Stratification of the Gut Microbiota Composition Landscape across the Alzheimer's Disease Continuum in a Turkish Cohort
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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.
URI
Authors
Yıldırım S, Nalbantoğlu ÖU, Bayraktar A, Ercan FB, Gündoğdu A, Velioğlu HA, Göl MF, Soylu AE, Koç F, Gülpınar EA, Kadak KS, Arıkan M, Mardinoğlu A, Koçak M, Köseoğlu E, Hanoğlu L
Journal
mSystems
Year
2022
Keywords:
16S rRNA, Alzheimer’s disease, brain-gut axis, gut microbiome, gut microbiota, precision medicine, precision nutrition, stratification
Alzheimer's disease (AD) is a heterogeneous disorder that spans a continuum with multiple phases, including preclinical, mild cognitive impairment, and dementia. Unlike for most other chronic diseases, human studies reporting on AD gut microbiota in the literature are very limited. With the scarcity of approved drugs for AD therapies, the rational and precise modulation of gut microbiota composition using diet and other tools is a promising approach to the management of AD. Such an approach could be personalized if an AD continuum can first be deconstructed into multiple strata based on specific microbiota features by using single or multiomics techniques. However, stratification of AD gut microbiota has not been systematically investigated before, leaving an important research gap for gut microbiota-based therapeutic approaches. Here, we analyze 16S rRNA amplicon sequencing of stool samples from 27 patients with mild cognitive impairment, 47 patients with AD, and 51 nondemented control subjects by using tools compatible with the compositional nature of microbiota. To stratify the AD gut microbiota community, we applied four machine learning techniques, including partitioning around the medoid clustering and fitting a probabilistic Dirichlet mixture model, the latent Dirichlet allocation model, and we performed topological data analysis for population-scale microbiome stratification based on the Mapper algorithm. These four distinct techniques all converge on Prevotella and Bacteroides stratification of the gut microbiota across the AD continuum, while some methods provided fine-scale resolution in stratifying the community landscape. Finally, we demonstrate that the signature taxa and neuropsychometric parameters together robustly classify the groups. Our results provide a framework for precision nutrition approaches aiming to modulate the AD gut microbiota. IMPORTANCE The prevalence of AD worldwide is estimated to reach 131 million by 2050. Most disease-modifying treatments and drug trials have failed, due partly to the heterogeneous and complex nature of the disease. Recent studies demonstrated that gut dybiosis can influence normal brain function through the so-called "gut-brain axis." Modulation of the gut microbiota, therefore, has drawn strong interest in the clinic in the management of the disease. However, there is unmet need for microbiota-informed stratification of AD clinical cohorts for intervention studies aiming to modulate the gut microbiota. Our study fills in this gap and draws attention to the need for microbiota stratification as the first step for microbiota-based therapy. We demonstrate that while Prevotella and Bacteroides clusters are the consensus partitions, the newly developed probabilistic methods can provide fine-scale resolution in partitioning the AD gut microbiome landscape.
