Gut microbiome alterations in Alzheimer's disease.
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ABSTRACT:
SUBMITTER: Vogt NM
PROVIDER: S-EPMC5648830 | biostudies-other | 2017 Oct
REPOSITORIES: biostudies-other
Publications
Gut microbiome alterations in Alzheimer's disease.
Vogt Nicholas M NM Kerby Robert L RL Dill-McFarland Kimberly A KA Harding Sandra J SJ Merluzzi Andrew P AP Johnson Sterling C SC Carlsson Cynthia M CM Asthana Sanjay S Zetterberg Henrik H Blennow Kaj K Bendlin Barbara B BB Rey Federico E FE
Scientific reports 20171019 1
Alzheimer's disease (AD) is the most common form of dementia. However, the etiopathogenesis of this devastating disease is not fully understood. Recent studies in rodents suggest that alterations in the gut microbiome may contribute to amyloid deposition, yet the microbial communities associated with AD have not been characterized in humans. Towards this end, we characterized the bacterial taxonomic composition of fecal samples from participants with and without a diagnosis of dementia due to AD ...[more]
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Project description:BackgroundAlthough some human studies have reported gut microbiome changes in individuals with Alzheimer's disease (AD) dementia or mild cognitive impairment (MCI), gut microbiome alterations in preclinical AD, i.e., cerebral amyloidosis without cognitive impairment, is largely unknown.ObjectiveWe aimed to identify gut microbial alterations associated with preclinical AD by comparing cognitively normal (CN) older adults with cerebral Aβ deposition (Aβ+ CN) and those without cerebral Aβ deposition (Aβ- CN).MethodsSeventy-eight CN older participants (18 Aβ+ CN and 60 Aβ- CN) were included, and all participants underwent clinical assessment and Pittsburg compound B-positron emission tomography. The V3-V4 region of the 16S rRNA gene of genomic DNA extracted from feces was amplified and sequenced to establish the microbial community.ResultsGeneralized linear model analysis revealed that the genera Megamonas (B = 3.399, q<0.001), Serratia (B = 3.044, q = 0.005), Leptotrichia (B = 5.862, q = 0.024) and Clostridium (family Clostridiaceae) (B = 0.788, q = 0.034) were more abundant in the Aβ+ CN group than the Aβ- CN group. In contrast, genera CF231 (B = -3.237, q< 0.001), Victivallis (B = -3.447, q = 0.004) Enterococcus (B = -2.044, q = 0.042), Mitsuokella (B = -2.119, q = 0.042) and Clostridium (family Erysipelotrichaceae) (B = -2.222, q = 0.043) were decreased in Aβ+ CN compared to Aβ- CN. Notably, the classification model including the differently abundant genera could effectively distinguish Aβ+ CN from Aβ- CN (AUC = 0.823).ConclusionOur findings suggest that specific alterations of gut bacterial taxa are related to preclinical AD, which means these changes may precede cognitive decline. Therefore, examining changes in the microbiome may be helpful in preclinical AD screening.
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Project description:Emerging evidence suggests that the gut microbiome actively regulates cognitive functions and that gut microbiome imbalance is associated with Alzheimer's disease (AD), the most prevalent neurodegenerative disorder. However, the changes in gut microbiome composition in AD and their association with disease pathology, especially in the early stages, are unclear. Here, we compared the profiles of gut microbiota between APP/PS1 transgenic mice (an AD mouse model) and their wild-type littermates at different ages by amplicon-based sequencing of 16S ribosomal RNA genes. Microbiota composition started diverging between the APP/PS1 and wild-type mice at young ages (i.e., 1-3 months), before obvious amyloid deposition and plaque-localized microglial activation in the cerebral cortex in APP/PS1 mice. At later ages (i.e., 6 and 9 months), there were distinct changes in the abundance of inflammation-related bacterial taxa including Escherichia-Shigella, Desulfovibrio, Akkermansia, and Blautia in APP/PS1 mice. These findings suggest that gut microbiota alterations precede the development of key pathological features of AD, including amyloidosis and plaque-localized neuroinflammation. Thus, the investigation of gut microbiota might provide new avenues for developing diagnostic biomarkers and therapeutic targets for AD.
