated glomerular filtration rate. Most notably, Akkermansia was significantly negatively correlated with the production of interleukin-10. The results of the present study suggest that microbiota dysbiosis may promote chronic systemic inflammation in CKD. Furthermore, they support that modifying the gut microbiota, especially Akkermansia, may be a promising potential therapeutic strategy to attenuate the progression of, and/or systemic inflammation in, CKD.

Experiment 1


Reviewed Marked as Reviewed by Claregrieve1 on 2022/07/3

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): Claregrieve1, WikiWorks, Victoria

Subjects

Location of subjects
China
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
Chronic kidney disease chronic kidney disease,chronic kidney failure,Chronic Kidney Insufficiencies,Chronic Kidney Insufficiency,chronic renal disease,Chronic Renal Failure,chronic renal failure syndrome,Chronic Renal Insufficiencies,chronic renal insufficiency,CKD,CKD - chronic kidney disease,Disease, End-Stage Kidney,Disease, End-Stage Renal,END STAGE KIDNEY DIS,End Stage Kidney Disease,END STAGE RENAL DIS,End Stage Renal Disease,End-Stage Kidney Disease,End-Stage Renal Disease,End-Stage Renal Failure,ESRD,kidney disease, chronic,Kidney Disease, End-Stage,Kidney Failure, Chronic,Kidney Insufficiencies, Chronic,Kidney Insufficiency, Chronic,RENAL DIS END STAGE,Renal Disease, End Stage,Renal Disease, End-Stage,renal failure - chronic,Renal Failure, Chronic,Renal Failure, End Stage,Renal Failure, End-Stage,Renal Insufficiencies, Chronic,Renal Insufficiency, Chronic,Chronic kidney disease
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
chronic kidney disease patients
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
individuals diagnosed with chronic kidney disease because they exhibited an effective glomerular filtration rate of <60mL/min for a 3 month period
Group 0 sample size Number of subjects in the control (unexposed) group
22
Group 1 sample size Number of subjects in the case (exposed) group
50
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
3 months

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

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
LEfSe
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
LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
2

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
unchanged
Simpson Estimator of species richness and species evenness: more weight on species evenness
unchanged

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/07/3

Curated date: 2021/01/10

Curator: Fatima Zohra

Revision editor(s): Claregrieve1, WikiWorks

Source: Figure 2a

Description: Taxonomic differences in fecal microbiota exhibited by patients with chronic kidney disease compared with healthy controls

Abundance in Group 1: increased abundance in chronic kidney disease patients

NCBI Quality ControlLinks
Actinomycetota
Actinomycetales
Actinomycetes
Alloprevotella
Clostridiaceae
Clostridium
Coriobacteriaceae
Coriobacteriales
Desulfovibrio
Methylobacteriaceae
Methylobacterium
Paraprevotella

Revision editor(s): Claregrieve1, WikiWorks

Signature 2

Reviewed Marked as Reviewed by Claregrieve1 on 2022/07/3

Curated date: 2021/01/10

Curator: Fatima Zohra

Revision editor(s): Lwaldron, Claregrieve1, WikiWorks

Source: Figure 2a

Description: Taxonomic differences in fecal microbiota exhibited by patients with chronic kidney disease compared with healthy controls

Abundance in Group 1: decreased abundance in chronic kidney disease patients

NCBI Quality ControlLinks
Akkermansia
Allobaculum
Bacilli
Betaproteobacteria
Burkholderiales
Campylobacterales
Deferribacteraceae
Deferribacterales
Deferribacteres
Deferribacterota
Enterorhabdus
Campylobacterota
Eubacteriaceae
Eubacterium
Helicobacter
Helicobacteraceae
Lactobacillaceae
Lactobacillales
Lactobacillus
Lactococcus
Leuconostoc
Micrococcaceae
Mucispirillum
Olsenella
Oribacterium
Parasutterella
Parvibacter
Pyramidobacter
Rothia
Sutterellaceae
Synergistaceae
Synergistales
Synergistes
Synergistota
Synergistia
Verrucomicrobiota
Verrucomicrobiaceae
Verrucomicrobiia
Verrucomicrobiales

Revision editor(s): Lwaldron, Claregrieve1, WikiWorks