Experiment 1
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-13
Curated date: 2023/09/27
Curator: Janezhang
Revision editor(s): Janezhang, Chikamso, Joan Chuks, Peace Sandy
Subjects
- Location of subjects
- Turkey
- 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
- Alzheimer's disease [X]Dementia in Alzheimer's disease,[X]Dementia in Alzheimer's disease (disorder),AD,AD - Alzheimer's disease,Alzheimer Dementia,Alzheimer dementia,Alzheimer Dementia, Presenile,ALZHEIMER DIS,Alzheimer Disease,Alzheimer disease,Alzheimer disease, familial,Alzheimer Type Dementia,Alzheimer's,Alzheimer's Dementia,Alzheimer's dementia,Alzheimer's disease,Alzheimer's disease (disorder),Alzheimer's disease, NOS,Alzheimers,Alzheimers Dementia,Alzheimers dementia,ALZHEIMERS DIS,Alzheimers disease,DAT - Dementia Alzheimer's type,Dementia in Alzheimer's disease,Dementia in Alzheimer's disease (disorder),Dementia in Alzheimer's disease, unspecified (disorder),Dementia of the Alzheimer's type,Dementia, Alzheimer Type,Dementia, Presenile,Dementia, Presenile Alzheimer,Disease, Alzheimer,Disease, Alzheimer's,Presenile Alzheimer Dementia,sporadic Alzheimer's disease,alzheimer's disease
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Non-demented Controls
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Alzheimer's disease patients
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients with Alzheimer's disease, mostly exhibiting mild to very mild dementia
- Group 0 sample size Number of subjects in the control (unexposed) group
- 51
- Group 1 sample size Number of subjects in the case (exposed) group
- 47
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- 1 month
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
- Kruskall-Wallis
- 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
- Matched on Factors on which subjects have been matched on in a case-control study
- diet
- Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
- age, sex
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- increased
- Chao1 Abundance-based estimator of species richness
- increased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- unchanged
- Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
- unchanged
Signature 1
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-13
Source: Supplementary Table S2A and Supplementary Table S2CC
Description: Differentially Abundant Genus level Taxa Between Alzheimer's disease Patients and Non-demented control groups Detected by Limma-Voom Model (Age and Sex Adjusted)
Abundance in Group 1: increased abundance in Alzheimer's disease patients
| NCBI | Quality Control | Links |
|---|---|---|
| Bacteroides | ||
| Collinsella | ||
| Escherichia/Shigella sp. | ||
| Odoribacter | ||
| Oscillospiraceae | ||
| Parabacteroides | ||
| Parabacteroides sp. | ||
| Paraprevotella | ||
| Prevotella | ||
| unclassified Erysipelotrichaceae |
Revision editor(s): Joan Chuks, Peace Sandy
Signature 2
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-13
Curated date: 2023/10/24
Curator: Joan Chuks
Revision editor(s): Joan Chuks, Iram jamshed, Peace Sandy
Source: Supplementary Table S2A and Supplementary Table S2CC
Description: Differentially Abundant Genus level Taxa Between Alzheimer's disease Patients and Non-demented control groups Detected by Limma-Voom Model (Age and Sex Adjusted)
Abundance in Group 1: decreased abundance in Alzheimer's disease patients
| NCBI | Quality Control | Links |
|---|---|---|
| Butyricicoccus | ||
| Erysipelotrichaceae | ||
| Faecalibacterium | ||
| Lachnospiraceae | ||
| Parasutterella | ||
| Prevotella | ||
| Roseburia | ||
| unclassified Mollicutes |
Revision editor(s): Joan Chuks, Iram jamshed, Peace Sandy
Experiment 2
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-13
Differences from previous experiment shown
Subjects
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Mild Cognitive Impairment group
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Amnestic patients with mild cognitive impairment (MCI)
- Group 1 sample size Number of subjects in the case (exposed) group
- 27
Lab analysis
Statistical Analysis
- Matched on Factors on which subjects have been matched on in a case-control study
- Not specified
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- increased
- Chao1 Abundance-based estimator of species richness
- decreased
- Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
- increased
- Richness Number of species
- increased
Signature 1
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-13
Source: Supplementary Table S2D and Supplementary Table S2B
Description: Differentially Abundant Genus level Taxa Between mild cognitive impairment (MCI) and Non-demented Control (C) groups Detected by Limma-Voom Model (Age and Sex Adjusted)
Abundance in Group 1: increased abundance in Mild Cognitive Impairment group
| NCBI | Quality Control | Links |
|---|---|---|
| Catenisphaera | ||
| Dialister | ||
| Holdemanella | ||
| Lachnospiraceae | ||
| Muribaculaceae | ||
| Parabacteroides | ||
| Prevotella | ||
| Rikenellaceae | ||
| Sutterella | ||
| Clostridium |
Revision editor(s): Joan Chuks, Peace Sandy, Welile
Signature 2
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-13
Curated date: 2023/10/24
Curator: Joan Chuks
Revision editor(s): Joan Chuks, ChiomaBlessing, Peace Sandy
Source: Supplementary Table S2D
Description: Differentially Abundant Genus level Taxa Between mild cognitive impairment (MCI) and Non-demented Control (C) groups Detected by Limma-Voom Model (Age and Sex Adjusted)
Abundance in Group 1: decreased abundance in Mild Cognitive Impairment group
Revision editor(s): Joan Chuks, ChiomaBlessing, Peace Sandy
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