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Project description:In the last decade, the role of the microbiota-gut-brain axis has been gaining momentum in the context of many neurodegenerative and metabolic disorders, including Alzheimer's disease (AD) and diabetes, respectively. Notably, a balanced gut microbiota contributes to the epithelial intestinal barrier maintenance, modulates the host immune system, and releases neurotransmitters and/or neuroprotective short-chain fatty acids. However, dysbiosis may provoke immune dysregulation, impacting neuroinflammation through peripheral-central immune communication. Moreover, lipopolysaccharide or detrimental microbial end-products can cross the blood-brain barrier and induce or at least potentiate the neuropathological progression of AD. Thus, after repeated failure to find a cure for this dementia, a necessary paradigmatic shift towards considering AD as a systemic disorder has occurred. Here, we present an overview of the use of germ-free and/or transgenic animal models as valid tools to unravel the connection between dysbiosis, metabolic diseases, and AD, and to investigate novel therapeutical targets. Given the high impact of dietary habits, not only on the microbiota but also on other well-established AD risk factors such as diabetes or obesity, consistent changes of lifestyle along with microbiome-based therapies should be considered as complementary approaches.
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Project description:A growing body of evidence suggests that dysbiosis of the human gut microbiota is associated with neurodegenerative diseases like Alzheimer's disease (AD) via neuroinflammatory processes across the microbiota-gut-brain axis. The gut microbiota affects brain health through the secretion of toxins and short-chain fatty acids, which modulates gut permeability and numerous immune functions. Observational studies indicate that AD patients have reduced microbiome diversity, which could contribute to the pathogenesis of the disease. Uncovering the genetic basis of microbial abundance and its effect on AD could suggest lifestyle changes that may reduce an individual's risk for the disease. Using the largest genome-wide association study of gut microbiota genera from the MiBioGen consortium, we used polygenic risk score (PRS) analyses with the "best-fit" model implemented in PRSice-2 and determined the genetic correlation between 119 genera and AD in a discovery sample (ADc12 case/control: 1278/1293). To confirm the results from the discovery sample, we next repeated the PRS analysis in a replication sample (GenADA case/control: 799/778) and then performed a meta-analysis with the PRS results from both samples. Finally, we conducted a linear regression analysis to assess the correlation between the PRSs for the significant genera and the APOE genotypes. In the discovery sample, 20 gut microbiota genera were initially identified as genetically associated with AD case/control status. Of these 20, three genera (Eubacterium fissicatena as a protective factor, Collinsella, and Veillonella as a risk factor) were independently significant in the replication sample. Meta-analysis with discovery and replication samples confirmed that ten genera had a significant correlation with AD, four of which were significantly associated with the APOE rs429358 risk allele in a direction consistent with their protective/risk designation in AD association. Notably, the proinflammatory genus Collinsella, identified as a risk factor for AD, was positively correlated with the APOE rs429358 risk allele in both samples. Overall, the host genetic factors influencing the abundance of ten genera are significantly associated with AD, suggesting that these genera may serve as biomarkers and targets for AD treatment and intervention. Our results highlight that proinflammatory gut microbiota might promote AD development through interaction with APOE. Larger datasets and functional studies are required to understand their causal relationships.
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Project description:Gut microbiota make up the largest microecosystem in the human body and are closely related to chronic metabolic diseases. Herein, 520 fecal samples are collected from different regions of China, the gut microbiome in chronic kidney disease (CKD) is characterized, and CKD classifiers based on microbial markers are constructed. Compared with healthy controls (HC, n = 210), gut microbial diversity is significantly decreased in CKD (n = 110), and the microbial community is remarkably distinguished from HC. Genera Klebsiella and Enterobacteriaceae are enriched, while Blautia and Roseburia are reduced in CKD. Fifty predicted microbial functions including tryptophan and phenylalanine metabolisms increase, while 36 functions including arginine and proline metabolisms decrease in CKD. Notably, five optimal microbial markers are identified using the random forest model. The area under the curve (AUC) reaches 0.9887 in the discovery cohort and 0.9512 in the validation cohort (49 CKD vs 63 HC). Importantly, the AUC reaches 0.8986 in the extra diagnosis cohort from Hangzhou. Moreover, Thalassospira and Akkermansia are increased with CKD progression. Thirteen operational taxonomy units are correlated with six clinical indicators of CKD. In conclusion, this study comprehensively characterizes gut microbiome in non-dialysis CKD and demonstrates the potential of microbial markers as non-invasive diagnostic tools for CKD in different regions of China.
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Project description:Coronary heart disease (CHD) is closely related to gut microbiota, which may be significantly affected by ethnicity and the environment. Knowledge regarding the gut microbiome of Tibetan CHD patients living in the Qinghai-Tibet Plateau is very limited. In this study, we characterized the physiological parameters and gut microbiota from 23 healthy Tibetans (HT), 18 CHD patients, and 12 patients with non-stenosis coronary heart disease (NCHD). We analyzed the alterations of the gut microbiome in CHD patients and investigated the relationship between these alterations and the pathological indicators. We found no changes in trimethylamine N-oxide, however, a significant increase in lipopolysaccharides and white blood cells, and a decrease in high-density lipoprotein were observed in the blood of CHD patients, compared to that in the HT group. The gut microbiota of the NCHD group had a significantly higher Shannon index than that of the HT group. Adonis analysis showed that both microbial compositions and functions of the three groups were significantly separated. The Dialister genus was significantly lower and Blautia, Desulfovibrio, and Succinivibrio were significantly higher in abundance in CHD patients compared with the HT group, and the changes were significantly correlated with physiological indexes, such as increased lipopolysaccharides. Moreover, enrichment of genes decreased in four pathways of amino acid metabolism, such as arginine biosynthesis and histidine metabolism, although two lipid metabolism pathways, including fatty acid degradation and arachidonic acid metabolism, increased in the CHD group. Additionally, occupation and a family history of CHD were shown to be risk factors and affected the gut microbiota in Tibetans. Our study will provide insights into the understanding of CHD, leading to better diagnosis and treatment of Tibetan patients.
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Project description:BackgroundCoronary artery disease (CAD) is associated with gut microbiota alterations in different populations. Gut microbe-derived metabolites have been proposed as markers of major adverse cardiac events. However, the relationship between the gut microbiome and the different stages of CAD pathophysiology remains to be established by a systematic study.ResultsBased on multi-omic analyses (sequencing of the V3-V4 regions of the 16S rRNA gene and metabolomics) of 161 CAD patients and 40 healthy controls, we found that the composition of both the gut microbiota and metabolites changed significantly with CAD severity. We identified 29 metabolite modules that were separately classified as being positively or negatively correlated with CAD phenotypes, and the bacterial co-abundance group (CAG) with characteristic changes at different stages of CAD was represented by Roseburia, Klebsiella, Clostridium IV and Ruminococcaceae. The result revealed that certain bacteria might affect atherosclerosis by modulating the metabolic pathways of the host, such as taurine, sphingolipid and ceramide, and benzene metabolism. Moreover, a disease classifier based on differential levels of microbes and metabolites was constructed to discriminate cases from controls and was even able to distinguish stable coronary artery disease from acute coronary syndrome accurately.ConclusionOverall, the composition and functions of the gut microbial community differed from healthy controls to diverse coronary artery disease subtypes. Our study identified the relationships between the features of the gut microbiota and circulating metabolites, providing a new direction for future studies aiming to understand the host-gut microbiota interplay in atherosclerotic pathogenesis.
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Project description:Introduction: Human gut microbiota is believed to be directly or indirectly involved in cardiovascular diseases and hypertension. However, the identification and functional status of the hypertension-related gut microbe(s) have not yet been surveyed in a comprehensive manner. Methods: Here we characterized the gut microbiome in hypertension status by comparing fecal samples of 60 patients with primary hypertension and 60 gender-, age-, and body weight-matched healthy controls based on whole-metagenome shotgun sequencing. Results: Hypertension implicated a remarkable gut dysbiosis with significant reduction in within-sample diversity and shift in microbial composition. Metagenome-wide association study (MGWAS) revealed 53,953 microbial genes that differ in distribution between the patients and healthy controls (false discovery rate, 0.05) and can be grouped into 68 clusters representing bacterial species. Opportunistic pathogenic taxa, such as, Klebsiella spp., Streptococcus spp., and Parabacteroides merdae were frequently distributed in hypertensive gut microbiome, whereas the short-chain fatty acid producer, such as, Roseburia spp. and Faecalibacterium prausnitzii, were higher in controls. The number of hypertension-associated species also showed stronger correlation to the severity of disease. Functionally, the hypertensive gut microbiome exhibited higher membrane transport, lipopolysaccharide biosynthesis and steroid degradation, while in controls the metabolism of amino acid, cofactors and vitamins was found to be higher. We further provided the microbial markers for disease discrimination and achieved an area under the receiver operator characteristic curve (AUC) of 0.78, demonstrating the potential of gut microbiota in prediction of hypertension. Conclusion: These findings represent specific alterations in microbial diversity, genes, species and functions of the hypertensive gut microbiome. Further studies on the causality relationship between hypertension and gut microbiota will offer new prospects for treating and preventing the hypertension and its associated diseases.
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Project description:Gut microbiome is a community of microorganisms in the gastrointestinal tract. These bacteria have a tremendous impact on the human physiology in healthy individuals and during an illness. Intestinal microbiome can influence one's health either directly by secreting biologically active substances such as vitamins, essential amino acids, lipids et cetera or indirectly by modulating metabolic processes and the immune system. In recent years considerable information has been accumulated on the relationship between gut microbiome and brain functions. Moreover, significant quantitative and qualitative changes of gut microbiome have been reported in patients with Alzheimer's disease. On the other hand, gut microbiome is highly sensitive to negative external lifestyle aspects, such as diet, sleep deprivation, circadian rhythm disturbance, chronic noise, and sedentary behavior, which are also considered as important risk factors for the development of sporadic Alzheimer's disease. In this regard, this review is focused on analyzing the links between gut microbiome, modern lifestyle, aging, and Alzheimer's disease.
| S-EPMC7093326 | biostudies-literature
Project description:BackgroundParkinson's disease (PD) is a systemic disease clinically defined by the degeneration of dopaminergic neurons in the brain. While alterations in the gut microbiome composition have been reported in PD, their functional consequences remain unclear. Herein, we addressed this question by an analysis of stool samples from the Luxembourg Parkinson's Study (n = 147 typical PD cases, n = 162 controls).ResultsAll individuals underwent detailed clinical assessment, including neurological examinations and neuropsychological tests followed by self-reporting questionnaires. Stool samples from these individuals were first analysed by 16S rRNA gene sequencing. Second, we predicted the potential secretion for 129 microbial metabolites through personalised metabolic modelling using the microbiome data and genome-scale metabolic reconstructions of human gut microbes. Our key results include the following. Eight genera and seven species changed significantly in their relative abundances between PD patients and healthy controls. PD-associated microbial patterns statistically depended on sex, age, BMI, and constipation. Particularly, the relative abundances of Bilophila and Paraprevotella were significantly associated with the Hoehn and Yahr staging after controlling for the disease duration. Furthermore, personalised metabolic modelling of the gut microbiomes revealed PD-associated metabolic patterns in the predicted secretion potential of nine microbial metabolites in PD, including increased methionine and cysteinylglycine. The predicted microbial pantothenic acid production potential was linked to the presence of specific non-motor symptoms.ConclusionOur results suggest that PD-associated alterations of the gut microbiome can translate into substantial functional differences affecting host metabolism and disease phenotype.
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